Feedback from Network States Generates Variability in a Probabilistic Olfactory Circuit
Author(s) -
Andrew Gordus,
Navin Pokala,
Sagi Levy,
Steven W. Flavell,
Cornelia I. Bargmann
Publication year - 2015
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2015.02.018
Subject(s) - odor , neuroscience , interneuron , sensory system , biology , stimulus (psychology) , olfactory system , probabilistic logic , biological neural network , olfaction , premovement neuronal activity , computer science , inhibitory postsynaptic potential , psychology , artificial intelligence , cognitive psychology
Variability is a prominent feature of behavior and is an active element of certain behavioral strategies. To understand how neuronal circuits control variability, we examined the propagation of sensory information in a chemotaxis circuit of C. elegans where discrete sensory inputs can drive a probabilistic behavioral response. Olfactory neurons respond to odor stimuli with rapid and reliable changes in activity, but downstream AIB interneurons respond with a probabilistic delay. The interneuron response to odor depends on the collective activity of multiple neurons-AIB, RIM, and AVA-when the odor stimulus arrives. Certain activity states of the network correlate with reliable responses to odor stimuli. Artificially generating these activity states by modifying neuronal activity increases the reliability of odor responses in interneurons and the reliability of the behavioral response to odor. The integration of sensory information with network states may represent a general mechanism for generating variability in behavior.
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