%0 Journal Article %J Amyotroph Lateral Scler Frontotemporal Degener %D 2014 %T Brain-computer interface (BCI) evaluation in people with amyotrophic lateral sclerosis. %A McCane, Lynn M %A Sellers, Eric W %A Dennis J. McFarland %A Mak, Joseph N %A Carmack, C Steve %A Zeitlin, Debra %A Jonathan Wolpaw %A Theresa M Vaughan %K Adult %K Aged %K Amyotrophic Lateral Sclerosis %K Biofeedback, Psychology %K brain-computer interfaces %K Communication Disorders %K Electroencephalography %K Event-Related Potentials, P300 %K Female %K Humans %K Male %K Middle Aged %K Online Systems %K Photic Stimulation %K Psychomotor Performance %K Reaction Time %X Brain-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. %B Amyotroph Lateral Scler Frontotemporal Degener %V 15 %P 207-15 %8 06/2014 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/24555843 %N 3-4 %R 10.3109/21678421.2013.865750 %0 Journal Article %J J Neurophysiol %D 2014 %T Locomotor impact of beneficial or nonbeneficial H-reflex conditioning after spinal cord injury. %A Yi Chen %A Lu Chen %A Liu, Rongliang %A Wang, Yu %A Xiang Yang Chen %A Jonathan Wolpaw %K Animals %K Conditioning, Operant %K Female %K H-Reflex %K Learning %K Locomotion %K Male %K Rats %K Rats, Sprague-Dawley %K Spinal Cord Injuries %X When new motor learning changes neurons and synapses in the spinal cord, it may affect previously learned behaviors that depend on the same spinal neurons and synapses. To explore these effects, we used operant conditioning to strengthen or weaken the right soleus H-reflex pathway in rats in which a right spinal cord contusion had impaired locomotion. When up-conditioning increased the H-reflex, locomotion improved. Steps became longer, and step-cycle asymmetry (i.e., limping) disappeared. In contrast, when down-conditioning decreased the H-reflex, locomotion did not worsen. Steps did not become shorter, and asymmetry did not increase. Electromyographic and kinematic analyses explained how H-reflex increase improved locomotion and why H-reflex decrease did not further impair it. Although the impact of up-conditioning or down-conditioning on the H-reflex pathway was still present during locomotion, only up-conditioning affected the soleus locomotor burst. Additionally, compensatory plasticity apparently prevented the weaker H-reflex pathway caused by down-conditioning from weakening the locomotor burst and further impairing locomotion. The results support the hypothesis that the state of the spinal cord is a "negotiated equilibrium" that serves all the behaviors that depend on it. When new learning changes the spinal cord, old behaviors undergo concurrent relearning that preserves or improves their key features. Thus, if an old behavior has been impaired by trauma or disease, spinal reflex conditioning, by changing a specific pathway and triggering a new negotiation, may enable recovery beyond that achieved simply by practicing the old behavior. Spinal reflex conditioning protocols might complement other neurorehabilitation methods and enhance recovery. %B J Neurophysiol %V 111 %P 1249-58 %8 03/2014 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/24371288 %N 6 %R 10.1152/jn.00756.2013 %0 Journal Article %J J Neural Eng %D 2014 %T A practical, intuitive brain-computer interface for communicating 'yes' or 'no' by listening. %A Jeremy Jeremy Hill %A Ricci, Erin %A Haider, Sameah %A McCane, Lynn M %A Susan M Heckman %A Jonathan Wolpaw %A Theresa M Vaughan %K Adult %K Aged %K Algorithms %K Auditory Perception %K brain-computer interfaces %K Communication Aids for Disabled %K Electroencephalography %K Equipment Design %K Equipment Failure Analysis %K Female %K Humans %K Male %K Man-Machine Systems %K Middle Aged %K Quadriplegia %K Treatment Outcome %K User-Computer Interface %X OBJECTIVE: Previous work has shown that it is possible to build an EEG-based binary brain-computer interface system (BCI) driven purely by shifts of attention to auditory stimuli. However, previous studies used abrupt, abstract stimuli that are often perceived as harsh and unpleasant, and whose lack of inherent meaning may make the interface unintuitive and difficult for beginners. We aimed to establish whether we could transition to a system based on more natural, intuitive stimuli (spoken words 'yes' and 'no') without loss of performance, and whether the system could be used by people in the locked-in state. APPROACH: We performed a counterbalanced, interleaved within-subject comparison between an auditory streaming BCI that used beep stimuli, and one that used word stimuli. Fourteen healthy volunteers performed two sessions each, on separate days. We also collected preliminary data from two subjects with advanced amyotrophic lateral sclerosis (ALS), who used the word-based system to answer a set of simple yes-no questions. MAIN RESULTS: The N1, N2 and P3 event-related potentials elicited by words varied more between subjects than those elicited by beeps. However, the difference between responses to attended and unattended stimuli was more consistent with words than beeps. Healthy subjects' performance with word stimuli (mean 77% ± 3.3 s.e.) was slightly but not significantly better than their performance with beep stimuli (mean 73% ± 2.8 s.e.). The two subjects with ALS used the word-based BCI to answer questions with a level of accuracy similar to that of the healthy subjects. SIGNIFICANCE: Since performance using word stimuli was at least as good as performance using beeps, we recommend that auditory streaming BCI systems be built with word stimuli to make the system more pleasant and intuitive. Our preliminary data show that word-based streaming BCI is a promising tool for communication by people who are locked in. %B J Neural Eng %V 11 %P 035003 %8 06/2014 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/24838278 %N 3 %R 10.1088/1741-2560/11/3/035003 %0 Journal Article %J Neuroimage %D 2011 %T Spatiotemporal dynamics of electrocorticographic high gamma activity during overt and covert word repetition. %A Pei, Xiao-Mei %A Leuthardt, E C %A Charles M Gaona %A Peter Brunner %A Jonathan Wolpaw %A Gerwin Schalk %K Adolescent %K Adult %K Brain %K Brain Mapping %K Electroencephalography %K Female %K Humans %K Male %K Middle Aged %K Signal Processing, Computer-Assisted %K Verbal Behavior %X

