Invasive as well as non-invasive neurotechnologies conceptualized to interface the central and peripheral nervous system have been probed for the past decades,which refer to electroencephalography,electrocorticography...Invasive as well as non-invasive neurotechnologies conceptualized to interface the central and peripheral nervous system have been probed for the past decades,which refer to electroencephalography,electrocorticography and microelectrode arrays.The challenges of these mentioned approaches are characterized by the bandwidth of the spatiotemporal resolution,which in turn is essential for large-area neuron recordings(Abiri et al.,2019).展开更多
Brain-computer interfaces(BCIs)represent an emerging technology that facilitates direct communication between the brain and external devices.In recent years,numerous review articles have explored various aspects of BC...Brain-computer interfaces(BCIs)represent an emerging technology that facilitates direct communication between the brain and external devices.In recent years,numerous review articles have explored various aspects of BCIs,including their fundamental principles,technical advancements,and applications in specific domains.However,these reviews often focus on signal processing,hardware development,or limited applications such as motor rehabilitation or communication.This paper aims to offer a comprehensive review of recent electroencephalogram(EEG)-based BCI applications in the medical field across 8 critical areas,encompassing rehabilitation,daily communication,epilepsy,cerebral resuscitation,sleep,neurodegenerative diseases,anesthesiology,and emotion recognition.Moreover,the current challenges and future trends of BCIs were also discussed,including personal privacy and ethical concerns,network security vulnerabilities,safety issues,and biocompatibility.展开更多
Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for ...Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for stakeholders and the entire community.Aims This study aims to establish a multidisciplinary consensus of principles for ethical governance of clinical BCI research for mental disorders and offer practical ethical guidance to stakeholders involved.Methods A systematic literature review,symposium and roundtable discussions,and a pre-Delphi(round 0)survey were conducted to form the questionnaire for the three-round modified Delphi study.Two rounds of surveys,followed by a third round of independent interviews of 25 experts from BCI-related research domains,were involved.We conducted quantitative analysis of responses and agreements among experts to reveal the consensus and differences regarding the ethical governance of mental BCI research from a multidisciplinary perspective.Results The Delphi panel emphasised important concerns of ethical review practices and ethical principles within the BCI context,identified qualified and highly influential institutions and personnel in conducting and advancing clinical BCI research,and recognised prioritised aspects in the risk-benefit evaluation.Experts expressed diverse opinions on specific ethical concerns,including concerns about invasive technology,its impact on humanity and potential social consequences.Agreement was reached that the practices of ethical governance of clinical BCI for mental disorders should focus on patient voluntariness,autonomy,long-term effects and related assessments of BCI interventions,as well as privacy protection,transparent reporting and ensuring that the research is conducted in qualified institutions with strong data security.Conclusions Ethical governance of clinical research on BCI for mental disorders should include interdisciplinary experts to balance various needs and incorporate the expertise of different stakeholders to avoid serious ethical issues.It requires scientifically grounded approaches,continuous monitoring and interdisciplinary collaboration to ensure evidence-based policies,comprehensive risk assessments and transparency,thereby promoting responsible innovations and protecting patient rights and well-being.展开更多
In recent years,with the continuous advancement of technolo-gies such as artificial intelligence,neurobiology,and sensors,braincomputer interface(Bcl)technology has embraced opportunitiesfor rapid development The"...In recent years,with the continuous advancement of technolo-gies such as artificial intelligence,neurobiology,and sensors,braincomputer interface(Bcl)technology has embraced opportunitiesfor rapid development The"Guidelines for the Establishment ofNeurological Medical Service Price ltems(Trial)"recently issued bythe National Healthcare Security Administration specifically sets upseparate prospective items for new BCl technologies,which will un-doubtedly strongly facilitate the clinical application of BCl technologyas soon as possible,benefiting a broad range of patients.展开更多
The central nervous system(CNS)does not function in isolation-it engages in continuous molecular dialogue with the vascular and immune systems.Traditionally,the blood-brain barrier(BBB)was portrayed solely as an imper...The central nervous system(CNS)does not function in isolation-it engages in continuous molecular dialogue with the vascular and immune systems.Traditionally,the blood-brain barrier(BBB)was portrayed solely as an impermeable wall,safeguarding the CNS by excluding blood-derived molecules and circulating cells.However,this view has evolved.The BBB is now recognized as a dynamic interface that selectively regulates the exchange of signals,cells.展开更多
