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Human connectome project

Abbas Babajani-Feremi
Comprehension of narratives constitutes a fundamental part of our everyday life experience. Although the neural mechanism of auditory narrative comprehension has been investigated in some studies, the neural correlates underlying this mechanism and its heritability remain poorly understood. We investigated comprehension of naturalistic speech in a large, healthy adult population (n = 429; 176/253 M/F; 22-36 years of age) consisting of 192 twin pairs (49 monozygotic and 47 dizygotic pairs) and 237 of their siblings...
February 18, 2017: Brain Topography
Peng-Hu Wei, Zhi-Qi Mao, Fei Cong, Bo Wang, Zhi-Pei Ling, Shu-Li Liang, Xin-Guang Yu
Temporal lobe epilepsy often propagates inter-hemispherically. Although the pathway of the propagation was verified by electrophysiology, the trajectory remains poorly defined. DTI can depict fiber trajectory but it has limited angular resolution and cannot adequately assess cortical regions. We visualized potential pathways of bitemporal epilepsy propagation using diffusion spectrum imaging (DSI) with data consisting of 8 groups of 514 directions and diffusion templates of 842 subjects from the human connectome project (HCP)...
February 10, 2017: Journal of Clinical Neuroscience: Official Journal of the Neurosurgical Society of Australasia
Pierre Besson, Nicolas Carrière, S Kathleen Bandt, Marc Tommasi, Xavier Leclerc, Philippe Derambure, Renaud Lopes, Louise Tyvaert
The present study describes extraction of high-resolution structural connectome (HRSC) in 99 healthy subjects, acquired and made available by the Human Connectome Project. Single subject connectomes were then registered to the common surface space to allow assessment of inter-individual reproducibility of this novel technique using a leave-one-out approach. The anatomic relevance of the surface-based connectome was examined via a clustering algorithm, which identified anatomic subdivisions within the striatum...
February 7, 2017: Brain Topography
Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz
Connections of the living human brain, on a macroscopic scale, can be mapped by a diffusion MR imaging based workflow. Since the same anatomic regions can be corresponded between distinct brains, one can compare the presence or the absence of the edges, connecting the very same two anatomic regions, among multiple cortices. Previously, we have constructed the consensus braingraphs on 1015 vertices first in five, then in 96 subjects in the Budapest Reference Connectome Server v1.0 and v2.0, respectively. Here we report the construction of the version 3...
February 2017: Cognitive Neurodynamics
Guillermo Gallardo, William Wells Iii, Rachid Deriche, Demian Wassermann
Current theories hold that brain function is highly related to long-range physical connections through axonal bundles, namely extrinsic connectivity. However, obtaining a groupwise cortical parcellation based on extrinsic connectivity remains challenging. Current parcellation methods are computationally expensive; need tuning of several parameters or rely on ad-hoc constraints. Furthermore, none of these methods present a model for the cortical extrinsic connectivity of the cortex. To tackle these problems, we propose a parsimonious model for the extrinsic connectivity and an efficient parceling technique based on clustering of tractograms...
February 1, 2017: NeuroImage
Bahram Marami, Benoit Scherrer, Onur Afacan, Simon K Warfield, Ali Gholipour
Simultaneous multi-slice (SMS) echo-planar imaging has had a huge impact on the acceleration and routine use of diffusion-weighted MRI (DWI) in neuroimaging studies in particular the human connectome project; but also holds the potential to facilitate DWI of moving subjects, as proposed by the new technique developed in this paper. We present a novel registration-based motion tracking technique that takes advantage of the multi-plane coverage of the anatomy by simultaneously acquired slices to enable robust reconstruction of neural microstructure from SMS DWI of moving subjects...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
Roberta Riccelli, Nicola Toschi, Salvatore Nigro, Antonio Terracciano, Luca Passamonti
The five-factor model (FFM) is a widely used taxonomy of human personality; yet its neuro anatomical basis remains unclear. This is partly because past associations between gray-matter volume and FFM were driven by different surface-based morphometry (SBM) indices (i.e. cortical thickness, surface area, cortical folding or any combination of them). To overcome this limitation, we used Free-Surfer to study how variability in SBM measures was related to the FFM in n = 507 participants from the Human Connectome Project...
