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Liénard JF, Aubin L, Cos I, Girard B. Estimation of the transmission delays in the basal ganglia of the macaque monkey and subsequent predictions about oscillatory activity under dopamine depletion. Eur J Neurosci 2024; 59:1657-1680. [PMID: 38414108 DOI: 10.1111/ejn.16271] [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: 07/20/2023] [Revised: 12/31/2023] [Accepted: 01/21/2024] [Indexed: 02/29/2024]
Abstract
The timescales of the dynamics of a system depend on the combination of the timescales of its components and of its transmission delays between components. Here, we combine experimental stimulation data from 10 studies in macaque monkeys that reveal the timing of excitatory and inhibitory events in the basal ganglia circuit, to estimate its set of transmission delays. In doing so, we reveal possible inconsistencies in the existing data, calling for replications, and we propose two possible sets of transmission delays. We then integrate these delays in a model of the primate basal ganglia that does not rely on direct and indirect pathways' segregation and show that extrastriatal dopaminergic depletion in the external part of the globus pallidus and in the subthalamic nucleus is sufficient to generate β-band oscillations (in the high part, 20-35 Hz, of the band). More specifically, we show that D2 and D5 dopamine receptors in these nuclei play opposing roles in the emergence of these oscillations, thereby explaining how completely deactivating D5 receptors in the subthalamic nucleus can, paradoxically, cancel oscillations.
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Affiliation(s)
- Jean F Liénard
- Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France
| | - Lise Aubin
- Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France
| | - Ignasi Cos
- Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France
- Facultat de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain
- Serra-Hunter Fellow Program, Barcelona, Spain
| | - Benoît Girard
- Sorbonne Université, CNRS, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France
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2
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Ahmadipour M, Barkhordari-Yazdi M, Seydnejad SR. Subspace-based predictive control of Parkinson's disease: A model-based study. Neural Netw 2021; 142:680-689. [PMID: 34403908 DOI: 10.1016/j.neunet.2021.07.025] [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: 08/13/2020] [Revised: 06/19/2021] [Accepted: 07/21/2021] [Indexed: 10/20/2022]
Abstract
Deep brain stimulation (DBS) of the Basal Ganglia (BG) is an effective treatment to suppress the symptoms of Parkinson's disease (PD). Using a closed-loop scheme in DBS can not only improve its therapeutic effects but it can also reduce its energy consumption and possible side effects. In this paper, a predictive closed loop control strategy is employed to suppress the PD in real-time. A linear multi-input multi-output (MIMO) state-delayed system is considered as a simplified model of the BG neuronal network relating the stimulation signals as inputs to the beta power of local field potentials as PD biomarkers. The effect of time delay in different areas of the BG is incorporated into this model and a real-time subspace-based identification is implemented to continuously model the state of the BG neuronal network and drive the predictive control strategy. Simulation results show that the proposed MIMO subspace based predictive controller can suppress PD symptoms more effectively and with less power consumption compared to the conventional open-loop DBS and a recently proposed single-input single-output closed loop controller.
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Affiliation(s)
- Mahboubeh Ahmadipour
- Department of Electrical Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
| | - Mojtaba Barkhordari-Yazdi
- Department of Electrical Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
| | - Saeid R Seydnejad
- Department of Electrical Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
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3
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Girard B, Lienard J, Gutierrez CE, Delord B, Doya K. A biologically constrained spiking neural network model of the primate basal ganglia with overlapping pathways exhibits action selection. Eur J Neurosci 2020; 53:2254-2277. [PMID: 32564449 PMCID: PMC8246891 DOI: 10.1111/ejn.14869] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 05/19/2020] [Accepted: 06/08/2020] [Indexed: 12/19/2022]
Abstract
Action selection has been hypothesized to be a key function of the basal ganglia, yet the nuclei involved, their interactions and the importance of the direct/indirect pathway segregation in such process remain debated. Here, we design a spiking computational model of the monkey basal ganglia derived from a previously published population model, initially parameterized to reproduce electrophysiological activity at rest and to embody as much quantitative anatomical data as possible. As a particular feature, both models exhibit the strong overlap between the direct and indirect pathways that has been documented in non-human primates. Here, we first show how the translation from a population to an individual neuron model was achieved, with the addition of a minimal number of parameters. We then show that our model performs action selection, even though it was built without any assumption on the activity carried out during behaviour. We investigate the mechanisms of this selection through circuit disruptions and found an instrumental role of the off-centre/on-surround structure of the MSN-STN-GPi circuit, as well as of the MSN-MSN and FSI-MSN projections. This validates their potency in enabling selection. We finally study the pervasive centromedian and parafascicular thalamic inputs that reach all basal ganglia nuclei and whose influence is therefore difficult to anticipate. Our model predicts that these inputs modulate the responsiveness of action selection, making them a candidate for the regulation of the speed-accuracy trade-off during decision-making.
