Robert J. van Beers

This study shows motor effort biases perceptual decisions during later-stage evidence accumulation, not early sensory processing.

This study investigates whether stimulus autocorrelation affects central tendency and serial dependence in vestibular path integration, finding these biases persist regardless of sequence protocol.

This study examines how sensorimotor beta oscillations from an initial motor action influence perceptual decision bias in a subsequent task, finding no significant group-level bias but suggesting individual susceptibility.

The paper investigates central tendency and serial dependence biases in vestibular path integration using a distance reproduction task in darkness, finding similar biases to those observed in visual path integration.

This study investigates whether participants build an internal model of steering dynamics to predict vestibular reafference during self-motion estimation.

This study investigates whether early-stage Alzheimer's disease affects the fast, declarative component of motor adaptation, finding that AD patients have reduced retention rates in this process while the slow, non-declarative process remains unaffected.

The paper shows that humans integrate artificial motor signals with vestibular feedback during self-motion tasks, updating internal models when control dynamics change.

The paper shows that a Gaussian prior better explains perceptual observations in spatial orientation than non-Gaussian priors, despite natural head motion having non-Gaussian statistics.

This study shows that repeating well-practiced movements reduces movement variability and improves precision, even in short sequences of reaching tasks.

The paper proposes a neural network model that uses multilateration to decode touch location on the body, showing it matches psychophysical experiments.

The paper investigates how different perturbation schedules during initial training affect error sensitivity in visuomotor adaptation, finding that all schedules similarly modulate sensitivity.

The paper shows that people use prediction errors, not actual temporal errors, for trial-to-trial motor corrections in fast movements.

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