1
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Callahan JW, Morales JC, Atherton JF, Wang D, Kostic S, Bevan MD. Movement-related increases in subthalamic activity optimize locomotion. Cell Rep 2024; 43:114495. [PMID: 39068661 DOI: 10.1016/j.celrep.2024.114495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 05/27/2024] [Accepted: 06/27/2024] [Indexed: 07/30/2024] Open
Abstract
The subthalamic nucleus (STN) is traditionally thought to restrict movement. Lesion or prolonged STN inhibition increases movement vigor and propensity, while optogenetic excitation has opposing effects. However, STN neurons often exhibit movement-related increases in firing. To address this paradox, STN activity was recorded and manipulated in head-fixed mice at rest and during self-initiated and self-paced treadmill locomotion. We found that (1) most STN neurons (type 1) exhibit locomotion-dependent increases in activity, with half firing preferentially during the propulsive phase of the contralateral locomotor cycle; (2) a minority of STN neurons exhibit dips in activity or are uncorrelated with movement; (3) brief optogenetic inhibition of the lateral STN (where type 1 neurons are concentrated) slows and prematurely terminates locomotion; and (4) in Q175 Huntington's disease mice, abnormally brief, low-velocity locomotion is associated with type 1 hypoactivity. Together, these data argue that movement-related increases in STN activity contribute to optimal locomotor performance.
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Affiliation(s)
- Joshua W Callahan
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Juan Carlos Morales
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Jeremy F Atherton
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Dorothy Wang
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Selena Kostic
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Mark D Bevan
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
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2
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D'Ascanio I, Giannini G, Baldelli L, Cani I, Giannoni A, Leogrande G, Lopane G, Calandra-Buonaura G, Cortelli P, Chiari L, Palmerini L. A method for the synchronization of inertial sensor signals and local field potentials from deep brain stimulation systems. Biomed Phys Eng Express 2024; 10:057001. [PMID: 38959873 DOI: 10.1088/2057-1976/ad5e83] [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: 04/15/2024] [Accepted: 07/03/2024] [Indexed: 07/05/2024]
Abstract
Objective. Recent innovative neurostimulators allow recording local field potentials (LFPs) while performing motor tasks monitored by wearable sensors. Inertial sensors can provide quantitative measures of motor impairment in people with subthalamic nucleus deep brain stimulation. To the best of our knowledge, there is no validated method to synchronize inertial sensors and neurostimulators without an additional device. This study aims to define a new synchronization method to analyze disease-related brain activity patterns during specific motor tasks and evaluate how LFPs are affected by stimulation and medication.Approach. Fourteen male subjects treated with subthalamic nucleus deep brain stimulation were recruited to perform motor tasks in four different medication and stimulation conditions. In each condition, a synchronization protocol was performed consisting of taps on the implanted neurostimulator, which produces artifacts in the LFPs that a nearby inertial sensor can simultaneously record.Main results. In 64% of the recruited subjects, induced artifacts were detected at least in one condition. Among those subjects, 83% of the recordings could be synchronized offline analyzing LFPs and wearables data. The remaining recordings were synchronized by video analysis.Significance. The proposed synchronization method does not require an external system (e.g., TENS electrodes) and can be easily integrated into clinical practice. The procedure is simple and can be carried out in a short time. A proper and simple synchronization will also be useful to analyze subthalamic neural activity in the presence of specific events (e.g., freezing of gait events) to identify predictive biomarkers.
