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Zhang Y, Zhang H, Xu T, Liu J, Mu J, Chen R, Yang J, Wang P, Jian X. A simulation study of transcranial magnetoacoustic stimulation of the basal ganglia thalamic neural network to improve pathological beta oscillations in Parkinson's disease. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 254:108297. [PMID: 38905990 DOI: 10.1016/j.cmpb.2024.108297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 05/30/2024] [Accepted: 06/17/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Parkinson's disease (PD) is a common neurodegenerative disease. Transcranial magnetoacoustic stimulation (TMAS) is a new therapy that combines a transcranial focused acoustic pressure field with a magnetic field to excite or inhibit neurons in targeted area, which suppresses the abnormally elevated beta band amplitude in PD states, with high spatial resolution and non-invasively. OBJECTIVE To study the effective stimulation parameters of TMAS mononuclear and multinuclear stimulation for the treatment of PD with reduced beta band energy, improved abnormal synchronization, and no thermal damage. METHODS The TMAS model is constructed based on the volunteer's computed tomography, 128 arrays of phase-controlled transducers, and permanent magnets. A basal ganglia-thalamic (BG-Th) neural network model of the PD state was constructed on the basis of the Izhikevich model and the acoustic model. An ultrasound stimulation neuron model is constructed based on the Hodgkin-Huxley model. Numerical simulations of transcranial focused acoustic pressure field, temperature field and induced electric field at single and dual targets were performed using the locations of STN, GPi, and GPe in the human brain as the main stimulation target areas. And the acoustic and electric parameters at the focus were extracted to stimulate mononuclear and multinuclear in the BG-Th neural network. RESULTS When the stimulating effect of ultrasound is ignored, TMAS-STN simultaneously inhibits the beta-band amplitude of the GPi nucleus, whereas TMAS-GPi fails to simultaneously have an inhibitory effect on the STN. TMAS-STN&GPi can reduce the beta band amplitude. TMAS-STN&GPi&GPe suppressed the PD pathologic beta band amplitude of each nucleus to a greater extent. When considering the stimulatory effect of ultrasound, lower sound pressures of ultrasound do not affect the neuronal firing state, but higher sound pressures may promote or inhibit the stimulatory effect of induced currents. CONCLUSIONS At 9 T static magnetic field, 0.5-1.5 MPa and 1.5-2.0 MPa ultrasound had synergistic effects on individual STN and GPi neurons. TMAS multinuclear stimulation with appropriate ultrasound intensity was the most effective in suppressing the amplitude of pathological beta oscillations in PD and may be clinically useful.
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Affiliation(s)
- Yanqiu Zhang
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China
| | - Hao Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin International Joint Research Centre for Neural Engineering, and Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China; Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin 300392, China
| | - Tianya Xu
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China
| | - Jiahe Liu
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China
| | - Jiayang Mu
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China
| | - Rongjie Chen
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Jiumin Yang
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China
| | - Peiguo Wang
- Department of Radiotherapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center of Cancer, Key Laboratory of Caner Prevention and Therapy, Tianjin 300060, China
| | - Xiqi Jian
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China.
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Agarwal H, Rathore H. BGRL: Basal Ganglia inspired Reinforcement Learning based framework for deep brain stimulators. Artif Intell Med 2024; 147:102736. [PMID: 38184360 DOI: 10.1016/j.artmed.2023.102736] [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: 10/09/2022] [Revised: 10/13/2023] [Accepted: 11/28/2023] [Indexed: 01/08/2024]
Abstract
Deep Brain Stimulation (DBS) is an implantable medical device used for electrical stimulation to treat neurological disorders. Traditional DBS devices provide fixed frequency pulses, but personalized adjustment of stimulation parameters is crucial for optimal treatment. This paper introduces a Basal Ganglia inspired Reinforcement Learning (BGRL) approach, incorporating a closed-loop feedback mechanism to suppress neural synchrony during neurological fluctuations. The BGRL approach leverages the resemblance between the Basal Ganglia region of brain by incorporating the actor-critic architecture of reinforcement learning (RL). Simulation results demonstrate that BGRL significantly reduces synchronous electrical pulses compared to other standard RL algorithms. BGRL algorithm outperforms existing RL methods in terms of suppression capability and energy consumption, validated through comparisons using ensemble oscillators. Results shown in the paper demonstrate BGRL suppressed the synchronous electrical pulses across three signaling regimes namely regular, chaotic and bursting by 40%, 146% and 40% respectively as compared to soft actor-critic model. BGRL shows promise in effectively suppressing neural synchrony in DBS therapy, providing an efficient alternative to open-loop methodologies.
