A Deficit in Face-Voice Integration in Developing Vervet Monkeys Exposed to Ethanol during Gestation
Bibliographic record
Abstract
Children with fetal alcohol spectrum disorders display behavioural and intellectual impairments that strongly implicate dysfunction within the frontal cortex. Deficits in social behaviour and cognition are amongst the most pervasive outcomes of prenatal ethanol exposure. Our naturalistic vervet monkey model of fetal alcohol exposure (FAE) provides an unparalleled opportunity to study the neurobehavioral outcomes of prenatal ethanol exposure in a controlled experimental setting. Recent work has revealed a significant reduction of the neuronal population in the frontal lobes of these monkeys. We used an intersensory matching procedure to investigate audiovisual perception of socially relevant stimuli in young FAE vervet monkeys. Here we show a domain-specific deficit in audiovisual integration of socially relevant stimuli. When FAE monkeys were shown a pair of side-by-side videos of a monkey concurrently presenting two different calls along with a single audio track matching the content of one of the calls, they were not able to match the correct video to the single audio track. This was manifest by their average looking time being equally spent towards both the matching and non-matching videos. However, a group of normally developing monkeys exhibited a significant preference for the non-matching video. This inability to integrate and thereby discriminate audiovisual stimuli was confined to the integration of faces and voices as revealed by the monkeys' ability to match a dynamic face to a complex tone or a black-and-white checkerboard to a pure tone, presumably based on duration and/or onset-offset synchrony. Together, these results suggest that prenatal ethanol exposure negatively affects a specific domain of audiovisual integration. This deficit is confined to the integration of information that is presented by the face and the voice and does not affect more elementary aspects of sensory integration.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".