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A neural circuit for flexible control of persistent behavioral states

Ni Ji, Gurrein K. Madan, Guadalupe I. Fabre, Alyssa Dayan, Casey M. Baker, Ijeoma Nwabudike, Steven W. Flavell
doi: https://doi.org/10.1101/2020.02.04.934547
Ni Ji
1Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Gurrein K. Madan
1Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Guadalupe I. Fabre
1Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Alyssa Dayan
1Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Casey M. Baker
1Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Ijeoma Nwabudike
1Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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Steven W. Flavell
1Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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  • For correspondence: flavell@mit.edu
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ABSTRACT

To adapt to their environments, animals must generate behaviors that are closely aligned to a rapidly changing sensory world. However, behavioral states such as foraging or courtship typically persist over long time scales to ensure proper execution. It remains unclear how neural circuits generate persistent behavioral states while maintaining the flexibility to select among alternative states when the sensory context changes. Here, we elucidate the functional architecture of a neural circuit controlling the choice between roaming and dwelling states, which underlie exploration and exploitation during foraging in C. elegans. By imaging ensemble-level neural activity in freely-moving animals, we identify stable, circuit-wide activity patterns corresponding to each behavioral state. Combining circuit-wide imaging with genetic analysis, we find that mutual inhibition between two antagonistic neuromodulatory systems underlies the persistence and mutual exclusivity of the opposing network states. Through machine learning analysis and circuit perturbations, we identify a sensory processing neuron that can transmit information about food odors to both the roaming and dwelling circuits and bias the animal towards different states in different sensory contexts, giving rise to context-appropriate state transitions. Our findings reveal a potentially general circuit architecture that enables flexible, sensory-driven control of persistent behavioral states.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted September 06, 2020.
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A neural circuit for flexible control of persistent behavioral states
Ni Ji, Gurrein K. Madan, Guadalupe I. Fabre, Alyssa Dayan, Casey M. Baker, Ijeoma Nwabudike, Steven W. Flavell
bioRxiv 2020.02.04.934547; doi: https://doi.org/10.1101/2020.02.04.934547
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A neural circuit for flexible control of persistent behavioral states
Ni Ji, Gurrein K. Madan, Guadalupe I. Fabre, Alyssa Dayan, Casey M. Baker, Ijeoma Nwabudike, Steven W. Flavell
bioRxiv 2020.02.04.934547; doi: https://doi.org/10.1101/2020.02.04.934547

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