Mathematics Department, University of Chicago, USA
Wednesday 23 September 2009
Seminar Room B10 (Basement)
Alexandra House, 17 Queen Square, London, WC1N 3AR
A stochastic model of large-scale brain activity
We have recently found a way to describe large-scale neural activity in terms of non -equilibrium statistical mechanics. This allows us to calculate perturbatively the effects of fluctuations and correlations on neural activity. Major results of this formulation include a role for critical branching, and the demonstration that there exist non-equilibrium phase transitions in neocortical activity which are in the same universality class as directed percolation. This result leads to explanations for the origin of many of the scaling laws found in LFP, EEG, fMRI, and in ISI distributions, and provides a possible explanation for the origin of various brain waves. It also leads to ways of calculating how correlations can affect neocortical activity, and therefore provides a new tool for investigating the connections between neural dynamics, cognition and behavior.