MétaCan
Menu
Back to cohort
Record W2775502108 · doi:10.1027/2151-2604/a000307

Frontostriatal Connectivity During Reward Anticipation

2017· article· en· W2775502108 on OpenAlexaff
Alena Becker, Martin Fungisai Gerchen, Martina Kirsch, Bettina Ubl, Sivaniya Subramaniapillai, Carsten Diener, Christine Kuehner, Falk Kiefer, Peter Kirsch

Bibliographic record

VenueZeitschrift für Psychologie · 2017
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsVentral striatumAnticipation (artificial intelligence)Alcohol use disorderPsychologyFunctional magnetic resonance imagingDepression (economics)StriatumNeuroscienceComorbidityDorsumBipolar disorderAlcohol dependenceClinical psychologyPsychiatryMedicineAlcoholCognitionBiology

Abstract

fetched live from OpenAlex

Abstract. Neurobiological research indicates that altered reward processing is among the most promising risk mechanisms in alcohol use disorder and depression. To elucidate differences and similarities between both disorders, we investigated clinical patients and at-risk individuals in two studies using a functional magnetic resonance imaging (fMRI) monetary reward paradigm. In the first study, alcohol use disorder patients compared to depressed and healthy individuals showed increased activation of the ventral striatum during reward anticipation. In contrast, both patient groups showed reduced frontostriatal connectivity compared to controls. In the second study, at-risk comorbid individuals showed decreased activation in the dorsal striatum along with decreased frontostriatal connectivity. While the connectivity results replicate the common pattern found for the patient groups, the activation results indicate a more depression-related pattern in individuals prone to developing both disorders. In conclusion, frontostriatal connectivity might be a promising transdiagnostic marker for depression, alcohol use disorder, and their comorbidity.

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)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.613
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.111
GPT teacher head0.383
Teacher spread0.272 · 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.

Study designObservational
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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueZeitschrift für PsychologieSame topicFunctional Brain Connectivity StudiesFrench-language works237,207