Dynamic transition of neuronal firing induced by abnormal astrocytic glutamate oscillation

Li, Jiajia; Tang, Jun; Ma, Jun; Du, Mengmeng; Wang, Rong

doi:10.1038/srep32343

Cited by 47 publications

(36 citation statements)

References 71 publications

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“…The modeling approaches for neurons varied depending on the author. Half of the studied publications utilized relatively complex biophysical neuron models, namely Hodgkin and Huxley ( 1952 ) model (Nadkarni and Jung, 2003 ; Sotero and Martínez-Cancino, 2010 ; Tewari and Majumdar, 2012a , b ; Tang et al, 2013 , 2016 ; Guo et al, 2017 ; Li et al, 2017 ), Traub et al ( 1991 ) model or its derivative Pinsky and Rinzel ( 1994 ) model (Nadkarni and Jung, 2004 , 2005 , 2007 ; Silchenko and Tass, 2008 ; Tewari and Parpura, 2013 ; Li et al, 2016a , b ), or Olufsen et al ( 2003 ) model (Di Garbo et al, 2007 ; Di Garbo, 2009 ). Simpler phenomenological models used in the studied publications were the FitzHugh-Nagumo (FitzHugh, 1961 ) model (Postnov et al, 2007 ), leaky integrate-and-fire (LIF, Gerstner and Kistler, 2002 ) model (Wade et al, 2011 , 2012 ; Amiri et al, 2016 ; De Pittà and Brunel, 2016 ; Nazari et al, 2017 ; Liu et al, 2018 ), Izhikevich ( 2007 ) model (Valenza et al, 2011 ; Nazari et al, 2015a , b , c ), Morris and Lecar ( 1981 ) model or its derivatives (Volman et al, 2007 ; Amiri et al, 2011b , 2013b ), and Suffczynski et al ( 2004 ) neuronal population model (Amiri et al, 2011a ).…”

Section: Resultsmentioning

confidence: 99%

“…Two of the newest models were provided by Li et al ( 2016a , 2017 ). However, these studies contained, to the best of our understanding, fundamental errors in the biological terminology.…”

Section: Resultsmentioning

confidence: 99%

“…Most of the astrocyte models presented here are based on ordinary differential equations (ODEs), modeling well-stirred astrocytes (see e.g., Nadkarni and Jung, 2003 ; Ullah et al, 2006 ; Volman et al, 2007 ; De Pittà et al, 2009a ; Goldberg et al, 2010 ; Dupont et al, 2011 ; Valenza et al, 2011 ; Amiri et al, 2012a ; Wade et al, 2012 ; Hadfield et al, 2013 ; Tang et al, 2013 ; Lallouette et al, 2014 ; Wallach et al, 2014 ; Li et al, 2016a ; Chan et al, 2017 ; Guo et al, 2017 ; Handy et al, 2017 ; Taheri et al, 2017 ). These models make the assumption that chemical species have the same concentrations throughout the entire volume of the astrocyte, which can also be called as average concentrations.…”

Section: Methodsmentioning

confidence: 99%

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Computational Models for Calcium-Mediated Astrocyte Functions

Manninen

Havela

Linne

2018

Front. Comput. Neurosci.

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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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Section: Resultsmentioning

confidence: 99%

“…Two of the newest models were provided by Li et al ( 2016a , 2017 ). However, these studies contained, to the best of our understanding, fundamental errors in the biological terminology.…”

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Computational Models for Calcium-Mediated Astrocyte Functions

Manninen

Havela

Linne

2018

Front. Comput. Neurosci.

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“…Many Ca 2+ -models include the dynamics of intracellular Ca 2+ concentration 373839434950515253, which is tightly related to the Ca 2+ influx through voltage-gated channels. It has been used in modeling373940 and experimental1516 studies to characterize dendritic Ca 2+ spike.…”

Section: Discussionmentioning

confidence: 99%

Action potential initiation in a two-compartment model of pyramidal neuron mediated by dendritic Ca2+ spike

Wang

Wei

et al. 2017

Sci Rep

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Dendritic Ca2+ spike endows cortical pyramidal cell with powerful ability of synaptic integration, which is critical for neuronal computation. Here we propose a two-compartment conductance-based model to investigate how the Ca2+ activity of apical dendrite participates in the action potential (AP) initiation to affect the firing properties of pyramidal neurons. We have shown that the apical input with sufficient intensity triggers a dendritic Ca2+ spike, which significantly boosts dendritic inputs as it propagates to soma. Such event instantaneously shifts the limit cycle attractor of the neuron and results in a burst of APs, which makes its firing rate reach a plateau steady-state level. Delivering current to two chambers simultaneously increases the level of neuronal excitability and decreases the threshold of input-output relation. Here the back-propagating APs facilitate the initiation of dendritic Ca2+ spike and evoke BAC firing. These findings indicate that the proposed model is capable of reproducing in vitro experimental observations. By determining spike initiating dynamics, we have provided a fundamental link between dendritic Ca2+ spike and output APs, which could contribute to mechanically interpreting how dendritic Ca2+ activity participates in the simple computations of pyramidal neuron.

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“…They have also elaborated the relationships between firing rate, temperature, information transmission, and the metabolic energy they consume. Based on their method, Ju et al (2016) have estimated the energy consumption by AP conduction along axons with different geometric shapes; Li et al (2016) have investigated the energy cost of the seizure-like discharges induced by abnormal astrocytic glutamate oscillation; our earlier study (Yi et al, 2015a) has characterized the energy efficiency of neurons associated with different dynamics of firing threshold. These earlier investigations attest the predictive power of this method for quantifying the metabolic energy involved in the dynamics of biophysical model neurons.…”

Section: Introductionmentioning

confidence: 99%

Metabolic Energy of Action Potentials Modulated by Spike Frequency Adaptation

Wang

et al. 2016

Front. Neurosci.

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Spike frequency adaptation (SFA) exists in many types of neurons, which has been demonstrated to improve their abilities to process incoming information by synapses. The major carrier used by a neuron to convey synaptic signals is the sequences of action potentials (APs), which have to consume substantial metabolic energies to initiate and propagate. Here we use conductance-based models to investigate how SFA modulates the AP-related energy of neurons. The SFA is attributed to either calcium-activated K+ (IAHP) or voltage-activated K+ (IM) current. We observe that the activation of IAHP or IM increases the Na+ load used for depolarizing membrane, while produces few effects on the falling phase of AP. Then, the metabolic energy involved in Na+ current significantly increases from one AP to the next, while for K+ current it is less affected. As a consequence, the total energy cost by each AP gets larger as firing rate decays down. It is also shown that the minimum Na+ charge needed for the depolarization of each AP is unaffected during the course of SFA. This indicates that the activation of either adaptation current makes APs become less efficient to use Na+ influx for their depolarization. Further, our simulations demonstrate that the different biophysical properties of IM and IAHP result in distinct modulations of metabolic energy usage for APs. These investigations provide a fundamental link between adaptation currents and neuronal energetics, which could facilitate to interpret how SFA participates in neuronal information processing.

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Dynamic transition of neuronal firing induced by abnormal astrocytic glutamate oscillation

Cited by 47 publications

References 71 publications

Computational Models for Calcium-Mediated Astrocyte Functions

Computational Models for Calcium-Mediated Astrocyte Functions

Action potential initiation in a two-compartment model of pyramidal neuron mediated by dendritic Ca2+ spike

Metabolic Energy of Action Potentials Modulated by Spike Frequency Adaptation

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