@article {pmid39178637,
year = {2024},
author = {Zheng, M and Hong, T and Zhou, H and Garland, EL and Hu, Y},
title = {The acute effect of mindfulness-based regulation on neural indices of cue-induced craving in smokers.},
journal = {Addictive behaviors},
volume = {159},
number = {},
pages = {108134},
doi = {10.1016/j.addbeh.2024.108134},
pmid = {39178637},
issn = {1873-6327},
abstract = {Mindfulness has garnered attention for its potential in alleviating cigarette cravings; however, the neural mechanisms underlying its efficacy remain inadequately understood. This study (N=46, all men) aims to examine the impact of a mindfulness strategy on regulating cue-induced craving and associated brain activity. Twenty-three smokers, consuming over 10 cigarettes daily for at least 2 years， were compared to twenty-three non-smokers. During a regulation of craving task, participants were asked to practice mindfulness during smoking cue-exposure or passively view smoking cues while fMRI scans were completed. A 2 (condition: mindfulness-cigarette and look-cigarette) × 2 (phase: early, late of whole smoking cue-exposure period) repeated measures ANOVA showed a significant interaction of the craving scores between condition and phase, indicating that the mindfulness strategy dampened late-phase craving. Additionally, within the smoker group, the fMRI analyses revealed a significant main effect of mindfulness condition and its interaction with time in several brain networks involving reward, emotion, and interoception. Specifically, the bilateral insula, ventral striatum, and amygdala showed lower activation in the mindfulness condition, whereas the activation of right orbitofrontal cortex mirrored the strategy-time interaction effect of the craving change. This study illuminates the dynamic interplay between mindfulness, smoking cue-induced craving, and neural activity, offering insights into how mindfulness may effectively regulate cigarette cravings.},
}

@article {pmid39178112,
year = {2024},
author = {Tu, WY and Xu, W and Bai, L and Liu, J and Han, Y and Luo, B and Wang, B and Zhang, K and Shen, C},
title = {Local protein synthesis at neuromuscular synapses is required for motor functions.},
journal = {Cell reports},
volume = {43},
number = {9},
pages = {114661},
doi = {10.1016/j.celrep.2024.114661},
pmid = {39178112},
issn = {2211-1247},
abstract = {Motor neurons are highly polarized, and their axons extend over great distances to form connections with myofibers via neuromuscular junctions (NMJs). Local translation at the NMJs in vivo has not been identified. Here, we utilized motor neuron-labeled RiboTag mice and the TRAP (translating ribosome affinity purification) technique to spatiotemporally profile the translatome at NMJs. We found that mRNAs associated with glucose catabolism, synaptic connection, and protein homeostasis are enriched at presynapses. Local translation at the synapse shifts from the assembly of cytoskeletal components during early developmental stages to energy production in adulthood. The mRNA of neuronal Agrin (Agrn), the key molecule for NMJ assembly, is present at motor axon terminals and locally translated. Disrupting the axonal location of Agrn mRNA causes impairment of synaptic transmission and motor functions in adult mice. Our findings indicate that spatiotemporal regulation of mRNA local translation at NMJs plays critical roles in synaptic transmission and motor functions in vivo.},
}

@article {pmid39175558,
year = {2024},
author = {Azadi Moghadam, M and Maleki, A},
title = {Comparative Study of Frequency Recognition Techniques for Steady-State Visual Evoked Potentials According to the Frequency Harmonics and Stimulus Number.},
journal = {Journal of biomedical physics & engineering},
volume = {14},
number = {4},
pages = {365-378},
pmid = {39175558},
issn = {2251-7200},
abstract = {BACKGROUND: A key challenge in steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems is to effectively recognize frequencies within a short time window. To address this challenge, the specific characteristics of the data are needed to select the frequency recognition method. These characteristics include factors, such as the number of stimulation targets and the presence of harmonic frequencies, resulting in optimizing the performance and accuracy of SSVEP-based BCI systems.

OBJECTIVE: The current study aimed to examine the effect of data characteristics on frequency recognition accuracy.

MATERIAL AND METHODS: In this analytical study, five commonly used frequency recognition methods were examined, used to various datasets containing different numbers of frequencies, including sub-data with and without frequency harmonics.

RESULTS: The increase in the number of frequencies in the Multivariate Linear Regression (MLR) method has led to a decrease in frequency recognition accuracy by 9%. Additionally, the presence of harmonic frequencies resulted in an 8% decrease in accuracy for the MLR method.

CONCLUSION: Frequency recognition using the MLR method reduces the effect of the number of different frequencies and harmonics of the stimulation frequencies on the frequency recognition accuracy.},
}

@article {pmid39175425,
year = {2024},
author = {Yao, J and Li, Z and Zhou, Z and Bao, A and Wang, Z and Wei, H and He, H},
title = {Distinct regional vulnerability to Aβ and iron accumulation in post mortem AD brains.},
journal = {Alzheimer's & dementia : the journal of the Alzheimer's Association},
volume = {},
number = {},
pages = {},
doi = {10.1002/alz.14188},
pmid = {39175425},
issn = {1552-5279},
support = {2020AAA0109502//National Key R&D Program of China/ ; 82372036//National Natural Science Foundation of China/ ; 226-2023-00095//Fundamental Research Funds for the Central Universities/ ; 82151303//National Natural Science Foundation/ ; 2021ZD0204000//STI2030-Major Projects/ ; },
abstract = {INTRODUCTION: The paramagnetic iron, diamagnetic amyloid beta (Aβ) plaques and their interaction are crucial in Alzheimer's disease (AD) pathogenesis, complicating non-invasive magnetic resonance imaging for prodromal AD detection.

METHODS: We used a state-of-the-art sub-voxel quantitative susceptibility mapping method to simultaneously measure Aβ and iron levels in post mortem human brains, validated by histology. Further transcriptomic analysis using Allen Human Brain Atlas elucidated the underlying biological processes.

RESULTS: Regional increased paramagnetic and diamagnetic susceptibility were observed in medial prefrontal, medial parietal, and para-hippocampal cortices associated with iron deposition (R = 0.836, p = 0.003) and Aβ accumulation (R = 0.853, p = 0.002) in AD brains. Higher levels of gene expression relating to cell cycle, post-translational protein modifications, and cellular response to stress were observed.

DISCUSSION: These findings provide quantitative insights into the variable vulnerability of cortical regions to higher levels of Aβ aggregation, iron overload, and subsequent neurodegeneration, indicating changes preceding clinical symptoms.

HIGHLIGHTS: The vulnerability of distinct brain regions to amyloid beta (Aβ) and iron accumulation varies. Histological validation was performed on stained sections of ex-vivo human brains. Regional variations in susceptibility were linked to gene expression profiles. Iron and Aβ levels in ex-vivo brains were simultaneously quantified.},
}

@article {pmid39173928,
year = {2024},
author = {Cao, HL and Yu, H and Xue, R and Yang, X and Ma, X and Wang, Q and Deng, W and Guo, WJ and Li, ML and Li, T},
title = {Convergence and divergence in neurostructural signatures of unipolar and bipolar depressions: Insights from surface-based morphometry and prospective follow-up.},
journal = {Journal of affective disorders},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.jad.2024.08.101},
pmid = {39173928},
issn = {1573-2517},
abstract = {BACKGROUND: Bipolar disorder (BD) is often misidentified as unipolar depression (UD) during its early stages, typically until the onset of the first manic episode. This study aimed to explore both shared and unique neurostructural changes in patients who transitioned from UD to BD during follow-up, as compared to those with UD.

METHODS: This study utilized high-resolution structural magnetic resonance imaging (MRI) to collect brain data from individuals initially diagnosed with UD. During the average 3-year follow-up, 24 of the UD patients converted to BD (cBD). For comparison, the study included 48 demographically matched UD patients who did not convert and 48 healthy controls. The MRI data underwent preprocessing using FreeSurfer, followed by surface-based morphometry (SBM) analysis to identify cortical thickness (CT), surface area (SA), and cortical volume (CV) among groups.

RESULTS: The SBM analysis identified shared neurostructural characteristics between the cBD and UD groups, specifically thinner CT in the right precentral cortex compared to controls. Unique to the cBD group, there was a greater SA in the right inferior parietal cortex compared to the UD group. Furthermore, no significant correlations were observed between cortical morphological measures and cognitive performance and clinical features in the cBD and UD groups.

LIMITATIONS: The sample size is relatively small.

CONCLUSIONS: Our findings suggest that while cBD and UD exhibit some common alterations in cortical macrostructure, numerous distinct differences are also present. These differences offer valuable insights into the neuropathological underpinnings that distinguish these two conditions.},
}

@article {pmid39171098,
year = {2024},
author = {Freudenburg, Z and Berezutskaya, J and Herbert, C},
title = {Editorial: The ethics of speech ownership in the context of neural control of augmented assistive communication.},
journal = {Frontiers in human neuroscience},
volume = {18},
number = {},
pages = {1468938},
pmid = {39171098},
issn = {1662-5161},
}

@article {pmid39170600,
year = {2024},
author = {Pan, H and Fu, Y and Zhang, Q and Zhang, J and Qin, X},
title = {The decoder design and performance comparative analysis for closed-loop brain-machine interface system.},
journal = {Cognitive neurodynamics},
volume = {18},
number = {1},
pages = {147-164},
pmid = {39170600},
issn = {1871-4080},
abstract = {Brain-machine interface (BMI) can convert electroencephalography signals (EEGs) into the control instructions of external devices, and the key of control performance is the accuracy and efficiency of decoder. However, the performance of different decoders obtaining control instructions from complex and variable EEG signals is very different and irregular in the different neural information transfer model. Aiming at this problem, the off-line and on-line performance of eight decoders based on the improved single-joint information transmission (SJIT) model is compared and analyzed in this paper, which can provide a theoretical guidance for decoder design. Firstly, in order to avoid the different types of neural activities in the decoding process on the decoder performance, eight decoders based on the improved SJIT model are designed. And then the off-line decoding performance of these decoders is tested and compared. Secondly, a closed-loop BMI system which combining by the designed decoder and the random forest encoder based on the improved SJIT model is constructed. Finally, based on the constructed closed-loop BMI system, the on-line decoding performance of decoders is compared and analyzed. The results show that the LSTM-based decoder has better on-line decoding performance than others in the improved SJIT model.},
}

@article {pmid39167669,
year = {2024},
author = {Matsiko, A},
title = {Bilingual speech neuroprosthesis.},
journal = {Science robotics},
volume = {9},
number = {93},
pages = {eads4122},
doi = {10.1126/scirobotics.ads4122},
pmid = {39167669},
issn = {2470-9476},
mesh = {Humans ; *Multilingualism ; *Speech ; *Brain-Computer Interfaces ; Neural Prostheses ; Brain/physiology ; Prosthesis Design ; Male ; },
abstract = {A neuroprosthesis could decode two languages from the brain activity of a bilingual participant who was unable to articulate speech.},
}

Humans
*Multilingualism
*Speech
*Brain-Computer Interfaces
Neural Prostheses
Brain/physiology
Prosthesis Design
Male

@article {pmid39169955,
year = {2022},
author = {Ukhovskyi, V and Pyskun, A and Korniienko, L and Aliekseieva, H and Moroz, O and Pyskun, O and Kyivska, G and Mezhenskyi, A},
title = {Serological prevalence of Leptospira serovars among pigs in Ukraine during the period of 2001-2019.},
journal = {Veterinarni medicina},
volume = {67},
number = {1},
pages = {13-27},
pmid = {39169955},
issn = {0375-8427},
abstract = {Leptospirosis is a widespread infection among pigs throughout the world. In most cases in Ukraine, only the microscopic agglutination test (MAT) is used for the diagnosis of leptospirosis in animals. In general, during the period of 2001-2019, 2 381 163 samples of blood sera from swine were tested in our country and 85 338 positive reactions were received, which is 3.58% [binomial confidence intervals (BCI), 3.56-3.61%]. It was established that the serovars copenhageni - 33.91% (BCI, 33.59-34.23%), bratislava - 14.14% (BCI, 13.90-14.37%), pomona - 8.58% (BCI, 8.39-8.77%), and tarassovi - 7.12% (BCI, 6.95-7.30%) play a leading role in the aetiological structure of swine leptospirosis. A large number of positive reactions to several serovars was observed - 29.78% (BCI, 29.47-30.09%) of the total number of positive cases. In addition, the article presents data according to a retrospective analysis of the eight serovars circulating among pigs in Ukraine. Thus, during the nineteen year period, there was a decrease in the number of positive reactions to bratislava, pomona, and tarassovi and an increase in the number of positive reactions to copenhageni, polonica, and kabura. Mapping Ukraine's territory for leptospirosis among pigs was carried out. This allows one to identify zones with a risk of leptospirosis infections among swine. The maps show that the highest incidence rates were identified in the eastern and central parts of Ukraine.},
}

@article {pmid39166947,
year = {2024},
author = {Zhang, H and Jiao, L and Yang, S and Li, H and Jiang, X and Feng, J and Zou, S and Xu, Q and Gu, J and Wang, X and Wei, B},
title = {Brain-computer interfaces: The innovative key to unlocking neurological conditions.},
journal = {International journal of surgery (London, England)},
volume = {},
number = {},
pages = {},
doi = {10.1097/JS9.0000000000002022},
pmid = {39166947},
issn = {1743-9159},
abstract = {Neurological disorders such as Parkinson's disease, stroke, and spinal cord injury can result in impairments of motor function, consciousness, cognition, and sensory processing. Brain-Computer Interface (BCI) technology, which facilitates direct communication between the brain and external devices, emerges as an innovative key to unlocking neurological conditions, demonstrating significant promise in this context. This comprehensive review uniquely synthesizes the latest advancements in BCI research across multiple neurological disorders, offering an interdisciplinary perspective on both clinical applications and emerging technologies. We explore the progress in BCI research and its applications in addressing various neurological conditions, with a particular focus on recent clinical studies and prospective developments. Initially, the review provides an up-to-date overview of BCI technology, encompassing its classification, operational principles, and prevalent paradigms. It then critically examines specific BCI applications in movement disorders, disorders of consciousness, cognitive and mental disorders, as well as sensory disorders, highlighting novel approaches and their potential impact on patient care. This review reveals emerging trends in BCI applications, such as the integration of artificial intelligence and the development of closed-loop systems, which represent significant advancements over previous technologies. The review concludes by discussing the prospects and directions of BCI technology, underscoring the need for interdisciplinary collaboration and ethical considerations. It emphasizes the importance of prioritizing bidirectional and high-performance BCIs, areas that have been underexplored in previous reviews. Additionally, we identify crucial gaps in current research, particularly in long-term clinical efficacy and the need for standardized protocols. The role of neurosurgery in spearheading the clinical translation of BCI research is highlighted. Our comprehensive analysis presents BCI technology as an innovative key to unlocking neurological disorders, offering a transformative approach to diagnosing, treating, and rehabilitating neurological conditions, with substantial potential to enhance patients' quality of life and advance the field of neurotechnology.},
}

@article {pmid39166824,
year = {2024},
author = {Hata, J and Matsuoka, K and Akaihata, H and Yaginuma, K and Meguro, S and Hoshi, S and Koguchi, T and Sato, Y and Kataoka, M and Ogawa, S and Uemura, M and Kojima, Y},
title = {Prognosis of lower urinary tract symptoms and function after robot-assisted radical prostatectomy in patients with preoperative low bladder contractility: A prospective, observational study.},
journal = {Neurourology and urodynamics},
volume = {},
number = {},
pages = {},
doi = {10.1002/nau.25577},
pmid = {39166824},
issn = {1520-6777},
abstract = {OBJECTIVES: To examine the prognosis of lower urinary tract symptoms and function after robot-assisted radical prostatectomy (RARP) in patients with low preoperative bladder contractility.

METHODS: A total of 115 patients who underwent RARP were enrolled and divided into two groups by preoperative urodynamic findings: normal (patients with bladder contractility index [BCI] ≥ 100; n = 70) and low contractility (patients with BCI < 100; n = 45) groups. Lower urinary tract symptoms and function parameters were prospectively evaluated at 1, 3, 6, 9, and 12 months after RARP in both groups.

RESULTS: International Prostatic Symptom Score voiding scores 1, 3, 6, 9, and 12 months after RARP were significantly higher (p < 0.05), and the maximum flow rate (Qmax) values before and 1, 3, 9, and 12 months after RARP were significantly lower in the low contractility group (p < 0.05). Comparing preoperative and postoperative parameters, IPSS voiding scores in the normal contractility group were significantly improved from 6 months after RARP, whereas those in the low contractility group were almost unchanged. Qmax and the 1-h pad test in both groups temporarily deteriorated 1 month after RARP, whereas voided volume and postvoiding residual volume significantly decreased from 1 to 12 months after RARP.

CONCLUSIONS: This observational study showed that patients with low preoperative bladder contractility might have a weak improvement in voiding symptoms and function after RARP.},
}

@article {pmid39165885,
year = {2024},
author = {Singh, AK and Bianchi, L and Valeriani, D and Nakanishi, M},
title = {Editorial: Advances and challenges to bridge computational intelligence and neuroscience for brain-computer interface.},
journal = {Frontiers in neuroergonomics},
volume = {5},
number = {},
pages = {1461494},
pmid = {39165885},
issn = {2673-6195},
}

@article {pmid39165780,
year = {2024},
author = {Tapia, JL and Lopez, A and Turner, DB and Fairley, T and Tomlin-Harris, T and Hawkins, M and Holbert, PR and Treviño, LS and Teteh-Brooks, DK},
title = {The bench to community initiative: community-based participatory research model for translating research discoveries into community solutions.},
journal = {Frontiers in public health},
volume = {12},
number = {},
pages = {1394069},
pmid = {39165780},
issn = {2296-2565},
mesh = {*Community-Based Participatory Research ; Humans ; *Breast Neoplasms ; Female ; Translational Research, Biomedical ; Black or African American ; Quality of Life ; },
abstract = {UNLABELLED: Community-based participatory research (CBPR) is an effective methodology for translating research findings from academia to community interventions. The Bench to Community Initiative (BCI), a CBPR program, builds on prior research to engage stakeholders across multiple disciplines with the goal of disseminating interventions to reduce breast cancer disparities and improve quality of life of Black communities.

METHODS: The BCI program was established to understand sociocultural determinants of personal care product use, evaluate the biological impact of endocrine disrupting chemicals, and develop community interventions. The three pillars of the program include research, outreach and engagement as well as advocacy activities. The research pillar of the BCI includes development of multidisciplinary partnerships to understand the sociocultural and biological determinants of harmful chemical (e.g., endocrine disrupting chemicals) exposures from personal care products and to implement community interventions. The outreach and engagement pillar includes education and translation of research into behavioral practice. The research conducted through the initiative provides the foundation for advocacy engagement with applicable community-based organizations. Essential to the mission of the BCI is the participation of community members and trainees from underrepresented backgrounds who are affected by breast cancer disparities.

RESULTS: Two behavioral interventions will be developed building on prior research on environmental exposures with the focus on personal care products including findings from the BCI. In person and virtual education activities include tabling at community events with do-it-yourself product demonstrations, Salon Conversations-a virtual platform used to bring awareness, education, and pilot behavior change interventions, biennial symposiums, and social media engagement. BCI's community advisory board members support activities across the three pillars, while trainees participate in personal and professional activities that enhance their skills in research translation.

DISCUSSION: This paper highlights the three pillars of the BCI, lessons learned, testimonies from community advisory board members and trainees on the impact of the initiative, as well as BCI's mission driven approaches to achieving health equity.},
}

*Community-Based Participatory Research
Humans
*Breast Neoplasms
Female
Translational Research, Biomedical
Black or African American
Quality of Life

@article {pmid39165718,
year = {2024},
author = {Qiu, Y and Lian, YN and Wu, C and Liu, L and Zhang, C and Li, XY},
title = {Coordination between midcingulate cortex and retrosplenial cortex in pain regulation.},
journal = {Frontiers in molecular neuroscience},
volume = {17},
number = {},
pages = {1405532},
pmid = {39165718},
issn = {1662-5099},
abstract = {INTRODUCTION: The cingulate cortex, with its subregions ACC, MCC, and RSC, is key in pain processing. However, the detailed interactions among these regions in modulating pain sensation have remained unclear.

METHODS: In this study, chemogenetic tools were employed to selectively activate or inhibit neuronal activity in the MCC and RSC of rodents to elucidate their roles in pain regulation.Results: Our results showed that chemogenetic activation in both the RSC and MCC heightened pain sensitivity. Suppression of MCC activity disrupted the RSC's regulation of both mechanical and thermal pain, while RSC inhibition specifically affected the MCC's regulation of thermal pain.

DISCUSSION: The findings indicate a complex interplay between the MCC and RSC, with the MCC potentially governing the RSC's pain regulatory mechanisms. The RSC, in turn, is crucial for the MCC's control over thermal sensation, revealing a collaborative mechanism in pain processing.

