03082nas a2200313   4500008004100000022001400041245013800055210006900193260001600262490000700278520206400285653001002349653002102359653002502380653002702405653003702432653001102469653001102480653000902491653001702500653001602517653003102533653002502564653001602589100001702605700002102622700001302643856011202656       2026                        eng d  a1741-255200aMethodological optimization for eliciting robust median nerve somatosensory evoked potentials for realtime single trial applications.0 aMethodological optimization for eliciting robust median nerve so  c2026 Jan 090 v233 a<p>Single-trial measurement of median nerve somatosensory evoked potentials (SEPs) with noninvasive electroencephalography (EEG) is challenging due to low signal-to-noise ratio (SNR), limiting its use in real-time neurorehabilitation applications. We describe and evaluate methodological optimizations for eliciting reliable median nerve SEPs measurable in real time, with reduced reliance on post-processing.In twelve healthy participants, two sessions each, SEPs were assessed at three pulse widths (0.1, 0.5, 1 ms), at a low-frequency stimulation (0.5 Hz ± 10%), and at an intensity sufficient to evoke consistent and robust sensory nerve action potentials and compound muscle action potentials. The evoked potential operant conditioning system platform was used to monitor responses in real time. Feasibility was also evaluated in a participant with incomplete spinal cord injury (iSCI).SEP P50 and N70 were reliably elicited in healthy participants, and in individual with iSCI, across all tested pulse widths with minimal discomfort. N70 amplitude increased significantly with pulse width (χ2= 17.64,= 0.0001,= 0.80), while P50 amplitude remained unchanged. SNR showed a significant pulse width-dependent increase (χ2= 7.82,= 0.02,= 0.35) with improvements of 40% and 52% at 0.5 and 1 ms, respectively. N70 single-trial separability significantly improved at 1 ms (AUC of 0.83,χ2= 8.17,= 0.017), including the iSCI participant (0.84-less impaired hand, 0.79-more impaired hand). Test-retest reliability (intraclass correlation coefficient = 0.70-0.84,< 0.05) was highest at 0.5 ms, indicating more consistent N70 and P50 measurements across sessions at a longer pulse width.Robust median nerve SEPs can be measured at single trials with methodological optimizations such as a longer pulse width (0.5-1 ms), low frequency (0.5 Hz), a consistent afferent excitation guided by nerve and muscle responses, and a robust EEG acquisition system. This setup can be useful for real time SEP-based brain computer interface applications for rehabilitation.</p>10aAdult10aComputer Systems10aElectric Stimulation10aElectroencephalography10aEvoked Potentials, Somatosensory10aFemale10aHumans10aMale10aMedian Nerve10aMiddle Aged10aReproducibility of Results10aSpinal Cord Injuries10aYoung Adult1 aGupta, Disha1 aBrangaccio, Jodi1 aHill, NJ  uhttps://www.neurotechcenter.org/publications/2026/methodological-optimization-eliciting-robust-median-nerve03030nas a2200265   4500008004100000022001400041245016500055210006900220260001600289490000700305520208500312653002502397653002102422653001302443653001102456653002102467653002202488653002602510100002502536700001702561700002202578700002202600700002202622856012002644       2023                        eng d  a1741-255200aMethods for automated delineation and assessment of EMG responses evoked by peripheral nerve stimulation in diagnostic and closed-loop therapeutic applications.0 aMethods for automated delineation and assessment of EMG response  c2023 Jul 210 v203 a<p>Surface electromyography measurements of the Hoffmann (H-) reflex are essential in a wide range of neuroscientific and clinical applications. One promising emerging therapeutic application is H-reflex operant conditioning, whereby a person is trained to modulate the H-reflex, with generalized beneficial effects on sensorimotor function in chronic neuromuscular disorders. Both traditional diagnostic and novel realtime therapeutic applications rely on accurate definitions of the H-reflex and M-wave temporal bounds, which currently depend on expert case-by-case judgment. The current study automates such judgments.Our novel wavelet-based algorithm automatically determines temporal extent and amplitude of the human soleus H-reflex and M-wave. In each of 20 participants, the algorithm was trained on data from a preliminary 3 or 4 min recruitment-curve measurement. Output was evaluated on parametric fits to subsequent sessions' recruitment curves (92 curves across all participants) and on the conditioning protocol's subsequent baseline trials (∼1200 per participant) performed near. Results were compared against the original temporal bounds estimated at the time, and against retrospective estimates made by an expert 6 years later.Automatic bounds agreed well with manual estimates: 95% lay within ±2.5 ms. The resulting H-reflex magnitude estimates showed excellent agreement (97.5% average across participants) between automatic and retrospective bounds regarding which trials would be considered successful for operant conditioning. Recruitment-curve parameters also agreed well between automatic and manual methods: 95% of the automatic estimates of the current required to elicitfell within±1.4%of the retrospective estimate; for the 'threshold' current that produced an M-wave 10% of maximum, this value was±3.5%.Such dependable automation of M-wave and H-reflex definition should make both established and emerging H-reflex protocols considerably less vulnerable to inter-personnel variability and human error, increasing translational potential.