Abstract
This publication serves as an overview of clique topology -- a novel matrix analysis technique used to extract structural features from neural activity data that contains hidden nonlinearities. We highlight work done by Gusti et al. which introduces clique topology and verifies its applicability to neural feature extraction by showing that neural correlations in the rat hippocampus are determined by geometric structure of hippocampal circuits, rather than being a consequence of positional coding.
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