1
|
Spiliotis K, Appali R, Fontes Gomes AK, Payonk JP, Adrian S, van Rienen U, Starke J, Köhling R. Utilising activity patterns of a complex biophysical network model to optimise intra-striatal deep brain stimulation. Sci Rep 2024; 14:18919. [PMID: 39143173 PMCID: PMC11324959 DOI: 10.1038/s41598-024-69456-7] [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: 04/25/2024] [Accepted: 08/05/2024] [Indexed: 08/16/2024] Open
Abstract
A large-scale biophysical network model for the isolated striatal body is developed to optimise potential intrastriatal deep brain stimulation applied to, e.g. obsessive-compulsive disorder. The model is based on modified Hodgkin-Huxley equations with small-world connectivity, while the spatial information about the positions of the neurons is taken from a detailed human atlas. The model produces neuronal spatiotemporal activity patterns segregating healthy from pathological conditions. Three biomarkers were used for the optimisation of stimulation protocols regarding stimulation frequency, amplitude and localisation: the mean activity of the entire network, the frequency spectrum of the entire network (rhythmicity) and a combination of the above two. By minimising the deviation of the aforementioned biomarkers from the normal state, we compute the optimal deep brain stimulation parameters, regarding position, amplitude and frequency. Our results suggest that in the DBS optimisation process, there is a clear trade-off between frequency synchronisation and overall network activity, which has also been observed during in vivo studies.
Collapse
Affiliation(s)
- Konstantinos Spiliotis
- Institute of Mathematics, University of Rostock, Rostock, Germany.
- Laboratory of Mathematics and Informatics (ISCE), Department of Civil Engineering, Democritus University of Thrace, Xanthi, Greece.
| | - Revathi Appali
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
| | | | - Jan Philipp Payonk
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
| | - Simon Adrian
- Faculty of Computer Science and Electrical Engineering, University of Rostock, Rostock, Germany
| | - Ursula van Rienen
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
- Department of Life, Light and Matter, University of Rostock, Rostock, Germany
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
| | - Jens Starke
- Institute of Mathematics, University of Rostock, Rostock, Germany
| | - Rüdiger Köhling
- Department of Life, Light and Matter, University of Rostock, Rostock, Germany
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
- Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany
| |
Collapse
|
2
|
Smith JN, Dorfman N, Hurley M, Cenolli I, Kostick-Quenet K, Storch EA, Lázaro-Muñoz G, Blumenthal-Barby J. Adolescent OCD Patient and Caregiver Perspectives on Identity, Authenticity, and Normalcy in Potential Deep Brain Stimulation Treatment. Camb Q Healthc Ethics 2024:1-14. [PMID: 38602092 DOI: 10.1017/s0963180124000203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2024]
Abstract
The ongoing debate within neuroethics concerning the degree to which neuromodulation such as deep brain stimulation (DBS) changes the personality, identity, and agency (PIA) of patients has paid relatively little attention to the perspectives of prospective patients. Even less attention has been given to pediatric populations. To understand patients' views about identity changes due to DBS in obsessive-compulsive disorder (OCD), the authors conducted and analyzed semistructured interviews with adolescent patients with OCD and their parents/caregivers. Patients were asked about projected impacts to PIA generally due to DBS. All patient respondents and half of caregivers reported that DBS would impact patient self-identity in significant ways. For example, many patients expressed how DBS could positively impact identity by allowing them to explore their identities free from OCD. Others voiced concerns that DBS-related resolution of OCD might negatively impact patient agency and authenticity. Half of patients expressed that DBS may positively facilitate social access through relieving symptoms, while half indicated that DBS could increase social stigma. These views give insights into how to approach decision-making and informed consent if DBS for OCD becomes available for adolescents. They also offer insights into adolescent experiences of disability identity and "normalcy" in the context of OCD.
Collapse
Affiliation(s)
- Jared N Smith
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, USA
| | - Natalie Dorfman
- Department of Philosophy, University of Washington, Seattle, WA, USA
| | - Meghan Hurley
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, USA
| | - Ilona Cenolli
- Center for Bioethics, Harvard Medical School, Boston, MA, USA
| | - Kristin Kostick-Quenet
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, USA
| | - Eric A Storch
- Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | | | | |
Collapse
|
3
|
Johnson KA, Okun MS, Scangos KW, Mayberg HS, de Hemptinne C. Deep brain stimulation for refractory major depressive disorder: a comprehensive review. Mol Psychiatry 2024; 29:1075-1087. [PMID: 38287101 DOI: 10.1038/s41380-023-02394-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 12/18/2023] [Accepted: 12/21/2023] [Indexed: 01/31/2024]
Abstract
Deep brain stimulation (DBS) has emerged as a promising treatment for select patients with refractory major depressive disorder (MDD). The clinical effectiveness of DBS for MDD has been demonstrated in meta-analyses, open-label studies, and a few controlled studies. However, randomized controlled trials have yielded mixed outcomes, highlighting challenges that must be addressed prior to widespread adoption of DBS for MDD. These challenges include tracking MDD symptoms objectively to evaluate the clinical effectiveness of DBS with sensitivity and specificity, identifying the patient population that is most likely to benefit from DBS, selecting the optimal patient-specific surgical target and stimulation parameters, and understanding the mechanisms underpinning the therapeutic benefits of DBS in the context of MDD pathophysiology. In this review, we provide an overview of the latest clinical evidence of MDD DBS effectiveness and the recent technological advancements that could transform our understanding of MDD pathophysiology, improve the clinical outcomes for MDD DBS, and establish a path forward to develop more effective neuromodulation therapies to alleviate depressive symptoms.
Collapse
Affiliation(s)
- Kara A Johnson
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- Department of Neurology, University of Florida, Gainesville, FL, USA
| | - Michael S Okun
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- Department of Neurology, University of Florida, Gainesville, FL, USA
| | - Katherine W Scangos
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Coralie de Hemptinne
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA.
- Department of Neurology, University of Florida, Gainesville, FL, USA.
| |
Collapse
|
4
|
Ranjan M, Mahoney JJ, Rezai AR. Neurosurgical neuromodulation therapy for psychiatric disorders. Neurotherapeutics 2024; 21:e00366. [PMID: 38688105 PMCID: PMC11070709 DOI: 10.1016/j.neurot.2024.e00366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 04/09/2024] [Accepted: 04/16/2024] [Indexed: 05/02/2024] Open
Abstract
Psychiatric disorders are among the leading contributors to global disease burden and disability. A significant portion of patients with psychiatric disorders remain treatment-refractory to best available therapy. With insights from the neurocircuitry of psychiatric disorders and extensive experience of neuromodulation with deep brain stimulation (DBS) in movement disorders, DBS is increasingly being considered to modulate the neural network in psychiatric disorders. Currently, obsessive-compulsive disorder (OCD) is the only U.S. FDA (United States Food and Drug Administration) approved DBS indication for psychiatric disorders. Medically refractory depression, addiction, and other psychiatric disorders are being explored for DBS neuromodulation. Studies evaluating DBS for psychiatric disorders are promising but lack larger, controlled studies. This paper presents a brief review and the current state of DBS and other neurosurgical neuromodulation therapies for OCD and other psychiatric disorders. We also present a brief review of MR-guided Focused Ultrasound (MRgFUS), a novel form of neurosurgical neuromodulation, which can target deep subcortical structures similar to DBS, but in a noninvasive fashion. Early experiences of neurosurgical neuromodulation therapies, including MRgFUS neuromodulation are encouraging in psychiatric disorders; however, they remain investigational. Currently, DBS and VNS are the only FDA approved neurosurgical neuromodulation options in properly selected cases of OCD and depression, respectively.
Collapse
Affiliation(s)
- Manish Ranjan
- Department of Neurosurgery, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA.
| | - James J Mahoney
- Department of Behavioral Medicine and Psychiatry, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA; Department of Neuroscience, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA
| | - Ali R Rezai
- Department of Neurosurgery, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA; Department of Neuroscience, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA
| |
Collapse
|
5
|
Persad AR, Coote NR, Waterhouse K, McLeod S, Norton JA, Gould L, Vitali AM. Medial forebrain bundle stimulation after failed subcallosal cingulate deep brain stimulation for treatment-resistant depression: Efficacy of a dual deep brain stimulation system for depression. Brain Stimul 2024; 17:68-70. [PMID: 38159905 DOI: 10.1016/j.brs.2023.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 12/26/2023] [Indexed: 01/03/2024] Open
Affiliation(s)
- Amit R Persad
- Department of Neurological Surgery, Stanford University, Stanford, CA, USA
| | - Nicole R Coote
- Division of Neurosurgery, Department of Surgery, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Karen Waterhouse
- Division of Neurosurgery, Department of Surgery, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Sara McLeod
- Division of Neurosurgery, Department of Surgery, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Jonathan A Norton
- Division of Neurosurgery, Department of Surgery, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Layla Gould
- Division of Neurosurgery, Department of Surgery, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Aleksander M Vitali
- Division of Neurosurgery, Department of Surgery, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
| |
Collapse
|
6
|
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.
Collapse
Affiliation(s)
- Alik S Widge
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
| |
Collapse
|
7
|
Yuan Z, Qi Z, Wang R, Cui Y, An S, Wu G, Feng Q, Lin R, Dai R, Li A, Gong H, Luo Q, Fu L, Luo M. A corticoamygdalar pathway controls reward devaluation and depression using dynamic inhibition code. Neuron 2023; 111:3837-3853.e5. [PMID: 37734380 DOI: 10.1016/j.neuron.2023.08.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 07/03/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023]
Abstract
Reward devaluation adaptively controls reward intake. It remains unclear how cortical circuits causally encode reward devaluation in healthy and depressed states. Here, we show that the neural pathway from the anterior cingulate cortex (ACC) to the basolateral amygdala (BLA) employs a dynamic inhibition code to control reward devaluation and depression. Fiber photometry and imaging of ACC pyramidal neurons reveal reward-induced inhibition, which weakens during satiation and becomes further attenuated in depression mouse models. Ablating or inhibiting these neurons desensitizes reward devaluation, causes reward intake increase and ultimate obesity, and ameliorates depression, whereas activating the cells sensitizes reward devaluation, suppresses reward consumption, and produces depression-like behaviors. Among various ACC neuron subpopulations, the BLA-projecting subset bidirectionally regulates reward devaluation and depression-like behaviors. Our study thus uncovers a corticoamygdalar circuit that encodes reward devaluation via blunted inhibition and suggests that enhancing inhibition within this circuit may offer a therapeutic approach for treating depression.
Collapse
Affiliation(s)
- Zhengwei Yuan
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; School of Life Sciences, Tsinghua University, Beijing 100084, China; National Institute of Biological Sciences, Beijing 102206, China; Chinese Institute for Brain Research, Beijing 102206, China; Tsinghua Institute of Multidisciplinary Biomedical Research (TIMBR), Beijing 102206, China
| | - Zhongyang Qi
- National Institute of Biological Sciences, Beijing 102206, China; Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Ruiyu Wang
- National Institute of Biological Sciences, Beijing 102206, China; School of Life Sciences, Peking University, Beijing 100871, China
| | - Yuting Cui
- National Institute of Biological Sciences, Beijing 102206, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Sile An
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Guoli Wu
- National Institute of Biological Sciences, Beijing 102206, China
| | - Qiru Feng
- National Institute of Biological Sciences, Beijing 102206, China
| | - Rui Lin
- National Institute of Biological Sciences, Beijing 102206, China; Tsinghua Institute of Multidisciplinary Biomedical Research (TIMBR), Beijing 102206, China
| | - Ruicheng Dai
- National Institute of Biological Sciences, Beijing 102206, China; School of Life Sciences, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Anan Li
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Hui Gong
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Qingming Luo
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Ling Fu
- Wuhan National Laboratory for Optoelectronics-Huazhong, Britton Chance Center for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Minmin Luo
- National Institute of Biological Sciences, Beijing 102206, China; Chinese Institute for Brain Research, Beijing 102206, China; Tsinghua Institute of Multidisciplinary Biomedical Research (TIMBR), Beijing 102206, China; Research Unit of Medical Neurobiology, Chinese Academy of Medical Sciences, Beijing 100005, China; New Cornerstone Science Laboratory, Shenzhen 518054, China; Beijing Tiantan Hospital, 100070 Beijing, China.
| |
Collapse
|
8
|
Ramírez-Moreno MA, Cruz-Garza JG, Acharya A, Chatufale G, Witt W, Gelok D, Reza G, Contreras-Vidal JL. Brain-to-brain communication during musical improvisation: a performance case study. F1000Res 2023; 11:989. [PMID: 37809054 PMCID: PMC10558998 DOI: 10.12688/f1000research.123515.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/01/2023] [Indexed: 10/10/2023] Open
Abstract
Understanding and predicting others' actions in ecological settings is an important research goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) methodology to analyze inter-brain communication between professional musicians during a live jazz performance. Specifically, bispectral analysis was conducted to assess the synchronization of scalp electroencephalographic (EEG) signals from three expert musicians during a three-part 45 minute jazz performance, during which a new musician joined every five minutes. The bispectrum was estimated for all musician dyads, electrode combinations, and five frequency bands. The results showed higher bispectrum in the beta and gamma frequency bands (13-50 Hz) when more musicians performed together, and when they played a musical phrase synchronously. Positive bispectrum amplitude changes were found approximately three seconds prior to the identified synchronized performance events suggesting preparatory cortical activity predictive of concerted behavioral action. Moreover, a higher amount of synchronized EEG activity, across electrode regions, was observed as more musicians performed, with inter-brain synchronization between the temporal, parietal, and occipital regions the most frequent. Increased synchrony between the musicians' brain activity reflects shared multi-sensory processing and movement intention in a musical improvisation task.