</p>10aElectric Stimulation10aElectromyography10aH-Reflex10aHumans10aMuscle, Skeletal10aPeripheral Nerves10aRetrospective Studies1 aMcKinnon, Michael, L1 aHill, Jeremy1 aCarp, Jonathan, S1 aDellenbach, Blair1 aThompson, Aiko, K  uhttps://www.neurotechcenter.org/publications/2023/methods-automated-delineation-and-assessment-emg-responses-evoked02881nas a2200397   4500008004100000022001400041245011100055210006900166260001200235300001100247490000700258520172500265653001501990653002002005653001802025653002002043653002502063653002702088653002402115653001102139653001102150653001302161653002902174653003202203653001102235100002602246700001902272700002602291700002402317700001902341700001902360700001802379700002302397700001502420856004802435       2014                        eng d  a1933-071500aReal-time functional mapping: potential tool for improving language outcome in pediatric epilepsy surgery.0 aRealtime functional mapping potential tool for improving languag  c09/2014  a287-950 v143 a<p>Accurate language localization expands surgical treatment options for epilepsy patients and reduces the risk of postsurgery language deficits. Electrical cortical stimulation mapping (ESM) is considered to be the clinical gold standard for language localization. While ESM affords clinically valuable results, it can be poorly tolerated by children, requires active participation and compliance, carries a risk of inducing seizures, is highly time consuming, and is labor intensive. Given these limitations, alternative and/or complementary functional localization methods such as analysis of electrocorticographic (ECoG) activity in high gamma frequency band in real time are needed to precisely identify eloquent cortex in children. In this case report, the authors examined 1) the use of real-time functional mapping (RTFM) for language localization in a high gamma frequency band derived from ECoG to guide surgery in an epileptic pediatric patient and 2) the relationship of RTFM mapping results to postsurgical language outcomes. The authors found that RTFM demonstrated relatively high sensitivity (75%) and high specificity (90%) when compared with ESM in a "next-neighbor" analysis. While overlapping with ESM in the superior temporal region, RTFM showed a few other areas of activation related to expressive language function, areas that were eventually resected during the surgery. The authors speculate that this resection may be associated with observed postsurgical expressive language deficits. With additional validation in more subjects, this finding would suggest that surgical planning and associated assessment of the risk/benefit ratio would benefit from information provided by RTFM mapping.</p>10aAdolescent10aAnticonvulsants10aBrain Mapping10aCerebral Cortex10aElectric Stimulation10aElectroencephalography10aEpilepsies, Partial10aFemale10aHumans10aLanguage10aNeuropsychological Tests10aSensitivity and Specificity10aSpeech1 aKorostenskaja, Milena1 aChen, Po-Ching1 aSalinas, Christine, M1 aWesterveld, Michael1 aBrunner, Peter1 aSchalk, Gerwin1 aCook, Jane, C1 aBaumgartner, James1 aLee, Ki, H  uhttp://www.ncbi.nlm.nih.gov/pubmed/2499581507936nas a2200361   4500008004100000022001400041245009600055210006900151260001200220300001100232490000800243520694900251653001507200653001007215653002807225653002007253653001007273653002507283653002407308653001107332653001107343653000907354653001607363653001907379653001607398100001607414700001907430700002207449700001707471700001707488700002107505856004807526       2010                        eng d  a1091-649000aCortical activity during motor execution, motor imagery, and imagery-based online feedback.0 aCortical activity during motor execution motor imagery and image  c03/2010  a4430-50 v1073 a<p><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Imagery</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;of&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;movement plays an important role in learning of complex&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;skills, from learning to serve in tennis to perfecting a pirouette in ballet. What and where are the neural substrates that underlie&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">imagery-based</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;learning? We measured electrocorticographic&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">cortical</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;surface potentials in eight human subjects during overt action and kinesthetic&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">imagery</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;of