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Data
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Activity constraints on stable neuronal or network parameters (Olypher and Calabrese 2007)
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"In this study, we developed a general description of parameter combinations for which specified
characteristics of neuronal or network activity are constant.
Our approach is based on the implicit function theorem and is applicable
to activity characteristics that smoothly depend on parameters.
Such smoothness is often intrinsic to neuronal systems when they are in
stable functional states.
The conclusions about how parameters compensate each other, developed in this study, can thus be used even
without regard to the specific mathematical model describing a particular
neuron or neuronal network. ..."
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