Journal of Robotics, Networking and Artificial Life

Volume 2, Issue 4, March 2016, Pages 238 - 242

An FPGA-based cortical and thalamic silicon neuronal network

Authors
Takuya Nanami, Takashi Kohno
Corresponding Author
Takuya Nanami
Available Online 1 March 2016.
DOI
https://doi.org/10.2991/jrnal.2016.2.4.8How to use a DOI?
Keywords
silicon neuronal network, neuron model, FPGA, cortex, thalamus.
Abstract

A DSSN model is a neuron model which is designed to be implemented efficiently by digital arithmetic circuit. In our previous study, we expanded this model to support the neuronal activities of several cortical and thalamic neurons; Regular spiking, fast spiking, intrinsically bursting and low-threshold spike. In this paper, we report our implementation of this expanded DSSN model and a kinetic-model-based silicon synapse on an FPGA device. Here, synaptic efficacy was stored in block RAMs, and external connection was realized based on a bus that conform to the address event representation. We simulated our circuit by the Xilinx Vivado design suit.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
2 - 4
Pages
238 - 242
Publication Date
2016/03/01
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
https://doi.org/10.2991/jrnal.2016.2.4.8How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Takuya Nanami
AU  - Takashi Kohno
PY  - 2016
DA  - 2016/03/01
TI  - An FPGA-based cortical and thalamic silicon neuronal network
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 238
EP  - 242
VL  - 2
IS  - 4
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2016.2.4.8
DO  - https://doi.org/10.2991/jrnal.2016.2.4.8
ID  - Nanami2016
ER  -