1
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Gao Z, Wu L, Zhao X, Wei Z, Lu L, Yi M. Random fluctuations and synaptic plasticity enhance working memory activities in the neuron-astrocyte network. Cogn Neurodyn 2024; 18:503-518. [PMID: 38699624 PMCID: PMC11061073 DOI: 10.1007/s11571-023-10002-y] [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: 06/08/2023] [Revised: 07/30/2023] [Accepted: 08/13/2023] [Indexed: 05/05/2024] Open
Abstract
Random fluctuations are inescapable feature in biological systems, but appropriate intensity of randomness can effectively facilitate information transfer and memory encoding within the nervous system. In the study, a modified spiking neuron-astrocyte network model with excitatory-inhibitory balance and synaptic plasticity is established. This model considers external input noise, and allows investigating the effects of intrinsic random fluctuations on working memory tasks. It is found that the astrocyte network, acting as a low-pass filter, reduces the noise component of the total input currents and improves the recovered images. The memory performance is enhanced by selecting appropriate intensity of random fluctuations, while excessive intensity can inhibit signal transmission of network. As the intensity of random fluctuations gradually increases, there exists a maximum value of the working memory performance. The cued recall of the network markedly decreases excessive input noise relative to test images. Meanwhile, a greater contrast effect is observed as the external input noise increases. In addition, synaptic plasticity reduces the firing rates and firing peaks of neurons, thus stabilizing the working memory activity during the test. The outcomes of this study may provide some inspirations for comprehending the role of random fluctuations in working memory mechanisms and neural information processing within the cerebral cortex.
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Affiliation(s)
- Zhuoheng Gao
- School of Mathematics and Physics, China University of Geosciences, Wuhan, 430074 China
| | - Liqing Wu
- School of Mathematics and Physics, China University of Geosciences, Wuhan, 430074 China
| | - Xin Zhao
- School of Mathematics and Physics, China University of Geosciences, Wuhan, 430074 China
| | - Zhuochao Wei
- School of Mathematics and Physics, China University of Geosciences, Wuhan, 430074 China
| | - Lulu Lu
- School of Mathematics and Physics, China University of Geosciences, Wuhan, 430074 China
| | - Ming Yi
- School of Mathematics and Physics, China University of Geosciences, Wuhan, 430074 China
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2
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Hosaka T. Effects of parity, frustration, and stochastic fluctuations on integrated conceptual information for networks with two small-sized loops. Neural Netw 2023; 162:131-146. [PMID: 36905823 DOI: 10.1016/j.neunet.2023.02.034] [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] [Received: 04/10/2021] [Revised: 02/18/2023] [Accepted: 02/21/2023] [Indexed: 03/12/2023]
Abstract
This paper presents an evaluation of the system-level integrated conceptual information of a major complex for a small-scale network containing two loops in accordance with the integrated information theory 3.0 framework. We focus on the following parameters characterizing the system model: (1) number of nodes in the loop, (2) frustration of the loop, and (3) temperature controlling the stochastic fluctuation of the state transition. Effects of these parameters on the integrated conceptual information and conditions for major complexes formed by a single loop, rather than the entire network, are investigated. Our first finding is that parity of the number of nodes forming a loop has a strong effect on the integrated conceptual information. For loops with an even number of nodes, the number of concepts tends to decrease, and the integrated conceptual information becomes smaller. Our second finding is that a major complex is more likely to be formed by a small number of nodes under small stochastic fluctuations. On the other hand, the entire network can easily become a major complex under larger stochastic fluctuations, and this tendency can be reinforced by frustration. It is also shown that, although counterintuitive, the integrated conceptual information can be maximized in the presence of stochastic fluctuations. These results suggest that even when several small subnetworks are connected by only a few connections, such as a bridge, the entire network may become a major complex by introducing some stochastic fluctuations and by frustrating loops with an even number of nodes.
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Affiliation(s)
- Tadaaki Hosaka
- Tokyo University of Science, 1-11-2 Fujimi, Chiyoda Ward, Tokyo, Japan.
