Effects of Training of Processing Speed on Neural Systems
Bibliographic record
Abstract
Processing speed (PS) training improves performance on untrained PS tasks in the elderly. However, PS training's effects on the PS of young adults and on neural mechanisms are still unknown. In humans, we investigated this issue using psychological measures, voxel-based morphometry, the n-back task [a typical task for functional magnetic resonance imaging (fMRI) studies with conditions of 0-back (simple cognitive processes) and 2-back tasks (working memory; WM)], resting-state fMRI for the analysis of functional connectivity between brain regions during rest (resting-FC), and intensive adaptive training of PS. PS training was associated with (1) significant or substantial improvement in the performance of PS measures, (2) changes in the gray matter structures of the left superior temporal gyrus and the bilateral regions around the occipitotemporal junction, (3) changes in functional activity that are related to simple cognitive processes (but not those of WM) in the left perisylvian region, and (4) increased resting-FC between the left perisylvian area and the area that extends to the lingual gyrus and calcarine cortex. These results confirm the PS-training-induced plasticity in PS and the training-induced plasticity of functions and structures that are associated with speeded cognitive processes. The observed neural changes caused by PS training may give us new insights into how PS training, and possibly other cognitive training, can improve PS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".