Evan James Livesey

The paper investigates the contextual specificity of motor pauses during action cancellation and attentional capture, showing that EMG suppression is context-dependent rather than a generalizable pause process.

This paper introduces a Distributed Model to better capture continuous outcomes in contingency learning, showing it fits empirical data better than traditional models.

This study shows that awareness is necessary for predictive learning and motor attenuation, as only aware participants exhibited reduced motor system excitability in response to predictable stimuli.

The paper shows that sensory and motor prediction errors are linked, as auditory attenuation predicts motor attenuation during TMS.

This study investigates whether predictive coding affects neural responses to transcranial magnetic stimulation (TMS) by comparing MEP amplitudes under predictable and unpredictable conditions.

This study shows that stop-associated stimuli can reduce corticospinal excitability through associative learning, suggesting automatic motor inhibition triggered by learned cues.

The paper develops a hybrid computational model of the inverse base rate effect and uses fMRI to show that dissimilarity-based processing contributes to the effect, with activation patterns in left rostrolateral prefrontal cortex tracking model predictions.