Shenzhen Key Lab of Neuropsychiatric Modulation, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, the Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Shenzhen Key Lab of Neuropsychiatric Modulation, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, the Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Department of Electrical Engineering, City University of Hong Kong, Hong Kong 999077, China; University of Science and Technology of China, Hefei 230026, China.
Neuron. 2023 May 17;111(10):1651-1665.e5. doi: 10.1016/j.neuron.2023.02.025. Epub 2023 Mar 15.
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.
进食需要复杂的神经过程协调，以在自然、多变的环境中满足食欲。然而，在整个进食过程中，离散的神经群体在协调不同行为和动机方面的互补作用在很大程度上是未知的。在这里，我们通过开发一种机器学习辅助的行为跟踪系统来描绘小鼠的行为范围，并表明进食是碎片化的，并且对食物消费或环境探索的不同动机在整个进食过程中相互竞争。弓状核（ARC）中表达 AgRP 的神经元、下丘脑外侧（LH）中的 GABA 能神经元和中脑导水管周围灰质（DR）中的神经元的迭代激活序列分别通过解决动机冲突来协调进食片段的准备、启动和维持。这种支配不同动机竞争的迭代神经处理序列进一步表明了优化目标导向行为的一般规则。