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Affiliation(s)
- Ilaria D'Ascanio
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" (DEI), University of Bologna, Bologna, Italy
| | - Giulia Giannini
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Luca Baldelli
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Ilaria Cani
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Alice Giannoni
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" (DEI), University of Bologna, Bologna, Italy
| | | | - Giovanna Lopane
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Giovanna Calandra-Buonaura
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Pietro Cortelli
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Lorenzo Chiari
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" (DEI), University of Bologna, Bologna, Italy
- Health Sciences and Technologies - Interdepartmental Center for Industrial Research (CIRI-SDV), University of Bologna, Bologna, Italy
| | - Luca Palmerini
- Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" (DEI), University of Bologna, Bologna, Italy
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3
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Welter ML, Lehongre K, Faillot M, Collomb-Clerc A, Belaid H, Lau B, Karachi C. Virtual walking through a doorway promotes a beta-gamma power imbalance in the subthalamic nucleus in Parkinson's disease. Clin Neurophysiol 2024; 162:28-30. [PMID: 38554472 DOI: 10.1016/j.clinph.2024.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 03/14/2024] [Accepted: 03/14/2024] [Indexed: 04/01/2024]
Affiliation(s)
- Marie-Laure Welter
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital Pitié-Salpêtrière, Paris, France; PANAM Platform, CENIR, ICM, Paris, France; Neurophysiology Department, Rouen University Hospital, CHU Rouen, Rouen, France; University of Rouen, Rouen, France.
| | - Katia Lehongre
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital Pitié-Salpêtrière, Paris, France; STIM Platform, CENIR, ICM, Paris, France
| | - Matthieu Faillot
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital Pitié-Salpêtrière, Paris, France; Neurosurgery Department AP-HP, Hôpitaux Universitaires Pitié Salpêtrière - Charles Foix, Paris, France
| | - Antoine Collomb-Clerc
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital Pitié-Salpêtrière, Paris, France
| | - Hayat Belaid
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital Pitié-Salpêtrière, Paris, France; Neurosurgery Department AP-HP, Hôpitaux Universitaires Pitié Salpêtrière - Charles Foix, Paris, France
| | - Brian Lau
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital Pitié-Salpêtrière, Paris, France
| | - Carine Karachi
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital Pitié-Salpêtrière, Paris, France; STIM Platform, CENIR, ICM, Paris, France; Neurosurgery Department AP-HP, Hôpitaux Universitaires Pitié Salpêtrière - Charles Foix, Paris, France
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Callahan JW, Morales JC, Atherton JF, Wang D, Kostic S, Bevan MD. Movement-related increases in subthalamic activity optimize locomotion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.07.570617. [PMID: 38105984 PMCID: PMC10723456 DOI: 10.1101/2023.12.07.570617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The subthalamic nucleus (STN) is traditionally thought to restrict movement. Lesion or prolonged STN inhibition increases movement vigor and propensity, while ontogenetic excitation typically has opposing effects. Subthalamic and motor activity are also inversely correlated in movement disorders. However, most STN neurons exhibit movement-related increases in firing. To address this paradox, STN activity was recorded and manipulated in head-fixed mice at rest and during self-initiated treadmill locomotion. The majority of STN neurons (type 1) exhibited locomotion-dependent increases in activity, with half encoding the locomotor cycle. A minority of neurons exhibited dips in activity or were uncorrelated with movement. Brief optogenetic inhibition of the dorsolateral STN (where type 1 neurons are concentrated) slowed and prematurely terminated locomotion. In Q175 Huntington's disease mice abnormally brief, low-velocity locomotion was specifically associated with type 1 hyperactivity. Together these data argue that movement-related increases in STN activity contribute to optimal locomotor performance.
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Yin Z, Yuan T, Yang A, Xu Y, Zhu G, An Q, Ma R, Gan Y, Shi L, Bai Y, Zhang N, Wang C, Jiang Y, Meng F, Neumann WJ, Tan H, Zhang JG. Contribution of basal ganglia activity to REM sleep disorder in Parkinson's disease. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-332014. [PMID: 38641368 DOI: 10.1136/jnnp-2023-332014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 03/14/2024] [Indexed: 04/21/2024]
Abstract
BACKGROUND Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the most common sleep problems and represents a key prodromal marker in Parkinson's disease (PD). It remains unclear whether and how basal ganglia nuclei, structures that are directly involved in the pathology of PD, are implicated in the occurrence of RBD. METHOD Here, in parallel with whole-night video polysomnography, we recorded local field potentials from two major basal ganglia structures, the globus pallidus internus and subthalamic nucleus, in two cohorts of patients with PD who had varied severity of RBD. Basal ganglia oscillatory patterns during RBD and REM sleep without atonia were analysed and compared with another age-matched cohort of patients with dystonia that served as controls. RESULTS We found that beta power in both basal ganglia nuclei was specifically elevated during REM sleep without atonia in patients with PD, but not in dystonia. Basal ganglia beta power during REM sleep positively correlated with the extent of atonia loss, with beta elevation preceding the activation of chin electromyogram activities by ~200 ms. The connectivity between basal ganglia beta power and chin muscular activities during REM sleep was significantly correlated with the clinical severity of RBD in PD. CONCLUSIONS These findings support that basal ganglia activities are associated with if not directly contribute to the occurrence of RBD in PD. Our study expands the understanding of the role basal ganglia played in RBD and may foster improved therapies for RBD by interrupting the basal ganglia-muscular communication during REM sleep in PD.
