1
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Duchet B, Bogacz R. How to design optimal brain stimulation to modulate phase-amplitude coupling? J Neural Eng 2024; 21:10.1088/1741-2552/ad5b1a. [PMID: 38985096 PMCID: PMC7616267 DOI: 10.1088/1741-2552/ad5b1a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 06/24/2024] [Indexed: 07/11/2024]
Abstract
Objective.Phase-amplitude coupling (PAC), the coupling of the amplitude of a faster brain rhythm to the phase of a slower brain rhythm, plays a significant role in brain activity and has been implicated in various neurological disorders. For example, in Parkinson's disease, PAC between the beta (13-30 Hz) and gamma (30-100 Hz) rhythms in the motor cortex is exaggerated, while in Alzheimer's disease, PAC between the theta (4-8 Hz) and gamma rhythms is diminished. Modulating PAC (i.e. reducing or enhancing PAC) using brain stimulation could therefore open new therapeutic avenues. However, while it has been previously reported that phase-locked stimulation can increase PAC, it is unclear what the optimal stimulation strategy to modulate PAC might be. Here, we provide a theoretical framework to narrow down the experimental optimisation of stimulation aimed at modulating PAC, which would otherwise rely on trial and error.Approach.We make analytical predictions using a Stuart-Landau model, and confirm these predictions in a more realistic model of coupled neural populations.Main results.Our framework specifies the critical Fourier coefficients of the stimulation waveform which should be tuned to optimally modulate PAC. Depending on the characteristics of the amplitude response curve of the fast population, these components may include the slow frequency, the fast frequency, combinations of these, as well as their harmonics. We also show that the optimal balance of energy between these Fourier components depends on the relative strength of the endogenous slow and fast rhythms, and that the alignment of fast components with the fast rhythm should change throughout the slow cycle. Furthermore, we identify the conditions requiring to phase-lock stimulation to the fast and/or slow rhythms.Significance.Together, our theoretical framework lays the foundation for guiding the development of innovative and more effective brain stimulation aimed at modulating PAC for therapeutic benefit.
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Affiliation(s)
- Benoit Duchet
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United
Kingdom
| | - Rafal Bogacz
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United
Kingdom
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2
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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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3
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Xu M, Hu B, Wang Z, Zhu L, Lin J, Wang D. Mathematical derivation and mechanism analysis of beta oscillations in a cortex-pallidum model. Cogn Neurodyn 2024; 18:1359-1378. [PMID: 38826645 PMCID: PMC11143146 DOI: 10.1007/s11571-023-09951-1] [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: 05/31/2022] [Revised: 01/07/2023] [Accepted: 03/09/2023] [Indexed: 06/04/2024] Open
Abstract
In this paper, we develop a new cortex-pallidum model to study the origin mechanism of Parkinson's oscillations in the cortex. In contrast to many previous models, the globus pallidus internal (GPi) and externa (GPe) both exert direct inhibitory feedback to the cortex. Using Hopf bifurcation analysis, two new critical conditions for oscillations, which can include the self-feedback projection of GPe, are obtained. In this paper, we find that the average discharge rate (ADR) is an important marker of oscillations, which can divide Hopf bifurcations into two types that can uniformly be used to explain the oscillation mechanism. Interestingly, the ADR of the cortex first increases and then decreases with increasing coupling weights that are projected to the GPe. Regarding the Hopf bifurcation critical conditions, the quantitative relationship between the inhibitory projection and excitatory projection to the GPe is monotonically increasing; in contrast, the relationship between different coupling weights in the cortex is monotonically decreasing. In general, the oscillation amplitude is the lowest near the bifurcation points and reaches the maximum value with the evolution of oscillations. The GPe is an effective target for deep brain stimulation to alleviate oscillations in the cortex.
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Affiliation(s)
- Minbo Xu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou, 310023 China
| | - Bing Hu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou, 310023 China
| | - Zhizhi Wang
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou, 310023 China
| | - Luyao Zhu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou, 310023 China
| | - Jiahui Lin
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou, 310023 China
| | - Dingjiang Wang
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou, 310023 China
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4
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Fang Z, Sack AT, Leunissen I. The phase of tACS-entrained pre-SMA beta oscillations modulates motor inhibition. Neuroimage 2024; 290:120572. [PMID: 38490584 DOI: 10.1016/j.neuroimage.2024.120572] [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: 09/15/2023] [Revised: 03/06/2024] [Accepted: 03/08/2024] [Indexed: 03/17/2024] Open
Abstract
Inhibitory control has been linked to beta oscillations in the fronto-basal ganglia network. Here we aim to investigate the functional role of the phase of this oscillatory beta rhythm for successful motor inhibition. We applied 20 Hz transcranial alternating current stimulation (tACS) to the pre-supplementary motor area (pre-SMA) while presenting stop signals at 4 (Experiment 1) and 8 (Experiment 2) equidistant phases of the tACS entrained beta oscillations. Participants showed better inhibitory performance when stop signals were presented at the trough of the beta oscillation whereas their inhibitory control performance decreased with stop signals being presented at the oscillatory beta peak. These results are consistent with the communication through coherence theory, in which postsynaptic effects are thought to be greater when an input arrives at an optimal phase within the oscillatory cycle of the target neuronal population. The current study provides mechanistic insights into the neural communication principles underlying successful motor inhibition and may have implications for phase-specific interventions aimed at treating inhibitory control disorders such as PD or OCD.
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Affiliation(s)
- Zhou Fang
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands; Maastricht Brain Imaging Centre (MBIC), Maastricht University, Oxfordlaan 55, 6229EV, Maastricht, The Netherlands
| | - Alexander T Sack
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands; Maastricht Brain Imaging Centre (MBIC), Maastricht University, Oxfordlaan 55, 6229EV, Maastricht, The Netherlands; Centre for Integrative Neuroscience, Faculty of Psychology and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands
| | - Inge Leunissen
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands; Maastricht Brain Imaging Centre (MBIC), Maastricht University, Oxfordlaan 55, 6229EV, Maastricht, The Netherlands.
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5
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Spooner RK, Hizli BJ, Bahners BH, Schnitzler A, Florin E. Modulation of DBS-induced cortical responses and movement by the directionality and magnitude of current administered. NPJ Parkinsons Dis 2024; 10:53. [PMID: 38459031 PMCID: PMC10923868 DOI: 10.1038/s41531-024-00663-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 02/16/2024] [Indexed: 03/10/2024] Open
Abstract
Subthalamic deep brain stimulation (STN-DBS) is an effective therapy for alleviating motor symptoms in people with Parkinson's disease (PwP), although some may not receive optimal clinical benefits. One potential mechanism of STN-DBS involves antidromic activation of the hyperdirect pathway (HDP), thus suppressing cortical beta synchrony to improve motor function, albeit the precise mechanisms underlying optimal DBS parameters are not well understood. To address this, 18 PwP with STN-DBS completed a 2 Hz monopolar stimulation of the left STN during MEG. MEG data were imaged in the time-frequency domain using minimum norm estimation. Peak vertex time series data were extracted to interrogate the directional specificity and magnitude of DBS current on evoked and induced cortical responses and accelerometer metrics of finger tapping using linear mixed-effects models and mediation analyses. We observed increases in evoked responses (HDP ~ 3-10 ms) and synchronization of beta oscillatory power (14-30 Hz, 10-100 ms) following DBS pulse onset in the primary sensorimotor cortex (SM1), supplementary motor area (SMA) and middle frontal gyrus (MFG) ipsilateral to the site of stimulation. DBS parameters significantly modulated neural and behavioral outcomes, with clinically effective contacts eliciting significant increases in medium-latency evoked responses, reductions in induced SM1 beta power, and better movement profiles compared to suboptimal contacts, often regardless of the magnitude of current applied. Finally, HDP-related improvements in motor function were mediated by the degree of SM1 beta suppression in a setting-dependent manner. Together, these data suggest that DBS-evoked brain-behavior dynamics are influenced by the level of beta power in key hubs of the basal ganglia-cortical loop, and this effect is exacerbated by the clinical efficacy of DBS parameters. Such data provides novel mechanistic and clinical insight, which may prove useful for characterizing DBS programming strategies to optimize motor symptom improvement in the future.
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Affiliation(s)
- Rachel K Spooner
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany.
| | - Baccara J Hizli
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Bahne H Bahners
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
- Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
- Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany.
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6
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Rosenblum M. Feedback control of collective dynamics in an oscillator population with time-dependent connectivity. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1358146. [PMID: 38371453 PMCID: PMC10869593 DOI: 10.3389/fnetp.2024.1358146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 01/23/2024] [Indexed: 02/20/2024]
Abstract
We present a numerical study of pulsatile feedback-based control of synchrony level in a highly-interconnected oscillatory network. We focus on a nontrivial case when the system is close to the synchronization transition point and exhibits collective rhythm with strong amplitude modulation. We pay special attention to technical but essential steps like causal real-time extraction of the signal of interest from a noisy measurement and estimation of instantaneous phase and amplitude. The feedback loop's parameters are tuned automatically to suppress synchrony. Though the study is motivated by neuroscience, the results are relevant to controlling oscillatory activity in ensembles of various natures and, thus, to the rapidly developing field of network physiology.
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Affiliation(s)
- Michael Rosenblum
- Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany
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7
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Händel BF, Chen X, Murali S. Reduced occipital alpha power marks a movement induced state change that facilitates creative thinking. Neuropsychologia 2024; 193:108743. [PMID: 38096980 DOI: 10.1016/j.neuropsychologia.2023.108743] [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: 07/26/2023] [Revised: 11/21/2023] [Accepted: 11/30/2023] [Indexed: 12/18/2023]
Abstract
Walking and minimized movement restriction has a positive effect on creativity, such as divergent thinking. Walking is further known to reduce occipital alpha activity. We used mobile EEG during free and restricted movement, while subjects (N = 23) solved a Guilford's alternate uses test, to understand if occipital alpha power is also affected by movement restriction and if it is a neural marker for creativity. We found that, independent of the task, relative occipital alpha power was higher during movement restriction and showed a negative relationship with creativity scores even though the task was purely based on auditory information. Alpha lateralization was only modulated during the task related think-time (mainly during sitting) and showed a positive relationship with creativity scores but no correlation with the relative alpha power. This indicates that the ongoing alpha power and alpha lateralization mark two independent processes. Overall, our work shows that movement and movement restriction leads to a general change in state which affects cognitive processes. Specifically, limiting one's movements e.g. due to sitting and fixating on a screen can introduce a state of increased occipital alpha power and lowered creativity.
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Affiliation(s)
- Barbara F Händel
- Department of Neurology, University Hospital Würzburg, 97080 Würzburg, Germany
| | - Xinyu Chen
- Institute of Psychology III, University of Würzburg, 97070, Germany.
| | - Supriya Murali
- Institute of Psychology III, University of Würzburg, 97070, Germany
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8
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Widge AS. Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity. Neuropsychopharmacology 2024; 49:138-149. [PMID: 37415081 PMCID: PMC10700701 DOI: 10.1038/s41386-023-01643-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 05/28/2023] [Accepted: 06/20/2023] [Indexed: 07/08/2023]
Abstract
Deep brain stimulation (DBS) is an invasive approach to precise modulation of psychiatrically relevant circuits. Although it has impressive results in open-label psychiatric trials, DBS has also struggled to scale to and pass through multi-center randomized trials. This contrasts with Parkinson disease, where DBS is an established therapy treating thousands of patients annually. The core difference between these clinical applications is the difficulty of proving target engagement, and of leveraging the wide range of possible settings (parameters) that can be programmed in a given patient's DBS. In Parkinson's, patients' symptoms change rapidly and visibly when the stimulator is tuned to the correct parameters. In psychiatry, those same changes take days to weeks, limiting a clinician's ability to explore parameter space and identify patient-specific optimal settings. I review new approaches to psychiatric target engagement, with an emphasis on major depressive disorder (MDD). Specifically, I argue that better engagement may come by focusing on the root causes of psychiatric illness: dysfunction in specific, measurable cognitive functions and in the connectivity and synchrony of distributed brain circuits. I overview recent progress in both those domains, and how it may relate to other technologies discussed in companion articles in this issue.