the same movement, focusing on power in "high frequency" (76-100 Hz) and "low frequency" (8-32 Hz) ranges. We quantitatively establish that the spatial distribution of local neuronal population&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">activity</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;during&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">imagery</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;mimics the spatial distribution of&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">activity</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;during actual&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;movement. By comparing responses to electrocortical stimulation with&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">imagery</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">-induced&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">cortical</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;surface&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">activity</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">, we demonstrate the role of primary&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;areas in movement&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">imagery</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">. The magnitude of&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">imagery</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">-induced&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">cortical</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">activity</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;change was approximately 25% of that associated with actual movement. However, when subjects learned to use this&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">imagery</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;to control a computer cursor in a simple&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">feedback</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;task, the&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">imagery</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">-induced&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">activity</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;change was significantly augmented, even exceeding that of overt movement.</span></p>10aAdolescent10aAdult10aBiofeedback, Psychology10aCerebral Cortex10aChild10aElectric Stimulation10aElectrocardiography10aFemale10aHumans10aMale10aMiddle Aged10aMotor Activity10aYoung Adult1 aMiller, K J1 aSchalk, Gerwin1 aFetz, Eberhard, E1 aNijs, Marcel1 aOjemann, J G1 aRao, Rajesh, P N  uhttp://www.ncbi.nlm.nih.gov/pubmed/2016008403481nas a2200289   4500008004100000022001400041245009200055210006900147260001200216300001000228490000700238520264000245653001802885653002002903653002002923653001502943653002502958653002702983653001103010653002703021100001803048700001903066700002003085700001903105700001903124856004803143       2010                        eng d  a1525-506900aPassive real-time identification of speech and motor cortex during an awake craniotomy.0 aPassive realtime identification of speech and motor cortex durin  c05/2010  a123-80 v183 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Precise localization of eloquent cortex is a clinical necessity prior to surgical resections adjacent to speech or&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;cortex. In the intraoperative setting, this traditionally requires inducing temporary lesions by direct electrocortical stimulation (DECS). In an attempt to increase efficiency and potentially reduce the amount of necessary stimulation, we used a passive mapping procedure in the setting of an awake craniotomy for tumor in two patients resection. We recorded electrocorticographic (ECoG) signals from exposed cortex while patients performed simple cue-directed&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;and speech tasks. SIGFRIED, a procedure for real-time event detection, was used to identify areas of&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">cortical</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;activation by detecting task-related modulations in the ECoG high gamma band. SIGFRIED's real-time output quickly localized&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">motor</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;and speech areas of cortex similar to those identified by DECS. In conclusion, real-time passive identification of&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">cortical</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;function using SIGFRIED may serve as a useful adjunct to&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">cortical</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;stimulation mapping in the intraoperative setting.