Table 2.

Regression equations for the regression lines describing the best fit of the data points in Figures 4A–C.

f(x) = a · ebx + c · edx	a	b	c	d
ATPNa+ (neuron)	6.37 × 107	−0.25	1.60 × 105	0.72
ATPCa++ (neuron)	2.61 × 108	0.17	3.647 × 105	0.69
f(x) = c· xa	c	a	R2/DF	p-value
ATPCa++ (|Branches|) 20% blocked	781,628	0.968	0.9996/11	«0.0001
ATPCa++ (Surface) 20% blocked	16,144	1.015	0.9949/11	«0.0001
ATPCa++ (|Branches|) 40% blocked	591,562	0.959	0.9986/11	« 0.0001
ATPCa++ (Surface) 40% blocked	13,335	1	0.9948/11	«0.0001

A double exponential (Figure 4A) and a power law function (Figures 4B,C) has been used for the regression fits.