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Lu 呂宏耘 HY, Zhao 趙懿 Y, Stealey HM, Barnett CR, Tobler PN, Santacruz SR. Volitional Regulation and Transferable Patterns of Midbrain Oscillations. J Neurosci 2025; 45:e1808242025. [PMID: 39909565 PMCID: PMC11949472 DOI: 10.1523/jneurosci.1808-24.2025] [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: 09/22/2024] [Revised: 12/16/2024] [Accepted: 01/23/2025] [Indexed: 02/07/2025] Open
Abstract
Dopaminergic brain areas are crucial for cognition and their dysregulation is linked to neuropsychiatric disorders typically treated with pharmacological interventions. These treatments often have side effects and variable effectiveness, underscoring the need for alternatives. We introduce the first demonstration of neurofeedback using local field potentials (LFP) from the ventral tegmental area (VTA). This approach leverages the real-time temporal resolution of LFP and ability to target deep brain. In our study, two male rhesus macaque monkeys (Macaca mulatta) learned to regulate VTA beta power using a customized normalized metric to stably quantify VTA LFP signal modulation. The subjects demonstrated flexible and specific control with different strategies for specific frequency bands, revealing new insights into the plasticity of VTA neurons contributing to oscillatory activity that is functionally relevant to many aspects of cognition. Excitingly, the subjects showed transferable patterns, a key criterion for clinical applications beyond training settings. This work provides a foundation for neurofeedback-based treatments, which may be a promising alternative to conventional approaches and open new avenues for understanding and managing neuropsychiatric disorders.
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Affiliation(s)
- Hung-Yun Lu 呂宏耘
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas 78712
| | - Yi Zhao 趙懿
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas 78712
| | - Hannah M Stealey
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas 78712
| | - Cole R Barnett
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas 78712
| | - Philippe N Tobler
- Department of Economics, University of Zurich, Zurich CH-8006, Switzerland
- Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich CH-8006, Switzerland
| | - Samantha R Santacruz
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas 78712
- Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, Texas 78712
- Interdisciplinary Neuroscience Program, University of Texas at Austin, Austin, Texas 78712
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2
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Osborne KJ, Walther S, Mittal VA. Motor actions across psychiatric disorders: A research domain criteria (RDoC) perspective. Clin Psychol Rev 2024; 114:102511. [PMID: 39510028 DOI: 10.1016/j.cpr.2024.102511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 08/19/2024] [Accepted: 10/23/2024] [Indexed: 11/15/2024]
Abstract
The motor system is critical for understanding the pathophysiology and treatment of mental illness. Abnormalities in the processes that allow us to plan and execute movement in a goal-directed, context-appropriate manner (i.e., motor actions) are especially central to clinical motor research. Within this context, the NIMH Research Domain Criteria (RDoC) framework now includes a Motor Actions construct within the recently incorporated Sensorimotor Systems Domain, providing a useful framework for conducting research on motor action processes. However, there is limited available resources for understanding or implementing this framework. We address this gap by providing a comprehensive critical review and conceptual integration of the current clinical literature on the subconstructs comprising the Motor Actions construct. This includes a detailed discussion of each Motor Action subconstruct (e.g., action planning/execution) and its measurement across different units of analysis (e.g., molecules to behavior), the temporal and conceptual relationships among the Motor Action subconstructs (and other relevant RDoC domain constructs), and how abnormalities in these Motor Action subconstructs manifest in mental illness. Together, the review illustrates how motor system dysfunction is implicated in the pathophysiology of many psychiatric conditions and demonstrates shared and distinct mechanisms that may account for similar manifestations of motor abnormalities across disorders.
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Affiliation(s)
- K Juston Osborne
- Washington University in St. Louis, Department of Psychiatry, 4444 Forest Park Ave., St. Louis, MO, USA; Northwestern University, Department of Psychology, 633 Clark St. Evanston, IL, USA.
| | - Sebastian Walther
- University Hospital Würzburg, Department of Psychiatry, Psychosomatics, and Psychotherapy, Center of Mental Health, Margarete-Höppel-Platz 1, 97080 Würzburg, Germany
| | - Vijay A Mittal
- Northwestern University, Department of Psychology, 633 Clark St. Evanston, IL, USA; Northwestern University, Department of Psychiatry, 676 N. St. Claire, Chicago, IL, USA; Northwestern University, Department of Psychiatry, Institute for Policy Research, Department of Medical Social Sciences, Institute for Innovations in Developmental Sciences (DevSci), 633 Clark St., Evanston, Chicago, IL, USA
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3
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Rohr-Fukuma M, Stieglitz LH, Bujan B, Jedrysiak P, Oertel MF, Salzmann L, Baumann CR, Imbach LL, Gassert R, Bichsel O. Neurofeedback-enabled beta power control with a fully implanted DBS system in patients with Parkinson's disease. Clin Neurophysiol 2024; 165:1-15. [PMID: 38941959 DOI: 10.1016/j.clinph.2024.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 04/18/2024] [Accepted: 06/03/2024] [Indexed: 06/30/2024]
Abstract
OBJECTIVE Parkinsonian motor symptoms are linked to pathologically increased beta oscillations in the basal ganglia. Studies with externalised deep brain stimulation electrodes showed that Parkinson patients were able to rapidly gain control over these pathological basal ganglia signals through neurofeedback. Studies with fully implanted deep brain stimulation systems duplicating these promising results are required to grant transferability to daily application. METHODS In this study, seven patients with idiopathic Parkinson's disease and one with familial Parkinson's disease were included. In a postoperative setting, beta oscillations from the subthalamic nucleus were recorded with a fully implanted deep brain stimulation system and converted to a real-time visual feedback signal. Participants were instructed to perform bidirectional neurofeedback tasks with the aim to modulate these oscillations. RESULTS While receiving regular medication and deep brain stimulation, participants were able to significantly improve their neurofeedback ability and achieved a significant decrease of subthalamic beta power (median reduction of 31% in the final neurofeedback block). CONCLUSION We could demonstrate that a fully implanted deep brain stimulation system can provide visual neurofeedback enabling patients with Parkinson's disease to rapidly control pathological subthalamic beta oscillations. SIGNIFICANCE Fully-implanted DBS electrode-guided neurofeedback is feasible and can now be explored over extended timespans.
