Neurofunctional Underpinnings of Audiovisual Emotion Processing in Teens with Autism Spectrum Disorders
Bibliographic record
Abstract
Despite successful performance on some audiovisual emotion tasks, hypoactivity has been observed in frontal and temporal integration cortices in individuals with autism spectrum disorders (ASD). Little is understood about the neurofunctional network underlying this ability in individuals with ASD. Research suggests that there may be processing biases in individuals with ASD, based on their ability to obtain meaningful information from the face and/or the voice. This functional magnetic resonance imaging study examined brain activity in teens with ASD (n = 18) and typically developing controls (n = 16) during audiovisual and unimodal emotion processing. Teens with ASD had a significantly lower accuracy when matching an emotional face to an emotion label. However, no differences in accuracy were observed between groups when matching an emotional voice or face-voice pair to an emotion label. In both groups brain activity during audiovisual emotion matching differed significantly from activity during unimodal emotion matching. Between-group analyses of audiovisual processing revealed significantly greater activation in teens with ASD in a parietofrontal network believed to be implicated in attention, goal-directed behaviors, and semantic processing. In contrast, controls showed greater activity in frontal and temporal association cortices during this task. These results suggest that in the absence of engaging integrative emotional networks during audiovisual emotion matching, teens with ASD may have recruited the parietofrontal network as an alternate compensatory system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".