Alex Chatburn

This study investigates how sleep-induced homeostatic changes, measured by aperiodic slope, influence memory consolidation and N400 amplitudes in humans.

The paper examines how certainty modulates anticipatory neural oscillations before feedback, showing distinct alpha and beta power changes linked to learning stages and memory updating.

This study compares representational merging during retrieval training and sleep, finding increased similarity between similar objects only during retrieval training.

This study compares how sleep and retrieval training affect memory generalization and episodic recollection using EEG measures, finding distinct neural and behavioral patterns.

This study compares sleep-based and retrieval-mediated memory consolidation using sigma-band activity, finding no enhancement of weakly encoded memories but a negative relationship between sigma power and memory outcomes.

This study investigates how predictability and individual alpha frequency affect memory using event-related potentials, finding that lower alpha frequencies correlate with better memory for predictable stimuli.

The paper reanalyzes data to explore how prediction and memory encoding relate, finding that memory encoding may occur independently of prediction error and that individual differences in neural activity affect this relationship.

The study reanalyzes language comprehension data to show that predictive processing in language depends on prior context and individual neural factors like alpha frequency.

The paper shows that resting-state EEG metrics, including oscillatory and aperiodic components, predict cognitive performance in dynamic tasks, with specific parameters linked to learning and testing outcomes.

The paper uses EEG data from dyads in training scenarios to show that resting-state and task-related neural activity predict team performance.

The paper investigates aperiodic neural activity as a marker for excessive daytime somnolence, finding it predictive of EDS with high accuracy using logistic regression.

The paper shows that sleep spindles correlate with learning patterns and predict memory consolidation in humans.

This study investigates how sleep affects true and false memory processing using ERP measurements in a DRM paradigm with a daytime nap.

This study shows that individual differences in visuomotor performance and learning can be predicted by resting-state aperiodic neural dynamics parameters, specifically 1/f intercept and slope.