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Mechanisms that drive the variation of aversive behavior

Mechanisms that drive the variation of aversive behavior
驱动厌恶行为变化的机制
批准号:
10018918
负责人:
Su Guo
金额:
$61.59万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-16 至 2023-07-31

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PROJECT SUMMARY How behavior is regulated is a fundamental unsolved problem. Approaching this problem requires tractable behavioral readouts. It also requires model systems that are amenable to molecular genetic and systems level dissection. The long-term goal of this project is to elucidate the molecular and cellular basis of aversive behavior, an action that is propelled by un-wanting, “dislike”, or fear. Understanding how aversive behavior is regulated at the basic molecular, cellular, systems, and population levels shall provide fundamental insights into our understanding of brain function, and are therefore of high significance. Larval zebrafish provide a salient vertebrate system that enables the understanding of behavior from molecules to systems. For example, they exhibit a light/dark preference behavior, with dark being perceived aversive. Light/dark preference as a choice behavior is observed across the animal kingdom. The underlying mechanisms are however not understood. In mammals, light/dark preference is considered an anxiety-like trait and used to assess the anxiolytic properties of drugs. Intriguingly, treatment of larval zebrafish with the same anti-anxiety medications also significantly relieves their dark aversion. We have demonstrated heritable variation of the dark aversion behavior in larval zebrafish. In this application, we propose to exploit the unique strengths of larval zebrafish for high throughput phenotyping/genotyping and brain-wide calcium imaging. We will team up with experts in population genetics and computational science to understand the molecular and cellular basis of this behavioral variation. The central objectives of this proposal are: 1) Determine, at the molecular genetic level, the driving forces for this behavioral variation. 2) Uncover cellular and network level mechanisms that underlie this behavioral variation. Successful completion of these aims will link genes to brain and to behavior. Impact and Outcomes: Complex behaviors are observed in a spectrum across the population, with the extreme ends of the spectrum often classified as disease states. The proposed work harvests a unique resource of behavioral variation in a tractable vertebrate model organism, and is expected to uncover new and potentially evolutionarily conserved insights into behavioral regulation. These findings should have a positive impact on informing human studies of behavioral variation ranging from normal spectrum to disease states. The proposed work also lay foundation for other researchers to use zebrafish for mapping naturally existing quantitative traits.
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