Privacy Policy Disclaimer
  Advanced SearchBrowse




Journal Article

Structural anomalies in brain networks induce dynamical pacemaker effects


Koulierakis,  I.
External Organizations;

Verganelakis,  D. A.
External Organizations;

Omelchenko,  I.
External Organizations;

Zakharova,  A.
External Organizations;


Schöll,  Eckehard
Potsdam Institute for Climate Impact Research;

Provata,  A.
External Organizations;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in PIKpublic
Supplementary Material (public)
There is no public supplementary material available

Koulierakis, I., Verganelakis, D. A., Omelchenko, I., Zakharova, A., Schöll, E., Provata, A. (2020): Structural anomalies in brain networks induce dynamical pacemaker effects. - Chaos, 30, 11, 113137.

Cite as: https://publications.pik-potsdam.de/pubman/item/item_25169
Dynamical effects on healthy brains and brains affected by tumor are investigated via numerical simulations. The brains are modeled as multilayer networks consisting of neuronal oscillators whose connectivities are extracted from Magnetic Resonance Imaging (MRI) data. The numerical results demonstrate that the healthy brain presents chimera-like states where regions with high white matter concentrations in the direction connecting the two hemispheres act as the coherent domain, while the rest of the brain presents incoherent oscillations. To the contrary, in brains with destructed structures, traveling waves are produced initiated at the region where the tumor is located. These areas act as the pacemaker of the waves sweeping across the brain. The numerical simulations are performed using two neuronal models: (a) the FitzHugh–Nagumo model and (b) the leaky integrate-and-fire model. Both models give consistent results regarding the chimera-like oscillations in healthy brains and the pacemaker effect in the tumorous brains. These results are considered a starting point for further investigation in the detection of tumors with small sizes before becoming discernible on MRI recordings as well as in tumor development and evolution.