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Chauhan K, Neiman AB, Tass PA. Synaptic reorganization of synchronized neuronal networks with synaptic weight and structural plasticity. PLoS Comput Biol 2024; 20:e1012261. [PMID: 38980898 PMCID: PMC11259284 DOI: 10.1371/journal.pcbi.1012261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 07/19/2024] [Accepted: 06/20/2024] [Indexed: 07/11/2024] Open
Abstract
Abnormally strong neural synchronization may impair brain function, as observed in several brain disorders. We computationally study how neuronal dynamics, synaptic weights, and network structure co-emerge, in particular, during (de)synchronization processes and how they are affected by external perturbation. To investigate the impact of different types of plasticity mechanisms, we combine a network of excitatory integrate-and-fire neurons with different synaptic weight and/or structural plasticity mechanisms: (i) only spike-timing-dependent plasticity (STDP), (ii) only homeostatic structural plasticity (hSP), i.e., without weight-dependent pruning and without STDP, (iii) a combination of STDP and hSP, i.e., without weight-dependent pruning, and (iv) a combination of STDP and structural plasticity (SP) that includes hSP and weight-dependent pruning. To accommodate the diverse time scales of neuronal firing, STDP, and SP, we introduce a simple stochastic SP model, enabling detailed numerical analyses. With tools from network theory, we reveal that structural reorganization may remarkably enhance the network's level of synchrony. When weaker contacts are preferentially eliminated by weight-dependent pruning, synchrony is achieved with significantly sparser connections than in randomly structured networks in the STDP-only model. In particular, the strengthening of contacts from neurons with higher natural firing rates to those with lower rates and the weakening of contacts in the opposite direction, followed by selective removal of weak contacts, allows for strong synchrony with fewer connections. This activity-led network reorganization results in the emergence of degree-frequency, degree-degree correlations, and a mixture of degree assortativity. We compare the stimulation-induced desynchronization of synchronized states in the STDP-only model (i) with the desynchronization of models (iii) and (iv). The latter require stimuli of significantly higher intensity to achieve long-term desynchronization. These findings may inform future pre-clinical and clinical studies with invasive or non-invasive stimulus modalities aiming at inducing long-lasting relief of symptoms, e.g., in Parkinson's disease.
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Affiliation(s)
- Kanishk Chauhan
- Department of Physics and Astronomy, Ohio University, Athens, Ohio, United States of America
- Neuroscience Program, Ohio University, Athens, Ohio, United States of America
| | - Alexander B. Neiman
- Department of Physics and Astronomy, Ohio University, Athens, Ohio, United States of America
- Neuroscience Program, Ohio University, Athens, Ohio, United States of America
| | - Peter A. Tass
- Department of Neurosurgery, Stanford University, Stanford, California, United States of America
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Kromer JA, Tass PA. Coordinated reset stimulation of plastic neural networks with spatially dependent synaptic connections. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1351815. [PMID: 38863734 PMCID: PMC11165135 DOI: 10.3389/fnetp.2024.1351815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/15/2024] [Indexed: 06/13/2024]
Abstract
Background Abnormal neuronal synchrony is associated with several neurological disorders, including Parkinson's disease (PD), essential tremor, dystonia, and epilepsy. Coordinated reset (CR) stimulation was developed computationally to counteract abnormal neuronal synchrony. During CR stimulation, phase-shifted stimuli are delivered to multiple stimulation sites. Computational studies in plastic neural networks reported that CR stimulation drove the networks into an attractor of a stable desynchronized state by down-regulating synaptic connections, which led to long-lasting desynchronization effects that outlasted stimulation. Later, corresponding long-lasting desynchronization and therapeutic effects were found in animal models of PD and PD patients. To date, it is unclear how spatially dependent synaptic connections, as typically observed in the brain, shape CR-induced synaptic downregulation and long-lasting effects. Methods We performed numerical simulations of networks of leaky integrate-and-fire neurons with spike-timing-dependent plasticity and spatially dependent synaptic connections to study and further improve acute and long-term responses to CR stimulation. Results The characteristic length scale of synaptic connections relative to the distance between stimulation sites plays a key role in CR parameter adjustment. In networks with short synaptic length scales, a substantial synaptic downregulation can be achieved by selecting appropriate stimulus-related parameters, such as the stimulus amplitude and shape, regardless of the employed spatiotemporal pattern of stimulus deliveries. Complex stimulus shapes can induce local connectivity patterns in the vicinity of the stimulation sites. In contrast, in networks with longer synaptic length scales, the spatiotemporal sequence of stimulus deliveries is of major importance for synaptic downregulation. In particular, rapid shuffling of the stimulus sequence is advantageous for synaptic downregulation. Conclusion Our results suggest that CR stimulation parameters can be adjusted to synaptic connectivity to further improve the long-lasting effects. Furthermore, shuffling of CR sequences is advantageous for long-lasting desynchronization effects. Our work provides important hypotheses on CR parameter selection for future preclinical and clinical studies.