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3
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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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4
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Lu L, Gao Z, Wei Z, Yi M. Working memory depends on the excitatory-inhibitory balance in neuron-astrocyte network. CHAOS (WOODBURY, N.Y.) 2023; 33:013127. [PMID: 36725632 DOI: 10.1063/5.0126890] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 12/19/2022] [Indexed: 06/18/2023]
Abstract
Previous studies have shown that astrocytes are involved in information processing and working memory (WM) in the central nervous system. Here, the neuron-astrocyte network model with biological properties is built to study the effects of excitatory-inhibitory balance and neural network structures on WM tasks. It is found that the performance metrics of WM tasks under the scale-free network are higher than other network structures, and the WM task can be successfully completed when the proportion of excitatory neurons in the network exceeds 30%. There exists an optimal region for the proportion of excitatory neurons and synaptic weight that the memory performance metrics of the WM tasks are higher. The multi-item WM task shows that the spatial calcium patterns for different items overlap significantly in the astrocyte network, which is consistent with the formation of cognitive memory in the brain. Moreover, complex image tasks show that cued recall can significantly reduce systematic noise and maintain the stability of the WM tasks. The results may contribute to understand the mechanisms of WM formation and provide some inspirations into the dynamic storage and recall of memory.
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Affiliation(s)
- Lulu Lu
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
| | - Zhuoheng Gao
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
| | - Zhouchao Wei
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
| | - Ming Yi
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
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5
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Controlling synchronization of gamma oscillations by astrocytic modulation in a model hippocampal neural network. Sci Rep 2022; 12:6970. [PMID: 35484169 PMCID: PMC9050920 DOI: 10.1038/s41598-022-10649-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 04/11/2022] [Indexed: 12/13/2022] Open
Abstract
Recent in vitro and in vivo experiments demonstrate that astrocytes participate in the maintenance of cortical gamma oscillations and recognition memory. However, the mathematical understanding of the underlying dynamical mechanisms remains largely incomplete. Here we investigate how the interplay of slow modulatory astrocytic signaling with fast synaptic transmission controls coherent oscillations in the network of hippocampal interneurons that receive inputs from pyramidal cells. We show that the astrocytic regulation of signal transmission between neurons improves the firing synchrony and extends the region of coherent oscillations in the biologically relevant values of synaptic conductance. Astrocyte-mediated potentiation of inhibitory synaptic transmission markedly enhances the coherence of network oscillations over a broad range of model parameters. Astrocytic regulation of excitatory synaptic input improves the robustness of interneuron network gamma oscillations induced by physiologically relevant excitatory model drive. These findings suggest a mechanism, by which the astrocytes become involved in cognitive function and information processing through modulating fast neural network dynamics.
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6
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Bistability and Chaos Emergence in Spontaneous Dynamics of Astrocytic Calcium Concentration. MATHEMATICS 2022. [DOI: 10.3390/math10081337] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
In this work, we consider a mathematical model describing spontaneous calcium signaling in astrocytes. Based on biologically relevant principles, this model simulates experimentally observed calcium oscillations and can predict the emergence of complicated dynamics. Using analytical and numerical analysis, various attracting sets were found and investigated. Employing bifurcation theory analysis, we examined steady state solutions, bistability, simple and complicated periodic limit cycles and also chaotic attractors. We found that astrocytes possess a variety of complex dynamical modes, including chaos and multistability, that can further provide different modulations of neuronal circuits, enhancing their plasticity and flexibility.
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7
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Astrocytes mediate analogous memory in a multi-layer neuron–astrocyte network. Neural Comput Appl 2022. [DOI: 10.1007/s00521-022-06936-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
AbstractModeling the neuronal processes underlying short-term working memory remains the focus of many theoretical studies in neuroscience. In this paper, we propose a mathematical model of a spiking neural network (SNN) which simulates the way a fragment of information is maintained as a robust activity pattern for several seconds and the way it completely disappears if no other stimuli are fed to the system. Such short-term memory traces are preserved due to the activation of astrocytes accompanying the SNN. The astrocytes exhibit calcium transients at a time scale of seconds. These transients further modulate the efficiency of synaptic transmission and, hence, the firing rate of neighboring neurons at diverse timescales through gliotransmitter release. We demonstrate how such transients continuously encode frequencies of neuronal discharges and provide robust short-term storage of analogous information. This kind of short-term memory can store relevant information for seconds and then completely forget it to avoid overlapping with forthcoming patterns. The SNN is inter-connected with the astrocytic layer by local inter-cellular diffusive connections. The astrocytes are activated only when the neighboring neurons fire synchronously, e.g., when an information pattern is loaded. For illustration, we took grayscale photographs of people’s faces where the shades of gray correspond to the level of applied current which stimulates the neurons. The astrocyte feedback modulates (facilitates) synaptic transmission by varying the frequency of neuronal firing. We show how arbitrary patterns can be loaded, then stored for a certain interval of time, and retrieved if the appropriate clue pattern is applied to the input.
