Long-term functional connectivity dynamics during brain development


Networks defined by sets of nodes and links conveniently represent many natural and human-made systems. Most studies still focus, however, on static networks, and the field of temporal networks, whereby the links evolve in time, is far from mature. In particular, while static network representations have led to many interesting insights into the structure and dynamics of the brain at different scales, the study of the dynamics of the functional connectivity between neurons is often seen as the next frontier. In this respect, the study of developing brain networks is particularly appealing: (1) their functional link dynamics can be studied on an extended timescale (days); (2) their functional structure is a biomarker of physiological brain growth; (3) their functional connectivity evolution is now experimentally accessible in vivo with all-optical approaches.
In this context, the Cossart lab has collected an imaging dataset tracking the identity and activity of thousands of active neurons in the cortex of mouse pups, from early development into adulthood. The project consists in (i) an in-depth analysis of this dataset, which will require the development of new adequate temporal network tools and the characterization of highly connected cells (hubs), (ii) the design of a temporal network model to describe the network evolution and (iii) the formulation of experimentally testable predictions concerning the rules of connectivity evolution and the emergence of hub nodes.


Temporal Networks; Development; Hubs; Functional connectivity dynamics


1) Extract functional connectivity evolution from the imaging datasets
2) Describe the evolution of the functional network structure across days, tracking the emergence of hub cells and the de-activation of other cells
3) Design a descriptive model of cortical network growth
4) Use the model to predict the characteristics of future hubs and design experiments to test these predictions.

Expected profile

We aim at recruiting a statistical physicist/applied mathematician specialized in network science or a computational neuroscientist for a project at the crossroads between computational neuroscience and network science. Previous knowledge of the basics of network science and machine learning tools will be a plus.

Articles related to the project

Bonifazi et al. GABAergic Hub Neurons Orchestrate Synchrony in Developing Hippocampal Networks. Science (2009)
Modol-Vidal et al. Assemblies of Perisomatic GABAergic Neurons in the Developing Barrel Cortex. Neuron (2020)
Muldoon S. and Cossart R. Dissecting Functional Connectivity of Neuronal Microcircuits: Experimental and Theoretical Insights. TINS (2011)
P. Holme. Modern temporal network theory: a colloquium. EPJ B 88:234 (2015)