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Titolo:
Deterministic dynamics emerging from a cortical functional architecture
Autore:
Siegel, RM; Read, HL;
Indirizzi:
Rutgers State Univ, Ctr Mol & Behav Neurosci, Newark, NJ 07102 USA RutgersState Univ Newark NJ USA 07102 hav Neurosci, Newark, NJ 07102 USA
Titolo Testata:
NEURAL NETWORKS
fascicolo: 6-7, volume: 14, anno: 2001,
pagine: 697 - 713
SICI:
0893-6080(200107/09)14:6-7<697:DDEFAC>2.0.ZU;2-K
Fonte:
ISI
Lingua:
ENG
Soggetto:
CAT VISUAL-CORTEX; MUSCIMOL BINDING-SITES; NEURONAL SPIKE TRAINS; STRIATE CORTEX; HORIZONTAL CONNECTIONS; INHIBITORY CONNECTIONS; ORGANIZING CENTERS; ONGOING ACTIVITY; EXCITABLE MEDIA; MACAQUE MONKEY;
Keywords:
chaos; cortex; oscillations; perception; population dynamics; vision;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
98
Recensione:
Indirizzi per estratti:
Indirizzo: Siegel, RM Rutgers State Univ, Ctr Mol & Behav Neurosci, 197 Univ Ave, Newark, NJ 07102 USA Rutgers State Univ 197 Univ Ave Newark NJ USA 07102 J 07102 USA
Citazione:
R.M. Siegel e H.L. Read, "Deterministic dynamics emerging from a cortical functional architecture", NEURAL NETW, 14(6-7), 2001, pp. 697-713

Abstract

Cerebral cortex has a range of interconnected functional architectures. Some appear random and without structure, while others are geometrical. Although the biological details certainly constrain spatial temporal patterns inneural networks, the influence that the laws of deterministic dynamics bring to bear on even isolated simple geometries are unknown. Layer HMI of primary visual cortex has long range horizontal connections with projections to and from other layers. The long range excitatory connections were modeledin isolation as an isolated laterally connected functional architecture. The Hodgkin-Huxley or Pinsky-Rinzel equations were used to simulate the neuronal elements. Waves of activity could propagate through the functional architecture; depending on the synaptic kinetics, the system could settle downinto quiescence, oscillations, or seemingly random behavior. Order could be found in random-looking behavior by the application of techniques from chaos theory. Furthermore, the range and transitions of the temporal patternsin the modeled collection of neurons are similar to those found in other non-linear systems. The possibility that the temporal patterns of neurons insitu are also constrained by these mathematical laws is discussed. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Documento generato il 21/01/20 alle ore 07:03:48