Inhibition in the nervous system: models of its roles in choice and context determination.
Neural inhibition has often been regarded as playing an important role in stabilizing and tuning the responses of networks of excitatory neurons. Some partial quantitative bases for this qualitative notion are discussed in the context of current neural network models. Such neural network principles as associative learning, competition, opponent processing, and interlevel resonant feedback are explained and related to behavioral and neurochemical data. Tentative analogies of parts of these model networks with specific neurotransmitter systems are explored; these analogies are likely to become more precise as the networks are further refined.
Department of Mathematics, University of Texas, Arlington 76019-0408.
D S
DS
Levine
S J
SJ
Leven
D000818:Animals; D006801:Humans; D008954:Models, Biological; D009433:Neural Inhibition / Q000502:physiology*; D016571:Neural Networks, Computer; D018377:Neurotransmitter Agents / Q000502:physiology
D018377:Neurotransmitter Agents