Filling the Gaps: How Attentional States Influence Memory Formation in Children and Adults
Bibliographic record
Abstract
To understand the complex world around them, children critically depend on the ability to form memories. But in many moments, children struggle to form memories and often remember qualitatively different (and less goal-relevant) information than adults. Although these findings could reflect immature memory processes, another possibility is that worse memory in childhood reflects the slow development of attention. In adults, successful memory depends on the ability to endogenously sustain and selectively attend to task relevant content–abilities that are immature in childhood. In this dissertation I report 4 experiments that explore the relationship between attention and memory formation in children and adults. In Chapter 2, I describe a study examining how endogenous fluctuations in attention influence the ability to form memories in each moment. I find that endogenous fluctuations in attention closely correlate with the ability to form memories in children and adults, but covary with memory formation more closely in children. In Chapter 3, I turn to exploring how reactive shifts in attention, elicited by errors, shape memory formation in adults. I find that making an error increases arousal and captures attention leading to immediate memory decrements. Finally, in Chapter 4, I ask why children tend to be more likely to remember goal-irrelevant information than adults. I find that children have reduced memory for target information but enhanced memory for goal-irrelevant information relative to adults. Moreover, lower memory selectivity is closely related to poorer performance on an attentionally demanding task which mediates age-differences in memory selectivity. Overall, I argue that these data illustrate that the slow development of attention (rather than memory per se) may in large part explain age differences in memory performance after middle childhood.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".