@article {4335, title = {Within-subject reaction time variability: Role of cortical networks and underlying neurophysiological mechanisms.}, journal = {Neuroimage}, volume = {237}, year = {2021}, month = {08/2021}, pages = {118127}, abstract = {

Variations in reaction time are a ubiquitous characteristic of human behavior. Extensively documented, they have been successfully modeled using parameters of the subject or the task, but the neural basis of behavioral reaction time that varies within the same subject and the same task has been minimally studied. In this paper, we investigate behavioral reaction time variance using 28 datasets of direct cortical recordings in humans who engaged in four different types of simple sensory-motor reaction time tasks. Using a previously described technique that can identify the onset of population-level cortical activity and a novel functional connectivity algorithm described herein, we show that the cumulative latency difference of population-level neural activity across the task-related cortical network can explain up to 41\% of the trial-by-trial variance in reaction time. Furthermore, we show that reaction time variance may primarily be due to the latencies in specific brain regions and demonstrate that behavioral latency variance is accumulated across the whole task-related cortical network. Our results suggest that population-level neural activity monotonically increases prior to movement execution, and that trial-by-trial changes in that increase are, in part, accounted for by inhibitory activity indexed by low-frequency oscillations. This pre-movement neural activity explains 19\% of the measured variance in neural latencies in our data. Thus, our study provides a mechanistic explanation for a sizable fraction of behavioral reaction time when the subject{\textquoteright}s task is the same from trial to trial.

}, keywords = {Adult, Algorithms, Alpha Rhythm, Cerebral Cortex, Connectome, Electrocorticography, Female, Gamma Rhythm, Humans, Male, Middle Aged, Nerve Net, Psychomotor Performance, Reaction Time, Young Adult}, issn = {1095-9572}, doi = {10.1016/j.neuroimage.2021.118127}, author = {Paraskevopoulou, Sivylla E and Coon, William G and Peter Brunner and Miller, Kai J and Schalk, Gerwin} } @article {3370, title = {Brain-computer interface (BCI) evaluation in people with amyotrophic lateral sclerosis.}, journal = {Amyotroph Lateral Scler Frontotemporal Degener}, volume = {15}, year = {2014}, month = {06/2014}, pages = {207-15}, abstract = {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 {\texttimes} 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 ({\textpm} 3)\% (range 71-100\%), which is adequate for communication (G70 group). Eight averaged 12 ({\textpm} 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.}, keywords = {Adult, Aged, Amyotrophic Lateral Sclerosis, Biofeedback, Psychology, brain-computer interfaces, Communication Disorders, Electroencephalography, Event-Related Potentials, P300, Female, Humans, Male, Middle Aged, Online Systems, Photic Stimulation, Psychomotor Performance, Reaction Time}, issn = {2167-9223}, doi = {10.3109/21678421.2013.865750}, url = {http://www.ncbi.nlm.nih.gov/pubmed/24555843}, author = {McCane, Lynn M and Sellers, Eric W and Dennis J. McFarland and Mak, Joseph N and Carmack, C Steve and Zeitlin, Debra and Jonathan Wolpaw and Theresa M Vaughan} } @article {2194, title = {Brain-computer interfacing based on cognitive control.}, journal = {Ann Neurol}, volume = {67}, year = {2010}, month = {06/2010}, pages = {809-16}, abstract = {

OBJECTIVE:\ 

Brain-computer interfaces (BCIs) translate deliberate intentions and associated changes in brain activity into action, thereby offering patients with severe paralysis an alternative means of communication with and control over their environment. Such systems are not available yet, partly due to the high performance standard that is required. A major challenge in the development of implantable BCIs is to identify cortical regions and related functions that an individual can reliably and consciously manipulate. Research predominantly focuses on the sensorimotor cortex, which can be activated by imagining motor actions. However, because this region may not provide an optimal solution to all patients, other neuronal networks need to be examined. Therefore, we investigated whether the cognitive control network can be used for BCI purposes. We also determined the feasibility of using functional magnetic resonance imaging (fMRI) for noninvasive localization of the cognitive control network.

METHODS:\ 

Three patients with intractable epilepsy, who were temporarily implanted with subdural grid electrodes for diagnostic purposes, attempted to gain BCI control using the electrocorticographic (ECoG) signal of the left dorsolateral prefrontal cortex (DLPFC).

RESULTS:\ 

All subjects quickly gained accurate BCI control by modulation of gamma-power of the left DLPFC. Prelocalization of the relevant region was performed with fMRI and was confirmed using the ECoG signals obtained during mental calculation localizer tasks.

INTERPRETATION:\ 

The results indicate that the cognitive control network is a suitable source of signals for BCI applications. They also demonstrate the feasibility of translating understanding about cognitive networks derived from functional neuroimaging into clinical applications.