Language is one of the defining abilities of humans. Many studies have characterized the neural correlates of different aspects of language processing. However, the imaging techniques typically used in these studies were limited in either their temporal or spatial resolution. Electrocorticographic (ECoG) recordings from the surface of the brain combine high spatial with high temporal resolution and thus could be a valuable tool for the study of neural correlates of language function. In this study, we defined the spatiotemporal dynamics of ECoG activity during a word repetition task in nine human subjects. ECoG was recorded while each subject overtly or covertly repeated words that were presented either visually or auditorily. ECoG amplitudes in the high gamma (HG) band confidently tracked neural changes associated with stimulus presentation and with the subject's verbal response. Overt word production was primarily associated with HG changes in the superior and middle parts of temporal lobe, Wernicke's area, the supramarginal gyrus, Broca's area, premotor cortex (PMC), primary motor cortex. Covert word production was primarily associated with HG changes in superior temporal lobe and the supramarginal gyrus. Acoustic processing from both auditory stimuli as well as the subject's own voice resulted in HG power changes in superior temporal lobe and Wernicke's area. In summary, this study represents a comprehensive characterization of overt and covert speech using electrophysiological imaging with high spatial and temporal resolution. It thereby complements the findings of previous neuroimaging studies of language and thus further adds to current understanding of word processing in humans.

%B Neuroimage %V 54 %P 2960-72 %8 02/2011 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/21029784 %N 4 %R 10.1016/j.neuroimage.2010.10.029 %0 Journal Article %J J Neural Eng %D 2010 %T Does the 'P300' speller depend on eye gaze?. %A Peter Brunner %A Joshi, S %A S Briskin %A Jonathan Wolpaw %A H Bischof %A Gerwin Schalk %K Adult %K Event-Related Potentials, P300 %K Eye Movements %K Female %K Humans %K Male %K Middle Aged %K Models, Neurological %K Photic Stimulation %K User-Computer Interface %K Young Adult %X

