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Suresh V, Dave T, Ghosh S, Jena R, Sanker V. Deep brain stimulation in Parkinson's disease: A scientometric and bibliometric analysis, trends, and research hotspots. Medicine (Baltimore) 2024; 103:e38152. [PMID: 38758903 PMCID: PMC11098246 DOI: 10.1097/md.0000000000038152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/16/2024] [Indexed: 05/19/2024] Open
Abstract
Parkinson disease (PD), a prevalent neurodegenerative ailment in the elderly, relies mainly on pharmacotherapy, yet deep brain stimulation (DBS) emerges as a vital remedy for refractory cases. This study performs a bibliometric analysis on DBS in PD, delving into research trends and study impact to offer comprehensive insights for researchers, clinicians, and policymakers, illuminating the current state and evolutionary trajectory of research in this domain. A systematic search on March 13, 2023, in the Scopus database utilized keywords like "Parkinson disease," "PD," "Parkinsonism," "Deep brain stimulation," and "DBS." The top 1000 highly cited publications on DBS in PD underwent scientometric analysis via VOS Viewer and R Studio's Bibliometrix package, covering publication characteristics, co-authorship, keyword co-occurrence, thematic clustering, and trend topics. The bibliometric analysis spanned 1984 to 2021, involving 1000 cited articles from 202 sources. The average number of citations per document were 140.9, with 31,854 references. "Movement Disorders" led in publications (n = 98), followed by "Brain" (n = 78) and "Neurology" (n = 65). The University of Oxford featured prominently. Thematic keyword clustering identified 9 core research areas, such as neuropsychological function and motor circuit electrophysiology. The shift from historical neurosurgical procedures to contemporary focuses like "beta oscillations" and "neuroethics" was evident. The bibliometric analysis emphasizes UK and US dominance, outlining 9 key research areas pivotal for reshaping Parkinson treatment. A discernible shift from invasive neurosurgery to DBS is observed. The call for personalized DBS, integration with NIBS, and exploration of innovative avenues marks the trajectory for future research.
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Affiliation(s)
- Vinay Suresh
- King George’s Medical University, Lucknow, India
| | - Tirth Dave
- Bukovinian State Medical University, Chernivtsi, Ukraine
| | | | - Rahul Jena
- Bharati Vidyapeeth Medical College, Pune, India
| | - Vivek Sanker
- Society of Brain Mapping and Therapeutics, Los Angeles, CA
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2
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Bath JE, Wang DD. Unraveling the threads of stability: A review of the neurophysiology of postural control in Parkinson's disease. Neurotherapeutics 2024; 21:e00354. [PMID: 38579454 PMCID: PMC11000188 DOI: 10.1016/j.neurot.2024.e00354] [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: 11/30/2023] [Revised: 03/18/2024] [Accepted: 03/23/2024] [Indexed: 04/07/2024] Open
Abstract
Postural instability is a detrimental and often treatment-refractory symptom of Parkinson's disease. While many existing studies quantify the biomechanical deficits among various postural domains (static, anticipatory, and reactive) in this population, less is known regarding the neural network dysfunctions underlying these phenomena. This review will summarize current studies on the cortical and subcortical neural activities during postural responses in healthy subjects and those with Parkinson's disease. We will also review the effects of current therapies, including neuromodulation and feedback-based wearable devices, on postural instability symptoms. With recent advances in implantable devices that allow chronic, ambulatory neural data collection from patients with Parkinson's disease, combined with sensors that can quantify biomechanical measurements of postural responses, future work using these devices will enable better understanding of the neural mechanisms of postural control. Bridging this knowledge gap will be the critical first step towards developing novel neuromodulatory interventions to enhance the treatment of postural instability in Parkinson's disease.
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Affiliation(s)
- Jessica E Bath
- Department of Physical Therapy & Rehabilitation Science, University of California, San Francisco, USA; Department of Neurological Surgery, University of California, San Francisco, USA
| | - Doris D Wang
- Department of Neurological Surgery, University of California, San Francisco, USA.
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3
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Farokhniaee A, Palmisano C, Del Vecchio Del Vecchio J, Pezzoli G, Volkmann J, Isaias IU. Gait-related beta-gamma phase amplitude coupling in the subthalamic nucleus of parkinsonian patients. Sci Rep 2024; 14:6674. [PMID: 38509158 PMCID: PMC10954750 DOI: 10.1038/s41598-024-57252-2] [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: 06/15/2023] [Accepted: 03/15/2024] [Indexed: 03/22/2024] Open
Abstract
Analysis of coupling between the phases and amplitudes of neural oscillations has gained increasing attention as an important mechanism for large-scale brain network dynamics. In Parkinson's disease (PD), preliminary evidence indicates abnormal beta-phase coupling to gamma-amplitude in different brain areas, including the subthalamic nucleus (STN). We analyzed bilateral STN local field potentials (LFPs) in eight subjects with PD chronically implanted with deep brain stimulation electrodes during upright quiet standing and unperturbed walking. Phase-amplitude coupling (PAC) was computed using the Kullback-Liebler method, based on the modulation index. Neurophysiological recordings were correlated with clinical and kinematic measurements and individual molecular brain imaging studies ([123I]FP-CIT and single-photon emission computed tomography). We showed a dopamine-related increase in subthalamic beta-gamma PAC from standing to walking. Patients with poor PAC modulation and low PAC during walking spent significantly more time in the stance and double support phase of the gait cycle. Our results provide new insights into the subthalamic contribution to human gait and suggest cross-frequency coupling as a gateway mechanism to convey patient-specific information of motor control for human locomotion.
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Affiliation(s)
- AmirAli Farokhniaee
- Fondazione Grigioni Per Il Morbo Di Parkinson, Via Gianfranco Zuretti 35, 20125, Milano, Italy.
- Parkinson Institute Milan, ASST G. Pini CTO, Via Bignami 1, 20126, Milano, Italy.
| | - Chiara Palmisano
- Department of Neurology, University Hospital of Würzburg, and Julius Maximilian University of Würzburg, Josef-Schneider-Straße 11, 97080, Würzburg, Germany
| | - Jasmin Del Vecchio Del Vecchio
- Department of Neurology, University Hospital of Würzburg, and Julius Maximilian University of Würzburg, Josef-Schneider-Straße 11, 97080, Würzburg, Germany
| | - Gianni Pezzoli
- Fondazione Grigioni Per Il Morbo Di Parkinson, Via Gianfranco Zuretti 35, 20125, Milano, Italy
- Parkinson Institute Milan, ASST G. Pini CTO, Via Bignami 1, 20126, Milano, Italy
| | - Jens Volkmann
- Department of Neurology, University Hospital of Würzburg, and Julius Maximilian University of Würzburg, Josef-Schneider-Straße 11, 97080, Würzburg, Germany
| | - Ioannis U Isaias
- Parkinson Institute Milan, ASST G. Pini CTO, Via Bignami 1, 20126, Milano, Italy
- Department of Neurology, University Hospital of Würzburg, and Julius Maximilian University of Würzburg, Josef-Schneider-Straße 11, 97080, Würzburg, Germany
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4
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Averna A, Coelli S, Ferrara R, Cerutti S, Priori A, Bianchi AM. Entropy and fractal analysis of brain-related neurophysiological signals in Alzheimer's and Parkinson's disease. J Neural Eng 2023; 20:051001. [PMID: 37746822 DOI: 10.1088/1741-2552/acf8fa] [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: 12/16/2022] [Accepted: 09/12/2023] [Indexed: 09/26/2023]
Abstract
Brain-related neuronal recordings, such as local field potential, electroencephalogram and magnetoencephalogram, offer the opportunity to study the complexity of the human brain at different spatial and temporal scales. The complex properties of neuronal signals are intrinsically related to the concept of 'scale-free' behavior and irregular dynamic, which cannot be fully described through standard linear methods, but can be measured by nonlinear indexes. A remarkable application of these analysis methods on electrophysiological recordings is the deep comprehension of the pathophysiology of neurodegenerative diseases, that has been shown to be associated to changes in brain activity complexity. In particular, a decrease of global complexity has been associated to Alzheimer's disease, while a local increase of brain signals complexity characterizes Parkinson's disease. Despite the recent proliferation of studies using fractal and entropy-based analysis, the application of these techniques is still far from clinical practice, due to the lack of an agreement about their correct estimation and a conclusive and shared interpretation. Along with the aim of helping towards the realization of a multidisciplinary audience to approach nonlinear methods based on the concepts of fractality and irregularity, this survey describes the implementation and proper employment of the mostly known and applied indexes in the context of Alzheimer's and Parkinson's diseases.
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Affiliation(s)
- Alberto Averna
- Department of Neurology, Bern University Hospital, University of Bern, Bern, Switzerland
- CRC 'Aldo Ravelli' per le Neurotecnologie e le Terapie Neurologiche Sperimentali, Dipartimento di Scienze della Salute, Università degli Studi di Milano, via Antonio di Rudinì 8, 20122 Milano, Italy
| | - Stefania Coelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
| | - Rosanna Ferrara
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
- CRC 'Aldo Ravelli' per le Neurotecnologie e le Terapie Neurologiche Sperimentali, Dipartimento di Scienze della Salute, Università degli Studi di Milano, via Antonio di Rudinì 8, 20122 Milano, Italy
| | - Sergio Cerutti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
| | - Alberto Priori
- CRC 'Aldo Ravelli' per le Neurotecnologie e le Terapie Neurologiche Sperimentali, Dipartimento di Scienze della Salute, Università degli Studi di Milano, via Antonio di Rudinì 8, 20122 Milano, Italy
| | - Anna Maria Bianchi
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
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Georgiades MJ, Shine JM, Gilat M, McMaster J, Owler B, Mahant N, Lewis SJ. Subthalamic Nucleus Activity during Cognitive Load and Gait Dysfunction in Parkinson's Disease. Mov Disord 2023; 38:1549-1554. [PMID: 37226972 PMCID: PMC10946988 DOI: 10.1002/mds.29455] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 05/01/2023] [Accepted: 05/08/2023] [Indexed: 05/26/2023] Open
Abstract
BACKGROUND Gait freezing is a common, disabling symptom of Parkinson's disease characterized by sudden motor arrest during walking. Adaptive deep brain stimulation devices that detect freezing and deliver real-time, symptom-specific stimulation are a potential treatment strategy. Real-time alterations in subthalamic nucleus firing patterns have been demonstrated with lower limb freezing, however, whether similar abnormal signatures occur with freezing provoked by cognitive load, is unknown. METHODS We obtained subthalamic nucleus microelectrode recordings from eight Parkinson's disease patients performing a validated virtual reality gait task, requiring responses to on-screen cognitive cues while maintaining motor output. RESULTS Signal analysis during 15 trials containing freezing or significant motor output slowing precipitated by dual-tasking demonstrated reduced θ frequency (3-8 Hz) firing compared to 18 unaffected trials. CONCLUSIONS These preliminary results reveal a potential neurobiological basis for the interplay between cognitive factors and gait disturbances including freezing in Parkinson's disease, informing development of adaptive deep brain stimulation protocols. © 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)
- Matthew J. Georgiades
- ForeFront Parkinson's Disease Research Clinic, Brain and Mind CentreUniversity of SydneySydneyNew South WalesAustralia
- Sydney Medical SchoolThe University of SydneySydneyNew South WalesAustralia
| | - James M. Shine
- ForeFront Parkinson's Disease Research Clinic, Brain and Mind CentreUniversity of SydneySydneyNew South WalesAustralia
- Sydney Medical SchoolThe University of SydneySydneyNew South WalesAustralia
| | - Moran Gilat
- ForeFront Parkinson's Disease Research Clinic, Brain and Mind CentreUniversity of SydneySydneyNew South WalesAustralia
- KU Leuven, Department of Rehabilitation SciencesNeurorehabilitation Research Group (eNRGy)Belgium
| | | | - Brian Owler
- Sydney Medical SchoolThe University of SydneySydneyNew South WalesAustralia
- Westmead Private HospitalSydneyNew South WalesAustralia
| | - Neil Mahant
- Sydney Medical SchoolThe University of SydneySydneyNew South WalesAustralia
- Westmead Private HospitalSydneyNew South WalesAustralia
| | - Simon J.G. Lewis
- ForeFront Parkinson's Disease Research Clinic, Brain and Mind CentreUniversity of SydneySydneyNew South WalesAustralia
- Sydney Medical SchoolThe University of SydneySydneyNew South WalesAustralia
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6
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Wang S, Zhu G, Shi L, Zhang C, Wu B, Yang A, Meng F, Jiang Y, Zhang J. Closed-Loop Adaptive Deep Brain Stimulation in Parkinson's Disease: Procedures to Achieve It and Future Perspectives. JOURNAL OF PARKINSON'S DISEASE 2023:JPD225053. [PMID: 37182899 DOI: 10.3233/jpd-225053] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Parkinson's disease (PD) is a neurodegenerative disease with a heavy burden on patients, families, and society. Deep brain stimulation (DBS) can improve the symptoms of PD patients for whom medication is insufficient. However, current open-loop uninterrupted conventional DBS (cDBS) has inherent limitations, such as adverse effects, rapid battery consumption, and a need for frequent parameter adjustment. To overcome these shortcomings, adaptive DBS (aDBS) was proposed to provide responsive optimized stimulation for PD. This topic has attracted scientific interest, and a growing body of preclinical and clinical evidence has shown its benefits. However, both achievements and challenges have emerged in this novel field. To date, only limited reviews comprehensively analyzed the full framework and procedures for aDBS implementation. Herein, we review current preclinical and clinical data on aDBS for PD to discuss the full procedures for its achievement and to provide future perspectives on this treatment.
