Proceedings of the Cognitive Neuroscience Society meeting
April 18-24 - 2004 - San Francisco (CA, USA)
 
Spectral activity of motor response-related EEG sources predicts visual reaction time in single trials
 
Arnaud Delorme(1), Marissa Westerfield(2), Scott Makeig(1)
 

(1)Institute for Neural Computation, University of California San Diego

(2)Department of Neurosciences, UCSD

arno@salk.edu, marissa@salk.edu, scott@salk.edu

 
    We recorded reaction time and electroencephalographic (EEG) activity from 15 subjects while they performed a simple visual selective attention task. One location out of five displayed along the horizontal axis, was covertly attended during 76-sec blocks. Subjects had to respond whenever a disk appeared at the attended locations. The attended location was balanced across blocks. Here, we consider responses to targets appearing at the attended location (about 500 trials per subject), which included a typical 'P300' ERP peak. Infomax independent component analysis (ICA) (sccn.ucsd.edu/eeglab) was applied to the concatenated single-trial data epochs for each subject. The resulting independent components were then clustered across subjects, producing 6 clusters of artifacts and 9 clusters of EEG components, plus unclustered components. The nine EEG clusters accounted for 60% of the artifact-corrected EEG and 87% of the grand-mean ERP. Four of the nine clusters (right and left mu, vertex-centered, and frontal midline) showed strong motor response-related activity, including a partially coherent two-cycle post-response theta burst whose amplitude did not covary with reaction time (RT) We computed spectral amplitude of the single-trial activity for each component cluster using a three-cycle wavelet. At each trial latency, we then correlated spectral amplitude with RT in single trials. For the four clusters of interest only, power in the beta band (18-25 Hz) before the stimulus correlated positively (p<0.00001) with RT, i.e., higher baseline beta amplitude preceded slower responses.