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Record W4318169236 · doi:10.1192/bjp.2022.157

Processing of social and monetary rewards in autism spectrum disorders

2023· article· en· W4318169236 on OpenAlexaff
Sarah Baumeister, Carolin Moessnang, Nico Bast, Sarah Hohmann, Pascal-M. Aggensteiner, Anna Kaiser, Julian Tillmann, David Goyard, Tony Charman, Sara Ambrosino, Simon Baron‐Cohen, Christian F. Beckmann, Sven Bölte, Thomas Bourgeron, Annika Rausch, Daisy Crawley, Flavio Dell’Acqua, Guillaume Dumas, Sarah Durston, Christine Ecker, Dorothea L. Floris, Vincent Frouin, Hannah Hayward, Rosemary Holt, Mark H. Johnson, Emily J. H. Jones, Meng‐Chuan Lai, Michael Lombardo, Luke Mason, Bethany Oakley, Marianne Oldehinkel, Antonio M. Persico, Antonia San José Cáceres, Thomas Wolfers, Eva Loth, Declan Murphy, Jan K. Buitelaar, Heike Tost, Andreas Meyer‐Lindenberg, Tobias Banaschewski, Daniel Brandeis

Bibliographic record

VenueThe British Journal of Psychiatry · 2023
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoSickKids FoundationCentre for Addiction and Mental Health
FundersCilagMedical Research CouncilHector Stiftung IIH. Lundbeck A/SInnovative Medicines InitiativeUniversität HeidelbergAutisticaServierRadboud UniversiteitSiemens HealthineersKarolinska InstitutetLundbeckfondenÉcole Polytechnique Fédérale de LausanneUniversity of OxfordEuropean College of NeuropsychopharmacologyKing's College LondonFondation FondaMentalSage TherapeuticsAgence Nationale de la RechercheEuropean Federation of Pharmaceutical Industries and AssociationsAutism SpeaksSimons Foundation Autism Research InitiativeUniversität WienHector StiftungDaimler und Benz StiftungUniversiteit UtrechtEuropean CommissionPfizer
KeywordsVentral striatumAnticipation (artificial intelligence)Autism spectrum disorderPsychologyReward systemFunctional magnetic resonance imagingAutismReward dependenceCognitive psychologyDevelopmental psychologyStriatumNeuroscienceAudiologyMedicineNovelty seekingSocial psychology

Abstract

fetched live from OpenAlex

Background Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD. Aims Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD. Method Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6–30.6 years of age) and 181 typically developing participants (7.6–30.8 years of age). Results Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD. Conclusions Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.293
Teacher spread0.274 · 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 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

Citations37
Published2023
Admission routes1
Has abstractyes

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