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Human connectome project

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https://www.readbyqxmd.com/read/28716967/contextual-and-developmental-differences-in-the-neural-architecture-of-cognitive-control
#1
Raluca Petrican, Cheryl L Grady
Since both development and context impact functional brain architecture, the neural connectivity signature of a cognitive or affective predisposition may similarly vary across different ages and circumstances. To test this hypothesis, we investigated the effects of age and cognitive versus social-affective context on the stable and time-varying neural architecture of inhibition, the putative core cognitive control component, in a subsample (N= 359 [22-36 yrs], 174 men) of the Human Connectome Project. Among younger individuals, a neural signature of superior inhibition emerged in both stable and dynamic connectivity analyses...
July 17, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28716714/functional-density-and-edge-maps-characterizing-functional-architecture-in-individuals-and-improving-cross-subject-registration
#2
Tong Tong, Iman Aganj, Tian Ge, Jonathan R Polimeni, Bruce Fischl
Population-level inferences and individual-level analyses are two important aspects in functional magnetic resonance imaging (fMRI) studies. Extracting reliable and informative features from fMRI data that capture biologically meaningful inter-subject variation is critical for aligning and comparing functional networks across subjects, and connecting the properties of functional brain organization with variations in behavior, cognition and genetics. In this study, we derive two new measures, which we term functional density map and edge map, and demonstrate their usefulness in characterizing the function of individual brains...
July 14, 2017: NeuroImage
https://www.readbyqxmd.com/read/28710040/evaluating-the-replicability-specificity-and-generalizability-of-connectome-fingerprints
#3
Lea Waller, Henrik Walter, Johann D Kruschwitz, Lucia Reuter, Sabine Müller, Susanne Erk, Ilya M Veer
Establishing reliable, robust, and unique brain signatures from neuroimaging data is a prerequisite for precision psychiatry, and therefore a highly sought-after goal in contemporary neuroscience. Recently, the procedure of connectome fingerprinting, using brain functional connectivity profiles as such signatures, was shown to be able to accurately identify individuals from a group of 126 subjects from the Human Connectome Project (HCP). However, the specificity and generalizability of this procedure were not tested...
July 11, 2017: NeuroImage
https://www.readbyqxmd.com/read/28687517/comparing-test-retest-reliability-of-dynamic-functional-connectivity-methods
#4
Ann S Choe, Mary Beth Nebel, Anita D Barber, Jessica R Cohen, Yuting Xu, James J Pekar, Brian Caffo, Martin A Lindquist
Due to the dynamic, condition-dependent nature of brain activity, interest in estimating rapid functional connectivity (FC) changes that occur during resting-state functional magnetic resonance imaging (rs-fMRI) has recently soared. However, studying dynamic FC is methodologically challenging, due to the low signal-to-noise ratio of the blood oxygen level dependent (BOLD) signal in fMRI and the massive number of data points generated during the analysis. Thus, it is important to establish methods and summary measures that maximize reliability and the utility of dynamic FC to provide insight into brain function...
July 5, 2017: NeuroImage
https://www.readbyqxmd.com/read/28684331/fiberprint-a-subject-fingerprint-based-on-sparse-code-pooling-for-white-matter-fiber-analysis
#5
Kuldeep Kumar, Christian Desrosiers, Kaleem Siddiqi, Olivier Colliot, Matthew Toews
White matter characterization studies use the information provided by diffusion magnetic resonance imaging (dMRI) to draw cross-population inferences. However, the structure, function, and white matter geometry vary across individuals. Here, we propose a subject fingerprint, called Fiberprint, to quantify the individual uniqueness in white matter geometry using fiber trajectories. We learn a sparse coding representation for fiber trajectories by mapping them to a common space defined by a dictionary. A subject fingerprint is then generated by applying a pooling function for each bundle, thus providing a vector of bundle-wise features describing a particular subject's white matter geometry...
July 3, 2017: NeuroImage
https://www.readbyqxmd.com/read/28676985/functional-connectivity-density-mapping-comparing-multiband-and-conventional-epi-protocols
#6
Alexander D Cohen, Dardo Tomasi, Ehsan Shokri-Kojori, Andrew S Nencka, Yang Wang
Functional connectivity density mapping (FCDM) is a newly developed data-driven technique that quantifies the number of local and global functional connections for each voxel in the brain. In this study, we evaluated reproducibility, sensitivity, and specificity of both local functional connectivity density (lFCD) and global functional connectivity density (gFCD). We compared these metrics using the human connectome project (HCP) compatible high-resolution (2 mm isotropic, TR = 0.8 s) multiband (MB), and more typical, lower resolution (3...
