Effects of computerized cognitive training on neuroimaging outcomes in older adults: a systematic review
Bibliographic record
Abstract
BACKGROUND: Worldwide, the population is aging and the number of individuals diagnosed with dementia is rising rapidly. Currently, there are no effective pharmaceutical cures. Hence, identifying lifestyle approaches that may prevent, delay, or treat cognitive impairment and dementia in older adults is becoming increasingly important. Computerized Cognitive Training (CCT) is a promising strategy to combat cognitive decline. Yet, the underlying mechanisms of the effect of CCT on cognition remain poorly understood. Hence, the primary objective of this systematic review was to examine peer-reviewed literature ascertaining the effect of CCT on both structural and functional neuroimaging measures among older adults to gain insight into the underlying mechanisms by which CCT may benefit cognitive function. METHODS: In accordance with PRISMA guidelines, we used the following databases: MEDLINE, EMBASE, and CINAHL. Two independent reviewers abstracted data using pre-defined terms. These included: main study characteristics such as the type of training (i.e., single- versus multi-domain), participant demographics (age ≥ 50 years; no psychiatric conditions), and the inclusion of neuroimaging outcomes. The Physiotherapy Evidence Database (PEDro) scale was used to assess quality of all studies included in this systematic review. RESULTS: Nine studies were included in this systematic review, with four studies including multiple MRI sequences. Results of this systematic review are mixed: CCT was found to increase and decrease both brain structure and function in older adults. In addition, depending on region of interest, both increases and decreases in structure and function were associated with behavioural performance. CONCLUSIONS: Of all studies included in this systematic review, results from the highest quality studies, which were two randomized controlled trials, demonstrated that multi-domain CCT could lead to increases in hippocampal functional connectivity. Further high quality studies that include an active control, a sample size calculation, and an appropriate training dosage, are needed to confirm these findings and their relation to 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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".