A Topological Paradigm for Hippocampal Spatial Map Formation Using Persistent Homology
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Abstract
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DOI: 10.1371/journal.pcbi.1002581
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References listed on IDEAS
- Carina Curto & Vladimir Itskov, 2008. "Cell Groups Reveal Structure of Stimulus Space," PLOS Computational Biology, Public Library of Science, vol. 4(10), pages 1-13, October.
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Cited by:
- Samir Chowdhury & Bowen Dai & Facundo Mémoli, 2018. "The importance of forgetting: Limiting memory improves recovery of topological characteristics from neural data," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-20, September.
- Mamiko Arai & Vicky Brandt & Yuri Dabaghian, 2014. "The Effects of Theta Precession on Spatial Learning and Simplicial Complex Dynamics in a Topological Model of the Hippocampal Spatial Map," PLOS Computational Biology, Public Library of Science, vol. 10(6), pages 1-14, June.
- Chong, Woon Kian & Chang, Chiachi, 2024. "Information exploitation of human resource data with persistent homology," Journal of Business Research, Elsevier, vol. 172(C).
- Zixuan Cang & Lin Mu & Guo-Wei Wei, 2018. "Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-44, January.
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