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Record W2020617511 · doi:10.1155/2014/862048

The Role of Habenula in Motivation and Reward

2014· article· en· W2020617511 on OpenAlexaff
Marc Fakhoury, Sergio Domínguez López

Bibliographic record

VenueAdvances in Neuroscience · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHabenulaNeuroscienceForebrainPsychologyLimbic systemReward systemSchizophrenia (object-oriented programming)HindbrainCentral nervous systemPsychiatry

Abstract

fetched live from OpenAlex

Located centrally along the dorsal diencephalic system, the habenula is divided into two structures: the medial and the lateral portions. It serves as an important relay between the forebrain and several hindbrain sites. In the last few years, a huge attention has been devoted to this structure, especially the lateral habenula (LHb), which seems to play an important role in emotion, motivation, and reward. Recent studies using techniques such as electrophysiology and neuroimaging have shown that the LHb is involved in motivational control of behavior. Its dysfunction is often associated with depression, schizophrenia, and mood disorder. This review focuses on providing a neuroanatomical and behavioral overview of some of the research previously done on the LHb. First, we describe the anatomical structure of the habenula and we explain how it is involved in reward and motivation. Then, we will discuss how this structure is linked to the limbic system, to finally provide a comparison between several studies that have used electrolytic lesions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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

Citations14
Published2014
Admission routes1
Has abstractyes

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