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Gambosi B, Jamal Sheiban F, Biasizzo M, Antonietti A, D'angelo E, Mazzoni A, Pedrocchi A. A Model with Dopamine Depletion in Basal Ganglia and Cerebellum Predicts Changes in Thalamocortical Beta Oscillations. Int J Neural Syst 2024; 34:2450045. [PMID: 38886870 DOI: 10.1142/s012906572450045x] [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] [Indexed: 06/20/2024]
Abstract
Parkinsonism is presented as a motor syndrome characterized by rigidity, tremors, and bradykinesia, with Parkinson's disease (PD) being the predominant cause. The discovery that those motor symptoms result from the death of dopaminergic cells in the substantia nigra led to focus most of parkinsonism research on the basal ganglia (BG). However, recent findings point to an active involvement of the cerebellum in this motor syndrome. Here, we have developed a multiscale computational model of the rodent brain's BG-cerebellar network. Simulations showed that a direct effect of dopamine depletion on the cerebellum must be taken into account to reproduce the alterations of neural activity in parkinsonism, particularly the increased beta oscillations widely reported in PD patients. Moreover, dopamine depletion indirectly impacted spike-time-dependent plasticity at the parallel fiber-Purkinje cell synapses, degrading associative motor learning as observed in parkinsonism. Overall, these results suggest a relevant involvement of cerebellum in parkinsonism associative motor symptoms.
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Affiliation(s)
- Benedetta Gambosi
- NearLab, Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milano, Italy
| | - Francesco Jamal Sheiban
- NearLab, Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milano, Italy
| | - Marco Biasizzo
- Department of Excellence in Robotics & AI Scuola Superiore Sant'Anna, Pisa, Italy
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Information Engineering (DIE), University of Pisa, Pisa, Italy
| | - Alberto Antonietti
- NearLab, Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milano, Italy
| | - Egidio D'angelo
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Digital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Alberto Mazzoni
- Department of Excellence in Robotics & AI Scuola Superiore Sant'Anna, Pisa, Italy
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Alessandra Pedrocchi
- NearLab, Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milano, Italy
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2
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Clapp M, Bahuguna J, Giossi C, Rubin JE, Verstynen T, Vich C. CBGTPy: An extensible cortico-basal ganglia-thalamic framework for modeling biological decision making. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.05.556301. [PMID: 37732280 PMCID: PMC10508778 DOI: 10.1101/2023.09.05.556301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Here we introduce CBGTPy, a virtual environment for designing and testing goal-directed agents with internal dynamics that are modeled on the cortico-basal-ganglia-thalamic (CBGT) pathways in the mammalian brain. CBGTPy enables researchers to investigate the internal dynamics of the CBGT system during a variety of tasks, allowing for the formation of testable predictions about animal behavior and neural activity. The framework has been designed around the principle of flexibility, such that many experimental parameters in a decision making paradigm can be easily defined and modified. Here we demonstrate the capabilities of CBGTPy across a range of single and multi-choice tasks, highlighting the ease of set up and the biologically realistic behavior that it produces. We show that CBGTPy is extensible enough to apply to a range of experimental protocols and to allow for the implementation of model extensions with minimal developmental effort.
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Affiliation(s)
- Matthew Clapp
- Department of Psychology & Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Jyotika Bahuguna
- Department of Psychology & Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Cristina Giossi
- Departament de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears, Palma, Spain
- Institute of Applied Computing and Community Code, Palma, Spain
| | - Jonathan E. Rubin
- Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America
- Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Timothy Verstynen
- Department of Psychology & Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America
| | - Catalina Vich
- Departament de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears, Palma, Spain
- Institute of Applied Computing and Community Code, Palma, Spain
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3
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Sheheitli H, Jirsa V. Incorporating slow NMDA-type receptors with nonlinear voltage-dependent magnesium block in a next generation neural mass model: derivation and dynamics. J Comput Neurosci 2024; 52:207-222. [PMID: 38967732 PMCID: PMC11327200 DOI: 10.1007/s10827-024-00874-2] [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: 06/28/2023] [Revised: 03/11/2024] [Accepted: 06/26/2024] [Indexed: 07/06/2024]
Abstract
We derive a next generation neural mass model of a population of quadratic-integrate-and-fire neurons, with slow adaptation, and conductance-based AMPAR, GABAR and nonlinear NMDAR synapses. We show that the Lorentzian ansatz assumption can be satisfied by introducing a piece-wise polynomial approximation of the nonlinear voltage-dependent magnesium block of NMDAR current. We study the dynamics of the resulting system for two example cases of excitatory cortical neurons and inhibitory striatal neurons. Bifurcation diagrams are presented comparing the different dynamical regimes as compared to the case of linear NMDAR currents, along with sample comparison simulation time series demonstrating different possible oscillatory solutions. The omission of the nonlinearity of NMDAR currents results in a shift in the range (and possible disappearance) of the constant high firing rate regime, along with a modulation in the amplitude and frequency power spectrum of oscillations. Moreover, nonlinear NMDAR action is seen to be state-dependent and can have opposite effects depending on the type of neurons involved and the level of input firing rate received. The presented model can serve as a computationally efficient building block in whole brain network models for investigating the differential modulation of different types of synapses under neuromodulatory influence or receptor specific malfunction.
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Affiliation(s)
- Hiba Sheheitli
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France.
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States.
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States.
| | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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4
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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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5
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Song J, Lin H, Liu S. Basal ganglia network dynamics and function: Role of direct, indirect and hyper-direct pathways in action selection. NETWORK (BRISTOL, ENGLAND) 2023; 34:84-121. [PMID: 36856435 DOI: 10.1080/0954898x.2023.2173816] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 10/11/2022] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
Basal ganglia (BG) are a widely recognized neural basis for action selection, but its decision-making mechanism is still a difficult problem for researchers. Therefore, we constructed a spiking neural network inspired by the BG anatomical data. Simulation experiments were based on the principle of dis-inhibition and our functional hypothesis within the BG: the direct pathway, the indirect pathway, and the hyper-direct pathway of the BG jointly implement the initiation execution and termination of motor programs. Firstly, we studied the dynamic process of action selection with the network, which contained intra-group competition and inter-group competition. Secondly, we focused on the effects of the stimulus intensity and the proportion of excitation and inhibition on the GPi/SNr. The results suggested that inhibition and excitation shape action selection. They also explained why the firing rate of GPi/SNr did not continue to increase in the action-selection experiment. Finally, we discussed the experimental results with the functional hypothesis. Uniquely, this paper summarized the decision-making neural mechanism of action selection based on the direct pathway, the indirect pathway, and the hyper-direct pathway within BG.
