Spatial Uncertainty and Information Processing Speed in Infants and Adults: Age Differences in Saccadic Reaction Time Sensitivity
Bibliographic record
Abstract
Speed of information processing (SIP) as determined by response to spatial uncertainty is an important, perhaps limiting factor for cognitive development. With adults, although their manual response RTs for spatial uncertainty increase linearly with increasing choices, their saccadic RTs do not. In contrast, 7-month-old infants' saccadic RTs have been shown to increase with more target choices. What is the developmental course that enables this saccadic RT discrepancy between 7-month-oldsand adults? To address this question, the present study assessed adults' and 5- and 9-month-old infants' reactive saccades in a comparable choice reaction time task that varied spatial uncertainty. Both 5- and 9-month-olds' saccadic RTs increased linearly with more choice alternatives and uncertainty. Nine-month-olds' saccadic RTs increased at a shallower rate, however, approaching the slope of adults' saccadic RT function, which did not exhibit an increase with more uncertainty. Thus, there is a developmental trend for assessing spatial SIP with saccadic RTs. As infants age, saccadic responses become less sensitive to spatial uncertainty and approach adult-like performance. Decreasing saccade sensitivity may be due to developmental changes in the influence of response selection or in the functioning of inhibitory mechanisms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".