02427nas a2200349 4500008004100000022001400041245011100055210006900166260001200235300001100247490000700258520132200265653001501587653002801602653003001630653003701660653002701697653002901724653001101753653001601764653001701780653001301797653003501810653003101845653003201876653004101908653002901949100001201978700001301990700002602003856004802029 2014 eng d a1558-021000aAdaptive spatio-temporal filtering for movement related potentials in EEG-based brain-computer interfaces.0 aAdaptive spatiotemporal filtering for movement related potential c07/2014 a847-570 v223 aMovement related potentials (MRPs) are used as features in many brain-computer interfaces (BCIs) based on electroencephalogram (EEG). MRP feature extraction is challenging since EEG is noisy and varies between subjects. Previous studies used spatial and spatio-temporal filtering methods to deal with these problems. However, they did not optimize temporal information or may have been susceptible to overfitting when training data are limited and the feature space is of high dimension. Furthermore, most of these studies manually select data windows and low-pass frequencies. We propose an adaptive spatio-temporal (AST) filtering method to model MRPs more accurately in lower dimensional space. AST automatically optimizes all parameters by employing a Gaussian kernel to construct a low-pass time-frequency filter and a linear ridge regression (LRR) algorithm to compute a spatial filter. Optimal parameters are simultaneously sought by minimizing leave-one-out cross-validation error through gradient descent. Using four BCI datasets from 12 individuals, we compare the performances of AST filter to two popular methods: the discriminant spatial pattern filter and regularized spatio-temporal filter. The results demonstrate that our AST filter can make more accurate predictions and is computationally feasible.10aAlgorithms10aArtificial Intelligence10abrain-computer interfaces10aData Interpretation, Statistical10aElectroencephalography10aEvoked Potentials, Motor10aHumans10aImagination10aMotor Cortex10aMovement10aPattern Recognition, Automated10aReproducibility of Results10aSensitivity and Specificity10aSignal Processing, Computer-Assisted10aSpatio-Temporal Analysis1 aLu, Jun1 aXie, Kan1 aMcFarland, Dennis, J. uhttp://www.ncbi.nlm.nih.gov/pubmed/2472363202595nas a2200421 4500008004100000022001400041245009200055210006900147260001200216300001100228490000700239520137400246653001001620653000901630653003401639653002801673653003001701653002801731653002701759653003501786653001101821653001101832653000901843653001601852653001901868653002301887653002801910653001801938100002001956700002101976700002601997700001902023700001902042700001902061700002102080700002402101856004802125 2014 eng d a2167-922300aBrain-computer interface (BCI) evaluation in people with amyotrophic lateral sclerosis.0 aBraincomputer interface BCI evaluation in people with amyotrophi c06/2014 a207-150 v153 aBrain-computer interfaces (BCIs) might restore communication to people severely disabled by amyotrophic lateral sclerosis (ALS) or other disorders. We sought to: 1) define a protocol for determining whether a person with ALS can use a visual P300-based BCI; 2) determine what proportion of this population can use the BCI; and 3) identify factors affecting BCI performance. Twenty-five individuals with ALS completed an evaluation protocol using a standard 6 × 6 matrix and parameters selected by stepwise linear discrimination. With an 8-channel EEG montage, the subjects fell into two groups in BCI accuracy (chance accuracy 3%). Seventeen averaged 92 (± 3)% (range 71-100%), which is adequate for communication (G70 group). Eight averaged 12 (± 6)% (range 0-36%), inadequate for communication (L40 subject group). Performance did not correlate with disability: 11/17 (65%) of G70 subjects were severely disabled (i.e. ALSFRS-R < 5). All L40 subjects had visual impairments (e.g. nystagmus, diplopia, ptosis). P300 was larger and more anterior in G70 subjects. A 16-channel montage did not significantly improve accuracy. In conclusion, most people severely disabled by ALS could use a visual P300-based BCI for communication. In those who could not, visual impairment was the principal obstacle. For these individuals, auditory P300-based BCIs might be effective.10aAdult10aAged10aAmyotrophic