  Neural computation is associated with the emergence, reconfiguration and
dissolution of cell assemblies in the context of varying oscillatory states.
Here, we describe the complex spatio-temporal dynamics of cell assemblies
through temporal network formalism. We use a sliding window approach to extract
sequences of networks of information sharing among single units in hippocampus
and enthorinal cortex during anesthesia and study how global and node-wise
functional connectivity properties evolve along time. First, we find that
information sharing networks display, at any time, a core-periphery structure
in which an integrated core of more tightly functionally interconnected units
link to more loosely connected network leaves. However the units participating
to the core or to the periphery substantially change across time-windows.
Second, we find that discrete network states can be defined on top of this
continuously ongoing liquid core-periphery reorganization. Switching between
network states results in a more abrupt modification of the units belonging to
the core and is only loosely linked to transitions between global oscillatory
states. Third, we characterize different styles of temporal connectivity that
cells can exhibit within each state of the sharing network. While inhibitory
cells tend to be central, we show that, otherwise, anatomical localization only
poorly influences the patterns of temporal connectivity of the different cells.
Cells can also change temporal connectivity style when the network changes
state. Altogether, these findings reveal that the sharing of information
mediated by the intrinsic dynamics of hippocampal and enthorinal cortex cell
assemblies have a rich spatiotemporal structure, which could not have been
identified by more conventional time- or state-averaged analyses of functional
connectivity.