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Affiliation(s)
- Benoît Girard
- Institut des Systèmes Intelligent et de Robotique (ISIR), Sorbonne Université, CNRS, Paris, France
| | - Jean Lienard
- Neural Computation Unit, Okinawa Institute of Science and Technology, Kunigami-gun, Japan
| | | | - Bruno Delord
- Institut des Systèmes Intelligent et de Robotique (ISIR), Sorbonne Université, CNRS, Paris, France
| | - Kenji Doya
- Neural Computation Unit, Okinawa Institute of Science and Technology, Kunigami-gun, Japan
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Zhao D, Sun Q, Cheng S, He M, Chen X, Hou X. Extraction of Parkinson’s Disease-Related Features from Local Field Potentials for Adaptive Deep Brain Stimulation. NEUROPHYSIOLOGY+ 2018. [DOI: 10.1007/s11062-018-9717-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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Liu C, Zhu Y, Liu F, Wang J, Li H, Deng B, Fietkiewicz C, Loparo KA. Neural mass models describing possible origin of the excessive beta oscillations correlated with Parkinsonian state. Neural Netw 2017; 88:65-73. [PMID: 28192762 DOI: 10.1016/j.neunet.2017.01.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 11/18/2016] [Accepted: 01/24/2017] [Indexed: 10/20/2022]
Abstract
In Parkinson's disease, the enhanced beta rhythm is closely associated with akinesia/bradykinesia and rigidity. An increase in beta oscillations (12-35 Hz) within the basal ganglia (BG) nuclei does not proliferate throughout the cortico-basal ganglia loop in uniform fashion; rather it can be subdivided into two distinct frequency bands, i.e. the lower beta (12-20 Hz) and upper beta (21-35 Hz). A computational model of the excitatory and inhibitory neural network that focuses on the population properties is proposed to explore the mechanism underlying the pathological beta oscillations. Simulation results show several findings. The upper beta frequency in the BG originates from a high frequency cortical beta, while the emergence of exaggerated lower beta frequency in the BG depends greatly on the enhanced excitation of a reciprocal network consisting of the globus pallidus externus (GPe) and the subthalamic nucleus (STN). There is also a transition mechanism between the upper and lower beta oscillatory activities, and we explore the impact of self-inhibition within the GPe on the relationship between the upper beta and lower beta oscillations. It is shown that increased self-inhibition within the GPe contributes to increased upper beta oscillations driven by the cortical rhythm, while decrease in the self-inhibition within the GPe facilitates an enhancement of the lower beta oscillations induced by the increased excitability of the BG. This work provides an analysis for understanding the mechanism underlying pathological synchronization in neurological diseases.
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Affiliation(s)
- Chen Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China; Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, OH, USA
| | - Yulin Zhu
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Fei Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Jiang Wang
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Huiyan Li
- School of Automation and Electrical Engineering, Tianjin University of Technology and Educations, 300222, Tianjin, China
| | - Bin Deng
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China.
| | - Chris Fietkiewicz
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, OH, USA
| | - Kenneth A Loparo
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, OH, USA
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Liu F, Wang J, Liu C, Li H, Deng B, Fietkiewicz C, Loparo KA. A neural mass model of basal ganglia nuclei simulates pathological beta rhythm in Parkinson's disease. CHAOS (WOODBURY, N.Y.) 2016; 26:123113. [PMID: 28039987 DOI: 10.1063/1.4972200] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
An increase in beta oscillations within the basal ganglia nuclei has been shown to be associated with movement disorder, such as Parkinson's disease. The motor cortex and an excitatory-inhibitory neuronal network composed of the subthalamic nucleus (STN) and the external globus pallidus (GPe) are thought to play an important role in the generation of these oscillations. In this paper, we propose a neuron mass model of the basal ganglia on the population level that reproduces the Parkinsonian oscillations in a reciprocal excitatory-inhibitory network. Moreover, it is shown that the generation and frequency of these pathological beta oscillations are varied by the coupling strength and the intrinsic characteristics of the basal ganglia. Simulation results reveal that increase of the coupling strength induces the generation of the beta oscillation, as well as enhances the oscillation frequency. However, for the intrinsic properties of each nucleus in the excitatory-inhibitory network, the STN primarily influences the generation of the beta oscillation while the GPe mainly determines its frequency. Interestingly, describing function analysis applied on this model theoretically explains the mechanism of pathological beta oscillations.
