A long-standing goal in neuroscience is to understand how a circuit’s form influences its function. Here, we reconstruct and analyze a synaptic wiring diagram of the larval zebrafish brainstem to predict key functional properties and validate them through comparison with physiological data. We identify modules of strongly connected neurons that turn out to be specialized for different behavioral functions, the control of eye and body movements. The eye movement module is further organized into two three-block cycles that support the positive feedback long hypothesized to underlie low-dimensional attractor dynamics in oculomotor control. We construct a neural network model based directly on the reconstructed wiring diagram that makes predictions for the cellular-resolution coding of eye position and neural dynamics. These predictions are verified statistically with calcium imaging-based neural activity recordings. This work demonstrates how connectome-based brain modeling can reveal previously unknown anatomical structure in a neural circuit and provide insights linking network form to function.

神经科学的一个长期目标是了解回路的形式如何影响其功能。在这里，我们重建和分析了斑马鱼幼虫脑干的突触布线图，以预测关键功能特性并通过与生理数据进行比较来验证它们。我们确定了强连接神经元的模块，这些模块专门用于不同的行为功能，即控制眼睛和身体运动。眼动模块进一步组织成两个三块循环，支持长期以来假设的正反馈是动眼神经控制中低维吸引子动力学的基础。我们直接基于重建的布线图构建了一个神经网络模型，该模型对眼睛位置和神经动力学的细胞分辨率编码进行预测。这些预测通过基于钙成像的神经活动记录进行统计验证。这项工作展示了基于连接组的大脑建模如何揭示神经回路中以前未知的解剖结构，并提供将网络形式与功能联系起来的见解。