Many people affected by debilitating neuromuscular disorders such as amyotrophic lateral sclerosis, brainstem stroke or spinal cord injury are impaired in their ability to, or are even unable to, communicate. A brain-computer interface (BCI) uses brain signals, rather than muscles, to re-establish communication with the outside world. One particular BCI approach is the so-called 'P300 matrix speller' that was first described by Farwell and Donchin (1988 Electroencephalogr. Clin. Neurophysiol. 70 510-23). It has been widely assumed that this method does not depend on the ability to focus on the desired character, because it was thought that it relies primarily on the P300-evoked potential and minimally, if at all, on other EEG features such as the visual-evoked potential (VEP). This issue is highly relevant for the clinical application of this BCI method, because eye movements may be impaired or lost in the relevant user population. This study investigated the extent to which the performance in a 'P300' speller BCI depends on eye gaze. We evaluated the performance of 17 healthy subjects using a 'P300' matrix speller under two conditions. Under one condition ('letter'), the subjects focused their eye gaze on the intended letter, while under the second condition ('center'), the subjects focused their eye gaze on a fixation cross that was located in the center of the matrix. The results show that the performance of the 'P300' matrix speller in normal subjects depends in considerable measure on gaze direction. They thereby disprove a widespread assumption in BCI research, and suggest that this BCI might function more effectively for people who retain some eye-movement control. The applicability of these findings to people with severe neuromuscular disabilities (particularly in eye-movements) remains to be determined.

%B J Neural Eng %V 7 %P 056013 %8 10/2010 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/20858924 %N 5 %R 10.1088/1741-2560/7/5/056013 %0 Journal Article %J J Neural Eng %D 2009 %T Decoding flexion of individual fingers using electrocorticographic signals in humans. %A Kubánek, J %A Miller, John W %A Ojemann, J G %A Jonathan Wolpaw %A Gerwin Schalk %K Adolescent %K Adult %K Biomechanics %K Brain %K Electrodiagnosis %K Epilepsy %K Female %K Fingers %K Humans %K Male %K Microelectrodes %K Middle Aged %K Motor Activity %K Rest %K Thumb %K Time Factors %K Young Adult %X

Brain signals can provide the basis for a non-muscular communication and control system, a brain-computer interface (BCI), for people with motor disabilities. A common approach to creating BCI devices is to decode kinematic parameters of movements using signals recorded by intracortical microelectrodes. Recent studies have shown that kinematic parameters of hand movements can also be accurately decoded from signals recorded by electrodes placed on the surface of the brain (electrocorticography (ECoG)). In the present study, we extend these results by demonstrating that it is also possible to decode the time course of the flexion of individual fingers using ECoG signals in humans, and by showing that these flexion time courses are highly specific to the moving finger. These results provide additional support for the hypothesis that ECoG could be the basis for powerful clinically practical BCI systems, and also indicate that ECoG is useful for studying cortical dynamics related to motor function.

%B J Neural Eng %V 6 %P 066001 %8 12/2009 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/19794237 %N 6 %R 10.1088/1741-2560/6/6/066001 %0 Journal Article %J J Neurosci Methods %D 2008 %T Brain-computer interfaces (BCIs): Detection Instead of Classification. %A Gerwin Schalk %A Peter Brunner %A Lester A Gerhardt %A H Bischof %A Jonathan Wolpaw %K Adult %K Algorithms %K Brain %K Brain Mapping %K Electrocardiography %K Electroencephalography %K Humans %K Male %K Man-Machine Systems %K Normal Distribution %K Online Systems %K Signal Detection, Psychological %K Signal Processing, Computer-Assisted %K Software Validation %K User-Computer Interface %X

Many studies over the past two decades have shown that people can use brain signals to convey their intent to a computer through brain-computer interfaces (BCIs). These devices operate by recording signals from the brain and translating these signals into device commands. They can be used by people who are severely paralyzed to communicate without any use of muscle activity. One of the major impediments in translating this novel technology into clinical applications is the current requirement for preliminary analyses to identify the brain signal features best suited for communication. This paper introduces and validates signal detection, which does not require such analysis procedures, as a new concept in BCI signal processing. This detection concept is realized with Gaussian mixture models (GMMs) that are used to model resting brain activity so that any change in relevant brain signals can be detected. It is implemented in a package called SIGFRIED (SIGnal modeling For Real-time Identification and Event Detection). The results indicate that SIGFRIED produces results that are within the range of those achieved using a common analysis strategy that requires preliminary identification of signal features. They indicate that such laborious analysis procedures could be replaced by merely recording brain signals during rest. In summary, this paper demonstrates how SIGFRIED could be used to overcome one of the present impediments to translation of laboratory BCI demonstrations into clinically practical applications.

