Actively Recruiting

Phase Not Applicable
Age: 18Years - 35Years
All Genders
Healthy Volunteers
NCT05910762

Human Learning of New Structured Information Across Time and Sleep

Led by University of Pennsylvania · Updated on 2025-08-01

105

Participants Needed

1

Research Sites

247 weeks

Total Duration

On this page

Sponsors

U

University of Pennsylvania

Lead Sponsor

N

National Institute of Mental Health (NIMH)

Collaborating Sponsor

AI-Summary

What this Trial Is About

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

Official Title

Human Learning of New Structured Information Across Time and Sleep

Who Can Participate

Age: 18Years - 35Years
All Genders
Healthy Volunteers

Eligibility Criteria

Eligible

You may qualify if you...

  • Between 18 and 35 years of age
  • Not a member of a vulnerable population
  • Normal or corrected-to-normal vision
  • Normal hearing
  • Able to speak English fluently
  • No prior history of major psychiatric or neurological disorders (for MRI-related aims)
  • Not currently taking any antidepressants or sedatives (for MRI-related aims)
  • No known neurological disorders (for EEG-related aim)
Not Eligible

You will not qualify if you...

  • Presence of MR contraindications such as non-removable biomedical devices or metal in or on the body (for MRI-related aims)
  • Claustrophobia (for MRI-related aims)
  • Pregnancy (excluded from neuroimaging due to unknown effects of MR on pregnancy)

AI-Screening

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Trial Site Locations

Total: 1 location

1

University of Pennsylvania

Philadelphia, Pennsylvania, United States, 19104

Actively Recruiting

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Research Team

A

Anna C Schapiro, PhD

CONTACT

R

Rishi Krishnamurthy, BA

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

SINGLE

Allocation

RANDOMIZED

Model

PARALLEL

Primary Purpose

BASIC_SCIENCE

Number of Arms

3

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