The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform

Mikael Landen - One of the best experts on this subject based on the ideXlab platform.

  • manic episodes are associated with grey matter volume reduction a voxel based morphometry Brain Analysis
    Acta Psychiatrica Scandinavica, 2010
    Co-Authors: Carl Johan Ekman, Johanna Lind, Eleonore Ryden, Mikael Landen, Martin Ingvar
    Abstract:

    Ekman CJ, Lind J, Ryden E, Ingvar M, Landen M. Manic episodes are associated with grey matter volume reduction — a voxel-based morphometry Brain Analysis. Objective:  To investigate whether the lifetime number of affective episodes or illness duration is associated with changes in local grey matter volume, in patients with bipolar I disorder without comorbid conditions. Method:  Magnetic resonance imaging scans of 55 patients with bipolar I disorder were analysed using VBM. Results:  Smaller grey matter volume in the inferior frontal gyri of the dorsolateral prefrontal cortices (DLPFC) correlated significantly to the lifetime number of manic episodes. No association between local grey matter volume and the lifetime number of depression episodes or illness duration was found. Conclusion:  We found strong evidence for a linear correlation between a decrease in DLPFC volume and the lifetime number of manic episodes in patients with bipolar I disorder. Interestingly, DLPFC is known to be important for executive functions and the findings in this study might hence be linked to the executive cognitive deficits associated with bipolar disorder.

  • manic episodes are associated with grey matter volume reduction a voxel based morphometry Brain Analysis
    Acta Psychiatrica Scandinavica, 2010
    Co-Authors: Carl Johan Ekman, Johanna Lind, Eleonore Ryden, Mikael Landen, Martin Ingvar
    Abstract:

    Ekman CJ, Lind J, Ryden E, Ingvar M, Landen M. Manic episodes are associated with grey matter volume reduction — a voxel-based morphometry Brain Analysis. Objective:  To investigate whether the lifetime number of affective episodes or illness duration is associated with changes in local grey matter volume, in patients with bipolar I disorder without comorbid conditions. Method:  Magnetic resonance imaging scans of 55 patients with bipolar I disorder were analysed using VBM. Results:  Smaller grey matter volume in the inferior frontal gyri of the dorsolateral prefrontal cortices (DLPFC) correlated significantly to the lifetime number of manic episodes. No association between local grey matter volume and the lifetime number of depression episodes or illness duration was found. Conclusion:  We found strong evidence for a linear correlation between a decrease in DLPFC volume and the lifetime number of manic episodes in patients with bipolar I disorder. Interestingly, DLPFC is known to be important for executive functions and the findings in this study might hence be linked to the executive cognitive deficits associated with bipolar disorder.

Chang Uk Lee - One of the best experts on this subject based on the ideXlab platform.

  • apathy and white matter integrity in alzheimer s disease a whole Brain Analysis with tract based spatial statistics
    PLOS ONE, 2013
    Co-Authors: Changtae Hahn, Hyunkook Lim, Wang Yeon Won, Kook Jin Ahn, Wonsang Jung, Chang Uk Lee
    Abstract:

    The aim of this study was to investigate the microstructural alterations of white matter (WM) in Alzheimer’s disease (AD) patients with apathy and to observe the relationships with the severity of apathy. Sixty drug-naive subjects took part in this study (30 apathetic and 30 nonapathetic subjects with AD). The loss of integrity in WM was compared in AD patients with and without apathy through measurement of fractional anisotropy (FA) using by tract-based spatial statistics (TBSS). In addition, we explored the correlation pattern between FA values and the severity of apathy in AD patients with apathy. The apathy group had significantly reduced FA values (pcorrected<0.05) in the genu of the corpus callosum compared to the nonapathy group. The severity of apathy was negatively correlated with FA values of the left anterior and posterior cingulum, right superior longitudinal fasciculus, splenium, body and genu of the corpus callosum and bilateral uncinate fasciculusin the apathy group (pcorrected<0.05). This study was the first to explore FA values in whole Brain WM in AD patients with apathy. The findings of these microstructural alterations of WM may be the key to the understanding of underlying neurobiological mechanism and clinical significances of apathy in AD.

  • Apathy and white matter integrity in Alzheimer's disease: a whole Brain Analysis with tract-based spatial statistics.
    PloS one, 2013
    Co-Authors: Changtae Hahn, Hyunkook Lim, Wang Yeon Won, Kook Jin Ahn, Wonsang Jung, Chang Uk Lee
    Abstract:

    The aim of this study was to investigate the microstructural alterations of white matter (WM) in Alzheimer’s disease (AD) patients with apathy and to observe the relationships with the severity of apathy. Sixty drug-naive subjects took part in this study (30 apathetic and 30 nonapathetic subjects with AD). The loss of integrity in WM was compared in AD patients with and without apathy through measurement of fractional anisotropy (FA) using by tract-based spatial statistics (TBSS). In addition, we explored the correlation pattern between FA values and the severity of apathy in AD patients with apathy. The apathy group had significantly reduced FA values (pcorrected

Changtae Hahn - One of the best experts on this subject based on the ideXlab platform.

