Nonrandom network connectivity comes in pairs

Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, Pij =...

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Bibliographic Details
Published in:Network neuroscience (Cambridge, Mass.) Mass.), 2017-02, Vol.1 (1), p.31-41
Main Authors: Felix Z. Hoffmann, Jochen Triesch
Format: Article
Language:English
Subjects:
Bidirectional connections
Cortical circuit
Nonrandom connectivity
Random graph model
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Summary:Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, Pij = Pji, the occurrences of bidirectional connections and nonrandom structures are inherently linked; an overabundance of reciprocally connected pairs emerges necessarily when some pairs of neurons are more likely to be connected than others. Our numerical results imply that such overrepresentation can also be sustained when connection probabilities are only approximately symmetric.
ISSN:2472-1751
DOI:10.1162/NETN_a_00004