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Int J Psychophysiol ; 79(2): 175-83, 2011 Feb.
Article in English | MEDLINE | ID: mdl-20955738

ABSTRACT

A computer-administered assessment for decision making relevant to daily-living decisions, using the technique of complex decision making (CDM), has been previously developed and tested in our laboratory. The present study sought to identify unique patterns of brain activity in the alpha band associated with CDM. We recorded electroencephalogram (EEG) from 30 scalp sites, during a series of baseline, eyes open fixation tasks, and CDM tasks, in different contexts, in a group of 9 male and 7 female young healthy adults, aged 18 to 34. The decision making contexts, designed to simulate real-world, daily-living decisions, were about taking a bus, choosing a friend, job, medication, and participating in research. Electroencephalograms (EEGs) were divided into the frequency bands, alpha, beta, delta, theta, and gamma, though the primary focus of this paper is the alpha band. Analysis of mean EEG power spectra across the alpha bands - alpha1 (8-10 Hz), alpha2 (10-12 Hz), and alpha 3 (12-14 Hz) - showed significant decreases from baseline to the CDM task. In addition, we observed significant increases in delta, theta, beta, and gamma. There were also significant bivariate correlations between EEG spectra, mostly in low and mid alpha bands, behavioral performance on the CDM task, and scores on standardized measures of executive functioning, including the Trail-making Test and the Wisconsin Card Sorting Task. These results demonstrate how brain activity in complex decision making is distributed across alpha frequency bands and electrode regions and this activity relates to executive functioning.


Subject(s)
Alpha Rhythm/physiology , Brain/physiology , Decision Making/physiology , Electroencephalography , Adolescent , Adult , Analysis of Variance , Brain Mapping , Electroencephalography/methods , Executive Function/physiology , Female , Humans , Male , Neuropsychological Tests , Photic Stimulation/methods , Reaction Time/physiology , Spectrum Analysis , Statistics as Topic , User-Computer Interface , Young Adult
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