03596nas a2200505 4500008004100000022001400041245010700055210006900162260001200231300001300243490000700256520217800263653002502441653001502466653001002481653002502491653001802516653001602534653002002550653002402570653002702594653001302621653002202634653001102656653001102667653000902678653001602687653002902703653002302732653002302755653001802778653002202796653001702818653001502835100002202850700001802872700002902890700002402919700002002943700001802963700002302981700001903004700001903023856004803042 2011 eng d a1529-240100aNonuniform high-gamma (60-500 Hz) power changes dissociate cognitive task and anatomy in human cortex.0 aNonuniform highgamma 60500 Hz power changes dissociate cognitive c02/2011 a2091-1000 v313 a

High-gamma-band (>60 Hz) power changes in cortical electrophysiology are a reliable indicator of focal, event-related cortical activity. Despite discoveries of oscillatory subthreshold and synchronous suprathreshold activity at the cellular level, there is an increasingly popular view that high-gamma-band amplitude changes recorded from cellular ensembles are the result of asynchronous firing activity that yields wideband and uniform power increases. Others have demonstrated independence of power changes in the low- and high-gamma bands, but to date, no studies have shown evidence of any such independence above 60 Hz. Based on nonuniformities in time-frequency analyses of electrocorticographic (ECoG) signals, we hypothesized that induced high-gamma-band (60-500 Hz) power changes are more heterogeneous than currently understood. Using single-word repetition tasks in six human subjects, we showed that functional responsiveness of different ECoG high-gamma sub-bands can discriminate cognitive task (e.g., hearing, reading, speaking) and cortical locations. Power changes in these sub-bands of the high-gamma range are consistently present within single trials and have statistically different time courses within the trial structure. Moreover, when consolidated across all subjects within three task-relevant anatomic regions (sensorimotor, Broca's area, and superior temporal gyrus), these behavior- and location-dependent power changes evidenced nonuniform trends across the population. Together, the independence and nonuniformity of power changes across a broad range of frequencies suggest that a new approach to evaluating high-gamma-band cortical activity is necessary. These findings show that in addition to time and location, frequency is another fundamental dimension of high-gamma dynamics.

10aAcoustic Stimulation10aAdolescent10aAdult10aAnalysis of Variance10aBrain Mapping10aBrain Waves10aCerebral Cortex10aCognition Disorders10aElectroencephalography10aEpilepsy10aEvoked Potentials10aFemale10aHumans10aMale10aMiddle Aged10aNeuropsychological Tests10aNonlinear Dynamics10aPhotic Stimulation10aReaction Time10aSpectrum Analysis10aTime Factors10aVocabulary1 aGaona, Charles, M1 aSharma, Mohit1 aFreudenberg, Zachary, V.1 aBreshears, Jonathan1 aBundy, David, T1 aRoland, Jarod1 aBarbour, Dennis, L1 aSchalk, Gerwin1 aLeuthardt, E C uhttp://www.ncbi.nlm.nih.gov/pubmed/2130724604192nas 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/2051794301606nas a2200301 4500008004100000022001400041245007000055210006600125260001200191300001200203490000700215520071500222653001000937653002100947653002700968653002200995653001101017653002501028653003101053653004101084653001701125653002801142100002001170700002301190700001901213700002401232856004801256 2010 eng d a1558-253100aA procedure for measuring latencies in brain-computer interfaces.0 aprocedure for measuring latencies in braincomputer interfaces c06/2010 a1785-970 v573 a

Brain-computer interface (BCI) systems must process neural signals with consistent timing in order to support adequate system performance. Thus, it is important to have the capability to determine whether a particular BCI configuration (i.e., hardware and software) provides adequate timing performance for a particular experiment. This report presents a method of measuring and quantifying different aspects of system timing in several typical BCI experiments across a range of settings, and presents comprehensive measures of expected overall system latency for each experimental configuration.

10aBrain10aComputer Systems10aElectroencephalography10aEvoked Potentials10aHumans10aModels, Neurological10aReproducibility of Results10aSignal Processing, Computer-Assisted10aTime Factors10aUser-Computer Interface1 aWilson, Adam, J1 aMellinger, Jürgen1 aSchalk, Gerwin1 aWilliams, Justin, C uhttp://www.ncbi.nlm.nih.gov/pubmed/2040378102146nas a2200397 4500008004100000022001400041245009000055210006900145260001200214300001100226490000600237520112800243653001501371653001001386653001701396653001001413653002101423653001301444653001101457653001201468653001101480653000901491653002001500653001601520653001901536653000901555653001001564653001701574653001601591100001601607700002001623700001701643700002101660700001901681856004801700 2009 eng d a1741-255200aDecoding flexion of individual fingers using electrocorticographic signals in humans.0 aDecoding flexion of individual fingers using electrocorticograph c12/2009 a0660010 v63 a

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.

