Mapping neuronal ensembles and pattern-completion neurons through graphical models

通过图形模型绘制神经元集合和模式补全神经元图

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Abstract

Neuronal ensembles are coordinated groups of neurons that serve as functional building blocks of neural circuits. Here, we present PatMap, a computational toolbox for identifying pattern-completion neurons, key trigger cells capable of reactivating entire neuronal ensembles. We describe a protocol for modeling neural circuits as probabilistic graphical models, linking behavior with specific neuronal ensembles, and identifying their pattern-completion neurons. By linking the cellular and circuit level, PatMap provides a springboard for targeted manipulation and control of neural circuits. For complete details on the use and execution of this protocol, please refer to Carrillo-Reid et al. (2021).(1).

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