“Cortico-hippocampal organization and dynamics influence memory for complex events”
Hosted by the WashU Neuroimaging Community (WUNIC)
Abstract: According to most memory theories, encoding involves continuous communication between the hippocampus and neocortex leaving the temporal dynamics of hippocampal-neocortical interactions often overlooked. Recent work has shown that we perceive complex events in our lives as dynamic, with relatively distinct starting and stopping points known as event boundaries. Event boundaries may be important for memory, as they are associated with increased activity in the hippocampus, and extended neocortical regions (the posterior cingulate cortex, lateral parietal cortex, and parahippocampal cortex). Our objective was to determine how functional connectivity between the hippocampus and neocortical regions during the encoding of naturalistic events (movies) related to subsequent retrieval and retention of those events. Participants encoded two 16-minute cartoon movies during fMRI scanning. After encoding, participants freely recalled one of the movies immediately, and the other after a 2-day delay. We quantified hippocampal-neocortical functional connectivity (FC) at time windows around each event onset, middle, and offset, and compared these FC measures with subsequent recall. These analyses revealed that higher FC between the hippocampus and the posterior medial network (PMN) at an event’s offset related to whether that event was subsequently recalled. In contrast, mid-event connectivity between the hippocampus and PMN was associated with poorer memory. Furthermore, hippocampal-PMN offset connectivity predicted not only whether events were retained in memory, but also the degree to which these events could be recalled in detail after a 2-day delay. These data demonstrate that the relationship between memory encoding and hippocampal-neocortical interaction is more dynamic than suggested by most memory theories, and they converge with recent modeling work suggesting that event offset is an optimal time for encoding.
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