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Asaad WF, Sheth SA. What's the n? On sample size vs. subject number for brain-behavior neurophysiology and neuromodulation. Neuron 2024:S0896-6273(24)00323-4. [PMID: 38781973 DOI: 10.1016/j.neuron.2024.04.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/01/2024] [Accepted: 04/26/2024] [Indexed: 05/25/2024]
Abstract
Neurophysiology and neuromodulation strive to understand the neural basis of behavior through a one-to-one correspondence between a particular brain and its behavioral output. Within this framework, studies with few subjects but sufficient sample sizes can be both rigorous and impactful.
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Affiliation(s)
- Wael F Asaad
- Department of Neuroscience, Brown University, Providence, RI, USA; Department of Neurosurgery, Brown University Alpert Medical School, Providence, RI, USA; Carney Institute for Brain Science, Brown University, Providence, RI, USA; Norman Prince Neurosciences Institute, Rhode Island Hospital, Providence, RI, USA.
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA; Jan and Dan Duncan Neurological Research Institute, Baylor College of Medicine, Houston, TX, USA
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2
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Sadeghzadeh S, Swaminathan A, Bhanot P, Steeman S, Xu A, Shah V, Purger DA, Buch VP. Emerging Outlook on Personalized Neuromodulation for Depression: Insights from Tractography-Based Targeting. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00109-5. [PMID: 38679323 DOI: 10.1016/j.bpsc.2024.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/07/2024] [Accepted: 04/11/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND Deep brain stimulation (DBS) has shown individual promise in treating treatment resistant depression (TRD), but larger-scale trials have been less successful. Here, we create the largest meta-analysis with individual patient data (IPD) to date to explore if the use of tractography enhances the efficacy of DBS for TRD. METHODS We systematically reviewed 1823 articles, selecting 32 that contributed data from 366 patients. We stratified the IPD based on stimulation target and use of tractography. Utilizing two-way type III Analysis of Variance (ANOVA), Welch Two Sample t-tests, and mixed-effects linear regression models, we evaluated changes in depression severity 9-15 months post-surgery (1-Y) and at last follow-up (LFU) (4 weeks - 8 years) as assessed by depression scales. RESULTS Tractography was used for medial forebrain bundle (MFB, n=17/32), subcallosal cingulate (SCC, n=39/241), and ventral capsule/ventral striatum (VC/VS, n=3/41) targets; and not used for bed nucleus of stria terminalis (n=11), lateral habenula (n=10), and inferior thalamic peduncle (n=1). Across all patients, tractography significantly improved mean depression scores at 1-Y (p<0.001) and LFU (p=0.009). Within the target cohorts, tractography improved depression scores at 1-Y for both MFB and SCC, though significance was only met at the alpha = 0.1 level (SCC: β=15.8%, p=0.09; MFB: β=52.4%, p=0.10). Within the tractography cohort, MFB with tractography patients showed greater improvement than those with SCC with tractography (72.42±7.17% versus 54.78±4.08%) at 1-Y (p=0.044). CONCLUSIONS Our findings underscore the promise of tractography in DBS for TRD as a methodology for personalization of therapy, supporting its inclusion in future trials.
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Affiliation(s)
| | | | - Priya Bhanot
- Icahn School of Medicine at Mount Sinai, New York City, NY.
| | | | - Audrey Xu
- Department of Biology, Stanford University, Stanford, CA.
| | - Vaibhavi Shah
- Stanford University School of Medicine, Stanford, CA.
| | - David A Purger
- Department of Neurosurgery, Stanford University, Stanford, CA.
| | - Vivek P Buch
- Department of Neurosurgery, Stanford University, Stanford, CA.
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3
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Unadkat P, Quevedo J, Soares J, Fenoy A. Opportunities and challenges for the use of deep brain stimulation in the treatment of refractory major depression. DISCOVER MENTAL HEALTH 2024; 4:9. [PMID: 38483709 PMCID: PMC10940557 DOI: 10.1007/s44192-024-00062-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 03/08/2024] [Indexed: 03/17/2024]
Abstract
Major Depressive Disorder continues to remain one of the most prevalent psychiatric diseases globally. Despite multiple trials of conventional therapies, a subset of patients fail to have adequate benefit to treatment. Deep brain stimulation (DBS) is a promising treatment in this difficult to treat population and has shown strong antidepressant effects across multiple cohorts. Nearly two decades of work have provided insights into the potential for chronic focal stimulation in precise brain targets to modulate pathological brain circuits that are implicated in the pathogenesis of depression. In this paper we review the rationale that prompted the selection of various brain targets for DBS, their subsequent clinical outcomes and common adverse events reported. We additionally discuss some of the pitfalls and challenges that have prevented more widespread adoption of this technology as well as future directions that have shown promise in improving therapeutic efficacy of DBS in the treatment of depression.
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Affiliation(s)
- Prashin Unadkat
- Elmezzi Graduate School of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Department of Neurosurgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell Health, Hempstead, NY, USA
| | - Joao Quevedo
- Center of Excellence On Mood Disorders, Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, (UT Health), Houston, TX, USA
| | - Jair Soares
- Center of Excellence On Mood Disorders, Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, (UT Health), Houston, TX, USA
| | - Albert Fenoy
- Elmezzi Graduate School of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
- Department of Neurosurgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell Health, Hempstead, NY, USA.
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell Health, Hempstead, NY, USA.
- Department of Neurosurgery, Donald and Barbara Zucker School of Medicine, Feinstein Institutes for Medical Research, Northwell Health, 805 Northern Boulevard, Suite 100, Great Neck, NY, 11021, USA.
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4
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Johnson KA, Dosenbach NUF, Gordon EM, Welle CG, Wilkins KB, Bronte-Stewart HM, Voon V, Morishita T, Sakai Y, Merner AR, Lázaro-Muñoz G, Williamson T, Horn A, Gilron R, O'Keeffe J, Gittis AH, Neumann WJ, Little S, Provenza NR, Sheth SA, Fasano A, Holt-Becker AB, Raike RS, Moore L, Pathak YJ, Greene D, Marceglia S, Krinke L, Tan H, Bergman H, Pötter-Nerger M, Sun B, Cabrera LY, McIntyre CC, Harel N, Mayberg HS, Krystal AD, Pouratian N, Starr PA, Foote KD, Okun MS, Wong JK. Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements. Front Hum Neurosci 2024; 18:1320806. [PMID: 38450221 PMCID: PMC10915873 DOI: 10.3389/fnhum.2024.1320806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/05/2024] [Indexed: 03/08/2024] Open
Abstract
The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.
