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- Thompson, Paul M., et al.
(author)
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The ENIGMA Consortium : large-scale collaborative analyses of neuroimaging and genetic data
- 2014
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In: BRAIN IMAGING BEHAV. - : Springer Science and Business Media LLC. - 1931-7557 .- 1931-7565. ; 8:2, s. 153-182
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Journal article (peer-reviewed)abstract
- The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
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- Nunes, A, et al.
(author)
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Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
- 2020
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In: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 25:9, s. 2130-2143
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Journal article (peer-reviewed)abstract
- Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.
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- Scheffel, Jan, et al.
(author)
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Confinement scaling laws for the conventional reversed-field pinch
- 2000
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In: Physical Review Letters. - 0031-9007 .- 1079-7114. ; 85:2, s. 322-325
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Journal article (peer-reviewed)abstract
- A series of high resolution, 3D, resistive MHD numerical simulations of the reversed-field pinch are performed to obtain scaling laws for poloidal beta and energy confinement ar Lundquist numbers approaching 10(6). Optimum plasma conditions are attained by taking the transport coefficients to be classical, and ignoring radiation losses and resistive wall effects. We find that poloidal beta scales as beta(theta) proportional to I-0.40 and that the energy confinement time scales as tau(E) proportional to I-0.34 For fixed I/N, with aspect ratio R/a = 1.25.
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| 9. |
- Scheffel, Jan, 1954-, et al.
(author)
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Energy Confinement in the Advanced RFP
- 2003
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In: 45th Annual Meeting of the Division of Plasma Physics; Albuquerque, New Mexico, USA, 27-31 October 2003.
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Conference paper (peer-reviewed)abstract
- In earlier numerical studies [1,2] of confinement in the optimized, conventional reversed-field pinch (RFP), the scaling of energy confinement time with plasma current and density was found to be too weak to lead into fusion relevant regimes. In the advanced RFP, however, the detrimental magnetic (dynamo) fluctuations are largely eliminated by the presence of an externally applied electric field. This field is adjusted to generate a tearing mode stable parallel current density profile. Previous studies [3,4] used a gaussian shaped electric field with given width and amplitude that was localised at some minor radius of the plasma. A threefold increase in energy confinement was found, but the three associated parameters made further optimisation difficult. In the present work a new, parameter free scheme for current profile control is introduced. An automatic control system continuously replaces the dynamo electric field. Early results indicate strong energy confinement enhancement.[1] J. Scheffel and D. D. Schnack, Phys. Rev. Lett. 85 (2000) 322.[2] J. Scheffel and D. D. Schnack, Nucl. Fusion 40 (2000) 1885.[3] C. R. Sovinec and S. C. Prager, Nucl. Fusion 39 (1999) 777.[4] J. Scheffel and D. D. Schnack, International RFP Workshop, Stockholm 2002.
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| 10. |
- Scheffel, Jan, et al.
(author)
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Numerical studies of confinement scaling in the conventional reversed field pinch
- 2000
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In: Nuclear Fusion. - : IOP Publishing. - 0029-5515 .- 1741-4326. ; 40:11, s. 1885-1896
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Journal article (peer-reviewed)abstract
- Scaling laws for reversed field pinch (RFP) confinement parameters versus plasma current and density are found from computer simulations. The RFP dynamics at high Lundquist numbers approaching 10(6) is studied using a high resolution, 3-D, resistive MHD numerical code. Optimum plasma conditions are attained by assuming that the transport coefficients are classical, and by ignoring radiation losses and resistive wall effects. Anomalous global transport results from classical parallel heat conduction along stochastic field lines in the plasma core. The pinch parameter is Theta = 1.8 and the aspect ratio is R/a = 1.25. Poloidal beta is found to scale as beta (theta) proportional to (I/N)(-0.40) I-0.40 and energy confinement time as tau (E) proportional to (I/N)(0.34) I-0.34. On-axis temperature scales as T(0) proportional to (I/N)(0.56) I-0.56. Experimental results from T2, RFX and MST agree well with the above numerical results and also with the obtained magnetic fluctuation scaling proportional to S-0.14, where S is the Lundquist number. Thus stochastic core field lines appear to persist also at higher, reactor relevant currents and temperatures in the conventional RFP, indicating the need to further pursue confinement enhancement techniques.
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