The Experts below are selected from a list of 23226 Experts worldwide ranked by ideXlab platform
Patric Hagmann - One of the best experts on this subject based on the ideXlab platform.
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predicting human resting state functional connectivity from Structural connectivity
Proceedings of the National Academy of Sciences of the United States of America, 2009Co-Authors: Ch Honey, Olaf Sporns, Leila Cammoun, Xavier Gigandet, Jeanphilippe Thiran, Reto Meuli, Patric HagmannAbstract:In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with Structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks—including their spatial statistics and their persistence across time—can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and Structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed (i) that strong functional connections commonly exist between regions with no direct Structural connection, rendering the inference of Structural connectivity from functional connectivity impractical; (ii) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct Structural connectivity; and (iii) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct Structural Linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex.
Billy G Hudson - One of the best experts on this subject based on the ideXlab platform.
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seminiferous tubule basement membrane composition and organization of type iv collagen chains and the Linkage of α3 iv and α5 iv chains
Journal of Biological Chemistry, 1997Co-Authors: Tesfamichael Z Kahsai, George C Enders, Sripad Gunwar, Charlott Brunmark, Jorgen Wieslander, Raghuram Kalluri, Milton E Noelken, Jing Zhou, Billy G HudsonAbstract:Abstract Seminiferous tubule basement membrane (STBM) plays an important role in spermatogenesis. In the present study, the composition and Structural organization of type IV collagen of bovine STBM was investigated. STBM was found to be composed of all six α-chains of type IV collagen based upon immunocytochemical and biochemical analysis. The content of α3(IV) chain (40%) and the α4(IV) chain (18%) was substantially higher than in any other basement membrane collagen. The supramolecular structure of the six α(IV) chains was investigated using pseudolysin (EC 3.4.24.26) digestion to excise triple-helical molecules, subsequent collagenase digestion to produce NC1 hexamers and antibody affinity chromatography to resolve populations of NC1 hexamers. The hexamers, which reflect specific arrangements of α(IV) chains, were characterized for their α(IV) chain composition using high performance liquid chromatography, two-dimensional electrophoresis, and immunoblotting with α(IV) chain-specific antibodies. Three major hexamer populations were found that represent the classical network of the α1(IV) and α2(IV) chains and two novel networks, one composed of the α1(IV)-α6(IV) chains and the other composed of the α3(IV)-α6(IV) chains. The results establish a Structural Linkage between the α3(IV) and α5(IV) chains, suggesting a molecular basis for the conundrum in which mutations in the gene encoding the α5(IV) chain cause defective assembly of the α3(IV) chain in the glomerular basement membrane of patients with Alport syndrome.
Thomas C S Keller - One of the best experts on this subject based on the ideXlab platform.
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smooth muscle titin zq domain interaction with the smooth muscle α actinin central rod
Journal of Biological Chemistry, 2008Co-Authors: Richard J Chi, Alanna R Simon, Ewa A Bienkiewicz, Augustine Felix, Thomas C S KellerAbstract:Actin-myosin II filament-based contractile structures in striated muscle, smooth muscle, and nonmuscle cells contain the actin filament-cross-linking protein α-actinin. In striated muscle Z-disks, α-actinin interacts with N-terminal domains of titin to provide a Structural Linkage crucial for the integrity of the sarcomere. We previously discovered a long titin isoform, originally smitin, hereafter sm-titin, in smooth muscle and demonstrated that native sm-titin interacts with C-terminal EF hand region and central rod R2-R3 spectrin-like repeat region sites in α-actinin. Reverse transcription-PCR analysis of RNA from human adult smooth muscles and cultured rat smooth muscle cells and Western blot analysis with a domain-specific antibody presented here revealed that sm-titin contains the titin gene-encoded Zq domain that may bind to the α-actinin R2-R3 central rod domain as well as Z-repeat domains that bind to the EF hand region. We investigated whether the sm-titin Zq domain binds to α-actinin R2 and R3 spectrin repeat-like domain loops that lie in proximity with two-fold symmetry on the surface of the central rod. Mutations in α-actinin R2 and R3 domain loop residues decreased interaction with expressed sm-titin Zq domain in glutathione S-transferase pull-down and solid phase binding assays. Alanine mutation of a region of the Zq domain with high propensity for α-helix formation decreased apparent Zq domain dimer formation and decreased Zq interaction with the α-actinin R2-R3 region in surface plasmon resonance assays. We present a model in which two sm-titin Zq domains interact with each other and with the two R2-R3 sites in the α-actinin central rod.
Tesfamichael Z Kahsai - One of the best experts on this subject based on the ideXlab platform.
