Fig. 2: Biological networks with memory exhibit an increase of causal emergence during training and do so more than random networks.
From: Associative conditioning in gene regulatory network models increases integrative causal emergence
A Error bars for the % change in causal emergence from before to after training for biological and random networks; each point corresponds to one circuit of one network. Biological networks are significantly more causally emergent after training. The asterisks above the brackets indicate significance at p < 0.001 with the Mann-Whitney test. B Bars for the % of those networks that have memory and those that, if they have memory, show an increase in causal emergence after training. Associative training results in increased causal emergence among almost all networks with memory.
