Detection of Chronic Cognitive-Motor Deficits in Adults With a History of Concussion Using Computerized Eye-Hand Coordination Tasks: Preliminary Experimental Design Study
Bibliographic record
Abstract
Background: Concussion has been a major public health concern due to the substantial cognitive sequelae it results. Although the dysfunctions of the frontal lobe and corpus callosum owing to concussions have been documented, the existing concussion screening tools merely examine cognitive functions in isolation of motor functions and failed to detect the chronic cognitive-motor impairments following concussions. Yet, there has been no concussion screening test aimed specifically to assess the coupled cognitive-motor functions. Objective: This study aimed to provide preliminary evidence for using computerized eye-hand coordination tasks to detect chronic cognitive-motor deficits associated with concussion history. Methods: The computerized eye-hand coordination tasks were used to assess the coupled cognitive-motor functions of the participants with and with no history of concussion. In experiment 1, a total of 12 participants (6 young adults with a history of concussion and 6 healthy controls) completed longitudinal assessments of coordination profiles across a year. Experiment 2 examined a total of 20 participants (10 participants with a history of concussion and 10 healthy controls) using an iterated single-session protocol. Just noticeable difference (JND) and proportion of time-on-task (PTT) were used to assess cognitive-motor performance. Mixed-design ANOVAs were used to examine group differences, and the effect sizes were assessed using Cohen d test. Results: In experiment 1, participants with a history of concussion exhibited more inconsistent ability to visually discriminate the in-phase coordination pattern (coefficient of variation of JND: participants with a history of concussion = mean 0.27, SD 0.04, and healthy controls = mean 0.17, SD 0.07; t10=2.93; P=.02). Similarly, their performance on unimanual and bimanual in-phase and anti-phase coordination patterns was significantly poorer (at in-phase: PTTConcussed=mean 0.63, SD 0.10, and PTTHealthy=mean 0.73, SD 0.08 [F1,10=8.49; P=.02]; at anti-phase: PTTConcussed=mean 0.46, SD 0.14, and PTTHealthy=mean 0.60, SD 0.10 [F1,10=10.67; P=.008]). In experiment, 2 where only the unimanual coordination tasks were implemented for screening, participants with a history of concussion showed impaired performance in both in-phase and anti-phase tasks (at in-phase: PTTConcussed=mean 0.62, SD 0.13, and PTTHealthy=mean 0.74, SD 0.07 [F1,54=4.20; P=.045]; at anti-phase: PTTConcussed=mean 0.37, SD 0.15, and PTTHealthy=mean 0.56, SD 0.14 [F1,54=10.26; P=.002]), and they also failed to show the differentiated performance between anti-phase and 90° coordination patterns (PTTAnti-phase=mean 0.37, SD 0.15, and PTT90° coordination=mean 0.37, SD 0.13). Conclusions: Due to their ability to detect both impaired and undifferentiated performance in producing intrinsic and novel coordination patterns, the unimanual coordination tasks appear to be a sensitive screening tool for chronic cognitive-motor deficits associated with history of concussion.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".