@article {2208, title = {Proceedings of the Second International Workshop on Advances in Electrocorticography.}, journal = {Epilepsy Behav}, volume = {22}, year = {2011}, month = {12/2011}, pages = {641-50}, abstract = {

The Second International Workshop on Advances in Electrocorticography (ECoG) was convened in San Diego, CA, USA, on November 11-12, 2010. Between this meeting and the inaugural 2009 event, a much clearer picture has been emerging of cortical ECoG physiology and its relationship to local field potentials and single-cell recordings. Innovations in material engineering are advancing the goal of a stable long-term recording interface. Continued evolution of ECoG-driven brain-computer interface technology is determining innovation in neuroprosthetics. Improvements in instrumentation and statistical methodologies continue to elucidate ECoG correlates of normal human function as well as the ictal state. This proceedings document summarizes the current status of this rapidly evolving field.

}, keywords = {Brain, Brain Mapping, Brain Waves, Diagnosis, Computer-Assisted, Electroencephalography, Epilepsy, Humans, United States, User-Computer Interface}, issn = {1525-5069}, doi = {10.1016/j.yebeh.2011.09.028}, url = {http://www.ncbi.nlm.nih.gov/pubmed/22036287}, author = {A L Ritaccio and Boatman-Reich, Dana and Peter Brunner and Cervenka, Mackenzie C and Cole, Andrew J and Nathan E. Crone and Duckrow, Robert and Korzeniewska, Anna and Litt, Brian and Miller, John W and Moran, D and Parvizi, Josef and Viventi, Jonathan and Williams, Justin C and Gerwin Schalk} } @article {2193, title = {Decoding flexion of individual fingers using electrocorticographic signals in humans.}, journal = {J Neural Eng}, volume = {6}, year = {2009}, month = {12/2009}, pages = {066001}, abstract = {

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.

}, keywords = {Adolescent, Adult, Biomechanics, Brain, Electrodiagnosis, Epilepsy, Female, Fingers, Humans, Male, Microelectrodes, Middle Aged, Motor Activity, Rest, Thumb, Time Factors, Young Adult}, issn = {1741-2552}, doi = {10.1088/1741-2560/6/6/066001}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19794237}, author = {Kub{\'a}nek, J and Miller, John W and Ojemann, J G and Jonathan Wolpaw and Gerwin Schalk} }