Subthalamic Deep Brain Stimulation: Mapping Non-Motor Outcomes to Structural Connections

Abstract

In Parkinson's Disease (PD), deep brain stimulation of the subthalamic nucleus (STN-DBS) reliably improves motor symptoms, and the circuits mediating these effects have largely been identified. However, non-motor outcomes are more variable, and it remains unclear which specific brain circuits need to be modulated or avoided to improve them. Since numerous non-motor symptoms potentially respond to DBS, it is challenging to independently identify the circuits mediating each one of them. Data compression algorithms such as principal component analysis (PCA) may provide a powerful alternative. This study aimed at providing a proof of concept for this approach by mapping changes along extensive score batteries to a few anatomical fiber bundles and, in turn, estimating changes in individual scores based on stimulation of these tracts. Retrospective data from 56 patients with PD and bilateral STN-DBS was included. The patients had undergone comprehensive clinical assessments covering changes in appetitive behaviors, mood, anxiety, impulsivity, cognition, and empathy. PCA was implemented to identify the main dimensions of neuropsychiatric and neuropsychological outcomes. Using DBS fiber filtering, we identified the structural connections whose stimulation was associated with change along these dimensions. Then, estimates of individual symptom outcomes were derived based on the stimulation of these connections by inverting the PCA. Finally, changes along a specific non-motor score were estimated in an independent validation dataset (N = 68) using the tract model. Four principal components were retained, which could be interpreted to reflect (i) general non-motor improvement; (ii) improvement of mood and cognition and worsening of trait impulsivity; (iii) improvement of cognition; and (iv) improvement of empathy and worsening of impulsive-compulsive behaviors. Each component was associated with the stimulation of spatially segregated fiber bundles connecting regions of the frontal cortex with the subthalamic nucleus. The extent of stimulation of these tracts was able to explain significant amounts of variance in outcomes for individual symptoms in the original cohort (circular analysis), as well as in the rank of depression outcomes in the independent validation cohort. Our approach represents an innovative concept for mapping changes along extensive score batteries to a few anatomical fiber bundles and could pave the way toward personalized deep brain stimulation.

Keywords: Parkinson's disease; deep brain stimulation; non‐motor symptoms; structural connectivity; subthalamic nucleus.

FIGURE 1

Development of the four‐tract model. (A) Principal component analysis (PCA) was performed to identify the principal dimensions of non‐motor outcomes. Then, the fiber tracts whose stimulation was associated with variance along these four dimensions were identified using DBS fiber filtering. (B) For each fiber in a normative pathway atlas, the probabilistic impact of each E‐field on the fiber was estimated by taking the peak E‐field value along the fiber. (C) These values were then correlated with PC scores. Hence, for each PC, positive R‐values were attributed to fibers preferentially stimulated in patients who scored high on this given PC, while negative R‐values were attributed to fibers preferentially stimulated in patients who scored low on this given PC. (D) The top 1000 positive and negative fibers (strongest positive and negative R‐values) were retained as part of the four‐tract model. (E) Overlap between E‐fields and these fibers was used to obtain estimates of PC scores, which were then mapped back to estimates for the original variables by applying PCA weights (F). BDI, Beck depression inventory; BIS‐11, Barratt impulsiveness scale; EQ, empathy quotient; GAI, geriatric anxiety inventory; MMSE, mini‐mental state examination; MoCA, Montreal cognitive assessment; QUIP‐RS, questionnaire for impulsive and compulsive behaviors rating scale; SAS, Starkstein apathy scale.

FIGURE 2

Electrode and active contact locations for the main cohort (N = 56). Electrode (A) and active contact locations (B) are shown relative to basal ganglia structures (derived from the DISTAL atlas, Ewert et al. 2018), overlaid on the Big Brain template (Amunts et al. ; Xiao et al. ; superior view). (C, D) Axial and coronal views of the N‐map, representing the number of stimulation volumes (i.e., E‐fields thresholded above 200 V/m, Åström et al. 2015) covering each voxel. Greater overlap between the stimulation volumes was seen in the dorsolateral motor region of the STN. GPe, external pallidum; GPi, internal pallidum; RN, red nucleus; STN, subthalamic nucleus.

FIGURE 3

Structural connectivity results. (A) Four principal components were retained which could be interpreted as reflecting general non‐motor improvement (PC1), improvement in mood and cognition and worsening in trait impulsivity (PC2), improvement in cognition (PC3), and improvement of empathy and worsening in impulsive‐compulsive behaviors (PC4). These principal components were associated with spatially segregated fiber tracts linking the subthalamic region and frontal cortices (i.e., with fiber tract profiles peaking in different locations; see also unthresholded fiber tract profiles available as Figure S2). The positive and negative fiber tracts are displayed in (B) for each of the PCs (positive fibers in the respective color, and negative fibers in white), while (D) shows all positive fiber tracts together (view from postero‐superior). (C) illustrates the correlation between empirical PC scores and PC scores as estimated based on the overlap of E‐fields with the tracts.

FIGURE 4

Estimation of the individual score outcomes. Correlations between estimated and empirical outcomes for each of the 10 clinical scores. Estimates of outcomes were derived based on the four‐tract model. Because these estimates were derived in a circular fashion (see text for detail), we refrain from reporting p‐values.

FIGURE 5

Out‐of‐sample validation of the four‐tract model. An independent cohort of 68 PD patients with bilateral STN‐DBS and depression assessment (BDI) was used as a validation cohort. The procedure used to derive estimates of depression outcomes based on the four‐tract model is illustrated for two example patients (top and bottom rows). Estimates of PC scores were first obtained based on the overlap of E‐fields with the previously identified fiber tracts. Note that volumes of tissue activated (VTAs) are used for visualization only, while unthresholded E‐fields were used for analysis (see Section 2). Then, the estimates of PC scores were multiplied with PCA weights to obtain estimates of individual symptom outcomes. Across all patients, the rank correlation between estimated and empirical BDI improvements was weak but statistically significant.