Lateral Sclerosis10aBiofeedback, Psychology10abrain-computer interfaces10aCommunication Disorders10aElectroencephalography10aEvent-Related Potentials, P30010aFemale10aHumans10aMale10aMiddle Aged10aOnline Systems10aPhotic Stimulation10aPsychomotor Performance10aReaction Time1 aMcCane, Lynn, M1 aSellers, Eric, W1 aMcFarland, Dennis, J.1 aMak, Joseph, N1 aCarmack, Steve1 aZeitlin, Debra1 aWolpaw, Jonathan1 aVaughan, Theresa, M uhttp://www.ncbi.nlm.nih.gov/pubmed/2455584300766nas a2200217 4500008004100000022001400041245013600055210006900191260001200260300001000272490000700282653002400289653003400313653004400347653001100391653002900402653002000431100002600451700002300477856004800500 2014 eng d a2157-310700aModality specificity is the preferred method for diagnosing the auditory processing disorder (APD): response to Moore and Ferguson.0 aModality specificity is the preferred method for diagnosing the  c08/2014 a698-90 v2510aAuditory Perception10aAuditory Perceptual Disorders10aEvoked Potentials, Auditory, Brain Stem10aHumans10aNeuropsychological Tests10aPsychoacoustics1 aMcFarland, Dennis, J.1 aCacace, Anthony, T uhttp://www.ncbi.nlm.nih.gov/pubmed/2536537300757nas a2200217 4500008004100000022001400041245012700055210006900182260001200251300001000263490000700273653002400280653003400304653004400338653001100382653002900393653002000422100002300442700002600465856004800491 2014 eng d a2157-310700aModality Specificity trumps other methods for diagnosing the auditory processing disorder (APD): response to Dillon et al.0 aModality Specificity trumps other methods for diagnosing the aud c08/2014 a703-50 v2510aAuditory Perception10aAuditory Perceptual Disorders10aEvoked Potentials, Auditory, Brain Stem10aHumans10aNeuropsychological Tests10aPsychoacoustics1 aCacace, Anthony, T1 aMcFarland, Dennis, J. uhttp://www.ncbi.nlm.nih.gov/pubmed/2536537500719nas a2200217 4500008004100000022001400041245011900055210006900174260001200243300002600255490000800281653004400289653001100333653001800344653001100362653000900373653002200382100002600404700002300430856004800453 2012 eng d a1878-589100aQuestionable reliability of the speech-evoked auditory brainstem response (sABR) in typically-developing children.0 aQuestionable reliability of the speechevoked auditory brainstem  c05/2012 a1-2; author reply 3-50 v28710aEvoked Potentials, Auditory, Brain Stem10aFemale10aHearing Tests10aHumans10aMale10aSpeech Perception1 aMcFarland, Dennis, J.1 aCacace, Anthony, T uhttp://www.ncbi.nlm.nih.gov/pubmed/2244617801970nas a2200205 4500008004100000022001400041245009800055210006900153260001200222300001100234490000700245520134700252653001301599653001401612653001101626653002401637653002901661100002601690856004801716 2012 eng d a1744-411X00aA single g factor is not necessary to simulate positive correlations between cognitive tests.0 asingle g factor is not necessary to simulate positive correlatio c01/2012 a378-840 v343 aIn the area of abilities testing, one issue of continued dissent is whether abilities are best conceptualized as manifestations of a single underlying general factor or as reflecting the combination of multiple traits that may be dissociable. The fact that diverse cognitive tests tend to be positively correlated has been taken as evidence for a single general ability or "g" factor. In the present study, simulations of test performance were run to evaluate the hypothesis that multiple independent abilities that affect test performance in a consistent manner will produce a positive manifold. Correlation matrices were simulated from models using either one or eight independent factors. The extent to which these factors operated in a consistent manner across tests (i.e., that a factor that facilitates performance on one test tends to facilitate performance on other tests) was manipulated by varying the mean value of the randomly selected weights. The tendency of both a single factor and eight independent factors to produce positive correlations increased as the randomly selected weights operated in a more consistent fashion. Thus the presence of a positive manifold in the correlations between diverse cognitive tests does not provide differential support for either single factor or multiple factor models of general abilities.10aAptitude10aCognition10aHumans10aModels, Theoretical10aNeuropsychological Tests1 