Visual fixation is an item in the visual function subscale of the Coma Recovery Scale-Revised （CRS-R）. Sometimes clinicians using the behavioral scales find it difficult to detect because of the motor impairment in ...Visual fixation is an item in the visual function subscale of the Coma Recovery Scale-Revised （CRS-R）. Sometimes clinicians using the behavioral scales find it difficult to detect because of the motor impairment in patients with disorders of consciousness （DOCs）. Brain- computer interface （BCI） can be used to improve clinical assessment because it directly detects the brain response to an external stimulus in the absence of behavioral expres- sion. In this study, we designed a BCI system to assist the visual fixation assessment of DOC patients. The results from 15 patients indicated that three showed visual fixation in both CRS-R and BCI assessments and one did not show such behavior in the CRS-R assessment but achieved significant online accuracy in the BCI assessment. The results revealed that electroencephalography-based BCI can detect the brain response for visual fixation. Therefore, the proposed BCI may provide a promising method for assisting behavioral assessment using the CRS-R.展开更多
While brain computer interfaces(BCIs)ofer the potential of allowing those sufering from loss of muscle control to once again fully engage with their environment by bypassing the afected motor system and decoding user ...While brain computer interfaces(BCIs)ofer the potential of allowing those sufering from loss of muscle control to once again fully engage with their environment by bypassing the afected motor system and decoding user intentions directly from brain activity,they are prone to errors.One possible avenue for BCI performance improvement is to detect when the BCI user perceives the BCI to have made an unintended action and thus take corrective actions.Error-related potentials(ErrPs)are neural correlates of error awareness and as such can provide an indication of when a BCI system is not performing according to the user’s intentions.Here,we investigate the brain signals of an implanted BCI user sufering from locked-in syndrome(LIS)due to late-stage ALS that prevents her from being able to speak or move but not from using her BCI at home on a daily basis to communicate,for the presence of error-related signals.We frst establish the presence of an ErrP originating from the dorsolateral pre-frontal cortex(dLPFC)in response to errors made during a discrete feedback task that mimics the click-based spelling software she uses to communicate.Then,we show that this ErrP can also be elicited by cursor movement errors in a continuous BCI cursor control task.This work represents a frst step toward detecting ErrPs during the daily home use of a communications BCI.展开更多
Abstract-Common spatial pattern （CSP） algorithm is a successful tool in feature estimate of brain-computer interface （BCI）. However, CSP is sensitive to outlier and may result in poor outcomes since it is based on...Abstract-Common spatial pattern （CSP） algorithm is a successful tool in feature estimate of brain-computer interface （BCI）. However, CSP is sensitive to outlier and may result in poor outcomes since it is based on pooling the covariance matrices of trials. In this paper, we propose a simple yet effective approach, named common spatial pattern ensemble （CSPE） classifier, to improve CSP performance. Through division of recording channels, multiple CSP filters are constructed. By projection, log-operation, and subtraction on the original signal, an ensemble classifier, majority voting, is achieved and outlier contaminations are alleviated. Experiment results demonstrate that the proposed CSPE classifier is robust to various artifacts and can achieve an average accuracy of 83.02%.展开更多
In this paper, we proposed a new concept: depth of drowsiness, which can more precisely describe the drowsiness than existing binary description. A set of effective markers for drowsiness: normalized band norm was suc...In this paper, we proposed a new concept: depth of drowsiness, which can more precisely describe the drowsiness than existing binary description. A set of effective markers for drowsiness: normalized band norm was successfully developed. These markers are invariant from voltage amplitude of brain waves, eliminating the need for calibrating the voltage output of the brain-computer interface devices. A new polling algorithm was designed and implemented for computing the depth of drowsiness. The time cost of data acquisition and processing for each estimate is about one second, which is well suited for real-time applications. Test results with a portable brain-computer interface device show that the depth of drowsiness computed by the method in this paper is generally invariant from ages of test subjects and sensor channels (P3 and C4). The comparison between experiment and computing results indicate that the new method is noticeably better than one of the recent methods in terms of accuracy for predicting the drowsiness.展开更多
A two-stage state recognition method is proposed for asynchronous SSVEP(steady-state visual evoked potential) based brain-computer interface(SBCI) system.The two-stage method is composed of the idle state(IS) detectio...A two-stage state recognition method is proposed for asynchronous SSVEP(steady-state visual evoked potential) based brain-computer interface(SBCI) system.The two-stage method is composed of the idle state(IS) detection and control state(CS) discrimination modules.Based on blind source separation and continuous wavelet transform techniques,the proposed method integrates functions of multi-electrode spatial filtering and feature extraction.In IS detection module,a method using the ensemble IS feature is proposed.In CS discrimination module,the ensemble CS feature is designed as feature vector for control intent classification.Further,performance comparisons are investigated among our IS detection module and other existing ones.Also the experimental results validate the satisfactory performance of our CS discrimination module.展开更多
