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Record W2590236599 · doi:10.1038/ncomms14140

Blunted ventral striatal responses to anticipated rewards foreshadow problematic drug use in novelty-seeking adolescents

2017· article· en· W2590236599 on OpenAlexaff
Christian Büchel, Jan Peters, Tobias Banaschewski, Arun L.W. Bokde, Uli Bromberg, Patricia Conrod, Herta Flor, Dimitri Papadopoulos, Hugh Garavan, Penny Gowland, Andreas Heinz, Henrik Walter, Bernd Ittermann, Karl Mann, Jean‐Luc Martinot, Marie‐Laure Paillère Martinot, Frauke Nees, Tomáš Paus, Zdenka Pausová, Luise Poustka, Marcella Rietschel, Trevor W. Robbins, Michael N. Smolka, Juergen Gallinat, Günter Schumann, Brian Knutson, Mercedes Arroyo, Éric Artiges, Semiha Aydın, Christine Bach, Alexis Barbot, Gareth J. Barker, Ruediger Bruehl, Anna Cattrell, Patrick Constant, Hans S. Crombag, Katharina Czech, Jeffrey W. Dalley, Benjamin Decideur, Sylvane Desrivières, Tahmine Fadai, Mira Fauth‐Bühler, Jianfeng Feng, Irinia Filippi, Vincent Frouin, Birgit Fuchs, Isabel Gemmeke, Alexander Genauck, Éanna Hanratty, Bert Heinrichs, Nadja Heym, Thomas Hübner, Albrecht Ihlenfeld, Alex Ing, James Ireland, Tianye Jia, Jennifer Jones, Sarah Jurk, Mehri Kaviani, Arno Klaassen, Johann Kruschwitz, Christophe Lalanne, Dirk Lanzerath, Mark Lathrop, Claire Lawrence, Hervé Lemaître, Christine Macare, Catherine Mallik, Adam C. Mar, Lourdes Martinez-Medina, Eva Mennigen, Fabiana Mesquita de Carvahlo, Xavier Mignon, Sabina Millenet, Rubén Miranda, Kathrin Müller, Charlotte Nymberg, Caroline Parchetka, Yolanda Peña‐Oliver, Jani Pentillä, Jean‐Baptiste Poline, Erin Burke Quinlan, Michael A. Rapp, Stephan Ripke, Tamzin L. Ripley, Guillaume Robert, John Rogers, Alexander Romanowski, Barbara Ruggeri, Christine Schmäl, Dirk Schmidt, Sophia Schneider, Yannick Schwartz, Wolfgang H. Sommer, Rainer Spanagel, Claudia Speiser, Tade Matthias Spranger, Alicia Stedman, D.N. Stephens, Nicole Strache, Andreas Ströhle, Maren Struve, Naresh Subramaniam, David Theobald, Nora C. Vetter, Hélène Vulser, Katharina Weiß, Robert Whelan, Steven Williams, Bing Xu, Juliana Yacubian, Tao Yu, Veronika Ziesch

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsMcGill UniversityHospital for Sick ChildrenMcGill University and Génome Québec Innovation CentreBaycrest HospitalToronto Rehabilitation InstituteSickKids FoundationUniversity of TorontoMontreal Neurological Institute and HospitalUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersBundesministerium für Bildung und ForschungDeutsche Forschungsgemeinschaft
KeywordsNoveltyNovelty seekingPsychologyDrugNeuroscienceBiologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Novelty-seeking tendencies in adolescents may promote innovation as well as problematic impulsive behaviour, including drug abuse. Previous research has not clarified whether neural hyper- or hypo-responsiveness to anticipated rewards promotes vulnerability in these individuals. Here we use a longitudinal design to track 144 novelty-seeking adolescents at age 14 and 16 to determine whether neural activity in response to anticipated rewards predicts problematic drug use. We find that diminished BOLD activity in mesolimbic (ventral striatal and midbrain) and prefrontal cortical (dorsolateral prefrontal cortex) regions during reward anticipation at age 14 predicts problematic drug use at age 16. Lower psychometric conscientiousness and steeper discounting of future rewards at age 14 also predicts problematic drug use at age 16, but the neural responses independently predict more variance than psychometric measures. Together, these findings suggest that diminished neural responses to anticipated rewards in novelty-seeking adolescents may increase vulnerability to future problematic drug use.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.096
GPT teacher head0.380
Teacher spread0.284 · 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 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

Citations119
Published2017
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicNeurotransmitter Receptor Influence on BehaviorFrench-language works237,207