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Ricci A, Rubino E, Serra GP, Wallén-Mackenzie Å. Concerning neuromodulation as treatment of neurological and neuropsychiatric disorder: Insights gained from selective targeting of the subthalamic nucleus, para-subthalamic nucleus and zona incerta in rodents. Neuropharmacology 2024; 256:110003. [PMID: 38789078 DOI: 10.1016/j.neuropharm.2024.110003] [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: 02/06/2024] [Revised: 04/26/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024]
Abstract
Neuromodulation such as deep brain stimulation (DBS) is advancing as a clinical intervention in several neurological and neuropsychiatric disorders, including Parkinson's disease, dystonia, tremor, and obsessive-compulsive disorder (OCD) for which DBS is already applied to alleviate severely afflicted individuals of symptoms. Tourette syndrome and drug addiction are two additional disorders for which DBS is in trial or proposed as treatment. However, some major remaining obstacles prevent this intervention from reaching its full therapeutic potential. Side-effects have been reported, and not all DBS-treated individuals are relieved of their symptoms. One major target area for DBS electrodes is the subthalamic nucleus (STN) which plays important roles in motor, affective and associative functions, with impact on for example movement, motivation, impulsivity, compulsivity, as well as both reward and aversion. The multifunctionality of the STN is complex. Decoding the anatomical-functional organization of the STN could enhance strategic targeting in human patients. The STN is located in close proximity to zona incerta (ZI) and the para-subthalamic nucleus (pSTN). Together, the STN, pSTN and ZI form a highly heterogeneous and clinically important brain area. Rodent-based experimental studies, including opto- and chemogenetics as well as viral-genetic tract tracings, provide unique insight into complex neuronal circuitries and their impact on behavior with high spatial and temporal precision. This research field has advanced tremendously over the past few years. Here, we provide an inclusive review of current literature in the pre-clinical research fields centered around STN, pSTN and ZI in laboratory mice and rats; the three highly heterogeneous and enigmatic structures brought together in the context of relevance for treatment strategies. Specific emphasis is placed on methods of manipulation and behavioral impact.
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Affiliation(s)
- Alessia Ricci
- Uppsala University, Department of Organism Biology, 756 32 Uppsala, Sweden; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Eleonora Rubino
- Uppsala University, Department of Organism Biology, 756 32 Uppsala, Sweden; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Gian Pietro Serra
- Uppsala University, Department of Organism Biology, 756 32 Uppsala, Sweden; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA
| | - Åsa Wallén-Mackenzie
- Uppsala University, Department of Organism Biology, 756 32 Uppsala, Sweden; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA.
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Fasano A, Mure H, Oyama G, Murase N, Witt T, Higuchi Y, Singer A, Sannelli C, Morelli N. Subthalamic nucleus local field potential stability in patients with Parkinson's disease. Neurobiol Dis 2024; 199:106589. [PMID: 38969232 DOI: 10.1016/j.nbd.2024.106589] [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: 03/05/2024] [Revised: 06/19/2024] [Accepted: 07/02/2024] [Indexed: 07/07/2024] Open
Abstract
BACKGROUND Despite the large body of work on local field potentials (LFPs), a measure of oscillatory activity in patients with Parkinson's disease (PD), the longitudinal evolution of LFPs is less explored. OBJECTIVE To determine LFP fluctuations collected in clinical settings in patients with PD and STN deep brain stimulation (DBS). METHODS Twenty-two STN-DBS patients (age: 67.6 ± 8.3 years; 9 females; disease duration: 10.3 ± 4.5 years) completed bilateral LFP recordings over three visits in the OFF-stimulation setting. Peak and band power measures were calculated from each recording. RESULTS After bilateral LFP recordings, at least one peak was detected in 18 (81.8%), 20 (90.9%), and 22 (100%) patients at visit 1, 2, and 3, respectively. No significant differences were seen in primary peak amplitude (F = 2.91, p = 0.060) over time. Amplitude of the second largest peak (F = 5.49, p = 0.006) and low-beta (F = 6.89, p = 0.002), high-beta (F = 13.23, p < 0.001), and gamma (F = 12.71, p < 0.001) band power demonstrated a significant effect of time. Post hoc comparisons determined low-beta power (Visit 1-Visit 2: t = 3.59, p = 0.002; Visit 1-Visit 3: t = 2.61, p = 0.031), high-beta (Visit 1-Visit 2: t = 4.64, p < 0.001; Visit 1-Visit 3: t = 4.23, p < 0.001) and gamma band power (Visit 1-Visit 2: t = 4.65, p < 0.001; Visit 1-Visit 3: t = 4.00, p < 0.001) were significantly increased from visit 1 recordings to both follow-up visits. CONCLUSION Our results provide substantial evidence that LFP can reliably be detected across multiple real-world clinical visits in patients with STN-DBS for PD. Moreover, it provides insights on the evolution of these LFPs.
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Affiliation(s)
- Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Toronto, Canada; Division of Neurology, University of Toronto, Toronto, Canada; Krembil Brain Institute, University Health Network, Toronto, Canada; Center for Advancing Neurotechnological Innovation to Application, Toronto, Canada.
| | - Hideo Mure
- Center for Neuromodulation, Department of Neurosurgery, Kurashiki Heisei Hospital, Kurashiki, Japan
| | - Genko Oyama
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Nagako Murase
- Department of Neurology, National Hospital Organization Nara Medical Center, Nara, Japan
| | - Thomas Witt
- Department of Neurosurgery, Indiana University Medical Center, Indianapolis, IN, USA
| | - Yoshinori Higuchi
- Department of Neurological Surgery, Graduate School of Medicine, Chiba University Hospital, Chiba, Japan
| | - Alexa Singer
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic PLC, Minneapolis, MN, USA
| | - Claudia Sannelli
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic PLC, Minneapolis, MN, USA
| | - Nathan Morelli
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic PLC, Minneapolis, MN, USA
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Rohr-Fukuma M, Stieglitz LH, Bujan B, Jedrysiak P, Oertel MF, Salzmann L, Baumann CR, Imbach LL, Gassert R, Bichsel O. Neurofeedback-enabled beta power control with a fully implanted DBS system in patients with Parkinson's disease. Clin Neurophysiol 2024; 165:1-15. [PMID: 38941959 DOI: 10.1016/j.clinph.2024.06.001] [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: 09/13/2023] [Revised: 04/18/2024] [Accepted: 06/03/2024] [Indexed: 06/30/2024]
Abstract
OBJECTIVE Parkinsonian motor symptoms are linked to pathologically increased beta oscillations in the basal ganglia. Studies with externalised deep brain stimulation electrodes showed that Parkinson patients were able to rapidly gain control over these pathological basal ganglia signals through neurofeedback. Studies with fully implanted deep brain stimulation systems duplicating these promising results are required to grant transferability to daily application. METHODS In this study, seven patients with idiopathic Parkinson's disease and one with familial Parkinson's disease were included. In a postoperative setting, beta oscillations from the subthalamic nucleus were recorded with a fully implanted deep brain stimulation system and converted to a real-time visual feedback signal. Participants were instructed to perform bidirectional neurofeedback tasks with the aim to modulate these oscillations. RESULTS While receiving regular medication and deep brain stimulation, participants were able to significantly improve their neurofeedback ability and achieved a significant decrease of subthalamic beta power (median reduction of 31% in the final neurofeedback block). CONCLUSION We could demonstrate that a fully implanted deep brain stimulation system can provide visual neurofeedback enabling patients with Parkinson's disease to rapidly control pathological subthalamic beta oscillations. SIGNIFICANCE Fully-implanted DBS electrode-guided neurofeedback is feasible and can now be explored over extended timespans.
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Affiliation(s)
- Manabu Rohr-Fukuma
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | - Lennart H Stieglitz
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | | | | | - Markus F Oertel
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | - Lena Salzmann
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Christian R Baumann
- Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland; Department of Neurology, University Hospital Zurich, University of Zurich, Switzerland
| | | | - Roger Gassert
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Oliver Bichsel
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland; Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland.
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Lefaucheur JP, Moro E, Shirota Y, Ugawa Y, Grippe T, Chen R, Benninger DH, Jabbari B, Attaripour S, Hallett M, Paulus W. Clinical neurophysiology in the treatment of movement disorders: IFCN handbook chapter. Clin Neurophysiol 2024; 164:57-99. [PMID: 38852434 DOI: 10.1016/j.clinph.2024.05.007] [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: 10/17/2023] [Revised: 03/02/2024] [Accepted: 05/15/2024] [Indexed: 06/11/2024]
Abstract
In this review, different aspects of the use of clinical neurophysiology techniques for the treatment of movement disorders are addressed. First of all, these techniques can be used to guide neuromodulation techniques or to perform therapeutic neuromodulation as such. Neuromodulation includes invasive techniques based on the surgical implantation of electrodes and a pulse generator, such as deep brain stimulation (DBS) or spinal cord stimulation (SCS) on the one hand, and non-invasive techniques aimed at modulating or even lesioning neural structures by transcranial application. Movement disorders are one of the main areas of indication for the various neuromodulation techniques. This review focuses on the following techniques: DBS, repetitive transcranial magnetic stimulation (rTMS), low-intensity transcranial electrical stimulation, including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), and focused ultrasound (FUS), including high-intensity magnetic resonance-guided FUS (MRgFUS), and pulsed mode low-intensity transcranial FUS stimulation (TUS). The main clinical conditions in which neuromodulation has proven its efficacy are Parkinson's disease, dystonia, and essential tremor, mainly using DBS or MRgFUS. There is also some evidence for Tourette syndrome (DBS), Huntington's disease (DBS), cerebellar ataxia (tDCS), and axial signs (SCS) and depression (rTMS) in PD. The development of non-invasive transcranial neuromodulation techniques is limited by the short-term clinical impact of these techniques, especially rTMS, in the context of very chronic diseases. However, at-home use (tDCS) or current advances in the design of closed-loop stimulation (tACS) may open new perspectives for the application of these techniques in patients, favored by their easier use and lower rate of adverse effects compared to invasive or lesioning methods. Finally, this review summarizes the evidence for keeping the use of electromyography to optimize the identification of muscles to be treated with botulinum toxin injection, which is indicated and widely performed for the treatment of various movement disorders.
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Affiliation(s)
- Jean-Pascal Lefaucheur
- Clinical Neurophysiology Unit, Henri Mondor University Hospital, AP-HP, Créteil, France; EA 4391, ENT Team, Paris-Est Créteil University, Créteil, France.
| | - Elena Moro
- Grenoble Alpes University, Division of Neurology, CHU of Grenoble, Grenoble Institute of Neuroscience, Grenoble, France
| | - Yuichiro Shirota
- Department of Neurology, Division of Neuroscience, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yoshikazu Ugawa
- Department of Human Neurophysiology, School of Medicine, Fukushima Medical University, Fukushima, Japan
| | - Talyta Grippe
- Division of Neurology, University of Toronto, Toronto, Ontario, Canada; Neuroscience Graduate Program, Federal University of Minas Gerais, Belo Horizonte, Brazil; Krembil Brain Institute, Toronto, Ontario, Canada
| | - Robert Chen
- Division of Neurology, University of Toronto, Toronto, Ontario, Canada; Krembil Brain Institute, Toronto, Ontario, Canada
| | - David H Benninger
- Service of Neurology, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Bahman Jabbari
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Sanaz Attaripour
- Department of Neurology, University of California, Irvine, CA, USA
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Walter Paulus
- Department of Neurology, Ludwig Maximilians University, Munich, Germany
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Li Y, Nie Y, Quan Z, Zhang H, Song R, Feng H, Cheng X, Liu W, Geng X, Sun X, Fu Y, Wang S. Brain-machine interactive neuromodulation research tool with edge AI computing. Heliyon 2024; 10:e32609. [PMID: 38975192 PMCID: PMC11225749 DOI: 10.1016/j.heliyon.2024.e32609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 06/06/2024] [Indexed: 07/09/2024] Open
Abstract
Closed-loop neuromodulation with intelligence methods has shown great potentials in providing novel neuro-technology for treating neurological and psychiatric diseases. Development of brain-machine interactive neuromodulation strategies could lead to breakthroughs in precision and personalized electronic medicine. The neuromodulation research tool integrating artificial intelligent computing and performing neural sensing and stimulation in real-time could accelerate the development of closed-loop neuromodulation strategies and translational research into clinical application. In this study, we developed a brain-machine interactive neuromodulation research tool (BMINT), which has capabilities of neurophysiological signals sensing, computing with mainstream machine learning algorithms and delivering electrical stimulation pulse by pulse in real-time. The BMINT research tool achieved system time delay under 3 ms, and computing capabilities in feasible computation cost, efficient deployment of machine learning algorithms and acceleration process. Intelligent computing framework embedded in the BMINT enable real-time closed-loop neuromodulation developed with mainstream AI ecosystem resources. The BMINT could provide timely contribution to accelerate the translational research of intelligent neuromodulation by integrating neural sensing, edge AI computing and stimulation with AI ecosystems.
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Affiliation(s)
- Yan Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Yingnan Nie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Zhaoyu Quan
- Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, China
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Han Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Rui Song
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Hao Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Xi Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Wei Liu
- Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, China
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Xinyi Geng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Xinwei Sun
- School of Data Science, Fudan University, Shanghai, China
| | - Yanwei Fu
- School of Data Science, Fudan University, Shanghai, China
| | - Shouyan Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
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Bayman E, Chee K, Mendlen M, Denman DJ, Tien RN, Ojemann S, Kramer DR, Thompson JA. Subthalamic nucleus synchronization between beta band local field potential and single-unit activity in Parkinson's disease. Physiol Rep 2024; 12:e16001. [PMID: 38697943 PMCID: PMC11065686 DOI: 10.14814/phy2.16001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 12/24/2023] [Accepted: 03/26/2024] [Indexed: 05/05/2024] Open
Abstract
Local field potential (LFP) oscillations in the beta band (13-30 Hz) in the subthalamic nucleus (STN) of Parkinson's disease patients have been implicated in disease severity and treatment response. The relationship between single-neuron activity in the STN and regional beta power changes remains unclear. We used spike-triggered average (STA) to assess beta synchronization in STN. Beta power and STA magnitude at the beta frequency range were compared in three conditions: STN versus other subcortical structures, dorsal versus ventral STN, and high versus low beta power STN recordings. Magnitude of STA-LFP was greater within the STN compared to extra-STN structures along the trajectory path, despite no difference in percentage of the total power. Within the STN, there was a higher percent beta power in dorsal compared to ventral STN but no difference in STA-LFP magnitude. Further refining the comparison to high versus low beta peak power recordings inside the STN to evaluate if single-unit activity synchronized more strongly with beta band activity in areas of high beta power resulted in a significantly higher STA magnitude for areas of high beta power. Overall, these results suggest that STN single units strongly synchronize to beta activity, particularly units in areas of high beta power.
