Literature DB >> 16792305

ECoG factors underlying multimodal control of a brain-computer interface.

J Adam Wilson1, Elizabeth A Felton, P Charles Garell, Gerwin Schalk, Justin C Williams.   

Abstract

Most current brain-computer interface (BCI) systems for humans use electroencephalographic activity recorded from the scalp, and may be limited in many ways. Electrocorticography (ECoG) is believed to be a minimally-invasive alternative to electroencephalogram (EEG) for BCI systems, yielding superior signal characteristics that could allow rapid user training and faster communication rates. In addition, our preliminary results suggest that brain regions other than the sensorimotor cortex, such as auditory cortex, may be trained to control a BCI system using similar methods as those used to train motor regions of the brain. This could prove to be vital for users who have neurological disease, head trauma, or other conditions precluding the use of sensorimotor cortex for BCI control.

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Year:  2006        PMID: 16792305     DOI: 10.1109/TNSRE.2006.875570

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  45 in total

Review 1.  Brain-computer interfaces in medicine.

Authors:  Jerry J Shih; Dean J Krusienski; Jonathan R Wolpaw
Journal:  Mayo Clin Proc       Date:  2012-02-10       Impact factor: 7.616

2.  Dynamics of electrocorticographic (ECoG) activity in human temporal and frontal cortical areas during music listening.

Authors:  Cristhian Potes; Aysegul Gunduz; Peter Brunner; Gerwin Schalk
Journal:  Neuroimage       Date:  2012-04-14       Impact factor: 6.556

3.  Describing different brain computer interface systems through a unique model: a UML implementation.

Authors:  Lucia Rita Quitadamo; Maria Grazia Marciani; Gian Carlo Cardarilli; Luigi Bianchi
Journal:  Neuroinformatics       Date:  2008-07-08

Review 4.  Advanced neurotechnologies for chronic neural interfaces: new horizons and clinical opportunities.

Authors:  Daryl R Kipke; William Shain; György Buzsáki; E Fetz; Jaimie M Henderson; Jamille F Hetke; Gerwin Schalk
Journal:  J Neurosci       Date:  2008-11-12       Impact factor: 6.167

5.  Histological evaluation of a chronically-implanted electrocorticographic electrode grid in a non-human primate.

Authors:  Alan D Degenhart; James Eles; Richard Dum; Jessica L Mischel; Ivan Smalianchuk; Bridget Endler; Robin C Ashmore; Elizabeth C Tyler-Kabara; Nicholas G Hatsopoulos; Wei Wang; Aaron P Batista; X Tracy Cui
Journal:  J Neural Eng       Date:  2016-06-28       Impact factor: 5.379

6.  Characterization of the effects of the human dura on macro- and micro-electrocorticographic recordings.

Authors:  David T Bundy; Erik Zellmer; Charles M Gaona; Mohit Sharma; Nicholas Szrama; Carl Hacker; Zachary V Freudenburg; Amy Daitch; Daniel W Moran; Eric C Leuthardt
Journal:  J Neural Eng       Date:  2014-02       Impact factor: 5.379

7.  Decoding three-dimensional reaching movements using electrocorticographic signals in humans.

Authors:  David T Bundy; Mrinal Pahwa; Nicholas Szrama; Eric C Leuthardt
Journal:  J Neural Eng       Date:  2016-02-23       Impact factor: 5.379

Review 8.  Evolution of brain-computer interfaces: going beyond classic motor physiology.

Authors:  Eric C Leuthardt; Gerwin Schalk; Jarod Roland; Adam Rouse; Daniel W Moran
Journal:  Neurosurg Focus       Date:  2009-07       Impact factor: 4.047

9.  Decoding movement-related cortical potentials from electrocorticography.

Authors:  Chandan G Reddy; Goutam G Reddy; Hiroto Kawasaki; Hiroyuki Oya; Lee E Miller; Matthew A Howard
Journal:  Neurosurg Focus       Date:  2009-07       Impact factor: 4.047

10.  Massively Parallel Signal Processing using the Graphics Processing Unit for Real-Time Brain-Computer Interface Feature Extraction.

Authors:  J Adam Wilson; Justin C Williams
Journal:  Front Neuroeng       Date:  2009-07-14
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