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Record W2903634660 · doi:10.1101/496729

Empirical examination of the replicability of associations between brain structure and psychological variables

2018· preprint· en· W2903634660 on OpenAlexfundno aff
Shahrzad Kharabian Masouleh, Simon B. Eickhoff, Felix Hoffstaedter, Sarah Genon

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
FundersNational Institute on AgingNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchNational Institutes of HealthGenentechIXICOH. Lundbeck A/SServierEisaiDeutsche ForschungsgemeinschaftNorthern California Institute for Research and EducationPfizerBiogenBioClinicaF. Hoffmann-La RocheUniversity of Southern CaliforniaEuropean CommissionEli Lilly and CompanyU.S. Department of DefenseMeso Scale DiagnosticsAlzheimer's Disease Neuroimaging InitiativeNovartis Pharmaceuticals CorporationBristol-Myers SquibbAlzheimer's AssociationFoundation for the National Institutes of Health
KeywordsPsychologyBrain morphometryBrain sizeAssociation (psychology)CognitionClinical psychologySample size determinationNeuroimagingMedicineNeurosciencePsychotherapistStatistics

Abstract

fetched live from OpenAlex

Abstract Linking interindividual differences in psychological phenotype to variations in brain structure is an old dream for psychology and a crucial question for cognitive neurosciences. Yet, replicability of the previously-reported “structural brain behavior” (SBB)-associations has been questioned, recently. Here, we conducted an empirical investigation, assessing replicability of SBB among heathy adults. For a wide range of psychological measures, the replicability of associations with gray matter volume was assessed. Our results revealed that among healthy individuals 1) finding an association between performance at standard psychological tests and brain morphology is relatively unlikely 2) significant associations, found using an exploratory approach, have overestimated effect sizes and 3) can hardly be replicated in an independent sample. After considering factors such as sample size and comparing our findings with more replicable SBB-associations in a clinical cohort and replicable associations between brain structure and non-psychological phenotype, we discuss the potential causes and consequences of these findings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.087
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.298
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainReproducibility
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2018
Admission routes1
Has abstractyes

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