@article {3407, title = {Real-time functional mapping: potential tool for improving language outcome in pediatric epilepsy surgery.}, journal = {J Neurosurg Pediatr}, volume = {14}, year = {2014}, month = {09/2014}, pages = {287-95}, abstract = {

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.

}, keywords = {Adolescent, Anticonvulsants, Brain Mapping, Cerebral Cortex, Electric Stimulation, Electroencephalography, Epilepsies, Partial, Female, Humans, Language, Neuropsychological Tests, Sensitivity and Specificity, Speech}, issn = {1933-0715}, doi = {10.3171/2014.6.PEDS13477}, url = {http://www.ncbi.nlm.nih.gov/pubmed/24995815}, author = {Korostenskaja, Milena and Chen, Po-Ching and Salinas, Christine M and Westerveld, Michael and Peter Brunner and Gerwin Schalk and Cook, Jane C and Baumgartner, James and Lee, Ki H} } @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 {2137, title = {Voluntary brain regulation and communication with electrocorticogram signals.}, journal = {Epilepsy Behav}, volume = {13}, year = {2008}, month = {08/2008}, pages = {300-6}, abstract = {

Brain-computer interfaces\ (BCIs) can be used for communication in writing without muscular activity or for learning to control seizures by voluntary regulation of\ brain\ signals such as the electroencephalogram (EEG). Three of five patients with epilepsy were able to spell their names with electrocorticogram (ECoG) signals derived from motor-related areas within only one or two training sessions. Imagery of finger or tongue movements was classified with support-vector classification of autoregressive coefficients derived from the ECoG signals. After training of the classifier, binary classification responses were used to select letters from a\ computer-generated menu. Offline analysis showed increased theta activity in the unsuccessful patients, whereas the successful patients exhibited dominant sensorimotor rhythms that they could control. The high spatial resolution and increased signal-to-noise ratio in ECoG signals, combined with short training periods, may offer an alternative for communication in complete paralysis, locked-in syndrome, and motor restoration.

}, keywords = {Adult, Biofeedback, Psychology, Cerebral Cortex, Communication Aids for Disabled, Dominance, Cerebral, Electroencephalography, Epilepsies, Partial, Female, Humans, Imagination, Male, Middle Aged, Motor Activity, Motor Cortex, Signal Processing, Computer-Assisted, Software, Somatosensory Cortex, Theta Rhythm, User-Computer Interface, Writing}, issn = {1525-5069}, doi = {10.1016/j.yebeh.2008.03.014}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18495541}, author = {Hinterberger, T. and Widman, Guido and Lal, T.N and Jeremy Jeremy Hill and Tangermann, Michael and Rosenstiel, W. and Sch{\"o}lkopf, B and Elger, Christian and Niels Birbaumer} }