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Affiliation(s)
- Manabu Rohr-Fukuma
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | - Lennart H Stieglitz
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | | | | | - Markus F Oertel
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland
| | - Lena Salzmann
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Christian R Baumann
- Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland; Department of Neurology, University Hospital Zurich, University of Zurich, Switzerland
| | | | - Roger Gassert
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Oliver Bichsel
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Centre, University Hospital Zurich, University of Zurich, Switzerland; Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland.
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Baker SK, Radcliffe EM, Kramer DR, Ojemann S, Case M, Zarns C, Holt-Becker A, Raike RS, Baumgartner AJ, Kern DS, Thompson JA. Comparison of beta peak detection algorithms for data-driven deep brain stimulation programming strategies in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:150. [PMID: 39122725 PMCID: PMC11315991 DOI: 10.1038/s41531-024-00762-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 07/24/2024] [Indexed: 08/12/2024] Open
Abstract
Oscillatory activity within the beta frequency range (13-30 Hz) serves as a Parkinson's disease biomarker for tailoring deep brain stimulation (DBS) treatments. Currently, identifying clinically relevant beta signals, specifically frequencies of peak amplitudes within the beta spectral band, is a subjective process. To inform potential strategies for objective clinical decision making, we assessed algorithms for identifying beta peaks and devised a standardized approach for both research and clinical applications. Employing a novel monopolar referencing strategy, we utilized a brain sensing device to measure beta peak power across distinct contacts along each DBS electrode implanted in the subthalamic nucleus. We then evaluated the accuracy of ten beta peak detection algorithms against a benchmark established by expert consensus. The most accurate algorithms, all sharing similar underlying algebraic dynamic peak amplitude thresholding approaches, matched the expert consensus in performance and reliably predicted the clinical stimulation parameters during follow-up visits. These findings highlight the potential of algorithmic solutions to overcome the subjective bias in beta peak identification, presenting viable options for standardizing this process. Such advancements could lead to significant improvements in the efficiency and accuracy of patient-specific DBS therapy parameterization.
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Affiliation(s)
- Sunderland K Baker
- Pennsylvania State University, Department of Biobehavioral Health, University Park, PA, 16802, USA
| | - Erin M Radcliffe
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
- University of Colorado Anschutz Medical Campus, Department of Bioengineering, Aurora, CO, 80045, USA
| | - Daniel R Kramer
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
| | - Steven Ojemann
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
- University of Colorado Anschutz Medical Campus, Department of Neurology, Aurora, CO, 80045, USA
| | - Michelle Case
- Medtronic PLC, Neuromodulation Operating Unit, Minneapolis, MN, 55432, USA
| | - Caleb Zarns
- Medtronic PLC, Neuromodulation Operating Unit, Minneapolis, MN, 55432, USA
| | - Abbey Holt-Becker
- Medtronic PLC, Neuromodulation Operating Unit, Minneapolis, MN, 55432, USA
| | - Robert S Raike
- Medtronic PLC, Neuromodulation Operating Unit, Minneapolis, MN, 55432, USA
| | - Alexander J Baumgartner
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
- University of Colorado Anschutz Medical Campus, Department of Neurology, Aurora, CO, 80045, USA
| | - Drew S Kern
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA
- University of Colorado Anschutz Medical Campus, Department of Neurology, Aurora, CO, 80045, USA
| | - John A Thompson
- University of Colorado Anschutz Medical Campus, Department of Neurosurgery, Aurora, CO, 80045, USA.
- University of Colorado Anschutz Medical Campus, Department of Neurology, Aurora, CO, 80045, USA.
- University of Colorado Anschutz Medical Campus, Department of Psychiatry, Aurora, CO, 80045, USA.
