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 =...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2017-02-01
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| Series: | Network Neuroscience |
| Subjects: | |
| Online Access: | https://www.mitpressjournals.org/doi/pdf/10.1162/NETN_a_00004 |
| _version_ | 1818700480327450624 |
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| author | Felix Z. Hoffmann Jochen Triesch |
| author_facet | Felix Z. Hoffmann Jochen Triesch |
| author_sort | Felix Z. Hoffmann |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T15:05:37Z |
| format | Article |
| id | doaj.art-a019fd76315f4c84b2ad6523d36dd2b4 |
| institution | Directory Open Access Journal |
| issn | 2472-1751 |
| language | English |
| last_indexed | 2024-12-17T15:05:37Z |
| publishDate | 2017-02-01 |
| publisher | The MIT Press |
| record_format | Article |
| series | Network Neuroscience |
| spelling | doaj.art-a019fd76315f4c84b2ad6523d36dd2b42022-12-21T21:43:48ZengThe MIT PressNetwork Neuroscience2472-17512017-02-0111314110.1162/NETN_a_00004NETN_a_00004Nonrandom network connectivity comes in pairsFelix Z. Hoffmann0Jochen Triesch1Frankfurt Institute for Advanced Studies (FIAS), Johann Wolfgang Goethe University, Frankfurt am Main, GermanyFrankfurt Institute for Advanced Studies (FIAS), Johann Wolfgang Goethe University, Frankfurt am Main, GermanyOverrepresentation 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.https://www.mitpressjournals.org/doi/pdf/10.1162/NETN_a_00004Nonrandom connectivityCortical circuitBidirectional connectionsRandom graph model |
| spellingShingle | Felix Z. Hoffmann Jochen Triesch Nonrandom network connectivity comes in pairs Network Neuroscience Nonrandom connectivity Cortical circuit Bidirectional connections Random graph model |
| title | Nonrandom network connectivity comes in pairs |
| title_full | Nonrandom network connectivity comes in pairs |
| title_fullStr | Nonrandom network connectivity comes in pairs |
| title_full_unstemmed | Nonrandom network connectivity comes in pairs |
| title_short | Nonrandom network connectivity comes in pairs |
| title_sort | nonrandom network connectivity comes in pairs |
| topic | Nonrandom connectivity Cortical circuit Bidirectional connections Random graph model |
| url | https://www.mitpressjournals.org/doi/pdf/10.1162/NETN_a_00004 |
| work_keys_str_mv | AT felixzhoffmann nonrandomnetworkconnectivitycomesinpairs AT jochentriesch nonrandomnetworkconnectivitycomesinpairs |