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Cited by 118Neurological disorders and treatmentsObsessive-Compulsive Spectrum DisordersTranscranial Magnetic Stimulation Studies

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

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Rajamani, Nanditha, Friedrich, Helen, Butenko, Konstantin, Dembek, Till, Lange, Florian, Navrátil, Pavel, Zvarova, Patricia, Hollunder, Barbara +22 more·2024·Nature Communications
DOI 10.1038/s41467-024-48731-1PMC PMC11143329
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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.

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  • Preoperative tractography can guide deep brain stimulation (DBS) or MR-guided focused ultrasound (MRgFUS) planning, identify the structural connectivity of the volume of tissue activated, and help avoid pathways associated with motor, cognitive, or mood-related adverse effects.

    “Preoperative tractography can guide deep brain stimulation (DBS) or MR-guided focused ultrasound (MRgFUS) planning, identify the structural connectivity of the volume of tissue activated, and help avoid pathways associated with motor, cognitive, or mood-related adverse effects (Pujol et al., 2017; Rajamani et al., 2024; Vanegas-Arroyave et al., 2016).”

    From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Rajamani et al., 2024

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  1. [1]Deuschl, G. et al. A randomized trial of deep-brain stimulation for Parkinson’s disease. N. Engl. J. Med. 355, 896–908 (2006). 16943402
  2. [2]Fasano, A., Aquino, C. C., Krauss, J. K., Honey, C. R. & Bloem, B. R. Axial disability and deep brain stimulation in patients with Parkinson disease. Nat. Rev. Neurol. 11, 98–110 (2015). 25582445
  3. [3]Schrader, C. et al. GPi-DBS may induce a hypokinetic gait disorder with freezing of gait in patients with dystonia. Neurology 77, 483–488 (2011). 21775741
  4. [4]Barbe, M. T. et al. Deep brain stimulation for freezing of gait in Parkinson’s disease with early motor complications. Mov. Disord. 35, 82–90 (2020). 31755599
  5. [5]Yin, Z. et al. Persistent adverse effects following different targets and periods after bilateral deep brain stimulation in patients with Parkinson’s disease. J. Neurol. Sci. 393, 116–127 (2018). 30153572
  6. [6]Aviles-Olmos, I. et al. Long-term outcome of subthalamic nucleus deep brain stimulation for Parkinson’s disease using an MRI-guided and MRI-verified approach. J. Neurol. Neurosurg. Psychiatry 85, 1419–1425 (2014). 24790212 PMC4451170
  7. [7]Bejjani, B.-P. et al. Bilateral subthalamic stimulation for Parkinson’s disease by using three-dimensional stereotactic magnetic resonance imaging and electrophysiological guidance. J. Neurosurg. 92, 615–625 (2000). 10761650
  8. [8]Picillo, M., Lozano, A. M., Kou, N., Puppi Munhoz, R. & Fasano, A. Programming deep brain stimulation for Parkinson’s disease: the toronto western hospital algorithms. Brain Stimul. 9, 425–437 (2016). 26968806
  9. [9]Hassler, R., Riechert, T., Mundinger, F., Umbach, W. & Ganglberger, J. A. Physiological observations in stereotaxic operations in extrapyramidal motor disturbances. Brain 83, 337–350 (1960). 13852002
  10. [10]McGregor, M. M. & Nelson, A. B. Circuit mechanisms of Parkinson’s disease. Neuron 101, 1042–1056 (2019). 30897356
  11. [11]Strotzer, Q. D. et al. Deep brain stimulation: Connectivity profile for bradykinesia alleviation. Ann. Neurol. 85, 852–864 (2019). 30937956
  12. [12]Akram, H. et al. Subthalamic deep brain stimulation sweet spots and hyperdirect cortical connectivity in Parkinson’s disease. NeuroImage 158, 332–345 (2017). 28711737 PMC6581538
  13. [13]Ni, Z., Pinto, A. D., Lang, A. E. & Chen, R. Involvement of the cerebellothalamocortical pathway in Parkinson disease. Ann. Neurol. 68, 816–824 (2010). 21194152
  14. [15]Sturman, M. M., Vaillancourt, D. E., Metman, L. V., Bakay, R. A. E. & Corcos, D. M. Effects of subthalamic nucleus stimulation and medication on resting and postural tremor in Parkinson’s disease. Brain 127, 2131–2143 (2004). 15240437
  15. [16]Li, N. et al. A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nat. Commun. 11, 3364 (2020). 32620886 PMC7335093
  16. [17]Grill, W. M., Snyder, A. N. & Miocinovic, S. Deep brain stimulation creates an informational lesion of the stimulated nucleus. NeuroReport 15, 1137–1140 (2004). 15129161
  17. [18]Hollunder, B. & Horn, A. Mapping the dysfunctome provides an avenue for targeted brain circuit therapy. Nat. Neurosci. 10.1038/s41593-024-01572-z (2024). 38388735 · DOI
  18. [19]Horn, A. et al. Connectivity Predicts Deep Brain Stimulation Outcome in Parkinson Disease. Ann. Neurol. 82, 67–78 (2017). 28586141 PMC5880678
  19. [20]Treu, S. et al. Deep brain stimulation: Imaging on a group level. NeuroImage 219, 117018 (2020). 32505698
