In recent years, the application of network analysis to neuroimaging data has provided useful insights about the brain's functional and structural organization in both health and disease. This has proven a significant paradigm shift from the study of individual brain regions in isolation.
In a new paper published in Frontiers in Systems Neuroscience, an international team of researchers including ISI Foundation Senior Researcher Francesco Vaccarino and ISI Foundation Principal Researcher Giovanni Petri investigates the relationship between standard network metrics computed from dyadic interactions in a functional network, and a metric defined on the persistence homological scaffold of the network (a summary network that differs in important ways from the standard network representations of functional neuroimaging data).
The results suggest that topologically central nodes in the persistence scaffold may play important roles toward supporting the functional integration of information across brain modules. Scientists suggest that future work should investigate the sensitivity of the homological scaffolds and derived measures to disease-related changes in brain function as well as the specific type of integration performed by the strongest edges and nodes in the scaffolds.
Insights into Brain Architectures from the Homological Scaffolds of Functional Connectivity Networks
L. Lord, P. Expert, H. M. Fernandes, G. Petri, T. J. Van Hartevelt, F. Vaccarino, G. Deco, F. Turkheimer, M. L. Kringelbach
Front. Syst. Neurosci. 10:85. doi: 10.3389/fnsys.2016.00085 (2016)