Spike-Based Bayesian-Hebbian Learning of Temporal Sequences
Fig 7
Rank ordered ramps of Vm depolariziations forecast the serial position of upcoming attractors during cue-triggered recall of a temporal sequence.
(A) A cue (red star) presented 1 second into recall resonates through the trained network. (B) Activity levels based on (A) and sorted by attractor membership as in Figs 3H and 4D. (C) Average Vm (1 ms bins) taken for all excitatory cells in the network and smoothed per attractor index by a moving average with 200 ms window length. Truncated Vm values at the beginning and end are artifacts of the moving average procedure. In this example both before and after the cued sequence, patterns spontaneously but weakly activated, which could occur randomly due to the sensitivity of the system. Black arrows represent time periods occurring after the midpoint of the cue initially and after the midpoint of each attractor thereafter, during which the average Vm of the upcoming attractors are ranked according to their relative serial order within the sequence.