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8
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Nazhestkin IA, Svarnik OE. Variations in the Value of Integrated Information Theory Estimated from Hippocampal Neural Activity During Acquisition of Operant Behavior in Rats. Biophysics (Nagoya-shi) 2022. [DOI: 10.1134/s0006350922010110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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9
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Makovkin S, Laptyeva T, Jalan S, Ivanchenko M. Synchronization in multiplex models of neuron-glial systems: Small-world topology and inhibitory coupling. CHAOS (WOODBURY, N.Y.) 2021; 31:113111. [PMID: 34881599 DOI: 10.1063/5.0069357] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 10/14/2021] [Indexed: 06/13/2023]
Abstract
In this work, we investigate the impact of mixed coupling on synchronization in a multiplex oscillatory network. The network mimics the neural-glial systems by incorporating interacting slow ("glial") and fast ("neural") oscillatory layers. Connections between the "glial" elements form a regular periodic structure, in which each element is connected to the eight other neighbor elements, whereas connections among "neural" elements are represented by Watts-Strogatz networks (from regular and small-world to random Erdös-Rényi graph) with a matching mean node degree. We find that the random rewiring toward small-world topology readily yields the dynamics close to that exhibited for a completely random graph, in particular, leading to coarse-graining of dynamics, suppressing multi-stability of synchronization regimes, and the onset of Kuramoto-type synchrony in both layers. The duration of transient dynamics in the system measured by relaxation times is minimized with the increase of random connections in the neural layer, remaining substantial only close to synchronization-desynchronization transitions. "Inhibitory" interactions in the "neural" subnetwork layer undermine synchronization; however, the strong coupling with the "glial" layer overcomes this effect.
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Affiliation(s)
- Sergey Makovkin
- Department of Applied Mathematics and Laboratory of Systems Medicine of Healthy Aging, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod 603950, Russia
| | - Tetyana Laptyeva
- Department of Control Theory and Systems Dynamics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod 603950, Russia
| | - Sarika Jalan
- Complex Systems Lab, Department of Physics, Indian Institute of Technology Indore, Simrol, Indore 452020, India
| | - Mikhail Ivanchenko
- Department of Applied Mathematics and Laboratory of Systems Medicine of Healthy Aging, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod 603950, Russia
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10
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Gordleeva SY, Tsybina YA, Krivonosov MI, Ivanchenko MV, Zaikin AA, Kazantsev VB, Gorban AN. Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes. Front Cell Neurosci 2021; 15:631485. [PMID: 33867939 PMCID: PMC8044545 DOI: 10.3389/fncel.2021.631485] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 03/04/2021] [Indexed: 01/07/2023] Open
Abstract
We propose a novel biologically plausible computational model of working memory (WM) implemented by a spiking neuron network (SNN) interacting with a network of astrocytes. The SNN is modeled by synaptically coupled Izhikevich neurons with a non-specific architecture connection topology. Astrocytes generating calcium signals are connected by local gap junction diffusive couplings and interact with neurons via chemicals diffused in the extracellular space. Calcium elevations occur in response to the increased concentration of the neurotransmitter released by spiking neurons when a group of them fire coherently. In turn, gliotransmitters are released by activated astrocytes modulating the strength of the synaptic connections in the corresponding neuronal group. Input information is encoded as two-dimensional patterns of short applied current pulses stimulating neurons. The output is taken from frequencies of transient discharges of corresponding neurons. We show how a set of information patterns with quite significant overlapping areas can be uploaded into the neuron-astrocyte network and stored for several seconds. Information retrieval is organized by the application of a cue pattern representing one from the memory set distorted by noise. We found that successful retrieval with the level of the correlation between the recalled pattern and ideal pattern exceeding 90% is possible for the multi-item WM task. Having analyzed the dynamical mechanism of WM formation, we discovered that astrocytes operating at a time scale of a dozen of seconds can successfully store traces of neuronal activations corresponding to information patterns. In the retrieval stage, the astrocytic network selectively modulates synaptic connections in the SNN leading to successful recall. Information and dynamical characteristics of the proposed WM model agrees with classical concepts and other WM models.
