New strategies for the cognitive science of dreaming.
Remington Mallett, Karen R Konkoly, Tore Nielsen, Michelle Carr, Ken A Paller
Trends in Cognitive Sciences December 1, 2024 DOI: 10.1016/j.tics.2024.10.004 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Review Peer reviewed |
|---|---|
| Topics | Dreaming |
| Keywords | Dreams Memory Natural language processing Sleep |
| Key findings | Recent interdisciplinary advances in neural decoding, targeted stimulation, and computational analysis enable systematic observation, engineering, and analysis of dreams, overcoming historical methodological barriers. |
Abstract
Dreams have long captivated human curiosity, but empirical research in this area has faced significant methodological challenges. Recent interdisciplinary advances have now opened up new opportunities for studying dreams. This review synthesizes these advances into three methodological frameworks and describes how they overcome historical barriers in dream research. First, with observable dreaming, neural decoding and real-time reporting offer more direct measures of dream content. Second, with dream engineering, targeted stimulation and lucidity provide routes to experimentally manipulate dream content. Third, with computational dream analysis, the generation and exploration of large dream-report databases offer powerful avenues to identify patterns in dream content. By enabling researchers to systematically observe, engineer, and analyze dreams, these innovations herald a new era in dream science.