Friedrich et al. 2023

High-resolution brain atlas for deep brain stimulation imaging

Poster PDF

Mesoscale Brain Mapping Symposium 2023 | Poster Abstract

A High Resolution Brain Atlas for Deep Brain Stimulation Imaging

Helen Friedrich1,2, Simon Oxenford3, Eduardo J. L. Alho4, Brian L. Edlow5,6, Clemens Neudorfer1,3,7, Andreas Horn1,3,5,7

Contact: hfriedrich@bwh.harvard.edu; ahorn1@bwh.harvard.edu

1 Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women’s Hospital, Harvard Medical School, Boston MA 02115, USA

2 Julius-Maximilian-University Wuerzburg, Germany

3 Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Department of Neurology, 10117 Berlin, Germany

4 Clinic of Pain and Functional Neurosurgery, São Paulo, Brazil

5 Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA

6 Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA

7 Brain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA

Background

The success of deep brain stimulation therapy is defined by the exact placement of electrodes in relation to their targets. Overlaps between stimulation volumes and anatomical structures may account for clinical outcomes. To investigate this, precise definitions of anatomical structures are critical. These target structures frequently comprise anatomical structures or tracts that are often not discernable on conventional neuroimaging.

Methods

We aimed to create a high-resolution atlas including both grey and white matter based on a 100-micron ex-vivo MRI brain scan (Edlow et al., 2019). Histological data, postmortem fiber dissections, and expert opinions of clinicians and anatomists were used to inform and enrich anatomical validity. Segmentations of gray- (n=15) and white- (n=16) matter structures at the level of the subthalamus were carried out on the high resolution MRI scan and converted into MNI ICBM 2009b NLIN ASYM space. This spatial transform from MRI native to template space was carried out using a manually curated warpfield that accounts for proper definitions of target structures in standard space.

Results & Conclusions

The main result of this work should be seen in a high-resolution atlas of the human subthalamus comprising a total of 31 gray and white matter regions per hemisphere. Together with the ex-vivo MRI template and a precise manual registration to MNI space, this dataset is deformable to patient MRIs and can be readily applied in DBS imaging studies.

Goede et al. (MDS 2023)

Connectomic DBS informed multifocal transcranial direct current stimulation (tDCS) in Parkinson’s Disease:

a crossover double-blinded study

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Affiliations

Department of Neurology with Experimental Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany

Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Junior Clinician Scientist Program, Berlin, Germany

Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

MGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA

Bernstein Center for Computational Neuroscience, Humboldt-Universität, Berlin, Germany

NeuroCure, Exzellenzcluster, Charité-Universitätsmedizin Berlin, Berlin, Germany

DZNE, German Center for Neurodegenerative Diseases, Berlin, Germany

Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany

Dr. Goede is participant in the BIH Charité Junior Clinician Scientist Program

funded by the Charité – Universitätsmedizin Berlin, and the Berlin Institute of Health at Charité (BIH).

Dr. Lofredi is participant in the BIH Charité Clinician Scientist Program

funded by the Charité – Universitätsmedizin Berlin, and the Berlin Institute of Health at Charité (BIH).

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 424778381 – TRR 295 and Emmy Noether Stipend 410169619 to A.H.

References

[1] Fox MD, Buckner RL, Liu H, Chakravarty MM, Lozano AM, Pascual-Leone A. Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases. Proceedings of the National Academy of Sciences. 2014;111:E4367–E4375.

[2] Horn A, Reich M, Vorwerk J, et al. Connectivity Predicts deep brain stimulation outcome in Parkinson disease: DBS Outcome in PD.  Ann Neurol. 2017;82:67–78.

[3] Sobesky L, Goede L, Odekerken VJJ, et al. Subthalamic and pallidal deep brain stimulation: are we modulating the same network? Brain. 2022;145:251–262.

[4] Fischer DB, Fried PJ, Ruffini G, et al. Multifocal tDCS targeting the resting state motor network increases cortical excitability beyond traditional tDCS targeting unilateral motor cortex. NeuroImage. 2017;157:34–44.

