Journal
PHYSICAL REVIEW E
Volume 94, Issue 5, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.94.050101
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Funding
- NSF CAREER [IIS-1254123]
- NEI [P30 EY019005, T32 EY020503]
- Salk Institute Innovations Grant Program
- NSF [IOS-1556388]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1254123] Funding Source: National Science Foundation
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Using the diagrammatic method, we derive a set of self-consistent equations that describe eigenvalue distributions of large correlated asymmetric random matrices. The matrix elements can have different variances and be correlated with each other. The analytical results are confirmed by numerical simulations. The results have implications for the dynamics of neural and other biological networks where plasticity induces correlations in the connection strengths within the network. We find that the presence of correlations can have a major impact on network stability.
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