Article ID Journal Published Year Pages File Type
6272226 Neuroscience 2015 11 Pages PDF
Abstract

•EEG reveals differential temporal dynamics of network activation in a visuospatial and color-judgment control task.•During visuospatial judgment and color judgment the same cortical networks get activated.•Task-specific network activations are mainly characterized by differential timing in later processing stages.•The described temporal dynamics can serve as a baseline for changes in network activation in clinical conditions.

Recent functional magnetic resonance imaging (fMRI) studies consistently revealed contributions of fronto-parietal and related networks to the execution of a visuospatial judgment task, the so-called “Clock Task”. However, due to the low temporal resolution of fMRI, the exact cortical dynamics and timing of processing during task performance could not be resolved until now. In order to clarify the detailed cortical activity and temporal dynamics, 14 healthy subjects performed an established version of the “Clock Task”, which comprises a visuospatial task (angle discrimination) and a control task (color discrimination) with the same stimulus material, in an electroencephalography (EEG) experiment. Based on the time-resolved analysis of network activations (microstate analysis), differences in timing between the angle compared to the color discrimination task were found after sensory processing in a time window starting around 200 ms. Significant differences between the two tasks were observed in an analysis window from 192 ms to 776 ms. We divided this window in two parts: an early phase - from 192 ms to ∼440 ms, and a late phase - from ∼440 ms to 776 ms. For both tasks, the order of network activations and the types of networks were the same, but, in each phase, activations for the two conditions were dominated by differing network states with divergent temporal dynamics. Our results provide an important basis for the assessment of deviations in processing dynamics during visuospatial tasks in clinical populations.

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