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Affiliation(s)
- Alik S Widge
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
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9
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Fleming JE, Pont Sanchis I, Lemmens O, Denison-Smith A, West TO, Denison T, Cagnan H. From dawn till dusk: Time-adaptive bayesian optimization for neurostimulation. PLoS Comput Biol 2023; 19:e1011674. [PMID: 38091368 PMCID: PMC10718444 DOI: 10.1371/journal.pcbi.1011674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 11/09/2023] [Indexed: 12/18/2023] Open
Abstract
Stimulation optimization has garnered considerable interest in recent years in order to efficiently parametrize neuromodulation-based therapies. To date, efforts focused on automatically identifying settings from parameter spaces that do not change over time. A limitation of these approaches, however, is that they lack consideration for time dependent factors that may influence therapy outcomes. Disease progression and biological rhythmicity are two sources of variation that may influence optimal stimulation settings over time. To account for this, we present a novel time-varying Bayesian optimization (TV-BayesOpt) for tracking the optimum parameter set for neuromodulation therapy. We evaluate the performance of TV-BayesOpt for tracking gradual and periodic slow variations over time. The algorithm was investigated within the context of a computational model of phase-locked deep brain stimulation for treating oscillopathies representative of common movement disorders such as Parkinson's disease and Essential Tremor. When the optimal stimulation settings changed due to gradual and periodic sources, TV-BayesOpt outperformed standard time-invariant techniques and was able to identify the appropriate stimulation setting. Through incorporation of both a gradual "forgetting" and periodic covariance functions, the algorithm maintained robust performance when a priori knowledge differed from observed variations. This algorithm presents a broad framework that can be leveraged for the treatment of a range of neurological and psychiatric conditions and can be used to track variations in optimal stimulation settings such as amplitude, pulse-width, frequency and phase for invasive and non-invasive neuromodulation strategies.
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Affiliation(s)
- John E. Fleming
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, United Kingdom
| | - Ines Pont Sanchis
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Oxford, United Kingdom
| | - Oscar Lemmens
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Oxford, United Kingdom
| | - Angus Denison-Smith
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Oxford, United Kingdom
| | - Timothy O. West
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, United Kingdom
- Department of Bioengineering, Imperial College London, White City Campus, London, United Kingdom
| | - Timothy Denison
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, United Kingdom
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Oxford, United Kingdom
| | - Hayriye Cagnan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, United Kingdom
- Department of Bioengineering, Imperial College London, White City Campus, London, United Kingdom
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10
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Ochoa JÁ, Gonzalez-Burgos I, Nicolás MJ, Valencia M. Open Hardware Implementation of Real-Time Phase and Amplitude Estimation for Neurophysiologic Signals. Bioengineering (Basel) 2023; 10:1350. [PMID: 38135941 PMCID: PMC10740741 DOI: 10.3390/bioengineering10121350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/16/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023] Open
Abstract
Adaptive deep brain stimulation (aDBS) is a promising concept in the field of DBS that consists of delivering electrical stimulation in response to specific events. Dynamic adaptivity arises when stimulation targets dynamically changing states, which often calls for a reliable and fast causal estimation of the phase and amplitude of the signals. Here, we present an open-hardware implementation that exploits the concepts of resonators and Hilbert filters embedded in an open-hardware platform. To emulate real-world scenarios, we built a hardware setup that included a system to replay and process different types of physiological signals and test the accuracy of the instantaneous phase and amplitude estimates. The results show that the system can provide a precise and reliable estimation of the phase even in the challenging scenario of dealing with high-frequency oscillations (~250 Hz) in real-time. The framework might be adopted in neuromodulation studies to quickly test biomarkers in clinical and preclinical settings, supporting the advancement of aDBS.
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Affiliation(s)
- José Ángel Ochoa
- Biomedical Engineering Program, Physiological Monitoring and Control Laboratory, CIMA, Universidad de Navarra, Avda Pio XII 55, 31080 Pamplona, Spain; (J.Á.O.); (I.G.-B.); (M.J.N.)
- IdiSNA, Navarra Institute for Health Research, C/Irunlarrea, 31008 Pamplona, Spain
| | - Irene Gonzalez-Burgos
- Biomedical Engineering Program, Physiological Monitoring and Control Laboratory, CIMA, Universidad de Navarra, Avda Pio XII 55, 31080 Pamplona, Spain; (J.Á.O.); (I.G.-B.); (M.J.N.)
- IdiSNA, Navarra Institute for Health Research, C/Irunlarrea, 31008 Pamplona, Spain
| | - María Jesús Nicolás
- Biomedical Engineering Program, Physiological Monitoring and Control Laboratory, CIMA, Universidad de Navarra, Avda Pio XII 55, 31080 Pamplona, Spain; (J.Á.O.); (I.G.-B.); (M.J.N.)
- IdiSNA, Navarra Institute for Health Research, C/Irunlarrea, 31008 Pamplona, Spain
| | - Miguel Valencia
- Biomedical Engineering Program, Physiological Monitoring and Control Laboratory, CIMA, Universidad de Navarra, Avda Pio XII 55, 31080 Pamplona, Spain; (J.Á.O.); (I.G.-B.); (M.J.N.)
- IdiSNA, Navarra Institute for Health Research, C/Irunlarrea, 31008 Pamplona, Spain
- Institute of Data Science and Artificial Intelligence, Universidad de Navarra, Campus Universitario, 31009 Pamplona, Spain
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11
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Sandoval-Pistorius SS, Hacker ML, Waters AC, Wang J, Provenza NR, de Hemptinne C, Johnson KA, Morrison MA, Cernera S. Advances in Deep Brain Stimulation: From Mechanisms to Applications. J Neurosci 2023; 43:7575-7586. [PMID: 37940596 PMCID: PMC10634582 DOI: 10.1523/jneurosci.1427-23.2023] [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: 07/27/2023] [Revised: 08/14/2023] [Accepted: 08/15/2023] [Indexed: 11/10/2023] Open
Abstract
Deep brain stimulation (DBS) is an effective therapy for various neurologic and neuropsychiatric disorders, involving chronic implantation of electrodes into target brain regions for electrical stimulation delivery. Despite its safety and efficacy, DBS remains an underutilized therapy. Advances in the field of DBS, including in technology, mechanistic understanding, and applications have the potential to expand access and use of DBS, while also improving clinical outcomes. Developments in DBS technology, such as MRI compatibility and bidirectional DBS systems capable of sensing neural activity while providing therapeutic stimulation, have enabled advances in our understanding of DBS mechanisms and its application. In this review, we summarize recent work exploring DBS modulation of target networks. We also cover current work focusing on improved programming and the development of novel stimulation paradigms that go beyond current standards of DBS, many of which are enabled by sensing-enabled DBS systems and have the potential to expand access to DBS.
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Affiliation(s)
| | - Mallory L Hacker
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee 37232
| | - Allison C Waters
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York 10029
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York 10029
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota 55455
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas 77030
| | - Coralie de Hemptinne
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida 32608
| | - Kara A Johnson
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida 32608
| | - Melanie A Morrison
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Stephanie Cernera
- Department of Neurological Surgery, University of California-San Francisco, San Francisco, California 94143
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12
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Fleming JE, Senneff S, Lowery MM. Multivariable closed-loop control of deep brain stimulation for Parkinson's disease. J Neural Eng 2023; 20:056029. [PMID: 37733003 DOI: 10.1088/1741-2552/acfbfa] [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: 06/28/2022] [Accepted: 09/21/2023] [Indexed: 09/22/2023]
Abstract
Objective. Closed-loop deep brain stimulation (DBS) methods for Parkinson's disease (PD) to-date modulate either stimulation amplitude or frequency to control a single biomarker. While good performance has been demonstrated for symptoms that are correlated with the chosen biomarker, suboptimal regulation can occur for uncorrelated symptoms or when the relationship between biomarker and symptom varies. Control of stimulation-induced side-effects is typically not considered.Approach.A multivariable control architecture is presented to selectively target suppression of either tremor or subthalamic nucleus beta band oscillations. DBS pulse amplitude and duration are modulated to maintain amplitude below a threshold and avoid stimulation of distal large diameter axons associated with stimulation-induced side effects. A supervisor selects between a bank of controllers which modulate DBS pulse amplitude to control rest tremor or beta activity depending on the level of muscle electromyographic (EMG) activity detected. A secondary controller limits pulse amplitude and modulates pulse duration to target smaller diameter axons lying close to the electrode. The control architecture was investigated in a computational model of the PD motor network which simulated the cortico-basal ganglia network, motoneuron pool, EMG and muscle force signals.Main results.Good control of both rest tremor and beta activity was observed with reduced power delivered when compared with conventional open loop stimulation, The supervisor avoided over- or under-stimulation which occurred when using a single controller tuned to one biomarker. When DBS amplitude was constrained, the secondary controller maintained the efficacy of stimulation by increasing pulse duration to compensate for reduced amplitude. Dual parameter control delivered effective control of the target biomarkers, with additional savings in the power delivered.Significance.Non-linear multivariable control can enable targeted suppression of motor symptoms for PD patients. Moreover, dual parameter control facilitates automatic regulation of the stimulation therapeutic dosage to prevent overstimulation, whilst providing additional power savings.
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Affiliation(s)
- John E Fleming
- Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford OX1 3TH, United Kingdom
| | - Sageanne Senneff
- Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland
| | - Madeleine M Lowery
- Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland
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13
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Gilbert Z, Mason X, Sebastian R, Tang AM, Martin Del Campo-Vera R, Chen KH, Leonor A, Shao A, Tabarsi E, Chung R, Sundaram S, Kammen A, Cavaleri J, Gogia AS, Heck C, Nune G, Liu CY, Kellis SS, Lee B. A review of neurophysiological effects and efficiency of waveform parameters in deep brain stimulation. Clin Neurophysiol 2023; 152:93-111. [PMID: 37208270 DOI: 10.1016/j.clinph.2023.04.007] [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: 09/20/2022] [Revised: 02/09/2023] [Accepted: 04/15/2023] [Indexed: 05/21/2023]
Abstract
Neurostimulation has diverse clinical applications and potential as a treatment for medically refractory movement disorders, epilepsy, and other neurological disorders. However, the parameters used to program electrodes-polarity, pulse width, amplitude, and frequency-and how they are adjusted have remained largely untouched since the 1970 s. This review summarizes the state-of-the-art in Deep Brain Stimulation (DBS) and highlights the need for further research to uncover the physiological mechanisms of neurostimulation. We focus on studies that reveal the potential for clinicians to use waveform parameters to selectively stimulate neural tissue for therapeutic benefit, while avoiding activating tissue associated with adverse effects. DBS uses cathodic monophasic rectangular pulses with passive recharging in clinical practice to treat neurological conditions such as Parkinson's Disease. However, research has shown that stimulation efficiency can be improved, and side effects reduced, through modulating parameters and adding novel waveform properties. These developments can prolong implantable pulse generator lifespan, reducing costs and surgery-associated risks. Waveform parameters can stimulate neurons based on axon orientation and intrinsic structural properties, providing clinicians with more precise targeting of neural pathways. These findings could expand the spectrum of diseases treatable with neuromodulation and improve patient outcomes.
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Affiliation(s)
- Zachary Gilbert
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
| | - Xenos Mason
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States; USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Rinu Sebastian
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Austin M Tang
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Roberto Martin Del Campo-Vera
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Kuang-Hsuan Chen
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Andrea Leonor
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Arthur Shao
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Emiliano Tabarsi
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Ryan Chung
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Shivani Sundaram
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Alexandra Kammen
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Jonathan Cavaleri
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Angad S Gogia
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Christi Heck
- Department of Neurology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States; USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - George Nune
- Department of Neurology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States; USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Charles Y Liu
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States; Department of Neurology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States; USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Spencer S Kellis
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States; USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Brian Lee
- Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States; USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, United States
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14
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Widge AS. Closed-Loop Deep Brain Stimulation for Psychiatric Disorders. Harv Rev Psychiatry 2023; 31:162-171. [PMID: 37171475 PMCID: PMC10188203 DOI: 10.1097/hrp.0000000000000367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
ABSTRACT Deep brain stimulation (DBS) is a well-established approach to treating medication-refractory neurological disorders and holds promise for treating psychiatric disorders. Despite strong open-label results in extremely refractory patients, DBS has struggled to meet endpoints in randomized controlled trials. A major challenge is stimulation "dosing"-DBS systems have many adjustable parameters, and clinicians receive little feedback on whether they have chosen the correct parameters for an individual patient. Multiple groups have proposed closed loop technologies as a solution. These systems sense electrical activity, identify markers of an (un)desired state, then automatically deliver or adjust stimulation to alter that electrical state. Closed loop DBS has been successfully deployed in movement disorders and epilepsy. The availability of that technology, as well as advances in opportunities for invasive research with neurosurgical patients, has yielded multiple pilot demonstrations in psychiatric illness. Those demonstrations split into two schools of thought, one rooted in well-established diagnoses and symptom scales, the other in the more experimental Research Domain Criteria (RDoC) framework. Both are promising, and both are limited by the boundaries of current stimulation technology. They are in turn driving advances in implantable recording hardware, signal processing, and stimulation paradigms. The combination of these advances is likely to change both our understanding of psychiatric neurobiology and our treatment toolbox, though the timeframe may be limited by the realities of implantable device development.