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Affiliation(s)
- Jian Song
- School of Mathematics, South China University of Technology, Guangzhou, China
| | - Hui Lin
- Department of Precision Instruments, Tsinghua University, Beijing, China
| | - Shenquan Liu
- School of Mathematics, South China University of Technology, Guangzhou, China
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6
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Song J, Liu S, Lin H. Model-based quantitative optimization of deep brain stimulation and prediction of parkinson's states. Neuroscience 2022; 498:105-124. [PMID: 35750111 DOI: 10.1016/j.neuroscience.2022.05.019] [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: 01/05/2022] [Revised: 05/01/2022] [Accepted: 05/16/2022] [Indexed: 10/18/2022]
Abstract
Although the exact etiology of Parkinson's disease (PD) is still unknown, there are a variety of treatments available to alleviate its symptoms according to the development stage of PD. Deep brain stimulation (DBS), the most common surgical treatment for advanced PD, accurately locates and implants stimulating electrodes at specific targets in the brain to deliver high-frequency electrical stimulation that alters the excitability of the corresponding nuclei. However, for different patients and stages of PD development, there exists a choice of the optimal DBS protocol. In this paper, we propose a quantitative method (multi-dimensional feature indexes) to determine the stimulation pattern, stimulation parameters, and target of DBS from the perspective of the network model. On the other hand, based on this method, the development of PD can be predicted so that timely treatment can be given to patients. Simulation results show that, first, different network states can be distinguished by extracting features of the firing activity of neuronal populations within the basal ganglia network system. Secondly, the optimal DBS treatment can be selected by comparing the feature indexes vectors of the pre- and post-state of the network after the action of different modes of DBS. Lastly, the evolution of the network state from normal to pathological is simulated. The critical point of network state transitions is determined. These results provide a quantitative and qualitative method for determining the optimal regimen for DBS for PD, which is helpful for clinical practice.
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Affiliation(s)
- Jian Song
- School of mathematics, South China University of technology, Guangzhou, China.
| | - Shenquan Liu
- School of mathematics, South China University of technology, Guangzhou, China.
| | - Hui Lin
- Department of Precision Instruments, Tsinghua University, Beijing, China.
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7
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Meier JM, Perdikis D, Blickensdörfer A, Stefanovski L, Liu Q, Maith O, Dinkelbach HÜ, Baladron J, Hamker FH, Ritter P. Virtual deep brain stimulation: Multiscale co-simulation of a spiking basal ganglia model and a whole-brain mean-field model with the virtual brain. Exp Neurol 2022; 354:114111. [DOI: 10.1016/j.expneurol.2022.114111] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 04/04/2022] [Accepted: 05/05/2022] [Indexed: 11/04/2022]
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8
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Transient Response of Basal Ganglia Network in Healthy and Low-Dopamine State. eNeuro 2022; 9:ENEURO.0376-21.2022. [PMID: 35140075 PMCID: PMC8938981 DOI: 10.1523/eneuro.0376-21.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/27/2021] [Accepted: 01/04/2022] [Indexed: 12/30/2022] Open
Abstract
The basal ganglia (BG) are crucial for a variety of motor and cognitive functions. Changes induced by persistent low-dopamine (e.g., in Parkinson’s disease; PD) result in aberrant changes in steady-state population activity (β band oscillations) and the transient response of the BG. Typically, a brief cortical stimulation results in a triphasic response in the substantia nigra pars reticulata (SNr; an output of the BG). The properties of the triphasic responses are shaped by dopamine levels. While mechanisms underlying aberrant steady state activity are well studied, it is still unclear which BG interactions are crucial for the aberrant transient responses in the BG. Moreover, it is also unclear whether mechanisms underlying the aberrant changes in steady-state activity and transient response are the same. Here, we used numerical simulations of a network model of BG to identify the key factors that determine the shape of the transient responses. We show that an aberrant transient response of the SNr in the low-dopamine state involves changes in the direct pathway and the recurrent interactions within the globus pallidus externa (GPe) and between GPe and subthalamic nucleus (STN). However, the connections from D2-type spiny projection neurons (D2-SPN) to GPe are most crucial in shaping the transient response and by restoring them to their healthy level, we could restore the shape of transient response even in low-dopamine state. Finally, we show that the changes in BG that result in aberrant transient response are also sufficient to generate pathologic oscillatory activity in the steady state.
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Humphries MD, Gurney K. Making decisions in the dark basement of the brain: A look back at the GPR model of action selection and the basal ganglia. BIOLOGICAL CYBERNETICS 2021; 115:323-329. [PMID: 34272969 DOI: 10.1007/s00422-021-00887-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 07/06/2021] [Indexed: 06/13/2023]
Abstract
How does your brain decide what you will do next? Over the past few decades compelling evidence has emerged that the basal ganglia, a collection of nuclei in the fore- and mid-brain of all vertebrates, are vital to action selection. Gurney, Prescott, and Redgrave published an influential computational account of this idea in Biological Cybernetics in 2001. Here we take a look back at this pair of papers, outlining the "GPR" model contained therein, the context of that model's development, and the influence it has had over the past twenty years. Tracing its lineage into models and theories still emerging now, we are encouraged that the GPR model is that rare thing, a computational model of a brain circuit whose advances were directly built on by others.
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Predicting Synaptic Connectivity for Large-Scale Microcircuit Simulations Using Snudda. Neuroinformatics 2021; 19:685-701. [PMID: 34282528 PMCID: PMC8566446 DOI: 10.1007/s12021-021-09531-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/09/2021] [Indexed: 12/25/2022]
Abstract
Simulation of large-scale networks of neurons is an important approach to understanding and interpreting experimental data from healthy and diseased brains. Owing to the rapid development of simulation software and the accumulation of quantitative data of different neuronal types, it is possible to predict both computational and dynamical properties of local microcircuits in a ‘bottom-up’ manner. Simulated data from these models can be compared with experiments and ‘top-down’ modelling approaches, successively bridging the scales. Here we describe an open source pipeline, using the software Snudda, for predicting microcircuit connectivity and for setting up simulations using the NEURON simulation environment in a reproducible way. We also illustrate how to further ‘curate’ data on single neuron morphologies acquired from public databases. This model building pipeline was used to set up a first version of a full-scale cellular level model of mouse dorsal striatum. Model components from that work are here used to illustrate the different steps that are needed when modelling subcortical nuclei, such as the basal ganglia.