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Anil K, Ganis G, Freeman JA, Marsden J, Hall SD. Exploring the Feasibility of Bidirectional Control of Beta Oscillatory Power in Healthy Controls as a Potential Intervention for Parkinson's Disease Movement Impairment. SENSORS (BASEL, SWITZERLAND) 2024; 24:5107. [PMID: 39204803 PMCID: PMC11358931 DOI: 10.3390/s24165107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 07/30/2024] [Accepted: 08/05/2024] [Indexed: 09/04/2024]
Abstract
Neurofeedback (NF) is a promising intervention for improvements in motor performance in Parkinson's disease. This NF pilot study in healthy participants aimed to achieve the following: (1) determine participants' ability to bi-directionally modulate sensorimotor beta power and (2) determine the effect of NF on movement performance. A real-time EEG-NF protocol was used to train participants to increase and decrease their individual motor cortex beta power amplitude, using a within-subject double-blind sham-controlled approach. Movement was assessed using a Go/No-go task. Participants completed the NASA Task Load Index and provided verbal feedback of the NF task difficulty. All 17 participants (median age = 38 (19-65); 10 females) reliably reduced sensorimotor beta power. No participant could reliably increase their beta activity. Participants reported that the NF task was challenging, particularly increasing beta. A modest but significant increase in reaction time correlated with a reduction in beta power only in the real condition. Findings suggest that beta power control difficulty varies by modulation direction, affecting participant perceptions. A correlation between beta power reduction and reaction times only in the real condition suggests that intentional beta power reduction may shorten reaction times. Future research should examine the minimum beta threshold for meaningful motor improvements, and the relationship between EEG mechanisms and NF learning to optimise NF outcomes.
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Affiliation(s)
- Krithika Anil
- School of Health Professions, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK;
- Brain Research and Imaging Centre, Faculty of Health, University of Plymouth, Research Way, Plymouth PL6 8BU, UK; (G.G.); (S.D.H.)
| | - Giorgio Ganis
- Brain Research and Imaging Centre, Faculty of Health, University of Plymouth, Research Way, Plymouth PL6 8BU, UK; (G.G.); (S.D.H.)
- School of Psychology, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK
| | - Jennifer A. Freeman
- Peninsula Allied Health Centre, School of Health Professions, University of Plymouth, Derriford Road, Plymouth PL6 8BH, UK
| | - Jonathan Marsden
- School of Health Professions, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK;
- Brain Research and Imaging Centre, Faculty of Health, University of Plymouth, Research Way, Plymouth PL6 8BU, UK; (G.G.); (S.D.H.)
| | - Stephen D. Hall
- Brain Research and Imaging Centre, Faculty of Health, University of Plymouth, Research Way, Plymouth PL6 8BU, UK; (G.G.); (S.D.H.)
- School of Psychology, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK
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Guo X, He S, Geng X, Yao P, Wiest C, Nie Y, Tan H, Wang S. Quantifying local field potential dynamics with amplitude and frequency stability between ON and OFF medication and stimulation in Parkinson's disease. Neurobiol Dis 2024; 197:106519. [PMID: 38685358 PMCID: PMC7616028 DOI: 10.1016/j.nbd.2024.106519] [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: 01/29/2024] [Revised: 03/26/2024] [Accepted: 04/25/2024] [Indexed: 05/02/2024] Open
Abstract
Neural oscillations are critical to understanding the synchronisation of neural activities and their relevance to neurological disorders. For instance, the amplitude of beta oscillations in the subthalamic nucleus has gained extensive attention, as it has been found to correlate with medication status and the therapeutic effects of continuous deep brain stimulation in people with Parkinson's disease. However, the frequency stability of subthalamic nucleus beta oscillations, which has been suggested to be associated with dopaminergic information in brain states, has not been well explored. Moreover, the administration of medicine can have inverse effects on changes in frequency and amplitude. In this study, we proposed a method based on the stationary wavelet transform to quantify the amplitude and frequency stability of subthalamic nucleus beta oscillations and evaluated the method using simulation and real data for Parkinson's disease patients. The results suggest that the amplitude and frequency stability quantification has enhanced sensitivity in distinguishing pathological conditions in Parkinson's disease patients. Our quantification shows the benefit of combining frequency stability information with amplitude and provides a new potential feedback signal for adaptive deep brain stimulation.
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Affiliation(s)
- Xuanjun Guo
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Shenghong He
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Xinyi Geng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Pan Yao
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; State Key Laboratory of Transducer Technology, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences, 100094 Beijing, China; School of Electronic, Electrical, and Communication Engineering, University of Chinese Academy of Sciences (UCAS), 100049 Beijing, China
| | - Christoph Wiest
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Yingnan Nie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
| | - Shouyan Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Shanghai, China; Shanghai Engineering Research Center of AI & Robotics, Fudan University, Shanghai, China; Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, China.