The present study utilized motor imaginary-based brain-computer interface technology combined with rehabilitation training in 20 stroke patients. Results from the Berg Balance Scale and the Holden Walking Classificati...The present study utilized motor imaginary-based brain-computer interface technology combined with rehabilitation training in 20 stroke patients. Results from the Berg Balance Scale and the Holden Walking Classification were significantly greater at 4 weeks after treatment （P 〈 0.01）, which suggested that motor imaginary-based brain-computer interface technology improved balance and walking in stroke patients.展开更多
Abstract-Two probabilistic methods are extended to research multi-class motor imagery of brain-computer interface （BCI）： support vector machine （SVM） with posteriori probability （PSVM） and Bayesian linear discr...Abstract-Two probabilistic methods are extended to research multi-class motor imagery of brain-computer interface （BCI）： support vector machine （SVM） with posteriori probability （PSVM） and Bayesian linear discriminant analysis with probabilistic output （PBLDA）. A comparative evaluation of these two methods is conducted. The results shows that： 1） probabilistie information can improve the performance of BCI for subjects with high kappa coefficient, and 2） PSVM usually results in a stable kappa coefficient whereas PBLDA is more efficient in estimating the model parameters.展开更多
R. Penrose and S. Hameroff have proposed an idea that the brain can attain high efficient quantum computation by functioning of microtubular structure of neurons in the cytoskelton of biological cells, including neuro...R. Penrose and S. Hameroff have proposed an idea that the brain can attain high efficient quantum computation by functioning of microtubular structure of neurons in the cytoskelton of biological cells, including neurons of the brain. But Tegmark estimated the duration of coherence of a quantum state in a warm wet brain to be on the order of 10>–13 </supseconds, which is far smaller than the one tenth of a second associated with consciousness. Contrary to his calculation, it can be shown that the microtubule in a biological brain can perform computation satisfying the time scale required for quantum computation to achieve large quantum bits calculation compared with the conventional silicon processors even at the room temperature from the assumption that tunneling photons are superluminal particles called tachyons. According to the non-local property of tachyons, it is considered that the tachyon field created inside the brain has the capability to exert an influence around the space outside the brain and it functions as a macroscopic quantum dynamical system to meditate the long-range physical correlations with the surrounding world. From standpoint of the brain model based on superluminal tunneling photons, the authors theoretically searched for the possibility to realize the brain-computer interface that allows paralyzed patient to operate computers by their thoughts and they obtained the positive result for its realization from the experiments conducted by using the prototype of a brain-computer interface system.展开更多
The tactile P300 brain-computer interface( BCI) is related to the somatosensory perception and response of the human brain,and is different from visual or audio BCIs. Recently,several studies focused on the tactile st...The tactile P300 brain-computer interface( BCI) is related to the somatosensory perception and response of the human brain,and is different from visual or audio BCIs. Recently,several studies focused on the tactile stimuli delivered to different parts of the human body. Most of these stimuli were symmetrically bilateral.Only a fewstudies explored the influence of tactile stimuli laterality.In the current study,we extensively tested the performance of a vibrotactile BCI system using ipsilateral stimuli and bilateral stimuli.Two vibrotactile P300-based paradigms were tested. The target stimuli were located on the left and right forearms for the left forearm and right forearm( LFRF) paradigm,and on the left forearm and calf for the left forearm and left calf( LFLC)paradigm. Ten healthy subjects participated in this study. Our experiments and analysis showed that the bilateral paradigm( LFRF) elicited larger P300 amplitude and achieved significantly higher classification accuracy than the ipsilateral paradigm( LFLC). However, both paradigms achieved classification accuracies higher than 70% after the completion of several trials on average,which was usually regarded as the minimum accuracy level required for BCI system to be deemed useful.展开更多
