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Brian hears: online auditory processing using vectorization over channels

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Title: Brian hears: online auditory processing using vectorization over channels
Author(s): Fontaine, B
Goodman, DF
Benichoux, V
Brette, R
Item Type: Journal Article
Abstract: The human cochlea includes about 3000 inner hair cells which filter sounds at frequencies between 20 Hz and 20 kHz. This massively parallel frequency analysis is reflected in models of auditory processing, which are often based on banks of filters. However, existing implementations do not exploit this parallelism. Here we propose algorithms to simulate these models by vectorizing computation over frequency channels, which are implemented in "Brian Hears," a library for the spiking neural network simulator package "Brian." This approach allows us to use high-level programming languages such as Python, because with vectorized operations, the computational cost of interpretation represents a small fraction of the total cost. This makes it possible to define and simulate complex models in a simple way, while all previous implementations were model-specific. In addition, we show that these algorithms can be naturally parallelized using graphics processing units, yielding substantial speed improvements. We demonstrate these algorithms with several state-of-the-art cochlear models, and show that they compare favorably with existing, less flexible, implementations.
Publication Date: 22-Jul-2011
Date of Acceptance: 30-Jun-2011
URI: http://hdl.handle.net/10044/1/40617
DOI: http://dx.doi.org/10.3389/fninf.2011.00009
ISSN: 1662-5196
Publisher: Frontiers Media
Journal / Book Title: Frontiers in Neuroinformatics
Volume: 5
Copyright Statement: © 2011 Fontaine, Goodman, Benichoux and Brette. This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with.
Keywords: Brian
GPU
Python
auditory filter
vectorization
Publication Status: Published
Article Number: 9
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering



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