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Andrews L, Keller SS, Osman-Farah J, Macerollo A. A structural magnetic resonance imaging review of clinical motor outcomes from deep brain stimulation in movement disorders. Brain Commun 2023; 5:fcad171. [PMID: 37304793 PMCID: PMC10257440 DOI: 10.1093/braincomms/fcad171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/05/2023] [Accepted: 05/30/2023] [Indexed: 06/13/2023] Open
Abstract
Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive of clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson's disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between 1 January 2000 and 1 April 2022 and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson's disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson's disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions was also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimizing individualized therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer the powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.
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Affiliation(s)
- Luke Andrews
- Correspondence to: Luke Andrews The BRAIN Lab, University of Liverpool Cancer Research Centre 200 London Rd, Liverpool L3 9TA, United Kingdom E-mail:
| | - Simon S Keller
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L3 9TA, UK
| | - Jibril Osman-Farah
- Department of Neurology and Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool L97LJ, UK
| | - Antonella Macerollo
- Correspondence may also be sent to: Antonella Macerollo. The Walton Centre NHS Trust, Lower Lane Liverpool L9 7LJ, United Kingdom E-mail:
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Yu H, Meng Z, Li H, Liu C, Wang J. Intensity-Varied Closed-Loop Noise Stimulation for Oscillation Suppression in the Parkinsonian State. IEEE TRANSACTIONS ON CYBERNETICS 2022; 52:9861-9870. [PMID: 34398769 DOI: 10.1109/tcyb.2021.3079100] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
This work explores the effectiveness of the intensity-varied closed-loop noise stimulation on the oscillation suppression in the Parkinsonian state. Deep brain stimulation (DBS) is the standard therapy for Parkinson's disease (PD), but its effects need to be improved. The noise stimulation has compelling results in alleviating the PD state. However, in the open-loop control scheme, the noise stimulation parameters cannot be self-adjusted to adapt to the amplitude of the synchronized neuronal activities in real time. Thus, based on the delayed-feedback control algorithm, an intensity-varied closed-loop noise stimulation strategy is proposed. Based on a computational model of the basal ganglia (BG) that can present the intrinsic properties of the BG neurons and their interactions with the thalamic neurons, the proposed stimulation strategy is tested. Simulation results show that the noise stimulation suppresses the pathological beta (12-35 Hz) oscillations without any new rhythms in other bands compared with traditional high-frequency DBS. The intensity-varied closed-loop noise stimulation has a more profound role in removing the pathological beta oscillations and improving the thalamic reliability than open-loop noise stimulation, especially for different PD states. And the closed-loop noise stimulation enlarges the parameter space of the delayed-feedback control algorithm due to the randomness of noise signals. We also provide a theoretical analysis of the effective parameter domain of the delayed-feedback control algorithm by simplifying the BG model to an oscillator model. This exploration may guide a new approach to treating PD by optimizing the noise-induced improvement of the BG dysfunction.
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Yu Y, Hao Y, Wang Q. Model-based optimized phase-deviation deep brain stimulation for Parkinson 's disease. Neural Netw 2019; 122:308-319. [PMID: 31739269 DOI: 10.1016/j.neunet.2019.11.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 10/21/2019] [Accepted: 11/01/2019] [Indexed: 01/09/2023]
Abstract
High-frequency deep brain stimulation (HF-DBS) of the subthalamic nucleus (STN), globus pallidus interna (GPi) and globus pallidus externa (GPe) are often considered as effective methods for the treatment of Parkinson's disease (PD). However, the stimulation of a single nucleus by HF-DBS can cause specific physical damage, produce side effects and usually consume more electrical energy. Therefore, we use a biophysically-based model of basal ganglia-thalamic circuits to explore more effective stimulation patterns to reduce adverse effects and save energy. In this paper, we computationally investigate the combined DBS of two nuclei with the phase deviation between two stimulation waveforms (CDBS). Three different stimulation combination strategies are proposed, i.e., STN and GPe CDBS (SED), STN and GPi CDBS (SID), as well as GPi and GPe CDBS (GGD). Resultantly, it is found that anti-phase CDBS is more effective in improving parkinsonian dynamical properties, including desynchronization of neurons and the recovery of the thalamus relay ability. Detailed simulation investigation shows that anti-phase SED and GGD are superior to SID. Besides, the energy consumption can be largely reduced by SED and GGD (72.5% and 65.5%), compared to HF-DBS. These results provide new insights into the optimal stimulation parameter and target choice of PD, which may be helpful for the clinical practice.
