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How local excitation-inhibition ratio impacts the whole brain dynamics.

  • Deco G Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, and Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Barcelona, 08010, Spain.
  • Ponce-Alvarez A Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, and adrian.ponce@upf.edu.
  • Hagmann P Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), 1011 Lausanne, Switzerland, Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
  • Romani GL Institute of Advanced Biomedical Technologies, G. d'Annunzio University Foundation, Department of Neuroscience and Imaging, G. d'Annunzio University, Chieti, 66013, Italy.
  • Mantini D Department of Health Sciences and Technology, ETH Zurich, 8057, Zurich, Switzerland, Department of Experimental Psychology, University of Oxford, OX1 3UD, Oxford, United Kingdom, and.
  • Corbetta M Department of Neurology, Radiology, Anatomy of Neurobiology, School of Medicine, Washington University in St Louis, St Louis, Missouri 63110.
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  • 2014-06-06
Published in:
  • The Journal of neuroscience : the official journal of the Society for Neuroscience. - 2014
anatomical connectivity
functional connectivity
large-scale brain model
local feedback inhibition
resting-state activity
Action Potentials
Brain
Computer Simulation
Entropy
Feedback, Physiological
Humans
Models, Neurological
Nerve Net
Neural Inhibition
Neural Pathways
Neurons
Nonlinear Dynamics
English The spontaneous activity of the brain shows different features at different scales. On one hand, neuroimaging studies show that long-range correlations are highly structured in spatiotemporal patterns, known as resting-state networks, on the other hand, neurophysiological reports show that short-range correlations between neighboring neurons are low, despite a large amount of shared presynaptic inputs. Different dynamical mechanisms of local decorrelation have been proposed, among which is feedback inhibition. Here, we investigated the effect of locally regulating the feedback inhibition on the global dynamics of a large-scale brain model, in which the long-range connections are given by diffusion imaging data of human subjects. We used simulations and analytical methods to show that locally constraining the feedback inhibition to compensate for the excess of long-range excitatory connectivity, to preserve the asynchronous state, crucially changes the characteristics of the emergent resting and evoked activity. First, it significantly improves the model's prediction of the empirical human functional connectivity. Second, relaxing this constraint leads to an unrealistic network evoked activity, with systematic coactivation of cortical areas which are components of the default-mode network, whereas regulation of feedback inhibition prevents this. Finally, information theoretic analysis shows that regulation of the local feedback inhibition increases both the entropy and the Fisher information of the network evoked responses. Hence, it enhances the information capacity and the discrimination accuracy of the global network. In conclusion, the local excitation-inhibition ratio impacts the structure of the spontaneous activity and the information transmission at the large-scale brain level.
Language
  • English
Open access status
bronze
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Persistent URL
https://sonar.ch/global/documents/253636
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