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Special Physics Colloquium: Professor Alessandro Villa
(Physics Lecture Series) University of Lausanne, Switzerland, Neuroheuristic Research Group
“Spatiotemporal Patterns of Activity in Cerebral Neural Networks: a Dynamical Systems Perspective”
The simultaneous recording of the time series formed by the timing of neuronal discharges produced by a cell assembly reveals important features of the dynamic of information processing in the brain. Experimental evidence of firing sequences with precision of few milliseconds over intervals lasting hundreds of milliseconds have suggested that particular topologies of converging/diverging chains of neuronal assemblies may propagate the activity with the necessary time accuracy. The central hypothesis for brain attractors is that, once activated, the network behaviour is maintained by a continuous reentry of activity. This involves strong correlations between neuronal activities in the network and a high incidence of repeating firing patterns therein, being generated by the underlying attractors. Recurring firing patterns without a specific association to a specific sensory or behavioral event may be viewed as ‘spurious patterns’ generated by ‘spurious attractors’. On the contrary, spatiotemporal firing patterns in behaving animals, from rats to primates, where preferred firing sequences can be associated to specific types of stimuli or behaviours can be viewed as ‘meaningful patterns’ associated with ‘meaningful attractors’. Simulation studies of critical phases of brain development suggest the emergence of stimulus-driven cell assemblies that will form the ‘wiring’ of the adult brain out of randomly connected large scale networks. These results are presented from the viewpoint of dynamical systems and chaotic attractors.