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Poshtkohi A, Wade J, McDaid L, Liu J, Dallas ML, Bithell A. Mathematical Modeling of PI3K/Akt Pathway in Microglia. Neural Comput 2024; 36:645-676. [PMID: 38457763 DOI: 10.1162/neco_a_01643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/20/2023] [Indexed: 03/10/2024]
Abstract
The motility of microglia involves intracellular signaling pathways that are predominantly controlled by changes in cytosolic Ca2+ and activation of PI3K/Akt (phosphoinositide-3-kinase/protein kinase B). In this letter, we develop a novel biophysical model for cytosolic Ca2+ activation of the PI3K/Akt pathway in microglia where Ca2+ influx is mediated by both P2Y purinergic receptors (P2YR) and P2X purinergic receptors (P2XR). The model parameters are estimated by employing optimization techniques to fit the model to phosphorylated Akt (pAkt) experimental modeling/in vitro data. The integrated model supports the hypothesis that Ca2+ influx via P2YR and P2XR can explain the experimentally reported biphasic transient responses in measuring pAkt levels. Our predictions reveal new quantitative insights into P2Rs on how they regulate Ca2+ and Akt in terms of physiological interactions and transient responses. It is shown that the upregulation of P2X receptors through a repetitive application of agonist results in a continual increase in the baseline [Ca2+], which causes the biphasic response to become a monophasic response which prolongs elevated levels of pAkt.
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Affiliation(s)
- Alireza Poshtkohi
- School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield, Hertfordshire, U.K.
| | - John Wade
- School of Computing, Engineering and Intelligent Systems, University of Ulster, Londonderry, U.K.
| | - Liam McDaid
- School of Computing, Engineering and Intelligent Systems, University of Ulster, Londonderry, U.K.
| | - Junxiu Liu
- School of Computing, Engineering and Intelligent Systems, University of Ulster, Londonderry, U.K.
| | - Mark L Dallas
- School of Pharmacy, University of Reading, Reading, U.K.
| | - Angela Bithell
- School of Pharmacy, University of Reading, Reading, U.K.
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2
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Manninen T, Aćimović J, Linne ML. Analysis of Network Models with Neuron-Astrocyte Interactions. Neuroinformatics 2023; 21:375-406. [PMID: 36959372 PMCID: PMC10085960 DOI: 10.1007/s12021-023-09622-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2023] [Indexed: 03/25/2023]
Abstract
Neural networks, composed of many neurons and governed by complex interactions between them, are a widely accepted formalism for modeling and exploring global dynamics and emergent properties in brain systems. In the past decades, experimental evidence of computationally relevant neuron-astrocyte interactions, as well as the astrocytic modulation of global neural dynamics, have accumulated. These findings motivated advances in computational glioscience and inspired several models integrating mechanisms of neuron-astrocyte interactions into the standard neural network formalism. These models were developed to study, for example, synchronization, information transfer, synaptic plasticity, and hyperexcitability, as well as classification tasks and hardware implementations. We here focus on network models of at least two neurons interacting bidirectionally with at least two astrocytes that include explicitly modeled astrocytic calcium dynamics. In this study, we analyze the evolution of these models and the biophysical, biochemical, cellular, and network mechanisms used to construct them. Based on our analysis, we propose how to systematically describe and categorize interaction schemes between cells in neuron-astrocyte networks. We additionally study the models in view of the existing experimental data and present future perspectives. Our analysis is an important first step towards understanding astrocytic contribution to brain functions. However, more advances are needed to collect comprehensive data about astrocyte morphology and physiology in vivo and to better integrate them in data-driven computational models. Broadening the discussion about theoretical approaches and expanding the computational tools is necessary to better understand astrocytes' roles in brain functions.
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Affiliation(s)
- Tiina Manninen
- Faculty of Medicine and Health Technology, Tampere University, Korkeakoulunkatu 3, FI-33720, Tampere, Finland.
| | - Jugoslava Aćimović
- Faculty of Medicine and Health Technology, Tampere University, Korkeakoulunkatu 3, FI-33720, Tampere, Finland
| | - Marja-Leena Linne
- Faculty of Medicine and Health Technology, Tampere University, Korkeakoulunkatu 3, FI-33720, Tampere, Finland.
