Models that contain the Model Concept : Signaling pathways

(Signaling chemical pathways are typically described with kinetic equations which model the reactions of molecules.)
Re-display model names without descriptions
    Models   Description
1.  A kinetic model of dopamine- and calcium-dependent striatal synaptic plasticity (Nakano et al. 2010)
A signaling pathway model of spines that express D1-type dopamine receptors was constructed to analyze the dynamic mechanisms of dopamine- and calcium-dependent plasticity. The model incorporated all major signaling molecules, including dopamine- and cyclic AMP-regulated phosphoprotein with a molecular weight of 32 kDa (DARPP32), as well as AMPA receptor trafficking in the post-synaptic membrane. Simulations with dopamine and calcium inputs reproduced dopamine- and calcium-dependent plasticity. Further in silico experiments revealed that the positive feedback loop consisted of protein kinase A (PKA), protein phosphatase 2A (PP2A), and the phosphorylation site at threonine 75 of DARPP-32 (Thr75) served as the major switch for inducing LTD and LTP. The present model elucidated the mechanisms involved in bidirectional regulation of corticostriatal synapses and will allow for further exploration into causes and therapies for dysfunctions such as drug addiction."
2.  A model of cerebellar LTD including RKIP inactivation of Raf and MEK (Hepburn et al 2017)
An updated stochastic model of cerebellar Long Term Depression (LTD) with improved realism. Dissociation of Raf kinase inhibitor protein (RKIP) from Mitogen-activated protein kinase kinase (MEK) and Raf kinase are added to an earlier published model. Calcium dynamics is updated as a constant-rate influx to more closely match experiment. AMPA receptor interactions are improved by adding phosphorylation and dephosphorylation of AMPA receptors when bound to glutamate receptor interacting protein (GRIP). The model is tuned to reproduce experimental calcium peak vs LTD amplitude curves accurately at 4 different calcium pulse durations.
3.  A multiscale approach to analyze circadian rhythms (Vasalou & Henson, 2010) (CellML)
" ... We developed a firing rate code model to incorporate known electrophysiological properties of SCN (suprachiasmatic nucleus) pacemaker cells, including circadian dependent changes in membrane voltage and ion conductances. Calcium dynamics were included in the model as the putative link between electrical firing and gene expression. Individual ion currents exhibited oscillatory patterns matching experimental data both in current levels and phase relationships. VIP and GABA neurotransmitters, which encode synaptic signals across the SCN, were found to play critical roles in daily oscillations of membrane excitability and gene expression. Blocking various mechanisms of intracellular calcium accumulation by simulated pharmacological agents (nimodipine, IP3- and ryanodine-blockers) reproduced experimentally observed trends in firing rate dynamics and core-clock gene transcription. The intracellular calcium concentration was shown to regulate diverse circadian processes such as firing frequency, gene expression and system periodicity. The model predicted a direct relationship between firing frequency and gene expression amplitudes, demonstrated the importance of intracellular pathways for single cell behavior and provided a novel multiscale framework which captured characteristics of the SCN at both the electrophysiological and gene regulatory levels."
4.  A multiscale approach to analyze circadian rhythms (Vasalou & Henson, 2010) (SBML)
" ... We developed a firing rate code model to incorporate known electrophysiological properties of SCN (suprachiasmatic nucleus) pacemaker cells, including circadian dependent changes in membrane voltage and ion conductances. Calcium dynamics were included in the model as the putative link between electrical firing and gene expression. Individual ion currents exhibited oscillatory patterns matching experimental data both in current levels and phase relationships. VIP and GABA neurotransmitters, which encode synaptic signals across the SCN, were found to play critical roles in daily oscillations of membrane excitability and gene expression. Blocking various mechanisms of intracellular calcium accumulation by simulated pharmacological agents (nimodipine, IP3- and ryanodine-blockers) reproduced experimentally observed trends in firing rate dynamics and core-clock gene transcription. The intracellular calcium concentration was shown to regulate diverse circadian processes such as firing frequency, gene expression and system periodicity. The model predicted a direct relationship between firing frequency and gene expression amplitudes, demonstrated the importance of intracellular pathways for single cell behavior and provided a novel multiscale framework which captured characteristics of the SCN at both the electrophysiological and gene regulatory levels."
