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Human orbital and anterior medial prefrontal cortex: Intrinsic connectivity parcellation and functional organization.

ABSTRACT: The orbital and medial prefrontal cortex (OMPFC) has been implicated in decision-making, reward and emotion processing, and psychopathology, such as depression and obsessive-compulsive disorder. Human and monkey anatomical studies indicate the presence of various cortical subdivisions and suggest that these are organized in two extended networks, a medial and an orbital one. Attempts have been made to replicate these neuroanatomical findings in vivo using MRI techniques for imaging connectivity. These revealed several consistencies, but also many inconsistencies between reported results. Here, we use fMRI resting-state functional connectivity (FC) and data-driven modularity optimization to parcellate the OMPFC to investigate replicability of in vivo parcellation more systematically. By collecting two resting-state data sets per participant, we were able to quantify the reliability of the observed modules and their boundaries. Results show that there was significantly more than chance overlap in modules and their boundaries at the level of individual data sets. Moreover, some of these consistent boundaries significantly co-localized across participants. Hierarchical clustering showed that the whole-brain FC profiles of the OMPFC subregions separate them in two networks, a medial and orbital one, which overlap with the organization proposed by Barbas and Pandya (J Comp Neurol 286:353-375, 1989) and Ongür and Price (Cereb Cortex 10:206-219, 2000). We conclude that in vivo resting-state FC can delineate reliable and neuroanatomically plausible subdivisions that agree with established cytoarchitectonic trends and connectivity patterns, while other subdivisions do not show the same consistency across data sets and studies.

SUBMITTER: Samara Z

PROVIDER: S-EPMC5581738 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Altered functional connectivity (FC) between the medial prefrontal cortex (mPFC) and amygdala is widely implicated as a neural mechanism explaining risk for psychopathology among those exposed to early life trauma. Nonetheless, contemporary neuroimaging research has shifted toward large-scale network models of brain function, and it is not clear how this common bi-nodal finding fits into larger-scale network models. Here, using dynamic functional connectivity (DFC) approaches combined with large-scale network analyses, the larger role of bi-nodal FC between mPFC and amygdala among a sample of adolescent girls is investigated. The sample was comprised of 30 healthy control girls and 26 girls exposed to either physical or sexual assault who underwent a resting-state scan during 3T MRI. DFC using a sliding window approach was used to create weighted, undirected, graphs from the resting-state data following parcellation with a 215 regions-of-interest (ROI) atlas. Using a priori ROI, the predicted finding of lessor FC between mPFC and amygdala as a function of early life trauma was replicated in this sample. By contrast, early life trauma was associated with greater large-scale network modularity. Using a dynamic FC approach, it is also demonstrated that within-subject variability in this bi-nodal FC closely tracks within-subject fluctuations in large-scale network patterns, including connectivity between a limbic and default mode network (in which the amygdala and mPFC nodes belong, respectively) as well as overall modular organization. These results suggest that bi-nodal FC, such as amygdala-mPFC FC, may generally reflect larger-scale network patterns. Future research is necessary to understand whether these associations between nodal FC and large-scale network organization better reflect top-down processes (larger-scale network organization drives bi-nodal FC) or bottom-up processes (bi-nodal FC drives larger-scale network organization) and the related impact of early life trauma.

Dataset Information

Human orbital and anterior medial prefrontal cortex: Intrinsic connectivity parcellation and functional organization.

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