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Affiliation(s)
- Eric Bayman
- Department of NeurosurgeryUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Keanu Chee
- Department of NeurosurgeryUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Madelyn Mendlen
- Department of NeurosurgeryUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Daniel J. Denman
- Department of Neurophysiology and BiophysicsUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Rex N. Tien
- Department of NeurosurgeryUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Steven Ojemann
- Department of NeurosurgeryUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Daniel R. Kramer
- Department of NeurosurgeryUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - John A. Thompson
- Department of NeurosurgeryUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
- Department of NeurologyUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
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Mathiopoulou V, Lofredi R, Feldmann LK, Habets J, Darcy N, Neumann WJ, Faust K, Schneider GH, Kühn AA. Modulation of subthalamic beta oscillations by movement, dopamine, and deep brain stimulation in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:77. [PMID: 38580641 PMCID: PMC10997749 DOI: 10.1038/s41531-024-00693-3] [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] [Received: 09/21/2023] [Accepted: 03/21/2024] [Indexed: 04/07/2024] Open
Abstract
Subthalamic beta band activity (13-35 Hz) is known as a real-time correlate of motor symptom severity in Parkinson's disease (PD) and is currently explored as a feedback signal for closed-loop deep brain stimulation (DBS). Here, we investigate the interaction of movement, dopaminergic medication, and deep brain stimulation on subthalamic beta activity in PD patients implanted with sensing-enabled, implantable pulse generators. We recorded subthalamic activity from seven PD patients at rest and during repetitive movements in four conditions: after withdrawal of dopaminergic medication and DBS, with medication only, with DBS only, and with simultaneous medication and DBS. Medication and DBS showed additive effects in improving motor performance. Distinct effects of each therapy were seen in subthalamic recordings, with medication primarily suppressing low beta activity (13-20 Hz) and DBS being associated with a broad decrease in beta band activity (13-35 Hz). Movement suppressed beta band activity compared to rest. This suppression was most prominent when combining medication with DBS and correlated with motor improvement within patients. We conclude that DBS and medication have distinct effects on subthalamic beta activity during both rest and movement, which might explain their additive clinical effects as well as their difference in side-effect profiles. Importantly, subthalamic beta activity significantly correlated with motor symptoms across all conditions, highlighting its validity as a feedback signal for closed-loop DBS.
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Affiliation(s)
- Varvara Mathiopoulou
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Roxanne Lofredi
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Lucia K Feldmann
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Jeroen Habets
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Natasha Darcy
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Wolf-Julian Neumann
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Katharina Faust
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Gerd-Helge Schneider
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Andrea A Kühn
- Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
- Berlin School of Mind and Brain, Charité Universitätsmedizin Medicine, Berlin, Germany.
- NeuroCure Clinical Research Centre, Charité Universitätsmedizin, Berlin, Germany.
- DZNE, German Center for Degenerative Diseases, Berlin, Germany.
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Abdulbaki A, Doll T, Helgers S, Heissler HE, Voges J, Krauss JK, Schwabe K, Alam M. Subthalamic Nucleus Deep Brain Stimulation Restores Motor and Sensorimotor Cortical Neuronal Oscillatory Activity in the Free-Moving 6-Hydroxydopamine Lesion Rat Parkinson Model. Neuromodulation 2024; 27:489-499. [PMID: 37002052 DOI: 10.1016/j.neurom.2023.01.014] [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: 08/10/2022] [Revised: 12/28/2022] [Accepted: 01/04/2023] [Indexed: 03/31/2023]
Abstract
OBJECTIVES Enhanced beta oscillations in cortical-basal ganglia (BG) thalamic circuitries have been linked to clinical symptoms of Parkinson's disease. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces beta band activity in BG regions, whereas little is known about activity in cortical regions. In this study, we investigated the effect of STN DBS on the spectral power of oscillatory activity in the motor cortex (MCtx) and sensorimotor cortex (SMCtx) by recording via an electrocorticogram (ECoG) array in free-moving 6-hydroxydopamine (6-OHDA) lesioned rats and sham-lesioned controls. MATERIALS AND METHODS Male Sprague-Dawley rats (250-350 g) were injected either with 6-OHDA or with saline in the right medial forebrain bundle, under general anesthesia. A stimulation electrode was then implanted in the ipsilateral STN, and an ECoG array was placed subdurally above the MCtx and SMCtx areas. Six days after the second surgery, the free-moving rats were individually recorded in three conditions: 1) basal activity, 2) during STN DBS, and 3) directly after STN DBS. RESULTS In 6-OHDA-lesioned rats (N = 8), the relative power of theta band activity was reduced, whereas activity of broad-range beta band (12-30 Hz) along with two different subbeta bands, that is, low (12-30 Hz) and high (20-30 Hz) beta band and gamma band, was higher in MCtx and SMCtx than in sham-lesioned controls (N = 7). This was, to some extent, reverted toward control level by STN DBS during and after stimulation. No major differences were found between contacts of the electrode grid or between MCtx and SMCtx. CONCLUSION Loss of nigrostriatal dopamine leads to abnormal oscillatory activity in both MCtx and SMCtx, which is compensated by STN stimulation, suggesting that parkinsonism-related oscillations in the cortex and BG are linked through their anatomic connections.
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Affiliation(s)
- Arif Abdulbaki
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany.
| | - Theodor Doll
- Fraunhofer Institute for Toxicology and Experimental Medicine, Hannover, Germany
| | - Simeon Helgers
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Hans E Heissler
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Jürgen Voges
- Department of Stereotactic Neurosurgery, University Hospital Magdeburg, Magdeburg, Germany
| | - Joachim K Krauss
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Kerstin Schwabe
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Mesbah Alam
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
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9
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Pardo-Valencia J, Fernández-García C, Alonso-Frech F, Foffani G. Oscillatory vs. non-oscillatory subthalamic beta activity in Parkinson's disease. J Physiol 2024; 602:373-395. [PMID: 38084073 DOI: 10.1113/jp284768] [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: 04/02/2023] [Accepted: 11/13/2023] [Indexed: 01/16/2024] Open
Abstract
Parkinson's disease is characterized by exaggerated beta activity (13-35 Hz) in cortico-basal ganglia motor loops. Beta activity includes both periodic fluctuations (i.e. oscillatory activity) and aperiodic fluctuations reflecting spiking activity and excitation/inhibition balance (i.e. non-oscillatory activity). However, the relative contribution, dopamine dependency and clinical correlations of oscillatory vs. non-oscillatory beta activity remain unclear. We recorded, modelled and analysed subthalamic local field potentials in parkinsonian patients at rest while off or on medication. Autoregressive modelling with additive 1/f noise clarified the relationships between measures of beta activity in the time domain (i.e. amplitude and duration of beta bursts) or in the frequency domain (i.e. power and sharpness of the spectral peak) and oscillatory vs. non-oscillatory activity: burst duration and spectral sharpness are specifically sensitive to oscillatory activity, whereas burst amplitude and spectral power are ambiguously sensitive to both oscillatory and non-oscillatory activity. Our experimental data confirmed the model predictions and assumptions. We subsequently analysed the effect of levodopa, obtaining strong-to-extreme Bayesian evidence that oscillatory beta activity is reduced in patients on vs. off medication, with moderate evidence for absence of modulation of the non-oscillatory component. Finally, specifically the oscillatory component of beta activity correlated with the rate of motor progression of the disease. Methodologically, these results provide an integrative understanding of beta-based biomarkers relevant for adaptive deep brain stimulation. Biologically, they suggest that primarily the oscillatory component of subthalamic beta activity is dopamine dependent and may play a role not only in the pathophysiology but also in the progression of Parkinson's disease. KEY POINTS: Beta activity in Parkinson's disease includes both true periodic fluctuations (i.e. oscillatory activity) and aperiodic fluctuations reflecting spiking activity and synaptic balance (i.e. non-oscillatory activity). The relative contribution, dopamine dependency and clinical correlations of oscillatory vs. non-oscillatory beta activity remain unclear. Burst duration and spectral sharpness are specifically sensitive to oscillatory activity, while burst amplitude and spectral power are ambiguously sensitive to both oscillatory and non-oscillatory activity. Only the oscillatory component of subthalamic beta activity is dopamine-dependent. Stronger beta oscillatory activity correlates with faster motor progression of the disease.
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Affiliation(s)
- Jesús Pardo-Valencia
- HM CINAC (Centro Integral de Neurociencias Abarca Campal), Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
| | - Carla Fernández-García
- HM CINAC (Centro Integral de Neurociencias Abarca Campal), Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
| | - Fernando Alonso-Frech
- HM CINAC (Centro Integral de Neurociencias Abarca Campal), Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Department of Neurology, San Carlos Research Health Intitute (IdISSC), Hospital Clínico San Carlos, Madrid, Spain
| | - Guglielmo Foffani
- HM CINAC (Centro Integral de Neurociencias Abarca Campal), Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Hospital Nacional de Parapléjicos, SESCAM, Toledo, Spain
- Instituto de Salud Carlos III, CIBERNED, Madrid, Spain
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10
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Hill ME, Johnson LA, Wang J, Sanabria DE, Patriat R, Cooper SE, Park MC, Harel N, Vitek JL, Aman JE. Paradoxical Modulation of STN β-Band Activity with Medication Compared to Deep Brain Stimulation. Mov Disord 2024; 39:192-197. [PMID: 37888906 PMCID: PMC10843006 DOI: 10.1002/mds.29634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 09/20/2023] [Accepted: 10/04/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND Excessive subthalamic nucleus (STN) β-band (13-35 Hz) synchronized oscillations has garnered interest as a biomarker for characterizing disease state and developing adaptive stimulation systems for Parkinson's disease (PD). OBJECTIVES To report on a patient with abnormal treatment-responsive modulation in the β-band. METHODS We examined STN local field potentials from an externalized deep brain stimulation (DBS) lead while assessing PD motor signs in four conditions (OFF, MEDS, DBS, and MEDS+DBS). RESULTS The patient presented here exhibited a paradoxical increase in β power following administration of levodopa and pramipexole (MEDS), but an attenuation in β power during DBS and MEDS+DBS despite clinical improvement of 50% or greater under all three therapeutic conditions. CONCLUSIONS This case highlights the need for further study on the role of β oscillations in the pathophysiology of PD and the importance of personalized approaches to the development of β or other biomarker-based DBS closed loop algorithms. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Meghan E. Hill
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Luke A. Johnson
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | | | - Rémi Patriat
- Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Scott E. Cooper
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Michael C. Park
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA
| | - Noam Harel
- Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Joshua E. Aman
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
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Guehl D, Guillaud E, Langbour N, Doat E, Auzou N, Courtin E, Branchard O, Engelhardt J, Benazzouz A, Eusebio A, Cuny E, Burbaud P. Usefulness of thalamic beta activity for closed-loop therapy in essential tremor. Sci Rep 2023; 13:22332. [PMID: 38102180 PMCID: PMC10724233 DOI: 10.1038/s41598-023-49511-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 12/08/2023] [Indexed: 12/17/2023] Open
Abstract
A partial loss of effectiveness of deep brain stimulation of the ventral intermediate nucleus of the thalamus (VIM) has been reported in some patients with essential tremor (ET), possibly due to habituation to permanent stimulation. This study focused on the evolution of VIM local-field potentials (LFPs) data over time to assess the long-term feasibility of closed-loop therapy based on thalamic activity. We performed recordings of thalamic LFPs in 10 patients with severe ET using the ACTIVA™ PC + S (Medtronic plc.) allowing both recordings and stimulation in the same region. Particular attention was paid to describing the evolution of LFPs over time from 3 to 24 months after surgery when the stimulation was Off. We demonstrated a significant decrease in high-beta LFPs amplitude during movements inducing tremor in comparison to the rest condition 3 months after surgery (1.91 ± 0.89 at rest vs. 1.27 ± 1.37 µV2/Hz during posture/action for N = 8/10 patients; p = 0.010), 12 months after surgery (2.92 ± 1.75 at rest vs. 2.12 ± 1.78 µV2/Hz during posture/action for N = 7/10 patients; p = 0.014) and 24 months after surgery (2.32 ± 0.35 at rest vs 0.75 ± 0.78 µV2/Hz during posture/action for 4/6 patients; p = 0.017). Among the patients who exhibited a significant decrease of high-beta LFP amplitude when stimulation was Off, this phenomenon was observed at least twice during the follow-up. Although the extent of this decrease in high-beta LFPs amplitude during movements inducing tremor may vary over time, this thalamic biomarker of movement could potentially be usable for closed-loop therapy in the long term.
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Affiliation(s)
- Dominique Guehl
- Service de Neurophysiologie Clinique de l'enfant et de l'adulte, Hôpital Pellegrin, Pôle des Neurosciences Cliniques, CHU de Bordeaux, Bordeaux, France.