5.  A systems model of Parkinson’s disease using biochemical systems theory (Sasidharakurup et al. 2017)
Major pathways involving in Parkinson's disease (PD) such as alphasynuclein aggregation, dopamine synthesis, lewy body formation, tau phosphorylation, parkin, and apoptosis were modeled using stochastic differential equations. Pathways were modeled and simulated using the biochemical pathway visualization program CellDesigner, a modeling tool for gene-regulatory and biochemical networks that support graphical notation and listing of symbols. The model allows a qualitative analysis of PD and a key signalling pathways for evaluating PD treatment conditions relating pathophysiology to molecular concentration changes recorded in experiments.
6.  Active dendrites shape signaling microdomains in hippocampal neurons (Basak & Narayanan 2018)
The spatiotemporal spread of biochemical signals in neurons and other cells regulate signaling specificity, tuning of signal propagation, along with specificity and clustering of adaptive plasticity. Theoretical and experimental studies have demonstrated a critical role for cellular morphology and the topology of signaling networks in regulating this spread. In this study, we add a significantly complex dimension to this narrative by demonstrating that voltage-gated ion channels (A-type Potassium channels and T-type Calcium channels) on the plasma membrane could actively amplify or suppress the strength and spread of downstream signaling components. We employed a multiscale, multicompartmental, morphologically realistic, conductance-based model that accounted for the biophysics of electrical signaling and the biochemistry of calcium handling and downstream enzymatic signaling in a hippocampal pyramidal neuron. We chose the calcium – calmodulin – calcium/calmodulin-dependent protein kinase II (CaMKII) – protein phosphatase 1 (PP1) signaling pathway owing to its critical importance to several forms of neuronal plasticity, and employed physiologically relevant theta-burst stimulation (TBS) or theta-burst pairing (TBP) protocol to initiate a calcium microdomain through NMDAR activation at a synapse.
7.  An allosteric kinetics of NMDARs in STDP (Urakubo et al. 2008)
"... We developed a detailed biophysical model of STDP and found that the model required spike timing-dependent distinct suppression of NMDARs by Ca2+-calmodulin. This led us to predict an allosteric kinetics of NMDARs: a slow and rapid suppression of NMDARs by Ca2+-calmodulin with prespiking -> postspiking and postspiking -> prespiking, respectively. We found that the allosteric kinetics, but not the conventional kinetics, is consistent with specific features of amplitudes and peak time of NMDAR-mediated EPSPs in experiments. ..." See paper for more and details.
8.  An integrative dynamic model of brain energy metabolism (Coultier et al 2009)
An integrative, systems approach to the modelling of brain energy metabolism is presented. Mechanisms such as glutamate cycling between neurons and astrocytes and glycogen storage in astrocytes have been implemented. A unique feature of the model is its calibration using in vivo data of brain glucose and lactate from freely moving rats under various stimuli. The model has been used to perform simulated perturbation experiments that show that glycogen breakdown in astrocytes is significantly activated during sensory (tail pinch) stimulation. This mechanism provides an additional input of energy substrate during high consumption phases. By way of validation, data from the perfusion of 50?µM propranolol in the rat brain was compared with the model outputs. Propranolol affects the glucose dynamics during stimulation, and this was accurately reproduced in the model by a reduction in the glycogen breakdown in astrocytes. The model’s predictive capacity was verified by using data from a sensory stimulation (restraint) that was not used for model calibration. Finally, a sensitivity analysis was conducted on the model parameters, this showed that the control of energy metabolism and transport processes are critical in the metabolic behaviour of cerebral tissue.
9.  Boolean network-based analysis of the apoptosis network (Mai and Liu 2009)
"To understand the design principles of the molecular interaction network associated with the irreversibility of cell apoptosis and the stability of cell surviving, we constructed a Boolean network integrating both the intrinsic and extrinsic pro-apoptotic pathways with pro-survival signal transduction pathways. We performed statistical analyses of the dependences of cell fate on initial states and on input signals. The analyses reproduced the well-known pro- and anti-apoptotic effects of key external signals and network components. We found that the external GF signal by itself did not change the apoptotic ratio from randomly chosen initial states when there is no external TNF signal, but can significantly offset apoptosis induced by the TNF signal. ..."
10.  Ca(2+) oscillations based on Ca-induced Ca-release (Dupont et al 1991)
We consider a simple, minimal model for signal-induced Ca2+ oscillations based on Ca(2+)-induced Ca2+ release. The model takes into account the existence of two pools of intracellular Ca2+, namely, one sensitive to inositol 1,4,5 trisphosphate (InsP3) whose synthesis is elicited by the stimulus, and one insensitive to InsP3. See paper for more and details.
