Robert Stickgold

The paper shows that hippocampal ripples during rest breaks predict motor learning in humans, suggesting a role for ripples in procedural memory.

The paper examines sleep spindle activity and memory consolidation in early psychosis patients and their relatives, finding spindle deficits and memory issues in patients but not relatives.

This study replicates group-level sleep EEG differences in schizophrenia and shows increased patient-to-patient variability in NREM metrics, with medication and age-related effects contributing to this heterogeneity.

This study identifies biases in group-level EEG microstate analysis and proposes a paired analysis approach to reduce errors from subgroup topography differences.

The paper investigates how emotional memory consolidation during sleep stages affects memory retention, finding that reactivating memories during slow wave sleep enhances them, while reactivation during REM impairs them.

This study identifies NREM sleep and wake EEG biomarkers associated with schizophrenia symptom severity and disease status.

The paper examines EEG microstate dynamics during post-encoding rest and finds increased microstate D and decreased microstate C, associated with memory consolidation and encoding strength.

The paper shows sleep spindles help consolidate weakly encoded memories, reducing forgetting rates compared to staying awake.

This study investigates how time of day affects generalization ability, finding better performance in the morning than the evening, with no benefit from sleep.

The paper shows that the hippocampus is necessary for consolidating a task not initially requiring it, using motor sequence learning in hippocampal amnesics and controls.

The paper examines how sleep affects the retention of negative and neutral memories, finding that sleep selectively stabilizes negative contextual memories.

The paper characterizes the spatial and temporal dynamics of slow oscillation-spindle coupling during sleep and finds individual variability in coupling phase that is stable across nights but not linked to memory change.

This study characterizes large-scale cortical oscillation patterns across individuals and time, finding both common templates and stable individual-specific networks.

This study characterizes individual variability in slow and fast sleep spindle frequency and topography using EEG recordings and introduces a method to reliably separate spindle components across sleep stages.