Geometry-based finite-element modeling of the electrical contact between a cultured neuron and a microelectrode

The electrical contact between a substrate embedded microelectrode and a cultured neuron depends on the geometry of the neuron-electrode interface. Interpretation and improvement of these contacts requires proper modeling of all coupling mechanisms. In literature, it is common practice to model the neuron-electrode contact using lumped circuits in which large simplifications are made in the representation of the interface geometry. In this paper, the finite-element method is used to model the neuron-electrode interface, which permits numerical solutions for a variety of interface geometries. The simulation results offer detailed spatial and temporal information about the combined electrical behavior of extracellular volume, electrode-electrolyte interface and neuronal membrane

EMG Modeling

The aim of this chapter is to describe the approaches used for modelling electromyographic (EMG) signals as well as the principles of electrical conduction within the muscle. Sections are organized into a progressive, step-by-step EMG modeling of structures of increasing complexity. First, the basis of the electrical conduction that allows for the propagation of the EMG signals within the muscle is presented. Second, the models used for describing the electrical activity generated by a single fibre described. The third section is devoted to modeling the organization of the motor unit and the generation of motor unit potentials. Based on models of the architectural organization of motor units and their activation and firing mechanisms, the last section focuses on modeling the electrical activity of a complete muscle as recorded at the surface

Analysis of Simulated Electromyography (EMG) Signals Using Integrated Computer Muscle Model

Introduction Electromyography (EMG) is a technique used to study the activity of muscle through detection and analysis of the electrical signals generated during muscular contractions. Electromyographic activity is recorded from skeletal muscles to obtain information about their anatomy and physiology. Electromyography, in interplay with various anatomical techniques, provides the present knowledge of the structural organization and the nervous control of muscle. EMG is the prime source of information about the status of the neuromuscular system, and EMG has developed into a diagnostic tool that allows the clinician to follow changes in nerve and muscle caused by neuromuscular diseases. EMG provides both invasive and noninvasive means for the study of muscular functions [1, 2]. It is also useful in interpreting pathologic states of musculoskeletal or neuromuscular systems [3, 4]. In particular, EMG offers valuable information concerning the timing of muscular activity and its relative intensity [5, 6]. Standard EMG is typically recorded from fine wire or two surface electrodes placed at discrete sites over a muscle or muscle belly. Currently surface grid electrode EMG is widely used. The cell bodies of these neurons reside in the brainstem and spinal cord. The interfacing fiber between motor neuron and muscle is called axon. At the distal end, an axon divides 1 into many terminal branches. Each terminal branch innervates a group of muscle fibers. When a nerve signal approaches the end of an axon, it spreads out over all its terminal branches and stimulates all the muscle fibers supplied by them. So, all the excited muscle fibers contract almost simultaneously. Since they behave as a single functional unit, one nerve fiber and all the muscle fibers innervated by it are called a motor unit (MU) [7, 8]. Generally, the muscle fibers of a motor unit are distributed throughout muscle rather than being clustered together. The fine control of the muscle force is performed through the intricate mechanism and interaction of the brain and muscle. During contraction, these motor units are recruited systematically and the recruited motor units discharge in a train of pulses in a complex manner [9, 10]. The recorded EMG is the temporal summation of all the recruited motor unit action potential trains. Because movement is controlled by motor unit activity, an understanding of motor unit physiology can have a significant impact on the evaluation and treatment of movement disorders. The neuromuscular system is an intricate physiological organization of brain, nerve and muscle. These neural control properties are not well understood mostly because of the experimental difficulties in quantifying the neural input to the muscle. Moreover, the muscle itself is a complex system. It is necessary to address these complexities as accurately as possible. Understanding of these complex systems facilitates the understanding of EMG generation, which is a highly complex signal by itself

Comparison of Propagation Models and Forward Calculation Methods on Cellular, Tissue and Organ Scale Atrial Electrophysiology