aMcFarland, Dennis, J. uhttp://www.ncbi.nlm.nih.gov/pubmed/2226019002099nas a2200241 4500008004100000022001400041245011200055210006900167260001200236300001000248490000700258520136500265653001501630653001001645653002701655653001101682653001701693653002801710100002401738700002601762700002101788856004801809 2012 eng d a1873-274700aValue of amplitude, phase, and coherence features for a sensorimotor rhythm-based brain-computer interface.0 aValue of amplitude phase and coherence features for a sensorimot c01/2012 a130-40 v873 aMeasures that quantify the relationship between two or more brain signals are drawing attention as neuroscientists explore the mechanisms of large-scale integration that enable coherent behavior and cognition. Traditional Fourier-based measures of coherence have been used to quantify frequency-dependent relationships between two signals. More recently, several off-line studies examined phase-locking value (PLV) as a possible feature for use in brain-computer interface (BCI) systems. However, only a few individuals have been studied and full statistical comparisons among the different classes of features and their combinations have not been conducted. The present study examines the relative BCI performance of spectral power, coherence, and PLV, alone and in combination. The results indicate that spectral power produced classification at least as good as PLV, coherence, or any possible combination of these measures. This may be due to the fact that all three measures reflect mainly the activity of a single signal source (i.e., an area of sensorimotor cortex). This possibility is supported by the finding that EEG signals from different channels generally had near-zero phase differences. Coherence, PLV, and other measures of inter-channel relationships may be more valuable for BCIs that use signals from more than one distinct cortical source.10aAlgorithms10aBrain10aElectroencephalography10aHumans10aMotor Cortex10aUser-Computer Interface1 aKrusienski, Dean, J1 aMcFarland, Dennis, J.1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/2198598403784nas a2200337 4500008004100000022001400041245006200055210006100117260001200178300001100190490000700201520283200208653001503040653001003055653002403065653002903089653001103118653002603129653001103155653000903166653002903175653002103204653003103225653003403256653002203290653001603312100002103328700002603349700002303375856004803398 2011 eng d a1050-054500aDichotic and dichoptic digit perception in normal adults.0 aDichotic and dichoptic digit perception in normal adults c06/2011 a332-410 v223 aBACKGROUND: Verbally based dichotic-listening experiments and reproduction-mediated response-selection strategies have been used for over four decades to study perceptual/cognitive aspects of auditory information processing and make inferences about hemispheric asymmetries and language lateralization in the brain. Test procedures using dichotic digits have also been used to assess for disorders of auditory processing. However, with this application, limitations exist and paradigms need to be developed to improve specificity of the diagnosis. Use of matched tasks in multiple sensory modalities is a logical approach to address this issue. Herein, we use dichotic listening and dichoptic viewing of visually presented digits for making this comparison. PURPOSE: To evaluate methodological issues involved in using matched tasks of dichotic listening and dichoptic viewing in normal adults. RESEARCH DESIGN: A multivariate assessment of the effects of modality (auditory vs. visual), digit-span length (1-3 pairs), response selection (recognition vs. reproduction), and ear/visual hemifield of presentation (left vs. right) on dichotic and dichoptic digit perception. STUDY SAMPLE: Thirty adults (12 males, 18 females) ranging in age from 18 to 30 yr with normal hearing sensitivity and normal or corrected-to-normal visual acuity. DATA COLLECTION AND ANALYSIS: A computerized, custom-designed program was used for all data collection and analysis. A four-way repeated measures analysis of variance (ANOVA) evaluated the effects of modality, digit-span length, response selection, and ear/visual field of presentation. RESULTS: The ANOVA revealed that performances on dichotic listening and dichoptic viewing tasks were dependent on complex interactions