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11
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Nejad MM, Rotter S, Schmidt R. Basal ganglia and cortical control of thalamic rebound spikes. Eur J Neurosci 2021; 54:4295-4313. [PMID: 33914390 DOI: 10.1111/ejn.15258] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 04/09/2021] [Accepted: 04/24/2021] [Indexed: 12/29/2022]
Abstract
Movement-related decreases in firing rate have been observed in basal ganglia output neurons. They may transmit motor signals to the thalamus, but the effect of these firing rate decreases on downstream neurons in the motor thalamus is not known. One possibility is that they lead to thalamic post-inhibitory rebound spikes. However, it has also been argued that the physiological conditions permitting rebound spiking are pathological, and primarily present in Parkinson's disease. As in Parkinson's disease neural activity becomes pathologically correlated, we investigated the impact of correlations in basal ganglia output on the transmission of motor signals using a Hodgkin-Huxley model of thalamocortical neurons. We found that such correlations disrupt the transmission of motor signals via rebound spikes by decreasing the signal-to-noise ratio and increasing the trial-to-trial variability. We further examined the role of sensory responses in basal ganglia output neurons and the effect of cortical excitation of motor thalamus in modulating rebound spiking. Interestingly, both could either promote or suppress the generation of rebound spikes depending on their timing relative to the motor signal. Finally, we determined parameter regimes, such as levels of excitation, under which rebound spiking is feasible in the model, and confirmed that the conditions for rebound spiking are primarily given in pathological regimes. However, we also identified specific conditions in the model that would allow rebound spiking to occur in healthy animals in a small subset of thalamic neurons. Overall, our model provides novel insights into differences between normal and pathological transmission of motor signals.
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Affiliation(s)
- Mohammadreza Mohagheghi Nejad
- Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany
- Department of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Stefan Rotter
- Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Robert Schmidt
- Department of Psychology, University of Sheffield, Sheffield, UK
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Gandolfi D, Boiani GM, Bigiani A, Mapelli J. Modeling Neurotransmission: Computational Tools to Investigate Neurological Disorders. Int J Mol Sci 2021; 22:4565. [PMID: 33925434 PMCID: PMC8123833 DOI: 10.3390/ijms22094565] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/22/2021] [Accepted: 04/25/2021] [Indexed: 02/06/2023] Open
Abstract
The investigation of synaptic functions remains one of the most fascinating challenges in the field of neuroscience and a large number of experimental methods have been tuned to dissect the mechanisms taking part in the neurotransmission process. Furthermore, the understanding of the insights of neurological disorders originating from alterations in neurotransmission often requires the development of (i) animal models of pathologies, (ii) invasive tools and (iii) targeted pharmacological approaches. In the last decades, additional tools to explore neurological diseases have been provided to the scientific community. A wide range of computational models in fact have been developed to explore the alterations of the mechanisms involved in neurotransmission following the emergence of neurological pathologies. Here, we review some of the advancements in the development of computational methods employed to investigate neuronal circuits with a particular focus on the application to the most diffuse neurological disorders.
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Affiliation(s)
- Daniela Gandolfi
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy; (D.G.); (G.M.B.); (A.B.)
| | - Giulia Maria Boiani
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy; (D.G.); (G.M.B.); (A.B.)
| | - Albertino Bigiani
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy; (D.G.); (G.M.B.); (A.B.)
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy
| | - Jonathan Mapelli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy; (D.G.); (G.M.B.); (A.B.)
- Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy
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Gorodetski L, Loewenstern Y, Faynveitz A, Bar-Gad I, Blackwell KT, Korngreen A. Endocannabinoids and Dopamine Balance Basal Ganglia Output. Front Cell Neurosci 2021; 15:639082. [PMID: 33815062 PMCID: PMC8010132 DOI: 10.3389/fncel.2021.639082] [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: 12/08/2020] [Accepted: 02/18/2021] [Indexed: 12/04/2022] Open
Abstract
The entopeduncular nucleus is one of the basal ganglia's output nuclei, thereby controlling basal ganglia information processing. Entopeduncular nucleus neurons integrate GABAergic inputs from the Striatum and the globus pallidus, together with glutamatergic inputs from the subthalamic nucleus. We show that endocannabinoids and dopamine interact to modulate the long-term plasticity of all these primary afferents to the entopeduncular nucleus. Our results suggest that the interplay between dopamine and endocannabinoids determines the balance between direct pathway (striatum) and indirect pathway (globus pallidus) in entopeduncular nucleus output. Furthermore, we demonstrate that, despite the lack of axon collaterals, information is transferred between neighboring neurons in the entopeduncular nucleus via endocannabinoid diffusion. These results transform the prevailing view of the entopeduncular nucleus as a feedforward “relay” nucleus to an intricate control unit, which may play a vital role in the process of action selection.
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Affiliation(s)
- Lilach Gorodetski
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel
| | - Yocheved Loewenstern
- The Leslie and Susan Gonda Interdisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
| | - Anna Faynveitz
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel
| | - Izhar Bar-Gad
- The Leslie and Susan Gonda Interdisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
| | - Kim T Blackwell
- Department of Bioengineering, George Mason University, Fairfax, VA, United States
| | - Alon Korngreen
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan, Israel.,The Leslie and Susan Gonda Interdisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
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14
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Azevedo Carvalho N, Contassot-Vivier S, Buhry L, Martinez D. Simulation of Large Scale Neural Models With Event-Driven Connectivity Generation. Front Neuroinform 2020; 14:522000. [PMID: 33154719 PMCID: PMC7591773 DOI: 10.3389/fninf.2020.522000] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 08/31/2020] [Indexed: 11/15/2022] Open
Abstract
Accurate simulations of brain structures is a major problem in neuroscience. Many works are dedicated to design better models or to develop more efficient simulation schemes. In this paper, we propose a hybrid simulation scheme that combines time-stepping second-order integration of Hodgkin-Huxley (HH) type neurons with event-driven updating of the synaptic currents. As the HH model is a continuous model, there is no explicit spike events. Thus, in order to preserve the accuracy of the integration method, a spike detection algorithm is developed that accurately determines spike times. This approach allows us to regenerate the outgoing connections at each event, thereby avoiding the storage of the connectivity. Consequently, memory consumption is significantly reduced while preserving execution time and accuracy of the simulations, especially the spike times of detailed point neuron models. The efficiency of the method, implemented in the SiReNe software1, is demonstrated by the simulation of a striatum model which consists of more than 106 neurons and 108 synapses (each neuron has a fan-out of 504 post-synaptic neurons), under normal and Parkinson's conditions.
