Population dynamics: variance and the sigmoid activation function.
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.
Wellcome Trust Centre for Neuroimaging, University College London, UK. a.marreiros@fil.ion.ucl.ac.uk <a.marreiros@fil.ion.ucl.ac.uk>
André C
AC
Marreiros
Jean
J
Daunizeau
Stefan J
SJ
Kiebel
Karl J
KJ
Friston
D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D015233:Models, Statistical; D016008:Statistical Distributions