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Ubeda Matzilevich E, Daniel PL, Little S. Towards therapeutic electrophysiological neurofeedback in Parkinson's disease. Parkinsonism Relat Disord 2024; 121:106010. [PMID: 38245382 DOI: 10.1016/j.parkreldis.2024.106010] [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: 09/11/2023] [Revised: 01/10/2024] [Accepted: 01/12/2024] [Indexed: 01/22/2024]
Abstract
Neurofeedback (NF) techniques support individuals to self-regulate specific features of brain activity, which has been shown to impact behavior and potentially ameliorate clinical symptoms. Electrophysiological NF (epNF) may be particularly impactful for patients with Parkinson's disease (PD), as evidence mounts to suggest a central role of pathological neural oscillations underlying symptoms in PD. Exaggerated beta oscillations (12-30 Hz) in the basal ganglia-cortical network are linked to motor symptoms (e.g., bradykinesia, rigidity), and beta is reduced by successful therapy with dopaminergic medication and Deep Brain Stimulation (DBS). PD patients also experience non-motor symptoms related to sleep, mood, motivation, and cognitive control. Although less is known about the mechanisms of non-motor symptoms in PD and how to successfully treat them, low frequency neural oscillations (1-12 Hz) in the basal ganglia-cortical network are particularly implicated in non-motor symptoms. Here, we review how cortical and subcortical epNF could be used to target motor and non-motor specific oscillations, and potentially serve as an adjunct therapy that enables PD patients to endogenously control their own pathological neural activities. Recent studies have demonstrated that epNF protocols can successfully support volitional control of cortical and subcortical beta rhythms. Importantly, this endogenous control of beta has been linked to changes in motor behavior. epNF for PD, as a casual intervention on neural signals, has the potential to increase understanding of the neurophysiology of movement, mood, and cognition and to identify new therapeutic approaches for motor and non-motor symptoms.
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Affiliation(s)
- Elena Ubeda Matzilevich
- Movement Disorders and Neuromodulation Division, Department of Neurology, University of California San Francisco, CA, USA
| | - Pria Lauren Daniel
- Movement Disorders and Neuromodulation Division, Department of Neurology, University of California San Francisco, CA, USA; Department of Psychology, University of California San Diego, CA, USA.
| | - Simon Little
- Movement Disorders and Neuromodulation Division, Department of Neurology, University of California San Francisco, CA, USA
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8
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Guo Z, Lin JP, Simeone O, Mills KR, Cvetkovic Z, McClelland VM. Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia. Brain Commun 2024; 6:fcae061. [PMID: 38487552 PMCID: PMC10939448 DOI: 10.1093/braincomms/fcae061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 01/10/2024] [Accepted: 02/23/2024] [Indexed: 03/17/2024] Open
Abstract
Sensory processing and sensorimotor integration are abnormal in dystonia, including impaired modulation of beta-corticomuscular coherence. However, cortex-muscle interactions in either direction are rarely described, with reports limited predominantly to investigation of linear coupling, using corticomuscular coherence or Granger causality. Information-theoretic tools such as transfer entropy detect both linear and non-linear interactions between processes. This observational case-control study applies transfer entropy to determine intra- and cross-frequency cortex-muscle coupling in young people with dystonia/dystonic cerebral palsy. Fifteen children with dystonia/dystonic cerebral palsy and 13 controls, aged 12-18 years, performed a grasp task with their dominant hand. Mechanical perturbations were provided by an electromechanical tapper. Bipolar scalp EEG over contralateral sensorimotor cortex and surface EMG over first dorsal interosseous were recorded. Multi-scale wavelet transfer entropy was applied to decompose signals into functional frequency bands of oscillatory activity and to quantify intra- and cross-frequency coupling between brain and muscle. Statistical significance against the null hypothesis of zero transfer entropy was established, setting individual 95% confidence thresholds. The proportion of individuals in each group showing significant transfer entropy for each frequency combination/direction was compared using Fisher's exact test, correcting for multiple comparisons. Intra-frequency transfer entropy was detected in all participants bidirectionally in the beta (16-32 Hz) range and in most participants from EEG to EMG in the alpha (8-16 Hz) range. Cross-frequency transfer entropy across multiple frequency bands was largely similar between groups, but a specific coupling from low-frequency EMG to beta EEG was significantly reduced in dystonia [P = 0.0061 (corrected)]. The demonstration of bidirectional cortex-muscle communication in dystonia emphasizes the value of transfer entropy for exploring neural communications in neurological disorders. The novel finding of diminished coupling from low-frequency EMG to beta EEG in dystonia suggests impaired cortical feedback of proprioceptive information with a specific frequency signature that could be relevant to the origin of the excessive low-frequency drive to muscle.