10aAdolescent10aAdult10aBiomechanics10aBrain10aElectrodiagnosis10aEpilepsy10aFemale10aFingers10aHumans10aMale10aMicroelectrodes10aMiddle Aged10aMotor Activity10aRest10aThumb10aTime Factors10aYoung Adult1 aKubánek, J1 aMiller, John, W1 aOjemann, J G1 aWolpaw, Jonathan1 aSchalk, Gerwin uhttp://www.ncbi.nlm.nih.gov/pubmed/1979423702084nas a2200229 4500008004100000022001400041245009200055210006900147260001200216300001400228490000700242520141400249653001701663100002101680700002201701700001301723700001301736700001301749700002301762700002101785856004801806 2007 eng d a0022-307700aSpinal and supraspinal effects of long-term stimulation of sensorimotor cortex in rats.0 aSpinal and supraspinal effects of longterm stimulation of sensor c08/2007 a878–8870 v983 aSensorimotor cortex (SMC) modifies spinal cord reflex function throughout life and is essential for operant conditioning of the H-reflex. To further explore this long-term SMC influence over spinal cord function and its possible clinical uses, we assessed the effect of long-term SMC stimulation on the soleus H-reflex. In freely moving rats, the soleus H-reflex was measured 24 h/day for 12 wk. The soleus background EMG and M response associated with H-reflex elicitation were kept stable throughout. SMC stimulation was delivered in a 20-day-on/20-day-off/20-day-on protocol in which a train of biphasic 1-ms pulses at 25 Hz for 1 s was delivered every 10 s for the on-days. The SMC stimulus was automatically adjusted to maintain a constant descending volley. H-reflex size gradually increased during the 20 on-days, stayed high during the 20 off-days, and rose further during the next 20 on-days. In addition, the SMC stimulus needed to maintain a stable descending volley rose steadily over days. It fell during the 20 off-days and rose again when stimulation resumed. These results suggest that SMC stimulation, like H-reflex operant conditioning, induces activity-dependent plasticity in both the brain and the spinal cord and that the plasticity responsible for the H-reflex increase persists longer after the end of SMC stimulation than that underlying the change in the SMC response to stimulation.10aTime Factors1 aChen, Xiang Yang1 aPillai, Shreejith1 aChen, Yi1 aWang, Yu1 aChen, Lu1 aCarp, Jonathan, S.1 aWolpaw, Jonathan uhttp://www.ncbi.nlm.nih.gov/pubmed/1752217901909nas a2200181 4500008004100000022001400041245006900055210006600124260001200190300001400202490000800216520138400224653001701608100002101625700002101646700001301667856004701680 1994 eng d a0304-394000aOperant conditioning of primate H-reflex: phases of development.0 aOperant conditioning of primate Hreflex phases of development c04/1994 a203–2070 v1703 aThis study sought to determine whether operantly conditioned change in the primate triceps surae (TS) H-reflex develops in distinct phases. Data from 20 animals in which the TS H-reflex in one leg was trained up (i.e., HRup mode) and 18 in which it was trained down (i.e., HRdown mode) were averaged to define H-reflex behavior in trained and control legs. In HRup animals, the trained-leg H-reflex showed a large phase I increase in the first two days followed by gradual phase II increase that continued for weeks. The control-leg H-reflex appeared to show much smaller phase I and phase II increases. In HRdown animals, the trained-leg H-reflex decreased gradually over weeks, while the control-leg H-reflex appeared to increase within 2 days and did not change from then on. The initial rapid increase in the HRdown control leg suggested that two early events occurred in the HRdown trained leg: a nonspecific increase like that in the control leg and an operantly conditioned mode-specific decrease. These two effects may have obscured each other, so that H-reflex size in the HRdown trained leg did not drop rapidly in the first few days. These results improve understanding of adaptive H-reflex change as an operantly conditioned phenomenon, and provide encouragement and direction for efforts to reproduce and study the phenomenon in reduced or anesthetized preparations.10aTime Factors1 aWolpaw, Jonathan1 aManiccia, D., M.1 aElia, T. uhttp://www.ncbi.nlm.nih.gov/pubmed/805818802101nas