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Homeostasis Meets Motivation in the Battle to Control Food Intake

2016· review· en· W2556106115 on OpenAlexaff
Carrie R. Ferrario, Gwenaël Labouèbe, Shuai Liu, Edward H. Nieh, Vanessa H. Routh, Shengjin Xu, Eoin C. O’Connor

Bibliographic record

VenueJournal of Neuroscience · 2016
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of Calgary
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesAmerican Heart AssociationNational Institutes of HealthNational Science Foundation
KeywordsNeuroscienceBiological neural networkEnergy homeostasisFood intakeVentral tegmental areaHomeostasisHypothalamusPsychologyObesityEnergy expenditureBiologyEndocrinology

Abstract

fetched live from OpenAlex

Signals of energy homeostasis interact closely with neural circuits of motivation to control food intake. An emerging hypothesis is that the transition to maladaptive feeding behavior seen in eating disorders or obesity may arise from dysregulation of these interactions. Focusing on key brain regions involved in the control of food intake (ventral tegmental area, striatum, hypothalamus, and thalamus), we describe how activity of specific cell types embedded within these regions can influence distinct components of motivated feeding behavior. We review how signals of energy homeostasis interact with these regions to influence motivated behavioral output and present evidence that experience-dependent neural adaptations in key feeding circuits may represent cellular correlates of impaired food intake control. Future research into mechanisms that restore the balance of control between signals of homeostasis and motivated feeding behavior may inspire new treatment options for eating disorders and obesity.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.993
Threshold uncertainty score0.831

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.095
GPT teacher head0.331
Teacher spread0.236 · 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 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

Citations215
Published2016
Admission routes1
Has abstractyes

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