The Topography of Non-Linear Cortical Dynamics at Rest, in Mental Calculation and Moving Shape Perception

Differential cortical activation by cognitive processing was studied using dimensional complexity, a measure derived from nonlinear dynamics that indicates the degrees of freedom (complexity) of a dynamic system. We examined the EEG of 32 healthy subjects at rest, during a visually presented calculation task, and during a moving shape perception task. As a nonlinear measure of connectivity, the mutual dimension of selected electrode pairs was used. The first Lyapunov coefficient was also calculated. Data were tested for non-linearity using a surrogate data method and compared to spectral EEG measures (power, coherence). Surrogate data testing confirmed the presence of nonlinear structure in the data. Cognitive activation led to a highly significant rise in dimensional complexity. While both tasks activated central, parietal and temporal areas, mental arithmetic showed frontal activation and an activity maximum at T3, while the moving shape task led to occipital activation and a right parietal activity maximum. Analysis of mutual dimension showed activation of a bilateral temporal-right frontal network in calculation. The Lyapunov coefficent showed clear topographic variation, but was not significantly changed by mental tasks (p<.09). While dimensional complexity was almost unrelated to power values, nonlinear (mutual dimension) and linear (coherence) measures of connectivity shared up to 37% of variance. Data are interpreted in terms of increased cortical complexity as a result of recruitment of asynchronously active, distributed neuronal assemblies in cognition. The topography of nonlinear dynamics are related to neuropsychological and neuroimaging findings on mental calculation and moving shape perception.