Yamil Vidal

This paper introduces a model that performs exact Bayesian inference over a discrete state space using a local Hebbian rule, demonstrating its ability to account for perception and decision-making under noise.

A preregistered multimodal neuroimaging study across 256 human participants directly tests Integrated Information Theory against Global Neuronal Workspace Theory, confirming some predictions while revealing major empirical challenges for both.

The paper investigates semantic and morphological priming in natural sentence reading using eye movements and EEG, finding semantic facilitation but no morphological priming effect.

The paper shows that a general-purpose visual learning mechanism underlies both reading and non-orthographic visual stimuli recognition.

The paper uses speech-like stimuli to study auditory prediction errors and finds that prediction errors are modulated by preceding syllable structure, not just immediate transitions.