  The functional network of the brain continually adapts to changing
environmental demands. The environmental changes closely connect with changes
of active cognitive processes. In recent years, the network approach has
emerged as a promising method for analyzing the neurophysiological mechanisms
that underlie psychological functions. The present study examines topological
characteristics of functional brain networks in resting state and in cognitive
load, provided by the execution of the Sternberg Item Recognition Paradigm
(SIRP) based on electroencephalographic data. We propose that the topological
properties of the functional networks in the human brain are distinct between
cognitive load and resting state with higher integration in the networks during
cognitive load. It was shown that topological features of functional
connectomes strongly depend on the type of cognitive process performed by the
subject and change in accordance with task change. The analysis also
demonstrated that functional connectivity during working memory tasks showed a
faster emergence of homology groups generators, supporting the idea of a
relationship between the initial stages of working memory execution and an
increase in faster network integration, with connector hubs playing a crucial
role.