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Affiliation(s)
- Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Campus Mitte, Charite - Universitatsmedizin Berlin, Berlin, Germany
| | - Tianshuo Yuan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yichen Xu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Qi An
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yifei Gan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lin Shi
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yutong Bai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ning Zhang
- Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunxue Wang
- Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Campus Mitte, Charite - Universitatsmedizin Berlin, Berlin, Germany
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Jian-Guo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
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Marano M, Anzini G, Saltarocchi L, Ricciuti R, Capone F, Tan H, Torrecillos F, Lanzone J, Lazzaro VD. Left Vagus Stimulation Modulates Contralateral Subthalamic β Power Improving the Gait in Parkinson's Disease. Mov Disord 2024; 39:424-428. [PMID: 38111224 PMCID: PMC7615838 DOI: 10.1002/mds.29690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 11/09/2023] [Accepted: 11/28/2023] [Indexed: 12/20/2023] Open
Abstract
BACKGROUND Transcutaneous vagus nerve stimulation (VNS) showed early evidence of efficacy for the gait treatment of Parkinson's disease (PD). OBJECTIVES Providing data on neurophysiological and clinical effects of transauricular VNS (taVNS). METHODS Ten patients with recording deep brain stimulation (DBS) have been enrolled in a within participant design pilot study, double-blind crossover sham-controlled trial of taVNS. Subthalamic local field potentials (β band power), Unified Parkinson's Disease Rating Scales (UPDRS), and a digital timed-up-and-go test (TUG) were measured and compared with real versus sham taVNS during medication-off/DBS-OFF condition. RESULTS The left taVNS induced a reduction of the total β power in the contralateral (ie, right) subthalamic nucleus and an improvement of TUG time, speed, and variability. The taVNS-induced β reduction correlated with the improvement of gait speed. No major clinical changes were observed at UPDRS. CONCLUSIONS taVNS is a promising strategy for the management of PD gait, deserving prospective trials of chronic neuromodulation. © 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)
- Massimo Marano
- Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy
| | - Gaia Anzini
- Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy
| | - Luca Saltarocchi
- Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Roma, Italy
| | - Riccardo Ricciuti
- Neurosurgery Unit, Ospedale Belcolle, ASL di Viterbo, Viterbo, Italy
| | - Fioravante Capone
- Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Flavie Torrecillos
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jacopo Lanzone
- Department of the Neurorehabilitation, Istituti Clinici Scientifici Maugeri IRCCS, Milano Institute, Milan, Italy
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Roma, Italy
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7
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Burtscher J, Moraud EM, Malatesta D, Millet GP, Bally JF, Patoz A. Exercise and gait/movement analyses in treatment and diagnosis of Parkinson's Disease. Ageing Res Rev 2024; 93:102147. [PMID: 38036102 DOI: 10.1016/j.arr.2023.102147] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/23/2023] [Accepted: 11/23/2023] [Indexed: 12/02/2023]
Abstract
Cardinal motor symptoms in Parkinson's disease (PD) include bradykinesia, rest tremor and/or rigidity. This symptomatology can additionally encompass abnormal gait, balance and postural patterns at advanced stages of the disease. Besides pharmacological and surgical therapies, physical exercise represents an important strategy for the management of these advanced impairments. Traditionally, diagnosis and classification of such abnormalities have relied on partially subjective evaluations performed by neurologists during short and temporally scattered hospital appointments. Emerging sports medical methods, including wearable sensor-based movement assessment and computational-statistical analysis, are paving the way for more objective and systematic diagnoses in everyday life conditions. These approaches hold promise to facilitate customizing clinical trials to specific PD groups, as well as personalizing neuromodulation therapies and exercise prescriptions for each individual, remotely and regularly, according to disease progression or specific motor symptoms. We aim to summarize exercise benefits for PD with a specific emphasis on gait and balance deficits, and to provide an overview of recent advances in movement analysis approaches, notably from the sports science community, with value for diagnosis and prognosis. Although such techniques are becoming increasingly available, their standardization and optimization for clinical purposes is critically missing, especially in their translation to complex neurodegenerative disorders such as PD. We highlight the importance of integrating state-of-the-art gait and movement analysis approaches, in combination with other motor, electrophysiological or neural biomarkers, to improve the understanding of the diversity of PD phenotypes, their response to therapies and the dynamics of their disease progression.
