A biologically inspired spiking neural network model of the auditory midbrain for sound source localisation

  • Authors:

  • Jindong Liu;David Perez-Gonzalez;Adrian Rees;Harry Erwin;Stefan Wermter

  • Affiliations:

  • School of Computing and Technology, University of Sunderland, Sunderland SR6 0DD, UK;Institute of Neuroscience, The Medical School, Newcastle University, Newcastle upon Tyne NE2 4HH, UK;Institute of Neuroscience, The Medical School, Newcastle University, Newcastle upon Tyne NE2 4HH, UK;School of Computing and Technology, University of Sunderland, Sunderland SR6 0DD, UK;Department of Informatics, University of Hamburg, 22527 Hamburg, Germany

  • Venue:
  • Neurocomputing
  • Year:
  • 2010

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Abstract

This paper proposes a spiking neural network (SNN) of the mammalian subcortical auditory pathway to achieve binaural sound source localisation. The network is inspired by neurophysiological studies on the organisation of binaural processing in the medial superior olive (MSO), lateral superior olive (LSO) and the inferior colliculus (IC) to achieve a sharp azimuthal localisation of a sound source over a wide frequency range. Three groups of artificial neurons are constructed to represent the neurons in the MSO, LSO and IC that are sensitive to interaural time difference (ITD), interaural level difference (ILD) and azimuth angle (@q), respectively. The neurons in each group are tonotopically arranged to take into account the frequency organisation of the auditory pathway. To reflect the biological organisation, only ITD information extracted by the MSO is used for localisation of low frequency (