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Affiliation(s)
- Kara A. Johnson
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Nico U. F. Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Evan M. Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Cristin G. Welle
- Department of Physiology and Biophysics, University of Colorado School of Medicine, Aurora, CO, United States
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, United States
| | - Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Helen M. Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Takashi Morishita
- Department of Neurosurgery, Fukuoka University Faculty of Medicine, Fukuoka, Japan
| | - Yuki Sakai
- ATR Brain Information Communication Research Laboratory Group, Kyoto, Japan
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Amanda R. Merner
- Center for Bioethics, Harvard Medical School, Boston, MA, United States
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard Medical School, Boston, MA, United States
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
| | - Theresa Williamson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States
| | - Andreas Horn
- Department of Neurology, Center for Brain Circuit Therapeutics, Harvard Medical School, Brigham & Women's Hospital, Boston, MA, United States
- MGH Neurosurgery and Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Berlin, Germany
| | | | | | - Aryn H. Gittis
- Biological Sciences and Center for Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Berlin, Germany
| | - Simon Little
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Nicole R. Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease, Division of Neurology, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network (UHN), University of Toronto, Toronto, ON, Canada
- Krembil Brain Institute, Toronto, ON, Canada
| | - Abbey B. Holt-Becker
- Restorative Therapies Group Implantables, Research, and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | - Robert S. Raike
- Restorative Therapies Group Implantables, Research, and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | - Lisa Moore
- Boston Scientific Neuromodulation Corporation, Valencia, CA, United States
| | | | - David Greene
- NeuroPace, Inc., Mountain View, CA, United States
| | - Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | - Lothar Krinke
- Newronika SPA, Milan, Italy
- Department of Neuroscience, West Virginia University, Morgantown, WV, United States
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Hagai Bergman
- Edmond and Lily Safar Center (ELSC) for Brain Research and Department of Medical Neurobiology (Physiology), Institute of Medical Research Israel-Canada, Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurosurgery, Hadassah Medical Center, Jerusalem, Israel
| | - Monika Pötter-Nerger
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Laura Y. Cabrera
- Neuroethics, Department of Engineering Science and Mechanics, Philosophy, and Bioethics, and the Rock Ethics Institute, Pennsylvania State University, State College, PA, United States
| | - Cameron C. McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
- Department of Neurosurgery, Duke University, Durham, NC, United States
| | - Noam Harel
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Helen S. Mayberg
- Department of Neurology, Neurosurgery, Psychiatry, and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Andrew D. Krystal
- Departments of Psychiatry and Behavioral Science and Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Nader Pouratian
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Philip A. Starr
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Kelly D. Foote
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, University of Florida, Gainesville, FL, United States
| | - Michael S. Okun
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Joshua K. Wong
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
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5
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Allawala A, Bijanki KR, Oswalt D, Mathura RK, Adkinson J, Pirtle V, Shofty B, Robinson M, Harrison MT, Mathew SJ, Goodman WK, Pouratian N, Sheth SA, Borton DA. Prefrontal network engagement by deep brain stimulation in limbic hubs. Front Hum Neurosci 2024; 17:1291315. [PMID: 38283094 PMCID: PMC10813208 DOI: 10.3389/fnhum.2023.1291315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 12/26/2023] [Indexed: 01/30/2024] Open
Abstract
Prefrontal circuits in the human brain play an important role in cognitive and affective processing. Neuromodulation therapies delivered to certain key hubs within these circuits are being used with increasing frequency to treat a host of neuropsychiatric disorders. However, the detailed neurophysiological effects of stimulation to these hubs are largely unknown. Here, we performed intracranial recordings across prefrontal networks while delivering electrical stimulation to two well-established white matter hubs involved in cognitive regulation and depression: the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS). We demonstrate a shared frontotemporal circuit consisting of the ventromedial prefrontal cortex, amygdala, and lateral orbitofrontal cortex where gamma oscillations are differentially modulated by stimulation target. Additionally, we found participant-specific responses to stimulation in the dorsal anterior cingulate cortex and demonstrate the capacity for further tuning of neural activity using current-steered stimulation. Our findings indicate a potential neurophysiological mechanism for the dissociable therapeutic effects seen across the SCC and VC/VS targets for psychiatric neuromodulation and our results lay the groundwork for personalized, network-guided neurostimulation therapy.
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Affiliation(s)
- Anusha Allawala
- School of Engineering, Brown University, Providence, RI, United States
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Kelly R. Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Denise Oswalt
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, United States
| | - Raissa K. Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Joshua Adkinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Victoria Pirtle
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Ben Shofty
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, United States
| | - Meghan Robinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Matthew T. Harrison
- Division of Applied Mathematics, Brown University, Providence, RI, United States
| | - Sanjay J. Mathew
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Wayne K. Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX, United States
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - David A. Borton
- School of Engineering, Brown University, Providence, RI, United States
- Department of Veterans Affairs, Center for Neurorestoration and Neurotechnology, Providence, RI, United States
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6
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Sellers KK, Cohen JL, Khambhati AN, Fan JM, Lee AM, Chang EF, Krystal AD. Closed-loop neurostimulation for the treatment of psychiatric disorders. Neuropsychopharmacology 2024; 49:163-178. [PMID: 37369777 PMCID: PMC10700557 DOI: 10.1038/s41386-023-01631-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 06/29/2023]
Abstract
Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joshua L Cohen
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - A Moses Lee
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
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7
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Widge AS. Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity. Neuropsychopharmacology 2024; 49:138-149. [PMID: 37415081 PMCID: PMC10700701 DOI: 10.1038/s41386-023-01643-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 05/28/2023] [Accepted: 06/20/2023] [Indexed: 07/08/2023]
Abstract
Deep brain stimulation (DBS) is an invasive approach to precise modulation of psychiatrically relevant circuits. Although it has impressive results in open-label psychiatric trials, DBS has also struggled to scale to and pass through multi-center randomized trials. This contrasts with Parkinson disease, where DBS is an established therapy treating thousands of patients annually. The core difference between these clinical applications is the difficulty of proving target engagement, and of leveraging the wide range of possible settings (parameters) that can be programmed in a given patient's DBS. In Parkinson's, patients' symptoms change rapidly and visibly when the stimulator is tuned to the correct parameters. In psychiatry, those same changes take days to weeks, limiting a clinician's ability to explore parameter space and identify patient-specific optimal settings. I review new approaches to psychiatric target engagement, with an emphasis on major depressive disorder (MDD). Specifically, I argue that better engagement may come by focusing on the root causes of psychiatric illness: dysfunction in specific, measurable cognitive functions and in the connectivity and synchrony of distributed brain circuits. I overview recent progress in both those domains, and how it may relate to other technologies discussed in companion articles in this issue.
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Affiliation(s)
- Alik S Widge
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
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8
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Sandoval-Pistorius SS, Hacker ML, Waters AC, Wang J, Provenza NR, de Hemptinne C, Johnson KA, Morrison MA, Cernera S. Advances in Deep Brain Stimulation: From Mechanisms to Applications. J Neurosci 2023; 43:7575-7586. [PMID: 37940596 PMCID: PMC10634582 DOI: 10.1523/jneurosci.1427-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/14/2023] [Accepted: 08/15/2023] [Indexed: 11/10/2023] Open
Abstract
Deep brain stimulation (DBS) is an effective therapy for various neurologic and neuropsychiatric disorders, involving chronic implantation of electrodes into target brain regions for electrical stimulation delivery. Despite its safety and efficacy, DBS remains an underutilized therapy. Advances in the field of DBS, including in technology, mechanistic understanding, and applications have the potential to expand access and use of DBS, while also improving clinical outcomes. Developments in DBS technology, such as MRI compatibility and bidirectional DBS systems capable of sensing neural activity while providing therapeutic stimulation, have enabled advances in our understanding of DBS mechanisms and its application. In this review, we summarize recent work exploring DBS modulation of target networks. We also cover current work focusing on improved programming and the development of novel stimulation paradigms that go beyond current standards of DBS, many of which are enabled by sensing-enabled DBS systems and have the potential to expand access to DBS.
