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Reichert C, Dürschmid S, Hinrichs H. EEG als Steuersignal: Gehirnaktivität entschlüsseln
und effizient als Kommunikationsmittel für Patienten mit motorischen
Defiziten nutzen. KLIN NEUROPHYSIOL 2020. [DOI: 10.1055/a-1135-3782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Zusammenfassung
Ziel der Studie Ereignis-korrelierte Potenziale werden in der Regel in
einzelnen EEG-Kanälen ermittelt. Mit einem einzelnen Kanal wird jedoch
nur ein Teil des gesamten Hirnprozesses erfasst. Für eine
Gehirn-Computer Schnittstelle, die in kurzer Zeit eine Entscheidung treffen
muss, ist diese singuläre Gehirnantwort häufig unzureichend
wogegen die Information aus mehreren Kanälen häufig redundant
ist. Beide Vorgehensweisen sind nicht optimal. Daher ist es unser Ziel, die
Kanäle zu wenigen Komponenten zu kombinieren, die die relevantesten
Modulationen eines Hirnprozesses erfassen.
Methodik Wir nutzen die kanonische Korrelationsanalyse, um datengetrieben
räumliche Filter aus dem EEG zu bestimmen. Mit der Produkt-Moment
Korrelation ermitteln wir, auf welche von 12 verschiedenen Stimulussequenzen die
Studienteilnehmer geachtet haben.
Ergebnisse Die verdeckte Aufmerksamkeit der Studienteilnehmer konnte mit
hoher Genauigkeit (89,3±9,2%) aus dem räumlich
gefilterten EEG und signifikant besser als aus einzelnen Kanälen
dekodiert werden.
Schlussfolgerung Die aus dem EEG erlernten räumlichen Filter
ermöglichen die Extraktion von Komponenten, die einen event-korrelierten
Gehirnprozess charakterisieren und eine Gehirn-Computer Schnittstelle effektiv
steuern können, was von hoher Relevanz für Patienten ist, die
nicht mehr anderweitig kommunizieren können.
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Affiliation(s)
- Christoph Reichert
- Abteilung Verhaltensneurologie, Leibniz-Institut für
Neurobiologie, Magdeburg
- Center for Behavioral Brain Sciences (CBBS), Magdeburg
- Forschungscampus STIMULATE, Magdeburg
| | - Stefan Dürschmid
- Abteilung Verhaltensneurologie, Leibniz-Institut für
Neurobiologie, Magdeburg
- Klinik für Neurologie, Universitätsklinikum
Magdeburg
| | - Hermann Hinrichs
- Abteilung Verhaltensneurologie, Leibniz-Institut für
Neurobiologie, Magdeburg
- Center for Behavioral Brain Sciences (CBBS), Magdeburg
- Forschungscampus STIMULATE, Magdeburg
- Klinik für Neurologie, Universitätsklinikum
Magdeburg
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Aseem A, Hussain ME. Sleep quality and its effect on event related potential P300 in adolescents with and without sleep disturbances. Int J Adolesc Med Health 2019; 34:ijamh-2019-0097. [PMID: 31874097 DOI: 10.1515/ijamh-2019-0097] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 07/02/2019] [Indexed: 06/10/2023]
Abstract
OBJECTIVES The present study aimed: (i) to investigate the sleep quality and cortical arousal (ERP P300) in adolescents with and without sleep disturbances, and (ii) to examine whether P300 vary as a function of quality of the previous night's sleep in sleep disturbed adolescents and to compare the findings with healthy controls. METHODS Fifteen sleep disturbed adolescents and 15 age-matched controls were recruited. Participants filled 10 days of sleep logs to identify their good (GN) and bad nights (BN). GN and BN were scored as a measure of sleep efficiency (SE), with nights having greater SE defined as GN and nights with lower SE scores labelled as BN. Afterwards, subjects were summoned to the lab for recording ERP P300 once after a night of good sleep (GN) and once after a night of bad sleep (BN). RESULTS The findings demonstrate that sleep disturbed adolescents exhibited poorer quality of sleep than controls. The ERP P300 also revealed significant difference in participants with and without sleep disturbance. Moreover, the P300 amplitude was higher and the latency was shorter after a GN in sleep disturbed as well as in controls, however, the values were better for adolescents without disturbed sleep. Similarly, amplitude and latency of P300 was lower and longer, respectively, after a BN in both the groups, however, participants with sleep disturbance demonstrated very penurious scores for amplitude and latency than the controls. CONCLUSION Adolescents with sleep disturbance have poorer sleep quality and ERP characteristics than their healthy counterparts. Moreover, the quality of the previous night sleep determines cortical arousal in both sleep disturbed and healthy controls.
