<?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%">Gruenwald, Johannes</style></author><author><style face="normal" font="default" size="100%">Sieghartsleitner, Sebastian</style></author><author><style face="normal" font="default" size="100%">Kapeller, Christoph</style></author><author><style face="normal" font="default" size="100%">Scharinger, Josef</style></author><author><style face="normal" font="default" size="100%">Kamada, Kyousuke</style></author><author><style face="normal" font="default" size="100%">Brunner, Peter</style></author><author><style face="normal" font="default" size="100%">Guger, Christoph</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization of High-Gamma Activity in Electrocorticographic signals</style></title><secondary-title><style face="normal" font="default" size="100%">Frontiers in Neuroscience</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2023</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.frontiersin.org/articles/10.3389/fnins.2023.1206120</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">17</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Introduction: Electrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly adjusted, such that they miss valuable physiological information.

Methods: To address these issues, we conducted a thorough qualitative and quantitative characterization of HGA in ECoG signals. Our study is based on ECoG signals recorded from 18 epilepsy patients while performing motor control, listening, and visual perception tasks. In this study, we first categorize HGA into HGA types based on the cognitive/behavioral task. For each HGA type, we then systematically quantify three fundamental signal properties of HGA: the high-gamma frequency band, the HGA bandwidth, and the temporal dynamics of HGA.

Results: The high-gamma frequency band strongly varies across subjects and across cognitive/behavioral tasks. In addition, HGA time courses have lowpass character, with transients limited to 10 Hz. The task-related rise time and duration of these HGA time courses depend on the individual subject and cognitive/behavioral task. Task-related HGA amplitudes are comparable across the investigated tasks.

Discussion: This study is of high practical relevance because it provides a systematic basis for optimizing experiment design, ECoG acquisition and processing, and HGA estimation. Our results reveal previously unknown characteristics of HGA, the physiological principles of which need to be investigated in further studies.</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%">Huggins, Jane E</style></author><author><style face="normal" font="default" size="100%">Krusienski, Dean</style></author><author><style face="normal" font="default" size="100%">Vansteensel, Mariska J</style></author><author><style face="normal" font="default" size="100%">Valeriani, Davide</style></author><author><style face="normal" font="default" size="100%">Thelen, Antonia</style></author><author><style face="normal" font="default" size="100%">Stavisky, Sergey</style></author><author><style face="normal" font="default" size="100%">Norton, James J S</style></author><author><style face="normal" font="default" size="100%">Nijholt, Anton</style></author><author><style face="normal" font="default" size="100%">Müller-Putz, Gernot</style></author><author><style face="normal" font="default" size="100%">Kosmyna, Nataliya</style></author><author><style face="normal" font="default" size="100%">Korczowski, Louis</style></author><author><style face="normal" font="default" size="100%">Kapeller, Christoph</style></author><author><style face="normal" font="default" size="100%">Herff, Christian</style></author><author><style face="normal" font="default" size="100%">Halder, Sebastian</style></author><author><style face="normal" font="default" size="100%">Guger, Christoph</style></author><author><style face="normal" font="default" size="100%">Grosse-Wentrup, Moritz</style></author><author><style face="normal" font="default" size="100%">Gaunt, Robert</style></author><author><style face="normal" font="default" size="100%">Dusang, Aliceson Nicole</style></author><author><style face="normal" font="default" size="100%">Clisson, Pierre</style></author><author><style face="normal" font="default" size="100%">Chavarriaga, Ricardo</style></author><author><style face="normal" font="default" size="100%">Anderson, Charles W</style></author><author><style face="normal" font="default" size="100%">Allison, Brendan Z</style></author><author><style face="normal" font="default" size="100%">Aksenova, Tetiana</style></author><author><style face="normal" font="default" size="100%">Aarnoutse, Erik</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.</style></title><secondary-title><style face="normal" font="default" size="100%">Brain Comput Interfaces (Abingdon)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Brain Comput Interfaces (Abingdon)</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2022</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">69-101</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></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%">Prueckl, Robert</style></author><author><style face="normal" font="default" size="100%">Kapeller, Christoph</style></author><author><style face="normal" font="default" size="100%">Potes, Cristhian</style></author><author><style face="normal" font="default" size="100%">Korostenskaja, Milena</style></author><author><style face="normal" font="default" size="100%">Gerwin Schalk</style></author><author><style face="normal" font="default" size="100%">Lee, Ki H</style></author><author><style face="normal" font="default" size="100%">Guger, Christoph</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CortiQ - clinical software for electrocorticographic real-time functional mapping of the eloquent 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><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/24111197</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">2013</style></volume><pages><style face="normal" font="default" size="100%">6365-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Planning for epilepsy surgery depends substantially on the localization of brain cortical areas responsible for sensory, motor, or cognitive functions, clinically also known as eloquent cortex. In this paper, we present the novel software package 'cortiQ' that allows clinicians to localize eloquent cortex, thus providing a safe margin for surgical resection with a low incidence of neurological deficits. This software can be easily used in addition to traditional mapping procedures such as the electrical cortical stimulation (ECS) mapping. The software analyses task-related changes in gamma activity recorded from implanted subdural electrocorticography electrodes using extensions to previously published methods. In this manuscript, we describe the system's architecture and workflow required to obtain a map of the eloquent cortex. We validate the system by comparing our mapping results with those acquired using ECS mapping in two subjects. Our results indicate that cortiQ reliably identifies eloquent cortex much faster (several minutes compared to an hour or more) than ECS mapping. Next-neighbour analyses show that there are no false positives and an average of 1.24% false negatives.</style></abstract></record></records></xml>