Hot Executive Function in Autism Spectrum Disorder: A Brief Narrative Review
Bibliographic record
Abstract
Executive function (EF), encompassing high-order cognitive processes essential for goal-directed behavior, is often impaired in Autism Spectrum Disorder (ASD). This review addresses the problem of limited understanding regarding the distinction between “cool” and “hot” EF, their respective manifestations, and developmental trajectories in ASD. While cool EF in ASD has been widely investigated, the impairments and development of hot EF are less explored despite potentially also playing a role in ASD's socio-cognitive challenges. The purpose of this narrative review is to synthesize existing literature on hot EF and its development in ASD, particularly in relation to cool EF. Our approach involves a comprehensive examination of current studies to identify gaps and propose directions for future research. The review highlights the scarcity of studies on hot EF in ASD and concludes that targeted interventions should address both cool and hot EF deficits. Future research directions include longitudinal studies, neural investigations, and culturally diverse samples to further elucidate the role of hot EF in ASD. Understanding these distinctions can refine intervention strategies, ultimately enhancing support for individuals with ASD.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".