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Affiliation(s)
- Anam Aseem
- Sleep Research Group, Neurophysiology Lab, Centre for Physiotherapy and Rehabilitation Sciences, Jamia Millia Islamia (A Central University), New Delhi 110025, India, Phone: +91-8826837035
| | - Mohammed Ejaz Hussain
- Sleep Research Group, Neurophysiology Lab, Centre for Physiotherapy and Rehabilitation Sciences, Jamia Millia Islamia (A Central University), New Delhi 110025, India
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Ma Z, Qiu T. Quasi-periodic fluctuation in Donchin's speller signals and its potential use for asynchronous control. ACTA ACUST UNITED AC 2018; 63:105-112. [PMID: 27655447 DOI: 10.1515/bmt-2016-0050] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2016] [Accepted: 08/19/2016] [Indexed: 11/15/2022]
Abstract
When we examine the event-related potential (ERP) responses of Donchin's brain-computer interface (BCI) speller, a type of quasi-periodic fluctuation (FLUC) overlapping with the ERP components can be observed; this fluctuation is traditionally treated as interference. However, if the FLUC is detectable in a working BCI, it can be used for asynchronous control, i.e. to indicate whether the BCI is under the control state (CS) or under the non-control idle state (NC). Asynchronous control is an important issue to address to enable BCI's practical use. In this paper, we examine the characteristics of the FLUC and explore the possibility of using the FLUC for asynchronous control of the BCI. For detecting the FLUC, we propose a method based on the power spectrum and evaluate the detection rates in a simulation. As a result, high true positive rates (TPRs) and low false positive rates (FPRs) are obtained. Our work reveals that the FLUC is of great value for implementing an asynchronous BCI.
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Affiliation(s)
- Zheng Ma
- Department of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China
| | - Tianshuang Qiu
- Department of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China
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Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2018; 2018:6058065. [PMID: 29861712 PMCID: PMC5976923 DOI: 10.1155/2018/6058065] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Revised: 03/05/2018] [Accepted: 04/01/2018] [Indexed: 11/25/2022]
Abstract
Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain–computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects' ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.
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Carabalona R. The Role of the Interplay between Stimulus Type and Timing in Explaining BCI-Illiteracy for Visual P300-Based Brain-Computer Interfaces. Front Neurosci 2017; 11:363. [PMID: 28713233 PMCID: PMC5492449 DOI: 10.3389/fnins.2017.00363] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2016] [Accepted: 06/12/2017] [Indexed: 11/13/2022] Open
Abstract
Visual P300-based Brain-Computer Interface (BCI) spellers enable communication or interaction with the environment by flashing elements in a matrix and exploiting consequent changes in end-user's brain activity. Despite research efforts, performance variability and BCI-illiteracy still are critical issues for real world applications. Moreover, there is a quite unaddressed kind of BCI-illiteracy, which becomes apparent when the same end-user operates BCI-spellers intended for different applications: our aim is to understand why some well performers can become BCI-illiterate depending on speller type. We manipulated stimulus type (factor STIM: either characters or icons), color (factor COLOR: white, green) and timing (factor SPEED: fast, slow). Each BCI session consisted of training (without feedback) and performance phase (with feedback), both in copy-spelling. For fast flashing spellers, we observed a performance worsening for white icon-speller. Our findings are consistent with existing results reported on end-users using identical white×fast spellers, indicating independence of worsening trend from users' group. The use of slow stimulation timing shed a new light on the perceptual and cognitive phenomena related to the use of a BCI-speller during both the training and the performance phase. We found a significant STIM main effect for the N1 component on P z and PO7 during the training phase and on PO8 during the performance phase, whereas in both phases neither the STIM×COLOR interaction nor the COLOR main effect was statistically significant. After collapsing data for factor COLOR, it emerged a statistically significant modulation of N1 amplitude depending to the phase of BCI session: N1 was more negative for icons than for characters both on P z and PO7 (training), whereas the opposite modulation was observed for PO8 (performance). Results indicate that both feedback and expertise with respect to the stimulus type can modulate the N1 component and that icons require more perceptual analysis. Therefore, fast flashing is likely to be more detrimental for end-users' performance in case of icon-spellers. In conclusion, the interplay between stimulus type and timing seems relevant for a satisfactory and efficient end-user's BCI-experience.
