Impaired Processing in the Primary Auditory Cortex of an Animal Model of Autism
Bibliographic record
Abstract
Autism is a neurodevelopmental disorder clinically characterized by deficits in communication, lack of social interaction and repetitive behaviors with restricted interests. A number of studies have reported that sensory perception abnormalities are common in autistic individuals and might contribute to the complex behavioral symptoms of the disorder. In this context, hearing incongruence is particularly prevalent. Considering that some of this abnormal processing might stem from the unbalance of inhibitory and excitatory drives in brain circuitries, we used an animal model of autism induced by valproic acid (VPA) during pregnancy in order to investigate the tonotopic organization of the primary auditory cortex (AI) and its local inhibitory circuitry. Our results show that VPA rats have distorted primary auditory maps with over-representation of high frequencies, broadly tuned receptive fields and higher sound intensity thresholds as compared to controls. However, we did not detect differences in the number of parvalbumin-positive interneurons in AI of VPA and control rats. Altogether our findings show that neurophysiological impairments of hearing perception in this autism model occur independently of alterations in the number of parvalbumin-expressing interneurons. These data support the notion that fine circuit alterations, rather than gross cellular modification, could lead to neurophysiological changes in the autistic brain.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".