Evidence map›Paper›PMID 40800473›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2024

Longitudinal stability of cortical grey matter measures varies across brain regions, imaging metrics, and testing sites in the ABCD study.

Sam Parsons, Andreas M Brandmaier, Ulman Lindenberger, Rogier Kievit

Abstract read
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Article in Imaging neuroscience (Cambridge, Mass.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Sam ParsonsDonders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, Netherlands.
Andreas M BrandmaierCenter for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
Ulman LindenbergerCenter for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
Rogier KievitDonders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic resonance imaging (MRI) is a vital tool for the study of brain structure and function. It is increasingly being used in individual differences research to examine brain-behaviour associations. Prior work has demonstrated low test-retest stability of functional MRI measures, highlighting the need to examine the longitudinal stability (test-retest reliability across long timespans) of MRI measures across brain regions and imaging metrics, particularly in adolescence. In this study, we examined the longitudinal stability of grey matter measures (cortical thickness, surface area, and volume) across brain regions, and testing sites in the Adolescent Brain Cognitive Development (ABCD) study release v4.0. Longitudinal stability ICC estimates ranged from 0 to .98, depending on the measure, parcellation, and brain region. We used Intra-Class Effect Decomposition (ICED) to estimate between-subjects variance and error variance, and assess the relative contribution of each across brain regions and testing sites on longitudinal stability. In further exploratory analyses, we examined the influence of parcellation used (Desikan-Killiany-Tourville and Destrieux) on longitudinal stability. Our results highlight meaningful heterogeneity in longitudinal stability across brain regions, structural measures (cortical thickness in particular), parcellations, and ABCD testing sites. Differences in longitudinal stability across brain regions were largely driven by between-subjects variance, whereas differences in longitudinal stability across testing sites were largely driven by differences in error variance. We argue that investigations such as this are essential to capture patterns of longitudinal stability heterogeneity that would otherwise go undiagnosed. Such improved understanding allows the field to more accurately interpret results, compare effect sizes, and plan more powerful studies.

Indexed as

ABCDdevelopmental neuroscienceintraclass effect decompositionlongitudinal stabilitystructural MRI

Identifiers

PMID40800473
PMCPMC12224482

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.