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Sample records for model neurons nt2

  1. Potential for Cell-Transplant Therapy with Human Neuronal Precursors to Treat Neuropathic Pain in Models of PNS and CNS Injury: Comparison of hNT2.17 and hNT2.19 Cell Lines

    PubMed Central

    Eaton, Mary J.; Berrocal, Yerko; Wolfe, Stacey Q.

    2012-01-01

    Effective treatment of sensory neuropathies in peripheral neuropathies and spinal cord injury (SCI) is one of the most difficult problems in modern clinical practice. Cell therapy to release antinociceptive agents near the injured spinal cord is a logical next step in the development of treatment modalities. But few clinical trials, especially for chronic pain, have tested the potential of transplant of cells to treat chronic pain. Cell lines derived from the human neuronal NT2 cell line parentage, the hNT2.17 and hNT2.19 lines, which synthesize and release the neurotransmitters gamma-aminobutyric acid (GABA) and serotonin (5HT), respectively, have been used to evaluate the potential of cell-based release of antinociceptive agents near the lumbar dorsal (horn) spinal sensory cell centers to relieve neuropathic pain after PNS (partial nerve and diabetes-related injury) and CNS (spinal cord injury) damage in rat models. Both cell lines transplants potently and permanently reverse behavioral hypersensitivity without inducing tumors or other complications after grafting. Functioning as cellular minipumps for antinociception, human neuronal precursors, like these NT2-derived cell lines, would likely provide a useful adjuvant or replacement for current pharmacological treatments for neuropathic pain. PMID:22619713

  2. Expression of α5 integrin rescues fibronectin responsiveness in NT2N CNS neuronal cells

    PubMed Central

    Meland, Marit N.; Herndon, Mary E.; Stipp, Christopher S.

    2010-01-01

    The extracellular matrix protein fibronectin is implicated in neuronal regeneration in the peripheral nervous system. In the central nervous system (CNS), fibronectin is upregulated at sites of penetrating injuries and stroke; however, CNS neurons downregulate the fibronectin receptor, α5β1 integrin, during differentiation and generally respond poorly to fibronectin. NT2N CNS neuron-like cells (derived from NT2 precursor cells) have been used in pre-clinical and clinical studies for treatment of stroke and a variety of CNS injury and disease models. Here we show that, like primary CNS neurons, NT2N cells downregulate α5β1 integrin during differentiation and respond poorly to fibronectin. The poor neurite outgrowth by NT2N cells on fibronectin can be rescued by transducing NT2 precursors with a retroviral vector expressing α5 integrin under the control of the Murine Stem Cell Virus 5′ long terminal repeat. Sustained α5 integrin expression is compatible with the CNS-like neuronal differentiation of NT2N cells and does not prevent robust neurite outgrowth on other integrin ligands. Thus, α5 integrin expression in CNS neuronal precursor cells may provide a strategy for enhancing the outgrowth and survival of implanted cells in cell replacement therapies for CNS injury and disease. PMID:19598247

  3. Data for the morphometric characterization of NT2-derived postmitotic neurons.

    PubMed

    González-Burguera, Imanol; Ricobaraza, Ana; Aretxabala, Xabier; Barrondo, Sergio; García Del Caño, Gontzal; López de Jesús, Maider; Sallés, Joan

    2016-06-01

    NTERA2/D1 human teratocarcinoma progenitors induced to differentiate into postmitotic neurons by either long-term treatment with retinoic acid or short-term treatment with the nucleoside analog cytosine β-D-arabinofuranoside were subjected to morphometric analysis and compared. Our data provide a methodological and conceptual framework for future investigations aiming at distinguishing neuronal phenotypes on the basis of morphometric analysis. Data presented here are related to research concurrently published in "Highly Efficient Generation of Glutamatergic/Cholinergic NT2-Derived Postmitotic Human Neurons by Short-Term treatment with the Nucleoside Analogue Cytosine β-D-Arabinofuranoside" [1]. PMID:27158648

  4. Data for the morphometric characterization of NT2-derived postmitotic neurons

    PubMed Central

    González-Burguera, Imanol; Ricobaraza, Ana; Aretxabala, Xabier; Barrondo, Sergio; García del Caño, Gontzal; López de Jesús, Maider; Sallés, Joan

    2016-01-01

    NTERA2/D1 human teratocarcinoma progenitors induced to differentiate into postmitotic neurons by either long-term treatment with retinoic acid or short-term treatment with the nucleoside analog cytosine β-D-arabinofuranoside were subjected to morphometric analysis and compared. Our data provide a methodological and conceptual framework for future investigations aiming at distinguishing neuronal phenotypes on the basis of morphometric analysis. Data presented here are related to research concurrently published in “Highly Efficient Generation of Glutamatergic/Cholinergic NT2-Derived Postmitotic Human Neurons by Short-Term treatment with the Nucleoside Analogue Cytosine β-D-Arabinofuranoside” [1]. PMID:27158648

  5. REST-VP16 activates multiple neuronal differentiation genes in human NT2 cells.

    PubMed

    Immaneni, A; Lawinger, P; Zhao, Z; Lu, W; Rastelli, L; Morris, J H; Majumder, S

    2000-09-01

    The RE1-silencing transcription factor (REST)/neuron-restrictive silencer factor (NRSF) can repress transcription of a battery of neuronal differentiation genes in non-neuronal cells by binding to a specific consensus DNA sequence present in their regulatory regions. However, REST/NRSF(-/-) mice suggest that the absence of REST/NRSF-dependent repression alone is not sufficient for the expression of these neuronal differentiation genes and that the presence of other promoter/enhancer-specific activators is required. Here we describe the construction of a recombinant transcription factor, REST-VP16, by replacing repressor domains of REST/NRSF with the activation domain of a viral activator VP16. In transient transfection experiments, REST-VP16 was found to operate through RE1 binding site/neuron-restrictive enhancer element (RE1/NRSE), activate plasmid-encoded neuronal promoters in various mammalian cell types and activate cellular REST/NRSF target genes, even in the absence of factors that are otherwise required to activate such genes. Efficient expression of REST-VP16 through adenoviral vectors in NT2 cells, which resemble human committed neuronal progenitor cells, was found to cause activation of multiple neuronal genes that are characteristic markers for neuronal differentiation. Thus, REST-VP16 could be used as a unique tool to study neuronal differentiation pathways and neuronal diseases that arise due to the deregulation of this process. PMID:10954611

  6. Spatiotemporal changes in Cx30 and Cx43 expression during neuronal differentiation of P19 EC and NT2/D1 cells

    PubMed Central

    Wan, Carthur K; O'Carroll, Simon J; Kim, Sue-Ling; Green, Colin R; Nicholson, Louise F B

    2013-01-01

    While connexins (Cxs) are thought to be involved in differentiation, their expression and role has yet to be fully elucidated. We investigated the temporal expression of Cx30, Cx36 and Cx43 in two in vitro models of neuronal differentiation: human NT2/D1 and murine P19 cells, and the spatial localisation of Cx30 and Cx43 in these models. A temporal Cx43 downregulation was confirmed in both cell lines during RA-induced neuronal differentiation using RT-PCR (P < 0.05) preceding an increase in neuronal doublecortin protein. RT-PCR showed Cx36 was upregulated twofold in NT2/D1 cells (P < 0.05) and sixfold in P19 cells (P < 0.001) during neuronal differentiation. Cx30 exhibited a transient peak in expression midway through the timecourse of differentiation increasing threefold in NT2/D1 cells (P < 0.001) and eightfold in P19 cells (P < 0.01). Qualitative immunocytochemistry was used to examine spatiotemporal patterns of Cx protein distribution alongside neuronal differentiation markers. The temporal immunolabelling pattern was similar to that seen using RT-PCR. Cx43 was observed intracellularly and on cell surfaces, while Cx30 was seen as puncta. Spatially Cx43 was seen on doublecortin-negative cells, which may indicate Cx43 downregulation is requisite for differentiation in these models. Conversely, Cx30 puncta were observed on doublecortin-positive and -negative cells in NT2/D1 cells and examination of the Cx30 peak showed puncta also localized to nestin-positive cells, with few puncta on MAP2-positive cells. In P19 cells Cx30 was localized on clusters of cells surrounded by MAP2- and doublecortin-positive processes. The expression pattern of Cx30 indicates a role in neuronal differentiation; the nature of that role warrants future investigation. PMID:25505515

  7. Interleukin-1β stimulates macrophage inflammatory protein-1α and -1β expression in human neuronal cells (NT2-N)

    PubMed Central

    Guo, Chang-Jiang; Douglas, Steven D.; Lai, Jian-Ping; Pleasure, David E.; Li, Yuan; Williams, Marge; Bannerman, Peter; Song, Li; Ho, Wen-Zhe

    2014-01-01

    Chemokines are important mediators in immune responses and inflammatory processes of neuroimmunologic and infectious diseases. Although chemokines are expressed predominantly by cells of the immune system, neurons also express chemokines and chemokine receptors. We report herein that human neuronal cells (NT2-N) produce macrophage inflammatory protein-1α and -1β (MIP-1α and MIP-1β), which could be enhanced by interleukin (IL)-1β at both mRNA and protein levels. The addition of supernatants from human peripheral blood monocyte-derived macrophage (MDM) cultures induced MIP-1β mRNA expression in NT2-N cells. Anti-IL-1β antibody removed most, but not all, of the MDM culture supernatant-induced MIP-1β mRNA expression in NT2-N cells, suggesting that IL-1β in the MDM culture supernatants is a major factor in the induction of MIP-1β expression. Investigation of the mechanism(s) responsible for IL-1β-induced MIP-1α and -1β expression demonstrated that IL-1β activated nuclear factor kappa B (NF-κB) promoter-directed luciferase activity in NT2-N cells. Caffeic acid phenethyl ester, a potent and specific inhibitor of activation of NF-κB, not only blocked IL-1β-induced activation of the NF-κB promoter but also decreased IL-1β-induced MIP-1α and -1β expression in NT2-N cells. These data suggest that NF-κB is at least partially involved in the IL-1β-mediated action on MIP-1α and -1β in NT2-N cells. IL-1β-mediated up-regulation of β-chemokine expression may have important implications in the immuno-pathogenesis of inflammatory diseases in the CNS. PMID:12603824

  8. Non ionising radiation as a non chemical strategy in regenerative medicine: Ca(2+)-ICR "In Vitro" effect on neuronal differentiation and tumorigenicity modulation in NT2 cells.

    PubMed

    Ledda, Mario; Megiorni, Francesca; Pozzi, Deleana; Giuliani, Livio; D'Emilia, Enrico; Piccirillo, Sara; Mattei, Cristiana; Grimaldi, Settimio; Lisi, Antonella

    2013-01-01

    In regenerative medicine finding a new method for cell differentiation without pharmacological treatment or gene modification and minimal cell manipulation is a challenging goal. In this work we reported a neuronal induced differentiation and consequent reduction of tumorigenicity in NT2 human pluripotent embryonal carcinoma cells exposed to an extremely low frequency electromagnetic field (ELF-EMF), matching the cyclotron frequency corresponding to the charge/mass ratio of calcium ion (Ca(2+)-ICR). These cells, capable of differentiating into post-mitotic neurons following treatment with Retinoic Acid (RA), were placed in a solenoid and exposed for 5 weeks to Ca(2+)-ICR. The solenoid was installed in a μ-metal shielded room to avoid the effect of the geomagnetic field and obtained totally controlled and reproducible conditions. Contrast microscopy analysis reveled, in the NT2 exposed cells, an important change in shape and morphology with the outgrowth of neuritic-like structures together with a lower proliferation rate and metabolic activity alike those found in the RA treated cells. A significant up-regulation of early and late neuronal differentiation markers and a significant down-regulation of the transforming growth factor-α (TGF-α) and the fibroblast growth factor-4 (FGF-4) were also observed in the exposed cells. The decreased protein expression of the transforming gene Cripto-1 and the reduced capability of the exposed NT2 cells to form colonies in soft agar supported these last results. In conclusion, our findings demonstrate that the Ca(2+)-ICR frequency is able to induce differentiation and reduction of tumorigenicity in NT2 exposed cells suggesting a new potential therapeutic use in regenerative medicine. PMID:23585910

  9. Subarachnoid Transplant of the Human Neuronal hNT2.19 Serotonergic Cell Line Attenuates Behavioral Hypersensitivity without Affecting Motor Dysfunction after Severe Contusive Spinal Cord Injury

    PubMed Central

    Eaton, Mary J.; Widerström-Noga, Eva; Wolfe, Stacey Quintero

    2011-01-01

    Transplant of cells which make biologic agents that can modulate the sensory and motor responses after spinal cord injury (SCI) would be useful to treat pain and paralysis. To address this need for clinically useful human cells, a unique neuronal cell line that synthesizes and secretes/releases the neurotransmitter serotonin (5HT) was isolated. Hind paw tactile allodynia and thermal hyperalgesia induced by severe contusive SCI were potently reversed after lumbar subarachnoid transplant of differentiated cells, but had no effect on open field motor scores, stride length, foot rotation, base of support, or gridwalk footfall errors associated with the SCI. The sensory effects appeared 1 week after transplant and did not diminish during the 8-week course of the experiment when grafts were placed 2 weeks after SCI. Many grafted cells were still present and synthesizing 5HT at the end of the study. These data suggest that the human neuronal serotonergic hNT2.19 cells can be used as a biologic minipump for receiving SCI-related neuropathic pain, but likely requires intraspinal grafts for motor recovery. PMID:21799949

  10. A note on four-particle form factors of operators {T}_{2n}{T}_{-2n} in the sinh-Gordon model

    NASA Astrophysics Data System (ADS)

    Lashkevich, Michael; Pugai, Yaroslav

    2016-07-01

    The diagonal matrix elements < {θ }1,{θ }2| {T}2n{T}-2n| {θ }1,{θ }2> between two-particle states in the sinh-Gordon model are computed analytically for all integers n\\gt 0. This confirms the proposal [1] by Smirnov and Zamolodchikov for these matrix elements and demonstrates the effectiveness of the algebraic approach to form factors.

  11. Rapid differentiation of NT2 cells in Sertoli-NT2 cell tissue constructs grown in the rotating wall bioreactor.

    PubMed

    Saporta, Samuel; Willing, Alison E; Shamekh, Rania; Bickford, Paula; Paredes, Daniel; Cameron, Don F

    2004-12-15

    Cell replacement therapy is of great interest as a long-term treatment of neurodegenerative diseases such as Parkinson's disease (PD). We have previously shown that Sertoli cells (SC) provide neurotrophic support to transplants of dopaminergic fetal neurons and NT2N neurons, derived from the human clonal precursors cell line NTera2/D1 (NT2), which differentiate into dopaminergic NT2N neurons when exposed to retinoic acid. We have created SC-NT2 cell tissue constructs cultured in the high aspect ratio vessel (HARV) rotating wall bioreactor. Sertoli cells, NT2, and SC plus NT2 cells combined in starting ratios of 1:1, 1:2, 1:4 and 1:8 were cultured in the HARV in DMEM with 10% fetal bovine serum and 1% growth factor reduced Matrigel for 3 days, without retinoic acid. Conventional, non-HARV, cultures grown in the same culture medium were used as controls. The presence of tyrosine hydroxylase (TH) was assessed in all culture conditions. Sertoli-neuron-aggregated-cell (SNAC) tissue constructs grown at starting ratios of 1:1 to 1:4 contained a significant amount of TH after 3 days of culture in the HARV. No TH was detected in SC HARV cultures, or SC, NT2 or SC-NT2 conventional co-cultures. Quantitative stereology of immunolabled 1:4 SNAC revealed that approximately 9% of NT2 cells differentiate into TH-positive (TH+) NT2N neurons after 3 days of culture in the HARV, without retinoic acid. SNAC tissue constructs also released dopamine (DA) when stimulated with KCl, suggesting that TH-positive NT2N neurons in the SNAC adopted a functional dopaminergic phenotype. SNAC tissue constructs may be an important source of dopaminergic neurons for neuronal transplantation. PMID:15561470

  12. Non Ionising Radiation as a Non Chemical Strategy in Regenerative Medicine: Ca2+-ICR “In Vitro” Effect on Neuronal Differentiation and Tumorigenicity Modulation in NT2 Cells

    PubMed Central

    Ledda, Mario; Megiorni, Francesca; Pozzi, Deleana; Giuliani, Livio; D’Emilia, Enrico; Piccirillo, Sara; Mattei, Cristiana; Grimaldi, Settimio; Lisi, Antonella

    2013-01-01

    In regenerative medicine finding a new method for cell differentiation without pharmacological treatment or gene modification and minimal cell manipulation is a challenging goal. In this work we reported a neuronal induced differentiation and consequent reduction of tumorigenicity in NT2 human pluripotent embryonal carcinoma cells exposed to an extremely low frequency electromagnetic field (ELF-EMF), matching the cyclotron frequency corresponding to the charge/mass ratio of calcium ion (Ca2+-ICR). These cells, capable of differentiating into post-mitotic neurons following treatment with Retinoic Acid (RA), were placed in a solenoid and exposed for 5 weeks to Ca2+-ICR. The solenoid was installed in a μ-metal shielded room to avoid the effect of the geomagnetic field and obtained totally controlled and reproducible conditions. Contrast microscopy analysis reveled, in the NT2 exposed cells, an important change in shape and morphology with the outgrowth of neuritic-like structures together with a lower proliferation rate and metabolic activity alike those found in the RA treated cells. A significant up-regulation of early and late neuronal differentiation markers and a significant down-regulation of the transforming growth factor-α (TGF-α) and the fibroblast growth factor-4 (FGF-4) were also observed in the exposed cells. The decreased protein expression of the transforming gene Cripto-1 and the reduced capability of the exposed NT2 cells to form colonies in soft agar supported these last results. In conclusion, our findings demonstrate that the Ca2+-ICR frequency is able to induce differentiation and reduction of tumorigenicity in NT2 exposed cells suggesting a new potential therapeutic use in regenerative medicine. PMID:23585910

  13. Towards in vitro DT/DNT testing: Assaying chemical susceptibility in early differentiating NT2 cells.

    PubMed

    Menzner, Ann-Katrin; Abolpour Mofrad, Sepideh; Friedrich, Oliver; Gilbert, Daniel F

    2015-12-01

    Human pluripotent embryonal carcinoma (NT2) cells are increasingly considered as a suitable model for in vitro toxicity testing, e.g. developmental toxicity and neurotoxicity (DT/DNT) studies, as they undergo neuronal differentiation upon stimulation with retinoic acid (RA) and permit toxicity testing at different stages of maturation. NT2 cells have recently been reported to show specific changes in dielectric resistance profiles during differentiation which can be observed as early as 24h upon RA-stimulation. These observations suggest altered susceptibility to chemicals at an early stage of differentiation. However, chemical susceptibility of early differentiating NT cells has not yet been studied. To address this question, we have established a cell fitness screening assay based on the analysis of intracellular ATP levels and we applied the assay in a large-scale drug screening experiment in NT2 stem cells and early differentiating NT2 cells. Subsequent analysis of ranked fitness phenotypes revealed 19 chemicals with differential toxicity profile in early differentiating NT2 cells. To evaluate whether any of the identified drugs have previously been associated with DT/DNT, we conducted a literature search on the identified molecules and quantified the fraction of chemicals assigned to the FDA (Food and Drug Administration) pregnancy risk categories (PRC) N, A, B, C, D, and X in the hit list and the small molecule library. While the fractions of the categories N and B were decreased (0.81 and 0.35-fold), the classes C, D and X were increased (1.35, 1.47 and 3.27-fold) in the hit list compared to the chemical library. From these data as well as from the literature review, identifying large fractions of chemicals being directly (∼42%) and indirectly associated with DT/DNT (∼32%), we conclude that our method may be beneficial to systematic in vitro-based primary screening for developmental toxicants and neurotoxicants and we propose cell fitness screening in

  14. A Predictive In Vitro Model of the Impact of Drugs with Anticholinergic Properties on Human Neuronal and Astrocytic Systems

    PubMed Central

    Woehrling, Elizabeth K.; Parri, H. Rheinallt; Tse, Erin H. Y.; Hill, Eric J.; Maidment, Ian D.; Fox, G. Christopher; Coleman, Michael D.

    2015-01-01

    The link between off-target anticholinergic effects of medications and acute cognitive impairment in older adults requires urgent investigation. We aimed to determine whether a relevant in vitro model may aid the identification of anticholinergic responses to drugs and the prediction of anticholinergic risk during polypharmacy. In this preliminary study we employed a co-culture of human-derived neurons and astrocytes (NT2.N/A) derived from the NT2 cell line. NT2.N/A cells possess much of the functionality of mature neurons and astrocytes, key cholinergic phenotypic markers and muscarinic acetylcholine receptors (mAChRs). The cholinergic response of NT2 astrocytes to the mAChR agonist oxotremorine was examined using the fluorescent dye fluo-4 to quantitate increases in intracellular calcium [Ca2+]i. Inhibition of this response by drugs classified as severe (dicycloverine, amitriptyline), moderate (cyclobenzaprine) and possible (cimetidine) on the Anticholinergic Cognitive Burden (ACB) scale, was examined after exposure to individual and pairs of compounds. Individually, dicycloverine had the most significant effect regarding inhibition of the astrocytic cholinergic response to oxotremorine, followed by amitriptyline then cyclobenzaprine and cimetidine, in agreement with the ACB scale. In combination, dicycloverine with cyclobenzaprine had the most significant effect, followed by dicycloverine with amitriptyline. The order of potency of the drugs in combination frequently disagreed with predicted ACB scores derived from summation of the individual drug scores, suggesting current scales may underestimate the effect of polypharmacy. Overall, this NT2.N/A model may be appropriate for further investigation of adverse anticholinergic effects of multiple medications, in order to inform clinical choices of suitable drug use in the elderly. PMID:25738989

  15. Stochastic models of neuronal dynamics

    PubMed Central

    Harrison, L.M; David, O; Friston, K.J

    2005-01-01

    Cortical activity is the product of interactions among neuronal populations. Macroscopic electrophysiological phenomena are generated by these interactions. In principle, the mechanisms of these interactions afford constraints on biologically plausible models of electrophysiological responses. In other words, the macroscopic features of cortical activity can be modelled in terms of the microscopic behaviour of neurons. An evoked response potential (ERP) is the mean electrical potential measured from an electrode on the scalp, in response to some event. The purpose of this paper is to outline a population density approach to modelling ERPs. We propose a biologically plausible model of neuronal activity that enables the estimation of physiologically meaningful parameters from electrophysiological data. The model encompasses four basic characteristics of neuronal activity and organization: (i) neurons are dynamic units, (ii) driven by stochastic forces, (iii) organized into populations with similar biophysical properties and response characteristics and (iv) multiple populations interact to form functional networks. This leads to a formulation of population dynamics in terms of the Fokker–Planck equation. The solution of this equation is the temporal evolution of a probability density over state-space, representing the distribution of an ensemble of trajectories. Each trajectory corresponds to the changing state of a neuron. Measurements can be modelled by taking expectations over this density, e.g. mean membrane potential, firing rate or energy consumption per neuron. The key motivation behind our approach is that ERPs represent an average response over many neurons. This means it is sufficient to model the probability density over neurons, because this implicitly models their average state. Although the dynamics of each neuron can be highly stochastic, the dynamics of the density is not. This means we can use Bayesian inference and estimation tools that have

  16. Simple neuron models of ITD sensitive neurons

    NASA Astrophysics Data System (ADS)

    Dasika, Vasant; White, John A.; Colburn, H. Steven

    2002-05-01

    Neurons which show sensitivity to interaural time delay (ITD) exist in both mammalian medial superior olive (MSO), and bird nucleus laminaris (NL). In this study, we examine simple mathematical models of single MSO and NL cells which respond probabilistically to a pair of isolated inputs with a response probability that depends on the input interpulse interval. Inputs are either isolated pulse pairs or pairs of periodic trains, with or without random jitter added to their event times. Refractoriness is incorporated in the input description and/or in the cell model in specified simulations. We find that periodic rate-ITD shapes are shaped by three interacting factors: the cell's temporal response (described by the paired-pulse response), input frequency, and the degree of input synchrony. Paired-pulse responses are able to predict the widths of rate-ITD curves obtained from deterministic periodic input simulations. Reduced input synchrony predictably smears rate-ITD curves. Larger numbers of weaker inputs yield stronger rate-ITD modulation than a few strong inputs. Model response is compared with in vivo and in vitro MSO and NL physiological data. Comparisons with published analytical models as well as more complex and realistic physiological cell models are examined.

  17. Single neuron modeling and data assimilation in BNST neurons

    NASA Astrophysics Data System (ADS)

    Farsian, Reza

    Neurons, although tiny in size, are vastly complicated systems, which are responsible for the most basic yet essential functions of any nervous system. Even the most simple models of single neurons are usually high dimensional, nonlinear, and contain many parameters and states which are unobservable in a typical neurophysiological experiment. One of the most fundamental problems in experimental neurophysiology is the estimation of these parameters and states, since knowing their values is essential in identification, model construction, and forward prediction of biological neurons. Common methods of parameter and state estimation do not perform well for neural models due to their high dimensionality and nonlinearity. In this dissertation, two alternative approaches for parameters and state estimation of biological neurons have been demonstrated: dynamical parameter estimation (DPE) and a Markov Chain Monte Carlo (MCMC) method. The first method uses elements of chaos control and synchronization theory for parameter and state estimation. MCMC is a statistical approach which uses a path integral formulation to evaluate a mean and an error bound for these unobserved parameters and states. These methods have been applied to biological system of neurons in Bed Nucleus of Stria Termialis neurons (BNST) of rats. State and parameters of neurons in both systems were estimated, and their value were used for recreating a realistic model and predicting the behavior of the neurons successfully. The knowledge of biological parameters can ultimately provide a better understanding of the internal dynamics of a neuron in order to build robust models of neuron networks.

  18. Modeling neuronal vulnerability in ALS.

    PubMed

    Roselli, Francesco; Caroni, Pico

    2014-08-20

    Using computational models of motor neuron ion fluxes, firing properties, and energy requirements, Le Masson et al. (2014) reveal how local imbalances in energy homeostasis may self-amplify and contribute to neurodegeneration in ALS. PMID:25144872

  19. Silencing of PNPLA6, the neuropathy target esterase (NTE) codifying gene, alters neurodifferentiation of human embryonal carcinoma stem cells (NT2).

    PubMed

    Pamies, D; Bal-Price, A; Fabbri, M; Gribaldo, L; Scelfo, B; Harris, G; Collotta, A; Vilanova, E; Sogorb, M A

    2014-12-01

    Neuropathy target esterase (NTE) is a protein involved in the development of a polyneuropathy caused by exposure to certain organophosphorus compounds. In vivo and in vitro studies have also associated NTE with embryonic development since NTE null mice embryos are non-viable, and silencing the NTE-codifying gene (Pnpla6) in mouse embryonic stem cells strongly alters the differentiation of vascular and nervous systems. In this paper, human embryonal carcinoma stem cells human-derived NTera2/D1 (hNT2) are used as an in vitro neurodifferentiation model to determine whether PNPLA6 silencing is able to alter the differentiation process. In control cultures, PNPLA6 mRNA levels increased in parallel with other neuroectodermal markers during neurodifferentiation. PNPLA6 silencing with specific interference RNA reached a 97% decrease in gene expression 3days after transfection and with a maximum reduction in NTE enzymatic activity (50%), observed on day 4. Silencing PNPLA6 showed an 80% decrease in quantifiable neuronal cells after 13days in vitro (DIV) compared to controls and absence of different neuronal markers after 66DIV. Microarray data analysis of the PNPLA6-silenced cells showed alterations in several developmental processes, mainly neurogenesis and epithelium tube morphogenesis. PNPLA6 silencing also led to a reduction in electrical activity and an altered neuronal phenotype. This work is the first proof supporting the hypothesis that NTE plays a role in human early neurodevelopment using a human cell differentiation model. PMID:25255935

  20. Neuron Model with Simplified Memristive Ionic Channels

    NASA Astrophysics Data System (ADS)

    Hegab, Almoatazbellah M.; Salem, Noha M.; Radwan, Ahmed G.; Chua, Leon

    2015-06-01

    A simplified neuron model is introduced to mimic the action potential generated by the famous Hodgkin-Huxley equations by using the genetic optimization algorithm. Comparison with different neuron models is investigated, and it is confirmed that the sodium and potassium channels in our simplified neuron model are made out of memristors. In addition, the channel equations in the simplified model may be adjusted to introduce a simplified memristor model that is in accordance with the theoretical conditions of the memristive systems.

  1. Neuronal cell lines as model dorsal root ganglion neurons

    PubMed Central

    Yin, Kathleen; Baillie, Gregory J

    2016-01-01

    Background Dorsal root ganglion neuron-derived immortal cell lines including ND7/23 and F-11 cells have been used extensively as in vitro model systems of native peripheral sensory neurons. However, while it is clear that some sensory neuron-specific receptors and ion channels are present in these cell lines, a systematic comparison of the molecular targets expressed by these cell lines with those expressed in intact peripheral neurons is lacking. Results In this study, we examined the expression of RNA transcripts in the human neuroblastoma-derived cell line, SH-SY5Y, and two dorsal root ganglion hybridoma cell lines, F-11 and ND7/23, using Illumina next-generation sequencing, and compared the results with native whole murine dorsal root ganglions. The gene expression profiles of these three cell lines did not resemble any specific defined dorsal root ganglion subclass. The cell lines lacked many markers for nociceptive sensory neurons, such as the Transient receptor potential V1 gene, but expressed markers for both myelinated and unmyelinated neurons. Global gene ontology analysis on whole dorsal root ganglions and cell lines showed similar enrichment of biological process terms across all samples. Conclusions This paper provides insights into the receptor repertoire expressed in common dorsal root ganglion neuron-derived cell lines compared with whole murine dorsal root ganglions, and illustrates the limits and potentials of these cell lines as tools for neuropharmacological exploration. PMID:27130590

  2. Elevated caspase 3 activity and cytosolic cytochrome c in NT2 cybrids containing amyotrophic lateral sclerosis subject mtDNA.

    PubMed

    Shrivastava, Mohita; Subbiah, Vivekanandhan

    2016-09-01

    Apoptosis of motor neurons is an important feature in amyotrophic lateral sclerosis (ALS). A vital role of mitochondria in apoptosis and cell survival is well documented. Eventually mitochondria have shown to be an early target in the pathogenesis of ALS. On account of these facts, we investigated the involvement of mitochondrial-dependent apoptosis in ALS and control (CTR) cybrids, generated fusing human platelets with mitochondrial DNA-depleted NT2-neuroteratocarcinoma cells. After a 6 week selection process during which transferred subject mtDNA repopulated the NT2 cells and restored mitochondrial oxygen consumption, we assessed cell viability and two programmed cell death parameters, caspase 3 activity and cytosolic cytochrome c levels. Compared to the control cybrid lines (n = 5), the ALS cybrid lines (n = 10) showed 45% less XTT reduction and higher caspase 3 activity ( p < 0.05, two-way Student's t test) exhibiting lesser cell viability and execution of apoptosis. Elevated cytosolic cytochrome c levels in ALS cybrid lines (n = 8) than in CTR (n = 4) ( p < 0.05, two-way Student's t-test) indicating its mitochondrial release and initiation of apoptosis. This indicates apoptosis as one of the possible mechanisms of cell death in ALS. Our findings support the view that in ALS, subject's mitochondria are altered in non-degenerating tissues in such a way that intrinsic apoptotic pathway activity is relatively increased. PMID:26268635

  3. Fitting Neuron Models to Spike Trains

    PubMed Central

    Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain

    2011-01-01

    Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925

  4. Map-based models in neuronal dynamics

    NASA Astrophysics Data System (ADS)

    Ibarz, B.; Casado, J. M.; Sanjuán, M. A. F.

    2011-04-01

    Ever since the pioneering work of Hodgkin and Huxley, biological neuron models have consisted of ODEs representing the evolution of the transmembrane voltage and the dynamics of ionic conductances. It is only recently that discrete dynamical systems-also known as maps-have begun to receive attention as valid phenomenological neuron models. The present review tries to provide a coherent perspective of map-based biological neuron models, describing their dynamical properties; stressing the similarities and differences, both among them and in relation to continuous-time models; exploring their behavior in networks; and examining their wide-ranging possibilities of application in computational neuroscience.

  5. An overview of the neuron ring model

    NASA Technical Reports Server (NTRS)

    Taber, Rod

    1991-01-01

    The Neuron Ring model employs an avalanche structure with two important distinctions at the neuron level. Each neuron has two memory latches; one traps maximum neuronal activation during pattern presentation, and the other records the time of latch content change. The latches filter short term memory. In the process, they preserve length 1 snapshots of activation theory history. The model finds utility in pattern classification. Its synaptic weights are first conditioned with sample spectra. The model then receives a test or unknown signal. The objective is to identify the sample closest to the test signal. Class decision follows complete presentation of the test data. The decision maker relies exclusively on the latch contents. Presented here is an overview of the Neuron Ring at the seminar level.

