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Topic: network function

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In Computational Neuroscience and Mathematical Modeling

Seminar · Computational Neuroscience

A geometric framework to predict structure from function in neural networks

James Fitzgerald · Janelia Research Campus

Wed, Feb 3, 2021 · 05:00 UTC

The structural connectivity matrix of synaptic weights between neurons is a critical determinant of overall network function. However, quantitative links between neural network structure and function are complex and subtle. For example, many networks can give rise to similar functional responses, and the same network can function differently depending on context. Whether certain patterns of synaptic connectivity are required to generate specific network-level computations is largely unknown. Here we introduce a geometric framework for identifying synaptic connections required by steady-state r

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