3 research outputs found
Spiking neuron models of the medial and lateral superior olive for sound localisation
Sound localisation is defined as the ability to identify the position of a sound source. The brain employs two cues to achieve this functionality for the horizontal plane, interaural time difference (ITD) by means of neurons in the medial superior olive (MSO) and interaural intensity difference (IID) by neurons of the lateral superior olive (LSO), both located in the superior olivary complex of the auditory pathway. This paper presents spiking neuron architectures of the MSO and LSO. An implementation of the Jeffress model using spiking neurons is presented as a representation of the MSO, while a spiking neuron architecture showing how neurons of the medial nucleus of the trapezoid body interact with LSO neurons to determine the azimuthal angle is discussed. Experimental results to support this work are presented
A comparison of sound localisation techniques using cross-correlation and spiking neural networks for mobile robotics
This paper outlines the development of a crosscorrelation
algorithm and a spiking neural network (SNN) for
sound localisation based on real sound recorded in a noisy and
dynamic environment by a mobile robot. The SNN architecture
aims to simulate the sound localisation ability of the
mammalian auditory pathways by exploiting the binaural cue
of interaural time difference (ITD). The medial superior olive
was the inspiration for the SNN architecture which required
the integration of an encoding layer which produced
biologically realistic spike trains, a model of the bushy cells
found in the cochlear nucleus and a supervised learning
algorithm. The experimental results demonstrate that
biologically inspired sound localisation achieved using a SNN
can compare favourably to the more classical technique of
cross-correlation