SINTESI CONTENENTE UNA BREVE DESCRIZIONE DEL LAVORO SVOLTO E DEI RISULTATI OTTENUTI: Gender is presumed to be one of the main factors causing interindividual variation in the electrophysiological parameters of the human brain. Male and female human brains display differences in network topology that represents the organizational patterns of brain connectivity across the entire brain, suggesting that gender differences represents a key factor that affects neural networks organization and impacts on behavioral and cognitive performance of individuals. Basing on advanced technique of graph theory analysis, with the present investigation we sought to contribute to the estimation of the gender effect on spontaneous brain electroencephalographic (EEG) activity to verify whether the topological organization of human brain functional networks is different for males and females to contribute to sex-differences in human behavior and to assess the importance of that effect for research and clinical examinations of individual subjects. Graph theory approach was chosen because is a natural framework for the mathematical representation of complex networks and provides a powerful way to quantitatively describe the topological organization of brain connectivity. The core parameter of graph theory analysis, represented by Small world coefficient, describes the balance between local connectedness and global integration of a network. EEG functional connectivity was computed in all frequency bands (delta, theta, alpha 1, alpha 2, beta 1, beta 2, gamma); in line with Jalili and colleagues (Jalili, 2015)- which didn’t find significant differences in global efficiency in theta e beta band- we found differences between genders only in delta, alpha and gamma bands underlining the similarity of no task resting EEG recordings. The main findings of the present study are the following: comparing males vs females in left and right hemisphere, we found higher values of small world (SW) parameter in alpha 2 band and viceversa lower in gamma band in males respect to females in the left hemisphere while no significant differences were found in the right one. In the Left hemisphere, Frontal network presented differences in both delta and alpha band, in particular lower values in delta and higher in alpha 2 in males respect to females; in the right hemisphere we found lower values of small world in males respect to females in gamma Attentional, delta Sensorimotor and delta and gamma Default Mode networks. Gender small worldness differences in some of resting state networks indicated that there are specific brain differences in the EEG rhythms when the brain is in the resting-state condition. These specific regions could be considered related to the functions of behavior and cognition and should be taken into account both for research on healthy and brain diseased subjects.