Collapse
Affiliation(s)
- Mauricio A. Ramírez-Moreno
- School of Engineering and Sciences, Mechatronics Department, Tecnologico de Monterrey, Monterrey, Nuevo Leon, 64849, Mexico
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
| | - Jesús G. Cruz-Garza
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
| | - Akanksha Acharya
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
| | - Girija Chatufale
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
- University of California, Los Angeles, Los Angeles, California, 90095, USA
| | - Woody Witt
- Moores School of Music, University of Houston, Houston, Texas, 77004, USA
- Houston Community College, Houston, Texas, 77004, USA
| | - Dan Gelok
- Moores School of Music, University of Houston, Houston, Texas, 77004, USA
| | | | - José L. Contreras-Vidal
- Noninvasive Brain-Machine Interface Systems Laboratory, NSF IUCRC BRAIN, University of Houston, Houston, Texas, 77004, USA
| |
Collapse
|
9
|
Zelmann R, Paulk AC, Tian F, Balanza Villegas GA, Dezha Peralta J, Crocker B, Cosgrove GR, Richardson RM, Williams ZM, Dougherty DD, Purdon PL, Cash SS. Differential cortical network engagement during states of un/consciousness in humans. Neuron 2023; 111:3479-3495.e6. [PMID: 37659409 PMCID: PMC10843836 DOI: 10.1016/j.neuron.2023.08.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 06/13/2023] [Accepted: 08/08/2023] [Indexed: 09/04/2023]
Abstract
What happens in the human brain when we are unconscious? Despite substantial work, we are still unsure which brain regions are involved and how they are impacted when consciousness is disrupted. Using intracranial recordings and direct electrical stimulation, we mapped global, network, and regional involvement during wake vs. arousable unconsciousness (sleep) vs. non-arousable unconsciousness (propofol-induced general anesthesia). Information integration and complex processing we`re reduced, while variability increased in any type of unconscious state. These changes were more pronounced during anesthesia than sleep and involved different cortical engagement. During sleep, changes were mostly uniformly distributed across the brain, whereas during anesthesia, the prefrontal cortex was the most disrupted, suggesting that the lack of arousability during anesthesia results not from just altered overall physiology but from a disconnection between the prefrontal and other brain areas. These findings provide direct evidence for different neural dynamics during loss of consciousness compared with loss of arousability.
Collapse
Affiliation(s)
- Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA.
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| | - Fangyun Tian
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Patrick L Purdon
- Department of Anesthesia, Massachusetts General Hospital, Boston, MA, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
| |
Collapse
|
10
|
Sabé M, Sulstarova A, Chen C, Hyde J, Poulet E, Aleman A, Downar J, Brandt V, Mallet L, Sentissi O, Nitsche MA, Bikson M, Brunoni AR, Cortese S, Solmi M. A century of research on neuromodulation interventions: A scientometric analysis of trends and knowledge maps. Neurosci Biobehav Rev 2023; 152:105300. [PMID: 37392815 DOI: 10.1016/j.neubiorev.2023.105300] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/24/2023] [Accepted: 06/27/2023] [Indexed: 07/03/2023]
Abstract
Interest in neurostimulation interventions has significantly grown in recent decades, yet a scientometric analysis objectively mapping scientific knowledge and recent trends remains unpublished. Using relevant keywords, we conducted a search in the Web of Science Core Collection on September 23, 2022, retrieving a total of 47,681 documents with 987,979 references. We identified two prominent research trends: 'noninvasive brain stimulation' and 'invasive brain stimulation.' These methods have interconnected over time, forming a cluster focused on evidence synthesis. Noteworthy emerging research trends encompassed 'transcutaneous auricular vagus nerve stimulation,' 'DBS/epilepsy in the pediatric population,' 'spinal cord stimulation,' and 'brain-machine interface.' While progress has been made for various neurostimulation interventions, their approval as adjuvant treatments remains limited, and optimal stimulation parameters lack consensus. Enhancing communication between experts of both neurostimulation types and encouraging novel translational research could foster further development. These findings offer valuable insights for funding agencies and research groups, guiding future directions in the field.
Collapse
Affiliation(s)
- Michel Sabé
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, 2, Chemin du Petit-Bel-Air, CH-1226 Thonex, Switzerland.
| | - Adi Sulstarova
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, 2, Chemin du Petit-Bel-Air, CH-1226 Thonex, Switzerland
| | - Chaomei Chen
- College of Computing & Informatics, Drexel University, Philadelphia, PA, USA
| | - Joshua Hyde
- Centre for Innovation in Mental Health, School of Psychology, University of Southampton, Southampton, UK
| | - Emmanuel Poulet
- Centre Hospitalier Le Vinatier, Bron, France; INSERM, U1028, CNRS, UMR5292, France; University Lyon 1, F-69000 Villeurbanne, France; Lyon Neuroscience Research Center, PSYR2 Team, F-69000 Lyon, France; Université Jean Monnet Saint Etienne, F-42000, France; Psychiatric Emergency Service, Hospices Civils de Lyon, F-69005 Lyon, France
| | - André Aleman
- University of Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, University Medical Center Groningen, Groningen, the Netherlands
| | - Jonathan Downar
- Krembil Research Institute, University Health Network, Toronto, ON, Canada; MRI-Guided rTMS Clinic, University Health Network, Toronto, ON, Canada; Centre for Mental Health, University Health Network, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Valerie Brandt
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK; Clinic of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hanover, Germany
| | - Luc Mallet
- Univ Paris-Est Créteil, DMU IMPACT, Département Médical-Universitaire de Psychiatrie et d'Addictologie, Hôpitaux Universitaires Henri Mondor, Albert Chenevier, Assistance Publique-Hôpitaux de Paris, Créteil, France; Sorbonne Université, Institut du Cerveau, Paris Brain Institute, ICM, Inserm, CNRS, Paris, France; Department of Mental Health and Psychiatry, Global Health Institute, University of Geneva, Geneva, Switzerland
| | - Othman Sentissi
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, 2, Chemin du Petit-Bel-Air, CH-1226 Thonex, Switzerland
| | - Michael A Nitsche
- Dept. Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund, Germany; Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy and University Clinic of Child and Adolescent Psychiatry and Psychotherapy, Germany
| | - Marom Bikson
- Department of Biomedical Engineering, City College of New York, New York, NY, USA
| | - André Russowsky Brunoni
- Departamento de Clínica Médica da Faculdade de Medicina da Universidade de São Paulo, Universidade de São Paulo, São Paulo, Brazil; Instituto de Psiquiatria do Hospital das Clínicas da Faculdade de Medicina da USP, São Paulo, Brazil
| | - Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK; Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK; Solent NHS Trust, Southampton, UK; Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York, NY, USA; Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
| | - Marco Solmi
- Department of Psychiatry, University of Ottawa, Ontario, Canada; Department of Mental Health, The Ottawa Hospital, Ontario, Canada; Ottawa Hospital Research Institute (OHRI) Clinical Epidemiology Program University of Ottawa, Ottawa, Ontario, Canada; School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada; Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| |
Collapse
|
11
|
Versalovic E, Klein E, Goering S, Ngo Q, Gliske K, Boulicault M, Sullivan LS, Thomas MJ, Widge AS. Deep Brain Stimulation for Substance Use Disorders? An Exploratory Qualitative Study of Perspectives of People Currently in Treatment. J Addict Med 2023; 17:e246-e254. [PMID: 37579102 PMCID: PMC10417220 DOI: 10.1097/adm.0000000000001150] [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: 06/07/2022] [Accepted: 01/05/2023] [Indexed: 03/06/2023]
Abstract
OBJECTIVE Although previous studies have discussed the promise of deep brain stimulation (DBS) as a possible treatment for substance use disorders (SUDs) and collected researcher perspectives on possible ethical issues surrounding it, none have consulted people with SUDs themselves. We addressed this gap by interviewing people with SUDs. METHODS Participants viewed a short video introducing DBS, followed by a 1.5-hour semistructured interview on their experiences with SUDs and their perspective on DBS as a possible treatment option. Interviews were analyzed by multiple coders who iteratively identified salient themes. RESULTS We interviewed 20 people in 12-step-based, inpatient treatment programs (10 [50%] White/Caucasian, 7 Black/African American [35%], 2 Asian [10%], 1 Hispanic/Latino [5%], and 1 [5%] Alaska Native/American Indian; 9 women [45%], 11 men [55%]). Interviewees described a variety of barriers they currently faced through the course of their disease that mirrored barriers often associated with DBS (stigma, invasiveness, maintenance burdens, privacy risks) and thus made them more open to the possibility of DBS as a future treatment option. CONCLUSIONS Individuals with SUDs gave relatively less weight to surgical risks and clinical burdens associated with DBS than previous surveys of provider attitudes anticipated. These differences derived largely from their experiences living with an often-fatal disease and encountering limitations of current treatment options. These findings support the study of DBS as a treatment option for SUDs, with extensive input from people with SUDs and advocates.
Collapse
|
12
|
Nagrale SS, Yousefi A, Netoff TI, Widge AS. In silicodevelopment and validation of Bayesian methods for optimizing deep brain stimulation to enhance cognitive control. J Neural Eng 2023; 20:036015. [PMID: 37105164 PMCID: PMC10193041 DOI: 10.1088/1741-2552/acd0d5] [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: 08/30/2022] [Revised: 03/18/2023] [Accepted: 04/27/2023] [Indexed: 04/29/2023]
Abstract
Objective.deep brain stimulation (DBS) of the ventral internal capsule/striatum (VCVS) is a potentially effective treatment for several mental health disorders when conventional therapeutics fail. Its effectiveness, however, depends on correct programming to engage VCVS sub-circuits. VCVS programming is currently an iterative, time-consuming process, with weeks between setting changes and reliance on noisy, subjective self-reports. An objective measure of circuit engagement might allow individual settings to be tested in seconds to minutes, reducing the time to response and increasing patient and clinician confidence in the chosen settings. Here, we present an approach to measuring and optimizing that circuit engagement.Approach.we leverage prior results showing that effective VCVS DBS engages cognitive control circuitry and improves performance on the multi-source interference task, that this engagement depends primarily on which contact(s) are activated, and that circuit engagement can be tracked through a state space modeling framework. We develop a simulation framework based on those empirical results, then combine this framework with an adaptive optimizer to simulate a principled exploration of electrode contacts and identify the contacts that maximally improve cognitive control. We explore multiple optimization options (algorithms, number of inputs, speed of stimulation parameter changes) and compare them on problems of varying difficulty.Main results.we show that an upper confidence bound algorithm outperforms other optimizers, with roughly 80% probability of convergence to a global optimum when used in a majority-vote ensemble.Significance.we show that the optimization can converge even with lag between stimulation and effect, and that a complete optimization can be done in a clinically feasible timespan (a few hours). Further, the approach requires no specialized recording or imaging hardware, and thus could be a scalable path to expand the use of DBS in psychiatric and other non-motor applications.
