By George L. Gerstein (auth.), Frank H. Eeckman (eds.)
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Extra resources for Analysis and Modeling of Neural Systems
Of Horm. Metabol. Res. Suppl. 10, 100-107. , Rosario, L. and Rojas E. (1983). Properties of calciumactivated potassium channels in the pancreatic ,8-cell. Cell Calcium 4, 451-461. [41 Chay, T. R. and Cook D. L. (1988). Endogenous bursting patterns in excitable cells. Math. Biosci. 90, 139-153. [51 Chay, T. R. and Kang, H. S. (1988). Role of single channel stochastic noise on bursting clusters of pancreatic ,8-cells. Biophys. J. 54, 427-435. [61 Chay, T. R. and Keizer, J. (1983). Minimal model for membrane oscillations in the pancreatic ,8-cell.
C. and Miura, R. M. (1978). A mathematical model for spreading cortical depression. Biophys. J. 23, 257-276. [321 Yarom, Y. and Spira, M. E. (1982). Extracellular potassium ions mediate specific neuronal interaction. Science 216, 80-82. Sparse-stimulation and Wiener Kernels Stanley A. edu Abstract Wiener and Volterra kernel analysis is useful for analyzing nonlinear neural systems. In order to obtain kernels with good signal to noise properties one must optimize the stimulus characteristics. This optimization has been hampered by the lack of simple expressions for kernel variance.
Such forced transitions relate to the phase resetting behavior of the bursting oscillator. The description we have given is approximate. We have dissected the model based on the disparity in time scales between the fast variables, V and n, and the slow variable S. The approximation, however, is quantitatively accurate; the actual computed burst pattern falls precisely in the phase plane where our 34 prediction says it should (Fig. lC). To complete the graphical representation we indicate, with the curve labeled S = 0, the values of V and S where, according to Eqn.
Analysis and Modeling of Neural Systems by George L. Gerstein (auth.), Frank H. Eeckman (eds.)