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Affiliation(s)
- Alik S Widge
- From the Department of Psychiatry & Behavioral Sciences and Medical Discovery Team on Addictions, University of Minnesota
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15
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Zaaimi B, Turnbull M, Hazra A, Wang Y, Gandara C, McLeod F, McDermott EE, Escobedo-Cousin E, Idil AS, Bailey RG, Tardio S, Patel A, Ponon N, Gausden J, Walsh D, Hutchings F, Kaiser M, Cunningham MO, Clowry GJ, LeBeau FEN, Constandinou TG, Baker SN, Donaldson N, Degenaar P, O'Neill A, Trevelyan AJ, Jackson A. Closed-loop optogenetic control of the dynamics of neural activity in non-human primates. Nat Biomed Eng 2023; 7:559-575. [PMID: 36266536 PMCID: PMC7614485 DOI: 10.1038/s41551-022-00945-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 08/14/2022] [Indexed: 11/08/2022]
Abstract
Electrical neurostimulation is effective in the treatment of neurological disorders, but associated recording artefacts generally limit its applications to open-loop stimuli. Real-time and continuous closed-loop control of brain activity can, however, be achieved by pairing concurrent electrical recordings and optogenetics. Here we show that closed-loop optogenetic stimulation with excitatory opsins enables the precise manipulation of neural dynamics in brain slices from transgenic mice and in anaesthetized non-human primates. The approach generates oscillations in quiescent tissue, enhances or suppresses endogenous patterns in active tissue and modulates seizure-like bursts elicited by the convulsant 4-aminopyridine. A nonlinear model of the phase-dependent effects of optical stimulation reproduced the modulation of cycles of local-field potentials associated with seizure oscillations, as evidenced by the systematic changes in the variability and entropy of the phase-space trajectories of seizures, which correlated with changes in their duration and intensity. We also show that closed-loop optogenetic neurostimulation could be delivered using intracortical optrodes incorporating light-emitting diodes. Closed-loop optogenetic approaches may be translatable to therapeutic applications in humans.
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Affiliation(s)
- B Zaaimi
- Biosciences Institute, Newcastle University, Newcastle, UK
- School of Life and Health Sciences, Aston University, Birmingham, UK
| | - M Turnbull
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - A Hazra
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - Y Wang
- School of Computing, Newcastle University, Newcastle, UK
| | - C Gandara
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - F McLeod
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - E E McDermott
- Biosciences Institute, Newcastle University, Newcastle, UK
| | | | - A Shah Idil
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - R G Bailey
- School of Engineering, Newcastle University, Newcastle, UK
| | - S Tardio
- School of Engineering, Newcastle University, Newcastle, UK
| | - A Patel
- School of Engineering, Newcastle University, Newcastle, UK
| | - N Ponon
- School of Engineering, Newcastle University, Newcastle, UK
| | - J Gausden
- School of Engineering, Newcastle University, Newcastle, UK
| | - D Walsh
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - F Hutchings
- School of Computing, Newcastle University, Newcastle, UK
| | - M Kaiser
- School of Computing, Newcastle University, Newcastle, UK
- NIHR, Nottingham Biomedical Research Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - M O Cunningham
- School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - G J Clowry
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - F E N LeBeau
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - T G Constandinou
- Department of Electrical and Electronic Engineering, Imperial College, London, UK
| | - S N Baker
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - N Donaldson
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - P Degenaar
- School of Engineering, Newcastle University, Newcastle, UK
| | - A O'Neill
- School of Engineering, Newcastle University, Newcastle, UK
| | - A J Trevelyan
- Biosciences Institute, Newcastle University, Newcastle, UK
| | - A Jackson
- Biosciences Institute, Newcastle University, Newcastle, UK.
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16
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Ma YF, Lin YA, Huang CL, Hsu CC, Wang S, Yeh SR, Tsai YC. Lactiplantibacillus plantarum PS128 Alleviates Exaggerated Cortical Beta Oscillations and Motor Deficits in the 6-Hydroxydopamine Rat Model of Parkinson's Disease. Probiotics Antimicrob Proteins 2023; 15:312-325. [PMID: 34449056 DOI: 10.1007/s12602-021-09828-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/29/2021] [Indexed: 10/20/2022]
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by midbrain dopaminergic neuronal loss and subsequent physical impairments. Levodopa manages symptoms best, while deep brain stimulation (DBS) is effective for advanced PD patients; however, side effects occur with the diminishing therapeutic window. Recently, Lactiplantibacillus plantarum PS128 (PS128) was found to elevate dopamine levels in rodent brains, suggesting its potential to prevent PD. Here, the therapeutic efficacy of PS128 was examined in the 6-hydroxydopamine rat PD model. Suppression of the power spectral density of beta oscillations (beta PSD) in the primary motor cortex (M1) was recorded as the indicator of disease progression. We found that 6 weeks of daily PS128 supplementation suppressed M1 beta PSD as well as did levodopa and DBS. Long-term normalization of M1 beta PSD was found in PS128-fed rats, whereas levodopa and DBS showed only temporal effects. PS128 + levodopa and PS128 + DBS exhibited better therapeutic effects than did levodopa + DBS or either alone. Significantly improved motor functions in PS128-fed rats were correlated with normalization of M1 beta PSD. Brain tissue analyses further demonstrated the role of PS128 in dopaminergic neuroprotection and the enhanced availability of neurotransmitters. These findings suggest that psychobiotic PS128 might be used alongside conventional therapies to treat PD patients.
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Affiliation(s)
- Yi-Fan Ma
- Biomedical Industry Ph.D. Program, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
- Microbiome Research Center, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
| | - Yi-An Lin
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 300, Taiwan
- EzInstrument Technology Co., Ltd., Hsinchu, 300, Taiwan
| | - Chin-Lin Huang
- Microbiome Research Center, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
- Bened Biomedical Co., Ltd., Taipei, 104, Taiwan
| | | | - Sabrina Wang
- Institute of Anatomy and Cell Biology, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan.
| | - Shih-Rung Yeh
- Institute of Molecular Medicine, National Tsing Hua University, Hsinchu, 300, Taiwan.
| | - Ying-Chieh Tsai
- Biomedical Industry Ph.D. Program, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan.
- Microbiome Research Center, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan.
- Institute of Biochemistry and Molecular Biology, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan.
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17
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Xu M, Hu B, Zhou W, Wang Z, Zhu L, Lin J, Wang D. The mechanism of Parkinson oscillation in the cortex: Possible evidence in a feedback model projecting from the globus pallidus to the cortex. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:6517-6550. [PMID: 37161117 DOI: 10.3934/mbe.2023281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
The origin, location and cause of Parkinson's oscillation are not clear at present. In this paper, we establish a new cortex-basal ganglia model to study the origin mechanism of Parkinson beta oscillation. Unlike many previous models, this model includes two direct inhibitory projections from the globus pallidus external (GPe) segment to the cortex. We first obtain the critical calculation formula of Parkinson's oscillation by using the method of Quasilinear analysis. Different from previous studies, the formula obtained in this paper can include the self-feedback connection of GPe. Then, we use the bifurcation analysis method to systematically explain the influence of some key parameters on the oscillation. We find that the bifurcation principle of different cortical nuclei is different. In general, the increase of the discharge capacity of the nuclei will cause oscillation. In some special cases, the sharp reduction of the discharge rate of the nuclei will also cause oscillation. The direction of bifurcation simulation is consistent with the critical condition curve. Finally, we discuss the characteristics of oscillation amplitude. At the beginning of the oscillation, the amplitude is relatively small; with the evolution of oscillation, the amplitude will gradually strengthen. This is consistent with the experimental phenomenon. In most cases, the amplitude of cortical inhibitory nuclei (CIN) is greater than that of cortical excitatory nuclei (CEX), and the two direct inhibitory projections feedback from GPe can significantly reduce the amplitude gap between them. We calculate the main frequency of the oscillation generated in this model, which basically falls between 13 and 30 Hz, belonging to the typical beta frequency band oscillation. Some new results obtained in this paper can help to better understand the origin mechanism of Parkinson's disease and have guiding significance for the development of experiments.
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Affiliation(s)
- Minbo Xu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Bing Hu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Weiting Zhou
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Zhizhi Wang
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Luyao Zhu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Jiahui Lin
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Dingjiang Wang
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
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18
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Bahadori-Jahromi F, Salehi S, Madadi Asl M, Valizadeh A. Efficient suppression of parkinsonian beta oscillations in a closed-loop model of deep brain stimulation with amplitude modulation. Front Hum Neurosci 2023; 16:1013155. [PMID: 36776221 PMCID: PMC9908610 DOI: 10.3389/fnhum.2022.1013155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 12/09/2022] [Indexed: 01/27/2023] Open
Abstract
Introduction Parkinson's disease (PD) is a movement disorder characterized by the pathological beta band (15-30 Hz) neural oscillations within the basal ganglia (BG). It is shown that the suppression of abnormal beta oscillations is correlated with the improvement of PD motor symptoms, which is a goal of standard therapies including deep brain stimulation (DBS). To overcome the stimulation-induced side effects and inefficiencies of conventional DBS (cDBS) and to reduce the administered stimulation current, closed-loop adaptive DBS (aDBS) techniques were developed. In this method, the frequency and/or amplitude of stimulation are modulated based on various disease biomarkers. Methods Here, by computational modeling of a cortico-BG-thalamic network in normal and PD conditions, we show that closed-loop aDBS of the subthalamic nucleus (STN) with amplitude modulation leads to a more effective suppression of pathological beta oscillations within the parkinsonian BG. Results Our results show that beta band neural oscillations are restored to their normal range and the reliability of the response of the thalamic neurons to motor cortex commands is retained due to aDBS with amplitude modulation. Furthermore, notably less stimulation current is administered during aDBS compared with cDBS due to a closed-loop control of stimulation amplitude based on the STN local field potential (LFP) beta activity. Discussion Efficient models of closed-loop stimulation may contribute to the clinical development of optimized aDBS techniques designed to reduce potential stimulation-induced side effects of cDBS in PD patients while leading to a better therapeutic outcome.
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Affiliation(s)
| | - Sina Salehi
- Shiraz Neuroscience Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mojtaba Madadi Asl
- School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
| | - Alireza Valizadeh
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
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19
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Verma AK, Yu Y, Acosta-Lenis SF, Havel T, Sanabria DE, Molnar GF, MacKinnon CD, Howell MJ, Vitek JL, Johnson LA. Parkinsonian daytime sleep-wake classification using deep brain stimulation lead recordings. Neurobiol Dis 2023; 176:105963. [PMID: 36521781 PMCID: PMC9869648 DOI: 10.1016/j.nbd.2022.105963] [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: 09/30/2022] [Revised: 12/01/2022] [Accepted: 12/10/2022] [Indexed: 12/14/2022] Open
Abstract
Excessive daytime sleepiness is a recognized non-motor symptom that adversely impacts the quality of life of people with Parkinson's disease (PD), yet effective treatment options remain limited. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for PD motor signs. Reliable daytime sleep-wake classification using local field potentials (LFPs) recorded from DBS leads implanted in STN can inform the development of closed-loop DBS approaches for prompt detection and disruption of sleep-related neural oscillations. We performed STN DBS lead recordings in three nonhuman primates rendered parkinsonian by administrating neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Reference sleep-wake states were determined on a second-by-second basis by video monitoring of eyes (eyes-open, wake and eyes-closed, sleep). The spectral power in delta (1-4 Hz), theta (4-8 Hz), low-beta (8-20 Hz), high-beta (20-35 Hz), gamma (35-90 Hz), and high-frequency (200-400 Hz) bands were extracted from each wake and sleep epochs for training (70% data) and testing (30% data) a support vector machines classifier for each subject independently. The spectral features yielded reasonable daytime sleep-wake classification (sensitivity: 90.68 ± 1.28; specificity: 88.16 ± 1.08; accuracy: 89.42 ± 0.68; positive predictive value; 88.70 ± 0.89, n = 3). Our findings support the plausibility of monitoring daytime sleep-wake states using DBS lead recordings. These results could have future clinical implications in informing the development of closed-loop DBS approaches for automatic detection and disruption of sleep-related neural oscillations in people with PD to promote wakefulness.
