PAX: A mixed hardware/software simulation
platform for spiking neural networks.
Renaud S, Tomas J, Lewis S, Bornat Y, Daouzli A, Rudolph M,
Destexhe A and Saïghi S.
Neural Networks 23: 905-916, 2010.
Many hardware-based solutions now exist for the simulation of
bio-like neural networks. Less conventional than software-based
systems, these types of simulators generally combine digital and
analog forms of computation. In this paper we present a mixed
hardware-software platform, specifically designed for the
simulation of spiking neural networks, using conductance-based
models of neurons and synaptic connections with dynamic
adaptation rules (Spike-Timing-Dependent Plasticity). The neurons
and networks are configurable, and are computed in "biological
real time" by which we mean that the difference between simulated
time and simulation time is guaranteed lower than 50 ms. After
presenting the issues and context involved in the design and use of
hardware-based spiking neural networks, we describe the analog
neuromimetic integrated circuits which form the core of the
platform. We then explain the organization and computation
principles of the modules within the platform, and present
experimental results which validate the system. Designed as a tool
for computational neuroscience, the platform is exploited in
collaborative research projects together with neurobiology and
computer science partners.
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