Deep brain stimulation has state-dependent effects on motor connectivity in Parkinson's disease

Abstract

Subthalamic nucleus deep brain stimulation is an effective treatment for advanced Parkinson's disease; however, its therapeutic mechanism is unclear. Previous modelling of functional MRI data has suggested that deep brain stimulation has modulatory effects on a number of basal ganglia pathways. This work uses an enhanced data collection protocol to collect rare functional MRI data in patients with subthalamic nucleus deep brain stimulation. Eleven patients with Parkinson's disease and subthalamic nucleus deep brain stimulation underwent functional MRI at rest and during a movement task; once with active deep brain stimulation, and once with deep brain stimulation switched off. Dynamic causal modelling and Bayesian model selection were first used to compare a series of plausible biophysical models of the cortico-basal ganglia circuit that could explain the functional MRI activity at rest in an attempt to reproduce and extend the findings from our previous work. General linear modelling of the movement task functional MRI data revealed deep brain stimulation-associated signal increases in the primary motor and cerebellar cortices. Given the significance of the cerebellum in voluntary movement, we then built a more complete model of the motor system by including cerebellar-basal ganglia interactions, and compared the modulatory effects deep brain stimulation had on different circuit components during the movement task and again using the resting state data. Consistent with previous results from our independent cohort, model comparison found that the rest data were best explained by deep brain stimulation-induced increased (effective) connectivity of the cortico-striatal, thalamo-cortical and direct pathway and reduced coupling of subthalamic nucleus afferent and efferent connections. No changes in cerebellar connectivity were identified at rest. In contrast, during the movement task, there was functional recruitment of subcortical-cerebellar pathways, which were additionally modulated by deep brain stimulation, as well as modulation of local (intrinsic) cortical and cerebellar circuits. This work provides in vivo evidence for the modulatory effects of subthalamic nucleus deep brain stimulation on effective connectivity within the cortico-basal ganglia loops at rest, as well as further modulations in the cortico-cerebellar motor system during voluntary movement. We propose that deep brain stimulation has both behaviour-independent effects on basal ganglia connectivity, as well as behaviour-dependent modulatory effects.

Keywords: Parkinson’s disease; basal ganglia; connectivity; deep brain stimulation; functional MRI.

Figure 1

Experiment II and III model space: 12 competing models of the functional architecture underlying both the voluntary movement and resting states. For the movement functional MRI data, the main effect of voluntary movement (magenta arrow) drives M1 (DCM C-matrix); this driving input was not present when models were fit to the resting data. Black arrows represent the recruitment of directed effective connectivity during the behavioural state (DCM A-matrix). Green arrows represent modulation of effective connectivity by active DBS during the behavioural state (DCM B-matrix). All models share modulatory effects on basal ganglia pathways, which are highlighted in a lighter green. All models assume that the STN–thalamus (Tha) pathways exerts inhibition on the thalamus. All other pathways are excitatory. Crb = cerebellum; Put = putamen.

Figure 2

Clinical improvements following STN DBS. All scoring was performed off medication. Higher scores confer greater impairment. Total scores were broken down into hemibody scores (not including axial scores), and into subdomains of impairment. Blue dashed line indicates the maximum number of points in the respective subscale. The central mark in each box is the median, the edges of the box are the 25th and 75th percentiles respectively, the whiskers extend to the most extreme data points the algorithm considers to be not outliers. *P < 0.05. L = left; R = right.

Figure 3

Experiment I model comparisons and coupling parameters: BMS revealed that model 32 was the most likely generator of the data. The direction of modulatory effects on the various basal ganglia pathways are summarized by the green arrows. Red arrows represent excitatory effective connectivity, whereas blue arrows represent inhibitory effective connectivity. T-tests revealed significant differences in all coupling parameters associated with active DBS. Note the difference in scale for the indirect and hyperdirect pathways compared to the direct pathway. The central mark in each box is the median, the edges of the box are the 25th and 75th percentiles, respectively, the whiskers extend to the most extreme data points the algorithm considers to be not outliers. *P < 0.05 corrected for multiple comparisons using the Bonferroni procedure.

Figure 4

The effect of DBS on V_max and reaction time and regional BOLD activity. (A) The mean velocity plot for a single movement trial – on and off compared. Cue sounds at time = 0 with joystick in central position. Positive velocity occurs when subject moves joystick away from the central position towards their chosen direction, slows to 0 at maximal displacement, then velocity is negative as the handle is returned to the centre position. (B) Mean reaction time and V_max on and off stimulation. Note that reaction time differences are only trend significant. (C and D) Scatter plots of total UPDRS score, and bradykinesia sub-score against V_max. Maroon plots represent off values, blue plots represent on values. Two clusters were identified as significant following whole brain correction in (E) M1 hand area contralateral to movements, and (F) midline cerebellum encompassing left crus V, vermis and right crus V and VI. Second level SPMs overlaid on the MNI brain. SPMs are thresholded at a voxel level of P < 0.001 (uncorrected), cluster extent threshold = 0. Additional activations at this threshold can be seen in the supplementary motor area and midbrain (E), although these did not survive cluster-wise corrected significance.

Figure 5

Model comparisons and coupling parameters: model comparison revealed that model 10 was the most likely generator of the movement data. Green arrows represent the pathways modulated by DBS. Black arrows represent non-modulated pathways engaged during voluntary movement. Box plots represent the distribution (median, interquartile range) of coupling strength values on (blue) and off (red) DBS across 11 subjects. Paired t-tests of these values revealed statistically significant changes in coupling strengths in 7 of 10 pathways founds to be modulated by DBS. Coloured circles represent data points considered to be outliers. Model comparison revealed that model 1 was the most likely generator of the resting state data. Green arrows represent the pathways modulated by DBS. Black arrows represent non-modulated pathways engaged during rest. *P < 0.05 (Bonferroni corrected). Crb/CRB = cerebellum; Put/PUT = putamen; Tha/THA = thalamus.

Figure 6

Exploratory correlation analysis looking for relationships between coupling strength and measured peak movement velocity (V_max). Blue data points and lines of best fit represent DBS on, red data points and lines of best fit represent DBS off. Pearson’s r and P-values are reported in line. CRB = cerebellum; Put = putamen.