Evidence map›Paper›PMID 42742391›Full record

ReviewSocial cognitive and affective neuroscience2026

Reward processing differences in autism: current understandings and future directions.

Kathryn E Unruh, Matthew W Mosconi

Abstract readReview
In one paragraph

Review in Social cognitive and affective neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Kathryn E UnruhLife Span Institute and Kansas Center for Autism Research and Training, University of Kansas, Lawrence, KS 66045, United States.ORCID 0000-0001-6745-5550
Matthew W MosconiLife Span Institute and Kansas Center for Autism Research and Training, University of Kansas, Lawrence, KS 66045, United States.

Funding

Institutional Career Development CoreKL2TR002367 · NCATS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI MATTHEW W MOSCONI, NICOLE L NOLLEN · 2017 to 2026
$7.3M
NCATS NIH HHS KL2 TR002367NCATS NIH HHS KL2TR002367
6 · The paper itself

Abstract

Differences in reward processing repeatedly have been implicated in autism. Still, the contexts in which these differences occur (e.g. social and non-social) and the extent to which they relate to autistic traits remain poorly understood. Notably, current frameworks for reward processing have yet to describe the impacts of reward processing differences on broader cognitive domains in autism. Evidence from studies of neurotypical individuals and non-human primates shows that reward has significant impacts on multiple cognitive domains, including executive control processes that have been linked to core social communication and repetitive behavior traits in autism. These findings suggest that examining reward processes in relation to cognitive functions in autism may provide important insights into neural systems that contribute to multiple developmental abilities and psychiatric features common to autism. In this review, we present a new, testable model that describes how interactions between reward and cognitive domains may have additive or synergistic contributions to key clinical traits in autism. This model is framed in context of existing evidence for reward processing differences in autism and their relationship to clinical features, as well as broader implications for expanding existing reward-based frameworks in this population.

Indexed as

Autistic DisorderRewardAnimalsCognitionExecutive FunctionHumansautismcognitionexecutive functionreward

Identifiers

PMID42742391
PMCPMC13649182

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.