Fig. 4: Re-instatement mechanism during the feedback conditions of runs with high regulation.

Linear mixed model analysis on the networks’ transition probabilities identified a triple interaction between condition, high-regulation, and initial network of the transition (p = 0.00058). Subsequent analysis revealed that in the feedback condition of runs with high regulation, three networks (PH, DMN^-, sensorimotor^-) significantly changed their transitions to other networks as compared to the feedback condition of runs where high regulation was not achieved. These changes in transition probabilities formed a reinforcement loop to the PH-network through networks that were similar to it. They were predominantly marked by increases in the transitions from the PH-network, to two networks which include activations over major PH-network clusters (DMN^- by 28%, and sensorimotor^- by 12%), by increases from the DMN^- to itself (22%) and to the sensorimotor^- (64%), and of the sensorimotor^- to itself (34%) and back to the PH-network (44%).