title: Quantitative evaluation of simulated functional brain networks in graph theoretical analysis.
abstract: There is increasing interest in the potential of whole-brain computational models to provide mechanistic insights into resting-state brain networks. It is therefore important to determine the degree to which computational models reproduce the topological features of empirical functional brain networks. We used empirical connectivity data derived from diffusion spectrum and resting-state functional magnetic resonance imaging data from healthy individuals. Empirical and simulated functional networks, constrained by structural connectivity, were defined based on 66 brain anatomical regions (nodes). Simulated functional data were generated using the Kuramoto model in which each anatomical region acts as a phase oscillator. Network topology was studied using graph theory in the empirical and simulated data. The difference (relative error) between graph theory measures derived from empirical and simulated data was then estimated. We found that simulated data can be used with confidence to model graph measures of global network organization at different dynamic states and highlight the sensitive dependence of the solutions obtained in simulated data on the specified connection densities. This study provides a method for the quantitative evaluation and external validation of graph theory metrics derived from simulated data that can be used to inform future study designs.
authors: Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
authors: Won Hee
authors: WH
authors: Lee
authors: Department of Psychiatry, Behavioural and Clinical Neurosciences Institute, University of Cambridge, Cambridge CB2 0SZ, United Kingdom; Cambridgeshire & Peterborough National Health Service (NHS) Foundation Trust, Cambridge CB21 5EF, United Kingdom; National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, United Kingdom; Immunopsychiatry, Alternative Discovery & Development, GlaxoSmithKline, Stevenage SG1 2NY, United Kingdom.
authors: Ed
authors: E
authors: Bullmore
authors: Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: sophia.frangou@mssm.edu.
authors: Sophia
authors: S
authors: Frangou
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008959:Models, Neurological; D009434:Neural Pathways / Q000502:physiology; D015203:Reproducibility of Results
keywords: Computational model; Criticality; Graph theory; Kuramoto model; Neural dynamics; Resting-state fMRI