<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Coon, W. G.</style></author><author><style face="normal" font="default" size="100%">Gerwin Schalk</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A method to establish the spatiotemporal evolution of task-related cortical activity from electrocorticographic signals in single trials.</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of neuroscience methods</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/27427301</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">271</style></volume><pages><style face="normal" font="default" size="100%">76–85</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Progress in neuroscience depends substantially on the ability to establish the detailed spatial and temporal sequence of neuronal population-level activity across large areas of the brain. Because there is substantial inter-trial variability in neuronal activity, traditional techniques that rely on signal averaging obscure where and when neuronal activity occurs. Thus, up to the present, it has been difficult to examine the detailed progression of neuronal activity across large areas of the brain.</style></abstract></record></records></xml>