# Interactive Virtual Games: Winners for Deep Cognitive Assessment

arXiv: https://arxiv.org/abs/2502.10290 · HTML: https://mlsanity.com/paper/2502.10290/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Feb 2025.

## Built on by (most cited first, 2 of 2)

- [pixelLOG: Logging of Online Gameplay for Cognitive Research](https://mlsanity.com/paper/2602.08941/) (2026)
- [Early Prediction of Future Behavioral Strategy from Process Traces](https://mlsanity.com/paper/2605.30550/) (2026)

## Abstract (arXiv)

Studies of human cognition often rely on brief, highly controlled tasks that emphasize group-level effects but poorly capture the rich variability within and between individuals. A suite of minigames built on the novel pixelDOPA platform was designed to overcome these limitations by embedding classic cognitive task paradigms in a 3D virtual interactive environment with continuous behavior logging. Four of the minigames explore constructs that overlap established NIH Toolbox tasks, including processing speed, rule shifting, inhibitory control and working memory. Across a clinical sample of 66 participants collected outside a controlled laboratory setting, large correlations (r = 0.47-0.92) between the pixelDOPA tasks and NIH Toolbox counterparts were found. Process-informed metrics improved both task convergence and data quality. Test-retest analyses revealed high reliability (ICC = 0.71-0.85) for all minigames. Beyond endpoint metrics, movement and gaze trajectories revealed stable, idiosyncratic profiles of gameplay strategy, with unsupervised clustering differentiating participants by their navigational and viewing behaviors. These trajectory-based features showed lower within-person variability than between-person variability, facilitating participant identification across repeated sessions. Game-based tasks can therefore retain the psychometric rigor of standard cognitive assessments while providing new insights into dynamic individual-specific behaviors. By leveraging a highly engaging, fully customizable game engine, comprehensive behavioral tracking can boost the power to detect individual differences without sacrificing group-level inference. This possibility reveals a path toward cognitive measures that are both psychometrically robust and deployable in less-than-ideal settings, while capturing richer behavioral data than traditional paradigms.