A neural circuit for flexible control of persistent behavioral states

eLife

Steven W Flavell¹  Alyssa Dayan¹  Gurrein K Madan¹  Guadalupe I Fabre¹  Casey M Baker¹  Ni Ji¹  Ijeoma Nwabudike¹  Talya S Kramer² 

[1] Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States;Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States;MIT Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, United States;

关键词: behavioral states;    neuromodulation;    foraging;    neural circuits;    sensorimotor;    C. elegans;   

DOI  :  10.7554/eLife.62889

来源: eLife Sciences Publications, Ltd

【 摘 要 】

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 stereotyped changes in circuit activity 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 neural activity patterns observed in each state. 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.

【 授权许可】

CC BY