Detection of cortical activation and effective connectivity using Dynamic Causal Modelling through functional magnetic resonance imaging

Abstract

Functional magnetic resonance imaging is an improved method for observing correlates of neural brain activity at high spatial resolution in human subjects. This technique is used for determining the specific regions of activation in the brain’s cortical areas while the subject performs a pre designed motor task. Localized changes in cortical blood oxygenation during voluntary fist movements are modeled in a statistical framework such as general linear model (GLM) to obtain statistical parametric maps that represent various neuronal activations in the brain. fMRI was performed during visually cued motor task on a healthy subject in a 3.0 T scanner using gradient echo planar imaging with a 60 s repetition time. Evaluation of fMRI data is performed using SPM and final results are used to determine effective connectivity within a bilateral network comprising M1, premotor cortex (PMC) and supplementary motor area (SMA). Dynamic Causal Modeling (DCM) is used to analyze the effective connectivity between the above specified regions of the brain.