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Record W4390191701 · doi:10.1002/alz.082744

Preliminary evaluation of the digital maze test in relation to neuropsychological tests and AD biomarkers

2023· article· en· W4390191701 on OpenAlexaff
Talia L. Robinson, Jessie Fanglu Fu, Grace A Del Carmen Montenegro, Michael J Properzi, Hannah M Klinger, Dana L. Penney, Randall Davis, Reisa A. Sperling, Keith A. Johnson, Rebecca E. Amariglio, Dorene M. Rentz

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsNeuropsychologyPsychologyNeuropsychological testTrail Making TestEntorhinal cortexNeuropsychological assessmentAudiologyHippocampusCognitionMedicineNeuroscience

Abstract

fetched live from OpenAlex

Abstract Background Digital cognitive tools may provide unique opportunities to detect subtle changes in preclinical Alzheimer’s disease (AD). Here, a maze test using a digital pen was evaluated in relation to AD pathological changes measured by amyloid‐β and tau burden. Method 172 participants (CN = 161, MCI = 6, dementia = 5) completed the digital maze test, which included multiple “no‐choice” (NC; i.e., no decisions required to complete maze) or “choice” (CH) conditions (i.e., problem‐solving required to complete maze). Maze composite scores were calculated using the total test duration, total number of strokes, and total pen‐off‐page time for the NC and CH conditions separately. Global amyloid‐β PET was quantified with [11C]Pittsburgh‐Compound‐B (PiB) in available participants (n = 171). Entorhinal and inferior temporal tau were quantified with [18F]Flortaucipir (FTP) in available participants (n = 135). Participants completed a battery of traditional neuropsychological tests, with domain factor scores calculated for Executive Functioning (EF), Processing Speed (PS), and Memory (Mem). The associations between maze composite scores, global amyloid‐β, entorhinal tau, and inferior temporal tau were evaluated in separate linear regression models for both the total sample and CN only, correcting for age and education. Result In the total sample, CH‐ and NC‐composites were moderately correlated with PS and EF factor scores (r’s = .41‐.46) and less so with Mem factor scores (r’s = 0.2‐0.35). In the total sample, higher PiB was significantly associated with worse performance in NC‐composite (β = 0.543, SE = 0.249, p <.05), but not for CH‐composite (β = 0.467, SE = 0.259, p = .07). Similar results were observed in the CN only sample (NC‐composite: β = 0.468, SE = 0.237, p <.05; CH‐composite: β = 0.469, SE = 0.278, p = .09). PiB was not associated with EF or PS factor scores in the total sample or CN only. Entorhinal and inferior temporal tau were not significantly associated with any maze composites. Conclusion In a largely cognitively normal sample, performance on the digital maze test was associated with global amyloid‐β burden, particularly in the no‐choice condition, but not with tau. Digitally captured, nuanced performance in EF and PS may be related to early amyloid‐β pathology, but less so with downstream effects of tau.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.057
GPT teacher head0.357
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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