CONCLUSION: This study provides evidence for the MCC and RSC's collaborative roles in pain regulation, highlighting the importance of their interactions for thermal and mechanical pain sensitivity. Understanding these mechanisms could aid in developing targeted therapies for pain disorders.},
}

@article {pmid39164787,
year = {2024},
author = {Li, JK and Tang, T and Zong, H and Wu, EM and Zhao, J and Wu, RR and Zheng, XN and Zhang, H and Li, YF and Zhou, XH and Zhang, CC and Zhang, ZL and Zhang, YH and Feng, WZ and Zhou, Y and Wang, J and Zhu, QY and Deng, Q and Zheng, JM and Yang, L and Wei, Q and Shen, BR},
title = {Intelligent medicine in focus: the 5 stages of evolution in robot-assisted surgery for prostate cancer in the past 20 years and future implications.},
journal = {Military Medical Research},
volume = {11},
number = {1},
pages = {58},
pmid = {39164787},
issn = {2054-9369},
support = {2023SCU12057//Fundamental Research Funds for the Central Universities/ ; 82373106//National Natural Science Foundation of China/ ; 82372831//National Natural Science Foundation of China/ ; 32270690//National Natural Science Foundation of China/ ; },
mesh = {Humans ; Male ; *Robotic Surgical Procedures/methods/history/trends ; *Prostatic Neoplasms/surgery ; Artificial Intelligence/trends ; },
abstract = {Robot-assisted surgery has evolved into a crucial treatment for prostate cancer (PCa). However, from its appearance to today, brain-computer interface, virtual reality, and metaverse have revolutionized the field of robot-assisted surgery for PCa, presenting both opportunities and challenges. Especially in the context of contemporary big data and precision medicine, facing the heterogeneity of PCa and the complexity of clinical problems, it still needs to be continuously upgraded and improved. Keeping this in mind, this article summarized the 5 stages of the historical development of robot-assisted surgery for PCa, encompassing the stages of emergence, promotion, development, maturity, and intelligence. Initially, safety concerns were paramount, but subsequent research and engineering advancements have focused on enhancing device efficacy, surgical technology, and achieving precise multi modal treatment. The dominance of da Vinci robot-assisted surgical system has seen this evolution intimately tied to its successive versions. In the future, robot-assisted surgery for PCa will move towards intelligence, promising improved patient outcomes and personalized therapy, alongside formidable challenges. To guide future development, we propose 10 significant prospects spanning clinical, research, engineering, materials, social, and economic domains, envisioning a future era of artificial intelligence in the surgical treatment of PCa.},
}

Humans
Male
*Robotic Surgical Procedures/methods/history/trends
*Prostatic Neoplasms/surgery
Artificial Intelligence/trends

@article {pmid39164105,
year = {2024},
author = {Kabir, A and Dhami, P and Dussault Gomez, MA and Blumberger, DM and Daskalakis, ZJ and Moreno, S and Farzan, F},
title = {Influence of Large-Scale Brain State Dynamics on the Evoked Response to Brain Stimulation.},
journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
volume = {},
number = {},
pages = {},
doi = {10.1523/JNEUROSCI.0782-24.2024},
pmid = {39164105},
issn = {1529-2401},
abstract = {Understanding how spontaneous brain activity influences the response to neurostimulation is crucial for the development of neurotherapeutics and brain-computer interfaces. Localized brain activity is suggested to influence the response to neurostimulation, but whether fast-fluctuating (i.e., tens of milliseconds) large-scale brain dynamics also have any such influence is unknown. By stimulating the prefrontal cortex using combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG), we examined how dynamic global brain state patterns, as defined by microstates, influence the magnitude of the evoked brain response. TMS applied during what resembled the canonical microstate C was found to induce a greater evoked response for up to 80 milliseconds compared to other microstates. This effect was found in a repeated experimental session, was absent during sham stimulation, and was replicated in an independent dataset. Ultimately, ongoing and fast-fluctuating global brain states, as probed by microstates, may be associated with intrinsic fluctuations in connectivity and excitation-inhibition balance and influence the neurostimulation outcome. We suggest that the fast-fluctuating global brain states be considered when developing any related paradigms.Significance Statement Previous findings suggested local spontaneous neural oscillations can influence neurophysiological response to stimuli. However, beyond the local oscillatory activity, the brain state is rapidly fluctuating on a millisecond time resolution on a global spatial scale. We investigated whether these rapid global fluctuations influenced the evoked response to brain stimulation. We used combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) to stimulate the prefrontal cortex while recording global brain states via EEG microstates. The evoked neurophysiological response was significantly larger when stimulation was applied after the occurrence of a specific global brain state (i.e., microstate C) linked to mind-wandering. The finding was selective to active stimulation, replicated for the same individuals in a repeated session, and replicated in an entirely independent dataset.},
}

@article {pmid39161850,
year = {2024},
author = {Dillen, A and Omidi, M and Díaz, MA and Ghaffari, F and Roelands, B and Vanderborght, B and Romain, O and De Pauw, K},
title = {Evaluating the real-world usability of BCI control systems with augmented reality: a user study protocol.},
journal = {Frontiers in human neuroscience},
volume = {18},
number = {},
pages = {1448584},
pmid = {39161850},
issn = {1662-5161},
abstract = {Brain-computer interfaces (BCI) enable users to control devices through their brain activity. Motor imagery (MI), the neural activity resulting from an individual imagining performing a movement, is a common control paradigm. This study introduces a user-centric evaluation protocol for assessing the performance and user experience of an MI-based BCI control system utilizing augmented reality. Augmented reality is employed to enhance user interaction by displaying environment-aware actions, and guiding users on the necessary imagined movements for specific device commands. One of the major gaps in existing research is the lack of comprehensive evaluation methodologies, particularly in real-world conditions. To address this gap, our protocol combines quantitative and qualitative assessments across three phases. In the initial phase, the BCI prototype's technical robustness is validated. Subsequently, the second phase involves a performance assessment of the control system. The third phase introduces a comparative analysis between the prototype and an alternative approach, incorporating detailed user experience evaluations through questionnaires and comparisons with non-BCI control methods. Participants engage in various tasks, such as object sorting, picking and placing, and playing a board game using the BCI control system. The evaluation procedure is designed for versatility, intending applicability beyond the specific use case presented. Its adaptability enables easy customization to meet the specific user requirements of the investigated BCI control application. This user-centric evaluation protocol offers a comprehensive framework for iterative improvements to the BCI prototype, ensuring technical validation, performance assessment, and user experience evaluation in a systematic and user-focused manner.},
}

@article {pmid39161655,
year = {2024},
author = {Chen, Y and Wang, F and Li, T and Zhao, L and Gong, A and Nan, W and Ding, P and Fu, Y},
title = {Considerations and discussions on the clear definition and definite scope of brain-computer interfaces.},
journal = {Frontiers in neuroscience},
volume = {18},
number = {},
pages = {1449208},
pmid = {39161655},
issn = {1662-4548},
abstract = {Brain-computer interface (BCI) is a revolutionizing human-computer interaction with potential applications in both medical and non-medical fields, emerging as a cutting-edge and trending research direction. Increasing numbers of groups are engaging in BCI research and development. However, in recent years, there has been some confusion regarding BCI, including misleading and hyped propaganda about BCI, and even non-BCI technologies being labeled as BCI. Therefore, a clear definition and a definite scope for BCI are thoroughly considered and discussed in the paper, based on the existing definitions of BCI, including the six key or essential components of BCI. In the review, different from previous definitions of BCI, BCI paradigms and neural coding are explicitly included in the clear definition of BCI provided, and the BCI user (the brain) is clearly identified as a key component of the BCI system. Different people may have different viewpoints on the definition and scope of BCI, as well as some related issues, which are discussed in the article. This review argues that a clear definition and definite scope of BCI will benefit future research and commercial applications. It is hoped that this review will reduce some of the confusion surrounding BCI and promote sustainable development in this field.},
}

@article {pmid39160882,
year = {2024},
author = {Pitkin, M and Park, H and Frossard, L and Klishko, AN and Prilutsky, BI},
title = {Transforming the Anthropomorphic Passive Free-Flow Foot Prosthesis Into a Powered Foot Prosthesis With Intuitive Control and Sensation (Bionic FFF).},
journal = {Military medicine},
volume = {189},
number = {Supplement_3},
pages = {439-447},
doi = {10.1093/milmed/usae149},
pmid = {39160882},
issn = {1930-613X},
support = {MR150051//U.S. Department of Defense/ ; AR43290//National Center for Medical Rehabilitation Research/ ; MR150051//U.S. Department of Defense/ ; AR43290//National Center for Medical Rehabilitation Research/ ; },
mesh = {*Artificial Limbs/statistics & numerical data ; Animals ; *Prosthesis Design/methods ; Cats ; Foot/physiology/physiopathology ; Amputees/rehabilitation ; Electromyography/methods/instrumentation ; Bionics/methods/instrumentation ; Walking/physiology/statistics & numerical data ; Humans ; },
abstract = {INTRODUCTION: Approximately 89% of all service members with amputations do not return to duty. Restoring intuitive neural control with somatosensory sensation is a key to improving the safety and efficacy of prosthetic locomotion. However, natural somatosensory feedback from lower-limb prostheses has not yet been incorporated into any commercial prostheses.

MATERIALS AND METHODS: We developed a neuroprosthesis with intuitive bidirectional control and somatosensation and evoking phase-dependent locomotor reflexes, we aspire to significantly improve the prosthetic rehabilitation and long-term functional outcomes of U.S. amputees. We implanted the skin and bone integrated pylon with peripheral neural interface pylon into the cat distal tibia, electromyographic electrodes into the residual gastrocnemius muscle, and nerve cuff electrodes on the distal tibial and sciatic nerves. Results. The bidirectional neural interface that was developed was integrated into the existing passive Free-Flow Foot and Ankle prosthesis, WillowWood, Mount Sterling, OH. The Free-Flow Foot was chosen because it had the highest Index of Anthropomorphicity among lower-limb prostheses and was the first anthropomorphic prosthesis brought to market. Conclusion. The cats walked on a treadmill with no cutaneous feedback from the foot in the control condition and with their residual distal tibial nerve stimulated during the stance phase of walking.},
}

*Artificial Limbs/statistics & numerical data
Animals
*Prosthesis Design/methods
Cats
Foot/physiology/physiopathology
Amputees/rehabilitation
Electromyography/methods/instrumentation
Bionics/methods/instrumentation
Walking/physiology/statistics & numerical data
Humans

@article {pmid39160021,
year = {2024},
author = {Zhu, L and Wang, W and Huang, A and Ying, N and Xu, P and Zhang, J},
title = {An efficient channel recurrent Criss-cross attention network for epileptic seizure prediction.},
journal = {Medical engineering & physics},
volume = {130},
number = {},
pages = {104213},
doi = {10.1016/j.medengphy.2024.104213},
pmid = {39160021},
issn = {1873-4030},
mesh = {Humans ; *Electroencephalography ; *Signal Processing, Computer-Assisted ; *Seizures/diagnosis/physiopathology ; *Neural Networks, Computer ; Epilepsy/physiopathology/diagnosis ; Algorithms ; },
abstract = {Epilepsy is a chronic disease caused by repeated abnormal discharge of neurons in the brain. Accurately predicting the onset of epilepsy can effectively improve the quality of life for patients with the condition. While there are many methods for detecting epilepsy, EEG is currently considered one of the most effective analytical tools due to the abundant information it provides about brain activity. The aim of this study is to explore potential time-frequency and channel features from multi-channel epileptic EEG signals and to develop a patient-specific seizure prediction network. In this paper, an epilepsy EEG signal classification algorithm called Channel Recurrent Criss-cross Attention Network (CRCANet) is proposed. Firstly, the spectrograms processed by the short-time fourier transform is input into a Convolutional Neural Network (CNN). Then, the spectrogram feature map obtained in the previous step is input into the channel attention module to establish correlations between channels. Subsequently, the feature diagram containing channel attention characteristics is input into the recurrent criss-cross attention module to enhance the information content of each pixel. Finally, two fully connected layers are used for classification. We validated the method on 13 patients in the public CHB-MIT scalp EEG dataset, achieving an average accuracy of 93.8 %, sensitivity of 94.3 %, and specificity of 93.5 %. The experimental results indicate that CRCANet can effectively capture the time-frequency and channel characteristics of EEG signals while improving training efficiency.},
}

Humans
*Electroencephalography
*Signal Processing, Computer-Assisted
*Seizures/diagnosis/physiopathology
*Neural Networks, Computer
Epilepsy/physiopathology/diagnosis
Algorithms

@article {pmid39159588,
year = {2024},
author = {Liu, L and Wang, D and Luo, Y and Liu, Y and Guo, Y and Yang, GZ and Qiu, G},
title = {Intraoperative assessment of microimplantation-induced acute brain inflammation with titanium oxynitride-based plasmonic biosensor.},
journal = {Biosensors & bioelectronics},
volume = {264},
number = {},
pages = {116664},
doi = {10.1016/j.bios.2024.116664},
pmid = {39159588},
issn = {1873-4235},
abstract = {Implantable devices for brain-machine interfaces and managing neurological disorders have experienced rapid growth in recent years. Although functional implants offer significant benefits, issues related to transient trauma and long-term biocompatibility and safety are of significant concern. Acute inflammatory reaction in the brain tissue caused by microimplants is known to be an issue but remains poorly studied. This study presents the use of titanium oxynitride (TiNO) nanofilm with defined surface plasmon resonance (SPR) properties for point-of-care characterizing of acute inflammatory responses during robot-controlled micro-neuro-implantation. By leveraging surface-enriched oxynitride, TiNO nanofilms can be biomolecular-functionalized through silanization. This label-free TiNO-SPR biosensor exhibits a high sensitivity toward the inflammatory cytokine interleukin-6 with a detection limit down to 6.3 fg ml[-1] and a short assay time of 25 min. Additionally, intraoperative monitoring of acute inflammatory responses during microelectrode implantation in the mice brain has been accomplished using the TiNO-SPR biosensors. Through intraoperative cerebrospinal fluid sampling and point-of-care plasmonic biosensing, the rhythm of acute inflammatory responses induced by the robot-controlled brain microelectrodes implantation has been successfully depicted, offering insights into intraoperative safety assessment of invasive brain-machine interfaces.},
}

@article {pmid39156926,
year = {2024},
author = {Zhu, H and Deng, X and Yakovlev, VV and Zhang, D},
title = {Dynamics of CH/n hydrogen bond networks probed by time-resolved CARS spectroscopy.},
journal = {Chemical science},
volume = {},
number = {},
pages = {},
pmid = {39156926},
issn = {2041-6520},
abstract = {Hydrogen bond (HB) networks are essential for stabilizing molecular structures in solution and govern the solubility and functionality of molecules in an aqueous environment. HBs are important in biological processes such as enzyme-substrate interactions, protein folding, and DNA replication. However, the exact role of weakly polarized C-H bonds as HB proton donors in solution, such as CH/n HBs, remains mostly unknown. Here, we employ a novel approach focusing on vibrational dephasing to investigate the coherence relaxation of induced dipoles in C-H bonds within CH/n HB networks, utilizing time-resolved coherent anti-Stokes Raman scattering (T-CARS) spectroscopy. Using a representative binary system of dimethyl sulfoxide (DMSO)-water, known for its C-H backboned HB system (i.e., C-H⋯S), we observed an increase in the dephasing time of the C-H bending mode with increasing water content until a percolation threshold at a 6 : 1 water : DMSO molar ratio, where the trend is reversed. These results provide compelling evidence for the existence of C-H⋯S structures and underscore the presence of a percolation effect, suggesting a critical threshold where long-range connectivity is disputed.},
}

@article {pmid39156581,
year = {2024},
author = {Xiong, L and Cao, J and Dong, H and Song, W and Ming, D},
title = {Multidisciplinary integration of frontier technologies facilitating the development of anesthesiology and perioperative medicine in aging society.},
journal = {Fundamental research},
volume = {4},
number = {4},
pages = {795-796},
pmid = {39156581},
issn = {2667-3258},
}

@article {pmid39155721,
year = {2024},
author = {Li, Y and Su, C and Pan, Y},
title = {Spontaneous movement synchrony as an exogenous source for interbrain synchronization in cooperative learning.},
journal = {Philosophical transactions of the Royal Society of London. Series B, Biological sciences},
volume = {379},
number = {1911},
pages = {20230155},
doi = {10.1098/rstb.2023.0155},
pmid = {39155721},
issn = {1471-2970},
support = {//Humanities and Social Sciences Research Project from the Ministry of Education of China/ ; //National Natural Science Foundation of China/ ; },
mesh = {Humans ; *Brain/physiology ; Male ; *Movement/physiology ; Female ; *Learning/physiology ; Young Adult ; Cooperative Behavior ; Spectroscopy, Near-Infrared ; Adult ; },
abstract = {Learning through cooperation with conspecifics-'cooperative learning'-is critical to cultural evolution and survival. Recent progress has established that interbrain synchronization (IBS) between individuals predicts success in cooperative learning. However, the likely sources of IBS during learning interactions remain poorly understood. To address this dearth of knowledge, we tested whether movement synchrony serves as an exogenous factor that drives IBS, taking an embodiment perspective. We formed dyads of individuals with varying levels of prior knowledge (high-high (HH), high-low (HL), low-low (LL) dyads) and instructed them to collaboratively analyse an ancient Chinese poem. During the task, we simultaneously recorded their brain activity using functional near-infrared spectroscopy and filmed the entire experiment to parse interpersonal movement synchrony using the computer-vision motion energy analysis. Interestingly, the homogeneous groups (HH and/or LL) exhibited stronger movement synchrony and IBS compared with the heterogeneous group. Importantly, mediation analysis revealed that spontaneous and synchronized body movements between individuals contribute to IBS, hence facilitating learning. This study therefore fills a critical gap in our understanding of how interpersonal transmission of information between individual brains, associated with behavioural entrainment, shapes social learning. This article is part of the theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'.},
}

Humans
*Brain/physiology
Male
*Movement/physiology
Female
*Learning/physiology
Young Adult
Cooperative Behavior
Spectroscopy, Near-Infrared
Adult

@article {pmid39154786,
year = {2024},
author = {Li, X and Ruan, Y and Wang, S and Pan, Y and Huang, Y},
title = {Taste or Health: The Impact of Packaging Cues on Consumer Decision-Making in Healthy Foods.},
journal = {Appetite},
volume = {},
number = {},
pages = {107636},
doi = {10.1016/j.appet.2024.107636},
pmid = {39154786},
issn = {1095-8304},
abstract = {According to the theory of dietary regulation, consumers frequently encounter conflicts between healthiness and tastiness when selecting healthy foods. This study explores how packaging cue that highlight "tasty" versus "healthy" affect consumers' intentions to purchase healthy food. After an Implicit Association Test (IAT) confirmed a perceived lack of tastiness in health foods in the preliminary test, Study 1 analyzed pricing and packaging details of the top 200 most-popular items in each of the ten healthy food categories on a major online shopping platform. Results showed that products with taste-focused cues commanded higher prices, indicating stronger consumer acceptance of healthy foods marketed as delicious. To address the causality limitations of observational studies, Study 2 used an experimental design to directly measure the impact of these cues on purchase intentions and perceptions of energy, healthiness, and tastiness. Findings revealed that taste-focused cues significantly boosted purchase intentions compared to health-focused cues, although they also diminished the perceived healthiness of the products. Moreover, in the control group exposed to unhealthy food options, health-emphasized packaging also increased purchase intentions, indicating that consumers seek a balance between healthiness and tastiness, rather than prioritizing health alone. Study 3 further explored the impact of cognitive load over these cue influences, revealing a heightened inclination among consumers to purchase healthy products with taste-focused cue under high cognitive load state. These insights have direct implications for food packaging design, suggesting that emphasizing a balance of taste and health benefits can effectively enhance consumer engagement. The study, which conducted in China, also opens avenues for future research to explore similar effects, maybe in different cultural contexts, different consumer groups, and under varied cognitive conditions.},
}

@article {pmid39151656,
year = {2024},
author = {Kuo, CH and Guan-Tze, L and Lee, CE and Wu, J and Casimo, K and Weaver, KE and Lo, YC and Chen, YY and Huang, WC and Ojemann, JG},
title = {Decoding Micro-Electrocorticographic Signals by Using Explainable 3D Convolutional Neural Network to Predict Finger Movements.},
journal = {Journal of neuroscience methods},
volume = {},
number = {},
pages = {110251},
doi = {10.1016/j.jneumeth.2024.110251},
pmid = {39151656},
issn = {1872-678X},
abstract = {BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing machine learning models requiring manual feature extraction.

NEW METHOD: This study introduces a 3D convolutional neural network (3D-CNN) model to decode finger movements using ECoG data. The model employs adaptive, explainable AI (xAI) techniques to interpret the physiological relevance of brain signals. ECoG signals from epilepsy patients during awake craniotomy were processed to extract power spectral density across multiple frequency bands. These data formed a 3D matrix used to train the 3D-CNN to predict finger trajectories.

RESULTS: The 3D-CNN model showed significant accuracy in predicting finger movements, with root-mean-square error (RMSE) values of 0.26-0.38 for single finger movements and 0.20-0.24 for combined movements. Explainable AI techniques, Grad-CAM and SHAP, identified the high gamma (HG) band as crucial for movement prediction, showing specific cortical regions involved in different finger movements. These findings highlighted the physiological significance of the HG band in motor control.

The 3D-CNN model outperformed traditional machine learning approaches by effectively capturing spatial and temporal patterns in ECoG data. The use of xAI techniques provided clearer insights into the model's decision-making process, unlike the "black box" nature of standard deep learning models.

CONCLUSIONS: The proposed 3D-CNN model, combined with xAI methods, enhances the decoding accuracy of finger movements from ECoG data. This approach offers a more efficient and interpretable solution for brain-computer interface (BCI) applications, emphasizing the HG band's role in motor control.},
}

@article {pmid38869771,
year = {2024},
author = {Telli, ML and Litton, JK and Beck, JT and Jones, JM and Andersen, J and Mina, LA and Brig, R and Danso, M and Yuan, Y and Symmans, WF and Hopkins, JF and Albacker, LA and Abbattista, A and Noonan, K and Mata, M and Laird, AD and Blum, JL},
title = {Neoadjuvant talazoparib in patients with germline BRCA1/2 mutation-positive, early-stage triple-negative breast cancer: exploration of tumor BRCA mutational status.},
journal = {Breast cancer (Tokyo, Japan)},
volume = {31},
number = {5},
pages = {886-897},
pmid = {38869771},
issn = {1880-4233},
mesh = {Humans ; Female ; *Triple Negative Breast Neoplasms/genetics/drug therapy/pathology ; *Germ-Line Mutation ; *Phthalazines/therapeutic use/administration & dosage ; *BRCA2 Protein/genetics ; *BRCA1 Protein/genetics ; *Neoadjuvant Therapy/methods ; Middle Aged ; Retrospective Studies ; Adult ; Biomarkers, Tumor/genetics ; Aged ; Loss of Heterozygosity ; },
abstract = {BACKGROUND: Talazoparib monotherapy in patients with germline BRCA-mutated, early-stage triple-negative breast cancer (TNBC) showed activity in the neoadjuvant setting in the phase II NEOTALA study (NCT03499353). These biomarker analyses further assessed the mutational landscape of the patients enrolled in the NEOTALA study.

METHODS: Baseline tumor tissue from the NEOTALA study was tested retrospectively using FoundationOne[®]CDx. To further hypothesis-driven correlative analyses, agnostic heat-map visualizations of the FoundationOne[®]CDx tumor dataset were used to assess overall mutational landscape and identify additional candidate predictive biomarkers of response.

RESULTS: All patients enrolled (N = 61) had TNBC. In the biomarker analysis population, 75.0% (39/52) and 25.0% (13/52) of patients exhibited BRCA1 and BRCA2 mutations, respectively. Strong concordance (97.8%) was observed between tumor BRCA and germline BRCA mutations, and 90.5% (38/42) of patients with tumor BRCA mutations evaluable for somatic-germline-zygosity were predicted to exhibit BRCA loss of heterozygosity (LOH). No patients had non-BRCA germline DNA damage response (DDR) gene variants with known/likely pathogenicity, based on a panel of 14 non-BRCA DDR genes. Ninety-eight percent of patients had TP53 mutations. Genomic LOH, assessed continuously or categorically, was not associated with response.

