Robert Englert

This paper introduces RLBF, a framework for real-time fMRI-based adaptive stimulus generation using reinforcement learning, validated in a study optimizing visual stimuli to enhance V1 responses.

This paper evaluates the replicability of diffusion-weighted MRI-based brain-behavior models and finds moderate replicability with small sample sizes, but higher replicability for trait-like phenotypes.

The paper proposes an adaptive splitting method for external validation of machine learning models to improve generalizability and replicability in predictive modeling studies.

This paper introduces fcANNs, a model of brain dynamics based on functional connectivity, showing it can reconstruct and predict brain activity in rest, tasks, and disease states.