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Affiliation(s)
- Ying Yu
- Department of Dynamics and Control, Beihang University, 100191, Beijing, China
| | - Yuqing Hao
- Department of Dynamics and Control, Beihang University, 100191, Beijing, China
| | - Qingyun Wang
- Department of Dynamics and Control, Beihang University, 100191, Beijing, China.
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Liu C, Wang J, Deng B, Li H, Fietkiewicz C, Loparo KA. Noise-Induced Improvement of the Parkinsonian State: A Computational Study. IEEE TRANSACTIONS ON CYBERNETICS 2019; 49:3655-3664. [PMID: 29994689 DOI: 10.1109/tcyb.2018.2845359] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The benefit of noise in improving the basal ganglia (BG) dysfunctions, especially Parkinsonian state, is explored in this paper. High frequency (≥ 100 Hz) deep brain stimulation (DBS), as a clinical effective stimulation method, has compelling and fantastic results in alleviating the motor symptoms of Parkinson's disease (PD). However, the mechanism of DBS is still unclear. And the selection of the DBS waveform parameters faces great challenges to further optimize the stimulation effects and to reduce its energy expenditure. Considering that the desynchronization of the BG neuronal activities is benefited from the forced high frequency regular spikes driven by standard high frequency DBS, we expect to explore a novel stimulation method that has capability of restoring the BG physiological firing patterns without introducing artificial high-frequency fires. In this paper, a colored noise stimulation is used as a neuromodulation method to disrupt the firing patterns of the pathological neuronal activities. A computational model of the BG that exhibits the intrinsic properties of the BG neurons and their interactions with the thalamic (Th) cells is employed. Based on the model, we investigate the effects of noise stimulation and explore the impacts of the noise stimulation parameters on both relay reliability of the Th neurons and energy expenditure of the stimulation. By comparison, it can be found that noise stimulation does not entrain the network to an artificial high-frequency firing state, but induces the pathological increased synchronous activities back to a normal physiological level. Moreover, besides the capability of restoring the neuronal state, the benefits of the noise also include its balanced waveform to avert potential tissue or electrode damage and its ability to reduce the energy expenditure to 50% less than that of the standard DBS, when the noise stimulation has low frequency (≤ 100 Hz) and appropriate intensity. Thus, the exploration of the optimal noise-induced improvement of the BG dysfunction is of great significance in treating symptoms of neurological disorders such as PD.
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Direct comparison of oscillatory activity in the motor system of Parkinson’s disease and dystonia: A review of the literature and meta-analysis. Clin Neurophysiol 2019; 130:917-924. [DOI: 10.1016/j.clinph.2019.02.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 01/29/2019] [Accepted: 02/16/2019] [Indexed: 12/12/2022]
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Goulenko V, da Costa Cruz PL, Niemeyer Filho P. Unilateral thalamic and pallidal deep brain stimulation for idiopathic hemidystonia: results of individual and combined stimulations. Case report. Neurosurg Focus 2017; 43:E2. [DOI: 10.3171/2017.4.focus17134] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Pallidal stimulation has been the usual surgical treatment for dystonia in the last decades. The continuous investigation of the physiopathology and the motor pathways involved leads to the search for complementary targets to improve results. The authors present the case of a 37-year-old woman who had suffered from idiopathic hemidystonia with hyperkinetic and hypokinetic movements for 11 years, and who was treated with deep brain stimulation. A brief literature review is also provided. The globus pallidus internus and the ventral intermediate/ventral oral posterior complex of the thalamus were stimulated separately and simultaneously for 3 months and compared using the Burke-Fahn-Marsden Dystonia Rating Scale and the Global Dystonia Severity Rating Scale, with a 3.5-year follow-up. The synergism of multiple-target stimulation resulted in a complete improvement of the mixed dystonic symptoms.
