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On The Phase Space Dynamics of Neuronal Systems: Model, Experiments, and Analysis.

Descriptive

Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Genre (authority = RULIB-FS)
Other
Genre (authority = marcgt)
technical report
PhysicalDescription
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application/pdf
Extent
72 p.
Note (type = special display note)
Technical report DCS-TR-373
Name (authority = RutgersOrg-School); (type = corporate)
NamePart
School of Arts and Sciences (SAS) (New Brunswick)
Name (authority = RutgersOrg-Department); (type = corporate)
NamePart
Computer Science (New Brunswick)
TypeOfResource
Text
TitleInfo
Title
On The Phase Space Dynamics of Neuronal Systems:
Model, Experiments, and Analysis.
Abstract (type = abstract)
We investigate the phase space dynamics of local systems of biological neurons in order to deduce the salient computational characteristics of such systems. We develop an abstract physical system that models local systems of spiking biological neurons. The system is based on a limited set of realistic assumptions and in consequence accommodates a wide range of neuronal models. An appropriate instantiation of the system is used to simulate the dynamics of a typical column in the neocortex. The results of the simulations demonstrate that the dynamical behavior of the system is akin to that observed in neurophysiological experiments. Analysis of local properties of flows in the phase space of the system reveals the classic characteristics of a chaotic system, namely, contraction, expansion, and folding. The criterion for the dynamics of the system to be sensitive to initial conditions is identified. Based on physiological parameters it is deduced that (a) periodic orbits in the region of the phase space corresponding to "normal operational conditions" are almost surely (with probability=1) unstable, (b) periodic orbits in the region of the phase space corresponding to "seizure like conditions" are almost surely stable, and (c) trajectories in the region of the phase space corresponding to "normal operational conditions" are almost surely sensitive to initial conditions. Based on these results preliminary conclusions are drawn about the computational nature of neocortical neuronal systems.
Name (type = personal)
NamePart (type = family)
Banerjee
NamePart (type = given)
Arunava
Affiliation
Computer Science (New Brunswick)
Role
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author
OriginInfo
DateCreated (encoding = w3cdtf); (keyDate = yes); (qualifier = exact)
1998-11
RelatedItem (type = host)
TitleInfo
Title
Computer Science (New Brunswick)
Identifier (type = local)
rucore21032500001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T35X2DHD
Genre (authority = ExL-Esploro)
Technical Documentation
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This Item is protected by copyright and/or related rights.You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use.For other uses you need to obtain permission from the rights-holder(s).
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Copyright protected
Availability
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Open
Reason
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Technical

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Document
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1.4
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GPL Ghostscript 9.07
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2018-06-06T12:28:39
DateCreated (point = start); (encoding = w3cdtf); (qualifier = exact)
2018-06-06T12:28:39
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