Aberrant Cortical Event-Related Potentials During Associative Learning in Rat Models for Presymptomatic Stages of Alzheimer’s Disease
Bibliographic record
Abstract
Trace eyeblink conditioning is a hippocampus-dependent associative learning paradigm which is impaired in patients with Alzheimer's disease (AD) and animal AD models. Learning in this paradigm accompanies changes in oscillatory activity in forebrain regions, some of which are loci of pathogenic changes in prodromal AD stages. These observations motivated us to examine how cortical event-related potentials (ERPs) during this paradigm are affected by two features of the asymptomatic, AD-related brain abnormality, entorhinal tau accumulation and mild cholinergic deficit. Adult rats received viral overexpression of P301L mutant human tau in the entorhinal cortex, low-dose scopolamine treatment, or both. Electroencephalograms were recorded with epidural electrodes on the surface of the frontal, parietal, and temporal cortices during differential and reversal trace eyeblink conditioning. All rats developed conditioned responses to one of two stimuli (auditory or visual) paired with mild eyelid shock (CS+), but not to the other stimulus presented alone (CS-). They were also able to adjust the response when the stimulus contingency was reversed. With learning, the amplitude of several ERP components in the frontal and temporal cortices came to differentiate the CS+ from CS-. Scopolamine affected the learning-related change in temporal P2 and other learning-unrelated components in three regions. Entorhinal tau overexpression primary affected the amplitude of temporal visual ERPs and learning-unrelated frontal and temporal auditory ERP components. The double manipulation only affected two components of temporal auditory ERPs. Thus, cortical ERPs during differential associative learning are sensitive to asymptomatic brain abnormality associated with AD.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".