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Affiliation(s)
- Harsh Agarwal
- Department of Electrical and Computer Engineering, Indian Institute of Technology, India.
| | - Heena Rathore
- Department of Computer Science at Texas State University, USA.
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Formaggio E, Tonellato M, Antonini A, Castiglia L, Gallo L, Manganotti P, Masiero S, Del Felice A. Oscillatory EEG-TMS Reactivity in Parkinson Disease. J Clin Neurophysiol 2023; 40:263-268. [PMID: 34280941 DOI: 10.1097/wnp.0000000000000881] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
PURPOSE A dysfunction of beta oscillatory activity is the neurophysiological hallmark of Parkinson disease (PD). How cortical activity reacts to external perturbations may provide insight into pathophysiological mechanisms. This study aims at identifying modifications in EEG rhythms after transcranial magnetic stimulation (TMS) in PD. We hypothesize that single-pulse TMS can modulate brain intrinsic oscillatory properties (e.g., beta excess). METHODS EEG data were coregistered during single-pulse TMS (100 stimuli over the primary motor cortex [M1, hotspot for Abductor Pollicis Brevis], random intertrial interval from 8 to 13 seconds). We used a time-frequency analysis based on wavelet method to characterize modification of oscillatory rhythms (delta [1-4 Hz], theta [4-7 Hz], alpha [8-12 Hz], and beta [13-30 Hz] in 15 participants with PD compared with 10 healthy controls. RESULTS An increase in beta power over the sensorimotor areas was recorded at rest in the PD group ( P < 0.05). Brain oscillations in PD transiently reset after TMS: beta power over M1 becomes comparable to that recorded in aged-matched healthy subjects in the 2 seconds following TMS. CONCLUSIONS Transcranial magnetic stimulation over the dominant motor cortex transiently normalizes cortical oscillations. More user-friendly noninvasive brain stimulation needs to be trialed, based on this proof of concept, to provide practical, portable techniques to treat motor symptoms in PD.
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Affiliation(s)
- Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Michele Tonellato
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Centre on Neurodegeneration (CESNE), Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
| | - Leonora Castiglia
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Laura Gallo
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Paolo Manganotti
- Neurology Section, Cattinara University Hospital, University of Trieste, Trieste, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy; and
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Xu G, Hao F, Zhao W, Qiu J, Zhao P, Zhang Q. The influential factors and non-pharmacological interventions of cognitive impairment in children with ischemic stroke. Front Neurol 2022; 13:1072388. [PMID: 36588886 PMCID: PMC9797836 DOI: 10.3389/fneur.2022.1072388] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 11/23/2022] [Indexed: 12/23/2022] Open
Abstract
Background The prevalence of pediatric ischemic stroke rose by 35% between 1990 and 2013. Affected patients can experience the gradual onset of cognitive impairment in the form of impaired language, memory, intelligence, attention, and processing speed, which affect 20-50% of these patients. Only few evidence-based treatments are available due to significant heterogeneity in age, pathological characteristics, and the combined epilepsy status of the affected children. Methods We searched the literature published by Web of Science, Scopus, and PubMed, which researched non-pharmacological rehabilitation interventions for cognitive impairment following pediatric ischemic stroke. The search period is from the establishment of the database to January 2022. Results The incidence of such impairment is influenced by patient age, pathological characteristics, combined epilepsy status, and environmental factors. Non-pharmacological treatments for cognitive impairment that have been explored to date mainly include exercise training, psychological intervention, neuromodulation strategies, computer-assisted cognitive training, brain-computer interfaces (BCI), virtual reality, music therapy, and acupuncture. In childhood stroke, the only interventions that can be retrieved are psychological intervention and neuromodulation strategies. Conclusion However, evidence regarding the efficacy of these interventions is relatively weak. In future studies, the active application of a variety of interventions to improve pediatric cognitive function will be necessary, and neuroimaging and electrophysiological measurement techniques will be of great value in this context. Larger multi-center prospective longitudinal studies are also required to offer more accurate evidence-based guidance for the treatment of patients with pediatric stroke.
