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This paper considers a quantitative description of intracellular and transmembrane currents in anisotropic muscle, with emphasis on the factors that determine the extracellular potentials. Although Vmax of the intracellular action potential had no relation to changes in conduction velocity in anisotropic tissue with constant membrane properties, the extracellular waveforms were quite sensitive to velocity changes. Large amplitude biphasic deflection occurred in the fast areas, and in the slow areas the waveforms were of lower amplitude and triphasic in shape; i.e., negative potentials preceded the biphasic positive-negative deflection. The extracellular potentials were simulated on the bases of a model of intracellular currents, and the theoretical and measured results showed good agreement. In tissue with anisotropic conductivity, the relationship between the spatial intracellualr potential gradient and the magnitude of the extracellular potential of the excitation wave was opposite to the classical relationship in isotropic tissue. Due to the influence of the effective intracellular conductivity on the spread of intracellular currents and on conduction velocity, in anisotropic tissue the extracellular potential decreased as the intracellular potential gradient increased. The peak values of the positive and negative potentials and the spatial distribution of the potential gradients varied considerably along the activation front. These findings were accounted for by differences in the distribution and spatial extent of the transmembrane currents, which were determined by the intracellular currents. The theoretical analysis showed that intracellular and transmembrane currents were proportional to the local conduction velocities of the wavefront. Thereby, it was not possible to have a "uniform layer" of current when there were differences in conduction velocity along the length of the excitation wave. The implications of the analysis are considerable, since the gratifying agreement between the theoretical and measured results indicates that the details of the extracellular waveforms can be explained on the basis of the distribution of intracellular currents; i.e., extracellular potentials provide a sensitive index of intracellular current flow.

A Gamma-Ray and Neutron Spectrometer (GRNS) instrument has been developed as part of the science payload for NASA's Discovery Program mission to the planet Mercury. Mercury Surface, Space ENvironment, GEochemistry, and Ranging (MESSEN-GER) launched successfully in 2004 and will journey more than six years before entering

A digital computer model is presented for the simulation of the body surface electrocardiogram (ECG) during ventricular activation and recovery. The ventricles of the heart are represented in detail by a three-dimensional array of approximately 4000 points which is subdivided into 23 regions. Excitation sequence and cellular action potential data taken from the literature are used to determine the spatial distribution of intracellular potentials at each instant of time during a simulated cardiac cycle. The moment of the single dipole representing each region is determined by summing the spatial gradient of the intracellular potential distribution throughout the region. The resulting set of 23 dipoles is then used to calculate the potentials on the surface of a bounded homogeneous volume conductor with the shape of an adult torso. Simulated isopotential surface maps during both activation and recovery are in good agreement with data for humans reported in the literature.

Cardiac muscle is considered to consist of an intracellular domain and an extracellular or interstitial domain. Current passes from one domain to the other through the cell membrane. Electric potentials in interstitial space are shown to be associated with current sources proportional to the spatial gradient of the cellular transmembrane action potential, phi m. Hence, given the distribution of phi m throughout the myocardium, one can calculate the surface electrocardiogram and extracorporeal magnetocardiogram. The problem is considerably complicated when anisotropy is considered. If interstitial space is approximately isotropic, however, the sources are still proportional to delta phi m. It is shown that the effects of intracellular anisotropy on the surface electrocardiogram may be relatively small. The inverse problem is discussed briefly, with consideration of the relationship of the magnetocardiogram to the electrocardiogram. Finally, it is shown that if the heart can be considered to be bounded by a closed surface, then the value of phi m on this surface is uniquely related to the surface electrocardiogram to within a constant, provided there are no internal discontinuities. Such discontinuities, however, would be expected to occur in cases of ischemia and necrosis.

This paper presents some results from a study of biped dynamic walking using reinforcement learning. During this study a hardware biped robot was built, a new reinforcement learning algorithm as well as a new learning architecture were developed. The biped learned dynamic walking without any previous knowledge about its dynamic model. The Self Scaling Reinforcement learning algorithm was developed in order to deal with the problem of reinforcement learning in continuous action domains. The learning architecture was developed in order to solve complex control problems. It uses different modules that consist of simple controllers and small neural networks. The architecture allows for easy incorporation of new modules that represent new knowledge, or new requirements for the desired task.

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