title: Learning and stabilization of winner-take-all dynamics through interacting excitatory and inhibitory plasticity.
abstract: Winner-Take-All (WTA) networks are recurrently connected populations of excitatory and inhibitory neurons that represent promising candidate microcircuits for implementing cortical computation. WTAs can perform powerful computations, ranging from signal-restoration to state-dependent processing. However, such networks require fine-tuned connectivity parameters to keep the network dynamics within stable operating regimes. In this article, we show how such stability can emerge autonomously through an interaction of biologically plausible plasticity mechanisms that operate simultaneously on all excitatory and inhibitory synapses of the network. A weight-dependent plasticity rule is derived from the triplet spike-timing dependent plasticity model, and its stabilization properties in the mean-field case are analyzed using contraction theory. Our main result provides simple constraints on the plasticity rule parameters, rather than on the weights themselves, which guarantee stable WTA behavior. The plastic network we present is able to adapt to changing input conditions, and to dynamically adjust its gain, therefore exhibiting self-stabilization mechanisms that are crucial for maintaining stable operation in large networks of interconnected subunits. We show how distributed neural assemblies can adjust their parameters for stable WTA function autonomously while respecting anatomical constraints on neural wiring.
authors: Institute of Neuroinformatics, University of Zurich and ETH Zurich Zurich, Switzerland.
authors: Jonathan
authors: J
authors: Binas
authors: Department of Neurosurgery and Department of Neurology, Cedars-Sinai Medical Center Los Angeles, CA, USA ; Computation and Neural Systems Program, Division of Biology and Biological Engineering, California Institute of Technology Pasadena, CA, USA.
authors: Ueli
authors: U
authors: Rutishauser
authors: Institute of Neuroinformatics, University of Zurich and ETH Zurich Zurich, Switzerland.
authors: Giacomo
authors: G
authors: Indiveri
authors: Institute of Neuroinformatics, University of Zurich and ETH Zurich Zurich, Switzerland.
authors: Michael
authors: M
authors: Pfeiffer
keywords: canonical microcircuits; competition; contraction theory; inhibitory plasticity; plasticity; self-organization; winner-take-all