- Institut des Maladies Neurodégénératives, Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000, Bordeaux, France.
| | - Etienne Guillaud
- Institute of Cognitive and Integrative Neurosciences, Univ. Bordeaux, CNRS, INCIA, UMR 5287, F-33000, Bordeaux, France
| | - Nicolas Langbour
- Centre de Recherche en Psychiatrie, CH de la Milétrie, 86000, Poitiers, France
| | - Emilie Doat
- Institute of Cognitive and Integrative Neurosciences, Univ. Bordeaux, CNRS, INCIA, UMR 5287, F-33000, Bordeaux, France
| | - Nicolas Auzou
- Institut des Maladies Neurodégénératives Clinique (IMNc), Pôle des Neurosciences Cliniques, CHU de Bordeaux, Bordeaux, France
| | - Edouard Courtin
- Service de Neurophysiologie Clinique de l'enfant et de l'adulte, Hôpital Pellegrin, Pôle des Neurosciences Cliniques, CHU de Bordeaux, Bordeaux, France
| | | | | | - Abdelhamid Benazzouz
- Institut des Maladies Neurodégénératives, Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000, Bordeaux, France
| | - Alexandre Eusebio
- Department of Neurology and Movement Disorders, APHM, Hôpitaux Universitaire de Marseille, Marseille, France
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Univ, CNRS, Marseille, France
| | - Emmanuel Cuny
- Service de Neurochirurgie, CHU de Bordeaux, Bordeaux, France
| | - Pierre Burbaud
- Service de Neurophysiologie Clinique de l'enfant et de l'adulte, Hôpital Pellegrin, Pôle des Neurosciences Cliniques, CHU de Bordeaux, Bordeaux, France
- Institut des Maladies Neurodégénératives, Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000, Bordeaux, France
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12
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Mirzai N, Polet K, Morisot A, Hesse S, Pesce A, Louchart de la Chapelle S, Iakimova G. Can the Ability to Recognize Facial Emotions in Individuals With Neurodegenerative Disease be Improved? A Systematic Review and Meta-analysis. Cogn Behav Neurol 2023; 36:202-218. [PMID: 37410880 PMCID: PMC10683976 DOI: 10.1097/wnn.0000000000000348] [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: 08/17/2022] [Accepted: 03/30/2023] [Indexed: 07/08/2023]
Abstract
BACKGROUND Facial emotion recognition (FER) is commonly impaired in individuals with neurodegenerative disease (NDD). This impairment has been linked to an increase in behavioral disorders and caregiver burden. OBJECTIVE To identify interventions targeting the improvement of FER ability in individuals with NDD and investigate the magnitude of the efficacy of the interventions. We also wanted to explore the duration of the effects of the intervention and their possible impacts on behavioral and psychological symptoms of dementia and caregiver burden. METHOD We included 15 studies with 604 individuals who had been diagnosed with NDD. The identified interventions were categorized into three types of approach (cognitive, neurostimulation, and pharmacological) as well as a combined approach (neurostimulation with pharmacological). RESULTS The three types of approaches pooled together had a significant large effect size for FER ability improvement (standard mean difference: 1.21, 95% CI = 0.11, 2.31, z = 2.15, P = 0.03). The improvement lasted post intervention, in tandem with a decrease in behavioral disorders and caregiver burden. CONCLUSION A combination of different approaches for FER ability improvement may be beneficial for individuals with NDD and their caregivers.
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Affiliation(s)
- Naz Mirzai
- Clinical Research Unit–Memory Clinic, Princess Grace Hospital, Monaco
- Cote d’Azur University, Laboratory of Clinical, Cognitive and Social Anthropology and Psychology, Nice, France
| | - Kévin Polet
- Clinical Research Unit–Memory Clinic, Princess Grace Hospital, Monaco
| | - Adeline Morisot
- Clinical Research Unit–Memory Clinic, Princess Grace Hospital, Monaco
- Public Health Department, Cote d’Azur University, University Hospital Center of Nice, Nice, France
| | - Solange Hesse
- Clinical Research Unit–Memory Clinic, Princess Grace Hospital, Monaco
| | - Alain Pesce
- Bibliographic Research Association for Neurosciences, Nice, France
| | | | - Galina Iakimova
- Cote d’Azur University, Laboratory of Clinical, Cognitive and Social Anthropology and Psychology, Nice, France
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13
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Su F, Wang H, Zu L, Chen Y. Closed-loop modulation of model parkinsonian beta oscillations based on CAR-fuzzy control algorithm. Cogn Neurodyn 2023; 17:1185-1199. [PMID: 37786652 PMCID: PMC10542090 DOI: 10.1007/s11571-022-09820-3] [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] [Received: 10/19/2021] [Revised: 04/20/2022] [Accepted: 04/28/2022] [Indexed: 12/01/2022] Open
Abstract
Closed-loop deep brain stimulation (DBS) can apply on-demand stimulation based on the feedback signal (e.g. beta band oscillation), which is deemed to lower side effects of clinically used open-loop DBS. To facilitate the application of model-based closed-loop DBS in clinical, studies must consider state variations, e.g., variation of desired signal with different movement conditions and variation of model parameters with time. This paper proposes to use the controlled autoregressive (CAR)-fuzzy control algorithm to modulate the pathological beta band (13-35 Hz) oscillation of a basal ganglia-cortex-thalamus model. The CAR model is used to identify the relationship between DBS frequency parameter and beta oscillation power. Then the error between the one-step-ahead predicted beta power of CAR model and the desired value is innovatively used as the input of fuzzy controller to calculate the next step stimulation frequency. Compared with 130 Hz open-loop DBS, the proposed closed-loop DBS method could lower the mean stimulation frequency to 74.04 Hz with similar beta oscillation suppression performance. The Mamdani fuzzy controller is selected because which could establish fuzzy controller rules according to human operation experience. Adding prediction module to closed-loop control improves the accuracy of fuzzy control, compared with proportional-integral control and fuzzy control, the proposed CAR-fuzzy control algorithm has higher tracking reliability, response speed and robustness.
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Affiliation(s)
- Fei Su
- School of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, 271018 China
| | - Hong Wang
- School of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, 271018 China
| | - Linlu Zu
- School of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, 271018 China
| | - Yan Chen
- Department of Neurology, Shanghai Jiahui International Hospital, Shanghai, 200233 China
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14
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Sil T, Hanafi I, Eldebakey H, Palmisano C, Volkmann J, Muthuraman M, Reich MM, Peach R. Wavelet-Based Bracketing, Time-Frequency Beta Burst Detection: New Insights in Parkinson's Disease. Neurotherapeutics 2023; 20:1767-1778. [PMID: 37819489 PMCID: PMC10684463 DOI: 10.1007/s13311-023-01447-4] [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] [Accepted: 09/25/2023] [Indexed: 10/13/2023] Open
Abstract
Studies have shown that beta band activity is not tonically elevated but comprises exaggerated phasic bursts of varying durations and magnitudes, for Parkinson's disease (PD) patients. Current methods for detecting beta bursts target a single frequency peak in beta band, potentially ignoring bursts in the wider beta band. In this study, we propose a new robust framework for beta burst identification across wide frequency ranges. Chronic local field potential at-rest recordings were obtained from seven PD patients implanted with Medtronic SenSight™ deep brain stimulation (DBS) electrodes. The proposed method uses wavelet decomposition to compute the time-frequency spectrum and identifies bursts spanning multiple frequency bins by thresholding, offering an additional burst measure, ∆f, that captures the width of a burst in the frequency domain. Analysis included calculating burst duration, magnitude, and ∆f and evaluating the distribution and likelihood of bursts between the low beta (13-20 Hz) and high beta (21-35 Hz). Finally, the results of the analysis were correlated to motor impairment (MDS-UPDRS III) med off scores. We found that low beta bursts with longer durations and larger width in the frequency domain (∆f) were positively correlated, while high beta bursts with longer durations and larger ∆f were negatively correlated with motor impairment. The proposed method, finding clear differences between bursting behavior in high and low beta bands, has clearly demonstrated the importance of considering wide frequency bands for beta burst behavior with implications for closed-loop DBS paradigms.
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Affiliation(s)
- Tanmoy Sil
- Department of Neurology, University Hospital Würzburg (UKW), Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Ibrahem Hanafi
- Department of Neurology, University Hospital Würzburg (UKW), Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Hazem Eldebakey
- Department of Neurology, University Hospital Würzburg (UKW), Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Chiara Palmisano
- Department of Neurology, University Hospital Würzburg (UKW), Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital Würzburg (UKW), Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, University Hospital Würzburg (UKW), Josef-Schneider-Str. 11, 97080, Würzburg, Germany.
| | - Martin M Reich
- Department of Neurology, University Hospital Würzburg (UKW), Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Robert Peach
- Department of Neurology, University Hospital Würzburg (UKW), Josef-Schneider-Str. 11, 97080, Würzburg, Germany
- Department of Brain Sciences, Imperial College London, London, UK
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15
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Ramdhani RA, Watts J, Kline M, Fitzpatrick T, Niethammer M, Khojandi A. Differential spatiotemporal gait effects with frequency and dopaminergic modulation in STN-DBS. Front Aging Neurosci 2023; 15:1206533. [PMID: 37842127 PMCID: PMC10570440 DOI: 10.3389/fnagi.2023.1206533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 09/01/2023] [Indexed: 10/17/2023] Open
Abstract
Objective The spatiotemporal gait changes in advanced Parkinson's disease (PD) remain a treatment challenge and have variable responses to L-dopa and subthalamic deep brain stimulation (STN-DBS). The purpose of this study was to determine whether low-frequency STN-DBS (LFS; 60 Hz) elicits a differential response to high-frequency STN-DBS (HFS; 180 Hz) in spatiotemporal gait kinematics. Methods Advanced PD subjects with chronic STN-DBS were evaluated in both the OFF and ON medication states with LFS and HFS stimulation. Randomization of electrode contact pairs and frequency conditions was conducted. Instrumented Stand and Walk assessments were carried out for every stimulation/medication condition. LM-ANOVA was employed for analysis. Results Twenty-two PD subjects participated in the study, with a mean age (SD) of 63.9 years. Significant interactions between frequency (both LFS and HFS) and electrode contact pairs (particularly ventrally located contacts) were observed for both spatial (foot elevation, toe-off angle, stride length) and temporal (foot speed, stance, single limb support (SLS) and foot swing) gait parameters. A synergistic effect was also demonstrated with L-dopa and both HFS and LFS for right SLS, left stance, left foot swing, right toe-off angle, and left arm range of motion. HFS produced significant improvement in trunk and lumbar range of motion compared to LFS. Conclusion The study provides evidence of synergism of L-dopa and STN-DBS on lower limb spatial and temporal measures in advanced PD. HFS and LFS STN-DBS produced equivalent effects among all other tested lower limb gait features. HFS produced significant trunk and lumbar kinematic improvements.
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Affiliation(s)
- Ritesh A. Ramdhani
- Department of Neurology, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Jeremy Watts
- Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN, United States
| | - Myriam Kline
- Center for Neurosciences, Feinstein Institutes for Medical Research at Northwell Health, Manhasset, NY, United States
| | - Toni Fitzpatrick
- Center for Neurosciences, Feinstein Institutes for Medical Research at Northwell Health, Manhasset, NY, United States
| | - Martin Niethammer
- Department of Neurology, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
- Center for Neurosciences, Feinstein Institutes for Medical Research at Northwell Health, Manhasset, NY, United States
| | - Anahita Khojandi
- Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN, United States
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Cohen SL, Woo Choi J, Toga AW, Pouratian N, Duncan D. Exaggerated High-Beta Oscillations are Associated with Cortical Thinning at the Motor Cortex in Parkinson's Disease. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083533 DOI: 10.1109/embc40787.2023.10341040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Elevated β oscillations (13-35 Hz) are characteristic pathophysiology in Parkinson's Disease (PD). Cortical thinning has also been reported in the disease, however the relationship between these biomarkers of PD has not been established. By comparing electrophysiological measurements with cortical thickness, this study aims to reveal the pathoetiology of disease and symptoms in PD. Preoperative magnetic resonance imaging (MRI) and intraoperative local field potentials (LFPs) were collected from 34 subjects diagnosed with PD. Cortical surfaces were reconstructed from the images, and cortical thickness was extracted from the subregions where the recording electrode was placed in M1. LFPs were preprocessed and cleaned using a semiautomatic artifact detection algorithm, then power spectral densities (PSD) were computed and periodic and aperiodic frequency components were calculated. Nonparametric Spearman rank correlations assessed the relationship between electrophysiological components (i.e. center frequency (CF), power, bandwidth, 1/f exponent, knee), with cortical thickness. According to the CF of each subject's PSD, the cohort was split into two sub-groups: low-β peak (13-20 Hz) and high-β peak (20-35 Hz) groups. There was a significant negative correlation between power and cortical thickness only in the high-β subgroup (r=-0.48, p(corrected)=0.049). This relationship remained significant when correcting for age (r=-0.52,p=0.015), indicating that the effect of age on cortical thinning was not the determining factor. We did not find significant differences between UPDRS-III motor symptom scores for the low-and high-β subgroups. Of note is the dominance of high-β oscillatory power and its relationship with cortical thickness. As suggested by the literature, increased high-β activity during movement may be exaggerated in PD. These findings suggest that the characteristic cortical thinning in PD causes variation in electrical activity, leading to elevated high-β activity.Clinical relevance- This multimodal study provides additional insights on the pathophysiology and its relevance with morphology of Parkinson's Disease.
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17
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Wilkins KB, Kehnemouyi YM, Petrucci MN, Anderson RW, Parker JE, Trager MH, Neuville RS, Koop MM, Velisar A, Blumenfeld Z, Quinn EJ, Bronte-Stewart HM. Bradykinesia and Its Progression Are Related to Interhemispheric Beta Coherence. Ann Neurol 2023; 93:1029-1039. [PMID: 36641645 PMCID: PMC10191890 DOI: 10.1002/ana.26605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 12/05/2022] [Accepted: 01/09/2023] [Indexed: 01/16/2023]
Abstract
OBJECTIVE Bradykinesia is the major cardinal motor sign of Parkinson disease (PD), but its neural underpinnings are unclear. The goal of this study was to examine whether changes in bradykinesia following long-term subthalamic nucleus (STN) deep brain stimulation (DBS) are linked to local STN beta (13-30 Hz) dynamics or a wider bilateral network dysfunction. METHODS Twenty-one individuals with PD implanted with sensing neurostimulators (Activa® PC + S, Medtronic, PLC) in the STN participated in a longitudinal 'washout' therapy study every three to 6 months for an average of 3 years. At each visit, participants were withdrawn from medication (12/24/48 hours) and had DBS turned off (>60 minutes) before completing a repetitive wrist-flexion extension task, a validated quantitative assessment of bradykinesia, while local field potentials were recorded. Local STN beta dynamics were investigated via beta power and burst duration, while interhemispheric beta synchrony was assessed with STN-STN beta coherence. RESULTS Higher interhemispheric STN beta coherence, but not contralateral beta power or burst duration, was significantly associated with worse bradykinesia. Bradykinesia worsened off therapy over time. Interhemispheric STN-STN beta coherence also increased over time, whereas beta power and burst duration remained stable. The observed change in bradykinesia was related to the change in interhemispheric beta coherence, with greater increases in synchrony associated with further worsening of bradykinesia. INTERPRETATION Together, these findings implicate interhemispheric beta synchrony as a neural correlate of the progression of bradykinesia following chronic STN DBS. This could imply the existence of a pathological bilateral network contributing to bradykinesia in PD. ANN NEUROL 2023;93:1029-1039.
