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Bocci T, Ferrara R, Albizzati T, Averna A, Guidetti M, Marceglia S, Priori A. Asymmetries of the subthalamic activity in Parkinson's disease: phase-amplitude coupling among local field potentials. Brain Commun 2024; 6:fcae201. [PMID: 38894949 PMCID: PMC11184348 DOI: 10.1093/braincomms/fcae201] [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: 07/30/2023] [Revised: 01/22/2024] [Accepted: 06/07/2024] [Indexed: 06/21/2024] Open
Abstract
The role of brain asymmetries of dopaminergic neurons in motor symptoms of Parkinson's disease is still undefined. Local field recordings from the subthalamic nucleus revealed some neurophysiological biomarkers of the disease: increased beta activity, increased low-frequency activity and high-frequency oscillations. Phase-amplitude coupling coordinates the timing of neuronal activity and allows determining the mechanism for communication within distinct regions of the brain. In this study, we discuss the use of phase-amplitude coupling to assess the differences between the two hemispheres in a cohort of 24 patients with Parkinson's disease before and after levodopa administration. Subthalamic low- (12-20 Hz) and high-beta (20-30 Hz) oscillations were compared with low- (30-45 Hz), medium- (70-100 Hz) and high-frequency (260-360 Hz) bands. We found a significant beta-phase-amplitude coupling asymmetry between left and right and an opposite-side-dependent effect of the pharmacological treatment, which is associated with the reduction of motor symptoms. In particular, high coupling between high frequencies and high-beta oscillations was found during the OFF condition (P < 0.01) and a low coupling during the ON state (P < 0.0001) when the right subthalamus was assessed; exactly the opposite happened when the left subthalamus was considered in the analysis, showing a lower coupling between high frequencies and high-beta oscillations during the OFF condition (P < 0.01), followed by a higher one during the ON state (P < 0.01). Interestingly, these asymmetries are independent of the motor onset side, either left or right. These findings have important implications for neural signals that may be used to trigger adaptive deep brain stimulation in Parkinson's and could provide more exhaustive insights into subthalamic dynamics.
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Affiliation(s)
- Tommaso Bocci
- ‘Aldo Ravelli’ Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy
- III Neurology Clinic, ASST-Santi Paolo e Carlo University Hospital, 20142 Milan, Italy
| | - Rosanna Ferrara
- ‘Aldo Ravelli’ Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy
| | - Tommaso Albizzati
- Department of Engineering and Architecture, University of Trieste, Trieste, 34127 Friuli-Venezia Giulia, Italy
| | - Alberto Averna
- Department of Neurology, Bern University Hospital and University of Bern, 3010 Bern, Switzerland
| | - Matteo Guidetti
- ‘Aldo Ravelli’ Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy
| | - Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, Trieste, 34127 Friuli-Venezia Giulia, Italy
- Newronika S.r.l., 20093 Cologno Monzese, Italy
| | - Alberto Priori
- ‘Aldo Ravelli’ Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy
- III Neurology Clinic, ASST-Santi Paolo e Carlo University Hospital, 20142 Milan, Italy
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Oliveira AM, Coelho L, Carvalho E, Ferreira-Pinto MJ, Vaz R, Aguiar P. Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop. J Neurol 2023; 270:5313-5326. [PMID: 37530789 PMCID: PMC10576725 DOI: 10.1007/s00415-023-11873-1] [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: 05/09/2023] [Revised: 07/08/2023] [Accepted: 07/10/2023] [Indexed: 08/03/2023]
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disease bearing a severe social and economic impact. So far, there is no known disease modifying therapy and the current available treatments are symptom oriented. Deep Brain Stimulation (DBS) is established as an effective treatment for PD, however current systems lag behind today's technological potential. Adaptive DBS, where stimulation parameters depend on the patient's physiological state, emerges as an important step towards "smart" DBS, a strategy that enables adaptive stimulation and personalized therapy. This new strategy is facilitated by currently available neurotechnologies allowing the simultaneous monitoring of multiple signals, providing relevant physiological information. Advanced computational models and analytical methods are an important tool to explore the richness of the available data and identify signal properties to close the loop in DBS. To tackle this challenge, machine learning (ML) methods applied to DBS have gained popularity due to their ability to make good predictions in the presence of multiple variables and subtle patterns. ML based approaches are being explored at different fronts such as the identification of electrophysiological biomarkers and the development of personalized control systems, leading to effective symptom relief. In this review, we explore how ML can help overcome the challenges in the development of closed-loop DBS, particularly its role in the search for effective electrophysiology biomarkers. Promising results demonstrate ML potential for supporting a new generation of adaptive DBS, with better management of stimulation delivery, resulting in more efficient and patient-tailored treatments.
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Affiliation(s)
- Andreia M Oliveira
- Faculdade de Engenharia da Universidade do Porto, Porto, Portugal
- Neuroengineering and Computational Neuroscience Lab, Instituto de Investigação e Inovação da Universidade do Porto, Porto, Portugal
| | - Luis Coelho
- Instituto Superior de Engenharia do Porto, Porto, Portugal
| | - Eduardo Carvalho
- Neuroengineering and Computational Neuroscience Lab, Instituto de Investigação e Inovação da Universidade do Porto, Porto, Portugal
- ICBAS-School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal
| | - Manuel J Ferreira-Pinto
- Centro Hospitalar Universitário de São João, Porto, Portugal
- Faculdade de Medicina da Universidade do Porto, Porto, Portugal
| | - Rui Vaz
- Centro Hospitalar Universitário de São João, Porto, Portugal
- Faculdade de Medicina da Universidade do Porto, Porto, Portugal
| | - Paulo Aguiar
- Faculdade de Engenharia da Universidade do Porto, Porto, Portugal.
- Neuroengineering and Computational Neuroscience Lab, Instituto de Investigação e Inovação da Universidade do Porto, Porto, Portugal.
- Faculdade de Medicina da Universidade do Porto, Porto, Portugal.
- i3S-Instituto de Investigação e Inovação em Saúde, Rua Alfredo Allen, 208, 4200-135, Porto, Portugal.
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Radcliffe EM, Baumgartner AJ, Kern DS, Al Borno M, Ojemann S, Kramer DR, Thompson JA. Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease. J Neurophysiol 2023; 129:1492-1504. [PMID: 37198135 DOI: 10.1152/jn.00055.2023] [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: 02/03/2023] [Revised: 04/23/2023] [Accepted: 05/17/2023] [Indexed: 05/19/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.
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Affiliation(s)
- Erin M Radcliffe
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Alexander J Baumgartner
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Drew S Kern
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Mazen Al Borno
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Computer Science and Engineering, University of Colorado Denver, Denver, Colorado, United States
| | - Steven Ojemann
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Daniel R Kramer
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - John A Thompson
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
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4
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Zhang R, Nie Y, Dai W, Wang S, Geng X. Balance between pallidal neural oscillations correlated with dystonic activity and severity. Neurobiol Dis 2023:106178. [PMID: 37268239 DOI: 10.1016/j.nbd.2023.106178] [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: 03/23/2023] [Revised: 05/14/2023] [Accepted: 05/28/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND AND OBJECTIVE The balance between neural oscillations provides valuable insights into the organisation of neural oscillations related to brain states, which may play important roles in dystonia. We aim to investigate the relationship of the balance in the globus pallidus internus (GPi) with the dystonic severity under different muscular contraction conditions. METHODS Twenty-one patients with dystonia were recruited. All of them underwent bilateral GPi implantation, and local field potentials (LFPs) from the GPi were recorded via simultaneous surface electromyography. The power spectral ratio between neural oscillations was computed as the measure of neural balance. This ratio was calculated under high and low dystonic muscular contraction conditions, and its correlation with the dystonic severity was assessed using clinical scores. RESULTS The power spectral of the pallidal LFPs peaked in the theta and alpha bands. Within participant comparison showed that the power spectral of the theta oscillations significantly increased during high muscle contraction compared with that during low contraction. The power spectral ratios between the theta and alpha, theta and low beta, and theta and high gamma oscillations were significantly higher during high contraction than during low contraction. The total score and motor score were associated with the power spectral ratio between the low and high beta oscillations, which was correlated with the dystonic severity both during high and low contractions. The power spectral ratios between the low beta and low gamma and between the low beta and high gamma oscillations showed a significantly positive correlation with the total score during both high and low contractions; a correlation with the motor scale score was found only during high contraction. Meanwhile, the power spectral ratio between the theta and alpha oscillations during low contraction showed a significantly negative correlation with the total score. The power spectral ratios between the alpha and high beta, alpha and low gamma, and alpha and high gamma oscillations were significantly correlated with the dystonic severity only during low contraction. CONCLUSION The balance between neural oscillations, as quantified by the power ratio between specific frequency bands, differed between the high and low muscular contraction conditions and was correlated with the dystonic severity. The balance between the low and high beta oscillations was correlated with the dystonic severity during both conditions, making this parameter a new possible biomarker for closed-loop deep brain stimulation in patients with dystonia.
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Affiliation(s)
- Ruili Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Yingnan Nie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wen Dai
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Shouyan Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Shanghai, China; Shanghai Engineering Research Center of AI & Robotics, Fudan University, Shanghai, China; Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, China
| | - Xinyi Geng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Shanghai, China.
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Neumann WJ, Gilron R, Little S, Tinkhauser G. Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation. Mov Disord 2023. [PMID: 37148553 DOI: 10.1002/mds.29415] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 03/27/2023] [Accepted: 04/05/2023] [Indexed: 05/08/2023] Open
Abstract
Closed-loop adaptive deep brain stimulation (aDBS) can deliver individualized therapy at an unprecedented temporal precision for neurological disorders. This has the potential to lead to a breakthrough in neurotechnology, but the translation to clinical practice remains a significant challenge. Via bidirectional implantable brain-computer-interfaces that have become commercially available, aDBS can now sense and selectively modulate pathophysiological brain circuit activity. Pilot studies investigating different aDBS control strategies showed promising results, but the short experimental study designs have not yet supported individualized analyses of patient-specific factors in biomarker and therapeutic response dynamics. Notwithstanding the clear theoretical advantages of a patient-tailored approach, these new stimulation possibilities open a vast and mostly unexplored parameter space, leading to practical hurdles in the implementation and development of clinical trials. Therefore, a thorough understanding of the neurophysiological and neurotechnological aspects related to aDBS is crucial to develop evidence-based treatment regimens for clinical practice. Therapeutic success of aDBS will depend on the integrated development of strategies for feedback signal identification, artifact mitigation, signal processing, and control policy adjustment, for precise stimulation delivery tailored to individual patients. The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years. Finally, it highlights the importance of interdisciplinary clinical neurotechnological research within and across DBS centers, toward an individualized patient-centered approach to invasive brain stimulation. © 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)
- Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | - Simon Little
- Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, California, USA
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
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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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Morelli N. Effect and Relationship of Gait on Subcortical Local Field Potentials in Parkinson's Disease: A Systematic Review. Neuromodulation 2023; 26:271-279. [PMID: 36244929 DOI: 10.1016/j.neurom.2022.09.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 08/19/2022] [Accepted: 09/05/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVES Developments in deep brain stimulation (DBS) technology have enabled the ability to detect local field potentials (LFPs) in Parkinson disease (PD). Gait dysfunction is one of the most prevalent deficits seen in PD. However, no consensus has been reached on the effect of gait on LFPs and the relationship between LFPs and clinical measures of gait. The objective of this systematic review was to synthesize existing research regarding the relationship between gait dysfunction and LFPs in PD. METHODS A systematic search of the literature yielded a total of ten articles, including 132 patients with PD, which met the criteria for inclusion. RESULTS Beta frequency band measures showed low-to-strong correlation to clinical gait measures (r = -0.50 to 0.82). Two studies found decreased beta power during gait; one found increased beta frequency peaks during gait; and one found higher beta power during dual-task gait than during single-task gait. One of the three studies comparing patients with and without freezing found significantly increased beta burst duration and power during gait in freezers compared with nonfreezers. All studies showed moderate-to-high methodologic quality. CONCLUSIONS This review highlights the need to consider the effect of gait on LFP recordings, particularly when used to guide DBS programming. Although sample sizes were small, it appears LFPs are associated to and modulated by gait in patients with PD. This evidence suggests that LFPs have the potential to be used as a biomarker of gait dysfunction in PD.
