Different clones for different contexts: Hippocampal cognitive maps as higher-order graphs of a cloned HMM
Gothoskar, N.; Guntupalli, J. S.; Rikhye, R. V.; Lazaro-Gredilla, M.; George, D.
Show abstract
Hippocampus encodes cognitive maps that support episodic memories, navigation, and planning. Under-standing 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 frame-work for understanding hippocampal function.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- The Tolman-Eichenbaum Machine: Unifying space and relational memory through generalisation in the hippocampal formation 93%
- Neurotransmitter Classification from Electron Microscopy Images at Synaptic Sites in Drosophila Melanogaster 92%
- Evolving super stimuli for real neurons using deep generative networks 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.