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Affiliation(s)
- Roberta Carabalona
- Biomedical Technological Department, Fondazione Don Carlo Gnocchi Onlus (IRCCS)Milan, Italy
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Lebedev MA, Nicolelis MAL. Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation. Physiol Rev 2017; 97:767-837. [PMID: 28275048 DOI: 10.1152/physrev.00027.2016] [Citation(s) in RCA: 235] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity. The classic goals of BMIs are 1) to unveil and utilize principles of operation and plastic properties of the distributed and dynamic circuits of the brain and 2) to create new therapies to restore mobility and sensations to severely disabled patients. Over the past decade, a wide range of BMI applications have emerged, which considerably expanded these original goals. BMI studies have shown neural control over the movements of robotic and virtual actuators that enact both upper and lower limb functions. Furthermore, BMIs have also incorporated ways to deliver sensory feedback, generated from external actuators, back to the brain. BMI research has been at the forefront of many neurophysiological discoveries, including the demonstration that, through continuous use, artificial tools can be assimilated by the primate brain's body schema. Work on BMIs has also led to the introduction of novel neurorehabilitation strategies. As a result of these efforts, long-term continuous BMI use has been recently implicated with the induction of partial neurological recovery in spinal cord injury patients.
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Basyul I. Oculomotor activity parameters of the operator in the P300 brain–computer interface with variating stimulus situations. EXPERIMENTAL PSYCHOLOGY (RUSSIA) 2017. [DOI: 10.17759/exppsy.2017100109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We tested the hypotheses about the correlation of visual environment properties in the BCI P300 with oculomotor activity and operator efficiency. We varied level of stimulus intensification and the frame surrounding the stimulus elements. So we had four situation: 1) low contrast, without frame; 2) low contrast, with frame; 3) high contrast, without frame; 4) high contrast, with frame. 12 subjects participated. Our study showed that visual environment which provides lowest level of operator’s errors and so the highest efficiency of the BCI P300 workflow combined with lowest fixation dispersion and highest fixation duration. However, various subjects demonstrated the highest level of the efficiency at the different visual environments. We did not define the best type of the visual environment for the most efficient BCI P300 workflow. This results demonstrate the opportunity to use the eyetracking for optimization visual environment of the BCI P300 for most efficient and comfort operator’s workflow. The study was funded by RFH, grant 15-36-01386 “Consistent pattern of organization oculomotor activity in an environ- ment of brain-computer interface”.
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Ordikhani-Seyedlar M, Lebedev MA, Sorensen HBD, Puthusserypady S. Neurofeedback Therapy for Enhancing Visual Attention: State-of-the-Art and Challenges. Front Neurosci 2016; 10:352. [PMID: 27536212 PMCID: PMC4971093 DOI: 10.3389/fnins.2016.00352] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 07/12/2016] [Indexed: 11/17/2022] Open
Abstract
We have witnessed a rapid development of brain-computer interfaces (BCIs) linking the brain to external devices. BCIs can be utilized to treat neurological conditions and even to augment brain functions. BCIs offer a promising treatment for mental disorders, including disorders of attention. Here we review the current state of the art and challenges of attention-based BCIs, with a focus on visual attention. Attention-based BCIs utilize electroencephalograms (EEGs) or other recording techniques to generate neurofeedback, which patients use to improve their attention, a complex cognitive function. Although progress has been made in the studies of neural mechanisms of attention, extraction of attention-related neural signals needed for BCI operations is a difficult problem. To attain good BCI performance, it is important to select the features of neural activity that represent attentional signals. BCI decoding of attention-related activity may be hindered by the presence of different neural signals. Therefore, BCI accuracy can be improved by signal processing algorithms that dissociate signals of interest from irrelevant activities. Notwithstanding recent progress, optimal processing of attentional neural signals remains a fundamental challenge for the development of efficient therapies for disorders of attention.