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Affiliation(s)
- Johannes Burtscher
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland.
| | - Eduardo Martin Moraud
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Defitech Centre for Interventional Neurotherapies (NeuroRestore), UNIL-CHUV and Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Davide Malatesta
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland
| | - Grégoire P Millet
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland
| | - Julien F Bally
- Service of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Aurélien Patoz
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland; Research and Development Department, Volodalen Swiss Sport Lab, Aigle, Switzerland
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8
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Tran S, Heida TC, Heijs JJA, Al-Ozzi T, Sumarac S, Alanazi FI, Kalia SK, Hodaie M, Lozano AM, Milosevic L, Chen R, Hutchison WD. Subthalamic and pallidal neurons are modulated during externally cued movements in Parkinson's disease. Neurobiol Dis 2024; 190:106384. [PMID: 38135193 DOI: 10.1016/j.nbd.2023.106384] [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: 07/03/2023] [Revised: 12/13/2023] [Accepted: 12/13/2023] [Indexed: 12/24/2023] Open
Abstract
External sensory cues can reduce freezing of gait in people with Parkinson's disease (PD), yet the role of the basal ganglia in these movements is unclear. We used microelectrode recordings to examine modulations in single unit (SU) and oscillatory local field potentials (LFP) during auditory-cued rhythmic pedaling movements of the feet. We tested five blocks of increasing cue frequencies (1 Hz, 1.5 Hz, 2 Hz, 2.5 Hz, and 3 Hz) in 24 people with PD undergoing deep brain stimulation surgery of the subthalamic nucleus (STN) or globus pallidus internus (GPi). Single unit firing and beta band LFPs (13-30 Hz) in response to movement onsets or cue onsets were examined. We found that the timing accuracy of foot pedaling decreased with faster cue frequencies. Increasing cue frequencies also attenuated firing rates in both STN and GPi neurons. Peak beta power in the GPi and STN showed different responses to the task. GPi beta power showed persistent suppression with fast cues and phasic modulation with slow cues. STN beta power showed enhanced beta synchronization following movement. STN beta power also correlated with rate of pedaling. Overall, we showed task-related responses in the GPi and STN during auditory-cued movements with differential roles in sensory and motor control. The results suggest a role for both input and output basal ganglia nuclei in auditory rhythmic pacing of gait-like movements in PD.