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Affiliation(s)
- Zhenghao Guo
- Department of Engineering, King's College London, London WC2R 2LS, UK
- School of Biomedical Engineering, Dalian University of Technology, Dalian 116024, China
| | - Jean-Pierre Lin
- Children's Neuroscience, Evelina London Children's Hospital, Guy's & St Thomas' NHS Foundation Trust (GSTT), London SE1 7EH, UK
| | - Osvaldo Simeone
- Department of Engineering, King's College London, London WC2R 2LS, UK
| | - Kerry R Mills
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London SE5 9RX, UK
| | - Zoran Cvetkovic
- Department of Engineering, King's College London, London WC2R 2LS, UK
| | - Verity M McClelland
- Children's Neuroscience, Evelina London Children's Hospital, Guy's & St Thomas' NHS Foundation Trust (GSTT), London SE1 7EH, UK
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London SE5 9RX, UK
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9
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He S, Baig F, Merla A, Torrecillos F, Perera A, Wiest C, Debarros J, Benjaber M, Hart MG, Ricciardi L, Morgante F, Hasegawa H, Samuel M, Edwards M, Denison T, Pogosyan A, Ashkan K, Pereira E, Tan H. Beta-triggered adaptive deep brain stimulation during reaching movement in Parkinson's disease. Brain 2023; 146:5015-5030. [PMID: 37433037 PMCID: PMC10690014 DOI: 10.1093/brain/awad233] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 05/30/2023] [Accepted: 06/28/2023] [Indexed: 07/13/2023] Open
Abstract
Subthalamic nucleus (STN) beta-triggered adaptive deep brain stimulation (ADBS) has been shown to provide clinical improvement comparable to conventional continuous DBS (CDBS) with less energy delivered to the brain and less stimulation induced side effects. However, several questions remain unanswered. First, there is a normal physiological reduction of STN beta band power just prior to and during voluntary movement. ADBS systems will therefore reduce or cease stimulation during movement in people with Parkinson's disease and could therefore compromise motor performance compared to CDBS. Second, beta power was smoothed and estimated over a time period of 400 ms in most previous ADBS studies, but a shorter smoothing period could have the advantage of being more sensitive to changes in beta power, which could enhance motor performance. In this study, we addressed these two questions by evaluating the effectiveness of STN beta-triggered ADBS using a standard 400 ms and a shorter 200 ms smoothing window during reaching movements. Results from 13 people with Parkinson's disease showed that reducing the smoothing window for quantifying beta did lead to shortened beta burst durations by increasing the number of beta bursts shorter than 200 ms and more frequent switching on/off of the stimulator but had no behavioural effects. Both ADBS and CDBS improved motor performance to an equivalent extent compared to no DBS. Secondary analysis revealed that there were independent effects of a decrease in beta power and an increase in gamma power in predicting faster movement speed, while a decrease in beta event related desynchronization (ERD) predicted quicker movement initiation. CDBS suppressed both beta and gamma more than ADBS, whereas beta ERD was reduced to a similar level during CDBS and ADBS compared with no DBS, which together explained the achieved similar performance improvement in reaching movements during CDBS and ADBS. In addition, ADBS significantly improved tremor compared with no DBS but was not as effective as CDBS. These results suggest that STN beta-triggered ADBS is effective in improving motor performance during reaching movements in people with Parkinson's disease, and that shortening of the smoothing window does not result in any additional behavioural benefit. When developing ADBS systems for Parkinson's disease, it might not be necessary to track very fast beta dynamics; combining beta, gamma, and information from motor decoding might be more beneficial with additional biomarkers needed for optimal treatment of tremor.
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Affiliation(s)
- Shenghong He
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Fahd Baig
- Neurosciences Research Centre, St George’s, University of London & St George’s University Hospitals NHS Foundation Trust, Institute of Molecular and Clinical Sciences, Cranmer Terrace, London SW17 0QT, UK
| | - Anca Merla
- Department of Neurosurgery, King’s College Hospital NHS Foundation Trust, London SE5 9RS, UK
| | - Flavie Torrecillos
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Andrea Perera
- Department of Neurosurgery, King’s College Hospital NHS Foundation Trust, London SE5 9RS, UK
| | - Christoph Wiest
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Jean Debarros
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Moaad Benjaber
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Michael G Hart
- Neurosciences Research Centre, St George’s, University of London & St George’s University Hospitals NHS Foundation Trust, Institute of Molecular and Clinical Sciences, Cranmer Terrace, London SW17 0QT, UK
| | - Lucia Ricciardi
- Neurosciences Research Centre, St George’s, University of London & St George’s University Hospitals NHS Foundation Trust, Institute of Molecular and Clinical Sciences, Cranmer Terrace, London SW17 0QT, UK
| | - Francesca Morgante
- Neurosciences Research Centre, St George’s, University of London & St George’s University Hospitals NHS Foundation Trust, Institute of Molecular and Clinical Sciences, Cranmer Terrace, London SW17 0QT, UK
| | - Harutomo Hasegawa
- Department of Neurosurgery, King’s College Hospital NHS Foundation Trust, London SE5 9RS, UK
| | - Michael Samuel
- Department of Neurology, King’s College Hospital NHS Foundation Trust, London, SE5 9RS, UK
| | - Mark Edwards
- Department of Clinical and Basic Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London WC2R 2LS, UK
| | - Timothy Denison
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Alek Pogosyan
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Keyoumars Ashkan
- Department of Neurosurgery, King’s College Hospital NHS Foundation Trust, London SE5 9RS, UK
| | - Erlick Pereira
- Neurosciences Research Centre, St George’s, University of London & St George’s University Hospitals NHS Foundation Trust, Institute of Molecular and Clinical Sciences, Cranmer Terrace, London SW17 0QT, UK
| | - Huiling Tan
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
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10
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Rahamim N, Slovik M, Mevorach T, Linkovski O, Bergman H, Rosin B, Eitan R. Tuned to Tremor: Increased Sensitivity of Cortico-Basal Ganglia Neurons to Tremor Frequency in the MPTP Nonhuman Primate Model of Parkinson's Disease. J Neurosci 2023; 43:7712-7722. [PMID: 37833067 PMCID: PMC10634551 DOI: 10.1523/jneurosci.0529-23.2023] [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: 03/22/2023] [Revised: 08/24/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
Rest tremor is one of the most prominent clinical features of Parkinson's disease (PD). Here, we hypothesized that cortico-basal ganglia neurons tend to fire in a pattern that matches PD tremor frequency, suggesting a resonance phenomenon. We recorded spiking activity in the primary motor cortex (M1) and globus pallidus external segment of 2 female nonhuman primates, before and after parkinsonian state induction with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The arm of nonhuman primates was passively rotated at seven different frequencies surrounding and overlapping PD tremor frequency. We found entrainment of the spiking activity to arm rotation and a significant sharpening of the tuning curves in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine state, with a peak response at frequencies that matched the frequency of PD tremor. These results reveal increased sensitivity of the cortico-basal ganglia network to tremor frequency and could indicate that this network acts not only as a tremor switch but is involved in setting its frequency.SIGNIFICANCE STATEMENT Tremor is a prominent clinical feature of Parkinson's disease; however, its underlying pathophysiology is still poorly understood. Using electrophysiological recordings of single cortico-basal ganglia neurons before and after the induction of a parkinsonian state, and in response to passive arm rotation, this study reports increased sensitivity to tremor frequency in Parkinson's disease. We found sharpening of the population tuning to the midrange of the tested frequencies (1-13.3 Hz) in the healthy state that further increased in the parkinsonian state. These results hint at the increased frequency-tuned sensitivity of cortico-basal ganglia neurons and suggest that they tend to resonate with the tremor.
