Objective To study the influence of white matter anisotropic conductivity on scalp electric potential distribution.Methods According to the volume constraint water diffusion tensor was converted to conductivity tensor,and the five-layer(white matter,grey matter,CSF,skull,scalp)finite element model(FEM)was constructed based on the DTI data.Based on this model first-order FEM algorithm was implemented.And the scalp electric potential distribution was calculated by using current dipole modal.Results Anisotropic conductivity of white matter has influence in EEG problem,and more influence when the ratio of radius and tangential of volume constraint is greater.The right-left dipoles have more influence than superior-inferior ones.Conclusion In the study of EEG,the anisotropic conductivity of brain tissue cannot be neglected.

Objective To generate finite element models of human head based on segmented computer tomography data.Methods A four-step procedure was adopted to configure the coarse mesh.The method of longest edge propagation path and the edge collapse were used to refine and optimize the final mesh.The method was evaluated by means of computer simulations in a 3-concentric-sphere head model and a three-layer realistic geometry human head model.Results The present simulation results showed reliability and rationality of the finite element computation,thus indicate the suitability of the developed method.Conclusion A multi-tissue finite element model is obtained by using this method.It can be applied to the computation of finite element based bio-mechanics and bio-electromagnetism.

Objective To develop a new Two-step magnetic resonance electrical impedance tomography(MREIT)algorithm based on radial basic function(RBF)neural network for imaging electrical impedance distribution of a head.Methods Firstly,the magnetic resonance imaging(MRI)system with high resolution was used to set up 3D model of the object and to identify the boundaries of different tissues.Then RBF MREIT algorithm was applied to estimate piece-wise homogeneous impedance values of those tissues,respectively.Furthermore,the impedance of each element within each region of the FEM model was estimated according to the RBF genetic algorithm method based on the piece-wise constant impedance.Results Computer simulations were conducted in a three-sphere head model(scalp-skull-brain,SSB)and the simulation results showed the applicability and feasibility of the present Two-step MREIT algorithm in imaging continuous electrical impedance distribution within the head.Conclusion The present Two-step MREIT algorithm is an effective method for imaging the continuous electrical impedance distribution within the human head.

Meshless methods are recently developed numerical methods which require only node informa- tion. This paper introduces the basic principles and history of meshless methods, the principles and implementation of the moving least square method taking Galerkin method as an example. Finite points mixed method (FPMM) and its application in solving electrocardiogram(ECG) forward problem is also introduced. Foreground and problems need to be solved concerning the application of meshless methods in the study of ECG forward problem are discussed.

The research of EEG is of grat significance and clinical importance in studying the cognitive function and neural activity of the brain. There are two key problems in the field of EEG, EEG forward problem and EEG inverse problem. EEG forward problem which aims to get the distribution of the scalp potential due to the known current distribution in the brain is the basis of the EEG inverse problem. Generally, EEG inverse problem depends on the accuracy and efficiency of the computational method of EEG forward problem. This paper gives a review of the head model and corresponding computational method about EEG forward problem studied in recent years.
Algorithms ; Brain ; anatomy & histology ; physiology ; Brain Mapping ; methods ; Electroencephalography ; Head ; anatomy & histology ; Image Processing, Computer-Assisted ; methods ; Mathematics ; Models, Anatomic ; Models, Neurological

The study of water molecule self-diffusion process is of importance not only for getting anatomical information of brain inner tissue, but also for shedding light on the diffusion process of some medicine in brain tissue. In this paper, we summarized the self-diffusion model of water molecule in brain inner tissue, and calculated the self-diffusion coefficient based on Monte Carlo simulation under different conditions. The comparison between this result and that of Latour model showed that the two self-diffusion coefficients were getting closer when the diffusion time became longer, and that the Latour model was a long time-depended self-diffusion model.
Body Water ; metabolism ; Brain ; metabolism ; Cell Membrane Permeability ; Diffusion ; Diffusion Magnetic Resonance Imaging ; methods ; Extracellular Space ; metabolism ; Humans ; Models, Biological ; Monte Carlo Method