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Affiliation(s)
- Justus A. Kromer
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
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Khanjanianpak M, Azimi-Tafreshi N, Valizadeh A. Emergence of complex oscillatory dynamics in the neuronal networks with long activity time of inhibitory synapses. iScience 2024; 27:109401. [PMID: 38532887 PMCID: PMC10963234 DOI: 10.1016/j.isci.2024.109401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 12/30/2023] [Accepted: 02/28/2024] [Indexed: 03/28/2024] Open
Abstract
The brain displays complex dynamics, including collective oscillations, and extensive research has been conducted to understand their generation. However, our understanding of how biological constraints influence these oscillations is incomplete. This study investigates the essential properties of neuronal networks needed to generate oscillations resembling those in the brain. A simple discrete-time model of interconnected excitable elements is developed, capable of closely resembling the complex oscillations observed in biological neural networks. In the model, synaptic connections remain active for a duration exceeding individual neuron activity. We show that the inhibitory synapses must exhibit longer activity than excitatory synapses to produce a diverse range of the dynamical states, including biologically plausible oscillations. Upon meeting this condition, the transition between different dynamical states can be controlled by external stochastic input to the neurons. The study provides a comprehensive explanation for the emergence of distinct dynamical states in neural networks based on specific parameters.
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Affiliation(s)
- Mozhgan Khanjanianpak
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran 1991633357, Iran
| | - Nahid Azimi-Tafreshi
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
| | - Alireza Valizadeh
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran 1991633357, Iran
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Shavikloo M, Esmaeili A, Valizadeh A, Madadi Asl M. Synchronization of delayed coupled neurons with multiple synaptic connections. Cogn Neurodyn 2024; 18:631-643. [PMID: 38699603 PMCID: PMC11061096 DOI: 10.1007/s11571-023-10013-9] [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: 04/17/2023] [Revised: 08/16/2023] [Accepted: 09/16/2023] [Indexed: 05/05/2024] Open
Abstract
Synchronization is a key feature of the brain dynamics and is necessary for information transmission across brain regions and in higher brain functions like cognition, learning and memory. Experimental findings demonstrated that in cortical microcircuits there are multiple synapses between pairs of connected neurons. Synchronization of neurons in the presence of multiple synaptic connections may be relevant for optimal learning and memory, however, its effect on the dynamics of the neurons is not adequately studied. Here, we address the question that how changes in the strength of the synaptic connections and transmission delays between neurons impact synchronization in a two-neuron system with multiple synapses. To this end, we analytically and computationally investigated synchronization dynamics by considering both phase oscillator model and conductance-based Hodgkin-Huxley (HH) model. Our results show that symmetry/asymmetry of feedforward and feedback connections crucially determines stability of the phase locking of the system based on the strength of connections and delays. In both models, the two-neuron system with multiple synapses achieves in-phase synchrony in the presence of small and large delays, whereas an anti-phase synchronization state is favored for median delays. Our findings can expand the understanding of the functional role of multisynaptic contacts in neuronal synchronization and may shed light on the dynamical consequences of pathological multisynaptic connectivity in a number of brain disorders.
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Affiliation(s)
- Masoumeh Shavikloo
- Department of Physics, Faculty of Science, Urmia University, Urmia, Iran
| | - Asghar Esmaeili
- Department of Physics, Faculty of Science, Urmia University, Urmia, 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
| | - 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
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Zeng Z, Huang P, Lin Z, Pan Y, Wan X, Zhang C, Sun B, Li D. Rescue subthalamic stimulation after unsatisfactory outcome of pallidal stimulation in Parkinson's disease: a case series and review. Front Aging Neurosci 2024; 15:1323541. [PMID: 38264547 PMCID: PMC10803461 DOI: 10.3389/fnagi.2023.1323541] [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: 10/18/2023] [Accepted: 12/20/2023] [Indexed: 01/25/2024] Open
Abstract
Background Subthalamic nucleus (STN) and globus pallidus interna (GPi) are two main structures primarily targeted by deep brain stimulation (DBS) to treat advanced Parkinson's disease (PD). A subset of cases with unsatisfactory outcomes may benefit from rescue DBS surgery targeting another structure, while these patients' characteristics have not been well described and this phenomenon has not been well reviewed. Methods This monocentric retrospective study included patients with PD, who underwent rescue STN DBS following an unsatisfactory outcome of the initial bilateral GPi DBS in a retrospective manner. A short review of the current literature was conducted to report the clinical outcome of rescue DBS surgeries. Results Eight patients were identified, and six of them were included in this study. The rescue STN DBS was performed 19.8 months after the initial GPi DBS. After 8.8 months from the rescue STN DBS, patients showed a significant off-medication improvement by 29.2% in motor symptoms compared to initial GPi DBS. Non-motor symptoms and the health-related quality of life were also significantly improved. Conclusion Our findings suggest that the rescue STN DBS may improve off-medication motor and non-motor symptoms and quality of life in patients with failure of initial GPi DBS. The short review of the current literature showed that the target switching from GPi to STN was mainly due to poor initial outcomes and was performed by target substitution, whereas the switching from STN to GPi was mainly due to a gradual waning of benefits, long-term axial symptoms, dyskinesia, and dystonia and was performed by target addition.