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Prenassi M, Borellini L, Bocci T, Scola E, Barbieri S, Priori A, Ferrucci R, Cogiamanian F, Locatelli M, Rampini P, Vergari M, Pastore S, Datola B, Marceglia S. Peri-lead edema and local field potential correlation in post-surgery subthalamic nucleus deep brain stimulation patients. Front Hum Neurosci 2022; 16:950434. [PMID: 36158622 PMCID: PMC9495298 DOI: 10.3389/fnhum.2022.950434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Accepted: 07/26/2022] [Indexed: 12/01/2022] Open
Abstract
Implanting deep brain stimulation (DBS) electrodes in patients with Parkinson’s disease often results in the appearance of a non-infectious, delayed-onset edema that disappears over time. However, the time window between the DBS electrode and DBS stimulating device implant is often used to record local field potentials (LFPs) which are used both to better understand basal ganglia pathophysiology and to improve DBS therapy. In this work, we investigated whether the presence of post-surgery edema correlates with the quality of LFP recordings in eight patients with advanced Parkinson’s disease implanted with subthalamic DBS electrodes. The magnetic resonance scans of the brain after 8.5 ± 1.5 days from the implantation surgery were segmented and the peri-electrode edema volume was calculated for both brain hemispheres. We found a correlation (ρ = −0.81, p < 0.0218, Spearman’s correlation coefficient) between left side local field potentials of the low beta band (11–20 Hz) and the edema volume of the same side. No other significant differences between the hemispheres were found. Despite the limited sample size, our results suggest that the effect on LFPs may be related to the edema localization, thus indicating a mechanism involving brain networks instead of a simple change in the electrode-tissue interface.
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Affiliation(s)
- Marco Prenassi
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
- Department of Engineering and Architecture, Università degli Studi di Trieste, Trieste, Italy
- *Correspondence: Marco Prenassi
| | - Linda Borellini
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
| | - Tommaso Bocci
- “Aldo Ravelli” Research Center for Neurotechnology and Experimental Brain Therapeutics, Department of Health Sciences, University of Milan Medical School, Milan, Italy
| | - Elisa Scola
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, Florence, Italy
| | - Sergio Barbieri
- Department of Engineering and Architecture, Università degli Studi di Trieste, Trieste, Italy
| | - Alberto Priori
- “Aldo Ravelli” Research Center for Neurotechnology and Experimental Brain Therapeutics, Department of Health Sciences, University of Milan Medical School, Milan, Italy
| | - Roberta Ferrucci
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
- “Aldo Ravelli” Research Center for Neurotechnology and Experimental Brain Therapeutics, Department of Health Sciences, University of Milan Medical School, Milan, Italy
| | | | - Marco Locatelli
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
- “Aldo Ravelli” Research Center for Neurotechnology and Experimental Brain Therapeutics, Department of Health Sciences, University of Milan Medical School, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Paolo Rampini
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
| | - Maurizio Vergari
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
| | - Stefano Pastore
- Department of Engineering and Architecture, Università degli Studi di Trieste, Trieste, Italy
| | - Bianca Datola
- Department of Engineering and Architecture, Università degli Studi di Trieste, Trieste, Italy
| | - Sara Marceglia
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
- Department of Engineering and Architecture, Università degli Studi di Trieste, Trieste, Italy
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Darcy N, Lofredi R, Al-Fatly B, Neumann WJ, Hübl J, Brücke C, Krause P, Schneider GH, Kühn A. Spectral and spatial distribution of subthalamic beta peak activity in Parkinson's disease patients. Exp Neurol 2022; 356:114150. [PMID: 35732220 DOI: 10.1016/j.expneurol.2022.114150] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/27/2022] [Accepted: 06/15/2022] [Indexed: 11/17/2022]
Abstract
Current efforts to optimize subthalamic deep brain stimulation in Parkinson's disease patients aim to harness local oscillatory activity in the beta frequency range (13-35 Hz) as a feedback-signal for demand-based adaptive stimulation paradigms. A high prevalence of beta peak activity is prerequisite for this approach to become routine clinical practice. In a large dataset of postoperative rest recordings from 106 patients we quantified occurrence and identified determinants of spectral peaks in the alpha, low and high beta bands. At least one peak in beta band occurred in 92% of patients and 84% of hemispheres off medication, irrespective of demographic parameters, clinical subtype or motor symptom severity. Distance to previously described clinical sweet spot was significantly related both to beta peak occurrence and to spectral power (rho -0.21, p 0.006), particularly in the high beta band. Electrophysiological landscapes of our cohort's dataset in normalised space showed divergent heatmaps for alpha and beta but found similar regions for low and high beta frequency bands. We discuss potential ramifications for clinicians' programming decisions. In summary, this report provides robust evidence that spectral peaks in beta frequency range can be detected in the vast majority of Parkinsonian subthalamic nuclei, increasing confidence in the broad applicability of beta-guided deep brain stimulation.
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Affiliation(s)
- Natasha Darcy
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany.
| | - Roxanne Lofredi
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany
| | - Bassam Al-Fatly
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Wolf-Julian Neumann
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt-Universität, Berlin, Germany
| | - Julius Hübl
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Christof Brücke
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Patricia Krause
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Gerd-Helge Schneider
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Andrea Kühn
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt-Universität, Berlin, Germany; NeuroCure, Exzellenzcluster, Charité - Universitätsmedizin Berlin, Berlin, Germany; DZNE, German center for neurodegenerative diseases, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Germany
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10
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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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11
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del Campo-Vera RM, Tang AM, Gogia AS, Chen KH, Sebastian R, Gilbert ZD, Nune G, Liu CY, Kellis S, Lee B. Neuromodulation in Beta-Band Power Between Movement Execution and Inhibition in the Human Hippocampus. Neuromodulation 2022; 25:232-244. [PMID: 35125142 PMCID: PMC8727636 DOI: 10.1111/ner.13486] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 05/08/2021] [Accepted: 06/01/2021] [Indexed: 02/03/2023]
Abstract
INTRODUCTION The hippocampus is thought to be involved in movement, but its precise role in movement execution and inhibition has not been well studied. Previous work with direct neural recordings has found beta-band (13-30 Hz) modulation in both movement execution and inhibition throughout the motor system, but the role of beta-band modulation in the hippocampus during movement inhibition is not well understood. Here, we perform a Go/No-Go reaching task in ten patients with medically refractory epilepsy to study human hippocampal beta-power changes during movement. MATERIALS AND METHODS Ten epilepsy patients (5 female; ages 21-46) were implanted with intracranial depth electrodes for seizure monitoring and localization. Local field potentials were sampled at 2000 Hz during a Go/No-Go movement task. Comparison of beta-band power between Go and No-Go conditions was conducted using Wilcoxon signed-rank hypothesis testing for each patient. Sub-analyses were conducted to assess differences in the anterior vs posterior contacts, ipsilateral vs contralateral contacts, and male vs female beta-power values. RESULTS Eight out of ten patients showed significant beta-power decreases during the Go movement response (p < 0.05) compared to baseline. Eight out of ten patients also showed significant beta-power increases in the No-Go condition, occurring in the absence of movement. No significant differences were noted between ipsilateral vs contralateral contacts nor in anterior vs posterior hippocampal contacts. Female participants had a higher task success rate than males and had significantly greater beta-power increases in the No-Go condition (p < 0.001). CONCLUSION These findings indicate that increases in hippocampal beta power are associated with movement inhibition. To the best of our knowledge, this study is the first to report this phenomenon in the human hippocampus. The beta band may represent a state-change signal involved in motor processing. Future focus on the beta band in understanding human motor and impulse control will be vital.
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Affiliation(s)
- Roberto Martin del Campo-Vera
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Austin M. Tang
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Angad S. Gogia
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Kuang-Hsuan Chen
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Rinu Sebastian
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Zachary D. Gilbert
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - George Nune
- Department of Neurology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States,USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Charles Y. Liu
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States,USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States,Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States
| | - Spencer Kellis
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States,USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States,Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States,Tianqiao and Chrissy Chen Brain-Machine Interface Center, Chen Institute for Neuroscience, California Institute of Technology, Pasadena, CA, United States
| | - Brian Lee
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States,USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States,Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States
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12
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Pozzi NG, Isaias IU. Adaptive deep brain stimulation: Retuning Parkinson's disease. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:273-284. [PMID: 35034741 DOI: 10.1016/b978-0-12-819410-2.00015-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A brain-machine interface represents a promising therapeutic avenue for the treatment of many neurologic conditions. Deep brain stimulation (DBS) is an invasive, neuro-modulatory tool that can improve different neurologic disorders by delivering electric stimulation to selected brain areas. DBS is particularly successful in advanced Parkinson's disease (PD), where it allows sustained improvement of motor symptoms. However, this approach is still poorly standardized, with variable clinical outcomes. To achieve an optimal therapeutic effect, novel adaptive DBS (aDBS) systems are being developed. These devices operate by adapting stimulation parameters in response to an input signal that can represent symptoms, motor activity, or other behavioral features. Emerging evidence suggests greater efficacy with fewer adverse effects during aDBS compared with conventional DBS. We address this topic by discussing the basics principles of aDBS, reviewing current evidence, and tackling the many challenges posed by aDBS for PD.
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Affiliation(s)
- Nicoló G Pozzi
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany
| | - Ioannis U Isaias
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany.
