Time-frequency analysis of event related brain potentials elicited with four different cognitive paradigms

Abstract

Event related potentials (ERPs), which reflect fundamental cognitive operations, are generated by the parallel and/or the sequential processing of different neural groups in the brain. In time domain representation of ERPs, temporally overlapping processes are hidden and they cannot be distinguished. However, the surface ERPs can be decomposed into functional neuronal components using time-frequency analysis. The aim of this study is to differentiate the time-frequency components that are related with specific cognitive operations (i.e. signal discrimination, motor response task, motor response inhibition, and context updating) in the auditory ERPs. For this purpose, by making systematic modification in cognitive content of the paradigms, experimental set that consists of four auditory paradigms was designed. ERP reflections of these modifications both in the time domain and in the time-frequency plane were explored in order to assign specific ERP sub-components to specific cognitive processes. Data obtained from 16 healthy volunteers were decomposed by discrete wavelet transform into six sets of wavelet coefficients. Alpha, theta, and delta band coefficients and P200 and P300 measurements of the midline electrodes (Fz, Cz, Pz) that were obtained from individual average ERPs for each stimulus condition were analyzed with five-factor analysis of variance (ANOVA) design. Compared to time domain analysis, results of the time-frequency analysis brought detailed information about the stimulus processing steps in different conditions. However, some components showed varying topographic distributions across the paradigm set. Namely, the wavelet transform could partially decompose these spatially overlapping events into functionally distinct sub-components. Therefore, in order to decompose ERPs more accurately into their functional sub-components, spatial decomposition methods should also be incorporated to the time-frequency analysis.