  6. Animal models for motor neuron disease.

    PubMed

    Green, S L; Tolwani, R J

    1999-10-01

    Motor neuron disease is a general term applied to a broad class of neurodegenerative diseases that are characterized by fatally progressive muscular weakness, atrophy, and paralysis attributable to loss of motor neurons. At present, there is no cure for most motor neuron diseases, including amyotrophic lateral sclerosis (ALS), the most common human motor neuron disease--the cause of which remains largely unknown. Animal models of motor neuron disease (MND) have significantly contributed to the remarkable recent progress in understanding the cause, genetic factors, and pathologic mechanisms proposed for this class of human neurodegenerative disorders. Largely driven by ALS research, animal models of MND have proven their usefulness in elucidating potential causes and specific pathogenic mechanisms, and have helped to advance promising new treatments from "benchside to bedside." This review summarizes important features of selected established animal models of MND: genetically engineered mice and inherited or spontaneously occurring MND in the murine, canine, and equine species. PMID:10551448

  7. Effective Stimuli for Constructing Reliable Neuron Models

    PubMed Central

    Druckmann, Shaul; Berger, Thomas K.; Schürmann, Felix; Hill, Sean; Markram, Henry; Segev, Idan

    2011-01-01

    The rich dynamical nature of neurons poses major conceptual and technical challenges for unraveling their nonlinear membrane properties. Traditionally, various current waveforms have been injected at the soma to probe neuron dynamics, but the rationale for selecting specific stimuli has never been rigorously justified. The present experimental and theoretical study proposes a novel framework, inspired by learning theory, for objectively selecting the stimuli that best unravel the neuron's dynamics. The efficacy of stimuli is assessed in terms of their ability to constrain the parameter space of biophysically detailed conductance-based models that faithfully replicate the neuron's dynamics as attested by their ability to generalize well to the neuron's response to novel experimental stimuli. We used this framework to evaluate a variety of stimuli in different types of cortical neurons, ages and animals. Despite their simplicity, a set of stimuli consisting of step and ramp current pulses outperforms synaptic-like noisy stimuli in revealing the dynamics of these neurons. The general framework that we propose paves a new way for defining, evaluating and standardizing effective electrical probing of neurons and will thus lay the foundation for a much deeper understanding of the electrical nature of these highly sophisticated and non-linear devices and of the neuronal networks that they compose. PMID:21876663

  8. A COMPUTATIONAL MODEL OF MOTOR NEURON DEGENERATION

    PubMed Central

    Le Masson, Gwendal; Przedborski, Serge; Abbott, L.F.

    2014-01-01

    SUMMARY To explore the link between bioenergetics and motor neuron degeneration, we used a computational model in which detailed morphology and ion conductance are paired with intracellular ATP production and consumption. We found that reduced ATP availability increases the metabolic cost of a single action potential and disrupts K+/Na+ homeostasis, resulting in a chronic depolarization. The magnitude of the ATP shortage at which this ionic instability occurs depends on the morphology and intrinsic conductance characteristic of the neuron. If ATP shortage is confined to the distal part of the axon, the ensuing local ionic instability eventually spreads to the whole neuron and involves fasciculation-like spiking events. A shortage of ATP also causes a rise in intracellular calcium. Our modeling work supports the notion that mitochondrial dysfunction can account for salient features of the paralytic disorder amyotrophic lateral sclerosis, including motor neuron hyperexcitability, fasciculation, and differential vulnerability of motor neuron subpopulations. PMID:25088365

  9. Bistable behaviour in a neocortical neurone model.

    PubMed

    Delord, B; Klaassen, A J; Burnod, Y; Costalat, R; Guigon, E

    1997-03-01

    Intracellular recordings have shown that neocortical pyramidal neurones have an intrinsic capacity for regenerative firing. The cellular mechanism of this firing was investigated by computer simulations of a model neurone endowed with standard action potential and persistent sodium (gNaP) conductances. The firing mode of the neurone was determined as a function of leakage and NaP maximal conductances (gl and gNaP). The neurone had two stable states of activity (bistable) over wide range of gl and gNaP, one at the resting potential and the other in a regenerative firing mode, that could be triggered by a transient input. This model points to a cellular mechanism that may contribute to the generation and maintenance of long-lasting sustained neuronal discharges in the cerebral cortex. PMID:9141084

  10. Context-aware modeling of neuronal morphologies

    PubMed Central

    Torben-Nielsen, Benjamin; De Schutter, Erik

    2014-01-01

    Neuronal morphologies are pivotal for brain functioning: physical overlap between dendrites and axons constrain the circuit topology, and the precise shape and composition of dendrites determine the integration of inputs to produce an output signal. At the same time, morphologies are highly diverse and variant. The variance, presumably, originates from neurons developing in a densely packed brain substrate where they interact (e.g., repulsion or attraction) with other actors in this substrate. However, when studying neurons their context is never part of the analysis and they are treated as if they existed in isolation. Here we argue that to fully understand neuronal morphology and its variance it is important to consider neurons in relation to each other and to other actors in the surrounding brain substrate, i.e., their context. We propose a context-aware computational framework, NeuroMaC, in which large numbers of neurons can be grown simultaneously according to growth rules expressed in terms of interactions between the developing neuron and the surrounding brain substrate. As a proof of principle, we demonstrate that by using NeuroMaC we can generate accurate virtual morphologies of distinct classes both in isolation and as part of neuronal forests. Accuracy is validated against population statistics of experimentally reconstructed morphologies. We show that context-aware generation of neurons can explain characteristics of variation. Indeed, plausible variation is an inherent property of the morphologies generated by context-aware rules. We speculate about the applicability of this framework to investigate morphologies and circuits, to classify healthy and pathological morphologies, and to generate large quantities of morphologies for large-scale modeling. PMID:25249944

  11. Modeling of Biological Neurons using Superconducting Circuitry

    NASA Astrophysics Data System (ADS)

    Khadka, Shreeya; Svitelskiy, Oleksiy; Kaplan, Steve; Segall, Kenneth

    2014-03-01

    With the goal of understanding the collective behavior of large network of neurons, we purpose a new analog method based on superconducting Josephson junction (JJ) circuitry. Through numerical simulations, we were able to show that these JJ neurons reproduce many characteristic features of biological neurons such as action potential, firing threshold and refractory period. For preliminary testing, we have designed and fabricated a superconducting chip consisting of two coupled JJ neurons, connected to each other in a closed loop. The numerical simulations of the two synchronized coupled neurons, showed a characteristic phase-flip-bifurcation where the two neurons would fire either in-phase or out-of-phase depending on their coupling strength. Thus, we are looking for the characteristic phase-flip-bifurcation in the experiment also. If these encouraging observations find further confirmation, our JJ model will open a way for developing a fast and low power method of studying the dynamics of large neural networks. We would like to thank Zictools/WRSpice for layout and simulation, and Hypres Inc. for fabricating the chip.

  12. Modelling the magnetic signature of neuronal tissue.

    PubMed

    Blagoev, K B; Mihaila, B; Travis, B J; Alexandrov, L B; Bishop, A R; Ranken, D; Posse, S; Gasparovic, C; Mayer, A; Aine, C J; Ulbert, I; Morita, M; Müller, W; Connor, J; Halgren, E

    2007-08-01

    Neuronal communication in the brain involves electrochemical currents, which produce magnetic fields. Stimulus-evoked brain responses lead to changes in these fields and can be studied using magneto- and electro-encephalography (MEG/EEG). In this paper we model the spatiotemporal distribution of the magnetic field of a physiologically idealized but anatomically realistic neuron to assess the possibility of using magnetic resonance imaging (MRI) for directly mapping the neuronal currents in the human brain. Our results show that the magnetic field several centimeters from the centre of the neuron is well approximated by a dipole source, but the field close to the neuron is not, a finding particularly important for understanding the possible contrast mechanism underlying the use of MRI to detect and locate these currents. We discuss the importance of the spatiotemporal characteristics of the magnetic field in cortical tissue for evaluating and optimizing an experiment based on this mechanism and establish an upper bound for the expected MRI signal change due to stimulus-induced cortical response. Our simulations show that the expected change of the signal magnitude is 1.6% and its phase shift is 1 degrees . An unexpected finding of this work is that the cortical orientation with respect to the external magnetic field has little effect on the predicted MRI contrast. This encouraging result shows that magnetic resonance contrast directly based on the neuronal currents present in the cortex is theoretically a feasible imaging technique. MRI contrast generation based on neuronal currents depends on the dendritic architecture and we obtained high-resolution optical images of cortical tissue to discuss the spatial structure of the magnetic field in grey matter. PMID:17544300

  13. Towards Reproducible Descriptions of Neuronal Network Models

    PubMed Central

    Nordlie, Eilen; Gewaltig, Marc-Oliver; Plesser, Hans Ekkehard

    2009-01-01

    Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing—and thinking about—complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain. PMID:19662159

  14. Nonsmooth dynamics in spiking neuron models

    NASA Astrophysics Data System (ADS)

    Coombes, S.; Thul, R.; Wedgwood, K. C. A.

    2012-11-01

    Large scale studies of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural tissue. One approach in computational neuroscience has been to consider the detailed electrophysiological properties of neurons and build vast computational compartmental models. An alternative has been to develop minimal models of spiking neurons with a reduction in the dimensionality of both parameter and variable space that facilitates more effective simulation studies. In this latter case the single neuron model of choice is often a variant of the classic integrate-and-fire model, which is described by a nonsmooth dynamical system. In this paper we review some of the more popular spiking models of this class and describe the types of spiking pattern that they can generate (ranging from tonic to burst firing). We show that a number of techniques originally developed for the study of impact oscillators are directly relevant to their analysis, particularly those for treating grazing bifurcations. Importantly we highlight one particular single neuron model, capable of generating realistic spike trains, that is both computationally cheap and analytically tractable. This is a planar nonlinear integrate-and-fire model with a piecewise linear vector field and a state dependent reset upon spiking. We call this the PWL-IF model and analyse it at both the single neuron and network level. The techniques and terminology of nonsmooth dynamical systems are used to flesh out the bifurcation structure of the single neuron model, as well as to develop the notion of Lyapunov exponents. We also show how to construct the phase response curve for this system, emphasising that techniques in mathematical neuroscience may also translate back to the field of nonsmooth dynamical systems. The stability of periodic spiking orbits is assessed using a linear stability analysis of spiking times. At the network level we consider linear coupling between voltage

  15. A drive-reinforcement model of single neuron function: An alternative to the Hebbian neuronal model

    NASA Astrophysics Data System (ADS)

    Klopf, A. Harry

    1986-08-01

    A neuronal learning mechanism is proposed that accounts for the basic animal learning phenomena that have been observed. Among the classical conditioning phenomena predicted by the neuronal model are delay conditioning, trace conditioning, simultaneous conditioning, conditioned stimulus duration and amplitude effects, unconditioned stimulus amplitude effects, interstimulus interval effects, second and higher order conditioning, conditioned inhibition, habituation and extinction, reacquisition effects, backward conditioning, blocking, overshadowing and serial compound conditioning. The proposed neuronal model and learning mechanism offer a new building block for constructing neural network-like computer arthitectures for artificial intelligence.

  16. Estimating Neuronal Ageing with Hidden Markov Models

    NASA Astrophysics Data System (ADS)

    Wang, Bing; Pham, Tuan D.

    2011-06-01

    Neuronal degeneration is widely observed in normal ageing, meanwhile the neurode-generative disease like Alzheimer's disease effects neuronal degeneration in a faster way which is considered as faster ageing. Early intervention of such disease could benefit subjects with potentials of positive clinical outcome, therefore, early detection of disease related brain structural alteration is required. In this paper, we propose a computational approach for modelling the MRI-based structure alteration with ageing using hidden Markov model. The proposed hidden Markov model based brain structural model encodes intracortical tissue/fluid distribution using discrete wavelet transformation and vector quantization. Further, it captures gray matter volume loss, which is capable of reflecting subtle intracortical changes with ageing. Experiments were carried out on healthy subjects to validate its accuracy and robustness. Results have shown its ability of predicting the brain age with prediction error of 1.98 years without training data, which shows better result than other age predition methods.

  17. Model reduction of strong-weak neurons.

    PubMed

    Du, Bosen; Sorensen, Danny; Cox, Steven J

    2014-01-01

    We consider neurons with large dendritic trees that are weakly excitable in the sense that back propagating action potentials are severly attenuated as they travel from the small, strongly excitable, spike initiation zone. In previous work we have shown that the computational size of weakly excitable cell models may be reduced by two or more orders of magnitude, and that the size of strongly excitable models may be reduced by at least one order of magnitude, without sacrificing the spatio-temporal nature of its inputs (in the sense we reproduce the cell's precise mapping of inputs to outputs). We combine the best of these two strategies via a predictor-corrector decomposition scheme and achieve a drastically reduced highly accurate model of a caricature of the neuron responsible for collision detection in the locust. PMID:25566048

  18. Ill-Posed Point Neuron Models.

    PubMed

    Nielsen, Bjørn Fredrik; Wyller, John

    2016-12-01

    We show that point-neuron models with a Heaviside firing rate function can be ill posed. More specifically, the initial-condition-to-solution map might become discontinuous in finite time. Consequently, if finite precision arithmetic is used, then it is virtually impossible to guarantee the accurate numerical solution of such models. If a smooth firing rate function is employed, then standard ODE theory implies that point-neuron models are well posed. Nevertheless, in the steep firing rate regime, the problem may become close to ill posed, and the error amplification, in finite time, can be very large. This observation is illuminated by numerical experiments. We conclude that, if a steep firing rate function is employed, then minor round-off errors can have a devastating effect on simulations, unless proper error-control schemes are used. PMID:27129667

  19. Model reduction of strong-weak neurons

    PubMed Central

    Du, Bosen; Sorensen, Danny; Cox, Steven J.

    2014-01-01

    We consider neurons with large dendritic trees that are weakly excitable in the sense that back propagating action potentials are severly attenuated as they travel from the small, strongly excitable, spike initiation zone. In previous work we have shown that the computational size of weakly excitable cell models may be reduced by two or more orders of magnitude, and that the size of strongly excitable models may be reduced by at least one order of magnitude, without sacrificing the spatio–temporal nature of its inputs (in the sense we reproduce the cell's precise mapping of inputs to outputs). We combine the best of these two strategies via a predictor-corrector decomposition scheme and achieve a drastically reduced highly accurate model of a caricature of the neuron responsible for collision detection in the locust. PMID:25566048

  20. Simple models for reading neuronal population codes.

    PubMed Central

    Seung, H S; Sompolinsky, H

    1993-01-01

    In many neural systems, sensory information is distributed throughout a population of neurons. We study simple neural network models for extracting this information. The inputs to the networks are the stochastic responses of a population of sensory neurons tuned to directional stimuli. The performance of each network model in psychophysical tasks is compared with that of the optimal maximum likelihood procedure. As a model of direction estimation in two dimensions, we consider a linear network that computes a population vector. Its performance depends on the width of the population tuning curves and is maximal for width, which increases with the level of background activity. Although for narrowly tuned neurons the performance of the population vector is significantly inferior to that of maximum likelihood estimation, the difference between the two is small when the tuning is broad. For direction discrimination, we consider two models: a perceptron with fully adaptive weights and a network made by adding an adaptive second layer to the population vector network. We calculate the error rates of these networks after exhaustive training to a particular direction. By testing on the full range of possible directions, the extent of transfer of training to novel stimuli can be calculated. It is found that for threshold linear networks the transfer of perceptual learning is nonmonotonic. Although performance deteriorates away from the training stimulus, it peaks again at an intermediate angle. This nonmonotonicity provides an important psychophysical test of these models. PMID:8248166

  1. Biophysically realistic minimal model of dopamine neuron

    NASA Astrophysics Data System (ADS)

    Oprisan, Sorinel

    2008-03-01

    We proposed and studied a new biophysically relevant computational model of dopaminergic neurons. Midbrain dopamine neurons are involved in motivation and the control of movement, and have been implicated in various pathologies such as Parkinson's disease, schizophrenia, and drug abuse. The model we developed is a single-compartment Hodgkin-Huxley (HH)-type parallel conductance membrane model. The model captures the essential mechanisms underlying the slow oscillatory potentials and plateau potential oscillations. The main currents involved are: 1) a voltage-dependent fast calcium current, 2) a small conductance potassium current that is modulated by the cytosolic concentration of calcium, and 3) a slow voltage-activated potassium current. We developed multidimensional bifurcation diagrams and extracted the effective domains of sustained oscillations. The model includes a calcium balance due to the fundamental importance of calcium influx as proved by simultaneous electrophysiological and calcium imaging procedure. Although there are significant evidences to suggest a partially electrogenic calcium pump, all previous models considered only elecrtogenic pumps. We investigated the effect of the electrogenic calcium pump on the bifurcation diagram of the model and compared our findings against the experimental results.

  2. Qualitative-Modeling-Based Silicon Neurons and Their Networks

    PubMed Central

    Kohno, Takashi; Sekikawa, Munehisa; Li, Jing; Nanami, Takuya; Aihara, Kazuyuki

    2016-01-01

    The ionic conductance models of neuronal cells can finely reproduce a wide variety of complex neuronal activities. However, the complexity of these models has prompted the development of qualitative neuron models. They are described by differential equations with a reduced number of variables and their low-dimensional polynomials, which retain the core mathematical structures. Such simple models form the foundation of a bottom-up approach in computational and theoretical neuroscience. We proposed a qualitative-modeling-based approach for designing silicon neuron circuits, in which the mathematical structures in the polynomial-based qualitative models are reproduced by differential equations with silicon-native expressions. This approach can realize low-power-consuming circuits that can be configured to realize various classes of neuronal cells. In this article, our qualitative-modeling-based silicon neuron circuits for analog and digital implementations are quickly reviewed. One of our CMOS analog silicon neuron circuits can realize a variety of neuronal activities with a power consumption less than 72 nW. The square-wave bursting mode of this circuit is explained. Another circuit can realize Class I and II neuronal activities with about 3 nW. Our digital silicon neuron circuit can also realize these classes. An auto-associative memory realized on an all-to-all connected network of these silicon neurons is also reviewed, in which the neuron class plays important roles in its performance. PMID:27378842

  3. Synchronized action of synaptically coupled chaotic model neurons.

    PubMed

    Abarbanel, H D; Huerta, R; Rabinovich, M I; Rulkov, N F; Rowat, P F; Selverston, A I

    1996-11-15

    Experimental observations of the intracellular recorded electrical activity in individual neurons show that the temporal behavior is often chaotic. We discuss both our own observations on a cell from the stomatogastric central pattern generator of lobster and earlier observations in other cells. In this paper we work with models with chaotic neurons, building on models by Hindmarsh and Rose for bursting, spiking activity in neurons. The key feature of these simplified models of neurons is the presence of coupled slow and fast subsystems. We analyze the model neurons using the same tools employed in the analysis of our experimental data. We couple two model neurons both electrotonically and electrochemically in inhibitory and excitatory fashions. In each of these cases, we demonstrate that the model neurons can synchronize in phase and out of phase depending on the strength of the coupling. For normal synaptic coupling, we have a time delay between the action of one neuron and the response of the other. We also analyze how the synchronization depends on this delay. A rich spectrum of synchronized behaviors is possible for electrically coupled neurons and for inhibitory coupling between neurons. In synchronous neurons one typically sees chaotic motion of the coupled neurons. Excitatory coupling produces essentially periodic voltage trajectories, which are also synchronized. We display and discuss these synchronized behaviors using two "distance" measures of the synchronization. PMID:8888609

  4. Stochastic resonance in models of neuronal ensembles

    NASA Astrophysics Data System (ADS)

    Chialvo, Dante R.; Longtin, André; Müautller-Gerking, Johannes

    1997-02-01

    Two recently suggested mechanisms for the neuronal encoding of sensory information involving the effect of stochastic resonance with aperiodic time-varying inputs are considered. It is shown, using theoretical arguments and numerical simulations, that the nonmonotonic behavior with increasing noise of the correlation measures used for the so-called aperiodic stochastic resonance (ASR) scenario does not rely on the cooperative effect typical of stochastic resonance in bistable and excitable systems. Rather, ASR with slowly varying signals is more properly interpreted as linearization by noise. Consequently, the broadening of the ``resonance curve'' in the multineuron stochastic resonance without tuning scenario can also be explained by this linearization. Computation of the input-output correlation as a function of both signal frequency and noise for the model system further reveals conditions where noise-induced firing with aperiodic inputs will benefit from stochastic resonance rather than linearization by noise. Thus, our study clarifies the tuning requirements for the optimal transduction of subthreshold aperiodic signals. It also shows that a single deterministic neuron can perform as well as a network when biased into a suprathreshold regime. Finally, we show that the inclusion of a refractory period in the spike-detection scheme produces a better correlation between instantaneous firing rate and input signal.

  5. Chaotic neuron models and their VLSI circuit implementations.

    PubMed

    Hsu, C C; Gobovic, D; Zaghloul, M E; Szu, H H

    1996-01-01

    The design of a chaotic neuron model is proposed and implemented in a CMOS very large scale integration (VLSI) chip. The transfer function of the neuron is defined as a piecewise linear (PWL) N-shaped function. In this paper, the new concept of the baseline function is introduced. It is the mapping of the neuron state to the neuron output. It is used to control the chaotic behavior of collective neurons. The chaotic behavior is analyzed and verified by Lyapunov exponents. An analog CMOS chip was designed to implement the theory and it was fabricated through the MOSIS program. The measurement diagnoses of the chip is demonstrated. PMID:18263529

  6. Computational models of neuron-astrocyte interaction in epilepsy

    PubMed Central

    Volman, Vladislav; Bazhenov, Maxim; Sejnowski, Terrence J.

    2012-01-01

    Astrocytes actively shape the dynamics of neurons and neuronal ensembles by affecting several aspects critical to neuronal function, such as regulating synaptic plasticity, modulating neuronal excitability, and maintaining extracellular ion balance. These pathways for astrocyte-neuron interaction can also enhance the information-processing capabilities of brains, but in other circumstances may lead the brain on the road to pathological ruin. In this article, we review the existing computational models of astrocytic involvement in epileptogenesis, focusing on their relevance to existing physiological data. PMID:23060780

  7. Determining the Oxidation States of Manganese in NT2 Cells and Cultured Astrocytes

    SciTech Connect

    Gunter,K.; Aschner, M.; Miller, L.; Eliseev, R.; Salter, J.; Andersen, K.; Gunter, T.

    2006-01-01

    Excessive brain manganese (Mn) can produce a syndrome called 'manganism', which correlates with loss of striatal dopamine and cell death in the striatum and globus pallidus. The prevalent hypothesis for the cause of this syndrome has been oxidation of cell components by the strong oxidizing agent, Mn{sup 3+}, either formed by oxidation of intracellular Mn{sup 2+} or transported into the cell as Mn{sup 3+}. We have recently used X-ray absorption near edge structure spectroscopy (XANES) to determine the oxidation states of manganese complexes in brain and liver mitochondria and in nerve growth factor (NGF)-induced and non-induced PC12 cells. No evidence was found for stabilization or accumulation of Mn{sup 3+} complexes because of oxidation of Mn{sup 2+} by reactive oxygen species in these tissues. Here we extend these studies of manganese oxidation state to cells of brain origin, human neuroteratocarcinoma (NT2) cells and primary cultures of rat astrocytes. Again we find no evidence for stabilization or accumulation of any Mn{sup 3+} complex derived from oxidation of Mn{sup 2+} under a range of conditions.

  8. The effects of cholinergic neuromodulation on neuronal phase-response curves of modeled cortical neurons

    PubMed Central

    Stiefel, Klaus M.; Gutkin, Boris S.; Sejnowski, Terrence J.

    2010-01-01

    The response of an oscillator to perturbations is described by its phase-response curve (PRC), which is related to the type of bifurcation leading from rest to tonic spiking. In a recent experimental study, we have shown that the type of PRC in cortical pyramidal neurons can be switched by cholinergic neuromodulation from type II (biphasic) to type I (monophasic). We explored how intrinsic mechanisms affected by acetylcholine influence the PRC using three different types of neuronal models: a theta neuron, single-compartment neurons and a multi-compartment neuron. In all of these models a decrease in the amount of a spike-frequency adaptation current was a necessary and sufficient condition for the shape of the PRC to change from biphasic (type II) to purely positive (type I). PMID:18784991

  9. Functionalized anatomical models for EM-neuron Interaction modeling.

    PubMed

    Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang

    2016-06-21

    The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions. PMID:27224508

  10. Functionalized anatomical models for EM-neuron Interaction modeling

    NASA Astrophysics Data System (ADS)

    Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang

    2016-06-01

    The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.

  11. A simple chaotic neuron model: stochastic behavior of neural networks.

    PubMed

    Aydiner, Ekrem; Vural, Adil M; Ozcelik, Bekir; Kiymac, Kerim; Tan, Uner

    2003-05-01

    We have briefly reviewed the occurrence of the post-synaptic potentials between neurons, the relationship between EEG and neuron dynamics, as well as methods of signal analysis. We propose a simple stochastic model representing electrical activity of neuronal systems. The model is constructed using the Monte Carlo simulation technique. The results yielded EEG-like signals with their phase portraits in three-dimensional space. The Lyapunov exponent was positive, indicating chaotic behavior. The correlation of the EEG-like signals was.92, smaller than those reported by others. It was concluded that this neuron model may provide valuable clues about the dynamic behavior of neural systems. PMID:12745622

  12. Comparing Realistic Subthalamic Nucleus Neuron Models

    NASA Astrophysics Data System (ADS)

    Njap, Felix; Claussen, Jens C.; Moser, Andreas; Hofmann, Ulrich G.

    2011-06-01

    The mechanism of action of clinically effective electrical high frequency stimulation is still under debate. However, recent evidence points at the specific activation of GABA-ergic ion channels. Using a computational approach, we analyze temporal properties of the spike trains emitted by biologically realistic neurons of the subthalamic nucleus (STN) as a function of GABA-ergic synaptic input conductances. Our contribution is based on a model proposed by Rubin and Terman and exhibits a wide variety of different firing patterns, silent, low spiking, moderate spiking and intense spiking activity. We observed that most of the cells in our network turn to silent mode when we increase the GABAA input conductance above the threshold of 3.75 mS/cm2. On the other hand, insignificant changes in firing activity are observed when the input conductance is low or close to zero. We thus reproduce Rubin's model with vanishing synaptic conductances. To quantitatively compare spike trains from the original model with the modified model at different conductance levels, we apply four different (dis)similarity measures between them. We observe that Mahalanobis distance, Victor-Purpura metric, and Interspike Interval distribution are sensitive to different firing regimes, whereas Mutual Information seems undiscriminative for these functional changes.

  13. Multistability in a neuron model with extracellular potassium dynamics

    NASA Astrophysics Data System (ADS)

    Wu, Xing-Xing; Shuai, J. W.

    2012-06-01

    Experiments show a primary role of extracellular potassium concentrations in neuronal hyperexcitability and in the generation of epileptiform bursting and depolarization blocks without synaptic mechanisms. We adopt a physiologically relevant hippocampal CA1 neuron model in a zero-calcium condition to better understand the function of extracellular potassium in neuronal seizurelike activities. The model neuron is surrounded by interstitial space in which potassium ions are able to accumulate. Potassium currents, Na+-K+ pumps, glial buffering, and ion diffusion are regulatory mechanisms of extracellular potassium. We also consider a reduced model with a fixed potassium concentration. The bifurcation structure and spiking frequency of the two models are studied. We show that, besides hyperexcitability and bursting pattern modulation, the potassium dynamics can induce not only bistability but also tristability of different firing patterns. Our results reveal the emergence of the complex behavior of multistability due to the dynamical [K+]o modulation on neuronal activities.

  14. A modular analog neuron-model for research and teaching.

    PubMed

    Koch, U T; Brunner, M

    1988-01-01

    An analog electronic neuron for modeling neuronal networks and for teaching purposes is presented. The circuitry represents a new approach, since ionic channels are all modeled by fast relay switches in combination with resistors. Thus, the synapse design includes nonlinear PSP superposition and reversal potentials. The spike is modeled with Na+ and K+ currents. Detailed circuit diagrams and examples of performance are given. Besides its use in network research, the model has been successfully used over 3 years of teaching practice. PMID:3196775

  15. SIMPEL: circuit model for photonic spike processing laser neurons.

    PubMed

    Shastri, Bhavin J; Nahmias, Mitchell A; Tait, Alexander N; Wu, Ben; Prucnal, Paul R

    2015-03-23

    We propose an equivalent circuit model for photonic spike processing laser neurons with an embedded saturable absorber—a simulation model for photonic excitable lasers (SIMPEL). We show that by mapping the laser neuron rate equations into a circuit model, SPICE analysis can be used as an efficient and accurate engine for numerical calculations, capable of generalization to a variety of different types of laser neurons with saturable absorber found in literature. The development of this model parallels the Hodgkin-Huxley model of neuron biophysics, a circuit framework which brought efficiency, modularity, and generalizability to the study of neural dynamics. We employ the model to study various signal-processing effects such as excitability with excitatory and inhibitory pulses, binary all-or-nothing response, and bistable dynamics. PMID:25837141

  16. Measuring neuronal branching patterns using model-based approach.

    PubMed

    Luczak, Artur

    2010-01-01

    Neurons have complex branching systems which allow them to communicate with thousands of other neurons. Thus understanding neuronal geometry is clearly important for determining connectivity within the network and how this shapes neuronal function. One of the difficulties in uncovering relationships between neuronal shape and its function is the problem of quantifying complex neuronal geometry. Even by using multiple measures such as: dendritic length, distribution of segments, direction of branches, etc, a description of three dimensional neuronal embedding remains incomplete. To help alleviate this problem, here we propose a new measure, a shape diffusiveness index (SDI), to quantify spatial relations between branches at the local and global scale. It was shown that growth of neuronal trees can be modeled by using diffusion limited aggregation (DLA) process. By measuring "how easy" it is to reproduce the analyzed shape by using the DLA algorithm it can be measured how "diffusive" is that shape. Intuitively, "diffusiveness" measures how tree-like is a given shape. For example shapes like an oak tree will have high values of SDI. This measure is capturing an important feature of dendritic tree geometry, which is difficult to assess with other measures. This approach also presents a paradigm shift from well-defined deterministic measures to model-based measures, which estimate how well a model with specific properties can account for features of analyzed shape. PMID:21079752

  17. Modeling schizophrenia using hiPSC neurons

    PubMed Central

    Brennand, Kristen; Simone, Anthony; Jou, Jessica; Gelboin-Burkhart, Chelsea; Tran, Ngoc; Sangar, Sarah; Li, Yan; Mu, Yangling; Chen, Gong; Yu, Diana; McCarthy, Shane; Sebat, Jonathan; Gage, Fred H.

