IMPACT OF AUDITORY ATTENTION ON THE EFFERENT AUDITORY SYSTEM IN THE ABSENCE OF REAL AUDITORY TARGETS.
Bibliographic record
Abstract
Previous studies have compared visual and auditory attention to no-task conditions and have demonstrated an attentiondriven modulation of the efferent auditory system (De Boer & Thornton, 2007;Maison, Micheyl, & Collet, 2001).However, it is unclear whether these effects are modality-specific or a result of generalized attentional processes.In the present study, 16 young adults observed facial speech gestures related to productions of vowels /a/ and /u/ in the presence of contralateral broad band noise (BBN) under two instructions: (a) visual attention: visually count the number of /a/ productions and ignore BBN and (b) sham condition/ auditory attention: these trials did not have any vowels embedded in BBN, but participants were made to believe that there were sounds embedded and instructed to count the number of /a/ productions.These "sham" trials investigated the effect of auditory attention in the absence of real auditory targets.The influence of visual and auditory attention on the efferent auditory system was indirectly assessed by examining their effects on contralateral inhibition of click-evoked otoacoustic emissions (CS-CEOAE paradigm; Collet, Chanel, & Morgon, 1990).The mean inhibition from baseline for visual attention and auditory attention were 2.19 and 1.88 dB SPL, respectively.Cohen's d for the mean difference between the two conditions yielded a moderate positive effect size = 0.52.Twelve out of sixteen participants (75%; exact binomial test significant at one tailed p = 0.03) demonstrated a greater inhibition of CEOAEs amplitudes (mean difference = 0.31 dB SPL) in the visual attention condition relative to the auditory attention condition.Our results show that these effects are obtainable even in the absence of real auditory targets (i.e.without stimulus confound).Overall, finding a difference in inhibition of CEOAEs for visual and auditory attention conditions provide preliminary evidence for a modalityspecific rather than a generalized attentional modulation in the efferent auditory system.
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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 | 0.003 |
| 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) | 0.002 | 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".