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Related Experiment Video

Updated: Jul 29, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Different MRI structural processing methods do not impact functional connectivity computation.

Lu Zhang¹, Lorenzo Pini¹, Maurizio Corbetta^2,3,4

¹Padova Neuroscience Center, University of Padova, 35131, Padua, Italy.

Scientific Reports

|May 26, 2023

Summary

This summary is machine-generated.

Different structural reconstructions minimally impact functional connectivity metrics derived from resting-state fMRI, though structural outcomes show significant variations. This suggests functional brain network analysis is robust to certain structural preprocessing choices.

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Area of Science:

Neuroimaging
Brain Connectivity Analysis
Structural and Functional MRI

Background:

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to assess brain connectivity.
Preprocessing steps significantly influence functional connectivity (FC) measures.
The impact of varying structural reconstructions on FC outcomes remains under-investigated.

Purpose of the Study:

To evaluate how different structural segmentation strategies affect functional connectivity metrics.
To compare unimodal (T1-weighted) and multimodal (T1/T2-weighted) registration approaches.
To determine the sensitivity of functional metrics to structural preprocessing variations.

Main Methods:

rs-fMRI data from 58 healthy adults were analyzed.
Two registration strategies were compared: unimodal (T1-weighted) and multimodal (T1/T2-weighted).
Structural measures (cortical thickness, volume, gyrification) and functional metrics (graph measures, seed-based FC, mean functional strength) were computed and compared.

Main Results:

Structural measures, particularly in the insula cortex, showed significant differences between unimodal and multimodal approaches.
Functional connectivity graph measures and seed-based maps were not significantly different.
Slight differences in mean functional strength were observed for specific parcels in the insula.

Conclusions:

Structural segmentation strategies have a substantial impact on structural brain measures.
Functional connectivity metrics derived from rs-fMRI are relatively robust to variations in structural reconstruction.
The choice between unimodal and multimodal structural approaches has minimal impact on overall functional connectivity outcomes.