First of all, we studied how hippocampal activation patterns can temporally organize to dynamically encode information either about current sensory information, or past experience. By studying the activity of so called ‘place cells’ while a mouse was freely exploring an environment, we found that these cells could modulate their activity in response to external input and local network processes, to form sequential patterns suited to either memory encoding or retrieval (Figure 1). Moreover, different groups of cells would be preferentially dedicated to one of the two functions, hinting at the existence of parallel information streams in the hippocampus, balancing the creation of novel memory traces and the maintenance of already existing ones. Current analysis of subsequent sleep activity aims at elucidate the role of these neurons in the consolidation of memory.
Looking at larger context of hippocampal-cortical dialogue, we took advantage of state-of-the-art imaging data of the entire cortical surface and applied advanced statistical methods to develop a model of cortical spontaneous activity propagation during sleep. We delineated the presence of multiple integrated functional networks, hierarchically organized and spatially segregated (Figure 2). Such networks largely overlapped with known subdivisions based on cortical connectivity and in particular appeared to indicate the existence of a set of networks (akin to the Default Mode Network found in humans) preferentially communicating with the hippocampus and actually controlling its activation during periods of rest. Interestingly these networks displayed many of the signatures of a critical state, even more strongly the closer was their interaction with the hippocampus, a finding that can have important implications for the processing of mnemonic information.
These results are now in the process of being published in high-profile peer reviewed journals and are the subject of multiple presentations at conferences and scientific meetings.
To better understand these implications, we are currently complementing these analyses on experimental data with a set of modeling studies aimed both at studying the importance of the temporal structure of hippocampal place cell activity, and at investigating the dynamics of learning in a neural network operating at a critical transition point.
