- Home
- Search Results
- Page 1 of 1
Search for: All records
-
Total Resources3
- Resource Type
-
30
- Availability
-
30
- Author / Contributor
- Filter by Author / Creator
-
-
Fumarola, Francesco (3)
-
Abbott, LF (1)
-
Hein, Bettina (1)
-
Khajeh, Ramin (1)
-
Miller, Kenneth D. (1)
-
#Tyler Phillips, Kenneth E. (0)
-
& Abreu-Ramos, E. D. (0)
-
& Abramson, C. I. (0)
-
& Ahmed, K. (0)
-
& Ahmed, Khadija. (0)
-
& Akcil-Okan, O. (0)
-
& Akuom, D. (0)
-
& Aleven, V. (0)
-
& Andrews-Larson, C. (0)
-
& Archibald, J. (0)
-
& Arya, G. (0)
-
& Attari, S. Z. (0)
-
& Ayala, O. (0)
-
& Babbitt, W. (0)
-
& Baek, Y. (0)
-
- Filter by Editor
-
-
Soltani, Alireza (1)
-
& Spizer, S. M. (0)
-
& . Spizer, S. (0)
-
& Ahn, J. (0)
-
& Bateiha, S. (0)
-
& Bosch, N. (0)
-
& Chen, B. (0)
-
& Chen, Bodong (0)
-
& Drown, S. (0)
-
& Ferretti, F. (0)
-
& Higgins, A. (0)
-
& J. Peters (0)
-
& Kali, Y. (0)
-
& Ruiz-Arias, P.M. (0)
-
& S. Spitzer (0)
-
& Spitzer, S. (0)
-
& Spitzer, S.M. (0)
-
2022 USENIX Annual Technical Conference (0)
-
:Chaosong Huang, Gang Lu (0)
-
A. Agarwal (0)
-
-
Have feedback or suggestions for a way to improve these results?
!
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
Khajeh, Ramin ; Fumarola, Francesco ; Abbott, LF ( , PLOS Computational Biology)Soltani, Alireza (Ed.)Cortical circuits generate excitatory currents that must be cancelled by strong inhibition to assure stability. The resulting excitatory-inhibitory (E-I) balance can generate spontaneous irregular activity but, in standard balanced E-I models, this requires that an extremely strong feedforward bias current be included along with the recurrent excitation and inhibition. The absence of experimental evidence for such large bias currents inspired us to examine an alternative regime that exhibits asynchronous activity without requiring unrealistically large feedforward input. In these networks, irregular spontaneous activity is supported by a continually changing sparse set of neurons. To support this activity, synaptic strengths must be drawn from high-variance distributions. Unlike standard balanced networks, these sparse balance networks exhibit robust nonlinear responses to uniform inputs and non-Gaussian input statistics. Interestingly, the speed, not the size, of synaptic fluctuations dictates the degree of sparsity in the model. In addition to simulations, we provide a mean-field analysis to illustrate the properties of these networks.
-
Fumarola, Francesco ( , Advances in Cognitive Psychology)