CONCLUSION: The results from this exploratory biomarker analysis support the central role of BRCA and TP53 mutations in tumor pathobiology. Furthermore, these data support assessing germline BRCA mutational status for molecular eligibility for talazoparib in patients with TNBC.},
}

Humans
Female
*Triple Negative Breast Neoplasms/genetics/drug therapy/pathology
*Germ-Line Mutation
*Phthalazines/therapeutic use/administration & dosage
*BRCA2 Protein/genetics
*BRCA1 Protein/genetics
*Neoadjuvant Therapy/methods
Middle Aged
Retrospective Studies
Adult
Biomarkers, Tumor/genetics
Aged
Loss of Heterozygosity

@article {pmid39150815,
year = {2024},
author = {Wu, H and Ma, Z and Guo, Z and Wu, Y and Zhang, J and Zhou, G and Long, J},
title = {Online Privacy-Preserving EEG Classification by Source-Free Transfer Learning.},
journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TNSRE.2024.3445115},
pmid = {39150815},
issn = {1558-0210},
abstract = {Electroencephalogram (EEG) signals play an important role in brain-computer interface (BCI) applications. Recent studies have utilized transfer learning to assist the learning task in the new subject, i.e., target domain, by leveraging beneficial information from previous subjects, i.e., source domains. Nevertheless, EEG signals involve sensitive personal mental and health information. Thus, privacy concern becomes a critical issue. In addition, existing methods mostly assume that a portion of the new subject's data is available and perform alignment or adaptation between the source and target domains. However, in some practical scenarios, new subjects prefer prompt BCI utilization over the time-consuming process of collecting data for calibration and adaptation, which makes the above assumption difficult to hold. To address the above challenges, we propose Online Source-Free Transfer Learning (OSFTL) for privacy-preserving EEG classification. Specifically, the learning procedure contains offline and online stages. At the offline stage, multiple model parameters are obtained based on the EEG samples from multiple source subjects. OSFTL only needs access to these source model parameters to preserve the privacy of the source subjects. At the online stage, a target classifier is trained based on the online sequence of EEG instances. Subsequently, OSFTL learns a weighted combination of the source and target classifiers to obtain the final prediction for each target instance. Moreover, to ensure good transferability, OSFTL dynamically updates the transferred weight of each source domain based on the similarity between each source classifier and the target classifier. Comprehensive experiments on both simulated and real-world applications demonstrate the effectiveness of the proposed method, indicating the potential of OSFTL to facilitate the deployment of BCI applications outside of controlled laboratory settings.},
}

@article {pmid39149481,
year = {2024},
author = {Liu, CW and Chen, SY and Wang, YM and Lu, LY and Chen, P and Liang, TY and Liu, WC and Kumar, A and Kuo, SH and Lee, JC and Lo, CC and Wu, SC and Pan, MK},
title = {The cerebellum computes frequency dynamics for motions with numerical precision and cross-individual uniformity.},
journal = {Research square},
volume = {},
number = {},
pages = {},
pmid = {39149481},
issn = {2693-5015},
support = {R01 NS104423/NS/NINDS NIH HHS/United States ; R01 NS118179/NS/NINDS NIH HHS/United States ; R01 NS124854/NS/NINDS NIH HHS/United States ; },
abstract = {Cross-individual variability is considered the essence of biology, preventing precise mathematical descriptions of biological motion[1-7] like the physics law of motion. Here we report that the cerebellum shapes motor kinematics by encoding dynamic motor frequencies with remarkable numerical precision and cross-individual uniformity. Using in-vivo electrophysiology and optogenetics in mice, we confirmed that deep cerebellar neurons encoded frequencies via populational tuning of neuronal firing probabilities, creating cerebellar oscillations and motions with matched frequencies. The mechanism was consistently presented in self-generated rhythmic and non-rhythmic motions triggered by a vibrational platform, or skilled tongue movements of licking in all tested mice with cross-individual uniformity. The precision and uniformity allowed us to engineer complex motor kinematics with designed frequencies. We further validated the frequency-coding function of the human cerebellum using cerebellar electroencephalography recordings and alternating-current stimulation during voluntary tapping tasks. Our findings reveal a cerebellar algorithm for motor kinematics with precision and uniformity, the mathematical foundation for brain-computer interface for motor control.},
}

@article {pmid39145953,
year = {2024},
author = {O'Regan, RM and Zhang, Y and Fleming, GF and Francis, PA and Kammler, R and Viale, G and Dell'Orto, P and Lang, I and Bellet, M and Bonnefoi, HR and Tondini, C and Villa, F and Bernardo, A and Ciruelos, EM and Neven, P and Karlsson, P and Müller, B and Jochum, W and Zaman, K and Martino, S and Geyer, CE and Jerzak, KJ and Davidson, NE and Coleman, RE and Ingle, JN and van Mackelenbergh, MT and Loi, S and Colleoni, M and Schnabel, CA and Treuner, K and Regan, MM},
title = {Breast Cancer Index in Premenopausal Women With Early-Stage Hormone Receptor-Positive Breast Cancer.},
journal = {JAMA oncology},
volume = {},
number = {},
pages = {},
pmid = {39145953},
issn = {2374-2445},
abstract = {IMPORTANCE: Adjuvant ovarian function suppression (OFS) with oral endocrine therapy improves outcomes for premenopausal patients with hormone receptor-positive (HR+) breast cancer but adds adverse effects. A genomic biomarker for selecting patients most likely to benefit from OFS-based treatment is lacking.

OBJECTIVE: To assess the predictive and prognostic performance of the Breast Cancer Index (BCI) for OFS benefit in premenopausal women with HR+ breast cancer.

This prospective-retrospective translational study used all available tumor tissue samples from female patients from the Suppression of Ovarian Function Trial (SOFT). These individuals were randomized to receive 5 years of adjuvant tamoxifen alone, tamoxifen plus OFS, or exemestane plus OFS. BCI testing was performed blinded to clinical data and outcome. The a priori hypothesis was that BCI HOXB13/IL17BR ratio (BCI[H/I])-high tumors would benefit more from OFS and high BCI portended poorer prognosis in this population. Settings spanned multiple centers internationally. Participants included premenopausal female patients with HR+ early breast cancer with specimens in the International Breast Cancer Study Group tumor repository available for RNA extraction. Data were collected from December 2003 to April 2021 and were analyzed from May 2022 to October 2022.

MAIN OUTCOMES AND MEASURES: Primary end points were breast cancer-free interval (BCFI) for the predictive analysis and distant recurrence-free interval (DRFI) for the prognostic analyses.

RESULTS: Tumor specimens were available for 1718 of the 3047 female patients in the SOFT intention-to-treat population. The 1687 patients (98.2%) who had specimens that yielded sufficient RNA for BCI testing represented the parent trial population. The median (IQR) follow-up time was 12 (10.5-13.4) years, and 512 patients (30.3%) were younger than 40 years. Tumors were BCI(H/I)-low for 972 patients (57.6%) and BCI(H/I)-high for 715 patients (42.4%). Patients with tumors classified as BCI(H/I)-low exhibited a 12-year absolute benefit in BCFI of 11.6% from exemestane plus OFS (hazard ratio [HR], 0.48 [95% CI, 0.33-0.71]) and an absolute benefit of 7.3% from tamoxifen plus OFS (HR, 0.69 [95% CI, 0.48-0.97]) relative to tamoxifen alone. In contrast, patients with BCI(H/I)-high tumors did not benefit from either exemestane plus OFS (absolute benefit, -0.4%; HR, 1.03 [95% CI, 0.70-1.53]; P for interaction = .006) or tamoxifen plus OFS (absolute benefit, -1.2%; HR, 1.05 [95% CI, 0.72-1.54]; P for interaction = .11) compared with tamoxifen alone. BCI continuous index was significantly prognostic in the N0 subgroup for DRFI (n = 1110; P = .004), with 12-year DRFI of 95.9%, 90.8%, and 86.3% in BCI low-risk, intermediate-risk, and high-risk N0 cancers, respectively.

CONCLUSIONS AND RELEVANCE: In this prospective-retrospective translational study of patients enrolled in SOFT, BCI was confirmed as prognostic in premenopausal women with HR+ breast cancer. The benefit from OFS-containing adjuvant endocrine therapy was greater for patients with BCI(H/I)-low tumors than BCI(H/I)-high tumors. BCI(H/I)-low status may identify premenopausal patients who are likely to benefit from this more intensive endocrine therapy.},
}

@article {pmid39145233,
year = {2024},
author = {Lakshminarayanan, K and Ramu, V and Shah, R and Haque Sunny, MS and Madathil, D and Brahmi, B and Wang, I and Fareh, R and Rahman, MH},
title = {Developing a tablet-based brain-computer interface and robotic prototype for upper limb rehabilitation.},
journal = {PeerJ. Computer science},
volume = {10},
number = {},
pages = {e2174},
pmid = {39145233},
issn = {2376-5992},
abstract = {BACKGROUND: The current study explores the integration of a motor imagery (MI)-based BCI system with robotic rehabilitation designed for upper limb function recovery in stroke patients.

METHODS: We developed a tablet deployable BCI control of the virtual iTbot for ease of use. Twelve right-handed healthy adults participated in this study, which involved a novel BCI training approach incorporating tactile vibration stimulation during MI tasks. The experiment utilized EEG signals captured via a gel-free cap, processed through various stages including signal verification, training, and testing. The training involved MI tasks with concurrent vibrotactile stimulation, utilizing common spatial pattern (CSP) training and linear discriminant analysis (LDA) for signal classification. The testing stage introduced a real-time feedback system and a virtual game environment where participants controlled a virtual iTbot robot.

RESULTS: Results showed varying accuracies in motor intention detection across participants, with an average true positive rate of 63.33% in classifying MI signals.

DISCUSSION: The study highlights the potential of MI-based BCI in robotic rehabilitation, particularly in terms of engagement and personalization. The findings underscore the feasibility of BCI technology in rehabilitation and its potential use for stroke survivors with upper limb dysfunctions.},
}

@article {pmid39144712,
year = {2024},
author = {Kim, MS and Park, H and Kwon, I and An, KO and Shin, JH},
title = {Brain-computer interface on wrist training with or without neurofeedback in subacute stroke: a study protocol for a double-blinded, randomized control pilot trial.},
journal = {Frontiers in neurology},
volume = {15},
number = {},
pages = {1376782},
pmid = {39144712},
issn = {1664-2295},
abstract = {BACKGROUND: After a stroke, damage to the part of the brain that controls movement results in the loss of motor function. Brain-computer interface (BCI)-based stroke rehabilitation involves patients imagining movement without physically moving while the system measures the perceptual-motor rhythm in the motor cortex. Visual feedback through virtual reality and functional electrical stimulation is provided simultaneously. The superiority of real BCI over sham BCI in the subacute phase of stroke remains unclear. Therefore, we aim to compare the effects of real and sham BCI on motor function and brain activity among patients with subacute stroke with weak wrist extensor strength.

METHODS: This is a double-blinded randomized controlled trial. Patients with stroke will be categorized into real BCI and sham BCI groups. The BCI task involves wrist extension for 60 min/day, 5 times/week for 4 weeks. Twenty sessions will be conducted. The evaluation will be conducted four times, as follows: before the intervention, 2 weeks after the start of the intervention, immediately after the intervention, and 4 weeks after the intervention. The assessments include a clinical evaluation, electroencephalography, and electromyography using motor-evoked potentials.

DISCUSSION: Patients will be categorized into two groups, as follows: those who will be receiving neurofeedback and those who will not receive this feedback during the BCI rehabilitation training. We will examine the importance of motor imaging feedback, and the effect of patients' continuous participation in the training rather than their being passive.Clinical Trial Registration: KCT0008589.},
}

@article {pmid39141859,
year = {2024},
author = {Chang, EF},
title = {Brain-Computer Interfaces for Restoring Communication.},
journal = {The New England journal of medicine},
volume = {391},
number = {7},
pages = {654-657},
doi = {10.1056/NEJMe2407363},
pmid = {39141859},
issn = {1533-4406},
mesh = {Humans ; *Brain-Computer Interfaces ; Communication ; *Articulation Disorders/etiology/rehabilitation ; *Amyotrophic Lateral Sclerosis/complications/rehabilitation ; },
}

Humans
*Brain-Computer Interfaces
Communication
*Articulation Disorders/etiology/rehabilitation
*Amyotrophic Lateral Sclerosis/complications/rehabilitation

@article {pmid39141854,
year = {2024},
author = {Vansteensel, MJ and Leinders, S and Branco, MP and Crone, NE and Denison, T and Freudenburg, ZV and Geukes, SH and Gosselaar, PH and Raemaekers, M and Schippers, A and Verberne, M and Aarnoutse, EJ and Ramsey, NF},
title = {Longevity of a Brain-Computer Interface for Amyotrophic Lateral Sclerosis.},
journal = {The New England journal of medicine},
volume = {391},
number = {7},
pages = {619-626},
doi = {10.1056/NEJMoa2314598},
pmid = {39141854},
issn = {1533-4406},
support = {UH3NS114439/NS/NINDS NIH HHS/United States ; INTENSE, 17619//Nederlandse Organisatie voor Wetenschappelijk Onderzoek/ ; UGT7685, Economic Affairs SSM06011 and STW 12803//Netherlands Institute of Government/ ; U01DC016686/DC/NIDCD NIH HHS/United States ; },
mesh = {Female ; Humans ; Middle Aged ; *Amyotrophic Lateral Sclerosis/complications/diagnostic imaging/rehabilitation ; *Atrophy/diagnostic imaging/etiology/prevention & control ; Brain/diagnostic imaging ; *Brain-Computer Interfaces ; Communication Aids for Disabled ; Time Factors ; Treatment Failure ; Electrodes, Implanted ; },
abstract = {The durability of communication with the use of brain-computer interfaces in persons with progressive neurodegenerative disease has not been extensively examined. We report on 7 years of independent at-home use of an implanted brain-computer interface for communication by a person with advanced amyotrophic lateral sclerosis (ALS), the inception of which was reported in 2016. The frequency of at-home use increased over time to compensate for gradual loss of control of an eye-gaze-tracking device, followed by a progressive decrease in use starting 6 years after implantation. At-home use ended when control of the brain-computer interface became unreliable. No signs of technical malfunction were found. Instead, the amplitude of neural signals declined, and computed tomographic imaging revealed progressive atrophy, which suggested that ALS-related neurodegeneration ultimately rendered the brain-computer interface ineffective after years of successful use, although alternative explanations are plausible. (Funded by the National Institute on Deafness and Other Communication Disorders and others; ClinicalTrials.gov number, NCT02224469.).},
}

Female
Humans
Middle Aged
*Amyotrophic Lateral Sclerosis/complications/diagnostic imaging/rehabilitation
*Atrophy/diagnostic imaging/etiology/prevention & control
Brain/diagnostic imaging
*Brain-Computer Interfaces
Communication Aids for Disabled
Time Factors
Treatment Failure
Electrodes, Implanted

@article {pmid39141853,
year = {2024},
author = {Card, NS and Wairagkar, M and Iacobacci, C and Hou, X and Singer-Clark, T and Willett, FR and Kunz, EM and Fan, C and Vahdati Nia, M and Deo, DR and Srinivasan, A and Choi, EY and Glasser, MF and Hochberg, LR and Henderson, JM and Shahlaie, K and Stavisky, SD and Brandman, DM},
title = {An Accurate and Rapidly Calibrating Speech Neuroprosthesis.},
journal = {The New England journal of medicine},
volume = {391},
number = {7},
pages = {609-618},
pmid = {39141853},
issn = {1533-4406},
support = {U01DC17844/DC/NIDCD NIH HHS/United States ; AL220043//Congressionally Directed Medical Research Programs/ ; U01 DC019430/DC/NIDCD NIH HHS/United States ; 872146SPI//Simons Foundation/ ; A2295-R//U.S. Department of Veterans Affairs/ ; DP2DC021055/DC/NIDCD NIH HHS/United States ; U01DC019430/DC/NIDCD NIH HHS/United States ; I01 RX002295/RX/RRD VA/United States ; DP2 DC021055/DC/NIDCD NIH HHS/United States ; U01 DC017844/DC/NIDCD NIH HHS/United States ; },
mesh = {Humans ; Male ; Middle Aged ; *Amyotrophic Lateral Sclerosis/complications/rehabilitation ; *Brain-Computer Interfaces ; Calibration ; Communication Aids for Disabled ; *Dysarthria/rehabilitation/etiology ; Electrodes, Implanted ; Microelectrodes ; Quadriplegia/etiology/rehabilitation ; *Speech ; },
abstract = {BACKGROUND: Brain-computer interfaces can enable communication for people with paralysis by transforming cortical activity associated with attempted speech into text on a computer screen. Communication with brain-computer interfaces has been restricted by extensive training requirements and limited accuracy.

METHODS: A 45-year-old man with amyotrophic lateral sclerosis (ALS) with tetraparesis and severe dysarthria underwent surgical implantation of four microelectrode arrays into his left ventral precentral gyrus 5 years after the onset of the illness; these arrays recorded neural activity from 256 intracortical electrodes. We report the results of decoding his cortical neural activity as he attempted to speak in both prompted and unstructured conversational contexts. Decoded words were displayed on a screen and then vocalized with the use of text-to-speech software designed to sound like his pre-ALS voice.

RESULTS: On the first day of use (25 days after surgery), the neuroprosthesis achieved 99.6% accuracy with a 50-word vocabulary. Calibration of the neuroprosthesis required 30 minutes of cortical recordings while the participant attempted to speak, followed by subsequent processing. On the second day, after 1.4 additional hours of system training, the neuroprosthesis achieved 90.2% accuracy using a 125,000-word vocabulary. With further training data, the neuroprosthesis sustained 97.5% accuracy over a period of 8.4 months after surgical implantation, and the participant used it to communicate in self-paced conversations at a rate of approximately 32 words per minute for more than 248 cumulative hours.

CONCLUSIONS: In a person with ALS and severe dysarthria, an intracortical speech neuroprosthesis reached a level of performance suitable to restore conversational communication after brief training. (Funded by the Office of the Assistant Secretary of Defense for Health Affairs and others; BrainGate2 ClinicalTrials.gov number, NCT00912041.).},
}

Humans
Male
Middle Aged
*Amyotrophic Lateral Sclerosis/complications/rehabilitation
*Brain-Computer Interfaces
Calibration
Communication Aids for Disabled
*Dysarthria/rehabilitation/etiology
Electrodes, Implanted
Microelectrodes
Quadriplegia/etiology/rehabilitation
*Speech

@article {pmid39141851,
year = {2024},
author = {},
title = {Restoring Lost Speech: ITT Episode 36.},
journal = {The New England journal of medicine},
volume = {391},
number = {7},
pages = {e13},
doi = {10.1056/NEJMp2407613},
pmid = {39141851},
issn = {1533-4406},
mesh = {Humans ; *Brain-Computer Interfaces ; *Neurodegenerative Diseases/complications/rehabilitation ; *Speech Disorders/etiology/rehabilitation ; Webcasts as Topic ; },
}

Humans
*Brain-Computer Interfaces
*Neurodegenerative Diseases/complications/rehabilitation
*Speech Disorders/etiology/rehabilitation
Webcasts as Topic

@article {pmid39140323,
year = {2024},
author = {Nakamura, T and He, X and Hattori, N and Hida, E and Hirata, M},
title = {Dilemma in patients with amyotrophic lateral sclerosis and expectations from brain-machine interfaces.},
journal = {Annals of medicine},
volume = {56},
number = {1},
pages = {2386516},
pmid = {39140323},
issn = {1365-2060},
mesh = {Humans ; *Amyotrophic Lateral Sclerosis/psychology/therapy ; *Brain-Computer Interfaces ; Male ; Female ; Middle Aged ; Aged ; Surveys and Questionnaires ; *Motivation ; *Caregivers/psychology ; *Anxiety/psychology/etiology ; Adult ; Tracheostomy ; Caregiver Burden/psychology ; Locked-In Syndrome/psychology ; },
abstract = {OBJECTIVE: We hypothesized that patients with amyotrophic lateral sclerosis (ALS) face a dilemma between motivation to live and difficulty in living, and brain-machine interfaces (BMIs) can reduce this dilemma. This study aimed to investigate the present situation of patients with ALS and their expectations from BMIs.

MATERIALS AND METHODS: Our survey design consisted of an anonymous mail-in questionnaire comprising questions regarding the use of tracheostomy positive pressure ventilation (TPPV), motivation to live, anxiety about the totally locked-in state (TLS), anxiety about caregiver burden, and expectations regarding the use of BMI. Primary outcomes were scores for motivation to live and anxiety about caregiver burden and the TLS. Outcomes were evaluated using the visual analogue scale.

RESULTS: Among 460 participants, 286 (62.6%) were already supported by or had decided to use TPPV. The median scores for motivation to live, anxiety about TLS, and anxiety about caregiver burden were 8.0, 9.0, and 7.0, respectively. Overall, 49% of patients intended to use BMI. Among patients who had refused TPPV, 15.9% intended to use BMI and TPPV. Significant factors for the use of BMI were motivation to live (p = .003), anxiety about TLS (p < .001), younger age (p < .001), and advanced disease stage (p < .001).

CONCLUSIONS: These results clearly revealed a serious dilemma among patients with ALS between motivation to live and their anxiety about TLS and caregiver burden. Patients expected BMI to reduce this dilemma. Thus, the development of better BMIs may meet these expectations.},
}

Humans
*Amyotrophic Lateral Sclerosis/psychology/therapy
*Brain-Computer Interfaces
Male
Female
Middle Aged
Aged
Surveys and Questionnaires
*Motivation
*Caregivers/psychology
*Anxiety/psychology/etiology
Adult
Tracheostomy
Caregiver Burden/psychology
Locked-In Syndrome/psychology

@article {pmid39139629,
year = {2024},
author = {Liu, X and Mu, J and Pang, M and Fan, X and Zhou, Z and Guo, F and Yu, K and Yu, H and Ming, D},
title = {A Male Patient with Hydrocephalus via Multimodality Diagnostic Approaches: A Case Report.},
journal = {Cyborg and bionic systems (Washington, D.C.)},
volume = {5},
number = {},
pages = {0135},
pmid = {39139629},
issn = {2692-7632},
abstract = {Introduction: Idiopathic normal pressure hydrocephalus (iNPH) is a kind of hydrocephalus that is easily to be misdiagnosed with brain atrophy due to the similarity of ventricular dilation and cognitive impairment. In this case, we present an old male patient who was diagnosed with iNPH by multimodality approaches. Outcomes: A 68-year-old male patient, with deteriorated gait, declined cognitive function for at least 3 years and urinary incontinence for 3 months. The doctors suspected him a patient with hydrocephalus or Alzheimer's disease based on his symptoms. We used multimodality diagnostic approaches including brain imaging, cerebrospinal fluid tap test, continuous intracranial pressure monitoring, and infusion study to make the final diagnosis of iNPH. He underwent ventriculoperitoneal shunt surgery and was well recovered. Conclusion: This case demonstrates the efficacy of using multimodality approaches for iNPH diagnosis, which saves patient time and clinical cost, worthy of further promotion.},
}

@article {pmid39138452,
year = {2024},
author = {Starke, G and Akmazoglu, TB and Colucci, A and Vermehren, M and van Beinum, A and Buthut, M and Soekadar, SR and Bublitz, C and Chandler, JA and Ienca, M},
title = {Qualitative studies involving users of clinical neurotechnology: a scoping review.},
journal = {BMC medical ethics},
volume = {25},
number = {1},
pages = {89},
pmid = {39138452},
issn = {1472-6939},
support = {HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B),//ERA-NET NEURON/ ; NGBMI (759370)//European Research Council (ERC)/ ; NGBMI (759370)//European Research Council (ERC)/ ; NGBMI (759370)//European Research Council (ERC)/ ; NGBMI (759370)//European Research Council (ERC)/ ; SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486)//Federal Ministry of Research and Education (BMBF)/ ; SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486)//Federal Ministry of Research and Education (BMBF)/ ; SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486)//Federal Ministry of Research and Education (BMBF)/ ; SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486)//Federal Ministry of Research and Education (BMBF)/ ; A-2019-558//Einstein Foundation Berlin/ ; A-2019-558//Einstein Foundation Berlin/ ; A-2019-558//Einstein Foundation Berlin/ ; A-2019-558//Einstein Foundation Berlin/ ; },
mesh = {Humans ; *Qualitative Research ; *Brain-Computer Interfaces ; Self Concept ; },
abstract = {BACKGROUND: The rise of a new generation of intelligent neuroprostheses, brain-computer interfaces (BCI) and adaptive closed-loop brain stimulation devices hastens the clinical deployment of neurotechnologies to treat neurological and neuropsychiatric disorders. However, it remains unclear how these nascent technologies may impact the subjective experience of their users. To inform this debate, it is crucial to have a solid understanding how more established current technologies already affect their users. In recent years, researchers have used qualitative research methods to explore the subjective experience of individuals who become users of clinical neurotechnology. Yet, a synthesis of these more recent findings focusing on qualitative methods is still lacking.

METHODS: To address this gap in the literature, we systematically searched five databases for original research articles that investigated subjective experiences of persons using or receiving neuroprosthetics, BCIs or neuromodulation with qualitative interviews and raised normative questions.

RESULTS: 36 research articles were included and analysed using qualitative content analysis. Our findings synthesise the current scientific literature and reveal a pronounced focus on usability and other technical aspects of user experience. In parallel, they highlight a relative neglect of considerations regarding agency, self-perception, personal identity and subjective experience.

