Spontaneous and evoked activity align through self-organization.

<p>The network was stimulated with the words “ABCD” (67%) and “EFGH” (33%). (a) The spontaneous activity follows the spatiotemporal trajectories of the evoked states in the PCA projection. (b) In the multidimensional scaling projection, the evoked activity (red) follows the spontaneous outline (black) and avoids the shuffled spontaneous states (blue) (cp. Fig 6c of [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004640#pcbi.1004640.ref013" target="_blank">13</a>]). (c) The evoked states are closer to the spontaneous states than to the shuffled spontaneous states: As in Fig 6 of [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004640#pcbi.1004640.ref013" target="_blank">13</a>], the distance from evoked states to the closest spontaneous states (D_spont) is smaller than the distance to the closest shuffled spontaneous state (D_shuff). The red dashed line shows equality. (d) Spontaneous activity becomes more similar to evoked activity during learning: After self-organizing to “ABCD” and “EFGH” with identical probabilities, spontaneous activity was compared to the evoked activity from the imprinted sequences (natural) or the two control sequences “EDCBA” and “FGH” (control) with Kullback-Leibler divergence. New networks were generated for each training time and condition. Error bars represent SEM over 50 independent realizations. ⋆ indicates <i>p</i> < 0.05 for a t-test assuming independent samples and identical variances.</p>