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Affiliation(s)
- Gang Xu
- Rehabilitation Branch, Tianjin Children's Hospital/Tianjin University Children's Hospital, Tianjin, China
| | - Fuchun Hao
- Medicine & Nursing Faculty, Tianjin Medical College, Tianjin, China
| | - Weiwei Zhao
- Chinese Teaching and Research Section, Tianjin Beichen Experimental Middle School, Tianjin, China
| | - Jiwen Qiu
- Research Center of Experimental Acupuncture Science, Tianjin University of Traditional Chinese Medicine, Tianjin, China,School of Medical Technology, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Peng Zhao
- Rehabilitation Branch, Tianjin Children's Hospital/Tianjin University Children's Hospital, Tianjin, China,*Correspondence: Peng Zhao
| | - Qian Zhang
- Child Health Care Department, Tianjin Beichen Women and Children Health Center, Tianjin, China,Qian Zhang
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Yuan C, Li X. Fitting of TC model according to key parameters affecting Parkinson's state based on improved particle swarm optimization algorithm. Sci Rep 2022; 12:13938. [PMID: 35977977 PMCID: PMC9385711 DOI: 10.1038/s41598-022-18267-9] [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: 06/27/2021] [Accepted: 08/08/2022] [Indexed: 11/10/2022] Open
Abstract
Biophysical models contain a large number of parameters, while the spiking characteristics of neurons are related to a few key parameters. For thalamic neurons, relay reliability is an important characteristic that affects Parkinson's state. This paper proposes a method to fit key parameters of the model based on the spiking characteristics of neurons, and improves the traditional particle swarm optimization algorithm. That is, a nonlinear concave function and a Logistic chaotic mapping are combined to adjust the inertia weight of particles to avoid the particle falling into a local optimum in the search process or appearing premature convergence. In this paper, three parameters that play an important role in Parkinson's state of the thalamic cell model are selected and fitted by the improved particle swarm optimization algorithm. Using the fitted parameters to reconstruct the neuron model can predict the spiking trajectories well, which verifies the effectiveness of the fitting method. By comparing the fitting results with other particle swarm optimization algorithms, it is shown that the proposed particle swarm optimization algorithm can better avoid local optima and converge to the optimal values quickly.
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Affiliation(s)
- Chunhua Yuan
- School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, 110159, China
| | - Xiangyu Li
- School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, 110159, China.
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Liu C, Zhao G, Meng Z, Zhou C, Zhu X, Zhang W, Wang J, Li H, Wu H, Fietkiewicz C, Loparo KA. Closing the loop of DBS using the beta oscillations in cortex. Cogn Neurodyn 2021; 15:1157-1167. [PMID: 34790273 DOI: 10.1007/s11571-021-09690-1] [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: 06/03/2020] [Revised: 04/25/2021] [Accepted: 06/05/2021] [Indexed: 10/21/2022] Open
Abstract
Cortical information has great importance to reflect the deep brain stimulation (DBS) effects for Parkinson's disease patients. Using cortical activities to feedback is an available closed-loop idea for DBS. Previous studies have demonstrated the pathological beta (12-35 Hz) cortical oscillations can be suppressed by appropriate DBS settings. Thus, here we propose to close the loop of DBS based on the beta oscillations in cortex. By modify the cortico-basal ganglia-thalamic neural loop model, more biologically realistic underlying the Parkinsonian phenomenon is approached. Stimulation results show the proposed closed-loop DBS strategy using cortical beta oscillation as feedback information has more profound roles in alleviating the pathological neural abnormality than the traditional open-loop DBS. Additionally, we compare the stimulation effects with subthalamic nucleus feedback strategy. It is shown that using cortical beta information as the feedback signals can further enlarge the control parameter space based on proportional-integral control structure with a lower energy expenditure. This work may pave the way to optimizing the DBS effects in a closed-loop arrangement.