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Affiliation(s)
- Susanna Yu Gordleeva
- Scientific and Educational Mathematical Center "Mathematics of Future Technology," Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.,Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Innopolis, Russia
| | - Yuliya A Tsybina
- Scientific and Educational Mathematical Center "Mathematics of Future Technology," Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Mikhail I Krivonosov
- Scientific and Educational Mathematical Center "Mathematics of Future Technology," Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Mikhail V Ivanchenko
- Scientific and Educational Mathematical Center "Mathematics of Future Technology," Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Alexey A Zaikin
- Scientific and Educational Mathematical Center "Mathematics of Future Technology," Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.,Center for Analysis of Complex Systems, Sechenov First Moscow State Medical University, Sechenov University, Moscow, Russia.,Institute for Women's Health and Department of Mathematics, University College London, London, United Kingdom
| | - Victor B Kazantsev
- Scientific and Educational Mathematical Center "Mathematics of Future Technology," Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.,Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Innopolis, Russia.,Neuroscience Research Institute, Samara State Medical University, Samara, Russia
| | - Alexander N Gorban
- Scientific and Educational Mathematical Center "Mathematics of Future Technology," Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.,Department of Mathematics, University of Leicester, Leicester, United Kingdom
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11
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Zheng Y, Huang Z, Xu J, Hou K, Yu Y, Lv S, Chen L, Li Y, Quan C, Chi G. MiR-124 and Small Molecules Synergistically Regulate the Generation of Neuronal Cells from Rat Cortical Reactive Astrocytes. Mol Neurobiol 2021; 58:2447-2464. [PMID: 33725319 DOI: 10.1007/s12035-021-02345-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 02/25/2021] [Indexed: 01/04/2023]
Abstract
Irreversible neuron loss caused by central nervous system injuries usually leads to persistent neurological dysfunction. Reactive astrocytes, because of their high proliferative capacity, proximity to neuronal lineage, and significant involvement in glial scarring, are ideal starting cells for neuronal regeneration. Having previously identified several small molecules as important regulators of astrocyte-to-neuron reprogramming, we established herein that miR-124, ruxolitinib, SB203580, and forskolin could co-regulate rat cortical reactive astrocyte-to-neuron conversion. The induced cells had reduced astroglial properties, displayed typical neuronal morphologies, and expressed neuronal markers, reflecting 25.9% of cholinergic neurons and 22.3% of glutamatergic neurons. Gene analysis revealed that induced neuron gene expression patterns were more similar to that of primary neurons than of initial reactive astrocytes. On the molecular level, miR-124-driven neuronal differentiation of reactive astrocytes was via targeting of the SOX9-NFIA-HES1 axis to inhibit HES1 expression. In conclusion, we present a novel approach to inducing endogenous rat cortical reactive astrocytes into neurons through co-regulation involving miR-124 and three small molecules. Thus, our research has potential implications for inhibiting glial scar formation and promoting neuronal regeneration after central nervous system injury or disease.