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Affiliation(s)
| | | | | | | | | | | | | | - Dianyou Li
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Sawicki J, Berner R, Loos SAM, Anvari M, Bader R, Barfuss W, Botta N, Brede N, Franović I, Gauthier DJ, Goldt S, Hajizadeh A, Hövel P, Karin O, Lorenz-Spreen P, Miehl C, Mölter J, Olmi S, Schöll E, Seif A, Tass PA, Volpe G, Yanchuk S, Kurths J. Perspectives on adaptive dynamical systems. CHAOS (WOODBURY, N.Y.) 2023; 33:071501. [PMID: 37486668 DOI: 10.1063/5.0147231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 05/24/2023] [Indexed: 07/25/2023]
Abstract
Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches.
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Affiliation(s)
- Jakub Sawicki
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Rico Berner
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Sarah A M Loos
- DAMTP, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, United Kingdom
| | - Mehrnaz Anvari
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53757 Sankt-Augustin, Germany
| | - Rolf Bader
- Institute of Systematic Musicology, University of Hamburg, Hamburg, Germany
| | - Wolfram Barfuss
- Transdisciplinary Research Area: Sustainable Futures, University of Bonn, 53113 Bonn, Germany
- Center for Development Research (ZEF), University of Bonn, 53113 Bonn, Germany
| | - Nicola Botta
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science and Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Nuria Brede
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science, University of Potsdam, An der Bahn 2, 14476 Potsdam, Germany
| | - Igor Franović
- Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia
| | - Daniel J Gauthier
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Sebastian Goldt
- Department of Physics, International School of Advanced Studies (SISSA), Trieste, Italy
| | - Aida Hajizadeh
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Philipp Hövel
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Omer Karin
- Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom
| | - Philipp Lorenz-Spreen
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
| | - Christoph Miehl
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Jan Mölter
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Boltzmannstraße 3, 85748 Garching bei München, Germany
| | - Simona Olmi
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Eckehard Schöll
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Alireza Seif
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, USA
| | - Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, California 94304, USA
| | - Giovanni Volpe
- Department of Physics, University of Gothenburg, Gothenburg, Sweden
| | - Serhiy Yanchuk
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Jürgen Kurths
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
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Schmalz J, Quinarez RV, Kothare MV, Kumar G. Controlling neocortical epileptic seizures using forced temporal spike-time stimulation: an in silico computational study. Front Comput Neurosci 2023; 17:1084080. [PMID: 37449082 PMCID: PMC10336226 DOI: 10.3389/fncom.2023.1084080] [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: 10/29/2022] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
Epileptic seizure is typically characterized by highly synchronized episodes of neural activity. Existing stimulation therapies focus purely on suppressing the pathologically synchronized neuronal firing patterns during the ictal (seizure) period. While these strategies are effective in suppressing seizures when they occur, they fail to prevent the re-emergence of seizures once the stimulation is turned off. Previously, we developed a novel neurostimulation motif, which we refer to as "Forced Temporal Spike-Time Stimulation" (FTSTS) that has shown remarkable promise in long-lasting desynchronization of excessively synchronized neuronal firing patterns by harnessing synaptic plasticity. In this paper, we build upon this prior work by optimizing the parameters of the FTSTS protocol in order to efficiently desynchronize the pathologically synchronous neuronal firing patterns that occur during epileptic seizures using a recently published computational model of neocortical-onset seizures. We show that the FTSTS protocol applied during the ictal period can modify the excitatory-to-inhibitory synaptic weight in order to effectively desynchronize the pathological neuronal firing patterns even after the ictal period. Our investigation opens the door to a possible new neurostimulation therapy for epilepsy.
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Affiliation(s)
- Joseph Schmalz
- Department of Chemical and Biological Engineering, University of Idaho, Moscow, ID, United States
| | - Rachel V. Quinarez
- Department of Aerospace Engineering, San José State University, San José, CA, United States
| | - Mayuresh V. Kothare
- Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA, United States
| | - Gautam Kumar
- Department of Chemical and Materials Engineering, San José State University, San José, CA, United States
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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,*Correspondence: Sina Salehi ✉
| | - 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,Mojtaba Madadi Asl ✉
| | - 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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Asp AJ, Chintaluru Y, Hillan S, Lujan JL. Targeted neuroplasticity in spatiotemporally patterned invasive neuromodulation therapies for improving clinical outcomes. Front Neuroinform 2023; 17:1150157. [PMID: 37035718 PMCID: PMC10080034 DOI: 10.3389/fninf.2023.1150157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Affiliation(s)
- Anders J. Asp
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, United States
| | - Yaswanth Chintaluru
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, United States
- Department of Neurology and Neurosurgery, University of Colorado Anschutz School of Medicine, Aurora, CO, United States
| | - Sydney Hillan
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, United States
| | - J. Luis Lujan
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, United States
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
- *Correspondence: J. Luis Lujan
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