Image Selection T1 and T1 phantom images based on colin27 are used Segmentation Segmentation was performed using BrainSuite Finite Element Mesh Generation.

Slides:



Advertisements
Similar presentations
Bioelectromagnetism Exercise #4 – Answers
Advertisements

Six-week project Lauren Villemaire MBP 3970Z Department of Medical Biophysics University of Western Ontario.
TMS-evoked EEG responses in symptomatic and recovered patients with mild traumatic brain injury Jussi Tallus 1, Pantelis Lioumis 2, Heikki Hämäläinen 3,
RESULTS METHODS Quantitative Metrics for Describing Topographic Organization in Individuals Cody Allen 1 ; Anthony I. Jack, PhD 2 1 Department of Physics;
Functional Magnetic Resonance Imaging or fMRI How does a brain get red and yellow spots ?  Center for Complex Systems and Brain Sciences, 2000 Created.
SPECULAR FLOW AND THE PERCEPTION OF SURFACE REFLECTANCE Stefan Roth * Fulvio Domini † Michael J. Black * * Computer Science † Cognitive and Linguistic.
Caudate Shape Discrimination in Schizophrenia Using Template-free Non-parametric Tests Y. Sampath K. Vetsa 1, Martin Styner 1, Stephen M. Pizer 1, Jeffrey.
Figure 1: Locations of rosette strain gauges (n = 10) on the cadaveric pelvis. * * * * * * * * * * G Figure 3: Fixture for loading the pelvis (A) actuator,
1 of 40 Lecture 4-Neuroanatomy Walter Schneider When we talk about the brain we need to be able to identify and communicate clearly on what part of the.
INTRODUCTION In studying the relation between the electric and the magnetic field produced by the current sources of different forms there is a challenging.
A 3D Vector-Additive Iterative Solver for the Anisotropic Inhomogeneous Poisson Equation in the Forward EEG problem V. Volkov 1, A. Zherdetsky 1, S. Turovets.
ADHD Arjun Watane Soumyabrata Dey. Work accomplished Extracted features for – Normalized brain, GM, WM, CSF Ran feature vectors through SVM Ready to fine.
1 ELEC 3105 Basic EM and Power Engineering Start Solutions to Poisson’s and/or Laplace’s.
ENE 325 Electromagnetic Fields and Waves Lecture 6 Capacitance and Magnetostatics 1.
Powerpoint Templates Page 1 Depth Effects of DEP Chip with Microcavities Array on Impedance Measurement for Live and Dead Cells Cheng-Hsin Chuang - STUST.
References: [1]S.M. Smith et al. (2004) Advances in functional and structural MR image analysis and implementation in FSL. Neuroimage 23: [2]S.M.
Phrenology Wrong!. Outer Surface of Human Brain Gray Matter = Neuron cell bodies & dendrites White Matter = Myelin (=fat)- covered axons Cortex = Outer.
M. Pokric, P.A. Bromiley, N.A. Thacker, M.L.J. Scott, and A. Jackson University of Manchester Imaging Science and Biomedical Engineering Probabilistic.
ENE 325 Electromagnetic Fields and Waves Lecture 4 Magnetostatics.
Conclusions Simulated fMRI phantoms with real motion and realistic susceptibility artifacts have been generated and tested using SPM2. Image distortion.
Acknowledgement Work supported by NINDS (grant NS39845), NIMH (grants MH42900 and 19116) and the Human Frontier Science Program Methods Fullhead.
Makeig-Worrell NCRR Project Overview Scott Makeig, Ph.D. is the Director of the Swartz Center for Computational Neuroscience Institute for Neural Computation.
The current density at each interfacial layer. The forward voltage is continuous at every point inside the body. A Layered Model for Breasts in Electrical.
The gray-white matter boundary defines the locations and directions of the primary currents in the cortex and can be used as an anatomical constraint for.
Date of download: 6/21/2016 Copyright © ASME. All rights reserved. From: In Vitro Quantification of Time Dependent Thrombus Size Using Magnetic Resonance.
Date of download: 6/23/2016 Copyright © 2016 SPIE. All rights reserved. (a) This image shows the fNIRS sources (dark blue filled circles), detectors (light.
