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Marc Wiedermann, Jonathan F Donges, Jürgen Kurths, Reik V Donner
Complex networks are usually characterized in terms of their topological, spatial, or information-theoretic properties and combinations of the associated metrics are used to discriminate networks into different classes or categories. However, even with the present variety of characteristics at hand it still remains a subject of current research to appropriately quantify a network's complexity and correspondingly discriminate between different types of complex networks, like infrastructure or social networks, on such a basis...
October 2017: Physical Review. E
Christos Davatzikos, Saima Rathore, Spyridon Bakas, Sarthak Pati, Mark Bergman, Ratheesh Kalarot, Patmaa Sridharan, Aimilia Gastounioti, Nariman Jahani, Eric Cohen, Hamed Akbari, Birkan Tunc, Jimit Doshi, Drew Parker, Michael Hsieh, Aristeidis Sotiras, Hongming Li, Yangming Ou, Robert K Doot, Michel Bilello, Yong Fan, Russell T Shinohara, Paul Yushkevich, Ragini Verma, Despina Kontos
The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer...
January 2018: Journal of Medical Imaging
Roger E Beaty, Yoed N Kenett, Alexander P Christensen, Monica D Rosenberg, Mathias Benedek, Qunlin Chen, Andreas Fink, Jiang Qiu, Thomas R Kwapil, Michael J Kane, Paul J Silvia
People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0...
January 16, 2018: Proceedings of the National Academy of Sciences of the United States of America
J D Kruschwitz, L Waller, L S Daedelow, H Walter, I M Veer
One hallmark example of a link between global topological network properties of complex functional brain connectivity and cognitive performance is the finding that general intelligence may depend on the efficiency of the brain's intrinsic functional network architecture. However, although this association has been featured prominently over the course of the last decade, the empirical basis for this broad association of general intelligence and global functional network efficiency is quite limited. In the current study, we set out to replicate the previously reported association between general intelligence and global functional network efficiency using the large sample size and high quality data of the Human Connectome Project, and extended the original study by testing for separate association of crystallized and fluid intelligence with global efficiency, characteristic path length, and global clustering coefficient...
January 12, 2018: NeuroImage
Danaële Puechmaille, Martin Styner, Juan C Prieto
Cloud based Interactive Visualization of Tractography Brain Connectome (CIVILITY) is an interactive visualization tool of brain connectome in the cloud. This application submits tasks to remote computing grids were the CIVILITY-tractography pipeline is deployed. The application will list the running tasks for the user and once a task is completed the brain connectome is visualized using Hierarchical Edge Bundling. The analysis pipeline uses FSL tools (bedpostx and probtrackx2) to generate a triangular matrix indicating the connectivity strength between different regions in the brain...
March 2017: Proceedings of SPIE
Jose L Cantero, Mercedes Atienza, Pascual Sanchez-Juan, Eloy Rodriguez-Rodriguez, Jose Luis Vazquez-Higuera, Ana Pozueta, Andrea Gonzalez-Suarez, Eduard Vilaplana, Jordi Pegueroles, Victor Montal, Rafael Blesa, Daniel Alcolea, Alberto Lleo, Juan Fortea
The diagnostic value of cerebrospinal fluid (CSF) biomarkers is well established in Alzheimer's disease, but our current knowledge about how abnormal CSF levels affect cerebral integrity, at local and network levels, is incomplete in asymptomatic older adults. Here, we have collected CSF samples and performed structural magnetic resonance imaging scans in cognitively normal elderly as part of a cross-sectional multicenter study (SIGNAL project). To identify group differences in cortical thickness, white matter volume, and properties of structural networks, participants were split into controls (N = 20), positive amyloid-β (Aβ1-42+) (N = 19), and positive phosphorylated tau (N = 18)...
December 20, 2017: Neurobiology of Aging
Kabilar Gunalan, Bryan Howell, Cameron C McIntyre
Medical imaging has played a major role in defining the general anatomical targets for deep brain stimulation (DBS) therapies. However, specifics on the underlying brain circuitry that is directly modulated by DBS electric fields remain relatively undefined. Detailed biophysical modeling of DBS provides an approach to quantify the theoretical responses to stimulation at the cellular level, and has established a key role for axonal activation in the therapeutic mechanisms of DBS. Estimates of DBS-induced axonal activation can then be coupled with advances in defining the structural connectome of the human brain to provide insight into the modulated brain circuitry and possible correlations with clinical outcomes...
