02749nas a2200373 4500008004100000022001400041245011800055210006900173260001200242300001100254490000800265520163200273653001001905653001501915653001701930653002001947653001501967653002501982653001102007653001702018653001102035653000902046653001602055653001402071653002802085653001802113653001602131100003202147700002102179700001902200700001902219700001902238856011802257 2021 eng d a1095-957200aWithin-subject reaction time variability: Role of cortical networks and underlying neurophysiological mechanisms.0 aWithinsubject reaction time variability Role of cortical network c08/2021 a1181270 v2373 a

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's task is the same from trial to trial.

10aAdult10aAlgorithms10aAlpha Rhythm10aCerebral Cortex10aConnectome10aElectrocorticography10aFemale10aGamma Rhythm10aHumans10aMale10aMiddle Aged10aNerve Net10aPsychomotor Performance10aReaction Time10aYoung Adult1 aParaskevopoulou, Sivylla, E1 aCoon, William, G1 aBrunner, Peter1 aMiller, Kai, J1 aSchalk, Gerwin uhttps://neurotechcenter.org/publications/2021/within-subject-reaction-time-variability-role-cortical-networks-and02595nas 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/2455584304192nas a2200409 4500008004100000022001400041245005900055210005700114260001200171300001100183490000700194520303500201653001403236653001403250653001503264653002703279653001303306653001103319653004003330653003103370653002903401653001103430653002203441653002803463653002203491653001703513653002803530100002803558700001703586700002303603700002503626700001903651700002003670700002403690700002003714856004803734 2010 eng d a1531-824900aBrain-computer interfacing based on cognitive control.0 aBraincomputer interfacing based on cognitive control c06/2010 a809-160 v673 a

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.

10aCognition10aComputers10aElectrodes10aElectroencephalography10aEpilepsy10aHumans10aImage Processing, Computer-Assisted10aMagnetic Resonance Imaging10aNeuropsychological Tests10aOxygen10aPrefrontal Cortex10aPsychomotor Performance10aSpectrum Analysis10aTime Factors10aUser-Computer Interface1 aVansteensel, Mariska, J1 aHermes, Dora1 aAarnoutse, Erik, J1 aBleichner, Martin, G1 aSchalk, Gerwin1 aRijen, Peter, C1 aLeijten, Frans, S S1 aRamsey, Nick, F uhttp://www.ncbi.nlm.nih.gov/pubmed/2051794305892nas a2200361 4500008004100000022001400041245010100055210006900156260001200225300001000237490000800247520480000255653001505055653002805070653001805098653002005116653002705136653002405163653001105187653000905198653001105207653003105218653003205249653002805281653004105309653002205350653002805372100002305400700002005423700002005443700001905463856004805482 2008 eng d a0165-027000aExtraction and localization of mesoscopic motor control signals for human ECoG neuroprosthetics.0 aExtraction and localization of mesoscopic motor control signals  c01/2008 a63-810 v1673 a

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.

10aAdolescent10aBiofeedback, Psychology10aBrain Mapping10aCerebral Cortex10aElectroencephalography10aEpilepsies, Partial10aFemale10aHand10aHumans10aMagnetic Resonance Imaging10aPhysical Therapy Modalities10aPsychomotor Performance10aSignal Processing, Computer-Assisted10aSpectrum Analysis10aUser-Computer Interface1 aSanchez, Justin, C1 aGunduz, Aysegul1 aCarney, Paul, R1 aPrincipe, Jose uhttp://www.ncbi.nlm.nih.gov/pubmed/1758250704121nas a2200457 4500008004100000022001400041245010800055210006900163260001200232300001100244490000700255520290000262653001503162653001003177653002103187653001203208653001803220653001003238653002403248653002703272653001103299653000903310653001103319653000903330653001603339653001703355653001303372653001203385653002203397653002803419653001103447653002803458653001303486100002303499700002603522700001903548700001603567700001303583700001903596856004803615 2008 eng d a1524-462800aUnique cortical physiology associated with ipsilateral hand movements and neuroprosthetic implications.0 aUnique cortical physiology associated with ipsilateral hand move c12/2008 a3351-90 v393 a

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.

10aAdolescent10aAdult10aArtificial Limbs10aBionics10aBrain Mapping10aChild10aDominance, Cerebral10aElectroencephalography10aFemale10aHand10aHumans10aMale10aMiddle Aged10aMotor Cortex10aMovement10aParesis10aProsthesis Design10aPsychomotor Performance10aStroke10aUser-Computer Interface10aVolition1 aWisneski, Kimberly1 aAnderson, Nicholas, R1 aSchalk, Gerwin1 aSmyth, Matt1 aMoran, D1 aLeuthardt, E C uhttp://www.ncbi.nlm.nih.gov/pubmed/18927456