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3
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Veisi N, Karimi G, Ranjbar M, Abbott D. Role of astrocytes in the self-repairing characteristics of analog neural networks. Neurocomputing 2022. [DOI: 10.1016/j.neucom.2022.01.077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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4
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Hong Q, Chen H, Sun J, Wang C. Memristive Circuit Implementation of a Self-Repairing Network Based on Biological Astrocytes in Robot Application. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2022; 33:2106-2120. [PMID: 33382661 DOI: 10.1109/tnnls.2020.3041624] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
A large number of studies have shown that astrocytes can be combined with the presynaptic terminals and postsynaptic spines of neurons to constitute a triple synapse via an endocannabinoid retrograde messenger to achieve a self-repair ability in the human brain. Inspired by the biological self-repair mechanism of astrocytes, this work proposes a self-repairing neuron network circuit that utilizes a memristor to simulate changes in neurotransmitters when a set threshold is reached. The proposed circuit simulates an astrocyte-neuron network and comprises the following: 1) a single-astrocyte-neuron circuit module; 2) an astrocyte-neuron network circuit; 3) a module to detect malfunctions; and 4) a neuron PR (release probability of synaptic transmission) enhancement module. When faults occur in a synapse, the neuron module becomes silent or near silent because of the low PR of the synapses. The circuit can detect faults automatically. The damaged neuron can be repaired by enhancing the PR of other healthy neurons, analogous to the biological repair mechanism of astrocytes. This mechanism helps to repair the damaged circuit. A simulation of the circuit revealed the following: 1) as the number of neurons in the circuit increases, the self-repair ability strengthens and 2) as the number of damaged neurons in the astrocyte-neuron network increases, the self-repair ability weakens, and there is a significant degradation in the performance of the circuit. The self-repairing circuit was used for a robot, and it effectively improved the robots' performance and reliability.
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Araki O, Nakahama Y, Urakawa T. Spatial synaptic modulation through IP3 diffusion triggered by ECB: a computational study with an astrocyte-neurons model. Cogn Neurodyn 2021; 15:1055-1065. [PMID: 34790270 DOI: 10.1007/s11571-021-09675-0] [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: 10/22/2020] [Revised: 02/15/2021] [Accepted: 03/26/2021] [Indexed: 10/21/2022] Open
Abstract
Recently, functional interactions between neurons and astrocytes have been steadily clarified. In particular, the effects of presynaptic depolarization-induced suppression of excitation (DSE) through endocannabinoid (ECB) and endocannabinoids-mediated synaptic potentiation (eSP) by an astrocyte have been used as an evidence of global heterosynaptic modulation. However, the mechanism of occurrence of spatial modulation in a neural network remains unknown. Although the Ca2+ density in astrocytes is strongly related to eSP through ECB, the mechanism of the rise in the ECB receptor in Ca2+ remains unclear. Since Ca2+ is closely related to inositol-1,4,5-trisphosphate (IP3), it is believed that the released IP3 affects Ca2+ in astrocytes that receive ECB. Therefore, this study approximately showed the spatial distribution of DSE or eSP with astrocyte-neuron computational models, assuming that the IP3 caused by ECB is transmitted in an astrocyte. The results showed doughnut-shaped DSE, eSP, and DSE regions from the central ECB released points to the surroundings. They suggested that IP3 diffusion plays an important role in mediating this synaptic modulation.
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Affiliation(s)
- Osamu Araki
- Department of Applied Physics, Tokyo University of Science, Tokyo, Japan
| | - Yusuke Nakahama
- Department of Applied Physics, Tokyo University of Science, Tokyo, Japan
| | - Tomokazu Urakawa
- Department of Applied Physics, Tokyo University of Science, Tokyo, Japan
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6
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Garg U, Yang K, Sengupta A. Emulation of Astrocyte Induced Neural Phase Synchrony in Spin-Orbit Torque Oscillator Neurons. Front Neurosci 2021; 15:699632. [PMID: 34712110 PMCID: PMC8546188 DOI: 10.3389/fnins.2021.699632] [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: 04/23/2021] [Accepted: 08/25/2021] [Indexed: 12/04/2022] Open
Abstract
Astrocytes play a central role in inducing concerted phase synchronized neural-wave patterns inside the brain. In this article, we demonstrate that injected radio-frequency signal in underlying heavy metal layer of spin-orbit torque oscillator neurons mimic the neuron phase synchronization effect realized by glial cells. Potential application of such phase coupling effects is illustrated in the context of a temporal "binding problem." We also present the design of a coupled neuron-synapse-astrocyte network enabled by compact neuromimetic devices by combining the concepts of local spike-timing dependent plasticity and astrocyte induced neural phase synchrony.
