Stable neuronal representations to repeated stimulation underlie cognitive resilience in Alzheimer’s disease pathology
Bibliographic record
Abstract
While Alzheimer's Disease (AD) typically triggers cognitive decline, some individuals with significant AD pathology maintain normal cognition into late life. Understanding the neuronal underpinnings of such cognitive resilience would propel the development of interventions for delaying dementia. To this end, we used cognitive testing to identify a subset of cognitively resilient 13-month-old TgF344-AD rats (established AD) and their non-transgenic littermates, followed by Neuropixels recording from 8500 neurons during repeated somatosensory stimulation. Cognitively resilient TgF344-AD rats recruited fewer neurons yet displayed more stable neuronal representations during repeated stimulations in cortical excitatory and hippocampal inhibitory ensembles, with reduced excitatory spike burstiness during network activation and a distinct pattern of functional synaptic connectivity. These associations existed independently of amyloid and tau levels. For the first time, our study revealed neuronal population-level hallmarks of maintained cognition that may serve as a novel neurophysiological biomarker of cognitive resilience and a target for stabilizing cognition.
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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) | 0.000 | 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".