Are bilateral motor planning impairments during reverse visually guided reaching evidence of cognitive-motor impairment or a motor control strategy among stroke survivors and older adults?
Bibliographic record
Abstract
Cognitive-motor impairments are common after stroke yet difficult to assess and separate from pure motor impairments. Reverse visually guided reaching (RVGR) assessments may capture cognitive-motor impairments. Stroke survivors show higher frequencies of bilateral impairments in reaction time (RT) and initial direction angle (iDA) compared to normal reaching. Interestingly, RVGR impairment is not related to general cognition, but may result from a speed-accuracy trade-off strategy. We assessed speed-accuracy trade-offs between RT and iDA in stroke survivors and age-matched controls with bilateral RVGR impairments. Participants (34 Stroke, 42 Controls) completed 3 KINARM assessments to measure: average RT and iDA during RVGR (cursor feedback rotated 180˚), dwell-time during Trail Making Test A indexed processing speed, and movement time (MT) during normal visually-guided reaching (VGR) represented reaching-specific movement impairment. Measures were Z-transformed relative to normative data. Z-scores >1.65 were classified as impaired. The relationships between RT and iDA, RT and dwell-time, and MT and iDA were tested. Bilateral RT impairment during RVGR was present in 16/34 Stroke and 13/42 Control participants. Fewer participants had bilateral iDA impairment (6 Stroke, 3 Control). Across all participants and hands, RT and iDA were not correlated. Yet for those with bilateral impaired RT, nearly all had normal iDA in both hands. Bilateral RT impairment was not associated with impaired dwell-time. MT was not associated with bilateral iDA impairment. Bilateral RVGR impairment may result from a speed-accuracy trade-off whereby slow RT enables normal accuracy. Neither cognitive or motor deficits were associated with presence of bilateral impairments.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".