Resting state functional magnetic resonance imaging: an analysis of the connectivity of brain large-scale networks

Abstract

Objective: To assess the possibilities of various methods for analyzing the functional integration of large-scale brain neural networks in healthy subjects according to functional MRI resting state.Material and methods. Functional MRI at rest was performed on 28 healthy male subjects aged 27.4 ± 5.1 years, without bad habits and craniocerebral injuries. A functional evaluation of large-scale neural networks included in the triple network model was carried out: default mode network, salience network, executive control network.Results. The analysis of independent components made it possible to fully identify the default mode network and the salience network, however, the executive control network were partially identified, and this mainly concerned structures with a bilateral location. Graph analysis has identified structures of greatest value for neurofunctional research. Almost all structures that have the highest graph indicators are related to the executive control network. The results of the Roi-analysis showed the interaction between all large-scale networks, which indicates their joint work in providing important brain functions. It was also determined that in healthy people, all structures within large-scale networks are functionally interconnected.Conclusion. Different methods of resting functional MRI data analysis reveal different aspects of connectivity in the brain, completely different principles are involved in the processing of each method, and the final quantification parameters also vary depending on the preferred method. Currently, there is no single method that in itself would be considered the standard of analysis. Applying multiple methods to the same dataset can produce more informative results.