Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results

Orlichenko, Anton; Qu, Gang; Su, Kuan-Jui; Liu, Anqi; Shen, Hui; Deng, Hong−Wen; Wang, Yuping

doi:10.36227/techrxiv.23826441.v1

2023

DOI: 10.36227/techrxiv.23826441.v1

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Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results

Anton Orlichenko¹,

Gang Qu²,

Kuan-Jui Su³

et al.

Abstract: <p>fMRI and phenotype data for the PNC dataset came from the Neurodevelopmental Genomics: Trajectories of Complex Phenotypes database of genotypes and phenotypes repository, dbGaP Study Accession ID phs000607.v3.p2. The authors would also like to thank the UK Biobank (UKB application ID 61915), the BSNIP study organizers, and OpenNeuro as well as the Fibromyalgia dataset curators for making data publicly available or available to authorized researchers.</p>

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Somatomotor-Visual Resting State Functional Connectivity Increases After Two Years in the UK Biobank Longitudinal Cohort

Orlichenko,

Su,

Tian

et al. 2023

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Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been observed in children, where high connectivity among all brain regions changes to a more modular structure with maturation. In older adults, prior work has identified changes in connectivity associated with the default mode network (DMN); other work has used brain age to predict pre-clinical Alzheimer's disease. In this work, we find an increasing connectivity between the Somatomotor (SMT) and Visual (VIS) Networks using the Power264 atlas in a longitudinal cohort of the UK Biobank (UKB). This cohort consists of 2,722 subjects, with scans being taken an average of two years apart. The average connectivity increase between SMT-VIS is 6.8% compared to the younger scan baseline (from \rho=0.39 to \rho=0.42), and occurs in male, female, older subject (>65 years old), and younger subject (<55 years old) groups. Among all inter-network connections, this average SMT-VIS connectivity is the best predictor of relative scan age, accurately predicting which scan is older 57% of the time. Using the full FC and a training set of 2,000 subjects, one is able to predict which scan is older 82.5% of the time when using the difference of FC between the two scans as input to a classifier. This previously under-reported relationship may shed light on normal changes in aging brain FC, identifies a potential confound for longitudinal studies, and proposes a new area for investigation, specifically the SMT-VIS connectivity.

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Somatomotor-Visual Resting State Functional Connectivity Increases After Two Years in the UK Biobank Longitudinal Cohort

Orlichenko,

Su,

Tian

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

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Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results

Cited by 1 publication

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Somatomotor-Visual Resting State Functional Connectivity Increases After Two Years in the UK Biobank Longitudinal Cohort

Somatomotor-Visual Resting State Functional Connectivity Increases After Two Years in the UK Biobank Longitudinal Cohort

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