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 gmail.com]; Schiff, Steven [sschiff at psu.edu]; Gluckman, Bruce [BruceGluckman at psu.edu]
References:
Sedigh-Sarvestani M, Schiff SJ, Gluckman BJ. (2012). Reconstructing mammalian sleep dynamics with data assimilation. PLoS computational biology. 8 [PubMed]