Hollunder et al. (OHBM 2023)

Mapping Dysfunctional Circuits in the Frontal Cortex Using Deep Brain Stimulation

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Affiliations

  1. Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
  2. Einstein Center for Neurosciences Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
  3. Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
  4. Movement Disorders and Neuromodulation Centre, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
  5. Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
  6. Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  7. Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin Berlin, Berlin, Germany
  8. Grenoble Alpes, Grenoble, France
  9. Inserm, U1216, Grenoble Institut des Neurosciences, Grenoble, France
  10. Psychiatry Department, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
  11. Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK
  12. National Hospital for Neurology and Neurosurgery, University College London Queen Square Institute of Neurology, London, UK
  13. The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy
  14. Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy
  15. Department of Neurosurgery, Rujin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
  16. Department of Neurology, University Hospital Würzburg, Würzburg, Germany
  17. Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
  18. Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  19. Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  20. Department of Stereotactic and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  21. Clinic of Pain and Functional Neurosurgery, São Paulo, Brazil
  22. Department of Neurology and Neurosurgery, University of Caxias do Sul, Rio Grande do Sul, Brazil
  23. NeuroCure Cluster of Excellence, Charité – Universitätsmedizin Berlin, Berlin, Germany
  24. Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  25. The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel
  26. Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, The Hebrew University, Hassadah Medical School, Jerusalem, Israel
  27. Department of Neurosurgery, Hadassah Medical Center, Jerusalem, Israel
  28. Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
  29. Parkinson and Movement Disorders Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
  30. Department of Neurosurgery, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
  31. Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA

References

[1] Neudorfer, C. et al. Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. Neuroimage 268, 119862 (2023).

[2] Horn, A. et al. Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia. Proc. Natl. Acad. Sci. 119, e2114985119 (2022).

[3] Irmen, F. et al. Left prefrontal connectivity links subthalamic stimulation with depressive symptoms. Ann. Neurol. 87, 962–975 (2020).

[4] Wang, F. et al. In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution. Sci. Data8, 122 (2021).

[5] Van Essen, D. C. et al. The WU-Minn Human Connectome Project: An overview. Neuroimage 80, 62–79 (2013).

[6] Li, N. et al. A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nat. Commun. 11, 3364 (2020).

[7] Petersen, M. V et al. Holographic reconstruction of axonal pathways in the human brain. Neuron 104, 1056-1064.e3 (2019).

[8] 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).

Meyer et al. (OHBM 2023)

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

Poster PDF

References

[1] Irmen, F. et al. 2020. Left Prefrontal Connectivity Links Subthalamic Stimulation with Depressive Symptoms. Annals of Neurology 87, 962–975.

[2] Mosley, P.E. et al. 2020. The structural connectivity of subthalamic deep brain stimulation correlates with impulsivity in Parkinson’s. Brain 143, 2235–2254.

[3] Neudorfer, C. et al. 2023. Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. NeuroImage 268, 119862.

Kim et al. (DBS Society Congress 2023)

Optimal Functional Connectivity Profiles in Subthalamic DBS

Poster PDF

References

[1] Horn A, Fox MD. Opportunities of connectomic neuromodulation. NeuroImage 2020;221:117180.

[2] Horn A, Reich M, Vorwerk J, et al. Connectivity Predicts deep brain stimulation outcome in Parkinson disease. Annals of Neurology 2017;82(1):67-78.

[3] Al-Fatly B, Ewert S, Kübler D, Kroneberg D, Horn A, Kühn AA. Connectivity profile of thalamic deep brain stimulation to effectively treat essential tremor. Brain 2019;142(10):3086-3098.

[4] Li N, Baldermann JC, Kibleur A, et al. A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nature Communications 2020;11(1):3364. (2018).

Sahin et al. (DBS Society Congress 2023)

Optimal Connections in Thalamic, Pallidal and Subthalamic DBS for Tourette’s Syndrome

Poster PDF

References

[1] Bronfeld, M. & Bar-Gad, I. Tic Disorders: What Happens in the Basal Ganglia? Neuroscientist 19, 101–108 (2013).

[2] Augustine, F. & Singer, H. S. Merging the Pathophysiology and Pharmacotherapy of Tics. Tremor Other Hyperkinet Mov (N Y) 8, 595 (2019).

[3] Billnitzer, A. & Jankovic, J. Current Management of Tics and Tourette Syndrome: Behavioral, Pharmacologic, and Surgical Treatments. Neurotherapeutics 17, 1681–1693 (2020).

