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蘑菇体研究的未来途径。

Future avenues in mushroom body research.

机构信息

Dynamics of Neuronal Circuits Group, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.

Department of Developmental Biology, RWTH Aachen University, Aachen, Germany.

出版信息

Learn Mem. 2024 Jun 11;31(5). doi: 10.1101/lm.053863.123. Print 2024 May.

Abstract

How does the brain translate sensory information into complex behaviors? With relatively small neuronal numbers, readable behavioral outputs, and an unparalleled genetic toolkit, the mushroom body (MB) offers an excellent model to address this question in the context of associative learning and memory. Recent technological breakthroughs, such as the freshly completed full-brain connectome, multiomics approaches, CRISPR-mediated gene editing, and machine learning techniques, led to major advancements in our understanding of the MB circuit at the molecular, structural, physiological, and functional levels. Despite significant progress in individual MB areas, the field still faces the fundamental challenge of resolving how these different levels combine and interact to ultimately control the behavior of an individual fly. In this review, we discuss various aspects of MB research, with a focus on the current knowledge gaps, and an outlook on the future methodological developments required to reach an overall view of the neurobiological basis of learning and memory.

摘要

大脑如何将感觉信息转化为复杂的行为?蘑菇体 (MB) 神经元数量相对较少、行为输出易于读取,并且具有无与伦比的遗传工具包,使其成为在关联学习和记忆背景下解决这一问题的极佳模型。最近的技术突破,如刚刚完成的全脑连接组、多组学方法、CRISPR 介导的基因编辑和机器学习技术,使我们在分子、结构、生理和功能水平上对 MB 回路的理解取得了重大进展。尽管在单个 MB 区域取得了重大进展,但该领域仍然面临着一个基本挑战,即如何将这些不同的层面结合和相互作用,最终控制个体果蝇的行为。在这篇综述中,我们讨论了 MB 研究的各个方面,重点关注当前的知识空白,并展望未来需要采用哪些方法学发展来全面了解学习和记忆的神经生物学基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd45/11199946/0c952357a9a9/LM053863Cha_F1.jpg

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