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Affiliation(s)
| | - Mallory L Hacker
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee 37232
| | - Allison C Waters
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York 10029
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York 10029
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota 55455
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas 77030
| | - Coralie de Hemptinne
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida 32608
| | - Kara A Johnson
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida 32608
| | - Melanie A Morrison
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Stephanie Cernera
- Department of Neurological Surgery, University of California-San Francisco, San Francisco, California 94143
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9
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Sheth SA, Shofty B, Allawala A, Xiao J, Adkinson JA, Mathura RK, Pirtle V, Myers J, Oswalt D, Provenza NR, Giridharan N, Noecker AM, Banks GP, Gadot R, Najera RA, Anand A, Devara E, Dang H, Bartoli E, Watrous A, Cohn J, Borton D, Mathew SJ, McIntyre CC, Goodman W, Bijanki K, Pouratian N. Stereo-EEG-guided network modulation for psychiatric disorders: Surgical considerations. Brain Stimul 2023; 16:1792-1798. [PMID: 38135358 PMCID: PMC10787578 DOI: 10.1016/j.brs.2023.07.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/30/2023] [Accepted: 07/30/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) and other neuromodulatory techniques are being increasingly utilized to treat refractory neurologic and psychiatric disorders. OBJECTIVE /Hypothesis: To better understand the circuit-level pathophysiology of treatment-resistant depression (TRD) and treat the network-level dysfunction inherent to this challenging disorder, we adopted an approach of inpatient intracranial monitoring borrowed from the epilepsy surgery field. METHODS We implanted 3 patients with 4 DBS leads (bilateral pair in both the ventral capsule/ventral striatum and subcallosal cingulate) and 10 stereo-electroencephalography (sEEG) electrodes targeting depression-relevant network regions. For surgical planning, we used an interactive, holographic visualization platform to appreciate the 3D anatomy and connectivity. In the initial surgery, we placed the DBS leads and sEEG electrodes using robotic stereotaxy. Subjects were then admitted to an inpatient monitoring unit for depression-specific neurophysiological assessments. Following these investigations, subjects returned to the OR to remove the sEEG electrodes and internalize the DBS leads to implanted pulse generators. RESULTS Intraoperative testing revealed positive valence responses in all 3 subjects that helped verify targeting. Given the importance of the network-based hypotheses we were testing, we required accurate adherence to the surgical plan (to engage DBS and sEEG targets) and stability of DBS lead rotational position (to ensure that stimulation field estimates of the directional leads used during inpatient monitoring were relevant chronically), both of which we confirmed (mean radial error 1.2±0.9 mm; mean rotation 3.6±2.6°). CONCLUSION This novel hybrid sEEG-DBS approach allows detailed study of the neurophysiological substrates of complex neuropsychiatric disorders.
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Affiliation(s)
- Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.
| | - Ben Shofty
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Anusha Allawala
- Department of Engineering, Brown University, Providence, RI, USA
| | - Jiayang Xiao
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Joshua A Adkinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Raissa K Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Victoria Pirtle
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - John Myers
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Denise Oswalt
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nisha Giridharan
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Angela M Noecker
- Departments of Biomedical Engineering and Neurosurgery, Duke University, Durham, NC, USA
| | - Garrett P Banks
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ron Gadot
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ricardo A Najera
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Adrish Anand
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ethan Devara
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Huy Dang
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Eleonora Bartoli
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Andrew Watrous
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Jeffrey Cohn
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - David Borton
- Department of Engineering, Brown University, Providence, RI, USA
| | - Sanjay J Mathew
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | | | - Wayne Goodman
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Kelly Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX, USA
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10
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Noecker AM, Mlakar J, Bijanki KR, Griswold MA, Pouratian N, Sheth SA, McIntyre CC. Stereo-EEG-guided network modulation for psychiatric disorders: Interactive holographic planning. Brain Stimul 2023; 16:1799-1805. [PMID: 38135359 PMCID: PMC10784872 DOI: 10.1016/j.brs.2023.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Connectomic modeling studies are expanding understanding of the brain networks that are modulated by deep brain stimulation (DBS) therapies. However, explicit integration of these modeling results into prospective neurosurgical planning is only beginning to evolve. One challenge of employing connectomic models in patient-specific surgical planning is the inherent 3D nature of the results, which can make clinically useful data integration and visualization difficult. METHODS We developed a holographic stereotactic neurosurgery research tool (HoloSNS) that integrates patient-specific brain models into a group-based visualization environment for interactive surgical planning using connectomic hypotheses. HoloSNS currently runs on the HoloLens 2 platform and it enables remote networking between headsets. This allowed us to perform surgical planning group meetings with study co-investigators distributed across the country. RESULTS We used HoloSNS to plan stereo-EEG and DBS electrode placements for each patient participating in a clinical trial (NCT03437928) that is targeting both the subcallosal cingulate and ventral capsule for the treatment of depression. Each patient model consisted of multiple components of scientific data and anatomical reconstructions of the head and brain (both patient-specific and atlas-based), which far exceed the data integration capabilities of traditional neurosurgical planning workstations. This allowed us to prospectively discuss and evaluate the positioning of the electrodes based on novel connectomic hypotheses. CONCLUSIONS The 3D nature of the surgical procedure, brain imaging data, and connectomic modeling results all highlighted the utility of employing holographic visualization to support the design of unique clinical experiments to explore brain network modulation with DBS.
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Affiliation(s)
- Angela M Noecker
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Jeffrey Mlakar
- Interactive Commons, Case Western Reserve University, Cleveland, OH, USA
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Mark A Griswold
- Interactive Commons, Case Western Reserve University, Cleveland, OH, USA; Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Nader Pouratian
- Department of Neurosurgery, University of Texas Southwestern, Dallas, TX, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Cameron C McIntyre
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Neurosurgery, Duke University, Durham, NC, USA.
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11
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Xiao J, Provenza NR, Asfouri J, Myers J, Mathura RK, Metzger B, Adkinson JA, Allawala AB, Pirtle V, Oswalt D, Shofty B, Robinson ME, Mathew SJ, Goodman WK, Pouratian N, Schrater PR, Patel AB, Tolias AS, Bijanki KR, Pitkow X, Sheth SA. Decoding Depression Severity From Intracranial Neural Activity. Biol Psychiatry 2023; 94:445-453. [PMID: 36736418 PMCID: PMC10394110 DOI: 10.1016/j.biopsych.2023.01.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 01/09/2023] [Accepted: 01/25/2023] [Indexed: 02/05/2023]
Abstract
BACKGROUND Disorders of mood and cognition are prevalent, disabling, and notoriously difficult to treat. Fueling this challenge in treatment is a significant gap in our understanding of their neurophysiological basis. METHODS We recorded high-density neural activity from intracranial electrodes implanted in depression-relevant prefrontal cortical regions in 3 human subjects with severe depression. Neural recordings were labeled with depression severity scores across a wide dynamic range using an adaptive assessment that allowed sampling with a temporal frequency greater than that possible with typical rating scales. We modeled these data using regularized regression techniques with region selection to decode depression severity from the prefrontal recordings. RESULTS Across prefrontal regions, we found that reduced depression severity is associated with decreased low-frequency neural activity and increased high-frequency activity. When constraining our model to decode using a single region, spectral changes in the anterior cingulate cortex best predicted depression severity in all 3 subjects. Relaxing this constraint revealed unique, individual-specific sets of spatiospectral features predictive of symptom severity, reflecting the heterogeneous nature of depression. CONCLUSIONS The ability to decode depression severity from neural activity increases our fundamental understanding of how depression manifests in the human brain and provides a target neural signature for personalized neuromodulation therapies.