[4] Martinez-Ramirez, D. et al. Efficacy and Safety of Deep Brain Stimulation in Tourette Syndrome: The International Tourette Syndrome Deep Brain Stimulation Public Database and Registry. JAMA Neurology 75, 353–359 (2018).

[5] Baldermann, J. C. et al. Deep Brain Stimulation for Tourette-Syndrome: A Systematic Review and Meta-Analysis. Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation 9, 296–304 (2016).

[6] Neudorfer, C. et al. Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. NeuroImage 268, 119862 (2023).

[7] Petersen, M. V. et al. Holographic Reconstruction of Axonal Pathways in the Human Brain. Neuron 104, 1056-1064.e3 (2019).

Hollunder et al. (OHBM & DBS Society Congress 2023)

Symptom Network Modulation of Deep Brain Stimulation in Obsessive-Compulsive Disorder

Poster PDF

Affiliations

  1. Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
  2. Einstein Center for Neurosciences Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
  3. Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
  4. Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
  5. Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  6. Biological and Health Psychology, School of Psychology, Universidad Autónoma de Madrid, Spain
  7. Clinical Brain Networks Group, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
  8. Neurosciences Queensland, St Andrew’s War Memorial Hospital, Spring Hill, Queensland, Australia
  9. Queensland Brain Institute, University of Queensland, St Lucia, Queensland, Australia
  10. Australian eHealth Research Centre, CSIRO Health and Biosecurity, Herston, Queensland, Australia
  11. Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
  12. National Hospital for Neurology and Neurosurgery, UCL Queen Square Institute of Neurology, London, UK
  13. Centre for Mental Health, Swinburne University of Technology, Melbourne, VIC, Australia
  14. Vincent’s Hospital Melbourne, Melbourne, Australia
  15. Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  16. Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
  17. Department of Neurosurgery, Hospital Clinico San Carlos, Instituto de Investigacion Sanitaria San Carlos, Universidad Complutense de Madrid, Madrid, Spain
  18. Laboratory for Clinical Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, IdISSC, Madrid, Spain
  19. Centre for Complex Interventions, Centre for Addiction and Mental Health, Toronto, ON, Canada
  20. Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
  21. Department of Psychiatry, University of Toronto, Toronto, ON, Canada
  22. Centre for Mental Health, Swinburne University, Melbourne, Australia
  23. Department of Psychiatry, University of Melbourne, Melbourne, Australia
  24. Department of Neurosurgery, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
  25. NeuroCure Cluster of Excellence, Charité – Universitätsmedizin Berlin, Berlin, Germany
  26. Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  27. Johanniter Hospital Oberhausen, EVKLN, Department of Psychiatry, Psychotherapy and Psychosomatics, Oberhausen, Germany
  28. Department of Stereotactic and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  29. Univ Grenoble Alpes, Grenoble, France
  30. Inserm, U1216, Grenoble Institut des Neurosciences, Grenoble, France
  31. Department of Psychiatry, Icahn School of Medicine, Mount Sinai Hospital, New York, USA
  32. Krembil Brain Institute, Toronto, ON, Canada
  33. Psychiatry Department, CHU Grenoble Alpes, Grenoble, France
  34. Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

References

[1] Figee, M., & Mayberg, H. (2021). The future of personalized brain stimulation. Nature Medicine, 27, 196–197. https://doi.org/10.1038/s41591-021-01243-7

[2] Baldermann, J. C. et al. (2019). Connectivity profile predictive of effective deep brain stimulation in obsessive-compulsive disorder. Biological Psychiatry, 85(9), 735–743. https://doi.org/10.1016/j.biopsych.2018.12.019

[3] Baldermann, J. C. et al. (2021). Connectomic deep brain stimulation for obsessive-compulsive disorder. Biological Psychiatry, 90(10), 678–688. https://doi.org/10.1016/j.biopsych.2021.07.010

[4] Li, N. et al. (2020). A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nature Communications, 11, 3364. https://doi.org/10.1038/s41467-020-16734-3

[5] Hollunder, B. et al. (2022). Toward personalized medicine in connectomic deep brain stimulation. Progress in Neurobiology, 210(210), 102211. https://doi.org/10.1016/j.pneurobio.2021.102211

