Rare long-range cortical connections enhance human information processing

• DOI: 10.1016/j.cub.2021.07.064
• Publication Date: 2021-08-25T14:31:27Z
• Authors: Gustavo Deco; Yonathan Sanz Perl; Peter Vuust; Enzo Tagliazucchi; Henry Kennedy; Morten L. Kringel...
• Keywords: Connectome/methods; Image Processing, Computer-Assisted/methods; MULTISTABILITY; whole-brain modeling; Neuroimaging; MECHANISMS; Magnetic Resonance Imaging/methods; LONG-RANGE EXCEPTIONS; diffusion MRI; 03 medical and health sciences; Mental Processes; 0302 clinical medicine; https://purl.org/becyt/ford/1.3; Connectome; Image Processing, Computer-Assisted; Animals; Humans; Neuroimaging/methods; GINZBURG-LANDAU EQUATION; https://purl.org/becyt/ford/1; SPECIFICITY; long-range exceptions; Mammals; WHOLE-BRAIN MODELING; NETWORK DYNAMICS; turbulence; Brain; FUNCTIONAL CONNECTIVITY; FUNCTIONAL MRI; Magnetic Resonance Imaging; EVOLUTION; 004; BRAIN NETWORKS; DISTANCE; DEFAULT-MODE; TURBULENCE; functional MRI; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; DIFFUSION MRI

What are the key topological features of connectivity critically relevant for generating the dynamics underlying efficient cortical function? A candidate feature that has recently emerged is that the connectivity of the mammalian cortex follows an exponential distance rule, which includes a small proportion of long-range high-weight anatomical exceptions to this rule. Whole-brain modeling of large-scale human neuroimaging data in 1,003 participants offers the unique opportunity to create two models, with and without long-range exceptions, and explicitly study their functional consequences. We found that rare long-range exceptions are crucial for significantly improving information processing. Furthermore, modeling in a simplified ring architecture shows that this improvement is greatly enhanced by the turbulent regime found in empirical neuroimaging data. Overall, the results provide strong empirical evidence for the immense functional benefits of long-range exceptions combined with turbulence for information processing.