    2012-01-01

    SUMMARY Schizophrenia (SCZD) is a debilitating neurological disorder with a world-wide prevalence of 1%; there is a strong genetic component, with an estimated heritability of 80–85%1. Though postmortem studies have revealed reduced brain volume, cell size, spine density and abnormal neural distribution in the prefrontal cortex and hippocampus of SCZD brain tissue2 and neuropharmacological studies have implicated dopaminergic, glutamatergic and GABAergic activity in SCZD3, the cell types affected in SCZD and the molecular mechanisms underlying the disease state remain unclear. To elucidate the cellular and molecular defects of SCZD, we directly reprogrammed fibroblasts from SCZD patients into human induced pluripotent stem cells (hiPSCs) and subsequently differentiated these disorder-specific hiPSCs into neurons (SI Fig. 1). SCZD hiPSC neurons showed diminished neuronal connectivity in conjunction with decreased neurite number, PSD95-protein levels and glutamate receptor expression. Gene expression profiles of SCZD hiPSC neurons identified altered expression of many components of the cAMP and WNT signaling pathways. Key cellular and molecular elements of the SCZD phenotype were ameliorated following treatment of SCZD hiPSC neurons with the antipsychotic Loxapine. To date, hiPSC neuronal pathology has only been demonstrated in diseases characterized by both the loss of function of a single gene product and rapid disease progression in early childhood4–6. We now report hiPSC neuronal phenotypes and gene expression changes associated with SCZD, a complex genetic psychiatric disorder (SI Table 1). PMID:21490598

  18. Small is beautiful: models of small neuronal networks

    PubMed Central

    Lamb, Damon G; Calabrese, Ronald L

    2013-01-01

    Modeling has contributed a great deal to our understanding of how individual neurons and neuronal networks function. In this review, we focus on models of the small neuronal networks of invertebrates, especially rhythmically active CPG networks. Models have elucidated many aspects of these networks, from identifying key interacting membrane properties to pointing out gaps in our understanding, for example missing neurons. Even the complex CPGs of vertebrates, such as those that underlie respiration, have been reduced to small network models to great effect. Modeling of these networks spans from simplified models, which are amenable to mathematical analyses, to very complicated biophysical models. Some researchers have now adopted a population approach, where they generate and analyze many related models that differ in a few to several judiciously chosen free parameters; often these parameters show variability across animals and thus justify the approach. Models of small neuronal networks will continue to expand and refine our understanding of how neuronal networks in all animals program motor output, process sensory information and learn. PMID:22364687

  19. Small is beautiful: models of small neuronal networks.

    PubMed

    Lamb, Damon G; Calabrese, Ronald L

    2012-08-01

    Modeling has contributed a great deal to our understanding of how individual neurons and neuronal networks function. In this review, we focus on models of the small neuronal networks of invertebrates, especially rhythmically active CPG networks. Models have elucidated many aspects of these networks, from identifying key interacting membrane properties to pointing out gaps in our understanding, for example missing neurons. Even the complex CPGs of vertebrates, such as those that underlie respiration, have been reduced to small network models to great effect. Modeling of these networks spans from simplified models, which are amenable to mathematical analyses, to very complicated biophysical models. Some researchers have now adopted a population approach, where they generate and analyze many related models that differ in a few to several judiciously chosen free parameters; often these parameters show variability across animals and thus justify the approach. Models of small neuronal networks will continue to expand and refine our understanding of how neuronal networks in all animals program motor output, process sensory information and learn. PMID:22364687

  20. How to bake a brain: yeast as a model neuron.

    PubMed

    Sarto-Jackson, Isabella; Tomaska, Lubomir

    2016-05-01

    More than 30 years ago Dan Koshland published an inspirational essay presenting the bacterium as a model neuron (Koshland, Trends Neurosci 6:133-137, 1983). In the article he argued that there are several similarities between neurons and bacterial cells in "how signals are processed within a cell or how this processing machinery can be modified to produce plasticity". He then explored the bacterial chemosensory system to emphasize its attributes that are analogous to information processing in neurons. In this review, we wish to expand Koshland's original idea by adding the yeast cell to the list of useful models of a neuron. The fact that yeasts and neurons are specialized versions of the eukaryotic cell sharing all principal components sets the stage for a grand evolutionary tinkering where these components are employed in qualitatively different tasks, but following analogous molecular logic. By way of example, we argue that evolutionarily conserved key components involved in polarization processes (from budding or mating in Saccharomyces cervisiae to neurite outgrowth or spinogenesis in neurons) are shared between yeast and neurons. This orthologous conservation of modules makes S. cervisiae an excellent model organism to investigate neurobiological questions. We substantiate this claim by providing examples of yeast models used for studying neurological diseases. PMID:26782173

  1. A Neuron-Based Model of Sleep-Wake Cycles

    NASA Astrophysics Data System (ADS)

    Postnova, Svetlana; Peters, Achim; Braun, Hans

    2008-03-01

    In recent years it was discovered that a neuropeptide orexin/hypocretin plays a main role in sleep processes. This peptide is produced by the neurons in the lateral hypothalamus, which project to almost all brain areas. We present a computational model of sleep-wake cycles, which is based on the Hodgkin-Huxley type neurons and considers reciprocal glutaminergic projections between the lateral hypothalamus and the prefrontal cortex. Orexin is released as a neuromodulator and is required to keep the neurons firing, which corresponds to the wake state. When orexin is depleted the neurons are getting silent as observed in the sleep state. They can be reactivated by the circadian signal from the suprachiasmatic nucleus and/or external stimuli (alarm clock). Orexin projections to the thalamocortical neurons also can account for their transition from tonic firing activity during wakefulness to synchronized burst discharges during sleep.

  2. A Statistical Model for In Vivo Neuronal Dynamics

    PubMed Central

    Surace, Simone Carlo; Pfister, Jean-Pascal

    2015-01-01

    Single neuron models have a long tradition in computational neuroscience. Detailed biophysical models such as the Hodgkin-Huxley model as well as simplified neuron models such as the class of integrate-and-fire models relate the input current to the membrane potential of the neuron. Those types of models have been extensively fitted to in vitro data where the input current is controlled. Those models are however of little use when it comes to characterize intracellular in vivo recordings since the input to the neuron is not known. Here we propose a novel single neuron model that characterizes the statistical properties of in vivo recordings. More specifically, we propose a stochastic process where the subthreshold membrane potential follows a Gaussian process and the spike emission intensity depends nonlinearly on the membrane potential as well as the spiking history. We first show that the model has a rich dynamical repertoire since it can capture arbitrary subthreshold autocovariance functions, firing-rate adaptations as well as arbitrary shapes of the action potential. We then show that this model can be efficiently fitted to data without overfitting. We finally show that this model can be used to characterize and therefore precisely compare various intracellular in vivo recordings from different animals and experimental conditions. PMID:26571371

  3. Neuronal trauma model: in search of Thanatos.

    PubMed

    Cole, Kasie; Perez-Polo, J Regino

    2004-11-01

    Trauma to the nervous system triggers responses that include oxidative stress due to the generation of reactive oxygen species (ROS). DNA is a major macromolecular target of ROS, and ROS-induced DNA strand breaks activate poly(ADP-ribose)polymerase-1 (PARP-1). Upon activation PARP-1 uses NAD(+) as a substrate to catalyze the transfer of ADP-ribose subunits to a host of nuclear proteins. In the face of extensive DNA strand breaks, PARP-1 activation can lead to depletion of intracellular NAD(P)(H) pools, large decreases in ATP, that threaten cell survival. Accordingly, inhibition of PARP-1 activity after acute oxidative injury has been shown to increase cell survival. When NGF-differentiated PC12 cells, an in vitro neuronal model, are exposed to H(2)O(2) there is increased synthesis of poly ADP-ribose and decreases in intracellular NAD(P)(H) and ATP. Addition of the chemical PARP inhibitor 3-aminobenzamide (AB) prior to H(2)O(2) exposure blocks the synthesis of poly ADP-ribose and maintains intracellular NAD(P)(H) and ATP levels. H(2)O(2) injury is characterized by an immediate, necrotic cell death 2h after injury and a delayed apoptotic-like death 12-24h after injury. This apoptotic-like death is characterized by apoptotic membrane changes and apoptotic DNA fragmentation but is not associated with measurable caspase-3 activity. AB delays cell death beyond 24h and increases cell survival by approximately 25%. This protective effect is accompanied by significantly decreased necrosis and the apoptotic-like death associated with H(2)O(2) exposure. AB also restores caspase-3 which can be attributed to the activation of the upstream activator of caspase-3, caspase-9. Thus, the maintenance of intracellular ATP levels associated with PARP-1 inhibition shifts cell death from necrosis to apoptosis and from apoptosis to cell survival. Furthermore, the shift from necrosis to apoptosis may be explained, in part, by an energy-dependent activation of caspase-9. PMID:15465278

  4. Virtual NEURON: a strategy for merged biochemical and electrophysiological modeling.

    PubMed

    Brown, Sherry-Ann; Moraru, Ion I; Schaff, James C; Loew, Leslie M

    2011-10-01

    Because of its highly branched dendrite, the Purkinje neuron requires significant computational resources if coupled electrical and biochemical activity are to be simulated. To address this challenge, we developed a scheme for reducing the geometric complexity; while preserving the essential features of activity in both the soma and a remote dendritic spine. We merged our previously published biochemical model of calcium dynamics and lipid signaling in the Purkinje neuron, developed in the Virtual Cell modeling and simulation environment, with an electrophysiological model based on a Purkinje neuron model available in NEURON. A novel reduction method was applied to the Purkinje neuron geometry to obtain a model with fewer compartments that is tractable in Virtual Cell. Most of the dendritic tree was subject to reduction, but we retained the neuron's explicit electrical and geometric features along a specified path from spine to soma. Further, unlike previous simplification methods, the dendrites that branch off along the preserved explicit path are retained as reduced branches. We conserved axial resistivity and adjusted passive properties and active channel conductances for the reduction in surface area, and cytosolic calcium for the reduction in volume. Rallpacks are used to validate the reduction algorithm and show that it can be generalized to other complex neuronal geometries. For the Purkinje cell, we found that current injections at the soma were able to produce similar trains of action potentials and membrane potential propagation in the full and reduced models in NEURON; the reduced model produces identical spiking patterns in NEURON and Virtual Cell. Importantly, our reduced model can simulate communication between the soma and a distal spine; an alpha function applied at the spine to represent synaptic stimulation gave similar results in the full and reduced models for potential changes associated with both the spine and the soma. Finally, we combined

  5. An experimental electronic model for a neuronal cell

    NASA Astrophysics Data System (ADS)

    Campos-Cantón, I.; Rangel-López, A.; Martel-Gallegos, G.; Zarazúa, S.; Vertiz-Hérnandez, A.

    2014-04-01

    Over the last two decades, the study of information transmission in living beings has acquired great relevance, because it regulates and conducts the functioning of all of the organs in the body. In information transmission pathways, the neuron plays an important role in that it receives, transmits, and processes electrical signals from different parts of the human body; these signals are transmitted as electrical impulses called action potentials, and they transmit information from one neuron to another. In this work, and with the aim of developing experiments for teaching biological processes, we implemented an electronic circuit of the neuron cell device and its mathematical model based on piecewise linear functions.

  6. Genesis and Control of bursting activity in a neuronal model

    NASA Astrophysics Data System (ADS)

    Cymbalyuk, Gennady

    2005-11-01

    Neurons are observed in one of four fundamental activity modes: silence, sub-threshold oscillations, tonic spiking, and bursting. Neurons exhibit various activity regimes and regime transitions that reflect their complement of ionic channels and modulatory state. The leech presents unique opportunities for experimental and theoretical studies on the dynamics of neuronal activity. The central pattern generator controlling the leech's heartbeat contains identified pairs of mutually inhibitory neurons. Bursting activity of neurons is an oscillatory activity consisting of intervals of repetitive spiking separated by intervals of quiescence. It has been observed in neurons under normal and pathological conditions. Neurons which are capable of generating bursting activity endogenously play an important role in motor control and other brain functions. Burst duration, interburst interval and spike frequency are crucial temporal characteristics of bursting activity and thus have to be regulated. Application of the bifurcation theory of dynamical systems suggests new mechanism of how bursting activity can be generated by neurons and how burst duration can be regulated. Here we describe two mechanisms for the transition between tonic spiking and bursting. First mechanism describes a smooth, continuous and reversible transition from tonic spiking into bursting in a model neuron. The burst duration increases with no bound as 1/(a-a0)^1/2, where a0 is a parameter determining the transition. The characteristic features of this mechanism are that (a) the burst duration can be made arbitrarily long while (b) inter-burst interval does not depend on the parameter. The second mechanism is concerned with bi-stability where simultaneous tonic spiking and bursting activities co-exist in a neuron. The mechanism is based on a saddle-node periodic orbit bifurcation with non-central homoclinic orbits. This bifurcation describes a transition between three qualitatively different types of

  7. Visual Attention Model Based on Statistical Properties of Neuron Responses

    PubMed Central

    Duan, Haibin; Wang, Xiaohua

    2015-01-01

    Visual attention is a mechanism of the visual system that can select relevant objects from a specific scene. Interactions among neurons in multiple cortical areas are considered to be involved in attentional allocation. However, the characteristics of the encoded features and neuron responses in those attention related cortices are indefinite. Therefore, further investigations carried out in this study aim at demonstrating that unusual regions arousing more attention generally cause particular neuron responses. We suppose that visual saliency is obtained on the basis of neuron responses to contexts in natural scenes. A bottom-up visual attention model is proposed based on the self-information of neuron responses to test and verify the hypothesis. Four different color spaces are adopted and a novel entropy-based combination scheme is designed to make full use of color information. Valuable regions are highlighted while redundant backgrounds are suppressed in the saliency maps obtained by the proposed model. Comparative results reveal that the proposed model outperforms several state-of-the-art models. This study provides insights into the neuron responses based saliency detection and may underlie the neural mechanism of early visual cortices for bottom-up visual attention. PMID:25747859

  8. An electromechanical model of neuronal dynamics using Hamilton's principle

    PubMed Central

    Drapaca, Corina S.

    2015-01-01

    Damage of the brain may be caused by mechanical loads such as penetration, blunt force, shock loading from blast, and by chemical imbalances due to neurological diseases and aging that trigger not only neuronal degeneration but also changes in the mechanical properties of brain tissue. An understanding of the interconnected nature of the electro-chemo-mechanical processes that result in brain damage and ultimately loss of functionality is currently lacking. While modern mathematical models that focus on how to link brain mechanics to its biochemistry are essential in enhancing our understanding of brain science, the lack of experimental data required by these models as well as the complexity of the corresponding computations render these models hard to use in clinical applications. In this paper we propose a unified variational framework for the modeling of neuronal electromechanics. We introduce a constrained Lagrangian formulation that takes into account Newton's law of motion of a linear viscoelastic Kelvin–Voigt solid-state neuron as well as the classic Hodgkin–Huxley equations of the electronic neuron. The system of differential equations describing neuronal electromechanics is obtained by applying Hamilton's principle. Numerical simulations of possible damage dynamics in neurons will be presented. PMID:26236195

  9. Inflection, canards and excitability threshold in neuronal models.

    PubMed

    Desroches, M; Krupa, M; Rodrigues, S

    2013-10-01

    A technique is presented, based on the differential geometry of planar curves, to evaluate the excitability threshold of neuronal models. The aim is to determine regions of the phase plane where solutions to the model equations have zero local curvature, thereby defining a zero-curvature (inflection) set that discerns between sub-threshold and spiking electrical activity. This transition can arise through a Hopf bifurcation, via the so-called canard explosion that happens in an exponentially small parameter variation, and this is typical for a large class of planar neuronal models (FitzHugh-Nagumo, reduced Hodgkin-Huxley), namely, type II neurons (resonators). This transition can also correspond to the crossing of the stable manifold of a saddle equilibrium, in the case of type I neurons (integrators). We compute inflection sets and study how well they approximate the excitability threshold of these neuron models, that is, both in the canard and in the non-canard regime, using tools from invariant manifold theory and singularity theory. With the latter, we investigate the topological changes that inflection sets undergo upon parameter variation. Finally, we show that the concept of inflection set gives a good approximation of the threshold in both the so-called resonator and integrator neuronal cases. PMID:22945512

  10. A neuronal model of vowel normalization and representation.

    PubMed

    Sussman, H M

    1986-05-01

    A speculative neuronal model for vowel normalization and representation is offered. The neurophysiological basis for the premise is the "combination-sensitive" neuron recently documented in the auditory cortex of the mustached bat (N. Suga, W. E. O'Neill, K. Kujirai, and T. Manabe, 1983, Journal of Neurophysiology, 49, 1573-1627). These neurons are specialized to respond to either precise frequency, amplitude, or time differentials between specific harmonic components of the pulse-echo pair comprising the biosonar signal of the bat. Such multiple frequency comparisons lie at the heart of human vowel perception and categorization. A representative vowel normalization algorithm is used to illustrate the operational principles of the neuronal model in accomplishing both normalization and categorization in early infancy. The neurological precursors to a phonemic vocalic system is described based on the neurobiological events characterizing regressive neurogenesis. PMID:3013360

  11. Tunable neuromimetic integrated system for emulating cortical neuron models.

    PubMed

    Grassia, Filippo; Buhry, Laure; Lévi, Timothée; Tomas, Jean; Destexhe, Alain; Saïghi, Sylvain

    2011-01-01

    Nowadays, many software solutions are currently available for simulating neuron models. Less conventional than software-based systems, hardware-based solutions generally combine digital and analog forms of computation. In previous work, we designed several neuromimetic chips, including the Galway chip that we used for this paper. These silicon neurons are based on the Hodgkin-Huxley formalism and they are optimized for reproducing a large variety of neuron behaviors thanks to tunable parameters. Due to process variation and device mismatch in analog chips, we use a full-custom fitting method in voltage-clamp mode to tune our neuromimetic integrated circuits. By comparing them with experimental electrophysiological data of these cells, we show that the circuits can reproduce the main firing features of cortical cell types. In this paper, we present the experimental measurements of our system which mimic the four most prominent biological cells: fast spiking, regular spiking, intrinsically bursting, and low-threshold spiking neurons into analog neuromimetic integrated circuit dedicated to cortical neuron simulations. This hardware and software platform will allow to improve the hybrid technique, also called "dynamic-clamp," that consists of connecting artificial and biological neurons to study the function of neuronal circuits. PMID:22163213

  12. Modeling pain in vitro using nociceptor neurons reprogrammed from fibroblasts

    PubMed Central

    Wainger, Brian J.; Buttermore, Elizabeth D.; Oliveira, Julia T.; Mellin, Cassidy; Lee, Seungkyu; Saber, Wardiya Afshar; Wang, Amy; Ichida, Justin K.; Chiu, Isaac M.; Barrett, Lee; Huebner, Eric A.; Bilgin, Canan; Tsujimoto, Naomi; Brenneis, Christian; Kapur, Kush; Rubin, Lee L.; Eggan, Kevin; Woolf, Clifford J.

    2015-01-01

    Reprogramming somatic cells from one cell fate to another can generate specific neurons suitable for disease modeling. To maximize the utility of patient-derived neurons, they must model not only disease-relevant cell classes but also the diversity of neuronal subtypes found in vivo and the pathophysiological changes that underlie specific clinical diseases. Here, we identify five transcription factors that reprogram mouse and human fibroblasts into noxious stimulus-detecting (nociceptor) neurons that recapitulate the expression of quintessential nociceptor-specific functional receptors and channels found in adult mouse nociceptor neurons as well as native subtype diversity. Moreover, the derived nociceptor neurons exhibit TrpV1 sensitization to the inflammatory mediator prostaglandin E2 and the chemotherapeutic drug oxaliplatin, modeling the inherent mechanisms underlying inflammatory pain hypersensitivity and painful chemotherapy-induced neuropathy. Using fibroblasts from patients with familial dysautonomia (hereditary sensory and autonomic neuropathy type III), we show that the technique can reveal novel aspects of human disease phenotypes in vitro. PMID:25420066

  13. Virtual NEURON: a strategy for merged biochemical and electrophysiological modeling

    PubMed Central

    Brown, Sherry-Ann; Moraru, Ion I.; Schaff, James C.

    2011-01-01

    Because of its highly branched dendrite, the Purkinje neuron requires significant computational resources if coupled electrical and biochemical activity are to be simulated. To address this challenge, we developed a scheme for reducing the geometric complexity; while preserving the essential features of activity in both the soma and a remote dendritic spine. We merged our previously published biochemical model of calcium dynamics and lipid signaling in the Purkinje neuron, developed in the Virtual Cell modeling and simulation environment, with an electrophysiological model based on a Purkinje neuron model available in NEURON. A novel reduction method was applied to the Purkinje neuron geometry to obtain a model with fewer compartments that is tractable in Virtual Cell. Most of the dendritic tree was subject to reduction, but we retained the neuron’s explicit electrical and geometric features along a specified path from spine to soma. Further, unlike previous simplification methods, the dendrites that branch off along the preserved explicit path are retained as reduced branches. We conserved axial resistivity and adjusted passive properties and active channel conductances for the reduction in surface area, and cytosolic calcium for the reduction in volume. Rallpacks are used to validate the reduction algorithm and show that it can be generalized to other complex neuronal geometries. For the Purkinje cell, we found that current injections at the soma were able to produce similar trains of action potentials and membrane potential propagation in the full and reduced models in NEURON; the reduced model produces identical spiking patterns in NEURON and Virtual Cell. Importantly, our reduced model can simulate communication between the soma and a distal spine; an alpha function applied at the spine to represent synaptic stimulation gave similar results in the full and reduced models for potential changes associated with both the spine and the soma. Finally, we combined

  14. Exploring the nonlinear dynamics of a physiologically viable model neuron

    SciTech Connect

    Lindner, J.F.; Ditto, W.L.

    1996-06-01

    We describe efforts underway to explore the nonlinear dynamics of the Pinsky-Rinzel model neuron. Via computer simulations, we seek to discover nonlinear phenomena in this physiologically accurate model, thereby complementing ongoing and future experiments. Here we describe the model in detail and analyze it using tools of nonlinear dynamics to demonstrate nontrivial behaviors. {copyright} {ital 1996 American Institute of Physics.}

  15. Mitochondrial bioenergetics and neuronal survival modelled in primary neuronal culture and isolated nerve terminals.

    PubMed

    Nicholls, David G; Brand, Martin D; Gerencser, Akos A

    2015-04-01

    Mitochondria play multiple roles in the maintenance of neuronal function under physiological and pathological conditions. In addition to ATP generation, they can act as major short-term calcium sinks and can both generate, and be damaged by, reactive oxygen species. Two complementary preparations have been extensively employed to investigate in situ neuronal mitochondrial bioenergetics, primary neuronal cultures and acutely isolated nerve terminals, synaptosomes. A major focus of the cell culture preparation has been the investigation of glutamate excitotoxicity. Oxidative phosphorylation, calcium transport and reactive oxygen species play complex interlocking roles in the life and death of the glutamate exposed neuron. Synaptosomes may be isolated from specific brain regions at any developmental stage and therefore provide a valuable ex vivo approach in studying mouse models. Recent advances have allowed synaptosomal bioenergetics to be studied on a microgram scale, and, in combination with approaches to correct for functional and transmitter heterogeneity, have allowed hypotheses concerning presynaptic mitochondrial dysfunction to be tested on a variety of genetic models of neurodegenerative disorders. PMID:25172197

  16. Mathematical modeling of subthreshold resonant properties in pyloric dilator neurons.

    PubMed

    Vazifehkhah Ghaffari, Babak; Kouhnavard, Mojgan; Aihara, Takeshi; Kitajima, Tatsuo

    2015-01-01

    Various types of neurons exhibit subthreshold resonance oscillation (preferred frequency response) to fluctuating sinusoidal input currents. This phenomenon is well known to influence the synaptic plasticity and frequency of neural network oscillation. This study evaluates the resonant properties of pacemaker pyloric dilator (PD) neurons in the central pattern generator network through mathematical modeling. From the pharmacological point of view, calcium currents cannot be blocked in PD neurons without removing the calcium-dependent potassium current. Thus, the effects of calcium (I(Ca)) and calcium-dependent potassium (I(KCa)) currents on resonant properties remain unclear. By taking advantage of Hodgkin-Huxley-type model of neuron and its equivalent RLC circuit, we examine the effects of changing resting membrane potential and those ionic currents on the resonance. Results show that changing the resting membrane potential influences the amplitude and frequency of resonance so that the strength of resonance (Q-value) increases by both depolarization and hyperpolarization of the resting membrane potential. Moreover, hyperpolarization-activated inward current (I(h)) and I(Ca) (in association with I(KCa)) are dominant factors on resonant properties at hyperpolarized and depolarized potentials, respectively. Through mathematical analysis, results indicate that I h and I(KCa) affect the resonant properties of PD neurons. However, I(Ca) only has an amplifying effect on the resonance amplitude of these neurons. PMID:25960999

  17. Mathematical Modeling of Subthreshold Resonant Properties in Pyloric Dilator Neurons

    PubMed Central

    Vazifehkhah Ghaffari, Babak; Kouhnavard, Mojgan; Aihara, Takeshi; Kitajima, Tatsuo

    2015-01-01

    Various types of neurons exhibit subthreshold resonance oscillation (preferred frequency response) to fluctuating sinusoidal input currents. This phenomenon is well known to influence the synaptic plasticity and frequency of neural network oscillation. This study evaluates the resonant properties of pacemaker pyloric dilator (PD) neurons in the central pattern generator network through mathematical modeling. From the pharmacological point of view, calcium currents cannot be blocked in PD neurons without removing the calcium-dependent potassium current. Thus, the effects of calcium (ICa) and calcium-dependent potassium (IKCa) currents on resonant properties remain unclear. By taking advantage of Hodgkin-Huxley-type model of neuron and its equivalent RLC circuit, we examine the effects of changing resting membrane potential and those ionic currents on the resonance. Results show that changing the resting membrane potential influences the amplitude and frequency of resonance so that the strength of resonance (Q-value) increases by both depolarization and hyperpolarization of the resting membrane potential. Moreover, hyperpolarization-activated inward current (Ih) and ICa (in association with IKCa) are dominant factors on resonant properties at hyperpolarized and depolarized potentials, respectively. Through mathematical analysis, results indicate that Ih and IKCa affect the resonant properties of PD neurons. However, ICa only has an amplifying effect on the resonance amplitude of these neurons. PMID:25960999

  18. The neuronal ceroid lipofuscinoses: Opportunities from model systems.

    PubMed

    Faller, Kiterie M E; Gutierrez-Quintana, Rodrigo; Mohammed, Alamin; Rahim, Ahad A; Tuxworth, Richard I; Wager, Kim; Bond, Michael

    2015-10-01

    The neuronal ceroid lipofuscinoses are a group of severe and progressive neurodegenerative disorders, generally with childhood onset. Despite the fact that these diseases remain fatal, significant breakthroughs have been made in our understanding of the genetics that underpin these conditions. This understanding has allowed the development of a broad range of models to study disease processes, and to develop new therapeutic approaches. Such models have contributed significantly to our knowledge of these conditions. In this review we will focus on the advantages of each individual model, describe some of the contributions the models have made to our understanding of the broader disease biology and highlight new techniques and approaches relevant to the study and potential treatment of the neuronal ceroid lipofuscinoses. This article is part of a Special Issue entitled: "Current Research on the Neuronal Ceroid Lipofuscinoses (Batten Disease)". PMID:25937302

  19. Spiking neuron model for temporal sequence recognition.

    PubMed

    Byrnes, Sean; Burkitt, Anthony N; Grayden, David B; Meffin, Hamish

    2010-01-01

    A biologically inspired neuronal network that stores and recognizes temporal sequences of symbols is described. Each symbol is represented by excitatory input to distinct groups of neurons (symbol pools). Unambiguous storage of multiple sequences with common subsequences is ensured by partitioning each symbol pool into subpools that respond only when the current symbol has been preceded by a particular sequence of symbols. We describe synaptic structure and neural dynamics that permit the selective activation of subpools by the correct sequence. Symbols may have varying durations of the order of hundreds of milliseconds. Physiologically plausible plasticity mechanisms operate on a time scale of tens of milliseconds; an interaction of the excitatory input with periodic global inhibition bridges this gap so that neural events representing successive symbols occur on this much faster timescale. The network is shown to store multiple overlapping sequences of events. It is robust to variation in symbol duration, it is scalable, and its performance degrades gracefully with perturbation of its parameters. PMID:19842991

  20. A Developmental Approach to Predicting Neuronal Connectivity from Small Biological Datasets: A Gradient-Based Neuron Growth Model

    PubMed Central

    Borisyuk, Roman; Azad, Abul Kalam al; Conte, Deborah; Roberts, Alan; Soffe, Stephen R.

    2014-01-01

    Relating structure and function of neuronal circuits is a challenging problem. It requires demonstrating how dynamical patterns of spiking activity lead to functions like cognitive behaviour and identifying the neurons and connections that lead to appropriate activity of a circuit. We apply a “developmental approach” to define the connectome of a simple nervous system, where connections between neurons are not prescribed but appear as a result of neuron growth. A gradient based mathematical model of two-dimensional axon growth from rows of undifferentiated neurons is derived for the different types of neurons in the brainstem and spinal cord of young tadpoles of the frog Xenopus. Model parameters define a two-dimensional CNS growth environment with three gradient cues and the specific responsiveness of the axons of each neuron type to these cues. The model is described by a nonlinear system of three difference equations; it includes a random variable, and takes specific neuron characteristics into account. Anatomical measurements are first used to position cell bodies in rows and define axon origins. Then a generalization procedure allows information on the axons of individual neurons from small anatomical datasets to be used to generate larger artificial datasets. To specify parameters in the axon growth model we use a stochastic optimization procedure, derive a cost function and find the optimal parameters for each type of neuron. Our biologically realistic model of axon growth starts from axon outgrowth from the cell body and generates multiple axons for each different neuron type with statistical properties matching those of real axons. We illustrate how the axon growth model works for neurons with axons which grow to the same and the opposite side of the CNS. We then show how, by adding a simple specification for dendrite morphology, our model “developmental approach” allows us to generate biologically-realistic connectomes. PMID:24586794

  1. Reconstruction of neuronal input through modeling single-neuron dynamics and computations

    NASA Astrophysics Data System (ADS)

    Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin; Chan, Wai-lok

    2016-06-01

    Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

  2. Reconstruction of neuronal input through modeling single-neuron dynamics and computations.

    PubMed

    Qin, Qing; Wang, Jiang; Yu, Haitao; Deng, Bin; Chan, Wai-Lok

    2016-06-01

    Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is. PMID:27368786

  3. Parameter space of the Rulkov chaotic neuron model

    NASA Astrophysics Data System (ADS)

    Wang, Caixia; Cao, Hongjun

    2014-06-01

    The parameter space of the two dimensional Rulkov chaotic neuron model is taken into account by using the qualitative analysis, the co-dimension 2 bifurcation, the center manifold theorem, and the normal form. The goal is intended to clarify analytically different dynamics and firing regimes of a single neuron in a two dimensional parameter space. Our research demonstrates the origin that there exist very rich nonlinear dynamics and complex biological firing regimes lies in different domains and their boundary curves in the two dimensional parameter plane. We present the parameter domains of fixed points, the saddle-node bifurcation, the supercritical/subcritical Neimark-Sacker bifurcation, stability conditions of non hyperbolic fixed points and quasiperiodic solutions. Based on these parameter domains, it is easy to know that the Rulkov chaotic neuron model can produce what kinds of firing regimes as well as their transition mechanisms. These results are very useful for building-up a large-scale neuron network with different biological functional roles and cognitive activities, especially in establishing some specific neuron network models of neurological diseases.

  4. Minimal attractors in digraph system models of neuronal networks

    NASA Astrophysics Data System (ADS)

    Just, Winfried; Ahn, Sungwoo; Terman, David

    2008-12-01

    We study a class of discrete dynamical systems models of neuronal networks. In these models, each neuron is represented by a finite number of states and there are rules for how a neuron transitions from one state to another. In particular, the rules determine when a neuron fires and how this affects the state of other neurons. In an earlier paper [D. Terman, S. Ahn, X. Wang, W. Just, Reducing neuronal networks to discrete dynamics, Physica D 237 (2008) 324-338], we demonstrate that a general class of excitatory-inhibitory networks can, in fact, be rigorously reduced to the discrete model. In the present paper, we analyze how the connectivity of the network influences the dynamics of the discrete model. For randomly connected networks, we find two major phase transitions. If the connection probability is above the second but below the first phase transition, then starting in a generic initial state, most but not all cells will fire at all times along the trajectory as soon as they reach the end of their refractory period. Above the first phase transition, this will be true for all cells in a typical initial state; thus most states will belong to a minimal attractor of oscillatory behavior (in a sense that is defined precisely in the paper). The exact positions of the phase transitions depend on intrinsic properties of the cells including the lengths of the cells’ refractory periods and the thresholds for firing. Existence of these phase transitions is both rigorously proved for sufficiently large networks and corroborated by numerical experiments on networks of moderate size.