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Affiliation(s)
- Shu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lin Shi
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunkui Zhang
- Center of Cognition and Brain Science, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Bing Wu
- Center of Cognition and Brain Science, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
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7
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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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8
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A systematic review of local field potential physiomarkers in Parkinson's disease: from clinical correlations to adaptive deep brain stimulation algorithms. J Neurol 2023; 270:1162-1177. [PMID: 36209243 PMCID: PMC9886603 DOI: 10.1007/s00415-022-11388-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/16/2022] [Indexed: 02/03/2023]
Abstract
Deep brain stimulation (DBS) treatment has proven effective in suppressing symptoms of rigidity, bradykinesia, and tremor in Parkinson's disease. Still, patients may suffer from disabling fluctuations in motor and non-motor symptom severity during the day. Conventional DBS treatment consists of continuous stimulation but can potentially be further optimised by adapting stimulation settings to the presence or absence of symptoms through closed-loop control. This critically relies on the use of 'physiomarkers' extracted from (neuro)physiological signals. Ideal physiomarkers for adaptive DBS (aDBS) are indicative of symptom severity, detectable in every patient, and technically suitable for implementation. In the last decades, much effort has been put into the detection of local field potential (LFP) physiomarkers and in their use in clinical practice. We conducted a research synthesis of the correlations that have been reported between LFP signal features and one or more specific PD motor symptoms. Features based on the spectral beta band (~ 13 to 30 Hz) explained ~ 17% of individual variability in bradykinesia and rigidity symptom severity. Limitations of beta band oscillations as physiomarker are discussed, and strategies for further improvement of aDBS are explored.
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9
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Bahadori-Jahromi F, Salehi S, Madadi Asl M, Valizadeh A. Efficient suppression of parkinsonian beta oscillations in a closed-loop model of deep brain stimulation with amplitude modulation. Front Hum Neurosci 2023; 16:1013155. [PMID: 36776221 PMCID: PMC9908610 DOI: 10.3389/fnhum.2022.1013155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 12/09/2022] [Indexed: 01/27/2023] Open
Abstract
Introduction Parkinson's disease (PD) is a movement disorder characterized by the pathological beta band (15-30 Hz) neural oscillations within the basal ganglia (BG). It is shown that the suppression of abnormal beta oscillations is correlated with the improvement of PD motor symptoms, which is a goal of standard therapies including deep brain stimulation (DBS). To overcome the stimulation-induced side effects and inefficiencies of conventional DBS (cDBS) and to reduce the administered stimulation current, closed-loop adaptive DBS (aDBS) techniques were developed. In this method, the frequency and/or amplitude of stimulation are modulated based on various disease biomarkers. Methods Here, by computational modeling of a cortico-BG-thalamic network in normal and PD conditions, we show that closed-loop aDBS of the subthalamic nucleus (STN) with amplitude modulation leads to a more effective suppression of pathological beta oscillations within the parkinsonian BG. Results Our results show that beta band neural oscillations are restored to their normal range and the reliability of the response of the thalamic neurons to motor cortex commands is retained due to aDBS with amplitude modulation. Furthermore, notably less stimulation current is administered during aDBS compared with cDBS due to a closed-loop control of stimulation amplitude based on the STN local field potential (LFP) beta activity. Discussion Efficient models of closed-loop stimulation may contribute to the clinical development of optimized aDBS techniques designed to reduce potential stimulation-induced side effects of cDBS in PD patients while leading to a better therapeutic outcome.
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Affiliation(s)
| | - Sina Salehi
- Shiraz Neuroscience Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mojtaba Madadi Asl
- School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
| | - Alireza Valizadeh
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
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10
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Williams D. Basal ganglia functional connectivity network analysis does not support the 'noisy signal' hypothesis of Parkinson's disease. Brain Commun 2023; 5:fcad123. [PMID: 37124947 PMCID: PMC10139445 DOI: 10.1093/braincomms/fcad123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 02/23/2023] [Accepted: 04/12/2023] [Indexed: 05/02/2023] Open
Abstract
The 'noisy signal' hypothesis of basal ganglia dysfunction in Parkinson's disease (PD) suggests that major motor symptoms of the disorder are caused by the development of abnormal basal ganglia activity patterns resulting in the propagation of 'noisy' signals to target systems. While such abnormal activity patterns might be useful biomarkers for the development of therapeutic interventions, correlation between specific changes in activity and PD symptoms has been inconsistently demonstrated, and raises questions concerning the accuracy of the hypothesis. Here, we tested this hypothesis by considering three nodes of the basal ganglia network, the subthalamus, globus pallidus interna, and cortex during self-paced and cued movements in patients with PD. Interactions between these regions were analyzed using measures that assess both linear and non-linear relationships. Marked changes in the network are observed with dopamine state. Specifically, we detected functional disconnection of the basal ganglia from the cortex and higher network variability in untreated PD, but various patterns of directed functional connectivity with lower network variability in treated PD. When we examine the system output, significant correlation is observed between variability in the cortico-basal ganglia network and muscle activity variability but only in the treated state. Rather than supporting a role of the basal ganglia in the transmission of noisy signals in patients with PD, these findings suggest that cortico-basal ganglia network interactions by fault or design, in the treated Parkinsonian state, are actually associated with improved cortical network output variability.
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Affiliation(s)
- David Williams
- Correspondence to: Dr David Williams. Department of Internal Medicine, College of Medicine and Health Sciences, United Arab Emirates University, Khalifa Bin Zayed Street, Tawam, Next to Tawam Hospital, Al Ain, PO Box 15551, United Arab Emirates. E-mail:
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11
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Nwogo RO, Kammermeier S, Singh A. Abnormal neural oscillations during gait and dual-task in Parkinson’s disease. Front Syst Neurosci 2022; 16:995375. [PMID: 36185822 PMCID: PMC9522469 DOI: 10.3389/fnsys.2022.995375] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 08/23/2022] [Indexed: 12/03/2022] Open
Abstract
Gait dysfunctions are debilitating motor symptoms of Parkinson’s disease (PD) and may result in frequent falling with health complications. The contribution of the motor-cognitive network to gait disturbance can be studied more thoroughly by challenging motor-cognitive dual-task gait performances. Gait is a complex motor task that requires an appropriate contribution from motor and cognitive networks, reflected in frequency modulations among several cortical and subcortical networks. Electrophysiological recordings by scalp electroencephalography and implanted deep brain stimulation (DBS) electrodes have unveiled modulations of specific oscillatory patterns in the cortical-subcortical circuits in PD. In this review, we summarize oscillatory contributions of the cortical, basal ganglia, mesencephalic locomotor, and cerebellar regions during gait and dual-task activities in PD. We detail the involvement of the cognitive network in dual-task settings and compare how abnormal oscillations in the specific frequency bands in the cortical and subcortical regions correlate with gait deficits in PD, particularly freezing of gait (FOG). We suggest that altered neural oscillations in different frequencies can cause derangements in broader brain networks, so neuromodulation and pharmacological therapies should be considered to normalize those network oscillations to improve challenged gait and dual-task motor functions in PD. Specifically, the theta and beta bands in premotor cortical areas, subthalamic nucleus, as well as alpha band activity in the brainstem prepontine nucleus, modulate under clinically effective levodopa and DBS therapies, improving gait and dual-task performance in PD with FOG, compared to PD without FOG and age-matched healthy control groups.
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Affiliation(s)
- Rachel O. Nwogo
- Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, United States
| | | | - Arun Singh
- Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, United States
- *Correspondence: Arun Singh,
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12
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Thenaisie Y, Lee K, Moerman C, Scafa S, Gálvez A, Pirondini E, Burri M, Ravier J, Puiatti A, Accolla E, Wicki B, Zacharia A, Castro Jiménez M, Bally JF, Courtine G, Bloch J, Moraud EM. Principles of gait encoding in the subthalamic nucleus of people with Parkinson's disease. Sci Transl Med 2022; 14:eabo1800. [PMID: 36070366 DOI: 10.1126/scitranslmed.abo1800] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Disruption of subthalamic nucleus dynamics in Parkinson's disease leads to impairments during walking. Here, we aimed to uncover the principles through which the subthalamic nucleus encodes functional and dysfunctional walking in people with Parkinson's disease. We conceived a neurorobotic platform embedding an isokinetic dynamometric chair that allowed us to deconstruct key components of walking under well-controlled conditions. We exploited this platform in 18 patients with Parkinson's disease to demonstrate that the subthalamic nucleus encodes the initiation, termination, and amplitude of leg muscle activation. We found that the same fundamental principles determine the encoding of leg muscle synergies during standing and walking. We translated this understanding into a machine learning framework that decoded muscle activation, walking states, locomotor vigor, and freezing of gait. These results expose key principles through which subthalamic nucleus dynamics encode walking, opening the possibility to operate neuroprosthetic systems with these signals to improve walking in people with Parkinson's disease.
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Affiliation(s)
- Yohann Thenaisie
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne CH-1011, Switzerland.,NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland
| | - Kyuhwa Lee
- Wyss Center for Bio and Neuroengineering, Geneva CH-1202, Switzerland
| | - Charlotte Moerman
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne CH-1011, Switzerland.,NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland
| | - Stefano Scafa
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne CH-1011, Switzerland.,NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland.,Institute of Digital Technologies for Personalized Healthcare (MeDiTech) , University of Southern Switzerland (SUPSI), Lugano-Viganello CH-6962 Switzerland
| | - Andrea Gálvez
- NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland.,Faculty of Life Sciences, EPFL, NeuroX Institute, Lausanne CH-1015, Switzerland
| | - Elvira Pirondini
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne CH-1011, Switzerland.,Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh 15213, PA, USA.,Rehabilitation and Neural Engineering Labs, University of Pittsburgh, Pittsburgh 15213, PA, USA
| | - Morgane Burri
- NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland.,Faculty of Life Sciences, EPFL, NeuroX Institute, Lausanne CH-1015, Switzerland
| | - Jimmy Ravier
- NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland.,Faculty of Life Sciences, EPFL, NeuroX Institute, Lausanne CH-1015, Switzerland
| | - Alessandro Puiatti
- Institute of Digital Technologies for Personalized Healthcare (MeDiTech) , University of Southern Switzerland (SUPSI), Lugano-Viganello CH-6962 Switzerland
| | - Ettore Accolla
- Department of Neurology, Hôpital Fribourgeois, Fribourg University, Fribourg CH-1708, Switzerland
| | - Benoit Wicki
- Department of Neurology, Hôpital du Valais, Sion CH-1951, Switzerland
| | - André Zacharia
- Clinique Bernoise, Crans-Montana CH-3963, Switzerland.,Department of Neurology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne CH-1011, Switzerland.,Department of Medicine, University of Geneva, Geneva CH-1201, Switzerland
| | - Mayte Castro Jiménez
- Department of Neurology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Julien F Bally
- Department of Neurology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Grégoire Courtine
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne CH-1011, Switzerland.,NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland.,Faculty of Life Sciences, EPFL, NeuroX Institute, Lausanne CH-1015, Switzerland.,Department of Neurosurgery, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Jocelyne Bloch
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne CH-1011, Switzerland.,NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland.,Faculty of Life Sciences, EPFL, NeuroX Institute, Lausanne CH-1015, Switzerland.,Department of Neurosurgery, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Eduardo Martin Moraud
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne CH-1011, Switzerland.,NeuroRestore, Defitech Centre for Interventional Neurotherapies, CHUV, UNIL, and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1011, Switzerland
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13
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Lopes EM, Rego R, Rito M, Chamadoira C, Dias D, Cunha JPS. Estimation of ANT-DBS Electrodes on Target Positioning Based on a New Percept TM PC LFP Signal Analysis. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22176601. [PMID: 36081060 PMCID: PMC9460540 DOI: 10.3390/s22176601] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 08/27/2022] [Accepted: 08/28/2022] [Indexed: 06/12/2023]
Abstract
Deep brain stimulation of the Anterior Nucleus of the Thalamus (ANT-DBS) is an effective therapy in epilepsy. Poorer surgical outcomes are related to deviations of the lead from the ANT-target. The target identification relies on the visualization of anatomical structures by medical imaging, which presents some disadvantages. This study aims to research whether ANT-LFPs recorded with the PerceptTM PC neurostimulator can be an asset in the identification of the DBS-target. For this purpose, 17 features were extracted from LFPs recorded from a single patient, who stayed at an Epilepsy Monitoring Unit for a 5-day period. Features were then integrated into two machine learning (ML)-based methodologies, according to different LFP bipolar montages: Pass1 (nonadjacent channels) and Pass2 (adjacent channels). We obtained an accuracy of 76.6% for the Pass1-classifier and 83.33% for the Pass2-classifier in distinguishing locations completely inserted in the target and completely outside. Then, both classifiers were used to predict the target percentage of all combinations, and we found that contacts 3 (left hemisphere) and 2 and 3 (right hemisphere) presented higher signatures of the ANT-target, which agreed with the medical images. This result opens a new window of opportunity for the use of LFPs in the guidance of DBS target identification.
