Please use this identifier to cite or link to this item: https://observatorio.fm.usp.br/handle/OPI/3079
Title: Lack of systematic topographic difference between attention and reasoning beta correlates
Authors: BASILE, L. F. H.ALVARENGA, M. Y.HENRIQUE JR., N.PASQUINI, H. A.ALFENAS, W.
Citation: INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, v.85, n.3, Special Issue, p.302-302, 2012
Abstract: Based on previous evidence for individual-specific sets of cortical areas active during simple attention tasks, in this work we intended to perform within individual comparisons of task-induced beta oscillations between visual attention and a reasoning task. Since beta induced oscillations are not time-locked to task events and were first observed by Fourier transforms, in order to analyze the cortical topography of attention induced beta activity, we have previously computed corrected-latency averages based on spontaneous peaks of band-pass filtered epochs. We then used Independent Component Analysis (ICA) only to single out the significant portion of averaged data, above noise levels. In the present work ICA served as the main, exhaustive means for decomposing beta activity in both tasks, recorded by 128-channel EEG in 20 subjects. Given the previously observed similarity between tasks by visual inspection and by simple descriptive statistics, we now intended another quantitative approach: to statistically test whether each ICA component obtained in one task could be explained by a linear regression model based on the topographic patterns from the other task in each individual. Results confirmed the high topographic similarity between reasoning and attention beta correlates in that few components in some individuals (overall below 30%) were not satisfactorily explained by the complementary task, and if those could be considered “task-specific”, their scalp distribution and estimated cortical sources were not common across subjects. These findings, discussed along with those from task-related physiological studies based on individual data (and classical clinical observations), are compatible with the increasingly accepted view that individuals may use largely different sets of cortical association areas to perform a given task, but also with the new idea that those individual sets do not change much across tasks that differ in major psychological processes.
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