11.  Ca+/HCN channel-dependent persistent activity in multiscale model of neocortex (Neymotin et al 2016)
"Neuronal persistent activity has been primarily assessed in terms of electrical mechanisms, without attention to the complex array of molecular events that also control cell excitability. We developed a multiscale neocortical model proceeding from the molecular to the network level to assess the contributions of calcium regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in providing additional and complementary support of continuing activation in the network. ..."
12.  CA1 oriens alveus interneurons: signaling properties (Minneci et al. 2007)
The model supports the experimental findings showing that the dynamic interaction between cells with various firing patterns could differently affect GABAergic signaling, leading to a wide range of interneuronal communication within the hippocampal network.
13.  CA1 pyramidal cell receptor dependent cAMP dynamics (Chay et al. 2016)
We use a combination of live cell imaging and stochastic modeling of signaling pathways to investigate how noradrenergic receptor stimulation interacts with calcium to control cAMP, required for synaptic plasticity and memory in the hippocampus. Our simulation results explain the mechanism whereby prior noradrenergic receptor stimulation does not enhance the subsequent NMDA stimulated cAMP elevation. Specifically, our results demonstrate the the negative feedback loop from cAMP, through PKA, to PDE4 cannot explain the results, and that switching of the noradrenergic receptor from Gs to Gi is required.
14.  Ca2+ oscillations in single astrocytes (Lavrentovich and Hemkin 2008) (python) (Manninen et al 2017)
We tested the reproducibility and comparability of four astrocyte models (Manninen, Havela, Linne, 2017). Model by Lavrentovich and Hemkin (2008) was one of them. We implemented and ran the model by Lavrentovich and Hemkin (2008) using Jupyter Notebook. Model code produces results of Figure 1 in Manninen, Havela, Linne (2017).
15.  Ca2+ requirements for Long-Term Depression in Purkinje Cells (Criseida Zamora et al 2018)
An updated stochastic model of cerebellar Long-Term Depression (LTD) to study the requirements of calcium to induce LTD. Calcium signal is generated as a train of calcium pulses and this can be modulated by its amplitude, frequency, width and number of pulses. CaMKII activation and its regulatory pathway are added to an earlier published model to study the sensitivity to calcium frequency. The model is useful to investigate systematically the dependence of LTD induction on calcium stimuli parameters.
16.  Calcium waves and mGluR-dependent synaptic plasticity in CA1 pyr. neurons (Ashhad & Narayanan 2013)
A morphologically realistic, conductance-based model equipped with kinetic schemes that govern several calcium signalling modules and pathways in CA1 pyramidal neurons
17.  CaMKII system exhibiting bistability with respect to calcium (Graupner and Brunel 2007)
"... We present a detailed biochemical model of the CaMKII autophosphorylation and the protein signaling cascade governing the CaMKII dephosphorylation. ... it is shown that the CaMKII system can qualitatively reproduce results of plasticity outcomes in response to spike-timing dependent plasticity (STDP) and presynaptic stimulation protocols. This shows that the CaMKII protein network can account for both induction, through LTP/LTD-like transitions, and storage, due to its bistability, of synaptic changes."
18.  Cell signaling/ion channel variability effects on neuronal response (Anderson, Makadia, et al. 2015)
" ... We evaluated the impact of molecular variability in the expression of cell signaling components and ion channels on electrophysiological excitability and neuromodulation. We employed a computational approach that integrated neuropeptide receptor-mediated signaling with electrophysiology. We simulated a population of neurons in which expression levels of a neuropeptide receptor and multiple ion channels were simultaneously varied within a physiological range. We analyzed the effects of variation on the electrophysiological response to a neuropeptide stimulus. ..."
19.  Dendritic spine geometry, spine apparatus organization: spatiotemporal Ca dynamics (Bell et al 2019)
" ... we systematically investigated the relationship between the shape and size of both the spine head and spine apparatus, a specialized endoplasmic reticulum compartment within the spine head, in modulating rapid calcium dynamics using mathematical modeling. ..."
20.  Differential interactions between Notch and ID factors control neurogenesis (Boareto et al 2017)
"During embryonic and adult neurogenesis, neural stem cells (NSCs) generate the correct number and types of neurons in a temporospatial fashion. Control of NSC activity and fate is crucial for brain formation and homeostasis. Neurogenesis in the embryonic and adult brain differ considerably, but Notch signaling and inhibitor of DNA-binding (ID) factors are pivotal in both. Notch and ID factors regulate NSC maintenance; however, it has been difficult to evaluate how these pathways potentially interact. Here, we combined mathematical modeling with analysis of single-cell transcriptomic data to elucidate unforeseen interactions between the Notch and ID factor pathways. ..."
