Bridging the Gap: Dynamic Causal Modeling and Granger Causality Analysis of Resting State Functional Magnetic Resonance Imaging

2016 ◽  
Vol 6 (8) ◽  
pp. 652-661 ◽  
Author(s):  
Sahil Bajaj ◽  
Bhim M. Adhikari ◽  
Karl J. Friston ◽  
Mukesh Dhamala
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Causal Modeling ◽  
Causality Analysis ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Dynamic Causal Modeling ◽  
Granger Causality Analysis

scholarly journals Dynamic Causal Modeling Self-Connectivity Findings in the Functional Magnetic Resonance Imaging Neuropsychiatric Literature

2021 ◽  
Vol 15 ◽  
Author(s):  
Andrew D. Snyder ◽  
Liangsuo Ma ◽  
Joel L. Steinberg ◽  
Kyle Woisard ◽  
Frederick G. Moeller
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Functional Neuroimaging ◽  
Effective Connectivity ◽  
Brain Regions ◽  
Causal Modeling ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Dynamic Causal Modeling

Dynamic causal modeling (DCM) is a method for analyzing functional magnetic resonance imaging (fMRI) and other functional neuroimaging data that provides information about directionality of connectivity between brain regions. A review of the neuropsychiatric fMRI DCM literature suggests that there may be a historical trend to under-report self-connectivity (within brain regions) compared to between brain region connectivity findings. These findings are an integral part of the neurologic model represented by DCM and serve an important neurobiological function in regulating excitatory and inhibitory activity between regions. We reviewed the literature on the topic as well as the past 13 years of available neuropsychiatric DCM literature to find an increasing (but still, perhaps, and inadequate) trend in reporting these results. The focus of this review is fMRI as the majority of published DCM studies utilized fMRI and the interpretation of the self-connectivity findings may vary across imaging methodologies. About 25% of articles published between 2007 and 2019 made any mention of self-connectivity findings. We recommend increased attention toward the inclusion and interpretation of self-connectivity findings in DCM analyses in the neuropsychiatric literature, particularly in forthcoming effective connectivity studies of substance use disorders.

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