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. 2018 Oct 19;8(6):20180033. doi: 10.1098/rsfs.2018.0033

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© 2018 The Authors.

Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

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Figure 3. — Maximum storage load as a function of the field intensity for a network of N = 400 neurons. The correlations were recorded in windows of T = 20 time steps and the field intensity step was . The noise level in the retrieval phase is set to and the temperature to . The curve was obtained by averaging over 100 samples. The inset shows a comparison between the recurrent and external components of the inputs, for the same data points of the main panel. The mean recurrent input was computed as the 2-norm of the mean values. This shows that the DCM rule is effective even for relatively small stimuli. (Online version in colour.)

Inline graphic — Maximum storage load as a function of the field intensity for a network of N = 400 neurons. The correlations were recorded in windows of T = 20 time steps and the field intensity step was . The noise level in the retrieval phase is set to and the temperature to . The curve was obtained by averaging over 100 samples. The inset shows a comparison between the recurrent and external components of the inputs, for the same data points of the main panel. The mean recurrent input was computed as the 2-norm of the mean values. This shows that the DCM rule is effective even for relatively small stimuli. (Online version in colour.)