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Affiliation(s)
- Stephanie Tran
- Institute of Medical Science, University of Toronto, Ontario, Canada
| | - Tjitske C Heida
- Department of Biomedical Signals and Systems, University of Twente, Enschede, the Netherlands
| | - Janne J A Heijs
- Department of Biomedical Signals and Systems, University of Twente, Enschede, the Netherlands
| | - Tameem Al-Ozzi
- Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Ontario, Canada
| | - Srdjan Sumarac
- Krembil Brain Institute, Leonard Ave, Toronto, Ontario, Canada; Department of Biomedical Engineering, University of Toronto, Canada
| | - Frhan I Alanazi
- Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Ontario, Canada
| | - Suneil K Kalia
- Division of Neurosurgery, Toronto Western Hospital, 399 Bathurst St, Toronto, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Canada; Krembil Brain Institute, Leonard Ave, Toronto, Ontario, Canada
| | - Mojgan Hodaie
- Division of Neurosurgery, Toronto Western Hospital, 399 Bathurst St, Toronto, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Canada; Krembil Brain Institute, Leonard Ave, Toronto, Ontario, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Toronto Western Hospital, 399 Bathurst St, Toronto, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Canada; Krembil Brain Institute, Leonard Ave, Toronto, Ontario, Canada
| | - Luka Milosevic
- Krembil Brain Institute, Leonard Ave, Toronto, Ontario, Canada; Department of Biomedical Engineering, University of Toronto, Canada
| | - Robert Chen
- Krembil Brain Institute, Leonard Ave, Toronto, Ontario, Canada; Dept of Neurology, Temerty Faculty of Medicine, University of Toronto, Canada
| | - William D Hutchison
- Departments of Surgery and Physiology, Temerty Faculty of Medicine, University of Toronto, Canada, and Krembil Brain Institute, Leonard Ave, Toronto, Ontario, Canada.
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9
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Milekovic T, Moraud EM, Macellari N, Moerman C, Raschellà F, Sun S, Perich MG, Varescon C, Demesmaeker R, Bruel A, Bole-Feysot LN, Schiavone G, Pirondini E, YunLong C, Hao L, Galvez A, Hernandez-Charpak SD, Dumont G, Ravier J, Le Goff-Mignardot CG, Mignardot JB, Carparelli G, Harte C, Hankov N, Aureli V, Watrin A, Lambert H, Borton D, Laurens J, Vollenweider I, Borgognon S, Bourre F, Goillandeau M, Ko WKD, Petit L, Li Q, Buschman R, Buse N, Yaroshinsky M, Ledoux JB, Becce F, Jimenez MC, Bally JF, Denison T, Guehl D, Ijspeert A, Capogrosso M, Squair JW, Asboth L, Starr PA, Wang DD, Lacour SP, Micera S, Qin C, Bloch J, Bezard E, Courtine G. A spinal cord neuroprosthesis for locomotor deficits due to Parkinson's disease. Nat Med 2023; 29:2854-2865. [PMID: 37932548 DOI: 10.1038/s41591-023-02584-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 09/08/2023] [Indexed: 11/08/2023]
Abstract
People with late-stage Parkinson's disease (PD) often suffer from debilitating locomotor deficits that are resistant to currently available therapies. To alleviate these deficits, we developed a neuroprosthesis operating in closed loop that targets the dorsal root entry zones innervating lumbosacral segments to reproduce the natural spatiotemporal activation of the lumbosacral spinal cord during walking. We first developed this neuroprosthesis in a non-human primate model that replicates locomotor deficits due to PD. This neuroprosthesis not only alleviated locomotor deficits but also restored skilled walking in this model. We then implanted the neuroprosthesis in a 62-year-old male with a 30-year history of PD who presented with severe gait impairments and frequent falls that were medically refractory to currently available therapies. We found that the neuroprosthesis interacted synergistically with deep brain stimulation of the subthalamic nucleus and dopaminergic replacement therapies to alleviate asymmetry and promote longer steps, improve balance and reduce freezing of gait. This neuroprosthesis opens new perspectives to reduce the severity of locomotor deficits in people with PD.