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Affiliation(s)
- Fei Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072 Tianjin, China
| | - Jiang Wang
- School of Electrical Engineering and Automation, Tianjin University, 300072 Tianjin, China
| | - Chen Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072 Tianjin, China
| | - Huiyan Li
- School of Automation and Electrical Engineering, Tianjin University of Technology and Educations, 300222 Tianjin, China
| | - Bin Deng
- School of Electrical Engineering and Automation, Tianjin University, 300072 Tianjin, China
| | - Chris Fietkiewicz
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio 44106, USA
| | - Kenneth A Loparo
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio 44106, USA
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Karamintziou SD, Deligiannis NG, Piallat B, Polosan M, Chabardès S, David O, Stathis PG, Tagaris GA, Boviatsis EJ, Sakas DE, Polychronaki GE, Tsirogiannis GL, Nikita KS. Dominant efficiency of nonregular patterns of subthalamic nucleus deep brain stimulation for Parkinson’s disease and obsessive-compulsive disorder in a data-driven computational model. J Neural Eng 2015; 13:016013. [DOI: 10.1088/1741-2560/13/1/016013] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Davidson CM, de Paor AM, Cagnan H, Lowery MM. Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson's Disease During Deep Brain Stimulation. IEEE Trans Biomed Eng 2015; 63:86-96. [PMID: 26340768 DOI: 10.1109/tbme.2015.2475166] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Parkinson's disease is a progressive, neurodegenerative disorder, characterized by hallmark motor symptoms. It is associated with pathological, oscillatory neural activity in the basal ganglia. Deep brain stimulation (DBS) is often successfully used to treat medically refractive Parkinson's disease. However, the selection of stimulation parameters is based on qualitative assessment of the patient, which can result in a lengthy tuning period and a suboptimal choice of parameters. This study explores fourth-order, control theory-based models of oscillatory activity in the basal ganglia. Describing function analysis is applied to examine possible mechanisms for the generation of oscillations in interacting nuclei and to investigate the suppression of oscillations with high-frequency stimulation. The theoretical results for the suppression of the oscillatory activity obtained using both the fourth-order model, and a previously described second-order model, are optimized to fit clinically recorded local field potential data obtained from Parkinsonian patients with implanted DBS. Close agreement between the power of oscillations recorded for a range of stimulation amplitudes is observed ( R(2)=0.69-0.99 ). The results suggest that the behavior of the system and the suppression of pathological neural oscillations with DBS is well described by the macroscopic models presented. The results also demonstrate that in this instance, a second-order model is sufficient to model the clinical data, without the need for added complexity. Describing the system behavior with computationally efficient models could aid in the identification of optimal stimulation parameters for patients in a clinical environment.
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WEI WJ, SONG YL, FAN XY, ZHANG S, WANG L, XU SW, CAI XX. Microelectrode Array Probe for Simultaneous Detection of Glutamate and Local Field Potential during Brain Death. CHINESE JOURNAL OF ANALYTICAL CHEMISTRY 2015. [DOI: 10.1016/s1872-2040(15)60837-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Liénard J, Girard B. A biologically constrained model of the whole basal ganglia addressing the paradoxes of connections and selection. J Comput Neurosci 2014; 36:445-68. [PMID: 24077957 DOI: 10.1007/s10827-013-0476-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2012] [Revised: 05/30/2013] [Accepted: 08/04/2013] [Indexed: 11/28/2022]
Abstract
The basal ganglia nuclei form a complex network of nuclei often assumed to perform selection, yet their individual roles and how they influence each other is still largely unclear. In particular, the ties between the external and internal parts of the globus pallidus are paradoxical, as anatomical data suggest a potent inhibitory projection between them while electrophysiological recordings indicate that they have similar activities. Here we introduce a theoretical study that reconciles both views on the intra-pallidal projection, by providing a plausible characterization of the relationship between the external and internal globus pallidus. Specifically, we developed a mean-field model of the whole basal ganglia, whose parameterization is optimized to respect best a collection of numerous anatomical and electrophysiological data. We first obtained models respecting all our constraints, hence anatomical and electrophysiological data on the intrapallidal projection are globally consistent. This model furthermore predicts that both aforementioned views about the intra-pallidal projection may be reconciled when this projection is weakly inhibitory, thus making it possible to support similar neural activity in both nuclei and for the entire basal ganglia to select between actions. Second, we predicts that afferent projections are substantially unbalanced towards the external segment, as it receives the strongest excitation from STN and the weakest inhibition from the striatum. Finally, our study strongly suggests that the intrapallidal connection pattern is not focused but diffuse, as this latter pattern is more efficient for the overall selection performed in the basal ganglia.
