Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
3073020 | NeuroImage | 2008 | 11 Pages |
Abstract
This paper demonstrates how the sigmoid activation function of neural-mass models can be understood in terms of the variance or dispersion of neuronal states. We use this relationship to estimate the probability density on hidden neuronal states, using non-invasive electrophysiological (EEG) measures and dynamic casual modelling. The importance of implicit variance in neuronal states for neural-mass models of cortical dynamics is illustrated using both synthetic data and real EEG measurements of sensory evoked responses.
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Authors
André C. Marreiros, Jean Daunizeau, Stefan J. Kiebel, Karl J. Friston,