Neuroplasticity in autism spectrum disorder: a systematic review
Bibliographic record
Abstract
The brain's ability to adapt in response to stimuli is called neuroplasticity. Objective: This study investigates neuroplasticity in autistic individuals, focusing on neurobiological aspects, clinical correlations, and therapeutic interventions. Methods: This systematic review, registered in the International Prospective Register of Systematic Reviews-PROSPERO (ID: CRD42024522425) and guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses-PRISMA (2020) criteria, searched databases like Web of Science, Scopus, United States National Library of Medicine/ Medical Literature Analysis and Retrieval System Online (PubMed/Medline), Latin American and Caribbean Health Sciences Literature (LILACS), and Scientific Electronic Library Online (SciELO) for original articles published in 2018-2023. Results: Of the 2,316 studies found, 11 were selected, involving 1,943 autistic individuals, both children and adults. Most studies were classified as high/moderate quality using the Newcastle-Ottawa and Jadad scales. Observations included variations in SHANK2 gene expression, lower concentrations of α-synuclein, higher β-synuclein in children with autism spectrum disorder (ASD), correlations between NCAM1 expression and motor skills, and higher brain-derived neurotrophic factor (BDNF) concentration compared to non-autistic children. Conclusions: Alterations in SHANK2, α-synuclein, β-synuclein, NCAM1, and BDNF in ASD suggest biomarkers and therapeutic targets for more effective interventions, improving care for autistic individuals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".