  • apathy and white matter integrity in alzheimer s disease a whole Brain Analysis with tract based spatial statistics
    PLOS ONE, 2013
    Co-Authors: Changtae Hahn, Hyunkook Lim, Wang Yeon Won, Kook Jin Ahn, Wonsang Jung, Chang Uk Lee
    Abstract:

    The aim of this study was to investigate the microstructural alterations of white matter (WM) in Alzheimer’s disease (AD) patients with apathy and to observe the relationships with the severity of apathy. Sixty drug-naive subjects took part in this study (30 apathetic and 30 nonapathetic subjects with AD). The loss of integrity in WM was compared in AD patients with and without apathy through measurement of fractional anisotropy (FA) using by tract-based spatial statistics (TBSS). In addition, we explored the correlation pattern between FA values and the severity of apathy in AD patients with apathy. The apathy group had significantly reduced FA values (pcorrected<0.05) in the genu of the corpus callosum compared to the nonapathy group. The severity of apathy was negatively correlated with FA values of the left anterior and posterior cingulum, right superior longitudinal fasciculus, splenium, body and genu of the corpus callosum and bilateral uncinate fasciculusin the apathy group (pcorrected<0.05). This study was the first to explore FA values in whole Brain WM in AD patients with apathy. The findings of these microstructural alterations of WM may be the key to the understanding of underlying neurobiological mechanism and clinical significances of apathy in AD.

  • Apathy and white matter integrity in Alzheimer's disease: a whole Brain Analysis with tract-based spatial statistics.
    PloS one, 2013
    Co-Authors: Changtae Hahn, Hyunkook Lim, Wang Yeon Won, Kook Jin Ahn, Wonsang Jung, Chang Uk Lee
    Abstract:

    The aim of this study was to investigate the microstructural alterations of white matter (WM) in Alzheimer’s disease (AD) patients with apathy and to observe the relationships with the severity of apathy. Sixty drug-naive subjects took part in this study (30 apathetic and 30 nonapathetic subjects with AD). The loss of integrity in WM was compared in AD patients with and without apathy through measurement of fractional anisotropy (FA) using by tract-based spatial statistics (TBSS). In addition, we explored the correlation pattern between FA values and the severity of apathy in AD patients with apathy. The apathy group had significantly reduced FA values (pcorrected

Alexandra Badea - One of the best experts on this subject based on the ideXlab platform.

  • Small Animal Multivariate Brain Analysis (SAMBA) – a High Throughput Pipeline with a Validation Framework
    Neuroinformatics, 2019
    Co-Authors: Robert J. Anderson, James J. Cook, Natalie Delpratt, John C. Nouls, James O. Mcnamara, Brian B. Avants, G. Allan Johnson, Alexandra Badea
    Abstract:

    While many neuroscience questions aim to understand the human Brain, much current knowledge has been gained using animal models, which replicate genetic, structural, and connectivity aspects of the human Brain. While voxel-based Analysis (VBA) of preclinical magnetic resonance images is widely-used, a thorough examination of the statistical robustness, stability, and error rates is hindered by high computational demands of processing large arrays, and the many parameters involved therein. Thus, workflows are often based on intuition or experience, while preclinical validation studies remain scarce. To increase throughput and reproducibility of quantitative small animal Brain studies, we have developed a publicly shared, high throughput VBA pipeline in a high-performance computing environment, called SAMBA. The increased computational efficiency allowed large multidimensional arrays to be processed in 1–3 days—a task that previously took ~1 month. To quantify the variability and reliability of preclinical VBA in rodent models, we propose a validation framework consisting of morphological phantoms, and four metrics. This addresses several sources that impact VBA results, including registration and template construction strategies. We have used this framework to inform the VBA workflow parameters in a VBA study for a mouse model of epilepsy. We also present initial efforts towards standardizing small animal neuroimaging data in a similar fashion with human neuroimaging. We conclude that verifying the accuracy of VBA merits attention, and should be the focus of a broader effort within the community. The proposed framework promotes consistent quality assurance of VBA in preclinical neuroimaging, thus facilitating the creation and communication of robust results.

  • Small Animal Multivariate Brain Analysis (SAMBA) - a High Throughput Pipeline with a Validation Framework.
    Neuroinformatics, 2018
    Co-Authors: Robert J. Anderson, James J. Cook, Natalie Delpratt, John C. Nouls, James O. Mcnamara, Brian B. Avants, G. Allan Johnson, Alexandra Badea
    Abstract:

    While many neuroscience questions aim to understand the human Brain, much current knowledge has been gained using animal models, which replicate genetic, structural, and connectivity aspects of the human Brain. While voxel-based Analysis (VBA) of preclinical magnetic resonance images is widely-used, a thorough examination of the statistical robustness, stability, and error rates is hindered by high computational demands of processing large arrays, and the many parameters involved therein. Thus, workflows are often based on intuition or experience, while preclinical validation studies remain scarce. To increase throughput and reproducibility of quantitative small animal Brain studies, we have developed a publicly shared, high throughput VBA pipeline in a high-performance computing environment, called SAMBA. The increased computational efficiency allowed large multidimensional arrays to be processed in 1-3 days-a task that previously took ~1 month. To quantify the variability and reliability of preclinical VBA in rodent models, we propose a validation framework consisting of morphological phantoms, and four metrics. This addresses several sources that impact VBA results, including registration and template construction strategies. We have used this framework to inform the VBA workflow parameters in a VBA study for a mouse model of epilepsy. We also present initial efforts towards standardizing small animal neuroimaging data in a similar fashion with human neuroimaging. We conclude that verifying the accuracy of VBA merits attention, and should be the focus of a broader effort within the community. The proposed framework promotes consistent quality assurance of VBA in preclinical neuroimaging, thus facilitating the creation and communication of robust results.