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Affiliation(s)
- Elodie Múrias Lopes
- INESC TEC—Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
| | - Ricardo Rego
- Neurophysiology Unit, Neurology Department, Centro Hospitalar Universitário de São João, 4200-319 Porto, Portugal
| | - Manuel Rito
- Neurosurgery Department, Centro Hospitalar Universitário de São João, 4200-319 Porto, Portugal
| | - Clara Chamadoira
- Neurosurgery Department, Centro Hospitalar Universitário de São João, 4200-319 Porto, Portugal
| | - Duarte Dias
- INESC TEC—Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
| | - João Paulo Silva Cunha
- INESC TEC—Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
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14
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Chen R, Berardelli A, Bhattacharya A, Bologna M, Chen KHS, Fasano A, Helmich RC, Hutchison WD, Kamble N, Kühn AA, Macerollo A, Neumann WJ, Pal PK, Paparella G, Suppa A, Udupa K. Clinical neurophysiology of Parkinson's disease and parkinsonism. Clin Neurophysiol Pract 2022; 7:201-227. [PMID: 35899019 PMCID: PMC9309229 DOI: 10.1016/j.cnp.2022.06.002] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 06/11/2022] [Accepted: 06/22/2022] [Indexed: 01/01/2023] Open
Abstract
This review is part of the series on the clinical neurophysiology of movement disorders and focuses on Parkinson’s disease and parkinsonism. The pathophysiology of cardinal parkinsonian motor symptoms and myoclonus are reviewed. The recordings from microelectrode and deep brain stimulation electrodes are reported in detail.
This review is part of the series on the clinical neurophysiology of movement disorders. It focuses on Parkinson’s disease and parkinsonism. The topics covered include the pathophysiology of tremor, rigidity and bradykinesia, balance and gait disturbance and myoclonus in Parkinson’s disease. The use of electroencephalography, electromyography, long latency reflexes, cutaneous silent period, studies of cortical excitability with single and paired transcranial magnetic stimulation, studies of plasticity, intraoperative microelectrode recordings and recording of local field potentials from deep brain stimulation, and electrocorticography are also reviewed. In addition to advancing knowledge of pathophysiology, neurophysiological studies can be useful in refining the diagnosis, localization of surgical targets, and help to develop novel therapies for Parkinson’s disease.
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Affiliation(s)
- Robert Chen
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Ontario, Canada.,Edmond J. Safra Program in Parkinson's Disease, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Alfredo Berardelli
- Department of Human Neurosciences, Sapienza University of Rome, Italy.,IRCCS Neuromed Pozzilli (IS), Italy
| | - Amitabh Bhattacharya
- Department of Neurology, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India
| | - Matteo Bologna
- Department of Human Neurosciences, Sapienza University of Rome, Italy.,IRCCS Neuromed Pozzilli (IS), Italy
| | - Kai-Hsiang Stanley Chen
- Department of Neurology, National Taiwan University Hospital Hsinchu Branch, Hsinchu, Taiwan
| | - Alfonso Fasano
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Ontario, Canada.,Edmond J. Safra Program in Parkinson's Disease, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Rick C Helmich
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology and Centre of Expertise for Parkinson & Movement Disorders, Nijmegen, the Netherlands
| | - William D Hutchison
- Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Departments of Surgery and Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Nitish Kamble
- Department of Neurology, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India
| | - Andrea A Kühn
- Department of Neurology, Movement Disorder and Neuromodulation Unit, Charité - Universitätsmedizin Berlin, Germany
| | - Antonella Macerollo
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom.,The Walton Centre NHS Foundation Trust for Neurology and Neurosurgery, Liverpool, United Kingdom
| | - Wolf-Julian Neumann
- Department of Neurology, Movement Disorder and Neuromodulation Unit, Charité - Universitätsmedizin Berlin, Germany
| | - Pramod Kumar Pal
- Department of Neurology, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India
| | | | - Antonio Suppa
- Department of Human Neurosciences, Sapienza University of Rome, Italy.,IRCCS Neuromed Pozzilli (IS), Italy
| | - Kaviraja Udupa
- Department of Neurophysiology National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India
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15
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Pozzi NG, Palmisano C, Reich MM, Capetian P, Pacchetti C, Volkmann J, Isaias IU. Troubleshooting Gait Disturbances in Parkinson's Disease With Deep Brain Stimulation. Front Hum Neurosci 2022; 16:806513. [PMID: 35652005 PMCID: PMC9148971 DOI: 10.3389/fnhum.2022.806513] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 03/16/2022] [Indexed: 01/08/2023] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus or the globus pallidus is an established treatment for Parkinson's disease (PD) that yields a marked and lasting improvement of motor symptoms. Yet, DBS benefit on gait disturbances in PD is still debated and can be a source of dissatisfaction and poor quality of life. Gait disturbances in PD encompass a variety of clinical manifestations and rely on different pathophysiological bases. While gait disturbances arising years after DBS surgery can be related to disease progression, early impairment of gait may be secondary to treatable causes and benefits from DBS reprogramming. In this review, we tackle the issue of gait disturbances in PD patients with DBS by discussing their neurophysiological basis, providing a detailed clinical characterization, and proposing a pragmatic programming approach to support their management.
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Affiliation(s)
- Nicoló G. Pozzi
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Chiara Palmisano
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Martin M. Reich
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Philip Capetian
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Claudio Pacchetti
- Parkinson’s Disease and Movement Disorders Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Jens Volkmann
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
| | - Ioannis U. Isaias
- Department of Neurology, University Hospital of Würzburg and Julius Maximilian University of Würzburg, Würzburg, Germany
- Parkinson Institute Milan, ASST Gaetano Pini-CTO, Milan, Italy
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16
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Merk T, Peterson V, Köhler R, Haufe S, Richardson RM, Neumann WJ. Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation. Exp Neurol 2022; 351:113993. [PMID: 35104499 PMCID: PMC10521329 DOI: 10.1016/j.expneurol.2022.113993] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 11/18/2021] [Accepted: 01/22/2022] [Indexed: 12/30/2022]
Abstract
Sensing enabled implantable devices and next-generation neurotechnology allow real-time adjustments of invasive neuromodulation. The identification of symptom and disease-specific biomarkers in invasive brain signal recordings has inspired the idea of demand dependent adaptive deep brain stimulation (aDBS). Expanding the clinical utility of aDBS with machine learning may hold the potential for the next breakthrough in the therapeutic success of clinical brain computer interfaces. To this end, sophisticated machine learning algorithms optimized for decoding of brain states from neural time-series must be developed. To support this venture, this review summarizes the current state of machine learning studies for invasive neurophysiology. After a brief introduction to the machine learning terminology, the transformation of brain recordings into meaningful features for decoding of symptoms and behavior is described. Commonly used machine learning models are explained and analyzed from the perspective of utility for aDBS. This is followed by a critical review on good practices for training and testing to ensure conceptual and practical generalizability for real-time adaptation in clinical settings. Finally, first studies combining machine learning with aDBS are highlighted. This review takes a glimpse into the promising future of intelligent adaptive DBS (iDBS) and concludes by identifying four key ingredients on the road for successful clinical adoption: i) multidisciplinary research teams, ii) publicly available datasets, iii) open-source algorithmic solutions and iv) strong world-wide research collaborations.
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Affiliation(s)
- Timon Merk
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - Victoria Peterson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Richard Köhler
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging (BCAN), Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany.
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17
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Wagner JR, Schaper M, Hamel W, Westphal M, Gerloff C, Engel AK, Moll CKE, Gulberti A, Pötter-Nerger M. Combined Subthalamic and Nigral Stimulation Modulates Temporal Gait Coordination and Cortical Gait-Network Activity in Parkinson's Disease. Front Hum Neurosci 2022; 16:812954. [PMID: 35295883 PMCID: PMC8919031 DOI: 10.3389/fnhum.2022.812954] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 01/27/2022] [Indexed: 01/10/2023] Open
Abstract
Background Freezing of gait (FoG) is a disabling burden for Parkinson's disease (PD) patients with poor response to conventional therapies. Combined deep brain stimulation of the subthalamic nucleus and substantia nigra (STN+SN DBS) moved into focus as a potential therapeutic option to treat the parkinsonian gait disorder and refractory FoG. The mechanisms of action of DBS within the cortical-subcortical-basal ganglia network on gait, particularly at the cortical level, remain unclear. Methods Twelve patients with idiopathic PD and chronically-implanted DBS electrodes were assessed on their regular dopaminergic medication in a standardized stepping in place paradigm. Patients executed the task with DBS switched off (STIM OFF), conventional STN DBS and combined STN+SN DBS and were compared to healthy matched controls. Simultaneous high-density EEG and kinematic measurements were recorded during resting-state, effective stepping, and freezing episodes. Results Clinically, STN+SN DBS was superior to conventional STN DBS in improving temporal stepping variability of the more affected leg. During resting-state and effective stepping, the cortical activity of PD patients in STIM OFF was characterized by excessive over-synchronization in the theta (4-8 Hz), alpha (9-13 Hz), and high-beta (21-30 Hz) band compared to healthy controls. Both active DBS settings similarly decreased resting-state alpha power and reduced pathologically enhanced high-beta activity during resting-state and effective stepping compared to STIM OFF. Freezing episodes during STN DBS and STN+SN DBS showed spectrally and spatially distinct cortical activity patterns when compared to effective stepping. During STN DBS, FoG was associated with an increase in cortical alpha and low-beta activity over central cortical areas, while with STN+SN DBS, an increase in high-beta was prominent over more frontal areas. Conclusions STN+SN DBS improved temporal aspects of parkinsonian gait impairment compared to conventional STN DBS and differentially affected cortical oscillatory patterns during regular locomotion and freezing suggesting a potential modulatory effect on dysfunctional cortical-subcortical communication in PD.
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Affiliation(s)
- Jonas R. Wagner
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Miriam Schaper
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Wolfgang Hamel
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Manfred Westphal
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Andreas K. Engel
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian K. E. Moll
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alessandro Gulberti
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Monika Pötter-Nerger
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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18
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Wenger N, Vogt A, Skrobot M, Garulli EL, Kabaoglu B, Salchow-Hömmen C, Schauer T, Kroneberg D, Schuhmann M, Ip CW, Harms C, Endres M, Isaias I, Tovote P, Blum R. Rodent models for gait network disorders in Parkinson's disease - a translational perspective. Exp Neurol 2022; 352:114011. [PMID: 35176273 DOI: 10.1016/j.expneurol.2022.114011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 01/23/2022] [Accepted: 02/10/2022] [Indexed: 11/26/2022]
Abstract
Gait impairments in Parkinson's disease remain a scientific and therapeutic challenge. The advent of new deep brain stimulation (DBS) devices capable of recording brain activity from chronically implanted electrodes has fostered new studies of gait in freely moving patients. The hope is to identify gait-related neural biomarkers and improve therapy using closed-loop DBS. In this context, animal models offer the opportunity to investigate gait network activity at multiple biological scales and address unresolved questions from clinical research. Yet, the contribution of rodent models to the development of future neuromodulation therapies will rely on translational validity. In this review, we summarize the most effective strategies to model parkinsonian gait in rodents. We discuss how clinical observations have inspired targeted brain lesions in animal models, and whether resulting motor deficits and network oscillations match recent findings in humans. Gait impairments with hypo-, bradykinesia and altered limb rhythmicity were successfully modelled in rodents. However, clear evidence for the presence of freezing of gait was missing. The identification of reliable neural biomarkers for gait impairments has remained challenging in both animals and humans. Moving forward, we expect that the ongoing investigation of circuit specific neuromodulation strategies in animal models will lead to future optimizations of gait therapy in Parkinson's disease.
