Neural signatures of engagement and event segmentation during story listening in background noise
Bibliographic record
Abstract
Abstract Speech in everyday life is often masked by background noise, making comprehension effortful. Characterizing brain activity patterns when individuals listen to masked speech can help clarify the mechanisms underlying such effort. However, most previous research has focused on neural activity related to short, disconnected sentences that little resemble the more continuous, story-like spoken speech individuals typically encounter. In the current study, we used functional magnetic resonance imaging (fMRI) in humans (both sexes) to investigate how neural signatures of story listening change in the presence of masking by 12-talker babble noise. We show that, as speech masking increases, spatial and temporal activation patterns in auditory regions become more idiosyncratic to each listener. In contrast, spatial (and to some extent temporal) activity patterns in brain networks linked to effort (e.g. cinguloopercular network involving the anterior insula and anterior cingulate) are more similar across listeners when speech is highly masked and less intelligible, suggesting shared neural processes. Moreover, at times during stories when one meaningful event ended and another began, neural activation increased over extensive regions in frontal, parietal, and medial cortices. This event-boundary response appeared little affected by background noise, suggesting that listeners process meaningful units and, in turn, the gist in naturalistic, continuous speech even when it is masked somewhat by background noise. Overall, the current data may indicate that people stay engaged and cognitive processes associated with naturalistic speech processing remain intact under moderate levels of background noise, whereas auditory processing becomes more idiosyncratic to each listener. Significance statement This functional imaging study investigates how neural signatures of story listening change in the presence of masking multi-talker babble noise. We show that, as speech masking increases, auditory activity patterns become more idiosyncratic to each listener. Spatial activation patterns in effort-related regions (anterior insula, cingulate) become more similar across listeners when speech is strongly masked, indicating shared neural representations. Neural activation also increased at times when one meaningful story event ended and another began. This event-boundary response appeared little affected by moderate levels of background noise, suggesting that listeners process meaningful units in continuous speech even as background babble reduces speech intelligibility. The data indicate that many cognitive processes associated with listening to spoken stories remain intact under background noise.
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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 | 0.002 |
| 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 | 0.000 |
| 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".