21.  Discrimination on behavioral time-scales mediated by reaction-diffusion in dendrites (Bhalla 2017)
Sequences of events are ubiquitous in sensory, motor, and cognitive function. Key computational operations, including pattern recognition, event prediction, and plasticity, involve neural discrimination of spatio-temporal sequences. Here we show that synaptically-driven reaction diffusion pathways on dendrites can perform sequence discrimination on behaviorally relevant time-scales. We used abstract signaling models to show that selectivity arises when inputs at successive locations are aligned with, and amplified by, propagating chemical waves triggered by previous inputs. We incorporated biological detail using sequential synaptic input onto spines in morphologically, electrically, and chemically detailed pyramidal neuronal models based on rat data.
22.  Dopamine activation of signaling pathways in a medium spiny projection neuron (Oliveira et al. 2012)
Large scale stochastic reaction-diffusion model of signaling pathways in a medium spiny projection neuron dendrite with spines to investigate whether the critical function of anchoring is to locate PKA near the cAMP that activates it or near its targets, such as AMPA receptors located in the post-synaptic density. Simulations, implemented in NeuroRD, show that PKA colocalization with adenylate cyclase, either in the spine head or in the dendrite, leads to greater phosphorylation of DARPP-32 Thr34 and AMPA receptor GluA1 Ser845 than when PKA is anchored away from adenylate cyclase.
23.  Emergent properties of networks of biological signaling pathways (Bhalla, Iyengar 1999)
Biochemical signaling networks were constructed with experimentally obtained constants and analyzed by computational methods to understand their role in complex biological processes. These networks exhibit emergent properties such as integration of signals across multiple time scales, generation of distinct outputs depending on input strength and duration, and self-sustaining feedback loops. Properties of signaling networks raise the possibility that information for "learned behavior" of biological systems may be stored within intracellular biochemical reactions that comprise signaling pathways.
24.  Endocannabinoid dynamics gate spike-timing dependent depression and potentiation (Cui et al 2016)
The endocannabinoid (eCB) system is considered involved in synaptic depression. Recent reports have also linked eCBs to synaptic potentiation. However it is not known how eCB signaling may support such bidirectionality. To question the mechanisms of this phenomena in spike-timing dependent plasticity (STDP) at corticostriatal synapses, we combined electrophysiology experiments with biophysical modeling. We demonstrate that STDP is controlled by eCB levels and dynamics: prolonged and moderate levels of eCB lead to eCB-mediated long-term depression (eCB-tLTD) while short and large eCB transients produce eCB-mediated long-term potentiation (eCB-tLTP). Therefore, just like neurotransmitters glutamate or GABA, eCB form a bidirectional system.
25.  Endothelin action on pituitary latotrophs (Bertram et al. 2006)
Endothelin (ET-1, -2, and -3 designate three genes which produce different endothelin isopeptides) is a prolactin inhibiting substance of hypothalmic origin. ET-1 binding is part of at least four G protein signaling pathways in lactotrophs. The sequence of events in these pathways following the presentation of nano- and pico-molar concentrations of ET-1 is modeled in the paper.
26.  Excitation-contraction coupling/mitochondrial energetics (ECME) model (Cortassa et al. 2006)
"An intricate network of reactions is involved in matching energy supply with demand in the heart. This complexity arises because energy production both modulates and is modulated by the electrophysiological and contractile activity of the cardiac myocyte. Here, we present an integrated mathematical model of the cardiac cell that links excitation-contraction coupling with mitochondrial energy generation. The dynamics of the model are described by a system of 50 ordinary differential equations. The formulation explicitly incorporates cytoplasmic ATP-consuming processes associated with force generation and ion transport, as well as the creatine kinase reaction. Changes in the electrical and contractile activity of the myocyte are coupled to mitochondrial energetics through the ATP, Ca21, and Na1 concentrations in the myoplasmic and mitochondrial matrix compartments. ..."
27.  Firing neocortical layer V pyramidal neuron (Reetz et al. 2014; Stadler et al. 2014)
Neocortical Layer V model with firing behaviour adjusted to in vitro observations. The model was used to investigate the effects of IFN and PKC on the excitability of neurons (Stadler et al 2014, Reetz et al. 2014). The model contains new channel simulations for HCN1, HCN2 and the big calcium dependent potassium channel BK.
