Influence of Uncertainties in the Material Properties of Brain Tissue on the Probabilistic Volume of Tissue Activated
暂无分享,去创建一个
Ursula van Rienen | Christian Schmidt | Madeleine M. Lowery | Peadar F. Grant | M. Lowery | U. Rienen | P. F. Grant | C. Schmidt
[1] J. Latikka,et al. Conductivity of living intracranial tissues. , 2001, Physics in medicine and biology.
[2] Madeleine M. Lowery,et al. Effect of Dispersive Conductivity and Permittivity in Volume Conductor Models of Deep Brain Stimulation , 2010, IEEE Transactions on Biomedical Engineering.
[3] M. Eldred,et al. Evaluation of Non-Intrusive Approaches for Wiener-Askey Generalized Polynomial Chaos. , 2008 .
[4] Warren M Grill,et al. Impedance characteristics of deep brain stimulation electrodes in vitro and in vivo , 2009, Journal of neural engineering.
[5] Sang-Hoon Lee,et al. A comparative study of uncertainty propagation methods for black-box-type problems , 2008 .
[6] Ron Alterman,et al. Subthalamic deep brain stimulation with a constant-current device in Parkinson's disease: an open-label randomised controlled trial , 2012, The Lancet Neurology.
[7] Torsten Rohlfing,et al. The SRI24 Multi-Channel Brain Atlas: , 2009 .
[8] Robert Michael Kirby,et al. Using the Stochastic Collocation Method for the Uncertainty Quantification of Drug Concentration Due to Depot Shape Variability , 2009, IEEE Transactions on Biomedical Engineering.
[9] C. McIntyre,et al. Tissue and electrode capacitance reduce neural activation volumes during deep brain stimulation , 2005, Clinical Neurophysiology.
[10] D. Bowers,et al. Cognition and mood in Parkinson's disease in subthalamic nucleus versus globus pallidus interna deep brain stimulation: The COMPARE Trial , 2009, Annals of neurology.
[11] Nicholas T. Carnevale,et al. The NEURON Simulation Environment , 1997, Neural Computation.
[12] C. Gabriel,et al. Electrical conductivity of tissue at frequencies below 1 MHz , 2009, Physics in medicine and biology.
[13] Joakim Sundnes,et al. Uncertainty Analysis of Ventricular Mechanics Using the Probabilistic Collocation Method , 2012, IEEE Transactions on Biomedical Engineering.
[14] Fabio Nobile,et al. A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data , 2008, SIAM J. Numer. Anal..
[15] Ursula van Rienen,et al. Modeling the Field Distribution in Deep Brain Stimulation: The Influence of Anisotropy of Brain Tissue , 2012, IEEE Transactions on Biomedical Engineering.
[16] C. Gabriel. The Dielectric Properties of Tissues , 2000 .
[17] C. McIntyre,et al. Cellular effects of deep brain stimulation: model-based analysis of activation and inhibition. , 2004, Journal of neurophysiology.
[18] Nada Yousif,et al. Investigating the depth electrode–brain interface in deep brain stimulation using finite element models with graded complexity in structure and solution , 2009, Journal of Neuroscience Methods.
[19] Bruno Sudret,et al. A stochastic finite element procedure for moment and reliability analysis , 2006 .
[20] D. B. Heppner,et al. Considerations of quasi-stationarity in electrophysiological systems. , 1967, The Bulletin of mathematical biophysics.
[21] Eric Jones,et al. SciPy: Open Source Scientific Tools for Python , 2001 .
[22] Matthew D. Johnson,et al. Current-controlled deep brain stimulation reduces in vivo voltage fluctuations observed during voltage-controlled stimulation , 2010, Clinical Neurophysiology.
[23] Erwan Bezard,et al. Involvement of Sensorimotor, Limbic, and Associative Basal Ganglia Domains in L-3,4-Dihydroxyphenylalanine-Induced Dyskinesia , 2005, The Journal of Neuroscience.
[24] K. Foster,et al. Dielectric properties of tissues and biological materials: a critical review. , 1989, Critical reviews in biomedical engineering.
[25] J. Waldvogel. Fast Construction of the Fejér and Clenshaw–Curtis Quadrature Rules , 2006 .
[26] Christoph Palm,et al. A novel approach to the human connectome: Ultra-high resolution mapping of fiber tracts in the brain , 2011, NeuroImage.
[27] C. McIntyre,et al. Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle. , 2002, Journal of neurophysiology.
[28] Warren M Grill,et al. Analysis of the quasi-static approximation for calculating potentials generated by neural stimulation , 2008, Journal of neural engineering.
[29] A. Benabid. Deep brain stimulation for Parkinson’s disease , 2003, Current Opinion in Neurobiology.
[30] Ursula van Rienen,et al. Quantification of uncertainties in brain tissue conductivity in a heterogeneous model of deep brain stimulation using a non-intrusive projection approach , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[31] K. Mewes,et al. The subthalamic nucleus in Parkinson's disease: somatotopic organization and physiological characteristics. , 2001, Brain : a journal of neurology.
[32] L. Geddes,et al. The specific resistance of biological material—A compendium of data for the biomedical engineer and physiologist , 1967, Medical and biological engineering.
[33] Grant D. Huang,et al. Pallidal versus subthalamic deep-brain stimulation for Parkinson's disease. , 2010, The New England journal of medicine.
[34] Lyes Nechak,et al. Non-intrusive generalized polynomial chaos approach to the stability analysis of uncertain nonlinear dynamic systems , 2011, Eighth International Multi-Conference on Systems, Signals & Devices.
[35] C. McIntyre,et al. Sources and effects of electrode impedance during deep brain stimulation , 2006, Clinical Neurophysiology.
[36] D. Xiu. Numerical Methods for Stochastic Computations: A Spectral Method Approach , 2010 .