. 2014 Aug 13;34(33):10963–10974. doi: 10.1523/JNEUROSCI.0764-14.2014

Table 1.

Mean (SD) of the model parameters

Parameter	Meaning	Aggregate fits						Individual fits
		SS		MS1		MS2		SS		MS1		MS2
		KOR	CON	KOR	CON	KOR	CON	KOR	CON	KOR	CON	KOR	CON
μ_r\|old	M(f_r\|old)	0.69	2.48	0.72	2.49	0.72	2.49	1.06	2.66	1.01	2.66	1.01	2.66
								(0.76)	(0.57)	(0.83)	(0.57)	(0.83)	(0.57)
μ_p\|old	M(f_p\|old)	=μ_r\|old	=μ_r\|old	0.51	2.18	0.51	2.18	=μ_r\|old	=μ_r\|old	0.83	2.54	0.92	2.53
										(0.66)	(1.20)	(0.69)	(1.15)
w	r(f_r, f_p)	= 1	= 1	= 0	= 0	1.00	1.00	= 1	= 1	= 0	= 0	0.82	0.62
												(0.35)	(0.43)
C	Judgment criterion	0.69	1.45	0.71	1.45	0.71	1.46	0.80	1.55	0.77	1.55	0.77	1.55
								(0.83)	(0.43)	(0.78)	(0.43)	(0.78)	(0.43)
b	ID intercept	6.51	6.23	6.45	6.18	6.45	6.18	6.53	6.22	6.53	6.22	6.53	6.22
								(0.90)	(1.47)	(0.89)	(1.47)	(0.89)	(1.47)
s	ID slope	0.68	0.31	= SS	= SS	= SS	= SS	0.57	0.25	= SS	= SS	= SS	= SS
								(0.55)	(0.21)
σ_p	SD(e_p)	1.88	2.36	1.89	2.36	1.88	2.36	1.59	1.73	1.59	1.73	1.58	1.72
								(0.32)	(0.38)	(0.32)	(0.38)	(0.32)	(0.38)
σ_f	SD(f_r), SD(f_p)	=1/√2	=1/√2	=1/√2	=1/√2	=1/√2	=1/√2	=1/√2	=1/√2	=1/√2	=1/√2	=1/√2	=1/√2
σ_r	SD(e_r)	= σ_f	= σ_f	= σ_f	= σ_f	= σ_f	= σ_f	= σ_f	= σ_f	= σ_f	= σ_f	= σ_f	= σ_f
M(e_p)	M priming task noise	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0
M(e_r)	M recognition task noise	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0
μ_r\|new	M(f_r\|new)	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0	= 0
μ_p\|new	M(f_p\|new)	=μ_r\|new	=μ_r\|new	= 0	= 0	= 0	= 0	=μ_r\|new	=μ_r\|new	= 0	= 0	= 0	= 0

A value preceded by an equals sign indicates that the value was fixed, otherwise it was free to vary in fitting the data.