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Lateralized Circuitry for Verbal Fluency Changes After Subthalamic Nucleus Deep Brain Stimulation

Kim, M. J.; Zuccaroli, I.; Del Bene, V. A.; Brinkerhoff, S. A.; Martin, R. C.; Olson, J. W.; Nelson, M. J.; Gonzalez, C. L.; Kamath, V.; Bentley, J. N.; Knight, R. T.; Walker, H. C.; Mills, K. A.

2025-01-05 neurology
10.1101/2025.01.03.25319977 medRxiv
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BackgroundSubthalamic nucleus deep brain stimulation (STN-DBS) improves motor symptoms but can be associated with subtle cognitive changes, including declines in verbal fluency (VF). Network-based mechanisms underlying stimulation-induced fluency declines are not fully understood. ObjectiveThis study investigates how STN-DBS stimulation locations interact with brain connectivity patterns, and whether this differentially drives VF changes. Methods20 patients with Parkinsons disease and unilateral STN-DBS were analyzed. Electrodes were localized with estimates for volume of tissue activation (VTA). VTAs were seeded in normative functional and structural connectomes to identify connectivity profiles correlating with VF changes (R-maps). Additionally, amongst the fibers passing through VTAs, a two-sample t-test assigned fibers associated with VF improvement or decline. ResultsVF declines occurred following unilateral left but not right STN-DBS. R-maps revealed that improvements correlated with greater connectivity to prefrontal structures in right hemisphere such as inferior and superior frontal gyrus, whereas declines localized to structures on the left. Fibers filtered from right VTAs were associated with VF improvements. Fibers from left VTAs were associated with declines, but the gradient of fiber t-scores were distributed across an anterior-posterior axis ranging from supplementary motor area to paracentral lobule. ConclusionUnilateral STN-DBS interacts with distributed cognitive networks that display strong hemispheric lateralization. Beyond the effects of implant hemisphere, our findings suggest that connectivity between local STN subregions to larger whole-brain networks impact VF performance, in a manner that could yield more tailored approaches to electrode targeting and clinical programming.

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