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Affiliation(s)
- Umang Garg
- School of Electrical Engineering and Computer Science, Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, United States
- Department of Electronics and Instrumentation Engineering, Birla Institute of Technology and Science, Pilani, India
| | - Kezhou Yang
- School of Electrical Engineering and Computer Science, Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, United States
| | - Abhronil Sengupta
- School of Electrical Engineering and Computer Science, Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, United States
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7
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Pang L, Liu J, Harkin J, Martin G, McElholm M, Javed A, McDaid L. Case Study-Spiking Neural Network Hardware System for Structural Health Monitoring. SENSORS (BASEL, SWITZERLAND) 2020; 20:s20185126. [PMID: 32911869 PMCID: PMC7570929 DOI: 10.3390/s20185126] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 09/01/2020] [Accepted: 09/03/2020] [Indexed: 05/14/2023]
Abstract
This case study provides feasibility analysis of adapting Spiking Neural Networks (SNN) based Structural Health Monitoring (SHM) system to explore low-cost solution for inspection of structural health of damaged buildings which survived after natural disaster that is, earthquakes or similar activities. Various techniques are used to detect the structural health status of a building for performance benchmarking, including different feature extraction methods and classification techniques (e.g., SNN, K-means and artificial neural network etc.). The SNN is utilized to process the sensory data generated from full-scale seven-story reinforced concrete building to verify the classification performances. Results show that the proposed SNN hardware has high classification accuracy, reliability, longevity and low hardware area overhead.
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Affiliation(s)
- Lili Pang
- Industrial Center/School of Innovation and Entrepreneurship, Nanjing Institute of Technology, Nanjing 211167, China
- Correspondence: (L.P.); (J.L.)
| | - Junxiu Liu
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry BT48 7JL, UK; (J.H.); (G.M.); (M.M.); (A.J.); (L.M.)
- Correspondence: (L.P.); (J.L.)
| | - Jim Harkin
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry BT48 7JL, UK; (J.H.); (G.M.); (M.M.); (A.J.); (L.M.)
| | - George Martin
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry BT48 7JL, UK; (J.H.); (G.M.); (M.M.); (A.J.); (L.M.)
| | - Malachy McElholm
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry BT48 7JL, UK; (J.H.); (G.M.); (M.M.); (A.J.); (L.M.)
| | - Aqib Javed
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry BT48 7JL, UK; (J.H.); (G.M.); (M.M.); (A.J.); (L.M.)
| | - Liam McDaid
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry BT48 7JL, UK; (J.H.); (G.M.); (M.M.); (A.J.); (L.M.)
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8
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Liu J, McDaid L, Araque A, Wade J, Harkin J, Karim S, Henshall DC, Connolly NMC, Johnson AP, Tyrrell AM, Timmis J, Millard AG, Hilder J, Halliday DM. GABA Regulation of Burst Firing in Hippocampal Astrocyte Neural Circuit: A Biophysical Model. Front Cell Neurosci 2019; 13:335. [PMID: 31396055 PMCID: PMC6664076 DOI: 10.3389/fncel.2019.00335] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2019] [Accepted: 07/08/2019] [Indexed: 12/30/2022] Open
Abstract
It is now widely accepted that glia cells and gamma-aminobutyric acidergic (GABA) interneurons dynamically regulate synaptic transmission and neuronal activity in time and space. This paper presents a biophysical model that captures the interaction between an astrocyte cell, a GABA interneuron and pre/postsynaptic neurons. Specifically, GABA released from a GABA interneuron triggers in astrocytes the release of calcium (Ca2+) from the endoplasmic reticulum via the inositol 1, 4, 5-trisphosphate (IP3) pathway. This results in gliotransmission which elevates the presynaptic transmission probability rate (PR) causing weight potentiation and a gradual increase in postsynaptic neuronal firing, that eventually stabilizes. However, by capturing the complex interactions between IP3, generated from both GABA and the 2-arachidonyl glycerol (2-AG) pathway, and PR, this paper shows that this interaction not only gives rise to an initial weight potentiation phase but also this phase is followed by postsynaptic bursting behavior. Moreover, the model will show that there is a presynaptic frequency range over which burst firing can occur. The proposed model offers a novel cellular level mechanism that may underpin both seizure-like activity and neuronal synchrony across different brain regions.
