Neural Processing of Musical and Vocal Emotions Through Cochlear Implants Simulation
Bibliographic record
Abstract
Cochlear implants (CIs) partially restore the sense of hearing in the deaf. However, the ability to recognize emotions in speech and music is reduced due to the implant's electrical signal limitations and the patient's altered neural pathways. Electrophysiological correlations of these limitations are not yet well established. Here we aimed to characterize the effect of CIs on auditory emotion processing and, for the first time, directly compare vocal and musical emotion processing through a CI-simulator. We recorded 16 normal hearing participants' electroencephalographic activity while listening to vocal and musical emotional bursts in their original form and in a degraded (CI-simulated) condition. We found prolonged P50 latency and reduced N100-P200 complex amplitude in the CI-simulated condition. This points to a limitation in encoding sound signals processed through CI simulation. When comparing the processing of vocal and musical bursts, we found a delay in latency with the musical bursts compared to the vocal bursts in both conditions (original and CI-simulated). This suggests that despite the cochlear implants' limitations, the auditory cortex can distinguish between vocal and musical stimuli. In addition, it adds to the literature supporting the complexity of musical emotion. Replicating this study with actual CI users might lead to characterizing emotional processing in CI users and could ultimately help develop optimal rehabilitation programs or device processing strategies to improve CI users' quality of life.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".