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Karamintziou SD, Tsirogiannis GL, Stathis PG, Tagaris GA, Boviatsis EJ, Sakas DE, Nikita KS. Supporting clinical decision making during deep brain stimulation surgery by means of a stochastic dynamical model. J Neural Eng 2014; 11:056019. [DOI: 10.1088/1741-2560/11/5/056019] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Michmizos KP, Sakas D, Nikita KS. Parameter identification for a local field potential driven model of the Parkinsonian subthalamic nucleus spike activity. Neural Netw 2012; 36:146-56. [PMID: 23131592 DOI: 10.1016/j.neunet.2012.10.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2011] [Revised: 10/09/2012] [Accepted: 10/10/2012] [Indexed: 11/15/2022]
Abstract
Several models, with various degrees of complexity have been proposed to model the neuronal activity from different parts of the human brain. We have shown before that various modeling approaches, including a Hammerstein-Wiener (H-W) model, can be used to predict the spike trains from a deep nucleus, the subthalamic nucleus, using the underlying local field potentials. In this article, we present, in depth, the various choices one has to make, and the limitations that they introduce, during the H-W model parameter identification process. From a segment of the recorded data, which contains information about the spike times of a single neuron, we identify and extract the model parameters. We then use those parameters to numerically simulate the spike timing, the rhythm and the inter-spike intervals for the rest of the recording. To assess how well the model fits to the measured data we combine measures of spike train synchrony, namely the Victor-Purpura distance and the Gaussian similarity measure, with time-scale independent train distances. We show that a wise combination of metrics results in models that predict the spikes with temporal accuracy ranging, on average, from 53% to more than 80%, depending on the number of the neurons' spikes recorded. The model's prediction is adequate for estimating accurately the spike rhythm. Quantitative results establish the model's validity as a simple yet biologically plausible model of the spike activity recorded from a deep nucleus inside the human brain.
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Michmizos KP, Sakas D, Nikita KS. Prediction of the Timing and the Rhythm of the Parkinsonian Subthalamic Nucleus Neural Spikes Using the Local Field Potentials. ACTA ACUST UNITED AC 2012; 16:190-7. [DOI: 10.1109/titb.2011.2158549] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Guo Y, Rubin JE. Multi-site stimulation of subthalamic nucleus diminishes thalamocortical relay errors in a biophysical network model. Neural Netw 2011; 24:602-16. [DOI: 10.1016/j.neunet.2011.03.010] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2010] [Revised: 02/28/2011] [Accepted: 03/07/2011] [Indexed: 10/18/2022]
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Pedoto G, Santaniello S, Montgomery EB, Gale JT, Fiengo G, Glielmo L, Sarma SV. System identification of local field potentials under deep brain stimulation in a healthy primate. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2010; 2010:4144-7. [PMID: 21096635 PMCID: PMC3822772 DOI: 10.1109/iembs.2010.5627356] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
High frequency (HF) Deep Brain Stimulation (DBS) in the Sub-Thalamic Nucleus (STN) is a clinically recognized therapy for the treatment of motor disorders in Parkinson Disease (PD). The underlying mechanisms of DBS and how it impacts neighboring nuclei, however, are not yet completely understood. Electrophysiological data has been collected in PD patients and primates to better understand the impact of DBS on STN and the entire Basal Ganglia (BG) motor circuit. We use single unit recordings from Globus Pallidus, both pars interna and externa segments (GPi and GPe) in the BG, in a normal primate before and after DBS to reconstruct Local Field Potentials (LFPs) in the region. We then use system identification techniques to understand how GPe LFP activity and the DBS signal applied to STN influence GPi LFP activity. Our models suggest that when no stimulation is applied, the GPe LFPs have an inhibitory effect on GPi LFPs with a 2-3 ms delay, as is the case for single unit neuronal activity. On the other hand, when DBS is ON the models suggest that stimulation has a dominant effect on GPi LFPs which mask the inhibitory effects of GPe.
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Affiliation(s)
- Gilda Pedoto
- Engineering Department of Università degli Studi del Sannio , Benevento, Italy ()
| | - Sabato Santaniello
- Institute of Computational Medicine, Jhons Hopkins University, Baltimore, Maryland USA (ssantan5,)
| | - Erwin B. Montgomery
- Department of Neurology, National Primate Research Center, University of Wisconsin-Madison USA ()
| | - John T. Gale
- Department of Neurosurgery, Massachusetts General Hospital/Harvard Medical School, Boston USA
| | | | | | - Sridevi V. Sarma
- Institute of Computational Medicine, Jhons Hopkins University, Baltimore, Maryland USA
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