Graph Theoretic Analysis of Resting State Functional MR Imaging

Medaglia, John D.

doi:10.1016/j.nic.2017.06.008

Cited by 56 publications

(54 citation statements)

References 106 publications

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“…Neither seed-based functional connectivity nor the independent component analysis approach, which are the most widely used rs-fMRI analysis techniques, can completely characterize the brain functional network (Calhoun & de Lacy, 2017;Joel, Caffo, van Zijl, & Pekar, 2011), which is in turn dynamic, as it provides support for several cognitive and emotional processes (Carhart-Harris & Friston, 2010;Deco, Jirsa, & McIntosh, 2011) that might be altered in ET. For that reason, the graph theory approach has been recently applied to data obtained from rs-fMRI, to characterize the functional connectivity within the whole-brain network (Medaglia, 2017;Wang, Zuo, & He, 2010) with a moderate to high reliability (Braun et al, 2012). This technology has enabled the characterization of the human brain as a highly efficient large-scale network consisting of nodes or vertices (i.e., brain regions) and pair-wise edges (i.e., functional connectivity) which tend to a highly clustered organization also known as "small-world" network (Medaglia, 2017;.…”

Section: Introductionmentioning

confidence: 99%

“…For that reason, the graph theory approach has been recently applied to data obtained from rs-fMRI, to characterize the functional connectivity within the whole-brain network (Medaglia, 2017;Wang, Zuo, & He, 2010) with a moderate to high reliability (Braun et al, 2012). This technology has enabled the characterization of the human brain as a highly efficient large-scale network consisting of nodes or vertices (i.e., brain regions) and pair-wise edges (i.e., functional connectivity) which tend to a highly clustered organization also known as "small-world" network (Medaglia, 2017;. Lower small-worldness values are related with worse performance in neuropsychological tasks (Douw et al, 2011;Langer, von Bastian, Wirz, Oberauer, & Jancke, 2013) and are commonly found in a wide variety of diseases, such as schizophrenia or epilepsy, when comparing with healthy control groups (Lynall et al, 2010;Vlooswijk et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Graph theory analysis of resting‐state functional magnetic resonance imaging in essential tremor

Benito‐León

Sanz‐Morales

Melero

et al. 2019

Human Brain Mapping

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Essential tremor (ET) is a neurological disease with both motor and nonmotor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting‐state functional magnetic resonance imaging (MRI) data, in 23 ET patients versus 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small‐worldness values than healthy controls—less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo‐occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus (posterior part). In addition, ET patients showed significant higher local efficiency and clustering coefficient values in frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate cortex, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. Finally, the right intracalcarine cortex and the left orbitofrontal cortex showed a shorter average path length in ET patients, while the left frontal operculum and the right planum polare showed a higher betweenness centrality in ET patients. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Graph theory analysis of resting‐state functional magnetic resonance imaging in essential tremor

Benito‐León

Sanz‐Morales

Melero

et al. 2019

Human Brain Mapping

View full text Add to dashboard Cite

show abstract

“…Graph theory is a mathematical tool that allows for the analysis and quantification of brain networks [11]. Graph theoretical analysis can delineate the whole brain as a large-scale network consisting of nodes and edges [11].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Graph theoretical analysis can delineate the whole brain as a large-scale network consisting of nodes and edges [11]. Moreover, the graph theoretical approaches can also identify highly connected regions in a network, so-called hub nodes, which play central roles in integrating diverse information sources and supporting fast communication with minimal energy cost [11]. These network properties can be used to demonstrate fundamental aspects of normal brain organization and highlight important aspects of underlying brain pathology in various neurologic diseases such as Alzheimer disease [12], Parkinson disease [13], and epilepsy [14].…”

Section: Introductionmentioning

confidence: 99%

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Is Transient Global Amnesia a Network Disease?

2018

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Background: We evaluated a brain network using graph theoretical analysis and microstructural abnormalities of the white matter in patients with transient global amnesia (TGA). Methods: Twenty patients with TGA and healthy control subjects were recruited, and they underwent diffusion tensor imaging (DTI) scans. Graph theory was applied to obtain network measures based on DTI data. We investigated the network measures and microstructural abnormalities of white matter using tract-based spatial statistics (TBSS) analysis in the patients with TGA. Results: Measures of global topology were not different between the patients with TGA and healthy subjects. However, there were significant differences of hubs organization; the strength of the right superior and inferior orbitofrontal, the right inferior frontal operculum, the left superior parietal, and left postcentral gyrus, the cluster coefficient of the right middle orbitofrontal and left inferior parietal gyrus, the betweenness centrality of the left angular gyrus, and the pagerank centrality of the right superior and inferior orbitofrontal, right inferior frontal operculum, left superior parietal, and left postcentral gyrus in the patients with TGA were significantly lower than those in healthy subjects. Regarding the analysis of the white matter microstructure with TBSS, there were no differences in the fractional anisotropy and mean diffusivity values between the 2 groups. Conclusions: We newly identify a reorganization of network hubs of the brain network in patients with TGA, especially in the regions of the default-mode network. These alterations of the brain network may play a role in the pathophysiologic mechanism underlying TGA and suggest that TGA is a network disease.

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Hippocampal connectivity and memory decline in cognitively intact APOE ε4 carriers

Baxter

Limback-Stokin

Patten

et al. 2023

Alzheimer's & Dementia

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INTRODUCTIONResting‐state functional magnetic resonance imaging (fMRI) graph theory may help detect subtle functional connectivity changes affecting memory prior to impairment.METHODSCognitively normal apolipoprotein E (APOE) ε4 carriers/noncarriers underwent longitudinal cognitive assessment and one‐time MRI. The relationship of left/right hippocampal connectivity and memory trajectory were compared between carriers/noncarriers.RESULTSSteepness of verbal memory decline correlated with decreased connectivity in the left hippocampus, only among APOE ε4 carriers. Right hippocampal metrics were not correlated with memory and there were no significant correlations in the noncarriers. Verbal memory decline correlated with left hippocampal volume loss for both carriers and noncarriers, with no other significant volumetric findings.DISCUSSIONFindings support early hippocampal dysfunction in intact carriers, the AD disconnection hypothesis, and left hippocampal dysfunction earlier than the right. Combining lateralized graph theoretical metrics with a sensitive measure of memory trajectory allowed for detection of early‐stage changes in APOE ε4 carriers before symptoms of mild cognitive impairment are present.Highlights Graph theory connectivity detects preclinical hippocampal changes in APOE ε4 carriers. The AD disconnection hypothesis was supported in unimpaired APOE ε4 carriers. Hippocampal dysfunction starts asymmetrically on the left.

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Graph Theoretic Analysis of Resting State Functional MR Imaging

Cited by 56 publications

References 106 publications

Graph theory analysis of resting‐state functional magnetic resonance imaging in essential tremor

Graph theory analysis of resting‐state functional magnetic resonance imaging in essential tremor

Is Transient Global Amnesia a Network Disease?

Hippocampal connectivity and memory decline in cognitively intact APOE ε4 carriers

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