Speaker
Description
The medial entorhinal cortex (MEC) supports the brain’s representation of space with distinct cell types whose firing is tuned to features of the environment (grid, border, and object-vector cells) or navigation (head-direction and speed cells). These functionally-distinct cell types are anatomically intermingled in the superficial layers of the MEC. Since no single sensory stimulus can faithfully predict the firing of these cells, and activity patterns are preserved across environments and brain states, attractor network models postulate that spatially-tuned firing emerges from specific connectivity motives among neurons of the MEC. To determine how those connectivity motives constrain the self-organized activity in the MEC network, we tested mice in a spontaneous locomotion task under sensory-deprived conditions, when activity likely is determined primarily by the intrinsic structure of the network. Using 2-photon calcium imaging, we monitored the activity of large populations of MEC neurons in head-fixed mice running on a wheel in darkness, in the absence of external sensory feedback tuned to navigation.
To reveal network dynamics under these conditions, we applied both linear and non-linear dimensionality reduction techniques to the spike matrix of each individual session. This way we were able to unveil the presence of motifs that involve the sequential activation of neurons over epochs of tens of seconds to minutes (“waves”). To characterize the nature of these waves we split neurons into ensembles of cells and computed the transition probabilities between ensembles. This temporal analysis revealed stereotyped trajectories across multiple ensembles, lasting up to 2-3 minutes. Waves were not found in spike-time-shuffled data. Waves swept through the entire network of active cells with slow temporal dynamics and did not exhibit any anatomical organization. Furthermore, waves were only partially modulated by behavioural features, such as running epochs and speed. Taken together, our results suggest that a large fraction of MEC-L2 neurons participates in common global dynamics that often takes the form of stereotyped waves. These activity patterns might progress through multiple subnetworks and couple the activity of neurons with distinct tuning characteristics in MEC.