CONCLUSIONS: Our synthesis of the existing qualitative literature on clinical neurotechnology highlights the need to expand the current methodological focus as to investigate also non-technical aspects of user experience. Given the critical role considerations of agency, self-perception and personal identity play in assessing the ethical and legal significance of these technologies, our findings reveal a critical gap in the existing literature. This review provides a comprehensive synthesis of the current qualitative research landscape on neurotechnology and the limitations thereof. These findings can inform researchers on how to study the subjective experience of neurotechnology users more holistically and build patient-centred neurotechnology.},
}

Humans
*Qualitative Research
*Brain-Computer Interfaces
Self Concept

@article {pmid39138070,
year = {2024},
author = {Zhou, S and Chen, W and Yang, H},
title = {Dopamine.},
journal = {Trends in endocrinology and metabolism: TEM},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.tem.2024.07.005},
pmid = {39138070},
issn = {1879-3061},
}

@article {pmid39137009,
year = {2024},
author = {Denis-Robichaud, J and Rees, EE and Daley, P and Zarowsky, C and Diouf, A and Nasri, BR and de Montigny, S and Carabin, H},
title = {Linking Opinions Shared on Social Media About COVID-19 Public Health Measures to Adherence: Repeated Cross-Sectional Surveys of Twitter Use in Canada.},
journal = {Journal of medical Internet research},
volume = {26},
number = {},
pages = {e51325},
doi = {10.2196/51325},
pmid = {39137009},
issn = {1438-8871},
mesh = {Humans ; *COVID-19/prevention & control ; Cross-Sectional Studies ; Canada ; *Social Media/statistics & numerical data ; Adult ; Male ; Female ; *Public Health ; Middle Aged ; Bayes Theorem ; Young Adult ; Masks/statistics & numerical data ; Aged ; SARS-CoV-2 ; Surveys and Questionnaires ; Adolescent ; Patient Compliance/statistics & numerical data ; Self Report ; Vaccination/statistics & numerical data ; },
abstract = {BACKGROUND: The effectiveness of public health measures (PHMs) depends on population adherence. Social media were suggested as a tool to assess adherence, but representativeness and accuracy issues have been raised.

OBJECTIVE: The objectives of this repeated cross-sectional study were to compare self-reported PHM adherence and sociodemographic characteristics between people who used Twitter (subsequently rebranded X) and people who did not use Twitter.

METHODS: Repeated Canada-wide web-based surveys were conducted every 14 days from September 2020 to March 2022. Weighted proportions were calculated for descriptive variables. Using Bayesian logistic regression models, we investigated associations between Twitter use, as well as opinions in tweets, and self-reported adherence with mask wearing and vaccination.

RESULTS: Data from 40,230 respondents were analyzed. As self-reported, Twitter was used by 20.6% (95% CI 20.1%-21.2%) of Canadians, of whom 29.9% (95% CI 28.6%-31.3%) tweeted about COVID-19. The sociodemographic characteristics differed across categories of Twitter use and opinions. Overall, 11% (95% CI 10.6%-11.3%) of Canadians reported poor adherence to mask-wearing, and 10.8% (95% CI 10.4%-11.2%) to vaccination. Twitter users who tweeted about COVID-19 reported poorer adherence to mask wearing than nonusers, which was modified by the age of the respondents and their geographical region (odds ratio [OR] 0.79, 95% Bayesian credibility interval [BCI] 0.18-1.69 to OR 4.83, 95% BCI 3.13-6.86). The odds of poor adherence to vaccination of Twitter users who tweeted about COVID-19 were greater than those of nonusers (OR 1.76, 95% BCI 1.48-2.07). English- and French-speaking Twitter users who tweeted critically of PHMs were more likely (OR 4.07, 95% BCI 3.38-4.80 and OR 7.31, 95% BCI 4.26-11.03, respectively) to report poor adherence to mask wearing than non-Twitter users, and those who tweeted in support were less likely (OR 0.47, 95% BCI 0.31-0.64 and OR 0.96, 95% BCI 0.18-2.33, respectively) to report poor adherence to mask wearing than non-Twitter users. The OR of poor adherence to vaccination for those tweeting critically about PHMs and for those tweeting in support of PHMs were 4.10 (95% BCI 3.40-4.85) and 0.20 (95% BCI 0.10-0.32), respectively, compared to non-Twitter users.

CONCLUSIONS: Opinions shared on Twitter can be useful to public health authorities, as they are associated with adherence to PHMs. However, the sociodemographics of social media users do not represent the general population, calling for caution when using tweets to assess general population-level behaviors.},
}

Humans
*COVID-19/prevention & control
Cross-Sectional Studies
Canada
*Social Media/statistics & numerical data
Adult
Male
Female
*Public Health
Middle Aged
Bayes Theorem
Young Adult
Masks/statistics & numerical data
Aged
SARS-CoV-2
Surveys and Questionnaires
Adolescent
Patient Compliance/statistics & numerical data
Self Report
Vaccination/statistics & numerical data

@article {pmid39136271,
year = {2024},
author = {Tong, L and Zhang, D and Huang, Z and Gao, F and Zhang, S and Chen, F and Liu, C},
title = {Calcium Ion-Coupled Polyphosphates with Different Degrees of Polymerization for Bleeding Control.},
journal = {ACS applied materials & interfaces},
volume = {},
number = {},
pages = {},
doi = {10.1021/acsami.4c06698},
pmid = {39136271},
issn = {1944-8252},
abstract = {The development of efficient hemostatic materials is crucial for achieving rapid hemorrhage control and effective wound healing. Inorganic polyphosphate (polyP) is recognized as an effective modulator of the blood coagulation process. However, the specific effect of polyP chain length on coagulation is not yet fully understood. Furthermore, calcium ions (Ca[2+]) are essential for the coagulation process, promoting multiple enzyme-catalyzed reactions within the coagulation cascade. Hence, calcium ion-coupled polyphosphate powders with three different degrees of polymerization (CaPP-n, n = 20, 50, and 1500) are synthesized by an ion-exchange reaction. CaPP exhibits a crystalline phase at a low polymerization degree and transitions to an amorphous phase as the polymerization degree increases. Notably, the addition of Ca[2+] enhances the wettability of polyP, and CaPP promotes hemostasis, with varying degrees of effectiveness related to chain length. CaPP-50 exhibits the most promising hemostatic performance, with the lowest blood clotting index (BCI, 12.1 ± 0.7%) and the shortest clotting time (302.0 ± 10.5 s). By combining Ca[2+] with polyP of medium-chain length, CaPP-50 demonstrates an enhanced ability to accelerate the adhesion and activation of blood cells, initiate the intrinsic coagulation cascade, and form a stable blood clot, outperforming both CaPP-20 and CaPP-1500. The hemostatic efficacy of CaPP-50 is further validated using rat liver bleeding and femoral artery puncture models. CaPP-50 is proven to possess hemostatic properties comparable to those of commercial calcium-based zeolite hemostatic powder and superior to kaolin. In addition, CaPP-50 exhibits excellent biocompatibility and long-term storage stability. These results suggest that CaPP-50 has significant clinical and commercial potential as an active inorganic hemostatic agent for rapid control of bleeding.},
}

@article {pmid39135208,
year = {2024},
author = {Liu, XY and Song, X and Czosnyka, M and Robba, C and Czosnyka, Z and Summers, JL and Yu, HJ and Gao, GY and Smielewski, P and Guo, F and Pang, MJ and Ming, D},
title = {Congenital hydrocephalus: a review of recent advances in genetic etiology and molecular mechanisms.},
journal = {Military Medical Research},
volume = {11},
number = {1},
pages = {54},
pmid = {39135208},
issn = {2054-9369},
support = {2021YFF1200602//National Key Technologies Research and Development Program/ ; },
mesh = {Humans ; *Hydrocephalus/genetics/etiology ; Animals ; Genetic Predisposition to Disease ; },
abstract = {The global prevalence rate for congenital hydrocephalus (CH) is approximately one out of every five hundred births with multifaceted predisposing factors at play. Genetic influences stand as a major contributor to CH pathogenesis, and epidemiological evidence suggests their involvement in up to 40% of all cases observed globally. Knowledge about an individual's genetic susceptibility can significantly improve prognostic precision while aiding clinical decision-making processes. However, the precise genetic etiology has only been pinpointed in fewer than 5% of human instances. More occurrences of CH cases are required for comprehensive gene sequencing aimed at uncovering additional potential genetic loci. A deeper comprehension of its underlying genetics may offer invaluable insights into the molecular and cellular basis of this brain disorder. This review provides a summary of pertinent genes identified through gene sequencing technologies in humans, in addition to the 4 genes currently associated with CH (two X-linked genes L1CAM and AP1S2, two autosomal recessive MPDZ and CCDC88C). Others predominantly participate in aqueduct abnormalities, ciliary movement, and nervous system development. The prospective CH-related genes revealed through animal model gene-editing techniques are further outlined, focusing mainly on 4 pathways, namely cilia synthesis and movement, ion channels and transportation, Reissner's fiber (RF) synthesis, cell apoptosis, and neurogenesis. Notably, the proper functioning of motile cilia provides significant impulsion for cerebrospinal fluid (CSF) circulation within the brain ventricles while mutations in cilia-related genes constitute a primary cause underlying this condition. So far, only a limited number of CH-associated genes have been identified in humans. The integration of genotype and phenotype for disease diagnosis represents a new trend in the medical field. Animal models provide insights into the pathogenesis of CH and contribute to our understanding of its association with related complications, such as renal cysts, scoliosis, and cardiomyopathy, as these genes may also play a role in the development of these diseases. Genes discovered in animals present potential targets for new treatments but require further validation through future human studies.},
}

Humans
*Hydrocephalus/genetics/etiology
Animals
Genetic Predisposition to Disease

@article {pmid39134592,
year = {2024},
author = {Krueger, J and Krauth, R and Reichert, C and Perdikis, S and Vogt, S and Huchtemann, T and Dürschmid, S and Sickert, A and Lamprecht, J and Huremovic, A and Görtler, M and Nasuto, SJ and Tsai, IC and Knight, RT and Hinrichs, H and Heinze, HJ and Lindquist, S and Sailer, M and Millán, JDR and Sweeney-Reed, CM},
title = {Hebbian plasticity induced by temporally coincident BCI enhances post-stroke motor recovery.},
journal = {Scientific reports},
volume = {14},
number = {1},
pages = {18700},
pmid = {39134592},
issn = {2045-2322},
mesh = {Humans ; *Brain-Computer Interfaces ; Male ; *Neuronal Plasticity ; Female ; *Stroke Rehabilitation/methods ; Middle Aged ; *Stroke/physiopathology/complications ; Aged ; *Electroencephalography ; *Recovery of Function ; *Motor Cortex/physiopathology ; *Transcranial Magnetic Stimulation/methods ; *Evoked Potentials, Motor ; },
abstract = {Functional electrical stimulation (FES) can support functional restoration of a paretic limb post-stroke. Hebbian plasticity depends on temporally coinciding pre- and post-synaptic activity. A tight temporal relationship between motor cortical (MC) activity associated with attempted movement and FES-generated visuo-proprioceptive feedback is hypothesized to enhance motor recovery. Using a brain-computer interface (BCI) to classify MC spectral power in electroencephalographic (EEG) signals to trigger FES-delivery with detection of movement attempts improved motor outcomes in chronic stroke patients. We hypothesized that heightened neural plasticity earlier post-stroke would further enhance corticomuscular functional connectivity and motor recovery. We compared subcortical non-dominant hemisphere stroke patients in BCI-FES and Random-FES (FES temporally independent of MC movement attempt detection) groups. The primary outcome measure was the Fugl-Meyer Assessment, Upper Extremity (FMA-UE). We recorded high-density EEG and transcranial magnetic stimulation-induced motor evoked potentials before and after treatment. The BCI group showed greater: FMA-UE improvement; motor evoked potential amplitude; beta oscillatory power and long-range temporal correlation reduction over contralateral MC; and corticomuscular coherence with contralateral MC. These changes are consistent with enhanced post-stroke motor improvement when movement is synchronized with MC activity reflecting attempted movement.},
}

Humans
*Brain-Computer Interfaces
Male
*Neuronal Plasticity
Female
*Stroke Rehabilitation/methods
Middle Aged
*Stroke/physiopathology/complications
Aged
*Electroencephalography
*Recovery of Function
*Motor Cortex/physiopathology
*Transcranial Magnetic Stimulation/methods
*Evoked Potentials, Motor

@article {pmid39134021,
year = {2024},
author = {Bashford, L and Rosenthal, IA and Kellis, S and Bjanes, D and Pejsa, K and Brunton, BW and Andersen, RA},
title = {Neural subspaces of imagined movements in parietal cortex remain stable over several years in humans.},
journal = {Journal of neural engineering},
volume = {},
number = {},
pages = {},
doi = {10.1088/1741-2552/ad6e19},
pmid = {39134021},
issn = {1741-2552},
abstract = {Objective A crucial goal in brain-machine interfacing is the long-term stability of neural decoding performance, ideally without regular retraining. Long-term stability has only been previously demonstrated in non-human primate experiments and only in primary sensorimotor cortices. Here we extend previous methods to determine long-term stability in humans by identifying and aligning low-dimensional structures in neural data. Approach Over a period of 1106 and 871 days respectively, two participants completed an imagined center-out reaching task. The longitudinal accuracy between all day pairs was assessed by latent subspace alignment using principal components analysis and canonical correlations analysis of multi-unit intracortical recordings in different brain regions (Brodmann Area 5, Anterior Intraparietal Area and the junction of the postcentral and intraparietal sulcus). Main Results We show the long-term stable representation of neural activity in subspaces of intracortical recordings from higher-order association areas in humans. Significance These results can be practically applied to significantly expand the longevity and generalizability of brain-computer interfaces. Clinical Trials NCT01849822, NCT01958086, NCT01964261.},
}

@article {pmid39133845,
year = {2024},
author = {Wong, MMK and Sha, Z and Lütje, L and Kong, XZ and van Heukelum, S and van de Berg, WDJ and Jonkman, LE and Fisher, SE and Francks, C},
title = {The neocortical infrastructure for language involves region-specific patterns of laminar gene expression.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {121},
number = {34},
pages = {e2401687121},
doi = {10.1073/pnas.2401687121},
pmid = {39133845},
issn = {1091-6490},
support = {N/A//Max Planck Instituut voor Psycholinguïstiek (MAX-PLANCK-INSTITUT)/ ; 024.001.006//Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)/ ; },
mesh = {Humans ; *Neocortex/metabolism ; *Language ; Temporal Lobe/metabolism ; Male ; Female ; Schizophrenia/genetics/metabolism ; Neurons/metabolism ; Frontal Lobe/metabolism ; Transcriptome ; Adult ; },
abstract = {The language network of the human brain has core components in the inferior frontal cortex and superior/middle temporal cortex, with left-hemisphere dominance in most people. Functional specialization and interconnectivity of these neocortical regions is likely to be reflected in their molecular and cellular profiles. Excitatory connections between cortical regions arise and innervate according to layer-specific patterns. Here, we generated a gene expression dataset from human postmortem cortical tissue samples from core language network regions, using spatial transcriptomics to discriminate gene expression across cortical layers. Integration of these data with existing single-cell expression data identified 56 genes that showed differences in laminar expression profiles between the frontal and temporal language cortex together with upregulation in layer II/III and/or layer V/VI excitatory neurons. Based on data from large-scale genome-wide screening in the population, DNA variants within these 56 genes showed set-level associations with interindividual variation in structural connectivity between the left-hemisphere frontal and temporal language cortex, and with the brain-related disorders dyslexia and schizophrenia which often involve affected language. These findings identify region-specific patterns of laminar gene expression as a feature of the brain's language network.},
}

Humans
*Neocortex/metabolism
*Language
Temporal Lobe/metabolism
Male
Female
Schizophrenia/genetics/metabolism
Neurons/metabolism
Frontal Lobe/metabolism
Transcriptome
Adult

@article {pmid39133589,
year = {2024},
author = {Zhang, Z and He, Y and Mai, W and Luo, Y and Li, X and Cheng, Y and Huang, X and Lin, R},
title = {Convolutional Dynamically Convergent Differential Neural Network for Brain Signal Classification.},
journal = {IEEE transactions on neural networks and learning systems},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TNNLS.2024.3437676},
pmid = {39133589},
issn = {2162-2388},
abstract = {The brain signal classification is the basis for the implementation of brain-computer interfaces (BCIs). However, most existing brain signal classification methods are based on signal processing technology, which require a significant amount of manual intervention, such as channel selection and dimensionality reduction, and often struggle to achieve satisfactory classification accuracy. To achieve high classification accuracy and as little manual intervention as possible, a convolutional dynamically convergent differential neural network (ConvDCDNN) is proposed for solving the electroencephalography (EEG) signal classification problem. First, a single-layer convolutional neural network is used to replace the preprocessing steps in previous work. Then, focal loss is used to overcome the imbalance in the dataset. After that, a novel automatic dynamic convergence learning (ADCL) algorithm is proposed and proved for training neural networks. Experimental results on the BCI Competition 2003, BCI Competition III A, and BCI Competition III B datasets demonstrate that the proposed ConvDCDNN framework achieved state-of-the-art performance with accuracies of 100%, 99%, and 98%, respectively. In addition, the proposed algorithm exhibits a higher information transfer rate (ITR) compared with current algorithms.},
}

@article {pmid39132484,
year = {2024},
author = {Kunigk, NG and Schone, HR and Gontier, C and Hockeimer, W and Tortolani, AF and Hatsopoulos, NG and Downey, JE and Chase, SM and Boninger, ML and Dekleva, BD and Collinger, JL},
title = {Motor somatotopy impacts imagery strategy success in human intracortical brain-computer interfaces.},
journal = {medRxiv : the preprint server for health sciences},
volume = {},
number = {},
pages = {},
pmid = {39132484},
support = {R01 NS121079/NS/NINDS NIH HHS/United States ; UH3 NS107714/NS/NINDS NIH HHS/United States ; },
abstract = {The notion of a somatotopically organized motor cortex, with movements of different body parts being controlled by spatially distinct areas of cortex, is well known. However, recent studies have challenged this notion and suggested a more distributed representation of movement control. This shift in perspective has significant implications, particularly when considering the implantation location of electrode arrays for intracortical brain-computer interfaces (iBCIs). We sought to evaluate whether the location of neural recordings from the precentral gyrus, and thus the underlying somatotopy, has any impact on the imagery strategies that can enable successful iBCI control. Three individuals with a spinal cord injury were enrolled in an ongoing clinical trial of an iBCI. Participants had two intracortical microelectrode arrays implanted in the arm and/or hand areas of the precentral gyrus based on presurgical functional imaging. Neural data were recorded while participants attempted to perform movements of the hand, wrist, elbow, and shoulder. We found that electrode arrays that were located more medially recorded significantly more activity during attempted proximal arm movements (elbow, shoulder) than did lateral arrays, which captured more activity related to attempted distal arm movements (hand, wrist). We also evaluated the relative contribution from the two arrays implanted in each participant to decoding accuracy during calibration of an iBCI decoder for translation and grasping tasks. For both task types, imagery strategy (e.g., reaching vs. wrist movements) had a significant impact on the relative contributions of each array to decoding. Overall, we found some evidence of broad tuning to arm and hand movements; however, there was a clear bias in the amount of information accessible about each movement type in spatially distinct areas of cortex. These results demonstrate that classical concepts of somatotopy can have real consequences for iBCI use, and highlight the importance of considering somatotopy when planning iBCI implantation.},
}

@article {pmid39131629,
year = {2024},
author = {Huang, Z and Zhang, D and Tong, L and Gao, F and Zhang, S and Wang, X and Xie, Y and Chen, F and Liu, C},
title = {Protonated-chitosan sponge with procoagulation activity for hemostasis in coagulopathy.},
journal = {Bioactive materials},
volume = {41},
number = {},
pages = {174-192},
pmid = {39131629},
issn = {2452-199X},
abstract = {Hemostatic materials are essential for managing acute bleeding in medical settings. Chitosan (CS) shows promise in hemostasis but its underlying mechanism remains incompletely understood. We unexpectedly discovered that certain protonated-chitosan (PCS) rapidly assembled plasma proteins to form protein membrane (PM) upon contact with platelet-poor plasma (PPP). We hypothesized that the novel observation was intricately related to the procoagulant effect of chitosan. Herein, the study aimed to elucidate the conditions necessary and mechanism for PM formation, identify the proteins within the PM and PCS's procoagulant action at the molecule levels. We confirmed that the amount of -NH3 [+] groups (>4.9 mmol/g) on PCS molecules played a crucial role in promoting coagulation. The -NH3 [+] group interacted with blood's multiple active components to exert hemostatic effects: assembling plasma proteins including coagulation factors such as FII, FV, FX, activating blood cells and promoting the secretion of coagulation-related substances (FV, ADP, etc) by platelets. Notably, the hemostatic mechanism can be extended to protonated-chitosan derivatives like quaternized, alkylated, and catechol-chitosan. In the blood clotting index (BCI) experiment, compared to other groups, PCS95 achieved the lowest BCI value (∼6 %) within 30 s. Protonated-chitosan exhibited excellent biocompatibility and antibacterial properties, with PCS95 demonstrating inhibition effectiveness of over 95 % against Escherichia coli (E.coil) and Staphylococcus aureus (S. aureus). Moreover, PCS performed enhanced hemostatic effectiveness over chitosan-based commercially agents (Celox™ and ChitoGauze®XR) in diverse bleeding models. In particular, PCS95 reduced bleeding time by 70 % in rabbit models of coagulopathy. Overall, this study investigated the coagulation mechanism of materials at the molecular level, paving the way for innovative approaches in designing new hemostatic materials.},
}

@article {pmid39131333,
year = {2024},
author = {Tortolani, AF and Kunigk, NG and Sobinov, AR and Boninger, ML and Bensmaia, SJ and Collinger, JL and Hatsopoulos, NG and Downey, JE},
title = {How different immersive environments affect intracortical brain computer interfaces.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
pmid = {39131333},
issn = {2692-8205},
support = {R01 NS130302/NS/NINDS NIH HHS/United States ; T32 NS121763/NS/NINDS NIH HHS/United States ; UH3 NS107714/NS/NINDS NIH HHS/United States ; },
abstract = {As brain-computer interface (BCI) research advances, many new applications are being developed. Tasks can be performed in different environments, and whether a BCI user can switch environments seamlessly will influence the ultimate utility of a clinical device. Here we investigate the importance of the immersiveness of the virtual environment used to train BCI decoders on the resulting decoder and its generalizability between environments. Two participants who had intracortical electrodes implanted in their precentral gyrus used a BCI to control a virtual arm, either viewed immersively through virtual reality goggles or at a distance on a flat television monitor. Each participant performed better with a decoder trained and tested in the environment they had used the most prior to the study, one for each environment type. The neural tuning to the desired movement was minimally influenced by the immersiveness of the environment. Finally, in further testing with one of the participants, we found that decoders trained in one environment generalized well to the other environment, but the order in which the environments were experienced within a session mattered. Overall, experience with an environment was more influential on performance than the immersiveness of the environment, but BCI performance generalized well after accounting for experience.},
}