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13
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Arlotti M, Colombo M, Bonfanti A, Mandat T, Lanotte MM, Pirola E, Borellini L, Rampini P, Eleopra R, Rinaldo S, Romito L, Janssen MLF, Priori A, Marceglia S. A New Implantable Closed-Loop Clinical Neural Interface: First Application in Parkinson's Disease. Front Neurosci 2021; 15:763235. [PMID: 34949982 PMCID: PMC8689059 DOI: 10.3389/fnins.2021.763235] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 11/04/2021] [Indexed: 11/13/2022] Open
Abstract
Deep brain stimulation (DBS) is used for the treatment of movement disorders, including Parkinson’s disease, dystonia, and essential tremor, and has shown clinical benefits in other brain disorders. A natural path for the improvement of this technique is to continuously observe the stimulation effects on patient symptoms and neurophysiological markers. This requires the evolution of conventional deep brain stimulators to bidirectional interfaces, able to record, process, store, and wirelessly communicate neural signals in a robust and reliable fashion. Here, we present the architecture, design, and first use of an implantable stimulation and sensing interface (AlphaDBSR System) characterized by artifact-free recording and distributed data management protocols. Its application in three patients with Parkinson’s disease (clinical trial n. NCT04681534) is shown as a proof of functioning of a clinically viable implanted brain-computer interface (BCI) for adaptive DBS. Reliable artifact free-recordings, and chronic long-term data and neural signal management are in place.
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Affiliation(s)
| | | | - Andrea Bonfanti
- Newronika SpA, Milan, Italy.,Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy
| | - Tomasz Mandat
- Narodowy Instytut Onkologii im. Marii Skłodowskiej-Curie, Warsaw, Poland
| | - Michele Maria Lanotte
- Department of Neuroscience, University of Torino, Torino, Italy.,AOU Città della Salute e della Scienza, Molinette Hospital, Turin, Italy
| | - Elena Pirola
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Linda Borellini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Paolo Rampini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Roberto Eleopra
- Movement Disorders Unit, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Sara Rinaldo
- Movement Disorders Unit, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Luigi Romito
- Movement Disorders Unit, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Marcus L F Janssen
- Department of Neurology and Clinical Neurophysiology, Maastricht University Medical Center, Maastricht, Netherlands.,Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Alberto Priori
- Department of Health Sciences, Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, University of Milan, Milan, Italy
| | - Sara Marceglia
- Dipartimento di Ingegneria e Architettura, Università degli Studi di Trieste, Trieste, Italy
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14
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Sure M, Vesper J, Schnitzler A, Florin E. Dopaminergic Modulation of Spectral and Spatial Characteristics of Parkinsonian Subthalamic Nucleus Beta Bursts. Front Neurosci 2021; 15:724334. [PMID: 34867149 PMCID: PMC8636009 DOI: 10.3389/fnins.2021.724334] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 10/08/2021] [Indexed: 11/13/2022] Open
Abstract
In Parkinson’s disease (PD), subthalamic nucleus (STN) beta burst activity is pathologically elevated. These bursts are reduced by dopamine and deep brain stimulation (DBS). Therefore, these bursts have been tested as a trigger for closed-loop DBS. To provide better targeted parameters for closed-loop stimulation, we investigate the spatial distribution of beta bursts within the STN and if they are specific to a beta sub-band. Local field potentials (LFP) were acquired in the STN of 27 PD patients while resting. Based on the orientation of segmented DBS electrodes, the LFPs were classified as anterior, postero-medial, and postero-lateral. Each recording lasted 30 min with (ON) and without (OFF) dopamine. Bursts were detected in three frequency bands: ±3 Hz around the individual beta peak frequency, low beta band (lBB), and high beta band (hBB). Medication reduced the duration and the number of bursts per minute but not the amplitude of the beta bursts. The burst amplitude was spatially modulated, while the burst duration and rate were frequency dependent. Furthermore, the hBB burst duration was positively correlated with the akinetic-rigid UPDRS III subscore. Overall, these findings on differential dopaminergic modulation of beta burst parameters suggest that hBB burst duration is a promising target for closed-loop stimulation and that burst parameters could guide DBS programming.
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Affiliation(s)
- Matthias Sure
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Jan Vesper
- Department of Functional Neurosurgery and Stereotaxy, Medical Faculty, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.,Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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15
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Baumgartner AJ, Kushida CA, Summers MO, Kern DS, Abosch A, Thompson JA. Basal Ganglia Local Field Potentials as a Potential Biomarker for Sleep Disturbance in Parkinson's Disease. Front Neurol 2021; 12:765203. [PMID: 34777232 PMCID: PMC8581299 DOI: 10.3389/fneur.2021.765203] [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: 08/26/2021] [Accepted: 10/04/2021] [Indexed: 11/18/2022] Open
Abstract
Sleep disturbances, specifically decreases in total sleep time and sleep efficiency as well as increased sleep onset latency and wakefulness after sleep onset, are highly prevalent in patients with Parkinson's disease (PD). Impairment of sleep significantly and adversely impacts several comorbidities in this patient population, including cognition, mood, and quality of life. Sleep disturbances and other non-motor symptoms of PD have come to the fore as the effectiveness of advanced therapies such as deep brain stimulation (DBS) optimally manage the motor symptoms. Although some studies have suggested that DBS provides benefit for sleep disturbances in PD, the mechanisms by which this might occur, as well as the optimal stimulation parameters for treating sleep dysfunction, remain unknown. In patients treated with DBS, electrophysiologic recording from the stimulating electrode, in the form of local field potentials (LFPs), has led to the identification of several findings associated with both motor and non-motor symptoms including sleep. For example, beta frequency (13–30 Hz) oscillations are associated with worsened bradykinesia while awake and decrease during non-rapid eye movement sleep. LFP investigation of sleep has largely focused on the subthalamic nucleus (STN), though corresponding oscillatory activity has been found in the globus pallidus internus (GPi) and thalamus as well. LFPs are increasingly being recognized as a potential biomarker for sleep states in PD, which may allow for closed-loop optimization of DBS parameters to treat sleep disturbances in this population. In this review, we discuss the relationship between LFP oscillations in STN and the sleep architecture of PD patients, current trends in utilizing DBS to treat sleep disturbance, and future directions for research. In particular, we highlight the capability of novel technologies to capture and record LFP data in vivo, while patients continue therapeutic stimulation for motor symptoms. These technological advances may soon allow for real-time adaptive stimulation to treat sleep disturbances.
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Affiliation(s)
- Alexander J Baumgartner
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO, United States
| | - Clete A Kushida
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael O Summers
- Department of Medicine, Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Nebraska Medical Center, Omaha, NE, United States
| | - Drew S Kern
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO, United States.,Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, United States
| | - Aviva Abosch
- Department of Neurosurgery, University of Nebraska Medical Center, Omaha, NE, United States
| | - John A Thompson
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO, United States.,Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, United States
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16
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Marceglia S, Guidetti M, Harmsen IE, Loh A, Meoni S, Foffani G, Lozano AM, Volkmann J, Moro E, Priori A. Deep brain stimulation: is it time to change gears by closing the loop? J Neural Eng 2021; 18. [PMID: 34678794 DOI: 10.1088/1741-2552/ac3267] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 10/22/2021] [Indexed: 11/12/2022]
Abstract
Objective.Adaptive deep brain stimulation (aDBS) is a form of invasive stimulation that was conceived to overcome the technical limitations of traditional DBS, which delivers continuous stimulation of the target structure without considering patients' symptoms or status in real-time. Instead, aDBS delivers on-demand, contingency-based stimulation. So far, aDBS has been tested in several neurological conditions, and will be soon extensively studied to translate it into clinical practice. However, an exhaustive description of technical aspects is still missing.Approach.in this topical review, we summarize the knowledge about the current (and future) aDBS approach and control algorithms to deliver the stimulation, as reference for a deeper undestending of aDBS model.Main results.We discuss the conceptual and functional model of aDBS, which is based on the sensing module (that assesses the feedback variable), the control module (which interpretes the variable and elaborates the new stimulation parameters), and the stimulation module (that controls the delivery of stimulation), considering both the historical perspective and the state-of-the-art of available biomarkers.Significance.aDBS modulates neuronal circuits based on clinically relevant biofeedback signals in real-time. First developed in the mid-2000s, many groups have worked on improving closed-loop DBS technology. The field is now at a point in conducting large-scale randomized clinical trials to translate aDBS into clinical practice. As we move towards implanting brain-computer interfaces in patients, it will be important to understand the technical aspects of aDBS.
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Affiliation(s)
- Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy
| | - Matteo Guidetti
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy.,Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| | - Irene E Harmsen
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Aaron Loh
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Sara Meoni
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy.,Movement Disorders Unit, Division of Neurology, CHU Grenoble Alpes, Grenoble, France.,Grenoble Institute of Neurosciences, INSERM U1216, University Grenoble Alpes, Grenoble, France
| | - 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
| | - Andres M Lozano
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Jens Volkmann
- Department of Neurology, University of Wurzburg, Wurzburg, Germany
| | - Elena Moro
- Movement Disorders Unit, Division of Neurology, CHU Grenoble Alpes, Grenoble, France.,Grenoble Institute of Neurosciences, INSERM U1216, University Grenoble Alpes, Grenoble, France
| | - Alberto Priori
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy.,ASST Santi Paolo e Carlo, 20142 Milan, Italy
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17
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Averna A, Marceglia S, Arlotti M, Locatelli M, Rampini P, Priori A, Bocci T. Influence of inter-electrode distance on subthalamic nucleus local field potential recordings in Parkinson's disease. Clin Neurophysiol 2021; 133:29-38. [PMID: 34794045 DOI: 10.1016/j.clinph.2021.10.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 09/24/2021] [Accepted: 10/05/2021] [Indexed: 11/03/2022]
Abstract
OBJECTIVES To evaluate spectra and their correlations with clinical symptoms of local field potentials (LFP) acquired from wide- and close-spaced contacts (i.e. between contacts 0-3 or LFP03, and contacts 1-2 or LFP12 respectively) on the same DBS electrode within the subthalamus (STN) in Parkinson's disease (PD), before and after levodopa administration. METHODS LFP12 and LFP03 were recorded from 20 PD patients. We evaluated oscillatory power, local and switched phase-amplitude coupling (l- and Sw-PAC) and correlation with motor symptoms (UPDRSIII). RESULTS Before levodopa, both LFP03 and LFP12 power in the α band inversely correlated with UPDRSIII. Differences between contacts were found in the low-frequency bands power. After levodopa, differences in UPDRSIII were associated to changes in LFP03 low-β and LFP12 HFO (high frequency oscillations, 250-350 Hz) power, while a modulation of the low-β power and an increased β-LFO (low frequency oscillations, 15-45 Hz) PAC was found only for LFP12. CONCLUSION This study reveals differences in spectral pattern between LFP12 and LFP03 before and after levodopa administration, as well as different correlations with PD motor symptoms. SIGNIFICANCE Differences between LFP12 and LFP03 may offer an opportunity for optimizing adaptive deep brain stimulation (aDBS) protocols for PD. LFP12 can be used to detect β-HFO coupling and β power (i.e. bradykinesia), while LFP03 are optimal for low frequency oscillations (dyskinesias).
