The goal of this study is to investigate the possibility of analyzing spatio-temporal organization of the human cortical activity during different complex tasks, by means of fMRI. To evidence cortical areas synchronization we propose a computational approach based on a self-organizing neural networks (''neural gas'') that detects time-dependent alterations in the regional intensity of the functional signal. Results of the application of such approach are reported and are compared with the results obtained with a standard statistical package (SPM96). Future experimental investigations will be aimed at the analysis of spatio-temporal structures of cortical activity in pathological conditions, such as epilepsy.