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Affiliation(s)
- Kevin B Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Yasmine M Kehnemouyi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Bioengineering, Stanford Schools of Engineering & Medicine, Stanford, CA, United States
| | - Matthew N Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Bioengineering, Stanford Schools of Engineering & Medicine, Stanford, CA, United States
| | - Ross W Anderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Neurosurgery, Kaiser Permanente, Redwood City, CA, United States
| | - Jordan E Parker
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Psychology, University of California, Los Angeles, CA, United States
| | - Megan H Trager
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Columbia University Irving Medical Center, New York, NY, United States
| | - Raumin S Neuville
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- The University of California School of Medicine, Irvine, CA, United States
| | - Mandy M Koop
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Cleveland Clinic, Cleveland, OH, United States
| | - Anca Velisar
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- The Smith-Kettlewell Eye Research Institute, San Francisco, CA, United States
| | - Zack Blumenfeld
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States
- University of Southern California, Keck School of Medicine, Los Angeles, CA, United States
| | - Emma J Quinn
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Credit Karma, San Francisco, CA, United States
| | - Helen M Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Bioengineering, Stanford Schools of Engineering & Medicine, Stanford, CA, United States
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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Morelli N, Summers RLS. Association of subthalamic beta frequency sub-bands to symptom severity in patients with Parkinson's disease: A systematic review. Parkinsonism Relat Disord 2023; 110:105364. [PMID: 36997437 DOI: 10.1016/j.parkreldis.2023.105364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 03/08/2023] [Accepted: 03/10/2023] [Indexed: 03/29/2023]
Abstract
OBJECTIVE Local field potentials (LFP), specifically beta (13-30Hz) frequency measures, have been found to be associated with motor dysfunction in people with Parkinson's disease (PwPD). A consensus on beta subband (low- and high-beta) relationships to clinical state or therapy response has yet to be determined. The objective of this review is to synthesize literature reporting the association of low- and high-beta characteristics to clinical ratings of motor symptoms in PwPD. METHODS A systematic search of existing literature was completed using EMBASE. Articles which collected subthalamic nucleus (STN) LFPs using macroelectrodes in PwPD, analyzed low- (13-20 Hz) and high-beta (21-35 Hz) bands, collected UPDRS-III, and reported correlational strength or predictive capacity of LFPs to UPDRS-III scores. RESULTS The initial search yielded 234 articles, with 11 articles achieving inclusion. Beta measures included power spectral density, peak characteristics, and burst characteristics. High-beta was a significant predictor of UPDRS-III responses to therapy in 5 (100%) articles. Low-beta was significantly associated with UPDRS-III total score in 3 (60%) articles. Low- and high-beta associations to UPDRS-III subscores were mixed. CONCLUSION This systematic review reinforces previous reports that beta band oscillatory measures demonstrate a consistent relationship to Parkinsonian motor symptoms and ability to predict motor response to therapy. Specifically, high-beta, demonstrated a consistent ability to predict UPDRS-III responses to common PD therapies, while low-beta measures were associated with general Parkinsonian symptom severity. Continued research is needed to determine which beta subband demonstrates the greatest association to motor symptom subtypes and potentially offers clinical utility toward LFP-guided DBS programming and adaptive DBS.
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19
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Formaggio E, Tonellato M, Antonini A, Castiglia L, Gallo L, Manganotti P, Masiero S, Del Felice A. Oscillatory EEG-TMS Reactivity in Parkinson Disease. J Clin Neurophysiol 2023; 40:263-268. [PMID: 34280941 DOI: 10.1097/wnp.0000000000000881] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
PURPOSE A dysfunction of beta oscillatory activity is the neurophysiological hallmark of Parkinson disease (PD). How cortical activity reacts to external perturbations may provide insight into pathophysiological mechanisms. This study aims at identifying modifications in EEG rhythms after transcranial magnetic stimulation (TMS) in PD. We hypothesize that single-pulse TMS can modulate brain intrinsic oscillatory properties (e.g., beta excess). METHODS EEG data were coregistered during single-pulse TMS (100 stimuli over the primary motor cortex [M1, hotspot for Abductor Pollicis Brevis], random intertrial interval from 8 to 13 seconds). We used a time-frequency analysis based on wavelet method to characterize modification of oscillatory rhythms (delta [1-4 Hz], theta [4-7 Hz], alpha [8-12 Hz], and beta [13-30 Hz] in 15 participants with PD compared with 10 healthy controls. RESULTS An increase in beta power over the sensorimotor areas was recorded at rest in the PD group ( P < 0.05). Brain oscillations in PD transiently reset after TMS: beta power over M1 becomes comparable to that recorded in aged-matched healthy subjects in the 2 seconds following TMS. CONCLUSIONS Transcranial magnetic stimulation over the dominant motor cortex transiently normalizes cortical oscillations. More user-friendly noninvasive brain stimulation needs to be trialed, based on this proof of concept, to provide practical, portable techniques to treat motor symptoms in PD.
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Affiliation(s)
- Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Michele Tonellato
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Centre on Neurodegeneration (CESNE), Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
| | - Leonora Castiglia
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Laura Gallo
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Paolo Manganotti
- Neurology Section, Cattinara University Hospital, University of Trieste, Trieste, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
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20
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Effects of Contralateral Deep Brain Stimulation and Levodopa on Subthalamic Nucleus Oscillatory Activity and Phase-Amplitude Coupling. Neuromodulation 2023; 26:310-319. [PMID: 36513587 DOI: 10.1016/j.neurom.2022.11.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/14/2022] [Accepted: 11/07/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND The modulatory effects of medication and deep brain stimulation (DBS) on subthalamic nucleus (STN) neural activity in Parkinson's disease have been widely studied. However, effects on the contralateral side to the stimulated STN, in particular, changes in local field potential (LFP) oscillatory activity and phase-amplitude coupling (PAC), have not yet been reported. OBJECTIVE The aim of this study was to examine changes in STN LFP activity across a range of frequency bands and STN PAC for different combinations of DBS and medication on/off on the side contralateral to the applied stimulation. MATERIALS AND METHODS We examined STN LFPs that were recorded using externalized leads from eight parkinsonian patients during unilateral DBS from the side contralateral to the stimulation. LFP spectral power in alpha (5 to ∼13 Hz), low beta (13 to ∼20 Hz), high beta (20-30 Hz), and high gamma plus high-frequency oscillation (high gamma+HFO) (100-400 Hz) bands were estimated for different combinations of medication and unilateral stimulation (off/on). PAC between beta and high gamma+HFO in the STN LFPs was also investigated. The effect of the condition was examined using linear mixed models. RESULTS PAC in the STN LFP was reduced by DBS when compared to the baseline condition (no medication and stimulation). Medication had no significant effect on PAC. Alpha power decreased with DBS, both alone and when combined with medication. Beta power decreased with DBS, medication, and DBS and medication combined. High gamma+HFO power increased during the application of contralateral DBS and was unaltered by medication. CONCLUSIONS The results provide new insights into the effects of DBS and levodopa on STN LFP PAC and oscillatory activity on the side contralateral to stimulation. These may have important implications in understanding mechanisms underlying motor improvements with DBS, including changes on both contralateral and ipsilateral sides, while suggesting a possible role for contralateral sensing during unilateral DBS.
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21
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Lin HC, Wu YH, Huang CW, Ker MD. Verification of the beta oscillations in the subthalamic nucleus of the MPTP-induced parkinsonian minipig model. Brain Res 2022; 1798:148165. [DOI: 10.1016/j.brainres.2022.148165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 11/03/2022] [Accepted: 11/10/2022] [Indexed: 11/14/2022]
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22
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Bove F, Genovese D, Moro E. Developments in the mechanistic understanding and clinical application of deep brain stimulation for Parkinson's disease. Expert Rev Neurother 2022; 22:789-803. [PMID: 36228575 DOI: 10.1080/14737175.2022.2136030] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION. Deep brain stimulation (DBS) is a life-changing treatment for patients with Parkinson's disease (PD) and gives the unique opportunity to directly explore how basal ganglia work. Despite the rapid technological innovation of the last years, the untapped potential of DBS is still high. AREAS COVERED. This review summarizes the developments in the mechanistic understanding of DBS and the potential clinical applications of cutting-edge technological advances. Rather than a univocal local mechanism, DBS exerts its therapeutic effects through several multimodal mechanisms and involving both local and network-wide structures, although crucial questions remain unexplained. Nonetheless, new insights in mechanistic understanding of DBS in PD have provided solid bases for advances in preoperative selection phase, prediction of motor and non-motor outcomes, leads placement and postoperative stimulation programming. EXPERT OPINION. DBS has not only strong evidence of clinical effectiveness in PD treatment, but technological advancements are revamping its role of neuromodulation of brain circuits and key to better understanding PD pathophysiology. In the next few years, the worldwide use of new technologies in clinical practice will provide large data to elucidate their role and to expand their applications for PD patients, providing useful insights to personalize DBS treatment and follow-up.
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Affiliation(s)
- Francesco Bove
- Neurology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Danilo Genovese
- Fresco Institute for Parkinson's and Movement Disorders, Department of Neurology, New York University School of Medicine, New York, New York, USA
| | - Elena Moro
- Grenoble Alpes University, CHU of Grenoble, Division of Neurology, Grenoble, France.,Grenoble Institute of Neurosciences, INSERM, U1216, Grenoble, France
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23
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Muñoz D, Barria P, Cifuentes CA, Aguilar R, Baleta K, Azorín JM, Múnera M. EEG Evaluation in a Neuropsychological Intervention Program Based on Virtual Reality in Adults with Parkinson's Disease. BIOSENSORS 2022; 12:bios12090751. [PMID: 36140136 PMCID: PMC9496185 DOI: 10.3390/bios12090751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/09/2022] [Accepted: 08/18/2022] [Indexed: 05/05/2023]
Abstract
Nowadays, several strategies for treating neuropsychologic function loss in Parkinson’s disease (PD) have been proposed, such as physical activity performance and developing games to exercise the mind. However, few studies illustrate the incidence of these therapies in neuronal activity. This work aims to study the feasibility of a virtual reality-based program oriented to the cognitive functions’ rehabilitation of PD patients. For this, the study was divided into intervention with the program, acquisition of signals, data processing, and results analysis. The alpha and beta bands’ power behavior was determined by evaluating the electroencephalography (EEG) signals obtained during the execution of control tests and games of the “Hand Physics Lab” Software, from which five games related to attention, planning, and sequencing, concentration, and coordination were taken. Results showed the characteristic performance of the cerebral bands during resting states and activity states. In addition, it was determined that the beta band increased its activity in all the cerebral lobes in all the tested games (p-value < 0.05). On the contrary, just one game exhibited an adequate performance of the alpha band activity of the temporal and frontal lobes (p-value < 0.02). Furthermore, the visual attention and the capacity to process and interpret the information given by the surroundings was favored during the execution of trials (p-value < 0.05); thus, the efficacy of the virtual reality program to recover cognitive functions was verified. The study highlights implementing new technologies to rehabilitate people with neurodegenerative diseases.
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Affiliation(s)
- Daniela Muñoz
- Biomedical Engineering Department, Colombian School of Engineering Julio Garavito, Bogota 111166, Colombia
| | - Patricio Barria
- Club de Leones Cruz del Sur Rehabilitation Center, Punta Arenas 6210133, Chile
- Electrical Engineering Deparment, University of Magallanes, Punta Arenas 6210427, Chile
- Systems Engineering and Automation Department, Brain-Machine Interface Systems Lab, Miguel Hernández University of Elche UMH, 03202 Elche, Spain
| | - Carlos A. Cifuentes
- Bristol Robotics Laboratory, University of the West of England, Bristol BS16 1QY, UK
- School of Engineering, Science and Technology, Universidad del Rosario, Bogotá 111711, Colombia
- Correspondence:
| | - Rolando Aguilar
- Electrical Engineering Deparment, University of Magallanes, Punta Arenas 6210427, Chile
| | - Karim Baleta
- Club de Leones Cruz del Sur Rehabilitation Center, Punta Arenas 6210133, Chile
| | - José M. Azorín
- Systems Engineering and Automation Department, Brain-Machine Interface Systems Lab, Miguel Hernández University of Elche UMH, 03202 Elche, Spain
| | - Marcela Múnera
- Biomedical Engineering Department, Colombian School of Engineering Julio Garavito, Bogota 111166, Colombia
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24
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Dopamine depletion can be predicted by the aperiodic component of subthalamic local field potentials. Neurobiol Dis 2022; 168:105692. [DOI: 10.1016/j.nbd.2022.105692] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 03/06/2022] [Accepted: 03/11/2022] [Indexed: 12/19/2022] Open
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25
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Korsun O, Renvall H, Nurminen J, Mäkelä JP, Pekkonen E. Modulation of sensory cortical activity by deep brain stimulation in advanced Parkinson's Disease. Eur J Neurosci 2022; 56:3979-3990. [PMID: 35560964 PMCID: PMC9544049 DOI: 10.1111/ejn.15692] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 04/28/2022] [Accepted: 05/10/2022] [Indexed: 11/28/2022]
Abstract
Despite optimal oral drug treatment, about 90% of patients with Parkinson's disease develop motor fluctuation and dyskinesia within 5-10 years from the diagnosis. Moreover, the patients show non-motor symptoms in different sensory domains. Bilateral deep brain stimulation applied to the subthalamic nucleus is considered the most effective treatment in advanced Parkinson's disease and it has been suggested to affect sensorimotor modulation and relate to motor improvement in patients. However, observations on the relationship between sensorimotor activity and clinical improvement have remained sparse. Here we studied the somatosensory evoked magnetic fields in thirteen right-handed patients with advanced Parkinson's disease before and 7 months after stimulator implantation. Somatosensory processing was addressed with magnetoencephalography during alternated median nerve stimulation at both wrists. The strengths and the latencies of the ~60-ms responses at the contralateral primary somatosensory cortices were highly variable but detectable and reliably localized in all patients. The response strengths did not differ between preoperative and postoperative DBSON measurements. The change in the response strength between pre- and postoperative condition in the dominant left hemisphere of our right-handed patients correlated with the alleviation of their motor symptoms (p = 0.04). However, the result did not survive correction for multiple comparisons. Magnetoencephalography appears an effective tool to explore non-motor effects in patients with Parkinson's disease, and it may help in understanding the neurophysiological basis of deep brain stimulation. However, the high interindividual variability in the somatosensory responses and poor tolerability of DBSOFF condition warrants larger patient groups and measurements also in non-medicated patients.