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Affiliation(s)
- Ajay K Verma
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - Ying Yu
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - Sergio F Acosta-Lenis
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - Tyler Havel
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | | | - Gregory F Molnar
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - Colum D MacKinnon
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - Michael J Howell
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - Jerrold L Vitek
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - Luke A Johnson
- Department of Neurology, University of Minnesota, Minneapolis, United States of America.
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20
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McNamara CG, Rothwell M, Sharott A. Stable, interactive modulation of neuronal oscillations produced through brain-machine equilibrium. Cell Rep 2022; 41:111616. [PMID: 36351413 PMCID: PMC7614081 DOI: 10.1016/j.celrep.2022.111616] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 07/28/2022] [Accepted: 10/17/2022] [Indexed: 11/09/2022] Open
Abstract
Closed-loop interaction has the potential to regulate ongoing brain activity by continuously binding an external stimulation to specific dynamics of a neural circuit. Achieving interactive modulation requires a stable brain-machine feedback loop. Here, we demonstrate that it is possible to maintain oscillatory brain activity in a desired state by delivering stimulation accurately aligned with the timing of each cycle. We develop a fast algorithm that responds on a cycle-by-cycle basis to stimulate basal ganglia nuclei at predetermined phases of successive cortical beta cycles in parkinsonian rats. Using this approach, an equilibrium emerges between the modified brain signal and feedback-dependent stimulation pattern, leading to sustained amplification or suppression of the oscillation depending on the phase targeted. Beta amplification slows movement speed by biasing the animal's mode of locomotion. Together, these findings show that highly responsive, phase-dependent stimulation can achieve a stable brain-machine interaction that leads to robust modulation of ongoing behavior.
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Affiliation(s)
- Colin G McNamara
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK.
| | - Max Rothwell
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
| | - Andrew Sharott
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK.
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21
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Cortical beta burst dynamics are altered in Parkinson's disease but normalized by deep brain stimulation. Neuroimage 2022; 257:119308. [PMID: 35569783 DOI: 10.1016/j.neuroimage.2022.119308] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 04/12/2022] [Accepted: 05/10/2022] [Indexed: 11/21/2022] Open
Abstract
Exaggerated subthalamic beta oscillatory activity and increased beta range cortico-subthalamic synchrony have crystallized as the electrophysiological hallmarks of Parkinson's disease. Beta oscillatory activity is not tonic but occurs in 'bursts' of transient amplitude increases. In Parkinson's disease, the characteristics of these bursts are altered especially in the basal ganglia. However, beta oscillatory dynamics at the cortical level and how they compare with healthy brain activity is less well studied. We used magnetoencephalography (MEG) to study sensorimotor cortical beta bursting and its modulation by subthalamic deep brain stimulation in Parkinson's disease patients and age-matched healthy controls. We show that the changes in beta bursting amplitude and duration typical of Parkinson's disease can also be observed in the sensorimotor cortex, and that they are modulated by chronic subthalamic deep brain stimulation, which, in turn, is reflected in improved motor function at the behavioural level. In addition to the changes in individual beta bursts, their timing relative to each other was altered in patients compared to controls: bursts were more clustered in untreated Parkinson's disease, occurring in 'bursts of bursts', and re-burst probability was higher for longer compared to shorter bursts. During active deep brain stimulation, the beta bursting in patients resembled healthy controls' data. In summary, both individual bursts' characteristics and burst patterning are affected in Parkinson's disease, and subthalamic deep brain stimulation normalizes some of these changes to resemble healthy controls' beta bursting activity, suggesting a non-invasive biomarker for patient and treatment follow-up.
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22
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The phase of sensorimotor mu and beta oscillations has the opposite effect on corticospinal excitability. Brain Stimul 2022; 15:1093-1100. [PMID: 35964870 DOI: 10.1016/j.brs.2022.08.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 08/05/2022] [Accepted: 08/06/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Neural oscillations in the primary motor cortex (M1) shape corticospinal excitability. Power and phase of ongoing mu (8-13 Hz) and beta (14-30 Hz) activity may mediate motor cortical output. However, the functional dynamics of both mu and beta phase and power relationships and their interaction, are largely unknown. OBJECTIVE Here, we employ recently developed real-time targeting of the mu and beta rhythm, to apply phase-specific brain stimulation and probe motor corticospinal excitability non-invasively. For this, we used instantaneous read-out and analysis of ongoing oscillations, targeting four different phases (0°, 90°, 180°, and 270°) of mu and beta rhythms with suprathreshold single-pulse transcranial magnetic stimulation (TMS) to M1. Ensuing motor evoked potentials (MEPs) in the right first dorsal interossei muscle were recorded. Twenty healthy adults took part in this double-blind randomized crossover study. RESULTS Mixed model regression analyses showed significant phase-dependent modulation of corticospinal output by both mu and beta rhythm. Strikingly, these modulations exhibit a double dissociation. MEPs are larger at the mu trough and rising phase and smaller at the peak and falling phase. For the beta rhythm we found the opposite behavior. Also, mu power, but not beta power, was positively correlated with corticospinal output. Power and phase effects did not interact for either rhythm, suggesting independence between these aspects of oscillations. CONCLUSION Our results provide insights into real-time motor cortical oscillation dynamics, which offers the opportunity to improve the effectiveness of TMS by specifically targeting different frequency bands.
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Li M, Zhang X, He Q, Chen D, Chen F, Wang X, Sun S, Sun Y, Li Y, Zhu Z, Fang H, Shi X, Yao X, Sun H, Wang M. Functional Interactions Between the Parafascicular Thalamic Nucleus and Motor Cortex Are Altered in Hemiparkinsonian Rat. Front Aging Neurosci 2022; 14:800159. [PMID: 35677204 PMCID: PMC9168077 DOI: 10.3389/fnagi.2022.800159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Parkinson’s disease (PD) is characterized by aberrant discharge patterns and exaggerated oscillatory activity within basal ganglia-thalamocortical circuits. We have previously observed substantial alterations in spike and local field potential (LFP) activities recorded in the thalamic parafascicular nucleus (PF) and motor cortex (M1), respectively, of hemiparkinsonian rats during rest or catching movements. This study explored whether the mutual effects of the PF and M1 depended on the amplitude and phase relationship in their identified neuron spikes or group rhythmic activities. Microwire electrode arrays were paired and implanted in the PF and M1 of rats with unilateral dopaminergic cell lesions. The results showed that the identified PF neurons exhibited aberrant cell type-selective firing rates and preferential and excessive phase-locked firing to cortical LFP oscillations mainly at 12–35 Hz (beta frequencies), consistent with the observation of identified M1 neurons with ongoing PF LFP oscillations. Experimental evidence also showed a decrease in phase-locking at 0.7–12 Hz and 35–70 Hz in the PF and M1 circuits in the hemiparkinsonian rats. Furthermore, anatomical evidence was provided for the existence of afferent and efferent bidirectional reciprocal connectivity pathways between the PF and M1 using an anterograde and retrograde neuroanatomical tracing virus. Collectively, our results suggested that multiple alterations may be present in regional anatomical and functional modes with which the PF and M1 interact, and that parkinsonism-associated changes in PF integrate M1 activity in a manner that varies with frequency, behavioral state, and integrity of the dopaminergic system.
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Affiliation(s)
- Min Li
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Xiao Zhang
- Editorial Department of Journal of Shandong Jianzhu University, Jinan, China
| | - Qin He
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Dadian Chen
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Feiyu Chen
- School of International Education, Qilu University of Technology, Jinan, China
| | - Xiaojun Wang
- The First Hospital Affiliated With Shandong First Medical University, Jinan, China
| | - Shuang Sun
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Yue Sun
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Yuchuan Li
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Zhiwei Zhu
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Heyi Fang
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Xiaoman Shi
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Xiaomeng Yao
- School of Nursing, Qilu Institute of Technology, Jinan, China
| | - Haiji Sun
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
- *Correspondence: Haiji Sun,
| | - Min Wang
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
- Min Wang,
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24
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Alavi SM, Mirzaei A, Valizadeh A, Ebrahimpour R. Excitatory deep brain stimulation quenches beta oscillations arising in a computational model of the subthalamo-pallidal loop. Sci Rep 2022; 12:7845. [PMID: 35552409 PMCID: PMC9098470 DOI: 10.1038/s41598-022-10084-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 03/21/2022] [Indexed: 11/30/2022] Open
Abstract
Parkinson’s disease (PD) is associated with abnormal \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β band oscillations (13–30 Hz) in the cortico-basal ganglia circuits. Abnormally increased striato-pallidal inhibition and strengthening the synaptic coupling between subthalamic nucleus (STN) and globus pallidus externa (GPe), due to the loss of dopamine, are considered as the potential sources of \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β oscillations in the basal ganglia. Deep brain stimulation (DBS) of the basal ganglia subregions is known as a way to reduce the pathological \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β oscillations and motor deficits related to PD. Despite the success of the DBS, its underlying mechanism is poorly understood and, there is controversy about the inhibitory or excitatory role of the DBS in the literature. Here, we utilized a computational network model of basal ganglia which consists of STN, GPe, globus pallidus interna, and thalamic neuronal population. This model can reproduce healthy and pathological \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β oscillations similar to what has been observed in experimental studies. Using this model, we investigated the effect of DBS to understand whether its effect is excitatory or inhibitory. Our results show that the excitatory DBS is able to quench the pathological synchrony and \documentclass[12pt]{minimal}
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\begin{document}$$\beta$$\end{document}β oscillations, while, applying inhibitory DBS failed to quench the PD signs. In light of simulation results, we conclude that the effect of the DBS on its target is excitatory.
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Affiliation(s)
- Seyed Mojtaba Alavi
- Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.,School of Cognitive Sciences (SCS), Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | | | - Alireza Valizadeh
- Department of Physics, Institute for Advance Studies in Basic Sciences (IASBS), Zanjan, Iran.,School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Reza Ebrahimpour
- Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. .,School of Cognitive Sciences (SCS), Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
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25
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Khawaldeh S, Tinkhauser G, Torrecillos F, He S, Foltynie T, Limousin P, Zrinzo L, Oswal A, Quinn AJ, Vidaurre D, Tan H, Litvak V, Kühn A, Woolrich M, Brown P. Balance between competing spectral states in subthalamic nucleus is linked to motor impairment in Parkinson's disease. Brain 2022; 145:237-250. [PMID: 34264308 PMCID: PMC8967096 DOI: 10.1093/brain/awab264] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 06/11/2021] [Accepted: 07/04/2021] [Indexed: 11/14/2022] Open
Abstract
Exaggerated local field potential bursts of activity at frequencies in the low beta band are a well-established phenomenon in the subthalamic nucleus of patients with Parkinson's disease. However, such activity is only moderately correlated with motor impairment. Here we test the hypothesis that beta bursts are just one of several dynamic states in the subthalamic nucleus local field potential in Parkinson's disease, and that together these different states predict motor impairment with high fidelity. Local field potentials were recorded in 32 patients (64 hemispheres) undergoing deep brain stimulation surgery targeting the subthalamic nucleus. Recordings were performed following overnight withdrawal of anti-parkinsonian medication, and after administration of levodopa. Local field potentials were analysed using hidden Markov modelling to identify transient spectral states with frequencies under 40 Hz. Findings in the low beta frequency band were similar to those previously reported; levodopa reduced occurrence rate and duration of low beta states, and the greater the reductions, the greater the improvement in motor impairment. However, additional local field potential states were distinguished in the theta, alpha and high beta bands, and these behaved in an opposite manner. They were increased in occurrence rate and duration by levodopa, and the greater the increases, the greater the improvement in motor impairment. In addition, levodopa favoured the transition of low beta states to other spectral states. When all local field potential states and corresponding features were considered in a multivariate model it was possible to predict 50% of the variance in patients' hemibody impairment OFF medication, and in the change in hemibody impairment following levodopa. This only improved slightly if signal amplitude or gamma band features were also included in the multivariate model. In addition, it compares with a prediction of only 16% of the variance when using beta bursts alone. We conclude that multiple spectral states in the subthalamic nucleus local field potential have a bearing on motor impairment, and that levodopa-induced shifts in the balance between these states can predict clinical change with high fidelity. This is important in suggesting that some states might be upregulated to improve parkinsonism and in suggesting how local field potential feedback can be made more informative in closed-loop deep brain stimulation systems.