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Affiliation(s)
- Nikolaus Wenger
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; Berlin Institute of Health, Germany.
| | - Arend Vogt
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Matej Skrobot
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Elisa L Garulli
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Burce Kabaoglu
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Christina Salchow-Hömmen
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Thomas Schauer
- Technische Universität Berlin, Control Systems Group, 10587 Berlin, Germany
| | - Daniel Kroneberg
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; Berlin Institute of Health, Germany
| | - Michael Schuhmann
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Wuerzburg, Germany
| | - Chi Wang Ip
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Wuerzburg, Germany
| | - Christoph Harms
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Germany
| | - Matthias Endres
- Department of Neurology with experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany; Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Germany; DZHK (German Center for Cardiovascular Research), Berlin Site, Germany; DZNE (German Center for Neurodegenerative Disease), Berlin Site, Germany
| | - Ioannis Isaias
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Wuerzburg, Germany
| | - Philip Tovote
- Institute of Clinical Neurobiology, University Hospital Wuerzburg, Versbacher Str. 5, 97078 Wuerzburg, Germany; Center for Mental Health, University of Wuerzburg, Margarete-Höppel-Platz 1, 97080 Wuerzburg, Germany
| | - Robert Blum
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Wuerzburg, Germany
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19
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O’Day J, Lee M, Seagers K, Hoffman S, Jih-Schiff A, Kidziński Ł, Delp S, Bronte-Stewart H. Assessing inertial measurement unit locations for freezing of gait detection and patient preference. J Neuroeng Rehabil 2022; 19:20. [PMID: 35152881 PMCID: PMC8842967 DOI: 10.1186/s12984-022-00992-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 01/13/2022] [Indexed: 12/28/2022] Open
Abstract
Background Freezing of gait, a common symptom of Parkinson’s disease, presents as sporadic episodes in which an individual’s feet suddenly feel stuck to the ground. Inertial measurement units (IMUs) promise to enable at-home monitoring and personalization of therapy, but there is a lack of consensus on the number and location of IMUs for detecting freezing of gait. The purpose of this study was to assess IMU sets in the context of both freezing of gait detection performance and patient preference. Methods Sixteen people with Parkinson’s disease were surveyed about sensor preferences. Raw IMU data from seven people with Parkinson’s disease, wearing up to eleven sensors, were used to train convolutional neural networks to detect freezing of gait. Models trained with data from different sensor sets were assessed for technical performance; a best technical set and minimal IMU set were identified. Clinical utility was assessed by comparing model- and human-rater-determined percent time freezing and number of freezing events. Results The best technical set consisted of three IMUs (lumbar and both ankles, AUROC = 0.83), all of which were rated highly wearable. The minimal IMU set consisted of a single ankle IMU (AUROC = 0.80). Correlations between these models and human raters were good to excellent for percent time freezing (ICC = 0.93, 0.89) and number of freezing events (ICC = 0.95, 0.86) for the best technical set and minimal IMU set, respectively. Conclusions Several IMU sets consisting of three IMUs or fewer were highly rated for both technical performance and wearability, and more IMUs did not necessarily perform better in FOG detection. We openly share our data and software to further the development and adoption of a general, open-source model that uses raw signals and a standard sensor set for at-home monitoring of freezing of gait. Supplementary Information The online version contains supplementary material available at 10.1186/s12984-022-00992-x.
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20
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Lizárraga KJ, Gnanamanogaran B, Al‐Ozzi TM, Cohn M, Tomlinson G, Boutet A, Elias GJ, Germann J, Soh D, Kalia SK, Hodaie M, Munhoz RP, Marras C, Hutchison WD, Lozano AM, Lang AE, Fasano A. Lateralized Subthalamic Stimulation for Axial Dysfunction in Parkinson's Disease: A Randomized Trial. Mov Disord 2022; 37:1079-1087. [DOI: 10.1002/mds.28953] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 01/18/2022] [Accepted: 01/20/2022] [Indexed: 12/19/2022] Open
Affiliation(s)
- Karlo J. Lizárraga
- The Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic Toronto Western Hospital, University Hospital Network and Division of Neurology, Department of Medicine, University of Toronto Toronto Ontario Canada
- Motor Physiology and Neuromodulation Program, Division of Movement Disorders, Department of Neurology and Center for Health and Technology University of Rochester Rochester New York USA
| | - Bhairavei Gnanamanogaran
- The Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic Toronto Western Hospital, University Hospital Network and Division of Neurology, Department of Medicine, University of Toronto Toronto Ontario Canada
- University of Toronto Toronto Ontario Canada
| | - Tameem M. Al‐Ozzi
- University of Toronto Toronto Ontario Canada
- Krembil Research Institute Toronto Ontario Canada
- Departments of Surgery and Physiology University of Toronto Toronto Ontario Canada
| | - Melanie Cohn
- Krembil Research Institute Toronto Ontario Canada
- Department of Psychology University of Toronto Toronto Ontario Canada
| | - George Tomlinson
- Institute of Health Policy, Management and Evaluation University of Toronto Toronto Ontario Canada
- University Health Network Toronto Ontario Canada
| | - Alexandre Boutet
- University Health Network Toronto Ontario Canada
- Joint Department of Medical Imaging University of Toronto Toronto Ontario Canada
- Division of Neurosurgery, Department of Surgery University Health Network and University of Toronto Toronto Ontario Canada
| | - Gavin J.B. Elias
- University Health Network Toronto Ontario Canada
- Division of Neurosurgery, Department of Surgery University Health Network and University of Toronto Toronto Ontario Canada
| | - Jürgen Germann
- University Health Network Toronto Ontario Canada
- Division of Neurosurgery, Department of Surgery University Health Network and University of Toronto Toronto Ontario Canada
| | - Derrick Soh
- The Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic Toronto Western Hospital, University Hospital Network and Division of Neurology, Department of Medicine, University of Toronto Toronto Ontario Canada
- Alfred Hospital Melbourne Victoria Australia
| | - Suneil K. Kalia
- Krembil Research Institute Toronto Ontario Canada
- Division of Neurosurgery, Department of Surgery University Health Network and University of Toronto Toronto Ontario Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA) Toronto Ontario Canada
| | - Mojgan Hodaie
- Krembil Research Institute Toronto Ontario Canada
- Division of Neurosurgery, Department of Surgery University Health Network and University of Toronto Toronto Ontario Canada
| | - Renato P. Munhoz
- The Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic Toronto Western Hospital, University Hospital Network and Division of Neurology, Department of Medicine, University of Toronto Toronto Ontario Canada
- Krembil Research Institute Toronto Ontario Canada
| | - Connie Marras
- The Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic Toronto Western Hospital, University Hospital Network and Division of Neurology, Department of Medicine, University of Toronto Toronto Ontario Canada
- Krembil Research Institute Toronto Ontario Canada
| | - William D. Hutchison
- Krembil Research Institute Toronto Ontario Canada
- Departments of Surgery and Physiology University of Toronto Toronto Ontario Canada
- Division of Neurosurgery, Department of Surgery University Health Network and University of Toronto Toronto Ontario Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA) Toronto Ontario Canada
| | - Andres M. Lozano
- Krembil Research Institute Toronto Ontario Canada
- Division of Neurosurgery, Department of Surgery University Health Network and University of Toronto Toronto Ontario Canada
| | - Anthony E. Lang
- The Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic Toronto Western Hospital, University Hospital Network and Division of Neurology, Department of Medicine, University of Toronto Toronto Ontario Canada
- Krembil Research Institute Toronto Ontario Canada
| | - Alfonso Fasano
- The Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic Toronto Western Hospital, University Hospital Network and Division of Neurology, Department of Medicine, University of Toronto Toronto Ontario Canada
- Krembil Research Institute Toronto Ontario Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA) Toronto Ontario Canada
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21
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Zampogna A, D'Onofrio V, Suppa A. Theta rhythms may support executive functions in Parkinson’s disease with freezing of gait. Clin Neurophysiol 2022; 137:181-182. [DOI: 10.1016/j.clinph.2022.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 02/15/2022] [Indexed: 11/15/2022]
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22
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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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23
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Bange M, Gonzalez-Escamilla G, Marquardt T, Radetz A, Dresel C, Herz D, Schöllhorn WI, Groppa S, Muthuraman M. Deficient Interhemispheric Connectivity Underlies Movement Irregularities in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:381-395. [PMID: 34719510 DOI: 10.3233/jpd-212840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Movement execution is impaired in patients with Parkinson's disease. Evolving neurodegeneration leads to altered connectivity between distinct regions of the brain and altered activity at interconnected areas. How connectivity alterations influence complex movements like drawing spirals in Parkinson's disease patients remains largely unexplored. OBJECTIVE We investigated whether deteriorations in interregional connectivity relate to impaired execution of drawing. METHODS Twenty-nine patients and 31 age-matched healthy control participants drew spirals with both hands on a digital graphics tablet, and the regularity of drawing execution was evaluated by sample entropy. We recorded resting-state fMRI and task-related EEG, and calculated the time-resolved partial directed coherence to estimate effective connectivity for both imaging modalities to determine the extent and directionality of interregional interactions. RESULTS Movement performance in Parkinson's disease patients was characterized by increased sample entropy, corresponding to enhanced irregularities in task execution. Effective connectivity between the motor cortices of both hemispheres, derived from resting-state fMRI, was significantly reduced in Parkinson's disease patients in comparison to controls. The connectivity strength in the nondominant to dominant hemisphere direction in both modalities was inversely correlated with irregularities during drawing, but not with the clinical state. CONCLUSION Our findings suggest that interhemispheric connections are affected both at rest and during drawing movements by Parkinson's disease. This provides novel evidence that disruptions of interhemispheric information exchange play a pivotal role for impairments of complex movement execution in Parkinson's disease patients.
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Affiliation(s)
- Manuel Bange
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Tabea Marquardt
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Angela Radetz
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Christian Dresel
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Damian Herz
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, UK
| | | | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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24
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Neuville RS, Petrucci MN, Wilkins KB, Anderson RW, Hoffman SL, Parker JE, Velisar A, Bronte-Stewart HM. Differential Effects of Pathological Beta Burst Dynamics Between Parkinson's Disease Phenotypes Across Different Movements. Front Neurosci 2021; 15:733203. [PMID: 34858125 PMCID: PMC8631908 DOI: 10.3389/fnins.2021.733203] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/19/2021] [Indexed: 11/25/2022] Open
Abstract
Background: Resting state beta band (13-30 Hz) oscillations represent pathological neural activity in Parkinson's disease (PD). It is unknown how the peak frequency or dynamics of beta oscillations may change among fine, limb, and axial movements and different disease phenotypes. This will be critical for the development of personalized closed loop deep brain stimulation (DBS) algorithms during different activity states. Methods: Subthalamic (STN) and local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa® PC + S, Medtronic PLC.) in fourteen PD participants (six tremor-dominant and eight akinetic-rigid) off medication/off STN DBS during 30 s of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms and were compared among movement tasks and between tremor-dominant and akinetic-rigid groups. Results: Beta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during each type of movement. Burst power and duration were significantly larger in the high beta band, but not in the low beta band, in the akinetic-rigid group compared to the tremor-dominant group. Conclusion: The conservation of beta peak frequency during different activity states supports the feasibility of patient-specific closed loop DBS algorithms driven by the dynamics of the same beta band during different activities. Akinetic-rigid participants had greater power and longer burst durations in the high beta band than tremor-dominant participants during movement, which may relate to the difference in underlying pathophysiology between phenotypes.