%B J Neurosci Methods %V 167 %P 51-62 %8 01/2008 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17920134 %N 1 %R 10.1016/j.jneumeth.2007.08.010 %0 Journal Article %J Neuroimage %D 2008 %T Real-time detection of event-related brain activity. %A Gerwin Schalk %A Leuthardt, E C %A Peter Brunner %A Ojemann, J G %A Lester A Gerhardt %A Jonathan Wolpaw %K Adult %K Algorithms %K Brain Mapping %K Computer Systems %K Diagnosis, Computer-Assisted %K Electroencephalography %K Epilepsy %K Evoked Potentials %K Female %K Humans %K Male %K Pattern Recognition, Automated %K Reproducibility of Results %K Sensitivity and Specificity %X

The complexity and inter-individual variation of brain signals impedes real-time detection of events in raw signals. To convert these complex signals into results that can be readily understood, current approaches usually apply statistical methods to data from known conditions after all data have been collected. The capability to provide meaningful visualization of complex brain signals without the requirement to initially collect data from all conditions would provide a new tool, essentially a new imaging technique, that would open up new avenues for the study of brain function. Here we show that a new analysis approach, called SIGFRIED, can overcome this serious limitation of current methods. SIGFRIED can visualize brain signal changes without requiring prior data collection from all conditions. This capacity is particularly well suited to applications in which comprehensive prior data collection is impossible or impractical, such as intraoperative localization of cortical function or detection of epileptic seizures.

%B Neuroimage %V 43 %P 245-9 %8 11/2008 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/18718544 %N 2 %R 10.1016/j.neuroimage.2008.07.037 %0 Journal Article %J Clin Neurophysiol %D 2008 %T Towards an independent brain-computer interface using steady state visual evoked potentials. %A Brendan Z. Allison %A Dennis J. McFarland %A Gerwin Schalk %A Zheng, Shi Dong %A Moore-Jackson, Melody %A Jonathan Wolpaw %K Adolescent %K Adult %K Attention %K Brain %K Brain Mapping %K Dose-Response Relationship, Radiation %K Electroencephalography %K Evoked Potentials, Visual %K Female %K Humans %K Male %K Pattern Recognition, Visual %K Photic Stimulation %K Spectrum Analysis %K User-Computer Interface %X

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.

%B Clin Neurophysiol %V 119 %P 399-408 %8 02/2008 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/18077208 %N 2 %R 10.1016/j.clinph.2007.09.121 %0 Journal Article %J J Neural Eng %D 2008 %T Two-dimensional movement control using electrocorticographic signals in humans. %A Gerwin Schalk %A Miller, K.J. %A Nicholas R Anderson %A Adam J Wilson %A Smyth, Matt %A Ojemann, J G %A Moran, D %A Jonathan Wolpaw %A Leuthardt, E C %K Adolescent %K Adult %K Brain Mapping %K Data Interpretation, Statistical %K Drug Resistance %K Electrocardiography %K Electrodes, Implanted %K Electroencephalography %K Epilepsy %K Female %K Humans %K Male %K Movement %K User-Computer Interface %X

We show here that a brain-computer interface (BCI) using electrocorticographic activity (ECoG) and imagined or overt motor tasks enables humans to control a computer cursor in two dimensions. Over a brief training period of 12-36 min, each of five human subjects acquired substantial control of particular ECoG features recorded from several locations over the same hemisphere, and achieved average success rates of 53-73% in a two-dimensional four-target center-out task in which chance accuracy was 25%. Our results support the expectation that ECoG-based BCIs can combine high performance with technical and clinical practicality, and also indicate promising directions for further research.

