ArticleCommunications biology2025
Time-dependent consolidation mechanisms of durable memory in spaced learning.
Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Article
- Active Ingredients in Digital Cognitive Interventions: Integrating Dismantling Designs With Mechanistic Neuroscience.JMIR mental health · 2026Article
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Authors and funding
5 authors.
Funding
Abstract
Emerging studies suggest that time-dependent consolidation enables memory stabilization by promoting memory integration and hippocampal-cortical transfer. Compared to massed learning, how time-dependent consolidation contributes to forming durable memory and what neural signatures predict durable memory in spaced learning remain unclear. We recruited 48 participants who underwent either 3-day spaced learning or 1-day massed learning, and both resting-state and task-based fMRI data were collected in multiple delayed tests (i.e., immediate, 1-week, and 1-month). We use representational similarity analysis to assess neural integration and replay in the hippocampus and default mode network (DMN) subsystems. In contrast with massed learning, spaced learning induces higher neural pattern similarity during immediate retrieval only in DMN subsystems. Particularly, the neural pattern similarity in the dorsal-medial DMN (DMN
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.