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Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease

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TLDR
To identify regions of high connectivity in the human cerebral cortex, a computationally efficient approach was applied to map the degree of intrinsic functional connectivity across the brain and explored whether the topography of hubs could explain the pattern of vulnerability in Alzheimer's disease (AD).
Abstract
Recent evidence suggests that some brain areas act as hubs interconnecting distinct, functionally specialized systems. These nexuses are intriguing because of their potential role in integration and also because they may augment metabolic cascades relevant to brain disease. To identify regions of high connectivity in the human cerebral cortex, we applied a computationally efficient approach to map the degree of intrinsic functional connectivity across the brain. Analysis of two separate functional magnetic resonance imaging datasets (each n = 24) demonstrated hubs throughout heteromodal areas of association cortex. Prominent hubs were located within posterior cingulate, lateral temporal, lateral parietal, and medial/lateral prefrontal cortices. Network analysis revealed that many, but not all, hubs were located within regions previously implicated as components of the default network. A third dataset (n = 12) demonstrated that the locations of hubs were present across passive and active task states, suggesting that they reflect a stable property of cortical network architecture. To obtain an accurate reference map, data were combined across 127 participants to yield a consensus estimate of cortical hubs. Using this consensus estimate, we explored whether the topography of hubs could explain the pattern of vulnerability in Alzheimer's disease (AD) because some models suggest that regions of high activity and metabolism accelerate pathology. Positron emission tomography amyloid imaging in AD (n = 10) compared with older controls (n = 29) showed high amyloid-beta deposition in the locations of cortical hubs consistent with the possibility that hubs, while acting as critical way stations for information processing, may also augment the underlying pathological cascade in AD.

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Stepwise connectivity of the modal cortex reveals the multimodal organization of the human brain.

TL;DR: The present study analyzes the functional connectome and transitions from primary sensory cortices to higher-order brain systems and identifies the large-scale multimodal integration network and essential connectivity axes for perceptual integration in the human brain.
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The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders

TL;DR: It is shown that rather than simply altering the mean or range of correlation values amongst pairs of brain regions, Global Signal Regression systematically alters the rank ordering of values in addition to introducing negative values, which leads to a reversal in the direction of group correlation differences relative to other preprocessing approaches.
Journal ArticleDOI

Identifying and Mapping Connectivity Patterns of Brain Network Hubs in Alzheimer's Disease

TL;DR: It is found that AD selectively targeted highly connected hub regions (in terms of nodal functional connectivity strength) of brain networks, involving the medial and lateral prefrontal and parietal cortices, insula, and thalamus, thus suggesting the potential of using network hub connectivity as a diagnostic biomarker.
Journal ArticleDOI

Similarity-Based Extraction of Individual Networks from Gray Matter MRI Scans

TL;DR: This work proposes a new method that describes the gray matter morphology of an individual cortex as a network, and demonstrates that intracortical similarities can be used to provide a robust statistical description of individualgray matter morphology.
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The parcellation-based connectome: Limitations and extensions

TL;DR: The impact of the choice of parcellation scheme and resolution on the estimation of the brain's topological and spatial network features is addressed and quantitative measures of these principles may be significantly modulated.
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