between modality, digit-span length, response selection, and ear/visual hemifield of presentation. Correlation analysis suggested a common effect on overall accuracy of performance but isolated only an auditory factor for a laterality index. CONCLUSIONS: The variables used in this experiment affected performances in the auditory modality to a greater extent than in the visual modality. The right-ear advantage observed in the dichotic-digits task was most evident when reproduction mediated response selection was used in conjunction with three-digit pairs. This effect implies that factors such as "speech related output mechanisms" and digit-span length (working memory) contribute to laterality effects in dichotic listening performance with traditional paradigms. Thus, the use of multiple-digit pairs to avoid ceiling effects and the application of verbal reproduction as a means of response selection may accentuate the role of nonperceptual factors in performance. Ideally, tests of perceptual abilities should be relatively free of such effects.10aAdolescent10aAdult10aAuditory Perception10aDichotic Listening Tests10aFemale10aFunctional Laterality10aHumans10aMale10aRecognition (Psychology)10aReference Values10aReproducibility of Results10aTask Performance and Analysis10aVisual Perception10aYoung Adult1 aLawfield, Angela1 aMcFarland, Dennis, J.1 aCacace, Anthony, T uhttp://www.ncbi.nlm.nih.gov/pubmed/2186447101351nas a2200289 4500008004100000022001400041245009800055210006900153260001200222300001200234490000700246520047500253653001100728653002500739653002300764653002500787653002000812100002100832700002600853700002000879700002600899700001900925700002000944700002300964700002600987856004801013 2011 eng d a1552-684400aNeurological principles and rehabilitation of action disorders: rehabilitation interventions.0 aNeurological principles and rehabilitation of action disorders r c06/2011 a33S-43S0 v253 aThis third chapter discusses the evidence for the rehabilitation of the most common movement disorders of the upper extremity. The authors also present a framework, building on the computation, anatomy, and physiology (CAP) model, for incorporating some of the principles discussed in the 2 previous chapters by Frey et al and Sathian et al in the practice of rehabilitation and for discussing potentially helpful interventions based on emergent neuroscience principles.10aHumans10aModels, Neurological10aMovement Disorders10aRecovery of Function10aUpper Extremity1 aPomeroy, Valerie1 aAglioti, Salvatore, M1 aMark, Victor, W1 aMcFarland, Dennis, J.1 aStinear, Cathy1 aWolf, Steven, L1 aCorbetta, Maurizio1 aFitzpatrick, Susan, M uhttp://www.ncbi.nlm.nih.gov/pubmed/2161353601127nas a2200241 4500008004100000022001400041245003400055210003300089260001200122300001000134490000700144520043600151653005800587653001100645653002900656653002100685653002600706653002000732653003700752100002600789700002200815856004800837 2010 eng d a1469-182500aSymptoms as latent variables.0 aSymptoms as latent variables c06/2010 a165-60 v333 aIn the target article, Cramer et al. suggest that diagnostic classification is improved by modeling the relationship between manifest variables (i.e., symptoms) rather than modeling unobservable latent variables (i.e., diagnostic categories such as Generalized Anxiety Disorder). This commentary discusses whether symptoms represent manifest or latent variables and the implications of this distinction for diagnosis and treatment.10aDiagnostic and Statistical Manual of Mental Disorders10aHumans10aInterview, Psychological10aMental Disorders10aModels, Psychological10aSleep Disorders10aStress Disorders, Post-Traumatic1 aMcFarland, Dennis, J.1 aMalta, Loretta, S uhttp://www.ncbi.nlm.nih.gov/pubmed/2058438404357nas a2200385 4500008004100000022001400041245009700055210006900152260001200221300001200233490000800245520323100253653001503484653001003499653001403509653001003523653001803533653004203551653002703593653003003620653001103650653001103661653000903672653003203681653002303713653002203736653002803758100002503786700002603811700001903837700002003856700002603876700002103902856004803923 2008 eng d a1388-245700aTowards an independent brain-computer interface using steady state visual evoked potentials.0 aTowards an independent braincomputer interface using steady stat c02/2008 a399-4080 v1193 a

