Evidence map›Paper›PMID 38746222›Full record

ArticlebioRxiv : the preprint server for biology2025

Improving Predictability, Reliability and Generalisability of Brain-Wide Associations for Cognitive Abilities via Multimodal Stacking.

Alina Tetereva, Annchen R Knodt, Tracy R Melzer, William van der Vliet, Bryn Gibson, Ahmad R Hariri, Ethan T Whitman, Jean Li, Farzane Lal Khakpoor, Jeremiah Deng and 3 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Alina TeterevaDepartment of Psychology, University of Otago, Dunedin 9016, New Zealand.ORCID 0000-0003-2077-628X
Annchen R KnodtDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27710, USA.
Tracy R MelzerNew Zealand Brain Research Institute, Christchurch 8011, New Zealand.
William van der VlietDepartment of Psychology, University of Otago, Dunedin 9016, New Zealand.
Bryn GibsonDepartment of Psychology, University of Otago, Dunedin 9016, New Zealand.
Ahmad R HaririDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27710, USA.
Ethan T WhitmanDepartment of Psychology and Neuroscience, Duke University, Durham, NC 27710, USA.
Jean LiSchool of Computing, University of Otago, Dunedin 9016, New Zealand.
Farzane Lal KhakpoorDepartment of Psychology, University of Otago, Dunedin 9016, New Zealand.
Jeremiah DengSchool of Computing, University of Otago, Dunedin 9016, New Zealand.
David IrelandDunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin 9016, New Zealand.
Sandhya RamrakhaDunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin 9016, New Zealand.
Narun PatDepartment of Psychology, University of Otago, Dunedin 9016, New Zealand.ORCID 0000-0003-1459-5255

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
MAPPING THE HUMAN CONNECTOME DURING TYPICAL AGINGU01AG052564 · NIA · WASHINGTON UNIVERSITY · PI SALAT, DAVID H, TERPSTRA, MELISSA J · 2016 to 2020
$18.9M
Quantifying Individual Differences in Midlife Structural Brain Integrity Associated with Later AD/ADRD RiskR01AG049789 · NIA · DUKE UNIVERSITY · PI AHMAD R. HARIRI, TERRIE E MOFFITT · 2015 to 2026
$10.6M
Is mental disorder a preventable cause of age-related disease? The Dunedin Study.R01AG032282 · NIA · DUKE UNIVERSITY · PI CASPI, AVSHALOM, MOFFITT, TERRIE E · 2009 to 2025
$9.5M
NIA NIH HHS R01 AG032282NIA NIH HHS R01 AG049789NIA NIH HHS U01 AG052564NIMH NIH HHS U54 MH091657
6 · The paper itself

Abstract

Brain-wide association studies (BWASs) have attempted to relate cognitive abilities with brain phenotypes, but have been challenged by issues such as predictability, test-retest reliability, and cross-cohort generalisability. To tackle these challenges, we proposed a machine-learning "stacking" approach that draws information from whole-brain magnetic resonance imaging (MRI) across different modalities, from task-fMRI contrasts and functional connectivity during tasks and rest to structural measures, into one prediction model. We benchmarked the benefits of stacking, using the Human Connectome Projects: Young Adults (n=873, 22-35 years old) and Human Connectome Projects-Aging (n=504, 35-100 years old) and the Dunedin Multidisciplinary Health and Development Study (Dunedin Study, n=754, 45 years old). For predictability, stacked models led to out-of-sample

Indexed as

Brain-Wide Association StudiesCognitive AbilitiesGeneralisabilityMajor Category: Biological SciencesMinor Category: Psychological and Cognitive SciencesReliabilityStackingTask fMRI

Identifiers

PMID38746222
PMCPMC11092590

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.