Unraveling brain modularity through its slow oscillations

Maurizio Mattia, Maria V. Sanchez-Vives

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The intricate web of connections among the neurons composing the cerebral cortex is the seed of the complexity that our brain is capable to express. Such complexity is organized as it results from a hierarchical and modular organization of the network in which the roles of different cortical areas are distinct. Here, we speculate that such differentiation can be obtained by relying on the granular nature of the cortical surface tiled with ‘canonic’ modules which in turn can be flexibly tuned to compose diverse mesoscopic networks. The remarkable versatility of these cortical modules is governed by few key parameters like the excitability level and the sensitivity to the accumulated activity-dependent fatigue. These modules are naturally endowed with a rich repertoire of activity regimes which range from quasi-stable dynamics, possibly exploited to store information or provide persistent input to other modules, to collective oscillations reminiscent of the Up/Down activity cycle observed during sleep and deep anesthesia. Finally, we conclude showing that such slow oscillations, spontaneously expressed by the isolated cortex, can provide an ideal experimental framework to infer the dynamical properties of these cortical modules which in turn can inform also on cortical function in other brain states, such as during wakefulness.
Original languageEnglish
Title of host publicationNonlinear Dynamics in Computational Neuroscience
EditorsFernando Corinto, Alessandro Torcino
PublisherSpringer
Pages17-31
DOIs
Publication statusPublished - Jun 20 2018

Keywords

  • complex systems
  • computational physics
  • Neuroscience

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