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Results of DCM. ( A ) Bayesian Model Selection of all our models showing that model 14 is clearly the strongest. ( B ) Illustration and coupling parameters of our winning model (model 14). The net coupling parameter of the VIM>VIM self-connection is determined by the intrinsic coupling times modulation by dopamine (Ep.A × Ep.B = 0.921 × 1.002). MC = motor cortex.

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Results of DCM. ( A ) Bayesian Model Selection of all our models showing that model 14 is clearly the strongest. ( B ) Illustration and coupling parameters of our winning model (model 14). The net coupling parameter of the VIM>VIM self-connection is determined by the intrinsic coupling times modulation by dopamine (Ep.A × Ep.B = 0.921 × 1.002). MC = motor cortex.

We proceeded to investigate the estimated parameters of this winning model. The modulation by dopamine of the VIM>VIM self-connection as estimated by DCM (i.e. Ep.B parameter) is a scaling parameter of the fixed connection strength (i.e. Ep.A parameter) where a value >1 indicates an increase of the inhibitory self-connection strength ( Zeidman, 2015 ). A one-sample t -test showed that this scaling parameter was not significantly different from 1 across the whole group [ t (14); mean = 1.002, SD = 0.013, P = 0.48], indicating no significant modulatory effect of dopamine on the self-connection. This is perhaps at first surprising, because this model clearly outperformed a null-model with no modulatory effect of dopamine. However, this finding emphasizes the power of Bayesian model comparison: the combination of the absence of a significant directional effect at the parameter level across the group in context of positive model evidence indicates that this parameter is highly variable across individuals, yet meaningful. Indeed, we observed a significant relationship between the dopaminergic modulation of the inhibitory VIM self-connection (Ep.B) and the clinical dopamine response of resting tremor (R = 0.56, P = 0.03; Fig. 4 A). This indicates that dopamine increased the inhibitory VIM self-coupling most in patients with clinically more dopamine-responsive tremor.

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Brain–behaviour relationship. Figure displaying the correlation between the dopaminergic modulation of the inhibitory VIM self-connection (Ep.B) as estimated by DCM and the clinical dopamine responsiveness of resting tremor ( A ), bradykinesia ( B ), and rigidity ( C ) based on UPDRS differences score (OFF minus ON). Only dopamine responsiveness of tremor was significantly correlated with the Ep.B parameter, even when controlling for the dopamine responsiveness of the other two symptoms (partial correlation, R = 0.56, 0.046). *Significant effect.

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Brain–behaviour relationship. Figure displaying the correlation between the dopaminergic modulation of the inhibitory VIM self-connection (Ep.B) as estimated by DCM and the clinical dopamine responsiveness of resting tremor ( A ), bradykinesia ( B ), and rigidity ( C ) based on UPDRS differences score (OFF minus ON). Only dopamine responsiveness of tremor was significantly correlated with the Ep.B parameter, even when controlling for the dopamine responsiveness of the other two symptoms (partial correlation, R = 0.56, 0.046). *Significant effect.

Next, we tested whether this brain-behaviour relationship was specific for tremor. There were no correlations between the dopaminergic modulation of the inhibitory VIM self-connection (Ep.B) and the clinical dopamine response of bradykinesia (R = 0.06, P = 0.83; Fig. 4 B) or rigidity (R = 0.42, P = 0.11; Fig. 4 C). Furthermore, when we calculated partial correlations between each clinical symptom and dopaminergic modulation of the inhibitory VIM self-connection (Ep.B)—while controlling for the other two symptoms—we found a significant partial correlation only for resting tremor (R = 0.56, P = 0.046), but not for bradykinesia or rigidity.

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