28.  Genetic, biochemical and bioelectrical dynamics in pattern regulation (Pietak & Levin 2017)
"Gene regulatory networks (GRNs) describe interactions between gene products and transcription factors that control gene expression. In combination with reaction–diffusion models, GRNs have enhanced comprehension of biological pattern formation. However, although it is well known that biological systems exploit an interplay of genetic and physical mechanisms, instructive factors such as transmembrane potential (Vmem) have not been integrated into full GRN models. Here we extend regulatory networks to include bioelectric signalling, developing a novel synthesis: the bioelectricity-integrated gene and reaction (BIGR) network. ..."
29.  Glutamate-evoked Ca2+ oscillations in single astrocytes (De Pitta et al. 2009) (Manninen et al 2017)
We tested the reproducibility and comparability of four astrocyte models (Manninen, Havela, Linne, 2017). Model by De Pitta et al. (2009) was one of them. We implemented and ran the model by De Pitta et al. (2009) using Jupyter Notebook. Model code produces results of Figure 1 and Figures 3-5 in Manninen, Havela, Linne (2017).
30.  Glutamate-evoked Ca2+ oscillations in single astrocytes (Modified from Dupont et al. 2011)
We tested the reproducibility and comparability of four astrocyte models (Manninen, Havela, Linne, 2017). Model by Dupont et al. (2011) was one of them, but we had to modify the model to get more similar results as in the original publication. We implemented and ran the modified model using Jupyter Notebook. Model code produces results of Figure 1 and Figures 3-5 in Manninen, Havela, Linne (2017).
31.  Gq coupled signaling pathways involved in striatal synaptic plasticity (Kim et al. 2013)
Model of Gq coupled signaling pathways underlying synaptic plasticity in striatal medium spiny projection neurons. Reactions and diffusion are implemented stochastically in a dendrite with one or more diffusionally coupled spines. Simulations demonstrate that theta burst stimulation, which produces LTP, increases the ratio of PKC:2AG as compared to 20 Hz stimulation, which produces LTD.
32.  Hippocampus CA1: Simulations of LTP signaling pathways (Kim M et al. 2011)
This is a multi-compartmental, stochastic version of the Kim et al. 2010 paper. There are a few additional reactions, and some of the rate constants have been updated. It addresses the role of molecule anchoring in PKA dependent hippocampal LTP.
33.  Hippocampus CA1: Temporal sensitivity of signaling pathways underlying LTP (Kim et al. 2010)
Temporal sensitivity of signaling pathways underlying L-LTP. Single compartment, deterministic model of calcium and dopamine activated pathways, leading to CaMKII and PKA activation. Experimental verification of model prediction.
34.  Long term potentiation, LTP, protein synthesis, proteasome (Smolen et al. 2018)
The transition from early long-term potentiation (E-LTP) to late LTP (L-LTP) involves protein synthesis and degradation. L-LTP is blocked by inhibiting either protein synthesis or proteasome-dependent degradation prior to and during a tetanic stimulus, but paradoxically, L-LTP is not blocked when synthesis and degradation are inhibited simultaneously, suggesting counter-acting positive and negative proteins regulate L-LTP. To investigate this paradox, we modeled LTP at the Schaffer collateral synapse. Nine differential equations describe the levels of positive and negative regulator proteins (PP and NP) and transitions among five discrete synaptic states, a basal state (BAS), three E-LTP states (EP1, EP2, ED), and a L-LTP state (LP). A stimulus initiates the transition from BAS to EP1 and from EP1 to EP2, initiates the synthesis of PP and NP, and activates the ubiquitin-proteasome system (UPS). UPS mediates transitions of EP1 and EP2 to ED and the degradation of NP. The conversion of E-LTP to L-LTP is mediated by a PP-dependent transition from ED to LP. NP mediates reversal of EP2 to BAS. This model simulates empirical observations: 1) normal L-LTP, 2) block by either proteasome inhibitor or protein synthesis inhibitor alone, and 3) preservation of L-LTP when both inhibitors are applied together. Elements of this abstract model can be correlated with specific molecules and processes. Moreover, the model makes testable predictions, such as a unique synaptic state ED that precedes the transition to L-LTP, and a time window for the action of the UPS (during the transitions from EP1 and EP2 to ED). Tests of these predictions will provide insights into the processes of long-term synaptic plasticity.
35.  Model of a BDNF feedback loop (Zhang et al 2016)
"Inhibitory avoidance (IA) training in rodents initiates a molecular cascade within hippocampal neurons. This cascade contributes to the transition of short- to long-term memory (i.e., consolidation). Here, a differential equation-based model was developed to describe a positive feedback loop within this molecular cascade. The feedback loop begins with an IA-induced release of brain-derived neurotrophic factor (BDNF), which in turn leads to rapid phosphorylation of the cAMP response element-binding protein (pCREB), and a subsequent increase in the level of the beta isoform of the CCAAT/enhancer binding protein (C/EBPbeta). ... " See paper for more.