Collapse
Affiliation(s)
- Sumedh S Nagrale
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States of America
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States of America
| | - Ali Yousefi
- Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA, United States of America
| | - Theoden I Netoff
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States of America
| | - Alik S Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States of America
| |
Collapse
|
13
|
Widge AS. Closed-Loop Deep Brain Stimulation for Psychiatric Disorders. Harv Rev Psychiatry 2023; 31:162-171. [PMID: 37171475 PMCID: PMC10188203 DOI: 10.1097/hrp.0000000000000367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
ABSTRACT Deep brain stimulation (DBS) is a well-established approach to treating medication-refractory neurological disorders and holds promise for treating psychiatric disorders. Despite strong open-label results in extremely refractory patients, DBS has struggled to meet endpoints in randomized controlled trials. A major challenge is stimulation "dosing"-DBS systems have many adjustable parameters, and clinicians receive little feedback on whether they have chosen the correct parameters for an individual patient. Multiple groups have proposed closed loop technologies as a solution. These systems sense electrical activity, identify markers of an (un)desired state, then automatically deliver or adjust stimulation to alter that electrical state. Closed loop DBS has been successfully deployed in movement disorders and epilepsy. The availability of that technology, as well as advances in opportunities for invasive research with neurosurgical patients, has yielded multiple pilot demonstrations in psychiatric illness. Those demonstrations split into two schools of thought, one rooted in well-established diagnoses and symptom scales, the other in the more experimental Research Domain Criteria (RDoC) framework. Both are promising, and both are limited by the boundaries of current stimulation technology. They are in turn driving advances in implantable recording hardware, signal processing, and stimulation paradigms. The combination of these advances is likely to change both our understanding of psychiatric neurobiology and our treatment toolbox, though the timeframe may be limited by the realities of implantable device development.
Collapse
Affiliation(s)
- Alik S Widge
- From the Department of Psychiatry & Behavioral Sciences and Medical Discovery Team on Addictions, University of Minnesota
| |
Collapse
|
14
|
Bergs ACF, Liewald JF, Rodriguez-Rozada S, Liu Q, Wirt C, Bessel A, Zeitzschel N, Durmaz H, Nozownik A, Dill H, Jospin M, Vierock J, Bargmann CI, Hegemann P, Wiegert JS, Gottschalk A. All-optical closed-loop voltage clamp for precise control of muscles and neurons in live animals. Nat Commun 2023; 14:1939. [PMID: 37024493 PMCID: PMC10079764 DOI: 10.1038/s41467-023-37622-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
Excitable cells can be stimulated or inhibited by optogenetics. Since optogenetic actuation regimes are often static, neurons and circuits can quickly adapt, allowing perturbation, but not true control. Hence, we established an optogenetic voltage-clamp (OVC). The voltage-indicator QuasAr2 provides information for fast, closed-loop optical feedback to the bidirectional optogenetic actuator BiPOLES. Voltage-dependent fluorescence is held within tight margins, thus clamping the cell to distinct potentials. We established the OVC in muscles and neurons of Caenorhabditis elegans, and transferred it to rat hippocampal neurons in slice culture. Fluorescence signals were calibrated to electrically measured potentials, and wavelengths to currents, enabling to determine optical I/V-relationships. The OVC reports on homeostatically altered cellular physiology in mutants and on Ca2+-channel properties, and can dynamically clamp spiking in C. elegans. Combining non-invasive imaging with control capabilities of electrophysiology, the OVC facilitates high-throughput, contact-less electrophysiology in individual cells and paves the way for true optogenetic control in behaving animals.
Collapse
Affiliation(s)
- Amelie C F Bergs
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Jana F Liewald
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Silvia Rodriguez-Rozada
- Research Group Synaptic Wiring and Information Processing, Center for Molecular Neurobiology Hamburg, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
| | - Qiang Liu
- Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior, The Rockefeller University, New York, NY, 10065, USA
- Department of Neuroscience, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong, China
| | - Christin Wirt
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Artur Bessel
- Independent Researcher, Melatener Strasse 93, 52074, Aachen, Germany
| | - Nadja Zeitzschel
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Hilal Durmaz
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Adrianna Nozownik
- Research Group Synaptic Wiring and Information Processing, Center for Molecular Neurobiology Hamburg, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
| | - Holger Dill
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Maëlle Jospin
- Université Claude Bernard Lyon 1, Institut NeuroMyoGène, 8 Avenue Rockefeller, 69008, Lyon, France
| | - Johannes Vierock
- Institute for Biology, Experimental Biophysics, Humboldt University, 10115, Berlin, Germany
| | - Cornelia I Bargmann
- Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior, The Rockefeller University, New York, NY, 10065, USA
- Chan Zuckerberg Initiative, Palo Alto, CA, USA
| | - Peter Hegemann
- Institute for Biology, Experimental Biophysics, Humboldt University, 10115, Berlin, Germany
| | - J Simon Wiegert
- Research Group Synaptic Wiring and Information Processing, Center for Molecular Neurobiology Hamburg, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
- Medical Faculty Mannheim, University of Heidelberg, Ludolf-Krehl-Strasse 13-17, 68167, Mannheim, Germany
| | - Alexander Gottschalk
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany.
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany.
| |
Collapse
|
15
|
Basu I, Yousefi A, Crocker B, Zelmann R, Paulk AC, Peled N, Ellard KK, Weisholtz DS, Cosgrove GR, Deckersbach T, Eden UT, Eskandar EN, Dougherty DD, Cash SS, Widge AS. Closed-loop enhancement and neural decoding of cognitive control in humans. Nat Biomed Eng 2023; 7:576-588. [PMID: 34725508 PMCID: PMC9056584 DOI: 10.1038/s41551-021-00804-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 09/02/2021] [Indexed: 12/20/2022]
Abstract
Deficits in cognitive control-that is, in the ability to withhold a default pre-potent response in favour of a more adaptive choice-are common in depression, anxiety, addiction and other mental disorders. Here we report proof-of-concept evidence that, in participants undergoing intracranial epilepsy monitoring, closed-loop direct stimulation of the internal capsule or striatum, especially the dorsal sites, enhances the participants' cognitive control during a conflict task. We also show that closed-loop stimulation upon the detection of lapses in cognitive control produced larger behavioural changes than open-loop stimulation, and that task performance for single trials can be directly decoded from the activity of a small number of electrodes via neural features that are compatible with existing closed-loop brain implants. Closed-loop enhancement of cognitive control might remediate underlying cognitive deficits and aid the treatment of severe mental disorders.
Collapse
Affiliation(s)
- Ishita Basu
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ali Yousefi
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Departments of Computer Science and Neuroscience, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Noam Peled
- Department of Radiology, MGH/HST Martinos Center for Biomedical Imaging and Harvard Medical School, Boston, MA, USA
| | - Kristen K Ellard
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - G Rees Cosgrove
- Department of Neurological Surgery, Brigham & Womens Hospital, Boston, MA, USA
| | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Uri T Eden
- Department of Mathematics and Statistics, Boston University, Boston, MA, USA
| | - Emad N Eskandar
- Department of Neurological Surgery, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurological Surgery, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Alik S Widge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA.
| |
Collapse
|
16
|
Campos ACP, Pople C, Silk E, Surendrakumar S, Rabelo TK, Meng Y, Gouveia FV, Lipsman N, Giacobbe P, Hamani C. Neurochemical mechanisms of deep brain stimulation for depression in animal models. Eur Neuropsychopharmacol 2023; 68:11-26. [PMID: 36640729 DOI: 10.1016/j.euroneuro.2022.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 12/12/2022] [Accepted: 12/14/2022] [Indexed: 01/13/2023]
Abstract
Deep brain stimulation (DBS) has emerged as a neuromodulation therapy for treatment-resistant depression, but its actual efficacy and mechanisms of action are still unclear. Changes in neurochemical transmission are important mechanisms of antidepressant therapies. Here, we review the preclinical DBS literature reporting behavioural and neurochemical data associated with its antidepressant-like effects. The most commonly studied target in preclinical models was the ventromedial prefrontal cortex (vmPFC). In rodents, DBS delivered to this target induced serotonin (5-HT) release and increased 5-HT1B receptor expression. The antidepressant-like effects of vmPFC DBS seemed to be independent of the serotonin transporter and potentially mediated by the direct modulation of prefrontal projections to the raphe. Adenosinergic and glutamatergic transmission might have also play a role. Medial forebrain bundle (MFB) DBS increased dopamine levels and reduced D2 receptor expression, whereas nucleus accumbens (NAcc), and lateral habenula (LHb) stimulation increased catecholamine levels in different brain regions. In rodents, subthalamic nucleus (STN) DBS induced robust depression-like responses associated with a reduction in serotonergic transmission, as revealed by a decrease in serotonin release. Some of these effects seemed to be mediated by 5HT1A receptors. In conclusion, the antidepressant-like effects of DBS in preclinical models have been well documented in multiple targets. Though variable mechanisms have been proposed, DBS-induced acute and long-term changes in neurochemical substrates seem to play an important role in the antidepressant-like effects of this therapy.
Collapse
Affiliation(s)
- Ana Carolina P Campos
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Christopher Pople
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Esther Silk
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Shanan Surendrakumar
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Thallita K Rabelo
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Ying Meng
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Flavia Venetucci Gouveia
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Nir Lipsman
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Hurvitz Brain Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Division of Neurosurgery, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Peter Giacobbe
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Hurvitz Brain Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Neuropsychiatry Program, Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Clement Hamani
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Hurvitz Brain Sciences Centre, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Division of Neurosurgery, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada.
| |
Collapse
|
17
|
Concerns with the promotion of deep brain stimulation for obsessive-compulsive disorder. Nat Med 2023; 29:18. [PMID: 36604537 DOI: 10.1038/s41591-022-02087-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
|
18
|
Pinotsis DA, Fitzgerald S, See C, Sementsova A, Widge AS. Toward biophysical markers of depression vulnerability. Front Psychiatry 2022; 13:938694. [PMID: 36329919 PMCID: PMC9622949 DOI: 10.3389/fpsyt.2022.938694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Accepted: 09/22/2022] [Indexed: 11/13/2022] Open
Abstract
A major difficulty with treating psychiatric disorders is their heterogeneity: different neural causes can lead to the same phenotype. To address this, we propose describing the underlying pathophysiology in terms of interpretable, biophysical parameters of a neural model derived from the electroencephalogram. We analyzed data from a small patient cohort of patients with depression and controls. Using DCM, we constructed biophysical models that describe neural dynamics in a cortical network activated during a task that is used to assess depression state. We show that biophysical model parameters are biomarkers, that is, variables that allow subtyping of depression at a biological level. They yield a low dimensional, interpretable feature space that allowed description of differences between individual patients with depressive symptoms. They could capture internal heterogeneity/variance of depression state and achieve significantly better classification than commonly used EEG features. Our work is a proof of concept that a combination of biophysical models and machine learning may outperform earlier approaches based on classical statistics and raw brain data.
