Attentional demands modulate sensorimotor learning induced by persistent exposure to changes in auditory feedback
Bibliographic record
Abstract
Hearing one's own voice is important for regulating ongoing speech and for mapping speech sounds onto articulator movements. However, it is currently unknown whether attention mediates changes in the relationship between motor commands and their acoustic output, which are necessary as growth and aging inevitably cause changes to the vocal tract. In this study, participants produced vocalizations while they heard their vocal pitch persistently shifted downward one semitone in both single- and dual-task conditions. During the single-task condition, participants vocalized while passively viewing a visual stream. During the dual-task condition, participants vocalized while also monitoring a visual stream for target letters, forcing participants to divide their attention. Participants' vocal pitch was measured across each vocalization, to index the extent to which their ongoing vocalization was modified as a result of the deviant auditory feedback. Smaller compensatory responses were recorded during the dual-task condition, suggesting that divided attention interfered with the use of auditory feedback for the regulation of ongoing vocalizations. Participants' vocal pitch was also measured at the beginning of each vocalization, before auditory feedback was available, to assess the extent to which the deviant auditory feedback was used to modify subsequent speech motor commands. Smaller changes in vocal pitch at vocalization onset were recorded during the dual-task condition, suggesting that divided attention diminished sensorimotor learning. Together, the results of this study suggest that attention is required for the speech motor control system to make optimal use of auditory feedback for the regulation and planning of speech motor commands.
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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 | 0.001 |
| 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".