Anticipatory eye movements and long‐term memory in early infancy
Bibliographic record
Abstract
Advances in our understanding of long-term memory in early infancy have been made possible by studies that have used the Rovee-Collier's mobile conjugate reinforcement paradigm and its variants. One function that has been attributed to long-term memory is the formation of expectations (Rovee-Collier & Hayne, 1987); consequently, a long-term memory representation should be established during expectation formation. To examine this prediction and potentially open the door on a new paradigm for exploring infants' long-term memory, using the Visual Expectation Paradigm (Haith, Hazan, & Goodman, 1988), 3-month-old infants were trained to form an expectation for predictable color and spatial information of picture events and emit anticipatory eye movements to those events. One day later, infants' anticipatory eye movements decreased in number relative to the end of training when the predictable colors were changed but not when the spatial location of the predictable color events was changed. These findings confirm that information encoded during expectation formation are stored in long-term memory, as hypothesized by Rovee-Collier and colleagues. Further, this research suggests that eye movements are potentially viable measures of long-term memory in infancy, providing confirmatory evidence for early mnemonic processes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".