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Affiliation(s)
- Junxiu Liu
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry, United Kingdom
| | - Liam McDaid
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry, United Kingdom
| | - Alfonso Araque
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
| | - John Wade
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry, United Kingdom
| | - Jim Harkin
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry, United Kingdom
| | - Shvan Karim
- School of Computing, Engineering and Intelligent Systems, Ulster University, Derry, United Kingdom
| | - David C Henshall
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland.,FutureNeuro Research Centre, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Niamh M C Connolly
- Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Anju P Johnson
- Department of Electronic Engineering, University of York, York, United Kingdom
| | - Andy M Tyrrell
- Department of Electronic Engineering, University of York, York, United Kingdom
| | - Jon Timmis
- Department of Electronic Engineering, University of York, York, United Kingdom
| | - Alan G Millard
- Department of Electronic Engineering, University of York, York, United Kingdom
| | - James Hilder
- Department of Electronic Engineering, University of York, York, United Kingdom
| | - David M Halliday
- Department of Electronic Engineering, University of York, York, United Kingdom
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9
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Wade JJ, Breslin K, Wong-Lin K, Harkin J, Flanagan B, Van Zalinge H, Hall S, Dallas M, Bithell A, Verkhratsky A, McDaid L. Calcium Microdomain Formation at the Perisynaptic Cradle Due to NCX Reversal: A Computational Study. Front Cell Neurosci 2019; 13:185. [PMID: 31133809 PMCID: PMC6513884 DOI: 10.3389/fncel.2019.00185] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 04/12/2019] [Indexed: 01/06/2023] Open
Abstract
It has recently been proposed using a multi-compartmental mathematical model that negatively fixed charged membrane-associated sites constrain the flow of cations in perisynaptic astroglial processes. This restricted movement of ions between the perisynaptic cradle (PsC), principal astroglial processes and the astrocyte soma gives rise to potassium (K+) and sodium (Na+) microdomains at the PsC. The present paper extends the above model to demonstrate that the formation of an Na+ microdomain can reverse the Na+/Ca2+ exchanger (NCX) thus providing an additional source of calcium (Ca2+) at the PsC. Results presented clearly show that reversal of the Na+/Ca2+ exchanger is instigated by a glutamate transporter coupled increase in concentration of cytoplasmic [Na+]i at the PsC, which and instigates Ca2+ influx through the NCX. As the flow of Ca2+ along the astrocyte process and away from the PsC is also constrained by Ca2+ binding proteins, then a Ca2+ microdomain forms at the PsC. The paper also serves to demonstrate that the EAAT, NKA, and NCX represent the minimal requirement necessary and sufficient for the development of a Ca2+ microdomain and that these mechanisms directly link neuronal activity and glutamate release to the formation of localized Na+ and Ca2+ microdomains signals at the PsC. This local source of Ca2+ can provide a previously underexplored form of astroglial Ca2+ signaling.
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Affiliation(s)
- John Joseph Wade
- Computational Neuroscience and Neural Engineering (CNET) Research Team, Intelligent Systems Research Centre, Ulster University, Derry, United Kingdom
| | - Kevin Breslin
- Computational Neuroscience and Neural Engineering (CNET) Research Team, Intelligent Systems Research Centre, Ulster University, Derry, United Kingdom
| | - KongFatt Wong-Lin
- Neural Systems and Neurotechnology Research Team, Intelligent Systems Research Centre, Ulster University, Derry, United Kingdom
| | - Jim Harkin
- Computational Neuroscience and Neural Engineering (CNET) Research Team, Intelligent Systems Research Centre, Ulster University, Derry, United Kingdom
| | - Bronac Flanagan
- Computational Neuroscience and Neural Engineering (CNET) Research Team, Intelligent Systems Research Centre, Ulster University, Derry, United Kingdom
| | - Harm Van Zalinge
- Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, United Kingdom
| | - Steve Hall
- Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, United Kingdom
| | - Mark Dallas
- Reading School of Pharmacy, University of Reading, Reading, United Kingdom
| | - Angela Bithell
- Reading School of Pharmacy, University of Reading, Reading, United Kingdom
| | - Alexei Verkhratsky
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Achucarro Center for Neuroscience, IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
| | - Liam McDaid
- Computational Neuroscience and Neural Engineering (CNET) Research Team, Intelligent Systems Research Centre, Ulster University, Derry, United Kingdom
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10
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Liu J, Mcdaid LJ, Harkin J, Karim S, Johnson AP, Millard AG, Hilder J, Halliday DM, Tyrrell AM, Timmis J. Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2019; 30:865-875. [PMID: 30072349 DOI: 10.1109/tnnls.2018.2854291] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