a2200169 4500008004100000022001400041245009600055210006900151260001200220300001600232490000600248520157200254653001701826100002101843700002001864856004701884 1984 eng d a0270-647400aAdaptive plasticity in the primate spinal stretch reflex: evidence for a two-phase process.0 aAdaptive plasticity in the primate spinal stretch reflex evidenc c11/1984 a2718–27240 v43 aMonkeys can slowly increase or decrease the amplitude of the purely spinal, largely monosynaptic portion of the response to sudden muscle stretch, the spinal stretch reflex (SSR), when confronted by a task requiring such change (Wolpaw, J.R., V.A. Kieffer, R.F. Seegal, D.J. Braitman, and M.G. Sanders (1983) Brain Res. 267: 196-200; Wolpaw, J.R., D.J. Braitman, and R.F. Seegal (1983) J. Neurophysiol. 50: 1296-1311). Change occurs without alteration in initial muscle length or in background activity of agonist, antagonist, or synergist muscles. This study uses composite curves to describe in detail the development of SSR amplitude change. It reveals important, previously unexpected features of this development. SSR increase or decrease appears to occur in two distinct phases. Phase I, a nearly immediate 8% change, occurs within the first 6 hr. Phase II, a 2%/day change, continues for at least 2 months. Although phase II is much slower than phase I, its final magnitude is far greater. Phase I indicates a nearly immediate change in suprasegmental influence of the segmental arc of the SSR. Because stretch onset time is unpredictable and the SSR occurs before any other possible response, this change in descending activity must be tonic; it must be present continually, day after day, for the 5 to 7 hr/day the animal spends at the task. Phase I produces a rapid and significant increase in reward probability. Thus, it may be readily interpreted as an example of operant conditioning, provoked by the reward contingency.(ABSTRACT TRUNCATED AT 250 WORDS)10aTime Factors1 aWolpaw, Jonathan1 aO'Keefe, J., A. uhttp://www.ncbi.nlm.nih.gov/pubmed/650220002233nas a2200169 4500008004100000022001400041245005800055210005500113260001200168300001400180490000700194520176100201653001701962100002101979700001802000856004502018 1975 eng d a0013-469400aA temporal component of the auditory evoked response.0 atemporal component of the auditory evoked response c12/1975 a609–6200 v393 aWe studied the 75-225 msec portion of the auditory evoked response (AER) in 32 normal adults at vertex (Cz) and temporal (T3 and T4) placements referred to a balanced, noncephalic reference electrode using a monaural 1 msec click stimulus delivered every 4.7 sec at 60 dB above threshold. The tape-recorded EEG was filtered at 1-25 c/sec, and 128 individual responses were summed, sampling every 0.5 msec for 250 msec post-stimulation. The Cz AERs showed the classic vertex response, a negative peak, N1, at 100 msec, followed by a positive peak, P2, at 160-200 msec. The T3 and T4 AERs were similar to the Cz AERs from 0 to 80 msec and from 200 to 250 msec. They differed significantly from the Cz AERs from 80 to 200 msec. The difference is best explained by the hypothesis that the Cz AERs consisted of N1P2, while the T3 and T4 AERs consisted of N1P2 plus an additional superimposed component, which we called the T complex, comprising a positive peak, Ta, at 105-110 msec, and a negative peak, Tb, at 150-160 msec. By computer, the corresponding Cz and T3 or T4 AERs were normalized to equalize their amplitudes, and the former was subtracted from the latter, thus isolating the T complex. The Ta peak was found to occur 1.5 +/- 1.6 msec earlier at the electrode contralateral to stimulation, and 2.2 +/- 4.0 msec earlier at the T4 (right) electrode. Both differences were statistically significant. The T complex amplitude was greater at the electrode contralateral to stimulation and at the T4 electrode. These findings appear to resolve current controversies concerning the form of the temporal AER. While N1P2 is apparently a product of widespread areas of cortex, we conclude that the T complex is probably a product of secondary auditory cortex.10aTime Factors1 aWolpaw, Jonathan1 aPenry, J., K. uhttp://www.ncbi.nlm.nih.gov/pubmed/53139