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Affiliation(s)
| | | | - Laure Buhry
- Université de Lorraine, CNRS, Inria, LORIA, Nancy, France
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15
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Grillner S, Robertson B, Kotaleski JH. Basal Ganglia—A Motion Perspective. Compr Physiol 2020; 10:1241-1275. [DOI: 10.1002/cphy.c190045] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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16
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Maith O, Villagrasa Escudero F, Dinkelbach HÜ, Baladron J, Horn A, Irmen F, Kühn AA, Hamker FH. A computational model‐based analysis of basal ganglia pathway changes in Parkinson’s disease inferred from resting‐state fMRI. Eur J Neurosci 2020; 53:2278-2295. [DOI: 10.1111/ejn.14868] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 06/04/2020] [Accepted: 06/08/2020] [Indexed: 12/21/2022]
Affiliation(s)
- Oliver Maith
- Department of Computer Science Chemnitz University of Technology Chemnitz Germany
| | | | - Helge Ülo Dinkelbach
- Department of Computer Science Chemnitz University of Technology Chemnitz Germany
| | - Javier Baladron
- Department of Computer Science Chemnitz University of Technology Chemnitz Germany
| | - Andreas Horn
- Movement Disorders and Neuromodulation Unit, Department for Neurology Charité–University Medicine Berlin Berlin Germany
| | - Friederike Irmen
- Movement Disorders and Neuromodulation Unit, Department for Neurology Charité–University Medicine Berlin Berlin Germany
| | - Andrea A. Kühn
- Movement Disorders and Neuromodulation Unit, Department for Neurology Charité–University Medicine Berlin Berlin Germany
| | - Fred H. Hamker
- Department of Computer Science Chemnitz University of Technology Chemnitz Germany
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17
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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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18
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Petersson P, Halje P, Cenci MA. Significance and Translational Value of High-Frequency Cortico-Basal Ganglia Oscillations in Parkinson's Disease. JOURNAL OF PARKINSONS DISEASE 2020; 9:183-196. [PMID: 30594935 PMCID: PMC6484276 DOI: 10.3233/jpd-181480] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The mechanisms and significance of basal ganglia oscillations is a fundamental research question engaging both clinical and basic investigators. In Parkinson’s disease (PD), neural activity in basal ganglia nuclei is characterized by oscillatory patterns that are believed to disrupt the dynamic processing of movement-related information and thus generate motor symptoms. Beta-band oscillations associated with hypokinetic states have been reviewed in several excellent previous articles. Here we focus on faster oscillatory phenomena that have been reported in association with a diverse range of motor states. We review the occurrence of different types of fast oscillations and the evidence supporting their pathophysiological role. We also provide a general discussion on the definition, possible mechanisms, and translational value of synchronized oscillations of different frequencies in cortico-basal ganglia structures. Revealing how oscillatory phenomena are caused and spread in cortico-basal ganglia-thalamocortical networks will offer a key to unlock the neural codes of both motor and non-motor symptoms in PD. In preclinical therapeutic research, recording of oscillatory neural activities holds the promise to unravel mechanisms of action of current and future treatments.
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Affiliation(s)
- Per Petersson
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden.,Department of Experimental Medical Science, The Group for Integrative Neurophysiology and Neurotechnology, Lund University, Lund, Sweden
| | - Pär Halje
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden.,Department of Experimental Medical Science, The Group for Integrative Neurophysiology and Neurotechnology, Lund University, Lund, Sweden
| | - M Angela Cenci
- Department of Experimental Medical Science, Basal Ganglia Pathophysiology Unit, Lund University, Lund, Sweden
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19
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Hjorth JJJ, Kozlov A, Carannante I, Frost Nylén J, Lindroos R, Johansson Y, Tokarska A, Dorst MC, Suryanarayana SM, Silberberg G, Hellgren Kotaleski J, Grillner S. The microcircuits of striatum in silico. Proc Natl Acad Sci U S A 2020; 117:9554-9565. [PMID: 32321828 PMCID: PMC7197017 DOI: 10.1073/pnas.2000671117] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
The basal ganglia play an important role in decision making and selection of action primarily based on input from cortex, thalamus, and the dopamine system. Their main input structure, striatum, is central to this process. It consists of two types of projection neurons, together representing 95% of the neurons, and 5% of interneurons, among which are the cholinergic, fast-spiking, and low threshold-spiking subtypes. The membrane properties, soma-dendritic shape, and intrastriatal and extrastriatal synaptic interactions of these neurons are quite well described in the mouse, and therefore they can be simulated in sufficient detail to capture their intrinsic properties, as well as the connectivity. We focus on simulation at the striatal cellular/microcircuit level, in which the molecular/subcellular and systems levels meet. We present a nearly full-scale model of the mouse striatum using available data on synaptic connectivity, cellular morphology, and electrophysiological properties to create a microcircuit mimicking the real network. A striatal volume is populated with reconstructed neuronal morphologies with appropriate cell densities, and then we connect neurons together based on appositions between neurites as possible synapses and constrain them further with available connectivity data. Moreover, we simulate a subset of the striatum involving 10,000 neurons, with input from cortex, thalamus, and the dopamine system, as a proof of principle. Simulation at this biological scale should serve as an invaluable tool to understand the mode of operation of this complex structure. This platform will be updated with new data and expanded to simulate the entire striatum.
