Determination of a population rate model for slow oscillations using Bayesian inference

Bravo Padrós, Marçal

Determination of a population rate model for slow oscillations using Bayesian inference

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Citation

Bravo Padrós, M. Determination of a population rate model for slow oscillations using Bayesian inference. 2019. handle: http://hdl.handle.net/10230/43937

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Abstract

In this project we focused in the network level, where our object of study, population of neurons, are constantly shaping each others behaviour. Our aim is to determine a population rate model capable of replicating the dynamics of slow oscillations in the cerebral cortex, and applying to our simulated data a Bayesian inference technique, the Kalman filter, as a probabilistic interpretation of the problem to estimate variables and parameters of rate models.