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Network Dynamics in Memory Replay

Top left: images describing an online task. Bottom left: offline resting state MEG signals. Right: replay of events and resting state networks.
Inferring the relationship between inferred memory replay and activation of electrophysiological resting state networks.

Our brains at rest spontaneously replay the cellular patterns associated with recently acquired information in order to form stable memory traces. A significant question for neuroscience is how this process interacts with ongoing cognitive demands – for example, how we could replay recently acquired information without this interfering with our current focus of attention. 

We study this by analysing the resting state network patterns that activate around memory replay. We do this using the methods described here. We have found, for example, that replay is associated with whole brain patterns understood to inhibit bottom-up sensory processing, thereby blocking information from the senses from interfering with replayed memories. These patterns emerge over areas associated with internally oriented attention, that activate very transiently in time, and are interspersed with networks linked to direct sensory uptake.

We are aiming to further quantify how these networks are activated in time and how this might provide a framework by which immediate cognitive demands are balanced alongside longer term cognitive demands – such as the formation and consolidation of stable memories.

References

Higgins C, Liu Y, Vidaurre D, Kurth-Nelson Z, Dolan R, Behrens T, Woolrich M. Replay bursts in humans coincide with activation of the default mode and parietal alpha networks. Neuron 2021.

Liu Y, Dolan RJ, Higgins C, Penagos H, Woolrich MW, Ólafsdóttir HF, Barry C, Kurth-Nelson Z, Behrens TE. Temporally delayed linear modelling (TDLM) measures replay in both animals and humans. eLife 2021.