}, keywords = {Cognition, Computers, Electrodes, Electroencephalography, Epilepsy, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Neuropsychological Tests, Oxygen, Prefrontal Cortex, Psychomotor Performance, Spectrum Analysis, Time Factors, User-Computer Interface}, issn = {1531-8249}, doi = {10.1002/ana.21985}, url = {http://www.ncbi.nlm.nih.gov/pubmed/20517943}, author = {Vansteensel, Mariska J and Hermes, Dora and Aarnoutse, Erik J and Bleichner, Martin G and Gerwin Schalk and van Rijen, Peter C and Leijten, Frans S S and Ramsey, Nick F} } @article {2098, title = {Extraction and localization of mesoscopic motor control signals for human ECoG neuroprosthetics.}, journal = {J Neurosci Methods}, volume = {167}, year = {2008}, month = {01/2008}, pages = {63-81}, abstract = {

Electrocorticogram (ECoG) recordings for\ neuroprosthetics\ provide a\ mesoscopic\ level of abstraction of brain function between microwire single neuron recordings and the electroencephalogram (EEG). Single-trial\ ECoG\ neural interfaces require appropriate feature\ extraction\ and signal processing methods to identify and model in real-time signatures of\ motor\ events in spontaneous brain activity. Here, we develop the clinical experimental paradigm and analysis tools to record broadband (1Hz to 6kHz)\ ECoG\ from patients participating in a reaching and pointing task. Motivated by the significant role of amplitude modulated rate coding in extracellular spike based brain-machine interfaces (BMIs), we develop methods to quantify spatio-temporal intermittent increased\ ECoG\ voltages to determine if they provide viable\ control\ inputs for\ ECoG\ neural interfaces. This study seeks to explore preprocessing modalities that emphasize amplitude modulation across frequencies and channels in the\ ECoG\ above the level of noisy background fluctuations in order to derive the commands for complex, continuous\ control\ tasks. Preliminary experiments show that it is possible to derive online predictive models and spatially localize the generation of commands in the cortex for\ motor\ tasks using amplitude modulated\ ECoG.

}, keywords = {Adolescent, Biofeedback, Psychology, Brain Mapping, Cerebral Cortex, Electroencephalography, Epilepsies, Partial, Female, Hand, Humans, Magnetic Resonance Imaging, Physical Therapy Modalities, Psychomotor Performance, Signal Processing, Computer-Assisted, Spectrum Analysis, User-Computer Interface}, issn = {0165-0270}, doi = {10.1016/j.jneumeth.2007.04.019}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17582507}, author = {Sanchez, Justin C and Gunduz, Aysegul and Carney, Paul R and Principe, Jose} } @article {2188, title = {Unique cortical physiology associated with ipsilateral hand movements and neuroprosthetic implications.}, journal = {Stroke}, volume = {39}, year = {2008}, month = {12/2008}, pages = {3351-9}, abstract = {

BACKGROUND AND PURPOSE:\ 

Brain computer interfaces\ (BCIs) offer little direct benefit to patients with hemispheric stroke because current platforms rely on signals derived from the contralateral motor cortex (the same region injured by the stroke). For BCIs to assist hemiparetic patients, the implant must use unaffected cortex ipsilateral to the affected limb. This requires the identification of distinct electrophysiological features from the motor cortex associated with ipsilateral hand movements.

METHODS:\ 

In this study we studied 6 patients undergoing temporary placement of intracranial electrode arrays. Electrocorticographic (ECoG) signals were recorded while the subjects engaged in specific ipsilateral or contralateral hand motor tasks. Spectral changes were identified with regards to frequency, location, and timing.

RESULTS:\ 

Ipsilateral hand movements were associated with electrophysiological changes that occur in lower frequency spectra, at distinct anatomic locations, and earlier than changes associated with contralateral hand movements. In a subset of 3 patients, features specific to ipsilateral and contralateral hand movements were used to control a cursor on a screen in real time. In ipsilateral derived control this was optimal with lower frequency spectra.

CONCLUSIONS:\ 

There are distinctive cortical electrophysiological features associated with ipsilateral movements which can be used for device control. These findings have implications for patients with hemispheric stroke because they offer a potential methodology for which a single hemisphere can be used to enhance the function of a stroke induced hemiparesis.

}, keywords = {Adolescent, Adult, Artificial Limbs, Bionics, Brain Mapping, Child, Dominance, Cerebral, Electroencephalography, Female, Hand, Humans, Male, Middle Aged, Motor Cortex, Movement, Paresis, Prosthesis Design, Psychomotor Performance, Stroke, User-Computer Interface, Volition}, issn = {1524-4628}, doi = {10.1161/STROKEAHA.108.518175}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18927456}, author = {Wisneski, Kimberly and Nicholas R Anderson and Gerwin Schalk and Smyth, Matt and Moran, D and Leuthardt, E C} }