Pairing with Enriched Sound Exposure Restores Auditory Processing Degraded by an Antidepressant
Bibliographic record
Abstract
Antidepressants, while effective in treating depression and anxiety disorders, also induce deficits in sensory (particularly auditory) processing, which in turn may exacerbate psychiatric symptoms. How antidepressants cause auditory signature deficits remains largely unknown. Here, we found that fluoxetine-treated adult female rats were significantly less accurate when performing a tone-frequency discrimination task compared with age-matched control rats. Their cortical neurons also responded less selectively to sound frequencies. The degraded behavioral and cortical processing was accompanied by decreased cortical perineuronal nets, particularly those wrapped around parvalbumin-expressing inhibitory interneurons. Furthermore, fluoxetine induced critical period-like plasticity in their already mature auditory cortices; therefore, a brief rearing of these drug-treated rats under an enriched acoustic environment renormalized auditory processing degraded by fluoxetine. The altered cortical expression of perineuronal nets was also reversed as a result of enriched sound exposure. These findings suggest that the adverse effects of antidepressants on auditory processing, possibly because of a reduction in intracortical inhibition, can be substantially alleviated by simply pairing drug treatment with passive, enriched sound exposure. They have important implications for understanding the neurobiological basis of antidepressant effects on hearing and for designing novel pharmacological treatment strategies for psychiatric disorders. SIGNIFICANCE STATEMENTClinical experience suggests that antidepressants adversely affect sensory (particularly auditory) processing, which can exacerbate patients' psychiatric symptoms. Here, we show that the antidepressant fluoxetine reduces cortical inhibition in adult rats, leading to degraded behavioral and cortical spectral processing of sound. Importantly, fluoxetine induces a critical period-like state of plasticity in the mature cortex; therefore, a brief rearing under an enriched acoustic environment is sufficient to reverse the changes in auditory processing caused by the administration of fluoxetine. These results provide a putative neurobiological basis for the effects of antidepressants on hearing and indicate that antidepressant treatment combined with enriched sensory experiences could optimize clinical outcomes.
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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) | 0.000 | 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 | 0.001 |
| 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 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".