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Affiliation(s)
- Saed Khawaldeh
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
| | - Gerd Tinkhauser
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
- Department of Neurology, Bern University Hospital and University of Bern, 3010 Bern, Switzerland
| | - Flavie Torrecillos
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Shenghong He
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Thomas Foltynie
- Unit of Functional Neurosurgery, Department of Clinical and Movement Neurosciences, UCL Institute of Neurology, London WC1B 5EH, UK
| | - Patricia Limousin
- Unit of Functional Neurosurgery, Department of Clinical and Movement Neurosciences, UCL Institute of Neurology, London WC1B 5EH, UK
| | - Ludvic Zrinzo
- Unit of Functional Neurosurgery, Department of Clinical and Movement Neurosciences, UCL Institute of Neurology, London WC1B 5EH, UK
| | - Ashwini Oswal
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London WC1N 3AR, UK
| | - Andrew J Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
| | - Diego Vidaurre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
- Department of Clinical Health, Aarhus University, DK-8200 Aarhus, Denmark
| | - Huiling Tan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Vladimir Litvak
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London WC1N 3AR, UK
| | - Andrea Kühn
- Department of Neurology, Charitè—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Mark Woolrich
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
| | - Peter Brown
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
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26
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Swinnen BEKS, Buijink AW, Piña-Fuentes D, de Bie RMA, Beudel M. Diving into the Subcortex: The Potential of Chronic Subcortical Sensing for Unravelling Basal Ganglia Function and Optimization of Deep Brain STIMULATION. Neuroimage 2022; 254:119147. [PMID: 35346837 DOI: 10.1016/j.neuroimage.2022.119147] [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: 11/29/2021] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 11/18/2022] Open
Abstract
Subcortical structures are a relative neurophysiological 'terra incognita' owing to their location within the skull. While perioperative subcortical sensing has been performed for more than 20 years, the neurophysiology of the basal ganglia in the home setting has remained almost unexplored. However, with the recent advent of implantable pulse generators (IPG) that are able to record neural activity, the opportunity to chronically record local field potentials (LFPs) directly from electrodes implanted for deep brain stimulation opens up. This allows for a breakthrough of chronic subcortical sensing into fundamental research and clinical practice. In this review an extensive overview of the current state of subcortical sensing is provided. The widespread potential of chronic subcortical sensing for investigational and clinical use is discussed. Finally, status and future perspectives of the most promising application of chronic subcortical sensing -i.e., adaptive deep brain stimulation (aDBS)- are discussed in the context of movement disorders. The development of aDBS based on both chronic subcortical and cortical sensing has the potential to dramatically change clinical practice and the life of patients with movement disorders. However, several barriers still stand in the way of clinical implementation. Advancements regarding IPG and lead technology, physiomarkers, and aDBS algorithms as well as harnessing artificial intelligence, multimodality and sensing in the naturalistic setting are needed to bring aDBS to clinical practice.
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Affiliation(s)
- Bart E K S Swinnen
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland.
| | - Arthur W Buijink
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland
| | - Dan Piña-Fuentes
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland
| | - Rob M A de Bie
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland
| | - Martijn Beudel
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland
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27
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Toth K, Wilson D. Control of coupled neural oscillations using near-periodic inputs. CHAOS (WOODBURY, N.Y.) 2022; 32:033130. [PMID: 35364826 DOI: 10.1063/5.0076508] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 02/22/2022] [Indexed: 06/14/2023]
Abstract
Deep brain stimulation (DBS) is a commonly used treatment for medication resistant Parkinson's disease and is an emerging treatment for other neurological disorders. More recently, phase-specific adaptive DBS (aDBS), whereby the application of stimulation is locked to a particular phase of tremor, has been proposed as a strategy to improve therapeutic efficacy and decrease side effects. In this work, in the context of these phase-specific aDBS strategies, we investigate the dynamical behavior of large populations of coupled neurons in response to near-periodic stimulation, namely, stimulation that is periodic except for a slowly changing amplitude and phase offset that can be used to coordinate the timing of applied input with a specified phase of model oscillations. Using an adaptive phase-amplitude reduction strategy, we illustrate that for a large population of oscillatory neurons, the temporal evolution of the associated phase distribution in response to near-periodic forcing can be captured using a reduced order model with four state variables. Subsequently, we devise and validate a closed-loop control strategy to disrupt synchronization caused by coupling. Additionally, we identify strategies for implementing the proposed control strategy in situations where underlying model equations are unavailable by estimating the necessary terms of the reduced order equations in real-time from observables.
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Affiliation(s)
- Kaitlyn Toth
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - Dan Wilson
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee 37996, USA
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28
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West TO, Magill PJ, Sharott A, Litvak V, Farmer SF, Cagnan H. Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit. PLoS Comput Biol 2022; 18:e1009887. [PMID: 35245281 PMCID: PMC8939795 DOI: 10.1371/journal.pcbi.1009887] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 03/22/2022] [Accepted: 01/31/2022] [Indexed: 11/26/2022] Open
Abstract
Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson's disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple "reversible lesion" effect to augment network communication. Specifically, we examined the modulation of beta band (14-30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson's. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.
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Affiliation(s)
- Timothy O. West
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Peter J. Magill
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Oxford Parkinson’s Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Andrew Sharott
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Simon F. Farmer
- Department of Neurology, National Hospital for Neurology & Neurosurgery, London, United Kingdom
- Department of Clinical and Human Neuroscience, UCL Institute of Neurology, London, United Kingdom
| | - Hayriye Cagnan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
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29
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Pozzi NG, Isaias IU. Adaptive deep brain stimulation: Retuning Parkinson's disease. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:273-284. [PMID: 35034741 DOI: 10.1016/b978-0-12-819410-2.00015-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A brain-machine interface represents a promising therapeutic avenue for the treatment of many neurologic conditions. Deep brain stimulation (DBS) is an invasive, neuro-modulatory tool that can improve different neurologic disorders by delivering electric stimulation to selected brain areas. DBS is particularly successful in advanced Parkinson's disease (PD), where it allows sustained improvement of motor symptoms. However, this approach is still poorly standardized, with variable clinical outcomes. To achieve an optimal therapeutic effect, novel adaptive DBS (aDBS) systems are being developed. These devices operate by adapting stimulation parameters in response to an input signal that can represent symptoms, motor activity, or other behavioral features. Emerging evidence suggests greater efficacy with fewer adverse effects during aDBS compared with conventional DBS. We address this topic by discussing the basics principles of aDBS, reviewing current evidence, and tackling the many challenges posed by aDBS for PD.
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Affiliation(s)
- Nicoló G Pozzi
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany
| | - Ioannis U Isaias
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany.
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30
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Sanabria DE, Aman JE, Amaya VZ, Johnson LA, Farooqi H, Wang J, Hill M, Patriat R, Sovell-Brown K, Molnar GF, Darrow D, McGovern R, Cooper SE, Harel N, MacKinnon CD, Park MC, Vitek JL. Controlling pallidal oscillations in real-time in Parkinson's disease using evoked interference deep brain stimulation (eiDBS): Proof of concept in the human. Brain Stimul 2022; 15:1111-1119. [PMID: 35921960 PMCID: PMC9798539 DOI: 10.1016/j.brs.2022.07.047] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 04/26/2022] [Accepted: 07/20/2022] [Indexed: 01/01/2023] Open
Abstract
Approaches to control basal ganglia neural activity in real-time are needed to clarify the causal role of 13-35 Hz ("beta band") oscillatory dynamics in the manifestation of Parkinson's disease (PD) motor signs. Here, we show that resonant beta oscillations evoked by electrical pulses with precise amplitude and timing can be used to predictably suppress or amplify spontaneous beta band activity in the internal segment of the globus pallidus (GPi) in the human. Using this approach, referred to as closed-loop evoked interference deep brain stimulation (eiDBS), we could suppress or amplify frequency-specific (16-22 Hz) neural activity in a PD patient. Our results highlight the utility of eiDBS to characterize the role of oscillatory dynamics in PD and other brain conditions, and to develop personalized neuromodulation systems.
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Affiliation(s)
- David Escobar Sanabria
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA,Corresponding author: (D. Escobar Sanabria)
| | - Joshua E. Aman
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | | | - Luke A. Johnson
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Hafsa Farooqi
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Meghan Hill
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Remi Patriat
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Kelly Sovell-Brown
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Gregory F. Molnar
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - David Darrow
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Robert McGovern
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Scott E. Cooper
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Noam Harel
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Colum D. MacKinnon
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Michael C. Park
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, 55455, USA,Corresponding author: (J.L. Vitek)
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31
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Mau ETK, Rosenblum M. Optimizing charge-balanced pulse stimulation for desynchronization. CHAOS (WOODBURY, N.Y.) 2022; 32:013103. [PMID: 35105136 DOI: 10.1063/5.0070036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 12/09/2021] [Indexed: 06/14/2023]
Abstract
Collective synchronization in a large population of self-sustained units appears both in natural and engineered systems. Sometimes this effect is in demand, while in some cases, it is undesirable, which calls for control techniques. In this paper, we focus on pulsatile control, with the goal to either increase or decrease the level of synchrony. We quantify this level by the entropy of the phase distribution. Motivated by possible applications in neuroscience, we consider pulses of a realistic shape. Exploiting the noisy Kuramoto-Winfree model, we search for the optimal pulse profile and the optimal stimulation phase. For this purpose, we derive an expression for the change of the phase distribution entropy due to the stimulus. We relate this change to the properties of individual units characterized by generally different natural frequencies and phase response curves and the population's state. We verify the general result by analyzing a two-frequency population model and demonstrating a good agreement of the theory and numerical simulations.
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Affiliation(s)
- Erik T K Mau
- Department of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam-Golm, Germany
| | - Michael Rosenblum
- Department of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, D-14476 Potsdam-Golm, Germany
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Arruda BS, Reis C, Sermon JJ, Pogosyan A, Brown P, Cagnan H. Identifying and modulating distinct tremor states through peripheral nerve stimulation in Parkinsonian rest tremor. J Neuroeng Rehabil 2021; 18:179. [PMID: 34953492 PMCID: PMC8709974 DOI: 10.1186/s12984-021-00973-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 12/07/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Resting tremor is one of the most common symptoms of Parkinson's disease. Despite its high prevalence, resting tremor may not be as effectively treated with dopaminergic medication as other symptoms, and surgical treatments such as deep brain stimulation, which are effective in reducing tremor, have limited availability. Therefore, there is a clinical need for non-invasive interventions in order to provide tremor relief to a larger number of people with Parkinson's disease. Here, we explore whether peripheral nerve stimulation can modulate resting tremor, and under what circumstances this might lead to tremor suppression. METHODS We studied 10 people with Parkinson's disease and rest tremor, to whom we delivered brief electrical pulses non-invasively to the median nerve of the most tremulous hand. Stimulation was phase-locked to limb acceleration in the axis with the biggest tremor-related excursion. RESULTS We demonstrated that rest tremor in the hand could change from one pattern of oscillation to another in space. Median nerve stimulation was able to significantly reduce (- 36%) and amplify (117%) tremor when delivered at a certain phase. When the peripheral manifestation of tremor spontaneously changed, stimulation timing-dependent change in tremor severity could also alter during phase-locked peripheral nerve stimulation. CONCLUSIONS These results highlight that phase-locked peripheral nerve stimulation has the potential to reduce tremor. However, there can be multiple independent tremor oscillation patterns even within the same limb. Parameters of peripheral stimulation such as stimulation phase may need to be adjusted continuously in order to sustain systematic suppression of tremor amplitude.
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Affiliation(s)
- Beatriz S Arruda
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, OX1 3TH, UK
| | - Carolina Reis
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, OX1 3TH, UK
| | - James J Sermon
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, OX1 3TH, UK
| | - Alek Pogosyan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, OX1 3TH, UK
| | - Peter Brown
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, OX1 3TH, UK
| | - Hayriye Cagnan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford, OX1 3TH, UK.