  5. A Neuronal Network Model for Pitch Selectivity and Representation

    PubMed Central

    Huang, Chengcheng; Rinzel, John

    2016-01-01

    Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is developed for pitch frequency estimation using biophysically-based, high-resolution coincidence detector neurons. The neuronal units respond only to highly coincident input among convergent auditory nerve fibers across frequency channels. Their selectivity for only very fast rising slopes of convergent input enables these slope-detectors to distinguish the most prominent coincidences in multi-peaked input time courses. Pitch can then be estimated from the first-order interspike intervals of the slope-detectors. The regular firing pattern of the slope-detector neurons are similar for sounds sharing the same pitch despite the distinct timbres. The decoded pitch strengths also correlate well with the salience of pitch perception as reported by human listeners. Therefore, our model can serve as a neural representation for pitch. Our model performs successfully in estimating the pitch of missing fundamental complexes and reproducing the pitch variation with respect to the frequency shift of inharmonic complexes. It also accounts for the phase sensitivity of pitch perception in the cases of Schroeder phase, alternating phase and random phase relationships. Moreover, our model can also be applied to stochastic sound stimuli, iterated-ripple-noise, and account for their multiple pitch perceptions. PMID:27378900

  6. Rate of neuronal fallout in a transsynaptic cerebellar model.

    PubMed

    Triarhou, L C

    1998-10-01

    Quantitative analyses of transsynaptic granule cell death subsequent to the genetically determined degeneration of Purkinje cells in the cerebellum of pcd/pcd mutant mice show that granule neuron fallout follows a typical mathematical pattern of elemental decay. Biological and theoretical connotations are discussed in light of the empirical observations and a simulation model. PMID:9865853

  7. Modeling of Auditory Neuron Response Thresholds with Cochlear Implants.

    PubMed

    Venail, Frederic; Mura, Thibault; Akkari, Mohamed; Mathiolon, Caroline; Menjot de Champfleur, Sophie; Piron, Jean Pierre; Sicard, Marielle; Sterkers-Artieres, Françoise; Mondain, Michel; Uziel, Alain

    2015-01-01

    The quality of the prosthetic-neural interface is a critical point for cochlear implant efficiency. It depends not only on technical and anatomical factors such as electrode position into the cochlea (depth and scalar placement), electrode impedance, and distance between the electrode and the stimulated auditory neurons, but also on the number of functional auditory neurons. The efficiency of electrical stimulation can be assessed by the measurement of e-CAP in cochlear implant users. In the present study, we modeled the activation of auditory neurons in cochlear implant recipients (nucleus device). The electrical response, measured using auto-NRT (neural responses telemetry) algorithm, has been analyzed using multivariate regression with cubic splines in order to take into account the variations of insertion depth of electrodes amongst subjects as well as the other technical and anatomical factors listed above. NRT thresholds depend on the electrode squared impedance (β = -0.11 ± 0.02, P < 0.01), the scalar placement of the electrodes (β = -8.50 ± 1.97, P < 0.01), and the depth of insertion calculated as the characteristic frequency of auditory neurons (CNF). Distribution of NRT residues according to CNF could provide a proxy of auditory neurons functioning in implanted cochleas. PMID:26236725

  8. Silicon modeling of the Mihalaş-Niebur neuron.

    PubMed

    Folowosele, Fopefolu; Hamilton, Tara Julia; Etienne-Cummings, Ralph

    2011-12-01

    There are a number of spiking and bursting neuron models with varying levels of complexity, ranging from the simple integrate-and-fire model to the more complex Hodgkin-Huxley model. The simpler models tend to be easily implemented in silicon but yet not biologically plausible. Conversely, the more complex models tend to occupy a large area although they are more biologically plausible. In this paper, we present the 0.5 μm complementary metal-oxide-semiconductor (CMOS) implementation of the Mihalaş-Niebur neuron model--a generalized model of the leaky integrate-and-fire neuron with adaptive threshold--that is able to produce most of the known spiking and bursting patterns that have been observed in biology. Our implementation modifies the original proposed model, making it more amenable to CMOS implementation and more biologically plausible. All but one of the spiking properties--tonic spiking, class 1 spiking, phasic spiking, hyperpolarized spiking, rebound spiking, spike frequency adaptation, accommodation, threshold variability, integrator and input bistability--are demonstrated in this model. PMID:21990331

  9. Neuronal modelling of baroreflex response to orthostatic stress

    NASA Astrophysics Data System (ADS)

    Samin, Azfar

    The accelerations experienced in aerial combat can cause pilot loss of consciousness (GLOC) due to a critical reduction in cerebral blood circulation. The development of smart protective equipment requires understanding of how the brain processes blood pressure (BP) information in response to acceleration. We present a biologically plausible model of the Baroreflex to investigate the neural correlates of short-term BP control under acceleration or orthostatic stress. The neuronal network model, which employs an integrate-and-fire representation of a biological neuron, comprises the sensory, motor, and the central neural processing areas that form the Baroreflex. Our modelling strategy is to test hypotheses relating to the encoding mechanisms of multiple sensory inputs to the nucleus tractus solitarius (NTS), the site of central neural processing. The goal is to run simulations and reproduce model responses that are consistent with the variety of available experimental data. Model construction and connectivity are inspired by the available anatomical and neurophysiological evidence that points to a barotopic organization in the NTS, and the presence of frequency-dependent synaptic depression, which provides a mechanism for generating non-linear local responses in NTS neurons that result in quantifiable dynamic global baroreflex responses. The entire physiological range of BP and rate of change of BP variables is encoded in a palisade of NTS neurons in that the spike responses approximate Gaussian 'tuning' curves. An adapting weighted-average decoding scheme computes the motor responses and a compensatory signal regulates the heart rate (HR). Model simulations suggest that: (1) the NTS neurons can encode the hydrostatic pressure difference between two vertically separated sensory receptor regions at +Gz, and use changes in that difference for the regulation of HR; (2) even though NTS neurons do not fire with a cardiac rhythm seen in the afferents, pulse

  10. Stimulus Coding and Synchrony in Stochastic Neuron Models

    NASA Astrophysics Data System (ADS)

    Cieniak, Jakub

    A stochastic leaky integrate-and-fire neuron model was implemented in this study to simulate the spiking activity of the electrosensory "P-unit" receptor neurons of the weakly electric fish Apteronotus leptorhynchus. In the context of sensory coding, these cells have been previously shown to respond in experiment to natural random narrowband signals with either a linear or nonlinear coding scheme, depending on the intrinsic firing rate of the cell in the absence of external stimulation. It was hypothesised in this study that this duality is due to the relation of the stimulus to the neuron's excitation threshold. This hypothesis was validated with the model by lowering the threshold of the neuron or increasing its intrinsic noise, or randomness, either of which made the relation between firing rate and input strength more linear. Furthermore, synchronous P-unit firing to a common input also plays a role in decoding the stimulus at deeper levels of the neural pathways. Synchronisation and desynchronisation between multiple model responses for different types of natural communication signals were shown to agree with experimental observations. A novel result of resonance-induced synchrony enhancement of P-units to certain communication frequencies was also found.

  11. Parameter estimation of neuron models using in-vitro and in-vivo electrophysiological data

    PubMed Central

    Lynch, Eoin P.; Houghton, Conor J.

    2015-01-01

    Spiking neuron models can accurately predict the response of neurons to somatically injected currents if the model parameters are carefully tuned. Predicting the response of in-vivo neurons responding to natural stimuli presents a far more challenging modeling problem. In this study, an algorithm is presented for parameter estimation of spiking neuron models. The algorithm is a hybrid evolutionary algorithm which uses a spike train metric as a fitness function. We apply this to parameter discovery in modeling two experimental data sets with spiking neurons; in-vitro current injection responses from a regular spiking pyramidal neuron are modeled using spiking neurons and in-vivo extracellular auditory data is modeled using a two stage model consisting of a stimulus filter and spiking neuron model. PMID:25941485

  12. On the capabilities and computational costs of neuron models.

    PubMed

    Skocik, Michael J; Long, Lyle N

    2014-08-01

    We review the Hodgkin-Huxley, Izhikevich, and leaky integrate-and-fire neuron models in regular spiking modes solved with the forward Euler, fourth-order Runge-Kutta, and exponential Euler methods and determine the necessary time steps and corresponding computational costs required to make the solutions accurate. We conclude that the leaky integrate-and-fire needs the least number of computations, and that the Hodgkin-Huxley and Izhikevich models are comparable in computational cost. PMID:25050945

  13. Study on dynamic characteristics' change of hippocampal neuron reduced models caused by the Alzheimer's disease.

    PubMed

    Peng, Yueping; Wang, Jue; Zheng, Chongxun

    2016-01-01

    In the paper, based on the electrophysiological experimental data, the Hippocampal neuron reduced model under the pathology condition of Alzheimer's disease (AD) has been built by modifying parameters' values. The reduced neuron model's dynamic characteristics under effect of AD are comparatively studied. Under direct current stimulation, compared with the normal neuron model, the AD neuron model's dynamic characteristics have obviously been changed. The neuron model under the AD condition undergoes supercritical Andronov-Hopf bifurcation from the rest state to the continuous discharge state. It is different from the neuron model under the normal condition, which undergoes saddle-node bifurcation. So, the neuron model changes into a resonator with monostable state from an integrator with bistable state under AD's action. The research reveals the neuron model's dynamic characteristics' changing under effect of AD, and provides some theoretic basis for AD research by neurodynamics theory. PMID:26998957

  14. Neuronal and brain morphological changes in animal models of schizophrenia.

    PubMed

    Flores, Gonzalo; Morales-Medina, Julio César; Diaz, Alfonso

    2016-03-15

    Schizophrenia, a severe and debilitating disorder with a high social burden, affects 1% of the adult world population. Available therapies are unable to treat all the symptoms, and result in strong side effects. For this reason, numerous animal models have been generated to elucidate the pathophysiology of this disorder. All these models present neuronal remodeling and abnormalities in spine stability. It is well known that the complexity in dendritic arborization determines the number of receptive synaptic contacts. Also the loss of dendritic spines and arbor stability are strongly associated with schizophrenia. This review evaluates changes in spine density and dendritic arborization in animal models of schizophrenia. By understanding these changes, pharmacological treatments can be designed to target specific neural systems to attenuate neuronal remodeling and associated behavioral deficits. PMID:26738967

  15. The Neuroid: A novel and simplified neuron-model.

    PubMed

    Arguello, E; Silva, R; Castillo, C; Huerta, M

    2012-01-01

    In this paper we introduce a novel computational neuron-model, the Neuroid, which is based on three basic operations that are carried out by nerve cells to process the incoming information, such as comparison, and frequency pulse modulation-demodulation. The model was implemented using LabVIEW 10.0, in order to assign to each of these operations, an execution block (Virtual Instrument). The results of its implementation showed a very similar behavior to that exhibited by real neurons. Furthermore, due to its simplicity and low computational requirements, it is expected that the Neuroid can be used to create several software models of biological neural systems, either for research or teaching purposes. PMID:23366121

  16. The Volterra-Wiener approach in neuronal modeling.

    PubMed

    Mitsis, Georgios D

    2011-01-01

    Systems identification is being used increasingly in quantitative neurophysiology, including the auditory, visual and somatosensory systems. In this context, the Volterra-Wiener approach, which is an important branch of nonlinear systems identification, has met with considerable success in neuronal systems modeling, as these systems often exhibit complex nonlinear behavior. The Volterra-Wiener approach provides a comprehensive data-driven framework that does not place any a priori assumptions on the system structure. Therefore, it can approximate highly complex nonlinear mappings provided that experimental protocols are carefully designed in order to meet the requirements of the corresponding estimation procedure. In the present paper, we present a brief overview of Volterra-Wiener models and methodologies for their estimation as they relate to modeling neuronal systems. We also examine a specific example from a mechanoreceptor system. PMID:22255685

  17. Computational modeling of optogenetic neuronal excitation under complex illumination conditions using a Matlab-Neuron interface (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Yona, Guy; Weissler, Yonatan; Meitav, Nizan; Guzi, Eliran; Rifold, Dafna D.; Kahn, Itamar; Shoham, Shy

    2016-03-01

    Optogenetics has in recent years become a central tool in neuroscience research. Creating a realistic model of optogenetic neuronal excitation is of crucial importance for controlling the activation levels of various neuronal populations in different depths, predicting experimental results and designing the optical systems. However, current approaches to modeling light propagation through rodents' brain tissue suffer from major shortcomings and comprehensive modeling of local illumination levels together with other important factors governing excitation (i.e., cellular morphology, channel dynamics and expression), are still lacking. To address this challenge we introduce a new simulation tool for optogenetic neuronal excitation under complex and realistic illumination conditions that implements a detailed physical model for light scattering (in MATLAB) together with neuron morphology and channelrhodopsin-2 model (in NEURON). These two disparate simulation environments were interconnected using a newly developed generic interface termed 'NeuroLab'. Applying this method, we show that in a layer-V cortical neuron, the relative contribution of the apical dendrites to neuronal excitation is considerably greater than that of the soma or basal dendrites, when illuminated from the surface.

  18. Colored noise and memory effects on formal spiking neuron models

    NASA Astrophysics Data System (ADS)

    da Silva, L. A.; Vilela, R. D.

    2015-06-01

    Simplified neuronal models capture the essence of the electrical activity of a generic neuron, besides being more interesting from the computational point of view when compared to higher-dimensional models such as the Hodgkin-Huxley one. In this work, we propose a generalized resonate-and-fire model described by a generalized Langevin equation that takes into account memory effects and colored noise. We perform a comprehensive numerical analysis to study the dynamics and the point process statistics of the proposed model, highlighting interesting new features such as (i) nonmonotonic behavior (emergence of peak structures, enhanced by the choice of colored noise characteristic time scale) of the coefficient of variation (CV) as a function of memory characteristic time scale, (ii) colored noise-induced shift in the CV, and (iii) emergence and suppression of multimodality in the interspike interval (ISI) distribution due to memory-induced subthreshold oscillations. Moreover, in the noise-induced spike regime, we study how memory and colored noise affect the coherence resonance (CR) phenomenon. We found that for sufficiently long memory, not only is CR suppressed but also the minimum of the CV-versus-noise intensity curve that characterizes the presence of CR may be replaced by a maximum. The aforementioned features allow to interpret the interplay between memory and colored noise as an effective control mechanism to neuronal variability. Since both variability and nontrivial temporal patterns in the ISI distribution are ubiquitous in biological cells, we hope the present model can be useful in modeling real aspects of neurons.

  19. Modeling Neuronal Response to Simultaneous and Sequential Multi-Site Synaptic Stimulation

    NASA Astrophysics Data System (ADS)

    Johnston, David; Mekhail, Simon Peter; Go, Mary Ann; Daria, Vincent R.

    The flow of information in the brain theorizes that each neuron in a network receives synaptic inputs and sends off its processed signals to neighboring neurons. Here, we model these synaptic inputs to understand how each neuron processes these inputs and transmits neurotransmitters to neighboring neurons. We use the NEURON simulation package to stimulate a neuron at multiple synaptic locations along its dendritic tree. Accumulation of multiple synaptic inputs causes changes in the neuron's membrane potential leading to firing of an action potential. Our simulations show that simultaneous synaptic stimulation approaches firing of an action potential at lesser inputs compared to sequential stimulation at multiple sites distributed along several dendritic branches.

  20. Translating network models to parallel hardware in NEURON

    PubMed Central

    Hines, M.L.; Carnevale, N.T.

    2008-01-01

    The increasing complexity of network models poses a growing computational burden. At the same time, computational neuroscientists are finding it easier to access parallel hardware, such as multiprocessor personal computers, workstation clusters, and massively parallel supercomputers. The practical question is how to move a working network model from a single processor to parallel hardware. Here we show how to make this transition for models implemented with NEURON, in such a way that the final result will run and produce numerically identical results on either serial or parallel hardware. This allows users to develop and debug models on readily available local resources, then run their code without modification on a parallel supercomputer. PMID:17997162

  1. Optical computing based on neuronal models

    NASA Astrophysics Data System (ADS)

    Farhat, Nabil H.

    1987-10-01

    Ever since the fit between what neural net models can offer (collective, iterative, nonlinear, robust, and fault-tolerant approach to information processing) and the inherent capabilities of optics (parallelism and massive interconnectivity) was first pointed out and the first optical associative memory demonstrated in 1985, work and interest in neuromorphic optical signal processing has been growing steadily. For example, work in optical associative memories is currently being conducted at several academic institutions (e.g., California Institute of Technology, University of Colorado, University of California-San Diego, Stanford University, University of Rochester, and the author's own institution the University of Pennsylvania) and at several industrial and governmental laboratories (e.g., Hughes Research Laboratories - Malibu, the Naval Research Laboratory, and the Jet Propulsion Laboratory). In these efforts, in addition to the vector matrix multiplication with thresholding and feedback scheme utilized in early implementations, an arsenal of sophisticated optical tools such as holographic storage, phase conjugate optics, and wavefront modulation and mixing are being drawn on to realize associative memory functions.

  2. Stochastic resonance in neuron models: Endogenous stimulation revisited

    NASA Astrophysics Data System (ADS)

    Plesser, Hans E.; Geisel, Theo

    2001-03-01

    The paradigm of stochastic resonance (SR)-the idea that signal detection and transmission may benefit from noise-has met with great interest in both physics and the neurosciences. We investigate here the consequences of reducing the dynamics of a periodically driven neuron to a renewal process (stimulation with reset or endogenous stimulation). This greatly simplifies the mathematical analysis, but we show that stochastic resonance as reported earlier occurs in this model only as a consequence of the reduced dynamics.

  3. Analysis of Chaotic Resonance in Izhikevich Neuron Model.

    PubMed

    Nobukawa, Sou; Nishimura, Haruhiko; Yamanishi, Teruya; Liu, Jian-Qin

    2015-01-01

    In stochastic resonance (SR), the presence of noise helps a nonlinear system amplify a weak (sub-threshold) signal. Chaotic resonance (CR) is a phenomenon similar to SR but without stochastic noise, which has been observed in neural systems. However, no study to date has investigated and compared the characteristics and performance of the signal responses of a spiking neural system in some chaotic states in CR. In this paper, we focus on the Izhikevich neuron model, which can reproduce major spike patterns that have been experimentally observed. We examine and classify the chaotic characteristics of this model by using Lyapunov exponents with a saltation matrix and Poincaré section methods in order to address the measurement challenge posed by the state-dependent jump in the resetting process. We found the existence of two distinctive states, a chaotic state involving primarily turbulent movement and an intermittent chaotic state. In order to assess the signal responses of CR in these classified states, we introduced an extended Izhikevich neuron model by considering weak periodic signals, and defined the cycle histogram of neuron spikes as well as the corresponding mutual correlation and information. Through computer simulations, we confirmed that both chaotic states in CR can sensitively respond to weak signals. Moreover, we found that the intermittent chaotic state exhibited a prompter response than the chaotic state with primarily turbulent movement. PMID:26422140

  4. Analysis of Chaotic Resonance in Izhikevich Neuron Model

    PubMed Central

    Nobukawa, Sou; Nishimura, Haruhiko; Yamanishi, Teruya; Liu, Jian-Qin

    2015-01-01

    In stochastic resonance (SR), the presence of noise helps a nonlinear system amplify a weak (sub-threshold) signal. Chaotic resonance (CR) is a phenomenon similar to SR but without stochastic noise, which has been observed in neural systems. However, no study to date has investigated and compared the characteristics and performance of the signal responses of a spiking neural system in some chaotic states in CR. In this paper, we focus on the Izhikevich neuron model, which can reproduce major spike patterns that have been experimentally observed. We examine and classify the chaotic characteristics of this model by using Lyapunov exponents with a saltation matrix and Poincaré section methods in order to address the measurement challenge posed by the state-dependent jump in the resetting process. We found the existence of two distinctive states, a chaotic state involving primarily turbulent movement and an intermittent chaotic state. In order to assess the signal responses of CR in these classified states, we introduced an extended Izhikevich neuron model by considering weak periodic signals, and defined the cycle histogram of neuron spikes as well as the corresponding mutual correlation and information. Through computer simulations, we confirmed that both chaotic states in CR can sensitively respond to weak signals. Moreover, we found that the intermittent chaotic state exhibited a prompter response than the chaotic state with primarily turbulent movement. PMID:26422140

  5. Response characteristics of a low-dimensional model neuron.

    PubMed

    Cartling, B

    1996-11-15

    It is shown that a low-dimensional model neuron with a response time constant smaller than the membrane time constant closely reproduces the activity and excitability behavior of a detailed conductance-based model of Hodgkin-Huxley type. The fast response of the activity variable also makes it possible to reduce the model to a one-dimensional model, in particular for typical conditions. As an example, the reduction to a single-variable model from a multivariable conductance-based model of a neocortical pyramidal cell with somatic input is demonstrated. The conditions for avoiding a spurious damped oscillatory response to a constant input are derived, and it is shown that a limit-cycle response cannot occur. The capability of the low-dimensional model to approximate higher-dimensional models accurately makes it useful for describing complex dynamics of nets of interconnected neurons. The simplicity of the model facilitates analytic studies, elucidations of neurocomputational mechanisms, and applications to large-scale systems. PMID:8888611

  6. TAL Effector-Nucleotide Targeter (TALE-NT) 2.0: tools for TAL effector design and target prediction

    PubMed Central

    Doyle, Erin L.; Booher, Nicholas J.; Standage, Daniel S.; Voytas, Daniel F.; Brendel, Volker P.; VanDyk, John K.; Bogdanove, Adam J.

    2012-01-01

    Transcription activator-like (TAL) effectors are repeat-containing proteins used by plant pathogenic bacteria to manipulate host gene expression. Repeats are polymorphic and individually specify single nucleotides in the DNA target, with some degeneracy. A TAL effector-nucleotide binding code that links repeat type to specified nucleotide enables prediction of genomic binding sites for TAL effectors and customization of TAL effectors for use in DNA targeting, in particular as custom transcription factors for engineered gene regulation and as site-specific nucleases for genome editing. We have developed a suite of web-based tools called TAL Effector-Nucleotide Targeter 2.0 (TALE-NT 2.0; https://boglab.plp.iastate.edu/) that enables design of custom TAL effector repeat arrays for desired targets and prediction of TAL effector binding sites, ranked by likelihood, in a genome, promoterome or other sequence of interest. Search parameters can be set by the user to work with any TAL effector or TAL effector nuclease architecture. Applications range from designing highly specific DNA targeting tools and identifying potential off-target sites to predicting effector targets important in plant disease. PMID:22693217

  7. Statistics of a neuron model driven by asymmetric colored noise

    NASA Astrophysics Data System (ADS)

    Müller-Hansen, Finn; Droste, Felix; Lindner, Benjamin

    2015-02-01

    Irregular firing of neurons can be modeled as a stochastic process. Here we study the perfect integrate-and-fire neuron driven by dichotomous noise, a Markovian process that jumps between two states (i.e., possesses a non-Gaussian statistics) and exhibits nonvanishing temporal correlations (i.e., represents a colored noise). Specifically, we consider asymmetric dichotomous noise with two different transition rates. Using a first-passage-time formulation, we derive exact expressions for the probability density and the serial correlation coefficient of the interspike interval (time interval between two subsequent neural action potentials) and the power spectrum of the spike train. Furthermore, we extend the model by including additional Gaussian white noise, and we give approximations for the interspike interval (ISI) statistics in this case. Numerical simulations are used to validate the exact analytical results for pure dichotomous noise, and to test the approximations of the ISI statistics when Gaussian white noise is included. The results may help to understand how correlations and asymmetry of noise and signals in nerve cells shape neuronal firing statistics.

  8. Realistic modeling of neurons and networks: towards brain simulation

    PubMed Central

    D’Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

    Summary Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field. PMID:24139652

  9. Motor neurones in culture as a model to study ALS.

    PubMed

    Silani, V; Braga, M; Ciammola, A; Cardin, V; Scarlato, G

    2000-03-01

    Defining the basis of the selective cell vulnerability of motor neurones (MN) represents the key issue in amyotrophic lateral sclerosis (ALS), and tissue culture models are the ideal system for the identification of the MN specific features at the single cell level. Neurone-astrocyte metabolic interactions, which have a critical role in MN through glutamatergic toxicity, have been mostly defined in vitro. Ca++ metabolism, which appears to play a critical role in inducing MN loss in ALS, has been successfully studied using in vitro cell models. Furthermore, primary cultures demonstrated that apoptotic or necrotic death of neurones after injury depends upon the cell energetic status. Superoxide dismutase- (SOD-1) mutations were successfully expressed in cultured rodent MNs, providing a critical assay to sequence the molecular processes responsible for MN degeneration due to the identified genetic defect. The recent identification of genes that separate humans from apes further increases the value of the human in vitro models to better understand specific human cellular properties. Purified human MNs and astrocytes can today be obtained from the human embryonic spinal cord anterior horns. Interactions at the single cell level can be dissected using the cDNA amplification techniques. The effects of molecules affecting MN survival, neurite extension, and metabolism can easily be defined in vitro, gaining a critical mass of information of immediate clinical application in the treatment of patients affected by ALS. Understanding the properties of human MNs in vitro represents today a significant and critical tool that can easily be reached after extension of the available knowledge from non-primate to human research. Human MN culture studies can greatly contribute to identifying the primitive critical cellular events responsible for the MN degeneration observed in ALS and to gaining crucial information on new therapeutical agents. PMID:10795884

  10. Multiple dynamical resonances in a discrete neuronal model

    SciTech Connect

    Jiang Yu

    2005-05-01

    The conditions for the occurrence of different multiple resonances in an excitable neuron model are analyzed numerically. It is shown that the excitable system may display both stochastic and coherence resonance, in response to periodic stimuli in the presence of different intensities of additive and parametric noises. It is found that double coherence resonances may take place in the low-amplitude oscillation regimes, and coherence resonance may persists even in the weak oscillatory regimes for control parameters slightly larger than the Hopf bifurcation point, where the system is in the incipient stage of large-amplitude excitation regime.

  11. A human pluripotent carcinoma stem cell-based model for in vitro developmental neurotoxicity testing: effects of methylmercury, lead and aluminum evaluated by gene expression studies.

    PubMed

    Laurenza, Incoronata; Pallocca, Giorgia; Mennecozzi, Milena; Scelfo, Bibiana; Pamies, David; Bal-Price, Anna

    2013-11-01

    The major advantage of the neuronal cell culture models derived from human stem cells is their ability to replicate the crucial stages of neurodevelopment such as the commitment of human stem cells to the neuronal lineage and their subsequent stages of differentiation into neuronal and glial-like cell. In these studies we used mixed neuronal/glial culture derived from the NTERA-2 (NT-2) cell line, which has been established from human pluripotent testicular embryonal carcinoma cells. After characterization of the different stages of cell differentiation into neuronal- and glial-like phenotype toxicity studies were performed to evaluate whether this model would be suitable for developmental neurotoxicity studies. The cells were exposed during the differentiation process to non-cytotoxic concentrations of methylmercury chloride, lead chloride and aluminum nitrate for two weeks. The toxicity was then evaluated by measuring the mRNA levels of cell specific markers (neuronal and glial). The results obtained suggest that lead chloride and aluminum nitrate at low concentrations were toxic primarily to astrocytes and at the higher concentrations it also induced neurotoxicity. In contrast, MetHgCl was toxic for both cell types, neuronal and glial, as mRNA specific for astrocytes and neuronal markers were affected. The results obtained suggest that a neuronal mixed culture derived from human NT2 precursor cells is a suitable model for developmental neurotoxicity studies and gene expression could be used as a sensitive endpoint for initial screening of potential neurotoxic compounds. PMID:23501475

  12. Minimal Conductance-Based Model of Auditory Coincidence Detector Neurons

    PubMed Central

    Ashida, Go; Funabiki, Kazuo; Kretzberg, Jutta

    2015-01-01

    Sound localization is a fundamental sensory function of a wide variety of animals. The interaural time difference (ITD), an important cue for sound localization, is computed in the auditory brainstem. In our previous modeling study, we introduced a two-compartment Hodgkin-Huxley type model to investigate how cellular and synaptic specializations may contribute to precise ITD computation of the barn owl's auditory coincidence detector neuron. Although our model successfully reproduced fundamental physiological properties observed in vivo, it was unsuitable for mathematical analyses and large scale simulations because of a number of nonlinear variables. In the present study, we reduce our former model into three types of conductance-based integrate-and-fire (IF) models. We test their electrophysiological properties using data from published in vivo and in vitro studies. Their robustness to parameter changes and computational efficiencies are also examined. Our numerical results suggest that the single-compartment active IF model is superior to other reduced models in terms of physiological reproducibility and computational performance. This model will allow future theoretical studies that use more rigorous mathematical analysis and network simulations. PMID:25844803

  13. Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models

    NASA Astrophysics Data System (ADS)

    Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Li, Huiyan; Loparo, Kenneth A.; Fietkiewicz, Chris

    2015-11-01

    Computational models play a significant role in exploring novel theories to complement the findings of physiological experiments. Various computational models have been developed to reveal the mechanisms underlying brain functions. Particularly, in the development of therapies to modulate behavioral and pathological abnormalities, computational models provide the basic foundations to exhibit transitions between physiological and pathological conditions. Considering the significant roles of the intrinsic properties of the globus pallidus and the coupling connections between neurons in determining the firing patterns and the dynamical activities of the basal ganglia neuronal network, we propose a hypothesis that pathological behaviors under the Parkinsonian state may originate from combined effects of intrinsic properties of globus pallidus neurons and synaptic conductances in the whole neuronal network. In order to establish a computational efficient network model, hybrid Izhikevich neuron model is used due to its capacity of capturing the dynamical characteristics of the biological neuronal activities. Detailed analysis of the individual Izhikevich neuron model can assist in understanding the roles of model parameters, which then facilitates the establishment of the basal ganglia-thalamic network model, and contributes to a further exploration of the underlying mechanisms of the Parkinsonian state. Simulation results show that the hybrid Izhikevich neuron model is capable of capturing many of the dynamical properties of the basal ganglia-thalamic neuronal network, such as variations of the firing rates and emergence of synchronous oscillations under the Parkinsonian condition, despite the simplicity of the two-dimensional neuronal model. It may suggest that the computational efficient hybrid Izhikevich neuron model can be used to explore basal ganglia normal and abnormal functions. Especially it provides an efficient way of emulating the large-scale neuron network

  14. Extending the mirror neuron system model, I. Audible actions and invisible grasps.

    PubMed

    Bonaiuto, James; Rosta, Edina; Arbib, Michael

    2007-01-01

    The paper introduces mirror neuron system II (MNS2), a new version of the MNS model (Oztop and Arbib in Biol Cybern 87 (2):116-140, 2002) of action recognition learning by mirror neurons of the macaque brain. The new model uses a recurrent architecture that is biologically more plausible than that of the original model. Moreover, MNS2 extends the capacity of the model to address data on audio-visual mirror neurons and on the response of mirror neurons when the target object was recently visible but is currently hidden. PMID:17028884

  15. Mapping Generative Models onto a Network of Digital Spiking Neurons.

    PubMed

    Pedroni, Bruno U; Das, Srinjoy; Arthur, John V; Merolla, Paul A; Jackson, Bryan L; Modha, Dharmendra S; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

    2016-08-01

    Stochastic neural networks such as Restricted Boltzmann Machines (RBMs) have been successfully used in applications ranging from speech recognition to image classification, and are particularly interesting because of their potential for generative tasks. Inference and learning in these algorithms use a Markov Chain Monte Carlo procedure called Gibbs sampling, where a logistic function forms the kernel of this sampler. On the other side of the spectrum, neuromorphic systems have shown great promise for low-power and parallelized cognitive computing, but lack well-suited applications and automation procedures. In this work, we propose a systematic method for bridging the RBM algorithm and digital neuromorphic systems, with a generative pattern completion task as proof of concept. For this, we first propose a method of producing the Gibbs sampler using bio-inspired digital noisy integrate-and-fire neurons. Next, we describe the process of mapping generative RBMs trained offline onto the IBM TrueNorth neurosynaptic processor-a low-power digital neuromorphic VLSI substrate. Mapping these algorithms onto neuromorphic hardware presents unique challenges in network connectivity and weight and bias quantization, which, in turn, require architectural and design strategies for the physical realization. Generative performance is analyzed to validate the neuromorphic requirements and to best select the neuron parameters for the model. Lastly, we describe a design automation procedure which achieves optimal resource usage, accounting for the novel hardware adaptations. This work represents the first implementation of generative RBM inference on a neuromorphic VLSI substrate. PMID:27214915

  16. Neurons compute internal models of the physical laws of motion.

    PubMed

    Angelaki, Dora E; Shaikh, Aasef G; Green, Andrea M; Dickman, J David

    2004-07-29

    A critical step in self-motion perception and spatial awareness is the integration of motion cues from multiple sensory organs that individually do not provide an accurate representation of the physical world. One of the best-studied sensory ambiguities is found in visual processing, and arises because of the inherent uncertainty in detecting the motion direction of an untextured contour moving within a small aperture. A similar sensory ambiguity arises in identifying the actual motion associated with linear accelerations sensed by the otolith organs in the inner ear. These internal linear accelerometers respond identically during translational motion (for example, running forward) and gravitational accelerations experienced as we reorient the head relative to gravity (that is, head tilt). Using new stimulus combinations, we identify here cerebellar and brainstem motion-sensitive neurons that compute a solution to the inertial motion detection problem. We show that the firing rates of these populations of neurons reflect the computations necessary to construct an internal model representation of the physical equations of motion. PMID:15282606

  17. Parametric Anatomical Modeling: a method for modeling the anatomical layout of neurons and their projections

    PubMed Central

    Pyka, Martin; Klatt, Sebastian; Cheng, Sen

    2014-01-01

    Computational models of neural networks can be based on a variety of different parameters. These parameters include, for example, the 3d shape of neuron layers, the neurons' spatial projection patterns, spiking dynamics and neurotransmitter systems. While many well-developed approaches are available to model, for example, the spiking dynamics, there is a lack of approaches for modeling the anatomical layout of neurons and their projections. We present a new method, called Parametric Anatomical Modeling (PAM), to fill this gap. PAM can be used to derive network connectivities and conduction delays from anatomical data, such as the position and shape of the neuronal layers and the dendritic and axonal projection patterns. Within the PAM framework, several mapping techniques between layers can account for a large variety of connection properties between pre- and post-synaptic neuron layers. PAM is implemented as a Python tool and integrated in the 3d modeling software Blender. We demonstrate on a 3d model of the hippocampal formation how PAM can help reveal complex properties of the synaptic connectivity and conduction delays, properties that might be relevant to uncover the function of the hippocampus. Based on these analyses, two experimentally testable predictions arose: (i) the number of neurons and the spread of connections is heterogeneously distributed across the main anatomical axes, (ii) the distribution of connection lengths in CA3-CA1 differ qualitatively from those between DG-CA3 and CA3-CA3. Models created by PAM can also serve as an educational tool to visualize the 3d connectivity of brain regions. The low-dimensional, but yet biologically plausible, parameter space renders PAM suitable to analyse allometric and evolutionary factors in networks and to model the complexity of real networks with comparatively little effort. PMID:25309338