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Affiliation(s)
- J J Johannes Hjorth
- Science for Life Laboratory, School of Electrical Engeneering and Computer Science, Royal Institute of Technology, SE-10044 Stockholm, Sweden
| | - Alexander Kozlov
- Science for Life Laboratory, School of Electrical Engeneering and Computer Science, Royal Institute of Technology, SE-10044 Stockholm, Sweden
- Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm
| | - Ilaria Carannante
- Science for Life Laboratory, School of Electrical Engeneering and Computer Science, Royal Institute of Technology, SE-10044 Stockholm, Sweden
| | | | - Robert Lindroos
- Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm
| | - Yvonne Johansson
- Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm
| | - Anna Tokarska
- Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm
| | - Matthijs C Dorst
- Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm
| | | | - Gilad Silberberg
- Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm
| | - Jeanette Hellgren Kotaleski
- Science for Life Laboratory, School of Electrical Engeneering and Computer Science, Royal Institute of Technology, SE-10044 Stockholm, Sweden;
- Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm
| | - Sten Grillner
- Department of Neuroscience, Karolinska Institutet, SE-17165 Stockholm
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20
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Mulcahy G, Atwood B, Kuznetsov A. Basal ganglia role in learning rewarded actions and executing previously learned choices: Healthy and diseased states. PLoS One 2020; 15:e0228081. [PMID: 32040519 PMCID: PMC7010262 DOI: 10.1371/journal.pone.0228081] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Accepted: 01/07/2020] [Indexed: 01/06/2023] Open
Abstract
The basal ganglia (BG) is a collection of nuclei located deep beneath the cerebral cortex that is involved in learning and selection of rewarded actions. Here, we analyzed BG mechanisms that enable these functions. We implemented a rate model of a BG-thalamo-cortical loop and simulated its performance in a standard action selection task. We have shown that potentiation of corticostriatal synapses enables learning of a rewarded option. However, these synapses became redundant later as direct connections between prefrontal and premotor cortices (PFC-PMC) were potentiated by Hebbian learning. After we switched the reward to the previously unrewarded option (reversal), the BG was again responsible for switching to the new option. Due to the potentiated direct cortical connections, the system was biased to the previously rewarded choice, and establishing the new choice required a greater number of trials. Guided by physiological research, we then modified our model to reproduce pathological states of mild Parkinson's and Huntington's diseases. We found that in the Parkinsonian state PMC activity levels become extremely variable, which is caused by oscillations arising in the BG-thalamo-cortical loop. The model reproduced severe impairment of learning and predicted that this is caused by these oscillations as well as a reduced reward prediction signal. In the Huntington state, the potentiation of the PFC-PMC connections produced better learning, but altered BG output disrupted expression of the rewarded choices. This resulted in random switching between rewarded and unrewarded choices resembling an exploratory phase that never ended. Along with other computational studies, our results further reconcile the apparent contradiction between the critical involvement of the BG in execution of previously learned actions and yet no impairment of these actions after BG output is ablated by lesions or deep brain stimulation. We predict that the cortico-BG-thalamo-cortical loop conforms to previously learned choice in healthy conditions, but impedes those choices in disease states.
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Affiliation(s)
- Garrett Mulcahy
- Department of Mathematics, Purdue University, West Lafayette, Indiana, United States of America
| | - Brady Atwood
- Departments of Psychiatry and Pharmacology & Toxicology, IUSM, Indianapolis, Indiana, United States of America
- Indiana Alcohol Research Center, IUSM, Indianapolis, Indiana, United States of America
| | - Alexey Kuznetsov
- Indiana Alcohol Research Center, IUSM, Indianapolis, Indiana, United States of America
- Department of Mathematical Sciences, IUPUI, Indianapolis, Indiana, United States of America
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21
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Jáidar O, Carrillo-Reid L, Nakano Y, Lopez-Huerta VG, Hernandez-Cruz A, Bargas J, Garcia-Munoz M, Arbuthnott GW. Synchronized activation of striatal direct and indirect pathways underlies the behavior in unilateral dopamine-depleted mice. Eur J Neurosci 2019; 49:1512-1528. [PMID: 30633847 PMCID: PMC6767564 DOI: 10.1111/ejn.14344] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 12/17/2018] [Accepted: 12/25/2018] [Indexed: 11/27/2022]
Abstract
For more than three decades it has been known, that striatal neurons become hyperactive after the loss of dopamine input, but the involvement of dopamine (DA) D1‐ or D2‐receptor‐expressing neurons has only been demonstrated indirectly. By recording neuronal activity using fluorescent calcium indicators in D1 or D2 eGFP‐expressing mice, we showed that following dopamine depletion, both types of striatal output neurons are involved in the large increase in neuronal activity generating a characteristic cell assembly of particular neurons that dominate the pattern. When we expressed channelrhodopsin in all the output neurons, light activation in freely moving animals, caused turning like that following dopamine loss. However, if the light stimulation was patterned in pulses the animals circled in the other direction. To explore the neuronal participation during this stimulation we infected normal mice with channelrhodopsin and calcium indicator in striatal output neurons. In slices made from these animals, continuous light stimulation for 15 s induced many cells to be active together and a particular dominant group of neurons, whereas light in patterned pulses activated fewer cells in more variable groups. These results suggest that the simultaneous activity of a large dominant group of striatal output neurons is intimately associated with parkinsonian symptoms.
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Affiliation(s)
- Omar Jáidar
- Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Luis Carrillo-Reid
- Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | - Yoko Nakano
- Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | | | | | - José Bargas
- Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
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22
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Cortico-Striatal Cross-Frequency Coupling and Gamma Genesis Disruptions in Huntington's Disease Mouse and Computational Models. eNeuro 2018; 5:eN-NWR-0210-18. [PMID: 30627632 PMCID: PMC6325534 DOI: 10.1523/eneuro.0210-18.2018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 10/19/2018] [Accepted: 11/12/2018] [Indexed: 12/16/2022] Open
Abstract
Abnormal gamma band power across cortex and striatum is an important phenotype of Huntington's disease (HD) in both patients and animal models, but neither the origin nor the functional relevance of this phenotype is well understood. Here, we analyzed local field potential (LFP) activity in freely behaving, symptomatic R6/2 and Q175 mouse models and corresponding wild-type (WT) controls. We focused on periods of quiet rest, which show strong γ activity in HD mice. Simultaneous recording from motor cortex and its target area in dorsal striatum in the R6/2 model revealed exaggerated functional coupling over that observed in WT between the phase of delta frequencies (1-4 Hz) in cortex and striatum and striatal amplitude modulation of low γ frequencies (25-55 Hz; i.e., phase-amplitude coupling, PAC), but no evidence that abnormal cortical activity alone can account for the increase in striatal γ power. Both HD mouse models had stronger coupling of γ amplitude to δ phase and more unimodal phase distributions than their WT counterparts. To assess the possible role of striatal fast-spiking interneurons (FSIs) in these phenomena, we developed a computational model based on additional striatal recordings from Q175 mice. Changes in peak γ frequency and power ratio were readily reproduced by our computational model, accounting for several experimental findings reported in the literature. Our results suggest that HD is characterized by both a reorganization of cortico-striatal drive and specific population changes related to intrastriatal synaptic coupling.
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23
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Humphries MD, Obeso JA, Dreyer JK. Insights into Parkinson's disease from computational models of the basal ganglia. J Neurol Neurosurg Psychiatry 2018; 89:1181-1188. [PMID: 29666208 PMCID: PMC6124639 DOI: 10.1136/jnnp-2017-315922] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Revised: 03/20/2018] [Accepted: 03/21/2018] [Indexed: 12/28/2022]
Abstract
Movement disorders arise from the complex interplay of multiple changes to neural circuits. Successful treatments for these disorders could interact with these complex changes in myriad ways, and as a consequence their mechanisms of action and their amelioration of symptoms are incompletely understood. Using Parkinson's disease as a case study, we review here how computational models are a crucial tool for taming this complexity, across causative mechanisms, consequent neural dynamics and treatments. For mechanisms, we review models that capture the effects of losing dopamine on basal ganglia function; for dynamics, we discuss models that have transformed our understanding of how beta-band (15-30 Hz) oscillations arise in the parkinsonian basal ganglia. For treatments, we touch on the breadth of computational modelling work trying to understand the therapeutic actions of deep brain stimulation. Collectively, models from across all levels of description are providing a compelling account of the causes, symptoms and treatments for Parkinson's disease.
