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Tonotopic representation of auditory responses using self-organizing maps

Authors
Journal
Mathematical and Computer Modelling
0895-7177
Publisher
Elsevier
Publication Date
Identifiers
DOI: 10.1016/0895-7177(95)00107-d
Keywords
  • Bat Echolocation
  • Biosonar
  • Artificial Neural Networks
  • Self-Organizing Maps
  • Auditory Systems
  • Tonotopic Organization
Disciplines
  • Biology
  • Computer Science
  • Mathematics

Abstract

Abstract A self-organizing neural network model called CORMAP has been developed to represent the tonotopic organization of the auditory cortex of an FM bat. The map self-organizes purely based on external input stimulus parameters. The weights in the competitive layer self-organizes into a topological map of the input space. This process in turn allows the representation of the similarity of inputs into the proximity of excited neurons. An additional output layer interconnected with the self-organized layer in the CORMAP model provides a mechanism to observe the functional characteristics of individual neurons. The CORMAP model is biologically motivated and the functional characteristics of the neuron used in the self-organizing layer were obtained directly from neurophysiological experiments. CORMAP demonstrates a plausible model for representing cortical activities in response to external stimulus inputs.

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