TAILIEUCHUNG - The NEURON Simulation Environment

Mercury is thought to be one of the first metals used by humans. Historical records provide evidence of mercury use by ancient Chinese and Hindu civilizations. Archaeologists have also found traces of mercury in an Egyptian tomb dating from 1500 BC and in the writing of a Chinese alchemist around 4500 BC. Both the Egyptians and Chinese may have been using the mercury ore, cinnabar, as a pigment to paint their tombs, anoint their statues and even preserve their dead. Many civilizations believed mercury had mystical properties and the power to prolong life. Alchemists tried for ages to transmute base metals into gold through the action. | The NEURON Simulation Environment . Hines1 3 and . Carnevale2 3 Departments of 1Computer Science and 2Psychology and 3Neuroengineering and Neuroscience Center Yale University an extended preprint of Hines . and Carnevale . The NEURON Simulation Environment Neural Computation 9 1179-1209 1997. Short course Using the NEURON Simulation Environment 10 97 MLH and NTC all rights reserved 2 The NEURON Simulation Environment Contents 1. The problem Experimental advances and quantitative 2. overview of 3. Mathematical The cable Spatial discretization in a biological context sections and Integration The forward Euler method simple unstable Numerical The backward Euler method inaccurate but Crank-Nicholson Method stable and more The integration methods used in 4. THE NEURON simulation The hoc A specific First step establish model Second step assign anatomical and biophysical Third step attach stimulating Fourth step control simulation time Section Range Specifying geometry stylized vs. Density mechanisms and point Graphical Object-oriented 5. appendix 1. listing of hoc code for the model in section Short course Using the NEURON Simulation Environment 10 97 MLH and NTC all rights reserved The NEURON Simulation Environment 3 1. Introduction NEURON Hines 1984 1989 1993 1994 provides a powerful and flexible environment for implementing biologically realistic models of electrical and chemical signaling in neurons and .

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