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Affiliation(s)
- Mark D Humphries
- Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, UK.,School of Psychology, University of Nottingham, Nottingham, UK
| | - Jose Angel Obeso
- HM-CINAC, Hospital Puerta del Sur, Mostoles, CEU-San Pablo University, Madrid, Spain
| | - Jakob Kisbye Dreyer
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.,Department of Bioinformatics, H Lundbeck A/S, Valby, Denmark
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24
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Suryanarayana SM, Hellgren Kotaleski J, Grillner S, Gurney KN. Roles for globus pallidus externa revealed in a computational model of action selection in the basal ganglia. Neural Netw 2018; 109:113-136. [PMID: 30414556 DOI: 10.1016/j.neunet.2018.10.003] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 08/28/2018] [Accepted: 10/09/2018] [Indexed: 01/12/2023]
Abstract
The basal ganglia are considered vital to action selection - a hypothesis supported by several biologically plausible computational models. Of the several subnuclei of the basal ganglia, the globus pallidus externa (GPe) has been thought of largely as a relay nucleus, and its intrinsic connectivity has not been incorporated in significant detail, in any model thus far. Here, we incorporate newly revealed subgroups of neurons within the GPe into an existing computational model of the basal ganglia, and investigate their role in action selection. Three main results ensued. First, using previously used metrics for selection, the new extended connectivity improved the action selection performance of the model. Second, low frequency theta oscillations were observed in the subpopulation of the GPe (the TA or 'arkypallidal' neurons) which project exclusively to the striatum. These oscillations were suppressed by increased dopamine activity - revealing a possible link with symptoms of Parkinson's disease. Third, a new phenomenon was observed in which the usual monotonic relationship between input to the basal ganglia and its output within an action 'channel' was, under some circumstances, reversed. Thus, at high levels of input, further increase of this input to the channel could cause an increase of the corresponding output rather than the more usually observed decrease. Moreover, this phenomenon was associated with the prevention of multiple channel selection, thereby assisting in optimal action selection. Examination of the mechanistic origin of our results showed the so-called 'prototypical' GPe neurons to be the principal subpopulation influencing action selection. They control the striatum via the arkypallidal neurons and are also able to regulate the output nuclei directly. Taken together, our results highlight the role of the GPe as a major control hub of the basal ganglia, and provide a mechanistic account for its control function.
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Affiliation(s)
| | - Jeanette Hellgren Kotaleski
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden; Science for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.
| | - Sten Grillner
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Kevin N Gurney
- Department of Psychology, University of Sheffield, Sheffield, UK.
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25
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Tian J, Yan Y, Xi W, Zhou R, Lou H, Duan S, Chen JF, Zhang B. Optogenetic Stimulation of GABAergic Neurons in the Globus Pallidus Produces Hyperkinesia. Front Behav Neurosci 2018; 12:185. [PMID: 30210317 PMCID: PMC6119815 DOI: 10.3389/fnbeh.2018.00185] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2017] [Accepted: 08/02/2018] [Indexed: 01/19/2023] Open
Abstract
The globus pallidus (GP) is emerging as a critical locus of basal ganglia control of motor activity, but the exact role of GABAergic GP neurons remain to be defined. By targeted expression of channelrhodopsin 2 (ChR2) in GABAergic neurons using the VGAT-ChR2-EYFP transgenic mice, we showed that optogenetic stimulation of GABAergic neurons in the right GP produced hyperkinesia. Optogenetic stimulation of GABAergic GP neurons increased c-Fos-positive cells in GP, M1 cortex, and caudate-putamen (CPu), and decreased c-Fos-positive cells in entopeduncular nucleus (EPN), compared to the contralateral hemisphere. In agreement with the canonical basal ganglia model. Furthermore, we delivered AAV-CaMKIIα-ChR2-mCherry virus to the excitatory neurons of the subthalamic nucleus (STN) and selectively stimulated glutamatergic afferent fibers from the STN onto the GP. This optogenetic stimulation produced abnormal movements, similar to the behaviors that observed in the VGAT-ChR2-EYFP transgenic mice. Meanwhile, we found that the c-Fos expression pattern in the GP, M1, STN, EPN, and CPu produced by optogenetic activation of glutamatergic afferent fibers from the STN in GP was similar to the c-Fos expression pattern in the VGAT-ChR2-EYFP transgenic mice. Taken together, our results suggest that excess GP GABAergic neurons activity could be the neural substrate of abnormal involuntary movements in hyperkinetic movement disorders. The neural circuitry underlying the abnormal involuntary movements is associated with excessive GP, M1, CPu activity, and reduced EPN activity. Inhibition of GP GABAergic neurons represents new treatment targets for hyperkinetic movement disorder.
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Affiliation(s)
- Jun Tian
- Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yaping Yan
- Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wang Xi
- Department of Neurobiology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Rui Zhou
- Department of Neurobiology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Huifang Lou
- Department of Neurobiology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Shumin Duan
- Department of Neurobiology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jiang Fan Chen
- School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, China
| | - Baorong Zhang
- Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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26
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Bahuguna J, Weidel P, Morrison A. Exploring the role of striatal D1 and D2 medium spiny neurons in action selection using a virtual robotic framework. Eur J Neurosci 2018; 49:737-753. [PMID: 29917291 PMCID: PMC6585768 DOI: 10.1111/ejn.14021] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 05/15/2018] [Accepted: 06/06/2018] [Indexed: 11/30/2022]
Abstract
The basal ganglia have been hypothesized to be involved in action selection, i.e. resolving competition between simultaneously activated motor programs. It has been shown that the direct pathway facilitates action execution whereas the indirect pathway inhibits it. However, as the pathways are both active during an action, it remains unclear whether their role is co-operative or competitive. In order to investigate this issue, we developed a striatal model consisting of D1 and D2 medium spiny neurons (MSNs) and interfaced it to a simulated robot moving in an environment. We demonstrate that this model is able to reproduce key behavioral features of several experiments involving optogenetic manipulation of the striatum, such as freezing and ambulation. We then investigate the interaction of D1- and D2-MSNs. We find that their fundamental relationship is co-operative within a channel and competitive between channels; this turns out to be crucial for action selection. However, individual pairs of D1- and D2-MSNs may exhibit predominantly competition or co-operation depending on their distance, and D1- and D2-MSNs population activity can alternate between co-operation and competition modes during a stimulation. Additionally, our results show that D2-D2 connectivity between channels is necessary for effective resolution of competition; in its absence, a conflict of two motor programs typically results in neither being selected.
