Spatial Cueing of Infants' Target Selection and Eye Movements
Bibliographic record
Abstract
In order to overcome our limited amount of attentional resources, particular items in space must be selected as targets. For infants, attentional resources are even more limited. Models of attention have proposed that resources are restricted to particular spatial locations, enhancing processing at these locations. Evidence for selection due to spatial attention has been provided by studies that use a spatial cueing paradigm, in which attending to the particular location indicated by a preceding cue results in faster and more accurate selection of, and eye movements to, items presented at that location compared to when no cue is presented. Whether infants exhibit similar spatial attention and target selection mechanisms has yet to examined. To this end, in the current study, 3-month-old infants were presented with either no cue or with a 150 msec cue to either the right or left of fixation indicating the subsequent location of the target to which they should make an eye movement. Then, either one stimulus or two stimuli were presented at 5° from fixation and the latency of infants’ eye movements was measured to the one of the stimuli or to the cued target. Preliminary results have indicated that, consistent to findings with adults, presentation of the spatial cue resulted in a facilitation of target selection as exhibited by a decrease in infants’ eye movement latency. Infants’ eye movement latencies, however, were much slower than typically found in studies with adults. This finding suggests that the mechanisms responsible for the allocation of spatial attention in guiding target selection is functioning in early infancy. Yet, these mechanisms require further development to reach full efficacy, though the full extent of the developmental deficiencies remains to be determined. Meeting abstract presented at VSS 2012
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".