Number of the records: 1
Brain Functional Connectivity Asymmetry: Left Hemisphere Is More Modular
- 1.
SYSNO ASEP 0557325 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Brain Functional Connectivity Asymmetry: Left Hemisphere Is More Modular Author(s) Jajcay, Lucia (UIVT-O) ORCID, SAI, RID
Tomeček, David (UIVT-O) RID, ORCID, SAI
Horáček, J. (CZ)
Španiel, F. (CZ)
Hlinka, Jaroslav (UIVT-O) RID, SAI, ORCIDNumber of authors 5 Article number 833 Source Title Symmetry-Basel. - : MDPI
Roč. 14, č. 4 (2022)Number of pages 11 s. Language eng - English Country CH - Switzerland Keywords cerebral dominance ; data analysis ; functional laterality ; fMRI ; functional connectivity ; graph theory ; modularity OECD category Neurosciences (including psychophysiology R&D Projects GA21-17211S GA ČR - Czech Science Foundation (CSF) GA21-32608S GA ČR - Czech Science Foundation (CSF) Method of publishing Open access Institutional support UIVT-O - RVO:67985807 UT WOS 000785289600001 EID SCOPUS 85129309396 DOI 10.3390/sym14040833 Annotation Graph-theoretical approaches are increasingly used to study the brain and may enhance our understanding of its asymmetries. In this paper, we hypothesize that the structure of the left hemisphere is, on average, more modular. To this end, we analyzed resting-state functional magnetic resonance imaging data of 90 healthy subjects. We computed functional connectivity by Pearson’s correlation coefficient, turned the matrix into an unweighted graph by keeping a certain percentage of the strongest connections, and quantified modularity separately for the subgraph formed by each hemisphere. Our results show that the left hemisphere is more modular. The result is consistent across a range of binarization thresholds, regardless of whether the two hemispheres are thresholded together or separately. This illustrates that graph-theoretical analysis can provide a robust characterization of lateralization of brain functional connectivity. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2023 Electronic address http://dx.doi.org/10.3390/sym14040833
Number of the records: 1