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Affiliation(s)
- Jiayang Xiao
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas; Department of Neuroscience, Baylor College of Medicine, Houston, Texas
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Joseph Asfouri
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas
| | - John Myers
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Raissa K Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Brian Metzger
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Joshua A Adkinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | | | - Victoria Pirtle
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Denise Oswalt
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Ben Shofty
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Meghan E Robinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Sanjay J Mathew
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas
| | - Wayne K Goodman
- Department of Psychiatry, Baylor College of Medicine, Houston, Texas
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, Texas
| | - Paul R Schrater
- Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota; Department of Psychology, University of Minnesota, Minneapolis, Minnesota
| | - Ankit B Patel
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas; Department of Electrical and Computer Engineering, Rice University, Houston, Texas; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas
| | - Andreas S Tolias
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas; Department of Electrical and Computer Engineering, Rice University, Houston, Texas; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Xaq Pitkow
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas; Department of Electrical and Computer Engineering, Rice University, Houston, Texas; Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas.
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12
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Wang DX, Ng N, Seger SE, Ekstrom AD, Kriegel JL, Lega BC. Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement. Cereb Cortex 2023; 33:8150-8163. [PMID: 36997155 PMCID: PMC10321120 DOI: 10.1093/cercor/bhad105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 03/04/2023] [Accepted: 03/05/2023] [Indexed: 04/01/2023] Open
Abstract
Successful neuromodulation approaches to alter episodic memory require closed-loop stimulation predicated on the effective classification of brain states. The practical implementation of such strategies requires prior decisions regarding electrode implantation locations. Using a data-driven approach, we employ support vector machine (SVM) classifiers to identify high-yield brain targets on a large data set of 75 human intracranial electroencephalogram subjects performing the free recall (FR) task. Further, we address whether the conserved brain regions provide effective classification in an alternate (associative) memory paradigm along with FR, as well as testing unsupervised classification methods that may be a useful adjunct to clinical device implementation. Finally, we use random forest models to classify functional brain states, differentiating encoding versus retrieval versus non-memory behavior such as rest and mathematical processing. We then test how regions that exhibit good classification for the likelihood of recall success in the SVM models overlap with regions that differentiate functional brain states in the random forest models. Finally, we lay out how these data may be used in the design of neuromodulation devices.
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Affiliation(s)
- David X Wang
- Department of Neurosurgery, The University of Texas – Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Nicole Ng
- Department of Neurosurgery, The University of Texas – Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Sarah E Seger
- Department of Neuroscience, University of Arizona, Tucson, Arizona 85721, United States
| | - Arne D Ekstrom
- Department of Neuroscience, University of Arizona, Tucson, Arizona 85721, United States
- Department of Psychology, University of Arizona, Tucson, Arizona 85721, United States
| | - Jennifer L Kriegel
- Department of Neurosurgery, The University of Texas – Southwestern Medical Center, Dallas, Texas 75390, United States
| | - Bradley C Lega
- Department of Neurosurgery, The University of Texas – Southwestern Medical Center, Dallas, Texas 75390, United States
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13
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Hitti FL, Widge AS, Riva-Posse P, Malone DA, Okun MS, Shanechi MM, Foote KD, Lisanby SH, Ankudowich E, Chivukula S, Chang EF, Gunduz A, Hamani C, Feinsinger A, Kubu CS, Chiong W, Chandler JA, Carbunaru R, Cheeran B, Raike RS, Davis RA, Halpern CH, Vanegas-Arroyave N, Markovic D, Bick SK, McIntyre CC, Richardson RM, Dougherty DD, Kopell BH, Sweet JA, Goodman WK, Sheth SA, Pouratian N. Future directions in psychiatric neurosurgery: Proceedings of the 2022 American Society for Stereotactic and Functional Neurosurgery meeting on surgical neuromodulation for psychiatric disorders. Brain Stimul 2023; 16:867-878. [PMID: 37217075 DOI: 10.1016/j.brs.2023.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/10/2023] [Accepted: 05/14/2023] [Indexed: 05/24/2023] Open
Abstract
OBJECTIVE Despite advances in the treatment of psychiatric diseases, currently available therapies do not provide sufficient and durable relief for as many as 30-40% of patients. Neuromodulation, including deep brain stimulation (DBS), has emerged as a potential therapy for persistent disabling disease, however it has not yet gained widespread adoption. In 2016, the American Society for Stereotactic and Functional Neurosurgery (ASSFN) convened a meeting with leaders in the field to discuss a roadmap for the path forward. A follow-up meeting in 2022 aimed to review the current state of the field and to identify critical barriers and milestones for progress. DESIGN The ASSFN convened a meeting on June 3, 2022 in Atlanta, Georgia and included leaders from the fields of neurology, neurosurgery, and psychiatry along with colleagues from industry, government, ethics, and law. The goal was to review the current state of the field, assess for advances or setbacks in the interim six years, and suggest a future path forward. The participants focused on five areas of interest: interdisciplinary engagement, regulatory pathways and trial design, disease biomarkers, ethics of psychiatric surgery, and resource allocation/prioritization. The proceedings are summarized here. CONCLUSION The field of surgical psychiatry has made significant progress since our last expert meeting. Although weakness and threats to the development of novel surgical therapies exist, the identified strengths and opportunities promise to move the field through methodically rigorous and biologically-based approaches. The experts agree that ethics, law, patient engagement, and multidisciplinary teams will be critical to any potential growth in this area.