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Affiliation(s)
- Alberto Averna
- Aldo Ravelli" Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy
| | - Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy
| | | | - Marco Locatelli
- Aldo Ravelli" Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy; Department of Neurosurgery, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Paolo Rampini
- Department of Neurosurgery, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Alberto Priori
- Aldo Ravelli" Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy; Clinical Neurology Unit I, San Paolo University Hospital, ASST Santi Paolo e Carlo and Department of Health Sciences, 20142 Milan, Italy
| | - Tommaso Bocci
- Aldo Ravelli" Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy; Clinical Neurology Unit I, San Paolo University Hospital, ASST Santi Paolo e Carlo and Department of Health Sciences, 20142 Milan, Italy..
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18
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David FJ, Munoz MJ, Shils JL, Pauciulo MW, Hale PT, Nichols WC, Afshari M, Sani S, Verhagen Metman L, Corcos DM, Pal GD. Subthalamic Peak Beta Ratio Is Asymmetric in Glucocerebrosidase Mutation Carriers With Parkinson's Disease: A Pilot Study. Front Neurol 2021; 12:723476. [PMID: 34659089 PMCID: PMC8514636 DOI: 10.3389/fneur.2021.723476] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 08/24/2021] [Indexed: 01/18/2023] Open
Abstract
Introduction: Up to 27% of individuals undergoing subthalamic nucleus deep brain stimulation (STN-DBS) have a genetic form of Parkinson's disease (PD). Glucocerebrosidase (GBA) mutation carriers, compared to sporadic PD, present with a more aggressive disease, less asymmetry, and fare worse on cognitive outcomes with STN-DBS. Evaluating STN intra-operative local field potentials provide the opportunity to assess and compare symmetry between GBA and non-GBA mutation carriers with PD; thus, providing insight into genotype and STN physiology, and eligibility for and programming of STN-DBS. The purpose of this pilot study was to test differences in left and right STN resting state beta power in non-GBA and GBA mutation carriers with PD. Materials and Methods: STN (left and right) resting state local field potentials were recorded intraoperatively from 4 GBA and 5 non-GBA patients with PD while off medication. Peak beta power expressed as a ratio to total beta power (peak beta ratio) was compared between STN hemispheres and groups while co-varying for age, age of disease onset, and disease severity. Results: Peak beta ratio was significantly different between the left and the right STN for the GBA group (p < 0.01) but not the non-GBA group (p = 0.56) after co-varying for age, age of disease onset, and disease severity. Discussion: Peak beta ratio in GBA mutation carriers was more asymmetric compared with non-mutation carriers and this corresponded with the degree of clinical asymmetry as measured by rating scales. This finding suggests that GBA mutation carriers have a physiologic signature that is distinct from that found in sporadic PD.
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Affiliation(s)
- Fabian J David
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, United States
| | - Miranda J Munoz
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, United States
| | - Jay L Shils
- Department of Anesthesiology, Rush University Medical Center, Chicago, IL, United States
| | - Michael W Pauciulo
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Philip T Hale
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - William C Nichols
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Mitra Afshari
- Department of Neurological Science, Rush University Medical Center, Chicago, IL, United States
| | - Sepehr Sani
- Department of Neurosurgery, Rush University Medical Center, Chicago, IL, United States
| | - Leo Verhagen Metman
- Department of Neurological Science, Rush University Medical Center, Chicago, IL, United States
| | - Daniel M Corcos
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, United States
| | - Gian D Pal
- Department of Neurological Science, Rush University Medical Center, Chicago, IL, United States.,Department of Neurology, Rutgers University, New Brunswick, NJ, United States
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19
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Priori A, Maiorana N, Dini M, Guidetti M, Marceglia S, Ferrucci R. Adaptive deep brain stimulation (aDBS). INTERNATIONAL REVIEW OF NEUROBIOLOGY 2021; 159:111-127. [PMID: 34446243 DOI: 10.1016/bs.irn.2021.06.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Deep brain stimulation is an established technique for the treatment of movement disorders related to neurodegenerative diseases such as Parkinson's disease (PD) and essential tremor (ET). Its application seems also feasible for the treatment of neuropsychiatric disorders such as treatment resistant depression (TRD) and Tourette's syndrome (TS). In a typical deep brain stimulation system, the amount of current delivered to the patients is constant and regulated by the physician. Conversely, an adaptive deep brain stimulation system (aDBS) is a closed loop system that adjusts the stimulation parameters according to biomarkers which reflect the patient's clinical state. In this chapter, we examined the main issues related to aDBS systems, which are both clinical and technological in nature. From a clinical point of view, we have reported the major findings related to symptoms management using aDBS and principal findings in animal models, showing that the implementation of closed loop adaptive deep brain stimulation can ameliorate symptom management in neurodegenerative disorders. From the technological point of view, we reported the major advances related to aDBS system design and implementation, such as noise filtering methods, biomarkers recording and processing to adjust pulse delivery. To date, aDBS systems represent a major evolution in brain stimulation, further developments are needed to maximize the efficacy of this technique and to expand its use in a wide range of neuropsychiatric disorders.
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Affiliation(s)
- Alberto Priori
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy.
| | - Natale Maiorana
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy
| | - Michelangelo Dini
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy
| | - Matteo Guidetti
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy
| | - Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | - Roberta Ferrucci
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy
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20
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Cummins DD, Kochanski RB, Gilron R, Swann NC, Little S, Hammer LH, Starr PA. Chronic Sensing of Subthalamic Local Field Potentials: Comparison of First and Second Generation Implantable Bidirectional Systems Within a Single Subject. Front Neurosci 2021; 15:725797. [PMID: 34447294 PMCID: PMC8382799 DOI: 10.3389/fnins.2021.725797] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 07/16/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Many adaptative deep brain stimulation (DBS) paradigms rely upon the ability to sense neural signatures of specific clinical signs or symptoms in order to modulate therapeutic stimulation. In first-generation bidirectional neurostimulators, the ability to sense neural signals during active stimulation was often limited by artifact. Newer devices, with improved design specifications for sensing, have recently been developed and are now clinically available. OBJECTIVE To compare the sensing capabilities of the first-generation Medtronic PC + S and second-generation Percept PC neurostimulators within a single patient. METHODS A 42-year-old man with Parkinson's disease was initially implanted with left STN DBS leads connected to a PC + S implantable pulse generator. Four years later, the PC + S was replaced with the Percept PC. Local field potential (LFP) signals were recorded, both with stimulation OFF and ON, at multiple timepoints with each device and compared. Offline processing of time series data included artifact removal using digital filtering and template subtraction, before subsequent spectral analysis. With Percept PC, embedded processing of spectral power within a narrow frequency band was also utilized. RESULTS In the absence of stimulation, both devices demonstrated a peak in the beta range (approximately 20 Hz), which was stable throughout the 4-year period. Similar to previous reports, recordings with the PC + S during active stimulation demonstrated significant stimulation artifact, limiting the ability to recover meaningful LFP signal. In contrast, the Percept PC, using the same electrodes and stimulation settings, produced time series data during stimulation with spectral analysis revealing a peak in the beta-band. Online analysis by the Percept demonstrated a reduction in beta-band activity with increasing stimulation amplitude. CONCLUSION This report highlights recent advances in implantable neurostimulator technology for DBS, demonstrating improvements in sensing capabilities during active stimulation between first- and second-generation devices. The ability to reliably sense during stimulation is an important step toward both the clinical implementation of adaptive algorithms and the further investigation into the neurophysiology underlying movement disorders.
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Affiliation(s)
- Daniel D. Cummins
- School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Ryan B. Kochanski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Roee Gilron
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Nicole C. Swann
- Department of Human Physiology, University of Oregon, Eugene, OR, United States
| | - Simon Little
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Lauren H. Hammer
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Philip A. Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
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21
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Ali HAM, Abdullah SS, Faraj MK. High impedance analysis in recordings of deep brain stimulation surgery. INTERDISCIPLINARY NEUROSURGERY 2021. [DOI: 10.1016/j.inat.2021.101115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
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22
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Yin Z, Zhu G, Zhao B, Bai Y, Jiang Y, Neumann WJ, Kühn AA, Zhang J. Local field potentials in Parkinson's disease: A frequency-based review. Neurobiol Dis 2021; 155:105372. [PMID: 33932557 DOI: 10.1016/j.nbd.2021.105372] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 04/25/2021] [Accepted: 04/26/2021] [Indexed: 12/19/2022] Open
Abstract
Deep brain stimulation (DBS) surgery offers a unique opportunity to record local field potentials (LFPs), the electrophysiological population activity of neurons surrounding the depth electrode in the target area. With direct access to the subcortical activity, LFP research has provided valuable insight into disease mechanisms and cognitive processes and inspired the advent of adaptive DBS for Parkinson's disease (PD). A frequency-based framework is usually employed to interpret the implications of LFP signatures in LFP studies on PD. This approach standardizes the methodology, simplifies the interpretation of LFP patterns, and makes the results comparable across studies. Importantly, previous works have found that activity patterns do not represent disease-specific activity but rather symptom-specific or task-specific neuronal signatures that relate to the current motor, cognitive or emotional state of the patient and the underlying disease. In the present review, we aim to highlight distinguishing features of frequency-specific activities, mainly within the motor domain, recorded from DBS electrodes in patients with PD. Associations of the commonly reported frequency bands (delta, theta, alpha, beta, gamma, and high-frequency oscillations) to motor signs are discussed with respect to band-related phenomena such as individual tremor and high/low beta frequency activity, as well as dynamic transients of beta bursts. We provide an overview on how electrophysiology research in DBS patients has revealed and will continuously reveal new information about pathophysiology, symptoms, and behavior, e.g., when combining deep LFP and surface electrocorticography recordings.
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Affiliation(s)
- Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Yutong Bai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Yin Jiang
- Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charite´ Campus Mitte, Charite´ - University Medicine Berlin, Berlin, Germany
| | - Andrea A Kühn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charite´ Campus Mitte, Charite´ - University Medicine Berlin, Berlin, Germany; Berlin School of Mind and Brain, Charité - Universitätsmedizin Berlin, Unter den Linden 6, 10099 Berlin, Germany; NeuroCure, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China.
