Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies

Vinata Vedam-Mai, Karl Deisseroth, James Giordano, Gabriel Lazaro-Munoz, Winston Chiong, Nanthia Suthana, Jean Philippe Langevin, Jay Gill, Wayne Goodman, Nicole R. Provenza, Casey H. Halpern, Rajat S. Shivacharan, Tricia N. Cunningham, Sameer A. Sheth, Nader Pouratian, Katherine W. Scangos, Helen S. Mayberg, Andreas Horn, Kara A. Johnson, Christopher R. ButsonRo’ee Gilron, Coralie de Hemptinne, Robert Wilt, Maria Yaroshinsky, Simon Little, Philip Starr, Greg Worrell, Prasad Shirvalkar, Edward Chang, Jens Volkmann, Muthuraman Muthuraman, Sergiu Groppa, Andrea A. Kühn, Luming Li, Matthew Johnson, Kevin J. Otto, Robert Raike, Steve Goetz, Chengyuan Wu, Peter Silburn, Binith Cheeran, Yagna J. Pathak, Mahsa Malekmohammadi, Aysegul Gunduz, Joshua K. Wong, Stephanie Cernera, Aparna Wagle Shukla, Adolfo Ramirez-Zamora, Wissam Deeb, Addie Patterson, Kelly D. Foote, Michael S. Okun

Research output: Contribution to journalArticlepeer-review

Abstract

We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer’s disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.

Original languageEnglish (US)
Article number644593
JournalFrontiers in Human Neuroscience
Volume15
DOIs
StatePublished - Apr 19 2021

Bibliographical note

Funding Information:
Funding. KD was supported by the National Institute on Drug Abuse (NIDA P50 Center), NIMH, DARPA, the Tarlton Foundation, the AE Foundation Borderline Research Fund, the NOMIS Foundation, the Else Kroner Fresenius Foundation and the NSF NeuroNex program. JamG was supported in part by the Henry M. Jackson Foundation for the Advancement of Military Medicine, Leadership Initiatives, NeurGen, BNB corporation, and the Creighton University Medical Visiting Professorship and receives federal funds from the National Center for Advancing Translational Sciences through the Clinical and Translational Science Awards Program, part of the Roadmap Initiative, Re-Engineering the Clinical Research Enterprise. GL-M was supported by the National Institutes of Health (R01MH114854). WC was supported by the National Institute of Mental Health of the National Institutes of Health under award [Number R01MH114860]. NS was supported by the NIH (NINDS UO1 NS103802) and the McKnight Foundation (Technological Innovations in Neuroscience Award). J-PL was supported by the NIH (NIMH UH3 NS107673). WG was supported by the NIH (NINDS UH3 NS100549). CHH was supported by the NIH (NINDS UH3 NS103446). SS was supported by the NIH BRAIN Initiative via the cooperative agreement UH3NS103549. NRP was supported by the NIH BRAIN Initiative via the cooperative agreement UH3NS103549. This work was supported by National Institutes of Health award K23NS110962, NARSAD Young Investigator grant from the Brain and Behavioral Research Foundation (KS), and a Ray and Dagmar Dolby Family Fund through the Department of Psychiatry at the University of California, San Francisco. HM was supported by the NIH (UH3 NS103550-02) and Hope for Depression Research Foundation. AH was supported by the German Research Foundation (DFG Grants 410169619 and 424778381 ? TRR 295). KJ was supported by the NSF Graduate Research Fellowship Program (1747505) and NIH P41 Center for Integrative Biomedical Computing (CIBC) (GM103545). CB was supported by NIH P41 Center for Integrative Biomedical Computing (CIBC) (GM103545) and NIH NINR (NR014852). RG was supported by the NIH BRAIN Initiative via the cooperative agreement UH3NS100544. RW was supported by the NIH BRAIN Initiative via the cooperative agreement UH3NS100544. PhS was supported by NIH BRAIN (UH3NS109556 and UH3NS100544). GW was supported by the NIH (R01 NS092882 & UH3 NS095495). PrS and EC were supported by NIH HEAL (UH3NS115631) and NIH BRAIN (UH3NS109556). EC was supported by NIH BRAIN (UH3NS109556). This work was supported by the German Research Foundation (DFG; SFB-TR-128, SFB-CRC 1193) and the Boehringer Ingelheim Fonds (BIF-03) (MuM and SeG). The work presented at the Think Tank was supported by the National Key Research and Development Program of China (2016YFC0105900), the National Natural Science Foundation of China (61901243) and the Research and Development Program of Beijing (LL). This work was supported in part by NIH grants R01-NS081118, R01-NS094206, P50-NS098573, and R25-NS118756 (MJ). Funding for the work was provided by Abbott (CW and PeS). JKW is supported by NIH (R25NS108939).

