Guiding Synchrony through Random Networks
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Sparse random networks contain structures that can be considered as diluted feed-forward networks. Modeling of cortical circuits has shown that feed-forward structures, if strongly pronounced compared to the embedding random network, enable reliable signal transmission by propagating localized (subnetwork) synchrony. This assumed prominence, however, is not experimentally observed in local cortical circuits. Here, we show that nonlinear dendritic interactions, as discovered in recent single-neuron experiments, naturally enable guided synchrony propagation already in random recurrent neural networks that exhibit mildly enhanced, biologically plausible substructures.
Details
Original language | English |
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Article number | 041016 |
Journal | Physical Review X |
Volume | 2 |
Issue number | 4 |
Publication status | Published - 13 Dec 2012 |
Peer-reviewed | Yes |
Externally published | Yes |
External IDs
ORCID | /0000-0002-5956-3137/work/142242481 |
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Keywords
ASJC Scopus subject areas
Keywords
- Biological physics, Complex systems