Percy K. Mistry

This paper introduces MDSI-AVI, a framework for modeling whole-brain causal interactions in fMRI data, revealing new insights into working memory mechanisms.

The paper investigates nonergodicity and Simpson's paradox in cognitive control dynamics using brain imaging and behavioral data from over 4,000 children, revealing brain-behavior associations that reverse between between-subjects and within-subjects analyses.

This paper develops a Bayesian model to uncover latent cognitive and affective processes in children's arithmetic problem-solving and shows it predicts academic outcomes and mediates the effects of anxiety.

This paper introduces a computational model to analyze inhibitory control mechanisms using data from a large cohort study, revealing individual variability and nonergodicity in cognitive processes.

The paper develops personalized deep neural networks to model learning disabilities in children, revealing how neuronal hyperexcitability affects learning performance and neural representation structures.

This study investigates the default mode network (DMN) in freely exploring rats, finding it dynamically encodes spatial exploration behaviors and challenges the notion of the DMN being task-negative.