  18. Parametric Anatomical Modeling: a method for modeling the anatomical layout of neurons and their projections.

    PubMed

    Pyka, Martin; Klatt, Sebastian; Cheng, Sen

    2014-01-01

    Computational models of neural networks can be based on a variety of different parameters. These parameters include, for example, the 3d shape of neuron layers, the neurons' spatial projection patterns, spiking dynamics and neurotransmitter systems. While many well-developed approaches are available to model, for example, the spiking dynamics, there is a lack of approaches for modeling the anatomical layout of neurons and their projections. We present a new method, called Parametric Anatomical Modeling (PAM), to fill this gap. PAM can be used to derive network connectivities and conduction delays from anatomical data, such as the position and shape of the neuronal layers and the dendritic and axonal projection patterns. Within the PAM framework, several mapping techniques between layers can account for a large variety of connection properties between pre- and post-synaptic neuron layers. PAM is implemented as a Python tool and integrated in the 3d modeling software Blender. We demonstrate on a 3d model of the hippocampal formation how PAM can help reveal complex properties of the synaptic connectivity and conduction delays, properties that might be relevant to uncover the function of the hippocampus. Based on these analyses, two experimentally testable predictions arose: (i) the number of neurons and the spread of connections is heterogeneously distributed across the main anatomical axes, (ii) the distribution of connection lengths in CA3-CA1 differ qualitatively from those between DG-CA3 and CA3-CA3. Models created by PAM can also serve as an educational tool to visualize the 3d connectivity of brain regions. The low-dimensional, but yet biologically plausible, parameter space renders PAM suitable to analyse allometric and evolutionary factors in networks and to model the complexity of real networks with comparatively little effort. PMID:25309338

  19. Neurons derived from transplanted neural stem cells restore disrupted neuronal circuitry in a mouse model of spinal cord injury

    PubMed Central

    Abematsu, Masahiko; Tsujimura, Keita; Yamano, Mariko; Saito, Michiko; Kohno, Kenji; Kohyama, Jun; Namihira, Masakazu; Komiya, Setsuro; Nakashima, Kinichi

    2010-01-01

    The body’s capacity to restore damaged neural networks in the injured CNS is severely limited. Although various treatment regimens can partially alleviate spinal cord injury (SCI), the mechanisms responsible for symptomatic improvement remain elusive. Here, using a mouse model of SCI, we have shown that transplantation of neural stem cells (NSCs) together with administration of valproic acid (VPA), a known antiepileptic and histone deacetylase inhibitor, dramatically enhanced the restoration of hind limb function. VPA treatment promoted the differentiation of transplanted NSCs into neurons rather than glial cells. Transsynaptic anterograde corticospinal tract tracing revealed that transplant-derived neurons reconstructed broken neuronal circuits, and electron microscopic analysis revealed that the transplant-derived neurons both received and sent synaptic connections to endogenous neurons. Ablation of the transplanted cells abolished the recovery of hind limb motor function, confirming that NSC transplantation directly contributed to restored motor function. These findings raise the possibility that epigenetic status in transplanted NSCs can be manipulated to provide effective treatment for SCI. PMID:20714104

  20. A Caenorhabditis elegans model for epithelial–neuronal transdifferentiation

    PubMed Central

    Jarriault, Sophie; Schwab, Yannick; Greenwald, Iva

    2008-01-01

    Understanding transdifferentiation—the conversion of one differentiated cell type into another—is important from both basic science and clinical perspectives. In Caenorhabditis elegans, an epithelial cell named Y is initially part of the rectum but later appears to withdraw, migrate, and then become a motor neuron named PDA. Here, we show that this represents a bona fide transdifferentiation event: Y has epithelial hallmarks without detectable neural characteristics, and PDA has no residual epithelial characteristics. Using available mutants and laser microsurgery, we found that transdifferentiation does not depend on fusion with a neighboring cell or require migration of Y away from the rectum, that other rectal epithelial cells are not competent to transdifferentiate, and that transdifferentiation requires the EGL-5 and SEM-4 transcription factors and LIN-12/Notch signaling. Our results establish Y-to-PDA transdifferentiation as a genetically tractable model for deciphering the mechanisms underlying cellular plasticity in vivo. PMID:18308937

  1. Dynamic characteristics of a simple bursting neuron model

    NASA Astrophysics Data System (ADS)

    Nakajima, Koji; Sato, Shigeo; Hayakawa, Yoshihiro

    We present a simple neuron model that shows a rich property in spite of the simple structure derived from the simplification of the Hindmarsh-Rose, the Morris-Lecar, and the Hodgkin-Huxley models. The model is a typical example whose characteristics can be discussed through the concept of potential with active areas. A potential function is able to provide a global landscape for dynamics of a model, and the dynamics is explained in connection with the disposition of the active areas on the potential, and hence we are able to discuss the global dynamic behaviors and the common properties among these realistic models. The obtained outputs are broadly classified as simple oscillations, spiking, bursting, and chaotic oscillations. The bursting outputs are classified as with spike undershoot and without spike undershoot, and the bursts without spike undershoot are classified as with tapered and without tapered. We show the parameter dependence of these outputs and discuss the connection between these outputs and the potential with active areas.

  2. A model based rule for selecting spiking thresholds in neuron models.

    PubMed

    Mikkelsen, Frederik Riis

    2016-06-01

    Determining excitability thresholds in neuronal models is of high interest due to its applicability in separating spiking from non-spiking phases of neuronal membrane potential processes. However, excitability thresholds are known to depend on various auxiliary variables, including any conductance or gating variables. Such dependences pose as a double-edged sword; they are natural consequences of the complexity of the model, but proves difficult to apply in practice, since gating variables are rarely measured. In this paper a technique for finding excitability thresholds, based on the local behaviour of the flow in dynamical systems, is presented. The technique incorporates the dynamics of the auxiliary variables, yet only produces thresholds for the membrane potential. The method is applied to several classical neuron models and the threshold's dependence upon external parameters is studied, along with a general evaluation of the technique. PMID:27106187

  3. A Computational Model for the Loss of Neuronal Organization in Microcolumns

    PubMed Central

    Henderson, Maxwell; Urbanc, Brigita; Cruz, Luis

    2014-01-01

    A population of neurons in the cerebral cortex of humans and other mammals organize themselves into vertical microcolumns perpendicular to the pial surface. Anatomical changes to these microcolumns have been correlated with neurological diseases and normal aging; in particular, in area 46 of the rhesus monkey brain, the strength of microcolumns was shown to decrease with age. These changes can be caused by alterations in the spatial distribution of the neurons in microcolumns and/or neuronal loss. Using a three-dimensional computational model of neuronal arrangements derived from thin tissue sections and validated in brain tissue from rhesus monkeys, we show that neuronal loss is inconsistent with the findings in aged individuals. In contrast, a model of simple random neuronal displacements, constrained in magnitude by restorative harmonic forces, is consistent with observed changes and provides mechanistic insights into the age-induced loss of microcolumnar structure. Connection of the model to normal aging and disease are discussed. PMID:24853752

  4. Simple Cortical and Thalamic Neuron Models for Digital Arithmetic Circuit Implementation

    PubMed Central

    Nanami, Takuya; Kohno, Takashi

    2016-01-01

    Trade-off between reproducibility of neuronal activities and computational efficiency is one of crucial subjects in computational neuroscience and neuromorphic engineering. A wide variety of neuronal models have been studied from different viewpoints. The digital spiking silicon neuron (DSSN) model is a qualitative model that focuses on efficient implementation by digital arithmetic circuits. We expanded the DSSN model and found appropriate parameter sets with which it reproduces the dynamical behaviors of the ionic-conductance models of four classes of cortical and thalamic neurons. We first developed a four-variable model by reducing the number of variables in the ionic-conductance models and elucidated its mathematical structures using bifurcation analysis. Then, expanded DSSN models were constructed that reproduce these mathematical structures and capture the characteristic behavior of each neuron class. We confirmed that statistics of the neuronal spike sequences are similar in the DSSN and the ionic-conductance models. Computational cost of the DSSN model is larger than that of the recent sophisticated Integrate-and-Fire-based models, but smaller than the ionic-conductance models. This model is intended to provide another meeting point for above trade-off that satisfies the demand for large-scale neuronal network simulation with closer-to-biology models. PMID:27242397

  5. Phase Sensitivity and Entrainment in a Modeled Bursting Neuron

    PubMed Central

    Demir, S. S.; Butera, R. J.; DeFranceschi, A. A.; Clark, J. W.; Byrne, J. H.

    1997-01-01

    A model of neuron R15 in Aplysia was used to study the mechanisms determining the phase-response curve (PRC) of the cell in response to both extrinsic current pulses and modeled synaptic input and to compare entrainment predictions from PRCs with those from actual simulations. Over the range of stimulus parameters studied, the PRCs of the model exhibited minimal dependence upon stimulus amplitude, and a strong dependence upon stimulus duration. State-space analysis of the effect of transient current pulses provided several important insights into the relationship between the PRC and the underlying dynamics of the model, such as a correlation between the prestimulus concentration of Ca2+ and the poststimulus phase of the oscillation. The system nullclines were also found to provide well-defined limits upon the perturbatory extent of a hyperpolarizing input. These results demonstrated that experimentally applied current pulses are sufficient to determine the shape of the PRC in response to a synaptic input, provided that the duration of the current pulse is of a duration similar to that of the evoked synaptic current. Furthermore, we found that predictions of phase-locked 1:m entrainment from PRCs were valid, even when the duration of the periodically applied pulses were a significant portion of the control limit cycle. ImagesFIGURE 5FIGURE 7FIGURE 8 PMID:9017188

  6. Continuum modeling of neuronal cell under blast loading

    PubMed Central

    Jérusalem, Antoine; Dao, Ming

    2012-01-01

    Traumatic brain injuries have recently been put under the spotlight as one of the most important causes of accidental brain dysfunctions. Significant experimental and modeling efforts are thus ongoing to study the associated biological, mechanical and physical mechanisms. In the field of cell mechanics, progresses are also being made at the experimental and modeling levels to better characterize many of the cell functions such as differentiation, growth, migration and death, among others. The work presented here aims at bridging both efforts by proposing a continuum model of neuronal cell submitted to blast loading. In this approach, cytoplasm, nucleus and membrane (plus cortex) are differentiated in a representative cell geometry, and different material constitutive models are adequately chosen for each one. The material parameters are calibrated against published experimental work of cell nanoindentation at multiple rates. The final cell model is ultimately subjected to blast loading within a complete fluid-structure interaction computational framework. The results are compared to the nanoindentation simulation and the specific effects of the blast wave on the pressure and shear levels at the interfaces are identified. As a conclusion, the presented model successfully captures some of the intrinsic intracellular phenomena occurring during its deformation under blast loading and potentially leading to cell damage. It suggests more particularly the localization of damage at the nucleus membrane similarly to what has already been observed at the overall cell membrane. This degree of damage is additionally predicted to be worsened by a longer blast positive phase duration. As a conclusion, the proposed model ultimately provides a new three dimensional computational tool to evaluate intracellular damage during blast loading. PMID:22562014

  7. Continuum modeling of a neuronal cell under blast loading.

    PubMed

    Jérusalem, Antoine; Dao, Ming

    2012-09-01

    Traumatic brain injuries have recently been put under the spotlight as one of the most important causes of accidental brain dysfunctions. Significant experimental and modeling efforts are thus underway to study the associated biological, mechanical and physical mechanisms. In the field of cell mechanics, progress is also being made at the experimental and modeling levels to better characterize many of the cell functions, including differentiation, growth, migration and death. The work presented here aims to bridge both efforts by proposing a continuum model of a neuronal cell submitted to blast loading. In this approach, the cytoplasm, nucleus and membrane (plus cortex) are differentiated in a representative cell geometry, and different suitable material constitutive models are chosen for each one. The material parameters are calibrated against published experimental work on cell nanoindentation at multiple rates. The final cell model is ultimately subjected to blast loading within a complete computational framework of fluid-structure interaction. The results are compared to the nanoindentation simulation, and the specific effects of the blast wave on the pressure and shear levels at the interfaces are identified. As a conclusion, the presented model successfully captures some of the intrinsic intracellular phenomena occurring during the cellular deformation under blast loading that potentially lead to cell damage. It suggests, more particularly, that the localization of damage at the nucleus membrane is similar to what has already been observed at the overall cell membrane. This degree of damage is additionally predicted to be worsened by a longer blast positive phase duration. In conclusion, the proposed model ultimately provides a new three-dimensional computational tool to evaluate intracellular damage during blast loading. PMID:22562014

  8. Block-Based Neural Networks with Pulsed Neuron Model

    NASA Astrophysics Data System (ADS)

    Iguchi, Syota; Koakutsu, Seiichi; Okamoto, Takashi; Hirata, Hironori

    In recent years, the study of hardware implementation of Neural Networks (NN) has been getting more important. In particular, Block-Based Neural Networks (BBNN) which are one of NN have been attracted attention. However, the conventional BBNN are analogue NN (ANN). The digital hardware implementation of ANN is very difficult, because the input and output signals are represented as analogue values. Pulsed Neural Networks (PNN) which adopt a pulsed neuron (PN) model instead of the AN model have been proposed in order to solve this problem. The input and output signals of PNN are represented as a series of pulses, and thus the digital hardware implementation of PNN becomes easy. In this paper, we propose Block-Based Pulsed Neural Networks (BBPNN) introducing the PN model into BBNN in order to faciliate the implementation of NN on digital hardware. We use particle swarm optimization (PSO) for optimization of weights of BBPNN, because PSO can produce a globally optimum solution of nonlinear continuous optimization problems in practicable calculation time by high accuracy. To evaluate the proposed BBPNN, we apply them to XOR problem and autonomous mobile robot control problems. Computational experiments indicate that the proposed BBPNN and the conventional BBNN can produce about the same results.

  9. Efficient estimation of detailed single-neuron models.

    PubMed

    Huys, Quentin J M; Ahrens, Misha B; Paninski, Liam

    2006-08-01

    Biophysically accurate multicompartmental models of individual neurons have significantly advanced our understanding of the input-output function of single cells. These models depend on a large number of parameters that are difficult to estimate. In practice, they are often hand-tuned to match measured physiological behaviors, thus raising questions of identifiability and interpretability. We propose a statistical approach to the automatic estimation of various biologically relevant parameters, including 1) the distribution of channel densities, 2) the spatiotemporal pattern of synaptic input, and 3) axial resistances across extended dendrites. Recent experimental advances, notably in voltage-sensitive imaging, motivate us to assume access to: i) the spatiotemporal voltage signal in the dendrite and ii) an approximate description of the channel kinetics of interest. We show here that, given i and ii, parameters 1-3 can be inferred simultaneously by nonnegative linear regression; that this optimization problem possesses a unique solution and is guaranteed to converge despite the large number of parameters and their complex nonlinear interaction; and that standard optimization algorithms efficiently reach this optimum with modest computational and data requirements. We demonstrate that the method leads to accurate estimations on a wide variety of challenging model data sets that include up to about 10(4) parameters (roughly two orders of magnitude more than previously feasible) and describe how the method gives insights into the functional interaction of groups of channels. PMID:16624998

  10. Basic neuron model electrical equivalent circuit: an undergraduate laboratory exercise.

    PubMed

    Dabrowski, Katie M; Castaño, Diego J; Tartar, Jaime L

    2013-01-01

    We developed a hands-on laboratory exercise for undergraduate students in which they can build and manipulate a neuron equivalent circuit. This exercise uses electrical circuit components that resemble neuron components and are easy to construct. We describe the methods for creating the equivalent circuit and how to observe different neuron properties through altering the structure of the equivalent circuit. We explain how this hands-on laboratory activity allows for the better understanding of this fundamental neuroscience concept. At the conclusion of this laboratory exercise, undergraduate students will be able to apply the principles of Ohm's law, cable theory with regards to neurons, and understand the functions of resistance and capacitance in a neuron. PMID:24319391

  11. Human in vitro reporter model of neuronal development and early differentiation processes

    PubMed Central

    Couillard-Despres, Sebastien; Quehl, Eike; Altendorfer, Katrin; Karl, Claudia; Ploetz, Sonja; Bogdahn, Ulrich; Winkler, Juergen; Aigner, Ludwig

    2008-01-01

    Background During developmental and adult neurogenesis, doublecortin is an early neuronal marker expressed when neural stem cells assume a neuronal cell fate. To understand mechanisms involved in early processes of neuronal fate decision, we investigated cell lines for their capacity to induce expression of doublecortin upon neuronal differentiation and develop in vitro reporter models using doublecortin promoter sequences. Results Among various cell lines investigated, the human teratocarcinoma cell line NTERA-2 was found to fulfill our criteria. Following induction of differentiation using retinoic acid treatment, we observed a 16-fold increase in doublecortin mRNA expression, as well as strong induction of doublecortin polypeptide expression. The acquisition of a neuronal precursor phenotype was also substantiated by the establishment of a multipolar neuronal morphology and expression of additional neuronal markers, such as Map2, βIII-tubulin and neuron-specific enolase. Moreover, stable transfection in NTERA-2 cells of reporter constructs encoding fluorescent or luminescent genes under the control of the doublecortin promoter allowed us to directly detect induction of neuronal differentiation in cell culture, such as following retinoic acid treatment or mouse Ngn2 transient overexpression. Conclusion Induction of doublecortin expression in differentiating NTERA-2 cells suggests that these cells accurately recapitulate some of the very early events of neuronal determination. Hence, the use of reporter genes under the control of the doublecortin promoter in NTERA-2 cells will help us to investigate factors involved early in the course of neuronal differentiation processes. Moreover the ease to detect the induction of a neuronal program in this model will permit to perform high throughput screening for compounds acting on the early neuronal differentiation mechanisms. PMID:18312642

  12. Genomic and Phenotypic Alterations of the Neuronal-Like Cells Derived from Human Embryonal Carcinoma Stem Cells (NT2) Caused by Exposure to Organophosphorus Compounds Paraoxon and Mipafox

    PubMed Central

    Pamies, David; Sogorb, Miguel A.; Fabbri, Marco; Gribaldo, Laura; Collotta, Angelo; Scelfo, Bibiana; Vilanova, Eugenio; Harris, Georgina; Bal-Price, Anna

    2014-01-01

    Historically, only few chemicals have been identified as neurodevelopmental toxicants, however, concern remains, and has recently increased, based upon the association between chemical exposures and increased developmental disorders. Diminution in motor speed and latency has been reported in preschool children from agricultural communities. Organophosphorus compounds (OPs) are pesticides due to their acute insecticidal effects mediated by the inhibition of acetylcholinesterase, although other esterases as neuropathy target esterase (NTE) can also be inhibited. Other neurological and neurodevelopmental toxic effects with unknown targets have been reported after chronic exposure to OPs in vivo. We studied the initial stages of retinoic acid acid-triggered differentiation of pluripotent cells towards neural progenitors derived from human embryonal carcinoma stem cells to determine if neuropathic OP, mipafox, and non-neuropathic OP, paraoxon, are able to alter differentiation of neural precursor cells in vitro. Exposure to 1 μM paraoxon (non-cytotoxic concentrations) altered the expression of different genes involved in signaling pathways related to chromatin assembly and nucleosome integrity. Conversely, exposure to 5 μM mipafox, a known inhibitor of NTE activity, showed no significant changes on gene expression. We conclude that 1 μM paraoxon could affect the initial stage of in vitro neurodifferentiation possibly due to a teratogenic effect, while the absence of transcriptional alterations by mipafox exposure did not allow us to conclude a possible effect on neurodifferentiation pathways at the tested concentration. PMID:24413757

  13. Characterization of Kiss1 neurons using transgenic mouse models

    PubMed Central

    Cravo, Roberta M.; Margatho, Lisandra O.; Osborne-Lawrence, Sherri; Donato, José; Atkin, Stan; Bookout, Angie L.; Rovinsky, Sherry; Frazão, Renata; Lee, Charlotte E.; Gautron, Laurent; Zigman, Jeffrey M.; Elias, Carol F.

    2010-01-01

    Humans and mice with loss-of-function mutations of the genes encoding kisspeptins (Kiss1) or kisspeptin receptors (Kiss1r) are infertile due to hypogonadotropic hypogonadism. Within the hypothalamus, Kiss1 mRNA is expressed in the anteroventral periventricular nucleus (AVPV) and the arcuate nucleus (Arc). In order to better study the different populations of kisspeptin cells we generated Kiss1-Cre transgenic mice. We obtained one line with Cre activity specifically within Kiss1 neurons (line J2-4), as assessed by generating mice with Cre-dependent expression of green fluorescent protein or β-galactosidase. Also, we demonstrated Kiss1 expression in the cerebral cortex and confirmed previous data showing Kiss1 mRNA in the medial nucleus of amygdala and anterodorsal preoptic nucleus. Kiss1 neurons were more concentrated towards the caudal levels of the Arc and higher leptin-responsivity was observed in the most caudal population of Arc Kiss1 neurons. No evidence for direct action of leptin in AVPV Kiss1 neurons was observed. Melanocortin fibers innervated subsets of Kiss1 neurons of the preoptic area and Arc, and both populations expressed MC4R. Specifically in the preoptic area, 18–28% of Kiss1 neurons expressed MC4R. In the Arc, 90% of Kiss1 neurons were glutamatergic, 50% of which also were GABAergic. In the AVPV, 20% of Kiss1 neurons were glutamatergic whereas 75% were GABAergic. The differences observed between the Kiss1 neurons in the preoptic area and the Arc likely represent neuronal evidence for their differential roles in metabolism and reproduction. PMID:21093546

  14. Use of human induced pluripotent stem cell-derived neurons as a model for Cerebral Toxoplasmosis.

    PubMed

    Tanaka, Naomi; Ashour, Danah; Dratz, Edward; Halonen, Sandra

    2016-01-01

    Toxoplasma gondii is a ubiquitous protozoan parasite with approximately one-third of the worlds' population chronically infected. In chronically infected individuals, the parasite resides primarily in cysts within neurons in the central nervous system. The chronic infection in immunocompetent individuals has been considered to be asymptomatic but increasing evidence indicates the chronic infection can lead to neuropsychiatric disorders such as Schizophrenia, prenatal depression and suicidal thoughts. A better understanding of the mechanism(s) by which the parasite exerts effects on human behavior is limited due to lack of suitable human neuronal models. In this paper, we report the use of human neurons derived from normal cord blood CD34+ cells generated via genetic reprogramming, as an in vitro model for the study T. gondii in neurons. This culture method resulted in a relatively pure monolayer of induced human neuronal-like cells that stained positive for neuronal markers, MAP2, NFL, NFH and NeuN. These induced human neuronal-like cells (iHNs) were efficiently infected by the Prugniad strain of the parasite and supported replication of the tachyzoite stage and development of the cyst stage. Infected iHNs could be maintained through 5 days of infection, allowing for formation of large cysts. This induced human neuronal model represents a novel culture method to study both tachyzoite and bradyzoite stages of T. gondii in human neurons. PMID:27083472

  15. Hypoxanthine deregulates genes involved in early neuronal development. Implications in Lesch-Nyhan disease pathogenesis.

    PubMed

    Torres, R J; Puig, J G

    2015-11-01

    Neurological manifestations in Lesch-Nyhan disease (LND) are attributed to the effect of hypoxanthine-guanine phosphoribosyltransferase (HPRT) deficiency on the nervous system development. HPRT deficiency causes the excretion of increased amounts of hypoxanthine into the extracellular medium and we hypothesized that HPRT deficiency related to hypoxanthine excess may then lead, directly or indirectly, to transcriptional aberrations in a variety of genes essential for the function and development of striatal progenitor cells. We have examined the effect of hypoxanthine excess on the differentiation of neurons in the well-established human NTERA-2 cl.D1 (NT2/D1) embryonic carcinoma neurogenesis model. NT2/D1 cells differentiate along neuroectodermal lineages after exposure to retinoic acid (RA). Hypoxanthine effects on RA-differentiation were examined by the changes on the expression of various transcription factor genes essential to neuronal differentiation and by the changes in tyrosine hydroxylase (TH), dopamine, adenosine and serotonin receptors (DRD, ADORA, HTR). We report that hypoxanthine excess deregulate WNT4, from Wnt/β-catenin pathway, and engrailed homeobox 1 gene and increased TH and dopamine DRD1, adenosine ADORA2A and serotonin HTR7 receptors, whose over expression characterize early neuro-developmental processes. PMID:25940910

  16. The Hopfield Model as the Minimum Noise Model for Neurons with Variable Firing Strength

    NASA Astrophysics Data System (ADS)

    Bassias, K. V.; Frank, B.

    A “non-standard Hopfield” network of neurons with variable maximum firing strength ai is studied and a noise analysis is employed. It is shown that the requirement of minimum noise forces the solution with ai=1, ∀i, namely, the standard Hopfield model. The minimum noise is calculated.

  17. Automatic parameter estimation of multicompartmental neuron models via minimization of trace error with control adjustment

    PubMed Central

    Goeritz, Marie L.; Marder, Eve

    2014-01-01

    We describe a new technique to fit conductance-based neuron models to intracellular voltage traces from isolated biological neurons. The biological neurons are recorded in current-clamp with pink (1/f) noise injected to perturb the activity of the neuron. The new algorithm finds a set of parameters that allows a multicompartmental model neuron to match the recorded voltage trace. Attempting to match a recorded voltage trace directly has a well-known problem: mismatch in the timing of action potentials between biological and model neuron is inevitable and results in poor phenomenological match between the model and data. Our approach avoids this by applying a weak control adjustment to the model to promote alignment during the fitting procedure. This approach is closely related to the control theoretic concept of a Luenberger observer. We tested this approach on synthetic data and on data recorded from an anterior gastric receptor neuron from the stomatogastric ganglion of the crab Cancer borealis. To test the flexibility of this approach, the synthetic data were constructed with conductance models that were different from the ones used in the fitting model. For both synthetic and biological data, the resultant models had good spike-timing accuracy. PMID:25008414

  18. Bistability, switches and working memory in a two-neuron inhibitory-feedback model.

    PubMed

    Kirillov, A B; Myre, C D; Woodward, D J

    1993-01-01

    It was reported earlier that an inhibitory-feedback network inspired by neostriatal circuitry may exhibit a bistable character and spontaneous switching phenomenon within the neuronal activity. In the presence of noise and external excitation, a few local neurons switch "on" and generate streams of impulses while other neurons remain quiescent. In time, the existing "on" neurons spontaneously switch "off" and other neurons switch "on". In this paper we examine the nature of the bistability and switching phenomenon using a simple model consisting of two mutually inhibitory neurons. For nonspiking neuron model, described by a system of nonlinear differential equations, we present a simple bifurcation analysis, which follows the birth and annihilation of two stable fixed points when model parameters are varied. We show that both nonspiking and spiking models may have two stable states, but only spiking neurons exhibit switching. The mechanism of switching for model spiking neurons, described by an equivalent RC circuit with a number of currents, is analyzed using computer simulations. It is shown that switching can be described by a two-state Markov chain with one parameter, which depends on the set of model physiological parameters, such as duration of afterhyperpolarization (AHP), maximum and the time duration of inhibitory post-synaptic potentials (IPSP's) and amplitude of the neuron noise input. "On" and "off" states of the model can be rapidly changed by localized excitatory input and the network then sustains the pattern of "on" and "off" states. That is, such a network can be used as a programmable memory device.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:8476984

  19. Modeling neuron-glia interactions: from parametric model to neuromorphic hardware.

    PubMed

    Ghaderi, Viviane S; Allam, Sushmita L; Ambert, N; Bouteiller, J-M C; Choma, J; Berger, T W

    2011-01-01

    Recent experimental evidence suggests that glial cells are more than just supporting cells to neurons - they play an active role in signal transmission in the brain. We herein propose to investigate the importance of these mechanisms and model neuron-glia interactions at synapses using three approaches: A parametric model that takes into account the underlying mechanisms of the physiological system, a non-parametric model that extracts its input-output properties, and an ultra-low power, fast processing, neuromorphic hardware model. We use the EONS (Elementary Objects of the Nervous System) platform, a highly elaborate synaptic modeling platform to investigate the influence of astrocytic glutamate transporters on postsynaptic responses in the detailed micro-environment of a tri-partite synapse. The simulation results obtained using EONS are then used to build a non-parametric model that captures the essential features of glutamate dynamics. The structure of the non-parametric model we use is specifically designed for efficient hardware implementation using ultra-low power subthreshold CMOS building blocks. The utilization of the approach described allows us to build large-scale models of neuron/glial interaction and consequently provide useful insights on glial modulation during normal and pathological neural function. PMID:22255113

  20. A neuron model of stochastic resonance using rectangular pulse trains.

    PubMed

    Danziger, Zachary; Grill, Warren M

    2015-02-01

    Stochastic resonance (SR) is the enhanced representation of a weak input signal by the addition of an optimal level of broadband noise to a nonlinear (threshold) system. Since its discovery in the 1980s the domain of input signals shown to be applicable to SR has greatly expanded, from strictly periodic inputs to now nearly any aperiodic forcing function. The perturbations (noise) used to generate SR have also expanded, from white noise to now colored noise or vibrational forcing. This study demonstrates that a new class of perturbations can achieve SR, namely, series of stochastically generated biphasic pulse trains. Using these pulse trains as 'noise' we show that a Hodgkin Huxley model neuron exhibits SR behavior when detecting weak input signals. This result is of particular interest to neuroscience because nearly all artificial neural stimulation is implemented with square current or voltage pulses rather than broadband noise, and this new method may facilitate the translation of the performance gains achievable through SR to neural prosthetics. PMID:25186655

  1. A Neuron Model of Stochastic Resonance Using Rectangular Pulse Trains

    PubMed Central

    Danziger, Zachary; Grill, Warren M

    2014-01-01

    Stochastic resonance (SR) is the enhanced representation of a weak input signal by the addition of an optimal level of broadband noise to a nonlinear (threshold) system. Since its discovery in the 1980s the domain of input signals shown to be applicable to SR has greatly expanded, from strictly periodic inputs to now nearly any aperiodic forcing function. The perturbations (noise) used to generate SR have also expanded, from white noise to now colored noise or vibrational forcing. This study demonstrates that a new class of perturbations can achieve SR, namely, series of stochastically generated biphasic pulse trains. Using these pulse trains as ‘noise’ we show that a Hodgkin Huxley model neuron exhibits SR behavior when detecting weak input signals. This result is of particular interest to neuroscience because nearly all artificial neural stimulation is implemented with square current or voltage pulses rather than broadband noise, and this new method may facilitate the translation of the performance gains achievable through SR to neural prosthetics. PMID:25186655

  2. Graph structure modeling for multi-neuronal spike data

    NASA Astrophysics Data System (ADS)

    Akaho, Shotaro; Higuchi, Sho; Iwasaki, Taishi; Hino, Hideitsu; Tatsuno, Masami; Murata, Noboru

    2016-03-01

    We propose a method to extract connectivity between neurons for extracellularly recorded multiple spike trains. The method removes pseudo-correlation caused by propagation of information along an indirect pathway, and is also robust against the influence from unobserved neurons. The estimation algorithm consists of iterations of a simple matrix inversion, which is scalable to large data sets. The performance is examined by synthetic spike data.

  3. Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.

    PubMed

    Siettos, Constantinos; Starke, Jens

    2016-09-01

    The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website. PMID:27340949

  4. A Modeling Approach on Why Simple Central Pattern Generators Are Built of Irregular Neurons

    PubMed Central

    Reyes, Marcelo Bussotti; Carelli, Pedro Valadão; Sartorelli, José Carlos; Pinto, Reynaldo Daniel

    2015-01-01

    The crustacean pyloric Central Pattern Generator (CPG) is a nervous circuit that endogenously provides periodic motor patterns. Even after about 40 years of intensive studies, the rhythm genesis is still not rigorously understood in this CPG, mainly because it is made of neurons with irregular intrinsic activity. Using mathematical models we addressed the question of using a network of irregularly behaving elements to generate periodic oscillations, and we show some advantages of using non-periodic neurons with intrinsic behavior in the transition from bursting to tonic spiking (as found in biological pyloric CPGs) as building components. We studied two- and three-neuron model CPGs built either with Hindmarsh-Rose or with conductance-based Hodgkin-Huxley-like model neurons. By changing a model’s parameter we could span the neuron’s intrinsic dynamical behavior from slow periodic bursting to fast tonic spiking, passing through a transition where irregular bursting was observed. Two-neuron CPG, half center oscillator (HCO), was obtained for each intrinsic behavior of the neurons by coupling them with mutual symmetric synaptic inhibition. Most of these HCOs presented regular antiphasic bursting activity and the changes of the bursting frequencies was studied as a function of the inhibitory synaptic strength. Among all HCOs, those made of intrinsic irregular neurons presented a wider burst frequency range while keeping a reliable regular oscillatory (bursting) behavior. HCOs of periodic neurons tended to be either hard to change their behavior with synaptic strength variations (slow periodic burster neurons) or unable to perform a physiologically meaningful rhythm (fast tonic spiking neurons). Moreover, 3-neuron CPGs with connectivity and output similar to those of the pyloric CPG presented the same results. PMID:25799556

  5. Serial correlation in neural spike trains: Experimental evidence, stochastic modeling, and single neuron variability

    NASA Astrophysics Data System (ADS)

    Farkhooi, Farzad; Strube-Bloss, Martin F.; Nawrot, Martin P.

