RIKEN BRAIN SCIENCE INSTITUTE (RIKEN BSI)

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[Forum] Professor Nestor Parga, Autonomous University of Madrid

“ The asynchronous state in cortical circuits ”

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Date

December 04, 2015 13:30 - 14:30

Location

BSI Central Building 1F Seminar Room

Abstract

Recurrent network dynamics can lead to active decorrelation of synaptic currents, resulting in a state of arbitrarily low mean correlation [1]. More recent studies have shown that in networks of spiking neurons the spike train cross-covariance functions obey balance relations that extend and generalize this result in several directions [2,3]. Under rather general conditions these balance equations, that relate spike train auto- and cross-covariance functions, necessarily have to be satisfied. Although both spike train and total current cross-covariance functions are small, in the asynchronous state cross-covariance functions between the current components are finite. Another signature of the asynchronous state is that the distribution of the spike count correlation coefficients has a small mean but a wide width. In two different network models, a purely inhibitory network and a network with excitatory and inhibitory populations, these predictions are explicitly shown to be true. Moreover, the balance equations for correlations are well-satisfied for network sizes in the physiological range.
 [1] Renart, A., de la Rocha, J., Bartho, P., Hollender, L., Parga, N., Reyes, A. and Harris, P. (2010). The asynchronous state in cortical circuits, Science 327:587.
[2] Manrique, J. (2014). Correlations in spontaneous activity states in the brain. PhD Thesis (Universidad Autónoma de Madrid.
[3] Manrique, J. and Parga, N (2014). Decorrelation in networks of spiking neurons: from microscopic to macroscopic magnitudes. COSYNE.

More Detail

Language
English
Admission
Open to Public
Host
Tomoki Fukai [Tomoki Fukai, Neural Circuit Theory ]
Contact
Name: Tomoki Fukai
Email:
Phone: 7461