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Record W4394687606 · doi:10.31234/osf.io/2jgvx

The Habenula in Mood Disorders: A Scoping Review of Human Studies

2024· review· en· W4394687606 on OpenAlexaff
Jean‐Simon Fortin, Mathilde Lafleur, Charles Parisien, Sébastien Hétu

Bibliographic record

Venuenot available
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicZiziphus Jujuba Studies and Applications
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMoodHabenulaMood disordersPsychologyCognitive psychologyNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

In animal models, the habenula has been identified as a key structure involved in depression. Thanks to recent technological advancements, a burgeoning body of work has also investigated the habenula in the context of human mood disorders. This scoping review aims to synthesize findings from human studies that pertain to the habenula and its relationship with mood disorders. The review was conducted according to PRISMA guidelines. The literature search was performed with PubMed and yielded 93 articles, of which 50 articles were included in the review. We found that the evidence for baseline habenular hyperactivity in human depression is mixed. As for findings from resting-state functional connectivity (RSFC) studies, they were mainly inconsistent across studies. Moreover, we found no evidence indicating that mood disorders are linked to changes in the volume of the habenula. In order to enhance the replicability of findings, given the small size of the habenula, higher image resolution and larger samples are recommended for future studies.

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0130.011
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.148
GPT teacher head0.436
Teacher spread0.287 · 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 designSystematic review
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

Citations0
Published2024
Admission routes1
Has abstractyes

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