Ammonium and nitrate concentrations were analyzed in near-bottom water and pore water collected from ten stations of the intertidal flat of the Changjiang Estuary during April, July, November and February. The magnitu...Ammonium and nitrate concentrations were analyzed in near-bottom water and pore water collected from ten stations of the intertidal flat of the Changjiang Estuary during April, July, November and February. The magnitudes of the benthic exchange fluxes were determined on the basis of concentration gradients of ammonium and nitrate at the near-bottom water and interstitial water interface in combination with calculations of a modified Fick＇ s first law. Ammonium fluxes varied from - 5.05 to 1.43 μg/（ cm^2·d） and were greatly regulated by the production of ammonium in surface sediments, while nitrate fluxes ranged from - 0. 38 to 1.36 μg/ （ cm^2·d） and were dominated by nitrate concentrations in the tidal water. It was found that ammonium was mainly released from sediments into water columns at most of stations whereas nitrate was mostly diffused from overlying waters to intertidal sediments. In total, 823.75 t/a ammonium-N was passed from intertidal sediments to water while about 521.90 t/a nitrate-N was removed from overlying waters to intertidal sediments. This suggests that intertidal sediments had the significant influence on modulating inorganic nitrogen in the tidal water.展开更多
Aiming at the topic of electroencephalogram （EEG） pattern recognition in brain computer interface （BCI）, a classification method based on probabilistic neural network （PNN） with supervised learning is presented ...Aiming at the topic of electroencephalogram （EEG） pattern recognition in brain computer interface （BCI）, a classification method based on probabilistic neural network （PNN） with supervised learning is presented in this paper. It applies the recognition rate of training samples to the learning progress of network parameters. The learning vector quantization is employed to group training samples and the Genetic algorithm （GA） is used for training the network＇ s smoothing parameters and hidden central vector for detemlining hidden neurons. Utilizing the standard dataset I （a） of BCI Competition 2003 and comparing with other classification methods, the experiment results show that the best performance of pattern recognition Js got in this way, and the classification accuracy can reach to 93.8%, which improves over 5% compared with the best result （88.7 % ） of the competition. This technology provides an effective way to EEG classification in practical system of BCI.展开更多
Brain-computer interfaces rely on electrodes to record neural activity,but most existing electrodes remain fixed once implanted,limiting their sampling range and often triggering immune responses that degrade signal q...Brain-computer interfaces rely on electrodes to record neural activity,but most existing electrodes remain fixed once implanted,limiting their sampling range and often triggering immune responses that degrade signal quality over time.As reported in a Nature paper(doi:10.1038/s41586-025-09344-w)on September 17,researchers from the Shenzhen Institutes of Advanced Technology(SIAT),Chinese Academy of Sciences,and Donghua University have now developed NeuroWorm-a soft,movable fiber electrode that can navigate through tissues while continuously recording high-quality signals.展开更多
Functional recovery in penetrating neurological injury is hampered by a lack of clinical regenerative therapies.Biomaterial therapies show promise as medical materials for neural repair through immunomodulation,struct...Functional recovery in penetrating neurological injury is hampered by a lack of clinical regenerative therapies.Biomaterial therapies show promise as medical materials for neural repair through immunomodulation,structural support,and delivery of therapeutic biomolecules.However,a lack of facile and pathology-mimetic models for therapeutic testing is a bottleneck in neural tissue engineering research.We have deployed a two-dimensional,high-density multicellular cortical brain sheet to develop a facile model of injury(macrotransection/scratch wound)in vitro.The model encompasses the major neural cell types involved in pathological responses post-injury.Critically,we observed hallmark pathological responses in injury foci including cell scarring,immune cell infiltration,precursor cell migration,and shortrange axonal sprouting.Delivering test magnetic particles to evaluate the potential of the model for biomaterial screening shows a high uptake of introduced magnetic particles by injury-activated immune cells,mimicking in vivo findings.Finally,we proved it is feasible to create reproducible traumatic injuries in the brain sheet(in multielectrode array devices in situ)characterized by focal loss of electrical spiking in injury sites,offering the potential for longer term,electrophysiology plus histology assays.To our knowledge,this is the first in vitro simulation of transecting injury in a two-dimensional multicellular cortical brain cell sheet,that allows for combined histological and electrophysiological readouts of damage/repair.The patho-mimicry and adaptability of this simplified model of brain injury could benefit the testing of biomaterial therapeutics in regenerative neurology,with the option for functional electrophysiological readouts.展开更多
Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in Ind...Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system （ANFIS） to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections （in India, vehicles are driven on the left side of a road）. Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver＇s decision （accepted/rejected）. ANFIS models are developed by using 80 % of the extracted data （total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles） and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.展开更多
文摘Invasive as well as non-invasive neurotechnologies conceptualized to interface the central and peripheral nervous system have been probed for the past decades,which refer to electroencephalography,electrocorticography and microelectrode arrays.The challenges of these mentioned approaches are characterized by the bandwidth of the spatiotemporal resolution,which in turn is essential for large-area neuron recordings(Abiri et al.,2019).