January 10, 2018: NeuroImage
Chao Zhang, Chase C Dougherty, Stefi A Baum, Tonya White, Andrew M Michael
Prevalence of certain forms of psychopathology, such as autism and depression, differs between genders and understanding gender differences of the neurotypical brain may provide insights into risk and protective factors. In recent research, resting state functional magnetic resonance imaging (rfMRI) is widely used to map the inherent functional networks of the brain. Although previous studies have reported gender differences in rfMRI, the robustness of gender differences is not well characterized. In this study, we use a large data set to test whether rfMRI functional connectivity (FC) can be used to predict gender and identify FC features that are most predictive of gender...
January 10, 2018: Human Brain Mapping
T M Lancaster, I Ihssen, L M Brindley, D E Linden
The reward-processing network is implicated in the aetiology of obesity. Several lines of evidence suggest obesity-linked genetic risk loci (such as DRD2 and FTO) may influence individual variation in body mass index (BMI) through neuropsychological processes reflected in alterations in activation of the striatum during reward processing. However, no study has tested the broader hypotheses that (a) the relationship between BMI and reward-related brain activation (measured through the blood oxygenation-dependent (BOLD) signal) may be observed in a large population study and (b) the overall genetic architecture of these phenotypes overlap, an assumption critical for the progression of imaging genetic studies in obesity research...
January 10, 2018: Translational Psychiatry
Youngwook Lyoo, Jieun E Kim, Sujung Yoon
The human connectome is a complex network that transmits information between interlinked brain regions. Using graph theory, previously well-known network measures of integration between brain regions have been constructed under the key assumption that information flows strictly along the shortest paths possible between two nodes. However, it is now apparent that information does flow through non-shortest paths in many real-world networks such as cellular networks, social networks, and the internet. In the current hypothesis, we present a novel framework using the maximum flow to quantify information flow along all possible paths within the brain, so as to implement an analogy to network traffic...
January 2018: Medical Hypotheses
Merle C Hoenig, Gérard N Bischof, Joseph Seemiller, Jochen Hammes, Juraj Kukolja, Özgür A Onur, Frank Jessen, Klaus Fliessbach, Bernd Neumaier, Gereon R Fink, Thilo van Eimeren, Alexander Drzezga
A stereotypical anatomical propagation of tau pathology has been described in Alzheimer's disease. According to recent concepts (network degeneration hypothesis), this propagation is thought to be indicative of misfolded tau proteins possibly spreading along functional networks. If true, tau pathology accumulation should correlate in functionally connected brain regions. Therefore, we examined whether independent components could be identified in the distribution pattern of in vivo tau pathology and whether these components correspond with specific functional connectivity networks...
January 5, 2018: Brain: a Journal of Neurology
Xindi Wang, Qixiang Lin, Mingrui Xia, Yong He
Very little is known regarding whether structural hubs of human brain networks that enable efficient information communication may be classified into different categories. Using three multimodal neuroimaging data sets, we construct individual structural brain networks and further identify hub regions based on eight widely used graph-nodal metrics, followed by comprehensive characteristics and reproducibility analyses. We show the three categories of structural hubs in the brain network, namely, aggregated, distributed, and connector hubs...
January 4, 2018: Human Brain Mapping
Erik H Middlebrooks, Vanessa M Holanda, Ibrahim S Tuna, Hrishikesh D Deshpande, Markus Bredel, Leonardo Almeida, Harrison C Walker, Barton L Guthrie, Kelly D Foote, Michael S Okun
PURPOSE: Deep brain stimulation is a common treatment for medication-refractory essential tremor. Current coordinate-based targeting methods result in variable outcomes due to variation in thalamic structure and the optimal patient-specific functional location. The purpose of this study was to compare the coordinate-based pre-operative targets to patient-specific thalamic segmentation utilizing a probabilistic tractography methodology. METHODS: Using available diffusion MRI of 32 subjects from the Human Connectome Project database, probabilistic tractography was performed...
January 6, 2018: Neuroradiology
Daniel V Olson, Volkan Arpinar, L Tugan Muftuler
PURPOSE: Diffusion kurtosis imaging (DKI) has gained popularity in recent years as an advanced diffusion-weighted MRI technique. This work aims to quantitatively compare the performance and accuracy of four DKI processing algorithms. For this purpose, a digital DKI brain phantom is developed. METHODS: Data from the Human Connectome Project database were used to generate a DKI digital phantom. In a Monte Carlo Rician noise simulation, four DKI processing algorithms were compared based on their mean square error, squared bias, and variance...
