Evaluating the Effect of Cognitive Dysfunction on Mental Imagery in Patients with Stroke Using Temporal Congruence and the Imagined ‘Timed Up and Go’ Test (iTUG)
Bibliographic record
Abstract
BACKGROUND: Motor imagery (MI) capacity may be altered following stroke. MI is evaluated by measuring temporal congruence between the timed performance of an imagined and an executed task. Temporal congruence between imagined and physical gait-related activities has not been evaluated following stroke. Moreover, the effect of cognitive dysfunction on temporal congruence is not known. OBJECTIVE: To assess temporal congruence between the Timed Up and Go test (TUG) and the imagined TUG (iTUG) tests in patients with stroke and to investigate the role played by cognitive dysfunctions in changes in temporal congruence. METHODS: TUG and iTUG performance were recorded and compared in twenty patients with chronic stroke and 20 controls. Cognitive function was measured using the Montreal Cognitive Assessment (MOCA), the Frontal Assessment Battery at Bedside (FAB) and the Bells Test. RESULTS: The temporal congruence of the patients with stroke was significantly altered compared to the controls, indicating a loss of MI capacity (respectively 45.11 ±35.11 vs 24.36 ±17.91, p = 0.02). Furthermore, iTUG test results were positively correlated with pathological scores on the Bells Test (r = 0.085, p = 0.013), likely suggesting that impairment of attention was a contributing factor. CONCLUSION: These results highlight the importance of evaluating potential attention disorder in patients with stroke to optimise the use of MI for rehabilitation and recovery. However further study is needed to determine how MI should be used in the case of cognitive dysfunction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".