Deep brain stimulation has local effects on the target structure, but also global effects via distributed brain networks. Horn et al. show that modulating the activity of the subthalamic nucleus in patients with Parkinson’s disease normalizes signatures of widespread network connectivity towards those found in healthy controls.

Dopamine exerts modulatory signals on cortex-basal ganglia circuits to enable flexible motor control. Parkinson's disease is characterized by a loss of dopaminergic innervation in the basal ganglia leading to complex motor and non-motor symptoms. Clinical symptom alleviation through dopaminergic medication and deep brain stimulation in the subthalamic nucleus likely depends on a complex interplay between converging basal ganglia pathways. As a unique translational research platform, deep brain stimulation allows instantaneous investigation of functional effects of subthalamic neuromodulation in human patients with Parkinson's disease. The present study aims at disentangling the role of the inhibitory basal ganglia pathways in cognitive and kinematic aspects of automatic and controlled movements in healthy and parkinsonian states by combining behavioural experiments, clinical observations, whole-brain deep brain stimulation fibre connectivity mapping and computational modelling. Twenty patients with Parkinson's disease undergoing subthalamic deep brain stimulation and 20 age-matched healthy controls participated in a visuomotor tracking task requiring normal (automatic) and inverted (controlled) reach movements. Parkinsonian patients on and off deep brain stimulation presented complex patterns of reaction time and kinematic changes, when compared to healthy controls. Stimulation of cortico-subthalamic fibres was correlated with reduced reaction time adaptation to task demand, but not kinematic aspects of motor control or alleviation of Parkinson's disease motor signs. By using clinically, behaviourally and fibre tracking informed computational models, our study reveals that loss of cognitive adaptation can be attributed to modulation of the hyperdirect pathway, while kinematic depends on suppression of indirect pathway activity. Our findings suggest that hyperdirect and indirect pathways, converging in the subthalamic nucleus, are differentially involved in cognitive aspects of cautious motor preparation and kinematic gain control during motor performance. Subthalamic deep brain stimulation modulates but does not restore these functions. Intelligent stimulation algorithms could re-enable flexible motor control in Parkinson's disease when adapted to instantaneous environmental demand. Our results may inspire new innovative pathway-specific approaches to reduce side effects and increase therapeutic efficacy of neuromodulation in patients with Parkinson's disease.

Objective: Subthalamic nucleus deep brain stimulation (STN-DBS) in Parkinson's disease (PD) not only stimulates focal target structures but also affects distributed brain networks. The impact this network modulation has on non-motor DBS effects is not well-characterized. By focusing on the affective domain, we systematically investigate the impact of electrode placement and associated structural connectivity on changes in depressive symptoms following STN-DBS, which have been reported to improve, worsen, or remain unchanged. Methods: Depressive symptoms before and after STN-DBS surgery were documented in 116 patients with PD from 3 DBS centers (Berlin, Queensland, and Cologne). Based on individual electrode reconstructions, the volumes of tissue activated (VTAs) were estimated and combined with normative connectome data to identify structural connections passing through VTAs. Berlin and Queensland cohorts formed a training and cross-validation dataset used to identify structural connectivity explaining change in depressive symptoms. The Cologne data served as the test-set for which depressive symptom change was predicted. Results: Structural connectivity was linked to depressive symptom change under STN-DBS. An optimal connectivity map trained on the Berlin cohort could predict changes in depressive symptoms in Queensland patients and vice versa. Furthermore, the joint training-set map predicted changes in depressive symptoms in the independent test-set. Worsening of depressive symptoms was associated with left prefrontal connectivity. Interpretation: Fibers connecting the electrode with left prefrontal areas were associated with worsening of depressive symptoms. Our results suggest that for the left STN-DBS lead, placement impacting fibers to left prefrontal areas should be avoided to maximize improvement of depressive symptoms.

