The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Synchronization in Networks of Excitatory and Inhibitory Neurons with Sparse, Random Connectivity
Abstract
In model networks of E-cells and I-cells (excitatory and inhibitory neurons, respectively), synchronous rhythmic spiking often comes about from the interplay between the two cell groups: the E-cells synchronize the I-cells and vice versa. Under ideal conditions—homogeneity in relevant network parameters and all-to-all connectivity, for instance—this mechanism can yield perfect synchronization. We find that approximate, imperfect synchronization is possible even with very sparse, random connectivity. The crucial quantity is the expected number of inputs per cell. As long as it is large enough (more precisely, as long as the variance of the total number of synaptic inputs per cell is small enough), tight synchronization is possible. The desynchronizing effect of random connectivity can be reduced by strengthening the E→I synapses. More surprising, it cannot be reduced by strengthening the I→E synapses. However, the decay time constant of inhibition plays an important role. Faster decay yields tighter synchrony. In particular, in models in which the inhibitory synapses are assumed to be instantaneous, the effects of sparse, random connectivity cannot be seen.
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Citations
Cites
Cortex: Statistics and Geometry of Neuronal Connectivity
Braitenberg, V., & Schüz, A. (1998) · doi:10.1007/978-3-662-03733-1 · Cited by 1,178 · cited 4×
“Several authors have pointed out that p EI N E and p IE N I are much more important than p EI , N E , p IE , and N I in isolation (Golomb & Hansel, 2000; Tiesinga, Fellous, José, & Sejnowski, 2002; Wang et al., 1995).”
BackgroundInfluentialType I membranes, phase resetting curves, and synchrony
Ermentrout, B. (1996) · Neural Computation · doi:10.1162/neco.1996.8.5.979 · Cited by 1,001
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Mechanisms of Gamma Oscillations
Buzsáki, G., & Wang, X.-J. (2012) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062111-150444 · Cited by 2,796
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition
Wang, X.-J. (2010) · Physiological Reviews · doi:10.1152/physrev.00035.2008 · Cited by 1,939
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Gonzalez-Burgos, G., Cho, R. Y., & Lewis, D. A. (2015) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.03.010 · Cited by 497
Exploring the network dynamics underlying brain activity during rest
Cabral, J., Kringelbach, M. L., & Deco, G. (2014) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2013.12.005 · Cited by 351
Metadata
- Authors
- Börgers, C., & Kopell, N.
- Venue
- Neural Computation
- Publisher
- MIT Press - Journals
- Published
- 2003-03-01
- Volume
- 15
- Issue
- 3
- Pages
- 509-538
- ISSN
- 0899-7667 (ISSN-L)
- 1530-888X
- OpenAlex
- W2170527455
- Cited by
- 526
- References
- 2
- FWCI
- 6.31
- Type
- journal article
- Language
- en
- Open access
- closed
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- Börgers, C., & Kopell, N. (2003). Synchronization in Networks of Excitatory and Inhibitory Neurons with Sparse, Random Connectivity. Neural Computation. https://doi.org/10.1162/089976603321192059
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