Numerically efficient and biophysically accurate neuroprocessing platform

Juan Carlos Moctezuma, Joseph P. McGeehan, Jose Luis Nunez-Yanez

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

2 Citations (Scopus)

Abstract

This paper presents a neuroprocessing system based on floating point arithmetic and a multi-core architecture in which optimized neuroprocessor cores model with biophysical accuracy different neuron sections like soma, dendrite and synapse. The system is focused on extracting detail information on the ion-channel dynamics and membrane voltage changes in single neurons (or groups of them) rather than implementing large neural networks; this details information is important from a neuroscience point of view. The neuroprocessors use numerical methods and floating point accuracy to solve the differential equations to create neuron representations based on the biological-compatible Hodking-Huxley and Traub models. The advanced extensible interface (AXI) interconnects the neuroprocessors to a central programmable processor in charge of monitoring, parameter loading and data distribution. The exponential operations involved in the modeling of the membrane voltage are optimized with floating-point look-up-tables. This approach reduces the computational time by 70% and complexity by around 40%. The accuracy and computation capabilities of the system are validated with experiments that involve the detection and discrimination of temporal input sequences, which is a fundamental brain function that underlies perception, cognition and motor output. Finally, a complete FPGA-PC platform is developed, the FPGA-based system interacts with a software interface in order to configure and receive results from the system running in hardware.

Original languageEnglish
Title of host publication2013 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2013
PublisherIEEE Computer Society
ISBN (Print)9781479920792
DOIs
Publication statusPublished - 1 Jan 2013
Event2013 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2013 - Cancun, United Kingdom
Duration: 9 Dec 201311 Dec 2013

Conference

Conference2013 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2013
CountryUnited Kingdom
CityCancun
Period9/12/1311/12/13

Keywords

  • Biophysical accurate neurons
  • Floating point FPGA arithmetic
  • FPGA
  • Multi-core architecture
  • Neuro-emulator

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