Characterising the complexity of neuronal interactions
Human Brain Mapping January 1, 1995 Karl Friston, Giulio Tononi, Olaf Sporns et al. 114 citations
Neuronal interactions in the brain balance two opposing organizational principles: functional segregation, where specialized cortical areas exhibit relatively high entropy (unpredictable dynamics), and functional integration, where distributed influence across areas produces lower entropy overall. A measure of complexity is highest when small brain regions have high entropy on average relative to the whole system's entropy, equivalent to the average mutual information between small regions and the rest of the system. Applied to nonlinear simulations and fMRI data during photic stimulation, complexity peaked between high-dimensional chaotic behavior and low-dimensional orderly behavior—between asynchronous oscillations and global synchrony—confirming the hypothesis.