DocumentCode
315407
Title
A biologically derived model for perception to serve as an interface between an intelligent system and its environments
Author
Freeman, Walter J.
Author_Institution
Dept. of Molecular & Cell Biol., California Univ., Berkeley, CA, USA
Volume
1
fYear
1997
fDate
27-23 May 1997
Firstpage
12
Abstract
There are two main levels of neural function to be modeled with appropriate state variables and operations. Microscopic activity is seen in the fraction of the variance of single neuron pulse trains (>99.9%) that is largely random and uncorrelated with pulse trains of other neurons in the neuropil. Macroscopic activity is revealed in the >0.1% of the total variance of each neuron that is covariant with all other neurons in neuropil comprising a population. It is observed in dendritic potentials recorded as surface EEGs. The “spontaneous” background activity of neuropil at both levels arises from mutual excitation within a population of excitatory neurons. Its governing point attractor is set by the macroscopic state, which acts as an order parameter to regulate the contributing neurons. The point attractor manifests a homogeneous field of white noise, which can be modeled by a continuous time state variable for pulse density. Neuropil comprises both excitatory and inhibitory neurons
Keywords
brain models; neural nets; continuous time state variable; excitatory neurons; homogeneous field; intelligent system; mutual excitation; neural function; neuron pulse trains; neuropil; perception; state variables; Biological system modeling; Brain modeling; Chaos; Difference equations; Integrodifferential equations; Intelligent systems; Microscopy; Nervous system; Neurons; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge-Based Intelligent Electronic Systems, 1997. KES '97. Proceedings., 1997 First International Conference on
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-3755-7
Type
conf
DOI
10.1109/KES.1997.616846
Filename
616846
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