    2009-02-01

    The activity of spiking neurons is frequently described by renewal point process models that assume the statistical independence and identical distribution of the intervals between action potentials. However, the assumption of independent intervals must be questioned for many different types of neurons. We review experimental studies that reported the feature of a negative serial correlation of neighboring intervals, commonly observed in neurons in the sensory periphery as well as in central neurons, notably in the mammalian cortex. In our experiments we observed the same short-lived negative serial dependence of intervals in the spontaneous activity of mushroom body extrinsic neurons in the honeybee. To model serial interval correlations of arbitrary lags, we suggest a family of autoregressive point processes. Its marginal interval distribution is described by the generalized gamma model, which includes as special cases the log-normal and gamma distributions, which have been widely used to characterize regular spiking neurons. In numeric simulations we investigated how serial correlation affects the variance of the neural spike count. We show that the experimentally confirmed negative correlation reduces single-neuron variability, as quantified by the Fano factor, by up to 50%, which favors the transmission of a rate code. We argue that the feature of a negative serial correlation is likely to be common to the class of spike-frequency-adapting neurons and that it might have been largely overlooked in extracellular single-unit recordings due to spike sorting errors.

  6. Serial correlation in neural spike trains: experimental evidence, stochastic modeling, and single neuron variability.

    PubMed

    Farkhooi, Farzad; Strube-Bloss, Martin F; Nawrot, Martin P

    2009-02-01

    The activity of spiking neurons is frequently described by renewal point process models that assume the statistical independence and identical distribution of the intervals between action potentials. However, the assumption of independent intervals must be questioned for many different types of neurons. We review experimental studies that reported the feature of a negative serial correlation of neighboring intervals, commonly observed in neurons in the sensory periphery as well as in central neurons, notably in the mammalian cortex. In our experiments we observed the same short-lived negative serial dependence of intervals in the spontaneous activity of mushroom body extrinsic neurons in the honeybee. To model serial interval correlations of arbitrary lags, we suggest a family of autoregressive point processes. Its marginal interval distribution is described by the generalized gamma model, which includes as special cases the log-normal and gamma distributions, which have been widely used to characterize regular spiking neurons. In numeric simulations we investigated how serial correlation affects the variance of the neural spike count. We show that the experimentally confirmed negative correlation reduces single-neuron variability, as quantified by the Fano factor, by up to 50%, which favors the transmission of a rate code. We argue that the feature of a negative serial correlation is likely to be common to the class of spike-frequency-adapting neurons and that it might have been largely overlooked in extracellular single-unit recordings due to spike sorting errors. PMID:19391776

  7. Optimizing neuronal differentiation from induced pluripotent stem cells to model ASD

    PubMed Central

    Kim, Dae-Sung; Ross, P. Joel; Zaslavsky, Kirill; Ellis, James

    2014-01-01

    Autism spectrum disorder (ASD) is an early-onset neurodevelopmental disorder characterized by deficits in social communication, and restricted and repetitive patterns of behavior. Despite its high prevalence, discovery of pathophysiological mechanisms underlying ASD has lagged due to a lack of appropriate model systems. Recent advances in induced pluripotent stem cell (iPSC) technology and neural differentiation techniques allow for detailed functional analyses of neurons generated from living individuals with ASD. Refinement of cortical neuron differentiation methods from iPSCs will enable mechanistic studies of specific neuronal subpopulations that may be preferentially impaired in ASD. In this review, we summarize recent accomplishments in differentiation of cortical neurons from human pluripotent stems cells and efforts to establish in vitro model systems to study ASD using personalized neurons. PMID:24782713

  8. Building a Large-Scale Computational Model of a Cortical Neuronal Network

    NASA Astrophysics Data System (ADS)

    Zemanová, Lucia; Zhou, Changsong; Kurths, Jürgen

    We introduce the general framework of the large-scale neuronal model used in the 5th Helmholtz Summer School — Complex Brain Networks. The main aim is to build a universal large-scale model of a cortical neuronal network, structured as a network of networks, which is flexible enough to implement different kinds of topology and neuronal models and which exhibits behavior in various dynamical regimes. First, we describe important biological aspects of brain topology and use them in the construction of a large-scale cortical network. Second, the general dynamical model is presented together with explanations of the major dynamical properties of neurons. Finally, we discuss the implementation of the model into parallel code and its possible modifications and improvements.

  9. Reliability of neuronal information conveyed by unreliable neuristor-based leaky integrate-and-fire neurons: a model study

    PubMed Central

    Lim, Hyungkwang; Kornijcuk, Vladimir; Seok, Jun Yeong; Kim, Seong Keun; Kim, Inho; Hwang, Cheol Seong; Jeong, Doo Seok

    2015-01-01

    We conducted simulations on the neuronal behavior of neuristor-based leaky integrate-and-fire (NLIF) neurons. The phase-plane analysis on the NLIF neuron highlights its spiking dynamics – determined by two nullclines conditional on the variables on the plane. Particular emphasis was placed on the operational noise arising from the variability of the threshold switching behavior in the neuron on each switching event. As a consequence, we found that the NLIF neuron exhibits a Poisson-like noise in spiking, delimiting the reliability of the information conveyed by individual NLIF neurons. To highlight neuronal information coding at a higher level, a population of noisy NLIF neurons was analyzed in regard to probability of successful information decoding given the Poisson-like noise of each neuron. The result demonstrates highly probable success in decoding in spite of large variability – due to the variability of the threshold switching behavior – of individual neurons. PMID:25966658

  10. Nonlinear Modeling of Dynamic Interactions within Neuronal Ensembles using Principal Dynamic Modes

    PubMed Central

    Marmarelis, V. Z.; Shin, D. C.; Song, D.; Hampson, R. E.; Deadwyler, S.; Berger, T. W.

    2012-01-01

    A methodology for nonlinear modeling of multi-input multi-output (MIMO) neuronal systems is presented that utilizes the concept of Principal Dynamic Modes (PDM). The efficacy of this new methodology is demonstrated in the study of the dynamic interactions between neuronal ensembles in the Pre-Frontal Cortex (PFC) of a behaving non-human primate (NHP) performing a Delayed Match-to-Sample task. Recorded spike trains from Layer-2 and Layer-5 neurons were viewed as the “inputs” and “outputs”, respectively, of a putative MIMO system/model that quantifies the dynamic transformation of multi-unit neuronal activity between Layer-2 and Layer-5 of the PFC. Model prediction performance was evaluated by means of computed Receiver Operating Characteristic (ROC) curves. The PDM-based approach seeks to reduce the complexity of MIMO models of neuronal ensembles in order to enable the practicable modeling of large-scale neural systems incorporating hundreds or thousands of neurons, which is emerging as a preeminent issue in the study of neural function. The “scaling-up” issue has attained critical importance as multi-electrode recordings are increasingly used to probe neural systems and advance our understanding of integrated neural function. The initial results indicate that the PDM-based modeling methodology may greatly reduce the complexity of the MIMO model without significant degradation of performance. Furthermore, the PDM-based approach offers the prospect of improved biological/physiological interpretation of the obtained MIMO models. PMID:23011343

  11. Motor neuron pathology and behavioral alterations at late stages in a SMA mouse model.

    PubMed

    Fulceri, Federica; Bartalucci, Alessia; Paparelli, Silvio; Pasquali, Livia; Biagioni, Francesca; Ferrucci, Michela; Ruffoli, Riccardo; Fornai, Francesco

    2012-03-01

    Spinal muscular atrophy (SMA) is a neurogenetic autosomal recessive disorder characterized by degeneration of lower motor neurons. The validation of appropriate animal models is key in fostering SMA research. Recent studies set up an animal model showing long survival and slow disease progression. This model is knocked out for mouse SMN (Smn(-/-)) gene and carries a human mutation of the SMN1 gene (SMN1A2G), along with human SMN2 gene. In the present study we used this knock out double transgenic mouse model (SMN2(+/+); Smn(-/-); SMN1A2G(+/-)) to characterize the spinal cord pathology along with motor deficit at prolonged survival times. In particular, motor neuron loss was established stereologically (44.77%) after motor deficit reached a steady state. At this stage, spared motor neurons showed significant cell body enlargement. Moreover, similar to what was described in patients affected by SMA we found neuronal heterotopy (almost 4% of total motor neurons) in the anterior white matter. The delayed disease progression was likely to maintain fair motor activity despite a dramatic loss of large motor neurons. This provides a wonderful tool to probe novel drugs finely tuning the survival of motor neurons. In fact, small therapeutic effects protracted over considerable time intervals (even more than a year) are expected to be magnified. PMID:22306031

  12. Channel-noise-induced stochastic facilitation in an auditory brainstem neuron model

    NASA Astrophysics Data System (ADS)

    Schmerl, Brett A.; McDonnell, Mark D.

    2013-11-01

    Neuronal membrane potentials fluctuate stochastically due to conductance changes caused by random transitions between the open and closed states of ion channels. Although it has previously been shown that channel noise can nontrivially affect neuronal dynamics, it is unknown whether ion-channel noise is strong enough to act as a noise source for hypothesized noise-enhanced information processing in real neuronal systems, i.e., “stochastic facilitation”. Here we demonstrate that biophysical models of channel noise can give rise to two kinds of recently discovered stochastic facilitation effects in a Hodgkin-Huxley-like model of auditory brainstem neurons. The first, known as slope-based stochastic resonance (SBSR), enables phasic neurons to emit action potentials that can encode the slope of inputs that vary slowly relative to key time constants in the model. The second, known as inverse stochastic resonance (ISR), occurs in tonically firing neurons when small levels of noise inhibit tonic firing and replace it with burstlike dynamics. Consistent with previous work, we conclude that channel noise can provide significant variability in firing dynamics, even for large numbers of channels. Moreover, our results show that possible associated computational benefits may occur due to channel noise in neurons of the auditory brainstem. This holds whether the firing dynamics in the model are phasic (SBSR can occur due to channel noise) or tonic (ISR can occur due to channel noise).

  13. Modeling Dravet syndrome using induced pluripotent stem cells (iPSCs) and directly converted neurons.

    PubMed

    Jiao, Jiao; Yang, Yuanyuan; Shi, Yiwu; Chen, Jiayu; Gao, Rui; Fan, Yong; Yao, Hui; Liao, Weiping; Sun, Xiao-Fang; Gao, Shaorong

    2013-11-01

    Severe myoclonic epilepsy of infancy (SMEI, also known as Dravet syndrome) and genetic epilepsy with febrile seizures plus (mild febrile seizures) can both arise due to mutations of SCN1A, the gene encoding alpha 1 pore-forming subunit of the Nav1.1 voltage-gated sodium channel. Owing to the inaccessibility of patient brain neurons, the precise mechanism of mild febrile seizures and SMEI remains elusive, and there is no effective pharmacotherapy. Induced pluripotent stem cells (iPSCs) and induced neurons (iNs) have been successfully generated from patients and applied for modeling various neuronal diseases. In this study, we established iPSC lines from one SMEI patient and one mild febrile seizures patient, respectively. Functional glutamatergic neurons were subsequently differentiated from these iPSCs. Electrophysiological analysis of patient iPSC-derived glutamatergic neurons revealed a hyperexcitable state of enlarged and persistent sodium channel activation, more intensive evoked action potentials and typical epileptic spontaneous action potentials. In consistent with the severity of the symptoms, the hyperexcitability of the neurons derived from SMEI patient was more serious than that of mild febrile seizures patient. Furthermore, the hyperexcitability of the neurons can be alleviated by treatment with phenytoin, a conventional antiepileptic drug. In parallel, iNs were directly converted from patient fibroblasts which also showed a delayed inactivation of sodium channels. Our results demonstrate that both iPSC-derived neurons and iNs from mild febrile seizures and SMEI patients exhibited a hyperexcitable state. More importantly, patient iPSC-derived neurons can recapitulate the neuronal pathophysiology and respond to drug treatment, indicating that these neurons can be potentially used for screening appropriate drugs for personalized therapies. PMID:23773995

  14. [Hardware Implementation of Numerical Simulation Function of Hodgkin-Huxley Model Neurons Action Potential Based on Field Programmable Gate Array].

    PubMed

    Wang, Jinlong; Lu, Mai; Hu, Yanwen; Chen, Xiaoqiang; Pan, Qiangqiang

    2015-12-01

    Neuron is the basic unit of the biological neural system. The Hodgkin-Huxley (HH) model is one of the most realistic neuron models on the electrophysiological characteristic description of neuron. Hardware implementation of neuron could provide new research ideas to clinical treatment of spinal cord injury, bionics and artificial intelligence. Based on the HH model neuron and the DSP Builder technology, in the present study, a single HH model neuron hardware implementation was completed in Field Programmable Gate Array (FPGA). The neuron implemented in FPGA was stimulated by different types of current, the action potential response characteristics were analyzed, and the correlation coefficient between numerical simulation result and hardware implementation result were calculated. The results showed that neuronal action potential response of FPGA was highly consistent with numerical simulation result. This work lays the foundation for hardware implementation of neural network. PMID:27079105

  15. Exogenous erythropoietin provides neuroprotection of grafted dopamine neurons in a rodent model of Parkinson's disease.

    PubMed

    Kanaan, Nicholas M; Collier, Timothy J; Marchionini, Deanna M; McGuire, Susan O; Fleming, Matthew F; Sortwell, Caryl E

    2006-01-12

    Parkinson's disease (PD) is a neurodegenerative disease marked by severe loss of dopamine (DA) neurons in the nigrostriatal system, which results in depletion of striatal DA. Transplantation of embryonic ventral mesencephalic (VM) DA neurons into the striatum is a currently explored experimental treatment aimed at replacing lost DA in the nigrostriatal system, but is plagued with poor survival (5-20%) of implanted neurons. Here, we tested the ability of erythropoietin (Epo) to provide neuroprotection for embryonic day 14 (E14) VM DA neurons. Epo was tested in vitro for the ability to augment tyrosine hydroxylase-immunoreactive (TH-ir) neuron survival under normal cell culture conditions. In vitro, Epo did not increase the number of TH-ir neurons when administered at the time of plating the E14 VM cells in culture. We also tested the efficacy of Epo to enhance E14 VM transplants in vivo. Rats unilaterally lesioned with 6-hydroxydopamine received transplants that were incubated in Epo. Treatment with Epo produced significant increases in TH-ir neuron number, soma size, and staining intensity. Animals receiving Epo-treated grafts exhibited significantly accelerated functional improvements and significantly greater overall improvements from rotational asymmetry compared to control grafted rats. These data indicate that the survival of embryonic mesencephalic TH-ir neurons is increased when Epo is administered with grafted cells in a rodent model of PD. As direct neurotrophic effects of Epo were not observed in vitro, the mechanism of Epo neuroprotection remains to be elucidated. PMID:16368081

  16. An optogenetic mouse model of rett syndrome targeting on catecholaminergic neurons.

    PubMed

    Zhang, Shuang; Johnson, Christopher M; Cui, Ningren; Xing, Hao; Zhong, Weiwei; Wu, Yang; Jiang, Chun

    2016-10-01

    Rett syndrome (RTT) is a neurodevelopmental disorder affecting multiple functions, including the norepinephrine (NE) system. In the CNS, NE is produced mostly by neurons in the locus coeruleus (LC), where defects in intrinsic neuronal properties, NE biosynthetic enzymes, neuronal CO2 sensitivity, and synaptic currents have been reported in mouse models of RTT. LC neurons in methyl-CpG-binding protein 2 gene (Mecp2) null mice show a high rate of spontaneous firing, although whether such hyperexcitability might increase or decrease the NE release from synapses is unknown. To activate the NEergic axonal terminals selectively, we generated an optogenetic mouse model of RTT in which NEergic neuronal excitability can be manipulated with light. Using commercially available mouse breeders, we produced a new strain of double-transgenic mice with Mecp2 knockout and channelrhodopsin (ChR) knockin in catecholaminergic neurons. Several RTT-like phenotypes were found in the tyrosine hydroxylase (TH)-ChR-Mecp2(-/Y) mice, including hypoactivity, low body weight, hindlimb clasping, and breathing disorders. In brain slices, optostimulation produced depolarization and an increase in the firing rate of LC neurons from TH-ChR control mice. In TH-ChR control mice, optostimulation of presynaptic NEergic neurons augmented the firing rate of hypoglossal neurons (HNs), which was blocked by the α-adrenoceptor antagonist phentolamine. Such optostimulation of NEergic terminals had almost no effect on HNs from two or three TH-ChR-Mecp2(-/Y) mice, indicating that excessive excitation of presynaptic neurons does not benefit NEergic modulation in mice with Mecp2 disruption. These results also demonstrate the feasibility of generating double-transgenic mice for studies of RTT with commercially available mice, which are inexpensive, labor/time efficient, and promising for cell-specific stimulation. © 2016 Wiley Periodicals, Inc. PMID:27317352

  17. Zinc Deficiency Induces Apoptosis via Mitochondrial p53- and Caspase-Dependent Pathways in Human Neuronal Precursor Cells

    ERIC Educational Resources Information Center

    Seth, Rohit; Corniola, Rikki S.; Gower-Winter, Shannon D.; Morgan, Thomas J., Jr.; Bishop, Brian; Levenson, Cathy W.

    2015-01-01

    Previous studies have shown that zinc deficiency leads to apoptosis of neuronal precursor cells in vivo and in vitro. In addition to the role of p53 as a nuclear transcription factor in zinc deficient cultured human neuronal precursors (NT-2), we have now identified the translocation of phosphorylated p53 to the mitochondria and p53-dependent…

  18. Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons

    PubMed Central

    Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang

    2011-01-01

    The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by sampling, which can explain a large number of macroscopic experimental data in neuroscience and cognitive science. But it has turned out to be surprisingly difficult to create a link between these abstract models for stochastic computations and more detailed models of the dynamics of networks of spiking neurons. Here we create such a link and show that under some conditions the stochastic firing activity of networks of spiking neurons can be interpreted as probabilistic inference via Markov chain Monte Carlo (MCMC) sampling. Since common methods for MCMC sampling in distributed systems, such as Gibbs sampling, are inconsistent with the dynamics of spiking neurons, we introduce a different approach based on non-reversible Markov chains that is able to reflect inherent temporal processes of spiking neuronal activity through a suitable choice of random variables. We propose a neural network model and show by a rigorous theoretical analysis that its neural activity implements MCMC sampling of a given distribution, both for the case of discrete and continuous time. This provides a step towards closing the gap between abstract functional models of cortical computation and more detailed models of networks of spiking neurons. PMID:22096452

  19. A model for the characterization of the spatial properties in vestibular neurons

    NASA Technical Reports Server (NTRS)

    Angelaki, D. E.; Bush, G. A.; Perachio, A. A.

    1992-01-01

    Quantitative study of the static and dynamic response properties of some otolith-sensitive neurons has been difficult in the past partly because their responses to different linear acceleration vectors exhibited no "null" plane and a dependence of phase on stimulus orientation. The theoretical formulation of the response ellipse provides a quantitative way to estimate the spatio-temporal properties of such neurons. Its semi-major axis gives the direction of the polarization vector (i.e., direction of maximal sensitivity) and it estimates the neuronal response for stimulation along that direction. In addition, the semi-minor axis of the ellipse provides an estimate of the neuron's maximal sensitivity in the "null" plane. In this paper, extracellular recordings from otolith-sensitive vestibular nuclei neurons in decerebrate rats were used to demonstrate the practical application of the method. The experimentally observed gain and phase dependence on the orientation angle of the acceleration vector in a head-horizontal plane was described and satisfactorily fit by the response ellipse model. In addition, the model satisfactorily fits neuronal responses in three-dimensions and unequivocally demonstrates that the response ellipse formulation is the general approach to describe quantitatively the spatial properties of vestibular neurons.

  20. Hippocampal adaptive response following extensive neuronal loss in an inducible transgenic mouse model.

    PubMed

    Myczek, Kristoffer; Yeung, Stephen T; Castello, Nicholas; Baglietto-Vargas, David; LaFerla, Frank M

    2014-01-01

    Neuronal loss is a common component of a variety of neurodegenerative disorders (including Alzheimer's, Parkinson's, and Huntington's disease) and brain traumas (stroke, epilepsy, and traumatic brain injury). One brain region that commonly exhibits neuronal loss in several neurodegenerative disorders is the hippocampus, an area of the brain critical for the formation and retrieval of memories. Long-lasting and sometimes unrecoverable deficits caused by neuronal loss present a unique challenge for clinicians and for researchers who attempt to model these traumas in animals. Can these deficits be recovered, and if so, is the brain capable of regeneration following neuronal loss? To address this significant question, we utilized the innovative CaM/Tet-DT(A) mouse model that selectively induces neuronal ablation. We found that we are able to inflict a consistent and significant lesion to the hippocampus, resulting in hippocampally-dependent behavioral deficits and a long-lasting upregulation in neurogenesis, suggesting that this process might be a critical part of hippocampal recovery. In addition, we provide novel evidence of angiogenic and vasculature changes following hippocampal neuronal loss in CaM/Tet-DTA mice. We posit that angiogenesis may be an important factor that promotes neurogenic upregulation following hippocampal neuronal loss, and both factors, angiogenesis and neurogenesis, can contribute to the adaptive response of the brain for behavioral recovery. PMID:25184527

  1. Is the Langevin phase equation an efficient model for oscillating neurons?

    NASA Astrophysics Data System (ADS)

    Ota, Keisuke; Tsunoda, Takamasa; Omori, Toshiaki; Watanabe, Shigeo; Miyakawa, Hiroyoshi; Okada, Masato; Aonishi, Toru

    2009-12-01

    The Langevin phase model is an important canonical model for capturing coherent oscillations of neural populations. However, little attention has been given to verifying its applicability. In this paper, we demonstrate that the Langevin phase equation is an efficient model for neural oscillators by using the machine learning method in two steps: (a) Learning of the Langevin phase model. We estimated the parameters of the Langevin phase equation, i.e., a phase response curve and the intensity of white noise from physiological data measured in the hippocampal CA1 pyramidal neurons. (b) Test of the estimated model. We verified whether a Fokker-Planck equation derived from the Langevin phase equation with the estimated parameters could capture the stochastic oscillatory behavior of the same neurons disturbed by periodic perturbations. The estimated model could predict the neural behavior, so we can say that the Langevin phase equation is an efficient model for oscillating neurons.

  2. Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity

    PubMed Central

    Hull, Michael J.; Soffe, Stephen R.; Willshaw, David J.; Roberts, Alan

    2016-01-01

    What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition. PMID:26824331

  3. Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity.

    PubMed

    Hull, Michael J; Soffe, Stephen R; Willshaw, David J; Roberts, Alan

    2016-01-01

    What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition. PMID:26824331

  4. Frequent Release of Low Amounts of Herpes Simplex Virus From Neurons: Results of a Mathematical Model

    PubMed Central

    Schiffer, Joshua T.; Abu-Raddad, Laith; Mark, Karen E.; Zhu, Jia; Selke, Stacy; Magaret, Amalia; Wald, Anna; Corey, Lawrence

    2010-01-01

    Herpes Simplex Virus-2 (HSV-2) is a sexually transmitted infection that is the leading cause of genital ulcers worldwide. Infection is life long and is characterized by repeated asymptomatic and symptomatic shedding episodes of virus that are initiated when virus is released from neurons into the genital tract. The pattern of HSV-2 release from neurons into the genital tract is poorly understood. We fit a mathematical model of HSV-2 pathogenesis to curves generated from daily quantification of HSV in mucosal swabs performed from patients with herpetic genital ulcers. We used virologic parameters derived from model fitting for stochastic model simulations. These simulations reproduced previously documented estimates for shedding frequency, and herpetic lesion diameter and frequency. The most realistic model output occurred when we assumed minimal amounts of daily neuronal virus introduction. In our simulations, small changes in average total quantity of HSV-2 released from neurons influenced detectable shedding frequency, while changes in frequency of neuronal HSV-2 release had little effect. Frequent HSV-2 shedding episodes in humans are explained by nearly constant release of small numbers of viruses from neurons that terminate in the genital tract. PMID:20161655

  5. Motor neuron degeneration in a mouse model of seipinopathy

    PubMed Central

    Guo, J; Qiu, W; Soh, S L Y; Wei, S; Radda, G K; Ong, W-Y; Pang, Z P; Han, W

    2013-01-01

    Heterozygosity for missense mutations (N88S/S90L) in BSCL2 (Berardinelli–Seip congenital lipodystrophy type 2)/Seipin is associated with a broad spectrum of motoneuron diseases. To understand the underlying mechanisms how the mutations lead to motor neuropathy, we generated transgenic mice with neuron-specific expression of wild-type (tgWT) or N88S/S90L mutant (tgMT) human Seipin. Transgenes led to the broad expression of WT or mutant Seipin in the brain and spinal cord. TgMT, but not tgWT, mice exhibited late-onset altered locomotor activities and gait abnormalities that recapitulate symptoms of seipinopathy patients. We found loss of alpha motor neurons in tgMT spinal cord. Mild endoreticular stress was present in both tgMT and tgWT neurons; however, only tgMT mice exhibited protein aggregates and disrupted Golgi apparatus. Furthermore, autophagosomes were significantly increased, along with elevated light chain 3 (LC3)-II level in tgMT spinal cord, consistent with the activation of autophagy pathway in response to mutant Seipin expression and protein aggregation. These results suggest that induction of autophagy pathway is involved in the cellular response to mutant Seipin in seipinopathy and that motoneuron loss is a key pathogenic process underlying the development of locomotor abnormalities. PMID:23470542

  6. Motor neuron degeneration in a mouse model of seipinopathy.

    PubMed

    Guo, J; Qiu, W; Soh, S L Y; Wei, S; Radda, G K; Ong, W-Y; Pang, Z P; Han, W

    2013-01-01

    Heterozygosity for missense mutations (N88S/S90L) in BSCL2 (Berardinelli-Seip congenital lipodystrophy type 2)/Seipin is associated with a broad spectrum of motoneuron diseases. To understand the underlying mechanisms how the mutations lead to motor neuropathy, we generated transgenic mice with neuron-specific expression of wild-type (tgWT) or N88S/S90L mutant (tgMT) human Seipin. Transgenes led to the broad expression of WT or mutant Seipin in the brain and spinal cord. TgMT, but not tgWT, mice exhibited late-onset altered locomotor activities and gait abnormalities that recapitulate symptoms of seipinopathy patients. We found loss of alpha motor neurons in tgMT spinal cord. Mild endoreticular stress was present in both tgMT and tgWT neurons; however, only tgMT mice exhibited protein aggregates and disrupted Golgi apparatus. Furthermore, autophagosomes were significantly increased, along with elevated light chain 3 (LC3)-II level in tgMT spinal cord, consistent with the activation of autophagy pathway in response to mutant Seipin expression and protein aggregation. These results suggest that induction of autophagy pathway is involved in the cellular response to mutant Seipin in seipinopathy and that motoneuron loss is a key pathogenic process underlying the development of locomotor abnormalities. PMID:23470542

  7. Using Strahler's analysis to reduce up to 200-fold the run time of realistic neuron models

    NASA Astrophysics Data System (ADS)

    Marasco, Addolorata; Limongiello, Alessandro; Migliore, Michele

    2013-10-01

    The cellular mechanisms underlying higher brain functions/dysfunctions are extremely difficult to investigate experimentally, and detailed neuron models have proven to be a very useful tool to help these kind of investigations. However, realistic neuronal networks of sizes appropriate to study brain functions present the major problem of requiring a prohibitively high computational resources. Here, building on our previous work, we present a general reduction method based on Strahler's analysis of neuron morphologies. We show that, without any fitting or tuning procedures, it is possible to map any morphologically and biophysically accurate neuron model into an equivalent reduced version. Using this method for Purkinje cells, we demonstrate how run times can be reduced up to 200-fold, while accurately taking into account the effects of arbitrarily located and activated synaptic inputs.

  8. From “Directed Differentiation” to “Neuronal Induction”: Modeling Neuropsychiatric Disease

    PubMed Central

    Ho, Seok-Man; Topol, Aaron; Brennand, Kristen J

    2015-01-01

    Aberrant behavior and function of neurons are believed to be the primary causes of most neurological diseases and psychiatric disorders. Human postmortem samples have limited availability and, while they provide clues to the state of the brain after a prolonged illness, they offer limited insight into the factors contributing to disease onset. Conversely, animal models cannot recapitulate the polygenic origins of neuropsychiatric disease. Novel methods, such as somatic cell reprogramming, deliver nearly limitless numbers of pathogenic human neurons for the study of the mechanism of neuropsychiatric disease initiation and progression. First, this article reviews the advent of human induced pluripotent stem cell (hiPSC) technology and introduces two major methods, “directed differentiation” and “neuronal induction,” by which it is now possible to generate neurons for modeling neuropsychiatric disease. Second, it discusses the recent applications, and the limitations, of these technologies to in vitro studies of psychiatric disorders. PMID:26045654

  9. Kilohertz Frequency Deep Brain Stimulation Is Ineffective at Regularizing the Firing of Model Thalamic Neurons

    PubMed Central

    Couto, João; Grill, Warren M.

    2016-01-01

    Deep brain stimulation (DBS) is an established therapy for movement disorders, including tremor, dystonia, and Parkinson's disease, but the mechanisms of action are not well understood. Symptom suppression by DBS typically requires stimulation frequencies ≥100 Hz, but when the frequency is increased above ~2 kHz, the effectiveness in tremor suppression declines (Benabid et al., 1991). We sought to test the hypothesis that the decline in efficacy at high frequencies is associated with desynchronization of the activity generated within a population of stimulated neurons. Regularization of neuronal firing is strongly correlated with tremor suppression by DBS, and desynchronization would disrupt the regularization of neuronal activity. We implemented computational models of CNS axons with either deterministic or stochastic membrane dynamics, and quantified the response of populations of model nerve fibers to extracellular stimulation at different frequencies and amplitudes. As stimulation frequency was increased from 2 to 80 Hz the regularity of neuronal firing increased (as assessed with direct estimates of entropy), in accord with the clinical effects on tremor of increasing stimulation frequency (Kuncel et al., 2006). Further, at frequencies between 80 and 500 Hz, increasing the stimulation amplitude (i.e., the proportion of neurons activated by the stimulus) increased the regularity of neuronal activity across the population, in accord with the clinical effects on tremor of stimulation amplitude (Kuncel et al., 2007). However, at stimulation frequencies above 1 kHz the regularity of neuronal firing declined due to irregular patterns of action potential generation and conduction block. The reductions in neuronal regularity that occurred at high frequencies paralleled the previously reported decline in tremor reduction and may be responsible for the loss of efficacy of DBS at very high frequencies. This analysis provides further support for the hypothesis that

  10. Two-population model for medial temporal lobe neurons: The vast majority are almost silent

    NASA Astrophysics Data System (ADS)

    Magyar, Andrew; Collins, John

    2015-07-01

    Recordings in the human medial temporal lobe have found many neurons that respond to pictures (and related stimuli) of just one particular person of those presented. It has been proposed that these are concept cells, responding to just a single concept. However, a direct experimental test of the concept cell idea appears impossible, because it would need the measurement of the response of each cell to enormous numbers of other stimuli. Here we propose a new statistical method for analysis of the data that gives a more powerful way to analyze how close data are to the concept-cell idea. Central to the model is the neuronal sparsity, defined as the total fraction of stimuli that elicit an above-threshold response in the neuron. The model exploits the large number of sampled neurons to give sensitivity to situations where the average response sparsity is much less than one response for the number of presented stimuli. We show that a conventional model where a single sparsity is postulated for all neurons gives an extremely poor fit to the data. In contrast, a model with two dramatically different populations gives an excellent fit to data from the hippocampus and entorhinal cortex. In the hippocampus, one population has 7% of the cells with a 2.6% sparsity. But a much larger fraction (93%) respond to only 0.1% of the stimuli. This can result in an extreme bias in the responsiveness of reported neurons compared with a typical neuron. Finally, we show how to allow for the fact that some identified units correspond to multiple neurons and find that our conclusions at the neural level are quantitatively changed but strengthened, with an even stronger difference between the two populations.