Collapse
Affiliation(s)
- D. A. Pinotsis
- Centre for Mathematical Neuroscience and Psychology, Department of Psychology, City, University of London, London, United Kingdom
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - S. Fitzgerald
- Centre for Mathematical Neuroscience and Psychology, Department of Psychology, City, University of London, London, United Kingdom
| | - C. See
- Department of Computer Science, City, University of London, London, United Kingdom
| | - A. Sementsova
- Department of Computer Science, City, University of London, London, United Kingdom
| | - A. S. Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
| |
Collapse
|
19
|
Widge AS. Deep Brain Stimulation for Treatment-Resistant Mental Illness. Psychiatr Ann 2022. [DOI: 10.3928/00485713-20220621-02] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
|
20
|
Liu W, Qiu JL, Zheng WL, Lu BL. Comparing Recognition Performance and Robustness of Multimodal Deep Learning Models for Multimodal Emotion Recognition. IEEE Trans Cogn Dev Syst 2022. [DOI: 10.1109/tcds.2021.3071170] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Wei Liu
- Department of Computer Science and Engineering, the Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering, Brain Science and Technology Research Center, Center for Brain-Like Computing and Machine Intelligence, Qing Yuan Research Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Jie-Lin Qiu
- Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Wei-Long Zheng
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bao-Liang Lu
- Department of Computer Science and Engineering, the Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering, Brain Science and Technology Research Center, Center for Brain-Like Computing and Machine Intelligence, Qing Yuan Research Institute, Shanghai Jiao Tong University, Shanghai, China
| |
Collapse
|
21
|
Fang H, Yang Y. Designing and Validating a Robust Adaptive Neuromodulation Algorithm for Closed-Loop Control of Brain States. J Neural Eng 2022; 19. [PMID: 35576912 DOI: 10.1088/1741-2552/ac7005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 05/16/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Neuromodulation systems that use closed-loop brain stimulation to control brain states can provide new therapies for brain disorders. To date, closed-loop brain stimulation has largely used linear time-invariant controllers. However, nonlinear time-varying brain network dynamics and external disturbances can appear during real-time stimulation, collectively leading to real-time model uncertainty. Real-time model uncertainty can degrade the performance or even cause instability of time-invariant controllers. Three problems need to be resolved to enable accurate and stable control under model uncertainty. First, an adaptive controller is needed to track the model uncertainty. Second, the adaptive controller additionally needs to be robust to noise and disturbances. Third, theoretical analyses of stability and robustness are needed as prerequisites for stable operation of the controller in practical applications. APPROACH We develop a robust adaptive neuromodulation algorithm that solves the above three problems. First, we develop a state-space brain network model that explicitly includes nonlinear terms of real-time model uncertainty and design an adaptive controller to track and cancel the model uncertainty. Second, to improve the robustness of the adaptive controller, we design two linear filters to increase steady-state control accuracy and reduce sensitivity to high-frequency noise and disturbances. Third, we conduct theoretical analyses to prove the stability of the neuromodulation algorithm and establish a trade-off between stability and robustness, which we further use to optimize the algorithm design. Finally, we validate the algorithm using comprehensive Monte Carlo simulations that span a broad range of model nonlinearity, uncertainty, and complexity. MAIN RESULTS The robust adaptive neuromodulation algorithm accurately tracks various types of target brain state trajectories, enables stable and robust control, and significantly outperforms state-of-the-art neuromodulation algorithms. SIGNIFICANCE Our algorithm has implications for future designs of precise, stable, and robust closed-loop brain stimulation systems to treat brain disorders and facilitate brain functions.
Collapse
Affiliation(s)
- Hao Fang
- University of Central Florida, Research 1 Room 334, 313/316, University of Central Florida, 4353 Scorpius St., Orlando, Florida, 32816-2368, UNITED STATES
| | - Yuxiao Yang
- Department of Electrical and Computer Engineering, University of Central Florida, 4353 Scorpius St., Orlando, Florida, 32816-2368, UNITED STATES
| |
Collapse
|
22
|
Sobstyl M, Kupryjaniuk A, Prokopienko M, Rylski M. Subcallosal Cingulate Cortex Deep Brain Stimulation for Treatment-Resistant Depression: A Systematic Review. Front Neurol 2022; 13:780481. [PMID: 35432155 PMCID: PMC9012165 DOI: 10.3389/fneur.2022.780481] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 01/04/2022] [Indexed: 11/25/2022] Open
Abstract
Background Deep brain stimulation (DBS) is considered a relatively new and still experimental therapeutic modality for treatment-resistant depression (TRD). There is clinical evidence to suggest that stimulation of the subcallosal cingulate cortex (SCC) involved in the pathogenesis of TRD may exert an antidepressant effect. Aims To conduct a systematic review of current studies, such as randomized clinical trials (RCTs), open-label trials, and placebo-controlled trials, examining SCC DBS for TRD in human participants. Method A formal review of the academic literature was performed using the Medical Literature, Analysis, and Retrieval System Online (MEDLINE) and Cochrane Central Register of Controlled Trials (CENTRAL) databases. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Suitable studies were screened and assessed based on patient characteristics, clinical outcomes, adverse events related to DBS, and the stereotactic technique used to guide the implantation of DBS electrodes. Results The literature search identified 14 clinical studies that enrolled a total of 230 patients with TRD who underwent SCC DBS. The average duration of follow-up was 14 months (range 6–24 months). The response and remission rates at the last available follow-up visit ranged between 23–92% and 27–66.7%, respectively. Conclusion The current results of SCC DBS are limited by the relatively small number of patients treated worldwide. Nevertheless, studies to date suggest that SCC can be a promising and efficacious target for DBS, considering the high response and remission rates among patients with TRD. The adverse events of SCC DBS are usually transient and stimulation-induced.
Collapse
Affiliation(s)
- Michał Sobstyl
- Department of Neurosurgery, Institute of Psychiatry and Neurology, Warsaw, Poland
| | - Anna Kupryjaniuk
- Department of Neurosurgery, Institute of Psychiatry and Neurology, Warsaw, Poland
- *Correspondence: Anna Kupryjaniuk
| | - Marek Prokopienko
- Department of Neurosurgery, Institute of Psychiatry and Neurology, Warsaw, Poland
| | - Marcin Rylski
- Department of Radiology, Institute of Psychiatry and Neurology, Warsaw, Poland
| |
Collapse
|
23
|
Widge AS, Zhang F, Gosai A, Papadimitrou G, Wilson-Braun P, Tsintou M, Palanivelu S, Noecker AM, McIntyre CC, O’Donnell L, McLaughlin NCR, Greenberg BD, Makris N, Dougherty DD, Rathi Y. Patient-specific connectomic models correlate with, but do not reliably predict, outcomes in deep brain stimulation for obsessive-compulsive disorder. Neuropsychopharmacology 2022; 47:965-972. [PMID: 34621015 PMCID: PMC8882183 DOI: 10.1038/s41386-021-01199-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/11/2021] [Accepted: 09/23/2021] [Indexed: 12/15/2022]
Abstract
Deep brain stimulation (DBS) of the ventral internal capsule/ventral striatum (VCVS) is an emerging treatment for obsessive-compulsive disorder (OCD). Recently, multiple studies using normative connectomes have correlated DBS outcomes to stimulation of specific white matter tracts. Those studies did not test whether these correlations are clinically predictive, and did not apply cross-validation approaches that are necessary for biomarker development. Further, they did not account for the possibility of systematic differences between DBS patients and the non-diagnosed controls used in normative connectomes. To address these gaps, we performed patient-specific diffusion imaging in 8 patients who underwent VCVS DBS for OCD. We delineated tracts connecting thalamus and subthalamic nucleus (STN) to prefrontal cortex via VCVS. We then calculated which tracts were likely activated by individual patients' DBS settings. We fit multiple statistical models to predict both OCD and depression outcomes from tract activation. We further attempted to predict hypomania, a VCVS DBS complication. We assessed all models' performance on held-out test sets. With this best-practices approach, no model predicted OCD response, depression response, or hypomania above chance. Coefficient inspection partly supported prior reports, in that capture of tracts projecting to cingulate cortex was associated with both YBOCS and MADRS response. In contrast to prior reports, however, tracts connected to STN were not reliably correlated with response. Thus, patient-specific imaging and a guideline-adherent analysis were unable to identify a tractographic target with sufficient effect size to drive clinical decision-making or predict individual outcomes. These findings suggest caution in interpreting the results of normative connectome studies.
Collapse
Affiliation(s)
- Alik S. Widge
- grid.17635.360000000419368657Department of Psychiatry, University of Minnesota, Minneapolis, MN USA
| | - Fan Zhang
- grid.62560.370000 0004 0378 8294Department of Radiology, Brigham and Womens Hospital, Boston, MA USA
| | - Aishwarya Gosai
- grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - George Papadimitrou
- grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Peter Wilson-Braun
- grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Magdalini Tsintou
- grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Senthil Palanivelu
- grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Angela M. Noecker
- grid.67105.350000 0001 2164 3847Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH USA
| | - Cameron C. McIntyre
- grid.67105.350000 0001 2164 3847Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH USA
| | - Lauren O’Donnell
- grid.62560.370000 0004 0378 8294Department of Radiology, Brigham and Womens Hospital, Boston, MA USA
| | - Nicole C. R. McLaughlin
- grid.40263.330000 0004 1936 9094Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI USA ,grid.273271.20000 0000 8593 9332Butler Hospital, Providence, RI USA
| | - Benjamin D. Greenberg
- grid.40263.330000 0004 1936 9094Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI USA ,grid.273271.20000 0000 8593 9332Butler Hospital, Providence, RI USA ,Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI USA
| | - Nikolaos Makris
- grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Darin D. Dougherty
- grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Yogesh Rathi
- grid.62560.370000 0004 0378 8294Department of Radiology, Brigham and Womens Hospital, Boston, MA USA ,grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| |
Collapse
|
24
|
Paulk AC, Zelmann R, Crocker B, Widge AS, Dougherty DD, Eskandar EN, Weisholtz DS, Richardson RM, Cosgrove GR, Williams ZM, Cash SS. Local and distant cortical responses to single pulse intracranial stimulation in the human brain are differentially modulated by specific stimulation parameters. Brain Stimul 2022; 15:491-508. [PMID: 35247646 PMCID: PMC8985164 DOI: 10.1016/j.brs.2022.02.017] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/23/2022] [Accepted: 02/24/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Electrical neuromodulation via direct electrical stimulation (DES) is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, likely due to our limited understanding of the relationship between the massive stimulation parameter space and brain tissue responses. OBJECTIVE To better understand how different parameters induce varied neural responses, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration, brain region, and whether grey or white matter was stimulated. METHODS We measured voltage peak amplitudes and area under the curve (AUC) of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N = 52, n = 719 stimulation sites). RESULTS Increasing stimulation pulse width increased responses near the stimulation location. Increasing stimulation amplitude (current) increased both evoked amplitudes and AUC nonlinearly. Locally (<15 mm), stimulation at the boundary between grey and white matter induced larger responses. In contrast, for distant sites (>15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. The stimulation location-response curves followed different trends for cingulate, lateral frontal, and lateral temporal cortical stimulation. CONCLUSION These results demonstrate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter could be needed for network activation. Thus, stimulation parameters tailored for a specific anatomical-functional outcome may be key to advancing neuromodulatory therapy.
Collapse
Affiliation(s)
- Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
| | - Rina Zelmann
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA; Harvard-MIT Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Alik S Widge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA
| | - Darin D Dougherty
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA
| | - Emad N Eskandar
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Daniel S Weisholtz
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, 02114, USA
| | - R Mark Richardson
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, 02114, USA
| | - Ziv M Williams
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| |
Collapse
|
25
|
Bujarski KA, Song Y, Xie T, Leeds Z, Kolankiewicz SI, Wozniak GH, Guillory S, Aronson JP, Chang L, Jobst BC. Modulation of Emotion Perception via Amygdala Stimulation in Humans. Front Neurosci 2022; 15:795318. [PMID: 35221888 PMCID: PMC8864965 DOI: 10.3389/fnins.2021.795318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 12/28/2021] [Indexed: 12/20/2022] Open
Abstract
Background Multiple lines of evidence show that the human amygdala is part of a neural network important for perception of emotion from environmental stimuli, including for processing of intrinsic attractiveness/“goodness” or averseness/“badness,” i.e., affective valence. Objective/Hypothesis With this in mind, we investigated the effect of electrical brain stimulation of the human amygdala on perception of affective valence of images taken from the International Affective Picture Set (IAPS). Methods Using intracranial electrodes in patients with epilepsy, we first obtained event-related potentials (ERPs) in eight patients as they viewed IAPS images of varying affective valence. Next, in a further cohort of 10 patients (five female and five male), we measured the effect of 50 Hz electrical stimulation of the left amygdala on perception of affective valence from IAPS images. Results We recorded distinct ERPs from the left amygdala and found significant differences in the responses between positively and negatively valenced stimuli (p = 0.002), and between neutral and negatively valenced stimuli (p = 0.017) 300–500 ms after stimulus onset. Next, we found that amygdala stimulation did not significantly affect how patients perceived valence for neutral images (p = 0.58), whereas stimulation induced patients to report both positively (p = 0.05) and negatively (< 0.01) valenced images as more neutral. Conclusion These results render further evidence that the left amygdala participates in a neural network for perception of emotion from environmental stimuli. These findings support the idea that electrical stimulation disrupts this network and leads to partial disruption of perception of emotion. Harnessing this effect may have clinical implications in treatment of certain neuropsychiatric disorders using deep brain stimulation (DBS) and neuromodulation.