Date of download: 7/8/2016 Copyright © ASME. All rights reserved. From: Voxelized Model of Brain Infusion That Accounts for Small Feature Fissures: Comparison.
Finite Element Modelling of the dipole source in EEG
Date of download: 10/12/2017 Copyright © ASME. All rights reserved.
FIGURE 1. Homonymous hemianopsia after LITT for TLE
Date of download: 10/24/2017 Copyright © ASME. All rights reserved.
Prepared BY: Helwan University Faculty Of Engineering
Figure 1. Whisker-evoked intrinsic signal in S1
Comparing Transcranial Magnetic Stimulation & Direct Electric Stimulation: An Application of the Finite Element Method Brandi Henry Mathematics Department,
Date of download: 1/9/2018 Copyright © ASME. All rights reserved.
Fig. 4. Reactive cerebral artery extraction using standard deviation (SD) map categorization is shown. (A) Image processing steps for the reactive artery.
Moo K. Chung1,3, Kim M. Dalton3, Richard J. Davidson2,3
Volume 60, Issue 4, Pages (November 2008)
G. Palacios 02/25/18 E_y field as a function of anode vertical position for 200kV CEBAF gun upgrade G. Palacios 02/25/18.
Volume 60, Issue 5, Pages (December 2008)
S. Levänen, V. Jousmäki, R. Hari  Current Biology 
Toward a Neural Basis for Social Behavior
Volume 26, Issue 13, Pages (July 2016)
Detecting Gray Matter Maturation via Tensor-based Surface Morphometry
Linking Electrical Stimulation of Human Primary Visual Cortex, Size of Affected Cortical Area, Neuronal Responses, and Subjective Experience  Jonathan.
Volume 41, Issue 5, Pages (March 2004)
Christian Grefkes, Peter H. Weiss, Karl Zilles, Gereon R. Fink  Neuron 
200 kV gun CST microwave studio simulations Shield modifications
200 kV gun CST microwave studio simulations Shield modifications
Towards a neural basis of auditory sentence processing
Volume 89, Issue 6, Pages (March 2016)
Measurement accuracy of focal cartilage defects from MRI and correlation of MRI graded lesions with histology: a preliminary study  Chris A McGibbon,
EEG and MEG: Relevance to Neuroscience
Rajdeep Ojha1, Vimal Chander1, Devakumar2
Voxel-based Morphometric Analysis
R. Lattanzi, C. Petchprapa, D. Ascani, J. S. Babb, D. Chu, R. I
Anatomical Measures John Ashburner
Comparison of reconstruction and acquisition choices for quantitative T2* maps and synthetic contrasts  Riikka Ruuth, Linda Kuusela, Teemu Mäkelä, Susanna.
Integration of Local Features into Global Shapes
Volume 26, Issue 13, Pages (July 2016)
Cortical Motion Deafness
Ingrid Bureau, Gordon M.G Shepherd, Karel Svoboda  Neuron 
Volume 64, Issue 4, Pages (November 2009)
C. R. Henak, E. D. Carruth, A. E. Anderson, M. D. Harris, B. J
Personalized Medicine in Psychiatry
Volume 84, Issue 3, Pages (March 2003)
Evaluating Intramural Virtual Electrodes in the Myocardial Wedge Preparation: Simulations of Experimental Conditions  G. Plank, A. Prassl, E. Hofer, N.A.
A Hippocampal Marker of Recollection Memory Ability among Healthy Young Adults: Contributions of Posterior and Anterior Segments  Jordan Poppenk, Morris.
Volume 74, Issue 5, Pages (May 1998)
Fig. 2 Tumor tracing, modeling, and optimization.