[6] Neudorfer, C. et al. Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. Neuroimage 268, 119862 (2023). https://doi.org/10.1016/j.neuroimage.2023.119862

[7] Irmen, F. et al. (2020). Left prefrontal connectivity links subthalamic stimulation with depressive symptoms. Annals of Neurology, 87(6), 962–975. https://doi.org/10.1002/ana.25734

Zvarova et al. (DBS Society Congress 2023)

A Novel Database Lookup Method for Deep Brain Stimulation Network Mapping

Poster PDF

References

[1] Horn, A., Reich, M., Vorwerk, J., Li, N., Wenzel, G., Fang, Q., Schmitz-Hübsch, T., Nickl, R., Kupsch, A., Volkmann, J., Kühn, A.A., Fox, M.D., 2017. Connectivity Predicts deep brain stimulation outcome in Parkinson disease: DBS Outcome in PD. Ann Neurol. 82, 67–78. https://doi.org/10.1002/ana.24974

[2] Van Essen, D.C., Ugurbil, K., Auerbach, E., Barch, D., Behrens, T.E.J., Bucholz, R., Chang, A., Chen, L., Corbetta, M., Curtiss, S.W., Della Penna, S., Feinberg, D., Glasser, M.F., Harel, N., Heath, A.C., Larson-Prior, L., Marcus, D., Michalareas, G., Moeller, S., Oostenveld, R., Petersen, S.E., Prior, F., Schlaggar, B.L., Smith, S.M., Snyder, A.Z., Xu, J., Yacoub, E., 2012. The Human Connectome Project: A data acquisition perspective. Neuroimage 62, 2222–2231. https://doi.org/10.1016/j.neuroimage.2012.02.018

[3] Ewert, S., Plettig, P., Li, N., Chakravarty, M. M., Collins, D. L., Herrington, T. M., Kühn, A. A., & Horn, A. (2018). Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity. NeuroImage, 170, 271–282. https://doi.org/10.1016/j.neuroimage.2017.05.015

Hollunder & Li et al. (Opto-DBS 2022)

Segregating the Prefrontal Cortex by Means of DBS

Poster PDF

Poster Pitch Video

Affiliations

  1. Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
  2. Einstein Center for Neurosciences Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
  3. Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
  4. Movement Disorders and Neuromodulation Centre, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
  5. Université Grenoble Alpes, Grenoble, France
  6. Inserm, U1216, Grenoble Institut des Neurosciences, Grenoble, France
  7. Psychiatry Department, CHU Grenoble Alpes, Grenoble, France
  8. Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
  9. National Hospital for Neurology and Neurosurgery, UCL Queen Square Institute of Neurology, London, UK
  10. The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy
  11. Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy
  12. Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  13. Department of Neurosurgery, Rujin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
  14. Department of Neurology, University Hospital Würzburg, Würzburg, Germany
  15. Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
  16. NeuroCure Cluster of Excellence, Charité – Universitätsmedizin Berlin, Berlin, Germany
  17. Parkinson and Movement Disorders Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
  18. Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
  19. Center for Brain Circuit Therapeutics, Brigham & Women’s Hospital, Boston, MA, USA

References

Benarroch, E. E. (2008). Subthalamic nucleus and its connections: Anatomic substrate for the network effects of deep brain stimulation. Neurology, 70(21), 1991–1996. https://doi.org/10.1212/01.wnl.0000313022.39329.65

Bonelli, R. M., & Cummings, J. L. (2007). Frontal-subcortical circuitry and behavior. Dialogues in Clinical Neuroscience, 9(2), 141–151. https://doi.org/10.31887/dcns.2007.9.2/rbonelli

Ganos, C., Al-Fatly, B., Fischer, J.-F., Baldermann, J. C., Hennen, C., Visser-Vandewalle, V., … & Horn, A. (2022). A neural network for tics: insights from causal brain lesions and deep brain stimulation, Brain, awac009. https://doi.org/10.1093/brain/awac009

Haber, S. N., Liu, H., Seidlitz, J., & Bullmore, E. (2021). Prefrontal connectomics: From anatomy to human imaging. Neuropsychopharmacology. https://doi.org/10.1038/s41386-021-01156-6

