The diversity and multiplexity of edge communities within and between brain systems
Youngheun Jo,
Farnaz Zamani Esfahlani,
Joshua Faskowitz,
Evgeny J. Chumin,
Olaf Sporns,
Richard F. Betzel
Affiliations
Youngheun Jo
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
Farnaz Zamani Esfahlani
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
Joshua Faskowitz
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA
Evgeny J. Chumin
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA
Olaf Sporns
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA; Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA
Richard F. Betzel
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA; Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA; Corresponding author
Summary: The human brain is composed of functionally specialized systems that support cognition. Recently, we proposed an edge-centric model for detecting overlapping communities. It remains unclear how these communities and brain systems are related. Here, we address this question using data from the Midnight Scan Club and show that all brain systems are linked via at least two edge communities. We then examine the diversity of edge communities within each system, finding that heteromodal systems are more diverse than sensory systems. Next, we cluster the entire cortex to reveal it according to the regions’ edge-community profiles. We find that regions in heteromodal systems are more likely to form their own clusters. Finally, we show that edge communities are personalized. Our work reveals the pervasive overlap of edge communities across the cortex and their relationship with brain systems. Our work provides pathways for future research using edge-centric brain networks.