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Affiliation(s)
- Mehdi Ordikhani-Seyedlar
- Division of Biomedical Engineering, Department of Electrical Engineering, Technical University of Denmark Lyngby, Denmark
| | - Mikhail A Lebedev
- Department of Neurobiology, Duke UniversityDurham, NC, USA; Center for Neuroengineering, Duke UniversityDurham, NC, USA
| | - Helge B D Sorensen
- Division of Biomedical Engineering, Department of Electrical Engineering, Technical University of Denmark Lyngby, Denmark
| | - Sadasivan Puthusserypady
- Division of Biomedical Engineering, Department of Electrical Engineering, Technical University of Denmark Lyngby, Denmark
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Chen L, Jin J, Daly I, Zhang Y, Wang X, Cichocki A. Exploring Combinations of Different Color and Facial Expression Stimuli for Gaze-Independent BCIs. Front Comput Neurosci 2016; 10:5. [PMID: 26858634 PMCID: PMC4731496 DOI: 10.3389/fncom.2016.00005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Accepted: 01/11/2016] [Indexed: 11/25/2022] Open
Abstract
Background: Some studies have proven that a conventional visual brain computer interface (BCI) based on overt attention cannot be used effectively when eye movement control is not possible. To solve this problem, a novel visual-based BCI system based on covert attention and feature attention has been proposed and was called the gaze-independent BCI. Color and shape difference between stimuli and backgrounds have generally been used in examples of gaze-independent BCIs. Recently, a new paradigm based on facial expression changes has been presented, and obtained high performance. However, some facial expressions were so similar that users couldn't tell them apart, especially when they were presented at the same position in a rapid serial visual presentation (RSVP) paradigm. Consequently, the performance of the BCI is reduced. New Method: In this paper, we combined facial expressions and colors to optimize the stimuli presentation in the gaze-independent BCI. This optimized paradigm was called the colored dummy face pattern. It is suggested that different colors and facial expressions could help users to locate the target and evoke larger event-related potentials (ERPs). In order to evaluate the performance of this new paradigm, two other paradigms were presented, called the gray dummy face pattern and the colored ball pattern. Comparison with Existing Method(s): The key point that determined the value of the colored dummy faces stimuli in BCI systems was whether the dummy face stimuli could obtain higher performance than gray faces or colored balls stimuli. Ten healthy participants (seven male, aged 21–26 years, mean 24.5 ± 1.25) participated in our experiment. Online and offline results of four different paradigms were obtained and comparatively analyzed. Results: The results showed that the colored dummy face pattern could evoke higher P300 and N400 ERP amplitudes, compared with the gray dummy face pattern and the colored ball pattern. Online results showed that the colored dummy face pattern had a significant advantage in terms of classification accuracy (p < 0.05) and information transfer rate (p < 0.05) compared to the other two patterns. Conclusions: The stimuli used in the colored dummy face paradigm combined color and facial expressions. This had a significant advantage in terms of the evoked P300 and N400 amplitudes and resulted in high classification accuracies and information transfer rates. It was compared with colored ball and gray dummy face stimuli.
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Affiliation(s)
- Long Chen
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology Shanghai, China
| | - Jing Jin
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology Shanghai, China
| | - Ian Daly
- Brain Embodiment Lab, School of Systems Engineering, University of Reading Reading, UK
| | - Yu Zhang
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology Shanghai, China
| | - Xingyu Wang
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology Shanghai, China
| | - Andrzej Cichocki
- Riken Brain Science InstituteWako-shi, Japan; Systems Research Institute of Polish Academy of SciencesWarsaw, Poland; Skolkovo Institute of Science and TechnologyMoscow, Russia
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Ceballos GA, Hernández LF. Non-target adjacent stimuli classification improves performance of classical ERP-based brain computer interface. J Neural Eng 2015; 12:026009. [PMID: 25710243 DOI: 10.1088/1741-2560/12/2/026009] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The classical ERP-based speller, or P300 Speller, is one of the most commonly used paradigms in the field of Brain Computer Interfaces (BCI). Several alterations to the visual stimuli presentation system have been developed to avoid unfavorable effects elicited by adjacent stimuli. However, there has been little, if any, regard to useful information contained in responses to adjacent stimuli about spatial location of target symbols. This paper aims to demonstrate that combining the classification of non-target adjacent stimuli with standard classification (target versus non-target) significantly improves classical ERP-based speller efficiency. APPROACH Four SWLDA classifiers were trained and combined with the standard classifier: the lower row, upper row, right column and left column classifiers. This new feature extraction procedure and the classification method were carried out on three open databases: the UAM P300 database (Universidad Autonoma Metropolitana, Mexico), BCI competition II (dataset IIb) and BCI competition III (dataset II). MAIN RESULTS The inclusion of the classification of non-target adjacent stimuli improves target classification in the classical row/column paradigm. A gain in mean single trial classification of 9.6% and an overall improvement of 25% in simulated spelling speed was achieved. SIGNIFICANCE We have provided further evidence that the ERPs produced by adjacent stimuli present discriminable features, which could provide additional information about the spatial location of intended symbols. This work promotes the searching of information on the peripheral stimulation responses to improve the performance of emerging visual ERP-based spellers.
