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Synchronization and coordination of sequences in two neural ensembles.

作者信息

Venaille Antoine, Varona Pablo, Rabinovich Mikhail I

机构信息

Institute for Nonlinear Science. University of California, San Diego, 9500 Gilman Dr. 0402, La Jolla, California 92093, USA.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Jun;71(6 Pt 1):061909. doi: 10.1103/PhysRevE.71.061909. Epub 2005 Jun 21.

DOI:10.1103/PhysRevE.71.061909
PMID:16089767
Abstract

There are many types of neural networks involved in the sequential motor behavior of animals. For high species, the control and coordination of the network dynamics is a function of the higher levels of the central nervous system, in particular the cerebellum. However, in many cases, especially for invertebrates, such coordination is the result of direct synaptic connections between small circuits. We show here that even the chaotic sequential activity of small model networks can be coordinated by electrotonic synapses connecting one or several pairs of neurons that belong to two different networks. As an example, we analyzed the coordination and synchronization of the sequential activity of two statocyst model networks of the marine mollusk Clione. The statocysts are gravity sensory organs that play a key role in postural control of the animal and the generation of a complex hunting motor program. Each statocyst network was modeled by a small ensemble of neurons with Lotka-Volterra type dynamics and nonsymmetric inhibitory interactions. We studied how two such networks were synchronized by electrical coupling in the presence of an external signal which lead to winnerless competition among the neurons. We found that as a function of the number and the strength of connections between the two networks, it is possible to coordinate and synchronize the sequences that each network generates with its own chaotic dynamics. In spite of the chaoticity, the coordination of the signals is established through an activation sequence lock for those neurons that are active at a particular instant of time.

摘要

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