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23
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Vedam-Mai V, Deisseroth K, Giordano J, Lazaro-Munoz G, Chiong W, Suthana N, Langevin JP, Gill J, Goodman W, Provenza NR, Halpern CH, Shivacharan RS, Cunningham TN, Sheth SA, Pouratian N, Scangos KW, Mayberg HS, Horn A, Johnson KA, Butson CR, Gilron R, de Hemptinne C, Wilt R, Yaroshinsky M, Little S, Starr P, Worrell G, Shirvalkar P, Chang E, Volkmann J, Muthuraman M, Groppa S, Kühn AA, Li L, Johnson M, Otto KJ, Raike R, Goetz S, Wu C, Silburn P, Cheeran B, Pathak YJ, Malekmohammadi M, Gunduz A, Wong JK, Cernera S, Wagle Shukla A, Ramirez-Zamora A, Deeb W, Patterson A, Foote KD, Okun MS. Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies. Front Hum Neurosci 2021; 15:644593. [PMID: 33953663 PMCID: PMC8092047 DOI: 10.3389/fnhum.2021.644593] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/10/2021] [Indexed: 12/20/2022] Open
Abstract
We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer’s disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.
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Affiliation(s)
- Vinata Vedam-Mai
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, United States.,Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
| | - James Giordano
- Department of Neurology and Neuroethics Studies Program, Georgetown University Medical Center, Washington, DC, United States
| | - Gabriel Lazaro-Munoz
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Winston Chiong
- Weill Institute for Neurosciences, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Nanthia Suthana
- Department of Neurosurgery, David Geffen School of Medicine and Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jean-Philippe Langevin
- Department of Neurosurgery, David Geffen School of Medicine and Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Neurosurgery Service, Department of Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, United States
| | - Jay Gill
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Wayne Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Nicole R Provenza
- School of Engineering, Brown University, Providence, RI, United States
| | - Casey H Halpern
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, United States
| | - Rajat S Shivacharan
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, United States
| | - Tricia N Cunningham
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, United States
| | - Sameer A Sheth
- Department of Neurological Surgery, Baylor College of Medicine, Houston, TX, United States
| | - Nader Pouratian
- Department of Neurosurgery, David Geffen School of Medicine and Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Katherine W Scangos
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
| | - Helen S Mayberg
- Department of Neurology and Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Andreas Horn
- Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité - University Medicine Berlin, Berlin, Germany
| | - Kara A Johnson
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States.,Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
| | - Christopher R Butson
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States.,Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
| | - Ro'ee Gilron
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Coralie de Hemptinne
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States.,Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Robert Wilt
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Maria Yaroshinsky
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Simon Little
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Philip Starr
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Greg Worrell
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Prasad Shirvalkar
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States.,Department of Anesthesiology (Pain Management) and Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Edward Chang
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Jens Volkmann
- Neurologischen Klinik Universitätsklinikum Würzburg, Würzburg, Germany
| | - Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Andrea A Kühn
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Matthew Johnson
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Kevin J Otto
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Robert Raike
- Restorative Therapies Group Implantables, Research and Core Technology, Medtronic, Minneapolis, MN, United States
| | - Steve Goetz
- Restorative Therapies Group Implantables, Research and Core Technology, Medtronic, Minneapolis, MN, United States
| | - Chengyuan Wu
- Department of Neurological Surgery, Thomas Jefferson University Hospitals, Philadelphia, PA, United States
| | - Peter Silburn
- Asia Pacific Centre for Neuromodulation, Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Binith Cheeran
- Neuromodulation Division, Abbott, Plano, TX, United States
| | - Yagna J Pathak
- Neuromodulation Division, Abbott, Plano, TX, United States
| | | | - Aysegul Gunduz
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States.,J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Joshua K Wong
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Stephanie Cernera
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States.,J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Aparna Wagle Shukla
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Adolfo Ramirez-Zamora
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Wissam Deeb
- Department of Neurology, University of Massachusetts, Worchester, MA, United States
| | - Addie Patterson
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Kelly D Foote
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Michael S Okun
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
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24
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Du T, Wang L, Liu W, Zhu G, Chen Y, Zhang J. Biomarkers and the Role of α-Synuclein in Parkinson's Disease. Front Aging Neurosci 2021; 13:645996. [PMID: 33833675 PMCID: PMC8021696 DOI: 10.3389/fnagi.2021.645996] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 03/05/2021] [Indexed: 12/13/2022] Open
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the presence of α-synuclein (α-Syn)-rich Lewy bodies (LBs) and the preferential loss of dopaminergic (DA) neurons in the substantia nigra (SN) pars compacta (SNpc). However, the widespread involvement of other central nervous systems (CNS) structures and peripheral tissues is now widely documented. The onset of the molecular and cellular neuropathology of PD likely occurs decades before the onset of the motor symptoms characteristic of PD, so early diagnosis of PD and adequate tracking of disease progression could significantly improve outcomes for patients. Because the clinical diagnosis of PD is challenging, misdiagnosis is common, which highlights the need for disease-specific and early-stage biomarkers. This review article aims to summarize useful biomarkers for the diagnosis of PD, as well as the biomarkers used to monitor disease progression. This review article describes the role of α-Syn in PD and how it could potentially be used as a biomarker for PD. Also, preclinical and clinical investigations encompassing genetics, immunology, fluid and tissue, imaging, as well as neurophysiology biomarkers are discussed. Knowledge of the novel biomarkers for preclinical detection and clinical evaluation will contribute to a deeper understanding of the disease mechanism, which should more effectively guide clinical applications.
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Affiliation(s)
- Tingting Du
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Le Wang
- Molecular Biology Laboratory for Neuropsychiatric Diseases, Department of Neurobiology, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China
| | - Weijin Liu
- Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Key Laboratory of Neural Regeneration and Repair, Beijing Key Laboratory on Parkinson’s Disease, Department of Neurobiology, School of Basic Medical Sciences, Capital Medical University, Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yingchuan Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing Municipal Science and Technology Commission, Beijing, China
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25
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Litvak V, Florin E, Tamás G, Groppa S, Muthuraman M. EEG and MEG primers for tracking DBS network effects. Neuroimage 2020; 224:117447. [PMID: 33059051 DOI: 10.1016/j.neuroimage.2020.117447] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 10/08/2020] [Accepted: 10/08/2020] [Indexed: 10/23/2022] Open
Abstract
Deep brain stimulation (DBS) is an effective treatment method for a range of neurological and psychiatric disorders. It involves implantation of stimulating electrodes in a precisely guided fashion into subcortical structures and, at a later stage, chronic stimulation of these structures with an implantable pulse generator. While the DBS surgery makes it possible to both record brain activity and stimulate parts of the brain that are difficult to reach with non-invasive techniques, electroencephalography (EEG) and magnetoencephalography (MEG) provide complementary information from other brain areas, which can be used to characterize brain networks targeted through DBS. This requires, however, the careful consideration of different types of artifacts in the data acquisition and the subsequent analyses. Here, we review both the technical issues associated with EEG/MEG recordings in DBS patients and the experimental findings to date. One major line of research is simultaneous recording of local field potentials (LFPs) from DBS targets and EEG/MEG. These studies revealed a set of cortico-subcortical coherent networks functioning at distinguishable physiological frequencies. Specific network responses were linked to clinical state, task or stimulation parameters. Another experimental approach is mapping of DBS-targeted networks in chronically implanted patients by recording EEG/MEG responses during stimulation. One can track responses evoked by single stimulation pulses or bursts as well as brain state shifts caused by DBS. These studies have the potential to provide biomarkers for network responses that can be adapted to guide stereotactic implantation or optimization of stimulation parameters. This is especially important for diseases where the clinical effect of DBS is delayed or develops slowly over time. The same biomarkers could also potentially be utilized for the online control of DBS network effects in the new generation of closed-loop stimulators that are currently entering clinical use. Through future studies, the use of network biomarkers may facilitate the integration of circuit physiology into clinical decision making.
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Affiliation(s)
- Vladimir Litvak
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Gertrúd Tamás
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Sergiu Groppa
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Muthuraman Muthuraman
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, 55131 Mainz, Germany.
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26
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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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27
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Gonzalez-Escamilla G, Muthuraman M, Ciolac D, Coenen VA, Schnitzler A, Groppa S. Neuroimaging and electrophysiology meet invasive neurostimulation for causal interrogations and modulations of brain states. Neuroimage 2020; 220:117144. [DOI: 10.1016/j.neuroimage.2020.117144] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/22/2020] [Accepted: 07/02/2020] [Indexed: 12/13/2022] Open
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28
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Little S, Brown P. Debugging Adaptive Deep Brain Stimulation for Parkinson's Disease. Mov Disord 2020; 35:555-561. [PMID: 32039501 PMCID: PMC7166127 DOI: 10.1002/mds.27996] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 01/22/2020] [Accepted: 01/27/2020] [Indexed: 12/20/2022] Open
Abstract
Deep brain stimulation (DBS) is a successful treatment for patients with Parkinson's disease. In adaptive DBS, stimulation is titrated according to feedback about clinical state and underlying pathophysiology. This contrasts with conventional stimulation, which is fixed and continuous. In acute trials, adaptive stimulation matches the efficacy of conventional stimulation while delivering about half the electrical energy. The latter means potentially fewer side-effects. The next step is to determine the long-term efficacy, efficiency, and side-effect profile of adaptive stimulation, and chronic trials are currently being considered by the medical devices industry. However, there are several different approaches to adaptive DBS, and several possible limitations have been highlighted. Here we review the findings to date to ascertain how and who to stimulate in chronic trials designed to establish the long-term utility of adaptive DBS. © 2020 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Simon Little
- Department of Movement Disorders and Neuromodulation, University of California San Francisco, San Francisco, California, USA
| | - Peter Brown
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Oxford, United Kingdom
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29
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LFP-Net: A deep learning framework to recognize human behavioral activities using brain STN-LFP signals. J Neurosci Methods 2020; 335:108621. [DOI: 10.1016/j.jneumeth.2020.108621] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 01/21/2020] [Accepted: 01/31/2020] [Indexed: 11/21/2022]
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30
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Krack P, Volkmann J, Tinkhauser G, Deuschl G. Deep Brain Stimulation in Movement Disorders: From Experimental Surgery to Evidence‐Based Therapy. Mov Disord 2019; 34:1795-1810. [DOI: 10.1002/mds.27860] [Citation(s) in RCA: 89] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 08/01/2019] [Accepted: 08/19/2019] [Indexed: 12/21/2022] Open
Affiliation(s)
- Paul Krack
- Department of Neurology Bern University Hospital and University of Bern Bern Switzerland
| | - Jens Volkmann
- Department of Neurology University Hospital and Julius‐Maximilian‐University Wuerzburg Germany
| | - Gerd Tinkhauser
- Department of Neurology Bern University Hospital and University of Bern Bern Switzerland
| | - Günther Deuschl
- Department of Neurology University Hospital Schleswig Holstein (UKSH), Kiel Campus; Christian‐Albrechts‐University Kiel Germany
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31
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Chen KS, Chen R. Invasive and Noninvasive Brain Stimulation in Parkinson's Disease: Clinical Effects and Future Perspectives. Clin Pharmacol Ther 2019; 106:763-775. [DOI: 10.1002/cpt.1542] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 05/07/2019] [Indexed: 01/18/2023]
Affiliation(s)
- Kai‐Hsiang Stanley Chen
- Krembil Research Institute University Health Network Toronto Ontario Canada
- Department of Neurology National Taiwan University Hospital Hsin‐Chu Branch Hsin‐Chu Taiwan
| | - Robert Chen
- Krembil Research Institute University Health Network Toronto Ontario Canada
- Division of Neurology Department of Medicine University of Toronto Toronto Ontario Canada
- Edmond J. Safra Program in Parkinson's Disease University Health Network Toronto Ontario Canada
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Tan H, Debarros J, He S, Pogosyan A, Aziz TZ, Huang Y, Wang S, Timmermann L, Visser-Vandewalle V, Pedrosa DJ, Green AL, Brown P. Decoding voluntary movements and postural tremor based on thalamic LFPs as a basis for closed-loop stimulation for essential tremor. Brain Stimul 2019; 12:858-867. [PMID: 30827864 PMCID: PMC6600875 DOI: 10.1016/j.brs.2019.02.011] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Revised: 02/17/2019] [Accepted: 02/18/2019] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND High frequency Deep brain stimulation (DBS) targeting motor thalamus is an effective therapy for essential tremor (ET). However, conventional continuous stimulation may deliver unnecessary current to the brain since tremor mainly affects voluntary movements and sustained postures in ET. OBJECTIVE We aim to decode both voluntary movements and the presence of postural tremor from the Local field potentials (LFPs) recorded from the electrode implanted in motor thalamus for stimulation, in order to close the loop for DBS so that stimulation could be delivered on demand, without the need for peripheral sensors or additional invasive electrodes. METHODS LFPs from the motor thalamus, surface electromyographic (EMG) signals and/or behavioural measurements were simultaneously recorded in seven ET patients during temporary lead externalisation 3-5 days after the first surgery for DBS when they performed different voluntary upper limb movements. Nine different patients were recorded during the surgery, when they were asked to lift their arms to trigger postural tremor. A machine learning based binary classifier was used to detect voluntary movements and postural tremor based on features extracted from thalamic LFPs. RESULTS Cross-validation demonstrated that both voluntary movements and postural tremor can be decoded with an average sensitivity of 0.8 and false detection rate of 0.2. Oscillatory activities in the beta frequency bands (13-23 Hz) and the theta frequency bands (4-7 Hz) contributed most to the decoding of movements and postural tremor, respectively, though incorporating features in different frequency bands using a machine learning approach increased the accuracy of decoding.
