Changes in the Networks of Attention across the Lifespan: A Graphical Meta-Analysis
Bibliographic record
Abstract
Three Posnerian networks of attention (alerting, orienting, and executive control) have been distinguished on the bases of behavioural, neuropsychological, and neuroscientific evidence. Here, we examined the trajectories of these networks throughout the human lifespan using the various Attention Network Tests (ANTs), which were specifically developed to measure the efficacy of these networks. The ANT Database was used to identify relevant research, resulting in the inclusion of 36 publications. We conducted a graphical meta-analysis using network scores from each study, based on reaction time plotted as a function of age group. Evaluation of attentional networks from childhood to early adulthood suggests that the alerting network develops relatively quickly, and reaches near-adult level by the age of 12. The developmental pattern of the orienting network seems to depend on the information value of the spatial cues. Executive control network scores show a consistent decrease (improvement) with age in childhood. During adulthood (ages 19-75), changes in alerting depend on the modality of the warning signal, while a moderate increase in orienting scores was seen with increasing age. Whereas executive control scores, as measured in reaction time, increase (deterioration) from young adulthood into later adulthood an opposite trend is seen when scores are based on error rates.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".