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The Emergence of Up and Down States in Cortical Networks
 

Summary: The Emergence of Up and Down States
in Cortical Networks
David Holcman1¤*
, Misha Tsodyks2,3
1 Department of Mathematics, Weizmann Institute of Science, Rehovot, Israel, 2 Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel, 3 Departement
d'etudes cognitives, Ecole Normale Superieure, Paris, France
The cerebral cortex is continuously active in the absence of external stimuli. An example of this spontaneous activity is
the voltage transition between an Up and a Down state, observed simultaneously at individual neurons. Since this
phenomenon could be of critical importance for working memory and attention, its explanation could reveal some
fundamental properties of cortical organization. To identify a possible scenario for the dynamics of Up­Down states,
we analyze a reduced stochastic dynamical system that models an interconnected network of excitatory neurons with
activity-dependent synaptic depression. The model reveals that when the total synaptic connection strength exceeds a
certain threshold, the phase space of the dynamical system contains two attractors, interpreted as Up and Down states.
In that case, synaptic noise causes transitions between the states. Moreover, an external stimulation producing a
depolarization increases the time spent in the Up state, as observed experimentally. We therefore propose that the
existence of Up­Down states is a fundamental and inherent property of a noisy neural ensemble with sufficiently
strong synaptic connections.
Citation: Holcman D, Tsodyks M (2006) The emergence of Up and Down states in cortical networks. PLoS Comput Biol 2(3): e23.
Introduction
In the absence of sensory inputs, cortical neural networks

  

Source: Andrzejak, Ralph Gregor - Departament de Tecnologia, Universitat Pompeu Fabra

 

Collections: Computer Technologies and Information Sciences