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