Scalable Biologically Inspired Neural Networks with Spike Time Based Learning

This paper describes the software and algorithmic issues involved in developing scalable large-scale biologically inspired spiking neural networks. These neural networks are useful in object recognition and signal processing tasks, but will also be useful in simulations to help understand the human brain. The software is written using object oriented programming and is very general and usable for processing a wide range of sensor data and for data fusion.

[1]  Juliette Gardner.  Genesis , 1985 .

[2]  Lyle N. Long,et al.  The critical need for software engineering education , 2008 .

[3]  L. Abbott,et al.  Competitive Hebbian learning through spike-timing-dependent synaptic plasticity , 2000, Nature Neuroscience.

[4]  Lyle N. Long,et al.  Scalable Massively Parallel Artificial Neural Networks , 2005, J. Aerosp. Comput. Inf. Commun..

[5]  D. Wilkin,et al.  Neuron , 2001, Brain Research.

[6]  勇一 作村,et al.  Biophysics of Computation , 2001 .

[7]  Lyle N. Long,et al.  Object-oriented unsteady vortex lattice method for flapping flight , 2004 .

[8]  Sandy Lovie.  How the mind works , 1980, Nature.

[9]  Lyle N. Long,et al.  A parallel, object-oriented unsteady vortex lattice method for flapping flight , 2004 .

[10]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[11]  Fiona E. N. LeBeau,et al.  Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts. , 2005, Journal of neurophysiology.

[12]  Ankur Gupta,et al.  Biologically-inspired spiking neural networks with Hebbian learning for vision processing , 2008 .

[13]  Vivien A. Casagrande,et al.  Biophysics of Computation: Information Processing in Single Neurons , 1999 .

[14]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1952, The Journal of physiology.

[15]  William E. Higgins,et al.  Gabor filter design for multiple texture segmentation , 1996 .

[16]  J. Knott.  The organization of behavior: A neuropsychological theory , 1951 .

[17]  Lyle N. Long,et al.  The Direct Simulation of Detonations , 2006 .

[18]  Kunihiko Fukushima,et al.  Neocognitron: A hierarchical neural network capable of visual pattern recognition , 1988, Neural Networks.

[19]  Jilles Vreeken,et al.  Spiking neural networks, an introduction , 2003 .

[20]  C. Koch.  The quest for consciousness : a neurobiological approach , 2004 .

[21]  G. Bi,et al.  Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.

[22]  Lyle N. Long,et al.  Character Recognition using Spiking Neural Networks , 2007, 2007 International Joint Conference on Neural Networks.

[23]  Lyle N. Long,et al.  Control of a Six-Legged Mobile Robot Using the Soar Cognitive Architecture , 2008 .

[24]  D. O. Hebb,et al.  The organization of behavior , 1988 .

[25]  D. Dennett.  Darwin's Dangerous Idea: Evolution and the Meanings of Life , 1995 .