36.  Model of AngII signaling and membrane electrophysiology (Makadia, Anderson, Fey et al., 2015)
We developed a novel multiscale model to bridge neuropeptide receptor-activated signaling pathway with membrane electrophysiology. The model studies the effects of Angiotensin II (AngII) on neuronal excitability changes mediated by signaling dynamics and downstream phosphorylation of ion channels. The multiscale model was implemented as a set of ordinary differential equations solved using the ode15s solver in Matlab (Mathworks, USA). The signaling reactions were modeled with either mass-action or Michaelis--Menten kinetics and ion channel electrophysiology was modeled according to the Hodgkin-Huxley formalism. These models were initially validated against their respective data domains independently and were integrated to develop a multiscale model of signaling and electrophysiology.
37.  Model of calcium oscillations in olfactory cilia (Reidl et al. 2006)
Simulation of experiments on olfactory receptor neurons (ORNs). Focussing on the negative feedback that calcium (through calmodulin) has on its own influx through CNG channels, this model is able to reproduce both calcium oscillations as well as adaptation behaviour as seen in experiments done with ORNs.
38.  Model of DARPP-32 phosphorylation in striatal medium spiny neurons (Lindskog et al. 2006)
The work describes a model of how transient calcium and dopamine inputs might affect phosphorylation of DARPP-32 in the medium spiny neurons in the striatum. The model is relevant for understanding both the "three-factor rule" for synaptic plasticity in corticostriatal synapses, and also for relating reinforcement learning theories to biology.
39.  Models of Na channels from a paper on the PKC control of I Na,P (Baker 2005)
"The tetrodotoxin-resistant (TTX-r) persistent Na(+) current, attributed to Na(V)1.9, was recorded in small (< 25 mum apparent diameter) dorsal root ganglion (DRG) neurones cultured from P21 rats and from adult wild-type and Na(V)1.8 null mice. ... Numerical simulation of the up-regulation qualitatively reproduced changes in sensory neurone firing properties. ..." Note: models of NaV1.8 and NaV1.9 and also persistent and transient Na channels that collectively model Nav 1.1, 1.6, and 1.7 are present in this model.
40.  Moose/PyMOOSE: interoperable scripting in Python for MOOSE (Ray and Bhalla 2008)
" ... We report the integration of Python scripting with the Multi-scale Object Oriented Simulation Environment (MOOSE). MOOSE is a general-purpose simulation system for compartmental neuronal models and for models of signaling pathways based on chemical kinetics. We show how the Python-scripting version of MOOSE, PyMOOSE, combines the power of a compiled simulator with the versatility and ease of use of Python. ... "
41.  Multiscale model of olfactory receptor neuron in mouse (Dougherty 2009)
Collection of XPP (.ode) files simulating the signal transduction (slow) and action potential (fast) currents in the olfactory receptor neuron of mouse. Collection contains model configured for dual odorant pulse delivery and model configured for prolonged odorant delivery. For those interested more in transduction processes, each whole cell recording model comes with a counter part file configured to show just the slow transduction current for ease of use and convenience. These transduction-only models typically run faster than the full multi-scale models but do not demonstrate action potentials.
42.  Multiscale simulation of the striatal medium spiny neuron (Mattioni & Le Novere 2013)
"… We present a new event-driven algorithm to synchronize different neuronal models, which decreases computational time and avoids superfluous synchronizations. The algorithm is implemented in the TimeScales framework. We demonstrate its use by simulating a new multiscale model of the Medium Spiny Neuron of the Neostriatum. The model comprises over a thousand dendritic spines, where the electrical model interacts with the respective instances of a biochemical model. Our results show that a multiscale model is able to exhibit changes of synaptic plasticity as a result of the interaction between electrical and biochemical signaling. …"
43.  Olfactory bulb network: neurogenetic restructuring and odor decorrelation (Chow et al. 2012)
Adult neurogenesis in the olfactory bulb has been shown experimentally to contribute to perceptual learning. Using a computational network model we show that fundamental aspects of the adult neurogenesis observed in the olfactory bulb -- the persistent addition of new inhibitory granule cells to the network, their activity-dependent survival, and the reciprocal character of their synapses with the principal mitral cells -- are sufficient to restructure the network and to alter its encoding of odor stimuli adaptively so as to reduce the correlations between the bulbar representations of similar stimuli. The model captures the experimentally observed role of neurogenesis in perceptual learning and the enhanced response of young granule cells to novel stimuli. Moreover, it makes specific predictions for the type of odor enrichment that should be effective in enhancing the ability of animals to discriminate similar odor mixtures. NSF grant DMS-0719944.
