A Spiking Neural Network Model of the Medial Superior Olive using Spike Timing Dependent Plasticity for Sound Localisation
Glackin, B., Wall, J., McGinnity, T.M., Maguire, L.P. and McDaid, L.J. 2010. A Spiking Neural Network Model of the Medial Superior Olive using Spike Timing Dependent Plasticity for Sound Localisation. Frontiers in Computational Neuroscience. 4 (18), pp. 1-16.
|Authors||Glackin, B., Wall, J., McGinnity, T.M., Maguire, L.P. and McDaid, L.J.|
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 Interaural Time 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 Spike Timing Dependent Plasticity learning rule using experimentally observed Head Related Transfer 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 degrees is used. For angular resolutions down to 2.5 degrees , 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.
|Keywords||sound localisation; MSO; SNN; STDP|
|Journal||Frontiers in Computational Neuroscience|
|Journal citation||4 (18), pp. 1-16|
|Web address (URL)||http://journal.frontiersin.org/article/10.3389/fncom.2010.00018/abstract|
|03 Aug 2010|
|Publication process dates|
|Deposited||21 Oct 2015|
|Copyright information||This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission.|
1views this month
1downloads this month