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Affiliation(s)
- Frederick L Hitti
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| | - Alik S Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota-Twin Cities, Minneapolis, MN, USA
| | - Patricio Riva-Posse
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Donald A Malone
- Department of Psychiatry, Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA
| | - Michael S Okun
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, Gainesville, FL, USA
| | - Maryam M Shanechi
- Departments of Electrical and Computer Engineering and Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Kelly D Foote
- Department of Neurosurgery, Norman Fixel Institute for Neurological Diseases, Gainesville, FL, USA
| | - Sarah H Lisanby
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Elizabeth Ankudowich
- Division of Translational Research, National Institute of Mental Health, Bethesda, MD, USA
| | - Srinivas Chivukula
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Aysegul Gunduz
- Department of Biomedical Engineering and Fixel Institute for Neurological Disorders, University of Florida, Gainesville, FL, USA
| | - Clement Hamani
- Sunnybrook Research Institute, Hurvitz Brain Sciences Centre, Harquail Centre for Neuromodulation, Division of Neurosurgery, University of Toronto, Toronto, Canada
| | - Ashley Feinsinger
- Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Cynthia S Kubu
- Department of Neurology, Cleveland Clinic and Case Western Reserve University, School of Medicine, Cleveland, OH, USA
| | - Winston Chiong
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Jennifer A Chandler
- Faculty of Law, University of Ottawa, Ottawa, ON, USA; Affiliate Investigator, Bruyère Research Institute, Ottawa, ON, USA
| | | | | | - Robert S Raike
- Global Research Organization, Medtronic Inc. Neuromodulation, Minneapolis, MN, USA
| | - Rachel A Davis
- Departments of Psychiatry and Neurosurgery, University of Colorado Anschutz, Aurora, CO, USA
| | - Casey H Halpern
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; The Cpl Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | | | - Dejan Markovic
- Department of Electrical Engineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Sarah K Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Cameron C McIntyre
- Departments of Biomedical Engineering and Neurosurgery, Duke University, Durham, NC, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Brian H Kopell
- Department of Neurosurgery, Center for Neuromodulation, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jennifer A Sweet
- Department of Neurosurgery, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Wayne K Goodman
- Department of Psychiatry and Behavior Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nader Pouratian
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
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14
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Webler RD, Oathes DJ, van Rooij SJH, Gewirtz JC, Nahas Z, Lissek SM, Widge AS. Causally mapping human threat extinction relevant circuits with depolarizing brain stimulation methods. Neurosci Biobehav Rev 2023; 144:105005. [PMID: 36549377 DOI: 10.1016/j.neubiorev.2022.105005] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/17/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022]
Abstract
Laboratory threat extinction paradigms and exposure-based therapy both involve repeated, safe confrontation with stimuli previously experienced as threatening. This fundamental procedural overlap supports laboratory threat extinction as a compelling analogue of exposure-based therapy. Threat extinction impairments have been detected in clinical anxiety and may contribute to exposure-based therapy non-response and relapse. However, efforts to improve exposure outcomes using techniques that boost extinction - primarily rodent extinction - have largely failed to date, potentially due to fundamental differences between rodent and human neurobiology. In this review, we articulate a comprehensive pre-clinical human research agenda designed to overcome these failures. We describe how connectivity guided depolarizing brain stimulation methods (i.e., TMS and DBS) can be applied concurrently with threat extinction and dual threat reconsolidation-extinction paradigms to causally map human extinction relevant circuits and inform the optimal integration of these methods with exposure-based therapy. We highlight candidate targets including the amygdala, hippocampus, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, and mesolimbic structures, and propose hypotheses about how stimulation delivered at specific learning phases could strengthen threat extinction.
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Affiliation(s)
- Ryan D Webler
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
| | - Desmond J Oathes
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sanne J H van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Jonathan C Gewirtz
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA; Department of Psychology, Arizona State University, AZ, USA
| | - Ziad Nahas
- Department of Psychology, Arizona State University, AZ, USA
| | - Shmuel M Lissek
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Alik S Widge
- Department of Psychiatry and Medical Discovery Team on Addictions, University of Minnesota Medical School, MN, USA
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15
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Idlett-Ali SL, Salazar CA, Bell MS, Short EB, Rowland NC. Neuromodulation for treatment-resistant depression: Functional network targets contributing to antidepressive outcomes. Front Hum Neurosci 2023; 17:1125074. [PMID: 36936612 PMCID: PMC10018031 DOI: 10.3389/fnhum.2023.1125074] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Non-invasive brain stimulation is designed to target accessible brain regions that underlie many psychiatric disorders. One such method, transcranial magnetic stimulation (TMS), is commonly used in patients with treatment-resistant depression (TRD). However, for non-responders, the choice of an alternative therapy is unclear and often decided empirically without detailed knowledge of precise circuit dysfunction. This is also true of invasive therapies, such as deep brain stimulation (DBS), in which responses in TRD patients are linked to circuit activity that varies in each individual. If the functional networks affected by these approaches were better understood, a theoretical basis for selection of interventions could be developed to guide psychiatric treatment pathways. The mechanistic understanding of TMS is that it promotes long-term potentiation of cortical targets, such as dorsolateral prefrontal cortex (DLPFC), which are attenuated in depression. DLPFC is highly interconnected with other networks related to mood and cognition, thus TMS likely alters activity remote from DLPFC, such as in the central executive, salience and default mode networks. When deeper structures such as subcallosal cingulate cortex (SCC) are targeted using DBS for TRD, response efficacy has depended on proximity to white matter pathways that similarly engage emotion regulation and reward. Many have begun to question whether these networks, targeted by different modalities, overlap or are, in fact, the same. A major goal of current functional and structural imaging in patients with TRD is to elucidate neuromodulatory effects on the aforementioned networks so that treatment of intractable psychiatric conditions may become more predictable and targeted using the optimal technique with fewer iterations. Here, we describe several therapeutic approaches to TRD and review clinical studies of functional imaging and tractography that identify the diverse loci of modulation. We discuss differentiating factors associated with responders and non-responders to these stimulation modalities, with a focus on mechanisms of action for non-invasive and intracranial stimulation modalities. We advance the hypothesis that non-invasive and invasive neuromodulation approaches for TRD are likely impacting shared networks and critical nodes important for alleviating symptoms associated with this disorder. We close by describing a therapeutic framework that leverages personalized connectome-guided target identification for a stepwise neuromodulation paradigm.
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Affiliation(s)
- Shaquia L. Idlett-Ali
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- *Correspondence: Shaquia L. Idlett-Ali,
| | - Claudia A. Salazar
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
| | - Marcus S. Bell
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
| | - E. Baron Short
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, United States
| | - Nathan C. Rowland
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
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16
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Sheth SA, Bijanki KR, Metzger B, Allawala A, Pirtle V, Adkinson JA, Myers J, Mathura RK, Oswalt D, Tsolaki E, Xiao J, Noecker A, Strutt AM, Cohn JF, McIntyre CC, Mathew SJ, Borton D, Goodman W, Pouratian N. Deep Brain Stimulation for Depression Informed by Intracranial Recordings. Biol Psychiatry 2022; 92:246-251. [PMID: 35063186 PMCID: PMC9124238 DOI: 10.1016/j.biopsych.2021.11.007] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 11/01/2021] [Accepted: 11/02/2021] [Indexed: 11/02/2022]
Abstract
The success of deep brain stimulation (DBS) for treating Parkinson's disease has led to its application to several other disorders, including treatment-resistant depression. Results with DBS for treatment-resistant depression have been heterogeneous, with inconsistencies largely driven by incomplete understanding of the brain networks regulating mood, especially on an individual basis. We report results from the first subject treated with DBS for treatment-resistant depression using an approach that incorporates intracranial recordings to personalize understanding of network behavior and its response to stimulation. These recordings enabled calculation of individually optimized DBS stimulation parameters using a novel inverse solution approach. In the ensuing double-blind, randomized phase incorporating these bespoke parameter sets, DBS led to remission of symptoms and dramatic improvement in quality of life. Results from this initial case demonstrate the feasibility of this personalized platform, which may be used to improve surgical neuromodulation for a vast array of neurologic and psychiatric disorders.
