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In the study, we attempt to quantify some of the important differences that exist between simulators, and we present a code generation approach that can solve the challenges caused by these differences. Furthermore, we highlight practical issues encountered while developing a convenient Python wrapper class for model code generated from the prototype language. This work is a step towards establishing a significant body of declarative models of neurons and identifies some of the issues related to interoperability of diverse neuroscience software.

Challenges of declarative modeling of conductance-based neurons in diverse simulation environments