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Affiliation(s)
- Tomislav Milekovic
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
- Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Eduardo Martin Moraud
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Nicolo Macellari
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Charlotte Moerman
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Flavio Raschellà
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- NeuroX Institute, School of Bioengineering, EPFL, Lausanne, Switzerland
| | - Shiqi Sun
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Matthew G Perich
- Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Camille Varescon
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Robin Demesmaeker
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Alice Bruel
- Institute of Bioengineering, School of Engineering, EPFL, Lausanne, Switzerland
| | - Léa N Bole-Feysot
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Giuseppe Schiavone
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Laboratory for Soft Bioelectronic Interfaces (LSBI), NeuroX Institute, EPFL, Lausanne, Switzerland
| | - Elvira Pirondini
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
| | - Cheng YunLong
- Motac Neuroscience, UK-M15 6WE, Manchester, UK
- China Academy of Medical Sciences, Beijing, China
- Institute of Laboratory Animal Sciences, Beijing, China
| | - Li Hao
- Motac Neuroscience, UK-M15 6WE, Manchester, UK
- China Academy of Medical Sciences, Beijing, China
- Institute of Laboratory Animal Sciences, Beijing, China
| | - Andrea Galvez
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Sergio Daniel Hernandez-Charpak
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Gregory Dumont
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Jimmy Ravier
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Camille G Le Goff-Mignardot
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Jean-Baptiste Mignardot
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Gaia Carparelli
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Cathal Harte
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Nicolas Hankov
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Viviana Aureli
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | | | | | - David Borton
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
- School of Engineering, Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Jean Laurens
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Isabelle Vollenweider
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Simon Borgognon
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - François Bourre
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Michel Goillandeau
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Wai Kin D Ko
- Motac Neuroscience, UK-M15 6WE, Manchester, UK
- China Academy of Medical Sciences, Beijing, China
- Institute of Laboratory Animal Sciences, Beijing, China
| | - Laurent Petit
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Qin Li
- Motac Neuroscience, UK-M15 6WE, Manchester, UK
- China Academy of Medical Sciences, Beijing, China
- Institute of Laboratory Animal Sciences, Beijing, China
| | | | | | - Maria Yaroshinsky
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jean-Baptiste Ledoux
- Department of Diagnostic and Interventional Radiology, CHUV/UNIL, Lausanne, Switzerland
| | - Fabio Becce
- Department of Diagnostic and Interventional Radiology, CHUV/UNIL, Lausanne, Switzerland
| | | | - Julien F Bally
- Department of Neurology, CHUV/UNIL, Lausanne, Switzerland
| | | | - Dominique Guehl
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Auke Ijspeert
- Institute of Bioengineering, School of Engineering, EPFL, Lausanne, Switzerland
| | - Marco Capogrosso
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jordan W Squair
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Leonie Asboth
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
- Department of Neurosurgery, CHUV, Lausanne, Switzerland
| | - Philip A Starr
- 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
| | - Stéphanie P Lacour
- NeuroX Institute, School of Bioengineering, EPFL, Lausanne, Switzerland
- Laboratory for Soft Bioelectronic Interfaces (LSBI), NeuroX Institute, EPFL, Lausanne, Switzerland
| | - Silvestro Micera
- NeuroX Institute, School of Bioengineering, EPFL, Lausanne, Switzerland
- Department of Excellence in Robotics and AI, Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Chuan Qin
- China Academy of Medical Sciences, Beijing, China
| | - Jocelyne Bloch
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland.
- Department of Neurosurgery, CHUV, Lausanne, Switzerland.
| | - Erwan Bezard
- Motac Neuroscience, UK-M15 6WE, Manchester, UK.
- China Academy of Medical Sciences, Beijing, China.
- Institute of Laboratory Animal Sciences, Beijing, China.
- Université de Bordeaux, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France.
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France.
| | - G Courtine
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland.
- Department of Neurosurgery, CHUV, Lausanne, Switzerland.
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10
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Mirzac D, Kreis SL, Luhmann HJ, Gonzalez-Escamilla G, Groppa S. Translating Pathological Brain Activity Primers in Parkinson's Disease Research. RESEARCH (WASHINGTON, D.C.) 2023; 6:0183. [PMID: 37383218 PMCID: PMC10298229 DOI: 10.34133/research.0183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 06/02/2023] [Indexed: 06/30/2023]
Abstract
Translational experimental approaches that help us better trace Parkinson's disease (PD) pathophysiological mechanisms leading to new therapeutic targets are urgently needed. In this article, we review recent experimental and clinical studies addressing abnormal neuronal activity and pathological network oscillations, as well as their underlying mechanisms and modulation. Our aim is to enhance our knowledge about the progression of Parkinson's disease pathology and the timing of its symptom's manifestation. Here, we present mechanistic insights relevant for the generation of aberrant oscillatory activity within the cortico-basal ganglia circuits. We summarize recent achievements extrapolated from available PD animal models, discuss their advantages and limitations, debate on their differential applicability, and suggest approaches for transferring knowledge on disease pathology into future research and clinical applications.