OBJECTIVE: 

Brain-computer interface (BCI) systems using steady state visual evoked potentials (SSVEPs) have allowed healthy subjects to communicate. However, these systems may not work in severely disabled users because they may depend on gaze shifting. This study evaluates the hypothesis that overlapping stimuli can evoke changes in SSVEP activity sufficient to control a BCI. This would provide evidence that SSVEP BCIs could be used without shifting gaze.

METHODS: 

Subjects viewed a display containing two images that each oscillated at a different frequency. Different conditions used overlapping or non-overlapping images to explore dependence on gaze function. Subjects were asked to direct attention to one or the other of these images during each of 12 one-minute runs.

RESULTS: 

Half of the subjects produced differences in SSVEP activity elicited by overlapping stimuli that could support BCI control. In all remaining users, differences did exist at corresponding frequencies but were not strong enough to allow effective control.

CONCLUSIONS: 

The data demonstrate that SSVEP differences sufficient for BCI control may be elicited by selective attention to one of two overlapping stimuli. Thus, some SSVEP-based BCI approaches may not depend on gaze control. The nature and extent of any BCI's dependence on muscle activity is a function of many factors, including the display, task, environment, and user.

SIGNIFICANCE: 

SSVEP BCIs might function in severely disabled users unable to reliably control gaze. Further research with these users is necessary to explore the optimal parameters of such a system and validate online performance in a home environment.

10aAdolescent10aAdult10aAttention10aBrain10aBrain Mapping10aDose-Response Relationship, Radiation10aElectroencephalography10aEvoked Potentials, Visual10aFemale10aHumans10aMale10aPattern Recognition, Visual10aPhotic Stimulation10aSpectrum Analysis10aUser-Computer Interface1 aAllison, Brendan, Z.1 aMcFarland, Dennis, J.1 aSchalk, Gerwin1 aZheng, Shi Dong1 aMoore-Jackson, Melody1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/1807720802623nas a2200289 4500008004100000022001400041245008600055210007000141260001200211300001100223490000700234520175100241653001501992653002002007653002902027653002702056653002202083653001102105653001602116653003502132653002802167100002402195700001902219700002602238700002102264856004802285 2007 eng d a0018-929400aA µ-rhythm Matched Filter for Continuous Control of a Brain-Computer Interface.0 aµrhythm Matched Filter for Continuous Control of a BrainComputer c02/2007 a273-800 v543 a

A brain-computer interface (BCI) is a system that provides an alternate nonmuscular communication/control channel for individuals with severe neuromuscular disabilities. With proper training, individuals can learn to modulate the amplitude of specific electroencephalographic (EEG) components (e.g., the 8-12 Hz mu rhythm and 18-26 Hz beta rhythm) over the sensorimotor cortex and use them to control a cursor on a computer screen. Conventional spectral techniques for monitoring the continuousamplitude fluctuations fail to capture essential amplitude/phase relationships of the mu and beta rhythms in a compact fashion and, therefore, are suboptimal. By extracting the characteristic mu rhythm for a user, the exact morphology can be characterized and exploited as a matched filter. A simple, parameterized model for the characteristic mu rhythm is proposed and its effectiveness as a matched filter is examined online for a one-dimensional cursor control task. The results suggest that amplitude/phase coupling exists between the mu and beta bands during event-related desynchronization, and that an appropriate matched filter can provide improved performance.

10aAlgorithms10aCerebral Cortex10aCortical Synchronization10aElectroencephalography10aEvoked Potentials10aHumans10aImagination10aPattern Recognition, Automated10aUser-Computer Interface1 aKrusienski, Dean, J1 aSchalk, Gerwin1 aMcFarland, Dennis, J.1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/1727858402977nas a2200361 4500008004100000022001400041245007400055210006800129260001200197300001100209490000700220520195300227653001202180653001002192653002702202653002202229653001102251653002702262653001302289653001302302653001602315653003102331653001702362653002802379100002402407700002602431700001902457700002502476700002402501700002102525700002102546856004802567 2006 eng d a1534-432000aThe Wadsworth BCI Research and Development Program: At Home with BCI.0 aWadsworth BCI Research and Development Program At Home with BCI c06/2006 a229-330 v143 a

