Magnetoencephalographic signals predict movement trajectory in space. Export

@article{citeulike:345433, abstract = {Brain-machine interface (BMI) efforts have been focused on using either invasive implanted electrodes or training-extensive conscious manipulation of brain rhythms to control prosthetic devices. Here we demonstrate an excellent prediction of movement trajectory by real-time magnetoencephalography (MEG). Ten human subjects copied a pentagon for 45 s using an X-Y joystick while MEG signals were being recorded from 248 sensors. A linear summation of weighted contributions of the MEG signals yielded a predicted movement trajectory of high congruence to the actual trajectory (median correlation coefficient: r = 0.91 and 0.97 for unsmoothed and smoothed predictions, respectively). This congruence was robust since it remained high in cross-validation analyses (based on the first half of data to predict the second half; median correlation coefficient: r = 0.76 and 0.85 for unsmoothed and smoothed predictions, respectively).}, address = {The Domenici Research Center for Mental Illness, Brain Sciences Center (11B), Veterans Affairs Medical Center, One Veterans Drive, Minneapolis, MN, 55417, USA.}, author = {Georgopoulos, Apostolos P. and Langheim, Frederick J. and Leuthold, Arthur C. and Merkle, Alexander N.}, citeulike-article-id = {345433}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/s00221-005-0028-8}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/16044305}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=16044305}, day = {26}, doi = {10.1007/s00221-005-0028-8}, issn = {0014-4819}, journal = {Exp Brain Res}, keywords = {copying, imitation, meg, movement, trajectory}, month = {July}, pages = {1--4}, posted-at = {2005-10-08 03:53:58}, priority = {3}, title = {Magnetoencephalographic signals predict movement trajectory in space.}, url = {http://dx.doi.org/10.1007/s00221-005-0028-8}, year = {2005} }

TY - JOUR ID - citeulike:345433 L3 - citeulike-article-id:345433 N2 - Brain-machine interface (BMI) efforts have been focused on using either invasive implanted electrodes or training-extensive conscious manipulation of brain rhythms to control prosthetic devices. Here we demonstrate an excellent prediction of movement trajectory by real-time magnetoencephalography (MEG). Ten human subjects copied a pentagon for 45 s using an X-Y joystick while MEG signals were being recorded from 248 sensors. A linear summation of weighted contributions of the MEG signals yielded a predicted movement trajectory of high congruence to the actual trajectory (median correlation coefficient: r = 0.91 and 0.97 for unsmoothed and smoothed predictions, respectively). This congruence was robust since it remained high in cross-validation analyses (based on the first half of data to predict the second half; median correlation coefficient: r = 0.76 and 0.85 for unsmoothed and smoothed predictions, respectively). JF - Exp Brain Res SN - 0014-4819 AD - The Domenici Research Center for Mental Illness, Brain Sciences Center (11B), Veterans Affairs Medical Center, One Veterans Drive, Minneapolis, MN, 55417, USA. EP - 4 TI - Magnetoencephalographic signals predict movement trajectory in space. SP - 1 KW - copying KW - imitation KW - meg KW - movement KW - trajectory AU - Georgopoulos, Apostolos AU - Langheim, Frederick AU - Leuthold, Arthur AU - Merkle, Alexander PY - 2005/07/26/ UR - http://dx.doi.org/10.1007/s00221-005-0028-8 ER -