Thursday, 22 January 2026, 15:00-16:00

Prof. Albert‑László Barabási

Network Science Institute and Department of Physics, Northeastern University 

Division of Network Medicine, Harvard University

Department of Network and Data Science, Central European University.

                                                                                    

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From physical networks to the structure of the connectome

Physical networks describe interconnected systems whose links are physical entities that cannot cross each other, describing many real systems, from the brain to metamaterials. I will explore how link physicality affects both the evolution and the structure of a network, in a way that is not captured by current graph-based approaches. I will then apply these concepts to the structure of the connectome: from branching optimization to the expected architecture of the network. Indeed, attempts to describe the brain using models well established in network science have yielded conflicting outcomes. By analyzing eight experimentally mapped connectomes, we also find that the degree and the strength distribution cannot be described by the established random or scale-free family of models. Rather, the brain’s architecture is driven by the physical nature of its neurons, which in turn allows us to analytically derive the multiplicative process responsible for the neuron length distributions, offering empirically falsifiable predictions on the degree and the strength distributions. Finally, I show that the unique connectome architecture bridges critical gaps between neural structure and function, with potential implications for brain dynamics, robustness, and synchronization.

Research partially supported by the European Union's Horizon 2020 research and innovation program under grant agreement No 810115 - DYNASNET.