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Affiliation(s)
- Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA,Corresponding Author: Sameer A. Sheth, MD, PhD, 7200 Cambridge Street, Suite 9B, Houston, TX 77030, 310-922-2596,
| | - Kelly R. Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA
| | - Brian Metzger
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA
| | - Anusha Allawala
- Department of Engineering, Brown University, Providence, RI, 02912 USA
| | - Victoria Pirtle
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA
| | - Josh A. Adkinson
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA
| | - John Myers
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA
| | - Raissa K. Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA
| | - Denise Oswalt
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA
| | - Evangelia Tsolaki
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, 90095 USA
| | - Jiayang Xiao
- Department of Neurosurgery, Baylor College of Medicine, Houston TX, 77030 USA
| | - Angela Noecker
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106 USA
| | - Adriana M. Strutt
- Department of Neurology, Baylor College of Medicine, Houston TX, 77030 USA
| | - Jeffrey F. Cohn
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, 19104 USA
| | - Cameron C. McIntyre
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106 USA
| | - Sanjay J. Mathew
- Department of Psychiatry, Baylor College of Medicine, Houston TX, 77030 USA
| | - David Borton
- Department of Engineering, Brown University, Providence, RI, 02912 USA
| | - Wayne Goodman
- Department of Psychiatry, Baylor College of Medicine, Houston TX, 77030 USA
| | - Nader Pouratian
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, 90095 USA
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17
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Malekmohammadi M, Mustakos R, Sheth S, Pouratian N, McIntyre CC, Bijanki KR, Tsolaki E, Chiu K, Robinson ME, Adkinson JA, Oswalt D, Carcieri S. Automated optimization of deep brain stimulation parameters for modulating neuroimaging-based targets. J Neural Eng 2022; 19:10.1088/1741-2552/ac7e6c. [PMID: 35790135 PMCID: PMC11090244 DOI: 10.1088/1741-2552/ac7e6c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 07/05/2022] [Indexed: 11/12/2022]
Abstract
Objective.Therapeutic efficacy of deep brain stimulation (DBS) in both established and emerging indications, is highly dependent on accurate lead placement and optimized clinical programming. The latter relies on clinicians' experience to search among available sets of stimulation parameters and can be limited by the time constraints of clinical practice. Recent innovations in device technology have expanded the number of possible electrode configurations and parameter sets available to clinicians, amplifying the challenge of time constraints. We hypothesize that patient specific neuroimaging data can effectively assist the clinical programming using automated algorithms.Approach.This paper introduces the DBS Illumina 3D algorithm as a tool which uses patient-specific imaging to find stimulation settings that optimizes activating a target area while minimizing the stimulation of areas outside the target that could result in unknown or undesired side effects. This approach utilizes preoperative neuroimaging data paired with the postoperative reconstruction of the lead trajectory to search the available stimulation space and identify optimized stimulation parameters. We describe the application of this algorithm in three patients with treatment-resistant depression who underwent bilateral implantation of DBS in subcallosal cingulate cortex and ventral capsule/ventral striatum using tractography optimized targeting with an imaging defined target previously described.Main results.Compared to the stimulation settings selected by the clinicians (informed by anatomy), stimulation settings produced by the algorithm that achieved similar or greater target coverage, produced a significantly smaller stimulation area that spilled outside the target (P= 0.002).Significance. The DBS Illumina 3D algorithm is seamlessly integrated with the clinician programmer software and effectively and rapidly assists clinicians with the analysis of image based anatomy, and provides a starting point to search the highly complex stimulation parameter space and arrive at the stimulation settings that optimize activating a target area.
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Affiliation(s)
- Mahsa Malekmohammadi
- Boston Scientific Neuromodulation, 25155 Rye Canyon Loop, Valencia, CA 91355, USA
| | - Richard Mustakos
- Boston Scientific Neuromodulation, 25155 Rye Canyon Loop, Valencia, CA 91355, USA
| | - Sameer Sheth
- Department of Neurosurgery, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Nader Pouratian
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, 8353 Harry Hines Blvd MC8855, Dallas, TX 75239, USA
| | - Cameron C. McIntyre
- Departments of Biomedical Engineering and Neurosurgery, Duke University, 100 Science Drive, Durham, NC 27708, USA
| | - Kelly R. Bijanki
- Department of Neurosurgery, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Evangelia Tsolaki
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, 300 Stein Plaza Suite 562, Los Angeles, CA 90095, USA
| | - Kevin Chiu
- Brainlab, Inc., 5 Westbrook Corporate Center, Suite 1000, Westchester IL 60154, USA
| | - Meghan E. Robinson
- Department of Neurosurgery, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Joshua A. Adkinson
- Department of Neurosurgery, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Denise Oswalt
- Department of Neurosurgery, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Stephen Carcieri
- Boston Scientific Neuromodulation, 25155 Rye Canyon Loop, Valencia, CA 91355, USA
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18
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Figee M, Riva-Posse P, Choi KS, Bederson L, Mayberg HS, Kopell BH. Deep Brain Stimulation for Depression. Neurotherapeutics 2022; 19:1229-1245. [PMID: 35817944 PMCID: PMC9587188 DOI: 10.1007/s13311-022-01270-3] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2022] [Indexed: 11/29/2022] Open
Abstract
Deep brain stimulation has been extensively studied as a therapeutic option for treatment-resistant depression (TRD). DBS across different targets is associated with on average 60% response rates in previously refractory chronically depressed patients. However, response rates vary greatly between patients and between studies and often require extensive trial-and-error optimizations of stimulation parameters. Emerging evidence from tractography imaging suggests that targeting combinations of white matter tracts, rather than specific grey matter regions, is necessary for meaningful antidepressant response to DBS. In this article, we review efficacy of various DBS targets for TRD, which networks are involved in their therapeutic effects, and how we can use this information to improve targeting and programing of DBS for individual patients. We will also highlight how to integrate these DBS network findings into developing adaptive stimulation and optimal trial designs.
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Affiliation(s)
- Martijn Figee
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Patricio Riva-Posse
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Georgia, GA, USA
| | - Ki Sueng Choi
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lucia Bederson
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian H Kopell
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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19
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Nowakowska M, Üçal M, Charalambous M, Bhatti SFM, Denison T, Meller S, Worrell GA, Potschka H, Volk HA. Neurostimulation as a Method of Treatment and a Preventive Measure in Canine Drug-Resistant Epilepsy: Current State and Future Prospects. Front Vet Sci 2022; 9:889561. [PMID: 35782557 PMCID: PMC9244381 DOI: 10.3389/fvets.2022.889561] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 05/23/2022] [Indexed: 11/28/2022] Open
Abstract
Modulation of neuronal activity for seizure control using various methods of neurostimulation is a rapidly developing field in epileptology, especially in treatment of refractory epilepsy. Promising results in human clinical practice, such as diminished seizure burden, reduced incidence of sudden unexplained death in epilepsy, and improved quality of life has brought neurostimulation into the focus of veterinary medicine as a therapeutic option. This article provides a comprehensive review of available neurostimulation methods for seizure management in drug-resistant epilepsy in canine patients. Recent progress in non-invasive modalities, such as repetitive transcranial magnetic stimulation and transcutaneous vagus nerve stimulation is highlighted. We further discuss potential future advances and their plausible application as means for preventing epileptogenesis in dogs.
