Philippe G. Schyns

The paper shows how task demands dynamically structure feature selection, routing, and integration in the human brain using dynamic faces and MEG data.

The paper identifies a functional social pathway in the brain that computes dynamic facial movements for emotion categorization using MEG data and representational interaction measures.

The paper shows that the strength of predicted category features biases decision behavior by using classifiers to analyze reactivation of specific stimulus features.

This study shows that top-down predictions of visual features reverse bottom-up processing in the occipito-ventral pathway, improving categorization speed and visual representation.

The paper shows that top-down predictions from temporal to occipital cortex sharpen visual feature representations for faster categorization.

The paper shows how four stages of task-specific computations over the same visual inputs achieve different behaviors in dynamic brain networks.

This paper investigates whether social and non-social decision-making share common neural mechanisms by analyzing EEG-fMRI data during a task with comparable decision evidence scales.

This paper introduces a Bayesian method to estimate population prevalence from individual participant data, offering a quantitative estimate with uncertainty instead of binary inferences.

The paper introduces a framework called Stimulus Information Representation (SIR) to understand how brain activity reflects information processing during tasks.

The paper investigates how ageing delays neural processing of face features, showing a 40 ms delay in occipital-temporal pathway activity that correlates with slower behavioural responses.

The paper uses an information theoretic framework to show how the brain reduces high-dimensional visual input into task-relevant representations in the right fusiform gyrus to support perceptual decisions.

The paper identifies two distinct computational mechanisms in different brain regions that support audiovisual speech comprehension: redundancy in the left posterior superior temporal gyrus and synergy in the left motor cortex.

The paper investigates how local speech encoding and functional connectivity contribute to audio-visual speech integration using MEG data, finding that enhanced connectivity, not local encoding, predicts the benefit of visual speech cues.

The paper identifies the content of predictions from memory that aid in face recognition by analyzing 3D facial features and their efficiency in distinguishing identities.

The paper introduces a statistical framework for neuroimaging data analysis using mutual information estimated via a Gaussian copula, validated on EEG and MEG data with applications to various signal features.

The paper shows the N170 ERP reflects cross-hemispheric transfer of visual features, not just local processing.