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Dense Circuit Reconstruction to Understand Neuronal Computation: Focus on Zebrafish
Annual Review of Neuroscience ( IF 12.1 ) Pub Date : 2021-07-08 , DOI: 10.1146/annurev-neuro-110220-013050
Rainer W Friedrich 1, 2 , Adrian A Wanner 3
Affiliation  

The dense reconstruction of neuronal wiring diagrams from volumetric electron microscopy data has the potential to generate fundamentally new insights into mechanisms of information processing and storage in neuronal circuits. Zebrafish provide unique opportunities for dynamical connectomics approaches that combine reconstructions of wiring diagrams with measurements of neuronal population activity and behavior. Such approaches have the power to reveal higher-order structure in wiring diagrams that cannot be detected by sparse sampling of connectivity and that is essential for neuronal computations. In the brain stem, recurrently connected neuronal modules were identified that can account for slow, low-dimensional dynamics in an integrator circuit. In the spinal cord, connectivity specifies functional differences between premotor interneurons. In the olfactory bulb, tuning-dependent connectivity implements a whitening transformation that is based on the selective suppression of responses to overrepresented stimulus features. These findings illustrate the potential of dynamical connectomics in zebrafish to analyze the circuit mechanisms underlying higher-order neuronal computations.

中文翻译:


密集电路重建以了解神经元计算:专注于斑马鱼

从体积电子显微镜数据中密集重建神经元接线图有可能从根本上对神经元回路中的信息处理和存储机制产生新的见解。斑马鱼为动态连接组学方法提供了独特的机会,将接线图的重建与神经元群体活动和行为的测量相结合。这种方法有能力揭示接线图中的高阶结构,这些结构无法通过连接的稀疏采样检测到,这对于神经元计算至关重要。在脑干中,确定了循环连接的神经元模块,这些模块可以解释积分器电路中缓慢、低维的动态。在脊髓中,连接指定了运动前中间神经元之间的功能差异。在嗅球中,依赖于调谐的连接实现了一种基于选择性抑制对过度表现的刺激特征的反应的白化转换。这些发现说明了斑马鱼中动态连接组学分析高阶神经元计算背后的电路机制的潜力。

更新日期:2021-07-09
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