基金supported by the National Key R&D Program of China(2021YFF1200602)the National Science Fund for Excellent Overseas Scholars(0401260011)+3 种基金the National Defense Science and Technology Innovation Fund of Chinese Academy of Sciences(c02022088)the Tianjin Science and Technology Program(20JCZDJC00810)the National Natural Science Foundation of China(82202798)the Shanghai Sailing Program(22YF1404200).
文摘Brain-computer interfaces(BCIs)represent an emerging technology that facilitates direct communication between the brain and external devices.In recent years,numerous review articles have explored various aspects of BCIs,including their fundamental principles,technical advancements,and applications in specific domains.However,these reviews often focus on signal processing,hardware development,or limited applications such as motor rehabilitation or communication.This paper aims to offer a comprehensive review of recent electroencephalogram(EEG)-based BCI applications in the medical field across 8 critical areas,encompassing rehabilitation,daily communication,epilepsy,cerebral resuscitation,sleep,neurodegenerative diseases,anesthesiology,and emotion recognition.Moreover,the current challenges and future trends of BCIs were also discussed,including personal privacy and ethical concerns,network security vulnerabilities,safety issues,and biocompatibility.
基金funded by the Shanghai Philosophy and Social Science Planning Project (2021BZX008)the National Social Science Foundation of China (23BZX110)the National Office for Philosophy and Social Science (20&ZD045).
文摘Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for stakeholders and the entire community.Aims This study aims to establish a multidisciplinary consensus of principles for ethical governance of clinical BCI research for mental disorders and offer practical ethical guidance to stakeholders involved.Methods A systematic literature review,symposium and roundtable discussions,and a pre-Delphi(round 0)survey were conducted to form the questionnaire for the three-round modified Delphi study.Two rounds of surveys,followed by a third round of independent interviews of 25 experts from BCI-related research domains,were involved.We conducted quantitative analysis of responses and agreements among experts to reveal the consensus and differences regarding the ethical governance of mental BCI research from a multidisciplinary perspective.Results The Delphi panel emphasised important concerns of ethical review practices and ethical principles within the BCI context,identified qualified and highly influential institutions and personnel in conducting and advancing clinical BCI research,and recognised prioritised aspects in the risk-benefit evaluation.Experts expressed diverse opinions on specific ethical concerns,including concerns about invasive technology,its impact on humanity and potential social consequences.Agreement was reached that the practices of ethical governance of clinical BCI for mental disorders should focus on patient voluntariness,autonomy,long-term effects and related assessments of BCI interventions,as well as privacy protection,transparent reporting and ensuring that the research is conducted in qualified institutions with strong data security.Conclusions Ethical governance of clinical research on BCI for mental disorders should include interdisciplinary experts to balance various needs and incorporate the expertise of different stakeholders to avoid serious ethical issues.It requires scientifically grounded approaches,continuous monitoring and interdisciplinary collaboration to ensure evidence-based policies,comprehensive risk assessments and transparency,thereby promoting responsible innovations and protecting patient rights and well-being.
文摘In recent years,with the continuous advancement of technolo-gies such as artificial intelligence,neurobiology,and sensors,braincomputer interface(Bcl)technology has embraced opportunitiesfor rapid development The"Guidelines for the Establishment ofNeurological Medical Service Price ltems(Trial)"recently issued bythe National Healthcare Security Administration specifically sets upseparate prospective items for new BCl technologies,which will un-doubtedly strongly facilitate the clinical application of BCl technologyas soon as possible,benefiting a broad range of patients.
基金supported by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Award Number K02NS110973 and R01NS126498(to MAP).
