An iterative neural processing sequence orchestrates feeding

Qingqing Liu; Xing Yang; Moxuan Luo; Junying Su; Jinling Zhong; Xiaofen Li; Rosa H.M. Chan; Liping Wang

doi:10.1016/j.neuron.2023.02.025

An iterative neural processing sequence orchestrates feeding

Qingqing Liu, Xing Yang, Moxuan Luo, Junying Su, Jinling Zhong, Xiaofen Li, Rosa H.M. Chan, Liping Wang^*

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

25 Citations (Scopus)

84 Downloads (CityUHK Scholars)

Abstract

Feeding requires sophisticated orchestration of neural processes to satiate appetite in natural, capricious settings. However, the complementary roles of discrete neural populations in orchestrating distinct behaviors and motivations throughout the feeding process are largely unknown. Here, we delineate the behavioral repertoire of mice by developing a machine-learning-assisted behavior tracking system and show that feeding is fragmented and divergent motivations for food consumption or environment exploration compete throughout the feeding process. An iterative activation sequence of agouti-related peptide (AgRP)-expressing neurons in arcuate (ARC) nucleus, GABAergic neurons in the lateral hypothalamus (LH), and in dorsal raphe (DR) orchestrate the preparation, initiation, and maintenance of feeding segments, respectively, via the resolution of motivational conflicts. The iterative neural processing sequence underlying the competition of divergent motivations further suggests a general rule for optimizing goal-directed behaviors. © 2023 The Authors.

Original language	English
Pages (from-to)	1651-1665.e5
Journal	Neuron
Volume	111
Issue number	10
Online published	15 Mar 2023
DOIs	https://doi.org/10.1016/j.neuron.2023.02.025
Publication status	Published - 17 May 2023

Funding

We thank Dr. Helmut Kettenmann for his edits of the manuscript. We thank Dr. Huan Tu and Dr. Zigang Li for their help with experiments during the lockdown. This work was funded by the National Natural Science Foundation of China (NSFC) 31700907, NSFC31700908, NSFC 31930047, NSFC 31630031, and NSFC 91732304; Ten Thousand Talent Program; Chang Jiang Scholars Program; International Partnership Program of Chinese Academy of Sciences (CAS) 172644KYS820170004; CAS Key Laboratory of Brain Connectome and Manipulation 2019DP173024; the Strategic Priority Research Program of CAS XDB32030100; the Guangdong Special Support Program; Key-Area Research and Development Program of Guangdong Province 2018B030331001; Shenzhen governmental grants JCYJ20180302145710934 and JCYJ20170413164535041; Financial Support for Outstanding Talents Training Fund in Shenzhen; Shenzhen Key Science and Technology Infrastructure Planning Project ZDKJ20190204002; and grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (C1020-19E).

Research Keywords

AgRP neuron
appetite
behavior identification
dorsal raphe
eating disorder
feeding initiation
feeding maintenance
food consumption
lateral hypothalamus
motivation competition

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This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

RGC Funding Information

RGC-funded

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10.1016/j.neuron.2023.02.025

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title = "An iterative neural processing sequence orchestrates feeding",

abstract = "Feeding requires sophisticated orchestration of neural processes to satiate appetite in natural, capricious settings. However, the complementary roles of discrete neural populations in orchestrating distinct behaviors and motivations throughout the feeding process are largely unknown. Here, we delineate the behavioral repertoire of mice by developing a machine-learning-assisted behavior tracking system and show that feeding is fragmented and divergent motivations for food consumption or environment exploration compete throughout the feeding process. An iterative activation sequence of agouti-related peptide (AgRP)-expressing neurons in arcuate (ARC) nucleus, GABAergic neurons in the lateral hypothalamus (LH), and in dorsal raphe (DR) orchestrate the preparation, initiation, and maintenance of feeding segments, respectively, via the resolution of motivational conflicts. The iterative neural processing sequence underlying the competition of divergent motivations further suggests a general rule for optimizing goal-directed behaviors. {\textcopyright} 2023 The Authors.",

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AU - Su, Junying

AU - Zhong, Jinling

AU - Li, Xiaofen

AU - Chan, Rosa H.M.

AU - Wang, Liping

PY - 2023/5/17

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N2 - Feeding requires sophisticated orchestration of neural processes to satiate appetite in natural, capricious settings. However, the complementary roles of discrete neural populations in orchestrating distinct behaviors and motivations throughout the feeding process are largely unknown. Here, we delineate the behavioral repertoire of mice by developing a machine-learning-assisted behavior tracking system and show that feeding is fragmented and divergent motivations for food consumption or environment exploration compete throughout the feeding process. An iterative activation sequence of agouti-related peptide (AgRP)-expressing neurons in arcuate (ARC) nucleus, GABAergic neurons in the lateral hypothalamus (LH), and in dorsal raphe (DR) orchestrate the preparation, initiation, and maintenance of feeding segments, respectively, via the resolution of motivational conflicts. The iterative neural processing sequence underlying the competition of divergent motivations further suggests a general rule for optimizing goal-directed behaviors. © 2023 The Authors.

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KW - eating disorder

KW - feeding initiation

KW - feeding maintenance

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KW - lateral hypothalamus

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JO - Neuron

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ER -

An iterative neural processing sequence orchestrates feeding

Abstract

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Research Keywords

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CRF: High-Resolution Antenna Measurement System with Robotic Arms for Millimeter-wave Frequencies

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An iterative neural processing sequence orchestrates feeding

Abstract

Funding

Research Keywords

Publisher's Copyright Statement

RGC Funding Information

Access Output

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CRF: High-Resolution Antenna Measurement System with Robotic Arms for Millimeter-wave Frequencies

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