@article {pmid39130131,
year = {2024},
author = {Ferro, MD and Proctor, CM and Gonzalez, A and Jayabal, S and Zhao, E and Gagnon, M and Slézia, A and Pas, J and Dijk, G and Donahue, MJ and Williamson, A and Raymond, J and Malliaras, GG and Giocomo, L and Melosh, NA},
title = {NeuroRoots, a bio-inspired, seamless brain machine interface for long-term recording in delicate brain regions.},
journal = {AIP advances},
volume = {14},
number = {8},
pages = {085109},
pmid = {39130131},
issn = {2158-3226},
abstract = {Scalable electronic brain implants with long-term stability and low biological perturbation are crucial technologies for high-quality brain-machine interfaces that can seamlessly access delicate and hard-to-reach regions of the brain. Here, we created "NeuroRoots," a biomimetic multi-channel implant with similar dimensions (7 μm wide and 1.5 μm thick), mechanical compliance, and spatial distribution as axons in the brain. Unlike planar shank implants, these devices consist of a number of individual electrode "roots," each tendril independent from the other. A simple microscale delivery approach based on commercially available apparatus minimally perturbs existing neural architectures during surgery. NeuroRoots enables high density single unit recording from the cerebellum in vitro and in vivo. NeuroRoots also reliably recorded action potentials in various brain regions for at least 7 weeks during behavioral experiments in freely-moving rats, without adjustment of electrode position. This minimally invasive axon-like implant design is an important step toward improving the integration and stability of brain-machine interfacing.},
}

@article {pmid39127752,
year = {2024},
author = {Wei, W and Wang, K and Qiu, S and He, H},
title = {A MultiModal Vigilance (MMV) dataset during RSVP and SSVEP brain-computer interface tasks.},
journal = {Scientific data},
volume = {11},
number = {1},
pages = {867},
pmid = {39127752},
issn = {2052-4463},
mesh = {Humans ; *Brain-Computer Interfaces ; *Electroencephalography ; *Evoked Potentials, Visual ; Eye Movements ; Electrocardiography ; Electrooculography ; Electromyography ; Male ; Attention ; },
abstract = {Vigilance represents an ability to sustain prolonged attention and plays a crucial role in ensuring the reliability and optimal performance of various tasks. In this report, we describe a MultiModal Vigilance (MMV) dataset comprising seven physiological signals acquired during two Brain-Computer Interface (BCI) tasks. The BCI tasks encompass a rapid serial visual presentation (RSVP)-based target image retrieval task and a steady-state visual evoked potential (SSVEP)-based cursor-control task. The MMV dataset includes four sessions of seven physiological signals for 18 subjects, which encompasses electroencephalogram(EEG), electrooculogram (EOG), electrocardiogram (ECG), photoplethysmogram (PPG), electrodermal activity (EDA), electromyogram (EMG), and eye movement. The MMV dataset provides data from four stages: 1) raw data, 2) pre-processed data, 3) trial data, and 4) feature data that can be directly used for vigilance estimation. We believe this dataset will achieve flexible reuse and meet the various needs of researchers. And this dataset will greatly contribute to advancing research on physiological signal-based vigilance research and estimation.},
}

Humans
*Brain-Computer Interfaces
*Electroencephalography
*Evoked Potentials, Visual
Eye Movements
Electrocardiography
Electrooculography
Electromyography
Male
Attention

@article {pmid39124036,
year = {2024},
author = {Kabir, MH and Akhtar, NI and Tasnim, N and Miah, ASM and Lee, HS and Jang, SW and Shin, J},
title = {Exploring Feature Selection and Classification Techniques to Improve the Performance of an Electroencephalography-Based Motor Imagery Brain-Computer Interface System.},
journal = {Sensors (Basel, Switzerland)},
volume = {24},
number = {15},
pages = {},
pmid = {39124036},
issn = {1424-8220},
mesh = {*Brain-Computer Interfaces ; *Electroencephalography/methods ; Humans ; Algorithms ; Signal Processing, Computer-Assisted ; Imagination/physiology ; Brain/physiology ; },
abstract = {The accuracy of classifying motor imagery (MI) activities is a significant challenge when using brain-computer interfaces (BCIs). BCIs allow people with motor impairments to control external devices directly with their brains using electroencephalogram (EEG) patterns that translate brain activity into control signals. Many researchers have been working to develop MI-based BCI recognition systems using various time-frequency feature extraction and classification approaches. However, the existing systems still face challenges in achieving satisfactory performance due to large amount of non-discriminative and ineffective features. To get around these problems, we suggested a multiband decomposition-based feature extraction and classification method that works well, along with a strong feature selection method for MI tasks. Our method starts by splitting the preprocessed EEG signal into four sub-bands. In each sub-band, we then used a common spatial pattern (CSP) technique to pull out narrowband-oriented useful features, which gives us a high-dimensional feature vector. Subsequently, we utilized an effective feature selection method, Relief-F, which reduces the dimensionality of the final features. Finally, incorporating advanced classification techniques, we classified the final reduced feature vector. To evaluate the proposed model, we used the three different EEG-based MI benchmark datasets, and our proposed model achieved better performance accuracy than existing systems. Our model's strong points include its ability to effectively reduce feature dimensionality and improve classification accuracy through advanced feature extraction and selection methods.},
}

*Brain-Computer Interfaces
*Electroencephalography/methods
Humans
Algorithms
Signal Processing, Computer-Assisted
Imagination/physiology
Brain/physiology

@article {pmid39123966,
year = {2024},
author = {Zhou, S and Zhang, P and Chen, H},
title = {Latent Prototype-Based Clustering: A Novel Exploratory Electroencephalography Analysis Approach.},
journal = {Sensors (Basel, Switzerland)},
volume = {24},
number = {15},
pages = {},
pmid = {39123966},
issn = {1424-8220},
mesh = {*Electroencephalography/methods ; Humans ; Cluster Analysis ; *Brain-Computer Interfaces ; Epilepsy/diagnosis/physiopathology ; Algorithms ; Signal Processing, Computer-Assisted ; Neural Networks, Computer ; },
abstract = {Electroencephalography (EEG)-based applications in brain-computer interfaces (BCIs), neurological disease diagnosis, rehabilitation, etc., rely on supervised approaches such as classification that requires given labels. However, with the ever-increasing amount of EEG data, incomplete or incorrectly labeled or unlabeled EEG data are increasing. It likely degrades the performance of supervised approaches. In this work, we put forward a novel unsupervised exploratory EEG analysis solution by clustering based on low-dimensional prototypes in latent space that are associated with the respective clusters. Having the prototype as a baseline of each cluster, a compositive similarity is defined to act as the critic function in clustering, which incorporates similarities on three levels. The approach is implemented with a Generative Adversarial Network (GAN), termed W-SLOGAN, by extending the Stein Latent Optimization for GANs (SLOGAN). The Gaussian Mixture Model (GMM) is utilized as the latent distribution to adapt to the diversity of EEG signal patterns. The W-SLOGAN ensures that images generated from each Gaussian component belong to the associated cluster. The adaptively learned Gaussian mixing coefficients make the model remain effective in dealing with an imbalanced dataset. By applying the proposed approach to two public EEG or intracranial EEG (iEEG) epilepsy datasets, our experiments demonstrate that the clustering results are close to the classification of the data. Moreover, we present several findings that were discovered by intra-class clustering and cross-analysis of clustering and classification. They show that the approach is attractive in practice in the diagnosis of the epileptic subtype, multiple labelling of EEG data, etc.},
}

*Electroencephalography/methods
Humans
Cluster Analysis
*Brain-Computer Interfaces
Epilepsy/diagnosis/physiopathology
Algorithms
Signal Processing, Computer-Assisted
Neural Networks, Computer

@article {pmid39120996,
year = {2024},
author = {Li, Y and Zhu, X and Qi, Y and Wang, Y},
title = {Revealing unexpected complex encoding but simple decoding mechanisms in motor cortex via separating behaviorally relevant neural signals.},
journal = {eLife},
volume = {12},
number = {},
pages = {},
pmid = {39120996},
issn = {2050-084X},
support = {no. 62336007//National Natural Science Foundation of China/ ; no. 2022C03011//Key Research and Development Program of Zhejiang/ ; SN-ZJU-SIAS-002//Starry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study/ ; },
mesh = {*Motor Cortex/physiology ; Animals ; *Macaca mulatta/physiology ; *Neurons/physiology ; Behavior, Animal/physiology ; Male ; Movement/physiology ; },
abstract = {In motor cortex, behaviorally relevant neural responses are entangled with irrelevant signals, which complicates the study of encoding and decoding mechanisms. It remains unclear whether behaviorally irrelevant signals could conceal some critical truth. One solution is to accurately separate behaviorally relevant and irrelevant signals at both single-neuron and single-trial levels, but this approach remains elusive due to the unknown ground truth of behaviorally relevant signals. Therefore, we propose a framework to define, extract, and validate behaviorally relevant signals. Analyzing separated signals in three monkeys performing different reaching tasks, we found neural responses previously considered to contain little information actually encode rich behavioral information in complex nonlinear ways. These responses are critical for neuronal redundancy and reveal movement behaviors occupy a higher-dimensional neural space than previously expected. Surprisingly, when incorporating often-ignored neural dimensions, behaviorally relevant signals can be decoded linearly with comparable performance to nonlinear decoding, suggesting linear readout may be performed in motor cortex. Our findings prompt that separating behaviorally relevant signals may help uncover more hidden cortical mechanisms.},
}

*Motor Cortex/physiology
Animals
*Macaca mulatta/physiology
*Neurons/physiology
Behavior, Animal/physiology
Male
Movement/physiology

@article {pmid39120991,
year = {2024},
author = {He, X and Allison, BZ and Qin, K and Liang, W and Wang, X and Cichocki, A and Jin, J},
title = {Leveraging Transfer Superposition Theory for StableState Visual Evoked Potential Cross-Subject Frequency Recognition.},
journal = {IEEE transactions on bio-medical engineering},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TBME.2024.3406603},
pmid = {39120991},
issn = {1558-2531},
abstract = {In steady-state visual evoked potential (SSVEP)based brain-computer interfaces (BCIs), various spatial filtering methods based on individual calibration data have been proposed to alleviate the interference of spontaneous activities in SSVEP signals for enhancing the SSVEP detection performance. However, the necessary calibration procedures take time, cause visual fatigue and reduce usability. For the calibration-free scenario, we propose a cross-subject frequency identification method based on transfer superimposed theory for SSVEP frequency decoding. First, a multi-channel signal decomposition model was constructed. Next, we used the cross least squares iterative method to create individual specific transfer spatial filters as well as source subject transfer superposition templates in the source subject. Then, we identified common knowledge among source subjects using a prototype spatial filter to make common transfer spatial filters and common impulse responses. Following, we reconstructed a global transfer superimposition template with SSVEP frequency characteristics. Finally, an ensemble cross-subject transfer learning method was proposed for SSVEP frequency recognition by combining the sourcesubject transfer mode, the global transfer mode, and the sinecosine reference template. Offline tests on two public datasets show that the proposed method significantly outperforms the FBCCA, TTCCA, and CSSFT methods. More importantly, the proposed method can be directly used in online SSVEP recognition without calibration. The proposed algorithm was robust, which is important for a practical BCI.},
}

@article {pmid39119268,
year = {2024},
author = {Li, P and Kim, S and Tian, B},
title = {Beyond 25 years of biomedical innovation in nano-bioelectronics.},
journal = {Device},
volume = {2},
number = {7},
pages = {},
pmid = {39119268},
issn = {2666-9986},
support = {R56 EB034289/EB/NIBIB NIH HHS/United States ; },
abstract = {Nano-bioelectronics, which blend the precision of nanotechnology with the complexity of biological systems, are evolving with innovations such as silicon nanowires, carbon nanotubes, and graphene. These elements serve applications from biochemical sensing to brain-machine interfacing. This review examines nano-bioelectronics' role in advancing biomedical interventions and discusses their potential in environmental monitoring, agricultural productivity, energy efficiency, and creative fields. The field is transitioning from molecular to ecosystem-level applications, with research exploring complex cellular mechanisms and communication. This fosters understanding of biological interactions at various levels, such as suggesting transformative approaches for ecosystem management and food security. Future research is expected to focus on refining nano-bioelectronic devices for integration with biological systems and on scalable manufacturing to broaden their reach and functionality.},
}

@article {pmid39117588,
year = {2024},
author = {Cassinadri, G and Ienca, M},
title = {Non-voluntary BCI explantation: assessing possible neurorights violations in light of contrasting mental ontologies.},
journal = {Journal of medical ethics},
volume = {},
number = {},
pages = {},
doi = {10.1136/jme-2023-109830},
pmid = {39117588},
issn = {1473-4257},
abstract = {In research involving patients with implantable brain-computer interfaces (BCIs), there is a regulatory gap concerning post-trial responsibilities and duties of sponsors and investigators towards implanted patients. In this article, we analyse the case of patient R, who underwent non-voluntary explantation of an implanted BCI, causing a discontinuation in her sense of agency and self. To clarify the post-trial duties and responsibilities involved in this case, we first define the ontological status of the BCI using both externalist (EXT) and internalist (INT) theories of cognition. We then give particular focus to the theories of extended and embedded cognition, hence considering the BCI either as a constitutive component of the patient's mind or as a causal supporter of her brain-based cognitive capacities. We argue that patient R can legitimately be considered both as an embedded and extended cognitive agent. Then, we analyse whether the non-voluntary explantation violated patient R's (neuro)rights to cognitive liberty, mental integrity, psychological continuity and mental privacy. We analyse whether and how different mental ontologies may imply morally relevant differences in interpreting these prima facie neurorights violations and the correlational duties of sponsors and investigators. We conclude that both mental ontologies support the identification of emerging neurorights of the patient and give rise to post-trial obligations of sponsors and investigators to provide for continuous technical maintenance of implanted BCIs that play a significant role in patients' agency and sense of self. However, we suggest that externalist mental ontologies better capture patient R's self-conception and support the identification of a more granular form of mental harm and associated neurorights violation, thus eliciting stricter post-trial obligations.},
}

@article {pmid39112576,
year = {2024},
author = {Naddaf, M and Drew, L},
title = {Second brain implant by Elon Musk's Neuralink: will it fare better than the first?.},
journal = {Nature},
volume = {632},
number = {8025},
pages = {481-482},
doi = {10.1038/d41586-024-02368-8},
pmid = {39112576},
issn = {1476-4687},
mesh = {Humans ; *Brain/surgery ; *Brain-Computer Interfaces ; Electrodes, Implanted ; Spinal Cord Injuries/surgery/therapy ; Treatment Outcome ; },
}

Humans
*Brain/surgery
*Brain-Computer Interfaces
Electrodes, Implanted
Spinal Cord Injuries/surgery/therapy
Treatment Outcome

@article {pmid39116892,
year = {2024},
author = {Xiong, H and Li, J and Liu, J and Song, J and Han, Y},
title = {Wasserstein generative adversarial network with gradient penalty and convolutional neural network based motor imagery EEG classification.},
journal = {Journal of neural engineering},
volume = {21},
number = {4},
pages = {},
doi = {10.1088/1741-2552/ad6cf5},
pmid = {39116892},
issn = {1741-2552},
mesh = {*Electroencephalography/methods/classification ; Humans ; *Imagination/physiology ; *Neural Networks, Computer ; *Brain-Computer Interfaces ; Deep Learning ; Wavelet Analysis ; },
abstract = {Objective.Due to the difficulty in acquiring motor imagery electroencephalography (MI-EEG) data and ensuring its quality, insufficient training data often leads to overfitting and inadequate generalization capabilities of deep learning-based classification networks. Therefore, we propose a novel data augmentation method and deep learning classification model to enhance the decoding performance of MI-EEG further.Approach.The raw EEG signals were transformed into the time-frequency maps as the input to the model by continuous wavelet transform. An improved Wasserstein generative adversarial network with gradient penalty data augmentation method was proposed, effectively expanding the dataset used for model training. Additionally, a concise and efficient deep learning model was designed to improve decoding performance further.Main results.It has been demonstrated through validation by multiple data evaluation methods that the proposed generative network can generate more realistic data. Experimental results on the BCI Competition IV 2a and 2b datasets and the actual collected dataset show that classification accuracies are 83.4%, 89.1% and 73.3%, and Kappa values are 0.779, 0.782 and 0.644, respectively. The results indicate that the proposed model outperforms state-of-the-art methods.Significance.Experimental results demonstrate that this method effectively enhances MI-EEG data, mitigates overfitting in classification networks, improves MI classification accuracy, and holds positive implications for MI tasks.},
}

*Electroencephalography/methods/classification
Humans
*Imagination/physiology
*Neural Networks, Computer
*Brain-Computer Interfaces
Deep Learning
Wavelet Analysis

@article {pmid39116878,
year = {2024},
author = {Wei, B and Cheng, G and Bi, Q and Lu, C and Sun, Q and Li, L and Chen, N and Hu, M and Lu, H and Xu, X and Mao, G and Wan, S and Hu, Z and Gu, Y and Zheng, J and Zhao, L and Shen, XZ and Liu, X and Shi, P},
title = {Microglia in the hypothalamic paraventricular nucleus sense hemodynamic disturbance and promote sympathetic excitation in hypertension.},
journal = {Immunity},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.immuni.2024.07.011},
pmid = {39116878},
issn = {1097-4180},
abstract = {Hypertension is usually accompanied by elevated sympathetic tonicity, but how sympathetic hyperactivity is triggered is not clear. Recent advances revealed that microglia-centered neuroinflammation contributes to sympathetic excitation in hypertension. In this study, we performed a temporospatial analysis of microglia at both morphological and transcriptomic levels and found that microglia in the hypothalamic paraventricular nucleus (PVN), a sympathetic center, were early responders to hypertensive challenges. Vasculature analyses revealed that the PVN was characterized by high capillary density, thin vessel diameter, and complex vascular topology relative to other brain regions. As such, the PVN was susceptible to the penetration of ATP released from the vasculature in response to hemodynamic disturbance after blood pressure increase. Mechanistically, ATP ligation to microglial P2Y12 receptor was responsible for microglial inflammatory activation and the eventual sympathetic overflow. Together, these findings identified a distinct vasculature pattern rendering vulnerability of PVN pre-sympathetic neurons to hypertension-associated microglia-mediated inflammatory insults.},
}

@article {pmid39116374,
year = {2024},
author = {Aboubakr, O and Houillier, C and Alentorn, A and Choquet, S and Dupont, S and Mokhtari, K and Leclercq, D and Nichelli, L and Kas, A and Rozenblum, L and Le Garff-Tavernier, M and Hoang-Xuan, K and Carpentier, A and Mathon, B},
title = {Epilepsy in Patients With Primary CNS Lymphoma: Prevalence, Risk Factors, and Prognostic Significance.},
journal = {Neurology},
volume = {103},
number = {5},
pages = {e209748},
doi = {10.1212/WNL.0000000000209748},
pmid = {39116374},
issn = {1526-632X},
mesh = {Humans ; Male ; Female ; Aged ; Retrospective Studies ; Middle Aged ; Risk Factors ; Prevalence ; Prognosis ; *Epilepsy/epidemiology ; *Central Nervous System Neoplasms/epidemiology/complications ; Lymphoma/epidemiology/complications ; Adult ; Aged, 80 and over ; },
abstract = {BACKGROUND AND OBJECTIVES: Epilepsy is a common comorbidity of brain tumors; however, little is known about the prevalence, onset time, semiology, and risk factors of seizures in primary CNS lymphoma (PCNSL). Our objectives were to determine the prevalence of epilepsy in PCNSL, to identify factors associated with epilepsy, and to investigate the prognostic significance of seizures in PCNSL.

METHODS: We performed an observational, retrospective single-center study at a tertiary neuro-oncology center (2011-2023) including immunocompetent patients with PCNSL and no history of seizures. We collected clinical, imaging, and treatment data; seizure status over the course of PCNSL; and oncological and seizure outcome. The primary outcome was to determine the prevalence of epilepsy. Furthermore, we aimed to identify clinical, radiologic, and treatment-related factors associated with epilepsy. Univariate analyses were conducted using the χ[2] test for categorical variables and unpaired t test for continuous variables. Predictors identified in the unadjusted analysis were included in backward stepwise logistic regression models.

RESULTS: We included 330 patients, 157 (47.6%) were male, median age at diagnosis was 68 years, and the median Karnofsky Performance Status score was 60. Eighty-three (25.2%) patients had at least 1 seizure from initial diagnosis to the last follow-up, 40 (12.1%) as the onset symptom, 16 (4.8%) during first line of treatment, 27 (8.2%) at tumor progression and 6 (1.8%) while in remission. Focal aware seizures were the most frequent seizure type, occurring in 43 (51.8%) patients. Seizure freedom under antiseizure medication was observed in 97.6% patients. Cortical contact (odds ratio [OR] 8.6, 95% CI 4.2-15.5, p < 0.001) and a higher proliferation index (OR 5.7, 95% CI 1.3-26.2, p = 0.02) were identified as independent risk factors of epilepsy. Patients with PCNSL and epilepsy had a significantly shorter progression-free survival (median progression-free survival 9.6 vs 14.1 months, adjusted hazard ratio 1.4, 95% CI 1.0-1.9, p = 0.03), but not a significantly shorter overall survival (17 vs 44.1 months, log-rank test, p = 0.09).

