Edward K. Vogel

The paper shows that neural patterns reconfigure with increasing memory load, revealing a low-dimensional trajectory linked to memory performance.

The paper investigates how working memory capacity influences voluntary task switching, finding that lower capacity individuals are more likely to switch after attentional lapses, while higher capacity individuals switch from focused states.

The paper identifies a unique neural signature of long-term memory encoding using EEG inter-electrode correlation, showing it predicts individual differences in LTM encoding independent of VWM performance.

This study investigates the relationship between sustained attention and cognitive processes, finding that individual differences in sustained attention are more closely linked to long-term memory than to attentional control and working memory.

This study examines how repetitive learning affects two ERP components associated with recognition memory, finding that the parietal old/new effect changes with repetition while the frontal effect remains stable.

This study identifies EEG signatures of attentional lapses distinct from selective attention failures using machine learning and reaction-time analysis.

This study compares objective and subjective measures of attentional fluctuations during sustained attention tasks, finding they capture distinct patterns.

This study shows that alpha-band EEG activity tracks dynamic transformations of spatial working memory representations during mental imagery tasks.

This study investigates pupil dynamics during sustained attention and working memory tasks, finding that pupil size correlates with attention levels and working memory load.

The paper shows sustained attention and spatial attention have distinct effects on long-term memory encoding through three experiments and EEG analysis.

The paper demonstrates that multivariate analysis of EEG voltage topography provides a sensitive and generalizable index of working memory load across multiple studies and tasks.

The paper investigates attentional capture in working memory, showing that relevant and irrelevant interrupters trigger different sub-component processes affecting WM maintenance.

The paper uses EEG connectivity patterns to predict individual differences in working memory capacity and fluid intelligence across datasets.

The paper investigates how task-irrelevant interruptions affect neural representations of working memory using EEG in humans, finding distinct responses in CDA and lateralized alpha power.

This study uses alpha-band oscillations and an inverted encoding model to track and reconstruct precise spatial memory retrieval from long-term memory.

The paper tests whether multiple items can be stored concurrently in working memory by analyzing alpha-band EEG activity during a spatial memory task.

The paper distinguishes neural processes for spatial attention and object-based storage in visual working memory using EEG recordings during attention and memory tasks.