Nature Communications (May 2024)

Deep brain stimulation of symptom-specific networks in Parkinson’s disease

  • Nanditha Rajamani,
  • Helen Friedrich,
  • Konstantin Butenko,
  • Till Dembek,
  • Florian Lange,
  • Pavel Navrátil,
  • Patricia Zvarova,
  • Barbara Hollunder,
  • Rob M. A. de Bie,
  • Vincent J. J. Odekerken,
  • Jens Volkmann,
  • Xin Xu,
  • Zhipei Ling,
  • Chen Yao,
  • Petra Ritter,
  • Wolf-Julian Neumann,
  • Georgios P. Skandalakis,
  • Spyridon Komaitis,
  • Aristotelis Kalyvas,
  • Christos Koutsarnakis,
  • George Stranjalis,
  • Michael Barbe,
  • Vanessa Milanese,
  • Michael D. Fox,
  • Andrea A. Kühn,
  • Erik Middlebrooks,
  • Ningfei Li,
  • Martin Reich,
  • Clemens Neudorfer,
  • Andreas Horn

DOI
https://doi.org/10.1038/s41467-024-48731-1
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 16

Abstract

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Abstract Deep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson’s disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient’s symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.