Collapse
Affiliation(s)
- Krzysztof A. Bujarski
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- *Correspondence: Krzysztof A. Bujarski,
| | - Yinchen Song
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Tiankang Xie
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States
- Department of Quantitative Biomedical Sciences, Dartmouth College, Lebanon, NH, United States
| | - Zachary Leeds
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Sophia I. Kolankiewicz
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Gabriella H. Wozniak
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Sean Guillory
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States
| | - Joshua P. Aronson
- Department of Surgery, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Luke Chang
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States
| | - Barbara C. Jobst
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| |
Collapse
|
26
|
Yuen J, Rusheen AE, Price JB, Barath AS, Shin H, Kouzani AZ, Berk M, Blaha CD, Lee KH, Oh Y. Biomarkers for Deep Brain Stimulation in Animal Models of Depression. Neuromodulation 2022; 25:161-170. [PMID: 35125135 PMCID: PMC8655028 DOI: 10.1111/ner.13483] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 04/20/2021] [Accepted: 05/11/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVES Despite recent advances in depression treatment, many patients still do not respond to serial conventional therapies and are considered "treatment resistant." Deep brain stimulation (DBS) has therapeutic potential in this context. This comprehensive review of recent studies of DBS for depression in animal models identifies potential biomarkers for improving therapeutic efficacy and predictability of conventional DBS to aid future development of closed-loop control of DBS systems. MATERIALS AND METHODS A systematic search was performed in Pubmed, EMBASE, and Cochrane Review using relevant keywords. Overall, 56 animal studies satisfied the inclusion criteria. RESULTS Outcomes were divided into biochemical/physiological, electrophysiological, and behavioral categories. Promising biomarkers include biochemical assays (in particular, microdialysis and electrochemical measurements), which provide real-time results in awake animals. Electrophysiological tests, showing changes at both the target site and downstream structures, also revealed characteristic changes at several anatomic targets (such as the medial prefrontal cortex and locus coeruleus). However, the substantial range of models and DBS targets limits the ability to draw generalizable conclusions in animal behavioral models. CONCLUSIONS Overall, DBS is a promising therapeutic modality for treatment-resistant depression. Different outcomes have been used to assess its efficacy in animal studies. From the review, electrophysiological and biochemical markers appear to offer the greatest potential as biomarkers for depression. However, to develop closed-loop DBS for depression, additional preclinical and clinical studies with a focus on identifying reliable, safe, and effective biomarkers are warranted.
Collapse
Affiliation(s)
- Jason Yuen
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA,Deakin University, IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong VIC 3216, Australia
| | - Aaron E. Rusheen
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA,Medical Scientist Training Program, Mayo Clinic, Rochester, MN 55905, USA
| | - J. Blair Price
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Hojin Shin
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA,Department of Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA
| | - Abbas Z. Kouzani
- School of Engineering, Deakin University, Geelong VIC 3216, Australia
| | - Michael Berk
- Deakin University, IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong VIC 3216, Australia
| | - Charles D. Blaha
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA
| | - Kendall H. Lee
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA,Department of Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA
| | - Yoonbae Oh
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA,Department of Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA
| |
Collapse
|
27
|
Coffey RJ, Caroff SN. Commentary on the Continued Investigational Status of DBS for Psychiatric Indications. Stereotact Funct Neurosurg 2022; 100:156-167. [PMID: 35104827 DOI: 10.1159/000521395] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 12/07/2021] [Indexed: 11/19/2022]
Abstract
Behavioral disorders exact a tragic toll on patients, families, and society. Consequently, the search for better treatments is a public health priority. Recent research promises to lead to advances in psychiatric treatment that may include implantation of deep brain stimulation (DBS) devices. In this commentary, the authors discuss how promising results from initial pilot studies of DBS in treatment-resistant depression (TRD) were not validated in 2 randomized, controlled, multicenter trials. Reliance on pilot data may have contributed to the selection of primary efficacy endpoints that were not achieved, and to the underestimation of adverse events and device-related complications. Published data on the population prevalence of affective disorders also may have led sponsors to overestimate the number of patients with TRD who were candidates for DBS therapy. Consequently, a more complete discussion of certain aspects of the depression trials may allow a realistic appraisal of the clinical and ethical situation of DBS therapy for TRD in a US regulatory context. A US regulatory perspective also may clarify the clinical research and reimbursement consequences of the Humanitarian Device Exemption (HDE) approval status of DBS for obsessive-compulsive disorder (OCD). Retrospective analyses akin to failure modes and effects analysis in engineering may clarify unexpected results in the DBS depression trials. Recent research suggests that subject selection in future trials may be augmented by advanced neuroimaging methods. For the present, the noncommercial research status of DBS to treat depression and the HDE status for OCD appear likely to remain in place.
Collapse
Affiliation(s)
| | - Stanley N Caroff
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| |
Collapse
|
28
|
Wendt K, Denison T, Foster G, Krinke L, Thomson A, Wilson S, Widge AS. Physiologically informed neuromodulation. J Neurol Sci 2021; 434:120121. [PMID: 34998239 PMCID: PMC8976285 DOI: 10.1016/j.jns.2021.120121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 12/19/2021] [Accepted: 12/21/2021] [Indexed: 01/09/2023]
Abstract
The rapid evolution of neuromodulation techniques includes an increasing amount of research into stimulation paradigms that are guided by patients' neurophysiology, to increase efficacy and responder rates. Treatment personalisation and target engagement have shown to be effective in fields such as Parkinson's disease, and closed-loop paradigms have been successfully implemented in cardiac defibrillators. Promising avenues are being explored for physiologically informed neuromodulation in psychiatry. Matching the stimulation frequency to individual brain rhythms has shown some promise in transcranial magnetic stimulation (TMS). Matching the phase of those rhythms may further enhance neuroplasticity, for instance when combining TMS with electroencephalographic (EEG) recordings. Resting-state EEG and event-related potentials may be useful to demonstrate connectivity between stimulation sites and connected areas. These techniques are available today to the psychiatrist to diagnose underlying sleep disorders, epilepsy, or lesions as contributing factors to the cause of depression. These technologies may also be useful in assessing the patient's brain network status prior to deciding on treatment options. Ongoing research using invasive recordings may allow for future identification of mood biomarkers and network structure. A core limitation is that biomarker research may currently be limited by the internal heterogeneity of psychiatric disorders according to the current DSM-based classifications. New approaches are being developed and may soon be validated. Finally, care must be taken when incorporating closed-loop capabilities into neuromodulation systems, by ensuring the safe operation of the system and understanding the physiological dynamics. Neurophysiological tools are rapidly evolving and will likely define the next generation of neuromodulation therapies.
Collapse
Affiliation(s)
- Karen Wendt
- Department of Engineering Science and MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
| | - Timothy Denison
- Department of Engineering Science and MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Gaynor Foster
- Welcony Inc., Plymouth, MN, United States of America
| | - Lothar Krinke
- Welcony Inc., Plymouth, MN, United States of America; Department of Neuroscience, School of Medicine, West Virginia University, Morgantown, WV, United States of America
| | - Alix Thomson
- Welcony Inc., Plymouth, MN, United States of America
| | - Saydra Wilson
- Department of Psychiatry and Behavioral Sciences, University of Minnesota-Twin Cities, Minneapolis, MN, United States of America
| | - Alik S Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota-Twin Cities, Minneapolis, MN, United States of America; Medical Discovery Team on Additions, University of Minnesota, Minneapolis, MN, United States of America
| |
Collapse
|
29
|
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.
Collapse
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.)
| |
Collapse
|
30
|
Farkhondeh Tale Navi F, Heysieattalab S, Ramanathan DS, Raoufy MR, Nazari MA. Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs. Neuroscience 2021; 483:104-126. [PMID: 34902494 DOI: 10.1016/j.neuroscience.2021.12.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/30/2021] [Accepted: 12/06/2021] [Indexed: 11/27/2022]
Abstract
Closed-loop approaches, setups, and experimental designs have been applied within the field of neuroscience to enhance the understanding of basic neurophysiology principles (closed-loop neuroscience; CLNS) and to develop improved procedures for modulating brain circuits and networks for clinical purposes (closed-loop neuromodulation; CLNM). The contents of this review are thus arranged into the following sections. First, we describe basic research findings that have been made using CLNS. Next, we provide an overview of the application, rationale, and therapeutic aspects of CLNM for clinical purposes. Finally, we summarize methodological concerns and critics in clinical practice of neurofeedback and novel applications of closed-loop perspective and techniques to improve and optimize its experiments. Moreover, we outline the theoretical explanations and experimental ideas to test animal models of neurofeedback and discuss technical issues and challenges associated with implementing closed-loop systems. We hope this review is helpful for both basic neuroscientists and clinical/ translationally-oriented scientists interested in applying closed-loop methods to improve mental health and well-being.
Collapse
Affiliation(s)
- Farhad Farkhondeh Tale Navi
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | - Soomaayeh Heysieattalab
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | | | - Mohammad Reza Raoufy
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Mohammad Ali Nazari
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran; Department of Neuroscience, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran.
| |
Collapse
|
31
|
Yuan H, Li Y, Yang J, Li H, Yang Q, Guo C, Zhu S, Shu X. State of the Art of Non-Invasive Electrode Materials for Brain-Computer Interface. MICROMACHINES 2021; 12:1521. [PMID: 34945371 PMCID: PMC8705666 DOI: 10.3390/mi12121521] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 02/02/2023]
Abstract
The brain-computer interface (BCI) has emerged in recent years and has attracted great attention. As an indispensable part of the BCI signal acquisition system, brain electrodes have a great influence on the quality of the signal, which determines the final effect. Due to the special usage scenario of brain electrodes, some specific properties are required for them. In this study, we review the development of three major types of EEG electrodes from the perspective of material selection and structural design, including dry electrodes, wet electrodes, and semi-dry electrodes. Additionally, we provide a reference for the current chaotic performance evaluation of EEG electrodes in some aspects such as electrochemical performance, stability, and so on. Moreover, the challenges and future expectations for EEG electrodes are analyzed.
Collapse
Affiliation(s)
- Haowen Yuan
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Yao Li
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Junjun Yang
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Hongjie Li
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Qinya Yang
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Cuiping Guo
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Shenmin Zhu
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Xiaokang Shu
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| |
Collapse
|
32
|
Sendi MS, Zendehrouh E, Sui J, Fu Z, Zhi D, Lv L, Ma X, Ke Q, Li X, Wang C, Abbott CC, Turner JA, Miller RL, Calhoun VD. Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder. Brain Connect 2021; 11:838-849. [PMID: 33514278 PMCID: PMC8713570 DOI: 10.1089/brain.2020.0748] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Background: Major depressive disorder (MDD) is a severe mental illness marked by a continuous sense of sadness and a loss of interest. The default mode network (DMN) is a group of brain areas that are more active during rest and deactivate when engaged in task-oriented activities. The DMN of MDD has been found to have aberrant static functional network connectivity (FNC) in recent studies. In this work, we extend previous findings by evaluating dynamic functional network connectivity (dFNC) within the DMN subnodes in MDD. Methods: We analyzed resting-state functional magnetic resonance imaging data of 262 patients with MDD and 277 healthy controls (HCs). We estimated dFNCs for seven subnodes of the DMN, including the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and precuneus (PCu), using a sliding window approach, and then clustered the dFNCs into five brain states. Classification of MDD and HC subjects based on state-specific FC was performed using a logistic regression classifier. Transition probabilities between dFNC states were used to identify relationships between symptom severity and dFNC data in MDD patients. Results: By comparing state-specific FNC between HC and MDD, a disrupted connectivity pattern was observed within the DMN. In more detail, we found that the connectivity of ACC is stronger, and the connectivity between PCu and PCC is weaker in individuals with MDD than in those of HC subjects. In addition, MDD showed a higher probability of transitioning from a state with weaker ACC connectivity to a state with stronger ACC connectivity, and this abnormality is associated with symptom severity. This is the first research to look at the dFC of the DMN in MDD with a large sample size. It provides novel evidence of abnormal time-varying DMN configuration in MDD and offers links to symptom severity in MDD subjects. Impact Statement This study is the first attempt that explored the temporal change on default mode network (DMN) connectivity in a relatively large cohort of patients with major depressive disorder (MDD). We also introduced a new hypothesis that explains the inconsistency in DMN functional network connectivity (FNC) comparison between MDD and healthy control based on static FNC in the previous literature. Additionally, our findings suggest that within anterior cingulate cortex connectivity and the connectivity between the precuneus and posterior cingulate cortex are the potential biomarkers for the future intervention of MDD.