Haynes, W. I. A., & Haber, S. N. (2013). The organization of prefrontal-subthalamic inputs in primates provides an anatomical substrate for both functional specificity and integration: Implications for basal ganglia models and deep brain stimulation. Journal of Neuroscience, 33(11), 4804–4814. https://doi.org/10.1523/JNEUROSCI.4674-12.2013

Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W. J., Reisert, M., Si, H., Oostenveld, R., Rorden, C., Yeh, F. C., Fang, Q., Herrington, T. M., Vorwerk, J., & Kühn, A. A. (2019). Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging. NeuroImage, 184(July 2018), 293–316. https://doi.org/10.1016/j.neuroimage.2018.08.068

Horn, A., Reich, M., Vorwerk, J., Li, N., Wenzel, G., Fang, Q., Schmitz-Hübsch, T., Nickl, R., Kupsch, A., Volkmann, J., Kühn, A. A., & Fox, M. D. (2017). Connectivity predicts deep brain stimulation outcome in Parkinson disease. Annals of Neurology, 82(1), 67–78. https://doi.org/10.1002/ana.24974

Li, N., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Elias, G. J. B., Boutet, A., Lozano, A. M., Al-Fatly, B., Strange, B., Barcia, J. A., Zrinzo, L., Joyce, E., Chabardes, S., Visser-Vandewalle, V., Polosan, M., Kuhn, J., Kühn, A. A., & Horn, A. (2020). A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nature Communications, 11, 3364. https://doi.org/10.1038/s41467-020-16734-3

Li, N., Hollunder, B., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Al-Fatly, B., Strange, B. A., Barcia, J. A., Zrinzo, L., Joyce, E. M., Chabardes, S., Visser-Vandewalle, V., Polosan, M., Kuhn, J., Kühn, A. A., & Horn, A. (2021). A unified functional network target for deep brain stimulation in obsessive-compulsive disorder. Biological Psychiatry, 90(10), 701–713. https://doi.org/10.1016/j.biopsych.2021.04.006

Wang, F., Dong, Z., Tian, Q., Liao, C., Fan, Q., Hoge, W. S., Keil, B., Polimeni, J. R., Wald, L. L., Huang, S. Y., & Setsompop, K. (2021). In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution. Scientific Data, 8, 122. https://doi.org/10.1038/s41597-021-00904-z

Hollunder & Li et al. (OHBM 2022)

Segregating the prefrontal cortex  by means of DBS

Poster PDF

Poster Pitch Video

Affiliations

  1. Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
  2. Einstein Center for Neurosciences Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
  3. Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
  4. Movement Disorders and Neuromodulation Centre, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
  5. Université Grenoble Alpes, Grenoble, France
  6. Inserm, U1216, Grenoble Institut des Neurosciences, Grenoble, France
  7. Psychiatry Department, CHU Grenoble Alpes, Grenoble, France
  8. Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK
  9. National Hospital for Neurology and Neurosurgery, UCL Queen Square Institute of Neurology, London, UK
  10. The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy
  11. Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy
  12. Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  13. Department of Neurosurgery, Rujin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
  14. Department of Neurology, University Hospital Würzburg, Würzburg, Germany
  15. Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
  16. NeuroCure Cluster of Excellence, Charité – Universitätsmedizin Berlin, Berlin, Germany
  17. Parkinson and Movement Disorders Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
  18. Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
  19. Center for Brain Circuit Therapeutics, Brigham & Women’s Hospital, Boston, MA, USA

References

Benarroch, E. E. (2008). Subthalamic nucleus and its connections: Anatomic substrate for the network effects of deep brain stimulation. Neurology, 70(21), 1991–1996. https://doi.org/10.1212/01.wnl.0000313022.39329.65

Bonelli, R. M., & Cummings, J. L. (2007). Frontal-subcortical circuitry and behavior. Dialogues in Clinical Neuroscience, 9(2), 141–151. https://doi.org/10.31887/dcns.2007.9.2/rbonelli

Ganos, C., Al-Fatly, B., Fischer, J.-F., Baldermann, J. C., Hennen, C., Visser-Vandewalle, V., … & Horn, A. (2022). A neural network for tics: insights from causal brain lesions and deep brain stimulation, Brain, awac009. https://doi.org/10.1093/brain/awac009

