Literature DB >> 14577852

Dynamical consequences of fast-rising, slow-decaying synapses in neuronal networks.

Bard Ermentrout1.   

Abstract

Synapses that rise quickly but have long persistence are shown to have certain computational advantages. They have some unique mathematical properties as well and in some instances can make neurons behave as if they are weakly coupled oscillators. This property allows us to determine their synchronization properties. Furthermore, slowly decaying synapses allow recurrent networks to maintain excitation in the absence of inputs, whereas faster decaying synapses do not. There is an interaction between the synaptic strength and the persistence that allows recurrent networks to fire at low rates if the synapses are sufficiently slow. Waves and localized structures are constructed in spatially extended networks with slowly decaying synapses.

Mesh:

Year:  2003        PMID: 14577852     DOI: 10.1162/089976603322385054

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  3 in total

1.  A recurrent network model of somatosensory parametric working memory in the prefrontal cortex.

Authors:  Paul Miller; Carlos D Brody; Ranulfo Romo; Xiao-Jing Wang
Journal:  Cereb Cortex       Date:  2003-11       Impact factor: 5.357

2.  Bistable, irregular firing and population oscillations in a modular attractor memory network.

Authors:  Mikael Lundqvist; Albert Compte; Anders Lansner
Journal:  PLoS Comput Biol       Date:  2010-06-03       Impact factor: 4.475

3.  Bifurcations of emergent bursting in a neuronal network.

Authors:  Yu Wu; Wenlian Lu; Wei Lin; Gareth Leng; Jianfeng Feng
Journal:  PLoS One       Date:  2012-06-07       Impact factor: 3.240

  3 in total

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