@article {2199, title = {Cortical activity during motor execution, motor imagery, and imagery-based online feedback.}, journal = {Proc Natl Acad Sci U S A}, volume = {107}, year = {2010}, month = {03/2010}, pages = {4430-5}, abstract = {

Imagery\ of\ motor\ movement plays an important role in learning of complex\ motor\ skills, from learning to serve in tennis to perfecting a pirouette in ballet. What and where are the neural substrates that underlie\ motorimagery-based\ learning? We measured electrocorticographic\ cortical\ surface potentials in eight human subjects during overt action and kinesthetic\ imagery\ 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\ activity\ during\ motorimagery\ mimics the spatial distribution of\ activity\ during actual\ motor\ movement. By comparing responses to electrocortical stimulation with\ imagery-induced\ cortical\ surface\ activity, we demonstrate the role of primary\ motor\ areas in movement\ imagery. The magnitude of\ imagery-induced\ corticalactivity\ change was approximately 25\% of that associated with actual movement. However, when subjects learned to use this\ imagery\ to control a computer cursor in a simple\ feedback\ task, the\ imagery-induced\ activity\ change was significantly augmented, even exceeding that of overt movement.

}, keywords = {Adolescent, Adult, Biofeedback, Psychology, Cerebral Cortex, Child, Electric Stimulation, Electrocardiography, Female, Humans, Male, Middle Aged, Motor Activity, Young Adult}, issn = {1091-6490}, doi = {10.1073/pnas.0913697107}, url = {http://www.ncbi.nlm.nih.gov/pubmed/20160084}, author = {Miller, K.J. and Gerwin Schalk and Fetz, Eberhard E and den Nijs, Marcel and Ojemann, J G and Rao, Rajesh P N} } @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} }