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Record W2147922574 · doi:10.1093/scan/nsp042

Adult attachment insecurity and hippocampal cell density

2009· article· en· W2147922574 on OpenAlexaff
Markus Quirin, Omri Gillath, Jens C. Pruessner, Lucas D. Eggert

Bibliographic record

VenueSocial Cognitive and Affective Neuroscience · 2009
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsMcGill University
FundersDeutsche Forschungsgemeinschaft
KeywordsPsychologyAnxietyHippocampal formationInsecure attachmentAttachment theoryYoung adultDevelopmental psychologyDepression (economics)Clinical psychologyNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

Recent findings associate attachment insecurity (assessed as levels of attachment anxiety and avoidance) with poor emotion regulation. In turn, emotion regulation has been shown to be associated with hippocampus (HC) functioning and structure. Clinical disorders such as depression and PTSD, which have been previously associated with attachment insecurity, are also known to be linked with reduced hippocampal cell density. This suggests that attachment insecurity may also be associated with reduced hippocampal cell density. We examined this hypothesis using T1 images of 22 healthy young adults. In line with our hypothesis, attachment avoidance was associated with bilateral HC reduction, whereas attachment anxiety was significantly related to reduced cell concentration in the left HC. The findings are compatible with a neurotoxical model of stress-induced cell reduction in the HC, providing further information on emotion regulation abilities among insecurely attached individuals.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.370
Teacher spread0.349 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
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

Citations72
Published2009
Admission routes1
Has abstractyes

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