Skip to main content
. 2021 Jul 26;10:e65459. doi: 10.7554/eLife.65459

Figure 2. 20-dimensional STORE-RECALL and sMNIST task.

Figure 2.

(A) Sample trial of the 20-dimensional STORE-RECALL task where a trained spiking neural network (SNN) of leaky integrate-and-fire (LIF) neurons with spike frequency adaptation (SFA) correctly stores (yellow shading) and recalls (green shading) a pattern. (B, C) Test accuracy comparison of recurrent SNNs with different slow mechanisms: dual version of SFA where the threshold is decreased and causes enhanced excitability (ELIF), predominantly depressing (STP-D) and predominantly facilitating short-term plasticity (STP-F). (B) Test set accuracy of five variants of the SNN model on the one-dimensional STORE-RECALL task. Bars represent the mean accuracy of 10 runs with different network initializations. (C) Test set accuracy of the same five variants of the SNN model for the sMNIST time-series classification task. Bars represent the mean accuracy of four runs with different network initializations. Error bars in (B) and (C) indicate standard deviation.