A computational model has been developed for the action potential and, more generally, the electrical behaviour of the rat sympathetic neurone. The neurone is simulated as a complex system in which five voltage-dependent conductances (g(Na), g(Ca), g(KV), g(A), g(KCA), one Ca2+-dependent voltage-independent conductance (g(AHP)) and the activating synaptic conductance coexist. The individual currents are mathematically described, based on a systematic analysis obtained for the first time in a mature and intact mammalian neurone using two-electrode voltage-clamp experiments. The simulation initiates by setting the starting values of each variable and by evaluating the holding current required to maintain the imposed membrane potential level. It is then possible to simulate current injection to reproduce either the experimental direct stimulation of the neurone or the physiological activation by the synaptic current flow. The subthreshold behaviour and the spiking activity, even during long-lasting current application, can be analysed. At every time step, the program calculates the amplitude of the individual currents and the ensuing changes; it also takes into account the accompanying K+ accumulation process in the perineuronal space and changes in Ca2+ load. It is shown that the computed time course of membrane potential must be filtered, in order to reproduce the limited bandwidth of the recording instruments, if it is to be compared with experimental measurements under current-clamp conditions. The membrane potential trajectory and single current data are written in files readable by graphic software. Finally, a screen image is obtained which displays in separate graphs the membrane potential time course, the synaptic current and the six ionic current flows. The simulated action potentials are comparable to the experimental ones as concerns overshoot amplitude and rising and falling rates. Therefore, this program is potentially helpful in investigating many aspects of neurone behaviour.

A model of signal processing at a mammalian sympathetic neurone

SACCHI, Oscar;BELLUZZI, Ottorino;CANELLA, Rita;
1998

Abstract

A computational model has been developed for the action potential and, more generally, the electrical behaviour of the rat sympathetic neurone. The neurone is simulated as a complex system in which five voltage-dependent conductances (g(Na), g(Ca), g(KV), g(A), g(KCA), one Ca2+-dependent voltage-independent conductance (g(AHP)) and the activating synaptic conductance coexist. The individual currents are mathematically described, based on a systematic analysis obtained for the first time in a mature and intact mammalian neurone using two-electrode voltage-clamp experiments. The simulation initiates by setting the starting values of each variable and by evaluating the holding current required to maintain the imposed membrane potential level. It is then possible to simulate current injection to reproduce either the experimental direct stimulation of the neurone or the physiological activation by the synaptic current flow. The subthreshold behaviour and the spiking activity, even during long-lasting current application, can be analysed. At every time step, the program calculates the amplitude of the individual currents and the ensuing changes; it also takes into account the accompanying K+ accumulation process in the perineuronal space and changes in Ca2+ load. It is shown that the computed time course of membrane potential must be filtered, in order to reproduce the limited bandwidth of the recording instruments, if it is to be compared with experimental measurements under current-clamp conditions. The membrane potential trajectory and single current data are written in files readable by graphic software. Finally, a screen image is obtained which displays in separate graphs the membrane potential time course, the synaptic current and the six ionic current flows. The simulated action potentials are comparable to the experimental ones as concerns overshoot amplitude and rising and falling rates. Therefore, this program is potentially helpful in investigating many aspects of neurone behaviour.
Sacchi, Oscar; Belluzzi, Ottorino; Canella, Rita; Fesce, R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1199229
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