Collapse
Affiliation(s)
- Mohammad S.E. Sendi
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Elaheh Zendehrouh
- Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
| | - Jing Sui
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- School of Future Technologies, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Dongmei Zhi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- School of Future Technologies, University of Chinese Academy of Sciences, Beijing, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
- Henan Key Laboratory of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
| | - Xiaohong Ma
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Qing Ke
- Department of Neurology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xianbin Li
- Beijing Key Lab of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Chuanyue Wang
- Beijing Key Lab of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | | | - Jessica A. Turner
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
- Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Robyn L. Miller
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
- Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
| | - Vince D. Calhoun
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
- Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
- Department of Psychology, Georgia State University, Atlanta, Georgia, USA
- Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| |
Collapse
|
33
|
Avvaru S, Provenza NR, Widge AS, Parhi KK. Spectral Features Based Decoding of Task Engagement: The Role of Theta and High Gamma Bands in Cognitive Control. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:6062-6065. [PMID: 34892499 DOI: 10.1109/embc46164.2021.9630923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
This paper analyzes local field potentials (LFP) from 10 human subjects to discover frequency-dependent biomarkers of cognitive conflict. We utilize cortical and sub-cortical LFP recordings from the subjects during a cognitive task known as the Multi-Source Interference Task (MSIT). We decode the task engagement and discover biomarkers that may facilitate closed-loop neuromodulation to enhance cognitive control. First, we show that spectral power features in predefined frequency bands can be used to classify task and non-task segments with a median accuracy of 88.1%. Here the features are first ranked using the Bayes Factor and then used as inputs to subject-specific linear support vector machine classifiers. Second, we show that theta (4-8 Hz) band, and high gamma (65-200 Hz) band oscillations are modulated during the task performance. Third, by isolating time-series from specific brain regions of interest, we observe that a subset of the dorsolateral prefrontal cortex features is sufficient to decode the task states. The paper shows that cognitive control evokes robust neurological signatures, especially in the prefrontal cortex (PFC).
Collapse
|
34
|
Avvaru S, Provenza NR, Widge AS, Parhi KK. Decoding Human Cognitive Control Using Functional Connectivity of Local Field Potentials. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:451-454. [PMID: 34891330 DOI: 10.1109/embc46164.2021.9630706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Many patients with mental illnesses characterized by impaired cognitive control have no relief from gold-standard clinical treatments resulting in a pressing need for new alternatives. This paper develops a neural decoder to detect task engagement in ten human subjects during a conflict-based behavioral task known as the multi-source interference task (MSIT). Task engagement is of particular interest here because closed-loop brain stimulation during those states can augment decision-making. The functional connectivity patterns of the electrodes are extracted. A principal component analysis of these patterns is carried out and the ranked principal components are used as inputs to train subject-specific linear support vector machine classifiers. In this paper, we show that task engagement can be differentiated from background brain activity with a median accuracy of 89.7%. This was accomplished by constructing distributed functional networks from local field potentials recording during the task performance. A further challenge is that goal-directed efforts take place over higher temporal resolution. Task engagement must thus be detected at a similar rate for proactive intervention. We show that our algorithms can detect task engagement from neural recordings in less than 2 seconds; this can be further improved using an application-specific device.
Collapse
|
35
|
Narcisse D, Mustafi SM, Carlson M, Batabyal S, Kim S, Wright W, Kumar Mohanty S. Bioluminescent Multi-Characteristic Opsin for Simultaneous Optical Stimulation and Continuous Monitoring of Cortical Activities. Front Cell Neurosci 2021; 15:750663. [PMID: 34759801 PMCID: PMC8573050 DOI: 10.3389/fncel.2021.750663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 09/20/2021] [Indexed: 12/02/2022] Open
Abstract
Stimulation and continuous monitoring of neural activities at cellular resolution are required for the understanding of the sensory processing of stimuli and development of effective neuromodulation therapies. We present bioluminescence multi-characteristic opsin (bMCOII), a hybrid optogenetic actuator, and a bioluminescence Ca2+ sensor for excitation-free, continuous monitoring of neural activities in the visual cortex, with high spatiotemporal resolution. An exceptionally low intensity (10 μW/mm2) of light could elicit neural activation that could be detected by Ca2+ bioluminescence imaging. An uninterrupted (>14 h) recording of visually evoked neural activities in the cortex of mice enabled the determination of strength of sensory activation. Furthermore, an artificial intelligence-based neural activation parameter transformed Ca2+ bioluminescence signals to network activity patterns. During continuous Ca2+-bioluminescence recordings, visual cortical activity peaked at the seventh to eighth hour of anesthesia, coinciding with circadian rhythm. For both direct optogenetic stimulation in cortical slices and visually evoked activities in the visual cortex, we observed secondary delayed Ca2+-bioluminescence responses, suggesting the involvement of neuron-astrocyte-neuron pathway. Our approach will enable the development of a modular and scalable interface system capable of serving a multiplicity of applications to modulate and monitor large-scale activities in the brain.
Collapse
|
36
|
Georgiev D, Akram H, Jahanshahi M. Deep brain stimulation for psychiatric disorders: role of imaging in identifying/confirming DBS targets, predicting, and optimizing outcome and unravelling mechanisms of action. PSYCHORADIOLOGY 2021; 1:118-151. [PMID: 38665808 PMCID: PMC10917192 DOI: 10.1093/psyrad/kkab012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/31/2021] [Accepted: 09/08/2021] [Indexed: 04/28/2024]
Abstract
Following the established application of deep brain stimulation (DBS) in the treatment of movement disorders, new non-neurological indications have emerged, such as for obsessive-compulsive disorders, major depressive disorder, dementia, Gilles de la Tourette Syndrome, anorexia nervosa, and addictions. As DBS is a network modulation surgical treatment, the development of DBS for both neurological and psychiatric disorders has been partly driven by advances in neuroimaging, which has helped explain the brain networks implicated. Advances in magnetic resonance imaging connectivity and electrophysiology have led to the development of the concept of modulating widely distributed, complex brain networks. Moreover, the increasing number of targets for treating psychiatric disorders have indicated that there may be a convergence of the effect of stimulating different targets for the same disorder, and the effect of stimulating the same target for different disorders. The aim of this paper is to review the imaging studies of DBS for psychiatric disorders. Imaging, and particularly connectivity analysis, offers exceptional opportunities to better understand and even predict the clinical outcomes of DBS, especially where there is a lack of objective biomarkers that are essential to properly guide DBS pre- and post-operatively. In future, imaging might also prove useful to individualize DBS treatment. Finally, one of the most important aspects of imaging in DBS is that it allows us to better understand the brain through observing the changes of the functional connectome under neuromodulation, which may in turn help explain the mechanisms of action of DBS that remain elusive.
Collapse
Affiliation(s)
- Dejan Georgiev
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Department of Neurology, University Medical Centre Ljubljana, Zaloška cesta 2, 1000 Ljubljana, Slovenia
- Artificial Intelligence Laboratory, Faculty of Computer and Information Science, University of Ljubljana, Večna pot 113, 1000 Ljubljana, Slovenia
| | - Harith Akram
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Marjan Jahanshahi
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China
| |
Collapse
|
37
|
Ranjan M, Ranjan N, Deogaonkar M, Rezai A. Deep Brain Stimulation for Refractory Depression, Obsessive-Compulsive Disorder and Addiction. Neurol India 2021; 68:S282-S287. [PMID: 33318363 DOI: 10.4103/0028-3886.302459] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background Depression, Obsessive-compulsive Disorder (OCD), and addiction are the leading disabling psychiatric conditions with huge health care and psychosocial burden besides increased morbidity and mortality. Deep brain stimulation (DBS) for depression, OCD, and addiction is increasingly explored and is quite challenging. We present a brief review of the pertinent literature of DBS for depression, OCD, and addiction and present the status and challenges. Objective The aim of this study was to review the current status and challenges with the DBS for Depression, Obsessive-compulsive Disorder (OCD), and addiction. Method The pertinent brief literature was reviewed in reference to the DBS for Depression, Obsessive-compulsive Disorder (OCD), and addiction. Results To date, OCD is the only psychiatric condition approved for DBS therapy (under humanitarian device exemption). Although the initial encouraging results of DBS in depression were encouraging but the two larger multicenter clinical trials failed to meet the primary objective. Further evaluation and studies are ongoing. Similarly, the initial results of DBS for addiction are encouraging; however, the experience is limited. Conclusion DBS for depression, OCD, and addiction seem challenging but promising. Further refinement of the target and evaluation in a larger and controlled setting is needed, specifically for depression and addiction.
Collapse
Affiliation(s)
- Manish Ranjan
- Department of Neurosurgery, Rockefeller Neuroscience Institute, USA
| | - Nutan Ranjan
- Department of Behavioral Medicine and Psychiatry, West Virginia University, West Virginia, USA
| | | | - Ali Rezai
- Department of Neurosurgery, Rockefeller Neuroscience Institute, USA
| |
Collapse
|
38
|
Allawala A, Bijanki KR, Goodman W, Cohn JF, Viswanathan A, Yoshor D, Borton DA, Pouratian N, Sheth SA. A Novel Framework for Network-Targeted Neuropsychiatric Deep Brain Stimulation. Neurosurgery 2021; 89:E116-E121. [PMID: 33913499 PMCID: PMC8279838 DOI: 10.1093/neuros/nyab112] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 02/14/2021] [Indexed: 12/28/2022] Open
Abstract
Deep brain stimulation (DBS) has emerged as a promising therapy for neuropsychiatric illnesses, including depression and obsessive-compulsive disorder, but has shown inconsistent results in prior clinical trials. We propose a shift away from the empirical paradigm for developing new DBS applications, traditionally based on testing brain targets with conventional stimulation paradigms. Instead, we propose a multimodal approach centered on an individualized intracranial investigation adapted from the epilepsy monitoring experience, which integrates comprehensive behavioral assessment, such as the Research Domain Criteria proposed by the National Institutes of Mental Health. In this paradigm-shifting approach, we combine readouts obtained from neurophysiology, behavioral assessments, and self-report during broad exploration of stimulation parameters and behavioral tasks to inform the selection of ideal DBS parameters. Such an approach not only provides a foundational understanding of dysfunctional circuits underlying symptom domains in neuropsychiatric conditions but also aims to identify generalizable principles that can ultimately enable individualization and optimization of therapy without intracranial monitoring.
Collapse
Affiliation(s)
- Anusha Allawala
- School of Engineering, Brown University, Providence, Rhode Island, USA
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas, USA
| | - Wayne Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Jeffrey F Cohn
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ashwin Viswanathan
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas, USA
| | - Daniel Yoshor
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas, USA.,Department of Neurosurgery, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David A Borton
- School of Engineering, Brown University, Providence, Rhode Island, USA.,Carney Institute for Brain Science, Brown University, Providence, Rhode Island, USA.,Department of Veterans Affairs, Providence VA Medical Center for Neurorestoration and Neurotechnology, Providence, Rhode Island, USA
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas, USA
| |
Collapse
|
39
|
Guerrero Moreno J, Biazoli CE, Baptista AF, Trambaiolli LR. Closed-loop neurostimulation for affective symptoms and disorders: An overview. Biol Psychol 2021; 161:108081. [PMID: 33757806 DOI: 10.1016/j.biopsycho.2021.108081] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 03/12/2021] [Accepted: 03/15/2021] [Indexed: 12/28/2022]
Abstract
Affective and anxiety disorders are the most prevalent and incident psychiatric disorders worldwide. Therapeutic approaches to these disorders using non-invasive brain stimulation (NIBS) and analogous techniques have been extensively investigated. In this paper, we discuss the combination of NIBS and neurofeedback in closed-loop setups and its application for affective symptoms and disorders. For this, we first provide a rationale for this combination by presenting some of the main original findings of NIBS, with a primary focus on transcranial magnetic stimulation (TMS), and neurofeedback, including protocols based on electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Then, we provide a scope review of studies combining real-time neurofeedback with NIBS protocols in the so-called closed-loop brain state-dependent neuromodulation (BSDS). Finally, we discuss the concomitant use of TMS and real-time functional near-infrared spectroscopy (fNIRS) as a possible solution to the current limitations of BSDS-based protocols for affective and anxiety disorders.