  20. [22]Neudorfer, C. et al. Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. NeuroImage 268, 119862 (2023). 36610682 PMC10144063
  21. [23]Irmen, F. et al. Left prefrontal impact links subthalamic stimulation with depressive symptoms. Ann. Neurol. 10.1002/ana.25734 (2020). 32239535 · DOI
  22. [24]Al-Fatly, B. et al. Connectivity profile of thalamic deep brain stimulation to effectively treat essential tremor. Brain J. Neurol. 18, 130 (2019). 31377766
  23. [25]Horn, A. et al. Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia. Proc. Natl Acad. Sci. 119, e2114985119 (2022). 35357970 PMC9168456
  24. [26]Hollunder, B. et al. Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation. Nat. Neurosci. 27, 573–586 (2024). 38388734 PMC10917675
  25. [27]Hollunder, B. et al. Toward personalized medicine in connectomic deep brain stimulation. Prog. Neurobiol. 210, 102211 (2022). 34958874
  26. [28]Middlebrooks, E. H. et al. Neuroimaging advances in deep brain stimulation: review of indications, anatomy, and brain connectomics. Am. J. Neuroradiol. 41, 1558–1568 (2020). 32816768 PMC7583111
  27. [29]Baldermann, J. C. et al. Connectivity profile predictive of effective deep brain stimulation in obsessive-compulsive disorder. Biol. Psychiatry 85, 735–743 (2019). 30777287
  28. [30]Coenen, V. A. et al. The dentato-rubro-thalamic tract as the potential common deep brain stimulation target for tremor of various origin: an observational case series. Acta Neurochir. (Wien.) 18, 130–14 (2020). PMC7156360 31997069
  29. [31]Helmich, R. C., Janssen, M. J. R., Oyen, W. J. G., Bloem, B. R. & Toni, I. Pallidal dysfunction drives a cerebellothalamic circuit into Parkinson tremor. Ann. Neurol. 69, 269–281 (2011). 21387372
  30. [32]Helmich, R. C., Hallett, M., Deuschl, G., Toni, I. & Bloem, B. R. Cerebral causes and consequences of parkinsonian resting tremor: a tale of two circuits?. Brain J. Neurol. 135, 3206–3226 (2012). PMC3501966 22382359
  31. [33]Kühn, A. A. et al. Pathological synchronisation in the subthalamic nucleus of patients with Parkinson’s disease relates to both bradykinesia and rigidity. Exp. Neurol. 215, 380–387 (2009). 19070616
  32. [34]Mazzone, P., Sposato, S., Insola, A. & Scarnati, E. The clinical effects of deep brain stimulation of the pedunculopontine tegmental nucleus in movement disorders may not be related to the anatomical target, leads location, and setup of electrical stimulation. Neurosurgery 73, 894 (2013). 23867299
  33. [35]Zrinzo, L. et al. Stereotactic localization of the human pedunculopontine nucleus: atlas-based coordinates and validation of a magnetic resonance imaging protocol for direct localization. Brain 131, 1588–1598 (2008). 18467343
  34. [36]Golestanirad, L., Elahi, B., Graham, S. J., Das, S. & Wald, L. L. Efficacy and Safety of Pedunculopontine Nuclei (PPN) Deep Brain Stimulation in the Treatment of Gait Disorders: A Meta-Analysis of Clinical Studies. Can. J. Neurol. Sci. J. Can. Sci. Neurol. 43, 120–126 (2016). 26786642
  35. [37]Vorwerk, J., Oostenveld, R., Piastra, M. C., Magyari, L. & Wolters, C. H. The FieldTrip-SimBio pipeline for EEG forward solutions. Biomed. Eng. OnLine 17, 37 (2018). 29580236 PMC5870695
  36. [38]Butenko, K., Bahls, C., Schröder, M., Köhling, R. & van Rienen, U. OSS-DBS: Open-source simulation platform for deep brain stimulation with a comprehensive automated modeling. PLoS Comput. Biol. 16, e1008023 (2020). 32628719 PMC7384674
  37. [39]Dembek, T. A. et al. Directional DBS increases side‐effect thresholds—A prospective, double‐blind trial. Mov. Disord. 32, 1380–1388 (2017). 28843009
  38. [40]Timmermann, L. et al. Multiple-source current steering in subthalamic nucleus deep brain stimulation for Parkinson's disease (the VANTAGE study): a non-randomised, prospective, multicentre, open-label study. Lancet Neurol. 14, 693–701 (2015). 26027940
  39. [41]Roediger, J. et al. Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm. Lancet Digit. Health 5, e59–e70 (2023). 36528541
  40. [42]Roediger, J. et al. StimFit—a data-driven algorithm for automated deep brain stimulation programming. Mov. Disord. 37, 574–584 (2022). 34837245
  41. [43]Makris, N. et al. Variability and anatomical specificity of the orbitofrontothalamic fibers of passage in the ventral capsule/ventral striatum (VC/VS): precision care for patient-specific tractography-guided targeting of deep brain stimulation (DBS) in obsessive compulsive disorder (OCD). Brain Imaging Behav. 10, 1054–1067 (2016). 26518214 PMC4851930
  42. [45]Coenen, V. A. et al. Machine learning—aided personalized DTI tractographic planning for deep brain stimulation of the superolateral medial forebrain bundle using HAMLET. Acta Neurochir. (Wien.) 161, 1559–1569 (2019). 31144167 PMC6616222
  43. [46]Hollunder, B., Ganos, C. & Horn, A. Deep Brain Stimulation: From Sweet Spots to Sweet Networks? Biol. Psychiatry Cogn. Neurosci. Neuroimaging 6, 939–941 (2021). 34625219
