Open AccessA Bayesian approach to determining connectivity of the human brain
Author(s) -
Patel Rajan S.,
Bowman F. DuBois,
Rilling James K.
Publication year - 2006
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.20182
Subject(s) - orbitofrontal cortex , psychology , anterior cingulate cortex , voxel , functional magnetic resonance imaging , neuroscience , insula , human brain , ventral striatum , brain mapping , causal model , cognitive psychology , computer science , prefrontal cortex , artificial intelligence , cognition , striatum , medicine , pathology , dopamine
Recent work regarding the analysis of brain imaging data has focused on examining functional and effective connectivity of the brain. We develop a novel descriptive and inferential method to analyze the connectivity of the human brain using functional MRI (fMRI). We assess the relationship between pairs of distinct brain regions by comparing expected joint and marginal probabilities of elevated activity of voxel pairs through a Bayesian paradigm, which allows for the incorporation of previously known anatomical and functional information. We define the relationship between two distinct brain regions by measures of functional connectivity and ascendancy. After assessing the relationship between all pairs of brain voxels, we are able to construct hierarchical functional networks from any given brain region and assess significant functional connectivity and ascendancy in these networks. We illustrate the use of our connectivity analysis using data from an fMRI study of social cooperation among women who played an iterated “Prisoner's Dilemma” game. Our analysis reveals a functional network that includes the amygdala, anterior insula cortex, and anterior cingulate cortex, and another network that includes the ventral striatum, orbitofrontal cortex, and anterior insula. Our method can be used to develop causal brain networks for use with structural equation modeling and dynamic causal models. Hum Brain Mapp, 2005. © 2005 Wiley‐Liss, Inc.