Abstract

This dissertation develops individualized models of perceptual and cognitive behavior, inferring latent capacities from limited data with sufficient efficiency, precision, and generality for person-level prediction. In perception, a nonparametric Bayesian framework for adaptive psychophysics is extended from audition to vision, producing an estimator that recovers dense individualized contrast sensitivity profiles through variational inference, a generalized kernel, and information-guided stimulus selection. A multitask extension enables simultaneous estimation of multiple psychometric fields by exploiting shared latent structure. Transferring this inferential logic to cognition, where relevant dimensions must be supplied by task design rather than physics, requires new measurement infrastructure. A Minecraft-based platform implements cognitive paradigms as immersive minigames that produce endpoint scores with convergent validity against the NIH Toolbox while capturing rich trial-level behavioral traces. An adaptive visuospatial working memory task extends the Gaussian process acquisition method to a two-dimensional demand surface of pattern size and color count. Decomposing person-level behavioral variance into level (typical behavior) and reorganization (how behavior changes under demand) reveals that binary-contrast tasks yield reliable level-layer characterization but unstable reorganization, whereas a demand-surface task recovers both layers and distinguishes construct-relevant variation from fingerprinting. Testing endpoint-based executive function batteries against an external mathematics criterion shows that the dominant measurement strategy collapses to a single speed-capacity axis, with executive-function contrasts contributing no predictive variance beyond demographic context. Together, these results show that advancing individualized cognitive measurement requires not only denser behavioral observation but task architectures rich enough to support the questions that observation is meant to answer.

Committee Chair

Dennis Barbour

Committee Members

Barani Raman; David Bundy; Ismael Seanez; Jason Hassenstab

Degree

Doctor of Philosophy (PhD)

Author's Department

Biomedical Engineering

Author's School

McKelvey School of Engineering

Document Type

Dissertation

Date of Award

4-29-2026

Language

English (en)

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