Dataset Information

The individual functional connectome is unique and stable over months to years.

ABSTRACT: Functional connectomes computed from fMRI provide a means to characterize individual differences in the patterns of BOLD synchronization across regions of the entire brain. Using four resting-state fMRI datasets with a wide range of ages, we show that individual differences of the functional connectome are stable across 3 months to 1-2 years (and even detectable at above-chance levels across 3 years). Medial frontal and frontoparietal networks appear to be both unique and stable, resulting in high ID rates, as did a combination of these two networks. We conduct analyses demonstrating that these results are not driven by head motion. We also show that edges contributing the most to a successful ID tend to connect nodes in the frontal and parietal cortices, while edges contributing the least tend to connect cross-hemispheric homologs. Our results demonstrate that the functional connectome is stable across years and that high ID rates are not an idiosyncratic aspect of a specific dataset, but rather reflect stable individual differences in the functional connectivity of the brain.

SUBMITTER: Horien C

PROVIDER: S-EPMC6422733 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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The individual functional connectome is unique and stable over months to years.

Horien Corey C Shen Xilin X Scheinost Dustin D Constable R Todd RT

NeuroImage 20190202

Functional connectomes computed from fMRI provide a means to characterize individual differences in the patterns of BOLD synchronization across regions of the entire brain. Using four resting-state fMRI datasets with a wide range of ages, we show that individual differences of the functional connectome are stable across 3 months to 1-2 years (and even detectable at above-chance levels across 3 years). Medial frontal and frontoparietal networks appear to be both unique and stable, resulting in hi ...[more]

PMID: 30721751

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Project description:Studying the causes and correlates of natural variation in gene expression in healthy populations assumes that individual differences in gene expression can be reliably and stably assessed across time. However, this is yet to be established. We examined 4-hour test-retest reliability and 10 month test-retest stability of individual differences in gene expression in ten 12-year-old children. Blood was collected on four occasions: 10 a.m. and 2 p.m. on Day 1 and 10 months later at 10 a.m. and 2 p.m. Total RNA was hybridized to Affymetrix-U133 plus 2.0 arrays. For each probeset, the correlation across individuals between 10 a.m. and 2 p.m. on Day 1 estimates test-retest reliability. We identified 3,414 variable and abundantly expressed probesets whose 4-hour test-retest reliability exceeded .70, a conventionally accepted level of reliability, which we had 80% power to detect. Of the 3,414 reliable probesets, 1,752 were also significantly reliable 10 months later. We assessed the long-term stability of individual differences in gene expression by correlating the average expression level for each probe-set across the two 4-hour assessments on Day 1 with the average level of each probe-set across the two 4-hour assessments 10 months later. 1,291 (73.7%) of the 1,752 probe-sets that reliably detected individual differences across 4 hours on two occasions, 10 months apart, also stably detected individual differences across 10 months. Heritability, as estimated from the MZ twin intraclass correlations, is twice as high for the 1,752 reliable probesets versus all present probesets on the array (0.68 vs 0.34), and is even higher (0.76) for the 1,291 reliable probesets that are also stable across 10 months. The 1,291 probesets that reliably detect individual differences from a single peripheral blood collection and stably detect individual differences over 10 months are promising targets for research on the causes (e.g., eQTLs) and correlates (e.g., psychopathology) of individual differences in gene expression.

Dataset Information

The individual functional connectome is unique and stable over months to years.

Publications

The individual functional connectome is unique and stable over months to years.

Similar Datasets

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