An Oscillatory Neural Network Model for Birdsong Learning and Generation

  • Maya Manaithunai
  • Srinivasa Chakravarthy
  • Ravindran Balaraman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6353)

Abstract

We present a model of bird song production in which the motor control pathway is modeled by a trainable network of oscillators and the Anterior Forebrain Pathway (AFP) is modeled as a stochastic system. We hypothesize 1) that the songbird learns only evaluations of songs during the sensory phase; 2) that the AFP plays a role analogous to the Explorer, a key component in Reinforcement Learning (RL); 3) the motor pathway learns the song by combining the evaluations (Value information) stored from the sensory phase, and the exploratory inputs from the AFP in a temporal stage-wise manner. Model performance from real birdsong samples is presented.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Maya Manaithunai
    • 1
  • Srinivasa Chakravarthy
    • 1
  • Ravindran Balaraman
    • 2
  1. 1.Department of BiotechnologyIndian Institute of Technology MadrasChennaiIndia
  2. 2.Department of Computer ScienceIndian Institute of Technology MadrasChennaiIndia

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