Jiayu Zhan

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