A biophysically accurate floating point somatic neuroprocessor

Y Zhang, JL Nunez-Yanez, JP McGeehan, EM Regan, S Kelly

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

10 Citations (Scopus)
633 Downloads (Pure)

Abstract

Biophysically accurate neuron models have emerged as a very useful tool for neuroscience research. These models are based on solving differential equations that govern membrane potentials and spike generation. The level of detail that needs to be presented in the model to accurately emulate the behaviour of an organic cell is still an open question, although the timing of the spikes is considered to convey essential information. Models targeting hardware are traditionally based on fixed point implementations and low precision algorithms which incur a significant loss of information. This, in turn, could affect the functionality of a bioelectronic neuroprocessor in an undefined way. In this paper, a 32-bit floating point reconfigurable somatic neuroprocessor is presented targeting an FPGA device for real-time processing. For each individual neuron, the dynamics of ionic channels are described by a set of first order kinetic equations. A dedicated CORDIC unit is developed to solve the nonlinear functions that regulate spike generation. The results have been verified using an experimental setup that combines an FPGA device and a digital-to-analogue converter.
Translated title of the contributionA biophysically accurate floating point somatic neuroprocessor
Original languageEnglish
Title of host publicationInternational Conference on Field Programmable Logic and Applications, 2009 (FPL 2009), Prague
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages26 - 31
Number of pages6
ISBN (Print)9781424438921
DOIs
Publication statusPublished - Aug 2009
EventInternational Conference on Field Programmable Logic and Applications - Prague, Czech Republic
Duration: 1 Aug 2009 → …

Publication series

Name
ISSN (Print)19461488

Conference

ConferenceInternational Conference on Field Programmable Logic and Applications
CountryCzech Republic
CityPrague
Period1/08/09 → …

Bibliographical note

Rose publication type: Conference contribution

Additional information: With accompanying conference presentation

Sponsorship: Sponsor acknowledgments for Oversea Research Student Award (ORSAS) and Postgraduate Research Award of University of Bristol and funding supplied by the Micron Foundation (USA)

Terms of use: Copyright © 2009 IEEE. Reprinted from International Conference on Field Programmable Logic and Applications, 2009 (FPL 2009).

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Keywords

  • neuroprocessor
  • floating point
  • neuron models

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