Synapse Classification

Reconstructing Networks with excitatory and inhibitory interactions from dynamics using Transfer Entropy

The inverse problem for neuronal networks is to infer its topology from analyzing its dynamics. Recently, transfer entropy[1], an information theoretical measure of directed interactions has become more popular for solving the inverse problem[2]. Due to its model-free nature, it can easily be applied to data in a variety of fields such as neuroscience, physiology, climate research and financial markets.

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