<?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%">Gunduz, Aysegul</style></author><author><style face="normal" font="default" size="100%">Sanchez, Justin C</style></author><author><style face="normal" font="default" size="100%">Principe, Jose</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Electrocorticographic interictal spike removal via denoising source separation for improved neuroprosthesis control.</style></title><secondary-title><style face="normal" font="default" size="100%">Conf Proc IEEE Eng Med Biol Soc</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Conf Proc IEEE Eng Med Biol Soc</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Artifacts</style></keyword><keyword><style  face="normal" font="default" size="100%">Diagnosis, Computer-Assisted</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Epilepsy</style></keyword><keyword><style  face="normal" font="default" size="100%">Evoked Potentials, Motor</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Sensitivity and Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19163895</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">2008</style></volume><pages><style face="normal" font="default" size="100%">5224-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Electrocorticographic (ECoG) neuroprosthesis is a promising area of research that could provide channels of communication and control for patients who have lost their motor functions due to damage to the nervous system. However, implantation of subdural electrodes are clinically restricted to diagnostics of pre-surgical epileptic patients. Hence, interictal activity is present in the recordings across various areas of the sensorimotor cortex and suppresses the amplitude modulated features extracted to model hand trajectories. Denoising source separation is a recently introduced framework which extracts hidden structures of interest within the&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;data&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;through denoising the source estimates with filters designed around prior knowledge on the observations. Herein, we exploit the high amplitude quasiperiodic nature of the observed interictal spikes and show that removal of the interictal activity improves linear prediction of hand trajectories.&lt;/span&gt;&lt;/p&gt;</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%">Wang, Yiwen</style></author><author><style face="normal" font="default" size="100%">Sanchez, Justin C</style></author><author><style face="normal" font="default" size="100%">Principe, Jose</style></author><author><style face="normal" font="default" size="100%">Mitzelfelt, Jeremiah D</style></author><author><style face="normal" font="default" size="100%">Gunduz, Aysegul</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of the correlation between local field potentials and neuronal firing rate in the motor cortex.</style></title><secondary-title><style face="normal" font="default" size="100%">Conf Proc IEEE Eng Med Biol Soc</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Conf Proc IEEE Eng Med Biol Soc</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Action Potentials</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Electric Stimulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Electrodes</style></keyword><keyword><style  face="normal" font="default" size="100%">Evoked Potentials, Motor</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Statistical</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurons</style></keyword><keyword><style  face="normal" font="default" size="100%">Rats</style></keyword><keyword><style  face="normal" font="default" size="100%">Rats, Sprague-Dawley</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Processing, Computer-Assisted</style></keyword><keyword><style  face="normal" font="default" size="100%">Synaptic Transmission</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2006</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17946745</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">6185-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Neuronal firing rate has been the signal of choice for invasive motor&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;brain&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;machine&amp;nbsp;&lt;/span&gt;&lt;span class=&quot;highlight&quot; style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;interfaces&lt;/span&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&amp;nbsp;(BMI). The use of local field potentials (LFP) in BMI experiments may provide additional dendritic information about movement intent and may improve performance. Here we study the time-varying amplitude modulated relationship between local field potentials (LFP) and single unit activity (SUA) in the motor cortex. We record LFP and SUA in the primary motor cortex of rats trained to perform a lever pressing task, and evaluate the correlation between pairs of peri-event time histograms (PETH) and movement evoked local field potentials (mEP) at the same electrode. Three different correlation coefficients were calculated and compared between the neuronal PETH and the magnitude and power of the mEP. Correlation as high as 0.7 for some neurons occurred between the PETH and the mEP magnitude. As expected, the correlations between the single trial LFP and SUV are much lower due to the inherent variability of both signals.&lt;/span&gt;&lt;/p&gt;</style></abstract></record></records></xml>