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Affiliation(s)
- Daniela Mirzac
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience, Rhine Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Svenja L. Kreis
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Heiko J. Luhmann
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience, Rhine Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience, Rhine Main Neuroscience Network, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
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11
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Rodriguez F, He S, Tan H. The potential of convolutional neural networks for identifying neural states based on electrophysiological signals: experiments on synthetic and real patient data. Front Hum Neurosci 2023; 17:1134599. [PMID: 37333834 PMCID: PMC10272439 DOI: 10.3389/fnhum.2023.1134599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 05/03/2023] [Indexed: 06/20/2023] Open
Abstract
Processing incoming neural oscillatory signals in real-time and decoding from them relevant behavioral or pathological states is often required for adaptive Deep Brain Stimulation (aDBS) and other brain-computer interface (BCI) applications. Most current approaches rely on first extracting a set of predefined features, such as the power in canonical frequency bands or various time-domain features, and then training machine learning systems that use those predefined features as inputs and infer what the underlying brain state is at each given time point. However, whether this algorithmic approach is best suited to extract all available information contained within the neural waveforms remains an open question. Here, we aim to explore different algorithmic approaches in terms of their potential to yield improvements in decoding performance based on neural activity such as measured through local field potentials (LFPs) recordings or electroencephalography (EEG). In particular, we aim to explore the potential of end-to-end convolutional neural networks, and compare this approach with other machine learning methods that are based on extracting predefined feature sets. To this end, we implement and train a number of machine learning models, based either on manually constructed features or, in the case of deep learning-based models, on features directly learnt from the data. We benchmark these models on the task of identifying neural states using simulated data, which incorporates waveform features previously linked to physiological and pathological functions. We then assess the performance of these models in decoding movements based on local field potentials recorded from the motor thalamus of patients with essential tremor. Our findings, derived from both simulated and real patient data, suggest that end-to-end deep learning-based methods may surpass feature-based approaches, particularly when the relevant patterns within the waveform data are either unknown, difficult to quantify, or when there may be, from the point of view of the predefined feature extraction pipeline, unidentified features that could contribute to decoding performance. The methodologies proposed in this study might hold potential for application in adaptive deep brain stimulation (aDBS) and other brain-computer interface systems.
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12
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Stangl M, Maoz SL, Suthana N. Mobile cognition: imaging the human brain in the 'real world'. Nat Rev Neurosci 2023; 24:347-362. [PMID: 37046077 PMCID: PMC10642288 DOI: 10.1038/s41583-023-00692-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/03/2023] [Indexed: 04/14/2023]
Abstract
Cognitive neuroscience studies in humans have enabled decades of impactful discoveries but have primarily been limited to recording the brain activity of immobile participants in a laboratory setting. In recent years, advances in neuroimaging technologies have enabled recordings of human brain activity to be obtained during freely moving behaviours in the real world. Here, we propose that these mobile neuroimaging methods can provide unique insights into the neural mechanisms of human cognition and contribute to the development of novel treatments for neurological and psychiatric disorders. We further discuss the challenges associated with studying naturalistic human behaviours in complex real-world settings as well as strategies for overcoming them. We conclude that mobile neuroimaging methods have the potential to bring about a new era of cognitive neuroscience in which neural mechanisms can be studied with increased ecological validity and with the ability to address questions about natural behaviour and cognitive processes in humans engaged in dynamic real-world experiences.
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Affiliation(s)
- Matthias Stangl
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute for Neuroscience and Human Behaviour, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Sabrina L Maoz
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nanthia Suthana
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute for Neuroscience and Human Behaviour, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA.