文摘The central nervous system(CNS)does not function in isolation-it engages in continuous molecular dialogue with the vascular and immune systems.Traditionally,the blood-brain barrier(BBB)was portrayed solely as an impermeable wall,safeguarding the CNS by excluding blood-derived molecules and circulating cells.However,this view has evolved.The BBB is now recognized as a dynamic interface that selectively regulates the exchange of signals,cells.
基金supported by the National Key Research and Development Program of China (2017YFB1002505)the National Natural Science Foundation of China (61633010, 91420302, and 61503143)+1 种基金the Natural Science Foundation of Guangdong Province, China (2014A030312005 and 2014A030310244)the Pearl River S&T Nova Program of Guangzhou Municipality, China (201710010038)
文摘Visual fixation is an item in the visual function subscale of the Coma Recovery Scale-Revised （CRS-R）. Sometimes clinicians using the behavioral scales find it difficult to detect because of the motor impairment in patients with disorders of consciousness （DOCs）. Brain- computer interface （BCI） can be used to improve clinical assessment because it directly detects the brain response to an external stimulus in the absence of behavioral expres- sion. In this study, we designed a BCI system to assist the visual fixation assessment of DOC patients. The results from 15 patients indicated that three showed visual fixation in both CRS-R and BCI assessments and one did not show such behavior in the CRS-R assessment but achieved significant online accuracy in the BCI assessment. The results revealed that electroencephalography-based BCI can detect the brain response for visual fixation. Therefore, the proposed BCI may provide a promising method for assisting behavioral assessment using the CRS-R.
文摘While brain computer interfaces(BCIs)ofer the potential of allowing those sufering from loss of muscle control to once again fully engage with their environment by bypassing the afected motor system and decoding user intentions directly from brain activity,they are prone to errors.One possible avenue for BCI performance improvement is to detect when the BCI user perceives the BCI to have made an unintended action and thus take corrective actions.Error-related potentials(ErrPs)are neural correlates of error awareness and as such can provide an indication of when a BCI system is not performing according to the user’s intentions.Here,we investigate the brain signals of an implanted BCI user sufering from locked-in syndrome(LIS)due to late-stage ALS that prevents her from being able to speak or move but not from using her BCI at home on a daily basis to communicate,for the presence of error-related signals.We frst establish the presence of an ErrP originating from the dorsolateral pre-frontal cortex(dLPFC)in response to errors made during a discrete feedback task that mimics the click-based spelling software she uses to communicate.Then,we show that this ErrP can also be elicited by cursor movement errors in a continuous BCI cursor control task.This work represents a frst step toward detecting ErrPs during the daily home use of a communications BCI.
基金supported by the National Natural Science Foundation of China under Grant No. 30525030, 60701015, and 60736029.
文摘Abstract-Common spatial pattern （CSP） algorithm is a successful tool in feature estimate of brain-computer interface （BCI）. However, CSP is sensitive to outlier and may result in poor outcomes since it is based on pooling the covariance matrices of trials. In this paper, we propose a simple yet effective approach, named common spatial pattern ensemble （CSPE） classifier, to improve CSP performance. Through division of recording channels, multiple CSP filters are constructed. By projection, log-operation, and subtraction on the original signal, an ensemble classifier, majority voting, is achieved and outlier contaminations are alleviated. Experiment results demonstrate that the proposed CSPE classifier is robust to various artifacts and can achieve an average accuracy of 83.02%.
文摘In this paper, we proposed a new concept: depth of drowsiness, which can more precisely describe the drowsiness than existing binary description. A set of effective markers for drowsiness: normalized band norm was successfully developed. These markers are invariant from voltage amplitude of brain waves, eliminating the need for calibrating the voltage output of the brain-computer interface devices. A new polling algorithm was designed and implemented for computing the depth of drowsiness. The time cost of data acquisition and processing for each estimate is about one second, which is well suited for real-time applications. Test results with a portable brain-computer interface device show that the depth of drowsiness computed by the method in this paper is generally invariant from ages of test subjects and sensor channels (P3 and C4). The comparison between experiment and computing results indicate that the new method is noticeably better than one of the recent methods in terms of accuracy for predicting the drowsiness.
基金National Natural Science Foundation of China(90820305,60775040)
文摘A two-stage state recognition method is proposed for asynchronous SSVEP(steady-state visual evoked potential) based brain-computer interface(SBCI) system.The two-stage method is composed of the idle state(IS) detection and control state(CS) discrimination modules.Based on blind source separation and continuous wavelet transform techniques,the proposed method integrates functions of multi-electrode spatial filtering and feature extraction.In IS detection module,a method using the ensemble IS feature is proposed.In CS discrimination module,the ensemble CS feature is designed as feature vector for control intent classification.Further,performance comparisons are investigated among our IS detection module and other existing ones.Also the experimental results validate the satisfactory performance of our CS discrimination module.
