Inter-regional correlation estimators for functional magnetic resonance imaging - Statistique pour le Vivant et l’Homme Access content directly
Journal Articles NeuroImage Year : 2023

Inter-regional correlation estimators for functional magnetic resonance imaging

Abstract

Functional magnetic resonance imaging (fMRI) functional connectivity between brain regions is often computed using parcellations defined by functional or structural atlases. Typically, some kind of voxel averaging is performed to obtain a single temporal correlation estimate per region pair. However, several estimators can be defined for this task, with various assumptions and degrees of robustness to local noise, global noise, and region size. In this paper, we systematically present and study the properties of 9 different functional connectivity estimators taking into account the spatial structure of fMRI data, based on a simple fMRI data spatial model. These include 3 existing estimators and 6 novel estimators. We demonstrate the empirical properties of the estimators using synthetic, animal, and human data, in terms of graph structure, repeatability and reproducibility, discriminability, dependence on region size, as well as local and global noise robustness.
Fichier principal
Vignette du fichier
inter_correlation_estimators(28).pdf (6.72 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04242995 , version 1 (15-10-2023)

Licence

Identifiers

Cite

Sophie Achard, Jean-François Coeurjolly, Pierre Lafaye de Micheaux, Hanâ Lbath, Jonas Richiardi. Inter-regional correlation estimators for functional magnetic resonance imaging. NeuroImage, 2023, 282, pp.120388. ⟨10.1016/j.neuroimage.2023.120388⟩. ⟨hal-04242995⟩
58 View
14 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More