4.7 Article

Bottom up modeling of the connectome: Linking structure and function in the resting brain and their changes in aging

Journal

NEUROIMAGE
Volume 80, Issue -, Pages 318-329

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.04.055

Keywords

Structure-function; Resting-state models; Criticality; MSE; Multiscale entropy; Aging; Complexity

Funding

  1. ERC [295129]
  2. Spanish Research Project [SAF2010-16085]
  3. CONSOLIDER-INGENIO Programme [CSD2007-00012]
  4. FP7-ICT BrainScales
  5. Brain Network Recovery Group through the James S. McDonnell Foundation
  6. SUR of the DEC of the Catalan Government
  7. FSE
  8. ICREA Funding Source: Custom
  9. European Research Council (ERC) [295129] Funding Source: European Research Council (ERC)

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With the increasing availability of advanced imaging technologies, we are entering a new era of neuroscience. Detailed descriptions of the complex brain network enable us to map out a structural connectome, characterize it with graph theoretical methods, and compare it to the functional networks with increasing detail. To link these two aspects and understand how dynamics and structure interact to form functional brain networks in task and in the resting state, we use theoretical models. The advantage of using theoretical models is that by recreating functional connectivity and time series explicitly from structure and pre-defined dynamics, we can extract critical mechanisms by linking structure and function in ways not directly accessible in the real brain. Recently, resting-state models with varying local dynamics have reproduced empirical functional connectivity patterns, and given support to the view that the brain works at a critical point at the edge of a bifurcation of the system. Here, we present an overview of a modeling approach of the resting brain network and give an application of a neural mass model in the study of complexity changes in aging. (C) 2013 Elsevier Inc. All rights reserved.

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