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Hu B, Xu M, Zhu L, Lin J, Zhizhi Wang, Wang D, Zhang D. A bidirectional Hopf bifurcation analysis of Parkinson's oscillation in a simplified basal ganglia model. J Theor Biol 2021; 536:110979. [PMID: 34942160 DOI: 10.1016/j.jtbi.2021.110979] [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: 08/05/2021] [Revised: 11/13/2021] [Accepted: 12/01/2021] [Indexed: 11/16/2022]
Abstract
In this paper, we study the parkinson oscillation mechanism in a computational model by bifurcation analysis and numerical simulation. Oscillatory activities can be induced by abnormal coupling weights and delays. The bidirectional Hopf bifurcation phenomena are found in simulations, which can uniformly explain the oscillation mechanism in this model. The Hopf1 represents the transition between the low firing rate stable state (SS) and oscillation state (OS), the Hopf2 represents the transition between the high firing rate stable state (HSS) and the OS, the mechanisms of them are different. The Hopf1 and Hopf2 bifurcations both show that when the state transfers from the stable region to the oscillation region, oscillatory activities always originate from the beta frequency band, and then gradually evolve into the alpha frequency band, the theta frequency band and delta frequency band in this model. We find that the changing trends of the DF and oscillation amplitude (OSAM) are contrary, oscillation activities in lower frequency band are more stable than that in higher frequency band. The effect of the delay in inhibitory pathways is greater than that of in excitatory pathways, and appropriate delays improve the discharge activation level (DAL) of the system. In all, we infer that oscillations can be induced by the follow factors: 1. Improvement of the DAL of the globus pallidus externa (GPe); 2. Reduce the DAL of the GPe from the HSS or the discharge saturation state; 3. The GPe can also resonate with the subthalamic nucleus (STN).
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Affiliation(s)
- Bing Hu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China.
| | - Minbo Xu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Luyao Zhu
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Jiahui Lin
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Zhizhi Wang
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
| | - Dingjiang Wang
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China.
| | - Dongmei Zhang
- Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou 310023, China
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Abdul Nabi Ali A, Alam M, Klein SC, Behmann N, Krauss JK, Doll T, Blume H, Schwabe K. Predictive accuracy of CNN for cortical oscillatory activity in an acute rat model of parkinsonism. Neural Netw 2021; 146:334-340. [PMID: 34923220 DOI: 10.1016/j.neunet.2021.11.025] [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: 06/11/2021] [Revised: 10/08/2021] [Accepted: 11/24/2021] [Indexed: 10/19/2022]
Abstract
In neurological and neuropsychiatric disorders neuronal oscillatory activity between basal ganglia and cortical circuits are altered, which may be useful as biomarker for adaptive deep brain stimulation. We investigated whether changes in the spectral power of oscillatory activity in the motor cortex (MCtx) and the sensorimotor cortex (SMCtx) of rats after injection of the dopamine (DA) receptor antagonist haloperidol (HALO) would be similar to those observed in Parkinson disease. Thereafter, we tested whether a convolutional neural network (CNN) model would identify brain signal alterations in this acute model of parkinsonism. A sixteen channel surface micro-electrocorticogram (ECoG) recording array was placed under the dura above the MCtx and SMCtx areas of one hemisphere under general anaesthesia in rats. Seven days after surgery, micro ECoG was recorded in individual free moving rats in three conditions: (1) basal activity, (2) after injection of HALO (0.5 mg/kg), and (3) with additional injection of apomorphine (APO) (1 mg/kg). Furthermore, a CNN-based classification consisting of 23,530 parameters was applied on the raw data. HALO injection decreased oscillatory theta band activity (4-8 Hz) and enhanced beta (12-30 Hz) and gamma (30-100 Hz) in MCtx and SMCtx, which was compensated after APO injection (P ¡ 0.001). Evaluation of classification performance of the CNN model provided accuracy of 92%, sensitivity of 90% and specificity of 93% on one-dimensional signals. The CNN proposed model requires a minimum of sensory hardware and may be integrated into future research on therapeutic devices for Parkinson disease, such as adaptive closed loop stimulation, thus contributing to more efficient way of treatment.
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Affiliation(s)
- Ali Abdul Nabi Ali
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Mesbah Alam
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany.
| | - Simon C Klein
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Nicolai Behmann
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Joachim K Krauss
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany
| | - Theodor Doll
- Biomaterial Engineering, Hannover Medical School and Translational Medical Engineering Fraunhofer ITEM, Hannover, D-30625, Lower Saxony, Germany
| | - Holger Blume
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Kerstin Schwabe
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany
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Nie Y, Guo X, Li X, Geng X, Li Y, Quan Z, Zhu G, Yin Z, Zhang J, Wang S. Real-time removal of stimulation artifacts in closed-loop deep brain stimulation. J Neural Eng 2021; 18. [PMID: 34818629 DOI: 10.1088/1741-2552/ac3cc5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 11/24/2021] [Indexed: 01/12/2023]
Abstract
Objective.Closed-loop deep brain stimulation (DBS) with neural feedback has shown great potential in improving the therapeutic effect and reducing side effects. However, the amplitude of stimulation artifacts is much larger than the local field potentials, which remains a bottleneck in developing a closed-loop stimulation strategy with varied parameters.Approach.We proposed an irregular sampling method for the real-time removal of stimulation artifacts. The artifact peaks were detected by applying a threshold to the raw recordings, and the samples within the contaminated period of the stimulation pulses were excluded and replaced with the interpolation of the samples prior to and after the stimulation artifact duration. This method was evaluated with both simulation signals andin vivoclosed-loop DBS applications in Parkinsonian animal models.Main results. The irregular sampling method was able to remove the stimulation artifacts effectively with the simulation signals. The relative errors between the power spectral density of the recovered and true signals within a wide frequency band (2-150 Hz) were 2.14%, 3.93%, 7.22%, 7.97% and 6.25% for stimulation at 20 Hz, 60 Hz, 130 Hz, 180 Hz, and stimulation with variable low and high frequencies, respectively. This stimulation artifact removal method was verified in real-time closed-loop DBS applicationsin vivo, and the artifacts were effectively removed during stimulation with frequency continuously changing from 130 Hz to 1 Hz and stimulation adaptive to beta oscillations.Significance.The proposed method provides an approach for real-time removal in closed-loop DBS applications, which is effective in stimulation with low frequency, high frequency, and variable frequency. This method can facilitate the development of more advanced closed-loop DBS strategies.
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Affiliation(s)
- Yingnan Nie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People's Republic of China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Ministry of Education), Fudan University, Shanghai, People's Republic of China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China.,Zhangjiang Fudan International Innovation Center, Shanghai, People's Republic of China
| | - Xuanjun Guo
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People's Republic of China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Ministry of Education), Fudan University, Shanghai, People's Republic of China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China.,Zhangjiang Fudan International Innovation Center, Shanghai, People's Republic of China
| | - Xiao Li
- Academy for Engineering and Technology, Fudan University, Shanghai, People's Republic of China.,Shanghai Engineering Research Center of AI & Robotics, Fudan University, Shanghai, People's Republic of China.,Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, People's Republic of China
| | - Xinyi Geng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People's Republic of China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Ministry of Education), Fudan University, Shanghai, People's Republic of China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China.,Zhangjiang Fudan International Innovation Center, Shanghai, People's Republic of China
| | - Yan Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People's Republic of China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Ministry of Education), Fudan University, Shanghai, People's Republic of China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China.,Zhangjiang Fudan International Innovation Center, Shanghai, People's Republic of China
| | - Zhaoyu Quan
- Academy for Engineering and Technology, Fudan University, Shanghai, People's Republic of China.,Shanghai Engineering Research Center of AI & Robotics, Fudan University, Shanghai, People's Republic of China.,Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, People's Republic of China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Shouyan Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People's Republic of China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Ministry of Education), Fudan University, Shanghai, People's Republic of China.,MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China.,Zhangjiang Fudan International Innovation Center, Shanghai, People's Republic of China.,Shanghai Engineering Research Center of AI & Robotics, Fudan University, Shanghai, People's Republic of China.,Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, People's Republic of China
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Seri R, Martinoli M. Asymptotic Properties of the Plug-in Estimator of the Discrete Entropy Under Dependence. IEEE TRANSACTIONS ON INFORMATION THEORY 2021; 67:7659-7683. [DOI: 10.1109/tit.2021.3109307] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
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Salimpour Y, Mills KA, Hwang BY, Anderson WS. Phase- targeted stimulation modulates phase-amplitude coupling in the motor cortex of the human brain. Brain Stimul 2021; 15:152-163. [PMID: 34856396 DOI: 10.1016/j.brs.2021.11.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 10/10/2021] [Accepted: 11/28/2021] [Indexed: 11/02/2022] Open
Abstract
BACKGROUND Phase-amplitude coupling (PAC) in which the amplitude of a faster field potential oscillation is coupled to the phase of a slower rhythm, is one of the most well-studied interactions between oscillations at different frequency bands. In a healthy brain, PAC accompanies cognitive functions such as learning and memory, and changes in PAC have been associated with neurological diseases including Parkinson's disease (PD), schizophrenia, obsessive-compulsive disorder, Alzheimer's disease, and epilepsy. OBJECTIVE /Hypothesis: In PD, normalization of PAC in the motor cortex has been reported in the context of effective treatments such as dopamine replacement therapy and deep brain stimulation (DBS), but the possibility of normalizing PAC through intervention at the cortex has not been shown in humans. Phase-targeted stimulation (PDS) has a strong potential to modulate PAC levels and potentially normalize it. METHODS We applied stimulation pulses triggered by specific phases of the beta oscillations, the low frequency oscillations that define phase of gamma amplitude in beta-gamma PAC, to the motor cortex of seven PD patients at rest during DBS lead placement surgery We measured the effect on PAC modulation in the motor cortex relative to stimulation-free periods. RESULTS We describe a system for phase-targeted stimulation locked to specific phases of a continuously updated slow local field potential oscillation (in this case, beta band oscillations) prediction. Stimulation locked to the phase of the peak of beta oscillations increased beta-gamma coupling both during and after stimulation in the motor cortex, and the opposite phase (trough) stimulation reduced the magnitude of coupling after stimulation. CONCLUSION These results demonstrate the capacity of cortical phase-targeted stimulation to modulate PAC without evoking motor activation, which could allow applications in the treatment of neurological disorders associated with abnormal PAC, such as PD.
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Affiliation(s)
- Yousef Salimpour
- Functional Neurosurgery Laboratory, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, USA.
| | - Kelly A Mills
- Neuromodulation and Advanced Therapies Clinic, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Brian Y Hwang
- Functional Neurosurgery Laboratory, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - William S Anderson
- Functional Neurosurgery Laboratory, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA
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38
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Sohanian Haghighi H, Markazi AHD. Control of epileptic seizures by electrical stimulation: a model-based study. Biomed Phys Eng Express 2021; 7. [PMID: 34488206 DOI: 10.1088/2057-1976/ac240d] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 09/06/2021] [Indexed: 11/12/2022]
Abstract
High frequency electrical stimulation of brain is commonly used in research experiments and clinical trials as a modern tool for control of epileptic seizures. However, the mechanistic basis by which periodic external stimuli alter the brain state is not well understood. This study provides a computational insight into the mechanism of seizure suppression by high frequency stimulation (HFS). In particular, a modified version of the Jansen-Rit neural mass model is employed, in which EEG signals can be considered as the input. The proposed model reproduces seizure-like activity in the output during the ictal period of the input signal. By applying a control signal to the model, a wide range of stimulation amplitudes and frequencies are systematically explored. Simulation results reveal that HFS can effectively suppress the seizure-like activity. Our results suggest that HFS has the ability of shifting the operating state of neural populations away from a critical condition. Furthermore, a closed-loop control strategy is proposed in this paper. The main objective has been to considerably reduce the control effort needed for blocking abnormal activity of the brain. Such an energy reduction could be of practical importance, to reduce possible side effects and increase battery life for implanted neurostimulators.
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Affiliation(s)
| | - Amir H D Markazi
- 1School of Mechanical Engineering, Iran University of Science and Technology, Tehran 16844, Iran
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Rosenblum M, Pikovsky A, Kühn AA, Busch JL. Real-time estimation of phase and amplitude with application to neural data. Sci Rep 2021; 11:18037. [PMID: 34508149 PMCID: PMC8433321 DOI: 10.1038/s41598-021-97560-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 08/06/2021] [Indexed: 11/12/2022] Open
Abstract
Computation of the instantaneous phase and amplitude via the Hilbert Transform is a powerful tool of data analysis. This approach finds many applications in various science and engineering branches but is not proper for causal estimation because it requires knowledge of the signal's past and future. However, several problems require real-time estimation of phase and amplitude; an illustrative example is phase-locked or amplitude-dependent stimulation in neuroscience. In this paper, we discuss and compare three causal algorithms that do not rely on the Hilbert Transform but exploit well-known physical phenomena, the synchronization and the resonance. After testing the algorithms on a synthetic data set, we illustrate their performance computing phase and amplitude for the accelerometer tremor measurements and a Parkinsonian patient's beta-band brain activity.
