Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation

Abstract

Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM) sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (1215 Hz) sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks.

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Document Details

Document Type
Technical Report
Publication Date
Feb 06, 2018
Accession Number
AD1072970

Entities

People

  • Diana M. Armstrong
  • Lexus T. Hernandez
  • Mario Aguilar
  • Michael P. Weisend
  • Nicola Cellini
  • Patrick M. Connolly
  • Renee E. Shimizu
  • Rolando Estrada
  • Sara Mednick
  • Stephen B. Simons

Organizations

  • University of California, Riverside

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Brain
  • Closed Loop Systems
  • Data Science
  • Detection
  • Eye Movements
  • Health Services
  • Identification
  • Information Science
  • Mobile Phones
  • Navigation
  • Neurosciences
  • Psychology
  • Standards
  • Statistical Analysis
  • United States
  • United States Government
  • Virtual Reality

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Circadian Sleep-Wake Regulation and Chronobiology