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Affiliation(s)
- Noa Rahamim
- Edmond and Lily Safra Center for Brain Science, Hebrew University, Jerusalem, 91120, Israel
| | - Maya Slovik
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, Hadassah-Hebrew University Medical School, Jerusalem, 91120, Israel
| | - Tomer Mevorach
- Department of Psychological Medicine, Schneider Children's Medical Center in Israel, Petah Tikva, 4920235, Israel
- Psychiatric Division, Tel Aviv Sourasky Medical Center-Ichilov, Tel Aviv, 6423906, Israel
| | - Omer Linkovski
- Department of Psychology, Bar-Ilan University, Ramat Gan, 590002, Israel
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, 590002, Israel
| | - Hagai Bergman
- Edmond and Lily Safra Center for Brain Science, Hebrew University, Jerusalem, 91120, Israel
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, Hadassah-Hebrew University Medical School, Jerusalem, 91120, Israel
| | - Boris Rosin
- Division of Ophthalmology, Hadassah-Hebrew University Medical Center, Jerusalem, 91120, Israel
| | - Renana Eitan
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, Hadassah-Hebrew University Medical School, Jerusalem, 91120, Israel
- Psychiatric Division, Tel Aviv Sourasky Medical Center-Ichilov, Tel Aviv, 6423906, Israel
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11
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Alva L, Bernasconi E, Torrecillos F, Fischer P, Averna A, Bange M, Mostofi A, Pogosyan A, Ashkan K, Muthuraman M, Groppa S, Pereira EA, Tan H, Tinkhauser G. Clinical neurophysiological interrogation of motor slowing: A critical step towards tuning adaptive deep brain stimulation. Clin Neurophysiol 2023; 152:43-56. [PMID: 37285747 PMCID: PMC7615935 DOI: 10.1016/j.clinph.2023.04.013] [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: 08/23/2022] [Revised: 03/07/2023] [Accepted: 04/18/2023] [Indexed: 06/09/2023]
Abstract
OBJECTIVE Subthalamic nucleus (STN) beta activity (13-30 Hz) is the most accepted biomarker for adaptive deep brain stimulation (aDBS) for Parkinson's disease (PD). We hypothesize that different frequencies within the beta range may exhibit distinct temporal dynamics and, as a consequence, different relationships to motor slowing and adaptive stimulation patterns. We aim to highlight the need for an objective method to determine the aDBS feedback signal. METHODS STN LFPs were recorded in 15 PD patients at rest and while performing a cued motor task. The impact of beta bursts on motor performance was assessed for different beta candidate frequencies: the individual frequency strongest associated with motor slowing, the individual beta peak frequency, the frequency most modulated by movement execution, as well as the entire-, low- and high beta band. How these candidate frequencies differed in their bursting dynamics and theoretical aDBS stimulation patterns was further investigated. RESULTS The individual motor slowing frequency often differs from the individual beta peak or beta-related movement-modulation frequency. Minimal deviations from a selected target frequency as feedback signal for aDBS leads to a substantial drop in the burst overlapping and in the alignment of the theoretical onset of stimulation triggers (to ∼ 75% for 1 Hz, to ∼ 40% for 3 Hz deviation). CONCLUSIONS Clinical-temporal dynamics within the beta frequency range are highly diverse and deviating from a reference biomarker frequency can result in altered adaptive stimulation patterns. SIGNIFICANCE A clinical-neurophysiological interrogation could be helpful to determine the patient-specific feedback signal for aDBS.