Haber, S. N., Liu, H., Seidlitz, J., & Bullmore, E. (2021). Prefrontal connectomics: From anatomy to human imaging. Neuropsychopharmacology. https://doi.org/10.1038/s41386-021-01156-6

Haynes, W. I. A., & Haber, S. N. (2013). The organization of prefrontal-subthalamic inputs in primates provides an anatomical substrate for both functional specificity and integration: Implications for basal ganglia models and deep brain stimulation. Journal of Neuroscience, 33(11), 4804–4814. https://doi.org/10.1523/JNEUROSCI.4674-12.2013

Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W. J., Reisert, M., Si, H., Oostenveld, R., Rorden, C., Yeh, F. C., Fang, Q., Herrington, T. M., Vorwerk, J., & Kühn, A. A. (2019). Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging. NeuroImage, 184(July 2018), 293–316. https://doi.org/10.1016/j.neuroimage.2018.08.068

Horn, A., Reich, M., Vorwerk, J., Li, N., Wenzel, G., Fang, Q., Schmitz-Hübsch, T., Nickl, R., Kupsch, A., Volkmann, J., Kühn, A. A., & Fox, M. D. (2017). Connectivity predicts deep brain stimulation outcome in Parkinson disease. Annals of Neurology, 82(1), 67–78. https://doi.org/10.1002/ana.24974

Li, N., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Elias, G. J. B., Boutet, A., Lozano, A. M., Al-Fatly, B., Strange, B., Barcia, J. A., Zrinzo, L., Joyce, E., Chabardes, S., Visser-Vandewalle, V., Polosan, M., Kuhn, J., Kühn, A. A., & Horn, A. (2020). A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nature Communications, 11, 3364. https://doi.org/10.1038/s41467-020-16734-3

Li, N., Hollunder, B., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Al-Fatly, B., Strange, B. A., Barcia, J. A., Zrinzo, L., Joyce, E. M., Chabardes, S., Visser-Vandewalle, V., Polosan, M., Kuhn, J., Kühn, A. A., & Horn, A. (2021). A unified functional network target for deep brain stimulation in obsessive-compulsive disorder. Biological Psychiatry, 90(10), 701–713. https://doi.org/10.1016/j.biopsych.2021.04.006

Wang, F., Dong, Z., Tian, Q., Liao, C., Fan, Q., Hoge, W. S., Keil, B., Polimeni, J. R., Wald, L. L., Huang, S. Y., & Setsompop, K. (2021). In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution. Scientific Data, 8, 122. https://doi.org/10.1038/s41597-021-00904-z

Goede et al. (DBS Expert Summit 2022)

DBS for Tremor: Network Effects



Goede et al. (DGKN 2022)

DBS for Tremor: Network Effects

Poster PDF

Affiliations

Lukas L. Goede1,5, Bassam Al-Fatly1, Clemens Neudorfer4, Ningfei Li1, Vincent J.J. Odekerken2, Martin Reich3, Jens Volkmann3, Rob M.A. de Bie2, Andrea A. Kühn1, Andreas Horn1,4

1 Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany

2 Department of Neurology, Amsterdam University Medical Center, Amsterdam, The Netherlands

3 Department of Neurology, University Clinic of Würzburg, Würzburg, Germany

4 Center for Brain Circuit Therapeutics, Department of Neurology Brigham & Women’s Hospital, Harvard Medical School, Boston, United States; MAMGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States

5 BIH – Berlin Institute of Health at Charité – Universitätsmedizin Berlin,

BIH Biomedical Innovation Academy, BIH Charité Junior Clinician Scientist Program, Charitéplatz 1, 10117 Berlin, Germany

References

Deuschl G, Bain P, Brin M. Consensus Statement of the Movement Disorder Society on Tremor. Mov Disord. 2008 Oct 20;13(S3):2–23.

Horn A, Li N, Dembek TA, Kappel A, Boulay C, Ewert S, et al. Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging. NeuroImage. 2019 Jan;184:293–316.

Horn A, Reich M, Vorwerk J, Li N, Wenzel G, Fang Q, et al. Connectivity Predicts deep brain stimulation outcome in Parkinson disease: DBS Outcome in PD. Ann Neurol. 2017 Jul;82(1):67–78.

