%0 Journal Article %J Neuroimage %D 2011 %T Causal influence of gamma oscillations on the sensorimotor rhythm. %A Grosse-Wentrup, Moritz %A Schölkopf, B %A Jeremy Jeremy Hill %K Adult %K Cerebral Cortex %K Electroencephalography %K Female %K Humans %K Imagination %K Male %K Signal Processing, Computer-Assisted %K User-Computer Interface %X

Gamma oscillations of the electromagnetic field of the brain are known to be involved in a variety of cognitive processes, and are believed to be fundamental for information processing within the brain. While gamma oscillations have been shown to be correlated with brain rhythms at different frequencies, to date no empirical evidence has been presented that supports a causal influence of gamma oscillations on other brain rhythms. In this work, we study the relation of gamma oscillations and the sensorimotor rhythm (SMR) in healthy human subjects using electroencephalography. We first demonstrate that modulation of the SMR, induced by motor imagery of either the left or right hand, is positively correlated with the power of frontal and occipital gamma oscillations, and negatively correlated with the power of centro-parietal gamma oscillations. We then demonstrate that the most simple causal structure, capable of explaining the observed correlation of gamma oscillations and the SMR, entails a causal influence of gamma oscillations on the SMR. This finding supports the fundamental role attributed to gamma oscillations for information processing within the brain, and is of particular importance for brain-computer interfaces (BCIs). As modulation of the SMR is typically used in BCIs to infer a subject's intention, our findings entail that gamma oscillations have a causal influence on a subject's capability to utilize a BCI for means of communication.

%B Neuroimage %V 56 %P 837-42 %8 05/2011 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/20451626 %N 2 %R 10.1016/j.neuroimage.2010.04.265 %0 Journal Article %J J Neural Eng %D 2011 %T Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery. %A Gomez-Rodriguez, M %A Peters, J %A Jeremy Jeremy Hill %A Schölkopf, B %A Gharabaghi, A %A Grosse-Wentrup, Moritz %K Brain %K Evoked Potentials, Motor %K Evoked Potentials, Somatosensory %K Feedback, Physiological %K Female %K Humans %K Imagination %K Male %K Movement %K Robotics %K Touch %K User-Computer Interface %X

The combination of brain-computer interfaces (BCIs) with robot-assisted physical therapy constitutes a promising approach to neurorehabilitation of patients with severe hemiparetic syndromes caused by cerebrovascular brain damage (e.g. stroke) and other neurological conditions. In such a scenario, a key aspect is how to reestablish the disrupted sensorimotor feedback loop. However, to date it is an open question how artificially closing the sensorimotor feedback loop influences the decoding performance of a BCI. In this paper, we answer this issue by studying six healthy subjects and two stroke patients. We present empirical evidence that haptic feedback, provided by a seven degrees of freedom robotic arm, facilitates online decoding of arm movement intention. The results support the feasibility of future rehabilitative treatments based on the combination of robot-assisted physical therapy with BCIs.

%B J Neural Eng %V 8 %P 036005 %8 06/2011 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/21474878 %N 3 %R 10.1088/1741-2560/8/3/036005