基金the National Natural Science Foundation of China,No.60970062the Shanghai Pujiang Program,No.09PJ1410200
文摘The present study utilized motor imaginary-based brain-computer interface technology combined with rehabilitation training in 20 stroke patients. Results from the Berg Balance Scale and the Holden Walking Classification were significantly greater at 4 weeks after treatment （P 〈 0.01）, which suggested that motor imaginary-based brain-computer interface technology improved balance and walking in stroke patients.
基金supported by the National Natural Science Foundation of China under Grant No. 30525030, 60701015, and 60736029.
文摘Abstract-Two probabilistic methods are extended to research multi-class motor imagery of brain-computer interface （BCI）： support vector machine （SVM） with posteriori probability （PSVM） and Bayesian linear discriminant analysis with probabilistic output （PBLDA）. A comparative evaluation of these two methods is conducted. The results shows that： 1） probabilistie information can improve the performance of BCI for subjects with high kappa coefficient, and 2） PSVM usually results in a stable kappa coefficient whereas PBLDA is more efficient in estimating the model parameters.
文摘R. Penrose and S. Hameroff have proposed an idea that the brain can attain high efficient quantum computation by functioning of microtubular structure of neurons in the cytoskelton of biological cells, including neurons of the brain. But Tegmark estimated the duration of coherence of a quantum state in a warm wet brain to be on the order of 10>–13 </supseconds, which is far smaller than the one tenth of a second associated with consciousness. Contrary to his calculation, it can be shown that the microtubule in a biological brain can perform computation satisfying the time scale required for quantum computation to achieve large quantum bits calculation compared with the conventional silicon processors even at the room temperature from the assumption that tunneling photons are superluminal particles called tachyons. According to the non-local property of tachyons, it is considered that the tachyon field created inside the brain has the capability to exert an influence around the space outside the brain and it functions as a macroscopic quantum dynamical system to meditate the long-range physical correlations with the surrounding world. From standpoint of the brain model based on superluminal tunneling photons, the authors theoretically searched for the possibility to realize the brain-computer interface that allows paralyzed patient to operate computers by their thoughts and they obtained the positive result for its realization from the experiments conducted by using the prototype of a brain-computer interface system.
基金National Key Research and Development Program,China(No.2017YFB13003002)National Natural Science Foundation of China(Nos.61573142,61773164,91420302)Programme of Introducing Talents of Discipline to Universities(the 111 Project)(No.B17017)
文摘The tactile P300 brain-computer interface( BCI) is related to the somatosensory perception and response of the human brain,and is different from visual or audio BCIs. Recently,several studies focused on the tactile stimuli delivered to different parts of the human body. Most of these stimuli were symmetrically bilateral.Only a fewstudies explored the influence of tactile stimuli laterality.In the current study,we extensively tested the performance of a vibrotactile BCI system using ipsilateral stimuli and bilateral stimuli.Two vibrotactile P300-based paradigms were tested. The target stimuli were located on the left and right forearms for the left forearm and right forearm( LFRF) paradigm,and on the left forearm and calf for the left forearm and left calf( LFLC)paradigm. Ten healthy subjects participated in this study. Our experiments and analysis showed that the bilateral paradigm( LFRF) elicited larger P300 amplitude and achieved significantly higher classification accuracy than the ipsilateral paradigm( LFLC). However, both paradigms achieved classification accuracies higher than 70% after the completion of several trials on average,which was usually regarded as the minimum accuracy level required for BCI system to be deemed useful.
基金This research is part of the project of the biogeochemical cycling of multi-materials in the Changjiang estuarine and coastal complex ecosystem supported by the National Natural Science Key Foundation of China under contract Nos 40131020 and 49801018 the Tidal Flat Project by Science and Technology Committee of Shanghai under contract No. 04DZ12049+1 种基金 China Postdoctoral Science Foundation under contract No. 2005037135 Shanghai Postdoctoral Science Foundation under contract No.04R214122.