Buckner RL, Krienen FM, Castellanos A, Diaz JC, Yeo BTT. The organization of the human cerebellum estimated by intrinsic functional connectivity. Journal of Neurophysiology. 2011 Nov;106(5):2322–45.

Middlebrooks EH, Okromelidze L, Wong JK, et al. Connectivity Correlates Predicting Deep Brain Stimulation Outcome in Essential Tremor: Evidence for a common treatment pathway. NeuroImage Clin. 2021.

Hollunder & Li et al. (DBS Expert Summit 2022)

Segregating the prefrontal cortex  by means of DBS

Poster PDF

References

Benarroch, E. E. (2008). Subthalamic nucleus and its connections: Anatomic substrate for the network effects of deep brain stimulation. Neurology, 70(21), 1991–1996. https://doi.org/10.1212/01.wnl.0000313022.39329.65

Bonelli, R. M., & Cummings, J. L. (2007). Frontal-subcortical circuitry and behavior. Dialogues in Clinical Neuroscience, 9(2), 141–151. https://doi.org/10.31887/dcns.2007.9.2/rbonelli

Ganos, C., Al-Fatly, B., Fischer, J.-F., Baldermann, J. C., Hennen, C., Visser-Vandewalle, V., … & Horn, A. (2022). A neural network for tics: insights from causal brain lesions and deep brain stimulation, Brain, awac009. https://doi.org/10.1093/brain/awac009

Haber, S. N., Liu, H., Seidlitz, J., & Bullmore, E. (2021). Prefrontal connectomics: From anatomy to human imaging. Neuropsychopharmacology. https://doi.org/10.1038/s41386-021-01156-6

Haynes, W. I. A., & Haber, S. N. (2013). The organization of prefrontal-subthalamic inputs in primates provides an anatomical substrate for both functional specificity and integration: Implications for basal ganglia models and deep brain stimulation. Journal of Neuroscience, 33(11), 4804–4814. https://doi.org/10.1523/JNEUROSCI.4674-12.2013

Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W. J., Reisert, M., Si, H., Oostenveld, R., Rorden, C., Yeh, F. C., Fang, Q., Herrington, T. M., Vorwerk, J., & Kühn, A. A. (2019). Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging. NeuroImage, 184(July 2018), 293–316. https://doi.org/10.1016/j.neuroimage.2018.08.068

Horn, A., Reich, M., Vorwerk, J., Li, N., Wenzel, G., Fang, Q., Schmitz-Hübsch, T., Nickl, R., Kupsch, A., Volkmann, J., Kühn, A. A., & Fox, M. D. (2017). Connectivity predicts deep brain stimulation outcome in Parkinson disease. Annals of Neurology, 82(1), 67–78. https://doi.org/10.1002/ana.24974

Li, N., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Elias, G. J. B., Boutet, A., Lozano, A. M., Al-Fatly, B., Strange, B., Barcia, J. A., Zrinzo, L., Joyce, E., Chabardes, S., Visser-Vandewalle, V., Polosan, M., Kuhn, J., Kühn, A. A., & Horn, A. (2020). A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nature Communications, 11, 3364. https://doi.org/10.1038/s41467-020-16734-3

Li, N., Hollunder, B., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Al-Fatly, B., Strange, B. A., Barcia, J. A., Zrinzo, L., Joyce, E. M., Chabardes, S., Visser-Vandewalle, V., Polosan, M., Kuhn, J., Kühn, A. A., & Horn, A. (2021). A unified functional network target for deep brain stimulation in obsessive-compulsive disorder. Biological Psychiatry, 90(10), 701–713. https://doi.org/10.1016/j.biopsych.2021.04.006

Wang, F., Dong, Z., Tian, Q., Liao, C., Fan, Q., Hoge, W. S., Keil, B., Polimeni, J. R., Wald, L. L., Huang, S. Y., & Setsompop, K. (2021). In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution. Scientific Data, 8, 122. https://doi.org/10.1038/s41597-021-00904-z

Mana et al. (DBS Expert Summit 2022)

Instrumental activities of daily living improve in Parkinson’s Disease after STN DBS