</span></p>10aBrain Mapping10aBrain Neoplasms10aCerebral Cortex10aCraniotomy10aElectric Stimulation10aElectroencephalography10aHumans10aNeurologic Examination1 aRoland, Jarod1 aBrunner, Peter1 aJohnston, James1 aSchalk, Gerwin1 aLeuthardt, E C  uhttp://www.ncbi.nlm.nih.gov/pubmed/2047874502591nas a2200433   4500008004100000022001400041245012500055210006900180260001200249300001100261490000700272520133300279653001001612653001801622653002001640653002501660653002601685653002701711653001301738653001101751653001101762653000901773653001601782653003301798653004101831653001601872100001901888700001801907700002201925700002201947700002001969700002401989700002302013700002002036700001902056700001502075700001902090856004802109       2009                        eng d  a1525-506900aA practical procedure for real-time functional mapping of eloquent cortex using electrocorticographic signals in humans.0 apractical procedure for realtime functional mapping of eloquent   c07/2009  a278-860 v153 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Functional mapping of eloquent cortex is often necessary prior to invasive brain surgery, but current techniques that derive this mapping have important limitations. In this article, we demonstrate the first comprehensive evaluation of a rapid, robust, and practical mapping system that uses passive recordings of electrocorticographic signals. This mapping procedure is based on the BCI2000 and SIGFRIED technologies that we have been developing over the past several years. In our study, we evaluated 10 patients with epilepsy from four different institutions and compared the results of our procedure with the results derived using electrical cortical stimulation (ECS) mapping. The results show that our procedure derives a functional motor cortical map in only a few minutes. They also show a substantial concurrence with the results derived using ECS mapping. Specifically, compared with ECS maps, a next-neighbor evaluation showed no false negatives, and only 0.46 and 1.10% false positives for hand and tongue maps, respectively. In summary, we demonstrate the first comprehensive evaluation of a practical and robust mapping procedure that could become a new tool for planning of invasive brain surgeries.</span></p>10aAdult10aBrain Mapping10aCerebral Cortex10aElectric Stimulation10aElectrodes, Implanted10aElectroencephalography10aEpilepsy10aFemale10aHumans10aMale10aMiddle Aged10aPractice Guidelines as Topic10aSignal Processing, Computer-Assisted10aYoung Adult1 aBrunner, Peter1 aRitaccio, A L1 aLynch, Timothy, M1 aEmrich, Joseph, F1 aWilson, Adam, J1 aWilliams, Justin, C1 aAarnoutse, Erik, J1 aRamsey, Nick, F1 aLeuthardt, E C1 aBischof, H1 aSchalk, Gerwin  uhttp://www.ncbi.nlm.nih.gov/pubmed/1936663804391nas a2200409   4500008004100000022001400041245010700055210006900162260001200231300002900243490000700272520323000279653001003509653002203519653001803541653002503559653002603584653002703610653001103637653000903648653001103657653000903668653001603677653001703693653001703710653004103727653001103768100001903779700002003798700002603818700001903844700002003863700002003883700001303903700001703916856004803933       2007                        eng d  a1524-404000aElectrocorticographic Frequency Alteration Mapping: A Clinical Technique for Mapping the Motor Cortex.0 aElectrocorticographic Frequency Alteration Mapping A Clinical Te  c04/2007  a260-70; discussion 270-10 v603 a<h4 style="font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;">OBJECTIVE:&nbsp;</h4>
<p style="margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Electrocortical stimulation (ECS) has been well established for delineating the eloquent cortex. However, ECS is still coarse and inefficient in delineating regions of the functional cortex and can be hampered by after-discharges. Given these constraints, an adjunct approach to defining the motor cortex is the use of electrocorticographic signal changes associated with active regions of the cortex. The broad range of frequency oscillations are categorized into two main groups with respect to the sensorimotor cortex: low and high frequency bands. The low frequency bands tend to show a power reduction with cortical activation, whereas the high frequency bands show power increases. These power changes associated with the activated cortex could potentially provide a powerful tool in delineating areas of the motor cortex. We explore electrocorticographic signal alterations as they occur with activated regions of the motor cortex, as well as its potential in clinical brain mapping applications.</p>
<h4 style="font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;">METHODS:&nbsp;</h4>
<p style="margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">We evaluated seven patients who underwent invasive monitoring for seizure localization. Each patient had extraoperative ECS mapping to identify the motor cortex. All patients also performed overt hand and tongue motor tasks to identify associated frequency power changes in regard to location and degree of concordance with ECS results that localized either hand or tongue motor function.</p>
<h4 style="font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;">RESULTS:&nbsp;</h4>
