Author : J. Meribah Jasmine 1
Date of Publication :8th November 2017
Abstract: This paper details the code development, implementation and testing of basic behavior and characterization of the biological neuron model in FPGA environment. In this work, the real behavior and function of the biological human neuron were studied and implemented as an artificial neuron in VHDL environment. To develop the biological neuron model, Perceptron algorithm was employed. The artificial biological neuron contains sub-blocks such as a timer, alpha, addition & comparison and inhibits blocks. Initially, the sub-blocks were developed individually and combined together according to the biological neuron model design. Simulation codes for the artificial neuron model were developed using VHDL language. Finally, the developed artificial neuron model was implemented on ANVYL SPARTAN-6 XC6SLX45 CSG484 package FPGA kit and the outputs were exhibited as simulation output in the PC monitor as well as in the LED indicators of the Anvyl Board. This work helps to learn the strategies of developing codes for neuronal behavior study using FPGA and VHDL language, which will be extended to advanced applications like computational neuroscience and artificial intelligence
Reference :
-
- Richard Morris and Marianne Fillenz, “Neuroscience: the Science of the Brain”, The British Neuroscience Association, 2003, pp. 1-4, ISBN: 0-9545204--0-8.
- WulframGerstner , Werner M. Kistler , Richard Naud, Liam Paninski, “Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition”, Cambridge University Press, July 2014, ISBN-13: 978-1107635197, ISBN-10: 1107635195.
- M.L. Hinesa and N.T. Carnevale,“Discrete event simulation in the Neuron”, Neurocomputing, Elsevier B.V., pp. 1117-1122, 2004.
- J.A. Bailey et.al., “Behavioral simulation and synthesis of biological neuron systems using synthesizable VHDL”, Neurocomputing, Elsevier B.V., pp. 2392-2406, 2011.
- R.R. Borges et.al., “Effects of the spiketimingdependent plasticity on the synchronisation in a random Hodgkin-Huxley neuronal network”, Communications in Nonlinear Science and Numerical Simulation, Elsevier B.V., pp. 12-22, 2015.
- Fernando Pérez-Peña et.al., “Inter-spikesintervals exponential and gamma distributions study of neuron firing rate for SVITE motor control model on FPGA”, Neurocomputing, Elsevier B.V., pp. 496-504, 2014.
- Javier Gomez Casado, “Implementation of an artificial neuron in VHDL”, 2008.
- Peter Tino etal., “Artificial Neural Network Models”, Springer handbook of computational intelligence, 1997, Volume 8, Issue 3, pp. 456- 457, ISBN: 978-3-662-43504-5.
- John D. Zakis and Brian J. Lithgow, “Neuron Modeling using VHDL”, 1999
- Xilinx ISE: https: // en. wikipedia . org/ wiki/ Xilinx _ ISE
- Anvyl™ FPGA Board Reference Manual: https://reference.digilentinc.com/_media/anvyl:a nvyl_rm.pdf