Human Learning of New Structured Information Across Time and Sleep

Summary

Acting adaptively requires quickly picking up on structure in the environment and storing the acquired knowledge for effective future use. Dominant theories of the hippocampus have focused on its ability to encode individual snapshots of experience, but the investigators and others have found evidence that it is also crucial for finding structure across experiences. The mechanisms of this essential form of learning have not been established. The investigators have developed a neural network model of the hippocampus instantiating the theory that one of its subfields can quickly encode structure using distributed representations, a powerful form of representation in which populations of neurons become responsive to multiple related features of the environment.

The first aim of this project is to test predictions of this model using high resolution functional magnetic resonance imaging (fMRI) in paradigms requiring integration of information across experiences. The results will clarify fundamental mechanisms of how humans learn novel structure, adjudicating between existing models of this process, and informing further model development. There are also competing theories as to the eventual fate of new hippocampal representations. One view posits that during sleep, the hippocampus replays recent information to build longer-term distributed representations in neocortex. Another view claims that memories are directly and independently formed and consolidated within the hippocampus and neocortex.

The second aim of this project is to test between these theories. The investigators will assess changes in hippocampal and cortical representations over time by re-scanning participants and tracking changes in memory at a one-week delay. Any observed changes in the brain and behavior across time, however, may be due to generic effects of time or to active processing during sleep.

The third aim is thus to assess the specific causal contributions of sleep to the consolidation of structured information. The investigators will use real-time sleep electroencephalography to play sound cues to bias memory reactivation. The investigators expect that this work will clarify the anatomical substrates and, critically, the nature of the representations that support encoding and consolidation of novel structure in the environment.

Conditions

• Learning
• Humans
• Consolidation
• Sleep

Interventions

BEHAVIORAL

Associative inference

Participants will engage in an associative inference paradigm. Memory will be assessed behaviorally and neural representations will be assessed using functional magnetic resonance imaging.

BEHAVIORAL

Category learning

Participants will engage in a category learning paradigm. Memory will be assessed behaviorally (Arms 2 and 3), and neural representations will be assessed using functional magnetic resonance imaging (Arm 2).

BEHAVIORAL

Sleep

Participants will sleep after engaging in a category learning paradigm while electroencephalography data are collected, and memory will be assessed behaviorally after sleep.

Sponsors & Collaborators

• National Institute of Mental Health (NIMH)

  collaborator NIH

• University of Pennsylvania

  lead OTHER

Principal Investigators

• Anna C Schapiro, PhD · University of Pennsylvania

Study Design

Allocation

RANDOMIZED

Purpose

BASIC_SCIENCE

Masking

SINGLE

Model

PARALLEL

Eligibility

Min Age

18 Years

Max Age

35 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2023-06-05

Primary Completion

2028-03-31

Completion

2028-03-31

Countries

• United States

Study Locations