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Prefiltering based on experimental paradigm for analysis of fMRI complex brain networks

Salvador Jiménez, Laura Rotger, Carlos Aguirre, Alberto Muñoz, Sergio Granados and Jesús Tornero

PLOS ONE, 2020, vol. 15, issue 10, 1-13

Abstract: Brain networks offers a new insight about connections between function and anatomical regions of human brain. We present results from brain networks built from functional magnetic resonance images during finger tapping paradigm. Pearson voxel-voxel correlation in time and frequency domains were performed for all subjects. Besides this standard framework we have implemented a new approach consisting in filtering the data with respect to the fMRI paradigm (finger tapping) in order to obtain a better understanding of the network involved in the execution of the task. The main topological graph measures have been compared in both cases: voxel-voxel correlation and voxel-paradigm filtering plus voxel-voxel correlation. With the standard voxel-voxel correlation a clearly free-scale network was obtained. On the other hand, when we prefiltered the paradigm we obtained two different kind of networks: 1) free-scale; 2) random-like. To our best knowledge, this behaviour is reported here for first time for brain networks. We suggest that paradigm signal prefiltering can provide more infomation about the brain networks.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0238994

DOI: 10.1371/journal.pone.0238994

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