title: Biologically inspired load balancing mechanism in neocortical competitive learning.
abstract: A unique delayed self-inhibitory pathway mediated by layer 5 Martinotti Cells was studied in a biologically inspired neural network simulation. Inclusion of this pathway along with layer 5 basket cell lateral inhibition caused balanced competitive learning, which led to the formation of neuronal clusters as were indeed reported in the same region. Martinotti pathway proves to act as a learning "conscience," causing overly successful regions in the network to restrict themselves and let others fire. It thus spreads connectivity more evenly throughout the net and solves the "dead unit" problem of clustering algorithms in a local and biologically plausible manner.
authors.affiliation: The Leslie and Susan Gonda Multidisciplinary Brain Research Center, Bar-Ilan University Ramat-Gan, Israel.
authors.forename: Amir
authors.initials: A
authors.lastname: Tal
authors.affiliation: The Leslie and Susan Gonda Multidisciplinary Brain Research Center, Bar-Ilan University Ramat-Gan, Israel.
authors.forename: Noam
authors.initials: N
authors.lastname: Peled
authors.affiliation: The Biologically Inspired Neural and Dynamical Systems Laboratory, Computer Science Department, University of Massachusetts Amherst, MA, USA.
authors.forename: Hava T
authors.initials: HT
authors.lastname: Siegelmann
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D007858:Learning / Q000502:physiology*; D008959:Models, Neurological; D019579:Neocortex / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D013569:Synapses / Q000502:physiology
keywords: STDP learning; brain circuitry development; competitive learning; dead units problem; layer 5 pyramidal cells