Validation of brain connectivity analysis using fMRI simulation. (2015)

• Record Type: Journal Article
• Authors: Hadi, Shamil M.; Siadat, Mohammad-Reza; Babajani-Feremi, Abbas
• Is Part Of: International journal of engineering systems modelling and simulation. Volume 7:Number 4(2015)
• Page Start: 279
• Page End: 293
• Publication Date: 2015
• Subjects: 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; Engineering systems -- Computer simulation -- Periodicals; Engineering systems -- Mathematical models -- Periodicals; 620.0042
• Languages: English
• ISSNs: 1755-9758

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.