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Affiliation(s)
- Michael Rosenblum
- Department of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, 14476, Potsdam-Golm, Germany.
| | - Arkady Pikovsky
- Department of Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, 14476, Potsdam-Golm, Germany
| | - Andrea A Kühn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Johannes L Busch
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
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40
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Essential tremor amplitude modulation by median nerve stimulation. Sci Rep 2021; 11:17720. [PMID: 34489503 PMCID: PMC8421420 DOI: 10.1038/s41598-021-96660-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 08/05/2021] [Indexed: 11/08/2022] Open
Abstract
Essential tremor is a common neurological disorder, characterised by involuntary shaking of a limb. Patients are usually treated using medications which have limited effects on tremor and may cause side-effects. Surgical therapies are effective in reducing essential tremor, however, the invasive nature of these therapies together with the high cost, greatly limit the number of patients benefiting from them. Non-invasive therapies have gained increasing traction to meet this clinical need. Here, we test a non-invasive and closed-loop electrical stimulation paradigm which tracks peripheral tremor and targets thalamic afferents to modulate the central oscillators underlying tremor. To this end, 9 patients had electrical stimulation delivered to the median nerve locked to different phases of tremor. Peripheral stimulation induced a subtle but significant modulation in five out of nine patients-this modulation consisted mainly of amplification rather than suppression of tremor amplitude. Modulatory effects of stimulation were more pronounced when patient's tremor was spontaneously weaker at stimulation onset, when significant modulation became more frequent amongst subjects. This data suggests that for selected individuals, a more sophisticated control policy entailing an online estimate of both tremor phase and amplitude, should be considered in further explorations of the treatment potential of tremor phase-locked peripheral stimulation.
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Dastolfo-Hromack C, Bush A, Chrabaszcz A, Alhourani A, Lipski W, Wang D, Crammond DJ, Shaiman S, Dickey MW, Holt LL, Turner RS, Fiez JA, Richardson RM. Articulatory Gain Predicts Motor Cortex and Subthalamic Nucleus Activity During Speech. Cereb Cortex 2021; 32:1337-1349. [PMID: 34470045 DOI: 10.1093/cercor/bhab251] [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: 10/19/2020] [Revised: 06/14/2021] [Accepted: 06/18/2021] [Indexed: 11/12/2022] Open
Abstract
Speaking precisely is important for effective verbal communication, and articulatory gain is one component of speech motor control that contributes to achieving this goal. Given that the basal ganglia have been proposed to regulate the speed and size of limb movement, that is, movement gain, we explored the basal ganglia contribution to articulatory gain, through local field potentials (LFP) recorded simultaneously from the subthalamic nucleus (STN), precentral gyrus, and postcentral gyrus. During STN deep brain stimulation implantation for Parkinson's disease, participants read aloud consonant-vowel-consonant syllables. Articulatory gain was indirectly assessed using the F2 Ratio, an acoustic measurement of the second formant frequency of/i/vowels divided by/u/vowels. Mixed effects models demonstrated that the F2 Ratio correlated with alpha and theta activity in the precentral gyrus and STN. No correlations were observed for the postcentral gyrus. Functional connectivity analysis revealed that higher phase locking values for beta activity between the STN and precentral gyrus were correlated with lower F2 Ratios, suggesting that higher beta synchrony impairs articulatory precision. Effects were not related to disease severity. These data suggest that articulatory gain is encoded within the basal ganglia-cortical loop.
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Affiliation(s)
- C Dastolfo-Hromack
- Department of Communication Science and Disorders, University of Pittsburgh School of Health and Rehabilitation Sciences, Pittsburgh, PA 15260, USA
| | - A Bush
- Department of Neurological Surgery, Massachusetts General Hospital, MA 02114, USA.,Harvard Medical School, Boston, MA 02115, USA
| | - A Chrabaszcz
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - A Alhourani
- Department of Neurosurgery, University of Louisville, Louisville, KY 40292, USA
| | - W Lipski
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - D Wang
- School of Medicine, Tsinghua University, Beijing 100084, China
| | - D J Crammond
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - S Shaiman
- Department of Communication Science and Disorders, University of Pittsburgh School of Health and Rehabilitation Sciences, Pittsburgh, PA 15260, USA
| | - M W Dickey
- Department of Communication Science and Disorders, University of Pittsburgh School of Health and Rehabilitation Sciences, Pittsburgh, PA 15260, USA
| | - L L Holt
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - R S Turner
- Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - J A Fiez
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - R M Richardson
- Department of Neurological Surgery, Massachusetts General Hospital, MA 02114, USA.,Harvard Medical School, Boston, MA 02115, USA
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Weerasinghe G, Duchet B, Bick C, Bogacz R. Optimal closed-loop deep brain stimulation using multiple independently controlled contacts. PLoS Comput Biol 2021; 17:e1009281. [PMID: 34358224 PMCID: PMC8405008 DOI: 10.1371/journal.pcbi.1009281] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 08/30/2021] [Accepted: 07/15/2021] [Indexed: 11/18/2022] Open
Abstract
Deep brain stimulation (DBS) is a well-established treatment option for a variety of neurological disorders, including Parkinson’s disease and essential tremor. The symptoms of these disorders are known to be associated with pathological synchronous neural activity in the basal ganglia and thalamus. It is hypothesised that DBS acts to desynchronise this activity, leading to an overall reduction in symptoms. Electrodes with multiple independently controllable contacts are a recent development in DBS technology which have the potential to target one or more pathological regions with greater precision, reducing side effects and potentially increasing both the efficacy and efficiency of the treatment. The increased complexity of these systems, however, motivates the need to understand the effects of DBS when applied to multiple regions or neural populations within the brain. On the basis of a theoretical model, our paper addresses the question of how to best apply DBS to multiple neural populations to maximally desynchronise brain activity. Central to this are analytical expressions, which we derive, that predict how the symptom severity should change when stimulation is applied. Using these expressions, we construct a closed-loop DBS strategy describing how stimulation should be delivered to individual contacts using the phases and amplitudes of feedback signals. We simulate our method and compare it against two others found in the literature: coordinated reset and phase-locked stimulation. We also investigate the conditions for which our strategy is expected to yield the most benefit. In this paper we use computer models of brain tissue to derive an optimal control algorithm for a recently developed new generation of deep brain stimulation (DBS) devices. DBS is a treatment for a variety of neurological disorders including Parkinson’s disease, essential tremor, depression and pain. There is a growing amount of evidence to suggest that delivering stimulation according to feedback from patients, or closed-loop, has the potential to improve the efficacy, efficiency and side effects of the treatment. An important recent development in DBS technology are electrodes with multiple independently controllable contacts and this paper is a theoretical study into the effects of using this new technology. On the basis of a theoretical model, we devise a closed-loop strategy and address the question of how to best apply DBS across multiple contacts to maximally desynchronise neural populations. We demonstrate using numerical simulation that, for the systems we consider, our methods are more effective than two well-known alternatives, namely phase-locked stimulation and coordinated reset. We also predict that the benefits of using multiple contacts should depend strongly on the intrinsic neuronal response. The insights from this work should lead to a better understanding of how to implement and optimise closed-loop multi-contact DBS systems which in turn should lead to more effective and efficient DBS treatments.
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Affiliation(s)
- Gihan Weerasinghe
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- * E-mail:
| | - Benoit Duchet
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Christian Bick
- Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Systems and Network Neuroscience, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Mathematical Institute, University of Oxford, Oxford, United Kingdom
- Department of Mathematics, University of Exeter, Exeter, United Kingdom
| | - Rafal Bogacz
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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van der Werf OJ, Ten Oever S, Schuhmann T, Sack AT. No evidence of rhythmic visuospatial attention at cued locations in a spatial cuing paradigm, regardless of their behavioural relevance. Eur J Neurosci 2021; 55:3100-3116. [PMID: 34131983 PMCID: PMC9542203 DOI: 10.1111/ejn.15353] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Revised: 06/04/2021] [Accepted: 06/09/2021] [Indexed: 12/01/2022]
Abstract
Recent evidence suggests that visuospatial attentional performance is not stable over time but fluctuates in a rhythmic fashion. These attentional rhythms allow for sampling of different visuospatial locations in each cycle of this rhythm. However, it is still unclear in which paradigmatic circumstances rhythmic attention becomes evident. First, it is unclear at what spatial locations rhythmic attention occurs. Second, it is unclear how the behavioural relevance of each spatial location determines the rhythmic sampling patterns. Here, we aim to elucidate these two issues. Firstly, we aim to find evidence of rhythmic attention at the predicted (i.e. cued) location under moderately informative predictor value, replicating earlier studies. Secondly, we hypothesise that rhythmic attentional sampling behaviour will be affected by the behavioural relevance of the sampled location, ranging from non-informative to fully informative. To these aims, we used a modified Egly-Driver task with three conditions: a fully informative cue, a moderately informative cue (replication condition), and a non-informative cue. We did not find evidence of rhythmic sampling at cued locations, failing to replicate earlier studies. Nor did we find differences in rhythmic sampling under different predictive values of the cue. The current data does not allow for robust conclusions regarding the non-cued locations due to the absence of a priori hypotheses. Post-hoc explorative data analyses, however, clearly indicate that attention samples non-cued locations in a theta-rhythmic manner, specifically when the cued location bears higher behavioural relevance than the non-cued locations.
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Affiliation(s)
- Olof J van der Werf
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Sanne Ten Oever
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Language and Computation in Neural Systems group, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.,Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
| | - Teresa Schuhmann
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Alexander T Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Brain and Nerve Centre, Maastricht University Medical Centre+ (MUMC+), Maastricht, The Netherlands
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Shi K, Liu X, Hou L, Qiao D, Peng Y. Exercise Improves Movement by Regulating the Plasticity of Cortical Function in Hemiparkinsonian Rats. Front Aging Neurosci 2021; 13:695108. [PMID: 34194319 PMCID: PMC8236842 DOI: 10.3389/fnagi.2021.695108] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 05/17/2021] [Indexed: 01/03/2023] Open
Abstract
Aberrant cortical spike-local field potential (LFP) coupling leads to abnormal basal ganglia activity, disruption of cortical function, and impaired movement in Parkinson's disease (PD). Here, the primary motor cortex mediated plasticity mechanism underlying behavioral improvement by exercise intervention was investigated. Exercise alleviates motor dysfunction and induces neuroplasticity in PD. In this study, Sprague-Dawley (SD) rats were injected with 6-hydroxydopamine (6-OHDA) to induce unilateral nigrostriatal dopamine depletion. Two weeks later, a 4-week exercise intervention was initiated in the PD + exercise (Ex) group. Multichannel recording technology recorded spikes and LFPs in rat motor cortices, and balanced ability tests evaluated behavioral performance. The balanced ability test showed that the total crossing time/front leg error/input latency time was significantly lower in PD + Ex rats than in PD rats (P < 0.05). Scalograms and LFP power spectra indicated increased beta-range LFP power in lesioned hemispheres, with exercise reducing LFP power spectral density. Spike-triggered LFP waveform averages showed strong phase-locking in PD motor cortex cells, and exercise reduced spike-LFP synchronization. Our results suggest that exercise can suppress overexcitability of LFPs and minimize spike-LFP synchronization in the motor cortex, leading to motor-improving effects in PD.
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Affiliation(s)
- Kaixuan Shi
- Department of Physical Education, China University of Geosciences, Beijing, China
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Xiaoli Liu
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Lijuan Hou
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Decai Qiao
- College of Physical Education and Sports, Beijing Normal University, Beijing, China
| | - Yuan Peng
- Department of Physical Education, China University of Geosciences, Beijing, China
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Sharma A, Vidaurre D, Vesper J, Schnitzler A, Florin E. Differential dopaminergic modulation of spontaneous cortico-subthalamic activity in Parkinson's disease. eLife 2021; 10:66057. [PMID: 34085932 PMCID: PMC8177893 DOI: 10.7554/elife.66057] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/12/2021] [Indexed: 11/20/2022] Open
Abstract
Pathological oscillations including elevated beta activity in the subthalamic nucleus (STN) and between STN and cortical areas are a hallmark of neural activity in Parkinson’s disease (PD). Oscillations also play an important role in normal physiological processes and serve distinct functional roles at different points in time. We characterised the effect of dopaminergic medication on oscillatory whole-brain networks in PD in a time-resolved manner by employing a hidden Markov model on combined STN local field potentials and magnetoencephalography (MEG) recordings from 17 PD patients. Dopaminergic medication led to coherence within the medial and orbitofrontal cortex in the delta/theta frequency range. This is in line with known side effects of dopamine treatment such as deteriorated executive functions in PD. In addition, dopamine caused the beta band activity to switch from an STN-mediated motor network to a frontoparietal-mediated one. In contrast, dopamine did not modify local STN–STN coherence in PD. STN–STN synchrony emerged both on and off medication. By providing electrophysiological evidence for the differential effects of dopaminergic medication on the discovered networks, our findings open further avenues for electrical and pharmacological interventions in PD.