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Affiliation(s)
- Olesia Korsun
- Biomag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University, and Aalto University School of Science, Helsinki, Finland.,Department of Neuroscience and Biomedical Engineering, Aalto University, School of Science, Espoo, Finland
| | - Hanna Renvall
- Biomag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University, and Aalto University School of Science, Helsinki, Finland.,Department of Neuroscience and Biomedical Engineering, Aalto University, School of Science, Espoo, Finland
| | - Jussi Nurminen
- Biomag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University, and Aalto University School of Science, Helsinki, Finland.,Motion Analysis Laboratory, Children's Hospital, Helsinki University Hospital and Helsinki University, Helsinki, Finland
| | - Jyrki P Mäkelä
- Biomag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University, and Aalto University School of Science, Helsinki, Finland
| | - Eero Pekkonen
- Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Helsinki, Finland
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26
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Toward therapeutic electrophysiology: beta-band suppression as a biomarker in chronic local field potential recordings. NPJ Parkinsons Dis 2022; 8:44. [PMID: 35440571 PMCID: PMC9018912 DOI: 10.1038/s41531-022-00301-2] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 03/04/2022] [Indexed: 11/08/2022] Open
Abstract
Adaptive deep brain stimulation (aDBS) is a promising concept for feedback-based neurostimulation, with the potential of clinical implementation with the sensing-enabled Percept neurostimulator. We aim to characterize chronic electrophysiological activity during stimulation and to validate beta-band activity as a biomarker for bradykinesia. Subthalamic activity was recorded during stepwise stimulation amplitude increase OFF medication in 10 Parkinson's patients during rest and finger tapping. Offline analysis of wavelet-transformed beta-band activity and assessment of inter-variable relationships in linear mixed effects models were implemented. There was a stepwise suppression of low-beta activity with increasing stimulation intensity (p = 0.002). Low-beta power was negatively correlated with movement speed and predictive for velocity improvements (p < 0.001), stimulation amplitude for beta suppression (p < 0.001). Here, we characterize beta-band modulation as a chronic biomarker for motor performance. Our investigations support the use of electrophysiology in therapy optimization, providing evidence for the use of biomarker analysis for clinical aDBS.
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27
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Sanmartino F, Cruz-Gómez ÁJ, Rashid-López R, Lozano-Soto E, López-Sosa F, Zuazo A, Riqué-Dormido J, Espinosa-Rosso R, González-Rosa JJ. Subthalamic Beta Activity in Parkinson's Disease May Be Linked to Dorsal Striatum Gray Matter Volume and Prefrontal Cortical Thickness: A Pilot Study. Front Neurol 2022; 13:799696. [PMID: 35401426 PMCID: PMC8985754 DOI: 10.3389/fneur.2022.799696] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 02/24/2022] [Indexed: 11/30/2022] Open
Abstract
Background Excessive oscillations at beta frequencies (13–35 Hz) in the subthalamic nucleus (STN) represent a pathophysiological hallmark of Parkinson's disease (PD), which correlates well with parkinsonian symptoms and is reduced in response to standard disease treatments. However, the association of disease-specific regional gray matter (GM) atrophy or cortical thickness (CT) with the presence of STN beta oscillatory activity has been poorly investigated but is of relevance given the potential of these variables for extracting information about PD pathophysiology. This exploratory study investigated the involvement of regional GM volume and CT in the basal ganglia-cortical network and its potential association with the presence of STN beta oscillatory activity in PD. Methods We acquired preoperative GM densities on T1-weighted magnetic resonance imaging scans and we carried out regional estimation of GM volume and CT. LFP activities from the STN were recorded post-operatively in 7 cognitively preserved PD patients off dopaminergic medication undergoing deep-brain stimulation surgery. Oscillatory beta power was determined by power spectral density of 4-min resting state STN LFP activity. Spearman partial correlations and regression analysis were used to screen the presence of STN beta power for their relationship with GM volume and CT measurements. Results After controlling for the effects of age, educational level, and disease duration, and after correcting for multiple testing, enhanced STN beta power showed significant and negative correlations between, first, volume of the right putamen and left caudate nucleus, and second, smaller CT in frontal regions involving the left rostral middle frontal gyrus (MFG) and left medial orbitofrontal gyrus. A lower volume in the right putamen and a lower CT in the left MFG demonstrated the strongest associations with increased STN beta power. Conclusions These tentative results seem to suggest that STN LFP beta frequencies may be mainly linked to different but ongoing parallel neurodegenerative processes, on the one hand, to GM volume reduction in dorsal striatum, and on the other hand, to CT reduction of prefrontal-“associative” regions. These findings could further delineate the brain structural interactions underpinning the exaggerated STN beta activity commonly observed in PD patients.
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Affiliation(s)
- Florencia Sanmartino
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Álvaro J Cruz-Gómez
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Raúl Rashid-López
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain.,Department of Neurology, Puerta del Mar University Hospital, Cádiz, Spain
| | - Elena Lozano-Soto
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Fernando López-Sosa
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Amaya Zuazo
- Department of Radiodiagnostic and Medical Imaging, Puerta del Mar University Hospital, Cádiz, Spain
| | - Jesús Riqué-Dormido
- Department of Neurosurgery, Puerta del Mar University Hospital, Cádiz, Spain
| | - Raúl Espinosa-Rosso
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain.,Department of Neurology, Puerta del Mar University Hospital, Cádiz, Spain.,Department of Neurology, Jerez de la Frontera University Hospital, Jerez de la Frontera, Spain
| | - Javier J González-Rosa
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
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28
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Wang MB, Boring MJ, Ward MJ, Richardson RM, Ghuman AS. Deep brain stimulation for parkinson's disease induces spontaneous cortical hypersynchrony in extended motor and cognitive networks. Cereb Cortex 2022; 32:4480-4491. [PMID: 35136991 PMCID: PMC9574237 DOI: 10.1093/cercor/bhab496] [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: 05/17/2021] [Revised: 12/04/2021] [Accepted: 12/05/2021] [Indexed: 11/14/2022] Open
Abstract
The mechanism of action of deep brain stimulation (DBS) to the basal ganglia for Parkinson's disease remains unclear. Studies have shown that DBS decreases pathological beta hypersynchrony between the basal ganglia and motor cortex. However, little is known about DBS's effects on long range corticocortical synchronization. Here, we use machine learning combined with graph theory to compare resting-state cortical connectivity between the off and on-stimulation states and to healthy controls. We found that turning DBS on increased high beta and gamma band synchrony (26 to 50 Hz) in a cortical circuit spanning the motor, occipitoparietal, middle temporal, and prefrontal cortices. The synchrony in this network was greater in DBS on relative to both DBS off and controls, with no significant difference between DBS off and controls. Turning DBS on also increased network efficiency and strength and subnetwork modularity relative to both DBS off and controls in the beta and gamma band. Thus, unlike DBS's subcortical normalization of pathological basal ganglia activity, it introduces greater synchrony relative to healthy controls in cortical circuitry that includes both motor and non-motor systems. This increased high beta/gamma synchronization may reflect compensatory mechanisms related to DBS's clinical benefits, as well as undesirable non-motor side effects.
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Affiliation(s)
- Maxwell B Wang
- Address correspondence to Maxwell B Wang, BS, Medical Scientist Training Program, University of Pittsburgh School of Medicine, Program of Neural Computation, Carnegie Mellon University, Pittsburgh, PA 15213. Tel: 815-200-9533;
| | - Matthew J Boring
- Center for Neuroscience at the University of Pittsburgh, Pittsburgh, PA 15213, USA,Center for the Neural Basis of Cognition, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, PA 15213, USA,Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Michael J Ward
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - R Mark Richardson
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA,Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA,Harvard Medical School, Boston, MA 02115, USA
| | - Avniel Singh Ghuman
- Program of Neural Computation, Carnegie Mellon University, Pittsburgh, PA 15213, USA,Center for Neuroscience at the University of Pittsburgh, Pittsburgh, PA 15213, USA,Center for the Neural Basis of Cognition, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, PA 15213, USA,Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
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29
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Neuville RS, Petrucci MN, Wilkins KB, Anderson RW, Hoffman SL, Parker JE, Velisar A, Bronte-Stewart HM. Differential Effects of Pathological Beta Burst Dynamics Between Parkinson's Disease Phenotypes Across Different Movements. Front Neurosci 2021; 15:733203. [PMID: 34858125 PMCID: PMC8631908 DOI: 10.3389/fnins.2021.733203] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/19/2021] [Indexed: 11/25/2022] Open
Abstract
Background: Resting state beta band (13-30 Hz) oscillations represent pathological neural activity in Parkinson's disease (PD). It is unknown how the peak frequency or dynamics of beta oscillations may change among fine, limb, and axial movements and different disease phenotypes. This will be critical for the development of personalized closed loop deep brain stimulation (DBS) algorithms during different activity states. Methods: Subthalamic (STN) and local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa® PC + S, Medtronic PLC.) in fourteen PD participants (six tremor-dominant and eight akinetic-rigid) off medication/off STN DBS during 30 s of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms and were compared among movement tasks and between tremor-dominant and akinetic-rigid groups. Results: Beta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during each type of movement. Burst power and duration were significantly larger in the high beta band, but not in the low beta band, in the akinetic-rigid group compared to the tremor-dominant group. Conclusion: The conservation of beta peak frequency during different activity states supports the feasibility of patient-specific closed loop DBS algorithms driven by the dynamics of the same beta band during different activities. Akinetic-rigid participants had greater power and longer burst durations in the high beta band than tremor-dominant participants during movement, which may relate to the difference in underlying pathophysiology between phenotypes.
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Affiliation(s)
- Raumin S. Neuville
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- School of Medicine, University of California, Irvine, Irvine, CA, United States
| | - Matthew N. Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Ross W. Anderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Shannon L. Hoffman
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Jordan E. Parker
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Anca Velisar
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Smith-Kettlewell Eye Research Institute, San Francisco, CA, United States
| | - Helen M. Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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30
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Sendi MSE, Inman CS, Bijanki KR, Blanpain L, Park JK, Hamann S, Gross RE, Willie JT, Mahmoudi B. Identifying the neurophysiological effects of memory-enhancing amygdala stimulation using interpretable machine learning. Brain Stimul 2021; 14:1511-1519. [PMID: 34619386 PMCID: PMC9116878 DOI: 10.1016/j.brs.2021.09.009] [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: 12/05/2020] [Revised: 09/13/2021] [Accepted: 09/17/2021] [Indexed: 10/20/2022] Open
Abstract
BACKGROUND Direct electrical stimulation of the amygdala can enhance declarative memory for specific events. An unanswered question is what underlying neurophysiological changes are induced by amygdala stimulation. OBJECTIVE To leverage interpretable machine learning to identify the neurophysiological processes underlying amygdala-mediated memory, and to develop more efficient neuromodulation technologies. METHOD Patients with treatment-resistant epilepsy and depth electrodes placed in the hippocampus and amygdala performed a recognition memory task for neutral images of objects. During the encoding phase, 160 images were shown to patients. Half of the images were followed by brief low-amplitude amygdala stimulation. For local field potentials (LFPs) recorded from key medial temporal lobe structures, feature vectors were calculated by taking the average spectral power in canonical frequency bands, before and after stimulation, to train a logistic regression classification model with elastic net regularization to differentiate brain states. RESULTS Classifying the neural states at the time of encoding based on images subsequently remembered versus not-remembered showed that theta and slow-gamma power in the hippocampus were the most important features predicting subsequent memory performance. Classifying the post-image neural states at the time of encoding based on stimulated versus unstimulated trials showed that amygdala stimulation led to increased gamma power in the hippocampus. CONCLUSION Amygdala stimulation induced pro-memory states in the hippocampus to enhance subsequent memory performance. Interpretable machine learning provides an effective tool for investigating the neurophysiological effects of brain stimulation.
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Affiliation(s)
- Mohammad S E Sendi
- Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, 313 Ferst Dr NW, Atlanta, 30332, GA, USA; Department of Electrical and Computer Engineering at Georgia Institute of Technology, 777 Atlantic Dr, Atlanta, GA, 30313, USA
| | - Cory S Inman
- Department of Psychology at University of Utah, 380 1530 E, Salt Lake City, UT, 84112, United States
| | - Kelly R Bijanki
- Department of Neurosurgery at Baylor College of Medicine, 7200 Cambridge St 9th Floor, Houston, TX, 77030, USA
| | - Lou Blanpain
- Neuroscience Graduate Program at Emory University, 1462 Clifton Rd. Suite 314, Atlanta, GA, 30322, USA
| | - James K Park
- Department of Neurosurgery at Emory University, 100 Woodruff Circle, Atlanta, GA, 30322, USA
| | - Stephan Hamann
- Department of Psychology at Emory University, 36 Eagle Row, Atlanta, GA, 3032, USA
| | - Robert E Gross
- Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, 313 Ferst Dr NW, Atlanta, 30332, GA, USA; Department of Neurosurgery at Emory University, 100 Woodruff Circle, Atlanta, GA, 30322, USA; Department of Neurology at Emory University, 12 Executive Park Dr NE, Atlanta, GA, 30322, USA
| | - Jon T Willie
- Department of Neurology at Washington University School of Medicine in Saint Louis, 660 S. Euclid Avenue Campus Box 8057 St, Louis, MO, 63110, USA
| | - Babak Mahmoudi
- Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, 313 Ferst Dr NW, Atlanta, 30332, GA, USA; Department of Biomedical Informatics at Emory University, 100 Woodruff Circle, Atlanta, GA, 30322, USA.
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Anderson RW, Wilkins KB, Parker JE, Petrucci MN, Kehnemouyi Y, Neuville RS, Cassini D, Trager MH, Koop MM, Velisar A, Blumenfeld Z, Quinn EJ, Henderson J, Bronte-Stewart HM. Lack of progression of beta dynamics after long-term subthalamic neurostimulation. Ann Clin Transl Neurol 2021; 8:2110-2120. [PMID: 34636182 PMCID: PMC8607445 DOI: 10.1002/acn3.51463] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 09/15/2021] [Indexed: 11/07/2022] Open
Abstract
OBJECTIVE To investigate the progression of neural and motor features of Parkinson's disease in a longitudinal study, after washout of medication and bilateral subthalamic nucleus deep brain stimulation (STN DBS). METHODS Participants with clinically established Parkinson's disease underwent bilateral implantation of DBS leads (18 participants, 13 male) within the STN using standard functional frameless stereotactic technique and multi-pass microelectrode recording. Both DBS leads were connected to an implanted investigative sensing neurostimulator (Activa™ PC + S, Medtronic, PLC). Resting state STN local field potentials (LFPs) were recorded and motor disability, (the Movement Disorder Society-Unified Parkinson's Disease Rating Scale - motor subscale, MDS-UPDRS III) was assessed off therapy at initial programming, and after 6 months, 1 year, and yearly out to 5 years of treatment. The primary endpoint was measured at 3 years. At each visit, medication had been held for over 12/24 h and DBS was turned off for at least 60 min, by which time LFP spectra reached a steady state. RESULTS After 3 years of chronic DBS, there were no increases in STN beta band dynamics (p = 0.98) but there were increases in alpha band dynamics (p = 0.0027, 25 STNs). Similar results were observed in a smaller cohort out to 5 years. There was no increase in the MDS-UPDRS III score. INTERPRETATION These findings provide evidence that the beta oscillopathy does not substantially progress following combined STN DBS plus medication in moderate to advanced Parkinson's disease.
