Table 4.

Example subject's neural parameters.

	Parametera	Description	Units	Expectation	Precision	Probability†
1	$A_{I11}$	Self-connection on lvF	None	−0.16	66.94	0.91
2	$A_{I22}$	Self-connection on ldF	None	−0.04	68.64	0.62
3	$A_{I33}$	Self-connection on rvF	None	−0.04	75.39	0.62
4	$A_{I44}$	Self-connection on rdF	None	−0.18	93.87	0.96
5	$A_{E21}$	lvF → ldF	Hz	0.42	233.16	1.00
6	$A_{E31}$	lvF → rvF	Hz	0.06	406.70	0.88
7	$A_{E12}$	ldF → lvF	Hz	−0.02	291.40	0.58
8	$A_{E42}$	ldF → rdF	Hz	0.57	145.30	1.00
9	$A_{E13}$	rvF → lvF	Hz	0.43	149.48	1.00
10	$A_{E43}$	rvF → rdF	Hz	0.10	102.21	0.86
11	$A_{E24}$	rdF → ldF	Hz	−0.03	483.41	0.73
12	$A_{E34}$	rdF → rvF	Hz	−0.21	858.90	1.00
13	$B_{I11}^{\left(2\right)}$	Pictures on lvF self	None	−0.47	41.73	1.00
14	$B_{I22}^{\left(2\right)}$	Pictures on ldF self	None	2.12	3.52	1.00
15	$B_{I33}^{\left(2\right)}$	Pictures on rvF self	None	0.13	16.78	0.70
16	$B_{I44}^{\left(2\right)}$	Pictures on rdF self	None	−0.16	19.21	0.68
17	$B_{I11}^{\left(3\right)}$	Words on lvF self	None	2.80	1.98	1.00
18	$B_{I22}^{\left(3\right)}$	Words on ldF self	None	0.27	9.98	0.81
19	$B_{I33}^{\left(3\right)}$	Words on rvF self	None	0.24	6.40	0.73
20	$B_{I44}^{\left(3\right)}$	Words on rdF self	None	0.11	13.41	0.71
21	$C_{11}$	Driving: task on lvF	Hz	−0.07	910.27	0.99
22	$C_{21}$	Driving: task on ldF	Hz	0.10	909.84	1.00
23	$C_{31}$	Driving: task on rvF	Hz	0.26	811.03	1.00
24	$C_{41}$	Driving: task on rdF	Hz	0.08	474.01	0.96

^aRegion names: 1 = lvF, 2 = ldF, 3 = rvF, 4 = rdF. Condition names (superscript on matrix $B_I$): 2 = Pictures, 3 = Words. †Probability that the posterior estimate of the parameter is not zero. For a parameter with marginal posterior density $N\left(\mu ,{\text{σ}}^2\right)$ this is given by $1–NCDF\left(abs\left(\mu \right),{\sigma }^2\right)$, where NCDF is the normal cumulative density function.