44.  Paired turbulence and light effect on calcium increase in Hermissenda (Blackwell 2004)
The sea slug Hermissenda learns to associate light and hair cell stimulation, but not when the stimuli are temporally uncorrelated...These issues were addressed using a multi-compartmental computer model of phototransduction, calcium dynamics, and ionic currents of the Hermissenda photoreceptor...simulations show that a potassium leak channel, which closes with an increase in calcium, is required to produce both the untrained LLD and the enhanced LLD due to the decrease in voltage dependent potassium currents.
45.  Regulation of KCNQ2/KCNQ3 current by G protein cycling (Suh et al 2004)
Receptor-mediated modulation of KCNQ channels regulates neuronal excitability. This study concerns the kinetics and mechanism of M1 muscarinic receptor-mediated regulation of the cloned neuronal M channel, KCNQ2/KCNQ3 (Kv7.2/Kv7.3). ... observations were successfully described by a kinetic model representing biochemical steps of the signaling cascade using published rate constants where available. The model supports the following sequence of events for this Gq-coupled signaling: A classical G-protein cycle, including competition for nucleotide-free G-protein by all nucleotide forms and an activation step requiring Mg2, followed by G-protein-stimulated phospholipase C and hydrolysis of PIP2, and finally PIP2 dissociation from binding sites for inositol lipid on the channels so that KCNQ current was suppressed. See paper for details and more.
46.  Reproducibility and comparability of models for astrocyte Ca2+ excitability (Manninen et al 2017)
We tested the reproducibility and comparability of four astrocyte models (Manninen, Havela, Linne, 2017). We implemented and ran the python models using Jupyter Notebook. Model code produces results of Figure 1 and Figures 3-5 and partly Figure 2 in Manninen, Havela, Linne (2017).
47.  Rescue of plasticity by a computationally predicted protocol (Liu et al. 2013)
" ... A computational model, which simulated molecular processes underlying long-term synaptic facilitation (LTF) induction, predicted a rescue protocol of five pulses of 5-HT at non-uniform interstimulus intervals that overcame the consequences of reduced CREB-binding protein (CBP) and restored LTF. ..."
48.  Roles of essential kinases in induction of late hippocampal LTP (Smolen et al., 2006)
"… Convergence of multiple kinase activities to induce L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply with the number of brief (tetanic) electrical stimuli. The model simulates tetanic, -burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to delineate mechanisms underlying L-LTP induction and expression. …"
49.  Signaling pathways In D1R containing striatal spiny projection neurons (Blackwell et al 2018)
We implemented a mechanistic model of signaling pathways activated by dopamine D1 receptors, acetylcholine receptors, and glutamate. We use our novel, computationally efficient simulator, NeuroRD, to simulate stochastic interactions both within and between dendritic spines. Results show that the combined activity of several key plasticity molecules correctly predicts the occurrence of either LTP, LTD or no plasticity for numerous experimental protocols.
50.  Signaling pathways underlying LTP in hippocampal CA1 pyramidal cells (Jedrzejewska-Szmek et al 2017)
" ...We investigated whether the diverse experimental evidence can be unified by creating a spatial, mechanistic model of multiple signaling pathways in hippocampal CA1 neurons. Our results show that the combination of activity of several key kinases can predict the occurrence of long-lasting forms of LTP for multiple experimental protocols. ..."
51.  Simulation of calcium signaling in fine astrocytic processes (Denizot et al 2019)
This model corresponds to the model presented in Denizot et al, 2019. The model indicates that the frequency of calcium signals crucially depends on the spatial organization of the IP3R channels, including their clustering and co-localization with the other sources of calcium influx to the cytosol. Spontaneous calcium signals generated by the model with realistic PAPs volume and calcium concentration successfully reproduce spontaneous calcium transients that we measured in calcium micro-domains with confocal microscopy. To our knowledge, this model is the first model suited to the investigation of spontaneous calcium dynamics in fine astrocytic processes, a crucial step towards a better understanding of the spatio-temporal integration of astrocyte signals in response to neuronal activity.
