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A spiking neural network model of the medial superior olive using spike timing dependent plasticity for sound localization

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Glackin, Brendan, Wall, Julie, McGinnity, TM, Maguire, LP and McDaid, Liam (2010) A spiking neural network model of the medial superior olive using spike timing dependent plasticity for sound localization. Frontiers in computational Neuroscience, 4 (18). pp. 1-16. [Journal article]


URL: http://www.frontiersin.org/Computational_Neuroscience/10.3389/fncom.2010.00018/abstract

DOI: doi:10.3389/fncom.2010.00018


Sound localization can be defined as the ability to identify the position of an input sound source and is considered a powerful aspect of mammalian perception. For low frequency sounds, i.e., in the range 270 Hz–1.5 KHz, the mammalian auditory pathway achieves this by extracting the InterauralTime Difference between sound signals being received by the left and right ear.This processing is performed in a region of the brain known as the Medial Superior Olive (MSO). This paper presents a Spiking Neural Network (SNN) based model of the MSO. The network model is trained using the SpikeTiming Dependent Plasticity learning rule using experimentally observed Head RelatedTransfer Function data in an adult domestic cat.The results presented demonstrate how the proposed SNN model is able to perform sound localization with an accuracy of 91.82% when an error tolerance of ␣10␣ is used. For angular resolutions down to 2.5␣, it will be demonstrated how software based simulations of the model incur significant computation times. The paper thus also addresses preliminary implementation on a Field Programmable Gate Array based hardware platform to accelerate system performance.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:17348
Deposited By:Professor Liam Maguire
Deposited On:02 Mar 2011 14:33
Last Modified:15 Jun 2011 11:09

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