文摘Ammonium and nitrate concentrations were analyzed in near-bottom water and pore water collected from ten stations of the intertidal flat of the Changjiang Estuary during April, July, November and February. The magnitudes of the benthic exchange fluxes were determined on the basis of concentration gradients of ammonium and nitrate at the near-bottom water and interstitial water interface in combination with calculations of a modified Fick＇ s first law. Ammonium fluxes varied from - 5.05 to 1.43 μg/（ cm^2·d） and were greatly regulated by the production of ammonium in surface sediments, while nitrate fluxes ranged from - 0. 38 to 1.36 μg/ （ cm^2·d） and were dominated by nitrate concentrations in the tidal water. It was found that ammonium was mainly released from sediments into water columns at most of stations whereas nitrate was mostly diffused from overlying waters to intertidal sediments. In total, 823.75 t/a ammonium-N was passed from intertidal sediments to water while about 521.90 t/a nitrate-N was removed from overlying waters to intertidal sediments. This suggests that intertidal sediments had the significant influence on modulating inorganic nitrogen in the tidal water.
基金Supported by the National Natural Science Foundation of China (No. 30570485)the Shanghai "Chen Guang" Project (No. 09CG69).
文摘Aiming at the topic of electroencephalogram （EEG） pattern recognition in brain computer interface （BCI）, a classification method based on probabilistic neural network （PNN） with supervised learning is presented in this paper. It applies the recognition rate of training samples to the learning progress of network parameters. The learning vector quantization is employed to group training samples and the Genetic algorithm （GA） is used for training the network＇ s smoothing parameters and hidden central vector for detemlining hidden neurons. Utilizing the standard dataset I （a） of BCI Competition 2003 and comparing with other classification methods, the experiment results show that the best performance of pattern recognition Js got in this way, and the classification accuracy can reach to 93.8%, which improves over 5% compared with the best result （88.7 % ） of the competition. This technology provides an effective way to EEG classification in practical system of BCI.
文摘Brain-computer interfaces rely on electrodes to record neural activity,but most existing electrodes remain fixed once implanted,limiting their sampling range and often triggering immune responses that degrade signal quality over time.As reported in a Nature paper(doi:10.1038/s41586-025-09344-w)on September 17,researchers from the Shenzhen Institutes of Advanced Technology(SIAT),Chinese Academy of Sciences,and Donghua University have now developed NeuroWorm-a soft,movable fiber electrode that can navigate through tissues while continuously recording high-quality signals.
基金supported by awards from the EPSRC Centre for Doctoral Training in Regenerative Medicine(EP/L014904/1,to JW)an NHS bursary(to RHB)an EPSRC Healthcare Technologies award(EP/T013885/1,to DMC)。
文摘Functional recovery in penetrating neurological injury is hampered by a lack of clinical regenerative therapies.Biomaterial therapies show promise as medical materials for neural repair through immunomodulation,structural support,and delivery of therapeutic biomolecules.However,a lack of facile and pathology-mimetic models for therapeutic testing is a bottleneck in neural tissue engineering research.We have deployed a two-dimensional,high-density multicellular cortical brain sheet to develop a facile model of injury(macrotransection/scratch wound)in vitro.The model encompasses the major neural cell types involved in pathological responses post-injury.Critically,we observed hallmark pathological responses in injury foci including cell scarring,immune cell infiltration,precursor cell migration,and shortrange axonal sprouting.Delivering test magnetic particles to evaluate the potential of the model for biomaterial screening shows a high uptake of introduced magnetic particles by injury-activated immune cells,mimicking in vivo findings.Finally,we proved it is feasible to create reproducible traumatic injuries in the brain sheet(in multielectrode array devices in situ)characterized by focal loss of electrical spiking in injury sites,offering the potential for longer term,electrophysiology plus histology assays.To our knowledge,this is the first in vitro simulation of transecting injury in a two-dimensional multicellular cortical brain cell sheet,that allows for combined histological and electrophysiological readouts of damage/repair.The patho-mimicry and adaptability of this simplified model of brain injury could benefit the testing of biomaterial therapeutics in regenerative neurology,with the option for functional electrophysiological readouts.
基金partially funded by Department of Science and Technology (DST), Govt. of Indiaproject SR/ FTP/ETA-61/2010
文摘Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system （ANFIS） to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections （in India, vehicles are driven on the left side of a road）. Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver＇s decision （accepted/rejected）. ANFIS models are developed by using 80 % of the extracted data （total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles） and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.
