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

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.

Model Type: Realistic Network

Transmitters: Acetylcholine; Norephinephrine; Gaba; Serotonin

Model Concept(s): Oscillations; Parameter Fitting; Tutorial/Teaching; Sleep; unscented Kalman filter

Simulation Environment: MATLAB

Implementer(s): Sedigh-Sarvestani, Madineh [m.sedigh.sarvestani at]; Schiff, Steven [sschiff at]; Gluckman, Bruce [BruceGluckman at]


Sedigh-Sarvestani M, Schiff SJ, Gluckman BJ. (2012). Reconstructing mammalian sleep dynamics with data assimilation. PLoS computational biology. 8 [PubMed]

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