Aging, Attention, and Bimanual Coordination
Bibliographic record
Abstract
ABSTRACT Although aging is normally associated with declines in motor performance, recent evidence suggests that older adults suffer no loss in some measures of bimanual coordination relative to younger adults. Two hypotheses for this finding were compared in the present research. One hypothesis was based on the assumption that these coordination patterns are automatic and relatively impervious to the effects of aging. An alternative explanation is that older adults maintain this level of bimanual coordination at a cost of increased attention demand. These hypotheses were tested in an experiment in which bimanual coordination patterns (in-phase and anti-phase) were paced at two metronome frequencies (1 and 2 Hz), either alone or together, with serial performance of an attention-demanding task (adding 3s to a two-digit number at a 1 Hz pace). The results of the study provided some support for both hypotheses. The automaticity view was supported only for the coordination patterns at the 1 Hz metronome frequency. Support for an attention allocation hypothesis was shown in the observed-movement frequency data, as older adults tended to sacrifice movement frequency at the 2 Hz metronome pace in order to maintain performance in the movement and counting tasks. These findings are discussed relative to recent accounts of the role of automaticity in the absence of age-related differences in the performance of cognitive tasks.
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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 | 0.002 |
| 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) | 0.002 | 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".