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Affiliation(s)
- Raumin S. Neuville
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- School of Medicine, University of California, Irvine, Irvine, CA, United States
| | - Matthew N. Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Ross W. Anderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Shannon L. Hoffman
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Jordan E. Parker
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Anca Velisar
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Smith-Kettlewell Eye Research Institute, San Francisco, CA, United States
| | - Helen M. Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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25
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Anderson RW, Wilkins KB, Parker JE, Petrucci MN, Kehnemouyi Y, Neuville RS, Cassini D, Trager MH, Koop MM, Velisar A, Blumenfeld Z, Quinn EJ, Henderson J, Bronte-Stewart HM. Lack of progression of beta dynamics after long-term subthalamic neurostimulation. Ann Clin Transl Neurol 2021; 8:2110-2120. [PMID: 34636182 PMCID: PMC8607445 DOI: 10.1002/acn3.51463] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 09/15/2021] [Indexed: 11/07/2022] Open
Abstract
OBJECTIVE To investigate the progression of neural and motor features of Parkinson's disease in a longitudinal study, after washout of medication and bilateral subthalamic nucleus deep brain stimulation (STN DBS). METHODS Participants with clinically established Parkinson's disease underwent bilateral implantation of DBS leads (18 participants, 13 male) within the STN using standard functional frameless stereotactic technique and multi-pass microelectrode recording. Both DBS leads were connected to an implanted investigative sensing neurostimulator (Activa™ PC + S, Medtronic, PLC). Resting state STN local field potentials (LFPs) were recorded and motor disability, (the Movement Disorder Society-Unified Parkinson's Disease Rating Scale - motor subscale, MDS-UPDRS III) was assessed off therapy at initial programming, and after 6 months, 1 year, and yearly out to 5 years of treatment. The primary endpoint was measured at 3 years. At each visit, medication had been held for over 12/24 h and DBS was turned off for at least 60 min, by which time LFP spectra reached a steady state. RESULTS After 3 years of chronic DBS, there were no increases in STN beta band dynamics (p = 0.98) but there were increases in alpha band dynamics (p = 0.0027, 25 STNs). Similar results were observed in a smaller cohort out to 5 years. There was no increase in the MDS-UPDRS III score. INTERPRETATION These findings provide evidence that the beta oscillopathy does not substantially progress following combined STN DBS plus medication in moderate to advanced Parkinson's disease.
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Affiliation(s)
- Ross W Anderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Neurosurgery, Kaiser Permanente, Redwood City, California, USA
| | - Kevin B Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Jordan E Parker
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Psychology, The University of California, Los Angeles, California, USA
| | - Matthew N Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Yasmine Kehnemouyi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Bioengineering, Stanford Schools of Engineering & Medicine, Stanford, California, USA
| | - Raumin S Neuville
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,The University of California School of Medicine, Irvine, California, USA
| | - Declan Cassini
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Megan H Trager
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Columbia University College of Physicians and Surgeons, New York City, New York, USA
| | - Mandy M Koop
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Cleveland Clinic, Cleveland, Ohio, USA
| | - Anca Velisar
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,The Smith-Kettlewell Eye Research Institute, San Francisco, California, USA
| | - Zack Blumenfeld
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,California Institute of Technology, Pasadena, California, USA
| | - Emma J Quinn
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Credit Karma, San Francisco, California, USA
| | - Jaimie Henderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA
| | - Helen M Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.,Department of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA
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26
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Gilron R, Little S, Perrone R, Wilt R, de Hemptinne C, Yaroshinsky MS, Racine CA, Wang SS, Ostrem JL, Larson PS, Wang DD, Galifianakis NB, Bledsoe IO, San Luciano M, Dawes HE, Worrell GA, Kremen V, Borton DA, Denison T, Starr PA. Long-term wireless streaming of neural recordings for circuit discovery and adaptive stimulation in individuals with Parkinson's disease. Nat Biotechnol 2021; 39:1078-1085. [PMID: 33941932 PMCID: PMC8434942 DOI: 10.1038/s41587-021-00897-5] [Citation(s) in RCA: 156] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 03/16/2021] [Indexed: 02/08/2023]
Abstract
Neural recordings using invasive devices in humans can elucidate the circuits underlying brain disorders, but have so far been limited to short recordings from externalized brain leads in a hospital setting or from implanted sensing devices that provide only intermittent, brief streaming of time series data. Here, we report the use of an implantable two-way neural interface for wireless, multichannel streaming of field potentials in five individuals with Parkinson's disease (PD) for up to 15 months after implantation. Bilateral four-channel motor cortex and basal ganglia field potentials streamed at home for over 2,600 h were paired with behavioral data from wearable monitors for the neural decoding of states of inadequate or excessive movement. We validated individual-specific neurophysiological biomarkers during normal daily activities and used those patterns for adaptive deep brain stimulation (DBS). This technological approach may be widely applicable to brain disorders treatable by invasive neuromodulation.
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Affiliation(s)
- Ro'ee Gilron
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
| | - Simon Little
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Randy Perrone
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Robert Wilt
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Coralie de Hemptinne
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Maria S Yaroshinsky
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Caroline A Racine
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Sarah S Wang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jill L Ostrem
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Paul S Larson
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Doris D Wang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Nick B Galifianakis
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Ian O Bledsoe
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Marta San Luciano
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Heather E Dawes
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Gregory A Worrell
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Vaclav Kremen
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - David A Borton
- School of Engineering and Carney Institute, Brown University, Providence, RI, USA
| | - Timothy Denison
- Department of Engineering Science, University of Oxford and MRC Brain Network Dynamics Unit, Oxford, UK
| | - Philip A Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
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27
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Kempster PA, Perju-Dumbrava L. The Thermodynamic Consequences of Parkinson's Disease. Front Neurol 2021; 12:685314. [PMID: 34512508 PMCID: PMC8427692 DOI: 10.3389/fneur.2021.685314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 08/04/2021] [Indexed: 12/31/2022] Open
Abstract
Several lines of evidence point to a pervasive disturbance of energy balance in Parkinson's disease (PD). Weight loss, common and multifactorial, is the most observable sign of this. Bradykinesia may be best understood as an underinvestment of energy in voluntary movement. This accords with rodent experiments that emphasise the importance of dopamine in allocating motor energy expenditure. Oxygen consumption studies in PD suggest that, when activities are standardised for work performed, these inappropriate energy thrift settings are actually wasteful. That the dopaminergic deficit of PD creates a problem with energy efficiency highlights the role played by the basal ganglia, and by dopamine, in thermodynamic governance. This involves more than balancing energy, since living things maintain their internal order by controlling transformations of energy, resisting probabilistic trends to more random states. This review will also look at recent research in PD on the analysis of entropy-an information theory metric of predictability in a message-in recordings from the basal ganglia. Close relationships between energy and information converge around the concept of entropy. This is especially relevant to the motor system, which regulates energy exchange with the outside world through its flow of information. The malignant syndrome in PD, a counterpart of neuroleptic malignant syndrome, demonstrates how much thermodynamic disruption can result from breakdown of motor signalling in an extreme hypodopaminergic state. The macroenergetic disturbances of PD are consistent with a unifying hypothesis of dopamine's neurotransmitter actions-to adapt energy expenditure to prevailing economic circumstances.
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Affiliation(s)
- Peter A. Kempster
- Neurosciences Department, Monash Medical Centre, Clayton, VIC, Australia
- Department of Medicine, School of Clinical Sciences, Monash University, Clayton, VIC, Australia
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28
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Sirica D, Hewitt AL, Tarolli CG, Weber MT, Zimmerman C, Santiago A, Wensel A, Mink JW, Lizárraga KJ. Neurophysiological biomarkers to optimize deep brain stimulation in movement disorders. Neurodegener Dis Manag 2021; 11:315-328. [PMID: 34261338 PMCID: PMC8977945 DOI: 10.2217/nmt-2021-0002] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Intraoperative neurophysiological information could increase accuracy of surgical deep brain stimulation (DBS) lead placement. Subsequently, DBS therapy could be optimized by specifically targeting pathological activity. In Parkinson’s disease, local field potentials (LFPs) excessively synchronized in the beta band (13–35 Hz) correlate with akinetic-rigid symptoms and their response to DBS therapy, particularly low beta band suppression (13–20 Hz) and high frequency gamma facilitation (35–250 Hz). In dystonia, LFPs abnormally synchronize in the theta/alpha (4–13 Hz), beta and gamma (60–90 Hz) bands. Phasic dystonic symptoms and their response to DBS correlate with changes in theta/alpha synchronization. In essential tremor, LFPs excessively synchronize in the theta/alpha and beta bands. Adaptive DBS systems will individualize pathological characteristics of neurophysiological signals to automatically deliver therapeutic DBS pulses of specific spatial and temporal parameters.
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Affiliation(s)
- Daniel Sirica
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA
| | - Angela L Hewitt
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Division of Child Neurology, Department of Neurology, University of Rochester, Rochester, NY 14623, USA
| | - Christopher G Tarolli
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Center for Health & Technology (CHeT), University of Rochester, Rochester, NY 14642, USA
| | - Miriam T Weber
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA
| | - Carol Zimmerman
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA
| | - Aida Santiago
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA
| | - Andrew Wensel
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Department of Neurosurgery, University of Rochester, Rochester, NY 14618, USA
| | - Jonathan W Mink
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Division of Child Neurology, Department of Neurology, University of Rochester, Rochester, NY 14623, USA
| | - Karlo J Lizárraga
- Motor Physiology & Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester, Rochester, NY 14618, USA.,Center for Health & Technology (CHeT), University of Rochester, Rochester, NY 14642, USA
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29
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Prevalence of freezing of gait in Parkinson's disease: a systematic review and meta-analysis. J Neurol 2021; 268:4138-4150. [PMID: 34236501 DOI: 10.1007/s00415-021-10685-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/19/2021] [Accepted: 06/21/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Freezing of gait (FOG) is considered one of the most disturbing and least understood symptoms in Parkinson's disease (PD). The reported prevalence rates of FOG in PD vary widely, ranging from 5 to 85.9%. OBJECTIVE We conducted a systematic review and meta-analysis to provide a reliable estimate of the average point prevalence of FOG in PD, and we further investigated the study characteristics that might have influenced the estimate. METHODS We searched different databases to identify studies that report the prevalence of FOG in PD or include relevant raw data for further calculation. The last inclusion date was February 20, 2020. The modified Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was used for the quality assessment, and articles that met the predefined criteria were included in the quantitative analysis. RESULTS Sixty-six studies were selected from 3392 references. A weighted prevalence of 50.6% in 9072 PD patients experienced FOG based on the special questionnaires (the FOG-Q and NFOG-Q), which was about twice as high as that assessed by the specific items of the clinical rating scales (UPDRS item2.14 and MDS-UPDRS item3.11) (23.2%) or simple clinical questions (25.4%). The weighted prevalence was 37.9% for early stage (≤ 5 years) and 64.6% for advanced stage (≥ 9 years). Moreover, a higher prevalence was calculated from the population-based studies than that in multicenter and single-center studies (47.3% vs. 33.5% and 37.1%, respectively). CONCLUSION The result from this systematic review confirms that FOG is very common in PD and its prevalence is usually underestimated in hospital settings. Importantly, a more accurate assessment of FOG in future clinical researches would involve the use of special FOG scale rather than a single item on a scale or a general clinical inquiry.
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30
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Sand D, Rappel P, Marmor O, Bick AS, Arkadir D, Lu BL, Bergman H, Israel Z, Eitan R. Machine learning-based personalized subthalamic biomarkers predict ON-OFF levodopa states in Parkinson patients. J Neural Eng 2021; 18. [PMID: 33906182 DOI: 10.1088/1741-2552/abfc1d] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 04/27/2021] [Indexed: 01/20/2023]
Abstract
Objective.Adaptive deep brain stimulation (aDBS) based on subthalamic nucleus (STN) electrophysiology has recently been proposed to improve clinical outcomes of DBS for Parkinson's disease (PD) patients. Many current models for aDBS are based on one or two electrophysiological features of STN activity, such as beta or gamma activity. Although these models have shown interesting results, we hypothesized that an aDBS model that includes many STN activity parameters will yield better clinical results. The objective of this study was to investigate the most appropriate STN neurophysiological biomarkers, detectable over long periods of time, that can predict OFF and ON levodopa states in PD patients.Approach.Long-term local field potentials (LFPs) were recorded from eight STNs (four PD patients) during 92 recording sessions (44 OFF and 48 ON levodopa states), over a period of 3-12 months. Electrophysiological analysis included the power of frequency bands, band power ratio and burst features. A total of 140 engineered features was extracted for 20 040 epochs (each epoch lasting 5 s). Based on these engineered features, machine learning (ML) models classified LFPs as OFF vs ON levodopa states.Main results.Beta and gamma band activity alone poorly predicts OFF vs ON levodopa states, with an accuracy of 0.66 and 0.64, respectively. Group ML analysis slightly improved prediction rates, but personalized ML analysis, based on individualized engineered electrophysiological features, were markedly better, predicting OFF vs ON levodopa states with an accuracy of 0.8 for support vector machine learning models.Significance.We showed that individual patients have unique sets of STN neurophysiological biomarkers that can be detected over long periods of time. ML models revealed that personally classified engineered features most accurately predict OFF vs ON levodopa states. Future development of aDBS for PD patients might include personalized ML algorithms.