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Affiliation(s)
- Huiling Tan
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, OX1 3TH, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, Oxford, United Kingdom.
| | - Jean Debarros
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, OX1 3TH, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, Oxford, United Kingdom
| | - Shenghong He
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, OX1 3TH, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, Oxford, United Kingdom
| | - Alek Pogosyan
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, OX1 3TH, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, Oxford, United Kingdom
| | - Tipu Z Aziz
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Yongzhi Huang
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Shouyan Wang
- Neural and Intelligence Engineering Center, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Lars Timmermann
- Department of Neurology, University Hospital of Gießen and Marburg, Marburg, Germany
| | - Veerle Visser-Vandewalle
- Department of Stereotactic and Functional Neurosurgery, University Hospital Cologne, 50924, Cologne, Germany
| | - David J Pedrosa
- Department of Neurology, University Hospital of Gießen and Marburg, Marburg, Germany
| | - Alexander L Green
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Peter Brown
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, OX1 3TH, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, Oxford, United Kingdom.
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Wichmann T. Changing views of the pathophysiology of Parkinsonism. Mov Disord 2019; 34:1130-1143. [PMID: 31216379 DOI: 10.1002/mds.27741] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 05/15/2019] [Accepted: 05/20/2019] [Indexed: 12/11/2022] Open
Abstract
Studies of the pathophysiology of parkinsonism (specifically akinesia and bradykinesia) have a long history and primarily model the consequences of dopamine loss in the basal ganglia on the function of the basal ganglia/thalamocortical circuit(s). Changes of firing rates of individual nodes within these circuits were originally considered central to parkinsonism. However, this view has now given way to the belief that changes in firing patterns within the basal ganglia and related nuclei are more important, including the emergence of burst discharges, greater synchrony of firing between neighboring neurons, oscillatory activity patterns, and the excessive coupling of oscillatory activities at different frequencies. Primarily focusing on studies obtained in nonhuman primates and human patients with Parkinson's disease, this review summarizes the current state of this field and highlights several emerging areas of research, including studies of the impact of the heterogeneity of external pallidal neurons on parkinsonism, the importance of extrastriatal dopamine loss, parkinsonism-associated synaptic and morphologic plasticity, and the potential role(s) of the cerebellum and brainstem in the motor dysfunction of Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Thomas Wichmann
- Department of Neurology/School of Medicine and Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, USA
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Shah SA, Tan H, Tinkhauser G, Brown P. Towards Real-Time, Continuous Decoding of Gripping Force From Deep Brain Local Field Potentials. IEEE Trans Neural Syst Rehabil Eng 2019; 26:1460-1468. [PMID: 29985155 DOI: 10.1109/tnsre.2018.2837500] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Lack of force information and longevity issues are impediments to the successful translation of brain-computer interface systems for prosthetic control from experimental settings to widespread clinical application. The ability to decode force using deep brain stimulation electrodes in the subthalamic nucleus (STN) of the basal ganglia provides an opportunity to address these limitations. This paper explores the use of various classes of algorithms (Wiener filter, Wiener-Cascade model, Kalman filter, and dynamic neural networks) and recommends the use of a Wiener-Cascade model for decoding force from STN. This recommendation is influenced by a combination of accuracy and practical considerations to enable real-time, continuous operation. This paper demonstrates an ability to decode a continuous signal (force) from the STN in real time, allowing the possibility of decoding more than two states from the brain at low latency.
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Babiloni C, Del Percio C, Lizio R, Noce G, Lopez S, Soricelli A, Ferri R, Pascarelli MT, Catania V, Nobili F, Arnaldi D, Famà F, Orzi F, Buttinelli C, Giubilei F, Bonanni L, Franciotti R, Onofrj M, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Fraioli L, Parnetti L, Farotti L, Pievani M, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Yener G, Emek-Savaş DD, Triggiani AI, Taylor JP, McKeith I, Stocchi F, Vacca L, Frisoni GB, De Pandis MF. Levodopa may affect cortical excitability in Parkinson's disease patients with cognitive deficits as revealed by reduced activity of cortical sources of resting state electroencephalographic rhythms. Neurobiol Aging 2019; 73:9-20. [DOI: 10.1016/j.neurobiolaging.2018.08.010] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 08/07/2018] [Accepted: 08/08/2018] [Indexed: 10/28/2022]
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36
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Zhao D, Sun Q, Cheng S, He M, Chen X, Hou X. Extraction of Parkinson’s Disease-Related Features from Local Field Potentials for Adaptive Deep Brain Stimulation. NEUROPHYSIOLOGY+ 2018. [DOI: 10.1007/s11062-018-9717-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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37
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Mohammed A, Bayford R, Demosthenous A. Toward adaptive deep brain stimulation in Parkinson's disease: a review. Neurodegener Dis Manag 2018; 8:115-136. [DOI: 10.2217/nmt-2017-0050] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Clinical deep brain stimulation (DBS) is now regarded as the therapeutic intervention of choice at the advanced stages of Parkinson's disease. However, some major challenges of DBS are stimulation induced side effects and limited pacemaker battery life. Side effects and shortening of pacemaker battery life are mainly as a result of continuous stimulation and poor stimulation focus. These drawbacks can be mitigated using adaptive DBS (aDBS) schemes. Side effects resulting from continuous stimulation can be reduced through adaptive control using closed-loop feedback, while those due to poor stimulation focus can be mitigated through spatial adaptation. Other advantages of aDBS include automatic, rather than manual, initial adjustment and programming, and long-term adjustments to maintain stimulation parameters with changes in patient's condition. Both result in improved efficacy. This review focuses on the major areas that are essential in driving technological advances for the various aDBS schemes. Their challenges, prospects and progress so far are analyzed. In addition, important advances and milestones in state-of-the-art aDBS schemes are highlighted – both for closed-loop adaption and spatial adaption. With perspectives and future potentials of DBS provided at the end.
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Affiliation(s)
- Ameer Mohammed
- Department of Electronic & Electrical Engineering, University College London, Torrington Place, London WC1E 7JE, UK
| | - Richard Bayford
- Department of Natural Sciences, Middlesex University, The Burroughs, London NW4 6BT, UK
| | - Andreas Demosthenous
- Department of Electronic & Electrical Engineering, University College London, Torrington Place, London WC1E 7JE, UK
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38
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A hierarchical structure for human behavior classification using STN local field potentials. J Neurosci Methods 2018; 293:254-263. [DOI: 10.1016/j.jneumeth.2017.10.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2017] [Revised: 09/29/2017] [Accepted: 10/02/2017] [Indexed: 11/23/2022]
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Marceglia S, Rosa M, Servello D, Porta M, Barbieri S, Moro E, Priori A. Adaptive Deep Brain Stimulation (aDBS) for Tourette Syndrome. Brain Sci 2017; 8:E4. [PMID: 29295486 PMCID: PMC5789335 DOI: 10.3390/brainsci8010004] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 12/12/2017] [Accepted: 12/13/2017] [Indexed: 12/16/2022] Open
Abstract
Deep brain stimulation (DBS) has emerged as a novel therapy for the treatment of several movement and neuropsychiatric disorders, and may also be suitable for the treatment of Tourette syndrome (TS). The main DBS targets used to date in patients with TS are located within the basal ganglia-thalamo-cortical circuit involved in the pathophysiology of this syndrome. They include the ventralis oralis/centromedian-parafascicular (Vo/CM-Pf) nucleus of the thalamus and the nucleus accumbens. Current DBS treatments deliver continuous electrical stimulation and are not designed to adapt to the patient's symptoms, thereby contributing to unwanted side effects. Moreover, continuous DBS can lead to rapid battery depletion, which necessitates frequent battery replacement surgeries. Adaptive deep brain stimulation (aDBS), which is controlled based on neurophysiological biomarkers, is considered one of the most promising approaches to optimize clinical benefits and to limit the side effects of DBS. aDBS consists of a closed-loop system designed to measure and analyse a control variable reflecting the patient's clinical condition and to modify on-line stimulation settings to improve treatment efficacy. Local field potentials (LFPs), which are sums of pre- and post-synaptic activity arising from large neuronal populations, directly recorded from electrodes implanted for DBS can theoretically represent a reliable correlate of clinical status in patients with TS. The well-established LFP-clinical correlations in patients with Parkinson's disease reported in the last few years provide the rationale for developing and implementing new aDBS devices whose efficacies are under evaluation in humans. Only a few studies have investigated LFP activity recorded from DBS target structures and the relationship of this activity to clinical symptoms in TS. Here, we review the available literature supporting the feasibility of an LFP-based aDBS approach in patients with TS. In addition, to increase such knowledge, we report explorative findings regarding LFP data recently acquired and analysed in patients with TS after DBS electrode implantation at rest, during voluntary and involuntary movements (tics), and during ongoing DBS. Data available up to now suggest that patients with TS have oscillatory patterns specifically associated with the part of the brain they are recorded from, and thereby with clinical manifestations. The Vo/CM-Pf nucleus of the thalamus is involved in movement execution and the pathophysiology of TS. Moreover, the oscillatory patterns in TS are specifically modulated by DBS treatment, as reflected by improvements in TS symptoms. These findings suggest that LFPs recorded from DBS targets may be used to control new aDBS devices capable of adaptive stimulation responsive to the symptoms of TS.