%B J Neural Eng %V 5 %P 75-84 %8 03/2008 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/18310813 %N 1 %R 10.1088/1741-2560/5/1/008 %0 Journal Article %J J Neural Eng %D 2007 %T Decoding two-dimensional movement trajectories using electrocorticographic signals in humans. %A Gerwin Schalk %A Kubánek, J %A Miller, John W %A Nicholas R Anderson %A Leuthardt, E C %A Ojemann, J G %A Limbrick, D %A Moran, D %A Lester A Gerhardt %A Jonathan Wolpaw %K Adult %K Algorithms %K Arm %K Brain Mapping %K Cerebral Cortex %K Electroencephalography %K Evoked Potentials, Motor %K Female %K Humans %K Male %K Movement %X

Signals from the brain could provide a non-muscular communication and control system, a brain-computer interface (BCI), for people who are severely paralyzed. A common BCI research strategy begins by decoding kinematic parameters from brain signals recorded during actual arm movement. It has been assumed that these parameters can be derived accurately only from signals recorded by intracortical microelectrodes, but the long-term stability of such electrodes is uncertain. The present study disproves this widespread assumption by showing in humans that kinematic parameters can also be decoded from signals recorded by subdural electrodes on the cortical surface (ECoG) with an accuracy comparable to that achieved in monkey studies using intracortical microelectrodes. A new ECoG feature labeled the local motor potential (LMP) provided the most information about movement. Furthermore, features displayed cosine tuning that has previously been described only for signals recorded within the brain. These results suggest that ECoG could be a more stable and less invasive alternative to intracortical electrodes for BCI systems, and could also prove useful in studies of motor function.

%B J Neural Eng %V 4 %P 264-75 %8 09/2007 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17873429 %N 3 %R 10.1088/1741-2560/4/3/012 %0 Journal Article %J Neurology %D 2005 %T Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. %A Kübler, A. %A Nijboer, F %A Mellinger, Jürgen %A Theresa M Vaughan %A Pawelzik, H %A Gerwin Schalk %A Dennis J. McFarland %A Niels Birbaumer %A Jonathan Wolpaw %K Aged %K Amyotrophic Lateral Sclerosis %K Electroencephalography %K Evoked Potentials, Motor %K Evoked Potentials, Somatosensory %K Female %K Humans %K Imagination %K Male %K Middle Aged %K Motor Cortex %K Movement %K Paralysis %K Photic Stimulation %K Prostheses and Implants %K Somatosensory Cortex %K Treatment Outcome %K User-Computer Interface %X

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.

%B Neurology %V 64 %P 1775-7 %8 05/2005 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/15911809 %N 10 %R 10.1212/01.WNL.0000158616.43002.6D %0 Journal Article %J J Neural Eng %D 2004 %T A brain-computer interface using electrocorticographic signals in humans. %A Leuthardt, E C %A Gerwin Schalk %A Jonathan Wolpaw %A Ojemann, J G %A Moran, D %K Adult %K Brain %K Communication Aids for Disabled %K Computer Peripherals %K Diagnosis, Computer-Assisted %K Electrodes, Implanted %K Electroencephalography %K Evoked Potentials %K Female %K Humans %K Imagination %K Male %K Movement Disorders %K User-Computer Interface %X

Brain-computer interfaces (BCIs) enable users to control devices with electroencephalographic (EEG) activity from the scalp or with single-neuron activity from within the brain. Both methods have disadvantages: EEG has limited resolution and requires extensive training, while single-neuron recording entails significant clinical risks and has limited stability. We demonstrate here for the first time that electrocorticographic (ECoG) activity recorded from the surface of the brain can enable users to control a one-dimensional computer cursor rapidly and accurately. We first identified ECoG signals that were associated with different types of motor and speech imagery. Over brief training periods of 3-24 min, four patients then used these signals to master closed-loop control and to achieve success rates of 74-100% in a one-dimensional binary task. In additional open-loop experiments, we found that ECoG signals at frequencies up to 180 Hz encoded substantial information about the direction of two-dimensional joystick movements. Our results suggest that an ECoG-based BCI could provide for people with severe motor disabilities a non-muscular communication and control option that is more powerful than EEG-based BCIs and is potentially more stable and less traumatic than BCIs that use electrodes penetrating the brain.

%B J Neural Eng %V 1 %P 63-71 %8 06/2004 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/15876624 %N 2 %R 10.1088/1741-2560/1/2/001