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Affiliation(s)
- Daniel Sand
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Pnina Rappel
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Odeya Marmor
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Atira S Bick
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - David Arkadir
- The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Bao-Liang Lu
- Center for Brain-like Computing and Machine Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Hagai Bergman
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel.,Functional Neurosurgery Unit, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Zvi Israel
- The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.,Functional Neurosurgery Unit, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Renana Eitan
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.,Jerusalem Mental Health Center, Hebrew University-Hadassah Medical School, Jerusalem, Israel.,Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States of America
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31
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Gait Parameters Measured from Wearable Sensors Reliably Detect Freezing of Gait in a Stepping in Place Task. SENSORS 2021; 21:s21082661. [PMID: 33920070 PMCID: PMC8069332 DOI: 10.3390/s21082661] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 03/31/2021] [Accepted: 04/08/2021] [Indexed: 11/17/2022]
Abstract
Freezing of gait (FOG), a debilitating symptom of Parkinson’s disease (PD), can be safely studied using the stepping in place (SIP) task. However, clinical, visual identification of FOG during SIP is subjective and time consuming, and automatic FOG detection during SIP currently requires measuring the center of pressure on dual force plates. This study examines whether FOG elicited during SIP in 10 individuals with PD could be reliably detected using kinematic data measured from wearable inertial measurement unit sensors (IMUs). A general, logistic regression model (area under the curve = 0.81) determined that three gait parameters together were overall the most robust predictors of FOG during SIP: arrhythmicity, swing time coefficient of variation, and swing angular range. Participant-specific models revealed varying sets of gait parameters that best predicted FOG for each participant, highlighting variable FOG behaviors, and demonstrated equal or better performance for 6 out of the 10 participants, suggesting the opportunity for model personalization. The results of this study demonstrated that gait parameters measured from wearable IMUs reliably detected FOG during SIP, and the general and participant-specific gait parameters allude to variable FOG behaviors that could inform more personalized approaches for treatment of FOG and gait impairment in PD.
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32
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Kehnemouyi YM, Wilkins KB, Anidi CM, Anderson RW, Afzal MF, Bronte-Stewart HM. Modulation of beta bursts in subthalamic sensorimotor circuits predicts improvement in bradykinesia. Brain 2021; 144:473-486. [PMID: 33301569 PMCID: PMC8240742 DOI: 10.1093/brain/awaa394] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 09/09/2020] [Indexed: 01/25/2023] Open
Abstract
No biomarker of Parkinson's disease exists that allows clinicians to adjust chronic therapy, either medication or deep brain stimulation, with real-time feedback. Consequently, clinicians rely on time-intensive, empirical, and subjective clinical assessments of motor behaviour and adverse events to adjust therapies. Accumulating evidence suggests that hypokinetic aspects of Parkinson's disease and their improvement with therapy are related to pathological neural activity in the beta band (beta oscillopathy) in the subthalamic nucleus. Additionally, effectiveness of deep brain stimulation may depend on modulation of the dorsolateral sensorimotor region of the subthalamic nucleus, which is the primary site of this beta oscillopathy. Despite the feasibility of utilizing this information to provide integrated, biomarker-driven precise deep brain stimulation, these measures have not been brought together in awake freely moving individuals. We sought to directly test whether stimulation-related improvements in bradykinesia were contingent on reduction of beta power and burst durations, and/or the volume of the sensorimotor subthalamic nucleus that was modulated. We recorded synchronized local field potentials and kinematic data in 16 subthalamic nuclei of individuals with Parkinson's disease chronically implanted with neurostimulators during a repetitive wrist-flexion extension task, while administering randomized different intensities of high frequency stimulation. Increased intensities of deep brain stimulation improved movement velocity and were associated with an intensity-dependent reduction in beta power and mean burst duration, measured during movement. The degree of reduction in this beta oscillopathy was associated with the improvement in movement velocity. Moreover, the reduction in beta power and beta burst durations was dependent on the theoretical degree of tissue modulated in the sensorimotor region of the subthalamic nucleus. Finally, the degree of attenuation of both beta power and beta burst durations, together with the degree of overlap of stimulation with the sensorimotor subthalamic nucleus significantly explained the stimulation-related improvement in movement velocity. The above results provide direct evidence that subthalamic nucleus deep brain stimulation-related improvements in bradykinesia are related to the reduction in beta oscillopathy within the sensorimotor region. With the advent of sensing neurostimulators, this beta oscillopathy combined with lead location could be used as a marker for real-time feedback to adjust clinical settings or to drive closed-loop deep brain stimulation in freely moving individuals with Parkinson's disease.
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Affiliation(s)
- Yasmine M Kehnemouyi
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Kevin B Wilkins
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Chioma M Anidi
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
- The University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Ross W Anderson
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Muhammad Furqan Afzal
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Helen M Bronte-Stewart
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
- Stanford University School of Medicine, Department of Neurosurgery, Stanford, CA, USA
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33
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Smith MD, Brazier DE, Henderson EJ. Current Perspectives on the Assessment and Management of Gait Disorders in Parkinson's Disease. Neuropsychiatr Dis Treat 2021; 17:2965-2985. [PMID: 34584414 PMCID: PMC8464370 DOI: 10.2147/ndt.s304567] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 08/25/2021] [Indexed: 12/31/2022] Open
Abstract
Gait dysfunction is a key defining feature of Parkinson's disease (PD), and is associated with symptoms of freezing and an increased risk of falls. In this narrative review, we cover the putative mechanisms of gait dysfunction in PD, the assessment of gait abnormalities, and the management of symptoms caused by the inherent difficulty in walking. Our understanding of the causes of gait problems in PD has progressed in recent times, moving from neurocognitive theory to correlates of affected neuronal pathways. In particular, this can be shown to correspond with abnormalities in responses to dual-task paradigms and dysfunction in cholinergic signaling. Great progress has been made in the sophistication and precision of gait assessment; however, it has firmly remained in the research domain. There is significant momentum behind wearable technologies that can be used by patients in their own environment, acting as digital biomarkers that can not only reflect progression but also independently discriminate PD from non-PD individuals. The treatment of gait dysfunction has historically relied on physical therapies and training combined with a view to mitigating the impact of such consequences as falls. Pharmacological therapies that are the mainstay of treatment in PD have tended to address symptoms like bradykinesia; however, optimization of dopaminergic therapies likely has a positive effect on quality of gait. Other targets have been assessed with the goal of improving gait, of which medications that improve cholinergic signaling appear most promising. Neuromodulation techniques are increasingly used in the form of deep-brain stimulation; however, standard targets, such as the globus pallidus interna, have a modest effect on gait. Considerable benefit has been seen through targeting the pedunculopontine nucleus, and a dual-target approach may be warranted. Stimulation of the spinal cord and brain through direct or magnetic approaches has been assessed, but requires further evidence.
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Affiliation(s)
- Matthew D Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,Older People's Unit, Royal United Hospital NHS Foundation Trust, Bath, UK
| | - Danielle E Brazier
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emily J Henderson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,Older People's Unit, Royal United Hospital NHS Foundation Trust, Bath, UK
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34
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Parakkal Unni M, Menon PP, Livi L, Wilson MR, Young WR, Bronte-Stewart HM, Tsaneva-Atanasova K. Data-Driven Prediction of Freezing of Gait Events From Stepping Data. FRONTIERS IN MEDICAL TECHNOLOGY 2020; 2:581264. [PMID: 35047881 PMCID: PMC8757792 DOI: 10.3389/fmedt.2020.581264] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 10/22/2020] [Indexed: 11/30/2022] Open
Abstract
Freezing of gait (FoG) is typically a symptom of advanced Parkinson's disease (PD) that negatively influences the quality of life and is often resistant to pharmacological interventions. Novel treatment options that make use of auditory or sensory cues might be optimized by prediction of freezing events. These predictions might help to trigger external sensory cues—shown to improve walking performance—when behavior is changed in a manner indicative of an impending freeze (i.e., when the user needs it the most), rather than delivering cue information continuously. A data-driven approach is proposed for predicting freezing events using Random Forrest (RF), Neural Network (NN), and Naive Bayes (NB) classifiers. Vertical forces, sampled at 100 Hz from a force platform were collected from 9 PD subjects as they stepped in place until they at least had one freezing episode or for 90 s. The F1 scores of RF/NN/NB algorithms were computed for different IL (input to the machine learning algorithm), and GL (how early the freezing event is predicted). A significant negative correlation between the F1 scores and GL, highlighting the difficulty of early detection is found. The IL that maximized the F1 score is approximately equal to 1.13 s. This indicates that the physiological (and therefore neurological) changes leading to freezing take effect at-least one step before the freezing incident. Our algorithm has the potential to support the development of devices to detect and then potentially prevent freezing events in people with Parkinson's which might occur if left uncorrected.
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Affiliation(s)
- Midhun Parakkal Unni
- Department of Mathematics, College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
- *Correspondence: Midhun Parakkal Unni
| | - Prathyush P. Menon
- Department of Mathematics, College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
| | - Lorenzo Livi
- Department of Computer Science, College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
- Departments of Computer Science and Mathematics, University of Manitoba, Winnipeg, MB, Canada
| | - Mark R. Wilson
- Sport & Health Sciences, University of Exeter, Exeter, United Kingdom
| | - William R. Young
- Sport & Health Sciences, University of Exeter, Exeter, United Kingdom
| | - Helen M. Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Krasimira Tsaneva-Atanasova
- Department of Mathematics, College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
- Department of Bioinformatics and Mathematical Modeling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
- Living Systems Institute, University of Exeter, Exeter, United Kingdom
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35
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Marquez JS, Hasan SMS, Siddiquee MR, Luca CC, Mishra VR, Mari Z, Bai O. Neural Correlates of Freezing of Gait in Parkinson's Disease: An Electrophysiology Mini-Review. Front Neurol 2020; 11:571086. [PMID: 33240199 PMCID: PMC7683766 DOI: 10.3389/fneur.2020.571086] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 09/23/2020] [Indexed: 12/13/2022] Open
Abstract
Freezing of gait (FoG) is a disabling symptom characterized as a brief inability to step or by short steps, which occurs when initiating gait or while turning, affecting over half the population with advanced Parkinson's disease (PD). Several non-competing hypotheses have been proposed to explain the pathophysiology and mechanism behind FoG. Yet, due to the complexity of FoG and the lack of a complete understanding of its mechanism, no clear consensus has been reached on the best treatment options. Moreover, most studies that aim to explore neural biomarkers of FoG have been limited to semi-static or imagined paradigms. One of the biggest unmet needs in the field is the identification of reliable biomarkers that can be construed from real walking scenarios to guide better treatments and validate medical and therapeutic interventions. Advances in neural electrophysiology exploration, including EEG and DBS, will allow for pathophysiology research on more real-to-life scenarios for better FoG biomarker identification and validation. The major aim of this review is to highlight the most up-to-date studies that explain the mechanisms underlying FoG through electrophysiology explorations. The latest methodological approaches used in the neurophysiological study of FoG are summarized, and potential future research directions are discussed.
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Affiliation(s)
- J. Sebastian Marquez
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, United States
| | - S. M. Shafiul Hasan
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, United States
| | - Masudur R. Siddiquee
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, United States
| | - Corneliu C. Luca
- Department of Neurology, University of Miami Hospital, Miami, FL, United States
| | - Virendra R. Mishra
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Las Vegas, NV, United States
| | - Zoltan Mari
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Las Vegas, NV, United States
| | - Ou Bai
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, United States
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36
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Gait-related frequency modulation of beta oscillatory activity in the subthalamic nucleus of parkinsonian patients. Brain Stimul 2020; 13:1743-1752. [DOI: 10.1016/j.brs.2020.09.006] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 09/13/2020] [Indexed: 01/24/2023] Open
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37
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Wang DD, Choi JT. Brain Network Oscillations During Gait in Parkinson's Disease. Front Hum Neurosci 2020; 14:568703. [PMID: 33192399 PMCID: PMC7645204 DOI: 10.3389/fnhum.2020.568703] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 09/29/2020] [Indexed: 11/15/2022] Open
Abstract
Human bipedal walking is a complex motor task that requires supraspinal control for balance and flexible coordination of timing and scaling of many muscles in different environment. Gait impairments are a hallmark of Parkinson’s disease (PD), reflecting dysfunction of cortico-basal ganglia-brainstem circuits. Recent studies using implanted electrodes and surface electroencephalography have demonstrated gait-related brain oscillations in the basal ganglia and cerebral cortex. Here, we review the physiological and pathophysiological roles of (1) basal ganglia oscillations, (2) cortical oscillations, and (3) basal ganglia-cortical interactions during walking. These studies extend a novel framework for movement of disorders where specific patterns of abnormal oscillatory synchronization in the basal ganglia thalamocortical network are associated with specific signs and symptoms. Therefore, we propose that many gait dysfunctions in PD arise from derangements in brain network, and discuss potential therapies aimed at restoring gait impairments through modulation of brain network in PD.