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Affiliation(s)
- Marta Nowakowska
- Research Unit of Experimental Neurotraumatology, Department of Neurosurgery, Medical University of Graz, Graz, Austria
| | - Muammer Üçal
- Research Unit of Experimental Neurotraumatology, Department of Neurosurgery, Medical University of Graz, Graz, Austria
| | - Marios Charalambous
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| | - Sofie F. M. Bhatti
- Small Animal Department, Faculty of Veterinary Medicine, Small Animal Teaching Hospital, Ghent University, Merelbeke, Belgium
| | - Timothy Denison
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Sebastian Meller
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| | | | - Heidrun Potschka
- Faculty of Veterinary Medicine, Institute of Pharmacology, Toxicology and Pharmacy, Ludwig-Maximilians-University, Munich, Germany
| | - Holger A. Volk
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
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20
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Wong JK, Deuschl G, Wolke R, Bergman H, Muthuraman M, Groppa S, Sheth SA, Bronte-Stewart HM, Wilkins KB, Petrucci MN, Lambert E, Kehnemouyi Y, Starr PA, Little S, Anso J, Gilron R, Poree L, Kalamangalam GP, Worrell GA, Miller KJ, Schiff ND, Butson CR, Henderson JM, Judy JW, Ramirez-Zamora A, Foote KD, Silburn PA, Li L, Oyama G, Kamo H, Sekimoto S, Hattori N, Giordano JJ, DiEuliis D, Shook JR, Doughtery DD, Widge AS, Mayberg HS, Cha J, Choi K, Heisig S, Obatusin M, Opri E, Kaufman SB, Shirvalkar P, Rozell CJ, Alagapan S, Raike RS, Bokil H, Green D, Okun MS. Proceedings of the Ninth Annual Deep Brain Stimulation Think Tank: Advances in Cutting Edge Technologies, Artificial Intelligence, Neuromodulation, Neuroethics, Pain, Interventional Psychiatry, Epilepsy, and Traumatic Brain Injury. Front Hum Neurosci 2022; 16:813387. [PMID: 35308605 PMCID: PMC8931265 DOI: 10.3389/fnhum.2022.813387] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/11/2022] [Indexed: 01/09/2023] Open
Abstract
DBS Think Tank IX was held on August 25-27, 2021 in Orlando FL with US based participants largely in person and overseas participants joining by video conferencing technology. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging deep brain stimulation (DBS) technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank IX speakers was that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. After collectively sharing our experiences, it was estimated that globally more than 230,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. As such, this year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia and Australia; cutting-edge technologies, neuroethics, interventional psychiatry, adaptive DBS, neuromodulation for pain, network neuromodulation for epilepsy and neuromodulation for traumatic brain injury.
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Affiliation(s)
- Joshua K. Wong
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Günther Deuschl
- Department of Neurology, Christian-Albrechts-University, Kiel, Germany
| | - Robin Wolke
- Department of Neurology, Christian-Albrechts-University, Kiel, Germany
| | - Hagai Bergman
- Department of Medical Neurobiology (Physiology), Institute of Medical Research Israel-Canada, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Muthuraman Muthuraman
- Biomedical Statistics and Multimodal Signal Processing Unit, Section of Movement Disorders and Neurostimulation, Focus Program Translational Neuroscience, Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Biomedical Statistics and Multimodal Signal Processing Unit, Section of Movement Disorders and Neurostimulation, Focus Program Translational Neuroscience, Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sameer A. Sheth
- Department of Neurological Surgery, Baylor College of Medicine, Houston, TX, United States
| | - Helen M. Bronte-Stewart
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Kevin B. Wilkins
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Matthew N. Petrucci
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Emilia Lambert
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Yasmine Kehnemouyi
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Philip A. Starr
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Simon Little
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Juan Anso
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Ro’ee Gilron
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Lawrence Poree
- Department of Anesthesia, University of California, San Francisco, San Francisco, CA, United States
| | - Giridhar P. Kalamangalam
- Department of Neurology, Wilder Center for Epilepsy Research, University of Florida, Gainesville, FL, United States
| | | | - Kai J. Miller
- Department of Neurosurgery, Mayo Clinic, Rochester, NY, United States
| | - Nicholas D. Schiff
- Department of Neurology, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, New York, NY, United States
| | - Christopher R. Butson
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Jaimie M. Henderson
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Jack W. Judy
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States
| | - Adolfo Ramirez-Zamora
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Kelly D. Foote
- Department of Neurosurgery, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Peter A. Silburn
- Queensland Brain Institute, University of Queensland and Saint Andrews War Memorial Hospital, Brisbane, QLD, Australia
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Genko Oyama
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Hikaru Kamo
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Satoko Sekimoto
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Nobutaka Hattori
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - James J. Giordano
- Neuroethics Studies Program, Department of Neurology, Georgetown University Medical Center, Washington, DC, United States
| | - Diane DiEuliis
- US Department of Defense Fort Lesley J. McNair, National Defense University, Washington, DC, United States
| | - John R. Shook
- Department of Philosophy and Science Education, University of Buffalo, Buffalo, NY, United States
| | - Darin D. Doughtery
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Alik S. Widge
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States
| | - Helen S. Mayberg
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Jungho Cha
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Kisueng Choi
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Stephen Heisig
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Mosadolu Obatusin
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Enrico Opri
- Department of Neurology, Emory University, Atlanta, GA, United States
| | - Scott B. Kaufman
- Department of Psychology, Columbia University, New York, NY, United States
| | - Prasad Shirvalkar
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
- Department of Anesthesiology (Pain Management) and Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Christopher J. Rozell
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Sankaraleengam Alagapan
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Robert S. Raike
- Restorative Therapies Group Implantables, Research and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | - Hemant Bokil
- Boston Scientific Neuromodulation Corporation, Valencia, CA, United States
| | - David Green
- NeuroPace, Inc., Mountain View, CA, United States
| | - Michael S. Okun
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
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21
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Rahman S, Rahman MM, Moscote-Salazar LR, Lozada-Martinez ID, Al-Salihi MM. Letter: A Novel Framework for Network-Targeted Neuropsychiatric Deep Brain Stimulation. Neurosurgery 2022; 90:e24-e25. [PMID: 34982894 DOI: 10.1227/neu.0000000000001771] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 09/18/2021] [Indexed: 11/19/2022] Open
Affiliation(s)
- Sabrina Rahman
- Department of Public Health , Independent University-Bangladesh, Dhaka , Bangladesh
| | - Md Moshiur Rahman
- Neurosurgery Department , Holy Family Red Crescent Medical College , Dhaka , Bangladesh
| | | | - Ivan David Lozada-Martinez
- Medical and Surgical Research Center, School of Medicine , University of Cartagena, Cartagena , Colombia
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22
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Allawala A, Sheth SA. In Reply: A Novel Framework for Network-Targeted Neuropsychiatric Deep Brain Stimulation. Neurosurgery 2022; 90:e26. [PMID: 34982895 PMCID: PMC9514729 DOI: 10.1227/neu.0000000000001772] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 09/18/2021] [Indexed: 11/19/2022] Open
Affiliation(s)
- Anusha Allawala
- School of Engineering, Brown University, Providence, Rhode Island, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas, USA
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23
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Dastin-van Rijn EM, König SD, Carlson D, Goel V, Grande A, Nixdorf DR, Benish S, Widge AS, Nahas Z, Park MC, Netoff TI, Herman AB, Darrow DP. Personalizing Dual-Target Cortical Stimulation with Bayesian Parameter Optimization Successfully Treats Central Post-Stroke Pain: A Case Report. Brain Sci 2021; 12:25. [PMID: 35053769 PMCID: PMC8773936 DOI: 10.3390/brainsci12010025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 12/22/2021] [Accepted: 12/22/2021] [Indexed: 11/16/2022] Open
Abstract
Central pain disorders, such as central post-stroke pain, remain clinically challenging to treat, despite many decades of pharmacological advances and the evolution of neuromodulation. For treatment refractory cases, previous studies have highlighted some benefits of cortical stimulation. Recent advances in new targets for pain and the optimization of neuromodulation encouraged our group to develop a dual cortical target approach paired with Bayesian optimization to provide a personalized treatment. Here, we present a case report of a woman who developed left-sided facial pain after multiple thalamic strokes. All previous pharmacologic and interventional treatments failed to mitigate the pain, leaving her incapacitated due to pain and medication side effects. She subsequently underwent a single burr hole for placement of motor cortex (M1) and dorsolateral prefrontal cortex (dlPFC) paddles for stimulation with externalization. By using Bayesian optimization to find optimal stimulation parameters and stimulation sites, we were able to reduce pain from an 8.5/10 to a 0/10 during a 5-day inpatient stay, with pain staying at or below a 2/10 one-month post-procedure. We found optimal treatment to be simultaneous stimulation of M1 and dlPFC without any evidence of seizure induction. In addition, we found no worsening in cognitive performance during a working memory task with dlPFC stimulation. This personalized approach using Bayesian optimization may provide a new foundation for treating central pain and other functional disorders through systematic evaluation of stimulation parameters.
