The Dynamical and Structural Basis of Human Mind Complexity: Segregation and Integration of Information and Processing in the Brain


Perceptions, memories, emotions, and everything that makes us human, demand the flexible integration of information represented and computed in a distributed manner. The human brain is structured into a large number of areas in which information and computation are highly segregated. Normal brain functions require the integration of functionally specialized but widely distributed brain areas. Furthermore, human behavior entails a flexible task-dependent interplay between different subsets of these brain areas in order to integrate them according to the corresponding goal-directed requirements. We contend that the functional and encoding roles of diverse neuronal populations across areas are subject to intra- and inter-cortical dynamics. The main aim of the current project is to elucidate precisely the interplay and mutual entrainment between local brain area dynamics and global network dynamics. We wish to better understand how segregated distributed information and processing are integrated in a flexible and context-dependent way as required for goal-directed behavior. More concretely, we hypothesize that coherent oscillations within frequency-specific large-scale networks and coherent structuring of the underlying fluctuations are crucial mechanisms for the flexible integration of distributed processing and interaction of representations. This project will allow us to comprehend the mechanisms underlying brain functions by complementing structural and activation based analyses with dynamics. We expect to gain a full explanation of the mechanisms that mediate the interactions between global and local spatio-temporal patterns of activity revealed at many levels of observations (fMRI, EEG, MEG) in humans under task and resting (i.e. no stimulation and no task) conditions. Besides, we will complement and further constrain our analyses by using more detailed characterization of brain dynamics via LFP (Local Field Potentials), and neuronal recording in animals under task and resting conditions. We also expect to demonstrate that the observation at the local level per se could reveal relevant information about the global level because of their mutual embedding of their dynamics (coming back in this way to a sort of global dynamics informed localizationism). A profound understanding of these operations will help elucidate the computational principles underlying higher brain functions and their breakdown in brain diseases. In the first sub-project, we will investigate computationally the interplay between local and global dynamics by studying a detailed global attractor large-scale spiking model of the whole brain. In the second sub-project, we will go beyond the numerical simulation of its dynamics, and develop theoretical descriptions of the large-scale model to gain a deeper insight into how network parameters control its dynamics. In the third sub-project, we will explore the effects of lesion and different types of damage in neuropsychiatric disorders.


  • Prof. Maurizio Corbetta, Washington University, St Louis, USA
  • Prof. Jochen Braun, University of Magdeburg, Germany
  • Prof. Alvaro Pacual-Leone, Harvard University, USA
  • Prof. Morten Kringelbach, Oxford University, UK
  • Prof. Ranulfo Romo, Universidad Autónoma de Mexico, Mexico
  • Prof. Nikos Logothetis, Max-Planck Institute for Cybernetics, Tübingen, Germany
  • Prof. Pascal Fries, Ernst Strüngmann Institute, Frankfurt, Germany

Funded by: European Union’s Seventh Framework Programme for research, technological development and demonstration, Programme IDEAS, European Research Council (ERC), Advanced Grant (AdG)

Project reference: 295129