Representational momentum in preterm and full-term children
Bibliographic record
Abstract
When an object that is moving along a particular path vanishes, observers' memory for the object's final position is biased in the direction of continuing motion (Freyd & Finke, 1984). This effect is seen even with static stimuli in which motion is simply implied (Freyd, 1983). This memory bias, referred to as the representational momentum (RM) effect, is seen in both children and adults (Futterweit & Beilin, 1994; Hubbard, Matzenbacher, & Davis 1999). Several recent studies (e.g., Senior et al., 2002) suggest that images depicting implied motion activate brain regions involved in actual motion processing. Given this, we might expect to see that children with motion-processing deficits would show an atypical RM effect. Previous research in our laboratory has shown that children born prematurely at very low birth weight (VLBW [[lt]] 1500 g) are at risk for impairments in both low-level and high-level motion processing (MacKay et al., 2005; Jakobson et al., 2006). In the present study, we compared the RM effect in 5–9 year old, VLBW children to that seen in an age-matched sample of full-term controls. Full-term children showed a robust RM effect, and the strength of this effect was negatively correlated with their global motion coherence thresholds (r = −.55); in other words, control children who were more proficient at global motion perception showed a larger memory bias. VLBW children did not show an RM effect, and tended to have higher motion coherence thresholds than controls, overall. There was, moreover, no relationship between performance on the RM task and motion coherence thresholds (r = −.06) in this group. These results are consistent with research suggesting overlap in the neural substrates supporting the processing of implied and actual motion, and extend our earlier work demonstrating that VLBW children are at risk for problems associated with poor motion processing.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".