Tell me why: A scoping review on the fundamental building blocks of fMRI-based network analysis DOI Creative Commons
Zarah van der Pal, Linda Douw, Amanda Genis

et al.

NeuroImage Clinical, Journal Year: 2025, Volume and Issue: unknown, P. 103785 - 103785

Published: April 1, 2025

Understanding complex brain-behaviour relationships in psychiatric and neurological conditions is crucial for advancing clinical insights. This review explores the current landscape of network estimation methods context functional MRI (fMRI) based neuroscience, focusing on static undirected analysis. We focused papers published a single year (2022) characterised what we consider fundamental building blocks analysis: sample size, association type, edge inclusion strategy, weights, modelling level, confounding factors. found that most common across all included studies (n = 191) were use pairwise correlations to estimate associations between brain regions (79.6 %), weighted networks (95.3 at individual level (86.9 %). Importantly, substantial number lacked comprehensive reporting their methodological choices, hindering synthesis research findings within field. underscores critical need careful consideration transparent fMRI methodologies advance our understanding relationships. By facilitating integration neuroscience psychometrics, aim significantly enhance these intricate connections.

Language: Английский

Tell me why: A scoping review on the fundamental building blocks of fMRI-based network analysis DOI Creative Commons
Zarah van der Pal, Linda Douw, Amanda Genis

et al.

NeuroImage Clinical, Journal Year: 2025, Volume and Issue: unknown, P. 103785 - 103785

Published: April 1, 2025

Understanding complex brain-behaviour relationships in psychiatric and neurological conditions is crucial for advancing clinical insights. This review explores the current landscape of network estimation methods context functional MRI (fMRI) based neuroscience, focusing on static undirected analysis. We focused papers published a single year (2022) characterised what we consider fundamental building blocks analysis: sample size, association type, edge inclusion strategy, weights, modelling level, confounding factors. found that most common across all included studies (n = 191) were use pairwise correlations to estimate associations between brain regions (79.6 %), weighted networks (95.3 at individual level (86.9 %). Importantly, substantial number lacked comprehensive reporting their methodological choices, hindering synthesis research findings within field. underscores critical need careful consideration transparent fMRI methodologies advance our understanding relationships. By facilitating integration neuroscience psychometrics, aim significantly enhance these intricate connections.

Language: Английский

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