Anna C. Schapiro

Arousal state modulates human hippocampal ripples

This study shows that human hippocampal ripples are modulated by arousal states, occurring more frequently during low arousal periods like sleep and certain wake states.

Memory reactivation during sleep promotes structure abstraction

This study shows that memory reactivation during sleep promotes structural abstraction, enabling knowledge transfer between categories with no feature overlap.

A unifying account of replay as context-driven memory reactivation

This paper proposes a theoretical framework explaining replay as context-driven memory reactivation, showing how it facilitates memory consolidation through context-experience interactions.

A gradient of complementary learning systems emerges through meta-learning

This study uses meta-learning in artificial neural networks to simulate brain organization, finding that hierarchical learning systems emerge with properties similar to primate brain subsystems.

Memory reactivation during sleep does not act holistically on object memory

The paper investigates how sleep reactivation affects memory transformation by improving distinguishing features while worsening shared features of object memories.

Semantic plasticity across timescales in the human brain

The paper investigates how the brain balances stability and plasticity in semantic representations over different timescales using fMRI data from multiple sessions.

Rapid learning of temporal dependencies at multiple timescales

This study investigates how humans and a model learn temporal patterns at multiple timescales through a game-based paradigm, finding stronger learning for short timescales.

A neural network model of hippocampal contributions to category learning

The paper uses a neural network model of the hippocampus to simulate category learning, finding that different pathways support exemplar-specific memory and category structure detection.

Building integrated representations through interleaved learning

This study shows interleaved learning promotes integrated representations in humans, enhancing generalization and inference.

A model of autonomous interactions between hippocampus and neocortex driving sleep-dependent memory consolidation

This paper presents a neural network model simulating hippocampus-neocortex interactions during sleep to explain memory consolidation and continual learning.

Representations of temporal community structure in hippocampus and precuneus predict inductive reasoning decisions

The paper shows that neural representations of temporal community structure in hippocampus and precuneus predict inductive reasoning decisions based on learned object relationships.

Tracking the relation between gist and item memory over the course of long term memory consolidation

This study investigates how gist and item memory change over time, finding that gist memory persists and influences item memory, with biases shifting based on item regularities.

Influences of time of day on generalization

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

Facilitating open-science with realistic fMRI simulation: validation and application

This paper introduces fmrisim, a Python package for simulating realistic fMRI data, validated to match real noise properties and used to optimize experimental design and pre-registration.

The hippocampus is necessary for the sleep-dependent consolidation of a task that does not require the hippocampus for initial learning

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.

Sleep selectively stabilizes contextual aspects of negative memories

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

Human hippocampal replay during rest prioritizes weakly-learned information and predicts memory performance

The paper shows that during rest, the human hippocampus replays weakly-learned memories more, which predicts better memory performance and relates to memory improvement after sleep.

Variability and stability of large-scale cortical oscillation patterns

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

Sleep Benefits Memory For Semantic Category Structure While Preserving Exemplar-Specific Information

This study shows sleep enhances memory for shared category properties while preserving unique exemplar information, with effects influenced by REM and non-REM sleep.

Individual differences in frequency and topography of slow and fast sleep spindles

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.