Real-Time simulations of synchronization in a conductance-based neuronal network with a digital FPGA hardware-core

Authors:
Marcel Beuler;Aubin Tchaptchet;Werner Bonath;Svetlana Postnova;Hans Albert Braun
Affiliations:
Department of Electrical Engineering and Information Technology, University of Applied Sciences, Giessen, Germany;Department of Electrical Engineering and Information Technology, University of Applied Sciences, Giessen, Germany,Institute of Physiology, University of Marburg, Marburg, Germany;Department of Electrical Engineering and Information Technology, University of Applied Sciences, Giessen, Germany;School of Physics, University of Sydney, NSW, Australia,Centre for Integrated Research and Understanding of Sleep, Sydney, NSW, Australia;Institute of Physiology, University of Marburg, Marburg, Germany
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Year:
2012

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Abstract

A FPGA hardware core has been designed for real-time network simulations with up to 400 physiologically realistic, conductance-based neurons of the Hodgkin-Huxley type. A PC-FPGA interface allows easy parameter adjustment and on-line display of basic synchronization measures like field potentials, spike times or color-coded voltages of the complete array. Simulations of 20 ·20 gap-junction coupled 4-dimensional neurons reveal remarkable alterations of the synchronization states and impulse patterns during linearly increasing coupling strengths.