Cortical auditory evoked potential morphology : response characteristics of the P1-N1-P2-N2 waves as determined by stimulus and subject parameters
Bibliographic record
Abstract
Analysis of cortical auditory evoked potentials (CAEPs) can provide valuable insight into how sounds are processed differently based on subject and stimulus parameters. Having a thorough understanding of these norms is necessary to use techniques for detecting a variety of neurological impairments, for evaluating hearing thresholds in patients who are unreliable or difficult to assess behaviourally, and for monitoring brain plasticity. Specifically, areas of central processing that can be investigated using electrophysiological methods include the ability to detect sounds, discriminate between sounds, and the ability to recognize and notice similarities or differences in sound patterns. There is also potential for CAEPs to be used to monitor speech processing. Possible applications of monitoring speech using CAEPs include validating hearing aids, assessing neural plasticity in hearing aid and cochlear implant users over time, and determining the efficacy of auditory training in improving speech perception. In order to effectively record and analyze CAEPs for any purpose, it is essential that clinicians have a thorough understanding of how stimulus factors such as intensity, duration, frequency, and presentation rate affect the positive and negative components of CAEPs. Furthermore, clinicians must be well versed in their understanding of CAEP maturational changes, as components show changes in latency, amplitude, and variability over the life span. On account of CAEPs being generated from higher level cortical areas, they are also highly mediated by subject state and attention. As such, it is critical that these factors be taken into consideration when comparing data across participants, and when comparing individual data with norms. Through the process of conducting a scoping review, this thesis outlines morphological trends of CAEPs as a function of both stimulus and subject parameters, highlights the interdependency of such variables, and identifies avenues for further research. Furthermore, data has been compiled into a freely available resource which clinicians may contribute to as additional research is conducted.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".