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A D'Aguanno

Publications and source records attributed to A D'Aguanno.

3 recordsLinked to original sources
PubMed1989

A system model for investigating passive electrical properties of neurons.

Passive membrane properties of neurons, characterized by a linear voltage response to constant current stimulation, were investigated by busing a system model approach. This approach utilizes the derived expression for the input impedance of a network, which simulates the passive properties of neurons, to correlate measured intracellular recordings with the response of network models. In this study, the input impedances of different network configurations and of dentate granule neurons, were derived as a function of the network elements and were validated with computer simulations. The parameters of the system model, which are the values of the network elements, were estimated using an optimization strategy. The system model provides for better estimation of the network elements than the previously described signal model, due to its explicit nature. In contrast, the signal model is an implicit function of the network elements which requires intermediate steps to estimate some of the passive properties.

Animals↗
PubMed1989

Computation of the passive electrical parameters of neurons using a system model.

Time-domain analysis of voltage responses to current pulse stimulation has been used to estimate the electrotonic parameters of neurons using the signal model. Errors are likely to accumulate from various steps of the analysis due to noise and electrode artifacts. A system model, which has inherent noise immunity and filtering properties, is presented here. This model employs frequency-domain analysis of the input impedance of a neuronal model (an RC cable). The resistances and capacitances of the system model are estimated from the cell-input impedance using an optimization strategy. Using the expression for the input impedance, any specified number of equalizing time constants can be computed exactly. The accessibility to these equalizing time constants 1) provides greater insight into the charge equalization along the length and circumference of the cable, and 2) improves the estimation of all other passive parameters including the electrotonic length. Thus, the system model approach allows information to be extracted more directly and accurately than the signal model approach.

Animals↗