O2‐01‐03: Training the brain: Can cognitive training alter the global effects of Alzheimer's disease?
Bibliographic record
Abstract
There is a growing need for novel behavioural interventions such as cognitive training that can benefit clinically vulnerable populations, such as people living with Alzheimer's disease (AD). Specifically, the potential for neural plasticity, which is the ability of the brain to adapt to changes at a cellular and molecular level, may still be present after trauma or neurodegeneration, particularly in the early stages of a disease. Consequently, there is great interest in the potential for neurologically compromised individuals, such as AD patients, to adapt to new challenges through neural plasticity and altered brain chemistry. Cognitive training (CT) for AD patients is a relatively new area of research however; recent evidence suggests that techniques such as CT may be effective way in stabilising and even enhancing cognition in mild AD1, perhaps through neuronal plasticity. Six participants diagnosed with probable or possible AD participated in a 14-week program consisting of twice-weekly on-site sessions of 2 hours each. Training tasks included: a visuomotor activity (Pac-man game playing), visuoconstructive procedures (e.g. Block design, 3-D puzzle construction), and a navigation task (finding on-site location using a map). Each participant also completed twice-weekly in-home sessions of 1 hour each, consisting primarily of visuospatial tasks (e.g. mazes and similar paper and pencil tasks).Neuropsychological testing occurred at 2 time points: baseline (pre-training) and follow-up (post-training). Completion of our neuropsychological test battery required approximately 100 min. This battery was selected to index all major cognitive domains, and to have a sufficient range of difficulty, i.e. floor and ceiling effects. The Neuropsychiatric Inventory2 and the Disability Assessment for Dementia3 were also scored to assess functional behaviour and activities of daily living (ADLs). Participants demonstrated improvement upon post-training neuropsychological evaluation, compared to pre-training. Importantly, for some patients the pre-training to post-training improvement in scores was from the impaired range to within normal limits. In addition, patients also demonstrated significant positive changes on a number of the training procedures. Providing regular and challenging cognitive training tasks for AD patients can lead to positive improvements in cognitive and functional performances.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".