July 4, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28675490/the-significance-of-negative-correlations-in-brain-connectivity
#7
Liang Zhan, Lisanne M Jenkins, Ouri E Wolfson, Johnson Jonaris GadElkarim, Kevin Nocito, Paul M Thompson, Olusola A Ajilore, Moo K Chung, Alex D Leow
Understanding the modularity of functional magnetic resonance imaging (fMRI)-derived brain networks or "connectomes" can inform the study of brain function organization. However, fMRI connectomes additionally involve negative edges, which may not be optimally accounted for by existing approaches to modularity that variably threshold, binarize, or arbitrarily weight these connections. Consequently, many existing Q maximization-based modularity algorithms yield variable modular structures. Here, we present an alternative complementary approach that exploits how frequent the blood-oxygen-level-dependent (BOLD) signal correlation between two nodes is negative...
July 4, 2017: Journal of Comparative Neurology
https://www.readbyqxmd.com/read/28645840/autoreject-automated-artifact-rejection-for-meg-and-eeg-data
#8
Mainak Jas, Denis A Engemann, Yousra Bekhti, Federico Raimondo, Alexandre Gramfort
We present an automated algorithm for unified rejection and repair of bad trials in magnetoencephalography (MEG) and electroencephalography (EEG) signals. Our method capitalizes on cross-validation in conjunction with a robust evaluation metric to estimate the optimal peak-to-peak threshold - a quantity commonly used for identifying bad trials in M/EEG. This approach is then extended to a more sophisticated algorithm which estimates this threshold for each sensor yielding trial-wise bad sensors. Depending on the number of bad sensors, the trial is then repaired by interpolation or by excluding it from subsequent analysis...
June 20, 2017: NeuroImage
https://www.readbyqxmd.com/read/28641247/modeling-task-fmri-data-via-deep-convolutional-autoencoder
#9
Heng Huang, Xintao Hu, Yu Zhao, Milad Makkie, Qinglin Dong, Shijie Zhao, Lei Guo, Tianming Liu
Task-based fMRI (tfMRI) has been widely used to study functional brain networks under task performance. Modeling tfMRI data is challenging due to at least two problems: the lack of the ground truth of underlying neural activity and the highly complex intrinsic structure of tfMRI data. To better understand brain networks based on fMRI data, data-driven approaches have been proposed, for instance, Independent Component Analysis (ICA) and Sparse Dictionary Learning (SDL). However, both ICA and SDL only build shallow models, and they are under the strong assumption that original fMRI signal could be linearly decomposed into time series components with their corresponding spatial maps...
June 15, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28641239/automatic-recognition-of-fmri-derived-functional-networks-using-3d-convolutional-neural-networks
#10
Yu Zhao, Qinglin Dong, Shu Zhang, Wei Zhang, Hanbo Chen, Xi Jiang, Lei Guo, Xintao Hu, Junwei Han, Tianming Liu
Current fMRI data modeling techniques such as Independent Component Analysis (ICA) and Sparse Coding methods can effectively reconstruct dozens or hundreds of concurrent interacting functional brain networks simultaneously from the whole brain fMRI signals. However, such reconstructed networks have no correspondences across different subjects. Thus, automatic, effective and accurate classification and recognition of these large numbers of fMRI-derived functional brain networks are very important for subsequent steps of functional brain analysis in cognitive and clinical neuroscience applications...
June 15, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28631354/cross-population-myelination-covariance-of-human-cerebral-cortex
#11
Zhiwei Ma, Nanyin Zhang
Cross-population covariance of brain morphometric quantities provides a measure of interareal connectivity, as it is believed to be determined by the coordinated neurodevelopment of connected brain regions. Although useful, structural covariance analysis predominantly employed bulky morphological measures with mixed compartments, whereas studies of the structural covariance of any specific subdivisions such as myelin are rare. Characterizing myelination covariance is of interest, as it will reveal connectivity patterns determined by coordinated development of myeloarchitecture between brain regions...
June 20, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28600738/functional-brain-networks-reconstruction-using-group-sparsity-regularized-learning
#12
Qinghua Zhao, Will X Y Li, Xi Jiang, Jinglei Lv, Jianfeng Lu, Tianming Liu
Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction...
June 9, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28600737/extendable-supervised-dictionary-learning-for-exploring-diverse-and-concurrent-brain-activities-in-task-based-fmri
#13
Shijie Zhao, Junwei Han, Xintao Hu, Xi Jiang, Jinglei Lv, Tuo Zhang, Shu Zhang, Lei Guo, Tianming Liu
Recently, a growing body of studies have demonstrated the simultaneous existence of diverse brain activities, e.g., task-evoked dominant response activities, delayed response activities and intrinsic brain activities, under specific task conditions. However, current dominant task-based functional magnetic resonance imaging (tfMRI) analysis approach, i.e., the general linear model (GLM), might have difficulty in discovering those diverse and concurrent brain responses sufficiently. This subtraction-based model-driven approach focuses on the brain activities evoked directly from the task paradigm, thus likely overlooks other possible concurrent brain activities evoked during the information processing...