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Affiliation(s)
- Jyotika Bahuguna
- Institute for Advanced Simulation (IAS-6), Institute of Neuroscience and Medicine (INM-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich Research Centre, Jülich, 52428, Germany
| | - Philipp Weidel
- Institute for Advanced Simulation (IAS-6), Institute of Neuroscience and Medicine (INM-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich Research Centre, Jülich, 52428, Germany
| | - Abigail Morrison
- Institute for Advanced Simulation (IAS-6), Institute of Neuroscience and Medicine (INM-6) and JARA Institute Brain Structure-Function Relationships (JBI-1/INM-10), Jülich Research Centre, Jülich, 52428, Germany.,Institute for Cognitive Neurosciences, Ruhr University, Bochum, Germany
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27
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Lindroos R, Dorst MC, Du K, Filipović M, Keller D, Ketzef M, Kozlov AK, Kumar A, Lindahl M, Nair AG, Pérez-Fernández J, Grillner S, Silberberg G, Hellgren Kotaleski J. Basal Ganglia Neuromodulation Over Multiple Temporal and Structural Scales-Simulations of Direct Pathway MSNs Investigate the Fast Onset of Dopaminergic Effects and Predict the Role of Kv4.2. Front Neural Circuits 2018; 12:3. [PMID: 29467627 PMCID: PMC5808142 DOI: 10.3389/fncir.2018.00003] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 01/09/2018] [Indexed: 12/16/2022] Open
Abstract
The basal ganglia are involved in the motivational and habitual control of motor and cognitive behaviors. Striatum, the largest basal ganglia input stage, integrates cortical and thalamic inputs in functionally segregated cortico-basal ganglia-thalamic loops, and in addition the basal ganglia output nuclei control targets in the brainstem. Striatal function depends on the balance between the direct pathway medium spiny neurons (D1-MSNs) that express D1 dopamine receptors and the indirect pathway MSNs that express D2 dopamine receptors. The striatal microstructure is also divided into striosomes and matrix compartments, based on the differential expression of several proteins. Dopaminergic afferents from the midbrain and local cholinergic interneurons play crucial roles for basal ganglia function, and striatal signaling via the striosomes in turn regulates the midbrain dopaminergic system directly and via the lateral habenula. Consequently, abnormal functions of the basal ganglia neuromodulatory system underlie many neurological and psychiatric disorders. Neuromodulation acts on multiple structural levels, ranging from the subcellular level to behavior, both in health and disease. For example, neuromodulation affects membrane excitability and controls synaptic plasticity and thus learning in the basal ganglia. However, it is not clear on what time scales these different effects are implemented. Phosphorylation of ion channels and the resulting membrane effects are typically studied over minutes while it has been shown that neuromodulation can affect behavior within a few hundred milliseconds. So how do these seemingly contradictory effects fit together? Here we first briefly review neuromodulation of the basal ganglia, with a focus on dopamine. We furthermore use biophysically detailed multi-compartmental models to integrate experimental data regarding dopaminergic effects on individual membrane conductances with the aim to explain the resulting cellular level dopaminergic effects. In particular we predict dopaminergic effects on Kv4.2 in D1-MSNs. Finally, we also explore dynamical aspects of the onset of neuromodulation effects in multi-scale computational models combining biochemical signaling cascades and multi-compartmental neuron models.
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Affiliation(s)
- Robert Lindroos
- Department of Neuroscience, Nobel Institute for Neurophysiology, Stockholm, Sweden
| | - Matthijs C. Dorst
- Department of Neuroscience, Nobel Institute for Neurophysiology, Stockholm, Sweden
| | - Kai Du
- Department of Neuroscience, Nobel Institute for Neurophysiology, Stockholm, Sweden
| | - Marko Filipović
- Bernstein Center Freiburg, University of Freiburg, Freiburg im Breisgau, Germany
| | - Daniel Keller
- Blue Brain Project, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Maya Ketzef
- Department of Neuroscience, Nobel Institute for Neurophysiology, Stockholm, Sweden
| | - Alexander K. Kozlov
- Science for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Solna, Sweden
| | - Arvind Kumar
- Bernstein Center Freiburg, University of Freiburg, Freiburg im Breisgau, Germany
- Department Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Mikael Lindahl
- Science for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Solna, Sweden
| | - Anu G. Nair
- Science for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Solna, Sweden
| | - Juan Pérez-Fernández
- Department of Neuroscience, Nobel Institute for Neurophysiology, Stockholm, Sweden
| | - Sten Grillner
- Department of Neuroscience, Nobel Institute for Neurophysiology, Stockholm, Sweden
| | - Gilad Silberberg
- Department of Neuroscience, Nobel Institute for Neurophysiology, Stockholm, Sweden
| | - Jeanette Hellgren Kotaleski
- Department of Neuroscience, Nobel Institute for Neurophysiology, Stockholm, Sweden
- Science for Life Laboratory, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Solna, Sweden
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Sharott A, Vinciati F, Nakamura KC, Magill PJ. A Population of Indirect Pathway Striatal Projection Neurons Is Selectively Entrained to Parkinsonian Beta Oscillations. J Neurosci 2017; 37:9977-9998. [PMID: 28847810 PMCID: PMC5637121 DOI: 10.1523/jneurosci.0658-17.2017] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2017] [Revised: 07/18/2017] [Accepted: 07/29/2017] [Indexed: 01/22/2023] Open
Abstract
Classical schemes of basal ganglia organization posit that parkinsonian movement difficulties presenting after striatal dopamine depletion stem from the disproportionate firing rates of spiny projection neurons (SPNs) therein. There remains, however, a pressing need to elucidate striatal SPN firing in the context of the synchronized network oscillations that are abnormally exaggerated in cortical-basal ganglia circuits in parkinsonism. To address this, we recorded unit activities in the dorsal striatum of dopamine-intact and dopamine-depleted rats during two brain states, respectively defined by cortical slow-wave activity (SWA) and activation. Dopamine depletion escalated striatal net output but had contrasting effects on "direct pathway" SPNs (dSPNs) and "indirect pathway" SPNs (iSPNs); their firing rates became imbalanced, and they disparately engaged in network oscillations. Disturbed striatal activity dynamics relating to the slow (∼1 Hz) oscillations prevalent during SWA partly generalized to the exaggerated beta-frequency (15-30 Hz) oscillations arising during cortical activation. In both cases, SPNs exhibited higher incidences of phase-locked firing to ongoing cortical oscillations, and SPN ensembles showed higher levels of rhythmic correlated firing, after dopamine depletion. Importantly, in dopamine-depleted striatum, a widespread population of iSPNs, which often displayed excessive firing rates and aberrant phase-locked firing to cortical beta oscillations, preferentially and excessively synchronized their firing at beta frequencies. Conversely, dSPNs were neither hyperactive nor synchronized to a large extent during cortical activation. These data collectively demonstrate a cell type-selective entrainment of SPN firing to parkinsonian beta oscillations. We conclude that a population of overactive, excessively synchronized iSPNs could orchestrate these pathological rhythms in basal ganglia circuits.SIGNIFICANCE STATEMENT Chronic depletion of dopamine from the striatum, a part of the basal ganglia, causes some symptoms of Parkinson's disease. Here, we elucidate how dopamine depletion alters striatal neuron firing in vivo, with an emphasis on defining whether and how spiny projection neurons (SPNs) engage in the synchronized beta-frequency (15-30 Hz) oscillations that become pathologically exaggerated throughout basal ganglia circuits in parkinsonism. We discovered that a select population of so-called "indirect pathway" SPNs not only fire at abnormally high rates, but are also particularly prone to being recruited to exaggerated beta oscillations. Our results provide an important link between two complementary theories that explain the presentation of disease symptoms on the basis of changes in firing rate or firing synchronization/rhythmicity.