DISCUSSION: Epilepsy affects a quarter of patients with PCNSL, with half experiencing it at the time of initial presentation and potentially serving as a marker of disease progression. Further research is necessary to assess the broader applicability of these findings because they are subject to the constraints of a retrospective design and tertiary center setting.},
}

Humans
Male
Female
Aged
Retrospective Studies
Middle Aged
Risk Factors
Prevalence
Prognosis
*Epilepsy/epidemiology
*Central Nervous System Neoplasms/epidemiology/complications
Lymphoma/epidemiology/complications
Adult
Aged, 80 and over

@article {pmid39116252,
year = {2024},
author = {Chen, M and Ma, S and Liu, H and Dong, Y and Tang, J and Ni, Z and Tan, Y and Duan, C and Li, H and Huang, H and Li, Y and Cao, X and Lingle, CJ and Yang, Y and Hu, H},
title = {Brain region-specific action of ketamine as a rapid antidepressant.},
journal = {Science (New York, N.Y.)},
volume = {385},
number = {6709},
pages = {eado7010},
doi = {10.1126/science.ado7010},
pmid = {39116252},
issn = {1095-9203},
mesh = {Animals ; Male ; Mice ; *Antidepressive Agents/pharmacology ; Brain-Derived Neurotrophic Factor/metabolism/genetics ; *Depression/drug therapy/metabolism ; *Habenula/drug effects/metabolism ; Hippocampus/drug effects/metabolism ; *Ketamine/pharmacology/administration & dosage ; Mice, Inbred C57BL ; Mice, Knockout ; Pyramidal Cells/drug effects/metabolism ; *Receptors, N-Methyl-D-Aspartate/antagonists & inhibitors/genetics ; Serotonin/metabolism ; },
abstract = {Ketamine has been found to have rapid and potent antidepressant activity. However, despite the ubiquitous brain expression of its molecular target, the N-methyl-d-aspartate receptor (NMDAR), it was not clear whether there is a selective, primary site for ketamine's antidepressant action. We found that ketamine injection in depressive-like mice specifically blocks NMDARs in lateral habenular (LHb) neurons, but not in hippocampal pyramidal neurons. This regional specificity depended on the use-dependent nature of ketamine as a channel blocker, local neural activity, and the extrasynaptic reservoir pool size of NMDARs. Activating hippocampal or inactivating LHb neurons swapped their ketamine sensitivity. Conditional knockout of NMDARs in the LHb occluded ketamine's antidepressant effects and blocked the systemic ketamine-induced elevation of serotonin and brain-derived neurotrophic factor in the hippocampus. This distinction of the primary versus secondary brain target(s) of ketamine should help with the design of more precise and efficient antidepressant treatments.},
}

Animals
Male
Mice
*Antidepressive Agents/pharmacology
Brain-Derived Neurotrophic Factor/metabolism/genetics
*Depression/drug therapy/metabolism
*Habenula/drug effects/metabolism
Hippocampus/drug effects/metabolism
*Ketamine/pharmacology/administration & dosage
Mice, Inbred C57BL
Mice, Knockout
Pyramidal Cells/drug effects/metabolism
*Receptors, N-Methyl-D-Aspartate/antagonists & inhibitors/genetics
Serotonin/metabolism

@article {pmid39115894,
year = {2024},
author = {Hu, B and Lu, D and Meng, L and Zhang, Y},
title = {When time theft promotes performance: Measure development and validation of time theft motives.},
journal = {The Journal of applied psychology},
volume = {},
number = {},
pages = {},
doi = {10.1037/apl0001229},
pmid = {39115894},
issn = {1939-1854},
support = {//National Natural Science Foundation of China/ ; //Shanghai Philosophy and Social Science Planning Project/ ; //Shanghai Key Laboratory of Brain-Machine Intelligence for Information Behavior/ ; },
abstract = {The prevailing viewpoint has long depicted employee time theft as inherently detrimental. However, this perspective may stem from a limited understanding of the underlying motives that drive such behavior. Time theft can paradoxically be motivated by neutral and even laudable intentions, such as promoting work efficiency, thus rendering it potentially beneficial and constructive. Across three mixed-methods studies, we explore the motives behind employee time theft, develop and validate an instrument to assess these motives, and examine how they differentially predict time theft behavior. Specifically, in Study 1, we use a qualitative method and identify 11 types of time theft motives. Study 2 embarks on the development of measures of these motives, subsequently validating their factor structure. Study 3 examines their incremental variance in predicting time theft behavior by controlling for personality and demographic variables. Overall, these studies reveal that employees' engagement in time theft can be driven not solely by self-oriented motives but also by others- and work-oriented motives. Further, each of these motives provides incremental value in understanding time theft behavior. Implications for both research and practice emanating from these findings are also discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).},
}

@article {pmid39115403,
year = {2024},
author = {Jeong, E and Seo, M and Kim, KS},
title = {Design of an fNIRS-EEG hybrid terminal for wearable BCI systems.},
journal = {The Review of scientific instruments},
volume = {95},
number = {8},
pages = {},
doi = {10.1063/5.0187070},
pmid = {39115403},
issn = {1089-7623},
mesh = {*Brain-Computer Interfaces ; *Spectroscopy, Near-Infrared/instrumentation/methods ; *Electroencephalography/instrumentation ; Humans ; *Wearable Electronic Devices ; Equipment Design ; },
abstract = {The importance of brain-computer interfaces (BCI) is increasing, and various methods have been developed. Among the developed BCI methods, functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) are favored due to their non-invasive feature and compact device sizes. EEG monitors the electrical potentials generated by the activation of neurons, and fNIRS monitors the blood flow also generated by neurons, resulting in signals with different properties between the two methods. As the two BCI methods greatly differ in the characteristics of the acquired neural activity signals, for cases of estimating the intention or thought of a subject by BCI, it has been proven that further accurate information may be extracted by utilizing both methods simultaneously. Both systems are powered by electricity, and as EEG systems are greatly sensitive to electrical noises, application of two separate fNIRS and EEG systems together may result in electrical interference as the systems are required to be in contact with the skin and stray currents from the fNIRS system may flow along the surface of the skin into the EEG system. This research proposes a wearable fNIRS-EEG hybrid BCI system, where a single terminal is capable of operating both as a continuous wave fNIRS emitter and as a detector, and also as an EEG electrode. The system has been designed such that the fNIRS and EEG components are electrically separated to avoid electrical interference between each other. It is expected that by utilizing the developed fNIRS-EEG hybrid terminals, the development of BCI analysis may be further accelerated in various fields.},
}

*Brain-Computer Interfaces
*Spectroscopy, Near-Infrared/instrumentation/methods
*Electroencephalography/instrumentation
Humans
*Wearable Electronic Devices
Equipment Design

@article {pmid39114591,
year = {2024},
author = {Berkmush-Antipova, A and Syrov, N and Yakovlev, L and Miroshnikov, A and Golovanov, F and Shusharina, N and Kaplan, A},
title = {Yes or no? A study of ErrPs in the "guess what I am thinking" paradigm with stimuli of different visual content.},
journal = {Frontiers in psychology},
volume = {15},
number = {},
pages = {1394496},
pmid = {39114591},
issn = {1664-1078},
abstract = {Error-related potentials (ErrPs) have attracted attention in part because of their practical potential for building brain-computer interface (BCI) paradigms. BCIs, facilitating direct communication between the brain and machines, hold great promise for brain-AI interaction. Therefore, a comprehensive understanding of ErrPs is crucial to ensure reliable BCI outcomes. In this study, we investigated ErrPs in the context of the "guess what I am thinking" paradigm. 23 healthy participants were instructed to imagine an object from a predetermined set, while an algorithm randomly selected another object that was either the same as or different from the imagined object. We recorded and analyzed the participants' EEG activity to capture their mental responses to the algorithm's "predictions". The study identified components distinguishing correct from incorrect responses. It discusses their nature and how they differ from ErrPs extensively studied in other BCI paradigms. We observed pronounced variations in the shape of ErrPs across different stimulus sets, underscoring the significant influence of visual stimulus appearance on ErrP peaks. These findings have implications for designing effective BCI systems, especially considering the less conventional BCI paradigm employed. They emphasize the necessity of accounting for stimulus factors in BCI development.},
}

@article {pmid39113778,
year = {2024},
author = {Bartkowiak, J and Agarwal, V and Lebehn, M and Nazif, TM and George, I and Kodali, SK and Vahl, TP and Hahn, RT},
title = {Strain assessment in patients with aortic regurgitation undergoing transcatheter aortic valve implantation: case series.},
journal = {European heart journal. Case reports},
volume = {8},
number = {8},
pages = {ytae261},
pmid = {39113778},
issn = {2514-2119},
abstract = {BACKGROUND: Limited data exist on strain changes after transcatheter aortic valve implantation (TAVI) in patients with aortic regurgitation (AR).

CASE SUMMARY: Three patients with AR undergoing TAVI showed an initial reduction in global longitudinal strain (GLS), followed by sustained GLS improvement within the first year.

DISCUSSION: Findings align with those of surgically treated patients with AR. There is a possible superiority of GLS to left ventricular end-diastolic diameter ratio in assessing patients with severe volume overload.},
}

@article {pmid39112461,
year = {2024},
author = {Qiu, L and Liang, C and Kochunov, P and Hutchison, KE and Sui, J and Jiang, R and Zhi, D and Vergara, VM and Yang, X and Zhang, D and Fu, Z and Bustillo, JR and Qi, S and Calhoun, VD},
title = {Associations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging.},
journal = {Translational psychiatry},
volume = {14},
number = {1},
pages = {326},
pmid = {39112461},
issn = {2158-3188},
support = {R01 MH118695/MH/NIMH NIH HHS/United States ; R01MH118695//Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)/ ; BK20220889//Natural Science Foundation of Jiangsu Province (Jiangsu Provincial Natural Science Foundation)/ ; 62376124//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
mesh = {Humans ; Female ; Male ; Adult ; *Psychotic Disorders/diagnostic imaging ; *Tobacco Use/adverse effects ; Brain/diagnostic imaging ; Magnetic Resonance Imaging ; Young Adult ; Depressive Disorder, Major/diagnostic imaging ; Middle Aged ; Multimodal Imaging ; Alcohol Drinking/adverse effects ; Neuroimaging ; Adolescent ; Autism Spectrum Disorder/diagnostic imaging ; },
abstract = {People affected by psychotic, depressive and developmental disorders are at a higher risk for alcohol and tobacco use. However, the further associations between alcohol/tobacco use and symptoms/cognition in these disorders remain unexplored. We identified multimodal brain networks involving alcohol use (n = 707) and tobacco use (n = 281) via supervised multimodal fusion and evaluated if these networks affected symptoms and cognition in people with psychotic (schizophrenia/schizoaffective disorder/bipolar, n = 178/134/143), depressive (major depressive disorder, n = 260) and developmental (autism spectrum disorder/attention deficit hyperactivity disorder, n = 421/346) disorders. Alcohol and tobacco use scores were used as references to guide functional and structural imaging fusion to identify alcohol/tobacco use associated multimodal patterns. Correlation analyses between the extracted brain features and symptoms or cognition were performed to evaluate the relationships between alcohol/tobacco use with symptoms/cognition in 6 psychiatric disorders. Results showed that (1) the default mode network (DMN) and salience network (SN) were associated with alcohol use, whereas the DMN and fronto-limbic network (FLN) were associated with tobacco use; (2) the DMN and fronto-basal ganglia (FBG) related to alcohol/tobacco use were correlated with symptom and cognition in psychosis; (3) the middle temporal cortex related to alcohol/tobacco use was associated with cognition in depression; (4) the DMN related to alcohol/tobacco use was related to symptom, whereas the SN and limbic system (LB) were related to cognition in developmental disorders. In summary, alcohol and tobacco use were associated with structural and functional abnormalities in DMN, SN and FLN and had significant associations with cognition and symptoms in psychotic, depressive and developmental disorders likely via different brain networks. Further understanding of these relationships may assist clinicians in the development of future approaches to improve symptoms and cognition among psychotic, depressive and developmental disorders.},
}

Humans
Female
Male
Adult
*Psychotic Disorders/diagnostic imaging
*Tobacco Use/adverse effects
Brain/diagnostic imaging
Magnetic Resonance Imaging
Young Adult
Depressive Disorder, Major/diagnostic imaging
Middle Aged
Multimodal Imaging
Alcohol Drinking/adverse effects
Neuroimaging
Adolescent
Autism Spectrum Disorder/diagnostic imaging

@article {pmid39111412,
year = {2024},
author = {Tian, H},
title = {Human-Robot Interaction in Motor Imagery: A System Based on the STFCN for Unilateral Upper Limb Rehabilitation Assistance.},
journal = {Journal of neuroscience methods},
volume = {},
number = {},
pages = {110240},
doi = {10.1016/j.jneumeth.2024.110240},
pmid = {39111412},
issn = {1872-678X},
abstract = {BACKGROUND: Rehabilitation training based on the brain-computer interface of motor imagery (MI-BCI) can help restore the connection between the brain and movement. However, the performance of most popular MI-BCI system is coarse-level, which means that they are good at guiding the rehabilitation exercises of different parts of the body, but not for the individual component. New methods In this paper, we designed a fine-level MI-BCI system for unilateral upper limb rehabilitation assistance. Besides, due to the low discrimination of different sample classes in a single part, a classification algorithm called spatial-temporal filtering convolutional network (STFCN) was proposed that used spatial filtering and deep learning.

Our STFCN outperforms popular methods in recent years using BCI IV 2a and 2b data sets.

RESULTS: To verify the effectiveness of our system, we recruited 6 volunteers and collected their data for a four-classification online experiments, resulting in an average accuracy of 62.7%.

CONCLUSION: This fine-level MI-BCI system has good appli-cation prospects, and inspires more exploration of rehabilitation in a single part of the human body.},
}

@article {pmid39111203,
year = {2024},
author = {Suwandjieff, P and Müller-Putz, GR},
title = {EEG Analyses of visual cue effects on executed movements.},
journal = {Journal of neuroscience methods},
volume = {410},
number = {},
pages = {110241},
doi = {10.1016/j.jneumeth.2024.110241},
pmid = {39111203},
issn = {1872-678X},
abstract = {BACKGROUND: In electroencephalographic (EEG) or electrocorticographic (ECoG) experiments, visual cues are commonly used for timing synchronization but may inadvertently induce neural activity and cognitive processing, posing challenges when decoding self-initiated tasks.

NEW METHOD: To address this concern, we introduced four new visual cues (Fade, Rotation, Reference, and Star) and investigated their impact on brain signals. Our objective was to identify a cue that minimizes its influence on brain activity, facilitating cue-effect free classifier training for asynchronous applications, particularly aiding individuals with severe paralysis.

RESULTS: 22 able-bodied, right-handed participants aged 18-30 performed hand movements upon presentation of the visual cues. Analysis of time-variability between movement onset and cue-aligned data, grand average MRCP, and classification outcomes revealed significant differences among cues. Rotation and Reference cue exhibited favorable results in minimizing temporal variability, maintaining MRCP patterns, and achieving comparable accuracy to self-paced signals in classification.

Our study contrasts with traditional cue-based paradigms by introducing novel visual cues designed to mitigate unintended neural activity. We demonstrate the effectiveness of Rotation and Reference cue in eliciting consistent and accurate MRCPs during motor tasks, surpassing previous methods in achieving precise timing and high discriminability for classifier training.

CONCLUSIONS: Precision in cue timing is crucial for training classifiers, where both Rotation and Reference cue demonstrate minimal variability and high discriminability, highlighting their potential for accurate classifications in online scenarios. These findings offer promising avenues for refining brain-computer interface systems, particularly for individuals with motor impairments, by enabling more reliable and intuitive control mechanisms.},
}

@article {pmid39110623,
year = {2024},
author = {Sun, Y and Liang, L and Li, Y and Chen, X and Gao, X},
title = {Dual-Alpha: a large EEG study for dual-frequency SSVEP brain-computer interface.},
journal = {GigaScience},
volume = {13},
number = {},
pages = {},
pmid = {39110623},
issn = {2047-217X},
support = {U2241208//National Natural Science Foundation of China/ ; 2023YFF1205300//National Key Research and Development Program of China/ ; },
mesh = {*Brain-Computer Interfaces ; Humans ; *Evoked Potentials, Visual ; *Electroencephalography ; Male ; Female ; Adult ; Young Adult ; Algorithms ; },
abstract = {BACKGROUND: The domain of brain-computer interface (BCI) technology has experienced significant expansion in recent years. However, the field continues to face a pivotal challenge due to the dearth of high-quality datasets. This lack of robust datasets serves as a bottleneck, constraining the progression of algorithmic innovations and, by extension, the maturation of the BCI field.

FINDINGS: This study details the acquisition and compilation of electroencephalogram data across 3 distinct dual-frequency steady-state visual evoked potential (SSVEP) paradigms, encompassing over 100 participants. Each experimental condition featured 40 individual targets with 5 repetitions per target, culminating in a comprehensive dataset consisting of 21,000 trials of dual-frequency SSVEP recordings. We performed an exhaustive validation of the dataset through signal-to-noise ratio analyses and task-related component analysis, thereby substantiating its reliability and effectiveness for classification tasks.

CONCLUSIONS: The extensive dataset presented is set to be a catalyst for the accelerated development of BCI technologies. Its significance extends beyond the BCI sphere and holds considerable promise for propelling research in psychology and neuroscience. The dataset is particularly invaluable for discerning the complex dynamics of binocular visual resource distribution.},
}

*Brain-Computer Interfaces
Humans
*Evoked Potentials, Visual
*Electroencephalography
Male
Female
Adult
Young Adult
Algorithms

@article {pmid39110554,
year = {2024},
author = {Wei, W and Li, X and Qiu, S and He, H},
title = {Preliminary Study on Rapid Serial Visualization Presentation Multi-Class Target EEG Classification.},
journal = {IEEE transactions on bio-medical engineering},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TBME.2024.3439820},
pmid = {39110554},
issn = {1558-2531},
abstract = {OBJECTIVE: Brain-Computer Interface (BCI) provides a direct communication channel between the brain and external devices. After combining with the Rapid Serial Visualization Presentation (RSVP) paradigm, the RSVP-BCI system can be utilized for human vision-based fast information retrieval. Currently only binary classification of single-trial EEG can be achieved, also the research on the multi-class target RSVP is few, which limited information transfer rate and the application scenarios of the system. In this paper, we focus on the RSVP multi-class target image retrieval task that contains two classes of targets for achieving triple classification for RSVP-EEG.

METHODS: Designed two experiments, each containing two tasks with different task difficulties. We recruited 30 subjects to participate in the experiments, collected EEG data, and made the data publicly available. Moreover, we conducted behavioral analysis, ERP analysis, and proposed a model, MDCNet, for EEG classification to study the feasibility of multi-class target RSVP and the impact of task difficulty.

RESULTS: The experimental results indicated that (1) RSVP-EEG classification that includes non-target and 2-class target is feasibility; (2) the different targets in the same task will evoke P300 with the same latency and different amplitudes, and the hit rate of the target in EEG classification is positively correlated with its amplitude; (3) the information hidden in the time dimension play an important role in EEG classification; (4) the harder the task is, the latency of P300 is longer.

CONCLUSION/SIGNIFICANCE: The experimental analysis obtained meaningful results, which provided a theoretical basis for subsequent research.},
}

@article {pmid39110553,
year = {2024},
author = {Blanco-Diaz, CF and Serafini, ERDS and Bastos-Filho, T and Dantas, AFOA and Santo, CCDE and Delisle-Rodriguez, D},
title = {A Gait Imagery-Based Brain-Computer Interface with Visual feedback for Spinal Cord Injury Rehabilitation on Lokomat.},
journal = {IEEE transactions on bio-medical engineering},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/TBME.2024.3440036},
pmid = {39110553},
issn = {1558-2531},
abstract = {OBJECTIVE: Motor Imagery (MI)-based Brain-Computer Interfaces (BCIs) have been proposed for the rehabilitation of people with disabilities, being a big challenge their successful application to restore motor functions in individuals with Spinal Cord Injury (SCI). This work proposes an Electroencephalography (EEG) gait imagery-based BCI to promote motor recovery on the Lokomat platform, in order to allow a clinical intervention by acting simultaneously on both central and peripheral nervous mechanisms.

METHODS: As a novelty, our BCI system accurately discriminates gait imagery tasks during walking and further provides a multi-channel EEG-based Visual Neurofeedback (VNFB) linked to μ (8-12 Hz) and β (15-20 Hz) rhythms around Cz. VNFB is carried out through a cluster analysis strategy-based Euclidean distance, where the weighted mean MI feature vector is used as a reference to teach individuals with SCI to modulate their cortical rhythms.

RESULTS: The developed BCI reached an average classification accuracy of 74.4%. In addition, feature analysis demonstrated a reduction in cluster variance after several sessions, whereas metrics associated with self-modulation indicated a greater distance between both classes: passive walking with gait MI and passive walking without MI.

CONCLUSION: The results suggest that intervention with a gait MI-based BCI with VNFB may allow the individuals to appropriately modulate their rhythms of interest around Cz.

SIGNIFICANCE: This work contributes to the development of advanced systems for gait rehabilitation by integrating Machine Learning and neurofeedback techniques, to restore lower-limb functions of SCI individuals.},
}

@article {pmid39107957,
year = {2024},
author = {Xu, P and Liu, Y and Wang, J and Zhang, A and Wang, K and Wang, Z and Fang, Y and Wang, X and Zhang, J},
title = {Gender-specific prognosis models reveal differences in subarachnoid hemorrhage patients between sexes.},
journal = {CNS neuroscience & therapeutics},
volume = {30},
number = {8},
pages = {e14894},
pmid = {39107957},
issn = {1755-5949},
support = {LGD22H090001//Natural Science Foundation of Zhejiang Province/ ; 81870916//National Natural Science Foundation of China/ ; 82071287//National Natural Science Foundation of China/ ; 82201430//National Natural Science Foundation of China/ ; 82271301//National Natural Science Foundation of China/ ; },
mesh = {Humans ; *Subarachnoid Hemorrhage/diagnosis ; Male ; Female ; Middle Aged ; Prognosis ; Aged ; *Sex Characteristics ; Adult ; Retrospective Studies ; },
abstract = {BACKGROUND: Subarachnoid hemorrhage (SAH) represents a severe stroke subtype. Our study aims to develop gender-specific prognostic prediction models derived from distinct prognostic factors observed among different-gender patients.

METHODS: Inclusion comprised SAH-diagnosed patients from January 2014 to March 2016 in our institution. Collected data encompassed patients' demographics, admission severity, treatments, imaging findings, and complications. Three-month post-discharge prognoses were obtained via follow-ups. Analyses assessed gender-based differences in patient information. Key factors underwent subgroup analysis, followed by univariate and multivariate analyses to identify gender-specific prognostic factors and establish/validate gender-specific prognostic models.

RESULTS: A total of 929 patients, with a median age of 57 (16) years, were analyzed; 372 (40%) were male, and 557 (60%) were female. Differences in age, smoking history, hypertension, aneurysm presence, and treatment interventions existed between genders (p < 0.01), yet no disparity in prognosis was noted. Subgroup analysis explored hypertension history, aneurysm presence, and treatment impact, revealing gender-specific variations in these factors' influence on the disease. Screening identified independent prognostic factors: age, SEBES score, admission GCS score, and complications for males; and age, admission GCS score, intraventricular hemorrhage, treatment interventions, symptomatic vasospasm, hydrocephalus, delayed cerebral ischemia, and seizures for females. Evaluation and validation of gender-specific models yielded an AUC of 0.916 (95% CI: 0.878-0.954) for males and 0.914 (95% CI: 0.885-0.944) for females in the ROC curve. Gender-specific prognostic models didn't significantly differ from the overall population-based model (model 3) but exhibited robust discriminative ability and clinical utility.

CONCLUSION: Variations in baseline and treatment-related factors among genders contribute partly to gender-based prognosis differences. Independent prognostic factors vary by gender. Gender-specific prognostic models exhibit favorable prognostic performance.},
}

Humans
*Subarachnoid Hemorrhage/diagnosis
Male
Female
Middle Aged
Prognosis
Aged
*Sex Characteristics
Adult
Retrospective Studies

@article {pmid39107319,
year = {2024},
author = {Luo, Y and Wang, L and Cao, Y and Shen, Y and Gu, Y and Wang, L},
title = {Reduced excitatory activity in the developing mPFC mediates a PVH-to-PVL transition and impaired social cognition in autism spectrum disorders.},
journal = {Translational psychiatry},
volume = {14},
number = {1},
pages = {325},
pmid = {39107319},
issn = {2158-3188},
support = {LR21C090001//Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation)/ ; 32070975//National Natural Science Foundation of China (National Science Foundation of China)/ ; 31820103005//National Natural Science Foundation of China (National Science Foundation of China)/ ; 32071021//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
mesh = {*Autism Spectrum Disorder/physiopathology ; Animals ; *Prefrontal Cortex/physiopathology/metabolism ; Mice ; *Interneurons/metabolism/physiology ; *Parvalbumins/metabolism ; *Disease Models, Animal ; Male ; *Social Cognition ; Behavior, Animal/physiology ; Social Behavior ; Mice, Inbred C57BL ; Female ; },
abstract = {Understanding the neuropathogenesis of impaired social cognition in autism spectrum disorders (ASD) is challenging. Altered cortical parvalbumin-positive (PV[+]) interneurons have been consistently observed in ASD, but their roles and the underlying mechanisms remain poorly understood. In our study, we observed a downward-shifted spectrum of PV expression in the developing medial prefrontal cortex (mPFC) of ASD mouse models due to decreased activity of PV[+] neurons. Surprisingly, chemogenetically suppressing PV[+] neuron activity during postnatal development failed to induce ASD-like behaviors. In contrast, lowering excitatory activity in the developing mPFC not only dampened the activity state and PV expression of individual PV[+] neurons, but also replicated ASD-like social deficits. Furthermore, enhancing excitation, but not PV[+] interneuron-mediated inhibition, rescued social deficits in ASD mouse models. Collectively, our findings propose that reduced excitatory activity in the developing mPFC may serve as a shared local circuitry mechanism triggering alterations in PV[+] interneurons and mediating impaired social functions in ASD.},
}

*Autism Spectrum Disorder/physiopathology
Animals
*Prefrontal Cortex/physiopathology/metabolism
Mice
*Interneurons/metabolism/physiology
*Parvalbumins/metabolism
*Disease Models, Animal
Male
*Social Cognition
Behavior, Animal/physiology
Social Behavior
Mice, Inbred C57BL
Female

@article {pmid39106199,
year = {2024},
author = {Dash, D and Ferrari, P and Wang, J},
title = {Neural Decoding of Spontaneous Overt and Intended Speech.},
journal = {Journal of speech, language, and hearing research : JSLHR},
volume = {},
number = {},
pages = {1-10},
doi = {10.1044/2024_JSLHR-24-00046},
pmid = {39106199},
issn = {1558-9102},
abstract = {PURPOSE: The aim of this study was to decode intended and overt speech from neuromagnetic signals while the participants performed spontaneous overt speech tasks without cues or prompts (stimuli).

