Volume 14 Supplement 1
Noise decouples covariances from interaction strength
© Grytskyy et al; licensee BioMed Central Ltd. 2013
Published: 8 July 2013
The mechanism is based on the increase of fluctuations in the input signal in proportion to the synaptic weight. The fluctuations cause portions of the gain function with smaller slope to be visited more frequently, effectively reducing the transmission gain. This keeps the linearized system away from instability, with the eigenvalues of its effective connectivity matrix bounded by a constant less than unity (see Figure 1C). Although of local origin the mechanism controls global features of the network dynamics.
We gratefully acknowledge funding by the Helmholtz Association: HASB and portfolio theme SMHB, the Next-Generation Supercomputer Project of MEXT, EU Grant 269921 (BrainScaleS). All network simulations were carried out with NEST (http://www.nest-initiative.org).
- Cohen MR, Kohn A: Measuring and interpreting neuronal correlations. Nat Rev Neurosci. 2011, 14 (7): 811-819. 10.1038/nn.2842.View ArticleGoogle Scholar
- Gerstein GL, Perkel DH: Simultaneously recorded trains of action potentials: analysis and functional interpretation. Science. 1969, 881 (164): 828-830.View ArticleGoogle Scholar
- Sompolinsky H: Theory of correlations in stochastic neural networks. Phys Rev E. 1994, 50 (4): 3171-3191. 10.1103/PhysRevE.50.3171.View ArticleGoogle Scholar
- Grytskyy D, Tetzlaff T, Diesmann M, Helias M: Taming the model zoo: A unified view on correlations in recurrent networks. BMC Neurosci. 2012, 13 (1): 147-10.1186/1471-2202-13-147.View ArticleGoogle Scholar
- van Vreeswijk CA, Sompolinsky H: Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science. 1996, 274: 1724-1726. 10.1126/science.274.5293.1724.View ArticlePubMedGoogle Scholar
- Grytskyy D, Tetzlaff T, Helias M: Invariance of covariances arises out of noise. AIP Conf Proc. 2013, 258-262. 1510
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.