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Affiliation(s)
- Ross W Anderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Neurosurgery, Kaiser Permanente, Redwood City, California, USA
| | - Kevin B Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Jordan E Parker
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Psychology, The University of California, Los Angeles, California, USA
| | - Matthew N Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Yasmine Kehnemouyi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Bioengineering, Stanford Schools of Engineering & Medicine, Stanford, California, USA
| | - Raumin S Neuville
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,The University of California School of Medicine, Irvine, California, USA
| | - Declan Cassini
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Megan H Trager
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Columbia University College of Physicians and Surgeons, New York City, New York, USA
| | - Mandy M Koop
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Cleveland Clinic, Cleveland, Ohio, USA
| | - Anca Velisar
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,The Smith-Kettlewell Eye Research Institute, San Francisco, California, USA
| | - Zack Blumenfeld
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,California Institute of Technology, Pasadena, California, USA
| | - Emma J Quinn
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Credit Karma, San Francisco, California, USA
| | - Jaimie Henderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA
| | - Helen M Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA
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Cagle JN, Wong JK, Johnson KA, Foote KD, Okun MS, de Hemptinne C. Suppression and Rebound of Pallidal Beta Power: Observation Using a Chronic Sensing DBS Device. Front Hum Neurosci 2021; 15:749567. [PMID: 34566612 PMCID: PMC8458625 DOI: 10.3389/fnhum.2021.749567] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 08/23/2021] [Indexed: 11/14/2022] Open
Abstract
Pallidal deep brain stimulation (DBS) is an increasingly used therapy for Parkinson’s disease (PD). Here, we study the effect of DBS on pallidal oscillatory activity as well as on symptom severity in an individual with PD implanted with a new pulse generator (Medtronic Percept system) which facilitates chronic recording of local field potentials (LFP) through implanted DBS lead. Pallidal LFPs were recorded while delivering stimulation in a monopolar configuration using stepwise increments (0.5 mA, every 20 s). At each stimulation amplitude, the power spectral density (PSD) was computed, and beta power (13–30 Hz) was calculated and correlated with the degree of bradykinesia. Pallidal beta power was reduced when therapeutic stimulation was delivered. Beta power correlated to the severity of bradykinesia. Worsening of parkinsonism when excessive stimulation was applied was associated with a rebound in the beta band power. These preliminary results suggest that pallidal beta power might be used as an objective marker of the disease state in PD. The use of brain sensing from implanted neural interfaces may in the future facilitate clinical programming. Detection of rebound could help to optimize benefits and minimize worsening from overstimulation.
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Affiliation(s)
- Jackson N Cagle
- Department of Neurology, University of Florida, Gainesville, FL, United States.,Norman Fixel Institute for Neurological Diseases, Gainesville, FL, United States
| | - Joshua K Wong
- Department of Neurology, University of Florida, Gainesville, FL, United States.,Norman Fixel Institute for Neurological Diseases, Gainesville, FL, United States
| | - Kara A Johnson
- Department of Neurology, University of Florida, Gainesville, FL, United States.,Norman Fixel Institute for Neurological Diseases, Gainesville, FL, United States
| | - Kelly D Foote
- Norman Fixel Institute for Neurological Diseases, Gainesville, FL, United States.,Department of Neurosurgery, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Michael S Okun
- Department of Neurology, University of Florida, Gainesville, FL, United States.,Norman Fixel Institute for Neurological Diseases, Gainesville, FL, United States
| | - Coralie de Hemptinne
- Department of Neurology, University of Florida, Gainesville, FL, United States.,Norman Fixel Institute for Neurological Diseases, Gainesville, FL, United States
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33
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Plate A, Hell F, Mehrkens JH, Koeglsperger T, Bovet A, Stanslaski S, Bötzel K. Peaks in the beta band of the human subthalamic nucleus: a case for low beta and high beta activity. J Neurosurg 2021; 136:672-680. [PMID: 34560646 DOI: 10.3171/2021.3.jns204113] [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: 11/22/2020] [Accepted: 03/03/2021] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Peaks in the beta band of local field potentials (LFPs) may serve as a biological feedback signal for closed-loop deep brain stimulation (DBS) in Parkinson's disease (PD). However, the specific frequency of such peaks and their response to DBS and to different types of movement remains uncertain. In the present study, the authors examined the abundance of discernible peaks in the beta band and the effect of different types of movement and DBS on these peaks. METHODS Subthalamic nucleus LFPs were analyzed from 38 patients with PD in a frequency range between 10 and 35 Hz, as well as the impact of movement (gait, hand movements) and electrical stimulation on these peaks. The position of the electrode segments from which LFPs were recorded was computed. RESULTS The authors found a bimodal distribution of peaks in the beta band with discernible high- (27 Hz) and low-frequency (15 Hz) peaks. Movement of either hand had no significant effect on these peaks, whereas walking significantly reduced high-frequency beta peaks but not the peaks in the low beta band. Stimulation caused an amplitude-dependent suppression of both peaks. CONCLUSIONS DBS suppresses LFP beta peaks of different frequencies, whereas beta suppression caused by movement is dependent on the type of movement and frequency of the peak. These results will support the investigation of distinct LFP spectra for the application of closed-loop DBS.
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Affiliation(s)
| | | | - Jan H Mehrkens
- 2Neurosurgery, Ludwig-Maximilians-Universität, Munich, Germany
| | - Thomas Koeglsperger
- Departments of1Neurology and.,4Department of Translational Brain Research, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Ayse Bovet
- 3Medtronic plc, Minneapolis, Minnesota; and
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34
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Sirica D, Hewitt AL, Tarolli CG, Weber MT, Zimmerman C, Santiago A, Wensel A, Mink JW, Lizárraga KJ. Neurophysiological biomarkers to optimize deep brain stimulation in movement disorders. Neurodegener Dis Manag 2021; 11:315-328. [PMID: 34261338 PMCID: PMC8977945 DOI: 10.2217/nmt-2021-0002] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Intraoperative neurophysiological information could increase accuracy of surgical deep brain stimulation (DBS) lead placement. Subsequently, DBS therapy could be optimized by specifically targeting pathological activity. In Parkinson’s disease, local field potentials (LFPs) excessively synchronized in the beta band (13–35 Hz) correlate with akinetic-rigid symptoms and their response to DBS therapy, particularly low beta band suppression (13–20 Hz) and high frequency gamma facilitation (35–250 Hz). In dystonia, LFPs abnormally synchronize in the theta/alpha (4–13 Hz), beta and gamma (60–90 Hz) bands. Phasic dystonic symptoms and their response to DBS correlate with changes in theta/alpha synchronization. In essential tremor, LFPs excessively synchronize in the theta/alpha and beta bands. Adaptive DBS systems will individualize pathological characteristics of neurophysiological signals to automatically deliver therapeutic DBS pulses of specific spatial and temporal parameters.
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Affiliation(s)
- Daniel Sirica
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA
| | - Angela L Hewitt
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Division of Child Neurology, Department of Neurology, University of Rochester, Rochester, NY 14623, USA
| | - Christopher G Tarolli
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Center for Health & Technology (CHeT), University of Rochester, Rochester, NY 14642, USA
| | - Miriam T Weber
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA
| | - Carol Zimmerman
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA
| | - Aida Santiago
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA
| | - Andrew Wensel
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Department of Neurosurgery, University of Rochester, Rochester, NY 14618, USA
| | - Jonathan W Mink
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Division of Child Neurology, Department of Neurology, University of Rochester, Rochester, NY 14623, USA
| | - Karlo J Lizárraga
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Center for Health & Technology (CHeT), University of Rochester, Rochester, NY 14642, USA
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35
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Impaired reach-to-grasp kinematics in parkinsonian patients relates to dopamine-dependent, subthalamic beta bursts. NPJ Parkinsons Dis 2021; 7:53. [PMID: 34188058 PMCID: PMC8242004 DOI: 10.1038/s41531-021-00187-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 03/17/2021] [Indexed: 11/17/2022] Open
Abstract
Excessive beta-band oscillations in the subthalamic nucleus are key neural features of Parkinson’s disease. Yet the distinctive contributions of beta low and high bands, their dependency on striatal dopamine, and their correlates with movement kinematics are unclear. Here, we show that the movement phases of the reach-to-grasp motor task are coded by the subthalamic bursting activity in a maximally-informative beta high range. A strong, three-fold correlation linked beta high range bursts, imbalanced inter-hemispheric striatal dopaminergic tone, and impaired inter-joint movement coordination. These results provide new insight into the neural correlates of motor control in parkinsonian patients, paving the way for more informative use of beta-band features for adaptive deep brain stimulation devices.
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36
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Dastin-van Rijn EM, Provenza NR, Calvert JS, Gilron R, Allawala AB, Darie R, Syed S, Matteson E, Vogt GS, Avendano-Ortega M, Vasquez AC, Ramakrishnan N, Oswalt DN, Bijanki KR, Wilt R, Starr PA, Sheth SA, Goodman WK, Harrison MT, Borton DA. Uncovering biomarkers during therapeutic neuromodulation with PARRM: Period-based Artifact Reconstruction and Removal Method. CELL REPORTS METHODS 2021; 1:100010. [PMID: 34532716 PMCID: PMC8443190 DOI: 10.1016/j.crmeth.2021.100010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 03/08/2021] [Accepted: 04/21/2021] [Indexed: 10/26/2022]
Abstract
Advances in therapeutic neuromodulation devices have enabled concurrent stimulation and electrophysiology in the central nervous system. However, stimulation artifacts often obscure the sensed underlying neural activity. Here, we develop a method, termed Period-based Artifact Reconstruction and Removal Method (PARRM), to remove stimulation artifacts from neural recordings by leveraging the exact period of stimulation to construct and subtract a high-fidelity template of the artifact. Benchtop saline experiments, computational simulations, five unique in vivo paradigms across animal and human studies, and an obscured movement biomarker are used for validation. Performance is found to exceed that of state-of-the-art filters in recovering complex signals without introducing contamination. PARRM has several advantages: (1) it is superior in signal recovery; (2) it is easily adaptable to several neurostimulation paradigms; and (3) it has low complexity for future on-device implementation. Real-time artifact removal via PARRM will enable unbiased exploration and detection of neural biomarkers to enhance efficacy of closed-loop therapies.
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Affiliation(s)
| | - Nicole R. Provenza
- Brown University School of Engineering, Providence, RI, USA
- Charles Stark Draper Laboratory, Cambridge, MA, USA
| | | | - Ro'ee Gilron
- Deparment of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | | | - Radu Darie
- Brown University School of Engineering, Providence, RI, USA
| | - Sohail Syed
- Department of Neurosurgery, Warren Alpert School of Medicine of Brown University, Providence, RI, USA
| | - Evan Matteson
- Brown University School of Engineering, Providence, RI, USA
| | - Gregory S. Vogt
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - Michelle Avendano-Ortega
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - Ana C. Vasquez
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - Nithya Ramakrishnan
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | - Denise N. Oswalt
- Department of Neurosurgery, Perelman School of Medicine, Philadelphia, PA, USA
| | - Kelly R. Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Robert Wilt
- Deparment of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Philip A. Starr
- Deparment of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Wayne K. Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - David A. Borton
- Brown University School of Engineering, Providence, RI, USA
- Carney Institute for Brain Science, Brown University, Providence, RI, USA
- Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of Veterans Affairs, Providence, RI, USA
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Matchen TD, Moehlis J. Leveraging deep learning to control neural oscillators. BIOLOGICAL CYBERNETICS 2021; 115:219-235. [PMID: 33909165 DOI: 10.1007/s00422-021-00874-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 04/10/2021] [Indexed: 06/12/2023]
Abstract
Modulation of the firing times of neural oscillators has long been an important control objective, with applications including Parkinson's disease, Tourette's syndrome, epilepsy, and learning. One common goal for such modulation is desynchronization, wherein two or more oscillators are stimulated to transition from firing in phase with each other to firing out of phase. The optimization of such stimuli has been well studied, but this typically relies on either a reduction of the dimensionality of the system or complete knowledge of the parameters and state of the system. This limits the applicability of results to real problems in neural control. Here, we present a trained artificial neural network capable of accurately estimating the effects of square-wave stimuli on neurons using minimal output information from the neuron. We then apply the results of this network to solve several related control problems in desynchronization, including desynchronizing pairs of neurons and achieving clustered subpopulations of neurons in the presence of coupling and noise.
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Affiliation(s)
- Timothy D Matchen
- Department of Mechanical Engineering, University of California, Santa Barbara, CA, 93106, USA.
| | - Jeff Moehlis
- Department of Mechanical Engineering, Program in Dynamical Neuroscience, University of California, Santa Barbara, CA, 93106, USA
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38
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Brinda AK, Doyle AM, Blumenfeld M, Krieg J, Alisch JSR, Spencer C, Lecy E, Wilmerding LK, DeNicola A, Johnson LA, Vitek JL, Johnson MD. Longitudinal analysis of local field potentials recorded from directional deep brain stimulation lead implants in the subthalamic nucleus. J Neural Eng 2021; 18:10.1088/1741-2552/abfc1c. [PMID: 33906174 PMCID: PMC8504120 DOI: 10.1088/1741-2552/abfc1c] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 04/27/2021] [Indexed: 11/12/2022]
Abstract
Objective.The electrode-tissue interface surrounding a deep brain stimulation (DBS) lead is known to be highly dynamic following implantation, which may have implications on the interpretation of intraoperatively recorded local field potentials (LFPs). We characterized beta-band LFP dynamics following implantation of a directional DBS lead in the sensorimotor subthalamic nucleus (STN), which is a primary target for treating Parkinson's disease.Approach.Directional STN-DBS leads were implanted in four healthy, non-human primates. LFPs were recorded over two weeks and again 1-4 months after implantation. Impedance was measured for two weeks post-implant without stimulation to compare the reactive tissue response to changes in LFP oscillations. Beta-band (12-30 Hz) peak power was calculated from the LFP power spectra using both common average referencing (CAR) and intra-row bipolar referencing (IRBR).Results.Resting-state LFPs in two of four subjects revealed a steady increase of beta power over the initial two weeks post-implant whereas the other two subjects showed variable changes over time. Beta power variance across days was significantly larger in the first two weeks compared to 1-4 months post-implant in all three long-term subjects. Further, spatial maps of beta power several hours after implantation did not correlate with those measured two weeks or 1-4 months post-implant. CAR and IRBR beta power correlated across short- and long-term time points. However, depending on the time period, subjects showed a significant bias towards larger beta power using one referencing scheme over the other. Lastly, electrode-tissue impedance increased over the two weeks post-implant but showed no significant correlation to beta power.Significance.These results suggest that beta power in the STN may undergo significant changes following DBS lead implantation. DBS lead diameter and electrode recording configurations can affect the post-implant interpretation of oscillatory features. Such insights will be important for extrapolating results from intraoperative and externalized LFP recordings.
