The human brain is probably the most complex container of interconnected networks in nature.The “network neuroscience” represents a very recent approach for its study. The network neuroscienceis based on mathematical algorithms that define the global and local organization of the brain respect to timing (seconds, minutes, hours, days …) and functions (cognitive, motor etc.). Recent studies have applied the graphtheory to electroencephalographic data (EEG) for the analysis of the brain network organization during aging and, in particular, along that continuous line linking normal aging (Normal Old = Nold), mild cognitive decline (Mild cognitive Impairment = MCI) and dementia.
Modern mathematical methods based on graph theory and network sciences can significantly contribute to understanding the functionality and dysfunctionality of the age-related brain. In particular, these techniques can be useful to map the brain and explore cognitive processes, as well as to better evaluate the link between the structural brain changes related to age and their functional implications. In a very close future this approach will allow us to develop new individualized therapeutic / rehabilitative strategies.

arises from a group of researches engaged in the application of graph theory to the functional connectivity analysis of the brain starting from the electroencephalographic signal (EEG, see list of publications). From the same group are born innovative ideas of fusion between the methods of NIBS (Transcranial Magnetic Stimulation = TMS, transcranial direct current Stimulation = tDCS and its variations) and the network analysis of the EEG signal through the graph theory. In other words, once you have defined the most representative network of task-related performances (“state” performance such as coma / consciousness or wake / fall or “function” performance like learning, excellent performance vs incorrect performance within a task) it is possible to energize the same network by stimulating the nodes of the network to the same EEG frequencies that constitute them. In short, it is possible to recreate and maintain the chosen network over time through NIBS customized over time, space and frequency. The fields of application of this approach are enormous and extend from neuroenhancement perspectives in the healthy subject (facilitating falling asleep, increasing concentration and storage capacity, minimizing error within a complex task etc.) to those for the treatment and rehabilitation of patients with brain injuries (stroke, Alzheimer’s, Brain Computer Interface for domotic applications in patients with serious disabilities of autonomous movement, etc.).