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13
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Yeh CH, Zhang C, Shi W, Lo MT, Tinkhauser G, Oswal A. Cross-Frequency Coupling and Intelligent Neuromodulation. CYBORG AND BIONIC SYSTEMS 2023; 4:0034. [PMID: 37266026 PMCID: PMC10231647 DOI: 10.34133/cbsystems.0034] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 05/02/2023] [Indexed: 06/03/2023] Open
Abstract
Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different frequencies. Evidence from both patient and healthy participant studies suggests that CFC plays an essential role in neuronal computation, interregional interaction, and disease pathophysiology. The present review discusses methodological advances and challenges in the computation of CFC with particular emphasis on potential solutions to spurious coupling, inferring intrinsic rhythms in a targeted frequency band, and causal interferences. We specifically focus on the literature exploring CFC in the context of cognition/memory tasks, sleep, and neurological disorders, such as Alzheimer's disease, epilepsy, and Parkinson's disease. Furthermore, we highlight the implication of CFC in the context and for the optimization of invasive and noninvasive neuromodulation and rehabilitation. Mainly, CFC could support advancing the understanding of the neurophysiology of cognition and motor control, serve as a biomarker for disease symptoms, and leverage the optimization of therapeutic interventions, e.g., closed-loop brain stimulation. Despite the evident advantages of CFC as an investigative and translational tool in neuroscience, further methodological improvements are required to facilitate practical and correct use in cyborg and bionic systems in the field.
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Affiliation(s)
- Chien-Hung Yeh
- School of Information and Electronics,
Beijing Institute of Technology, Beijing, China
| | - Chuting Zhang
- School of Information and Electronics,
Beijing Institute of Technology, Beijing, China
| | - Wenbin Shi
- School of Information and Electronics,
Beijing Institute of Technology, Beijing, China
| | - Men-Tzung Lo
- Department of Biomedical Sciences and Engineering,
National Central University, Taoyuan, Taiwan
| | - Gerd Tinkhauser
- Department of Neurology,
Bern University Hospital and University of Bern, Bern, Switzerland
| | - Ashwini Oswal
- MRC Brain Network Dynamics Unit,
University of Oxford, Oxford, UK
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14
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Neumann WJ, Horn A, Kühn AA. Insights and opportunities for deep brain stimulation as a brain circuit intervention. Trends Neurosci 2023; 46:472-487. [PMID: 37105806 DOI: 10.1016/j.tins.2023.03.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 03/13/2023] [Accepted: 03/17/2023] [Indexed: 04/29/2023]
Abstract
Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.
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Affiliation(s)
- Wolf-Julian Neumann
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt Universität zu Berlin, Berlin, Germany
| | - Andreas Horn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt Universität zu Berlin, Berlin, Germany; Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA; MGH Neurosurgery & Center for Neurotechnology and Neurorecovery at MGH Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrea A Kühn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt Universität zu Berlin, Berlin, Germany; NeuroCure Clinical Research Centre, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; DZNE, German Center for Degenerative Diseases, Berlin, Germany.
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15
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Sui Y, Yu H, Zhang C, Chen Y, Jiang C, Li L. Deep brain-machine interfaces: sensing and modulating the human deep brain. Natl Sci Rev 2022; 9:nwac212. [PMID: 36644311 PMCID: PMC9834907 DOI: 10.1093/nsr/nwac212] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/02/2022] [Accepted: 10/04/2022] [Indexed: 01/18/2023] Open
Abstract
Different from conventional brain-machine interfaces that focus more on decoding the cerebral cortex, deep brain-machine interfaces enable interactions between external machines and deep brain structures. They sense and modulate deep brain neural activities, aiming at function restoration, device control and therapeutic improvements. In this article, we provide an overview of multiple deep brain recording and stimulation techniques that can serve as deep brain-machine interfaces. We highlight two widely used interface technologies, namely deep brain stimulation and stereotactic electroencephalography, for technical trends, clinical applications and brain connectivity research. We discuss the potential to develop closed-loop deep brain-machine interfaces and achieve more effective and applicable systems for the treatment of neurological and psychiatric disorders.
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Affiliation(s)
- Yanan Sui
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
| | - Huiling Yu
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
| | - Chen Zhang
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
| | - Yue Chen
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
| | - Changqing Jiang
- National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing 100084, China
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