  44. [47]Merk, T. et al. Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation. Exp. Neurol. 351, 113993 (2022). 35104499 PMC10521329
  45. [48]Horn, A. et al. Teaching NeuroImages: In vivo visualization of Edinger comb and Wilson pencils. Neurology 92, e1663–e1664 (2019). 30936236 PMC6448452
  46. [49]Alho, E. J. L. et al. The Ansa Subthalamica: A Neglected Fiber Tract. Mov. Disord. 35, 75–80 (2020). 31758733
  47. [50]Petersen, M. V. et al. Holographic Reconstruction of Axonal Pathways in the Human Brain. Neuron 104, 1056–1064.e3 (2019). 31708306 PMC6948195
  48. [51]Horn, A. et al. Deep brain stimulation induced normalization of the human functional connectome in Parkinson’s disease. Brain J. Neurol. 18, 130–15 (2019). 31412106
  49. [52]Wang, Q. et al. Normative vs. patient-specific brain connectivity in deep brain stimulation. NeuroImage 224, 117307 (2020). 32861787
  50. [53]Horn, A. & Fox, M. D. Opportunities of Connectomic Neuromodulation. NeuroImage 117180 (2020) 10.1016/j.neuroimage.2020.117180. PMC7847552 32702488 · DOI · Paper page
  51. [54]Ewert, S. et al. Optimization and comparative evaluation of nonlinear deformation algorithms for atlas-based segmentation of DBS target nuclei. NeuroImage 184, 586–598 (2019). 30267856 PMC6506227
  52. [55]Oxenford, S. et al. WarpDrive: Improving spatial normalization using manual refinements. Med. Image Anal. 91, 103041 (2024). 38007978 PMC10842752
  53. [56]Schönecker, T., Kupsch, A., Kühn, A. A., Schneider, G.-H. & Hoffmann, K.-T. Automated optimization of subcortical cerebral MR imaging−atlas coregistration for improved postoperative electrode localization in deep brain stimulation. Am. J. Neuroradiol. 30, 1914–1921 (2009). 19713324 PMC7051288
  54. [57]Husch, A., V. Petersen, M., Gemmar, P., Goncalves, J. & Hertel, F. PaCER - A fully automated method for electrode trajectory and contact reconstruction in deep brain stimulation. NeuroImage Clin. 17, 80–89 (2018). 29062684 PMC5645007
  55. [58]Lofredi, R. et al. Interrater reliability of deep brain stimulation electrode localizations. NeuroImage 262, 119552 (2022). 35981644
  56. [59]Gunalan, K. et al. Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example. PLOS ONE 12, e0176132 (2017). 28441410 PMC5404874
  57. [60]Howell, B. & McIntyre, C. C. Analyzing the tradeoff between electrical complexity and accuracy in patient-specific computational models of deep brain stimulation. J. Neural Eng. 13, 036023 (2016). 27172137 PMC5259803
  58. [61]Åström, M. et al. Method for patient-specific finite element modeling and simulation of deep brain stimulation. Med. Biol. Eng. Comput.47, 21–28 (2009). 18936999
  59. [62]Horn, A. & Kühn, A. A. Lead-DBS: A toolbox for deep brain stimulation electrode localizations and visualizations. NeuroImage 107, 127–135 (2015). 25498389
  60. [63]Avants, B. B., Epstein, C. L., Grossman, M. & Gee, J. C. Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 12, 26–41 (2008). 17659998 PMC2276735
  61. [64]Ewert, S. et al. Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity. NeuroImage 170, 271–282 (2018). 28536045
  62. [65]Poldrack, R. A., Huckins, G. & Varoquaux, G. Establishment of Best Practices for Evidence for Prediction: A Review. JAMA Psychiatry77, 534–540 (2020). PMC7250718 31774490
  63. [66]Butenko, K. et al. Linking profiles of pathway activation with clinical motor improvements – A retrospective computational study. NeuroImage Clin. 36, 103185 (2022). 36099807 PMC9474565
  64. [67]Zhang, S. & Arfanakis, K. Evaluation of standardized and study-specific diffusion tensor imaging templates of the adult human brain: Template characteristics, spatial normalization accuracy, and detection of small inter-group FA differences. NeuroImage 172, 40–50 (2018). 29414497 PMC5910210
  65. [68]Butson, C. R. & McIntyre, C. C. Tissue and electrode capacitance reduce neural activation volumes during deep brain stimulation. Clin. Neurophysiol. 116, 2490–2500 (2005). 16125463 PMC3653320
  66. [69]McIntyre, C. C., Richardson, A. G. & Grill, W. M. Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle. J. Neurophysiol. 87, 995–1006 (2002). 11826063
  67. [70]Fox, C. A., Rafols, J. A. & Cowan, W. M. Computer measurements of axis cylinder diameters of radial fibers and “comb” bundle fibers. J. Comp. Neurol. 159, 201–223 (1975). 803515
  68. [71]Mathai, A., Wichmann, T. & Smith, Y. More than meets the Eye—Myelinated axons crowd the subthalamic nucleus. Mov. Disord. 28, 1811–1815 (2013). 23852565 PMC3825839
  69. [72]Verhaart, W. J. C. Fiber analysis of the basal ganglia. J. Comp. Neurol. 93, 425–440 (1950). 14803571
  70. [75]Coulombe, V. et al. A Topographic Atlas of the Human Brainstem in the Ponto-Mesencephalic Junction Plane. Front. Neuroanat. 15, 627656 (2021). 34483849 PMC8414831