  • Small Animal Multivariate Brain Analysis (SAMBA): A High Throughput Pipeline with a Validation Framework
    arXiv: Quantitative Methods, 2017
    Co-Authors: Robert J. Anderson, James J. Cook, Natalie Delpratt, John C. Nouls, James O. Mcnamara, Brian B. Avants, G. Allan Johnson, Alexandra Badea
    Abstract:

    While many neuroscience questions aim to understand the human Brain, much current knowledge has been gained using animal models, which replicate genetic, structural, and connectivity aspects of the human Brain. While voxel-based Analysis (VBA) of preclinical magnetic resonance images is widely-used, a thorough examination of the statistical robustness, stability, and error rates is hindered by high computational demands of processing large arrays, and the many parameters involved. Thus, workflows are often based on intuition or experience, while preclinical validation studies remain scarce. To increase throughput and reproducibility of quantitative small animal Brain studies, we have developed a publicly shared, high throughput VBA pipeline in a high-performance computing environment, called SAMBA. The increased computational efficiency allowed large multidimensional arrays to be processed in 1-3 days, a task that previously took ~1 month. To quantify the variability and reliability of preclinical VBA in rodent models, we propose a validation framework consisting of morphological phantoms, and four metrics. This addresses several sources that impact VBA results, including registration and template construction strategies. We have used this framework to inform the VBA workflow parameters in a VBA study for a mouse model of epilepsy. We also present initial efforts towards standardizing small animal neuroimaging data in a similar fashion with human neuroimaging. We conclude that verifying the accuracy of VBA merits attention, and should be the focus of a broader effort within the community. The proposed framework promotes consistent quality assurance of VBA in preclinical neuroimaging; facilitating the creation and communication of robust results.

Carl Johan Ekman - One of the best experts on this subject based on the ideXlab platform.

  • manic episodes are associated with grey matter volume reduction a voxel based morphometry Brain Analysis
    Acta Psychiatrica Scandinavica, 2010
    Co-Authors: Carl Johan Ekman, Johanna Lind, Eleonore Ryden, Mikael Landen, Martin Ingvar
    Abstract:

    Ekman CJ, Lind J, Ryden E, Ingvar M, Landen M. Manic episodes are associated with grey matter volume reduction — a voxel-based morphometry Brain Analysis. Objective:  To investigate whether the lifetime number of affective episodes or illness duration is associated with changes in local grey matter volume, in patients with bipolar I disorder without comorbid conditions. Method:  Magnetic resonance imaging scans of 55 patients with bipolar I disorder were analysed using VBM. Results:  Smaller grey matter volume in the inferior frontal gyri of the dorsolateral prefrontal cortices (DLPFC) correlated significantly to the lifetime number of manic episodes. No association between local grey matter volume and the lifetime number of depression episodes or illness duration was found. Conclusion:  We found strong evidence for a linear correlation between a decrease in DLPFC volume and the lifetime number of manic episodes in patients with bipolar I disorder. Interestingly, DLPFC is known to be important for executive functions and the findings in this study might hence be linked to the executive cognitive deficits associated with bipolar disorder.

  • manic episodes are associated with grey matter volume reduction a voxel based morphometry Brain Analysis
    Acta Psychiatrica Scandinavica, 2010
    Co-Authors: Carl Johan Ekman, Johanna Lind, Eleonore Ryden, Mikael Landen, Martin Ingvar
    Abstract:

    Ekman CJ, Lind J, Ryden E, Ingvar M, Landen M. Manic episodes are associated with grey matter volume reduction — a voxel-based morphometry Brain Analysis. Objective:  To investigate whether the lifetime number of affective episodes or illness duration is associated with changes in local grey matter volume, in patients with bipolar I disorder without comorbid conditions. Method:  Magnetic resonance imaging scans of 55 patients with bipolar I disorder were analysed using VBM. Results:  Smaller grey matter volume in the inferior frontal gyri of the dorsolateral prefrontal cortices (DLPFC) correlated significantly to the lifetime number of manic episodes. No association between local grey matter volume and the lifetime number of depression episodes or illness duration was found. Conclusion:  We found strong evidence for a linear correlation between a decrease in DLPFC volume and the lifetime number of manic episodes in patients with bipolar I disorder. Interestingly, DLPFC is known to be important for executive functions and the findings in this study might hence be linked to the executive cognitive deficits associated with bipolar disorder.