Benchmarking resting state fMRI connectivity pipelines for classification: Robust accuracy despite processing variability in cross-site eye state prediction

Abstract excerpt

The rapid evolution of machine learning (ML) methods has yielded promising results in human brain neuroscience. However, the reproducibility of ML applications in neuroimaging remains limited, challenging the generalizability of inferences to broader populations. In addition to the inherent variability of the brain activity (both in healthy and pathological states), poor reproducibility is further enhanced by inco...

Topics

Open a Topic to create a Post that cites this publication.

• Brain
• Follow-Up Studies
• Gene Expression
• Gene Regulatory Networks
• Magnetic Resonance Imaging
• Neural Pathways
• Phenotype
• Radiography

Identifiers and source

Literature Corpus work

0d0afd52-c215-5388-acb1-3fbafe18bbd4

DOI

10.1101/2025.10.20.683049