Title: Validation of brain connectivity analysis using fMRI simulation

Authors: Shamil M. Hadi; Mohammad-Reza Siadat; Abbas Babajani-Feremi

Addresses: Department of Computer Science and Engineering, Oakland University, 301 Engineering Center, 2200 N. Squirrel Road, Rochester, MI 48309-4401, USA ' Department of Computer Science and Engineering, Oakland University, 301 Engineering Center, 2200 N. Squirrel Road, Rochester, MI 48309-4401, USA ' Division of Clinical Neurosciences, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, USA; Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA

Abstract: Functional magnetic resonance imaging (fMRI) has been widely used in cognitive neuroscience. Brain connectivity analysis such as dynamic causal modelling (DCM) using fMRI has drawn increasing attention of neuroimaging researchers. However, performance of DCM under low SNR has not been explored and validated thoroughly. A reasonable question is what levels of noise can be handled by the DCM. Therefore, simulation is an appropriate methodology to address this question. We propose the Euler method to simulate fMRI signal. The results were compared to those of the SPM-generate. Some parameters estimated by DCM were significantly different. Unlike SPM-generate, DCM always converged when using signals generated by Euler method. Although DCM performed similarly in linear scenario for both methods, DCM handled higher noise levels for Euler compared to SPM-generate. The higher performance of DCM when using Euler method might be due to direct discretisation of the dynamic system of the neuronal state variables.

Keywords: simulation; Euler method; ordinary differential equations; ODEs; balloon model; SPM; dynamic causal modelling; DCM; hemodynamic modelling; neuronal models; model validation; brain connectivity; fMRI; functional MRI; magnetic resonance imaging; neuroimaging; signal-to-noise ratio; SNR.

DOI: 10.1504/IJESMS.2015.072514

International Journal of Engineering Systems Modelling and Simulation, 2015 Vol.7 No.4, pp.279 - 293

Received: 16 Sep 2013
Accepted: 20 Sep 2014
Published online: 16 Oct 2015 *

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