June 9, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28561418/heritability-of-hippocampal-subfield-volumes-using-a-twin-and-non-twin-siblings-design
#14
Sejal Patel, Min Tae M Park, Gabriel A Devenyi, Raihaan Patel, Mario Masellis, Jo Knight, M Mallar Chakravarty
The hippocampus is composed of distinct subfields linked to diverse functions and disorders. The subfields can be mapped using high-resolution magnetic resonance images, and their volumes can potentially be used as quantitative phenotypes for genetic investigation of hippocampal function. We estimated the heritability of hippocampus subfield volumes of 465 subjects from the Human Connectome Project (twins and non-twin siblings) using two methods. The first used a univariate model to estimate heritability with and without adjustment for total brain volume (TBV) and ipsilateral hippocampal volume to determine if heritability was uniquely attributable to subfield volume rather than confounds that attributed to global volumes...
May 31, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28557055/time-efficient-and-flexible-design-of-optimized-multishell-hardi-diffusion
#15
Jana Hutter, J Donald Tournier, Anthony N Price, Lucilio Cordero-Grande, Emer J Hughes, Shaihan Malik, Johannes Steinweg, Matteo Bastiani, Stamatios N Sotiropoulos, Saad Jbabdi, Jesper Andersson, A David Edwards, Joseph V Hajnal
PURPOSE: Advanced diffusion magnetic resonance imaging benefits from collecting as much data as is feasible but is highly sensitive to subject motion and the risk of data loss increases with longer acquisition times. Our purpose was to create a maximally time-efficient and flexible diffusion acquisition capability with built-in robustness to partially acquired or interrupted scans. Our framework has been developed for the developing Human Connectome Project, but different application domains are equally possible...
May 30, 2017: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
https://www.readbyqxmd.com/read/28491028/resting-state-functional-connectivity-and-network-analysis-of-cerebellum-with-respect-to-crystallized-iq-and-gender
#16
Vasileios C Pezoulas, Michalis Zervakis, Sifis Michelogiannis, Manousos A Klados
During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high crystallized Intelligence Quotient (IQ). Functional magnetic resonance imaging (fMRI) data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP) database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28486710/association-between-reward-reactivity-and-drug-use-severity-is-substance-dependent-preliminary-evidence-from-the-human-connectome-project
#17
Alyssa L Peechatka, Amy C Janes
Introduction: Blunted nucleus accumbens (NAc) reactivity to reward is common across drug users. One theory is that individuals abuse substances due to this reward deficit. However, whether there is a relationship between the amount an individual uses and the severity of NAc dysfunction is unclear. It also is possible that such a relationship is substance specific, as nicotine transiently increases reward system sensitivity while alcohol, another commonly used substance, does not. As smokers may use nicotine to bolster NAc reward function, we hypothesize that NAc reactivity to reward will be related to volume of cigarette use, but not volume of alcohol use...
June 1, 2017: Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco
https://www.readbyqxmd.com/read/28461700/connectome-imaging-for-mapping-human-brain-pathways
#18
Y Shi, A W Toga
With the fast advance of connectome imaging techniques, we have the opportunity of mapping the human brain pathways in vivo at unprecedented resolution. In this article we review the current developments of diffusion magnetic resonance imaging (MRI) for the reconstruction of anatomical pathways in connectome studies. We first introduce the background of diffusion MRI with an emphasis on the technical advances and challenges in state-of-the-art multi-shell acquisition schemes used in the Human Connectome Project...
May 2, 2017: Molecular Psychiatry
https://www.readbyqxmd.com/read/28461060/gray-matter-structural-variability-in-the-human-cerebellum-lobule-specific-differences-across-sex-and-hemisphere
#19
REVIEW
Christopher J Steele, M Mallar Chakravarty
Though commonly thought of as a "motor structure", we now know that the cerebellum's reciprocal connections to the cerebral cortex underlie contributions to both motor and non-motor behavior. Further, recent research has shown that cerebellar dysfunction may contribute to a wide range of neuropsychiatric disorders. However, there has been little characterization of normative variability at the level of cerebellar structure that can facilitate and further our understanding of disease biomarkers. In this manuscript we examine normative variation of the cerebellum using data from the Human Connectome Project (HCP)...
April 28, 2017: NeuroImage
https://www.readbyqxmd.com/read/28457575/objective-analysis-of-the-topological-organization-of-the-human-cortical-visual-connectome-suggests-three-visual-pathways
#20
Koen V Haak, Christian F Beckmann
The cortical visual system is composed of many areas serving various visual functions. In non-human primates, these are broadly organised into two distinct processing pathways: a ventral pathway for object recognition, and a dorsal pathway for action. In humans, recent theoretical proposals suggest the possible existence of additional pathways, but direct empirical evidence has yet to be presented. Here, we estimated the connectivity patterns between 22 human visual areas using resting-state functional MRI data of 470 individuals, leveraging the unprecedented data quantity and quality of the Human Connectome Project and a novel probabilistic atlas...
April 7, 2017: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
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