52.  Spike timing detection in different forms of LTD (Doi et al 2005)
To understand the spike-timing detection mechanisms in cerebellar long-term depression (LTD), we developed a kinetic model of Ca dynamics within a Purkinje dendritic spine. In our kinetic simulation, IP3 was first produced via the metabotropic pathway of parallel fiber (PF) inputs, and the Ca influx in response to the climbing fiber (CF) input triggered regenerative Ca-induced Ca release from the internal stores via the IP3 receptors activated by the increased IP3. The delay in IP3 increase caused by the PF metabotropic pathway generated the optimal PF–CF interval. The Ca dynamics revealed a threshold for large Ca2 release that decreased as IP3 increased, and it coherently explained the different forms of LTD. See paper for more and details.
53.  Spontaneous calcium oscillations in astrocytes (Lavrentovich and Hemkin 2008)
" ... We propose here a mathematical model of how spontaneous Ca2+ oscillations arise in astrocytes. This model uses the calcium-induced calcium release and inositol cross-coupling mechanisms coupled with a receptor-independent method for producing inositol (1,4,5)-trisphosphate as the heart of the model. By computationally mimicking experimental constraints we have found that this model provides results that are qualitatively similar to experiment."
54.  Spontaneous calcium oscillations in single astrocytes (Riera et al. 2011) (Manninen et al 2017)
We tested the reproducibility and comparability of four astrocyte models (Manninen, Havela, Linne, 2017). Model by Riera et al. (2011) was one of them. We implemented and ran the model by Riera et al. (2011) using Jupyter Notebook. Model codes produce results of Figures 1 and 2 in Manninen, Havela, Linne (2017).
55.  STDP and NMDAR Subunits (Gerkin et al. 2007)
The paper argues for competing roles of NR2A- and NR2B-containing NMDARs in spike-timing-dependent plasticity. This simple dynamical model recapitulates the results of STDP experiments involving selective blockers of NR2A- and NR2B-containing NMDARs, for which the stimuli are pre- and postsynaptic spikes in varying combinations. Experiments were done using paired recordings from glutamatergic neurons in rat hippocampal cultures. This model focuses on the dynamics of the putative potentiation and depression modules themselves, and their interaction For detailed dynamics involving NMDARs and Ca2+ transients, see Rubin et al., J. Neurophys., 2005.
56.  Stochastic model of the olfactory cilium transduction and adaptation (Antunes et al 2014)
" ... In this work, we have combined stochastic computational modeling and a systematic pharmacological study of different signaling pathways to investigate their impact during short-term adaptation (STA). ... These results suggest that G-coupled receptors (GPCRs) cycling is involved with the occurrence of STA. To gain insights on the dynamical aspects of this process, we developed a stochastic computational model. The model consists of the olfactory transduction currents mediated by the cyclic nucleotide gated (CNG) channels and calcium ion (Ca2+)-activated chloride (CAC) channels, and the dynamics of their respective ligands, cAMP and Ca2+, and it simulates the EOG (electroolfactogram) results obtained under different experimental conditions through changes in the amplitude and duration of cAMP and Ca2+ response, two second messengers implicated with STA occurrence. The model reproduced the experimental data for each pharmacological treatment and provided a mechanistic explanation for the action of GPCR cycling in the levels of second messengers modulating the levels of STA. All together, these experimental and theoretical results indicate the existence of a mechanism of regulation of STA by signaling pathways that control GPCR cycling and tune the levels of second messengers in OSNs, and not only by CNG channel desensitization as previously thought. "
57.  Strategy for kinase transport by microtubules to nerve terminals (Koon et al. 2014)
This model was used in the computational study of the strategies of protein transport in the context of JNK (c-JUN NH2-terminal kinase) transport along microtubules to the terminals of neuronal cells. Diffusion governs the first strategy. In the second strategy, proteins of the JNK signaling cascade bind to scaffolds and the whole protein-scaffold cargo is transported by kinesin motors along microtubules. Using the results from the simulations, the two distinct strategies for transport were compared.
58.  Synchronization by D4 dopamine receptor-mediated phospholipid methylation (Kuznetsova, Deth 2008)
"We describe a new molecular mechanism of dopamine-induced membrane protein modulation that can tune neuronal oscillation frequency to attention related gamma rhythm. This mechanism is based on the unique ability of D4 dopamine receptors (D4R) to carry out phospholipid methylation (PLM) that may affect the kinetics of ion channels. We show that by deceasing the inertia of the delayed rectifier potassium channel, a transition to 40 Hz oscillations can be achieved. ..."

Re-display model names without descriptions