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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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Zang J, Liu S, Helson P, Kumar A. Structural constraints on the emergence of oscillations in multi-population neural networks. eLife 2024; 12:RP88777. [PMID: 38477669 DOI: 10.7554/elife.88777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024] Open
Abstract
Oscillations arise in many real-world systems and are associated with both functional and dysfunctional states. Whether a network can oscillate can be estimated if we know the strength of interaction between nodes. But in real-world networks (in particular in biological networks) it is usually not possible to know the exact connection weights. Therefore, it is important to determine the structural properties of a network necessary to generate oscillations. Here, we provide a proof that uses dynamical system theory to prove that an odd number of inhibitory nodes and strong enough connections are necessary to generate oscillations in a single cycle threshold-linear network. We illustrate these analytical results in a biologically plausible network with either firing-rate based or spiking neurons. Our work provides structural properties necessary to generate oscillations in a network. We use this knowledge to reconcile recent experimental findings about oscillations in basal ganglia with classical findings.
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Affiliation(s)
- Jie Zang
- School of Mathematics, South China University of Technology, Guangzhou, China
- Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Shenquan Liu
- School of Mathematics, South China University of Technology, Guangzhou, China
| | - Pascal Helson
- Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Arvind Kumar
- Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
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Azizpour Lindi S, Mallet NP, Leblois A. Synaptic Changes in Pallidostriatal Circuits Observed in the Parkinsonian Model Triggers Abnormal Beta Synchrony with Accurate Spatio-temporal Properties across the Basal Ganglia. J Neurosci 2024; 44:e0419232023. [PMID: 38123981 PMCID: PMC10903930 DOI: 10.1523/jneurosci.0419-23.2023] [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: 03/06/2023] [Revised: 11/27/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023] Open
Abstract
Excessive oscillatory activity across basal ganglia (BG) nuclei in the β frequencies (12-30 Hz) is a hallmark of Parkinson's disease (PD). While the link between oscillations and symptoms remains debated, exaggerated β oscillations constitute an important biomarker for therapeutic effectiveness in PD. The neuronal mechanisms of β-oscillation generation however remain unknown. Many existing models rely on a central role of the subthalamic nucleus (STN) or cortical inputs to BG. Contrarily, neural recordings and optogenetic manipulations in normal and parkinsonian rats recently highlighted the central role of the external pallidum (GPe) in abnormal β oscillations, while showing that the integrity of STN or motor cortex is not required. Here, we evaluate the mechanisms for the generation of abnormal β oscillations in a BG network model where neuronal and synaptic time constants, connectivity, and firing rate distributions are strongly constrained by experimental data. Guided by a mean-field approach, we show in a spiking neural network that several BG sub-circuits can drive oscillations. Strong recurrent STN-GPe connections or collateral intra-GPe connections drive γ oscillations (>40 Hz), whereas strong pallidostriatal loops drive low-β (10-15 Hz) oscillations. We show that pathophysiological strengthening of striatal and pallidal synapses following dopamine depletion leads to the emergence of synchronized oscillatory activity in the mid-β range with spike-phase relationships between BG neuronal populations in-line with experiments. Furthermore, inhibition of GPe, contrary to STN, abolishes oscillations. Our modeling study uncovers the neural mechanisms underlying PD β oscillations and may thereby guide the future development of therapeutic strategies.
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Affiliation(s)
- Shiva Azizpour Lindi
- CNRS, Institut des Maladies Neurodégénératives (IMN), UMR 5293, Université de Bordeaux, Bordeaux F-33000, France
| | - Nicolas P Mallet
- CNRS, Institut des Maladies Neurodégénératives (IMN), UMR 5293, Université de Bordeaux, Bordeaux F-33000, France
| | - Arthur Leblois
- CNRS, Institut des Maladies Neurodégénératives (IMN), UMR 5293, Université de Bordeaux, Bordeaux F-33000, France
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Gigi I, Senatore R, Marcelli A. The onset of motor learning impairments in Parkinson's disease: a computational investigation. Brain Inform 2024; 11:4. [PMID: 38286886 PMCID: PMC11333672 DOI: 10.1186/s40708-023-00215-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 12/11/2023] [Indexed: 01/31/2024] Open
Abstract
The basal ganglia (BG) is part of a basic feedback circuit regulating cortical function, such as voluntary movements control, via their influence on thalamocortical projections. BG disorders, namely Parkinson's disease (PD), characterized by the loss of neurons in the substantia nigra, involve the progressive loss of motor functions. At the present, PD is incurable. Converging evidences suggest the onset of PD-specific pathology prior to the appearance of classical motor signs. This latent phase of neurodegeneration in PD is of particular relevance in developing more effective therapies by intervening at the earliest stages of the disease. Therefore, a key challenge in PD research is to identify and validate markers for the preclinical and prodromal stages of the illness. We propose a mechanistic neurocomputational model of the BG at a mesoscopic scale to investigate the behavior of the simulated neural system after several degrees of lesion of the substantia nigra, with the aim of possibly evaluating which is the smallest lesion compromising motor learning. In other words, we developed a working framework for the analysis of theoretical early-stage PD. While simulations in healthy conditions confirm the key role of dopamine in learning, in pathological conditions the network predicts that there may exist abnormalities of the motor learning process, for physiological alterations in the BG, that do not yet involve the presence of symptoms typical of the clinical diagnosis.
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Affiliation(s)
- Ilaria Gigi
- Institute of Cognitive Sciences and Technologies (ISTC), National Research Council of Italy (CNR), Via Beato Pellegrino 28, Padova, 35137, Veneto, Italy.
| | - Rosa Senatore
- Natural Intelligent Technologies Ltd, Piazza Vittorio Emanuele 10, Fisciano, 84084, Campania, Italy
| | - Angelo Marcelli
- Department of Information Engineering, Electrical Engineering, and Applied Mathematics (DIEM), University of Salerno, Via Giovanni Paolo II 132, Fisciano, 84084, Campania, Italy
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Zhai S, Cui Q, Simmons DV, Surmeier DJ. Distributed dopaminergic signaling in the basal ganglia and its relationship to motor disability in Parkinson's disease. Curr Opin Neurobiol 2023; 83:102798. [PMID: 37866012 PMCID: PMC10842063 DOI: 10.1016/j.conb.2023.102798] [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: 08/05/2023] [Revised: 09/19/2023] [Accepted: 09/20/2023] [Indexed: 10/24/2023]
Abstract
The degeneration of mesencephalic dopaminergic neurons that innervate the basal ganglia is responsible for the cardinal motor symptoms of Parkinson's disease (PD). It has been thought that loss of dopaminergic signaling in one basal ganglia region - the striatum - was solely responsible for the network pathophysiology causing PD motor symptoms. While our understanding of dopamine (DA)'s role in modulating striatal circuitry has deepened in recent years, it also has become clear that it acts in other regions of the basal ganglia to influence movement. Underscoring this point, examination of a new progressive mouse model of PD shows that striatal dopamine DA depletion alone is not sufficient to induce parkinsonism and that restoration of extra-striatal DA signaling attenuates parkinsonian motor deficits once they appear. This review summarizes recent advances in the effort to understand basal ganglia circuitry, its modulation by DA, and how its dysfunction drives PD motor symptoms.
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Affiliation(s)
- Shenyu Zhai
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Qiaoling Cui
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - DeNard V Simmons
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - D James Surmeier
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA.
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