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Storing serial order in intrinsic excitability: a working memory model (Conde-Sousa & Aguiar 2013)
 
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Accession:
147461
" … Here we present a model for working memory which relies on the modulation of the intrinsic excitability properties of neurons, instead of synaptic plasticity, to retain novel information for periods of seconds to minutes. We show that it is possible to effectively use this mechanism to store the serial order in a sequence of patterns of activity. … The presented model exhibits properties which are in close agreement with experimental results in working memory. ... "
Reference:
1 .
Conde-Sousa E, Aguiar P (2013) A working memory model for serial order that stores information in the intrinsic excitability properties of neurons.
J Comput Neurosci
35
:187-99
[
PubMed
]
Model Information
(Click on a link to find other models with that property)
Model Type:
Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
NEURON;
Model Concept(s):
Working memory;
Implementer(s):
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/
SeqLearn
README.txt
CaIntraCellDyn.mod
ComboSyn.mod
HH2.mod
iCaAN.mod
iCaL.mod
gate_interneuron.hoc
init.hoc
local_interneuron.hoc
mosinit.hoc
*
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principal_neuron.hoc
randperm.hoc
ranstream.hoc
utils.hoc
WMSeqLearn.hoc
WMSeqLearn.ses
load_file("init.hoc")
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