simrun ❭ synaptic_strength_fitting ❭ PSPs ❭ get_optimal_g

PSPs.get_optimal_g¶

simrun.synaptic_strength_fitting.PSPs.get_optimal_g(measured_data, method='dynamic_baseline', merge_celltype_kwargs=None)¶

Calculate the optimal synaptic conductance such that the EPSP matches empirical data.

For each celltype (or merged celltype), the optimal synaptic conductance is calculated by linearly interpolating the relationship between the synaptic strength and each of the EPSP statistics (mean, median and maximum). This linear interpolation is cross-referenced with empirically observed statistics to infer the optimal synaptic conductance.

Parameters:¶

measured_data (pd.DataFrame) – A table containing the empirical EPSP statistics (mean, median and maximum) for each celltype. Must contain the keys: [EPSP_mean_measured, EPSP_median_measured, EPSP_max_measured] and the index celltype.
method (str) – dynamic_baseline or constant_baseline.
merge_celltype_kwargs (dict) – Additional keyword arguments to pass to merge_celltypes().

Returns:¶

A table of the optimal synaptic conductance for each celltype.

Return type:¶

pd.DataFrame