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Affiliation(s)
- Chen Liu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Ge Zhao
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Zihan Meng
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies, Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
| | - Xiaodong Zhu
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Wei Zhang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Jiang Wang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Huiyan Li
- School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin, China
| | - Hao Wu
- School of Civil Engineering, Tianjin University, Tianjin, China
| | - Chris Fietkiewicz
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH USA
| | - Kenneth A Loparo
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH USA
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Wei X, Zhang H, Gong B, Chang S, Lu M, Yi G, Zhang Z, Deng B, Wang J. An Embedded Multi-Core Real-Time Simulation Platform of Basal Ganglia for Deep Brain Stimulation. IEEE Trans Neural Syst Rehabil Eng 2021; 29:1328-1340. [PMID: 34232884 DOI: 10.1109/tnsre.2021.3095316] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Closed-loop deep brain stimulation (DBS) paradigm is gaining tremendous favor due to its potential capability of further and more efficient improvements in neurological diseases. Preclinical validation of closed-loop controller is quite necessary in order to minimize injury risks of clinical trials to patients, which can greatly benefit from real-time computational models and thus potentially reduce research and development costs and time. Here we developed an embedded multi-core real-time simulation platform (EMC-RTP) for a biological-faithful computational network model of basal ganglia (BG). The single neuron model is implemented in a highly real-time manner using a reasonable simplification. A modular mapping architecture with hierarchical routing organization was constructed to mimic the pathological neural activities of BG observed in parkinsonian conditions. A closed-loop simulation testbed for DBS validation was then set up using a host computer as the DBS controller. The availability of EMC-RTP and the testbed system was validated by comparing the performance of open-loop and proportional-integral (PI) controllers. Our experimental results showed that the proposed EMC-RTP reproduces abnormal beta bursts of BG in parkinsonian conditions while meets requirements of both real-time and computational accuracy as well. Closed-loop DBS experiments using the EMC-RTP suggested that the platform could perform reasonable output under different kinds of DBS strategies, indicating the usability of the platform.
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Escobar I, Xu J, Jackson CW, Perez-Pinzon MA. Altered Neural Networks in the Papez Circuit: Implications for Cognitive Dysfunction after Cerebral Ischemia. J Alzheimers Dis 2020; 67:425-446. [PMID: 30584147 PMCID: PMC6398564 DOI: 10.3233/jad-180875] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Cerebral ischemia remains a leading cause of mortality worldwide. Although the incidence of death has decreased over the years, surviving patients may suffer from long-term cognitive impairments and have an increased risk for dementia. Unfortunately, research aimed toward developing therapies that can improve cognitive outcomes following cerebral ischemia has proved difficult given the fact that little is known about the underlying processes involved. Nevertheless, mechanisms that disrupt neural network activity may provide valuable insight, since disturbances in both local and global networks in the brain have been associated with deficits in cognition. In this review, we suggest that abnormal neural dynamics within different brain networks may arise from disruptions in synaptic plasticity processes and circuitry after ischemia. This discussion primarily concerns disruptions in local network activity within the hippocampus and other extra-hippocampal components of the Papez circuit, given their role in memory processing. However, impaired synaptic plasticity processes and disruptions in structural and functional connections within the Papez circuit have important implications for alterations within the global network, as well. Although much work is required to establish this relationship, evidence thus far suggests there is a link. If pursued further, findings may lead toward a better understanding of how deficits in cognition arise, not only in cerebral ischemia, but in other neurological diseases as well.
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Affiliation(s)
- Iris Escobar
- Department of Neurology, Cerebral Vascular Disease Research Laboratories, University of Miami Miller School of Medicine, Miami, FL, USA.,Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jing Xu
- Department of Neurology, Cerebral Vascular Disease Research Laboratories, University of Miami Miller School of Medicine, Miami, FL, USA.,Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Charles W Jackson
- Department of Neurology, Cerebral Vascular Disease Research Laboratories, University of Miami Miller School of Medicine, Miami, FL, USA.,Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Miguel A Perez-Pinzon
- Department of Neurology, Cerebral Vascular Disease Research Laboratories, University of Miami Miller School of Medicine, Miami, FL, USA.,Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA
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