  11. A flexible, interactive software tool for fitting the parameters of neuronal models.

    PubMed

    Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

    2014-01-01

    The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool. PMID

  12. A flexible, interactive software tool for fitting the parameters of neuronal models

    PubMed Central

    Friedrich, Péter; Vella, Michael; Gulyás, Attila I.; Freund, Tamás F.; Káli, Szabolcs

    2014-01-01

    The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool. PMID

  13. Physiological characterization of vestibular efferent brainstem neurons using a transgenic mouse model.

    PubMed

    Leijon, Sara; Magnusson, Anna K

    2014-01-01

    The functional role of efferent innervation of the vestibular end-organs in the inner ear remains elusive. This study provides the first physiological characterization of the cholinergic vestibular efferent (VE) neurons in the brainstem by utilizing a transgenic mouse model, expressing eGFP under a choline-acetyltransferase (ChAT)-locus spanning promoter in combination with targeted patch clamp recordings. The intrinsic electrical properties of the eGFP-positive VE neurons were compared to the properties of the lateral olivocochlear (LOC) brainstem neurons, which gives rise to efferent innervation of the cochlea. Both VE and the LOC neurons were marked by their negative resting membrane potential <-75 mV and their passive responses in the hyperpolarizing range. In contrast, the response properties of VE and LOC neurons differed significantly in the depolarizing range. When injected with positive currents, VE neurons fired action potentials faithfully to the onset of depolarization followed by sparse firing with long inter-spike intervals. This response gave rise to a low response gain. The LOC neurons, conversely, responded with a characteristic delayed tonic firing upon depolarizing stimuli, giving rise to higher response gain than the VE neurons. Depolarization triggered large TEA insensitive outward currents with fast inactivation kinetics, indicating A-type potassium currents, in both the inner ear-projecting neuronal types. Immunohistochemistry confirmed expression of Kv4.3 and 4.2 ion channel subunits in both the VE and LOC neurons. The difference in spiking responses to depolarization is related to a two-fold impact of these transient outward currents on somatic integration in the LOC neurons compared to in VE neurons. It is speculated that the physiological properties of the VE neurons might be compatible with a wide-spread control over motion and gravity sensation in the inner ear, providing likewise feed-back amplification of abrupt and strong phasic

  14. Reduced motor neuron excitability is an important contributor to weakness in a rat model of sepsis.

    PubMed

    Nardelli, Paul; Vincent, Jacob A; Powers, Randall; Cope, Tim C; Rich, Mark M

    2016-08-01

    The mechanisms by which sepsis triggers intensive care unit acquired weakness (ICUAW) remain unclear. We previously identified difficulty with motor unit recruitment in patients as a novel contributor to ICUAW. To study the mechanism underlying poor recruitment of motor units we used the rat cecal ligation and puncture model of sepsis. We identified striking dysfunction of alpha motor neurons during repetitive firing. Firing was more erratic, and often intermittent. Our data raised the possibility that reduced excitability of motor neurons was a significant contributor to weakness induced by sepsis. In this study we quantified the contribution of reduced motor neuron excitability and compared its magnitude to the contributions of myopathy, neuropathy and failure of neuromuscular transmission. We injected constant depolarizing current pulses (5s) into the soma of alpha motor neurons in the lumbosacral spinal cord of anesthetized rats to trigger repetitive firing. In response to constant depolarization, motor neurons in untreated control rats fired at steady and continuous firing rates and generated smooth and sustained tetanic motor unit force as expected. In contrast, following induction of sepsis, motor neurons were often unable to sustain firing throughout the 5s current injection such that force production was reduced. Even when firing, motor neurons from septic rats fired erratically and discontinuously, leading to irregular production of motor unit force. Both fast and slow type motor neurons had similar disruption of excitability. We followed rats after recovery from sepsis to determine the time course of resolution of the defect in motor neuron excitability. By one week, rats appeared to have recovered from sepsis as they had no piloerection and appeared to be in no distress. The defects in motor neuron repetitive firing were still striking at 2weeks and, although improved, were present at one month. We infer that rats suffered from weakness due to reduced

  15. Thalamic neuron models encode stimulus information by burst-size modulation

    PubMed Central

    Elijah, Daniel H.; Samengo, Inés; Montemurro, Marcelo A.

    2015-01-01

    Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons. PMID

  16. Thalamic neuron models encode stimulus information by burst-size modulation.

    PubMed

    Elijah, Daniel H; Samengo, Inés; Montemurro, Marcelo A

    2015-01-01

    Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons. PMID

  17. Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

    NASA Technical Reports Server (NTRS)

    Paulin, M. G.; Hoffman, L. F.

    1999-01-01

    We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

  18. A generalized Leaky Integrate-and-Fire neuron model with fast implementation method.

    PubMed

    Wang, Zhenzhong; Guo, Lilin; Adjouadi, Malek

    2014-08-01

    This study introduces a new Generalized Leaky Integrate-and-Fire (GLIF) neuron model with variable leaking resistor and bias current in order to reproduce accurately the membrane voltage dynamics of a biological neuron. The accuracy of this model is ensured by adjusting its parameters to the statistical properties of the Hodgkin-Huxley model outputs; while the speed is enhanced by introducing a Generalized Exponential Moving Average method that converts the parameterized kernel functions into pre-calculated lookup tables based on an analytic solution of the dynamic equations of the GLIF model. PMID:24875788

  19. Lateral information processing by spiking neurons: a theoretical model of the neural correlate of consciousness.

    PubMed

    Ebner, Marc; Hameroff, Stuart

    2011-01-01

    Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on "autopilot"). Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the "conscious pilot") suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious "auto-pilot" cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways "gap junctions" in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of synchrony, within which the contents of

  20. Computational Modeling of Seizure Dynamics Using Coupled Neuronal Networks: Factors Shaping Epileptiform Activity

    PubMed Central

    Naze, Sebastien; Bernard, Christophe; Jirsa, Viktor

    2015-01-01

    Epileptic seizure dynamics span multiple scales in space and time. Understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. Mathematical models have been developed to reproduce seizure dynamics across scales ranging from the single neuron to the neural population. In this study, we develop a network model of spiking neurons and systematically investigate the conditions, under which the network displays the emergent dynamic behaviors known from the Epileptor, which is a well-investigated abstract model of epileptic neural activity. This approach allows us to study the biophysical parameters and variables leading to epileptiform discharges at cellular and network levels. Our network model is composed of two neuronal populations, characterized by fast excitatory bursting neurons and regular spiking inhibitory neurons, embedded in a common extracellular environment represented by a slow variable. By systematically analyzing the parameter landscape offered by the simulation framework, we reproduce typical sequences of neural activity observed during status epilepticus. We find that exogenous fluctuations from extracellular environment and electro-tonic couplings play a major role in the progression of the seizure, which supports previous studies and further validates our model. We also investigate the influence of chemical synaptic coupling in the generation of spontaneous seizure-like events. Our results argue towards a temporal shift of typical spike waves with fast discharges as synaptic strengths are varied. We demonstrate that spike waves, including interictal spikes, are generated primarily by inhibitory neurons, whereas fast discharges during the wave part are due to excitatory neurons. Simulated traces are compared with in vivo experimental data from rodents at different stages of the disorder. We draw the conclusion that slow

  1. A model explaining synchronization of neuron bioelectric frequency under weak alternating low frequency magnetic field

    NASA Astrophysics Data System (ADS)

    del Moral, A.; Azanza, María J.

    2015-03-01

    A biomagnetic-electrical model is presented that explains rather well the experimentally observed synchronization of the bioelectric potential firing rate ("frequency"), f, of single unit neurons of Helix aspersa mollusc under the application of extremely low frequency (ELF) weak alternating (AC) magnetic fields (MF). The proposed model incorporates to our widely experimentally tested model of superdiamagnetism (SD) and Ca2+ Coulomb explosion (CE) from lipid (LP) bilayer membrane (SD-CE model), the electrical quadrupolar long range interaction between the bilayer LP membranes of synchronized neuron pairs, not considered before. The quadrupolar interaction is capable of explaining well the observed synchronization. Actual extension of our SD-CE-model shows that the neuron firing frequency field, B, dependence becomes not modified, but the bioelectric frequency is decreased and its spontaneous temperature, T, dependence is modified. A comparison of the model with synchronization experimental results of pair of neurons under weak (B0 ≅0.2-15 mT) AC-MF of frequency fM=50 Hz is reported. From the deduced size of synchronized LP clusters under B, is suggested the formation of small neuron networks via the membrane lipid correlation.

  2. Neuroanatomical and Functional Characterization of CRF Neurons of the Amygdala using a Novel Transgenic Mouse Model

    PubMed Central

    De Francesco, Pablo N.; Valdivia, Spring; Cabral, Agustina; Reynaldo, Mirta; Raingo, Jesica; Sakata, Ichiro; Osborne-Lawrence, Sherri; Zigman, Jeffrey M.; Perelló, Mario

    2015-01-01

    The corticotrophin releasing factor (CRF)-producing neurons of the amygdala have been implicated in behavioral and physiological responses associated with fear, anxiety, stress, food intake and reward. To overcome the difficulties in identifying CRF neurons within the amygdala, a novel transgenic mouse line, in which the humanized Renilla reniformis green fluorescent protein (hrGFP) is under the control of the CRF promoter (CRF-hrGFP mice), was developed. First, the CRF-hrGFP mouse model was validated and the localization of CRF neurons within the amygdala was systematically mapped. Amygdalar hrGFP-expressing neurons were located primarily in the interstitial nucleus of the posterior limb of the anterior commissure, but also present in the central amygdala. Secondly, the marker of neuronal activation c-Fos was used to explore the response of amygdalar CRF neurons in CRF-hrGFP mice under different experimental paradigms. C-Fos induction was observed in CRF neurons of CRF-hrGFP mice exposed to an acute social defeat stress event, a fasting/refeeding paradigm or LPS administration. In contrast, no c-Fos induction was detected in CRF neurons of CRF-hrGFP mice exposed to restraint stress, forced swimming test, 48 h fasting, acute high fat diet (HFD) consumption, intermittent HFD consumption, ad libitum HFD consumption, HFD withdrawal, conditioned HFD aversion, ghrelin administration or melanocortin 4 receptor agonist administration. Thus, this study fully characterizes the distribution of amygdala CRF neurons in mice and suggests that they are involved in some, but not all, stress or food intake-related behaviors recruiting the amygdala. PMID:25595987

  3. Neuroanatomical and functional characterization of CRF neurons of the amygdala using a novel transgenic mouse model.

    PubMed

    De Francesco, P N; Valdivia, S; Cabral, A; Reynaldo, M; Raingo, J; Sakata, I; Osborne-Lawrence, S; Zigman, J M; Perelló, M

    2015-03-19

    The corticotropin-releasing factor (CRF)-producing neurons of the amygdala have been implicated in behavioral and physiological responses associated with fear, anxiety, stress, food intake and reward. To overcome the difficulties in identifying CRF neurons within the amygdala, a novel transgenic mouse line, in which the humanized recombinant Renilla reniformis green fluorescent protein (hrGFP) is under the control of the CRF promoter (CRF-hrGFP mice), was developed. First, the CRF-hrGFP mouse model was validated and the localization of CRF neurons within the amygdala was systematically mapped. Amygdalar hrGFP-expressing neurons were located primarily in the interstitial nucleus of the posterior limb of the anterior commissure, but also present in the central amygdala. Secondly, the marker of neuronal activation c-Fos was used to explore the response of amygdalar CRF neurons in CRF-hrGFP mice under different experimental paradigms. C-Fos induction was observed in CRF neurons of CRF-hrGFP mice exposed to an acute social defeat stress event, a fasting/refeeding paradigm or lipopolysaccharide (LPS) administration. In contrast, no c-Fos induction was detected in CRF neurons of CRF-hrGFP mice exposed to restraint stress, forced swimming test, 48-h fasting, acute high-fat diet (HFD) consumption, intermittent HFD consumption, ad libitum HFD consumption, HFD withdrawal, conditioned HFD aversion, ghrelin administration or melanocortin 4 receptor agonist administration. Thus, this study fully characterizes the distribution of amygdala CRF neurons in mice and suggests that they are involved in some, but not all, stress or food intake-related behaviors recruiting the amygdala. PMID:25595987

  4. Minocycline reduces neuroinflammation but does not ameliorate neuron loss in a mouse model of neurodegeneration

    PubMed Central

    Cheng, Shanshan; Hou, Jinxing; Zhang, Chen; Xu, Congyu; Wang, Long; Zou, Xiaoxia; Yu, Huahong; Shi, Yun; Yin, Zhenyu; Chen, Guiquan

    2015-01-01

    Minocycline is a broad-spectrum tetracycline antibiotic. A number of preclinical studies have shown that minocycline exhibits neuroprotective effects in various animal models of neurological diseases. However, it remained unknown whether minocycline is effective to prevent neuron loss. To systematically evaluate its effects, minocycline was used to treat Dicer conditional knockout (cKO) mice which display age-related neuron loss. The drug was given to mutant mice prior to the occurrence of neuroinflammation and neurodegeneration, and the treatment had lasted 2 months. Levels of inflammation markers, including glial fibrillary acidic protein (GFAP), ionized calcium-binding adapter molecule1 (Iba1) and interleukin6 (IL6), were significantly reduced in minocycline-treated Dicer cKO mice. In contrast, levels of neuronal markers and the total number of apoptotic cells in Dicer cKO mice were not affected by the drug. In summary, inhibition of neuroinflammation by minocycline is insufficient to prevent neuron loss and apoptosis. PMID:26000566

  5. Restoring the encoding properties of a stochastic neuron model by an exogenous noise

    PubMed Central

    Paffi, Alessandra; Camera, Francesca; Apollonio, Francesca; d'Inzeo, Guglielmo; Liberti, Micaela

    2015-01-01

    Here we evaluate the possibility of improving the encoding properties of an impaired neuronal system by superimposing an exogenous noise to an external electric stimulation signal. The approach is based on the use of mathematical neuron models consisting of stochastic HH-like circuit, where the impairment of the endogenous presynaptic inputs is described as a subthreshold injected current and the exogenous stimulation signal is a sinusoidal voltage perturbation across the membrane. Our results indicate that a correlated Gaussian noise, added to the sinusoidal signal can significantly increase the encoding properties of the impaired system, through the Stochastic Resonance (SR) phenomenon. These results suggest that an exogenous noise, suitably tailored, could improve the efficacy of those stimulation techniques used in neuronal systems, where the presynaptic sensory neurons are impaired and have to be artificially bypassed. PMID:25999845

  6. Modelling the Effects of Electrical Coupling between Unmyelinated Axons of Brainstem Neurons Controlling Rhythmic Activity.

    PubMed

    Hull, Michael J; Soffe, Stephen R; Willshaw, David J; Roberts, Alan

    2015-05-01

    Gap junctions between fine unmyelinated axons can electrically couple groups of brain neurons to synchronise firing and contribute to rhythmic activity. To explore the distribution and significance of electrical coupling, we modelled a well analysed, small population of brainstem neurons which drive swimming in young frog tadpoles. A passive network of 30 multicompartmental neurons with unmyelinated axons was used to infer that: axon-axon gap junctions close to the soma gave the best match to experimentally measured coupling coefficients; axon diameter had a strong influence on coupling; most neurons were coupled indirectly via the axons of other neurons. When active channels were added, gap junctions could make action potential propagation along the thin axons unreliable. Increased sodium and decreased potassium channel densities in the initial axon segment improved action potential propagation. Modelling suggested that the single spike firing to step current injection observed in whole-cell recordings is not a cellular property but a dynamic consequence of shunting resulting from electrical coupling. Without electrical coupling, firing of the population during depolarising current was unsynchronised; with coupling, the population showed synchronous recruitment and rhythmic firing. When activated instead by increasing levels of modelled sensory pathway input, the population without electrical coupling was recruited incrementally to unpatterned activity. However, when coupled, the population was recruited all-or-none at threshold into a rhythmic swimming pattern: the tadpole "decided" to swim. Modelling emphasises uncertainties about fine unmyelinated axon physiology but, when informed by biological data, makes general predictions about gap junctions: locations close to the soma; relatively small numbers; many indirect connections between neurons; cause of action potential propagation failure in fine axons; misleading alteration of intrinsic firing properties

  7. Modelling the acquisition of goal-directed behaviors by populations of neurons.

    PubMed

    Guigon, E; Burnod, Y

    1995-03-01

    Recent neurophysiological studies have revealed the patterns of neuronal activity during the acquisition of goal-directed behaviors, both in single cells, and in large populations of neurons. We propose a model which helps three sets of experimental results in the monkey to be understood: (1) activity of single cells vary greatly and only population activities are causally related to behavior. The model shows how a population of stochastic neurons, whose behaviors vary widely, can learn a skilled conditioned movement with only local activity-dependent synaptic changes. (2) typical changes in neuronal activity occur when the rules governing the behavior are changed, i.e. when the relationship between cues and actions to reach a goal changes over time. There are two types of neuronal patterns during changes in reward contingency: a monotonic increasing pattern and a non-monotonic pattern which follows the change in the way the reward is obtained. Units in the model display these two types of change, which correspond to synaptic modifications related to the encoding of the behavioral significance of sensory and motor events. (3) These two patterns of neuronal activity define two populations whose anatomical distributions in the frontal lobe overlap with a gradient organized in the rostro-caudal direction. The model consists of two artificial neural networks, defined by the same set of equations, but which differ in the values of two parameters (P and Q). P defines the adaptive properties of processing units and Q describes the coding of information. The model suggests that a balance in the relative strengths of these parameters distributed along a rostro-caudal gradient can explain the distribution of neuronal types in the frontal lobe of the monkey. PMID:7622407

  8. Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data.

    PubMed

    Nogaret, Alain; Meliza, C Daniel; Margoliash, Daniel; Abarbanel, Henry D I

    2016-01-01

    We report on the construction of neuron models by assimilating electrophysiological data with large-scale constrained nonlinear optimization. The method implements interior point line parameter search to determine parameters from the responses to intracellular current injections of zebra finch HVC neurons. We incorporated these parameters into a nine ionic channel conductance model to obtain completed models which we then use to predict the state of the neuron under arbitrary current stimulation. Each model was validated by successfully predicting the dynamics of the membrane potential induced by 20-50 different current protocols. The dispersion of parameters extracted from different assimilation windows was studied. Differences in constraints from current protocols, stochastic variability in neuron output, and noise behave as a residual temperature which broadens the global minimum of the objective function to an ellipsoid domain whose principal axes follow an exponentially decaying distribution. The maximum likelihood expectation of extracted parameters was found to provide an excellent approximation of the global minimum and yields highly consistent kinetics for both neurons studied. Large scale assimilation absorbs the intrinsic variability of electrophysiological data over wide assimilation windows. It builds models in an automatic manner treating all data as equal quantities and requiring minimal additional insight. PMID:27605157

  9. Changes in Aβ non-nociceptive primary sensory neurons in a rat model of osteoarthritis pain

    PubMed Central

    2010-01-01

    Background Pain is a major debilitating factor in osteoarthritis (OA), yet few mechanism-based therapies are available. To address the need to understand underlying mechanisms the aim of the present study was to determine changes in sensory neurons in an animal model of OA pain. Results The model displayed typical osteoarthritis pathology characterized by cartilage degeneration in the knee joint and also manifested knee pathophysiology (edema and increased vasculature permeability of the joint) and altered nociception of the affected limb (hind paw tenderness and knee articulation-evoked reduction in the tail flick latency). Neurons included in this report innervated regions throughout the entire hind limb. Aβ-fiber low threshold mechanoreceptors exhibited a slowing of the dynamics of action potential (AP) genesis, including wider AP duration and slower maximum rising rate, and muscle spindle neurons were the most affected subgroup. Only minor AP configuration changes were observed in either C- or Aδ-fiber nociceptors. Conclusion Thus, at one month after induction of the OA model Aβ-fiber low threshold mechanoreceptors but not C- or Aδ-fiber nociceptors had undergone changes in electrophysiological properties. If these changes reflect a change in functional role of these neurons in primary afferent sensory processing, then Aβ-fiber non-nociceptive primary sensory neurons may be involved in the pathogenesis of OA pain. Further, it is important to point out that the patterns of the changes we observed are consistent with observations in models of peripheral neuropathy but not models of peripheral inflammation. PMID:20594346

  10. Mechanism of bistability: Tonic spiking and bursting in a neuron model

    NASA Astrophysics Data System (ADS)

    Shilnikov, Andrey; Calabrese, Ronald L.; Cymbalyuk, Gennady

    2005-05-01

    Neurons can demonstrate various types of activity; tonically spiking, bursting as well as silent neurons are frequently observed in electrophysiological experiments. The methods of qualitative theory of slow-fast systems applied to biophysically realistic neuron models can describe basic scenarios of how these regimes of activity can be generated and transitions between them can be made. Here we demonstrate that a bifurcation of a codimension one can explain a transition between tonic spiking behavior and bursting behavior. Namely, we argue that the Lukyanov-Shilnikov bifurcation of a saddle-node periodic orbit with noncentral homoclinics may initiate a bistability observed in a model of a leech heart interneuron under defined pharmacological conditions. This model can exhibit two coexisting types of oscillations: tonic spiking and bursting, depending on the initial state of the neuron model. Moreover, the neuron model also generates weakly chaotic bursts when a control parameter is close to the bifurcation values that correspond to homoclinic bifurcations of a saddle or a saddle-node periodic orbit.

  11. Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data

    PubMed Central

    Nogaret, Alain; Meliza, C. Daniel; Margoliash, Daniel; Abarbanel, Henry D. I.

    2016-01-01

    We report on the construction of neuron models by assimilating electrophysiological data with large-scale constrained nonlinear optimization. The method implements interior point line parameter search to determine parameters from the responses to intracellular current injections of zebra finch HVC neurons. We incorporated these parameters into a nine ionic channel conductance model to obtain completed models which we then use to predict the state of the neuron under arbitrary current stimulation. Each model was validated by successfully predicting the dynamics of the membrane potential induced by 20–50 different current protocols. The dispersion of parameters extracted from different assimilation windows was studied. Differences in constraints from current protocols, stochastic variability in neuron output, and noise behave as a residual temperature which broadens the global minimum of the objective function to an ellipsoid domain whose principal axes follow an exponentially decaying distribution. The maximum likelihood expectation of extracted parameters was found to provide an excellent approximation of the global minimum and yields highly consistent kinetics for both neurons studied. Large scale assimilation absorbs the intrinsic variability of electrophysiological data over wide assimilation windows. It builds models in an automatic manner treating all data as equal quantities and requiring minimal additional insight. PMID:27605157

  12. Cofilin Inhibition Restores Neuronal Cell Death in Oxygen-Glucose Deprivation Model of Ischemia.

    PubMed

    Madineni, Anusha; Alhadidi, Qasim; Shah, Zahoor A

    2016-03-01

    Ischemia is a condition associated with decreased blood supply to the brain, eventually leading to death of neurons. It is associated with a diverse cascade of responses involving both degenerative and regenerative mechanisms. At the cellular level, the changes are initiated prominently in the neuronal cytoskeleton. Cofilin, a cytoskeletal actin severing protein, is known to be involved in the early stages of apoptotic cell death. Evidence supports its intervention in the progression of disease states like Alzheimer's and ischemic kidney disease. In the present study, we have hypothesized the possible involvement of cofilin in ischemia. Using PC12 cells and mouse primary cultures of cortical neurons, we investigated the potential role of cofilin in ischemia in two different in vitro ischemic models: chemical induced oxidative stress and oxygen-glucose deprivation/reperfusion (OGD/R). The expression profile studies demonstrated a decrease in phosphocofilin levels in all models of ischemia, implying stress-induced cofilin activation. Furthermore, calcineurin and slingshot 1L (SSH) phosphatases were found to be the signaling mediators of the cofilin activation. In primary cultures of cortical neurons, cofilin was found to be significantly activated after 1 h of OGD. To delineate the role of activated cofilin in ischemia, we knocked down cofilin by small interfering RNA (siRNA) technique and tested the impact of cofilin silencing on neuronal viability. Cofilin siRNA-treated neurons showed a significant reduction of cofilin levels in all treatment groups (control, OGD, and OGD/R). Additionally, cofilin siRNA-reduced cofilin mitochondrial translocation and caspase 3 cleavage, with a concomitant increase in neuronal viability. These results strongly support the active role of cofilin in ischemia-induced neuronal degeneration and apoptosis. We believe that targeting this protein mediator has a potential for therapeutic intervention in ischemic brain injury and stroke

  13. Carbon monoxide improves neuronal differentiation and yield by increasing the functioning and number of mitochondria.

    PubMed

    Almeida, Ana S; Sonnewald, Ursula; Alves, Paula M; Vieira, Helena L A

    2016-08-01

    The process of cell differentiation goes hand-in-hand with metabolic adaptations, which are needed to provide energy and new metabolites. Carbon monoxide (CO) is an endogenous cytoprotective molecule able to inhibit cell death and improve mitochondrial metabolism. Neuronal differentiation processes were studied using the NT2 cell line, which is derived from human testicular embryonic teratocarcinoma and differentiates into post-mitotic neurons upon retinoic acid treatment. CO-releasing molecule A1 (CORM-A1) was used do deliver CO into cell culture. CO treatment improved NT2 neuronal differentiation and yield, since there were more neurons and the total cell number increased following the differentiation process. CO supplementation enhanced the mitochondrial population in post-mitotic neurons derived from NT2 cells, as indicated by an increase in mitochondrial DNA. CO treatment during neuronal differentiation increased the extent of the classical metabolic change that occurs during neuronal differentiation, from glycolytic to more oxidative metabolism, by decreasing the ratio of lactate production and glucose consumption. The expression of pyruvate and lactate dehydrogenases was higher, indicating an augmented oxidative metabolism. Moreover, these findings were corroborated by an increased percentage of (13) C incorporation from [U-(13) C]glucose into the tricarboxylic acid cycle metabolites malate and citrate, and also glutamate and aspartate in CO-treated cells. Finally, under low levels of oxygen (5%), which enhances glycolytic metabolism, some of the enhancing effects of CO on mitochondria were not observed. In conclusion, our data show that CO improves neuronal and mitochondrial yield by stimulation of tricarboxylic acid cycle activity, and thus oxidative metabolism of NT2 cells during the process of neuronal differentiation. The process of cell differentiation is coupled with metabolic adaptations. Carbon monoxide (CO) is an endogenous cytoprotective

  14. Nonlinear Dynamic Modeling of Synaptically Driven Single Hippocampal Neuron Intracellular Activity

    PubMed Central

    Song, Dong; Berger, Theodore W.

    2011-01-01

    A high-order nonlinear dynamic model of the input–output properties of single hippocampal CA1 pyramidal neurons was developed based on synaptically driven intracellular activity. The purpose of this study is to construct a model that: 1) can capture the nonlinear dynamics of both subthreshold activities [postsynaptic potentials (PSPs)] and suprathreshold activities (action potentials) in a single formalism; 2) is sufficiently general to be applied to any spike-input and spike-output neurons (point process input and point process output neural systems); and 3) is computationally efficient. The model consisted of three major components: 1) feedforward kernels (up to third order) that transform presynaptic action potentials into PSPs; 2) a constant threshold, above which action potentials are generated; and 3) a feedback kernel (first order) that describes spike-triggered after-potentials. The model was applied to CA1 pyramidal cells, as they were electrically stimulated with broadband Poisson random impulse trains through the Schaffer collaterals. The random impulse trains used here have physiological properties similar to spiking patterns observed in CA3 hippocampal neurons. PSPs and action potentials were recorded from the soma of CA1 pyramidal neurons using whole-cell patch-clamp recording. We evaluated the model performance separately with respect to PSP waveforms and the occurrence of spikes. The average normalized mean square error of PSP prediction is 14.4%. The average spike prediction error rate is 18.8%. In summary, although prediction errors still could be reduced, the model successfully captures the majority of high-order nonlinear dynamics of the single-neuron intracellular activity. The model captures the general biophysical processes with a small set of open parameters that are directly constrained by the intracellular recording, and thus, can be easily applied to any spike-input and spike-output neuron. PMID:21233041

  15. Statistics of a leaky integrate-and-fire model of neurons driven by dichotomous noise

    NASA Astrophysics Data System (ADS)

    Mankin, Romi; Lumi, Neeme

    2016-05-01

    The behavior of a stochastic leaky integrate-and-fire model of neurons is considered. The effect of temporally correlated random neuronal input is modeled as a colored two-level (dichotomous) Markovian noise. Relying on the Riemann method, exact expressions for the output interspike interval density and for the serial correlation coefficient are derived, and their dependence on noise parameters (such as correlation time and amplitude) is analyzed. Particularly, noise-induced sign reversal and a resonancelike amplification of the kurtosis of the interspike interval distribution are established. The features of spike statistics, analytically revealed in our study, are compared with recently obtained results for a perfect integrate-and-fire neuron model.

  16. Emergent Central Pattern Generator Behavior in Gap-Junction-Coupled Hodgkin-Huxley Style Neuron Model

    PubMed Central

    Memelli, Heraldo; Solomon, Irene C.

    2012-01-01

    Most models of central pattern generators (CPGs) involve two distinct nuclei mutually inhibiting one another via synapses. Here, we present a single-nucleus model of biologically realistic Hodgkin-Huxley neurons with random gap junction coupling. Despite no explicit division of neurons into two groups, we observe a spontaneous division of neurons into two distinct firing groups. In addition, we also demonstrate this phenomenon in a simplified version of the model, highlighting the importance of afterhyperpolarization currents (IAHP) to CPGs utilizing gap junction coupling. The properties of these CPGs also appear sensitive to gap junction conductance, probability of gap junction coupling between cells, topology of gap junction coupling, and, to a lesser extent, input current into our simulated nucleus. PMID:23365558

  17. Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models

    PubMed Central

    Hagens, Olivier; Naud, Richard; Koch, Christof; Gerstner, Wulfram

    2015-01-01

    Single-neuron models are useful not only for studying the emergent properties of neural circuits in large-scale simulations, but also for extracting and summarizing in a principled way the information contained in electrophysiological recordings. Here we demonstrate that, using a convex optimization procedure we previously introduced, a Generalized Integrate-and-Fire model can be accurately fitted with a limited amount of data. The model is capable of predicting both the spiking activity and the subthreshold dynamics of different cell types, and can be used for online characterization of neuronal properties. A protocol is proposed that, combined with emergent technologies for automatic patch-clamp recordings, permits automated, in vitro high-throughput characterization of single neurons. PMID:26083597

  18. Mechanism of stochastic resonance enhancement in neuronal models driven by 1/f noise

    NASA Astrophysics Data System (ADS)

    Nozaki, Daichi; Collins, James J.; Yamamoto, Yoshiharu

    1999-10-01

    Noise can assist neurons in the detection of weak signals via a mechanism known as stochastic resonance (SR). In a previous study [Phys. Lett. A 243, 281 (1998)], we showed that when colored noise with 1/fβ spectrum is added to the FitzHugh-Nagumo (FHN) neuronal model, the optimal noise variance for SR could be minimized with β~1. In this study, we investigate analytically how the noise color (β) affects the SR profile in a linearized version of the FHN model. We demonstrate that the aforementioned effect of 1/f noise is related to the dynamical characteristics of the model neuron, i.e., the refractory period, the low-pass filtering effect of the membrane capacitance, and the high-pass filtering effect of the recovery variable.

