Introduction Investigating how the brain adapts to increased mental workload through
large-scale functional reorganization appears as an important research question. Functional
connectivity (FC) aims at capturing how disparate regions of the brain dynamically
interact, while graph theory provides tools for the topological characterization of
the reconstructed functional networks. Although numerous studies investigated how
FC is altered in response to increased working memory (WM) demand, current results
are still contradictory as few studies confirmed the robustness of these findings
in a low-density setting.Methods In this study, we utilized the n-back WM paradigm,
in which subjects were presented stimuli (single digits) sequentially, and their task
was to decide for each given stimulus if it matched the one presented n-times earlier.
Electroencephalography recordings were performed under a control (0-back) and two
task conditions of varying difficulty (2- and 3-back). We captured the characteristic
connectivity patterns for each difficulty level by performing FC analysis and described
the reconstructed functional networks with various graph theoretical measures.Results
We found a substantial decrease in FC when transitioning from the 0- to the 2- or
3-back conditions, however, no differences relating to task difficulty were identified.
The observed changes in brain network topology could be attributed to the dissociation
of two (frontal and occipitotemporal) functional modules that were only present during
the control condition. Furthermore, behavioral and performance measures showed both
positive and negative correlations to connectivity indices, although only in the higher
frequency bands.Conclusion The marked decrease in FC may be due to temporarily abandoned
connections that are redundant or irrelevant in solving the specific task. Our results
indicate that FC analysis is a robust tool for investigating the response of the brain
to increased cognitive workload.
