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The Drosophila Mushroom Body: From Architecture to Algorithm in a Learning Circuit.
Annual Review of Neuroscience ( IF 12.1 ) Pub Date : 2020-07-08 , DOI: 10.1146/annurev-neuro-080317-0621333
Mehrab N Modi 1 , Yichun Shuai 1 , Glenn C Turner 1
Affiliation  

The Drosophila brain contains a relatively simple circuit for forming Pavlovian associations, yet it achieves many operations common across memory systems. Recent advances have established a clear framework for Drosophila learning and revealed the following key operations: a) pattern separation, whereby dense combinatorial representations of odors are preprocessed to generate highly specific, nonoverlapping odor patterns used for learning; b) convergence, in which sensory information is funneled to a small set of output neurons that guide behavioral actions; c) plasticity, where changing the mapping of sensory input to behavioral output requires a strong reinforcement signal, which is also modulated by internal state and environmental context; and d) modularization, in which a memory consists of multiple parallel traces, which are distinct in stability and flexibility and exist in anatomically well-defined modules within the network. Cross-module interactions allow for higher-order effects where past experience influences future learning. Many of these operations have parallels with processes of memory formation and action selection in more complex brains.

中文翻译:


果蝇蘑菇体:从架构到学习回路中的算法。

果蝇大脑含有形成巴甫洛夫协会比较简单的电路,但它可以实现诸多操作的通用跨存储系统。最近的进展为果蝇学习建立了一个清晰的框架,并揭示了以下关键操作:a ) 模式分离,由此对气味的密集组合表示进行预处理,以生成用于学习的高度特定的、不重叠的气味模式;b ) 收敛,其中感觉信息汇集到一小组指导行为动作的输出神经元;C) 可塑性,改变感官输入到行为输出的映射需要强烈的强化信号,这也受内部状态和环境背景的调节;及d)模块化,其中一个存储器由多个平行轨迹,这是在稳定性和灵活性不同,并在网络内的解剖学上定义良好的模块存在的。跨模块交互允许高阶效应,其中过去的经验会影响未来的学习。许多这些操作与更复杂大脑中的记忆形成和动作选择过程相似。

更新日期:2020-07-09
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