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Affiliation(s)
- G A Ceballos
- Center of Biomedical Engineering and Telemedicine, Faculty of Engineering, University of Los Andes, Merida, Venezuela
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Treder MS, Purwins H, Miklody D, Sturm I, Blankertz B. Decoding auditory attention to instruments in polyphonic music using single-trial EEG classification. J Neural Eng 2014; 11:026009. [PMID: 24608228 DOI: 10.1088/1741-2560/11/2/026009] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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Kamp SM, Murphy AR, Donchin E. The component structure of event-related potentials in the p300 speller paradigm. IEEE Trans Neural Syst Rehabil Eng 2013; 21:897-907. [PMID: 24235153 DOI: 10.1109/tnsre.2013.2285398] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
We investigated the componential structure of event-related potentials elicited while participants use the P300 BCI. Six healthy participants "typed" all characters in a 6 × 6 matrix twice in a random sequence. A principal component analysis indicated that in addition to the P300, target flashes elicited an earlier frontal positivity, possibly a Novelty P3. The amplitudes of both P300 and the Novelty P3 varied with the matrix row in which the target character was located. However, the P300 elicited by row flashes was largest for targets in the lower part of the matrix, whereas the Novelty P3 elicited by column flashes was largest in the top part. Classification accuracy using stepwise linear discriminant analysis mirrored the pattern in the Novelty P3 (an accuracy difference of 0.1 between rows 1 and 6). When separate classifiers were generated to rely solely on the P300 or solely on the Novelty P3, the latter function led to higher accuracy (a mean accuracy difference of about 0.2 between classifiers). A possible explanation is that some nontarget flashes elicit a P300, leading to lower selection accuracy of the respective classifier. In an additional set of data from six different participants we replicated the ERP structure of the initial analyses and characterized the spatial distributions more closely by using a dense electrode array. Overall, our findings provide new insights in the componential structure of ERPs elicited in the P300 speller paradigm and have important implications for optimizing the speller's selection accuracy.
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Ganin IP, Shishkin SL, Kaplan AY. A P300-based brain-computer interface with stimuli on moving objects: four-session single-trial and triple-trial tests with a game-like task design. PLoS One 2013; 8:e77755. [PMID: 24302977 PMCID: PMC3840230 DOI: 10.1371/journal.pone.0077755] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2013] [Accepted: 09/08/2013] [Indexed: 11/24/2022] Open
Abstract
Brain-computer interfaces (BCIs) are tools for controlling computers and other devices without using muscular activity, employing user-controlled variations in signals recorded from the user's brain. One of the most efficient noninvasive BCIs is based on the P300 wave of the brain's response to stimuli and is therefore referred to as the P300 BCI. Many modifications of this BCI have been proposed to further improve the BCI's characteristics or to better adapt the BCI to various applications. However, in the original P300 BCI and in all of its modifications, the spatial positions of stimuli were fixed relative to each other, which can impose constraints on designing applications controlled by this BCI. We designed and tested a P300 BCI with stimuli presented on objects that were freely moving on a screen at a speed of 5.4°/s. Healthy participants practiced a game-like task with this BCI in either single-trial or triple-trial mode within four sessions. At each step, the participants were required to select one of nine moving objects. The mean online accuracy of BCI-based selection was 81% in the triple-trial mode and 65% in the single-trial mode. A relatively high P300 amplitude was observed in response to targets in most participants. Self-rated interest in the task was high and stable over the four sessions (the medians in the 1st/4th sessions were 79/84% and 76/71% in the groups practicing in the single-trial and triple-trial modes, respectively). We conclude that the movement of stimulus positions relative to each other may not prevent the efficient use of the P300 BCI by people controlling their gaze, e.g., in robotic devices and in video games.
