Cortical Auditory Evoked Potentials in Response to Frequency Changes with Varied Magnitude, Rate, and Direction
Bibliographic record
Abstract
Recent literature on cortical auditory evoked potentials has focused on correlations with hearing performance with the aim to develop an objective clinical tool. However, cortical responses depend on the type of stimulus and choice of stimulus parameters. This study investigates cortical auditory evoked potentials to sound changes, so-called acoustic change complexes (ACC), and the effects of varying three stimulus parameters. In twelve normal-hearing subjects, ACC waveforms were evoked by presenting frequency changes with varying magnitude, rate, and direction. The N1 amplitude and latency were strongly affected by magnitude, which is known from the literature. Importantly, both of these N1 variables were also significantly affected by both rate and direction of the frequency change. Larger and earlier N1 peaks were evoked by increasing the magnitude and rate of the frequency change and with downward rather than upward direction of the frequency change. The P2 amplitude increased with magnitude and depended, to a lesser extent, on rate of the frequency change while direction had no effect on this peak. The N1-P2 interval was not affected by any of the stimulus parameters. In conclusion, the ACC is most strongly affected by magnitude and also substantially by rate and direction of the change. These stimulus dependencies should be considered in choosing stimuli for ACCs as objective clinical measure of hearing performance.
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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 | 0.004 |
| 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".