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Affiliation(s)
- Abhinav Sharma
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Diego Vidaurre
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Department of Clinical Health, Aarhus University, Aarhus, Denmark
| | - Jan Vesper
- Department of Neurosurgery, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.,Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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Sand D, Rappel P, Marmor O, Bick AS, Arkadir D, Lu BL, Bergman H, Israel Z, Eitan R. Machine learning-based personalized subthalamic biomarkers predict ON-OFF levodopa states in Parkinson patients. J Neural Eng 2021; 18. [PMID: 33906182 DOI: 10.1088/1741-2552/abfc1d] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 04/27/2021] [Indexed: 01/20/2023]
Abstract
Objective.Adaptive deep brain stimulation (aDBS) based on subthalamic nucleus (STN) electrophysiology has recently been proposed to improve clinical outcomes of DBS for Parkinson's disease (PD) patients. Many current models for aDBS are based on one or two electrophysiological features of STN activity, such as beta or gamma activity. Although these models have shown interesting results, we hypothesized that an aDBS model that includes many STN activity parameters will yield better clinical results. The objective of this study was to investigate the most appropriate STN neurophysiological biomarkers, detectable over long periods of time, that can predict OFF and ON levodopa states in PD patients.Approach.Long-term local field potentials (LFPs) were recorded from eight STNs (four PD patients) during 92 recording sessions (44 OFF and 48 ON levodopa states), over a period of 3-12 months. Electrophysiological analysis included the power of frequency bands, band power ratio and burst features. A total of 140 engineered features was extracted for 20 040 epochs (each epoch lasting 5 s). Based on these engineered features, machine learning (ML) models classified LFPs as OFF vs ON levodopa states.Main results.Beta and gamma band activity alone poorly predicts OFF vs ON levodopa states, with an accuracy of 0.66 and 0.64, respectively. Group ML analysis slightly improved prediction rates, but personalized ML analysis, based on individualized engineered electrophysiological features, were markedly better, predicting OFF vs ON levodopa states with an accuracy of 0.8 for support vector machine learning models.Significance.We showed that individual patients have unique sets of STN neurophysiological biomarkers that can be detected over long periods of time. ML models revealed that personally classified engineered features most accurately predict OFF vs ON levodopa states. Future development of aDBS for PD patients might include personalized ML algorithms.
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Affiliation(s)
- Daniel Sand
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Pnina Rappel
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Odeya Marmor
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel
| | - Atira S Bick
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - David Arkadir
- The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Bao-Liang Lu
- Center for Brain-like Computing and Machine Intelligence, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Hagai Bergman
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Edmond and Lily Safra Center for Brain Research, The Hebrew University, Jerusalem, Israel.,Functional Neurosurgery Unit, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Zvi Israel
- The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.,Functional Neurosurgery Unit, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Renana Eitan
- Department of Medical Neurobiology (Physiology), Institute of Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Brain Division, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.,Jerusalem Mental Health Center, Hebrew University-Hadassah Medical School, Jerusalem, Israel.,Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States of America
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Li M, Wang X, Yao X, Wang X, Chen F, Zhang X, Sun S, He F, Jia Q, Guo M, Chen D, Sun Y, Li Y, He Q, Zhu Z, Wang M. Roles of Motor Cortex Neuron Classes in Reach-Related Modulation for Hemiparkinsonian Rats. Front Neurosci 2021; 15:645849. [PMID: 33986639 PMCID: PMC8111217 DOI: 10.3389/fnins.2021.645849] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 03/24/2021] [Indexed: 01/12/2023] Open
Abstract
Disruption of the function of the primary motor cortex (M1) is thought to play a critical role in motor dysfunction in Parkinson's disease (PD). Detailed information regarding the specific aspects of M1 circuits that become abnormal is lacking. We recorded single units and local field potentials (LFPs) of M1 neurons in unilateral 6-hydroxydopamine (6-OHDA) lesion rats and control rats to assess the impact of dopamine (DA) cell loss during rest and a forelimb reaching task. Our results indicated that M1 neurons can be classified into two groups (putative pyramidal neurons and putative interneurons) and that 6-OHDA could modify the activity of different M1 subpopulations to a large extent. Reduced activation of putative pyramidal neurons during inattentive rest and reaching was observed. In addition, 6-OHDA intoxication was associated with an increase in certain LFP frequencies, especially those in the beta range (broadly defined here as any frequency between 12 and 35 Hz), which become pathologically exaggerated throughout cortico-basal ganglia circuits after dopamine depletion. Furthermore, assessment of different spike-LFP coupling parameters revealed that the putative pyramidal neurons were particularly prone to being phase-locked to ongoing cortical oscillations at 12-35 Hz during reaching. Conversely, putative interneurons were neither hypoactive nor synchronized to ongoing cortical oscillations. These data collectively demonstrate a neuron type-selective alteration in the M1 in hemiparkinsonian rats. These alterations hamper the ability of the M1 to contribute to motor conduction and are likely some of the main contributors to motor impairments in PD.
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Affiliation(s)
- Min Li
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Xuenan Wang
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China.,Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xiaomeng Yao
- School of Nursing, Qilu Institute of Technology, Jinan, China
| | - Xiaojun Wang
- The First Hospital Affiliated With Shandong First Medicine University, Jinan, China
| | - Feiyu Chen
- School of International Education, Qilu University of Technology, Jinan, China
| | - Xiao Zhang
- Editorial Department of Journal of Shandong Jianzhu University, Jinan, China
| | - Shuang Sun
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Feng He
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Qingmei Jia
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Mengnan Guo
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Dadian Chen
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Yue Sun
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Yuchuan Li
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Qin He
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Zhiwei Zhu
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
| | - Min Wang
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, Jinan, China
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48
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Duchet B, Weerasinghe G, Bick C, Bogacz R. Optimizing deep brain stimulation based on isostable amplitude in essential tremor patient models. J Neural Eng 2021; 18:046023. [PMID: 33821809 PMCID: PMC7610712 DOI: 10.1088/1741-2552/abd90d] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Deep brain stimulation is a treatment for medically refractory essential tremor. To improve the therapy, closed-loop approaches are designed to deliver stimulation according to the system's state, which is constantly monitored by recording a pathological signal associated with symptoms (e.g. brain signal or limb tremor). Since the space of possible closed-loop stimulation strategies is vast and cannot be fully explored experimentally, how to stimulate according to the state should be informed by modeling. A typical modeling goal is to design a stimulation strategy that aims to maximally reduce the Hilbert amplitude of the pathological signal in order to minimize symptoms. Isostables provide a notion of amplitude related to convergence time to the attractor, which can be beneficial in model-based control problems. However, how isostable and Hilbert amplitudes compare when optimizing the amplitude response to stimulation in models constrained by data is unknown. APPROACH We formulate a simple closed-loop stimulation strategy based on models previously fitted to phase-locked deep brain stimulation data from essential tremor patients. We compare the performance of this strategy in suppressing oscillatory power when based on Hilbert amplitude and when based on isostable amplitude. We also compare performance to phase-locked stimulation and open-loop high-frequency stimulation. MAIN RESULTS For our closed-loop phase space stimulation strategy, stimulation based on isostable amplitude is significantly more effective than stimulation based on Hilbert amplitude when amplitude field computation time is limited to minutes. Performance is similar when there are no constraints, however constraints on computation time are expected in clinical applications. Even when computation time is limited to minutes, closed-loop phase space stimulation based on isostable amplitude is advantageous compared to phase-locked stimulation, and is more efficient than high-frequency stimulation. SIGNIFICANCE Our results suggest a potential benefit to using isostable amplitude more broadly for model-based optimization of stimulation in neurological disorders.
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Affiliation(s)
- Benoit Duchet
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom. MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
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49
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Peles O, Werner-Reiss U, Bergman H, Israel Z, Vaadia E. Phase-Specific Microstimulation Differentially Modulates Beta Oscillations and Affects Behavior. Cell Rep 2021; 30:2555-2566.e3. [PMID: 32101735 DOI: 10.1016/j.celrep.2020.02.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 11/13/2019] [Accepted: 01/31/2020] [Indexed: 12/14/2022] Open
Abstract
It is widely accepted that Beta-band oscillations play a role in sensorimotor behavior. To further explore this role, we developed a hybrid platform to combine neural operant conditioning and phase-specific intracortical microstimulation (ICMS). We trained monkeys, implanted with 96 electrode arrays in the motor cortex, to volitionally enhance local field potential (LFP) Beta-band (20-30 Hz) activity at selected sites using a brain-machine interface. We find that Beta oscillations of LFP and single-unit spiking activity increase dramatically with brain-machine interface training and that pre-movement Beta power is anti-correlated with task performance. We also find that phase-specific ICMS modulates the power and phase of oscillations, shifting local networks between oscillatory and non-oscillatory states. Furthermore, ICMS induces phase-dependent effects in animal reaction times and success rates. These findings contribute to unraveling the functional role of cortical oscillations and to the future development of clinical tools for ameliorating abnormal neuronal activities in brain disease.
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Affiliation(s)
- Oren Peles
- Department of Medical Neurobiology, Institute of Medical Research-Israel Canada, The Hebrew University-Hadassah Medical School, Jerusalem 9112102, Israel; Edmond and Lily Safra Centre for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
| | - Uri Werner-Reiss
- Department of Medical Neurobiology, Institute of Medical Research-Israel Canada, The Hebrew University-Hadassah Medical School, Jerusalem 9112102, Israel; Edmond and Lily Safra Centre for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Hagai Bergman
- Department of Medical Neurobiology, Institute of Medical Research-Israel Canada, The Hebrew University-Hadassah Medical School, Jerusalem 9112102, Israel; Edmond and Lily Safra Centre for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Zvi Israel
- Department of Neurosurgery, Hadassah University Hospital, Jerusalem 9112102, Israel
| | - Eilon Vaadia
- Department of Medical Neurobiology, Institute of Medical Research-Israel Canada, The Hebrew University-Hadassah Medical School, Jerusalem 9112102, Israel; Edmond and Lily Safra Centre for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
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50
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Zhang W, Song A, Zeng H, Xu B, Miao M. Closed-Loop Phase-Dependent Vibration Stimulation Improves Motor Imagery-Based Brain-Computer Interface Performance. Front Neurosci 2021; 15:638638. [PMID: 33568973 PMCID: PMC7868341 DOI: 10.3389/fnins.2021.638638] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/06/2021] [Indexed: 11/13/2022] Open
Abstract
The motor imagery (MI) paradigm has been wildly used in brain-computer interface (BCI), but the difficulties in performing imagery tasks limit its application. Mechanical vibration stimulus has been increasingly used to enhance the MI performance, but its improvement consistence is still under debate. To develop more effective vibration stimulus methods for consistently enhancing MI, this study proposes an EEG phase-dependent closed-loop mechanical vibration stimulation method. The subject's index finger of the non-dominant hand was given 4 different vibration stimulation conditions (i.e., continuous open-loop vibration stimulus, two different phase-dependent closed-loop vibration stimuli and no stimulus) when performing two tasks of imagining movement and rest of the index finger from his/her dominant hand. We compared MI performance and brain oscillatory patterns under different conditions to verify the effectiveness of this method. The subjects performed 80 trials of each type in a random order, and the average phase-lock value of closed-loop stimulus conditions was 0.71. It was found that the closed-loop vibration stimulus applied in the falling phase helped the subjects to produce stronger event-related desynchronization (ERD) and sustain longer. Moreover, the classification accuracy was improved by about 9% compared with MI without any vibration stimulation (p = 0.012, paired t-test). This method helps to modulate the mu rhythm and make subjects more concentrated on the imagery and without negative enhancement during rest tasks, ultimately improves MI-based BCI performance. Participants reported that the tactile fatigue under closed-loop stimulation conditions was significantly less than continuous stimulation. This novel method is an improvement to the traditional vibration stimulation enhancement research and helps to make stimulation more precise and efficient.
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Affiliation(s)
- Wenbin Zhang
- The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Aiguo Song
- The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Hong Zeng
- The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Baoguo Xu
- The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Minmin Miao
- School of Information Engineering, Huzhou University, Huzhou, China
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