ArticleProceedings of the National Academy of Sciences of the United States of America2022
Multiple traces and altered signal-to-noise in systems consolidation: Evidence from the 7T fMRI Natural Scenes Dataset.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Drawings of THINGS: A large-scale drawing dataset of 1854 object concepts.Behavior research methods · 2026Article
- Memory consolidation during sleep: a facilitator of new learning?Neuropsychologia · 2026Review
- Exploring anterior thalamus functional connectivity with cortical regions in prospective memory with ultra-high-field functional MRI.Brain communications · 2025Article
- Human brain activity and functional connectivity associated with verbal long-term memory consolidation across 1 month.Frontiers in human neuroscience · 2024Article
- Structured memory representations develop at multiple time scales in hippocampal-cortical networks.bioRxiv : the preprint server for biology · 2023Article
- The functions of sleep: A cognitive neuroscience perspective.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
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Authors and funding
8 authors.
Funding
Abstract
The brain mechanisms of memory consolidation remain elusive. Here, we examine blood-oxygen-level-dependent (BOLD) correlates of image recognition through the scope of multiple influential systems consolidation theories. We utilize the longitudinal Natural Scenes Dataset, a 7-Tesla functional magnetic resonance imaging human study in which ∼135,000 trials of image recognition were conducted over the span of a year among eight subjects. We find that early- and late-stage image recognition associates with both medial temporal lobe (MTL) and visual cortex when evaluating regional activations and a multivariate classifier. Supporting multiple-trace theory (MTT), parts of the MTL activation time course show remarkable fit to a 20-y-old MTT time-dynamical model predicting early trace intensity increases and slight subsequent interference (
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