The Experts below are selected from a list of 60570 Experts worldwide ranked by ideXlab platform
Teresa D Figley - One of the best experts on this subject based on the ideXlab platform.
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probabilistic White Matter atlases of human auditory basal ganglia language precuneus sensorimotor visual and visuospatial networks
Frontiers in Human Neuroscience, 2017Co-Authors: Teresa D Figley, Behnoush Mortazavi Moghadam, Navdeep Bhullar, Jennifer Kornelsen, Susan M Courtney, Chase R FigleyAbstract:Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the White Matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided DTI tractography to create probabilistic White Matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Methods: Whole-brain diffusion Imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥ 0.15 and deviation angle < 50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. ROIs for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair. Results: The resulting functionally-defined White Matter atlases (i.e., for each tract and each network as a whole) were saved as NIfTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/). Conclusions: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map White Matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroImaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative White Matter Imaging signals) to these functional brain networks.
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Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks
Frontiers Media S.A., 2017Co-Authors: Teresa D Figley, Behnoush Mortazavi Moghadam, Navdeep Bhullar, Jennifer KornelsenAbstract:Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the White Matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided diffusion tensor Imaging (DTI) tractography to create probabilistic White Matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks.Methods: Whole-brain diffusion Imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥0.15 and deviation angle <50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. Regions-of-interest (ROIs) for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair.Results: The resulting functionally-defined White Matter atlases (i.e., for each tract and each network as a whole) were saved as NIFTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/).Conclusion: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map White Matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroImaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative White Matter Imaging signals) to these functional brain networks
Chase R Figley - One of the best experts on this subject based on the ideXlab platform.
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probabilistic White Matter atlases of human auditory basal ganglia language precuneus sensorimotor visual and visuospatial networks
Frontiers in Human Neuroscience, 2017Co-Authors: Teresa D Figley, Behnoush Mortazavi Moghadam, Navdeep Bhullar, Jennifer Kornelsen, Susan M Courtney, Chase R FigleyAbstract:Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the White Matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided DTI tractography to create probabilistic White Matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Methods: Whole-brain diffusion Imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥ 0.15 and deviation angle < 50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. ROIs for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair. Results: The resulting functionally-defined White Matter atlases (i.e., for each tract and each network as a whole) were saved as NIfTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/). Conclusions: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map White Matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroImaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative White Matter Imaging signals) to these functional brain networks.
Susan M Courtney - One of the best experts on this subject based on the ideXlab platform.
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probabilistic White Matter atlases of human auditory basal ganglia language precuneus sensorimotor visual and visuospatial networks
Frontiers in Human Neuroscience, 2017Co-Authors: Teresa D Figley, Behnoush Mortazavi Moghadam, Navdeep Bhullar, Jennifer Kornelsen, Susan M Courtney, Chase R FigleyAbstract:Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the White Matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided DTI tractography to create probabilistic White Matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Methods: Whole-brain diffusion Imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥ 0.15 and deviation angle < 50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. ROIs for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair. Results: The resulting functionally-defined White Matter atlases (i.e., for each tract and each network as a whole) were saved as NIfTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/). Conclusions: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map White Matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroImaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative White Matter Imaging signals) to these functional brain networks.
Navdeep Bhullar - One of the best experts on this subject based on the ideXlab platform.
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probabilistic White Matter atlases of human auditory basal ganglia language precuneus sensorimotor visual and visuospatial networks
Frontiers in Human Neuroscience, 2017Co-Authors: Teresa D Figley, Behnoush Mortazavi Moghadam, Navdeep Bhullar, Jennifer Kornelsen, Susan M Courtney, Chase R FigleyAbstract:Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the White Matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided DTI tractography to create probabilistic White Matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Methods: Whole-brain diffusion Imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥ 0.15 and deviation angle < 50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. ROIs for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair. Results: The resulting functionally-defined White Matter atlases (i.e., for each tract and each network as a whole) were saved as NIfTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/). Conclusions: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map White Matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroImaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative White Matter Imaging signals) to these functional brain networks.
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Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks
Frontiers Media S.A., 2017Co-Authors: Teresa D Figley, Behnoush Mortazavi Moghadam, Navdeep Bhullar, Jennifer KornelsenAbstract:Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the White Matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided diffusion tensor Imaging (DTI) tractography to create probabilistic White Matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks.Methods: Whole-brain diffusion Imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥0.15 and deviation angle <50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. Regions-of-interest (ROIs) for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair.Results: The resulting functionally-defined White Matter atlases (i.e., for each tract and each network as a whole) were saved as NIFTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/).Conclusion: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map White Matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroImaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative White Matter Imaging signals) to these functional brain networks
Behnoush Mortazavi Moghadam - One of the best experts on this subject based on the ideXlab platform.
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probabilistic White Matter atlases of human auditory basal ganglia language precuneus sensorimotor visual and visuospatial networks
Frontiers in Human Neuroscience, 2017Co-Authors: Teresa D Figley, Behnoush Mortazavi Moghadam, Navdeep Bhullar, Jennifer Kornelsen, Susan M Courtney, Chase R FigleyAbstract:Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the White Matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided DTI tractography to create probabilistic White Matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Methods: Whole-brain diffusion Imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥ 0.15 and deviation angle < 50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. ROIs for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair. Results: The resulting functionally-defined White Matter atlases (i.e., for each tract and each network as a whole) were saved as NIfTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/). Conclusions: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map White Matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual, and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroImaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative White Matter Imaging signals) to these functional brain networks.
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Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks
Frontiers Media S.A., 2017Co-Authors: Teresa D Figley, Behnoush Mortazavi Moghadam, Navdeep Bhullar, Jennifer KornelsenAbstract:Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the White Matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided diffusion tensor Imaging (DTI) tractography to create probabilistic White Matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks.Methods: Whole-brain diffusion Imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥0.15 and deviation angle <50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. Regions-of-interest (ROIs) for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair.Results: The resulting functionally-defined White Matter atlases (i.e., for each tract and each network as a whole) were saved as NIFTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/).Conclusion: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map White Matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroImaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative White Matter Imaging signals) to these functional brain networks