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Affiliation(s)
- Ilya P. Ganin
- Laboratory for Neurophysiology and Neuro-Computer Interfaces, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Sergei L. Shishkin
- Laboratory for Neurophysiology and Neuro-Computer Interfaces, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
- Laboratory for Neuroergonomics and Brain-Computer Interfaces, Centre of Converging of Nano-, Bio-, Information, Cognitive and Social Sciences and Technologies (NBICS Centre), National Research Centre “Kurchatov Institute”, Moscow, Russia
| | - Alexander Y. Kaplan
- Laboratory for Neurophysiology and Neuro-Computer Interfaces, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
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Kaplan AY, Shishkin SL, Ganin IP, Basyul IA, Zhigalov AY. Adapting the P300-Based Brain–Computer Interface for Gaming: A Review. IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES 2013. [DOI: 10.1109/tciaig.2012.2237517] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Andersson P, Pluim JPW, Viergever MA, Ramsey NF. Navigation of a telepresence robot via covert visuospatial attention and real-time fMRI. Brain Topogr 2012; 26:177-85. [PMID: 22965825 PMCID: PMC3536975 DOI: 10.1007/s10548-012-0252-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2012] [Accepted: 08/17/2012] [Indexed: 11/27/2022]
Abstract
Brain-computer interfaces (BCIs) allow people with severe neurological impairment and without ability to control their muscles to regain some control over their environment. The BCI user performs a mental task to regulate brain activity, which is measured and translated into commands controlling some external device. We here show that healthy participants are capable of navigating a robot by covertly shifting their visuospatial attention. Covert Visuospatial Attention (COVISA) constitutes a very intuitive brain function for spatial navigation and does not depend on presented stimuli or on eye movements. Our robot is equipped with motors and a camera that sends visual feedback to the user who can navigate it from a remote location. We used an ultrahigh field MRI scanner (7 Tesla) to obtain fMRI signals that were decoded in real time using a support vector machine. Four healthy subjects with virtually no training succeeded in navigating the robot to at least three of four target locations. Our results thus show that with COVISA BCI, realtime robot navigation can be achieved. Since the magnitude of the fMRI signal has been shown to correlate well with the magnitude of spectral power changes in the gamma frequency band in signals measured by intracranial electrodes, the COVISA concept may in future translate to intracranial application in severely paralyzed people.
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Affiliation(s)
- Patrik Andersson
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.
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Thurlings ME, Brouwer AM, Van Erp JBF, Blankertz B, Werkhoven PJ. Does bimodal stimulus presentation increase ERP components usable in BCIs? J Neural Eng 2012; 9:045005. [PMID: 22831989 DOI: 10.1088/1741-2560/9/4/045005] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Treder MS, Schmidt NM, Blankertz B. Gaze-independent brain–computer interfaces based on covert attention and feature attention. J Neural Eng 2011; 8:066003. [PMID: 21975312 DOI: 10.1088/1741-2560/8/6/066003] [Citation(s) in RCA: 147] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Comparison of classification methods for P300 brain-computer interface on disabled subjects. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2011; 2011:519868. [PMID: 21941530 PMCID: PMC3175727 DOI: 10.1155/2011/519868] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2011] [Revised: 05/26/2011] [Accepted: 07/04/2011] [Indexed: 11/18/2022]
Abstract
We report on tests with a mind typing paradigm based on a P300 brain-computer interface (BCI) on a group of amyotrophic lateral sclerosis (ALS), middle cerebral artery (MCA) stroke, and subarachnoid hemorrhage (SAH) patients, suffering from motor and speech disabilities. We investigate the achieved typing accuracy given the individual patient's disorder, and how it correlates with the type of classifier used. We considered 7 types of classifiers, linear as well as nonlinear ones, and found that, overall, one type of linear classifier yielded a higher classification accuracy. In addition to the selection of the classifier, we also suggest and discuss a number of recommendations to be considered when building a P300-based typing system for disabled subjects.
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Shishkin SL, Ganin IP, Kaplan AY. Event-related potentials in a moving matrix modification of the P300 brain–computer interface paradigm. Neurosci Lett 2011; 496:95-9. [DOI: 10.1016/j.neulet.2011.03.089] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2010] [Revised: 03/21/2011] [Accepted: 03/30/2011] [Indexed: 10/18/2022]
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