Effects of Aging on the Integration of Inter- and Intra-modal Motion Cues
Bibliographic record
Abstract
When two objects move toward one another, motion at the point of overlap is ambiguous: the objects may stream past one another or bounce off one another. A sound presented around the time of coincidence biases the percept toward bouncing (Sekuler et al., 1997, Zhou et al., 2007). In contrast, a visual occluder that obscures the motion coincidence biases the percept toward streaming (Sekuler and Sekuler, 1999). Because multisensory integration changes with age (Peiffer et al., 2007, Stephen et al., 2010), we exploited the bouncing-streaming percept to assay age-related changes in the integration of multiple inter- and intra-modal cues. We also examined the temporal development of occlusion by determining the percept for occluders of different durations. In 12 interleaved conditions, younger (n=9; mean age=20) and older (n=9; mean age=68) subjects judged whether two moving gray discs bounced or streamed. The discs were presented on their own (control), or accompanied by a sound, an occluder of varying duration, or both sound and occluder, all centered around the time of the discs’ coincidence. On half the trials, the discs differed in luminance (producing unambiguous streaming or bouncing in control conditions); on other trials, the discs had equal luminance (producing an ambiguous percept in control conditions). Younger, but not older, subjects showed a significant bias toward streaming responses in the ambiguous, control condition. A sound at the point of coincidence biased the percept toward bouncing in both groups, but its effect was reduced in older subjects. The effect of occluders depended on duration: brief occluders promoted bouncing in younger subjects, but not older subjects, whereas long occluders promoted streaming in both groups. The weakened inter- and intra-modal integration seen here could contribute to previously demonstrated age-related deficits in memory, and may be linked to age-related changes in neural processing in the gamma band 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| 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".