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Affiliation(s)
- Evan M. Dastin-van Rijn
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA; (E.M.D.-v.R.); (T.I.N.)
| | - Seth D. König
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical Center, Minneapolis, MN 55454, USA; (S.D.K.); (D.C.); (A.S.W.); (Z.N.); (A.B.H.)
- Department of Neurosurgery, University of Minnesota Medical Center, Minneapolis, MN 55455, USA; (A.G.); (M.C.P.)
| | - Danielle Carlson
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical Center, Minneapolis, MN 55454, USA; (S.D.K.); (D.C.); (A.S.W.); (Z.N.); (A.B.H.)
- Department of Neurosurgery, University of Minnesota Medical Center, Minneapolis, MN 55455, USA; (A.G.); (M.C.P.)
| | - Vasudha Goel
- Department of Anesthesiology, University of Minnesota Medical Center, Minneapolis, MN 55455, USA;
| | - Andrew Grande
- Department of Neurosurgery, University of Minnesota Medical Center, Minneapolis, MN 55455, USA; (A.G.); (M.C.P.)
| | - Donald R. Nixdorf
- Department of Diagnostic & Biological Sciences, School of Dentistry, Minneapolis, MN 55455, USA;
- Department of Radiology, Medical School, Minneapolis, MN 55455, USA
| | - Sarah Benish
- Department of Neurology, University of Minnesota Medical Center, Minneapolis, MN 55455, USA;
| | - Alik S. Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical Center, Minneapolis, MN 55454, USA; (S.D.K.); (D.C.); (A.S.W.); (Z.N.); (A.B.H.)
| | - Ziad Nahas
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical Center, Minneapolis, MN 55454, USA; (S.D.K.); (D.C.); (A.S.W.); (Z.N.); (A.B.H.)
| | - Michael C. Park
- Department of Neurosurgery, University of Minnesota Medical Center, Minneapolis, MN 55455, USA; (A.G.); (M.C.P.)
- Department of Neurology, University of Minnesota Medical Center, Minneapolis, MN 55455, USA;
| | - Tay I. Netoff
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA; (E.M.D.-v.R.); (T.I.N.)
| | - Alexander B. Herman
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical Center, Minneapolis, MN 55454, USA; (S.D.K.); (D.C.); (A.S.W.); (Z.N.); (A.B.H.)
| | - David P. Darrow
- Department of Neurosurgery, University of Minnesota Medical Center, Minneapolis, MN 55455, USA; (A.G.); (M.C.P.)
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24
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Toward personalized medicine in connectomic deep brain stimulation. Prog Neurobiol 2021; 210:102211. [PMID: 34958874 DOI: 10.1016/j.pneurobio.2021.102211] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 12/15/2021] [Accepted: 12/22/2021] [Indexed: 02/08/2023]
Abstract
At the group-level, deep brain stimulation leads to significant therapeutic benefit in a multitude of neurological and neuropsychiatric disorders. At the single-patient level, however, symptoms may sometimes persist despite "optimal" electrode placement at established treatment coordinates. This may be partly explained by limitations of disease-centric strategies that are unable to account for heterogeneous phenotypes and comorbidities observed in clinical practice. Instead, tailoring electrode placement and programming to individual patients' symptom profiles may increase the fraction of top-responding patients. Here, we propose a three-step, circuit-based framework with the aim of developing patient-specific treatment targets that address the unique symptom constellation prevalent in each patient. First, we describe how a symptom network target library could be established by mapping beneficial or undesirable DBS effects to distinct circuits based on (retrospective) group-level data. Second, we suggest ways of matching the resulting symptom networks to circuits defined in the individual patient (template matching). Third, we introduce network blending as a strategy to calculate optimal stimulation targets and parameters by selecting and weighting a set of symptom-specific networks based on the symptom profile and subjective priorities of the individual patient. We integrate the approach with published literature and conclude by discussing limitations and future challenges.
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25
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Sellers KK, Gilron R, Anso J, Louie KH, Shirvalkar PR, Chang EF, Little SJ, Starr PA. Analysis-rcs-data: Open-Source Toolbox for the Ingestion, Time-Alignment, and Visualization of Sense and Stimulation Data From the Medtronic Summit RC+S System. Front Hum Neurosci 2021; 15:714256. [PMID: 34322004 PMCID: PMC8312257 DOI: 10.3389/fnhum.2021.714256] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 06/22/2021] [Indexed: 12/15/2022] Open
Abstract
Closed-loop neurostimulation is a promising therapy being tested and clinically implemented in a growing number of neurological and psychiatric indications. This therapy is enabled by chronically implanted, bidirectional devices including the Medtronic Summit RC+S system. In order to successfully optimize therapy for patients implanted with these devices, analyses must be conducted offline on the recorded neural data, in order to inform optimal sense and stimulation parameters. The file format, volume, and complexity of raw data from these devices necessitate conversion, parsing, and time reconstruction ahead of time-frequency analyses and modeling common to standard neuroscientific analyses. Here, we provide an open-source toolbox written in Matlab which takes raw files from the Summit RC+S and transforms these data into a standardized format amenable to conventional analyses. Furthermore, we provide a plotting tool which can aid in the visualization of multiple data streams and sense, stimulation, and therapy settings. Finally, we describe an analysis module which replicates RC+S on-board power computations, a functionality which can accelerate biomarker discovery. This toolbox aims to accelerate the research and clinical advances made possible by longitudinal neural recordings and adaptive neurostimulation in people with neurological and psychiatric illnesses.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Ro'ee Gilron
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Juan Anso
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Kenneth H Louie
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Prasad R Shirvalkar
- Department of Anesthesiology (Pain Management), Neurology, and Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Simon J Little
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Philip A Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
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26
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Bijanki KR, Metzger BA, Steger CM. Leveraging Intracranial Neural Data to Accelerate Progress Toward Novel Therapies for Psychiatric Symptoms and Disorders. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 6:506-507. [PMID: 33965166 DOI: 10.1016/j.bpsc.2021.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 03/04/2021] [Indexed: 10/21/2022]
Affiliation(s)
- Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas.
| | - Brian A Metzger
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Camille M Steger
- Center for Clinical Investigation, Brigham and Women's Hospital, Boston, Massachusetts
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