Behavioral and Neurophysiological Correlates of Auditory Attention in Monolinguals and Bilinguals
Bibliographic record
Abstract
Our current understanding of human cognition, language, and brain is primarily based on monolingual data, despite nearly half of Canada’s and the world’s population being bilingual. One consequence of fewer bilingual investigations is linguistically/culturally inappropriate speech-language pathology services delivered to the bilingual clientele. The overarching goal of this dissertation is to advance theories of monolingual and bilingual cognition and spoken language processing. While most theories emphasize cognitive control in the nonlinguistic domain, here we investigate cognitive resources allocated within a linguistic context (i.e., auditory attention during speech processing). Specifically, we conducted four studies examining auditory attention via behavioral and neurophysiological correlates. Study 1 is a systematic review and meta-analysis querying if a bilingual advantage—putative cognitive enhancement due to bilingual experience—exists in auditory attention, measured by standardized tests in children. As expected, we observed mixed findings in test performance among monolingual and bilingual children—given these tests may not be appropriate for bilingual assessment due to bias toward monolinguals. To understand whether language group differences occur when measurement bias is minimized, we used three neurophysiological methods to quantify attentional resources allocated in speech processing in monolingual and simultaneous bilingual young adults. Study 2 examines pupil dilation, an indicator of attentional effort, as participants actively listen to passages in a familiar or unfamiliar language. Results illustrate greater effort, reflected by larger pupil size, in bilinguals than monolinguals during spoken language processing, which is more effortful in monolinguals when it is unfamiliar. To further explore the autonomic nervous system, Study 3 assesses the feasibility of using heart rate to index attention allocation to speech. Results demonstrate its promising application: processing unfamiliar speech requires more attention than familiar speech, evidenced by lower heartbeats and a trend toward longer interbeat intervals. Study 4 explores neural oscillations and reveals that processing unfamiliar speech demands more attention in bilinguals given increased alpha suppression. Further, a shorter stay in an English-speaking home correlates with enhanced attention to familiar speech, reflected in larger theta power. Overall, our findings indicate that bilingual experience shapes attention allocation in speech processing, expanding bilingual research on cognition beyond the nonlinguistic domain.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".