Continuous Theta-Burst Stimulation in Children With High-Functioning Autism Spectrum Disorder and Typically Developing Children
Bibliographic record
Abstract
Objectives: A neurophysiologic biomarker for autism spectrum disorder (ASD) is highly desirable and can improve diagnosis, monitoring, and assessment of therapeutic response among children with ASD. We investigated the utility of continuous theta-burst stimulation (cTBS) applied to motor cortex (M1) as a biomarker for children and adolescents with high-functioning (HF) ASD compared to their age- and gender-matched typically developing (TD) controls. We also compared the developmental trajectory of long-term depression- (LTD-)like plasticity in the two groups. Finally, we explored the influence of a common BDNF polymorphism on cTBS aftereffects in a subset of the ASD group. Methods: Twenty-nine children and adolescents (age range 10–16) in ASD (n=11) and TD (n=18) groups underwent M1 cTBS. Changes in MEP amplitude at 5–60 minutes post-cTBS and their cumulative measures in each group were calculated. We also assessed the relationship between age and maximum cTBS-induced MEP suppression (∆MEPMax) in each group. Finally, we compared cTBS aftereffects in BDNF Val/Val (n=4) and Val/Met (n=4) ASD participants. Results: Cumulative cTBS aftereffects were significantly more facilitatory in the ASD group than in the TD group (PFDR’s 0.18). Conclusions: The results support the utility of cTBS measures of cortical plasticity as a biomarker for children and adolescents with HF ASD and an aberrant developmental trajectory of LTD-like plasticity 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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".