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Authors
Rajamani, N., Friedrich, H., Butenko, K., Dembek, T., Lange, F., Navrátil, P., Zvarova, P., Hollunder, B., de Bie, R. M. A., Odekerken, V. J. J., Volkmann, J., Xu, X., Ling, Z., Yao, C., Ritter, P., Neumann, W.-J., Skandalakis, G. P., Komaitis, S., Kalyvas, A., Koutsarnakis, C., Stranjalis, G., Barbe, M., Milanese, V., Fox, M. D., Kühn, A. A., Middlebrooks, E., Li, N., Reich, M., Neudorfer, C., & Horn, A.
Affiliations
  • Humboldt-Universität zu Berlin (DE)
  • Brigham and Women's Hospital (US)
  • Universitätsklinikum Würzburg (DE)
  • Amsterdam UMC Location University of Amsterdam (NL)
  • Chinese PLA General Hospital (CN)
  • Dartmouth–Hitchcock Medical Center (US)
  • Nottingham University Hospitals NHS Trust (GB)
  • University Health Network (CA)
  • National and Kapodistrian University of Athens (GR)
  • University of Cologne (DE)
  • Beneficência Portuguesa de São Paulo (BR)
  • Mayo Clinic in Florida (US)
Corresponding author
Rajamani, Nanditha
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2024-05-31
Volume
15
Issue
1
Pages
4662-4662
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-024-48731-1
PMC
PMC11143329
OpenAlex
W4399204276
Cited by
118
References
4
Citations by year
2026: 53 · 2025: 54 · 2024: 11
FWCI
31.57
Type
journal article
Language
en
Update notices
correction (2024-08-20)
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Pure Amsterdam UMC (publishedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Deutsche Forschungsgemeinschaft (424778381 – TRR 295)
Topics
  • Health Sciences › Medicine › Neurology › Neurological disorders and treatments
  • Social Sciences › Psychology › Clinical Psychology › Obsessive-Compulsive Spectrum Disorders
  • Life Sciences › Neuroscience › Neurology › Transcranial Magnetic Stimulation Studies
Keywords
deep brain stimulation, Parkinson's disease, white matter tracts, tremor, bradykinesia, rigidity, axial symptoms, supplementary motor area, primary motor cortex, cerebellum, brainstem, premotor cortex
MeSH terms
Aged, Algorithms, Cerebellum, Female, Humans, Male, Middle Aged, Motor Cortex, Muscle Rigidity, Parkinson Disease, Tremor, Cohort Studies, Treatment Outcome, Hypokinesia, Deep Brain Stimulation, White Matter

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