Meeting Banner
Abstract #4133

Shannon entropy method applied to fMRI data series during evoked and resting state activity

Mauro DiNuzzo 1,2 , Daniele Mascali 1,2 , Marta Moraschi 1,3 , Michela Fratini 1,3 , Tommaso Gili 3 , Girolamo Garreffa 1,3 , Bruno Maraviglia 1,3 , and Federico Giove 1,2

1 MARBILab, Enrico Fermi Center, Rome, Rome, Italy, 2 Department of Physics, U Sapienza, Rome, Rome, Italy, 3 Santa Lucia Foundation IRCCS, Rome, Italy

We applied Shannon entropy method to fMRI time series in order to examine whether and how information can be extracted from different experimental paradigms, namely evoked or resting brain (RS) activity. Shannon entropy measures information content of the signal without making a priori assumptions. We found a striking match between the high-entropy voxels and activated voxels, while RS data did not reveal any cluster of high-entropy values. This finding indicates that RS activity cannot be extracted using a code (i.e., probability distribution) determined at the voxel-level, paving the way for different approaches to determine the code underlying RS activity.

This abstract and the presentation materials are available to members only; a login is required.

Join Here