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seminiferous tubule basement membrane composition and organization of type iv collagen chains and the Linkage of α3 iv and α5 iv chains
Journal of Biological Chemistry, 1997Co-Authors: Tesfamichael Z Kahsai, George C Enders, Sripad Gunwar, Charlott Brunmark, Jorgen Wieslander, Raghuram Kalluri, Milton E Noelken, Jing Zhou, Billy G HudsonAbstract:Abstract Seminiferous tubule basement membrane (STBM) plays an important role in spermatogenesis. In the present study, the composition and Structural organization of type IV collagen of bovine STBM was investigated. STBM was found to be composed of all six α-chains of type IV collagen based upon immunocytochemical and biochemical analysis. The content of α3(IV) chain (40%) and the α4(IV) chain (18%) was substantially higher than in any other basement membrane collagen. The supramolecular structure of the six α(IV) chains was investigated using pseudolysin (EC 3.4.24.26) digestion to excise triple-helical molecules, subsequent collagenase digestion to produce NC1 hexamers and antibody affinity chromatography to resolve populations of NC1 hexamers. The hexamers, which reflect specific arrangements of α(IV) chains, were characterized for their α(IV) chain composition using high performance liquid chromatography, two-dimensional electrophoresis, and immunoblotting with α(IV) chain-specific antibodies. Three major hexamer populations were found that represent the classical network of the α1(IV) and α2(IV) chains and two novel networks, one composed of the α1(IV)-α6(IV) chains and the other composed of the α3(IV)-α6(IV) chains. The results establish a Structural Linkage between the α3(IV) and α5(IV) chains, suggesting a molecular basis for the conundrum in which mutations in the gene encoding the α5(IV) chain cause defective assembly of the α3(IV) chain in the glomerular basement membrane of patients with Alport syndrome.
Olaf Sporns - One of the best experts on this subject based on the ideXlab platform.
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can structure predict function in the human brain
NeuroImage, 2010Co-Authors: Christopher J Honey, Jeanphilippe Thivierge, Olaf SpornsAbstract:Over the past decade, scientific interest in the properties of large-scale spontaneous neural dynamics has intensified. Concurrently, novel technologies have been developed for characterizing the connective anatomy of intra-regional circuits and inter-regional fiber pathways. It will soon be possible to build computational models that incorporate these newly detailed Structural network measurements to make predictions of neural dynamics at multiple scales. Here, we review the practicality and the value of these efforts, while at the same time considering in which cases and to what extent structure does determine neural function. Studies of the healthy brain, of neural development, and of pathology all yield examples of direct correspondences between Structural Linkage and dynamical correlation. Theoretical arguments further support the notion that brain network topology and spatial embedding should strongly influence network dynamics. Although future models will need to be tested more quantitatively and against a wider range of empirical neurodynamic features, our present large-scale models can already predict the macroscopic pattern of dynamic correlation across the brain. We conclude that as neuroscience grapples with datasets of increasing completeness and complexity, and attempts to relate the Structural and functional architectures discovered at different neural scales, the value of computational modeling will continue to grow.
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predicting human resting state functional connectivity from Structural connectivity
Proceedings of the National Academy of Sciences of the United States of America, 2009Co-Authors: Ch Honey, Olaf Sporns, Leila Cammoun, Xavier Gigandet, Jeanphilippe Thiran, Reto Meuli, Patric HagmannAbstract:In the cerebral cortex, the activity levels of neuronal populations are continuously fluctuating. When neuronal activity, as measured using functional MRI (fMRI), is temporally coherent across 2 populations, those populations are said to be functionally connected. Functional connectivity has previously been shown to correlate with Structural (anatomical) connectivity patterns at an aggregate level. In the present study we investigate, with the aid of computational modeling, whether systems-level properties of functional networks—including their spatial statistics and their persistence across time—can be accounted for by properties of the underlying anatomical network. We measured resting state functional connectivity (using fMRI) and Structural connectivity (using diffusion spectrum imaging tractography) in the same individuals at high resolution. Structural connectivity then provided the couplings for a model of macroscopic cortical dynamics. In both model and data, we observed (i) that strong functional connections commonly exist between regions with no direct Structural connection, rendering the inference of Structural connectivity from functional connectivity impractical; (ii) that indirect connections and interregional distance accounted for some of the variance in functional connectivity that was unexplained by direct Structural connectivity; and (iii) that resting-state functional connectivity exhibits variability within and across both scanning sessions and model runs. These empirical and modeling results demonstrate that although resting state functional connectivity is variable and is frequently present between regions without direct Structural Linkage, its strength, persistence, and spatial statistics are nevertheless constrained by the large-scale anatomical structure of the human cerebral cortex.
