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Record W2104277879 · doi:10.1177/0956797612457380

The Neural Basis of Difficulties Disengaging From Negative Irrelevant Material in Major Depression

2013· article· en· W2104277879 on OpenAlexaff
Lara C. Foland‐Ross, J. Paul Hamilton, Jutta Joormann, Marc G. Berman, John Jonides, Ian H. Gotlib

Bibliographic record

VenuePsychological Science · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersNational Institute of Mental HealthJohns Hopkins University
KeywordsPsychologyCognitionNeuroimagingNeural correlates of consciousnessDepression (economics)Association (psychology)NeuroscienceWorking memoryFunctional neuroimagingDorsumTask (project management)Cognitive psychologyDevelopmental psychologyMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Recurrent uncontrollable negative thoughts are a hallmark of depressive episodes. Deficits in cognitive control have been proposed to underlie this debilitating aspect of depression. Here, we used functional neuroimaging during an emotional working memory (WM) task to elucidate the neural correlates of these difficulties in cognitive control. In a WM manipulation involving depressed participants, the dorsal anterior cingulate and parietal and bilateral insular cortices were activated significantly more when negative words were removed from WM than when they were maintained in WM; in contrast, nondepressed participants exhibited stronger neural activations in these regions for positive than for negative material. These findings implicate anomalous activation of components of the task-positive network, known to be modulated by cognitive effort, in depression-associated difficulties in expelling negative material from WM. Future studies should examine the association between these aberrations and the maintenance of depressive symptoms.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.098
GPT teacher head0.378
Teacher spread0.280 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations65
Published2013
Admission routes1
Has abstractyes

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