METHOD: Magnetoencephalography (MEG), a noninvasive neuroimaging technique, was used to collect neural signals from seven healthy adult English speakers performing spontaneous, overt speech tasks. The participants randomly spoke the words yes or no at a self-paced rate without cues. Two machine learning models, namely, linear discriminant analysis (LDA) and one-dimensional convolutional neural network (1D CNN), were employed to classify the two words from the recorded MEG signals.

RESULTS: LDA and 1D CNN achieved average decoding accuracies of 79.02% and 90.40%, respectively, in decoding overt speech, significantly surpassing the chance level (50%). The accuracy for decoding intended speech was 67.19% using 1D CNN.

CONCLUSIONS: This study showcases the possibility of decoding spontaneous overt and intended speech directly from neural signals in the absence of perceptual interference. We believe that these findings make a steady step toward the future spontaneous speech-based brain-computer interface.},
}

@article {pmid39106147,
year = {2024},
author = {Lyu, J and Yang, Y and Zong, Y and Leng, Y and Zheng, W and Ge, S},
title = {Novel Sinusoidal Signal Assisted Multivariate Variational Mode Decomposition Combined With Task-Related Component Analysis for Enhancing SSVEP-Based BCI Performance.},
journal = {IEEE journal of biomedical and health informatics},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/JBHI.2024.3439391},
pmid = {39106147},
issn = {2168-2208},
abstract = {Brain-computer interfaces (BCIs) based on steady-state visually evoked potential (SSVEP) have a broad application prospect owing to their multiple command output and high performance. Each harmonic component of SSVEP individually contains unique features, which can be utilized to enhance the recognition performance of SSVEP-based BCIs. However, the existing subband analysis methods for SSVEP, including those based on filter banks and existing mode decomposition methods, have limitations in extracting and utilizing independent harmonic components. This study proposes a sinusoidal signal assisted multivariate variational mode decomposition (SA-MVMD) algorithm that allows the constraint of the center frequencies and narrowband filtering structures of the intrinsic mode functions (IMFs) based on the prior frequency knowledge of the signal. It preserves the target information of the signal during decomposition while avoiding mode mixing and incorrect decomposition, thereby enabling the effective extraction of each independent harmonic component of SSVEP. Building on this, a SA-MVMD based task-related component analysis (SA-MVMD-TRCA) method is further proposed to fully utilize the features within the overall SSVEP as well as its independent harmonics, thereby enhancing the recognition performance. Testing on the public SSVEP Benchmark dataset demonstrates that the proposed method significantly outperforms the filter bank-based control methods. This study confirms the effectiveness of SA-MVMD and the potential of this approach, which analyzes and utilizes each independent harmonic of SSVEP, providing new strategies and perspectives for performance enhancement in SSVEP-based BCIs.},
}

@article {pmid39104699,
year = {2024},
author = {Rabbani, MHR and Islam, SMR},
title = {Deep learning networks based decision fusion model of EEG and fNIRS for classification of cognitive tasks.},
journal = {Cognitive neurodynamics},
volume = {18},
number = {4},
pages = {1489-1506},
pmid = {39104699},
issn = {1871-4080},
abstract = {The detection of the cognitive tasks performed by a subject during data acquisition of a neuroimaging method has a wide range of applications: functioning of brain-computer interface (BCI), detection of neuronal disorders, neurorehabilitation for disabled patients, and many others. Recent studies show that the combination or fusion of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) demonstrates improved classification and detection performance compared to sole-EEG and sole-fNIRS. Deep learning (DL) networks are suitable for the classification of large volume time-series data like EEG and fNIRS. This study performs the decision fusion of EEG and fNIRS. The classification of EEG, fNIRS, and decision-fused EEG-fNIRSinto cognitive task labels is performed by DL networks. Two different open-source datasets of simultaneously recorded EEG and fNIRS are examined in this study. Dataset 01 is comprised of 26 subjects performing 3 cognitive tasks: n-back, discrimination or selection response (DSR), and word generation (WG). After data acquisition, fNIRS is converted to oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (HbR) in Dataset 01. Dataset 02 is comprised of 29 subjects who performed 2 tasks: motor imagery and mental arithmetic. The classification procedure of EEG and fNIRS (or HbO2, HbR) are carried out by 7 DL classifiers: convolutional neural network (CNN), long short-term memory network (LSTM), gated recurrent unit (GRU), CNN-LSTM, CNN-GRU, LSTM-GRU, and CNN-LSTM-GRU. After the classification of single modalities, their prediction scores or decisions are combined to obtain the decision-fused modality. The classification performance is measured by overall accuracy and area under the ROC curve (AUC). The highest accuracy and AUC recorded in Dataset 01 are 96% and 100% respectively; both by the decision fusion modality using CNN-LSTM-GRU. For Dataset 02, the highest accuracy and AUC are 82.76% and 90.44% respectively; both by the decision fusion modality using CNN-LSTM. The experimental result shows that decision-fused EEG-HbO2-HbR and EEG-fNIRSdeliver higher performances compared to their constituent unimodalities in most cases. For DL classifiers, CNN-LSTM-GRU in Dataset 01 and CNN-LSTM in Dataset 02 yield the highest performance.},
}

@article {pmid39104685,
year = {2024},
author = {Yin, X and Lin, M and Liang, J and Zeng, F},
title = {Time-frequency feature extraction based on multivariable synchronization index for training-free SSVEP-based BCI.},
journal = {Cognitive neurodynamics},
volume = {18},
number = {4},
pages = {1733-1741},
pmid = {39104685},
issn = {1871-4080},
abstract = {Multivariate synchronization index (MSI), as an effective recognition algorithm for steady-state visual evoked potential (SSVEP) brain-computer interface (BCI), can accurately decode target frequencies without training. To further consider temporal features or extract harmonic components, extended MSI (EMSI), temporally local MSI (TMSI), and filter bank MSI (FBMSI) have been proposed. However, the promotion effects of the above three strategies on MSI have not been compared in detail. In this paper, the performance of EMSI, TMSI, and FBMSI under different time windows was analyzed with the same dataset. The results indicated that the improvement effect of the temporally local method on MSI was better than that of the other two methods under the short time window, and the effect of the filter bank method was better when the time window was greater than 0.8 s. Based on the idea of simultaneously extracting time-frequency features, FBEMSI and FBTMSI were proposed by integrating time delay embedding and temporally local method into FBMSI respectively. The two improved methods, which has no significant difference, can improve the recognition effect of FBMSI. But the computing time of FBEMSI was shorter, which can be a potential method for SSVEP-BCI.},
}

@article {pmid39104677,
year = {2024},
author = {Li, M and Qi, E and Xu, G and Jin, J and Zhao, Q and Guo, M and Liao, W},
title = {A delayed matching task-based study on action sequence of motor imagery.},
journal = {Cognitive neurodynamics},
volume = {18},
number = {4},
pages = {1593-1607},
pmid = {39104677},
issn = {1871-4080},
abstract = {The way people imagine greatly affects performance of brain-computer interface (BCI) based on motion imagery (MI). Action sequence is a basic unit of imitation, learning, and memory for motor behavior. Whether it influences the MI-BCI is unknown, and how to manifest this influence is difficult since the MI is a spontaneous brain activity. To investigate the influence of the action sequence, this study proposes a novel paradigm named action sequences observing and delayed matching task to use images and videos to guide people to observe, match and reinforce the memory of sequence. Seven subjects' ERPs and MI performance are analyzed under four different levels of complexities or orders of the sequence. Results demonstrated that the action sequence in terms of complexity and sequence order significantly affects the MI. The complex action in positive order obtains stronger ERD/ERS and more pronounced MI feature distributions, and yields an MI classification accuracy that is 12.3% higher than complex action in negative order (p < 0.05). In addition, the ERP amplitudes derived from the supplementary motor area show a positive correlation to the MI. This study demonstrates a new perspective of improving imagery in the MI-BCI by considering the complexity and order of the action sequences, and provides a novel index for manifesting the MI performance by ERP.},
}

@article {pmid39104673,
year = {2024},
author = {Rezvani, S and Hosseini-Zahraei, SH and Tootchi, A and Guger, C and Chaibakhsh, Y and Saberi, A and Chaibakhsh, A},
title = {A review on the performance of brain-computer interface systems used for patients with locked-in and completely locked-in syndrome.},
journal = {Cognitive neurodynamics},
volume = {18},
number = {4},
pages = {1419-1443},
pmid = {39104673},
issn = {1871-4080},
abstract = {Patients with locked-in syndrome (LIS) and complete locked-in syndrome (CLIS) own a fully functional brain restricted within a non-functional body. In order to help LIS patients stay connected with their surroundings, brain-computer interfaces (BCIs) and related technologies have emerged. BCIs translate brain activity into actions that can be performed by external devices enabling LIS patients to communicate, leading to an increase in their quality of life. The past decade has seen the rapid development of BCIs that have the potential to be used for patients with locked-in syndrome, from which a great deal is tested only on healthy subjects and not on actual patients. This study aims to (1) provide the readers with a comprehensive study that contributes to this growing area of research by exploring the performance of BCIs tested specifically on LIS and CLIS patients, (2) give an overview of different modalities and paradigms used in different stages of the locked-in syndrome, and (3) discuss the contributions and limitations of BCIs introduced for the LIS and CLIS patients in the state-of-the-art and lay a groundwork for researchers interested in this field.},
}

@article {pmid39103461,
year = {2024},
author = {Chockboondee, M and Jatupornpoonsub, T and Lertsukprasert, K and Wongsawat, Y},
title = {Effects of daily listening to 6 Hz binaural beats over one month: an event-related potentials study.},
journal = {Scientific reports},
volume = {14},
number = {1},
pages = {18059},
pmid = {39103461},
issn = {2045-2322},
support = {B42G670043//This project is supported by the National Higher Education Science Research and Innovation Policy Council, PMU B/ ; },
mesh = {Humans ; Male ; Female ; Adult ; Young Adult ; *Acoustic Stimulation ; Evoked Potentials, Auditory/physiology ; Electroencephalography ; Evoked Potentials/physiology ; Auditory Perception/physiology ; Event-Related Potentials, P300/physiology ; Cognition/physiology ; },
abstract = {The aim of the present study was to identify cognitive alterations, as indicated by event-related potentials (ERPs), after one month of daily exposure to theta binaural beats (BBs) for 10 minutes. The recruited healthy subjects (n = 60) were equally divided into experimental and control groups. For a month, the experimental group was required to practice BBs listening daily, while the control group did not. ERPs were assessed at three separate visits over a span of one month, with a two-week interval between each visit. At each visit, ERPs were measured before and after listening. The auditory and visual ERPs significantly increased the auditory and visual P300 amplitudes consistently at each visit. BBs enhanced the auditory N200 amplitude consistently across all visits, but the visual N200 amplitude increased only at the second and third visits. Compared to the healthy controls, daily exposure to BBs for two weeks resulted in increased auditory P300 amplitude. Additionally, four weeks of BBs exposure not only increased auditory P300 amplitude but also reduced P300 latency. These preliminary findings suggest that listening to BBs at 6 Hz for 10 minutes daily may enhance certain aspects of cognitive function. However, further research is needed to confirm these effects and to understand the underlying mechanisms. Identifying the optimal duration and practice of listening to 6 Hz BBs could potentially contribute to cognitive enhancement strategies in healthy individuals.},
}

Humans
Male
Female
Adult
Young Adult
*Acoustic Stimulation
Evoked Potentials, Auditory/physiology
Electroencephalography
Evoked Potentials/physiology
Auditory Perception/physiology
Event-Related Potentials, P300/physiology
Cognition/physiology

@article {pmid39103336,
year = {2024},
author = {Sun, X and Dias, L and Peng, C and Zhang, Z and Ge, H and Wang, Z and Jin, J and Jia, M and Xu, T and Guo, W and Zheng, W and He, Y and Wu, Y and Cai, X and Agostinho, P and Qu, J and Cunha, RA and Zhou, X and Bai, R and Chen, JF},
title = {40 Hz light flickering facilitates the glymphatic flow via adenosine signaling in mice.},
journal = {Cell discovery},
volume = {10},
number = {1},
pages = {81},
pmid = {39103336},
issn = {2056-5968},
support = {31600859//National Natural Science Foundation of China (National Science Foundation of China)/ ; 31970948//National Natural Science Foundation of China (National Science Foundation of China)/ ; 82101556//National Natural Science Foundation of China (National Science Foundation of China)/ ; LQ22H090013//Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation)/ ; },
abstract = {The glymphatic-lymphatic system is increasingly recognized as fundamental for the homeostasis of the brain milieu since it defines cerebral spinal fluid flow in the brain parenchyma and eliminates metabolic waste. Animal and human studies have uncovered several important physiological factors regulating the glymphatic system including sleep, aquaporin-4, and hemodynamic factors. Yet, our understanding of the modulation of the glymphatic system is limited, which has hindered the development of glymphatic-based treatment for aging and neurodegenerative disorders. Here, we present the evidence from fluorescence tracing, two-photon recording, and dynamic contrast-enhanced magnetic resonance imaging analyses that 40 Hz light flickering enhanced glymphatic influx and efflux independently of anesthesia and sleep, an effect attributed to increased astrocytic aquaporin-4 polarization and enhanced vasomotion. Adenosine-A2A receptor (A2AR) signaling emerged as the neurochemical underpinning of 40 Hz flickering-induced enhancement of glymphatic flow, based on increased cerebrofluid adenosine levels, the abolishment of enhanced glymphatic flow by pharmacological or genetic inactivation of equilibrative nucleotide transporters-2 or of A2AR, and by the physical and functional A2AR-aquaporin-4 interaction in astrocytes. These findings establish 40 Hz light flickering as a novel non-invasive strategy of enhanced glymphatic flow, with translational potential to relieve brain disorders.},
}

@article {pmid39103043,
year = {2024},
author = {Shi, X and Li, B and Wang, W and Qin, Y and Wang, H and Wang, X},
title = {EEG-VTTCNet: A loss joint training model based on the vision transformer and the temporal convolution network for EEG-based motor imagery classification.},
journal = {Neuroscience},
volume = {},
number = {},
pages = {},
doi = {10.1016/j.neuroscience.2024.07.051},
pmid = {39103043},
issn = {1873-7544},
abstract = {Brain-computer interface (BCI) is a technology that directly connects signals between the human brain and a computer or other external device. Motor imagery electroencephalographic (MI-EEG) signals are considered a promising paradigm for BCI systems, with a wide range of potential applications in medical rehabilitation, human-computer interaction, and virtual reality. Accurate decoding of MI-EEG signals poses a significant challenge due to issues related to the quality of the collected EEG data and subject variability. Therefore, developing an efficient MI-EEG decoding network is crucial and warrants research. This paper proposes a loss joint training model based on the vision transformer (VIT) and the temporal convolutional network (EEG-VTTCNet) to classify MI-EEG signals. To take advantage of multiple modules together, the EEG-VTTCNet adopts a shared convolution strategy and a dual-branching strategy. The dual-branching modules perform complementary learning and jointly train shared convolutional modules with better performance. We conducted experiments on the BCI Competition IV-2a and IV-2b datasets, and the proposed network outperformed the current state-of-the-art techniques with an accuracy of 84.58% and 90.94%, respectively, for the subject-dependent mode. In addition, we used t-SNE to visualize the features extracted by the proposed network, further demonstrating the effectiveness of the feature extraction framework. We also conducted extensive ablation and hyperparameter tuning experiments to construct a robust network architecture that can be well generalized.},
}

@article {pmid39102329,
year = {2024},
author = {Shin, J and Chung, W},
title = {Multiband Convolutional Riemannian Network with Band-wise Riemannian Triplet Loss for Motor Imagery Classification.},
journal = {IEEE journal of biomedical and health informatics},
volume = {PP},
number = {},
pages = {},
doi = {10.1109/JBHI.2024.3438167},
pmid = {39102329},
issn = {2168-2208},
abstract = {This paper presents a novel motor imagery classification algorithm that uses an overlapping multiscale multiband convolutional Riemannian network with band-wise Riemannian triplet loss to improve classification performance. Despite the superior performance of the Riemannian approach over the common spatial pattern filter approach, deep learning methods that generalize the Riemannian approach have received less attention. The proposed algorithm develops a state-of-the-art multiband Riemannian network that reduces the potential overfitting problem of Riemannian networks, a drawback of Riemannian networks due to their inherent large feature dimension from covariance matrix, by using fewer subbands with discriminative frequency diversity, by inserting convolutional layers before computing the subband covariance matrix, and by regularizing subband networks with Riemannian triplet loss. The proposed method is evaluated using the publicly available datasets, the BCI Competition IV dataset 2a and the OpenBMI dataset. The experimental results confirm that the proposed method improves performance, in particular achieving state-of-the-art classification accuracy among the currently studied Riemannian networks.},
}

@article {pmid39099770,
year = {2024},
author = {Chen, W and Liao, Y and Dai, R and Dong, Y and Huang, L},
title = {EEG-based emotion recognition using graph convolutional neural network with dual attention mechanism.},
journal = {Frontiers in computational neuroscience},
volume = {18},
number = {},
pages = {1416494},
pmid = {39099770},
issn = {1662-5188},
abstract = {EEG-based emotion recognition is becoming crucial in brain-computer interfaces (BCI). Currently, most researches focus on improving accuracy, while neglecting further research on the interpretability of models, we are committed to analyzing the impact of different brain regions and signal frequency bands on emotion generation based on graph structure. Therefore, this paper proposes a method named Dual Attention Mechanism Graph Convolutional Neural Network (DAMGCN). Specifically, we utilize graph convolutional neural networks to model the brain network as a graph to extract representative spatial features. Furthermore, we employ the self-attention mechanism of the Transformer model which allocates more electrode channel weights and signal frequency band weights to important brain regions and frequency bands. The visualization of attention mechanism clearly demonstrates the weight allocation learned by DAMGCN. During the performance evaluation of our model on the DEAP, SEED, and SEED-IV datasets, we achieved the best results on the SEED dataset, showing subject-dependent experiments' accuracy of 99.42% and subject-independent experiments' accuracy of 73.21%. The results are demonstrably superior to the accuracies of most existing models in the realm of EEG-based emotion recognition.},
}

@article {pmid39099169,
year = {2024},
author = {Wang, J and Qiu, Y and Yang, L and Wang, J and He, J and Tang, C and Yang, Z and Hong, W and Yang, B and He, Q and Weng, Q},
title = {Preserving mitochondrial homeostasis protects against drug-induced liver injury via inducing OPTN (optineurin)-dependent Mitophagy.},
journal = {Autophagy},
volume = {},
number = {},
pages = {1-20},
doi = {10.1080/15548627.2024.2384348},
pmid = {39099169},
issn = {1554-8635},
abstract = {Disruption of mitochondrial function is observed in multiple drug-induced liver injuries (DILIs), a significant global health threat. However, how the mitochondrial dysfunction occurs and whether maintain mitochondrial homeostasis is beneficial for DILIs remains unclear. Here, we show that defective mitophagy by OPTN (optineurin) ablation causes disrupted mitochondrial homeostasis and aggravates hepatocytes necrosis in DILIs, while OPTN overexpression protects against DILI depending on its mitophagic function. Notably, mass spectrometry analysis identifies a new mitochondrial substrate, GCDH (glutaryl-CoA dehydrogenase), which can be selectively recruited by OPTN for mitophagic degradation, and a new cofactor, VCP (valosin containing protein) that interacts with OPTN to stabilize BECN1 during phagophore assembly, thus boosting OPTN-mediated mitophagy initiation to clear damaged mitochondria and preserve mitochondrial homeostasis in DILIs. Then, the accumulation of OPTN in different DILIs is further validated with a protective effect, and pyridoxine is screened and established to alleviate DILIs by inducing OPTN-mediated mitophagy. Collectively, our findings uncover a dual role of OPTN in mitophagy initiation and implicate the preservation of mitochondrial homeostasis via inducing OPTN-mediated mitophagy as a potential therapeutic approach for DILIs.Abbreviation: AILI: acetaminophen-induced liver injury; ALS: amyotrophic lateral sclerosis; APAP: acetaminophen; CALCOCO2/NDP52: calcium binding and coiled-coil domain 2; CHX: cycloheximide; Co-IP: co-immunoprecipitation; DILI: drug-induced liver injury; FL: full length; GCDH: glutaryl-CoA dehydrogenase; GOT1/AST: glutamic-oxaloacetic transaminase 1; GO: gene ontology; GSEA: gene set enrichment analysis; GPT/ALT: glutamic - pyruvic transaminase; INH: isoniazid; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MMP: mitochondrial membrane potential; MST: microscale thermophoresis; MT-CO2/COX-II: mitochondrially encoded cytochrome c oxidase II; OPTN: optineurin; PINK1: PTEN induced kinase 1; PRKN: parkin RBR E3 ubiquitin protein ligase; TIMM23: translocase of inner mitochondrial membrane 23; TOMM20: translocase of outer mitochondrial membrane 20; TSN: toosendanin; VCP: valosin containing protein, WIPI2: WD repeat domain, phosphoinositide interacting 2.},
}

@article {pmid39097741,
year = {2024},
author = {El Kirat, H and van Belle, S and Khattabi, A and Belrhiti, Z},
title = {Behavioral change interventions, theories, and techniques to reduce physical inactivity and sedentary behavior in the general population: a scoping review.},
journal = {BMC public health},
volume = {24},
number = {1},
pages = {2099},
pmid = {39097741},
issn = {1471-2458},
mesh = {Humans ; *Sedentary Behavior ; Exercise/psychology ; Health Promotion/methods ; Behavior Therapy/methods ; Health Behavior ; },
abstract = {BACKGROUND: Worldwide, physical inactivity (PIA) and sedentary behavior (SB) are recognized as significant challenges hindering the achievement of the United Nations (UN) sustainable development goals (SDGs). PIA and SB are responsible for 1.6 million deaths attributed to non-communicable diseases (NCDs). The World Health Organization (WHO) has urged governments to implement interventions informed by behavioral theories aimed at reducing PIA and SB. However, limited attention has been given to the range of theories, techniques, and contextual conditions underlying the design of behavioral theories. To this end, we set out to map these interventions, their levels of action, their mode of delivery, and how extensively they apply behavioral theories, constructs, and techniques.

METHODS: Following the scoping review methodology of Arksey and O'Malley (2005), we included peer-reviewed articles on behavioral theories interventions centered on PIA and SB, published between 2010 and 2023 in Arabic, French, and English in four databases (Scopus, Web of Science [WoS], PubMed, and Google Scholar). We adopted a framework thematic analysis based on the upper-level ontology of behavior theories interventions, Behavioral theories taxonomies, and the first version (V1) taxonomy of behavior change techniques(BCTs).

