James R. H. Cooke

This study shows that human steering behavior adjusts feedback control strategies based on spatial constraints, supporting three predictions about variability and corrective responses in different gate conditions.

This paper introduces a dynamic causal inference framework that unifies multisensory perception with motor control, showing it can reproduce empirical findings and extend to complex tasks.

The paper shows that combining visual and inertial feedback improves steering performance under dynamic perturbations, with better performance attributed to shorter vestibular delays.

The paper shows that subjective confidence correlates with decoded probability distributions from neural activity in visual cortex, supporting a Bayesian interpretation of confidence.

This study demonstrates that the brain uses Bayesian causal inference to weigh internal estimates and sensory feedback during spatial updating, showing nonlinear error patterns based on spatial discrepancies.

This paper introduces a Bayesian adaptive stimulus selection algorithm to improve model comparison in psychophysical experiments, showing it outperforms random sampling and predetermined stimuli.