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Inhibition-Based Rhythms: Experimental and Mathematical Observations on Network Dynamics (2000)
| Citations: | 51 - 7 self |
BibTeX
@MISC{Whittington00inhibition-basedrhythms:,
author = {M. A. Whittington and R. D. Traub and N. Kopell and B. Ermentrout},
title = {Inhibition-Based Rhythms: Experimental and Mathematical Observations on Network Dynamics},
year = {2000}
}
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Abstract
An increasingly large body of data exists which demonstrates that oscillations of frequency 12#80 Hz are a consequence of, or are inextricably linked to, the behaviour of inhibitory interneurons in the central nervous system. Z.Z. Z. This frequency range covers the EEG bands beta 1 (12-20 Hz), beta 2 (20-30 Hz) and gamma (30-80 Hz). The pharmacological profile of both spontaneous and sensory-evoked EEG potentials reveals a very strong influence on Z these rhythms by drugs which have direct effects on GABA receptor-mediated synaptic transmission general A .Z. anaesthetics, sedative#hypnotics or indirect effects on inhibitory neuronal function opiates, ketamine . In addition, a number of experimental models of, in particular, gamma-frequency oscillations, have revealed both common denominators for oscillation generation and function, and subtle differences in network dynamics between the different frequency ranges. Powerful computer and mathematical modelling techniques based around both clinical and experimental observations have recently provided invaluable insight into the behaviour of large networks of interconnected neurons. In particular, the mechanistic profile of oscillations generated as an emergent property of such networks, and the mathematical derivation of this complex phenomenon have much to contribute to our understanding of how and why neurons oscillate. This review will provide the reader with a brief outline of the basic properties of inhibition-based oscillations in the CNS by combining research from laboratory models, large-scale neuronal network simulations, and mathematical analysis.
Keyphrases
network dynamic mathematical observation inhibition-based rhythm mathematical modelling technique frequency range laboratory model gamma-frequency oscillation sedative hypnotic large network powerful computer emergent property invaluable insight direct effect 12-20 hz mathematical derivation gaba receptor-mediated synaptic transmission inhibition-based oscillation inhibitory interneurons central nervous system subtle difference interconnected neuron inhibitory neuronal function opiate large-scale neuronal network simulation data exists experimental observation complex phenomenon mathematical analysis mechanistic profile indirect effect oscillation generation 30-80 hz basic property large body brief outline sensory-evoked eeg potential 20-30 hz pharmacological profile experimental model strong influence common denominator different frequency
