Technical Program

Paper Detail

Paper: PS-1A.35
Session: Poster Session 1A
Location: H Lichthof
Session Time: Saturday, September 14, 16:30 - 19:30
Presentation Time:Saturday, September 14, 16:30 - 19:30
Presentation: Poster
Publication: 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany
Paper Title: Different clones for different contexts: Hippocampal cognitive maps as higher-order graphs of a cloned HMM
Manuscript:  Click here to view manuscript
License: Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
Authors: Nishad Gothoskar, J Swaroop Guntupalli, Rajeev Rikhye, Miguel Lázaro-Gredilla, Dileep George, Vicarious AI, United States
Abstract: Hippocampus encodes cognitive maps that support episodic memories, navigation, and planning. Understanding the commonality among those maps as well as how those maps are structured, learned from experience, and used for inference and planning is an interesting but unsolved problem. We propose higher-order graphs as the general principle and present, as a plausible model, a cloned hidden Markov model (HMM) that can learn these graphs efficiently from experienced sequences. In our experiments we use the cloned HMM for learning spatial and abstract representations. We show that inference and planning in the learned CHMM encapsulates many of the key properties of hippocampal cells observed in rodents and humans. Cloned HMM thus provides a new framework for understanding hippocampal function.