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Affiliation(s)
- Laura Alva
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Elena Bernasconi
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Flavie Torrecillos
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Petra Fischer
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, University Walk, BS8 1TD Bristol, United Kingdom
| | - Alberto Averna
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Manuel Bange
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Abteen Mostofi
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, London SW17 0RE, United Kingdom
| | - Alek Pogosyan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Keyoumars Ashkan
- Department of Neurosurgery, King's College Hospital, King's College London, SE59RS, United Kingdom
| | - Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Erlick A Pereira
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, London SW17 0RE, United Kingdom
| | - Huiling Tan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
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12
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Radcliffe EM, Baumgartner AJ, Kern DS, Al Borno M, Ojemann S, Kramer DR, Thompson JA. Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease. J Neurophysiol 2023; 129:1492-1504. [PMID: 37198135 DOI: 10.1152/jn.00055.2023] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/23/2023] [Accepted: 05/17/2023] [Indexed: 05/19/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.
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Affiliation(s)
- Erin M Radcliffe
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Alexander J Baumgartner
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Drew S Kern
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Mazen Al Borno
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Computer Science and Engineering, University of Colorado Denver, Denver, Colorado, United States
| | - Steven Ojemann
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Daniel R Kramer
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - John A Thompson
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
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13
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Chen Y, Zhang G, Guan L, Gong C, Ma B, Hao H, Li L. Progress in the development of a fully implantable brain-computer interface: the potential of sensing-enabled neurostimulators. Natl Sci Rev 2022; 9:nwac099. [PMID: 36196114 PMCID: PMC9522391 DOI: 10.1093/nsr/nwac099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 04/14/2022] [Accepted: 05/23/2022] [Indexed: 11/12/2022] Open
Abstract
This perspective article investigates the performance of using a sensing-enabled neurostimulator as a motor brain-computer interface.
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Affiliation(s)
- Yue Chen
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, China
| | - Guokun Zhang
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, China
| | - Linxiao Guan
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, China
| | - Chen Gong
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, China
| | - Bozhi Ma
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, China
| | - Hongwei Hao
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, China
| | - Luming Li
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, China
- Precision Medicine & Healthcare Research Center, Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, China
- IDG/McGovern Institute for Brain Research at Tsinghua University, China
- Institute of Epilepsy, Beijing Institute for Brain Disorders, China
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14
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Rauschenberger L, Güttler C, Volkmann J, Kühn AA, Ip CW, Lofredi R. A translational perspective on pathophysiological changes of oscillatory activity in dystonia and parkinsonism. Exp Neurol 2022; 355:114140. [PMID: 35690132 DOI: 10.1016/j.expneurol.2022.114140] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/14/2022] [Accepted: 06/03/2022] [Indexed: 11/19/2022]
Abstract
Intracerebral recordings from movement disorders patients undergoing deep brain stimulation have allowed the identification of pathophysiological patterns in oscillatory activity that correlate with symptom severity. Changes in oscillatory synchrony occur within and across brain areas, matching the classification of movement disorders as network disorders. However, the underlying mechanisms of oscillatory changes are difficult to assess in patients, as experimental interventions are technically limited and ethically problematic. This is why animal models play an important role in neurophysiological research of movement disorders. In this review, we highlight the contributions of translational research to the mechanistic understanding of pathological changes in oscillatory activity, with a focus on parkinsonism and dystonia, while addressing the limitations of current findings and proposing possible future directions.
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Affiliation(s)
- Lisa Rauschenberger
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Würzburg, Germany
| | - Christopher Güttler
- Department of Neurology, Movement Disorders and Neuromodulation Unit, Campus Charité Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Würzburg, Germany
| | - Andrea A Kühn
- Department of Neurology, Movement Disorders and Neuromodulation Unit, Campus Charité Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt-Universität, Berlin, Germany; NeuroCure, Exzellenzcluster, Charité-Universitätsmedizin Berlin, Berlin, Germany; DZNE, German Center for Neurodegenerative Diseases, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Chi Wang Ip
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Würzburg, Germany
| | - Roxanne Lofredi
- Department of Neurology, Movement Disorders and Neuromodulation Unit, Campus Charité Mitte, Charité-Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany.
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15
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Toward therapeutic electrophysiology: beta-band suppression as a biomarker in chronic local field potential recordings. NPJ Parkinsons Dis 2022; 8:44. [PMID: 35440571 PMCID: PMC9018912 DOI: 10.1038/s41531-022-00301-2] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 03/04/2022] [Indexed: 11/08/2022] Open
Abstract
Adaptive deep brain stimulation (aDBS) is a promising concept for feedback-based neurostimulation, with the potential of clinical implementation with the sensing-enabled Percept neurostimulator. We aim to characterize chronic electrophysiological activity during stimulation and to validate beta-band activity as a biomarker for bradykinesia. Subthalamic activity was recorded during stepwise stimulation amplitude increase OFF medication in 10 Parkinson's patients during rest and finger tapping. Offline analysis of wavelet-transformed beta-band activity and assessment of inter-variable relationships in linear mixed effects models were implemented. There was a stepwise suppression of low-beta activity with increasing stimulation intensity (p = 0.002). Low-beta power was negatively correlated with movement speed and predictive for velocity improvements (p < 0.001), stimulation amplitude for beta suppression (p < 0.001). Here, we characterize beta-band modulation as a chronic biomarker for motor performance. Our investigations support the use of electrophysiology in therapy optimization, providing evidence for the use of biomarker analysis for clinical aDBS.