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Affiliation(s)
- Doris D Wang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Julia T Choi
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
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38
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O'Day JJ, Kehnemouyi YM, Petrucci MN, Anderson RW, Herron JA, Bronte-Stewart HM. Demonstration of Kinematic-Based Closed-loop Deep Brain Stimulation for Mitigating Freezing of Gait in People with Parkinson's Disease. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3612-3616. [PMID: 33018784 DOI: 10.1109/embc44109.2020.9176638] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Impaired gait in Parkinson's disease is marked by slow, arrhythmic stepping, and often includes freezing of gait episodes where alternating stepping halts completely. Wearable inertial sensors offer a way to detect these gait changes and novel deep brain stimulation (DBS) systems can respond with clinical therapy in a real-time, closed-loop fashion. In this paper, we present two novel closed-loop DBS algorithms, one using gait arrhythmicity and one using a logistic-regression model of freezing of gait detection as control signals. Benchtop validation results demonstrate the feasibility of running these algorithms in conjunction with a closed-loop DBS system by responding to real-time human subject kinematic data and pre-recorded data from leg-worn inertial sensors from a participant with Parkinson's disease. We also present a novel control policy algorithm that changes neurostimulator frequency in response to the kinematic inputs. These results provide a foundation for further development, iteration, and testing in a clinical trial for the first closed-loop DBS algorithms using kinematic signals to therapeutically improve and understand the pathophysiological mechanisms of gait impairment in Parkinson's disease.
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39
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Madrid J, Benninger DH. Non-invasive brain stimulation for Parkinson's disease: Clinical evidence, latest concepts and future goals: A systematic review. J Neurosci Methods 2020; 347:108957. [PMID: 33017643 DOI: 10.1016/j.jneumeth.2020.108957] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 08/27/2020] [Accepted: 09/18/2020] [Indexed: 12/16/2022]
Abstract
Parkinson's disease (PD) is becoming a major public-health issue in an aging population. Available approaches to treat advanced PD still have limitations; new therapies are needed. The non-invasive brain stimulation (NIBS) may offer a complementary approach to treat advanced PD by personalized stimulation. Although NIBS is not as effective as the gold-standard levodopa, recent randomized controlled trials show promising outcomes in the treatment of PD symptoms. Nevertheless, only a few NIBS-stimulation paradigms have shown to improve PD's symptoms. Current clinical recommendations based on the level of evidence are reported in Table 1 through Table 3. Furthermore, novel technological advances hold promise and may soon enable the non-invasive stimulation of deeper brain structures for longer periods.
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Affiliation(s)
- Julian Madrid
- Service of Neurology, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.
| | - David H Benninger
- Service of Neurology, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.
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40
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Hwang BY, Salimpour Y, Tsehay YK, Anderson WS, Mills KA. Perspective: Phase Amplitude Coupling-Based Phase-Dependent Neuromodulation in Parkinson's Disease. Front Neurosci 2020; 14:558967. [PMID: 33132822 PMCID: PMC7550534 DOI: 10.3389/fnins.2020.558967] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 08/13/2020] [Indexed: 11/13/2022] Open
Abstract
Deep brain stimulation (DBS) is an effective surgical therapy for Parkinson's disease (PD). However, limitations of the DBS systems have led to great interest in adaptive neuromodulation systems that can dynamically adjust stimulation parameters to meet concurrent therapeutic demand. Constant high-frequency motor cortex stimulation has not been remarkably efficacious, which has led to greater focus on modulation of subcortical targets. Understanding of the importance of timing in both cortical and subcortical stimulation has generated an interest in developing more refined, parsimonious stimulation techniques based on critical oscillatory activities of the brain. Concurrently, much effort has been put into identifying biomarkers of both parkinsonian and physiological patterns of neuronal activities to drive next generation of adaptive brain stimulation systems. One such biomarker is beta-gamma phase amplitude coupling (PAC) that is detected in the motor cortex. PAC is strongly correlated with parkinsonian specific motor signs and symptoms and respond to therapies in a dose-dependent manner. PAC may represent the overall state of the parkinsonian motor network and have less instantaneously dynamic fluctuation during movement. These findings raise the possibility of novel neuromodulation paradigms that are potentially less invasiveness than DBS. Successful application of PAC in neuromodulation may necessitate phase-dependent stimulation technique, which aims to deliver precisely timed stimulation pulses to a specific phase to predictably modulate to selectively modulate pathological network activities and behavior in real time. Overcoming current technical challenges can lead to deeper understanding of the parkinsonian pathophysiology and development of novel neuromodulatory therapies with potentially less side-effects and higher therapeutic efficacy.
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Affiliation(s)
- Brian Y Hwang
- Functional Neurosurgery Laboratory, Division of Functional Neurosurgery, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Yousef Salimpour
- Functional Neurosurgery Laboratory, Division of Functional Neurosurgery, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Yohannes K Tsehay
- Functional Neurosurgery Laboratory, Division of Functional Neurosurgery, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - William S Anderson
- Functional Neurosurgery Laboratory, Division of Functional Neurosurgery, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Kelly A Mills
- Neuromodulation and Advanced Therapies Clinic, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, United States
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41
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Bronte-Stewart HM, Petrucci MN, O’Day JJ, Afzal MF, Parker JE, Kehnemouyi YM, Wilkins KB, Orthlieb GC, Hoffman SL. Perspective: Evolution of Control Variables and Policies for Closed-Loop Deep Brain Stimulation for Parkinson's Disease Using Bidirectional Deep-Brain-Computer Interfaces. Front Hum Neurosci 2020; 14:353. [PMID: 33061899 PMCID: PMC7489234 DOI: 10.3389/fnhum.2020.00353] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 08/05/2020] [Indexed: 11/21/2022] Open
Abstract
A deep brain stimulation system capable of closed-loop neuromodulation is a type of bidirectional deep brain-computer interface (dBCI), in which neural signals are recorded, decoded, and then used as the input commands for neuromodulation at the same site in the brain. The challenge in assuring successful implementation of bidirectional dBCIs in Parkinson's disease (PD) is to discover and decode stable, robust and reliable neural inputs that can be tracked during stimulation, and to optimize neurostimulation patterns and parameters (control policies) for motor behaviors at the brain interface, which are customized to the individual. In this perspective, we will outline the work done in our lab regarding the evolution of the discovery of neural and behavioral control variables relevant to PD, the development of a novel personalized dual-threshold control policy relevant to the individual's therapeutic window and the application of these to investigations of closed-loop STN DBS driven by neural or kinematic inputs, using the first generation of bidirectional dBCIs.
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Affiliation(s)
- Helen M. Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Matthew N. Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Johanna J. O’Day
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Bioengineering, Stanford University, Stanford, CA, United States
| | - Muhammad Furqan Afzal
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Jordan E. Parker
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Yasmine M. Kehnemouyi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Gerrit C. Orthlieb
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Shannon L. Hoffman
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
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42
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David FJ, Munoz MJ, Corcos DM. The effect of STN DBS on modulating brain oscillations: consequences for motor and cognitive behavior. Exp Brain Res 2020; 238:1659-1676. [PMID: 32494849 PMCID: PMC7415701 DOI: 10.1007/s00221-020-05834-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 05/15/2020] [Indexed: 12/11/2022]
Abstract
In this review, we highlight Professor John Rothwell's contribution towards understanding basal ganglia function and dysfunction, as well as the effects of subthalamic nucleus deep brain stimulation (STN DBS). The first section summarizes the rate and oscillatory models of basal ganglia dysfunction with a focus on the oscillation model. The second section summarizes the motor, gait, and cognitive mechanisms of action of STN DBS. In the final section, we summarize the effects of STN DBS on motor and cognitive tasks. The studies reviewed in this section support the conclusion that high-frequency STN DBS improves the motor symptoms of Parkinson's disease. With respect to cognition, STN DBS can be detrimental to performance especially when the task is cognitively demanding. Consolidating findings from many studies, we find that while motor network oscillatory activity is primarily correlated to the beta-band, cognitive network oscillatory activity is not confined to one band but is subserved by activity in multiple frequency bands. Because of these findings, we propose a modified motor and associative/cognitive oscillatory model that can explain the consistent positive motor benefits and the negative and null cognitive effects of STN DBS. This is clinically relevant because STN DBS should enhance oscillatory activity that is related to both motor and cognitive networks to improve both motor and cognitive performance.
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Affiliation(s)
- Fabian J David
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, 645 North Michigan Avenue, Suite 1100, Chicago, IL, 60611, USA.
| | - Miranda J Munoz
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, 645 North Michigan Avenue, Suite 1100, Chicago, IL, 60611, USA
| | - Daniel M Corcos
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, 645 North Michigan Avenue, Suite 1100, Chicago, IL, 60611, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
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43
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Anderson RW, Kehnemouyi YM, Neuville RS, Wilkins KB, Anidi CM, Petrucci MN, Parker JE, Velisar A, Brontë-Stewart HM. A novel method for calculating beta band burst durations in Parkinson's disease using a physiological baseline. J Neurosci Methods 2020; 343:108811. [PMID: 32565222 DOI: 10.1016/j.jneumeth.2020.108811] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 05/26/2020] [Accepted: 06/14/2020] [Indexed: 01/23/2023]
Abstract
BACKGROUND Pathologically prolonged bursts of neural activity in the 8-30 Hz frequency range in Parkinson's disease have been measured using high power event detector thresholds. NEW METHOD This study introduces a novel method for determining beta bursts using a power baseline based on spectral activity that overlapped a simulated 1/f spectrum. We used resting state local field potentials from people with Parkinson's disease and a simulated 1/f signal to measure beta burst durations, to demonstrate how tuning parameters (i.e., bandwidth and center frequency) affect burst durations, to compare burst duration distributions with high power threshold methods, and to study the effect of increasing neurostimulation intensities on burst duration. RESULTS The baseline method captured a broad distribution of resting state beta band burst durations. Mean beta band burst durations were significantly shorter on compared to off neurostimulation (p = 0.0046), and their distribution shifted towards that of the 1/f spectrum during increasing intensities of stimulation. COMPARISON WITH EXISTING METHODS High power event detection methods, measure duration of higher power bursts and omit portions of the neural signal. The baseline method captured the broadest distribution of burst durations and was more sensitive than high power detection methods in demonstrating the effect of neurostimulation on beta burst duration. CONCLUSIONS The baseline method captured a broad range of fluctuations in beta band neural activity and demonstrated that subthalamic neurostimulation shortened burst durations in a dose (intensity) dependent manner, suggesting that beta burst duration is a useful control variable for closed loop algorithms.
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Affiliation(s)
- R W Anderson
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Y M Kehnemouyi
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - R S Neuville
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA; The University of California School of Medicine, Irvine, CA, USA
| | - K B Wilkins
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - C M Anidi
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA; The University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - M N Petrucci
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - J E Parker
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - A Velisar
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA; The Smith-Kettlewell Eye Research Institute, San Francisco, CA, USA
| | - H M Brontë-Stewart
- Stanford University School of Medicine, Department of Neurology and Neurological Sciences, Stanford, CA, USA; Stanford University School of Medicine, Department of Neurosurgery, Stanford, CA, USA.
