Your new experience awaits. Try the new design now and help us make it even better

ORIGINAL RESEARCH article

Front. Neurosci.

Sec. Brain Imaging Methods

Volume 19 - 2025 | doi: 10.3389/fnins.2025.1653007

Exploring functional connectivity at different timescales with Multivariate Mode Decomposition

Provisionally accepted
  • Aarhus University, Aarhus, Denmark

The final, formatted version of the article will be published soon.

This paper explores an alternative way for analyzing static Functional Connectivity (FC) in functional Magnetic Resonance Imaging (fMRI) data across multiple timescales using a class of adaptive frequency-based methods referred to as Multivariate Mode Decomposition (MMD).The proposed method decomposes fMRI into their intrinsic multivariate oscillatory components through a fully data-driven approach, and enables the isolation of intrinsic neurophyisiological activation patterns across multiple frequency bands from other interfering components. Unlike other methods, this approach is inherently equipped to handle the multivariate nature of fMRI data by aligning frequency information across multiple regions of interest. The proposed method was validated using three fMRI experiments: resting-state, motor and gambling experiments.Results demonstrate the capability of the methodology to extract reliable and reproducible FC patterns across individuals while uncovering unique connectivity features at different times scales.In addition, the results evidence the effect of the different task on the spectral organization of FC patterns, highlighting the importance of multiscale analysis for understanding functional interactions.

Keywords: fMRI, functional connectivity (FC), Multiscale, Multivariate Mode Decomposition (MMD), multivariate variational mode decomposition (MVMD)

Received: 24 Jun 2025; Accepted: 14 Jul 2025.

Copyright: © 2025 Morante, Frølich and Rehman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Naveed ur Rehman, Aarhus University, Aarhus, Denmark

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.