@article {2132, title = {Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery.}, journal = {J Neural Eng}, volume = {8}, year = {2011}, month = {06/2011}, pages = {036005}, abstract = {

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.

}, keywords = {Brain, Evoked Potentials, Motor, Evoked Potentials, Somatosensory, Feedback, Physiological, Female, Humans, Imagination, Male, Movement, Robotics, Touch, User-Computer Interface}, issn = {1741-2552}, doi = {10.1088/1741-2560/8/3/036005}, url = {http://www.ncbi.nlm.nih.gov/pubmed/21474878}, author = {Gomez-Rodriguez, M and Peters, J and Jeremy Jeremy Hill and Sch{\"o}lkopf, B and Gharabaghi, A and Grosse-Wentrup, Moritz} } @article {2206, title = {Using the electrocorticographic speech network to control a brain-computer interface in humans.}, journal = {J Neural Eng}, volume = {8}, year = {2011}, month = {06/2011}, pages = {036004}, abstract = {

Electrocorticography (ECoG) has emerged as a new signal platform for\ brain-computer interface\ (BCI) systems. Classically, the cortical physiology that has been commonly investigated and utilized for device control in humans has been\ brain\ signals from the sensorimotor cortex. Hence, it was unknown whether other neurophysiological substrates, such as the speech network, could be used to further improve on or complement existing motor-based control paradigms. We demonstrate here for the first time that ECoG signals associated with different overt and imagined phoneme articulation can enable invasively monitored human patients to control a one-dimensional\ computer\ cursor rapidly and accurately. This phonetic content was distinguishable within higher gamma frequency oscillations and enabled users to achieve final target accuracies between 68\% and 91\% within 15 min. Additionally, one of the patients achieved robust control using recordings from a microarray consisting of 1 mm spaced microwires. These findings suggest that the cortical network associated with speech could provide an additional cognitive and physiologic substrate for\ BCI\ operation and that these signals can be acquired from a cortical array that is small and minimally invasive.

}, keywords = {Adult, Brain, Brain Mapping, Computer Peripherals, Electroencephalography, Evoked Potentials, Feedback, Physiological, Female, Humans, Imagination, Male, Middle Aged, Nerve Net, Speech Production Measurement, User-Computer Interface}, issn = {1741-2552}, doi = {10.1088/1741-2560/8/3/036004}, url = {http://www.ncbi.nlm.nih.gov/pubmed/21471638}, author = {Leuthardt, E C and Charles M Gaona and Sharma, Mohit and Szrama, Nicholas and Roland, Jarod and Zachary V. Freudenberg and Solisb, Jamie and Breshears, Jonathan and Gerwin Schalk} }