January 2, 2018: Magnetic Resonance Imaging
Mathijs Raemaekers, Wouter Schellekens, Natalia Petridou, Nick F Ramsey
The functional organization of left and right hemispheres is different, and hemispheric asymmetries are thought to underlie variations in brain function across individuals. In this study, we assess how differences between hemispheres are reflected in Asymmetric Functional Connectivity (AFC), which provides a full description of how the brain's connectivity structure during resting state differs from that of the same brain mirrored over the longitudinal fissure. In addition, we assess how AFC varies across subjects...
January 4, 2018: Brain Structure & Function
William S Sohn, Tae Young Lee, Seoyeon Kwak, Youngwoo Bryan Yoon, Jun Soo Kwon
Introduction: Dedication and training to a profession results in a certain level of expertise. This expertise, like any other skill obtained in our lifetime, is encoded in the brain and may be reflected in our brain's connectome. This property can be observed by mapping resting state connectivity. In this study, we examine the differences in resting state functional connectivity in four major networks between professional "Baduk" (Go) players and normal subjects. Methods: Resting state fMRI scans were acquired for professional "Baduk" (Go) players and normal controls...
December 2017: Brain and Behavior
Nabi Zorlu, Necip Çapraz, Esra Oztekin, Başak Bagci, Maria A Di Biase, Andrew Zalesky, Fazıl Gelal, Emre Bora, Ercan Durmaz, Lütfullah Beşiroğlu, Aybala Sarıçiçek
We aimed to examine the whole-brain white matter connectivity and local topology of reward system nodes in patients with alcohol use disorder (AUD) and unaffected siblings, relative to healthy comparison individuals. Diffusion-weighted magnetic resonance imaging scans were acquired from 18 patients with AUD, 15 unaffected siblings of AUD patients and 15 healthy controls. Structural networks were examined using network-based statistic and connectomic analysis. Connectomic analysis showed a significant ordered difference in normalized rich club organization (AUD < Siblings < Controls)...
December 27, 2017: Addiction Biology
Adon F G Rosen, David R Roalf, Kosha Ruparel, Jason Blake, Kevin Seelaus, Lakshmi P Villa, Rastko Ciric, Philip A Cook, Christos Davatzikos, Mark A Elliott, Angel Garcia de La Garza, Efstathios D Gennatas, Megan Quarmley, J Eric Schmitt, Russell T Shinohara, M Dylan Tisdall, R Cameron Craddock, Raquel E Gur, Ruben C Gur, Theodore D Satterthwaite
Data quality is increasingly recognized as one of the most important confounding factors in brain imaging research. It is particularly important for studies of brain development, where age is systematically related to in-scanner motion and data quality. Prior work has demonstrated that in-scanner head motion biases estimates of structural neuroimaging measures. However, objective measures of data quality are not available for most structural brain images. Here we sought to identify quantitative measures of data quality for T1-weighted volumes, describe how such measures of quality relate to cortical thickness, and delineate how this in turn may bias inference regarding associations with age in youth...
December 23, 2017: NeuroImage
Matthew C Murphy, Kevin C Chan, Seong-Gi Kim, Alberto L Vazquez
Functional imaging of spontaneous activity continues to play an important role in the field of connectomics. The most common imaging signal used for these experiments is the blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) signal, but how this signal relates to spontaneous neuronal activity remains incompletely understood. Genetically encoded calcium indicators represent a promising tool to study this problem, as they can provide brain-wide measurements of neuronal activity compared to point measurements afforded by electrophysiological recordings...
December 22, 2017: NeuroImage
František Váša, Edward T Bullmore, Ameera X Patel
Functional connectomes are commonly analysed as sparse graphs, constructed by thresholding cross-correlations between regional neurophysiological signals. Thresholding generally retains the strongest edges (correlations), either by retaining edges surpassing a given absolute weight, or by constraining the edge density. The latter (more widely used) method risks inclusion of false positive edges at high edge densities and exclusion of true positive edges at low edge densities. Here we apply new wavelet-based methods, which enable construction of probabilistically-thresholded graphs controlled for type I error, to a dataset of resting-state fMRI scans of 56 patients with schizophrenia and 71 healthy controls...
December 19, 2017: NeuroImage
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