It is now known that astrocytes modulate the activity at the tripartite synapses where indirect signaling via the retrograde messengers, endocannabinoids, leads to a localized self-repairing capability. In this paper, a self-repairing spiking astrocyte neural network (SANN) is proposed to demonstrate a distributed self-repairing capability at the network level. The SANN uses a novel learning rule that combines the spike-timing-dependent plasticity (STDP) and Bienenstock, Cooper, and Munro (BCM) learning rules (hereafter referred to as the BSTDP rule). In this learning rule, the synaptic weight potentiation is not only driven by the temporal difference between the presynaptic and postsynaptic neuron firing times but also by the postsynaptic neuron activity. We will show in this paper that the BSTDP modulates the height of the plasticity window to establish an input-output mapping (in the learning phase) and also maintains this mapping (via self-repair) if synaptic pathways become dysfunctional. It is the functional dependence of postsynaptic neuron firing activity on the height of the plasticity window that underpins how the proposed SANN self-repairs on the fly. The SANN also uses the coupling between the tripartite synapses and γ -GABAergic interneurons. This interaction gives rise to a presynaptic neuron frequency filtering capability that serves to route information, represented as spike trains, to different neurons in the subsequent layers of the SANN. The proposed SANN follows a feedforward architecture with multiple interneuron pathways and astrocytes modulate synaptic activity at the hidden and output neuronal layers. The self-repairing capability will be demonstrated in a robotic obstacle avoidance application, and the simulation results will show that the SANN can maintain learned maneuvers at synaptic fault densities of up to 80% regardless of the fault locations.
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11
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Manninen T, Havela R, Linne ML. Computational Models for Calcium-Mediated Astrocyte Functions. Front Comput Neurosci 2018; 12:14. [PMID: 29670517 PMCID: PMC5893839 DOI: 10.3389/fncom.2018.00014] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Accepted: 02/28/2018] [Indexed: 12/16/2022] Open
Abstract
The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro, but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop the models. Thus, we would like to emphasize that only via reproducible research are we able to build better computational models for astrocytes, which truly advance science. Our study is the first to characterize in detail the biophysical and biochemical mechanisms that have been modeled for astrocytes.
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Affiliation(s)
- Tiina Manninen
- Computational Neuroscience Group, BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland
| | | | - Marja-Leena Linne
- Computational Neuroscience Group, BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland
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12
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Liu J, Harkin J, Maguire LP, McDaid LJ, Wade JJ. SPANNER: A Self-Repairing Spiking Neural Network Hardware Architecture. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2018; 29:1287-1300. [PMID: 28287992 DOI: 10.1109/tnnls.2017.2673021] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Recent research has shown that a glial cell of astrocyte underpins a self-repair mechanism in the human brain, where spiking neurons provide direct and indirect feedbacks to presynaptic terminals. These feedbacks modulate the synaptic transmission probability of release (PR). When synaptic faults occur, the neuron becomes silent or near silent due to the low PR of synapses; whereby the PRs of remaining healthy synapses are then increased by the indirect feedback from the astrocyte cell. In this paper, a novel hardware architecture of Self-rePAiring spiking Neural NEtwoRk (SPANNER) is proposed, which mimics this self-repairing capability in the human brain. This paper demonstrates that the hardware can self-detect and self-repair synaptic faults without the conventional components for the fault detection and fault repairing. Experimental results show that SPANNER can maintain the system performance with fault densities of up to 40%, and more importantly SPANNER has only a 20% performance degradation when the self-repairing architecture is significantly damaged at a fault density of 80%.
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13
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Rahimian E, Zabihi S, Amiri M, Linares-Barranco B. Digital Implementation of the Two-Compartmental Pinsky-Rinzel Pyramidal Neuron Model. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2018; 12:47-57. [PMID: 29028209 DOI: 10.1109/tbcas.2017.2753541] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
It is believed that brain-like computing system can be achieved by the fusion of electronics and neuroscience. In this way, the optimized digital hardware implementation of neurons, primary units of nervous system, play a vital role in neuromorphic applications. Moreover, one of the main features of pyramidal neurons in cortical areas is bursting activities that has a critical role in synaptic plasticity. The Pinsky-Rinzel model is a nonlinear two-compartmental model for CA3 pyramidal cell that is widely used in neuroscience. In this paper, a modified Pinsky-Rinzel pyramidal model is proposed by replacing its complex nonlinear equations with piecewise linear approximation. Next, a digital circuit is designed for the simplified model to be able to implement on a low-cost digital hardware, such as field-programmable gate array (FPGA). Both original and proposed models are simulated in MATLAB and next digital circuit simulated in Vivado is compared to show that obtained results are in good agreement. Finally, the results of physical implementation on FPGA are also illustrated. The presented circuit advances preceding designs with regards to the ability to replicate essential characteristics of different firing responses including bursting and spiking in the compartmental model. This new circuit has various applications in neuromorphic engineering, such as developing new neuroinspired chips.
