The article recently published by Prof. Peppino Fazio, a member of the SUPERVenice team, and co-authors, presents a detailed analysis of functional connectivity in the human brain modeled upon the paradigm of telecommunication. Each brain region is seen as a transmitter and receiver, and the signal travels through functional pathways between brain regions. In particular, the authors consider a discrete finite-state model to map the behavior of neurons within a neuronal agglomerate, and investigate of the effect of disruption provoked by the presence of a disease. The authors complete the analysis with real data from healthy brains and brains of patients affected by Alzheimer’s disease.
Recent advances in nanoelectronics have spurred increased interest in the human brain and its complex functions. Numerous studies have explored brain behavior in varying levels of detail, from individual neurons to entire lobes. Intricately structured, the brain is a complex organ susceptible to diseases that may disrupt the connectivity between its internal regions. Investigating this phenomenon, the present study applies a discrete finite-state model to map the behavior of neurons within a neuronal agglomerate and examine of the effect of disease on these behaviors. Each agglomerate is then compared to a wireless clustered network and modeled as a finite-state system, with inter-cluster communications analyzed under conditions of temporal variations and degradation. This work represents one of the most advanced applications of discrete finite-state processes and routing theory in brain modeling.
The work of Prof. Fazio and co-authors addresses, in a cutting-edge and interdisciplinary way, a challenging problem, that is, the analysis of brain-network alterations occurring in presence of a neurodegenerative disease with high social impact such as Alzheimer’s disease. The methods are fully inspired by physics of complex networks and are mostly derived from computer engineering and telecommunication engineering, and they are applied to a problem of neurology. The attention is mainly focused on whole-brain analysis and signal exchange between brain regions. The method can be applied independently from the choice of the specific brain atlas.
The full article can be found at this link: https://www.nature.com/articles/s41598-026-50758-x