The ultimate goal of brain-computer interface (BCI) technology is to provide communication and control capacities to people with severe motor disabilities. BCI research at the Wadsworth Center focuses primarily on noninvasive, electroencephalography (EEG)-based BCI methods. We have shown that people, including those with severe motor disabilities, can learn to use sensorimotor rhythms (SMRs) to move a cursor rapidly and accurately in one or two dimensions. We have also improved P300-based BCI operation. We are now translating this laboratory-proven BCI technology into a system that can be used by severely disabled people in their homes with minimal ongoing technical oversight. To accomplish this, we have: improved our general-purpose BCI software (BCI2000); improved online adaptation and feature translation for SMR-based BCI operation; improved the accuracy and bandwidth of P300-based BCI operation; reduced the complexity of system hardware and software and begun to evaluate home system use in appropriate users. These developments have resulted in prototype systems for every day use in people's homes.

10aAnimals10aBrain10aElectroencephalography10aEvoked Potentials10aHumans10aNeuromuscular Diseases10aNew York10aResearch10aSwitzerland10aTherapy, Computer-Assisted10aUniversities10aUser-Computer Interface1 aVaughan, Theresa, M1 aMcFarland, Dennis, J.1 aSchalk, Gerwin1 aSarnacki, William, A1 aKrusienski, Dean, J1 aSellers, Eric, W1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/1679230102332nas a2200457 4500008004100000022001400041245009000055210006900145260001200214300001100226490000700237520103300244653000901277653003401286653002701320653002901347653003701376653001101413653001101424653001601435653000901451653001601460653001701476653001301493653001401506653002301520653002801543653002501571653002201596653002801618100001501646700001501661700002301676700002401699700001601723700001901739700002601758700002101784700002101805856004801826 2005 eng d a1526-632X00aPatients with ALS can use sensorimotor rhythms to operate a brain-computer interface.0 aPatients with ALS can use sensorimotor rhythms to operate a brai c05/2005 a1775-70 v643 a

People with severe motor disabilities can maintain an acceptable quality of life if they can communicate. Brain-computer interfaces (BCIs), which do not depend on muscle control, can provide communication. Four people severely disabled by ALS learned to operate a BCI with EEG rhythms recorded over sensorimotor cortex. These results suggest that a sensorimotor rhythm-based BCI could help maintain quality of life for people with ALS.

10aAged10aAmyotrophic Lateral Sclerosis10aElectroencephalography10aEvoked Potentials, Motor10aEvoked Potentials, Somatosensory10aFemale10aHumans10aImagination10aMale10aMiddle Aged10aMotor Cortex10aMovement10aParalysis10aPhotic Stimulation10aProstheses and Implants10aSomatosensory Cortex10aTreatment Outcome10aUser-Computer Interface1 aKübler, A1 aNijboer, F1 aMellinger, Jürgen1 aVaughan, Theresa, M1 aPawelzik, H1 aSchalk, Gerwin1 aMcFarland, Dennis, J.1 aBirbaumer, Niels1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/1591180902701nas a2200337 4500008004100000022001400041245007000055210006400125260001200189300001200201490000700213520166200220653001501882653001001897653001401907653003601921653002501957653002701982653002102009653003102030653002202061653001102083653002402094653002802118100001902146700002602165700002002191700002102211700002102232856011002253 2004 eng d a0018-929400aBCI2000: a general-purpose brain-computer interface (BCI) system.0 aBCI2000 a generalpurpose braincomputer interface BCI system c06/2004 a1034-430 v513 aMany laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BC12000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups.10aAlgorithms10aBrain10aCognition10aCommunication Aids for Disabled10aComputer Peripherals10aElectroencephalography10aEquipment Design10aEquipment Failure Analysis10aEvoked Potentials10aHumans10aSystems Integration10aUser-Computer Interface1 aSchalk, Gerwin1 aMcFarland, Dennis, J.1 aHinterberger, T1 aBirbaumer, Niels1 aWolpaw, Jonathan uhttps://neurotechcenter.org/publications/2004/bci2000-general-purpose-brain-computer-interface-bci-system00603nas a2200157 4500008004100000022001400041245016200055210006900217260001200286300003100298490000700329653001100336100002600347700002400373856004800397 2003 eng d a1050-054500aPotential problems in the differential diagnosis of (central) auditory processing disorder (CAPD or APD) and attention-deficit hyperactivity disorder (ADHD).0 aPotential problems in the differential diagnosis of central audi c07/2003 a278–80; author reply 2800 v1410aHumans1 aMcFarland, Dennis, J.1 aCacace, Anthony, T. uhttp://www.ncbi.nlm.nih.gov/pubmed/1295631203064nas a2200373 4500008004100000022001400041245009000055210006900145260001200214300001000226490000700236520200500243653002902248653001002277653001502287653001402302653001002316653001802326653002702344653003002371653001302401653001102414653001602425653002802441653001302469653002002482653002802502653002202530100002102552700002602573700002402599700001902623856004802642 2003 eng d a1534-432000aThe Wadsworth Center brain-computer interface (BCI) research and development program.0 aWadsworth Center braincomputer interface BCI research and develo c06/2003 a204-70 v113 a

