Functional Brain Networks Underlying Autobiographical Event Simulation: An Update

Functional magnetic resonance imaging (fMRI) studies typically explore changes in the blood-oxygen-level-dependent (BOLD) signal underlying discrete cognitive processes that occur over milliseconds to a few seconds. However, autobiographical cognition is a more protracted process and requires fMRI tasks with longer trials to capture the temporal dynamics of the underlying brain networks. In the current study, we provide an updated analysis of the fMRI data obtained from a published autobiographical event simulation task, with a slow-event-related design (34-second trials), that involved participants recalling past autobiographical events, imagining past/future autobiographical events, and completing a semantic association control task. Our updated analysis using Constrained Principal Component Analysis for fMRI (fMRI-CPCA) retrieved two networks reported in the original results, including the Default Mode Network (DMN) which was activated in the autobiographical event simulation conditions but deactivated in the semantic association control condition, and the Multiple Demand Network (MDN) which peaked early during all conditions but was more sustained in the recall condition. Two novel networks emerged, including the Maintaining Internal Attention network (MAIN) which, while active for all conditions, was more strongly engaged during the imagination and semantic association control conditions than during the Recall condition, suggesting a role in constructing novel associations. These results suggest that the DMN does not support autobiographical simulation alone, but co-activates with the MDN and MAIN networks, with the timing of peak activations depending on evolving task demands during the simulation process.