This work reports a transfer function-based approach to characterizing the operation of single neuronal cells in terms of the instantaneous frequency of the input and output signals. We adopt the leaky integrate-and-fire model. The transfer function is obtained by performing successive numeric-computational simulations and statistical regressions. Several interesting results are reported, including the identification  of linearity in the transfer functions , as well as the identification of regions in the parameter space characterized by sharper transfer functions  .
This work reports a transfer function-based approach to characterizing the operation of single neuronal cells in terms of the instantaneous frequency of the input and output signals. We adopt the leaky integrate-and-fire model. The transfer relationship is obtained by performing successive numeric-computational simulations and statistical regressions. Several interesting results are reported, including the identification and characterization of linearity in the transfer relationship , as well as the identification of regions in the parameter space characterized by sharper transfer functions . These properties can be used to facilitate simulations under certain circumstances and to validate the model by comparison with biological results .
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function
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and characterization
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functions
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. These properties can be used to facilitate simulations under certain circumstances and to validate the model by comparison with biological results