Brain-computer interface (BCI) research at the Wadsworth Center has focused primarily on using electroencephalogram (EEG) rhythms recorded from the scalp over sensorimotor cortex to control cursor movement in one or two dimensions. Recent and current studies seek to improve the speed and accuracy of this control by improving the selection of signal features and their translation into device commands, by incorporating additional signal features, and by optimizing the adaptive interaction between the user and system. In addition, to facilitate the evaluation, comparison, and combination of alternative BCI methods, we have developed a general-purpose BCI system called BCI-2000 and have made it available to other research groups. Finally, in collaboration with several other groups, we are developing simple BCI applications and are testing their practicality and long-term value for people with severe motor disabilities.

10aAcademic Medical Centers10aAdult10aAlgorithms10aArtifacts10aBrain10aBrain Mapping10aElectroencephalography10aEvoked Potentials, Visual10aFeedback10aHumans10aMiddle Aged10aNervous System Diseases10aResearch10aResearch Design10aUser-Computer Interface10aVisual Perception1 aWolpaw, Jonathan1 aMcFarland, Dennis, J.1 aVaughan, Theresa, M1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/1289927506596nas a2200265 4500008004100000022001400041245006100055210005900116260001200175300001100187490000800198520581800206653001906024653003606043653002106079653002706100653001106127653002806138100002106166700002106187700002606208700002406234700002406258856004806282 2002 eng d a1388-245700aBrain-computer interfaces for communication and control.0 aBraincomputer interfaces for communication and control c06/2002 a767-910 v1133 a

