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Resting state network (RSN) is a correlated activity of many brain areas in absence of external stimulation or functional tasks, and it is a fundamental endogenous feature of human and animal brain. The nature of this spontaneous activity remains poorly understood. According to our hypothesis it reflects hidden replay of neural networks of prior experience. We started a project on mouse cellular brain imaging that relates RSNs activity to animal’s past experiences. We characterized activity of 104 mouse brain areas and showed that RSNs identified by c-Fos expression were stable and reproducible. Then we modeled post-traumatic stress disorder (PTSD) and imaged c-Fos RS activity of 42 selected brain areas in PTSD and naive mice. We reconstructed RSNs for naive and PTSD mice and compared them with model networks (random, scale free and small world) using clustering, global efficiency and degree distribution. In both groups of mice, clustering was at the level of a random network. These clusters had weak interactions with each other: global efficiency of RSNs was extremely low. PTSD affected subsequent RS activity all over the brain and caused global changes in the RSN structure: PTSD network was less clustered and had longer routes than in naive mice. While in control animals cortical connectivity was high, in PTSD mice thalamus, striatum and amygdala were most connected. In naive mice cingulate and retrosplenial cortices were the main hubs, but in PTSD mice functional connectivity between those areas was lost, and paraventricular thalamus became a hub. Finally, in fos-Cre-dTomato mice stress-activated neurons were also preferentially active during rest. Thus, we showed that experience of stressful event could change RSN functional connectivity patterns long after the traumatic episode, and that cells previously involved in the consolidation of an impactful memory are predominantly reactivated in the RS.