Auditory Event-related Potentials in Mild Cognitive Impairment and Alzheimer’s Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Mild cognitive deficits are more likely to occur with increasing age, and become more pronounced for people diagnosed with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Conventional methods to identify cognitive declines (i.e., neuropsychological testing and clinical judgment) can lead to false positive diagnoses of cognitive impairment. Tools such as electroencephalography (EEG) offer additional measures of cognitive processing, indexing the electrophysiological changes associated with aging, MCI and AD. OBJECTIVE: We reviewed the literature on EEG to determine if auditory event-related potentials (ERPs) could distinguish between healthy aging, MCI, and AD. METHOD: We searched two electronic databases (Medline and PyscInfo) for articles published between January 2005 and April 2017. Articles were considered for review if they included: i) participants 60 years of age or older; ii) healthy older adults or those diagnosed with MCI or AD; iii) at least one auditory elicited ERP component. RESULTS: Our search revealed 1532 articles (800 after removing duplicates); 719 were excluded through title/abstract review, and of the 81 remaining articles, 30 satisfied inclusion criteria. All studies compared cognitive function between at least two of the three selected populations. Our findings suggest that the P300 and N200 components may distinguish between healthy cognitive aging, MCI, and AD. CONCLUSION: ERPs may be sensitive to progressive cognitive changes due to MCI and AD. The P300 and N200 may help identify patients who are likely to progress from MCI to AD, and could be a valuable clinical tool.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it