The subthalamic nucleus is part of a global stopping network that also includes the presupplementary motor area and inferior frontal gyrus of the right hemisphere. In Parkinson’s disease, subthalamic deep brain stimulation improves movement initiation and velocity, but its effect on stopping of ongoing movement is unknown. Here, we examine the relation between movement stopping and connectivity of stimulation volumes to the stopping network. Stop and go times were collected in 17 patients with Parkinson’s disease on and off subthalamic stimulation during visually cued initiation and termination of continuous, rotational movements. Deep brain stimulation contacts were localized; the stimulation volume computed and connectivity profiles estimated using an openly available, normative structural connectome. Subthalamic stimulation significantly increased stop times, which correlated with the connectivity of the stimulation volume to presupplementary motor area and inferior frontal gyrus of the right hemisphere. The robustness of this finding was validated using three separate analysis streams: voxel-wise whole-brain connectivity, region of interest connectivity and a tract-centred method. Our study sheds light on the role of the fronto-subthalamic inhibitory triangle in stopping of ongoing movements and may inspire circuit based adaptive stimulation strategies for control of stopping impairment, possibly reflected in stimulation-induced dyskinesia.

Previous computational model-based approaches for understanding the dynamic changes related to Parkinson's disease made particular assumptions about Parkinson's disease-related activity changes or specified dopamine-dependent activation or learning rules. Inspired by recent model-based analysis of resting-state fMRI, we have taken a data-driven approach. We fit the free parameters of a spiking neurocomputational model to match correlations of blood oxygen level-dependent signals between different basal ganglia nuclei and obtain subject-specific neuro-computational models of two subject groups: Parkinson patients and matched controls. When comparing mean firing rates at rest and connectivity strengths between the control and Parkinsonian model groups, several significant differences were found that are consistent with previous experimental observations. We discuss the implications of our approach and compare its results also with the popular "rate model" of the basal ganglia. Our study suggests that a model-based analysis of imaging data from healthy and Parkinsonian subjects is a promising approach for the future to better understand Parkinson-related changes in the basal ganglia and corresponding treatments. K E Y W O R D S BOLD correlations, data fitting, firing rate, spiking neuron model How to cite this article: Maith O, Villagrasa Escudero F, Dinkelbach HÜ, et al. A computational model-based analysis of basal ganglia pathway changes in Parkinson's disease inferred from resting-state fMRI.

A BS TRACT: Background: STN-DBS effectively treats motor symptoms of advanced PD. Nonmotor cognitive symptoms, such as impaired impulse control or decision making, may either improve or worsen with DBS. A potential mediating factor of DBS-induced modulation of cognition is the electrode position within the STN with regard to functional subareas of parallel motor, cognitive, and affective basal ganglia loops. However, to date, the volume of tissue activated and weighted stimulation of STN motor versus nonmotor territories are yet to be linked to differential DBS effects on cognition. Objectives: We aim to investigate whether STN-DBS influences risk-reward trade-off decisions and analyze its dependency on electrode placement. Methods: Seventeen PD patients ON and OFF STN-DBS and 17 age-matched healthy controls conducted a sequential decision-making task with escalating risk and reward. We computed the effect of STN-DBS on risk-reward trade-off decisions, localized patients' bilateral electrodes, and analyzed the predictive value of volume of tissue activated in STN motor and nonmotor territories on behavioral change. Results: We found that STN-DBS not only improves PD motor symptoms, but also normalizes overly risk-averse decision behavior in PD. Intersubject variance in electrode location could explain this behavioral change. Specifically, if STN-DBS activated preferentially STN motor territory, patients' risk-reward trade-off decisions more resembled those of healthy controls. Conclusions: Our findings support the notion of convergence of different functional circuits within the STN and imply a positive effect of well-placed STN-DBS on nonmotor cognitive functioning in PD.

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Motor adaptation tasks investigate our ability to adjust motor behaviors to an ever-changing and unpredictable world. Previous work has shown that punishment-based feedback delivered during a visuomotor adaptation task enhances error-reduction, whereas reward increases memory retention. While the neural underpinnings of the influence of punishment on the adaptation phase remain unclear, reward has been hypothesized to increase retention through dopaminergic mechanisms. We directly tested this hypothesis through pharmacological manipulation of the dopaminergic system. A total of 96 young healthy human participants were tested in a placebo-controlled double-blind between-subjects design in which they adapted to a 40° visuomotor rotation under reward or punishment conditions. We confirmed previous evidence that reward enhances retention, but the dopamine (DA) precursor levodopa (LD) or the DA antagonist haloperidol failed to influence performance. We reason that such a negative result could be due to experimental limitations or it may suggest that the effect of reward on motor memory retention is not driven by dopaminergic processes. This provides further insight regarding the role of motivational feedback in optimizing motor learning, and the basis for further decomposing the effect of reward on the subprocesses known to underlie motor adaptation paradigms.