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Affiliation(s)
- Andrew Sharott
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom, and
| | - Federica Vinciati
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom, and
| | - Kouichi C Nakamura
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom, and
| | - Peter J Magill
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom, and
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford OX1 3QX, United Kingdom
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29
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Bahuguna J, Tetzlaff T, Kumar A, Hellgren Kotaleski J, Morrison A. Homologous Basal Ganglia Network Models in Physiological and Parkinsonian Conditions. Front Comput Neurosci 2017; 11:79. [PMID: 28878643 PMCID: PMC5572265 DOI: 10.3389/fncom.2017.00079] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Accepted: 08/04/2017] [Indexed: 01/19/2023] Open
Abstract
The classical model of basal ganglia has been refined in recent years with discoveries of subpopulations within a nucleus and previously unknown projections. One such discovery is the presence of subpopulations of arkypallidal and prototypical neurons in external globus pallidus, which was previously considered to be a primarily homogeneous nucleus. Developing a computational model of these multiple interconnected nuclei is challenging, because the strengths of the connections are largely unknown. We therefore use a genetic algorithm to search for the unknown connectivity parameters in a firing rate model. We apply a binary cost function derived from empirical firing rate and phase relationship data for the physiological and Parkinsonian conditions. Our approach generates ensembles of over 1,000 configurations, or homologies, for each condition, with broad distributions for many of the parameter values and overlap between the two conditions. However, the resulting effective weights of connections from or to prototypical and arkypallidal neurons are consistent with the experimental data. We investigate the significance of the weight variability by manipulating the parameters individually and cumulatively, and conclude that the correlation observed between the parameters is necessary for generating the dynamics of the two conditions. We then investigate the response of the networks to a transient cortical stimulus, and demonstrate that networks classified as physiological effectively suppress activity in the internal globus pallidus, and are not susceptible to oscillations, whereas parkinsonian networks show the opposite tendency. Thus, we conclude that the rates and phase relationships observed in the globus pallidus are predictive of experimentally observed higher level dynamical features of the physiological and parkinsonian basal ganglia, and that the multiplicity of solutions generated by our method may well be indicative of a natural diversity in basal ganglia networks. We propose that our approach of generating and analyzing an ensemble of multiple solutions to an underdetermined network model provides greater confidence in its predictions than those derived from a unique solution, and that projecting such homologous networks on a lower dimensional space of sensibly chosen dynamical features gives a better chance than a purely structural analysis at understanding complex pathologies such as Parkinson's disease.
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Affiliation(s)
- Jyotika Bahuguna
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), JARA Brain Institute I, Jülich Research CenterJülich, Germany
| | - Tom Tetzlaff
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), JARA Brain Institute I, Jülich Research CenterJülich, Germany
| | - Arvind Kumar
- Computational Science and Technology, School of Computer Science and Communication, KTH Royal Institute of TechnologyStockholm, Sweden.,Faculty of Biology, Bernstein Center Freiburg, University of FreiburgFreiburg, Germany
| | - Jeanette Hellgren Kotaleski
- Computational Science and Technology, School of Computer Science and Communication, KTH Royal Institute of TechnologyStockholm, Sweden
| | - Abigail Morrison
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), JARA Brain Institute I, Jülich Research CenterJülich, Germany.,Faculty of Biology, Bernstein Center Freiburg, University of FreiburgFreiburg, Germany.,Institute for Cognitive Neurosciences, Ruhr UniversityBochum, Germany
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30
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Chen M, Guo D, Xia Y, Yao D. Control of Absence Seizures by the Thalamic Feed-Forward Inhibition. Front Comput Neurosci 2017; 11:31. [PMID: 28491031 PMCID: PMC5405150 DOI: 10.3389/fncom.2017.00031] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 04/10/2017] [Indexed: 11/17/2022] Open
Abstract
As a subtype of idiopathic generalized epilepsies, absence epilepsy is believed to be caused by pathological interactions within the corticothalamic (CT) system. Using a biophysical mean-field model of the CT system, we demonstrate here that the feed-forward inhibition (FFI) in thalamus, i.e., the pathway from the cerebral cortex (Ctx) to the thalamic reticular nucleus (TRN) and then to the specific relay nuclei (SRN) of thalamus that are also directly driven by the Ctx, may participate in controlling absence seizures. In particular, we show that increasing the excitatory Ctx-TRN coupling strength can significantly suppress typical electrical activities during absence seizures. Further, investigation demonstrates that the GABAA- and GABAB-mediated inhibitions in the TRN-SRN pathway perform combination roles in the regulation of absence seizures. Overall, these results may provide an insightful mechanistic understanding of how the thalamic FFI serves as an intrinsic regulator contributing to the control of absence seizures.
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Affiliation(s)
- Mingming Chen
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China
| | - Daqing Guo
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China.,Center for Information in BioMedicine, University of Electronic Science and Technology of ChinaChengdu, China
| | - Yang Xia
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China.,Center for Information in BioMedicine, University of Electronic Science and Technology of ChinaChengdu, China
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China.,Center for Information in BioMedicine, University of Electronic Science and Technology of ChinaChengdu, China
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