<p style="margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">The low frequency bands had a high sensitivity (88.9-100%) and a lower specificity (79.0-82.6%) for identifying electrodes with either hand or tongue ECS motor responses. The high frequency bands had a lower sensitivity (72.7-88.9%) and a higher specificity (92.4-94.9%) in correlation with the same respective ECS positive electrodes.</p>
<h4 style="font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;">CONCLUSION:&nbsp;</h4>
<p style="margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">The concordance between stimulation and spectral power changes demonstrate the possible utility of electrocorticographic frequency alteration mapping as an adjunct method to improve the efficiency and resolution of identifying the motor cortex.</p>10aAdult10aBiological Clocks10aBrain Mapping10aElectric Stimulation10aElectrodes, Implanted10aElectroencephalography10aFemale10aHand10aHumans10aMale10aMiddle Aged10aMotor Cortex10aOscillometry10aSignal Processing, Computer-Assisted10aTongue1 aLeuthardt, E C1 aMiller, John, W1 aAnderson, Nicholas, R1 aSchalk, Gerwin1 aDowling, Joshua1 aMiller, John, W1 aMoran, D1 aOjemann, J G  uhttp://www.ncbi.nlm.nih.gov/pubmed/1741516202708nas a2200373   4500008004100000022001400041245010900055210006900164260001200233300001100245490000600256520162400262653002201886653001201908653001001920653001801930653002501948653001501973653002901988653000902017653002402026653001702050653001202067653000902079653002502088653004102113653002602154100001602180700002302196700001902219700002802238700002002266856004802286       2006                        eng d  a1557-170X00aAnalysis of the correlation between local field potentials and neuronal firing rate in the motor cortex.0 aAnalysis of the correlation between local field potentials and n  c09/2006  a6185-80 v13 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Neuronal firing rate has been the signal of choice for invasive motor&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">brain</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;machine&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">interfaces</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;(BMI). The use of local field potentials (LFP) in BMI experiments may provide additional dendritic information about movement intent and may improve performance. Here we study the time-varying amplitude modulated relationship between local field potentials (LFP) and single unit activity (SUA) in the motor cortex. We record LFP and SUA in the primary motor cortex of rats trained to perform a lever pressing task, and evaluate the correlation between pairs of peri-event time histograms (PETH) and movement evoked local field potentials (mEP) at the same electrode. Three different correlation coefficients were calculated and compared between the neuronal PETH and the magnitude and power of the mEP. Correlation as high as 0.7 for some neurons occurred between the PETH and the mEP magnitude. As expected, the correlations between the single trial LFP and SUV are much lower due to the inherent variability of both signals.</span></p>10aAction Potentials10aAnimals10aBrain10aBrain Mapping10aElectric Stimulation10aElectrodes10aEvoked Potentials, Motor10aMale10aModels, Statistical10aMotor Cortex10aNeurons10aRats10aRats, Sprague-Dawley10aSignal Processing, Computer-Assisted10aSynaptic Transmission1 aWang, Yiwen1 aSanchez, Justin, C1 aPrincipe, Jose1 aMitzelfelt, Jeremiah, D1 aGunduz, Aysegul  uhttp://www.ncbi.nlm.nih.gov/pubmed/1794674501811nas a2200373   4500008004100000022001400041245008700055210006900142260001200211300001200223490000700235520078300242653001201025653002601037653001501063653001801078653002401096653002501120653002101145653002201166653001001188653002701198653002701225653001501252653001001267653002001277100001201297700001701309700001901326700001701345700001401362700001401376856004701390       1996                        eng d  a0006-349500aVortex shedding as a precursor of turbulent electrical activity in cardiac muscle.0 aVortex shedding as a precursor of turbulent electrical activity   c03/1996  a1105-110 v703 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">In cardiac tissue, during partial blockade of the membrane sodium channels, or at high frequencies of excitation, inexcitable obstacles with sharp edges may destabilize the propagation of electrical excitation waves, causing the formation of self-sustained vortices and turbulent cardiac electrical activity. The formation of such vortices, which visually resembles vortex shedding in hydrodynamic turbulent flows, was observed in sheep epicardial tissue using voltage-sensitive dyes in combination with video-imaging techniques. Vortex shedding is a potential mechanism leading to the spontaneous initiation of uncontrolled high-frequency excitation of the heart.</span></p>10aAnimals10aBiophysical Phenomena10aBiophysics10aCell Membrane10aComputer Simulation10aElectric Stimulation10aElectrochemistry10aElectrophysiology10aHeart10aModels, Cardiovascular10aMyocardial Contraction10aMyocardium10aSheep10aSodium Channels1 aCabo, C1 aPertsov, A V1 aDavidenko, J M1 aBaxter, Bill1 aGray, R A1 aJalife, J  uhttp://www.ncbi.nlm.nih.gov/pubmed/8785270