Table 5. Regression parameters corresponding to linear and segmented fit for firing properties of CA1 pyramidal neurons along the V–D axis.

	Linear regression				Segmented regression
										Breakpoint		Slopes comparison
	Cons.	Slope	Adj. R2	P-value	Cons.	Slope 1	Slope 2	Adj. R2	P-value	Location	P-value	Diff.	P-value
AP threshold (mV)	-48.53	0.81	0.29	<0.0001	-50.7	-1.72	-0.58	0.3	<0.0001	-1.7	0.09	-1.13	0.1
AP hw (ms)	1.14	0.052	0.11	<0.0001	0.65	-0.15	0.1	0.18*	<0.0001	-2	0.0001†	-0.26	0.001‡
AP amplitude (mV)	95	0.079	0.035	0.0274	105.1	5	-0.3	0.08*	0.003	-1.7	0.002†	5.3	0.012
AP max dV/dt (mv/ms)	382.2	-10.2	0.05	0.012	625	-90.2	-32.7	0.25	0.0001	-1.8	0.0001	122.9	0.0001‡
Firing freq. (500 pA) (Hz)	26.5	-2.97	0.32	<0.0001	32.7	-0.01	-5.2	0.37*	<0.0001	-0.7	0.27	5.23	0.005‡
Firing freq. (250 pA) (Hz)	14.39	-3.74	0.47	<0.0001	19.4	-1.36	-5.72	0.49*	<0.0001	-0.633	0.376	4.35	0.011‡
SFA	2.23	0.2	0.26	<0.0001	2.3	0.24	0.17	0.25	<0.0001	-0.52	0.897	0.069	0.61

V–D gradient in firing properties of CA1 pyramidal neurons was fitted by linear and segmented regressions. Linear regression had two factors: constant value (Cons.) and slope. Segmented regression had three factors: constant, slope of line one (slope 1) and slope of line two (slope 2). V–D change in a few electrophysiological properties fitted better with segmented regressions than linear regressions

^*significant increase in Adjusted R²;

^†significant estimation of change point;

^‡significant difference between the slopes of two lines in the segmented regression.