Funding Information:
KD was supported by the National Institute on Drug Abuse (NIDA P50 Center), NIMH, DARPA, the Tarlton Foundation, the AE Foundation Borderline Research Fund, the NOMIS Foundation, the Else Kroner Fresenius Foundation and the NSF NeuroNex program. JamG was supported in part by the Henry M. Jackson Foundation for the Advancement of Military Medicine, Leadership Initiatives, NeurGen, BNB corporation, and the Creighton University Medical Visiting Professorship and receives federal funds from the National Center for Advancing Translational Sciences through the Clinical and Translational Science Awards Program, part of the Roadmap Initiative, Re-Engineering the Clinical Research Enterprise. GL-M was supported by the National Institutes of Health (R01MH114854). WC was supported by the National Institute of Mental Health of the National Institutes of Health under award [Number R01MH114860]. NS was supported by the NIH (NINDS UO1 NS103802) and the McKnight Foundation (Technological Innovations in Neuroscience Award). J-PL was supported by the NIH (NIMH UH3 NS107673). WG was supported by the NIH (NINDS UH3 NS100549). CHH was supported by the NIH (NINDS UH3 NS103446). SS was supported by the NIH BRAIN Initiative via the cooperative agreement UH3NS103549. NRP was supported by the NIH BRAIN Initiative via the cooperative agreement UH3NS103549. This work was supported by National Institutes of Health award K23NS110962, NARSAD Young Investigator grant from the Brain and Behavioral Research Foundation (KS), and a Ray and Dagmar Dolby Family Fund through the Department of Psychiatry at the University of California, San Francisco. HM was supported by the NIH (UH3 NS103550-02) and Hope for Depression Research Foundation. AH was supported by the German Research Foundation (DFG Grants 410169619 and 424778381 – TRR 295). KJ was supported by the NSF Graduate Research Fellowship Program (1747505) and NIH P41 Center for Integrative Biomedical Computing (CIBC) (GM103545). CB was supported by NIH P41 Center for Integrative Biomedical Computing (CIBC) (GM103545) and NIH NINR (NR014852). RG was supported by the NIH BRAIN Initiative via the cooperative agreement UH3NS100544. RW was supported by the NIH BRAIN Initiative via the cooperative agreement UH3NS100544. PhS was supported by NIH BRAIN (UH3NS109556 and UH3NS100544). GW was supported by the NIH (R01 NS092882 & UH3 NS095495). PrS and EC were supported by NIH HEAL (UH3NS115631) and NIH BRAIN (UH3NS109556). EC was supported by NIH BRAIN (UH3NS109556). This work was supported by the German Research Foundation (DFG; SFB-TR-128, SFB-CRC 1193) and the Boehringer Ingelheim Fonds (BIF-03) (MuM and SeG). The work presented at the Think

Publisher Copyright:
© Copyright © 2021 Vedam-Mai, Deisseroth, Giordano, Lazaro-Munoz, Chiong, Suthana, Langevin, Gill, Goodman, Provenza, Halpern, Shivacharan, Cunningham, Sheth, Pouratian, Scangos, Mayberg, Horn, Johnson, Butson, Gilron, de Hemptinne, Wilt, Yaroshinsky, Little, Starr, Worrell, Shirvalkar, Chang, Volkmann, Muthuraman, Groppa, Kühn, Li, Johnson, Otto, Raike, Goetz, Wu, Silburn, Cheeran, Pathak, Malekmohammadi, Gunduz, Wong, Cernera, Wagle Shukla, Ramirez-Zamora, Deeb, Patterson, Foote and Okun.

Keywords

  • DBS (deep brain stimulation)
  • adaptive DBS
  • neuroethics
  • neuroimaging
  • novel hardware
  • optogenetics

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