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16
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Girges C, Vijiaratnam N, Zrinzo L, Ekanayake J, Foltynie T. Volitional Control of Brain Motor Activity and Its Therapeutic Potential. Neuromodulation 2022; 25:1187-1196. [DOI: 10.1016/j.neurom.2022.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 12/08/2021] [Accepted: 12/28/2021] [Indexed: 12/01/2022]
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17
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Subthalamic-Cortical Network Reorganization during Parkinson's Tremor. J Neurosci 2021; 41:9844-9858. [PMID: 34702744 DOI: 10.1523/jneurosci.0854-21.2021] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 09/08/2021] [Accepted: 10/10/2021] [Indexed: 01/08/2023] Open
Abstract
Tremor, a common and often primary symptom of Parkinson's disease, has been modeled with distinct onset and maintenance dynamics. To identify the neurophysiologic correlates of each state, we acquired intraoperative cortical and subthalamic nucleus recordings from 10 patients (9 male, 1 female) performing a naturalistic visual-motor task. From this task, we isolated short epochs of tremor onset and sustained tremor. Comparing these epochs, we found that the subthalamic nucleus was central to tremor onset, as it drove both motor cortical activity and tremor output. Once tremor became sustained, control of tremor shifted to cortex. At the same time, changes in directed functional connectivity across sensorimotor cortex further distinguished the sustained tremor state.SIGNIFICANCE STATEMENT Tremor is a common symptom of Parkinson's disease (PD). While tremor pathophysiology is thought to involve both basal ganglia and cerebello-thalamic-cortical circuits, it is unknown how these structures functionally interact to produce tremor. In this article, we analyzed intracranial recordings from the subthalamic nucleus and sensorimotor cortex in patients with PD undergoing deep brain stimulation surgery. Using an intraoperative task, we examined tremor in two separate dynamic contexts: when tremor first emerged, and when tremor was sustained. We believe that these findings reconcile several models of Parkinson's tremor, while describing the short-timescale dynamics of subcortical-cortical interactions during tremor for the first time. These findings may describe a framework for developing proactive and responsive neurostimulation models for specifically treating tremor.
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18
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di Biase L, Tinkhauser G, Martin Moraud E, Caminiti ML, Pecoraro PM, Di Lazzaro V. Adaptive, personalized closed-loop therapy for Parkinson's disease: biochemical, neurophysiological, and wearable sensing systems. Expert Rev Neurother 2021; 21:1371-1388. [PMID: 34736368 DOI: 10.1080/14737175.2021.2000392] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Motor complication management is one of the main unmet needs in Parkinson's disease patients. AREAS COVERED Among the most promising emerging approaches for handling motor complications in Parkinson's disease, adaptive deep brain stimulation strategies operating in closed-loop have emerged as pivotal to deliver sustained, near-to-physiological inputs to dysfunctional basal ganglia-cortical circuits over time. Existing sensing systems that can provide feedback signals to close the loop include biochemical-, neurophysiological- or wearable-sensors. Biochemical sensing allows to directly monitor the pharmacokinetic and pharmacodynamic of antiparkinsonian drugs and metabolites. Neurophysiological sensing relies on neurotechnologies to sense cortical or subcortical brain activity and extract real-time correlates of symptom intensity or symptom control during DBS. A more direct representation of the symptom state, particularly the phenomenological differentiation and quantification of motor symptoms, can be realized via wearable sensor technology. EXPERT OPINION Biochemical, neurophysiologic, and wearable-based biomarkers are promising technological tools that either individually or in combination could guide adaptive therapy for Parkinson's disease motor symptoms in the future.
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Affiliation(s)
- Lazzaro di Biase
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico Di Roma, Rome, Italy.,Brain Innovations Lab, Università Campus Bio-Medico Di Roma, Rome, Italy
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Eduardo Martin Moraud
- Department of Clinical Neurosciences, Lausanne University Hospital (Chuv) and University of Lausanne (Unil), Lausanne, Switzerland.,Defitech Center for Interventional Neurotherapies (.neurorestore), Lausanne University Hospital and Swiss Federal Institute of Technology (Epfl), Lausanne, Switzerland
| | - Maria Letizia Caminiti
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico Di Roma, Rome, Italy
| | - Pasquale Maria Pecoraro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico Di Roma, Rome, Italy
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico Di Roma, Rome, Italy
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19
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Arbuthnott GW. An Introspective Approach: A Lifetime of Parkinson's Disease Research and Not Much to Show for it Yet? Cells 2021; 10:cells10030513. [PMID: 33670933 PMCID: PMC7997292 DOI: 10.3390/cells10030513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 02/23/2021] [Accepted: 02/23/2021] [Indexed: 11/16/2022] Open
Abstract
I feel part of a massive effort to understand what is wrong with motor systems in the brain relating to Parkinson’s disease. Today, the symptoms of the disease can be modified slightly, but dopamine neurons still die; the disease progression continues inexorably. Maybe the next research phase will bring the power of modern genetics to bear on halting, or better, preventing cell death. The arrival of accessible human neuron assemblies in organoids perhaps will provide a better access to the processes underlying neuronal demise.
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Affiliation(s)
- Gordon W Arbuthnott
- Brain Mechanisms for Behaviour Unit, Okinawa Institute of Science and Technology, Graduate University, Onna-son, Okinawa 904-0495, Japan
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