January 24, 2017: Social Cognitive and Affective Neuroscience
Gaelle E Doucet, Natalie Rasgon, Bruce S McEwen, Nadia Micali, Sophia Frangou
Elevated body mass index (BMI) is associated with increased multi-morbidity and mortality. The investigation of the relationship between BMI and brain organization has the potential to provide new insights relevant to clinical and policy strategies for weight control. Here, we quantified the association between increasing BMI and the functional organization of resting-state brain networks in a sample of 496 healthy individuals that were studied as part of the Human Connectome Project. We demonstrated that higher BMI was associated with changes in the functional connectivity of the default-mode network (DMN), central executive network (CEN), sensorimotor network (SMN), visual network (VN), and their constituent modules...
January 23, 2017: Cerebral Cortex
Sebastiano Stramaglia, Leonardo Angelini, Guorong Wu, Jesus M Cortes, Luca Faes, Daniele Marinazzo
OBJECTIVES: We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. METHODS: The presence of redundancy and/or synergy in multivariate time series data renders difficult to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables...
April 28, 2016: IEEE Transactions on Bio-medical Engineering
Xi Jiang, Xiang Li, Jinglei Lv, Shijie Zhao, Shu Zhang, Wei Zhang, Tuo Zhang, Junwei Han, Lei Guo, Tianming Liu
OBJECTIVE: Various studies in the brain mapping field have demonstrated that there exist multiple concurrent functional networks that are spatially overlapped and interacting with each other during specific task performance to jointly realize the total brain function. Assessing such spatial overlap patterns of functional networks (SOPFNs) based on fMRI has thus received increasing interest for brain function studies. However, there are still two crucial issues to be addressed. First, the SOPFNs are assessed over the entire fMRI scan assuming the temporal stationarity, while possibly time-dependent dynamics of the SOPFNs is not sufficiently explored...
August 10, 2016: IEEE Transactions on Bio-medical Engineering
Lei Nie, Paul M Matthews, Yike Guo
OBJECTIVE: Functional parcellation of the cerebral cortex is variable across different subjects or between cognitive states. Ignoring individual - or state - dependent variations in the functional parcellation may lead to inaccurate representations of individual functional connectivity, limiting the precision of interpretations of differences in individual connectivity profiles. However, it is difficult to infer the individual-level variations due to the relatively low robustness of methods for parcellation of individual subjects...
May 19, 2016: IEEE Transactions on Bio-medical Engineering
Sheng Zhang, Sien Hu, Herta H Chao, Chiang-Shan R Li
Resting-state functional connectivity (rsFC) is widely used to examine cerebral functional organization. The ventral striatum (VS) is critical to motivated behavior, with extant studies suggesting functional hemispheric asymmetry. The current work investigated differences in rsFC between the left (L) and right (R) VS and explored gender differences in the extent of functional lateralization. In 106 adults, we computed a laterality index (fcLI) to query whether a target region shows greater or less connectivity to the L vs R VS...
January 21, 2017: Brain Structure & Function
Dogu Baran Aydogan, Yonggang Shi
While tractography is widely used in brain imaging research, its quantitative validation is highly difficult. Many fiber systems, however, have well-known topographic organization which can even be quantitatively mapped such as the retinotopy of visual pathway. Motivated by this previously untapped anatomical knowledge, we develop a novel tractography method that preserves both topographic and geometric regularity of fiber systems. For topographic preservation, we propose a novel likelihood function that tests the match between parallel curves and fiber orientation distributions...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
Peter N Taylor, Yujiang Wang, Marcus Kaiser
Previous structural brain connectivity studies have mainly focussed on the macroscopic scale of around 1,000 or fewer brain areas (network nodes). However, it has recently been demonstrated that high resolution structural connectomes of around 50,000 nodes can be generated reproducibly. In this study, we infer high resolution brain connectivity matrices using diffusion imaging data from the Human Connectome Project. With such high resolution we are able to analyse networks within brain areas in a single subject...
