Data from: NEURONpyxl: Fast, flexible, Python-integrated simulation of biophysical neural networks with complex plastic synapses

This dataset contains the data that are required to reproduce the figures
and results from Dickman et al. (2025, submitted). The manuscript
describes the development of a Python package that reads parameters from a
preformatted Excel spreadsheet to construct a conductance-based neuronal
network using the NEURON simulator. The manuscript demonstrates the
building of networks based on the formalism used to develop the Simulator
for Neural Networks and Action Potentials (SNNAP). The dataset contains
voltage and current traces from SNNAP and NEURON simulations, and data
from a parameter search that tuned parameters in a complex network.