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Affiliation(s)
- Yangyang Zheng
- The Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, 126 Xinmin Street, Changchun, 130021, Jilin, China
| | - Zhehao Huang
- China-Japan Union Hospital of Jilin University, 126 Xiantai Street, Changchun, 130031, Jilin, China
| | - Jinying Xu
- The Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, 126 Xinmin Street, Changchun, 130021, Jilin, China
| | - Kun Hou
- The First Hospital of Jilin University, No. 1 Xinmin Avenue, Changchun, 130021, Jilin, China
| | - Yifei Yu
- The Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, 126 Xinmin Street, Changchun, 130021, Jilin, China
| | - Shuang Lv
- The Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, 126 Xinmin Street, Changchun, 130021, Jilin, China
| | - Lin Chen
- China-Japan Union Hospital of Jilin University, 126 Xiantai Street, Changchun, 130031, Jilin, China
| | - Yulin Li
- The Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, 126 Xinmin Street, Changchun, 130021, Jilin, China.
| | - Chengshi Quan
- The Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, 126 Xinmin Street, Changchun, 130021, Jilin, China.
| | - Guangfan Chi
- The Key Laboratory of Pathobiology, Ministry of Education, College of Basic Medical Sciences, Jilin University, 126 Xinmin Street, Changchun, 130021, Jilin, China.
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12
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Abrego L, Gordleeva S, Kanakov O, Krivonosov M, Zaikin A. Estimating integrated information in bidirectional neuron-astrocyte communication. Phys Rev E 2021; 103:022410. [PMID: 33736090 DOI: 10.1103/physreve.103.022410] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 01/04/2021] [Indexed: 01/14/2023]
Abstract
There is growing evidence that suggests the importance of astrocytes as elements for neural information processing through the modulation of synaptic transmission. A key aspect of this problem is understanding the impact of astrocytes in the information carried by compound events in neurons across time. In this paper, we investigate how the astrocytes participate in the information integrated by individual neurons in an ensemble through the measurement of "integrated information." We propose a computational model that considers bidirectional communication between astrocytes and neurons through glutamate-induced calcium signaling. Our model highlights the role of astrocytes in information processing through dynamical coordination. Our findings suggest that the astrocytic feedback promotes synergetic influences in the neural communication, which is maximized when there is a balance between excess correlation and spontaneous spiking activity. The results were further linked with additional measures such as net synergy and mutual information. This result reinforces the idea that astrocytes have integrative properties in communication among neurons.
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Affiliation(s)
- Luis Abrego
- Department of Mathematics, University College London, London, United Kingdom
| | - Susanna Gordleeva
- Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Innopolis, Russia
- Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Oleg Kanakov
- Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Mikhail Krivonosov
- Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Alexey Zaikin
- Department of Mathematics, University College London, London, United Kingdom
- Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
- Institute for Women's Health, University College London, London WC1E 6BT, United Kingdom
- Centre for Analysis of Complex Systems, Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
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13
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Kanakov O, Gordleeva S, Zaikin A. Integrated Information in the Spiking-Bursting Stochastic Model. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E1334. [PMID: 33266518 PMCID: PMC7761117 DOI: 10.3390/e22121334] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 11/18/2020] [Accepted: 11/20/2020] [Indexed: 11/17/2022]
Abstract
Integrated information has been recently suggested as a possible measure to identify a necessary condition for a system to display conscious features. Recently, we have shown that astrocytes contribute to the generation of integrated information through the complex behavior of neuron-astrocyte networks. Still, it remained unclear which underlying mechanisms governing the complex behavior of a neuron-astrocyte network are essential to generating positive integrated information. This study presents an analytic consideration of this question based on exact and asymptotic expressions for integrated information in terms of exactly known probability distributions for a reduced mathematical model (discrete-time, discrete-state stochastic model) reflecting the main features of the "spiking-bursting" dynamics of a neuron-astrocyte network. The analysis was performed in terms of the empirical "whole minus sum" version of integrated information in comparison to the "decoder based" version. The "whole minus sum" information may change sign, and an interpretation of this transition in terms of "net synergy" is available in the literature. This motivated our particular interest in the sign of the "whole minus sum" information in our analytical considerations. The behaviors of the "whole minus sum" and "decoder based" information measures are found to bear a lot of similarity-they have mutual asymptotic convergence as time-uncorrelated activity increases, and the sign transition of the "whole minus sum" information is associated with a rapid growth in the "decoder based" information. The study aims at creating a theoretical framework for using the spiking-bursting model as an analytically tractable reference point for applying integrated information concepts to systems exhibiting similar bursting behavior. The model can also be of interest as a new discrete-state test bench for different formulations of integrated information.
