Functional interactions between brain regions or neurons have been described using features defined in network theory. For instance, the rich club phenomenon correspond to having high-degree nodes connected between them above chance-level. In our new Nature Physics paper we generalize this notion to dynamic networks. Indeed, in order for a certain spatial pattern in network connectivity to be functionally effective it is also important that it maintains its cohesion over a certain time, in order for the associated computations (e.g. information integration) to be performed and completed.
The temporal rich club phenomenon corresponds to nodes with high degree being connected between them for a sufficient time above chance level, where the chance-level is defined in terms of spatiotemporal and not uniquely spatial null models. Thus the temporal rich club and the classic static rich club are not equivalent properties, as we reveal through a series of examples from different domains of application.
Considering information sharing in hippocampal recordings we observed that the emergence and dissolution of cohesion within alternative sets of rich club nodes is the main determinant of transitions between network states. Furthermore, these switching transitions get more random and less structured in the case of epilepsy.
Our new results on temporal rich clubs generalize previous analyses where we already modeled hippocampal cell assembly dynamics in terms of temporal networks.
To know more:
- Pedreschi, N., Battaglia, D., Barrat, A. (2022) The temporal rich club phenomenon. Nature Physics, doi:10.1038/s41567-022-01634-8.
- Pedreschi, C. Bernard, W. Clawson, P. Quilichini, A. Barrat*, D. Battaglia* (2020). Dynamic core periphery structure of information sharing networks in entorhinal cortex and hippocampus. Network Neurosci 4, 946–975. [* Shared last authorship].