Poster PDF

References

Brennan, L., Siderowf, A., Rubright, J.D., Rick, J., Dahodwala, N., Duda, J.E., Hurtig, H., Stern, M., Xie, S.X., Rennert, L., Karlawish, J., Shea, J.A., Trojanowski, J.Q., and Weintraub, D. (2016a). Development and initial testing of the Penn Parkinson’s Daily Activities Questionnaire. Mov Disord 31, 126-134. https://doi.org/10.1002/mds.2633

Brennan, L., Siderowf, A., Rubright, J.D., Rick, J., Dahodwala, N., Duda, J.E., Hurtig, H., Stern, M., Xie, S.X., Rennert, L., Karlawish, J., Shea, J.A., Trojanowski, J.Q., and Weintraub, D. (2016b). The Penn Parkinson’s Daily Activities Questionnaire-15: Psychometric properties of a brief assessment of cognitive instrumental activities of daily living in Parkinson’s disease. Parkinsonism Relat Disord 25, 21-26. https://doi.org/10.1016/j.parkreldis.2016.02.020

Rios et al. (DBS Expert Summit 2022)

Optimal stimulation sites and networks for DBS of the fornix in Alzheimer’s Diesease

Poster PDF

References 

Chen, Guangyu et al. “Staging Alzheimer’s Disease Risk by Sequencing Brain Function and Structure, Cerebrospinal Fluid, and Cognition Biomarkers.” Journal of Alzheimer’s disease : JAD vol. 54,3 (2016): 983-993. doi:10.3233/JAD-160537

Laxton, Adrian W et al. “A phase I trial of deep brain stimulation of memory circuits in Alzheimer’s disease.” Annals of neurology vol. 68,4 (2010): 521-34. doi:10.1002/ana.22089

Lozano, Andres M et al. “A Phase II Study of Fornix Deep Brain Stimulation in Mild Alzheimer’s Disease.” Journal of Alzheimer’s disease : JAD vol. 54,2 (2016): 777-87. doi:10.3233/JAD-160017

Horn, Andreas et al. “Connectivity Predicts deep brain stimulation outcome in Parkinson disease.” Annals of neurology vol. 82,1 (2017): 67-78. doi:10.1002/ana.24974

Li, Ningfei et al. “A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder.” Nature communicationsvol. 11,1 3364. 3 Jul. 2020, doi:10.1038/s41467-020-16734-3

Choi, Ki Sueng et al. “Mapping the “Depression Switch” During Intraoperative Testing of Subcallosal Cingulate Deep Brain Stimulation.” JAMA neurology vol. 72,11 (2015): 1252-60. doi:10.1001/jamaneurol.2015.2564

Horn, Andreas et al. “Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging.” NeuroImage vol. 184 (2019): 293-316. doi:10.1016/j.neuroimage.2018.08.068

Wang, Fuyixue et al. “In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution.” Scientific data vol. 8,1 122. 29 Apr. 2021, doi:10.1038/s41597-021-00904-z

Yeo, B T Thomas et al. “The organization of the human cerebral cortex estimated by intrinsic functional connectivity.” Journal of neurophysiology vol. 106,3 (2011): 1125-65. doi:10.1152/jn.00338.2011

For figure background and structures

Edlow, Brian L et al. “7 Tesla MRI of the ex vivo human brain at 100 micron resolution.” Scientific data vol. 6,1 244. 30 Oct. 2019, doi:10.1038/s41597-019-0254-8

Amunts, Katrin et al. “Julich-Brain: A 3D probabilistic atlas of the human brain’s cytoarchitecture.” Science (New York, N.Y.)vol. 369,6506 (2020): 988-992. doi:10.1126/science.abb4588

Neudorfer, Clemens et al. “A high-resolution in vivo magnetic resonance imaging atlas of the human hypothalamic region.” Scientific datavol. 7,1 305. 15 Sep. 2020, doi:10.1038/s41597-020-00644-6

Amaral, Robert S C et al. “Manual segmentation of the fornix, fimbria, and alveus on high-resolution 3T MRI: Application via fully-automated mapping of the human memory circuit white and grey matter in healthy and pathological aging.” NeuroImage vol. 170 (2018): 132-150. doi:10.1016/j.neuroimage.2016.10.027

Oxenford et al. (DBS Expert Summit 2022)

Precision neuroimaging via manual refinement of the deformation fields

Poster PDF

WarpDrive Demo