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14
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Oschmann F, Berry H, Obermayer K, Lenk K. From in silico astrocyte cell models to neuron-astrocyte network models: A review. Brain Res Bull 2017; 136:76-84. [PMID: 28189516 DOI: 10.1016/j.brainresbull.2017.01.027] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 01/30/2017] [Accepted: 01/31/2017] [Indexed: 01/25/2023]
Abstract
The idea that astrocytes may be active partners in synaptic information processing has recently emerged from abundant experimental reports. Because of their spatial proximity to neurons and their bidirectional communication with them, astrocytes are now considered as an important third element of the synapse. Astrocytes integrate and process synaptic information and by doing so generate cytosolic calcium signals that are believed to reflect neuronal transmitter release. Moreover, they regulate neuronal information transmission by releasing gliotransmitters into the synaptic cleft affecting both pre- and postsynaptic receptors. Concurrent with the first experimental reports of the astrocytic impact on neural network dynamics, computational models describing astrocytic functions have been developed. In this review, we give an overview over the published computational models of astrocytic functions, from single-cell dynamics to the tripartite synapse level and network models of astrocytes and neurons.
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Affiliation(s)
- Franziska Oschmann
- Technical University Berlin, Neural Information Processing Group, Sekr. MAR 5-6, Marchstrasse 23, 10587 Berlin, Germany; Bernstein Center for Computational Neuroscience, Berlin, Germany.
| | - Hugues Berry
- INRIA, 69603 Villeurbanne, France; LIRIS UMR5205, University of Lyon, 69622 Villeurbanne, France
| | - Klaus Obermayer
- Technical University Berlin, Neural Information Processing Group, Sekr. MAR 5-6, Marchstrasse 23, 10587 Berlin, Germany; Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Kerstin Lenk
- Tampere University of Technology, BioMediTech, PL100, 33014 Tampere, Finland.
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Modulation of Synaptic Plasticity by Glutamatergic Gliotransmission: A Modeling Study. Neural Plast 2016; 2016:7607924. [PMID: 27195153 PMCID: PMC4852535 DOI: 10.1155/2016/7607924] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Accepted: 02/15/2016] [Indexed: 01/03/2023] Open
Abstract
Glutamatergic gliotransmission, that is, the release of glutamate from perisynaptic astrocyte processes in an activity-dependent manner, has emerged as a potentially crucial signaling pathway for regulation of synaptic plasticity, yet its modes of expression and function in vivo remain unclear. Here, we focus on two experimentally well-identified gliotransmitter pathways, (i) modulations of synaptic release and (ii) postsynaptic slow inward currents mediated by glutamate released from astrocytes, and investigate their possible functional relevance on synaptic plasticity in a biophysical model of an astrocyte-regulated synapse. Our model predicts that both pathways could profoundly affect both short- and long-term plasticity. In particular, activity-dependent glutamate release from astrocytes could dramatically change spike-timing-dependent plasticity, turning potentiation into depression (and vice versa) for the same induction protocol.
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Astrocytes: Orchestrating synaptic plasticity? Neuroscience 2015; 323:43-61. [PMID: 25862587 DOI: 10.1016/j.neuroscience.2015.04.001] [Citation(s) in RCA: 161] [Impact Index Per Article: 17.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Revised: 03/25/2015] [Accepted: 04/01/2015] [Indexed: 01/09/2023]
Abstract
Synaptic plasticity is the capacity of a preexisting connection between two neurons to change in strength as a function of neural activity. Because synaptic plasticity is the major candidate mechanism for learning and memory, the elucidation of its constituting mechanisms is of crucial importance in many aspects of normal and pathological brain function. In particular, a prominent aspect that remains debated is how the plasticity mechanisms, that encompass a broad spectrum of temporal and spatial scales, come to play together in a concerted fashion. Here we review and discuss evidence that pinpoints to a possible non-neuronal, glial candidate for such orchestration: the regulation of synaptic plasticity by astrocytes.
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