Patterns across multiple memories are identified over time
Abstract
Memories are not static but continue to be processed after encoding. This is thought to allow the integration of related episodes via the identification of patterns. Although this idea lies at the heart of contemporary theories of systems consolidation, it has yet to be demonstrated experimentally. Using a modified water-maze paradigm in which platforms are drawn stochastically from a spatial distribution, we found that mice were better at matching platform distributions 30 d compared to 1 d after training. Post-training time-dependent improvements in pattern matching were associated with increased sensitivity to new platforms that conflicted with the pattern. Increased sensitivity to pattern conflict was reduced by pharmacogenetic inhibition of the medial prefrontal cortex (mPFC). These results indicate that pattern identification occurs over time, which can lead to conflicts between new information and existing knowledge that must be resolved, in part, by computations carried out in the mPFC.
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The mPFC is involved in monitoring the degree of consistency between existing schemas and novel information.
“Given the known role of the mPFC in monitoring the contents of memory retrieval 22 , this finding suggests that the mPFC is involved in monitoring the degree of consistency between existing schemas and novel information 1,53,121 .”
From From cognitive maps to spatial schemas (2023) · cites this paper as [1]
In a water-maze paradigm, mice exposed to platform locations moved across trials according to selections from a normal distribution acquired a generalized representation of the spatial distribution.
“In a water-maze paradigm, mice exposed to platform locations that were moved across trials according to selections from a normal distribution were able to acquire a generalized representation of the spatial distribution that was disrupted by pharmacological inhibition of the mPFC 1 .”
From From cognitive maps to spatial schemas (2023) · cites this paper as [1]
Pattern recognition is a neural mechanism for gist extraction and schema formation in mice and humans.
“Pattern recognition is a neural mechanism for gist extraction and schema formation in mice 1 and humans 119,120 .”
From From cognitive maps to spatial schemas (2023) · cites this paper as [1]
The generalized representation of the spatial distribution in mice was disrupted by pharmacological inhibition of the mPFC.
“that was disrupted by pharmacological inhibition of the mPFC 1 .”
From From cognitive maps to spatial schemas (2023) · cites this paper as [1]
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- Authors
- Richards, B. A., Xia, F., Santoro, A., Husse, J., Woodin, M. A., Josselyn, S. A., & Frankland, P. W.
- Affiliations
- University of Toronto (CA)
- Corresponding author
- Frankland, Paul W
- Venue
- Nature Neuroscience
- Published
- 2014-06-01
- Volume
- 17
- Issue
- 7
- Pages
- 981-986
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2007232825
- Cited by
- 150
- References
- 45
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 14 · 2023: 15 · 2022: 12 · 2021: 20 · 2020: 12 · 2019: 16 · 2018: 17 · 2017: 13 · 2016: 9 · 2015: 5 · 2014: 3
- FWCI
- 5.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Canadian Institutes of Health Research (MOP74650, MOP123466, MOP77561)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
- Keywords
- pattern identification, systems consolidation, medial prefrontal cortex, spatial memory, water maze, memory updating, episodic memory, mice
- MeSH terms
- Dependovirus, Algorithms, Animals, Conflict, Psychological, Female, Genetic Vectors, Male, Membrane Potentials, Memory, Mice, Inbred C57BL, Models, Neurological, Pharmacogenetics, Stochastic Processes, Models, Statistical, Prefrontal Cortex, Maze Learning, Entropy, Mice, Electrophysiological Phenomena
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