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Affiliation(s)
- AnneMarie K Brinda
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church Street SE, Minneapolis, MN 55455, United States of America
| | - Alex M Doyle
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States of America
| | - Madeline Blumenfeld
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church Street SE, Minneapolis, MN 55455, United States of America
| | - Jordan Krieg
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church Street SE, Minneapolis, MN 55455, United States of America
| | - Joseph S R Alisch
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church Street SE, Minneapolis, MN 55455, United States of America
| | - Chelsea Spencer
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church Street SE, Minneapolis, MN 55455, United States of America
| | - Emily Lecy
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church Street SE, Minneapolis, MN 55455, United States of America
| | - Lucius K Wilmerding
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church Street SE, Minneapolis, MN 55455, United States of America
| | - Adele DeNicola
- Department of Neurology, University of Minnesota, Minneapolis, MN 55455, United States of America
| | - Luke A Johnson
- Department of Neurology, University of Minnesota, Minneapolis, MN 55455, United States of America
| | - Jerrold L Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN 55455, United States of America
| | - Matthew D Johnson
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church Street SE, Minneapolis, MN 55455, United States of America
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39
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Awad MZ, Vaden RJ, Irwin ZT, Gonzalez CL, Black S, Nakhmani A, Jaeger BC, Bentley JN, Guthrie BL, Walker HC. Subcortical short-term plasticity elicited by deep brain stimulation. Ann Clin Transl Neurol 2021; 8:1010-1023. [PMID: 33826240 PMCID: PMC8108424 DOI: 10.1002/acn3.51275] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 11/12/2020] [Accepted: 11/16/2020] [Indexed: 01/23/2023] Open
Abstract
Objective To investigate local short‐term neuroplasticity elicited by subthalamic, thalamic, and pallidal deep brain stimulation (DBS) for movement disorders. Methods During DBS surgery, we delivered pairs of stimulus pulses with both circular and directional leads across 90 interstimulus intervals in 17 participants and recorded local field potentials from unused contacts on the implanted electrode array. We removed the stimulus artifact, validated the neural origin of the underlying signals, and examined short‐term plasticity as a function of interstimulus interval and DBS target, using linear mixed effects models. Results DBS evokes short latency local field potentials that are readily detected with both circular and directional leads at all stimulation targets (0.31 ± 0.10 msec peak latency, mean ± SD). Peak amplitude, area, and latency are modified strongly by interstimulus interval (P < 0.001) and display absolute and relative refractory periods (0.56 ± 0.08 and 2.94 ± 1.05 msec, respectively). We also identified later oscillatory activity in the subthalamic‐pallidal circuit (4.50 ± 1.11 msec peak latency) that displays paired pulse facilitation (present in 5/8 subthalamic, 4/5 pallidal, and 0/6 thalamic trajectories, P = 0.018, Fisher’s exact test), and correlates with resting beta frequency power (P < 0.001), therapeutic DBS frequencies, and stimulation sites chosen later for therapy in the ambulatory setting (P = 0.031). Interpretation Paired DBS pulses synchronize local circuit electrophysiology and elicit short‐term neuroplasticity in the subthalamic‐pallidal circuit. Collectively, these responses likely represent the earliest detectable interaction between the DBS pulse and local neuronal tissue in humans. Evoked subcortical field potentials could serve as a predictive biomarker to guide the implementation of next‐generation directional and adaptive stimulation devices.
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Affiliation(s)
- Mohammad Z Awad
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Ryan J Vaden
- Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Zachary T Irwin
- Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Christopher L Gonzalez
- Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Sarah Black
- Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Arie Nakhmani
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Byron C Jaeger
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - J Nicole Bentley
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Barton L Guthrie
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Harrison C Walker
- Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, Alabama, USA
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40
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Pfeifer KJ, Kromer JA, Cook AJ, Hornbeck T, Lim EA, Mortimer BJP, Fogarty AS, Han SS, Dhall R, Halpern CH, Tass PA. Coordinated Reset Vibrotactile Stimulation Induces Sustained Cumulative Benefits in Parkinson's Disease. Front Physiol 2021; 12:624317. [PMID: 33889086 PMCID: PMC8055937 DOI: 10.3389/fphys.2021.624317] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/05/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Abnormal synchronization of neuronal activity in dopaminergic circuits is related to motor impairment in Parkinson's disease (PD). Vibrotactile coordinated reset (vCR) fingertip stimulation aims to counteract excessive synchronization and induce sustained unlearning of pathologic synaptic connectivity and neuronal synchrony. Here, we report two clinical feasibility studies that examine the effect of regular and noisy vCR stimulation on PD motor symptoms. Additionally, in one clinical study (study 1), we examine cortical beta band power changes in the sensorimotor cortex. Lastly, we compare these clinical results in relation to our computational findings. METHODS Study 1 examines six PD patients receiving noisy vCR stimulation and their cortical beta power changes after 3 months of daily therapy. Motor evaluations and at-rest electroencephalographic (EEG) recordings were assessed off medication pre- and post-noisy vCR. Study 2 follows three patients for 6+ months, two of whom received daily regular vCR and one patient from study 1 who received daily noisy vCR. Motor evaluations were taken at baseline, and follow-up visits were done approximately every 3 months. Computationally, in a network of leaky integrate-and-fire (LIF) neurons with spike timing-dependent plasticity, we study the differences between regular and noisy vCR by using a stimulus model that reproduces experimentally observed central neuronal phase locking. RESULTS Clinically, in both studies, we observed significantly improved motor ability. EEG recordings observed from study 1 indicated a significant decrease in off-medication cortical sensorimotor high beta power (21-30 Hz) at rest after 3 months of daily noisy vCR therapy. Computationally, vCR and noisy vCR cause comparable parameter-robust long-lasting synaptic decoupling and neuronal desynchronization. CONCLUSION In these feasibility studies of eight PD patients, regular vCR and noisy vCR were well tolerated, produced no side effects, and delivered sustained cumulative improvement of motor performance, which is congruent with our computational findings. In study 1, reduction of high beta band power over the sensorimotor cortex may suggest noisy vCR is effectively modulating the beta band at the cortical level, which may play a role in improved motor ability. These encouraging therapeutic results enable us to properly plan a proof-of-concept study.
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Affiliation(s)
- Kristina J. Pfeifer
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Justus A. Kromer
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Alexander J. Cook
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Traci Hornbeck
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Erika A. Lim
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | | | - Adam S. Fogarty
- Department of Neurology, Stanford University School of Medicine, Stanford, CA, United States
| | - Summer S. Han
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
- Quantitative Sciences Unit, Stanford University School of Medicine, Stanford, CA, United States
| | - Rohit Dhall
- Center for Neurodegenerative Disorders, Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Casey H. Halpern
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Peter A. Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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41
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Kehnemouyi YM, Wilkins KB, Anidi CM, Anderson RW, Afzal MF, Bronte-Stewart HM. Modulation of beta bursts in subthalamic sensorimotor circuits predicts improvement in bradykinesia. Brain 2021; 144:473-486. [PMID: 33301569 PMCID: PMC8240742 DOI: 10.1093/brain/awaa394] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 09/09/2020] [Indexed: 01/25/2023] Open
Abstract
No biomarker of Parkinson's disease exists that allows clinicians to adjust chronic therapy, either medication or deep brain stimulation, with real-time feedback. Consequently, clinicians rely on time-intensive, empirical, and subjective clinical assessments of motor behaviour and adverse events to adjust therapies. Accumulating evidence suggests that hypokinetic aspects of Parkinson's disease and their improvement with therapy are related to pathological neural activity in the beta band (beta oscillopathy) in the subthalamic nucleus. Additionally, effectiveness of deep brain stimulation may depend on modulation of the dorsolateral sensorimotor region of the subthalamic nucleus, which is the primary site of this beta oscillopathy. Despite the feasibility of utilizing this information to provide integrated, biomarker-driven precise deep brain stimulation, these measures have not been brought together in awake freely moving individuals. We sought to directly test whether stimulation-related improvements in bradykinesia were contingent on reduction of beta power and burst durations, and/or the volume of the sensorimotor subthalamic nucleus that was modulated. We recorded synchronized local field potentials and kinematic data in 16 subthalamic nuclei of individuals with Parkinson's disease chronically implanted with neurostimulators during a repetitive wrist-flexion extension task, while administering randomized different intensities of high frequency stimulation. Increased intensities of deep brain stimulation improved movement velocity and were associated with an intensity-dependent reduction in beta power and mean burst duration, measured during movement. The degree of reduction in this beta oscillopathy was associated with the improvement in movement velocity. Moreover, the reduction in beta power and beta burst durations was dependent on the theoretical degree of tissue modulated in the sensorimotor region of the subthalamic nucleus. Finally, the degree of attenuation of both beta power and beta burst durations, together with the degree of overlap of stimulation with the sensorimotor subthalamic nucleus significantly explained the stimulation-related improvement in movement velocity. The above results provide direct evidence that subthalamic nucleus deep brain stimulation-related improvements in bradykinesia are related to the reduction in beta oscillopathy within the sensorimotor region. With the advent of sensing neurostimulators, this beta oscillopathy combined with lead location could be used as a marker for real-time feedback to adjust clinical settings or to drive closed-loop deep brain stimulation in freely moving individuals with Parkinson's disease.
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Affiliation(s)
- Yasmine M Kehnemouyi
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Kevin B Wilkins
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Chioma M Anidi
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
- The University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Ross W Anderson
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Muhammad Furqan Afzal
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Helen M Bronte-Stewart
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
- Stanford University School of Medicine, Department of Neurosurgery, Stanford, CA, USA
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42
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Godinho F, Fim Neto A, Bianqueti BL, de Luccas JB, Varjão E, Terzian Filho PR, Figueiredo EG, Almeida TP, Yoneyama T, Takahata AK, Rocha MS, Soriano DC. Spectral characteristics of subthalamic nucleus local field potentials in Parkinson's disease: Phenotype and movement matter. Eur J Neurosci 2021; 53:2804-2818. [PMID: 33393163 DOI: 10.1111/ejn.15103] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 12/23/2020] [Accepted: 12/24/2020] [Indexed: 02/07/2023]
Abstract
Parkinson's disease (PD) is clinically heterogeneous across patients and may be classified in three motor phenotypes: tremor dominant (TD), postural instability and gait disorder (PIGD), and undetermined. Despite the significant clinical characterization of motor phenotypes, little is known about how electrophysiological data, particularly subthalamic nucleus local field potentials (STN-LFP), differ between TD and PIGD patients. This is relevant since increased STN-LFP bandpower at α-β range (8-35 Hz) is considered a potential PD biomarker and, therefore, a critical setpoint to drive adaptive deep brain stimulation. Acknowledging STN-LFP differences between phenotypes, mainly in rest and movement states, would better fit DBS to clinical and motor demands. We studied this issue through spectral analyses on 35 STN-LFP in TD and PIGD patients during rest and movement. We demonstrated that higher β2 activity (22-35 Hz) was observed in PIGD only during rest. Additionally, bandpower differences between rest and movement occurred at the α-β range, but with different patterns as per phenotypes: movement-induced desynchronization concerned lower frequencies in TD (10-20 Hz) and higher frequencies in PIGD patients (21-28 Hz). Finally, when supervised learning algorithms were employed aiming to discriminate PD phenotypes based on STN-LFP bandpower features, movement information had improved the classification accuracy, achieving peak performances when TD and PIGD movement-induced desynchronization ranges were considered. These results suggest that STN-LFP β-band encodes phenotype-movement dependent information in PD patients.
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Affiliation(s)
- Fabio Godinho
- Center of Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil.,Department of Functional Neurosurgery, Santa Marcelina Hospital, São Paulo, Brazil.,Division of Functional Neurosurgery of Institute of Psychiatry, Department of Neurology, University of São Paulo Medical School, São Paulo, Brazil
| | - Arnaldo Fim Neto
- Center of Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil.,Department of Cosmic Rays and Chronology, Institute of Physics, University of Campinas, Campinas, Brazil
| | - Bruno Leonardo Bianqueti
- Center of Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Julia Baldi de Luccas
- Center of Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Eduardo Varjão
- Department of Functional Neurosurgery, Santa Marcelina Hospital, São Paulo, Brazil
| | | | | | - Tiago Paggi Almeida
- Center of Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil.,Division of Electronic Engineering, Technological Institute of Aeronautics, São José dos Campos, Brazil.,Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Takashi Yoneyama
- Division of Electronic Engineering, Technological Institute of Aeronautics, São José dos Campos, Brazil
| | - André Kazuo Takahata
- Center of Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | | | - Diogo Coutinho Soriano
- Center of Engineering, Modeling and Applied Social Sciences, Federal University of ABC, São Bernardo do Campo, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
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43
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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.
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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
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44
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Bore JC, Campbell BA, Cho H, Gopalakrishnan R, Machado AG, Baker KB. Prediction of mild parkinsonism revealed by neural oscillatory changes and machine learning. J Neurophysiol 2020; 124:1698-1705. [PMID: 33052766 DOI: 10.1152/jn.00534.2020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Neural oscillatory changes within and across different frequency bands are thought to underlie motor dysfunction in Parkinson's disease (PD) and may serve as biomarkers for closed-loop deep brain stimulation (DBS) approaches. Here, we used neural oscillatory signals derived from chronically implanted cortical and subcortical electrode arrays as features to train machine learning algorithms to discriminate between naive and mild PD states in a nonhuman primate model. Local field potential (LFP) data were collected over several months from a 12-channel subdural electrocorticography (ECoG) grid and a 6-channel custom array implanted in the subthalamic nucleus (STN). Relative to the naive state, the PD state showed elevated primary motor cortex (M1) and STN power in the beta, high gamma, and high-frequency oscillation (HFO) bands and decreased power in the delta band. Theta power was found to be decreased in STN but not M1. In the PD state there was elevated beta-HFO phase-amplitude coupling (PAC) in the STN. We applied machine learning with support vector machines with radial basis function (SVM-RBF) kernel and k-nearest neighbors (KNN) classifiers trained by features related to power and PAC changes to discriminate between the naive and mild states. Our results show that the most predictive feature of parkinsonism in the STN was high beta (∼86% accuracy), whereas it was HFO in M1 (∼98% accuracy). A feature fusion approach outperformed every individual feature, particularly in the M1, where ∼98% accuracy was achieved with both classifiers. Overall, our data demonstrate the ability to use various frequency band power to classify the clinical state and are also beneficial in developing closed-loop DBS therapeutic approaches.NEW & NOTEWORTHY Neurophysiological biomarkers that correlate with motor symptoms or disease severity are vital to improve our understanding of the pathophysiology in Parkinson's disease (PD) and for the development of more effective treatments, including deep brain stimulation (DBS). This work provides direct insight into the application of these biomarkers in training classifiers to discriminate between brain states, which is a first step toward developing closed-loop DBS systems.
