title: Detecting semantic priming at the single-trial level.
abstract: Semantic priming is usually studied by examining ERPs over many trials and subjects. This article aims at detecting semantic priming at the single-trial level. By using machine learning techniques it is possible to analyse and classify short traces of brain activity, which could, for example, be used to build a Brain Computer Interface (BCI). This article describes an experiment where subjects were presented with word pairs and asked to decide whether the words were related or not. A classifier was trained to determine whether the subjects judged words as related or unrelated based on one second of EEG data. The results show that the classifier accuracy when training per subject varies between 54% and 67%, and is significantly above chance level for all subjects (N  = 12) and the accuracy when training over subjects varies between 51% and 63%, and is significantly above chance level for 11 subjects, pointing to a general effect.
authors.affiliation: Radboud University Nijmegen, Donders Institute for Brain, Cognition, and Behaviour, Nijmegen, The Netherlands. j.geuze@donders.ru.nl
authors.forename: Jeroen
authors.initials: J
authors.lastname: Geuze
authors.forename: Marcel A J
authors.initials: MA
authors.lastname: van Gerven
authors.forename: Jason
authors.initials: J
authors.lastname: Farquhar
authors.forename: Peter
authors.initials: P
authors.lastname: Desain
mesh_terms: D000328:Adult; D005071:Evoked Potentials / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D012660:Semantics; D055815:Young Adult
references.citation: Neuroinformatics. 2013 Apr;11(2):175-92
references.pmid: 23250668
references.citation: J Neural Eng. 2012 Aug;9(4):045002
references.pmid: 22831906
references.citation: Behav Res Methods. 2008 Feb;40(1):198-205
references.pmid: 18411543
references.citation: Psychol Rev. 1988 Jul;95(3):385-408
references.pmid: 3406246
references.citation: Clin Neurophysiol. 2002 Jun;113(6):767-91
references.pmid: 12048038
references.citation: Electroencephalogr Clin Neurophysiol. 1988 Dec;70(6):510-23
references.pmid: 2461285
references.citation: Behav Res Methods. 2007 Nov;39(4):973-8
references.pmid: 18183914
references.citation: IEEE Trans Rehabil Eng. 1998 Sep;6(3):326-33
references.pmid: 9749910
references.citation: J Cogn Neurosci. 1993 Winter;5(1):34-44
references.pmid: 23972118
references.citation: Psychophysiology. 1985 Nov;22(6):642-7
references.pmid: 4089090
references.citation: Electroencephalogr Clin Neurophysiol. 1985 Apr;60(4):343-55
references.pmid: 2579801
references.citation: Comput Intell Neurosci. 2010;:307254
references.pmid: 20169142
references.citation: J Exp Psychol. 1971 Oct;90(2):227-34
references.pmid: 5134329
references.citation: Comput Intell Neurosci. 2011;2011:156869
references.pmid: 21253357
references.citation: Brain Lang. 2009 Dec;111(3):161-72
references.pmid: 19815267
references.citation: Spat Vis. 1997;10(4):437-42
references.pmid: 9176953
references.citation: Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:4035-8
references.pmid: 19964338
references.citation: J Neural Eng. 2012 Feb;9(1):016009
references.pmid: 22248483
references.citation: J Neurosci Methods. 2007 Aug 15;164(1):177-90
references.pmid: 17517438
references.citation: Electroencephalogr Clin Neurophysiol Suppl. 1999;52:3-6
references.pmid: 10590970
references.citation: Brain. 2013 Jan;136(Pt 1):81-9
references.pmid: 23148350
references.citation: PLoS One. 2010 Apr 01;5(4):e9813
references.pmid: 20368976
references.citation: Brain Res Cogn Brain Res. 2002 Feb;13(1):27-39
references.pmid: 11867248
references.citation: J Neural Eng. 2012 Aug;9(4):045003
references.pmid: 22831919
references.citation: Nature. 1984 Jan 12-18;307(5947):161-3
references.pmid: 6690995
references.citation: Spat Vis. 1997;10(4):433-6
references.pmid: 9176952