Effect of dorsolateral prefrontal cortex structural measures on neuroplasticity and response to paired-associative stimulation in Alzheimer’s dementia
Bibliographic record
Abstract
Long-term potentiation (LTP)-like activity can be induced by stimulation protocols such as paired associative stimulation (PAS). We aimed to determine whether PAS-induced LTP-like activity (PAS-LTP) of the dorsolateral prefrontal cortex (DLPFC) is associated with cortical thickness and other structural measures impaired in Alzheimer's dementia (AD). We also explored longitudinal relationships between these brain structures and PAS-LTP response after a repetitive PAS (rPAS) intervention. Mediation and regression analyses were conducted using data from randomized controlled trials with AD and healthy control participants. PAS-electroencephalography assessed DLPFC PAS-LTP. DLPFC thickness and surface area were acquired from T1-weighted magnetic resonance imaging. Fractional anisotropy and mean diffusivity (MD) of the superior longitudinal fasciculus (SLF)-a tract important to induce PAS-LTP-were measured with diffusion-weighted imaging. AD participants exhibited reduced DLPFC thickness and increased SLF MD. There was also some evidence that reduction in DLPFC thickness mediates DLPFC PAS-LTP impairment. Longitudinal analyses showed preliminary evidence that SLF MD, and to a lesser extent DLPFC thickness, is associated with DLPFC PAS-LTP response to active rPAS. This study expands our understanding of the relationships between brain structural changes and neuroplasticity. It provides promising evidence for a structural predictor to improving neuroplasticity in AD with neurostimulation. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.
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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 | 0.002 | 0.002 |
| 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".