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Affiliation(s)
- Joyce Chelangat Bore
- Department of Neuroscience, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio
| | - Brett A Campbell
- Department of Neuroscience, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Hanbin Cho
- Department of Neuroscience, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio
| | - Raghavan Gopalakrishnan
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio
| | - Andre G Machado
- Department of Neuroscience, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio.,Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio.,Department of Neurosurgery, Neurological Institute, Cleveland Clinic, Cleveland, Ohio
| | - Kenneth B Baker
- Department of Neuroscience, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, Ohio
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45
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Shen L, Jiang C, Hubbard CS, Ren J, He C, Wang D, Dahmani L, Guo Y, Liu Y, Xu S, Meng F, Zhang J, Liu H, Li L. Subthalamic Nucleus Deep Brain Stimulation Modulates 2 Distinct Neurocircuits. Ann Neurol 2020; 88:1178-1193. [PMID: 32951262 DOI: 10.1002/ana.25906] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 09/15/2020] [Accepted: 09/16/2020] [Indexed: 12/31/2022]
Abstract
OBJECTIVE Current understanding of the neuromodulatory effects of deep brain stimulation (DBS) on large-scale brain networks remains elusive, largely due to the lack of techniques that can reveal DBS-induced activity at the whole-brain level. Using a novel 3T magnetic resonance imaging (MRI)-compatible stimulator, we investigated whole-brain effects of subthalamic nucleus (STN) stimulation in patients with Parkinson disease. METHODS Fourteen patients received STN-DBS treatment and participated in a block-design functional MRI (fMRI) experiment, wherein stimulations were delivered during "ON" blocks interleaved with "OFF" blocks. fMRI responses to low-frequency (60Hz) and high-frequency(130Hz) STN-DBS were measured 1, 3, 6, and 12 months postsurgery. To ensure reliability, multiple runs (48 minutes) of fMRI data were acquired at each postsurgical visit. Presurgical resting-state fMRI (30 minutes) data were also acquired. RESULTS Two neurocircuits showed highly replicable, but distinct responses to STN-DBS. A circuit involving the globus pallidus internus (GPi), thalamus, and deep cerebellar nuclei was significantly activated, whereas another circuit involving the primary motor cortex (M1), putamen, and cerebellum showed DBS-induced deactivation. These 2 circuits were dissociable in terms of their DBS-induced responses and resting-state functional connectivity. The GPi circuit was frequency-dependent, selectively responding to high-frequency stimulation, whereas the M1 circuit was responsive in a time-dependent manner, showing enhanced deactivation over time. Finally, activation of the GPi circuit was associated with overall motor improvement, whereas M1 circuit deactivation was related to reduced bradykinesia. INTERPRETATION Concurrent DBS-fMRI using 3T revealed 2 distinct circuits that responded differentially to STN-DBS and were related to divergent symptoms, a finding that may provide novel insights into the neural mechanisms underlying DBS. ANN NEUROL 2020;88:1178-1193.
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Affiliation(s)
- Lunhao Shen
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Changqing Jiang
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Catherine S Hubbard
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Jianxun Ren
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Changgeng He
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Danhong Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Louisa Dahmani
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Yi Guo
- Peking Union Medical College Hospital, Beijing, China
| | - Yiming Liu
- Qilu Hospital of Shandong University, Jinan, China
| | - Shujun Xu
- Qilu Hospital of Shandong University, Jinan, China
| | - Fangang Meng
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China.,Precision Medicine & Healthcare Research Center, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, China.,IDG(International Data Group)/McGovern Institute for Brain Research at Tsinghua University, Beijing, China.,Institute of Epilepsy, Beijing Institute for Brain Disorders, Beijing, China
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46
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Chen Y, Gong C, Tian Y, Orlov N, Zhang J, Guo Y, Xu S, Jiang C, Hao H, Neumann WJ, Kühn AA, Liu H, Li L. Neuromodulation effects of deep brain stimulation on beta rhythm: A longitudinal local field potential study. Brain Stimul 2020; 13:1784-1792. [PMID: 33038597 DOI: 10.1016/j.brs.2020.09.027] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 08/15/2020] [Accepted: 09/29/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) holds great promise in treating various brain diseases but its chronic therapeutic mechanisms are unclear. OBJECTIVE To explore the immediate and chronic effects of DBS on brain oscillations, and understand how different sub-bands of oscillations may be related to symptom improvement in Parkinson's patients. METHODS We carried out a longitudinal study to examine the effects of DBS on local field potentials recorded by sensing-enabled neurostimulators in the subthalamic nuclei of Parkinson's patients, using a novel block-design stimulation paradigm. RESULTS DBS significantly suppressed beta activity (13-35Hz) but the suppression effect appeared to gradually attenuate during a 6-month follow-up period after surgery (p = 0.002). However, beta suppression did not attenuate after repeated stimulation over several minutes (p > 0.110), suggesting that the changes in beta suppression may reflect a slow reconfiguration of neural pathways instead of habituation. Suppression of beta was also associated with clinical symptom improvement across subjects. Importantly, symptom-relevant features fell within the high beta band at month 1 but shifted to the low beta band at month 6, indicating that the high beta and the low beta oscillations may play different functional roles and respond differently to stimulation over the long-term treatment. CONCLUSION These data may advance understanding of chronic DBS effects on beta oscillations and their association with clinical improvement, offering novel insights to the therapeutic mechanisms of DBS.
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Affiliation(s)
- Yue Chen
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 10084, China
| | - Chen Gong
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 10084, China
| | - Ye Tian
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 10084, China
| | - Natasza Orlov
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Yi Guo
- Department of Neurosurgery, Peking Union Medical College Hospital, Beijing, 100032, China
| | - Shujun Xu
- Department of Neurosurgery, Qilu Hospital of Shandong University, Shandong, 250012, China
| | - Changqing Jiang
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 10084, China
| | - Hongwei Hao
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 10084, China
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, 10117, Germany
| | - Andrea A Kühn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, 10117, Germany
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, 29425, SC, USA.
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, 10084, China; Precision Medicine & Healthcare Research Center, Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, 518071, China; IDG/McGovern Institute for Brain Research at Tsinghua University, Beijing, 100084, China; Institute of Epilepsy, Beijing Institute for Brain Disorders, Beijing, 100093, China.
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47
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Wu YH, Ou-Yang YH, Chen CC, Lee CY, Wu CY, Ker MD. Miniaturized Intracerebral Potential Recorder for Long-Term Local Field Potential of Deep Brain Signals. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:5188-5191. [PMID: 33019154 DOI: 10.1109/embc44109.2020.9175384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
A miniaturized intracerebral potential recorder for long-term local field potential (LFP) of deep brain signals is proposed. LFP can be recorded by deep brain electrodes. The abnormal beta-band oscillation of LFP in subthalamic nucleus and internal globus pallidus in patients with Parkinson's disease (PD) are associated with the severity of the symptoms. The LFP signal from patients who have been implanted with deep brain electrode can be monitored by our system for at least 24 hours in real time. Graphical user interface has also been developed for use by medical personnel. Imitation experiments and in vivo experiments were performed to successfully verify that our system can measure LFP signals. With 24-hour intracerebral signals, researchers can analyze what is happened in the brain in daily life. In the future, more effective PD treatment can be developed, such as intelligent closed-loop deep brain stimulation.
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Nguyen TAK, Schüpbach M, Mercanzini A, Dransart A, Pollo C. Directional Local Field Potentials in the Subthalamic Nucleus During Deep Brain Implantation of Parkinson's Disease Patients. Front Hum Neurosci 2020; 14:521282. [PMID: 33192384 PMCID: PMC7556345 DOI: 10.3389/fnhum.2020.521282] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 09/15/2020] [Indexed: 11/29/2022] Open
Abstract
Segmented deep brain stimulation leads feature directional electrodes that allow for a finer spatial control of electrical stimulation compared to traditional ring-shaped electrodes. These segmented leads have demonstrated enlarged therapeutic windows and have thus the potential to improve the treatment of Parkinson's disease patients. Moreover, they provide a unique opportunity to record directional local field potentials. Here, we investigated whether directional local field potentials can help identify the best stimulation direction to assist device programming. Four Parkinson's disease patients underwent routine implantation of the subthalamic nucleus. Firstly, local field potentials were recorded in three directions for two conditions: In one condition, the patient was at rest; in the other condition, the patient's arm was moved. Secondly, current thresholds for therapeutic and side effects were identified intraoperatively for directional stimulation. Therapeutic windows were calculated from these two thresholds. Thirdly, the spectral power of the total beta band (13-35 Hz) and its sub-bands low, high, and peak beta were analyzed post hoc. Fourthly, the spectral power was used by different algorithms to predict the ranking of directions. The spectral power profiles were patient-specific, and spectral peaks were found both in the low beta band (13-20 Hz) and in the high beta band (20.5-35 Hz). The direction with the highest spectral power in the total beta band was most indicative of the 1st best direction when defined by therapeutic window. Based on the total beta band, the resting condition and the moving condition were similarly predictive about the direction ranking and classified 83.3% of directions correctly. However, different algorithms were needed to predict the ranking defined by therapeutic window or therapeutic current threshold. Directional local field potentials may help predict the best stimulation direction. Further studies with larger sample sizes are needed to better distinguish the informative value of different conditions and the beta sub-bands.
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Affiliation(s)
- T. A. Khoa Nguyen
- Department of Neurosurgery, University Hospital of Bern, Bern, Switzerland
| | - Michael Schüpbach
- Department of Neurology, University Hospital of Bern, Bern, Switzerland
| | - André Mercanzini
- Microsystems Laboratory 4, School of Engineering, EPF Lausanne, Lausanne, Switzerland
- Aleva Neurotherapeutics SA, Lausanne, Switzerland
| | | | - Claudio Pollo
- Department of Neurosurgery, University Hospital of Bern, Bern, Switzerland
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Bronte-Stewart HM, Petrucci MN, O’Day JJ, Afzal MF, Parker JE, Kehnemouyi YM, Wilkins KB, Orthlieb GC, Hoffman SL. Perspective: Evolution of Control Variables and Policies for Closed-Loop Deep Brain Stimulation for Parkinson's Disease Using Bidirectional Deep-Brain-Computer Interfaces. Front Hum Neurosci 2020; 14:353. [PMID: 33061899 PMCID: PMC7489234 DOI: 10.3389/fnhum.2020.00353] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 08/05/2020] [Indexed: 11/21/2022] Open
Abstract
A deep brain stimulation system capable of closed-loop neuromodulation is a type of bidirectional deep brain-computer interface (dBCI), in which neural signals are recorded, decoded, and then used as the input commands for neuromodulation at the same site in the brain. The challenge in assuring successful implementation of bidirectional dBCIs in Parkinson's disease (PD) is to discover and decode stable, robust and reliable neural inputs that can be tracked during stimulation, and to optimize neurostimulation patterns and parameters (control policies) for motor behaviors at the brain interface, which are customized to the individual. In this perspective, we will outline the work done in our lab regarding the evolution of the discovery of neural and behavioral control variables relevant to PD, the development of a novel personalized dual-threshold control policy relevant to the individual's therapeutic window and the application of these to investigations of closed-loop STN DBS driven by neural or kinematic inputs, using the first generation of bidirectional dBCIs.
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Affiliation(s)
- Helen M. Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Matthew N. Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Johanna J. O’Day
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Bioengineering, Stanford University, Stanford, CA, United States
| | - Muhammad Furqan Afzal
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Jordan E. Parker
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Yasmine M. Kehnemouyi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Gerrit C. Orthlieb
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Shannon L. Hoffman
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
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50
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Acute effects of adaptive Deep Brain Stimulation in Parkinson's disease. Brain Stimul 2020; 13:1507-1516. [PMID: 32738409 PMCID: PMC7116216 DOI: 10.1016/j.brs.2020.07.016] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 07/19/2020] [Accepted: 07/23/2020] [Indexed: 02/08/2023] Open
Abstract
Background Beta-based adaptive Deep Brain Stimulation (aDBS) is effective in Parkinson’s disease (PD), when assessed in the immediate post-implantation phase. However, the potential benefits of aDBS in patients with electrodes chronically implanted, in whom changes due to the microlesion effect have disappeared, are yet to be assessed. Methods To determine the acute effectiveness and side-effect profile of aDBS in PD compared to conventional continuous DBS (cDBS) and no stimulation (NoStim), years after DBS implantation, 13 PD patients undergoing battery replacement were pseudo-randomised in a crossover fashion, into three conditions (NoStim, aDBS or cDBS), with a 2-min interval between them. Patient videos were blindly evaluated using a short version of the Unified Parkinson’s Disease Rating Scale (subUPDRS), and the Speech Intelligibility Test (SIT). Results Mean disease duration was 16 years, and the mean time since DBS-implantation was 6.9 years. subUPDRS scores (11 patients tested) were significantly lower both in aDBS (p = <.001), and cDBS (p = .001), when compared to NoStim. Bradykinesia subscores were significantly lower in aDBS (p = .002), and did not achieve significance during cDBS (p = .08), when compared to NoStim. Two patients demonstrated re-emerging tremor during aDBS. SIT scores of patients who presented stimulation-induced dysarthria significantly worsened in cDBS (p = .009), but not in aDBS (p = .407), when compared to NoStim. Overall, stimulation was applied 48.8% of the time during aDBS. Conclusion Beta-based aDBS is effective in PD patients with bradykinetic phenotypes, delivers less stimulation than cDBS, and potentially has a more favourable speech side-effect profile. Patients with prominent tremor may require a modified adaptive strategy.
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