The Digital Maze Test (dMaze) Reveals Subtle Decision‐Making Difficulties in MCI: Hurrying to Keep Up?
Bibliographic record
Abstract
Abstract Background Traditional Maze tests are time‐consuming and insensitive to early AD cognitive changes. We combine behavior capture using a digitizing pen with novel test design to produce person‐centric/relative metrics that disembed cognitive from motor speeds. This enables comparison of complex decision‐making behavior across difficulty levels within a single test. We compare traditional measures with our person‐centric/relative measures. Method Participants were healthy (HC = 22), Mild Cognitive Impairment (MCI = 37), Alzheimer’s (AD = 39), and Parkinson’s (PD = 43) volunteers (N = 141). Diagnosis was determined by consensus using standard of care data (neuropsychological/neurological evaluations, MRI and DAT scans). Participant groups differed in age: HC (52.27) younger than PD (64.07), MCI (75.05) and AD (75.38) oldest. Groups differed in the expected direction for DCTclock and MoCA scores. The dMaze test contains a path‐following condition without choice points, followed by a choice (CH) condition with identical solution paths/motor demands. CH contains simple and complex choices. Relative measures use the participant’s overall speed to normalize within‐test speed deviations. We examined: Total Time (TTime) to completion, Max motor speed (MaxSpd) and Median speed (MedSpd), Choice point Average Speed (AveSpd) and Relative Average Speed (rAveSpd). Result TTime in seconds differentiated (p = .001) AD (141.24) from HC (52.98) and PD (77.35), not MCI (103.16). MaxSpd was slowest (p = .004) for HC (59.82mm/sec) compared to all clinical groups (MCI = 76.71mm/sec, PD = 77.11, AD = 85.52). Groups did not differ for MedSpd or choice point AveSpd. Simple choice point rAveSpd differentiated only AD (p = .001) from HC, PD & MCI. Complex choice point rAveSpd differentiated HC from MCI (p = .05) and AD (p = .001). HC and PD did not differ, suggesting simple motor speed did not account for ink speed differences. Conclusion Fast completion time despite slow maximum speed and relative average speed across choice points suggests HC use a modulated approach balancing speed and task difficulty. MCI faster relative maximum speed (hurrying) with completion time similar to HC, suggests a less well‐modulated approach. Relative speed differences for more complex choices may be sensitive to preclinical cognitive change even when total completion time is not. The ability to precisely measure and parse person‐centric motor and cognitive test behaviors provides opportunity to improve preclinical detection, disease monitoring and treatment efficacy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".