George R. Mangun

This study investigates the neural mechanisms of willed attention control using fMRI and EEG data, finding distinct activation patterns and decoding capabilities in the frontoparietal decision network.

This study uses fMRI and multivariate analysis to show how spatial attention templates guide stimulus selection through neural connectivity and decoding patterns.

This study investigates the role of the Ventral Attention Network (VAN) in attentional reorienting during cross-modal expectancy violations using EEG and fMRI.

The paper uses EEG to show that visual attention is influenced by object boundaries, supporting object-based attentional prioritization.

This study investigates willed attention to color, finding post-decision EEG differences but no pre-decision signals predicting color choice.

This study examines preparatory attention during spoken language comprehension by measuring alpha neural activity and finds that trial-by-trial alpha fluctuations predict memory encoding for focused words.

This study predicts the direction of the first saccade in visual search using EEG, finding broadband activity predicts it up to two seconds before the array onset, suggesting mechanisms similar to willed motor actions.

This study uses CNNs to explore how perceptual expertise and attention interact in object recognition, finding that attention enhances performance within expertise domains but not outside.

This paper investigates the hierarchical organization of visual feature attention control using EEG and multivariate decoding, finding that broad feature dimensions are biased before specific attributes.

The paper analyzes attention-related baseline activity using fMRI and two analytic approaches, finding that multivariate pattern analysis reveals top-down attentional biases across the visual hierarchy, which better predict behavioral performance than univariate activation.

The paper investigates how attentional control modulates a left visual field bias in cued visual spatial attention using pupillometry and fMRI.

This study uses EEG and machine learning to identify the onset and focus of voluntary visual-spatial attention without external cues.

This study investigates the role of the inferior frontal junction (IFJ) in feature versus spatial attention using fMRI, finding that right IFJ is involved in feature attention but not spatial attention.