Effects of processing speed training on cognitive functions and neural systems
Bibliographic record
Abstract
Processing speed (PS) is an individual cognitive ability that measures the speed with which individuals execute cognitive tasks, particularly elementary cognitive tasks. PS has been proposed to be a key cognitive component, along with working memory, and is psychologically and clinically important. Various types of speed training affect performance of untrained cognitive measures. In this article, we review studies of PS training or training involving speeded tasks and describe the methodologies along with the psychological and neuroimaging findings related to PS training. There are various types of PS (speed) training tasks. Evidence indicates that PS training can enhance performance on untrained speeded tasks. However, the extent of transfer may vary depending on the methodology. A particular type of speed training seems to affect mental health in older adults. Neuroimaging studies of speed training have shown that the effects of speed training on neural mechanisms may vary depending on the training tasks. Adaptive procedures to modulate the difficulties of training tasks based on a subject's performance by modulating the task speed can be applied to various cognitive tasks, and these procedures can perhaps be used to develop training protocols for enhancing various cognitive functions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".