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Reconstrucing sleep dynamics with data assimilation (Sedigh-Sarvestani et al., 2012)
 
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Model Information
Model File
Citations
Accession:
146554
We have developed a framework, based on the unscented Kalman filter, for estimating hidden states and parameters of a network model of sleep. The network model includes firing rates and neurotransmitter output of 5 cell-groups in the rat brain.
Reference:
1 .
Sedigh-Sarvestani M, Schiff SJ, Gluckman BJ (2012) Reconstructing mammalian sleep dynamics with data assimilation.
PLoS Comput Biol
8
:e1002788
[
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):
Acetylcholine;
Norephinephrine;
Gaba;
Serotonin;
Simulation Environment:
MATLAB;
Model Concept(s):
Oscillations;
Parameter Fitting;
Tutorial/Teaching;
Sleep;
unscented Kalman filter;
Implementer(s):
Sedigh-Sarvestani, Madineh [m.sedigh.sarvestani at gmail.com];
Schiff, Steven [sschiff at psu.edu];
Gluckman, Bruce [BruceGluckman at psu.edu];
Search NeuronDB
for information about:
Acetylcholine
;
Norephinephrine
;
Gaba
;
Serotonin
;
/
Figure Code
Figure 8_Hypno Param
figure8.m
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