replay_trajectory_classification
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Eden-Kramer-Lab
State space models for decoding hippocampal trajectories and determining their type using sorted or clusterless data
When there is missing data, the likelihood should be 1 for all states. Add an argument to predict to specify missing data timepoints.
Want the flexibility to add in a local state which directly encodes the animal's position. This requires evaluation of the likelihood at the predict state and passing in position. See...
Unsure if diffusion implementation is correctly handling the boundaries. Need to double check.
Currently, we ignore multiple spikes per bin. This seems to work okay, but we are losing data.
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State space models for decoding hippocampal trajectories and determining their type using sorted or clusterless data