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Does dopamine dysfunction drive depression?

2007· review· en· W2073017306 on OpenAlexaff
Gin S. Malhi, Michael Berk

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2007
Typereview
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsAstraZeneca (Canada)
Fundersnot available
KeywordsMelancholiaMelancholic depressionPsychologyDepression (economics)CognitionPsychiatryClinical psychologyNeuroscienceCognitive psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the evidence that dopamine (DA) dysfunction contributes to melancholic depression. METHOD: Database (EMBASE, PsychLit and MEDLINE) searches using relevant key words were conducted and citations were scrutinized. RESULTS: In this paper, we assume that the definition of melancholia is contingent upon the presence of psychomotor disturbance (PMD). In melancholic depression PMD comprises both a cognitive and motor component and DA is found to be important in both. DA neurotransmission modulates cognition in particular in attention, adaptation and motivational processes and has a pivotal role in motor function. CONCLUSION: DA is a credible aetiological candidate for the PMD in melancholic depression. However, melancholia needs first to be characterized both clinically and in terms of its pathophysiology. In this regard, illnesses such as bipolar depression and Parkinson's disease warrant consideration as they provide suitable models of both the cognitive and motor aspects of PMD, and hold the necessary markers to better define melancholia.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.044
GPT teacher head0.390
Teacher spread0.346 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations85
Published2007
Admission routes1
Has abstractyes

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