ModelDB: Sleep-wake transitions in corticothalamic system (Bazhenov et al 2002)

Sleep-wake transitions in corticothalamic system (Bazhenov et al 2002)

Accession: 28189

The authors investigate the transition between sleep and awake states with intracellular recordings in cats and computational models. The model describes many essential features of slow wave sleep and activated states as well as the transition between them.
Reference: Bazhenov M, Timofeev I, Steriade M, Sejnowski TJ (2002) Model of thalamocortical slow-wave sleep oscillations and transitions to activated States. J Neurosci 22:8691-704 [PubMed]

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

Model Type:	Network;
Brain Region(s)/Organism:	Thalamus;
Cell Type(s):	Thalamic relay neuron; Thalamic reticular neuron; Neocortical pyramidal neuron: deep;
Channel(s):	I Na,t; I L high threshold; I T low threshold; I K,leak; I M; I K,Ca;
Gap Junctions:
Receptor(s):	GabaA; GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment:	C or C++ program;
Model Concept(s):	Oscillations; Synchronization; Spatio-temporal Activity Patterns; Short-term Synaptic Plasticity; Depression; Sleep;
Implementer(s):	Bazhenov, Maxim [Bazhenov at Salk.edu];

Search NeuronDB for information about: Thalamic relay neuron; Thalamic reticular neuron; Neocortical pyramidal neuron: deep; GabaA; GabaB; AMPA; NMDA; I Na,t; I L high threshold; I T low threshold; I K,leak; I M; I K,Ca;

Model files

Help downloading and running models

thalamocort2002

index.html

PYactivity0to25secs.jpg

neur271.c

input27

rk.c

README

for the model associated with:

Bazhenov M, Timofeev I, Steriade M, Sejnowski TJ (2002)
Model of thalamocortical slow-wave sleep oscillations and transitions to activated states.
J Neurosci 22:8691-704

This model is written in C++. The following instructions work have worked under redhat linux 9 although the code should work with little or no modification on other platforms with ansi compilers.

How to compile:

Change to the directory in which you have unziped the archieve file, then type:

g++ neur271.c rk.c -lm -O4 -ffast-math -o neur271

How to run:

./neur271 input27 > tmp &

The run (~7.5 hours on a 800 MHz xeon redhat linux pc) creates data files equivalent to figure 6 in the paper, e.g. one can find in the time_cx file 25 seconds of 100 pyramidal cell's activity:

Correspondence:
Dr. Maxim Bazhenov, The Salk Institute,
10010 North Torrey Pines Road, La Jolla, CA 92037.
E-mail: bazhenov@salk.edu

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