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Affiliation(s)
- Sara Marceglia
- Clinical Center for Neurostimulation, Neurotechnology and Movement Disorders, Fondazione Istituto Ricovero e Cura a Carattere Scientifico (IRCCS) Ca' Granda, Ospedale Maggiore Policlinico, Milan 20122, Italy.
- Dipartimento di Ingegneria e Architettura, Università degli Studi di Trieste, Trieste 34127, Italy.
| | - Manuela Rosa
- Clinical Center for Neurostimulation, Neurotechnology and Movement Disorders, Fondazione Istituto Ricovero e Cura a Carattere Scientifico (IRCCS) Ca' Granda, Ospedale Maggiore Policlinico, Milan 20122, Italy.
| | - Domenico Servello
- Functional Neurosurgery Unit, Galeazzi Hospital and Tourette Center, Milan 20161, Italy.
| | - Mauro Porta
- Functional Neurosurgery Unit, Galeazzi Hospital and Tourette Center, Milan 20161, Italy.
| | - Sergio Barbieri
- Clinical Center for Neurostimulation, Neurotechnology and Movement Disorders, Fondazione Istituto Ricovero e Cura a Carattere Scientifico (IRCCS) Ca' Granda, Ospedale Maggiore Policlinico, Milan 20122, Italy.
| | - Elena Moro
- Division of Neurology, Centre Hospitalier Universitaire de Grenoble, CS 10217, 38043 Grenoble, France.
| | - Alberto Priori
- "Aldo Ravelli" Center for Neurotechnology and Experimental Brain Therapeutics, University of Milan, Milan 20142 , Italy.
- Department of Health Sciences, University of Milan & ASST Santi Paolo e Carlo, Milan 20142, Italy.
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40
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Parastarfeizabadi M, Kouzani AZ. Advances in closed-loop deep brain stimulation devices. J Neuroeng Rehabil 2017; 14:79. [PMID: 28800738 PMCID: PMC5553781 DOI: 10.1186/s12984-017-0295-1] [Citation(s) in RCA: 117] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Accepted: 08/04/2017] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Millions of patients around the world are affected by neurological and psychiatric disorders. Deep brain stimulation (DBS) is a device-based therapy that could have fewer side-effects and higher efficiencies in drug-resistant patients compared to other therapeutic options such as pharmacological approaches. Thus far, several efforts have been made to incorporate a feedback loop into DBS devices to make them operate in a closed-loop manner. METHODS This paper presents a comprehensive investigation into the existing research-based and commercial closed-loop DBS devices. It describes a brief history of closed-loop DBS techniques, biomarkers and algorithms used for closing the feedback loop, components of the current research-based and commercial closed-loop DBS devices, and advancements and challenges in this field of research. This review also includes a comparison of the closed-loop DBS devices and provides the future directions of this area of research. RESULTS Although we are in the early stages of the closed-loop DBS approach, there have been fruitful efforts in design and development of closed-loop DBS devices. To date, only one commercial closed-loop DBS device has been manufactured. However, this system does not have an intelligent and patient dependent control algorithm. A closed-loop DBS device requires a control algorithm to learn and optimize the stimulation parameters according to the brain clinical state. CONCLUSIONS The promising clinical effects of open-loop DBS have been demonstrated, indicating DBS as a pioneer technology and treatment option to serve neurological patients. However, like other commercial devices, DBS needs to be automated and modernized.
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Affiliation(s)
| | - Abbas Z. Kouzani
- School of Engineering, Deakin University, Waurn Ponds, VIC 3216 Australia
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41
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Shah SA, Brown P. Decoding force from deep brain electrodes in Parkinsonian patients. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2016:5717-5720. [PMID: 28269553 DOI: 10.1109/embc.2016.7592025] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Limitations of many Brain Machine Interface (BMI) systems using invasive electrodes include reliance on single neurons and decoding limited to kinematics only. This study investigates whether force-related information is present in the local field potential (LFP) recorded with deep brain electrodes using data from 14 patients with Parkinson's disease. A classifier based on logistic regression (LR) is developed to classify various force stages, using 10-fold cross validation. Least Absolute and Shrinkage Operator (Lasso) is then employed in order to identify the features with the most predictivity. The results show that force-related information is present in the LFP, and it is possible to distinguish between various force stages using certain frequency-domain (delta, beta, gamma) and time-domain (mobility) features in real-time.
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42
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Steiner LA, Neumann WJ, Staub-Bartelt F, Herz DM, Tan H, Pogosyan A, Kuhn AA, Brown P. Subthalamic beta dynamics mirror Parkinsonian bradykinesia months after neurostimulator implantation. Mov Disord 2017. [PMID: 28639263 PMCID: PMC5575541 DOI: 10.1002/mds.27068] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Background Exaggerated oscillatory activity in the beta frequency band in the subthalamic nucleus has been suggested to be related to bradykinesia in Parkinson's disease (PD). However, studies seeking correlations between such activity in the local field potential and motor performance have been limited to the immediate postoperative period, which may be confounded by a stun effect that leads to the temporary alleviation of PD deficits. Methods Local field potentials were recorded simultaneously with motor performance in PD patients several months after neurostimulator implantation. This was enabled by the chronic implantation of a pulse generator with the capacity to record and transmit local field potentials from deep brain stimulation electrodes. Specifically, we investigated oscillatory beta power dynamics and objective measures of bradykinesia during an upper limb alternating pronation and supination task in 9 patients. Results Although beta power was suppressed during continuously repeated movements, this suppression progressively diminished over time in tandem with a progressive decrement in the frequency and amplitude of movements. The relationship between changes within local field potentials and movement parameters was significant across patients, and not present for theta/alpha frequencies (5‐12 Hz). Change in movement frequency furthermore related to beta power dynamics within patients. Conclusions Changes in beta power are linked to changes in movement performance and the sequence effect of bradykinesia months after neurostimulator implantation. These findings provide further evidence that beta power may serve as a biomarker for bradykinesia and provide a suitable substrate for feedback control in chronic adaptive deep brain stimulation. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Leon Amadeus Steiner
- Department of Neurology, Charité, Campus Virchow Klinikum, University Medicine Berlin, Berlin, Germany.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Wolf-Julian Neumann
- Department of Neurology, Charité, Campus Virchow Klinikum, University Medicine Berlin, Berlin, Germany
| | - Franziska Staub-Bartelt
- Department of Neurology, Charité, Campus Virchow Klinikum, University Medicine Berlin, Berlin, Germany
| | - Damian M Herz
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Huiling Tan
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Alek Pogosyan
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Andrea A Kuhn
- Department of Neurology, Charité, Campus Virchow Klinikum, University Medicine Berlin, Berlin, Germany.,NeuroCure, Charité, University Medicine Berlin, Berlin, Germany
| | - Peter Brown
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK
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43
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Shah SA, Tan H, Brown P. Continuous Force Decoding from Deep Brain Local Field Potentials for Brain Computer Interfacing. INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING : [PROCEEDINGS]. INTERNATIONAL IEEE EMBS CONFERENCE ON NEURAL ENGINEERING 2017; 2017:371-374. [PMID: 28819547 DOI: 10.1109/ner.2017.8008367] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Current Brain Computer Interface (BCI) systems are limited by relying on neuronal spikes and decoding limited to kinematics only. For a BCI system to be practically useful, it should be able to decode brain information on a continuous basis with low latency. This study investigates if force can be decoded from local field potentials (LFP) recorded with deep brain electrodes located at the Subthalamic nucleus (STN) using data from 5 patients with Parkinson's disease, on a continuous basis with low latency. A Wiener-Cascade (WC) model based decoder was proposed using both time-domain and frequency-domain features. The results suggest that high gamma band (300-500Hz) activity, in addition to the beta (13-30Hz) and gamma band (55-90Hz) activity is the most informative for force prediction but combining all features led to better decoding performance. Furthermore, LFP signals preceding the force output by up to 1256 milliseconds were found to be predictive of the force output.
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Affiliation(s)
- Syed A Shah
- MRC Brain Network Dynamics Unit and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU United Kingdom
| | - Huiling Tan
- MRC Brain Network Dynamics Unit and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU United Kingdom
| | - Peter Brown
- MRC Brain Network Dynamics Unit and Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU United Kingdom
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Risk of Infection After Local Field Potential Recording from Externalized Deep Brain Stimulation Leads in Parkinson's Disease. World Neurosurg 2017; 97:64-69. [DOI: 10.1016/j.wneu.2016.09.069] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Revised: 09/14/2016] [Accepted: 09/16/2016] [Indexed: 11/22/2022]
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45
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Hanrahan SJ, Nedrud JJ, Davidson BS, Farris S, Giroux M, Haug A, Mahoor MH, Silverman AK, Zhang JJ, Hebb AO. Long-Term Task- and Dopamine-Dependent Dynamics of Subthalamic Local Field Potentials in Parkinson's Disease. Brain Sci 2016; 6:E57. [PMID: 27916831 PMCID: PMC5187571 DOI: 10.3390/brainsci6040057] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2016] [Revised: 11/02/2016] [Accepted: 11/17/2016] [Indexed: 11/29/2022] Open
Abstract
Subthalamic nucleus (STN) local field potentials (LFP) are neural signals that have been shown to reveal motor and language behavior, as well as pathological parkinsonian states. We use a research-grade implantable neurostimulator (INS) with data collection capabilities to record STN-LFP outside the operating room to determine the reliability of the signals over time and assess their dynamics with respect to behavior and dopaminergic medication. Seven subjects were implanted with the recording augmented deep brain stimulation (DBS) system, and bilateral STN-LFP recordings were collected in the clinic over twelve months. Subjects were cued to perform voluntary motor and language behaviors in on and off medication states. The STN-LFP recorded with the INS demonstrated behavior-modulated desynchronization of beta frequency (13-30 Hz) and synchronization of low gamma frequency (35-70 Hz) oscillations. Dopaminergic medication did not diminish the relative beta frequency oscillatory desynchronization with movement. However, movement-related gamma frequency oscillatory synchronization was only observed in the medication on state. We observed significant inter-subject variability, but observed consistent STN-LFP activity across recording systems and over a one-year period for each subject. These findings demonstrate that an INS system can provide robust STN-LFP recordings in ambulatory patients, allowing for these signals to be recorded in settings that better represent natural environments in which patients are in a variety of medication states.
