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BrainSLAM: SLAM on Neural Population Activity Data
This system uses a convolutional neural network (CNN) to decode velocity and familiarity information from wavelet scalograms of neural local field potential data recorded from rats as they navigate a 2D maze.
Learning offline: memory replay in biological and artificial reinforcement learning
Learning to act in an environment to maximise rewards is among the brain's key functions.
The infinite Viterbi alignment and decay-convexity
Quantitative bounds on the distance to the infinite Viterbi alignment, which are the first of their kind, are derived and used to illustrate how approximate estimation via parallelization can be accurate and scaleable to high-dimensional problems because the rate of convergence to the infinite Viterbi alignment does not necessarily depend on $d$.
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