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Affiliation(s)
- Oleg Kanakov
- Faculty of Radiophysics, Lobachevsky State University of Nizhny Novgorod, 603950 Nizhny Novgorod, Russia;
| | - Susanna Gordleeva
- Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 603950 Nizhny Novgorod, Russia;
- Center for Technologies in Robotics and Mechatronics Components, Innopolis University, 420500 Innopolis, Russia
| | - Alexey Zaikin
- Institute of Information Technology, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod, 603950 Nizhny Novgorod, Russia
- Institute for Women’s Health and Department of Mathematics, University College London, London WC1E 6BT, UK
- Centre for Analysis of Complex Systems, Sechenov University, 119991 Moscow, Russia
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14
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Whitwell HJ, Bacalini MG, Blyuss O, Chen S, Garagnani P, Gordleeva SY, Jalan S, Ivanchenko M, Kanakov O, Kustikova V, Mariño IP, Meyerov I, Ullner E, Franceschi C, Zaikin A. The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging. Front Aging Neurosci 2020; 12:136. [PMID: 32523526 PMCID: PMC7261843 DOI: 10.3389/fnagi.2020.00136] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 04/22/2020] [Indexed: 12/13/2022] Open
Abstract
Biological aging is a complex process involving multiple biological processes. These can be understood theoretically though considering them as individual networks-e.g., epigenetic networks, cell-cell networks (such as astroglial networks), and population genetics. Mathematical modeling allows the combination of such networks so that they may be studied in unison, to better understand how the so-called "seven pillars of aging" combine and to generate hypothesis for treating aging as a condition at relatively early biological ages. In this review, we consider how recent progression in mathematical modeling can be utilized to investigate aging, particularly in, but not exclusive to, the context of degenerative neuronal disease. We also consider how the latest techniques for generating biomarker models for disease prediction, such as longitudinal analysis and parenclitic analysis can be applied to as both biomarker platforms for aging, as well as to better understand the inescapable condition. This review is written by a highly diverse and multi-disciplinary team of scientists from across the globe and calls for greater collaboration between diverse fields of research.
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Affiliation(s)
- Harry J Whitwell
- Department of Chemical Engineering, Imperial College London, London, United Kingdom
| | | | - Oleg Blyuss
- School of Physics, Astronomy and Mathematics, University of Hertfordshire, Harfield, United Kingdom.,Department of Paediatrics and Paediatric Infectious Diseases, Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Shangbin Chen
- Britton Chance Centre for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, China
| | - Paolo Garagnani
- Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy
| | - Susan Yu Gordleeva
- Laboratory of Systems Medicine of Healthy Aging, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Sarika Jalan
- Complex Systems Laboratory, Discipline of Physics, Indian Institute of Technology Indore, Indore, India.,Centre for Bio-Science and Bio-Medical Engineering, Indian Institute of Technology Indore, Indore, India
| | - Mikhail Ivanchenko
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Oleg Kanakov
- Laboratory of Systems Medicine of Healthy Aging, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Valentina Kustikova
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Ines P Mariño
- Department of Biology and Geology, Physics and Inorganic Chemistry, Universidad Rey Juan Carlos, Madrid, Spain
| | - Iosif Meyerov
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Ekkehard Ullner
- Department of Physics (SUPA), Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen, United Kingdom
| | - Claudio Franceschi
- Laboratory of Systems Medicine of Healthy Aging, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.,Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Alexey Zaikin
- Department of Paediatrics and Paediatric Infectious Diseases, Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia.,Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.,Department of Mathematics, Institute for Women's Health, University College London, London, United Kingdom
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15
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Niizato T, Sakamoto K, Mototake YI, Murakami H, Tomaru T, Hoshika T, Fukushima T. Finding continuity and discontinuity in fish schools via integrated information theory. PLoS One 2020; 15:e0229573. [PMID: 32107495 PMCID: PMC7046263 DOI: 10.1371/journal.pone.0229573] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Accepted: 02/10/2020] [Indexed: 01/21/2023] Open
Abstract
Collective behaviours are known to be the result of diverse dynamics and are sometimes likened to living systems. Although many studies have revealed the dynamics of various collective behaviours, their main focus has been on the information processing performed by the collective, not on interactions within the collective. For example, the qualitative difference between three and four elements in a system has rarely been investigated. Tononi et al. proposed integrated information theory (IIT) to measure the degree of consciousness Φ. IIT postulates that the amount of information loss caused by the minimum information partition is equivalent to the degree of information integration in the system. This measure is not only useful for estimating the degree of consciousness but can also be applied to more general network systems. Here, we obtained two main results from the application of IIT (in particular, IIT 3.0) to the analysis of real fish schools (Plecoglossus altivelis). First, we observed that the discontinuity on 〈Φ(N)〉 distributions emerges for a school of four or more fish. This transition was not observed by measuring the mutual information or the sum of the transfer entropy. We also analysed the IIT on Boids simulations with respect to different coupling strengths; however, the results of the Boids model were found to be quite different from those of real fish. Second, we found a correlation between this discontinuity and the emergence of leadership. We discriminate leadership in this paper from its traditional meaning (e.g. defined by transfer entropy) because IIT-induced leadership refers not to group behaviour, as in other methods, but the degree of autonomy (i.e. group integrity). These results suggest that integrated information Φ can reveal the emergence of a new type of leadership which cannot be observed using other measures.