Collapse
Affiliation(s)
- Javier Guerrero Moreno
- Center of Mathematics, Computation and Cognition, Universidade Federal do ABC, Santo André, Brazil
| | - Claudinei Eduardo Biazoli
- Center of Mathematics, Computation and Cognition, Universidade Federal do ABC, Santo André, Brazil; Department of Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, UK
| | - Abrahão Fontes Baptista
- Center of Mathematics, Computation and Cognition, Universidade Federal do ABC, Santo André, Brazil; Laboratory of Medical Investigations 54 (LIM-54), Universidade de São Paulo, São Paulo, Brazil; NAPeN Network (Rede de Núcleos de Assistência e Pesquisa em Neuromodulação), Brazil; Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
| | - Lucas Remoaldo Trambaiolli
- McLean Hospital, Harvard Medical School, Boston, USA; School of Medicine and Dentistry, University of Rochester, Rochester, USA.
| |
Collapse
|
40
|
Sullivan CRP, Olsen S, Widge AS. Deep brain stimulation for psychiatric disorders: From focal brain targets to cognitive networks. Neuroimage 2021; 225:117515. [PMID: 33137473 PMCID: PMC7802517 DOI: 10.1016/j.neuroimage.2020.117515] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 08/19/2020] [Accepted: 10/24/2020] [Indexed: 01/16/2023] Open
Abstract
Deep brain stimulation (DBS) is a promising intervention for treatment-resistant psychiatric disorders, particularly major depressive disorder (MDD) and obsessive-compulsive disorder (OCD). Up to 90% of patients who have not recovered with therapy or medication have reported benefit from DBS in open-label studies. Response rates in randomized controlled trials (RCTs), however, have been much lower. This has been argued to arise from surgical variability between sites, and recent psychiatric DBS research has focused on refining targeting through personalized imaging. Much less attention has been given to the fact that psychiatric disorders arise from dysfunction in distributed brain networks, and that DBS likely acts by altering communication within those networks. This is in part because psychiatric DBS research relies on subjective rating scales that make it difficult to identify network biomarkers. Here, we overview recent DBS RCT results in OCD and MDD, as well as the follow-on imaging studies. We present evidence for a new approach to studying DBS' mechanisms of action, focused on measuring objective cognitive/emotional deficits that underpin these and many other mental disorders. Further, we suggest that a focus on cognition could lead to reliable network biomarkers at an electrophysiologic level, especially those related to inter-regional synchrony of the local field potential (LFP). Developing the network neuroscience of DBS has the potential to finally unlock the potential of this highly specific therapy.
Collapse
Affiliation(s)
- Christi R P Sullivan
- University of Minnesota Medical School Department of Psychiatry and Behavioral Sciences, 2001 6th Street SE, Minneapolis, MN 55454, USA.
| | - Sarah Olsen
- University of Minnesota Medical School Department of Psychiatry and Behavioral Sciences, 2001 6th Street SE, Minneapolis, MN 55454, USA.
| | - Alik S Widge
- University of Minnesota Medical School Department of Psychiatry and Behavioral Sciences, 2001 6th Street SE, Minneapolis, MN 55454, USA.
| |
Collapse
|
41
|
Stevens I, Gilbert F. Ethical examination of deep brain stimulation's 'last resort' status. JOURNAL OF MEDICAL ETHICS 2021; 47:medethics-2020-106609. [PMID: 33441307 DOI: 10.1136/medethics-2020-106609] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 10/26/2020] [Accepted: 11/01/2020] [Indexed: 06/12/2023]
Abstract
Deep brain stimulation (DBS) interventions are novel devices being investigated for the management of severe treatment-resistant psychiatric illnesses. These interventions require the invasive implantation of high-frequency neurostimulatory probes intracranially aiming to provide symptom relief in treatment-resistant disorders including obsessive-compulsive disorder and anorexia nervosa. In the scientific literature, these neurostimulatory interventions are commonly described as reversible and to be used as a last resort option for psychiatric patients. However, the 'last resort' status of these interventions is rarely expanded upon. Contrastingly, usages of DBS devices for neurological symptoms (eg, Parkinson's disease, epilepsy or dystonia) have paved the way for established safety and efficacy standards when used earlier in a disease's timeline. As DBS treatments for these neurological diseases progress to have earlier indications, there is a parallel ethical concern that early implementation may one day become prescribed for psychiatric illnesses. The purpose of this article is to build off contemporary understandings of reversible neurostimulatory interventions to examine and provide clarifications on the 'last resort' status of DBS to better address its ethically charged use in psychiatric neurosurgery. To do this, evaluative differences between DBS treatments will be discussed to demonstrate how patient autonomy would be a paramount guiding principle when one day implementing these devices at various points along a psychiatric disease's timeline. In presenting the clarification of 'last resort' status, the ethical tensions of early DBS interventions will be better understood to assist in providing psychiatric patients with more quality of life years in line with their values.
Collapse
Affiliation(s)
- Ian Stevens
- Philosophy & Gender Studies, University of Tasmania School of Humanities, Hobart, Tasmania, Australia
| | - Frederic Gilbert
- Philosophy & Gender Studies, University of Tasmania School of Humanities, Hobart, Tasmania, Australia
| |
Collapse
|
42
|
Cabrera LY, Nowak GR, McCright AM, Achtyes E, Bluhm R. A qualitative study of key stakeholders' perceived risks and benefits of psychiatric electroceutical interventions. HEALTH, RISK & SOCIETY 2021; 23:217-235. [PMID: 35574212 PMCID: PMC9103575 DOI: 10.1080/13698575.2021.1979194] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Amid a renewed interest in alternatives to psychotherapy and medication to treat depression, there is limited data as to how different stakeholders perceive of the risks and benefits of psychiatric electroceutical interventions (PEIs), including electroconvulsive therapy (ECT) and deep brain stimulation (DBS). To address this gap, we conducted 48 semi-structured interviews, including 16 psychiatrists, 16 persons diagnosed with depression, and 16 members of the general public. To provide a basis of comparison, we asked participants to also compare each modality to front-line therapies for depression and to neurosurgical procedures used for non-psychiatric conditions. Across all stakeholder groups, perceived memory loss was the most frequently mentioned potential risk with ECT. The most discussed benefits across all stakeholder groups were efficacy and quick response. Psychiatrists most often referenced effectiveness when discussing ECT, while patients and the public did so when discussing DBS. Taken as a whole, these data highlight stakeholders' contrasting perspectives on the risks and benefits of electroceuticals.
Collapse
Affiliation(s)
- Laura Y Cabrera
- Center for Neural Engineering, Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, United States
- Rock Ethics Institute, Pennsylvania State University, University Park, PA, United States
| | - Gerald R Nowak
- Department of Sociology, Michigan State University, East Lansing, MI, United States
| | - Aaron M McCright
- Department of Sociology, Michigan State University, East Lansing, MI, United States
| | - Eric Achtyes
- Division of Psychiatry and Behavioral Medicine, Michigan State University, East Grand Rapids, MI, United States
- Pine Rest Christian Mental Health Services, Grand Rapids, MI, United States
| | - Robyn Bluhm
- Lyman Briggs College and Department of Philosophy, Michigan State University, East Lansing, MI, United States
| |
Collapse
|
43
|
Ramasubbu R, Golding S, Williams K, Mackie A, MacQueen G, Kiss ZHT. Recruitment Challenges for Studies of Deep Brain Stimulation for Treatment-Resistant Depression. Neuropsychiatr Dis Treat 2021; 17:765-775. [PMID: 33731996 PMCID: PMC7956889 DOI: 10.2147/ndt.s299913] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 02/13/2021] [Indexed: 12/24/2022] Open
Abstract
INTRODUCTION Deep brain stimulation (DBS) is currently an investigational treatment for treatment-resistant depression (TRD). There is a need for more DBS trials to strengthen existing evidence of its efficacy for both regulatory and clinical reasons. Recruitment for DBS trials remains challenging due to unproven efficacy in sham-controlled DBS trials, invasive nature of the intervention and stringent eligibility criteria in patient selection. Here, we examined the referral patterns and reasons for exclusion of subjects in our DBS trial. METHODS Data were collected from all patients who expressed interest in participating in a DBS study involving subcallosal cingulate region from 2014 to 2016. Referral sources were categorized as either self-referral or professional referral. Evaluation for eligibility was performed in three stages; initial contact, brief telephone assessment, and in-person psychiatric evaluation. The reasons for exclusion were documented. Descriptive and inferential statistics were used for analysis. RESULTS Of the 225 patients who contacted us initially, 22 (9.2%) underwent DBS surgery. Self-referral was higher than the referral from professionals (72% versus 28%, P<0.0001). However, the acceptance rate for surgery was higher among the professional referrals than from self-referrals (40% versus 15%, P=0.03). The common reasons for exclusion were self-withdrawal (38.4%), residing out of province or country (26.1%) and psychiatric/medical comorbidity (21.7%). CONCLUSION These findings provide insight into DBS candidacy for future TRD trials. It suggests a need for comprehensive recruitment strategies including active engagement of patients and professionals throughout trials, and effective referral communication with education to optimize recruitment for future DBS trials.
Collapse
Affiliation(s)
- Rajamannar Ramasubbu
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada.,Mathison Centre for Mental Health Research & Education, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Sandra Golding
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
| | - Kimberly Williams
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Aaron Mackie
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Glenda MacQueen
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada.,Mathison Centre for Mental Health Research & Education, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Zelma H T Kiss
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada.,Mathison Centre for Mental Health Research & Education, University of Calgary, Calgary, AB, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| |
Collapse
|
44
|
Song X, Zhao X, Li X, Liu S, Ming D. Multi-channel transcranial temporally interfering stimulation (tTIS): application to living mice brain. J Neural Eng 2020; 18. [PMID: 33307539 DOI: 10.1088/1741-2552/abd2c9] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 12/11/2020] [Indexed: 01/10/2023]
Abstract
OBJECTIVE Transcranial temporally interfering stimulation (tTIS) is a noninvasive neuromodulation method, which has been reported to be able to affect the activity of small neuronal populations. To pinpoint smaller regions of the brain, multi-channel tTIS strategy is proposed with larger numbers of electrodes and multiple sets of interfering fields. APPROACH First, computational model is adopted to prove the concept of multi-channel tTIS theoretically. Besides, animal experiments are implemented to activate motor cortex neurons in living mice and different frequencies are attempted. Finally, to better understand the envelope modulation properties of the two applied fields, tissue phantom measurement is conducted. MAIN RESULTS The focality of six-channel (six electrode pairs) tTIS is increased by 46.7% and 70.2% respectively, compared with that of single-channel tTIS when maximal amplitude value drops by 3dB and 6dB in numerical computation experiment. Furthermore, the focality of multi-channel tTIS is less sensitive to the electrode position. Confirmed with myoelectricity signal, the movement frequencies of contralateral forepaw are consistent with the corresponding difference frequencies. What's more, compared single-channel (one electrode pair) tTIS with multi-channel (three electrode pairs) tTIS, the intensity of multi-channel tTIS stimulation is decreased by 28.5% on average in animal experiment. And the c-fos-positive neurons of target region are significantly higher than that of the non-target region. Results of the modulated envelope distribute around the whole regions and its amplitude reaches a maximum at the interfering region. SIGNIFICANCE Both computational modeling and animal experiment validate the feasibility of the proposed multi-channel tTIS strategy and confirm that it can enhance focality and reduce scalp sensation.
