Alterations in hippocampal network oscillations and theta–gamma coupling arise before <scp>Aβ</scp> overproduction in a mouse model of <scp>A</scp>lzheimer's disease
Bibliographic record
Abstract
Alzheimer's disease (AD) is an age-related neurodegenerative disorder characterized by memory impairments. Brain oscillatory activity is critical for cognitive function and is altered in AD patients. Recent evidence suggests that accumulation of soluble amyloid-beta (Aβ) induces reorganization of hippocampal networks. However, whether fine changes in network activity might be present at very early stages, before Aβ overproduction, remains to be determined. We therefore assessed whether theta and gamma oscillations and their cross-frequency coupling, which are known to be essential for normal memory function, were precociously altered in the hippocampus. Electrophysiological field potential recordings were performed using complete hippocampal preparations in vitro from young transgenic CRND8 mice, a transgenic mouse model of AD. Our results indicate that a significant proportion of 1-month-old TgCRND8 mice showed robust alterations of theta-gamma cross-frequency coupling in the principal output region of the hippocampus, the subiculum. In addition we showed that, compared to controls, these mice expressed negligible levels of Aβ. Finally, these network alterations were not due to genetic factors as 15-day-old animals did not exhibit theta-gamma coupling alterations. Thus, initial alterations in hippocampal network activity arise before Aβ accumulation and may represent an early biomarker for 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) | 0.000 | 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 | 0.001 |
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".