Features of the functional connectomes design according to fMRI data

The brain functioning is based on the parallel synchronous work of the neural networks, the architecture of which determines the properties of the cognitive processes. To construct functional connectomes of the human brain, data from non-invasive methods are usually used: electroencephalography (EEG), magnetic encephalography (MEG), and functional magnetic resonance imaging (fMRI), obtained in stimulus cognitive tasks or at resting state. For each combination of the above experimental methods and the studied cognitive process, there are features in the methods of constructing functional connectomes. Of particular interest is the study of neural network interaction at resting state, as a basic level of consciousness, based on the use of data from the fMRI method. With a bad spatial resolution (about 2 mm) and temporal signal resolution (0.5 Hz), fMRI is the only modern method for the simultaneous registration of physiological signals from the cortex and deep structures of the brain. In this work, using the fMRI data of the brain resting state as an example, we describe the characteristic features of the construction of functional connectomes.