Dataset Information

Graph theory analysis of cortical-subcortical networks in late-life depression.

ABSTRACT: Late-life major depression (LLD) is characterized by distinct epidemiologic and psychosocial factors, as well as medical comorbidities that are associated with specific neuroanatomical differences. The purpose of this study was to use interregional correlations of cortical and subcortical volumes to examine cortical-subcortical structural network properties in subjects with LLD compared with healthy comparison subjects.This was a cross-sectional neuroimaging study conducted in the general community. We recruited 73 healthy elderly comparison subjects and 53 subjects with LLD who volunteered in response to advertisements. Brain network connectivity measures were generated by correlating regional volumes after controlling for age, gender, and intracranial volume by using the Brain Connectivity Toolbox.Results for overall network strength revealed that LLD networks showed a greater magnitude of associations for both positive and negative correlation weights compared with healthy elderly networks. LLD networks also demonstrated alterations in brain network structure compared with healthy comparison subjects. LLD networks were also more vulnerable to targeted attacks compared with healthy elderly comparison subjects, and this vulnerability was attenuated when controlling for white matter alterations.Overall, this study demonstrates that cortical-subcortical network properties are altered in LLD and may reflect the underlying neuroanatomical vulnerabilities of the disorder.

SUBMITTER: Ajilore O

PROVIDER: S-EPMC3858393 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Graph theory analysis of cortical-subcortical networks in late-life depression.

Ajilore Olusola O Lamar Melissa M Leow Alex A Zhang Aifeng A Yang Shaolin S Kumar Anand A

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry 20130703 2

<h4>Objectives</h4>Late-life major depression (LLD) is characterized by distinct epidemiologic and psychosocial factors, as well as medical comorbidities that are associated with specific neuroanatomical differences. The purpose of this study was to use interregional correlations of cortical and subcortical volumes to examine cortical-subcortical structural network properties in subjects with LLD compared with healthy comparison subjects.<h4>Methods</h4>This was a cross-sectional neuroimaging st ...[more]

PMID: 23831171

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Project description:Pain perception involves multiple brain regions and networks. Understanding how these brain networks work together is fundamental for appreciating network-wise changes reported in patients with chronic pain disorders. Parcellating pain related networks and understanding their causal relationships is the first step to understand how painful information is processed, integrated, and modulated, and it requires direct manipulation of specific brain regions. Nonhuman primates (NHP) offer an ideal model system to achieve these goals because cortical and subcortical regions in the NHP brain are established based on a variety of different types of data collected in a way that is not feasible or, at least, extremely difficult in humans (i.e., histology data, tract-tracing, intracerebral recordings). In addition, different methodological techniques can also help characterize and further understand these brain cortical and subcortical regions over the course of development. Here we used a heat nociceptive stimulation that is proven to elicit activity of nociceptive neurons in the cortex to refine and parcellate the whole brain nociceptive functional networks, to identify key network hubs, and to characterize network-wise temporal dynamic signatures using high-resolution fMRI. We first functionally localized 24 cortical and subcortical regions that responded to heat nociceptive stimuli (somatosensory area 1/2, area 3a/3b, S2, posterior insula (pIns), anterior insula, area 7b, posterior parietal cortex, anterior cingulate cortex (ACC), prefrontal cortex, caudate, and mediodorsal (MD) and ventral posterior lateral (VPL) thalamic nuclei) and used them as seeds in resting state fMRI (rsfMRI) data analysis. We applied both hierarchical clustering and graph-theory analyses of the pairwise rsfMRI correlation metrics and identified five cortical and one subcortical sub-networks: strong resting state functional connectivity (rsFC) between ACC and prefrontal regions, parietal cortex and area 7b, S2 and posterior insula, areas 3a/3b and 1/2 within the S1 cortex, and thalamic MD and caudate nuclei. The rsFC strengths between cortical areas within each subnetwork were significantly stronger than those between subcortical regions. Regions within each sub-network also exhibited highly correlated temporal dynamics at rest, but the overall dynamic patterns varied drastically across sub-networks. Graph-theory analysis identified the MD nucleus as a hub that connects subcortical and cortical nociceptive sub-networks. The S2-pIns connection joins the sensory and affective/cognitive sub-networks.

Dataset Information

Graph theory analysis of cortical-subcortical networks in late-life depression.

Publications

Graph theory analysis of cortical-subcortical networks in late-life depression.

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