Presentation transcript:

Image Selection T1 and T1 phantom images based on colin27 are used Segmentation Segmentation was performed using BrainSuite Finite Element Mesh Generation Volume meshes suitable for Finite Element calculations were generated using mimics Electric Field Calculation The electric field calculations were performed using Comsol The Electric Field on the Cortical Surface of the Human Brain during tCS A. Mekonnen 1, M. Lu 1, R. Salvador 1, G. Ruffini 2, P. C. Miranda 1 1 Institute of Biophysics and Biomedical Engineering, Faculty of Science, University of Lisbon, Lisbon, Portugal; 2 Starlab Barcelona, Barcelona, Spain. Introduction Transcranial current stimulation (tCS) is a noninvasive brain stimulation technique that has been shown to modulate the cortical functions in humans ([1]). The level of modulation by tCS depends on the induced electric field in the brain. The spatial distribution of the electric field in the brain, in particular the electric field magnitude and direction in the cortical sheet are important factors in understanding stimulus intensity and localization. We implemented a realistic Finite Element (FE) head model based on MR images to investigate the effect of tissue heterogeneity and electrode size on the electric field distribution. Two types of electrodes are investigated : (1) 50 mm square electrode, area 25 cm 2, height 6 mm; (2) 11 mm diam. circular electrode, area 1.0 cm 2, height 2 mm. Methods The realistic FE head was built in four steps: Results 1. Effects of tissue inhomogeneity : 2. Effects of Electrode size : 3. Superimposition on anatomy: Acknowledgments: This work was supported by the Foundation for Science and Technology (FCT), Portugal and project HIVE. The project HIVE acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET-Open grant number: Fig. 1. Finite element mesh of the head model: (a): scalp and electrodes; (b): interface between GM and CSF. In the model, the x axis points in the left to right direction, the y axis in the posterior-anterior direction and the z axis in the inferior-superior direction. Fig. 2. Spatial distribution of the magnitude of the electric field in a sagittal slice located under the large anode. The image in (a) includes all the tissues in the model as well as the anode. In (b) the electric field is shown only in the GM and WM. In these calculations, CSF = 1.79 S/m, GM = 0.33 S/m, GM = 0.15 S/m. In (c) CSF = GM = 0.33 S/m and in (d) CSF = WM = GM = 0.33 S/m. The color bars represent the norm of the electric field, in V/m. Fig: 3. Electric field distribution on the GM-CSF interface : the top row shows the normal component of the electric field whereas the bottom row shows its tangential component. The first column shows the electric field due to the 25cm 2 electrode whereas the data in the second row pertains to the 1 cm 2 circular electrode. Note the use of different scales in the plots. a b Discussion Fig. 4. The distribution of the magnitude of the electric field in the gray and white matter on a sagittal slice (x=56, near the hand knob) overlaid on the anatomical image (Colin27) in MRIcro, (a) for the square electrode, (b) for the circular electrode. The analysis of the electric field distribution within the gray matter and the white matter showed that the maxima of the electric field magnitude occur at localized hot spots at the bottom of the sulci, further away from the electrodes. In addition, the electric field in the cortex under the stimulation electrode has a strong tangential component. This is a significant departure from earlier findings that use spherical head models in which the maxima always appear close to the electrodes and where the electric field is predominantly normal to the brain surface. The difference is attributed to the high conductivity of the CSF and also to the fact that the cortex is highly convoluted. The 1.0 cm 2 circular electrode produced a more focal electric field distribution than the 25 cm 2 square electrode, but in both cases the high electric field region is not limited to the vicinity of the electrode. A method was devised to superimpose the electric field or the current density distributions on anatomical images, using MRIcro. As the user navigates through the brain the corresponding field data is displayed as an overlay. Conclusion The distinctive feature of this model is an accurate representation of the cortical sheet and of the CSF that fills its fissures. Using this model it is possible to investigate the complexity of the combined effects of tissue heterogeneity and the convoluted shape of the cortex on the electric field distribution in the brain. References [1] M A Nitsche, W Paulus, Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation, J Physiol, 527(3): 633-9, A square 25 cm 2 cathode was placed over the right eyebrow and the anode, either a square 25 cm 2 or a circular 1.0 cm 2 electrode, was placed over M1. The injected current was always set to 1 mA. These results show that tissue heterogeneity has a considerable impact on the electric field distribution. When the conductivities of the intracranial tissues are set to the same value, the distribution becomes more like the one observed in spherical models. ab a |E n | c |E t | d b |E n | a b cd