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Krishnan S, Pisharady KK. Surgical Treatment of Levodopa-induced Dyskinesia in Parkinson's Disease. Ann Indian Acad Neurol 2017; 20:199-206. [PMID: 28904448 PMCID: PMC5586111 DOI: 10.4103/aian.aian_244_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
The treatment of motor manifestations of Parkinson's disease (PD) is essentially a trade-off between adequate relief of motor symptoms and prevention and control of motor complications, particularly levodopa-induced dyskinesia (LID). Progression of PD is paralleled by a progressive difficulty in achieving the balance. Functional neurosurgical procedures provide sustained relief of LID in carefully selected patients when further tailoring of medical therapy fails to achieve this goal. Though deep brain stimulation (DBS) has superseded lesioning surgeries, pallidotomy still has a role in those patients in whom DBS is not feasible for financial or other reasons.
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Affiliation(s)
- Syam Krishnan
- Comprehensive Care Center for Movement Disorders, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India,Address for correspondence: Dr. Syam Krishnan, Comprehensive Care Center for Movement Disorders, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram - 695 011, Kerala, India. E-mail:
| | - Krishnakumar Kesava Pisharady
- Comprehensive Care Center for Movement Disorders, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
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Cacciola A, Milardi D, Quartarone A. Role of cortico-pallidal connectivity in the pathophysiology of dystonia. Brain 2016; 139:e48. [PMID: 27190024 DOI: 10.1093/brain/aww102] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Alberto Cacciola
- 1 Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Italy
| | - Demetrio Milardi
- 1 Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Italy 2 IRCCS Centro Neurolesi 'Bonino Pulejo', S.S. 113, Via Palermo, C.da Casazza, 98124 Messina, Italy
| | - Angelo Quartarone
- 1 Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Italy 2 IRCCS Centro Neurolesi 'Bonino Pulejo', S.S. 113, Via Palermo, C.da Casazza, 98124 Messina, Italy
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Su F, Wang J, Deng B, Wei XL, Chen YY, Liu C, Li HY. Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters. Int J Neural Syst 2015; 25:1450030. [PMID: 25338775 DOI: 10.1142/s0129065714500300] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.
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Affiliation(s)
- Fei Su
- School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072, China
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Moustafa AA, Bar-Gad I, Korngreen A, Bergman H. Basal ganglia: physiological, behavioral, and computational studies. Front Syst Neurosci 2014; 8:150. [PMID: 25191233 PMCID: PMC4139593 DOI: 10.3389/fnsys.2014.00150] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2014] [Accepted: 08/04/2014] [Indexed: 12/19/2022] Open
Affiliation(s)
- Ahmed A Moustafa
- Department of Veterans Affairs, New Jersey Health Care System, School of Social Sciences and Psychology, Marcs Institute for Brain and Behaviour, University of Western Sydney Sydney, NSW, Australia
| | - Izhar Bar-Gad
- Gonda Brain Research Center, Bar-Ilan University Ramat Gan, Israel
| | - Alon Korngreen
- Gonda Brain Research Center, Bar-Ilan University Ramat Gan, Israel ; Everard Goodman Faculty of life sciences, Bar-Ilan University Ramat Gan, Israel
| | - Hagai Bergman
- Department of Neurobiology (Physiology), Faculty of Medicine, Edemond and Lily Safra Center for Brain Research, Institue of Medical Research Israel-Canada, The Hebrew University of Jerusalem Jerusalem, Israel
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