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Introduction

The UNT Center for Network Neuroscience was established January 1, 1987 to facilitate transdisciplinary studies of the self-organization and electrophysiological dynamics of mammalian networks in cell culture. From the beginning, investigations have focused on exploration of basic mechanisms and strategies underlying the phenomena of pattern generation, recognition, storage, and fault tolerance in neuronal ensembles. Most investigations use long-term multichannel monitoring of action potential (spike) traffic in spontaneously active networks.

Disciplines Represented

The CNNS is unique in its balanced experimental and theoretical approach to neuronal networks. The Center is a transdepartmental and interdisciplinary organization of scientists active in biology, biochemistry, computer science, mathematics, neuroscience, physics, and psychology, who have common interests in basic neurobiological research and its application to information processing, behavior, neural modeling, non-linear dynamics, computer design, and microelectronics.

 

    Network derived from dissociated murine spinal tissue growing on a 64-electrode recording matrix. Electrodes are spaced 40 µm laterally and 200 µm between rows. Indium-tin oxide conductors are10 µm wide.

 

Experimental Strategy

Our basic experimental strategy is to seed dissociated cells from specific embryonic neural tissues onto beds of substrate integrated, photoetched microelectrodes. A matrix of 64 shallow electrode craters in a 1 sq. mm area serves to monitor much of the spike traffic within the network and often provides a statistical sample of activity from neuronal ensembles that are generally 2 to 4 mm in diameter (cf Gross and Kowalski, 1991; Gross, 1994).

Applications

Application of spontaneously active networks to the fields of neurotoxicology, drug development, and biosensors are in progress. These experimental platforms are well suited for the rapid screening of compounds and allow the evaluation of physiological effects through changes in the spontaneous activity patterns.

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