RESULTS: We included 29 studies out of 1,173 that were initially screened/searched. The majority of interventions were individually focused (n = 15). Few studies have addressed interpersonal levels (n = 6) or organizational levels (n = 6). Only two interventions can be described as systemic (i.e., addressing the individual, interpersonal, organizational, and institutional factors)(n = 2). Most behavior change interventions use four theories: The Social cognitive theory (SCT), the socioecological model (SEM), SDT, and the transtheoretical model (TTM). Most behavior change interventions (BCIS) involve goal setting, social support, and action planning with various degrees of theoretical use (intensive [n = 15], moderate [n = 11], or low [n = 3]).

DISCUSSION AND CONCLUSION: Our review suggests the need to develop systemic and complementary interventions that entail the micro-, meso- and macro-level barriers to behavioral changes. Theory informed BCI need to integrate synergistic BCTs into models that use micro-, meso- and macro-level theories to determine behavioral change. Future interventions need to appropriately use a mix of behavioral theories and BCTs to address the systemic nature of behavioral change as well as the heterogeneity of contexts and targeted populations.},
}

Humans
*Sedentary Behavior
Exercise/psychology
Health Promotion/methods
Behavior Therapy/methods
Health Behavior

@article {pmid39095351,
year = {2024},
author = {Tian, F and Zhang, Y and Schriver, KE and Hu, JM and Roe, AW},
title = {A novel interface for cortical columnar neuromodulation with multipoint infrared neural stimulation.},
journal = {Nature communications},
volume = {15},
number = {1},
pages = {6528},
pmid = {39095351},
issn = {2041-1723},
support = {U20A20221//National Natural Science Foundation of China (National Science Foundation of China)/ ; 819611280292//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
mesh = {Animals ; Cats ; *Visual Cortex/physiology ; *Infrared Rays ; Photic Stimulation/methods ; Optical Fibers ; Visual Prosthesis ; },
abstract = {Cutting edge advances in electrical visual cortical prosthetics have evoked perception of shapes, motion, and letters in the blind. Here, we present an alternative optical approach using pulsed infrared neural stimulation. To interface with dense arrays of cortical columns with submillimeter spatial precision, both linear array and 100-fiber bundle array optical fiber interfaces were devised. We deliver infrared stimulation through these arrays in anesthetized cat visual cortex and monitor effects by optical imaging in contralateral visual cortex. Infrared neural stimulation modulation of response to ongoing visual oriented gratings produce enhanced responses in orientation-matched domains and suppressed responses in non-matched domains, consistent with a known higher order integration mediated by callosal inputs. Controls include dynamically applied speeds, directions and patterns of multipoint stimulation. This provides groundwork for a distinct type of prosthetic targeted to maps of visual cortical columns.},
}

Animals
Cats
*Visual Cortex/physiology
*Infrared Rays
Photic Stimulation/methods
Optical Fibers
Visual Prosthesis

@article {pmid39092732,
year = {2024},
author = {Islam, MM and Vashishat, A and Kumar, M},
title = {Advancements Beyond Limb Loss: Exploring the Intersection of AI and BCI in Prosthetic Evaluation.},
journal = {Current pharmaceutical design},
volume = {},
number = {},
pages = {},
doi = {10.2174/0113816128324653240731075146},
pmid = {39092732},
issn = {1873-4286},
}

@article {pmid39086375,
year = {2024},
author = {Angelopoulou, A and Chihi, I and Hemanth, J},
title = {Editorial: Methods and protocols in Brain-Computer Interfaces.},
journal = {Frontiers in human neuroscience},
volume = {18},
number = {},
pages = {1447973},
pmid = {39086375},
issn = {1662-5161},
}

@article {pmid39086374,
year = {2024},
author = {Xavier Fidêncio, A and Klaes, C and Iossifidis, I},
title = {A generic error-related potential classifier based on simulated subjects.},
journal = {Frontiers in human neuroscience},
volume = {18},
number = {},
pages = {1390714},
pmid = {39086374},
issn = {1662-5161},
abstract = {Error-related potentials (ErrPs) are brain signals known to be generated as a reaction to erroneous events. Several works have shown that not only self-made errors but also mistakes generated by external agents can elicit such event-related potentials. The possibility of reliably measuring ErrPs through non-invasive techniques has increased the interest in the brain-computer interface (BCI) community in using such signals to improve performance, for example, by performing error correction. Extensive calibration sessions are typically necessary to gather sufficient trials for training subject-specific ErrP classifiers. This procedure is not only time-consuming but also boresome for participants. In this paper, we explore the effectiveness of ErrPs in closed-loop systems, emphasizing their dependency on precise single-trial classification. To guarantee the presence of an ErrPs signal in the data we employ and to ensure that the parameters defining ErrPs are systematically varied, we utilize the open-source toolbox SEREEGA for data simulation. We generated training instances and evaluated the performance of the generic classifier on both simulated and real-world datasets, proposing a promising alternative to conventional calibration techniques. Results show that a generic support vector machine classifier reaches balanced accuracies of 72.9%, 62.7%, 71.0%, and 70.8% on each validation dataset. While performing similarly to a leave-one-subject-out approach for error class detection, the proposed classifier shows promising generalization across different datasets and subjects without further adaptation. Moreover, by utilizing SEREEGA, we can systematically adjust parameters to accommodate the variability in the ErrP, facilitating the systematic validation of closed-loop setups. Furthermore, our objective is to develop a universal ErrP classifier that captures the signal's variability, enabling it to determine the presence or absence of an ErrP in real EEG data.},
}

@article {pmid39083601,
year = {2024},
author = {Jia, K and Wang, M and Steinwurzel, C and Ziminski, JJ and Xi, Y and Emir, U and Kourtzi, Z},
title = {Recurrent inhibition refines mental templates to optimize perceptual decisions.},
journal = {Science advances},
volume = {10},
number = {31},
pages = {eado7378},
pmid = {39083601},
issn = {2375-2548},
mesh = {Humans ; *Decision Making/physiology ; *Magnetic Resonance Imaging/methods ; *Visual Cortex/physiology ; Male ; Adult ; Female ; gamma-Aminobutyric Acid/metabolism ; Visual Perception/physiology ; Neuronal Plasticity/physiology ; Young Adult ; Brain Mapping ; },
abstract = {Translating sensory inputs to perceptual decisions relies on building internal representations of features critical for solving complex tasks. Yet, we still lack a mechanistic account of how the brain forms these mental templates of task-relevant features to optimize decision-making. Here, we provide evidence for recurrent inhibition: an experience-dependent plasticity mechanism that refines mental templates by enhancing γ-aminobutyric acid (GABA)-mediated (GABAergic) inhibition and recurrent processing in superficial visual cortex layers. We combine ultrahigh-field (7 T) functional magnetic resonance imaging at submillimeter resolution with magnetic resonance spectroscopy to investigate the fine-scale functional and neurochemical plasticity mechanisms for optimized perceptual decisions. We demonstrate that GABAergic inhibition increases following training on a visual (i.e., fine orientation) discrimination task, enhancing the discriminability of orientation representations in superficial visual cortex layers that are known to support recurrent processing. Modeling functional and neurochemical plasticity interactions reveals that recurrent inhibitory processing optimizes brain computations for perpetual decisions and adaptive behavior.},
}

Humans
*Decision Making/physiology
*Magnetic Resonance Imaging/methods
*Visual Cortex/physiology
Male
Adult
Female
gamma-Aminobutyric Acid/metabolism
Visual Perception/physiology
Neuronal Plasticity/physiology
Young Adult
Brain Mapping

@article {pmid39082285,
year = {2024},
author = {Khorev, V and Kurkin, S and Badarin, A and Antipov, V and Pitsik, E and Andreev, A and Grubov, V and Drapkina, O and Kiselev, A and Hramov, A},
title = {Review on the Use of Brain Computer Interface Rehabilitation Methods for Treating Mental and Neurological Conditions.},
journal = {Journal of integrative neuroscience},
volume = {23},
number = {7},
pages = {125},
doi = {10.31083/j.jin2307125},
pmid = {39082285},
issn = {0219-6352},
support = {123020600127-4//Russian Ministry of Health as part of the scientific work "Development of a multimodal biofeedback-based hardware and software system for rehabilitation of patients with cognitive and motor disorders of different nature"/ ; },
mesh = {Humans ; *Brain-Computer Interfaces ; *Neurofeedback/methods ; *Mental Disorders/rehabilitation ; *Nervous System Diseases/rehabilitation ; Neurological Rehabilitation/methods ; },
abstract = {This review provides a comprehensive examination of recent developments in both neurofeedback and brain-computer interface (BCI) within the medical field and rehabilitation. By analyzing and comparing results obtained with various tools and techniques, we aim to offer a systematic understanding of BCI applications concerning different modalities of neurofeedback and input data utilized. Our primary objective is to address the existing gap in the area of meta-reviews, which provides a more comprehensive outlook on the field, allowing for the assessment of the current landscape and developments within the scope of BCI. Our main methodologies include meta-analysis, search queries employing relevant keywords, and a network-based approach. We are dedicated to delivering an unbiased evaluation of BCI studies, elucidating the primary vectors of research development in this field. Our review encompasses a diverse range of applications, incorporating the use of brain-computer interfaces for rehabilitation and the treatment of various diagnoses, including those related to affective spectrum disorders. By encompassing a wide variety of use cases, we aim to offer a more comprehensive perspective on the utilization of neurofeedback treatments across different contexts. The structured and organized presentation of information, complemented by accompanying visualizations and diagrams, renders this review a valuable resource for scientists and researchers engaged in the domains of biofeedback and brain-computer interfaces.},
}

Humans
*Brain-Computer Interfaces
*Neurofeedback/methods
*Mental Disorders/rehabilitation
*Nervous System Diseases/rehabilitation
Neurological Rehabilitation/methods

@article {pmid39082284,
year = {2024},
author = {Ou, Y and Wang, F and Feng, B and Tang, L and Pan, J},
title = {Spindle Detection Based on Elastic Time Window and Spatial Pyramid Pooling.},
journal = {Journal of integrative neuroscience},
volume = {23},
number = {7},
pages = {134},
doi = {10.31083/j.jin2307134},
pmid = {39082284},
issn = {0219-6352},
support = {2021A1515011853//Guangdong Basic and Applied Basic Research Foundation/ ; 61906019//National Natural Science Foundation of China/ ; 62006082//National Natural Science Foundation of China/ ; 2022ZD0208900//STI 2030-Major Projects/ ; },
mesh = {Humans ; *Electroencephalography/methods ; *Algorithms ; Sleep Stages/physiology ; Signal Processing, Computer-Assisted ; Adult ; },
abstract = {BACKGROUND: Sleep spindles have emerged as valuable biomarkers for assessing cognitive abilities and related disorders, underscoring the importance of their detection in clinical research. However, template matching-based algorithms using fixed templates may not be able to fully adapt to spindles of different durations. Moreover, inspired by the multiscale feature extraction of images, the use of multiscale feature extraction methods can be used to better adapt to spindles of different frequencies and durations.

METHODS: Therefore, this study proposes a novel automatic spindle detection algorithm based on elastic time windows and spatial pyramid pooling (SPP) for extracting multiscale features. The algorithm utilizes elastic time windows to segment electroencephalogram (EEG) signals, enabling the extraction of features across multiple scales. This approach accommodates significant variations in spindle duration and polarization positioning during different EEG epochs. Additionally, spatial pyramid pooling is integrated into a depthwise separable convolutional (DSC) network to perform multiscale pooling on the segmented spindle signal features at different scales.

RESULTS: Compared with existing template matching algorithms, this algorithm's spindle wave polarization positioning is more consistent with the real situation. Experimental results conducted on the public dataset DREAMS show that the average accuracy of this algorithm reaches 95.75%, with an average negative predictive value (NPV) of 96.55%, indicating its advanced performance.

CONCLUSIONS: The effectiveness of each module was verified through thorough ablation experiments. More importantly, the algorithm shows strong robustness when faced with changes in different experimental subjects. This feature makes the algorithm more accurate at identifying sleep spindles and is expected to help experts automatically detect spindles in sleep EEG signals, reduce the workload and time of manual detection, and improve efficiency.},
}

Humans
*Electroencephalography/methods
*Algorithms
Sleep Stages/physiology
Signal Processing, Computer-Assisted
Adult

@article {pmid39081972,
year = {2023},
author = {Perez Garcia, G and Bicak, M and Buros, J and Haure-Mirande, JV and Perez, GM and Otero-Pagan, A and Gama Sosa, MA and De Gasperi, R and Sano, M and Gage, FH and Barlow, C and Dudley, JT and Glicksberg, BS and Wang, Y and Readhead, B and Ehrlich, ME and Elder, GA and Gandy, S},
title = {Beneficial effects of physical exercise and an orally active mGluR2/3 antagonist pro-drug on neurogenesis and behavior in an Alzheimer's amyloidosis model.},
journal = {Frontiers in dementia},
volume = {2},
number = {},
pages = {1198006},
pmid = {39081972},
issn = {2813-3919},
abstract = {BACKGROUND: Modulation of physical activity represents an important intervention that may delay, slow, or prevent mild cognitive impairment (MCI) or dementia due to Alzheimer's disease (AD). One mechanism proposed to underlie the beneficial effect of physical exercise (PE) involves the apparent stimulation of adult hippocampal neurogenesis (AHN). BCI-838 is a pro-drug whose active metabolite BCI-632 is a negative allosteric modulator at group II metabotropic glutamate receptors (mGluR2/3). We previously demonstrated that administration of BCI-838 to a mouse model of brain accumulation of oligomeric Aβ[E22Q] (APP [E693Q] = "Dutch APP") reduced learning behavior impairment and anxiety, both of which are associated with the phenotype of Dutch APP mice.

METHODS: 3-month-old mice were administered BCI-838 and/or physical exercise for 1 month and then tested in novel object recognition, neurogenesis, and RNAseq.

RESULTS: Here we show that (i) administration of BCI-838 and a combination of BCI-838 and PE enhanced AHN in a 4-month old mouse model of AD amyloid pathology (APP [KM670/671NL] /PSEN1 [Δexon9]= APP/PS1), (ii) administration of BCI-838 alone or with PE led to stimulation of AHN and improvement in recognition memory, (iii) the hippocampal dentate gyrus transcriptome of APP/PS1 mice following BCI-838 treatment showed up-regulation of brain-derived neurotrophic factor (BDNF), PIK3C2A of the PI3K-mTOR pathway, and metabotropic glutamate receptors, and down-regulation of EIF5A involved in modulation of mTOR activity by ketamine, and (iv) validation by qPCR of an association between increased BDNF levels and BCI-838 treatment.

CONCLUSION: Our study points to BCI-838 as a safe and orally active compound capable of mimicking the beneficial effect of PE on AHN and recognition memory in a mouse model of AD amyloid pathology.},
}

@article {pmid39080312,
year = {2024},
author = {Wang, G and Marcucci, G and Peters, B and Braidotti, MC and Muckli, L and Faccio, D},
title = {Human-centred physical neuromorphics with visual brain-computer interfaces.},
journal = {Nature communications},
volume = {15},
number = {1},
pages = {6393},
pmid = {39080312},
issn = {2041-1723},
support = {EP/T021020/1//RCUK | Engineering and Physical Sciences Research Council (EPSRC)/ ; },
mesh = {*Brain-Computer Interfaces ; Humans ; *Evoked Potentials, Visual/physiology ; *Electroencephalography ; Male ; Adult ; Brain/physiology ; Photic Stimulation ; Female ; Young Adult ; Neural Networks, Computer ; },
abstract = {Steady-state visual evoked potentials (SSVEPs) are widely used for brain-computer interfaces (BCIs) as they provide a stable and efficient means to connect the computer to the brain with a simple flickering light. Previous studies focused on low-density frequency division multiplexing techniques, i.e. typically employing one or two light-modulation frequencies during a single flickering light stimulation. Here we show that it is possible to encode information in SSVEPs excited by high-density frequency division multiplexing, involving hundreds of frequencies. We then demonstrate the ability to transmit entire images from the computer to the brain/EEG read-out in relatively short times. High-density frequency multiplexing also allows to implement a photonic neural network utilizing SSVEPs, that is applied to simple classification tasks and exhibits promising scalability properties by connecting multiple brains in series. Our findings open up new possibilities for the field of neural interfaces, holding potential for various applications, including assistive technologies and cognitive enhancements, to further improve human-machine interactions.},
}

*Brain-Computer Interfaces
Humans
*Evoked Potentials, Visual/physiology
*Electroencephalography
Male
Adult
Brain/physiology
Photic Stimulation
Female
Young Adult
Neural Networks, Computer

@article {pmid39078880,
year = {2024},
author = {Codol, O and Michaels, JA and Kashefi, M and Pruszynski, JA and Gribble, PL},
title = {MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks.},
journal = {eLife},
volume = {12},
number = {},
pages = {},
pmid = {39078880},
issn = {2050-084X},
support = {RGPIN/05458-2018//Natural Sciences and Engineering Research Council of Canada/ ; PJT-175010/CAPMC/CIHR/Canada ; RGPIN-2022-04421//Natural Sciences and Engineering Research Council of Canada/ ; PJT-156241/CAPMC/CIHR/Canada ; },
mesh = {*Neural Networks, Computer ; Biomechanical Phenomena ; *Software ; Humans ; Algorithms ; },
abstract = {Artificial neural networks (ANNs) are a powerful class of computational models for unravelling neural mechanisms of brain function. However, for neural control of movement, they currently must be integrated with software simulating biomechanical effectors, leading to limiting impracticalities: (1) researchers must rely on two different platforms and (2) biomechanical effectors are not generally differentiable, constraining researchers to reinforcement learning algorithms despite the existence and potential biological relevance of faster training methods. To address these limitations, we developed MotorNet, an open-source Python toolbox for creating arbitrarily complex, differentiable, and biomechanically realistic effectors that can be trained on user-defined motor tasks using ANNs. MotorNet is designed to meet several goals: ease of installation, ease of use, a high-level user-friendly application programming interface, and a modular architecture to allow for flexibility in model building. MotorNet requires no dependencies outside Python, making it easy to get started with. For instance, it allows training ANNs on typically used motor control models such as a two joint, six muscle, planar arm within minutes on a typical desktop computer. MotorNet is built on PyTorch and therefore can implement any network architecture that is possible using the PyTorch framework. Consequently, it will immediately benefit from advances in artificial intelligence through PyTorch updates. Finally, it is open source, enabling users to create and share their own improvements, such as new effector and network architectures or custom task designs. MotorNet's focus on higher-order model and task design will alleviate overhead cost to initiate computational projects for new researchers by providing a standalone, ready-to-go framework, and speed up efforts of established computational teams by enabling a focus on concepts and ideas over implementation.},
}

*Neural Networks, Computer
Biomechanical Phenomena
*Software
Humans
Algorithms

@article {pmid39074028,
year = {2024},
author = {Lee, BH and Cho, JH and Kwon, BH and Lee, M and Lee, SW},
title = {Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control.},
journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
volume = {32},
number = {},
pages = {2793-2804},
doi = {10.1109/TNSRE.2024.3434983},
pmid = {39074028},
issn = {1558-0210},
mesh = {Humans ; *Electroencephalography/methods ; *Robotics ; Calibration ; *Algorithms ; Reproducibility of Results ; Male ; *Arm/physiology ; Adult ; Female ; Imagination/physiology ; Brain-Computer Interfaces ; Young Adult ; Neural Networks, Computer ; Speech/physiology ; },
abstract = {Robotic arms are increasingly being utilized in shared workspaces, which necessitates the accurate interpretation of human intentions for both efficiency and safety. Electroencephalogram (EEG) signals, commonly employed to measure brain activity, offer a direct communication channel between humans and robotic arms. However, the ambiguous and unstable characteristics of EEG signals, coupled with their widespread distribution, make it challenging to collect sufficient data and hinder the calibration performance for new signals, thereby reducing the reliability of EEG-based applications. To address these issues, this study proposes an iteratively calibratable network aimed at enhancing the reliability and efficiency of EEG-based robotic arm control systems. The proposed method integrates feature inputs with network expansion techniques. This integration allows a network trained on an extensive initial dataset to adapt effectively to new users during calibration. Additionally, our approach combines motor imagery and speech imagery datasets to increase not only its intuitiveness but also the number of command classes. The evaluation is conducted in a pseudo-online manner, with a robotic arm operating in real-time to collect data, which is then analyzed offline. The evaluation results demonstrated that the proposed method outperformed the comparison group in 10 sessions and demonstrated competitive results when the two paradigms were combined. Therefore, it was confirmed that the network can be calibrated and personalized using only the new data from new users.},
}

Humans
*Electroencephalography/methods
*Robotics
Calibration
*Algorithms
Reproducibility of Results
Male
*Arm/physiology
Adult
Female
Imagination/physiology
Brain-Computer Interfaces
Young Adult
Neural Networks, Computer
Speech/physiology

@article {pmid39074021,
year = {2024},
author = {Yi, Z and Pan, J and Chen, Z and Lu, D and Cai, H and Li, J and Xie, Q},
title = {A Hybrid BCI Integrating EEG and Eye-Tracking for Assisting Clinical Communication in Patients With Disorders of Consciousness.},
journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
volume = {32},
number = {},
pages = {2759-2771},
doi = {10.1109/TNSRE.2024.3435016},
pmid = {39074021},
issn = {1558-0210},
mesh = {Humans ; *Brain-Computer Interfaces ; *Electroencephalography/methods ; Male ; Female ; *Consciousness Disorders/physiopathology/diagnosis ; Adult ; *Eye-Tracking Technology ; *Event-Related Potentials, P300/physiology ; Middle Aged ; *Algorithms ; Young Adult ; Neural Networks, Computer ; Communication Aids for Disabled ; Communication ; Healthy Volunteers ; Attention/physiology ; },
abstract = {Assessing communication abilities in patients with disorders of consciousness (DOCs) is challenging due to limitations in the behavioral scale. Electroencephalogram-based brain-computer interfaces (BCIs) and eye-tracking for detecting ocular changes can capture mental activities without requiring physical behaviors and thus may be a solution. This study proposes a hybrid BCI that integrates EEG and eye tracking to facilitate communication in patients with DOC. Specifically, the BCI presented a question and two randomly flashing answers (yes/no). The subjects were instructed to focus on an answer. A multimodal target recognition network (MTRN) is proposed to detect P300 potentials and eye-tracking responses (i.e., pupil constriction and gaze) and identify the target in real time. In the MTRN, the dual-stream feature extraction module with two independent multiscale convolutional neural networks extracts multiscale features from multimodal data. Then, the multimodal attention strategy adaptively extracts the most relevant information about the target from multimodal data. Finally, a prototype network is designed as a classifier to facilitate small-sample data classification. Ten healthy individuals, nine DOC patients and one LIS patient were included in this study. All healthy subjects achieved 100% accuracy. Five patients could communicate with our BCI, with 76.1±7.9% accuracy. Among them, two patients who were noncommunicative on the behavioral scale exhibited communication ability via our BCI. Additionally, we assessed the performance of unimodal BCIs and compared MTRNs with other methods. All the results suggested that our BCI can yield more sensitive outcomes than the CRS-R and can serve as a valuable communication tool.},
}

Humans
*Brain-Computer Interfaces
*Electroencephalography/methods
Male
Female
*Consciousness Disorders/physiopathology/diagnosis
Adult
*Eye-Tracking Technology
*Event-Related Potentials, P300/physiology
Middle Aged
*Algorithms
Young Adult
Neural Networks, Computer
Communication Aids for Disabled
Communication
Healthy Volunteers
Attention/physiology