Collapse
Affiliation(s)
- Xizi Song
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, Tianjin, CHINA
| | - Xue Zhao
- , Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, Tianjin, 300072, CHINA
| | - Xiaohong Li
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Academy of Medical Engineering and Translational Medicine, Tianjin, 300072, CHINA
| | - Shuang Liu
- Tianjin University, Tianjin, 300072, CHINA
| | - Dong Ming
- Dept. of Biomedical Engineering, Tianjin University, School of Precision Instrument and Opto-Electronics Engineering, Tianjin 300072, Tianjin, 300072, CHINA
| |
Collapse
|
45
|
Zelmann R, Paulk AC, Basu I, Sarma A, Yousefi A, Crocker B, Eskandar E, Williams Z, Cosgrove GR, Weisholtz DS, Dougherty DD, Truccolo W, Widge AS, Cash SS. CLoSES: A platform for closed-loop intracranial stimulation in humans. Neuroimage 2020; 223:117314. [PMID: 32882382 PMCID: PMC7805582 DOI: 10.1016/j.neuroimage.2020.117314] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 07/15/2020] [Accepted: 08/25/2020] [Indexed: 01/02/2023] Open
Abstract
Targeted interrogation of brain networks through invasive brain stimulation has become an increasingly important research tool as well as therapeutic modality. The majority of work with this emerging capability has been focused on open-loop approaches. Closed-loop techniques, however, could improve neuromodulatory therapies and research investigations by optimizing stimulation approaches using neurally informed, personalized targets. Implementing closed-loop systems is challenging particularly with regard to applying consistent strategies considering inter-individual variability. In particular, during intracranial epilepsy monitoring, where much of this research is currently progressing, electrodes are implanted exclusively for clinical reasons. Thus, detection and stimulation sites must be participant- and task-specific. The system must run in parallel with clinical systems, integrate seamlessly with existing setups, and ensure safety features are in place. In other words, a robust, yet flexible platform is required to perform different tests with a single participant and to comply with clinical requirements. In order to investigate closed-loop stimulation for research and therapeutic use, we developed a Closed-Loop System for Electrical Stimulation (CLoSES) that computes neural features which are then used in a decision algorithm to trigger stimulation in near real-time. To summarize CLoSES, intracranial electroencephalography (iEEG) signals are acquired, band-pass filtered, and local and network features are continuously computed. If target features are detected (e.g. above a preset threshold for a certain duration), stimulation is triggered. Not only could the system trigger stimulation while detecting real-time neural features, but we incorporated a pipeline wherein we used an encoder/decoder model to estimate a hidden cognitive state from the neural features. CLoSES provides a flexible platform to implement a variety of closed-loop experimental paradigms in humans. CLoSES has been successfully used with twelve patients implanted with depth electrodes in the epilepsy monitoring unit. During cognitive tasks (N=5), stimulation in closed loop modified a cognitive hidden state on a trial by trial basis. Sleep spindle oscillations (N=6) and sharp transient epileptic activity (N=9) were detected in near real-time, and stimulation was applied during the event or at specified delays (N=3). In addition, we measured the capabilities of the CLoSES system. Total latency was related to the characteristics of the event being detected, with tens of milliseconds for epileptic activity and hundreds of milliseconds for spindle detection. Stepwise latency, the actual duration of each continuous step, was within the specified fixed-step duration and increased linearly with the number of channels and features. We anticipate that probing neural dynamics and interaction between brain states and stimulation responses with CLoSES will lead to novel insights into the mechanism of normal and pathological brain activity, the discovery and evaluation of potential electrographic biomarkers of neurological and psychiatric disorders, and the development and testing of patient-specific stimulation targets and control signals before implanting a therapeutic device.
Collapse
Affiliation(s)
- Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Ishita Basu
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, University of Cincinnati, OH, USA
| | - Anish Sarma
- Department of Neuroscience, Brown University, Providence, RI, USA
| | - Ali Yousefi
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Emad Eskandar
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Albert Einstein College of Medicine, NY, USA
| | - Ziv Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Wilson Truccolo
- Department of Neuroscience, Brown University, Providence, RI, USA
| | - Alik S Widge
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, University of Minnesota, MI, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| |
Collapse
|
46
|
Rabin JS, Davidson B, Giacobbe P, Hamani C, Cohn M, Illes J, Lipsman N. Neuromodulation for major depressive disorder: innovative measures to capture efficacy and outcomes. Lancet Psychiatry 2020; 7:1075-1080. [PMID: 33129374 DOI: 10.1016/s2215-0366(20)30187-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 04/02/2020] [Accepted: 04/14/2020] [Indexed: 12/13/2022]
Abstract
Major depressive disorder is a common and debilitating disorder. Although most patients with this disorder benefit from established treatments, a subset of patients have symptoms that remain treatment resistant. Novel treatment approaches, such as deep brain stimulation, are urgently needed for patients with treatment-resistant major depressive disorder. These novel treatments are currently being tested in clinical trials in which success hinges on how accurately and comprehensively the primary outcome measure captures the treatment effect. In this Personal View, we argue that current measures used to assess outcomes in neurosurgical trials of major depressive disorder might be missing clinically important treatment effects. A crucial problem of continuing to use suboptimal outcome measures is that true signals of efficacy might be missed, thereby disqualifying potentially effective treatments. We argue that a re-evaluation of how outcomes are measured in these trials is much overdue and describe several novel approaches that attempt to better capture meaningful change.
Collapse
Affiliation(s)
- Jennifer S Rabin
- Sunnybrook Research Institute, Toronto, ON, Canada; Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
| | - Benjamin Davidson
- Sunnybrook Research Institute, Toronto, ON, Canada; Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; Department of Medicine, Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Peter Giacobbe
- Sunnybrook Research Institute, Toronto, ON, Canada; Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Clement Hamani
- Sunnybrook Research Institute, Toronto, ON, Canada; Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; Department of Medicine, Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Melanie Cohn
- Department of Psychology, University of Toronto, Toronto, ON, Canada; Krembil Brain Institute, University Health Network, Toronto, ON, Canada
| | - Judy Illes
- Neuroethics Canada, Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Nir Lipsman
- Sunnybrook Research Institute, Toronto, ON, Canada; Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; Department of Medicine, Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
47
|
Davidson B, Lipsman N, Meng Y, Rabin JS, Giacobbe P, Hamani C. The Use of Tractography-Based Targeting in Deep Brain Stimulation for Psychiatric Indications. Front Hum Neurosci 2020; 14:588423. [PMID: 33304258 PMCID: PMC7701283 DOI: 10.3389/fnhum.2020.588423] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 10/27/2020] [Indexed: 12/15/2022] Open
Abstract
Deep Brain Stimulation (DBS) has been investigated as a treatment option for patients with refractory psychiatric illness. Over the past two decades, neuroimaging developments have helped to advance the field, particularly the use of diffusion tensor imaging (DTI) and tractographic reconstruction of white-matter pathways. In this article, we review translational considerations and how DTI and tractography have been used to improve targeting during DBS surgery for depression, obsessive compulsive disorder (OCD) and post-traumatic stress disorder (PTSD).
Collapse
Affiliation(s)
- Benjamin Davidson
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Nir Lipsman
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Ying Meng
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Jennifer S. Rabin
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Peter Giacobbe
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Clement Hamani
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
48
|
Deng ZD, Luber B, Balderston NL, Velez Afanador M, Noh MM, Thomas J, Altekruse WC, Exley SL, Awasthi S, Lisanby SH. Device-Based Modulation of Neurocircuits as a Therapeutic for Psychiatric Disorders. Annu Rev Pharmacol Toxicol 2020; 60:591-614. [PMID: 31914895 DOI: 10.1146/annurev-pharmtox-010919-023253] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Device-based neuromodulation of brain circuits is emerging as a promising new approach in the study and treatment of psychiatric disorders. This work presents recent advances in the development of tools for identifying neurocircuits as therapeutic targets and in tools for modulating neurocircuits. We review clinical evidence for the therapeutic efficacy of circuit modulation with a range of brain stimulation approaches, including subthreshold, subconvulsive, convulsive, and neurosurgical techniques. We further discuss strategies for enhancing the precision and efficacy of neuromodulatory techniques. Finally, we survey cutting-edge research in therapeutic circuit modulation using novel paradigms and next-generation devices.
Collapse
Affiliation(s)
- Zhi-De Deng
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA; .,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina 27710, USA
| | - Bruce Luber
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Nicholas L Balderston
- Section on Neurobiology of Fear and Anxiety, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Melbaliz Velez Afanador
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Michelle M Noh
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Jeena Thomas
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - William C Altekruse
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Shannon L Exley
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Shriya Awasthi
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
| | - Sarah H Lisanby
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA; .,Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina 27710, USA
| |
Collapse
|
49
|
Xia F, Kheirbek MA. Circuit-Based Biomarkers for Mood and Anxiety Disorders. Trends Neurosci 2020; 43:902-915. [PMID: 32917408 PMCID: PMC7606349 DOI: 10.1016/j.tins.2020.08.004] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 07/23/2020] [Accepted: 08/16/2020] [Indexed: 12/11/2022]
Abstract
Mood and anxiety disorders are complex heterogeneous syndromes that manifest in dysfunctions across multiple brain regions, cell types, and circuits. Biomarkers using brain-wide activity patterns in humans have proven useful in distinguishing between disorder subtypes and identifying effective treatments. In order to improve biomarker identification, it is crucial to understand the basic circuitry underpinning brain-wide activity patterns. Leveraging a large repertoire of techniques, animal studies have examined roles of specific cell types and circuits in driving maladaptive behavior. Recent advances in multiregion recording techniques, data-driven analysis approaches, and machine-learning-based behavioral analysis tools can further push the boundary of animal studies and bridge the gap with human studies, to assess how brain-wide activity patterns encode and drive emotional behavior. Together, these efforts will allow identifying more precise biomarkers to enhance diagnosis and treatment.
Collapse
Affiliation(s)
- Frances Xia
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Mazen A Kheirbek
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA.; Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, USA; Center for Integrative Neuroscience, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
50
|
Olsen ST, Basu I, Bilge MT, Kanabar A, Boggess MJ, Rockhill AP, Gosai AK, Hahn E, Peled N, Ennis M, Shiff I, Fairbank-Haynes K, Salvi JD, Cusin C, Deckersbach T, Williams Z, Baker JT, Dougherty DD, Widge AS. Case Report of Dual-Site Neurostimulation and Chronic Recording of Cortico-Striatal Circuitry in a Patient With Treatment Refractory Obsessive Compulsive Disorder. Front Hum Neurosci 2020; 14:569973. [PMID: 33192400 PMCID: PMC7645211 DOI: 10.3389/fnhum.2020.569973] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 09/15/2020] [Indexed: 12/11/2022] Open
Abstract
Psychiatric disorders are increasingly understood as dysfunctions of hyper- or hypoconnectivity in distributed brain circuits. A prototypical example is obsessive compulsive disorder (OCD), which has been repeatedly linked to hyper-connectivity of cortico-striatal-thalamo-cortical (CSTC) loops. Deep brain stimulation (DBS) and lesions of CSTC structures have shown promise for treating both OCD and related disorders involving over-expression of automatic/habitual behaviors. Physiologically, we propose that this CSTC hyper-connectivity may be reflected in high synchrony of neural firing between loop structures, which could be measured as coherent oscillations in the local field potential (LFP). Here we report the results from the pilot patient in an Early Feasibility study (https://clinicaltrials.gov/ct2/show/NCT03184454) in which we use the Medtronic Activa PC+ S device to simultaneously record and stimulate in the supplementary motor area (SMA) and ventral capsule/ventral striatum (VC/VS). We hypothesized that frequency-mismatched stimulation should disrupt coherence and reduce compulsive symptoms. The patient reported subjective improvement in OCD symptoms and showed evidence of improved cognitive control with the addition of cortical stimulation, but these changes were not reflected in primary rating scales specific to OCD and depression, or during blinded cortical stimulation. This subjective improvement was correlated with increased SMA and VC/VS coherence in the alpha, beta, and gamma bands, signals which persisted after correcting for stimulation artifacts. We discuss the implications of this research, and propose future directions for research in network modulation in OCD and more broadly across psychiatric disorders.
Collapse
Affiliation(s)
- Sarah T. Olsen
- Department of Psychiatry, Medical School, University of Minnesota Twin Cities, Minneapolis, MN, United States
| | - Ishita Basu
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Mustafa Taha Bilge
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Anish Kanabar
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Matthew J. Boggess
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Alexander P. Rockhill
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Aishwarya K. Gosai
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Emily Hahn
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Noam Peled
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
| | - Michaela Ennis
- McLean Institute for Technology in Psychiatry and Harvard Medical School, Belmont, MA, United States
| | - Ilana Shiff
- McLean Institute for Technology in Psychiatry and Harvard Medical School, Belmont, MA, United States
| | - Katherine Fairbank-Haynes
- McLean Institute for Technology in Psychiatry and Harvard Medical School, Belmont, MA, United States
| | - Joshua D. Salvi
- McLean Institute for Technology in Psychiatry and Harvard Medical School, Belmont, MA, United States
| | - Cristina Cusin
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Thilo Deckersbach
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Ziv Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States
| | - Justin T. Baker
- McLean Institute for Technology in Psychiatry and Harvard Medical School, Belmont, MA, United States
| | - Darin D. Dougherty
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Alik S. Widge
- Department of Psychiatry, Medical School, University of Minnesota Twin Cities, Minneapolis, MN, United States
| |
Collapse
|