Fig. 4: Comparison of features extracted from simulated signals.
From: A Python toolbox for neural circuit parameter inference
Distributions of features computed on simulation data are shown as a function of synaptic parameters of the LIF network model (E/I, \({\tau }_{{syn}}^{{exc}}\), \({\tau }_{{syn}}^{{inh}}\) and \({J}_{{syn}}^{{ext}}\)). Values of the parameters were binned into equal size intervals. In each bin, for a specific parameter, parameter values were within the limits of the bin, while the other synaptic parameters were free to vary without restriction. Each panel includes η2 as a measure of effect size (ANOVA model).
