Assessing plasticity in the primary sensory cortex and its relation with atypical tactile reactivity in autism: A TMS-EEG protocol
Bibliographic record
Abstract
BACKGROUND: Atypical sensory reactivity is a cardinal presentation in autism. Within the tactile domain, atypical tactile reactivity (TR) is common, it emerges early, persists into adulthood, and impedes social interaction and daily functioning. Hence, atypical TR is a key target for biological intervention to improve outcomes. Brain mechanisms informing biological interventions for atypical TR remains elusive. We previously reported hyper-plasticity in the motor cortex in autistic adults and found that repetitive transcranial magnetic stimulation (rTMS), designed to strengthen inhibitory processes in the brain, reduced hyper-plasticity. Whether the primary sensory cortex (S1) is characterized by hyper-plasticity, which may underlie atypical TR in autism is unknown. OBJECTIVES: We aim to test whether hyper-plasticity in the S1 underlies atypical TR in autism, and investigate if a single session of rTMS can safely reduce hyper-plasticity in S1 in autistic adults. METHOD: Plasticity will be assessed in the left S1 with integrated paired associative stimulation and electroencephalography (PAS-EEG) paradigm in 32 autistic adults and 32 age-, sex-, and intelligence quotient-matched controls. Autistic participants will be further randomized (double-blind, 1:1) to receive a single-session of either sham or active 20 Hz bilateral rTMS over the S1 and the plasticity will be re-assessed over the left S1 on the same day. CONCLUSIONS: Atypical TR has been identified as one of the top clinical research priorities that can influence outcome in autistic population. The study findings can be highly valuable to further elucidate the mechanism underlying atypical TR, which in turn can help with developing a mechanism-driven intervention.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".