simrun ❭ synaptic_strength_fitting ❭ PSPs ❭ get_summary_statistics

PSPs.get_summary_statistics¶

simrun.synaptic_strength_fitting.PSPs.get_summary_statistics(method='dynamic_baseline', merge_celltype_kwargs={}, ePSP_summary_statistics_kwargs={})¶

Calculate summary statistics of the PSP voltage and timing.

Parameters:¶

• method (str) –

  dynamic_baseline: a simulation without any synaptic activation is

  substracted from a simulation with cell activation. The maximum and timepoint of maximum is returned

  constant_baseline: the voltage at \(t = 110ms\) (i.e. directly before

  synapse activation) is considered as baseline and substracted from all voltages at all timepoints. The maximum and timepoint of the maximum after \(t = 110ms\) is returned.

• merge_celltype_kwargs (dict) – Additional keyword arguments to pass to merge_celltypes().

• ePSP_summary_statistics_kwargs (dict) – Additional keyword arguments to pass to ePSP_summary_statistics(). Options: (“threashold”, “tPSPStart”)

Returns:¶

A table of summary statistics.

Return type:¶

pd.DataFrame

Example:

>>> psp.get_summary_statistics(method='dynamic_baseline')
                    epspMean   epspStd   epspMed   epspMin   epspMax      tMean      tStd    tMed
celltype gAMPA gNMDA
L2      0.5   0.5   0.288331  0.141456  0.262698  0.100779  1.440870  15.509268  2.305882  15.050
        1.0   1.0    0.538904  0.273115  0.500306  0.129087  2.739804  15.696267  2.420884  15.150
        1.5   1.5    0.773226  0.395746  0.707955  0.181199  3.927223  15.741435  2.441578  15.175
        2.0   2.0    0.994781  0.513567  0.891020  0.108587  5.031582  15.881431  2.539182  15.350
...