The bidomain model and the finite element method are an established standard to mathematically describe cardiac electrophysiology, but are both suboptimal choices for fast and large-scale simulations due to high computational costs. We investigate to what extent simplified approaches for propagation models (monodomain, reaction-Eikonal and Eikonal) and forward calculation (boundary element and infinite volume conductor) deliver markedly accelerated, yet physiologically accurate simulation results in atrial electrophysiology. Methods: We compared action potential durations, local activation times (LATs), and electrocardiograms (ECGs) for sinus rhythm simulations on healthy and fibrotically infiltrated atrial models. Results: All simplified model solutions yielded LATs and P waves in accurate accordance with the bidomain results. Only for the Eikonal model with pre-computed action potential templates shifted in time to derive transmembrane voltages, repolarization behavior notably deviated from the bidomain results. ECGs calculated with the boundary element method were characterized by correlation coefficients >0.9 compared to the finite element method. The infinite volume conductor method led to lower correlation coefficients caused predominantly by systematic overestimations of P wave amplitudes in the precordial leads. Conclusion: Our results demonstrate that the Eikonal model yields accurate LATs and combined with the boundary element method precise ECGs compared to markedly more expensive full bidomain simulations. However, for an accurate representation of atrial repolarization dynamics, diffusion terms must be accounted for in simplified models. Significance: Simulations of atrial LATs and ECGs can be notably accelerated to clinically feasible time frames at high accuracy by resorting to the Eikonal and boundary element methods

Astrocytic Ion Dynamics: Implications for Potassium Buffering and Liquid Flow

We review modeling of astrocyte ion dynamics with a specific focus on the implications of so-called spatial potassium buffering, where excess potassium in the extracellular space (ECS) is transported away to prevent pathological neural spiking. The recently introduced Kirchoff-Nernst-Planck (KNP) scheme for modeling ion dynamics in astrocytes (and brain tissue in general) is outlined and used to study such spatial buffering. We next describe how the ion dynamics of astrocytes may regulate microscopic liquid flow by osmotic effects and how such microscopic flow can be linked to whole-brain macroscopic flow. We thus include the key elements in a putative multiscale theory with astrocytes linking neural activity on a microscopic scale to macroscopic fluid flow.Comment: 27 pages, 7 figure

Design and Optimisation of Extracellular Microelectrodes

The work described in this thesis concerns the development and application of design methods for the optimisation of thin film metal microelectrodes, to be used for recording the electrical signals generated by neurons in culture

Numerical modelling in transcranial magnetic stimulation

Tese de doutoramento, Engenharia Biomédica e Biofísica, Universidade de Lisboa, Faculdade de Ciências, 2009In this work powerful numerical methods were used to study several problems that still remain unsolved in TMS.The first problem that was studied is related to the difficulties that arise when stimulating sub-cortical deep regions with TMS, due to the fact that the induced field rapidly decays and loses focality with depth. This study's approach to overcome this difficulty was to combine ferromagnetic cores with a coil designed to induce an electric field that decays slowly. The efficacy of this approach was tested by using the FEM to calculate the field induced by this coil / core design in a realistically shaped head model. The results show that the core might make this coil even more suited for deep brain stimulation.The second problem that was tackled is related to the lack of knowledge about the dominant mechanisms through which the induced electric field excites neurons in TMS. In this work the electric field along lines, representing trajectories of actual cortical neurons, was calculated using the FEM. The neurons were embedded in a realistically shaped sulcus model, with a figure-8 coil placed above the model. The electric field was then incorporated into the cable equation. The solution of the latter allowed the determination of the site and threshold of activation of the neurons. The results highlight the importance of axonal terminations and bends and tissue heterogeneities on stimulation of neurons.The third problem that was studied concerns TMS of small animals and the lack of knowledge about the optimal geometry, size and orientation of the used coils. This was studied by using the FEM to calculate the electric field induced in a realistically shaped mouse model by several commercially available coils. The results showed that the smaller coils induced fields with higher magnitude, better focality, and smaller decay than the bigger coils.These results highlight the importance of numerical modelling in TMS, either in coil design, determination of basic neurophysiologic mechanisms or optimization of experimental procedures