The HexMaze: A Previous Knowledge Task on Map Learning for Mice
Open accessAbstract
New information is rarely learned in isolation; instead, most of what we experience can be incorporated into or uses previous knowledge networks in some form. Previous knowledge in form of a cognitive map can facilitate knowledge acquisition and will influence how we learn new spatial information. Here, we developed a new spatial navigation task where food locations are learned in a large, gangway maze to test how mice learn a large spatial map over a longer time period—the HexMaze. Analyzing performance across sessions as well as on specific trials, we can show simple memory effects as well as multiple effects of previous knowledge of the map accelerating both online learning and performance increases over offline periods when incorporating new information. We could identify the following three main phases: (1) learning the initial goal location; (2) faster learning after 2 weeks when learning a new goal location; and then (3) the ability to express one-session learning, leading to long-term memory effect after 12 weeks. Importantly, we are the first to show that buildup of a spatial map is dependent on how much time passes, not how often the animal is trained.
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In the HexMaze, the passage of time, rather than frequency of training, is responsible for accumulation of spatial knowledge into a long-term representation.
“The more recently developed 'HexMaze', a large-scale, complex, gangway maze experienced by mice for different durations, has been used to show that the passage of time, rather than the frequency of training, is responsible for the accumulation of spatial knowledge into a long-term representation 69 .”
From From cognitive maps to spatial schemas (2023) · cites this paper as [69]
Sleep contributes greatly to the development of spatial schemas in mice navigating environments with repeating connectivity patterns.
“A study in mice navigating environments with repeating connectivity patterns further shows that sleep contributes greatly to the development of spatial schemas 69 .”
From From cognitive maps to spatial schemas (2023) · cites this paper as [69]
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- Authors
- Alonso, A., Bokeria, L., van der Meij, J., Samanta, A., Eichler, R., Lotfi, A., Spooner, P., Navarro Lobato, I., & Genzel, L.
- Affiliations
- Radboud University Nijmegen (NL)
- University of Edinburgh (GB)
- Corresponding author
- Genzel, Lisa
- Venue
- eneuro
- Publisher
- Society for Neuroscience
- Published
- 2021-06-16
- Volume
- 8
- Issue
- 4
- Pages
- ENEURO.0554-20.2021
- ISSN
- 2373-2822 (ISSN-L)
- PMC
- PMC8362685
- OpenAlex
- W3172909361
- Cited by
- 13
- References
- 45
- Citations by year
- 2026: 3 · 2024: 4 · 2023: 2 · 2022: 2 · 2021: 1 · 2020: 1
- FWCI
- 1.18
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- eNeuro (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion)
- Funders
- EC | Horizon 2020 (765549)
- Society and Science Branco Weiss Fellowship
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Physical Sciences › Engineering › Automotive Engineering › Spatial Cognition and Navigation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Keywords
- cognitive maps, spatial learning, mice, spatial memory, long-term memory, learning stages, online and offline learning
- MeSH terms
- Animals, Maze Learning, Mice, Spatial Navigation
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