January 5, 2017: Scientific Reports
Taylor Bolt, Jason S Nomi, Mikail Rubinov, Lucina Q Uddin
Much of the literature exploring differences between intrinsic and task-evoked brain architectures has examined changes in functional connectivity patterns between specific brain regions. While informative, this approach overlooks important overall functional changes in hub organization and network topology that may provide insights about differences in integration between intrinsic and task-evoked states. Examination of changes in overall network organization, such as a change in the concentration of hub nodes or a quantitative change in network organization, is important for understanding the underlying processes that differ between intrinsic and task-evoked brain architectures...
January 4, 2017: Human Brain Mapping
Brian J Curtis, Paula G Williams, Christopher R Jones, Jeffrey S Anderson
BACKGROUND: Approximately 30% of the U.S. population reports recurrent short sleep; however, perceived sleep need varies widely among individuals. Some "habitual short sleepers" routinely sleep 4-6 hr/night without self-reported adverse consequences. Identifying neural mechanisms underlying individual differences in perceived sleep-related dysfunction has important implications for understanding associations between sleep duration and health. METHOD: This study utilized data from 839 subjects of the Human Connectome Project to examine resting functional connectivity associations with self-reported short sleep duration, as well as differences between short sleepers with versus without reported dysfunction...
December 2016: Brain and Behavior
Emanuele Olivetti, Nusrat Sharmin, Paolo Avesani
The white matter pathways of the brain can be reconstructed as 3D polylines, called streamlines, through the analysis of diffusion magnetic resonance imaging (dMRI) data. The whole set of streamlines is called tractogram and represents the structural connectome of the brain. In multiple applications, like group-analysis, segmentation, or atlasing, tractograms of different subjects need to be aligned. Typically, this is done with registration methods, that transform the tractograms in order to increase their similarity...
2016: Frontiers in Neuroscience
Emilie T McKinnon, Jens H Jensen, G Russell Glenn, Joseph A Helpern
PURPOSE: The dependence of the direction-averaged diffusion-weighted imaging (DWI) signal in brain was studied as a function of b-value in order to help elucidate the relationship between diffusion weighting and brain microstructure. METHODS: High angular resolution diffusion imaging (HARDI) data were acquired from two human volunteers with 128 diffusion-encoding directions and six b-value shells ranging from 1000 to 6000s/mm(2) in increments of 1000s/mm(2). The direction-averaged signal was calculated for each shell by averaging over all diffusion-encoding directions, and the signal was plotted as a function of b-value for selected regions of interest...
October 27, 2016: Magnetic Resonance Imaging
Ludovica Griffanti, Gwenaëlle Douaud, Janine Bijsterbosh, Stefania Evangelisti, Fidel Alfaro-Almagro, Matthew F Glasser, Eugene P Duff, Sean Fitzgibbon, Robert Westphal, Davide Carone, Christian F Beckmann, Stephen M Smith
We present a practical "how-to" guide to help determine whether single-subject fMRI independent components (ICs) characterise structured noise or not. Manual identification of signal and noise after ICA decomposition is required for efficient data denoising: to train supervised algorithms, to check the results of unsupervised ones or to manually clean the data. In this paper we describe the main spatial and temporal features of ICs and provide general guidelines on how to evaluate these. Examples of signal and noise components are provided from a wide range of datasets (3T data, including examples from the UK Biobank and the Human Connectome Project, and 7T data), together with practical guidelines for their identification...
December 16, 2016: NeuroImage
Amir Zolal, Stephan B Sobottka, Dino Podlesek, Jennifer Linn, Bernhard Rieger, Tareq A Juratli, Gabriele Schackert, Hagen H Kitzler
OBJECTIVE The depiction of cranial nerves (CNs) using diffusion tensor imaging (DTI) is of great interest in skull base tumor surgery and DTI used with deterministic tracking methods has been reported previously. However, there are still no good methods usable for the elimination of noise from the resulting depictions. The authors have hypothesized that probabilistic tracking could lead to more accurate results, because it more efficiently extracts information from the underlying data. Moreover, the authors have adapted a previously described technique for noise elimination using gradual threshold increases to probabilistic tracking...
December 16, 2016: Journal of Neurosurgery
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