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44
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Pozzi NG, Canessa A, Palmisano C, Brumberg J, Steigerwald F, Reich MM, Minafra B, Pacchetti C, Pezzoli G, Volkmann J, Isaias IU. Freezing of gait in Parkinson's disease reflects a sudden derangement of locomotor network dynamics. Brain 2020; 142:2037-2050. [PMID: 31505548 PMCID: PMC6598629 DOI: 10.1093/brain/awz141] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Revised: 03/20/2019] [Accepted: 04/02/2019] [Indexed: 01/07/2023] Open
Abstract
Freezing of gait is a disabling symptom of Parkinson's disease that causes a paroxysmal inability to generate effective stepping. The underlying pathophysiology has recently migrated towards a dysfunctional supraspinal locomotor network, but the actual network derangements during ongoing gait freezing are unknown. We investigated the communication between the cortex and the subthalamic nucleus, two main nodes of the locomotor network, in seven freely-moving subjects with Parkinson's disease with a novel deep brain stimulation device, which allows on-demand recording of subthalamic neural activity from the chronically-implanted electrodes months after the surgical procedure. Multisite neurophysiological recordings during (effective) walking and ongoing gait freezing were combined with kinematic measurements and individual molecular brain imaging studies. Patients walked in a supervised environment closely resembling everyday life challenges. We found that during (effective) walking, the cortex and subthalamic nucleus were synchronized in a low frequency band (4-13 Hz). In contrast, gait freezing was characterized in every patient by low frequency cortical-subthalamic decoupling in the hemisphere with less striatal dopaminergic innervation. Of relevance, this decoupling was already evident at the transition from normal (effective) walking into gait freezing, was maintained during the freezing episode, and resolved with recovery of the effective walking pattern. This is the first evidence for a decoding of the networked processing of locomotion in Parkinson's disease and suggests that freezing of gait is a 'circuitopathy' related to a dysfunctional cortical-subcortical communication. A successful therapeutic approach for gait freezing in Parkinson's disease should aim at directly targeting derangements of neural network dynamics.
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Affiliation(s)
- Nicoló G Pozzi
- Department of Neurology, University Hospital and Julius Maximilian University, Würzburg, Germany
| | - Andrea Canessa
- Fondazione Europea di Ricerca Biomedica (FERB Onlus), Cernusco s/N (Milan), Italy.,Department of Informatics, Bioengineering, Robotics and System Engineering, University of Genoa, Genoa, Italy
| | - Chiara Palmisano
- Department of Neurology, University Hospital and Julius Maximilian University, Würzburg, Germany.,Department of Electronics, Information and Bioengineering, MBMC Lab, Politecnico di Milano, Milan, Italy
| | - Joachim Brumberg
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Frank Steigerwald
- Department of Neurology, University Hospital and Julius Maximilian University, Würzburg, Germany
| | - Martin M Reich
- Department of Neurology, University Hospital and Julius Maximilian University, Würzburg, Germany
| | - Brigida Minafra
- Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Claudio Pacchetti
- Parkinson and Movement Disorder Unit, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Jens Volkmann
- Department of Neurology, University Hospital and Julius Maximilian University, Würzburg, Germany
| | - Ioannis U Isaias
- Department of Neurology, University Hospital and Julius Maximilian University, Würzburg, Germany.,Centro Parkinson ASST G. Pini-CTO, Milan, Italy
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45
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O’Day J, Syrkin-Nikolau J, Anidi C, Kidzinski L, Delp S, Bronte-Stewart H. The turning and barrier course reveals gait parameters for detecting freezing of gait and measuring the efficacy of deep brain stimulation. PLoS One 2020; 15:e0231984. [PMID: 32348346 PMCID: PMC7190141 DOI: 10.1371/journal.pone.0231984] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 04/03/2020] [Indexed: 01/06/2023] Open
Abstract
Freezing of gait (FOG) is a devastating motor symptom of Parkinson’s disease that leads to falls, reduced mobility, and decreased quality of life. Reliably eliciting FOG has been difficult in the clinical setting, which has limited discovery of pathophysiology and/or documentation of the efficacy of treatments, such as different frequencies of subthalamic deep brain stimulation (STN DBS). In this study we validated an instrumented gait task, the turning and barrier course (TBC), with the international standard FOG questionnaire question 3 (FOG-Q3, r = 0.74, p < 0.001). The TBC is easily assembled and mimics real-life environments that elicit FOG. People with Parkinson’s disease who experience FOG (freezers) spent more time freezing during the TBC compared to during forward walking (p = 0.007). Freezers also exhibited greater arrhythmicity during non-freezing gait when performing the TBC compared to forward walking (p = 0.006); this difference in gait arrhythmicity between tasks was not detected in non-freezers or controls. Freezers’ non-freezing gait was more arrhythmic than that of non-freezers or controls during all walking tasks (p < 0.05). A logistic regression model determined that a combination of gait arrhythmicity, stride time, shank angular range, and asymmetry had the greatest probability of classifying a step as FOG (area under receiver operating characteristic curve = 0.754). Freezers’ percent time freezing and non-freezing gait arrhythmicity decreased, and their shank angular velocity increased in the TBC during both 60 Hz and 140 Hz STN DBS (p < 0.05) to non-freezer values. The TBC is a standardized tool for eliciting FOG and demonstrating the efficacy of 60 Hz and 140 Hz STN DBS for gait impairment and FOG. The TBC revealed gait parameters that differentiated freezers from non-freezers and best predicted FOG; these may serve as relevant control variables for closed loop neurostimulation for FOG in Parkinson’s disease.
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Affiliation(s)
- Johanna O’Day
- Department of Bioengineering, Stanford University, Stanford, California, United States of America
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California, United States of America
| | - Judy Syrkin-Nikolau
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California, United States of America
| | - Chioma Anidi
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California, United States of America
| | - Lukasz Kidzinski
- Department of Bioengineering, Stanford University, Stanford, California, United States of America
| | - Scott Delp
- Department of Bioengineering, Stanford University, Stanford, California, United States of America
| | - Helen Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, California, United States of America
- Department of Neurosurgery, Stanford University, Stanford, California, United States of America
- * E-mail:
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46
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Weber I, Florin E, von Papen M, Visser-Vandewalle V, Timmermann L. Characterization of information processing in the subthalamic area of Parkinson’s patients. Neuroimage 2020; 209:116518. [DOI: 10.1016/j.neuroimage.2020.116518] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 12/19/2019] [Accepted: 01/02/2020] [Indexed: 12/21/2022] Open
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47
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Fleming JE, Dunn E, Lowery MM. Simulation of Closed-Loop Deep Brain Stimulation Control Schemes for Suppression of Pathological Beta Oscillations in Parkinson's Disease. Front Neurosci 2020; 14:166. [PMID: 32194372 PMCID: PMC7066305 DOI: 10.3389/fnins.2020.00166] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 02/14/2020] [Indexed: 11/17/2022] Open
Abstract
This study presents a computational model of closed-loop control of deep brain stimulation (DBS) for Parkinson's disease (PD) to investigate clinically viable control schemes for suppressing pathological beta-band activity. Closed-loop DBS for PD has shown promising results in preliminary clinical studies and offers the potential to achieve better control of patient symptoms and side effects with lower power consumption than conventional open-loop DBS. However, extensive testing of algorithms in patients is difficult. The model presented provides a means to explore a range of control algorithms in silico and optimize control parameters before preclinical testing. The model incorporates (i) the extracellular DBS electric field, (ii) antidromic and orthodromic activation of STN afferent fibers, (iii) the LFP detected at non-stimulating contacts on the DBS electrode and (iv) temporal variation of network beta-band activity within the thalamo-cortico-basal ganglia loop. The performance of on-off and dual-threshold controllers for suppressing beta-band activity by modulating the DBS amplitude were first verified, showing levels of beta suppression and reductions in power consumption comparable with previous clinical studies. Proportional (P) and proportional-integral (PI) closed-loop controllers for amplitude and frequency modulation were then investigated. A simple tuning rule was derived for selecting effective PI controller parameters to target long duration beta bursts while respecting clinical constraints that limit the rate of change of stimulation parameters. Of the controllers tested, PI controllers displayed superior performance for regulating network beta-band activity whilst accounting for clinical considerations. Proportional controllers resulted in undesirable rapid fluctuations of the DBS parameters which may exceed clinically tolerable rate limits. Overall, the PI controller for modulating DBS frequency performed best, reducing the mean error by 83% compared to DBS off and the mean power consumed to 25% of that utilized by open-loop DBS. The network model presented captures sufficient physiological detail to act as a surrogate for preclinical testing of closed-loop DBS algorithms using a clinically accessible biomarker, providing a first step for deriving and testing novel, clinically suitable closed-loop DBS controllers.
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Affiliation(s)
- John E. Fleming
- Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland
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48
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Darbin O, Hatanaka N, Takara S, Kaneko N, Chiken S, Naritoku D, Martino A, Nambu A. Parkinsonism Differently Affects the Single Neuronal Activity in the Primary and Supplementary Motor Areas in Monkeys: An Investigation in Linear and Nonlinear Domains. Int J Neural Syst 2020; 30:2050010. [PMID: 32019380 DOI: 10.1142/s0129065720500100] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The changes in neuronal firing activity in the primary motor cortex (M1) and supplementary motor area (SMA) were compared in monkeys rendered parkinsonian by treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The neuronal dynamic was characterized using mathematical tools defined in different frameworks (rate, oscillations or complex patterns). Then, and for each cortical area, multivariate and discriminate analyses were further performed on these features to identify those important to differentiate between the normal and the pathological neuronal activity. Our results show a different order in the importance of the features to discriminate the pathological state in each cortical area which suggests that the M1 and the SMA exhibit dissimilarities in their neuronal alterations induced by parkinsonism. Our findings highlight the need for multiple mathematical frameworks to best characterize the pathological neuronal activity related to parkinsonism. Future translational studies are warranted to investigate the causal relationships between cortical region-specificities, dominant pathological hallmarks and symptoms.
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Affiliation(s)
- Olivier Darbin
- Department of Neurology, University South Alabama, 307 University Blvd, Mobile, AL 36688, USA
| | - Nobuhiko Hatanaka
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
| | - Sayuki Takara
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
| | - Nobuya Kaneko
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
| | - Satomi Chiken
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
| | - Dean Naritoku
- Department of Neurology, University South Alabama, 307 University Blvd, Mobile, AL 36688, USA
| | - Anthony Martino
- Department of Neurology, University South Alabama, 307 University Blvd, Mobile, AL 36688, USA
| | - Atsushi Nambu
- Division of System Neurophysiology, National Institute for Physiological Sciences and Department of Physiological Sciences, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Aichi 444-8585, Japan
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49
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Fleming JE, Lowery MM. Changes in Neuronal Entropy in a Network Model of the Cortico-Basal Ganglia during Deep Brain Stimulation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:5172-5175. [PMID: 31947023 DOI: 10.1109/embc.2019.8857440] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Neuronal entropy changes are observed in the basal ganglia circuit in Parkinson's disease (PD). These changes are observed in both single unit recordings from globus pallidus (GP) neurons and in local field potential (LFP) recordings from the subthalamic nucleus (STN). These changes are hypothesized as representing changes in the information coding capacity of the network, with PD resulting in a reduction in the coding capacity of the basal ganglia network. Entropy changes in the LFP and in single unit recordings are investigated in a detailed physiological model of the cortico-basal ganglia network during STN deep brain stimulation (DBS). The model incorporates extracellular stimulation of STN afferent fibers, with both orthodromic and antidromic activation, and simulation of the LFP detected at a differential recording electrode. LFP sample entropy and beta-band oscillation power were found to be altered following the application of DBS. The ring pattern entropy of GP neurons in the network were observed to decrease during high frequency stimulation and increase during low frequency stimulation. Simulation results were consistent with experimentally reported changes in neuronal entropy during DBS.
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50
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Georgiades MJ, Shine JM, Gilat M, McMaster J, Owler B, Mahant N, Lewis SJG. Hitting the brakes: pathological subthalamic nucleus activity in Parkinson’s disease gait freezing. Brain 2019; 142:3906-3916. [DOI: 10.1093/brain/awz325] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Accepted: 08/22/2019] [Indexed: 11/14/2022] Open
Abstract
The neurobiology of gait freezing in Parkinson’s disease is poorly understood and therapies are largely ineffective. Using a virtual reality task to elicit freezing intra-operatively during implantation of DBS electrodes, Georgiades et al. identify pathological subthalamic nucleus activity associated with freezing onset and discernible from that of volitional stopping.
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Affiliation(s)
- Matthew J Georgiades
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Australia
- Sydney Medical School, The University of Sydney, Australia
| | - James M Shine
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Australia
- Sydney Medical School, The University of Sydney, Australia
| | - Moran Gilat
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Australia
- Research Group for Neuromotor Rehabilitation, Department of Rehabilitation Sciences, KU Leuven, Belgium
| | | | - Brian Owler
- Westmead Private Hospital, Sydney, Australia
| | - Neil Mahant
- Sydney Medical School, The University of Sydney, Australia
- Westmead Private Hospital, Sydney, Australia
| | - Simon J G Lewis
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Australia
- Sydney Medical School, The University of Sydney, Australia
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