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Affiliation(s)
- Takayuki Niizato
- Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Kotaro Sakamoto
- University of Tsukuba, Leading Graduate School Doctoral Program in Human Biology, Tsukuba, Japan
| | | | - Hisashi Murakami
- University of Tokyo, Research Center for Advanced Science and Technology, Tokyo, Japan
| | - Takenori Tomaru
- Department of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Japan
| | - Tomotaro Hoshika
- Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Toshiki Fukushima
- Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Ibaraki, Japan
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16
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Tlaie A, Leyva I, Sendiña-Nadal I. High-order couplings in geometric complex networks of neurons. Phys Rev E 2019; 100:052305. [PMID: 31869909 DOI: 10.1103/physreve.100.052305] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Indexed: 12/29/2022]
Abstract
We explore the consequences of introducing higher-order interactions in a geometric complex network of Morris-Lecar neurons. We focus on the regime where traveling synchronization waves are observed from a first-neighbors-based coupling to evaluate the changes induced when higher-order dynamical interactions are included. We observe that the traveling-wave phenomenon gets enhanced by these interactions, allowing the activity to travel further in the system without generating pathological full synchronization states. This scheme could be a step toward a simple phenomenological modelization of neuroglial networks.
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Affiliation(s)
- A Tlaie
- Complex Systems Group & GISC, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain.,Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain.,Department of Applied Mathematics and Statistics, ETSIT Aeronáuticos, Universidad Politécnica de Madrid, 28040 Madrid, Spain
| | - I Leyva
- Complex Systems Group & GISC, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain.,Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain
| | - I Sendiña-Nadal
- Complex Systems Group & GISC, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain.,Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain
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17
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Gordleeva SY, Ermolaeva AV, Kastalskiy IA, Kazantsev VB. Astrocyte as Spatiotemporal Integrating Detector of Neuronal Activity. Front Physiol 2019; 10:294. [PMID: 31057412 PMCID: PMC6482266 DOI: 10.3389/fphys.2019.00294] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Accepted: 03/06/2019] [Indexed: 11/21/2022] Open
Abstract
The functional role of astrocyte calcium signaling in brain information processing was intensely debated in recent decades. This interest was motivated by high resolution imaging techniques showing highly developed structure of distal astrocyte processes. Another point was the evidence of bi-directional astrocytic regulation of neuronal activity. To analyze the effects of interplay of calcium signals in processes and in soma mediating correlations between local signals and the cell-level response of the astrocyte we proposed spatially extended model of the astrocyte calcium dynamics. Specifically, we investigated how spatiotemporal properties of Ca2+ dynamics in spatially extended astrocyte model can coordinate (e.g., synchronize) networks of neurons and synapses.
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Affiliation(s)
- Susan Yu Gordleeva
- Department of Neurotechnology, Lobachevsky State University, Nizhny Novgorod, Russia
| | - Anastasia V Ermolaeva
- Department of Neurotechnology, Lobachevsky State University, Nizhny Novgorod, Russia
| | | | - Victor B Kazantsev
- Department of Neurotechnology, Lobachevsky State University, Nizhny Novgorod, Russia
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