Fuzzy Segmentation Spatiotemporal Patterns of Cognitive Potential into Microstates

Fuzzy c-mean algorithm was applied to segment spatiotemporal patterns of brainwave into microstates and memberships. The optimal clustering number was estimated with both the trends of objective function and the eigenvalue number of microstates. Comparable spatial patterns may occur at different temporal moments in consideration of fuzzy index that is beyond the limit of serial processing. Those techniques were illustrated with multichannel event-related potentials recorded from 9 subjects during Stroop test. Statistical parametric map of F value suggested that significant task (color decision and word decision) effect involve widespread cortical regions after stimulus onset 280 ms and this result supports the hypothesis that Stroop interference derives from response competition during post-perception stage. As significant stimulus (congruent stimulus and incongruent stimulus) effect only involves several separate visual regions within 100 ms after stimulus presentation, it may reflect top-down attentional regulation.