ModelDB: Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010)

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Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010)

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Accession:136095

"... We sought to measure how the activity of the network alters information flow from inputs to output patterns. Information handling by the network reflected the degree of internal connectivity. ... With greater connectivity strength, the recurrent network translated activity and information due to contribution of activity from intrinsic network dynamics. ... At still higher internal synaptic strength, the network corrupted the external information, producing a state where little external information came through. The association of increased information retrieved from the network with increased gamma power supports the notion of gamma oscillations playing a role in information processing."
Reference:
1 . Neymotin SA, Jacobs KM, Fenton AA, Lytton WW (2011) Synaptic information transfer in computer models of neocortical columns. J Comput Neurosci 30:69-84 [PubMed]

Model Information (Click on a link to find other models with that property)

Model Type:	Realistic Network;
Brain Region(s)/Organism:	Neocortex;
Cell Type(s):	Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex V1 interneuron basket PV GABA cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s):	I Na,t; I A; I K;
Gap Junctions:
Receptor(s):	GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment:	NEURON;
Model Concept(s):	Activity Patterns; Information transfer;
Implementer(s):	Lytton, William [bill.lytton at downstate.edu]; Neymotin, Sam [Samuel.Neymotin at nki.rfmh.org];