Reconstrucing sleep dynamics with data assimilation (Sedigh-Sarvestani et al., 2012)

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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.
1 . Sedigh-Sarvestani M, Schiff SJ, Gluckman BJ (2012) Reconstructing mammalian sleep dynamics with data assimilation. PLoS Comput Biol 8:e1002788 [PubMed]
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Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
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]; Schiff, Steven [sschiff at]; Gluckman, Bruce [BruceGluckman at];
Search NeuronDB for information about:  Acetylcholine; Norephinephrine; Gaba; Serotonin;
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