<?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%">Lawrence J. Crowther</style></author><author><style face="normal" font="default" size="100%">Peter Brunner</style></author><author><style face="normal" font="default" size="100%">Christoph Kapeller</style></author><author><style face="normal" font="default" size="100%">Christoph Guger</style></author><author><style face="normal" font="default" size="100%">Kyousuke Kamada</style></author><author><style face="normal" font="default" size="100%">Marjorie E. Bunch</style></author><author><style face="normal" font="default" size="100%">Bridget K. Frawley</style></author><author><style face="normal" font="default" size="100%">Timothy M. Lynch</style></author><author><style face="normal" font="default" size="100%">Anthony L. Ritaccio</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 quantitative method for evaluating cortical responses to electrical stimulation</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Neuroscience Methods</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Connectivity</style></keyword><keyword><style  face="normal" font="default" size="100%">Cortico-cortical evoked potentials</style></keyword><keyword><style  face="normal" font="default" size="100%">Electrical stimulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Electrocorticography</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S0165027018302796</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">311</style></volume><pages><style face="normal" font="default" size="100%">67 - 75</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Background Electrical stimulation of the cortex using subdurally implanted electrodes can causally reveal structural connectivity by eliciting cortico-cortical evoked potentials (CCEPs). While many studies have demonstrated the potential value of CCEPs, the methods to evaluate them were often relatively subjective, did not consider potential artifacts, and did not lend themselves to systematic scientific investigations. New method We developed an automated and quantitative method called SIGNI (Stimulation-Induced Gamma-based Network Identification) to evaluate cortical population-level responses to electrical stimulation that minimizes the impact of electrical artifacts. We applied SIGNI to electrocorticographic (ECoG) data from eight human subjects who were implanted with a total of 978 subdural electrodes. Across the eight subjects, we delivered 92 trains of approximately 200 discrete electrical stimuli each (amplitude 4–15 mA) to a total of 64 electrode pairs. Results We verified SIGNI's efficacy by demonstrating a relationship between the magnitude of evoked cortical activity and stimulation amplitude, as well as between the latency of evoked cortical activity and the distance from the stimulated locations. Conclusions SIGNI reveals the timing and amplitude of cortical responses to electrical stimulation as well as the structural connectivity supporting these responses. With these properties, it enables exploration of new and important questions about the neurophysiology of cortical communication and may also be useful for pre-surgical planning.</style></abstract></record><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%">Disha Gupta</style></author><author><style face="normal" font="default" size="100%">Pauly Ossenblok</style></author><author><style face="normal" font="default" size="100%">Gilles van Luijtelaar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Space–time network connectivity and cortical activations preceding spike wave discharges in human absence epilepsy: a MEG study.</style></title><secondary-title><style face="normal" font="default" size="100%">Medical and Biological Engineering and Computing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Absence epilepsy</style></keyword><keyword><style  face="normal" font="default" size="100%">Beamforming</style></keyword><keyword><style  face="normal" font="default" size="100%">Connectivity</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetoencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Nonlinear association analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Small world networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Spike wave discharge</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/21533620</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">49</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">To describe the spatial and temporal profiles of connectivity networks and sources preceding generalized spike-and-wave discharges (SWDs) in human absence epilepsy. Nonlinear associations of MEG signals and cluster indices obtained within the framework of graph theory were determined, while source localization in the frequency domain was performed in the low frequency bands with dynamic imaging of coherent sources. The results were projected on a three-dimensional surface rendering of the brain using a semi-realistic head model and MRI images obtained for each of the five patients studied. An increase in clustering and a decrease in path length preceding SWD onset and a rhythmic pattern of increasing and decreasing connectivity were seen during SWDs. Beamforming showed a consistent appearance of a low frequency frontal cortical source prior to the first generalized spikes. This source was preceded by a low frequency occipital source. The changes in the connectivity networks with the onset of SWDs suggest a pathologically predisposed state towards synchronous seizure networks with increasing connectivity from interictal to preictal and ictal state, while the occipital and frontal low frequency early preictal sources demonstrate that SWDs are not suddenly arising but gradually build up in a dynamic network.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><section><style face="normal" font="default" size="100%">555</style></section></record></records></xml>