Table 2 Bayesian model-averaged DCM parameters for endogenous and modulatory connections in the discovery sample

Connection	Ep	Cp	PP
Endogenous connections^a (A-matrix)
Habenula → Habenula	− 0.57	0.0016	1.00*
Habenula → PCC	− 0.18	0.0006	1.00*
Habenula → Hippocampus	<0.01	<0.0001	.00
Habenula → pOFC	<0.01	<0.0001	.00
PCC → PCC	− 0.49	0.0017	1.00*
PCC → Habenula	0.07	0.0005	.99*
Hippocampus → Hippocampus	− 0.44	0.0020	1.00*
Hippocampus → Habenula	− 0.09	0.0016	.93
pOFC → pOFC	− 0.27	0.0021	1.00*
pOFC → Habenula	0.13	0.0011	1.00*
Modulatory connections^b (B-matrix)
Challenge (CHAL)
Habenula → PCC	0.94	0.0121	1.00*
Habenula → Hippocampus	<0.01	<0.0001	.00
Habenula → pOFC	0.33	0.0052	1.00*
PCC → Habenula	<0.01	<0.0001	.00
Hippocampus → Habenula	< − 0.01	<0.0001	.00
pOFC → Habenula	<0.01	<0.0001	.00
Repeat (REP)
Habenula → PCC	0.44	0.0099	1.00*
Habenula → Hippocampus	< − 0.01	<0.0001	.00
Habenula → pOFC	< − 0.01	<0.0001	.00
PCC → Habenula	<0.01	<0.0001	.00
Hippocampus → Habenula	<0.01	<0.0001	.00
pOFC → Habenula	<0.01	<0.0001	.00

^aEndogenous parameters reflect the average effective coupling between regions across experimental conditions (context-independent).
^bModulatory parameters reflect the changes in effective coupling between regions induced by cognitive reappraisal (content-dependent).
^*Posterior probability (PP) exceeding .95 provides sufficient evidence for a non-zero group effect⁵⁶.
Cp posterior covariance, Ep posterior expectation, PCC posterior cingulate cortex, pOFC posterior orbitofrontal cortex, PP posterior probability.

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