30 research outputs found

    Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline.

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    Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges--management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu

    Voxel Based Morphometry Alterations in Mal de Debarquement Syndrome.

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    Mal de debarquement syndrome (MdDS) is a disorder of chronic self-motion perception that occurs though entrainment to rhythmic background motion, such as from sea voyage, and involves the perception of low-frequency rocking that can last for months or years. The neural basis of this persistent sensory perception abnormality is not well understood.We investigated grey matter volume differences underlying persistent MdDS by performing voxel-based morphometry on whole brain and pre-specified ROIs in 28 individuals with MdDS and comparing them to 18 age, sex, and handedness matched controls.MdDS participants exhibited greater grey matter volume in the left inferior parietal lobule, right inferior occipital gyrus (area V3v), right temporal pole, bilateral cerebellar hemispheric lobules VIII/IX and left lobule VIIa/VIIb. Grey matter volumes were lower in bilateral inferior frontal, orbitofrontal, pregenual anterior cingulate cortex (pgACC) and left superior medial gyri (t = 3.0, p<0.005uncorr). In ROI analyses, there were no volume differences in the middle occipital gyrus (region of V5/MT) or parietal operculum 2 (region of the parietoinsular vestibular cortex). Illness duration was positively related to grey matter volume in bilateral inferior frontal gyrus/anterior insula (IFG/AI), right posterior insula, superior parietal lobule, left middle occipital gyrus (V5/MT), bilateral postcentral gyrus, anterior cerebellum, and left cerebellar hemisphere and vermian lobule IX. In contrast, illness duration was negatively related to volume in pgACC, posterior middle cingulate gyrus (MCC), left middle frontal gyrus (dorsolateral prefrontal cortex-DLPFC), and right cerebellar hemispheric lobule VIIIb (t = 3.0, p<0.005uncorr). The most significant differences were decreased volume in the pgACC and increased volume in the left IFG/AI with longer illness duration (qFDRcorr <0.05). Concurrent medication use did not correlate with these findings or have a relationship with duration of illness. MdDS participants showed positive correlations between grey matter volume in pgACC and bilateral cerebellar lobules VIII/IX, which was not seen in controls.Individuals with MdDS show brain volume differences from healthy controls as well as duration of illness dependent volume changes in (a) visual-vestibular processing areas (IPL, SPL, V3, V5/MT), (b) default mode network structures (cerebellar IX, IPL, ACC), (c) salience network structures (ACC and IFG/AI) (d) somatosensory network structures (postcentral gyrus, MCC, anterior cerebellum, cerebellar lobule VIII), and (e) a structure within the central executive network (DLPFC). The identification of these associations may enhance future investigations into how exposure to oscillating environments can modulate brain function and affect motion perception as well cognitive and affective control

    Cerebellar Contrasts.

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    <p>Cerebellar Contrasts.</p

    Cerebral Contrasts.

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    <p>Cerebral Contrasts.</p

    Multiple regression analysis for duration in months, shown at a threshold of t = 3.0, extent voxels 30 for cerebrum and 10 for cerebellum for 27 MdDS participants.

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    <p>Blue areas represent areas of lower volume in individuals with longer duration of illness; red areas represent areas of higher volume in individuals with longer duration of illness. Scale values are in t scores. Coordinates are in MNI space.</p

    Association between SSRI and benzodiazepine use with duration and volume changes.

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    <p>Association between SSRI and benzodiazepine use with duration and volume changes.</p

    Pearson’s correlation coefficients between nodes with the most significant volume changes with time.

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    <p>Blue lines signify relationships that are not significant. The red lines are correlations at <0.05.</p

    Contrast images of grey matter volume differences between MdDS and controls shown at a threshold of t = 3.0, extent voxels 30 for cerebrum and 10 for cerebellum.

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    <p>Blue scales images represent areas with higher volume in Controls; red areas represent higher volumes in MdDS participants. Scale values are in t score. Coordinates are in MNI space.</p

    Multiple Regression: Positive Correlation with Duration.

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    <p>Multiple Regression: Positive Correlation with Duration.</p
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