Functional Brain Networks Underlying Autobiographical Event Simulation: An Update

Abstract fMRI studies typically explore changes in the BOLD signal underlying discrete cognitive processes that occur over milliseconds to a few seconds. However, autobiographical cognition is a protracted process and requires fMRI tasks with longer trials to capture the temporal dynamics of the underlying brain networks. In the current study, we provided an updated analysis of the fMRI data obtained from a published autobiographical event simulation study, with a slow event-related design (34-sec trials), that involved participants recalling past, imagining past, and imagining future autobiographical events, as well as completing a semantic association control task. Our updated analysis using Constrained Principal Component Analysis for fMRI retrieved two networks reported in the original study: (1) the default mode network, which activated during the autobiographical event simulation conditions but deactivated during the control condition, and (2) the multiple demand network, which activated early in all conditions during the construction of the required representations (i.e., autobiographical events or semantic associates). Two novel networks also emerged: (1) the Response Network, which activated during the scale-rating phase, and (2) the Maintaining Internal Attention Network, which, while active in all conditions during the elaboration of details associated with the simulated events, was more strongly engaged during the imagination and semantic association control conditions. Our findings suggest that the default mode network does not support autobiographical simulation alone, but it co-activates with the multiple demand network and Maintaining Internal Attention Network, with the timing of activations depending on evolving task demands during the simulation process.