Evidence map›Paper›PMID 42675178›Full record

ReviewMolecular psychiatry2026

Organoid intelligence: a promising paradigm for autism spectrum disorder research.

Xitong Zuo, Xinggao Zhang, Yulong Liu, Xin Li, Meiling Xia, Yuanyuan Ma, Xiaotang Fan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular psychiatry, 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

7 authors.

Xitong ZuoDepartment of Military Cognitive Psychology, School of Psychology, Army Medical University, Chongqing, 400038, China.
Xinggao ZhangDepartment of Military Cognitive Psychology, School of Psychology, Army Medical University, Chongqing, 400038, China.
Yulong LiuDepartment of Military Cognitive Psychology, School of Psychology, Army Medical University, Chongqing, 400038, China.
Xin LiArmy 953 Hospital, Shigatse Branch of Xinqiao Hospital, Army Medical University, Shigatse, 857000, China.
Meiling XiaDepartment of Military Cognitive Psychology, School of Psychology, Army Medical University, Chongqing, 400038, China.
Yuanyuan MaDepartment of Anesthesiology, The Affiliated Yongchuan Hospital of Chongqing Medical University, Chongqing, 402160, China. mayuan21991@126.com.
Xiaotang FanDepartment of Military Cognitive Psychology, School of Psychology, Army Medical University, Chongqing, 400038, China. fanxiaotang@tmmu.edu.cn.ORCID http://orcid.org/0000-0001-5694-1828

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition marked by heterogeneity in its clinical presentations, which complicates both its diagnosis and treatment. Despite advancements, the molecular mechanisms underlying ASD remain largely unclear. In recent years, two independent yet highly promising technological domains have made significant advancements: organoids and artificial intelligence (AI). Brain organoids can simulate critical processes of human neurodevelopment in both physiological and pathological states, providing an unprecedented window into the mechanisms and potential therapeutics of ASD. Simultaneously, AI has demonstrated formidable capabilities for processing and analyzing large-scale, high-dimensional biomedical data, and has been effectively applied to ASD imaging analysis, genomics research, and behavioral data interpretation. However, these two fields have developed mainly in parallel, leaving their potential for cross-disciplinary integration untapped in ASD research. This review aims to fill this gap by reviewing the current status and limitations of both fields in the context of ASD, and to elucidate a promising research paradigm that integrates AI with brain organoids, called "organoid intelligence", to enhance our understanding of predictive models, unravel ASD pathogenesis, and develop more effective and individualized therapies.

Identifiers

What OpenQuestion holds

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Registered trials

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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.