For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain function might provide a new non-muscular channel for sending messages and commands to the external world - a brain-computer interface (BCI). Over the past 15 years, productive BCI research programs have arisen. Encouraged by new understanding of brain function, by the advent of powerful low-cost computer equipment, and by growing recognition of the needs and potentials of people with disabilities, these programs concentrate on developing new augmentative communication and controltechnology for those with severe neuromuscular disorders, such as amyotrophic lateral sclerosis, brainstem stroke, and spinal cord injury. The immediate goal is to provide these users, who may be completely paralyzed, or 'locked in', with basic communication capabilities so that they can express their wishes to caregivers or even operate word processing programs or neuroprostheses. Present-day BCIs determine the intent of the user from a variety of different electrophysiological signals. These signals include slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronal activity recorded by implanted electrodes. They are translated in real-time into commands that operate a computer display or other device. Successful operation requires that the user encode commands in these signals and that the BCI derive the commands from the signals. Thus, the user and the BCI system need to adapt to each other both initially and continually so as to ensure stable performance. Current BCIs have maximum information transfer rates up to 10-25bits/min. This limited capacity can be valuable for people whose severe disabilities prevent them from using conventional augmentative communication methods. At the same time, many possible applications of BCI technology, such as neuroprosthesis control, may require higher information transfer rates. Future progress will depend on: recognition that BCI research and development is an interdisciplinary problem, involving neurobiology, psychology, engineering, mathematics, and computer science; identification of those signals, whether evoked potentials, spontaneous rhythms, or neuronal firing rates, that users are best able to control independent of activity in conventional motor output pathways; development of training methods for helping users to gain and maintain that control; delineation of the best algorithms for translating these signals into device commands; attention to the identification and elimination of artifacts such as electromyographic and electro-oculographic activity; adoption of precise and objective procedures for evaluating BCI performance; recognition of the need for long-term as well as short-term assessment of BCI performance; identification of appropriate BCI applications and appropriate matching of applications and users; and attention to factors that affect user acceptance of augmentative technology, including ease of use, cosmesis, and provision of those communication and control capacities that are most important to the user. Development of BCI technology will also benefit from greater emphasis on peer-reviewed research publications and avoidance of the hyperbolic and often misleading media attention that tends to generate unrealistic expectations in the public and skepticism in other researchers. With adequate recognition and effective engagement of all these issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.

10aBrain Diseases10aCommunication Aids for Disabled10aComputer Systems10aElectroencephalography10aHumans10aUser-Computer Interface1 aWolpaw, Jonathan1 aBirbaumer, Niels1 aMcFarland, Dennis, J.1 aPfurtscheller, Gert1 aVaughan, Theresa, M uhttp://www.ncbi.nlm.nih.gov/pubmed/1204803803091nas a2200373 4500008004100000022001400041245008600055210006900141260001200210300001100222490000600233520197800239653001502217653002002232653003602252653002102288653002702309653002202336653001102358653002702369653004102396653002802437100002102465700002102486700001902507700002602526700001702552700001902569700002102588700001802609700001802627700002402645856004802669 2000 eng d a1063-652800aBrain-computer interface technology: a review of the first international meeting.0 aBraincomputer interface technology a review of the first interna c06/2000 a164-730 v83 a

Over the past decade, many laboratories have begun to explore brain-computer interface (BCI) technology as a radically new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods. BCI's provide these users with communication channels that do not depend on peripheral nerves and muscles. This article summarizes the first international meeting devoted to BCI research and development. Current BCI's use electroencephalographic (EEG) activity recorded at the scalp or single-unit activity recorded from within cortex to control cursor movement, select letters or icons, or operate a neuroprosthesis. The central element in each BCI is a translation algorithm that converts electrophysiological input from the user into output that controls external devices. BCI operation depends on effective interaction between two adaptive controllers, the user who encodes his or her commands in the electrophysiological input provided to the BCI, and the BCI which recognizes the commands contained in the input and expresses them in device control. Current BCI's have maximum information transfer rates of 5-25 b/min. Achievement of greater speed and accuracy depends on improvements in signal processing, translation algorithms, and user training. These improvements depend on increased interdisciplinary cooperation between neuroscientists, engineers, computer programmers, psychologists, and rehabilitation specialists, and on adoption and widespread application of objective methods for evaluating alternative methods. The practical use of BCI technology depends on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users. BCI research and development will also benefit from greater emphasis on peer-reviewed publications, and from adoption of standard venues for presentations and discussion.

10aAlgorithms10aCerebral Cortex10aCommunication Aids for Disabled10aDisabled Persons10aElectroencephalography10aEvoked Potentials10aHumans10aNeuromuscular Diseases10aSignal Processing, Computer-Assisted10aUser-Computer Interface1 aWolpaw, Jonathan1 aBirbaumer, Niels1 aHeetderks, W J1 aMcFarland, Dennis, J.1 aPeckham, P H1 aSchalk, Gerwin1 aDonchin, Emanuel1 aQuatrano, L A1 aRobinson, C J1 aVaughan, Theresa, M uhttp://www.ncbi.nlm.nih.gov/pubmed/10896178