Neural Activity during Story Listening Is Synchronized across Individuals Despite Acoustic Masking
Bibliographic record
Abstract
Older people with hearing problems often experience difficulties understanding speech in the presence of background sound. As a result, they may disengage in social situations, which has been associated with negative psychosocial health outcomes. Measuring listening (dis)engagement during challenging listening situations has received little attention thus far. We recruit young, normal-hearing human adults (both sexes) and investigate how speech intelligibility and engagement during naturalistic story listening is affected by the level of acoustic masking (12-talker babble) at different signal-to-noise ratios (SNRs). In , we observed that word-report scores were above 80% for all but the lowest SNR (-3 dB SNR) we tested, at which performance dropped to 54%. In , we calculated intersubject correlation (ISC) using EEG data to identify dynamic spatial patterns of shared neural activity evoked by the stories. ISC has been used as a neural measure of participants' engagement with naturalistic materials. Our results show that ISC was stable across all but the lowest SNRs, despite reduced speech intelligibility. Comparing ISC and intelligibility demonstrated that word-report performance declined more strongly with decreasing SNR compared to ISC. Our measure of neural engagement suggests that individuals remain engaged in story listening despite missing words because of background noise. Our work provides a potentially fruitful approach to investigate listener engagement with naturalistic, spoken stories that may be used to investigate (dis)engagement in older adults with hearing impairment.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".