Infant and Adult Localization of a Conjunction Target: An Eye Movement Study
Bibliographic record
Abstract
Visual search studies have shown that 3-month-olds exhibit "pop out" and asymmetries in the localization of feature-present versus feature-absent targets similar to adults (Adler & Orprecio, 2006; Adler & Gallego, revision under review). Research, however, has suggested that infants do not accomplish a conjunction search until around 6 months of age (Bhatt, Bertin & Gilbert, 1999). Previous conjunction search research with infants, however, has assessed their behavior using habituation and preferential looking paradigms, which measure performance in seconds rather than milliseconds as is the case in studies of adults' search. To allow for direct comparison of the two ages and comparable assessment of the relative development of search and attentional mechanisms, this study measured infant and adult saccadic latencies in milliseconds to localize both conjunction and feature targets. Infants and adults were presented with arrays of 3 different set sizes (5, 8, 10), each consisting of a unique target (a green or red "X" or "O") being either present or absent. Surrounding distractors differed based on a single unique feature (shape or color) or a conjunction of features (shape and color) relative to the target. Results indicated that both infants' and adults' saccadic latencies exhibited relatively flat functions across set sizes in localizing the feature target. In localizaing the conjunction target, in contrast, adults' saccadic latencies increased as a function of set size, whereas infants' latencies did not increase with set size. Infants' latencies were also approximately 200 msec slower than adults' in the conjunction search. These results, consistent with previous studies, suggest a developmental progression in the availability of top-down mechanisms, with young infants relying solely on bottom-up processing of stimulus properties such as the saliency of the target. Adults, in contrast can use top-down mechanisms to facilitate their localization of the conjunction target. Meeting abstract presented at VSS 2014
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".