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. Author manuscript; available in PMC: 2018 Aug 1.
Published in final edited form as: Neural Comput. 2017 Nov 21;30(2):378–396. doi: 10.1162/neco_a_01041

Figure 2. A single RNN can encode many different feedforward trajectories.

Figure 2

A. The units of the same trained RNN in response to two different inputs. Each column shows the spatiotemporal pattern of activity triggered by a single input. Each row shows the activity sorted according to feedforward trajectory #1 (top row) or #2 (bottom row). Blue and pink dashed lines highlight the same two units in all panels. B. Performance (top) and failure rate (bottom) for ten networks trained to produce up to 20 trajectories. Each dot represents the average across 15 trials per target for a single network. Each network can reliably produce up to ten feedforward sequences before performance decreases. Error bars show the mean ± SEM