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Affiliation(s)
| | | | - Bradley S Davidson
- Department of Mechanical and Materials Engineering, University of Denver, Denver, CO 80208, USA.
| | - Sierra Farris
- Movement and Neuroperformance Center of Colorado, Englewood, CO 80113, USA.
| | - Monique Giroux
- Movement and Neuroperformance Center of Colorado, Englewood, CO 80113, USA.
| | - Aaron Haug
- Blue Sky Neurology, Englewood, CO 80113, USA.
| | - Mohammad H Mahoor
- Department of Electrical and Computer Engineering, University of Denver, CO 80208, USA.
| | - Anne K Silverman
- Department of Mechanical Engineering, Colorado School of Mines, Golden, CO 80401, USA.
| | - Jun Jason Zhang
- Department of Electrical and Computer Engineering, University of Denver, CO 80208, USA.
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Tan H, Pogosyan A, Ashkan K, Green AL, Aziz T, Foltynie T, Limousin P, Zrinzo L, Hariz M, Brown P. Decoding gripping force based on local field potentials recorded from subthalamic nucleus in humans. eLife 2016; 5. [PMID: 27855780 PMCID: PMC5148608 DOI: 10.7554/elife.19089] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2016] [Accepted: 11/14/2016] [Indexed: 01/16/2023] Open
Abstract
The basal ganglia are known to be involved in the planning, execution and control of gripping force and movement vigour. Here we aim to define the nature of the basal ganglia control signal for force and to decode gripping force based on local field potential (LFP) activities recorded from the subthalamic nucleus (STN) in patients with deep brain stimulation (DBS) electrodes. We found that STN LFP activities in the gamma (55-90 Hz) and beta (13-30m Hz) bands were most informative about gripping force, and that a first order dynamic linear model with these STN LFP features as inputs can be used to decode the temporal profile of gripping force. Our results enhance the understanding of how the basal ganglia control gripping force, and also suggest that deep brain LFPs could potentially be used to decode movement parameters related to force and movement vigour for the development of advanced human-machine interfaces.
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Affiliation(s)
- Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Alek Pogosyan
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Keyoumars Ashkan
- Department of Neurosurgery, Kings College Hospital, Kings College London, London, England
| | - Alexander L Green
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Tipu Aziz
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Thomas Foltynie
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Patricia Limousin
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Ludvic Zrinzo
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Marwan Hariz
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Peter Brown
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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Qian X, Chen Y, Feng Y, Ma B, Hao H, Li L. A Method for Removal of Deep Brain Stimulation Artifact From Local Field Potentials. IEEE Trans Neural Syst Rehabil Eng 2016; 25:2217-2226. [PMID: 28113981 DOI: 10.1109/tnsre.2016.2613412] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
This paper presents a signal processing method for the electrophysiology simultaneously recorded during deep brain stimulation (DBS) as a research tool. Regarding the local field potential (LFP) signals recorded during stimulation, a novel method was proposed for removal of stimulation artifacts caused by the much stronger stimulating pulse compared to typical LFP. This artifact suppression method was tested and evaluated in an in vitro situation. The results indicate that the stimulation artifacts are well suppressed by this method. Secondly, this method was tested in vivo in Parkinson's disease (PD) patients. It was used to process the LFP signals recorded intraoperatively from PD patients to preliminarily explore the quantitative dependencies of beta band synchronization variations in the subthalamic nucleus (STNs) on the applied DBS parameters, including stimulation voltage, frequency and pulse width. The results confirm that DBS therapy can suppress excessive beta frequency activity and that the degree of attenuation increases with increasing DBS voltage within a range of 1-3 V and increasing DBS frequency within a range of 60-120 Hz. The proposed artifact suppression method provides technical support for exploring the direct effect of electrical stimulation on the brain activities.
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Little S, Beudel M, Zrinzo L, Foltynie T, Limousin P, Hariz M, Neal S, Cheeran B, Cagnan H, Gratwicke J, Aziz TZ, Pogosyan A, Brown P. Bilateral adaptive deep brain stimulation is effective in Parkinson's disease. J Neurol Neurosurg Psychiatry 2016; 87:717-21. [PMID: 26424898 PMCID: PMC4941128 DOI: 10.1136/jnnp-2015-310972] [Citation(s) in RCA: 207] [Impact Index Per Article: 25.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Accepted: 08/17/2015] [Indexed: 11/26/2022]
Abstract
INTRODUCTION & OBJECTIVES Adaptive deep brain stimulation (aDBS) uses feedback from brain signals to guide stimulation. A recent acute trial of unilateral aDBS showed that aDBS can lead to substantial improvements in contralateral hemibody Unified Parkinson's Disease Rating Scale (UPDRS) motor scores and may be superior to conventional continuous DBS in Parkinson's disease (PD). We test whether potential benefits are retained with bilateral aDBS and in the face of concurrent medication. METHODS We applied bilateral aDBS in 4 patients with PD undergoing DBS of the subthalamic nucleus. aDBS was delivered bilaterally with independent triggering of stimulation according to the amplitude of β activity at the corresponding electrode. Mean stimulation voltage was 3.0±0.1 volts. Motor assessments consisted of double-blinded video-taped motor UPDRS scores that included both limb and axial features. RESULTS UPDRS scores were 43% (p=0.04; Cohen's d=1.62) better with aDBS than without stimulation. Motor improvement with aDBS occurred despite an average time on stimulation (ToS) of only 45%. Levodopa was well tolerated during aDBS and led to further reductions in ToS. CONCLUSION Bilateral aDBS can improve both axial and limb symptoms and can track the need for stimulation across drug states.
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Affiliation(s)
- Simon Little
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Martijn Beudel
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK Department of Neurology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Ludvic Zrinzo
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience & Movement Disorders, UCL Institute of Neurology, London, UK
| | - Thomas Foltynie
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience & Movement Disorders, UCL Institute of Neurology, London, UK
| | - Patricia Limousin
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience & Movement Disorders, UCL Institute of Neurology, London, UK
| | - Marwan Hariz
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience & Movement Disorders, UCL Institute of Neurology, London, UK
| | - Spencer Neal
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience & Movement Disorders, UCL Institute of Neurology, London, UK
| | - Binith Cheeran
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Hayriye Cagnan
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - James Gratwicke
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience & Movement Disorders, UCL Institute of Neurology, London, UK
| | - Tipu Z Aziz
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK Nuffield Department of Surgical Sciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Alex Pogosyan
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK The Medical Research Council Brain Networks Dynamics Unit, University of Oxford, Oxford, UK
| | - Peter Brown
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK The Medical Research Council Brain Networks Dynamics Unit, University of Oxford, Oxford, UK
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Arlotti M, Rosa M, Marceglia S, Barbieri S, Priori A. The adaptive deep brain stimulation challenge. Parkinsonism Relat Disord 2016; 28:12-7. [PMID: 27079257 DOI: 10.1016/j.parkreldis.2016.03.020] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Revised: 03/25/2016] [Accepted: 03/28/2016] [Indexed: 01/17/2023]
Abstract
Sub-optimal clinical outcomes of conventional deep brain stimulation (cDBS) in treating Parkinson's Disease (PD) have boosted the development of new solutions to improve DBS therapy. Adaptive DBS (aDBS), consisting of closed-loop, real-time changing of stimulation parameters according to the patient's clinical state, promises to achieve this goal and is attracting increasing interest in overcoming all of the challenges posed by its development and adoption. In the design, implementation, and application of aDBS, the choice of the control variable and of the control algorithm represents the core challenge. The proposed approaches, in fact, differ in the choice of the control variable and control policy, in the system design and its technological limits, in the patient's target symptom, and in the surgical procedure needed. Here, we review the current proposals for aDBS systems, focusing on the choice of the control variable and its advantages and drawbacks, thus providing a general overview of the possible pathways for the clinical translation of aDBS with its benefits, limitations and unsolved issues.
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Affiliation(s)
- Mattia Arlotti
- Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Electronics, Computer Science and Systems, University of Bologna, Cesena, Italy
| | - Manuela Rosa
- Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Sara Marceglia
- Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | - Sergio Barbieri
- Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Unità di Neurofisiopatologia, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico di Milano, Milan, Italy
| | - Alberto Priori
- Department of Health Sciences, University of Milan, Fondazione IRCCS Ca'Granda, Milan, Italy.
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50
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Arlotti M, Rossi L, Rosa M, Marceglia S, Priori A. An external portable device for adaptive deep brain stimulation (aDBS) clinical research in advanced Parkinson's Disease. Med Eng Phys 2016; 38:498-505. [PMID: 27029510 DOI: 10.1016/j.medengphy.2016.02.007] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Revised: 12/14/2015] [Accepted: 02/22/2016] [Indexed: 11/18/2022]
Abstract
Compared to conventional deep brain stimulation (DBS) for patients with Parkinson's Disease (PD), the newer approach of adaptive DBS (aDBS), regulating stimulation on the basis of the patient's clinical state, promises to achieve better clinical outcomes, avoid adverse-effects and save time for tuning parameters. A remaining challenge before aDBS comes into practical use is to prove its feasibility and its effectiveness in larger groups of patients and in more ecological conditions. We developed an external portable aDBS system prototype designed for clinical testing in freely-moving PD patients with externalized DBS electrodes. From a single-channel bipolar artifact-free recording, it analyses local field potentials (LFPs), during ongoing DBS for tuning stimulation parameters, independent from the specific feedback algorithm implemented. We validated the aDBS system in vitro, by testing both its sensing and closed-loop stimulation capabilities, and then tested it in vivo, focusing on the sensing capabilities. By applying the aDBS system prototype in a patient with PD, we provided evidence that it can track levodopa and DBS-induced LFP spectral power changes among different patient's clinical states. Our system, intended for testing LFP-based feedback strategies for aDBS, should help understanding how and whether aDBS therapy works in PD and indicating future technical and clinical advances.
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Affiliation(s)
- Mattia Arlotti
- Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Electronics, Computer Science and Systems, University of Bologna, Cesena, Italy.
| | | | - Manuela Rosa
- Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Sara Marceglia
- Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Engineering and Architecture, University of Trieste, Trieste, Italy.
| | - Alberto Priori
- Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Health Sciences, University of Milan, Ospedale San Paolo, Milan, Italy.
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