What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis

Psychological Science, Journal Year: 2020, Volume and Issue: 31(7), P. 792 - 806

Published: June 3, 2020

Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring activity using task functional MRI (fMRI) major focus biomarker development; however, the reliability fMRI has not been systematically evaluated. We present converging evidence demonstrating poor task-fMRI measures. First, meta-analysis 90 experiments ( N = 1,008) revealed overall reliability—mean intraclass correlation coefficient (ICC) .397. Second, test-retest reliabilities priori regions interest across 11 common tasks collected Human Connectome Project 45) and Dunedin Study 20) were (ICCs .067–.485). Collectively, these findings demonstrate that currently suitable discovery or individual-differences research. review how this state affairs came be highlight avenues improving reliability.

Language: Английский

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Harnessing reliability for neuroscience research

Nature Human Behaviour, Journal Year: 2019, Volume and Issue: 3(8), P. 768 - 771

Published: June 28, 2019

Language: Английский

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Individual Variation in Functional Topography of Association Networks in Youth

Neuron, Journal Year: 2020, Volume and Issue: 106(2), P. 340 - 353.e8

Published: Feb. 19, 2020

Language: Английский

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Is it time to put rest to rest?

Trends in Cognitive Sciences, Journal Year: 2021, Volume and Issue: 25(12), P. 1021 - 1032

Published: Oct. 6, 2021

Language: Английский

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Defining Individual-Specific Functional Neuroanatomy for Precision Psychiatry

Biological Psychiatry, Journal Year: 2019, Volume and Issue: 88(1), P. 28 - 39

Published: Nov. 7, 2019

Language: Английский

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Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: April 25, 2022

Abstract How individual differences in brain network organization track behavioral variability is a fundamental question systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the level. However, most studies focus on single traits, thus not capturing broader relationships across behaviors. In large sample of 1858 typically developing children from Adolescent Brain Cognitive Development (ABCD) study, we show predictive features are distinct domains cognitive performance, personality scores mental health assessments. On other hand, within each domain predicted by similar features. Predictive models generalize to measures same domain. Although tasks known modulate connectome, between resting task states. Overall, our findings reveal shared account for variation broad behavior childhood.

Language: Английский

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Toward a connectivity gradient-based framework for reproducible biomarker discovery

NeuroImage, Journal Year: 2020, Volume and Issue: 223, P. 117322 - 117322

Published: Sept. 1, 2020

Despite myriad demonstrations of feasibility, the high dimensionality fMRI data remains a critical barrier to its utility for reproducible biomarker discovery. Recent efforts address this challenge have capitalized on reduction techniques applied resting-state fMRI, identifying principal components intrinsic connectivity which describe smooth transitions across different cortical systems, so called "connectivity gradients". These gradients recapitulate neurocognitively meaningful organizational principles that are present in both human and primate brains, also appear differ among individuals clinical populations. Here, we provide assessment suitability Using Human Connectome Project (discovery subsample=209; two replication subsamples= 209 × 2) Midnight scan club (n = 9), tested following key traits - reliability, reproducibility predictive validity functional gradients. In doing so, systematically assessed effects three analytical settings, including i) algorithms (i.e., linear vs. non-linear methods), ii) input types raw time series, [un-]thresholded connectivity), iii) amount (resting-state time-series lengths). We found subsamples is generally higher those explaining more variances whole-brain data, as well having reliability. Notably, (principal component analysis our study), conservatively thresholded (e.g., 95-97%) longer (at least ≥20mins) was be preferential conditions obtain Those with reliability were able predict unseen phenotypic scores accuracy, highlighting prerequisite validity. Importantly, prediction accuracy exceeded observed traditional edge-based measures, suggesting added value low-dimensional multivariate gradient approach. Finally, work highlights importance benefits exploring parameter space new imaging methods before widespread deployment.

Language: Английский

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Toward Neurosubtypes in Autism

Biological Psychiatry, Journal Year: 2020, Volume and Issue: 88(1), P. 111 - 128

Published: April 22, 2020

Language: Английский

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Brain–phenotype models fail for individuals who defy sample stereotypes

Nature, Journal Year: 2022, Volume and Issue: 609(7925), P. 109 - 118

Published: Aug. 24, 2022

Abstract Individual differences in brain functional organization track a range of traits, symptoms and behaviours 1–12 . So far, work modelling linear brain–phenotype relationships has assumed that single such relationship generalizes across all individuals, but models do not equally well participants 13,14 A better understanding whom fail why is crucial to revealing robust, useful unbiased relationships. To this end, here we related activity phenotype using predictive models—trained tested on independent data ensure generalizability 15 —and examined model failure. We applied data-driven approach neurocognitive measures new, clinically demographically heterogeneous dataset, with the results replicated two independent, publicly available datasets 16,17 Across three datasets, find reflect unitary cognitive constructs, rather scores intertwined sociodemographic clinical covariates; is, stereotypical profiles, when individuals who defy them. Model failure reliable, specific generalizable datasets. Together, these highlight pitfalls one-size-fits-all effect biased phenotypic 18–20 interpretation utility resulting models. present framework address issues so may reveal neural circuits underlie phenotypes ultimately identify individualized targets for intervention.

Language: Английский

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Common variants contribute to intrinsic human brain functional networks

Nature Genetics, Journal Year: 2022, Volume and Issue: 54(4), P. 508 - 517

Published: April 1, 2022

Language: Английский

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