A neuroinformatics framework for systematic evaluation of multiple FC measures under small-sample rs-fMRI conditions and explicitly addresses data leakage and overfitting through strict cross-validation and training-only feature selection is proposed.
BACKGROUND
Language processing is organized in brain networks, generally lateralized to the left hemisphere. In clinical routine, task-based functional MRI (fMRI) is the gold standard for non-invasive evaluation of language lateralization. However, standard fMRI does not account for the individual heterogeneity of lang...
R. Stepponat, Mehmet-Salih Yildirim, M. Berger et al.· Clinical Neuroradiology· 0 citations
The evidence supports fNIRS as a research tool for cortical hemodynamic measurement, while specific fNIRS-derived patterns of regional activation or connectivity have yet to be validated as biomarkers.
A robust, interpretable, and externally validated neuroimaging-only framework for ASD risk screening that demonstrates strong generalization across multi-site rs-fMRI datasets and integrates GNNExplainer-based attribution maps, addressing a key barrier to clinical adoption of deep learning models in neurodevelopmental...
Sucharitha Gowdiperu, Sheshikala Martha· Current Psychiatry Research...· 0 citations
Sleep deprivation impacts large-scale brain network dynamics, and there are only limited neuroimaging biomarkers available to reliably detect sleep loss across individuals and age groups. In this study, Dynamic functional connectivity (DFC) analysis of resting-state fMRI was employed to classify partial sleep deprivati...
Tharindu Weerawickrama, N. Vithana, R. Rajapaksha· 2026 4th International Confe...· 0 citations
Abstract. Significance Resting-state functional connectivity (RSFC) is an important measure in advancing our understanding of brain function and development as well as various neurological and mental disorders. Studying RSFC with functional near-infrared spectroscopy (fNIRS) offers several advantages over functional ma...
Foivos Kotsogiannis, Sophie Raible, J. Pereira et al.· Neurophotonics· 0 citations
Background/Objectives: Synolitic graphs (SGs) were developed for task-based fMRI, where edge weights encode the discriminative power of pairwise regional features; whether similar information can be recovered from resting-state data was untested. We benchmarked SGs for autism spectrum disorder (ASD) classification usin...
Alexey Zaikin, Daniil Vlasenko, D. Zakharov et al.· Diagnostics· 0 citations
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