MIT CSAIL Talk: Modularity, synchronization, and what we may learn from the brain

Speaker: Jean-Jacques Slotine , Nonlinear Systems Laboratory, MIT
Date: Tuesday, October 25 2005

Although neurons as computational elements are 7 orders of magnitude slower than their artificial counterparts, the primate brain grossly outperforms robotic algorithms in all but the most structured tasks. Parallelism alone is a poor explanation, and much recent functional modelling of the central nervous system focuses on its modular, heavily feedback-based computational architecture, the result of accumulation of subsystems throughout evolution. We discuss this architecture from a global stability and convergence point of view. We then study synchronization as a model of computations at different scales in the brain, such as pattern matching, temporal binding of sensory data, and mirror neuron response. Finally, we derive a simple condition for a general dynamical system to globally converge to a regime where multiple groups of fully synchronized elements coexist. Applications of such "polyrhythms" to some classical questions in robotics and systems neuroscience are discussed.