  19. Use of model organisms for the study of neuronal ceroid lipofuscinosis.

    PubMed

    Bond, Michael; Holthaus, Sophia-Martha Kleine; Tammen, Imke; Tear, Guy; Russell, Claire

    2013-11-01

    Neuronal ceroid lipofuscinoses are a group of fatal progressive neurodegenerative diseases predominantly affecting children. Identification of mutations that cause neuronal ceroid lipofuscinosis, and subsequent functional and pathological studies of the affected genes, underpins efforts to investigate disease mechanisms and identify and test potential therapeutic strategies. These functional studies and pre-clinical trials necessitate the use of model organisms in addition to cell and tissue culture models as they enable the study of protein function within a complex organ such as the brain and the testing of therapies on a whole organism. To this end, a large number of disease models and genetic tools have been identified or created in a variety of model organisms. In this review, we will discuss the ethical issues associated with experiments using model organisms, the factors underlying the choice of model organism, the disease models and genetic tools available, and the contributions of those disease models and tools to neuronal ceroid lipofuscinosis research. This article is part of a Special Issue entitled: The Neuronal Ceroid Lipofuscinoses or Batten Disease. PMID:23338040

  20. Biophysical model for integrating neuronal activity, EEG, fMRI and metabolism.

    PubMed

    Sotero, Roberto C; Trujillo-Barreto, Nelson J

    2008-01-01

    Our goal is to model the coupling between neuronal activity, cerebral metabolic rates of glucose and oxygen consumption, cerebral blood flow (CBF), electroencephalography (EEG) and blood oxygenation level-dependent (BOLD) responses. In order to accomplish this, two previous models are coupled: a metabolic/hemodynamic model (MHM) for a voxel, linking BOLD signals and neuronal activity, and a neural mass model describing the neuronal dynamics within a voxel and its interactions with voxels of the same area (short-range interactions) and other areas (long-range interactions). For coupling both models, we take as the input to the BOLD model, the number of active synapses within the voxel, that is, the average number of synapses that will receive an action potential within the time unit. This is obtained by considering the action potentials transmitted between neuronal populations within the voxel, as well as those arriving from other voxels. Simulations are carried out for testing the integrated model. Results show that realistic evoked potentials (EP) at electrodes on the scalp surface and the corresponding BOLD signals for each voxel are produced by the model. In another simulation, the alpha rhythm was reproduced and reasonable similarities with experimental data were obtained when calculating correlations between BOLD signals and the alpha power curve. The origin of negative BOLD responses and the characteristics of EEG, PET and BOLD signals in Alzheimer's disease were also studied. PMID:17919931

  1. Theoretical Analysis of Transcranial Magneto-Acoustical Stimulation with Hodgkin-Huxley Neuron Model.

    PubMed

    Yuan, Yi; Chen, Yudong; Li, Xiaoli

    2016-01-01

    Transcranial magneto-acoustical stimulation (TMAS) is a novel stimulation technology in which an ultrasonic wave within a magnetostatic field generates an electric current in an area of interest in the brain to modulate neuronal activities. As a key part of the neural network, neurons transmit information in the nervous system. However, the effect of TMAS on the neuronal firing pattern remains unknown. To address this problem, we investigated the stimulatory mechanism of TMAS on neurons, by using a Hodgkin-Huxley neuron model. The simulation results indicated that the magnetostatic field intensity and ultrasonic power affect the amplitude and interspike interval of neuronal action potential under a continuous wave ultrasound. The simulation results also showed that the ultrasonic power, duty cycle and repetition frequency can alter the firing pattern of neural action potential under pulsed wave ultrasound. This study may help to reveal and explain the biological mechanism of TMAS and to provide a theoretical basis for TMAS in the treatment or rehabilitation of neuropsychiatric disorders. PMID:27148032

  2. Neuron-specific antioxidant OXR1 extends survival of a mouse model of amyotrophic lateral sclerosis

    PubMed Central

    Liu, Kevin X.; Edwards, Benjamin; Lee, Sheena; Finelli, Mattéa J.; Davies, Ben

    2015-01-01

    Amyotrophic lateral sclerosis is a devastating neurodegenerative disorder characterized by the progressive loss of spinal motor neurons. While the aetiological mechanisms underlying the disease remain poorly understood, oxidative stress is a central component of amyotrophic lateral sclerosis and contributes to motor neuron injury. Recently, oxidation resistance 1 (OXR1) has emerged as a critical regulator of neuronal survival in response to oxidative stress, and is upregulated in the spinal cord of patients with amyotrophic lateral sclerosis. Here, we tested the hypothesis that OXR1 is a key neuroprotective factor during amyotrophic lateral sclerosis pathogenesis by crossing a new transgenic mouse line that overexpresses OXR1 in neurons with the SOD1G93A mouse model of amyotrophic lateral sclerosis. Interestingly, we report that overexpression of OXR1 significantly extends survival, improves motor deficits, and delays pathology in the spinal cord and in muscles of SOD1G93A mice. Furthermore, we find that overexpression of OXR1 in neurons significantly delays non-cell-autonomous neuroinflammatory response, classic complement system activation, and STAT3 activation through transcriptomic analysis of spinal cords of SOD1G93A mice. Taken together, these data identify OXR1 as the first neuron-specific antioxidant modulator of pathogenesis and disease progression in SOD1-mediated amyotrophic lateral sclerosis, and suggest that OXR1 may serve as a novel target for future therapeutic strategies. PMID:25753484

  3. Loss of Miro1-directed mitochondrial movement results in a novel murine model for neuron disease

    PubMed Central

    Nguyen, Tammy T.; Oh, Sang S.; Weaver, David; Lewandowska, Agnieszka; Maxfield, Dane; Schuler, Max-Hinderk; Smith, Nathan K.; Macfarlane, Jane; Saunders, Gerald; Palmer, Cheryl A.; Debattisti, Valentina; Koshiba, Takumi; Pulst, Stefan; Feldman, Eva L.; Hajnóczky, György; Shaw, Janet M.

    2014-01-01

    Defective mitochondrial distribution in neurons is proposed to cause ATP depletion and calcium-buffering deficiencies that compromise cell function. However, it is unclear whether aberrant mitochondrial motility and distribution alone are sufficient to cause neurological disease. Calcium-binding mitochondrial Rho (Miro) GTPases attach mitochondria to motor proteins for anterograde and retrograde transport in neurons. Using two new KO mouse models, we demonstrate that Miro1 is essential for development of cranial motor nuclei required for respiratory control and maintenance of upper motor neurons required for ambulation. Neuron-specific loss of Miro1 causes depletion of mitochondria from corticospinal tract axons and progressive neurological deficits mirroring human upper motor neuron disease. Although Miro1-deficient neurons exhibit defects in retrograde axonal mitochondrial transport, mitochondrial respiratory function continues. Moreover, Miro1 is not essential for calcium-mediated inhibition of mitochondrial movement or mitochondrial calcium buffering. Our findings indicate that defects in mitochondrial motility and distribution are sufficient to cause neurological disease. PMID:25136135

  4. Loss of Miro1-directed mitochondrial movement results in a novel murine model for neuron disease.

    PubMed

    Nguyen, Tammy T; Oh, Sang S; Weaver, David; Lewandowska, Agnieszka; Maxfield, Dane; Schuler, Max-Hinderk; Smith, Nathan K; Macfarlane, Jane; Saunders, Gerald; Palmer, Cheryl A; Debattisti, Valentina; Koshiba, Takumi; Pulst, Stefan; Feldman, Eva L; Hajnóczky, György; Shaw, Janet M

    2014-09-01

    Defective mitochondrial distribution in neurons is proposed to cause ATP depletion and calcium-buffering deficiencies that compromise cell function. However, it is unclear whether aberrant mitochondrial motility and distribution alone are sufficient to cause neurological disease. Calcium-binding mitochondrial Rho (Miro) GTPases attach mitochondria to motor proteins for anterograde and retrograde transport in neurons. Using two new KO mouse models, we demonstrate that Miro1 is essential for development of cranial motor nuclei required for respiratory control and maintenance of upper motor neurons required for ambulation. Neuron-specific loss of Miro1 causes depletion of mitochondria from corticospinal tract axons and progressive neurological deficits mirroring human upper motor neuron disease. Although Miro1-deficient neurons exhibit defects in retrograde axonal mitochondrial transport, mitochondrial respiratory function continues. Moreover, Miro1 is not essential for calcium-mediated inhibition of mitochondrial movement or mitochondrial calcium buffering. Our findings indicate that defects in mitochondrial motility and distribution are sufficient to cause neurological disease. PMID:25136135

  5. Theoretical Analysis of Transcranial Magneto-Acoustical Stimulation with Hodgkin-Huxley Neuron Model

    PubMed Central

    Yuan, Yi; Chen, Yudong; Li, Xiaoli

    2016-01-01

    Transcranial magneto-acoustical stimulation (TMAS) is a novel stimulation technology in which an ultrasonic wave within a magnetostatic field generates an electric current in an area of interest in the brain to modulate neuronal activities. As a key part of the neural network, neurons transmit information in the nervous system. However, the effect of TMAS on the neuronal firing pattern remains unknown. To address this problem, we investigated the stimulatory mechanism of TMAS on neurons, by using a Hodgkin-Huxley neuron model. The simulation results indicated that the magnetostatic field intensity and ultrasonic power affect the amplitude and interspike interval of neuronal action potential under a continuous wave ultrasound. The simulation results also showed that the ultrasonic power, duty cycle and repetition frequency can alter the firing pattern of neural action potential under pulsed wave ultrasound. This study may help to reveal and explain the biological mechanism of TMAS and to provide a theoretical basis for TMAS in the treatment or rehabilitation of neuropsychiatric disorders. PMID:27148032

  6. Models and simulation of 3D neuronal dendritic trees using Bayesian networks.

    PubMed

    López-Cruz, Pedro L; Bielza, Concha; Larrañaga, Pedro; Benavides-Piccione, Ruth; DeFelipe, Javier

    2011-12-01

    Neuron morphology is crucial for neuronal connectivity and brain information processing. Computational models are important tools for studying dendritic morphology and its role in brain function. We applied a class of probabilistic graphical models called Bayesian networks to generate virtual dendrites from layer III pyramidal neurons from three different regions of the neocortex of the mouse. A set of 41 morphological variables were measured from the 3D reconstructions of real dendrites and their probability distributions used in a machine learning algorithm to induce the model from the data. A simulation algorithm is also proposed to obtain new dendrites by sampling values from Bayesian networks. The main advantage of this approach is that it takes into account and automatically locates the relationships between variables in the data instead of using predefined dependencies. Therefore, the methodology can be applied to any neuronal class while at the same time exploiting class-specific properties. Also, a Bayesian network was defined for each part of the dendrite, allowing the relationships to change in the different sections and to model heterogeneous developmental factors or spatial influences. Several univariate statistical tests and a novel multivariate test based on Kullback-Leibler divergence estimation confirmed that virtual dendrites were similar to real ones. The analyses of the models showed relationships that conform to current neuroanatomical knowledge and support model correctness. At the same time, studying the relationships in the models can help to identify new interactions between variables related to dendritic morphology. PMID:21305364

  7. Computational modeling of direct neuronal recruitment during intracortical microstimulation in somatosensory cortex

    NASA Astrophysics Data System (ADS)

    Overstreet, C. K.; Klein, J. D.; Helms Tillery, S. I.

    2013-12-01

    Objective. Electrical stimulation of cortical tissue could be used to deliver sensory information as part of a neuroprosthetic device, but current control of the location, resolution, quality, and intensity of sensations elicited by intracortical microstimulation (ICMS) remains inadequate for this purpose. One major obstacle to resolving this problem is the poor understanding of the neural activity induced by ICMS. Even with new imaging methods, quantifying the activity of many individual neurons within cortex is difficult. Approach. We used computational modeling to examine the response of somatosensory cortex to ICMS. We modeled the axonal arbors of eight distinct morphologies of interneurons and seven types of pyramidal neurons found in somatosensory cortex and identified their responses to extracellular stimulation. We then combined these axonal elements to form a multi-layered slab of simulated cortex and investigated the patterns of neural activity directly induced by ICMS. Specifically we estimated the number, location, and variety of neurons directly recruited by stimulation on a single penetrating microelectrode. Main results. The population of neurons activated by ICMS was dependent on both stimulation strength and the depth of the electrode within cortex. Strikingly, stimulation recruited interneurons and pyramidal neurons in very different patterns. Interneurons are primarily recruited within a dense, continuous region around the electrode, while pyramidal neurons were recruited in a sparse fashion both near the electrode and up to several millimeters away. Thus ICMS can lead to an unexpectedly complex spatial distribution of firing neurons. Significance. These results lend new insights to the complexity and range of neural activity that can be induced by ICMS. This work also suggests mechanisms potentially responsible for the inconsistency and unnatural quality of sensations initiated by ICMS. Understanding these mechanisms will aid in the design of

  8. Emulating the Visual Receptive Field Properties of MST Neurons with a Template Model of Heading Estimation

    NASA Technical Reports Server (NTRS)

    Perrone, John A.; Stone, Leland S.

    1997-01-01

    We have previously proposed a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. The model detectors were designed to extract self-translation (heading), self-rotation, as well as the scene layout (relative distances) ahead of a moving observer, and are arranged in cortical-like heading maps to perform this function. Heading estimation from optic flow has been postulated by some to be implemented within the medial superior temporal (MST) area. Others have questioned whether MST neurons can fulfill this role because some of their receptive-field properties appear inconsistent with a role in heading estimation. To resolve this issue, we systematically compared MST single-unit responses with the outputs of model detectors under matched stimulus conditions. We found that the basic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support heading estimation and that the template model provides an explicit set of testable hypotheses which can guide future exploration of MST and adjacent areas within the primate superior temporal sulcus.

  9. Transgenic Expression of Glud1 (Glutamate Dehydrogenase 1) in Neurons: In Vivo Model of Enhanced Glutamate Release, Altered Synaptic Plasticity, and Selective Neuronal Vulnerability

    PubMed Central

    Bao, Xiaodong; Pal, Ranu; Hascup, Kevin N.; Wang, Yongfu; Wang, Wen-Tung; Xu, Wenhao; Hui, Dongwei; Agbas, Abdulbaki; Wang, Xinkun; Michaelis, Mary L.; Choi, In-Young; Belousov, Andrei B.; Gerhardt, Greg A.; Michaelis, Elias K.

    2010-01-01

    The effects of lifelong, moderate excess release of glutamate (Glu) in the CNS have not been previously characterized. We created a transgenic (Tg) mouse model of lifelong excess synaptic Glu release in the CNS by introducing the gene for glutamate dehydrogenase 1 (Glud1) under the control of the neuron-specific enolase promoter. Glud1 is, potentially, an important enzyme in the pathway of Glu synthesis in nerve terminals. Increased levels of GLUD protein and activity in CNS neurons of hemizygous Tg mice were associated with increases in the in vivo release of Glu after neuronal depolarization in striatum and in the frequency and amplitude of miniature EPSCs in the CA1 region of the hippocampus. Despite overexpression of Glud1 in all neurons of the CNS, the Tg mice suffered neuronal losses in select brain regions (e.g., the CA1 but not the CA3 region). In vulnerable regions, Tg mice had decreases in MAP2A labeling of dendrites and in synaptophysin labeling of presynaptic terminals; the decreases in neuronal numbers and dendrite and presynaptic terminal labeling increased with advancing age. In addition, the Tg mice exhibited decreases in long-term potentiation of synaptic activity and in spine density in dendrites of CA1 neurons. Behaviorally, the Tg mice were significantly more resistant than wild-type mice to induction and duration of anesthesia produced by anesthetics that suppress Glu neurotransmission. The Glud1 mouse might be a useful model for the effects of lifelong excess synaptic Glu release on CNS neurons and for age-associated neurodegenerative processes. PMID:19890003

  10. Meox2 haploinsufficiency increases neuronal cell loss in a mouse model of Alzheimer's disease.

    PubMed

    Soto, Ileana; Grabowska, Weronika A; Onos, Kristen D; Graham, Leah C; Jackson, Harriet M; Simeone, Stephen N; Howell, Gareth R

    2016-06-01

    Evidence suggests that multiple genetic and environmental factors conspire together to increase susceptibility to Alzheimer's disease (AD). The amyloid cascade hypothesis states that deposition of the amyloid-β (Aβ) peptide is central to AD; however, evidence in humans and animals suggests that Aβ buildup alone is not sufficient to cause neuronal cell loss and cognitive decline. Mouse models that express high levels of mutant forms of amyloid precursor protein and/or cleaving enzymes deposit amyloid but do not show neuron loss. Therefore, a double-hit hypothesis for AD has been proposed whereby vascular dysfunction precedes and promotes Aβ toxicity. In support of this, copy number variations in mesenchyme homeobox 2 (MEOX2), a gene involved in vascular development, are associated with severe forms of AD. However, the role of MEOX2 in AD has not been studied. Here, we tested Meox2 haploinsufficiency in B6.APP/PS1 (B6.APB(Tg)) mice, a mouse model of AD. Despite no overt differences in plaque deposition or glial activation, B6.APB(Tg) mice that carry only one copy of Meox2 (B6.APB(Tg).Mx(-/+)) show increased neuronal cell loss, particularly in regions containing plaques, compared with B6.APB(Tg) mice. Neuronal cell loss corresponds with a significant decrease in plaque-associated microvessels, further supporting a synergistic effect of vascular compromise and amyloid deposition on neuronal cell dysfunction in AD. PMID:27143421

  11. The CNP signal is able to silence a supra threshold neuronal model

    PubMed Central

    Camera, Francesca; Paffi, Alessandra; Thomas, Alex W.; Apollonio, Francesca; D'Inzeo, Guglielmo; Prato, Frank S.; Liberti, Micaela

    2015-01-01

    Several experimental results published in the literature showed that weak pulsed magnetic fields affected the response of the central nervous system. However, the specific biological mechanisms that regulate the observed behaviors are still unclear and further scientific investigation is required. In this work we performed simulations on a neuronal network model exposed to a specific pulsed magnetic field signal that seems to be very effective in modulating the brain activity: the Complex Neuroelectromagnetic Pulse (CNP). Results show that CNP can silence the neurons of a feed-forward network for signal intensities that depend on the strength of the bias current, the endogenous noise level and the specific waveforms of the pulses. Therefore, it is conceivable that a neuronal network model responds to the CNP signal with an inhibition of its activity. Further studies on more realistic neuronal networks are needed to clarify if such an inhibitory effect on neuronal tissue may be the basis of the induced analgesia seen in humans and the antinociceptive effects seen in animals when exposed to the CNP. PMID:25972807

  12. Synaptic potentiation onto habenula neurons in the learned helplessness model of depression.

    PubMed

    Li, Bo; Piriz, Joaquin; Mirrione, Martine; Chung, ChiHye; Proulx, Christophe D; Schulz, Daniela; Henn, Fritz; Malinow, Roberto

    2011-02-24

    The cellular basis of depressive disorders is poorly understood. Recent studies in monkeys indicate that neurons in the lateral habenula (LHb), a nucleus that mediates communication between forebrain and midbrain structures, can increase their activity when an animal fails to receive an expected positive reward or receives a stimulus that predicts aversive conditions (that is, disappointment or anticipation of a negative outcome). LHb neurons project to, and modulate, dopamine-rich regions, such as the ventral tegmental area (VTA), that control reward-seeking behaviour and participate in depressive disorders. Here we show that in two learned helplessness models of depression, excitatory synapses onto LHb neurons projecting to the VTA are potentiated. Synaptic potentiation correlates with an animal's helplessness behaviour and is due to an enhanced presynaptic release probability. Depleting transmitter release by repeated electrical stimulation of LHb afferents, using a protocol that can be effective for patients who are depressed, markedly suppresses synaptic drive onto VTA-projecting LHb neurons in brain slices and can significantly reduce learned helplessness behaviour in rats. Our results indicate that increased presynaptic action onto LHb neurons contributes to the rodent learned helplessness model of depression. PMID:21350486

  13. Synaptic potentiation onto habenula neurons in the learned helplessness model of depression

    SciTech Connect

    Li, B.; Schulz, D.; Li, B; Piriz, J.; Mirrione, M.; Chung, C.H.; Proulx, C.D.; Schulz, D.; Henn, F.; Malinow, R.

    2011-02-24

    The cellular basis of depressive disorders is poorly understood. Recent studies in monkeys indicate that neurons in the lateral habenula (LHb), a nucleus that mediates communication between forebrain and midbrain structures, can increase their activity when an animal fails to receive an expected positive reward or receives a stimulus that predicts aversive conditions (that is, disappointment or anticipation of a negative outcome). LHb neurons project to, and modulate, dopamine-rich regions, such as the ventral tegmental area (VTA), that control reward-seeking behaviour and participate in depressive disorders. Here we show that in two learned helplessness models of depression, excitatory synapses onto LHb neurons projecting to the VTA are potentiated. Synaptic potentiation correlates with an animal's helplessness behaviour and is due to an enhanced presynaptic release probability. Depleting transmitter release by repeated electrical stimulation of LHb afferents, using a protocol that can be effective for patients who are depressed, markedly suppresses synaptic drive onto VTA-projecting LHb neurons in brain slices and can significantly reduce learned helplessness behaviour in rats. Our results indicate that increased presynaptic action onto LHb neurons contributes to the rodent learned helplessness model of depression.

  14. Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim.

    PubMed

    Parasuram, Harilal; Nair, Bipin; D'Angelo, Egidio; Hines, Michael; Naldi, Giovanni; Diwakar, Shyam

    2016-01-01

    Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals. PMID:27445781

  15. Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim

    PubMed Central

    Parasuram, Harilal; Nair, Bipin; D'Angelo, Egidio; Hines, Michael; Naldi, Giovanni; Diwakar, Shyam

    2016-01-01

    Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals. PMID:27445781

  16. A low-dimensional, time-resolved and adapting model neuron.

    PubMed

    Cartling, B

    1996-07-01

    A low-dimensional, time-resolved and adapting model neuron is formulated and evaluated. The model is an extension of the integrate-and-fire type of model with respect to adaptation and of a recent adapting firing-rate model with respect to time-resolution. It is obtained from detailed conductance-based models by a separation of fast and slow ionic processes of action potential generation. The model explicitly includes firing-rate regulation via the slow afterhyperpolarization phase of action potentials, which is controlled by calcium-sensitive potassium channels. It is demonstrated that the model closely reproduces the firing pattern and excitability behaviour of a detailed multicompartment conductance-based model of a neocortical pyramidal cell. The inclusion of adaptation in a model neuron is important for its capability to generate complex dynamics of networks of interconnected neurons. The time-resolution is required for studies of systems in which the temporal aspects of neural coding are important. The simplicity of the model facilitates analytical studies, insight into neurocomputational mechanisms and simulations of large-scale systems. The capability to generate complex network computations may also make the model useful in practical applications of artificial neural networks. PMID:8891839

  17. Evaluation of animal models of obsessive-compulsive disorder: correlation with phasic dopamine neuron activity.

    PubMed

    Sesia, Thibaut; Bizup, Brandon; Grace, Anthony A

    2013-07-01

    Obsessive compulsive disorder (OCD) is a psychiatric condition defined by intrusive thoughts (obsessions) associated with compensatory and repetitive behaviour (compulsions). However, advancement in our understanding of this disorder has been hampered by the absence of effective animal models and correspondingly analysis of the physiological changes that may be present in these models. To address this, we have evaluated two current rodent models of OCD; repeated injection of dopamine D2 agonist quinpirole and repeated adolescent injection of the tricyclic agent clomipramine in combination with a behavioural paradigm designed to produce compulsive lever pressing. These results were then compared with their relative impact on the state of activity of the mesolimbic dopaminergic system using extracellular recoding of spontaneously active dopamine neurons in the ventral tegmental area (VTA). The clomipramine model failed to exacerbate compulsive lever pressing and VTA dopamine neurons in clomipramine-treated rats had mildly diminished bursting activity. In contrast, quinpirole-treated animals showed significant increases in compulsive lever pressing, which was concurrent with a substantial diminution of bursting activity of VTA dopamine neurons. Therefore, VTA dopamine activity correlated with the behavioural response in these models. Taken together, these data support the view that compulsive behaviours likely reflect, at least in part, a disruption of the dopaminergic system, more specifically by a decrease in baseline phasic dopamine signalling mediated by burst firing of dopamine neurons. PMID:23360787

  18. Synergy of AMPA and NMDA Receptor Currents in Dopaminergic Neurons: A Modeling Study.

    PubMed

    Zakharov, Denis; Lapish, Christopher; Gutkin, Boris; Kuznetsov, Alexey

    2016-01-01

    Dopaminergic (DA) neurons display two modes of firing: low-frequency tonic and high-frequency bursts. The high frequency firing within the bursts is attributed to NMDA, but not AMPA receptor activation. In our models of the DA neuron, both biophysical and abstract, the NMDA receptor current can significantly increase their firing frequency, whereas the AMPA receptor current is not able to evoke high-frequency activity and usually suppresses firing. However, both currents are produced by glutamate receptors and, consequently, are often co-activated. Here we consider combined influence of AMPA and NMDA synaptic input in the models of the DA neuron. Different types of neuronal activity (resting state, low frequency, or high frequency firing) are observed depending on the conductance of the AMPAR and NMDAR currents. In two models, biophysical and reduced, we show that the firing frequency increases more effectively if both receptors are co-activated for certain parameter values. In particular, in the more quantitative biophysical model, the maximal frequency is 40% greater than that with NMDAR alone. The dynamical mechanism of such frequency growth is explained in the framework of phase space evolution using the reduced model. In short, both the AMPAR and NMDAR currents flatten the voltage nullcline, providing the frequency increase, whereas only NMDA prevents complete unfolding of the nullcline, providing robust firing. Thus, we confirm a major role of the NMDAR in generating high-frequency firing and conclude that AMPAR activation further significantly increases the frequency. PMID:27252643

  19. Synergy of AMPA and NMDA Receptor Currents in Dopaminergic Neurons: A Modeling Study

    PubMed Central

    Zakharov, Denis; Lapish, Christopher; Gutkin, Boris; Kuznetsov, Alexey

    2016-01-01

    Dopaminergic (DA) neurons display two modes of firing: low-frequency tonic and high-frequency bursts. The high frequency firing within the bursts is attributed to NMDA, but not AMPA receptor activation. In our models of the DA neuron, both biophysical and abstract, the NMDA receptor current can significantly increase their firing frequency, whereas the AMPA receptor current is not able to evoke high-frequency activity and usually suppresses firing. However, both currents are produced by glutamate receptors and, consequently, are often co-activated. Here we consider combined influence of AMPA and NMDA synaptic input in the models of the DA neuron. Different types of neuronal activity (resting state, low frequency, or high frequency firing) are observed depending on the conductance of the AMPAR and NMDAR currents. In two models, biophysical and reduced, we show that the firing frequency increases more effectively if both receptors are co-activated for certain parameter values. In particular, in the more quantitative biophysical model, the maximal frequency is 40% greater than that with NMDAR alone. The dynamical mechanism of such frequency growth is explained in the framework of phase space evolution using the reduced model. In short, both the AMPAR and NMDAR currents flatten the voltage nullcline, providing the frequency increase, whereas only NMDA prevents complete unfolding of the nullcline, providing robust firing. Thus, we confirm a major role of the NMDAR in generating high-frequency firing and conclude that AMPAR activation further significantly increases the frequency. PMID:27252643

  20. Computational and Electronic Analog Implementation of the Hodgkin-Huxley Model of Action Potentials in Neurons

    NASA Astrophysics Data System (ADS)

    Smith, Peter; Link, Justin

    2012-02-01

    Alan Loyd Hodgkin and Andrew Huxley's mathematical model of action potential initiation and propagation in neurons is one of the greatest hallmarks of biophysics. Two techniques for implementing the Hodgkin-Huxley model were explored: computational and electronic analog. Computational modeling was done using NEURON 7.1. NEURON is a free, robust, and relatively user friendly simulation environment that enables quantitatively accurate computational modeling of neurons and neural networks. An analog electronic circuit was built using field-effect transistors (FETs) to simulate the non-linear, voltage-dependent (sodium and potassium) conductances that are responsible for membrane excitability. While the electronic analog qualitatively reproduces many of the key features of the action potential including overall shape, inactivation period, and propagation, it was difficult to quantitatively reproduce the Hodgkin-Huxley model. In addition, while the relative cost to build circuits equivalent to small membrane patches is minimal (˜50), implementation of larger cells or networks would prove uneconomical. Still, both techniques are viable avenues toward introducing interdisciplinary research into either a computational or electronics lab setting at the undergraduate level.

  1. Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons

    PubMed Central

    Griesi-Oliveira, Karina; Acab, Allan; Gupta, Abha R.; Sunaga, Daniele Yumi; Chailangkarn, Thanathom; Nicol, Xavier; Nunez, Yanelli; Walker, Michael F.; Murdoch, John D.; Sanders, Stephan J.; Fernandez, Thomas V.; Ji, Weizhen; Lifton, Richard P.; Vadasz, Estevão; Dietrich, Alexander; Pradhan, Dennis; Song, Hongjun; Ming, Guo-li; Guoe, Xiang; Haddad, Gabriel; Marchetto, Maria C. N.; Spitzer, Nicholas; Passos-Bueno, Maria Rita; State, Matthew W.; Muotri, Alysson R.

    2014-01-01

    An increasing number of genetic variants have been implicated in autism spectrum disorders (ASD), and the functional study of such variants will be critical for the elucidation of autism pathophysiology. Here, we report a de novo balanced translocation disruption of TRPC6, a cation channel, in a non-syndromic autistic individual. Using multiple models, such as dental pulp cells, iPSC-derived neuronal cells and mouse models, we demonstrate that TRPC6 reduction or haploinsufficiency leads to altered neuronal development, morphology, and function. The observed neuronal phenotypes could then be rescued by TRPC6 complementation and by treatment with IGF1 or hyperforin, a TRPC6-specific agonist, suggesting that ASD individuals with alterations in this pathway might benefit from these drugs. We also demonstrate that MeCP2 levels affect TRPC6 expression. Mutations in MeCP2 cause Rett syndrome, revealing common pathways among ASDs. Genetic sequencing of TRPC6 in 1041 ASD individuals and 2872 controls revealed significantly more nonsynonymous mutations in the ASD population, and identified loss-of-function mutations with incomplete penetrance in two patients. Taken together, these findings suggest that TRPC6 is a novel predisposing gene for ASD that may act in a multiple-hit model. This is the first study to use iPSC-derived human neurons to model non-syndromic ASD and illustrate the potential of modeling genetically complex sporadic diseases using such cells. PMID:25385366

  2. microRNA-22 attenuates neuronal cell apoptosis in a cell model of traumatic brain injury

    PubMed Central

    Ma, Ji; Shui, Shaofeng; Han, Xinwei; Guo, Dong; Li, Tengfei; Yan, Lei

    2016-01-01

    Traumatic brain injury (TBI) is a major cause of injury-related deaths, and the mechanism of TBI has become a research focus, but little is known about the mechanism of microRNAs in TBI. The aim of this study is the role of microRNA-22 (miR-22) in TBI-induced neuronal cell apoptosis. Rat cortical neurons were cultured and the TBI model was induced by scratch injury in vitro, before which miR-22 level was altered by transfection of agomir or antagomir. Lactate dehydrogenase (LDH) release and TUNEL assays were performed to examine neuronal cell injury and apoptosis. The activity of caspase 3 (CASP3) and level changes of several apoptosis factors including B-cell lymphoma 2 (BCL2), BCL2-associated X protein (BAX), phosphatase and tensin homolog (PTEN) and v-AKT murine thymoma viral oncogene homolog 1 (AKT1) were detected. Results showed that TBI model cells possessed a downregulated miR-22 level (P < 0.001) and more LDH release and apoptotic cells indicating the aggravated neuronal cell injury and apoptosis induced by TBI. miR-22 agomir attenuated neuronal cell injury and apoptosis of the TBI model. It also caused the corresponding changes in CASP3 activity and other apoptosis factors, with cleaved CASP3, BAX and PTEN inhibited and BCL2 and phosphorylated AKT1 promoted, while miR-22 antagomir had the opposite effects. So miR-22 has neuroprotective roles of attenuating neuronal cell injury and apoptosis induced by TBI, which may be associated with its regulation on apoptosis factors. This study reveals miR-22 as a potential approach to TBI treatment and detailed mechanism remains to be uncovered. PMID:27186313

  3. ACCUMULATION OF METHYLMERCURY OR POLYCHLORINATED BIPHENYLS IN IN VITRO MODELS OF RAT NEURONAL TISSUE.

    EPA Science Inventory

    This manuscript reports data examining the accumulation of PCBs or methylmercury into the tissue of three commonly used in vitro neuronal models.

    ? The results demonstrate that these lipophilic compounds can accumulate to levels 5 to 100 fold higher than the surrounding s...

  4. On modeling the neuronal activity in movement disorder patients by using the Ornstein Uhlenbeck process.

    PubMed

    Shukla, Pitamber; Basu, Ishita; Tuninetti, Daniela; Graupe, Daniel; Slavin, Konstantin V

    2014-01-01

    Mathematical models of the neuronal activity in the affected brain regions of Essential Tremor (ET) and Parkinson's Disease (PD) patients could shed light into the underlying pathophysiology of these diseases, which in turn could help develop personalized treatments including adaptive Deep Brain Stimulation (DBS). In this paper, we use an Ornstein Uhlenbeck Process (OUP) to model the neuronal spiking activity recorded from the brain of ET and PD patients during DBS stereotactic surgery. The parameters of the OUP are estimated based on Inter Spike Interval (ISI) measurements, i.e., the time interval between two consecutive neuronal firings, by means of the Fortet Integral Equation (FIE). The OUP model parameters identified with the FIE method (OUP-FIE) are then used to simulate the ISI distribution resulting from the OUP. Other widely used neuronal activity models, such as the Poisson Process (PP), the Brownian Motion (BM), and the OUP whose parameters are extracted by matching the first two moments of the ISI (OUP-MOM), are also considered. To quantify how close the simulated ISI distribution is to the measured ISI distribution, the Integral Square Error (ISE) criterion is adopted. Amongst all considered stochastic processes, the ISI distribution generated by the OUP-FIE method is shown to produce the least ISE. Finally, a directional Wilcoxon signed rank test is used to show statistically significant reduction in the ISE value obtained from the OUP-FIE compared to the other stochastic processes. PMID:25570525

  5. A stochastic neuronal model predicts random search behaviors at multiple spatial scales in C. elegans

    PubMed Central

    Roberts, William M; Augustine, Steven B; Lawton, Kristy J; Lindsay, Theodore H; Thiele, Tod R; Izquierdo, Eduardo J; Faumont, Serge; Lindsay, Rebecca A; Britton, Matthew Cale; Pokala, Navin; Bargmann, Cornelia I; Lockery, Shawn R

    2016-01-01

    Random search is a behavioral strategy used by organisms from bacteria to humans to locate food that is randomly distributed and undetectable at a distance. We investigated this behavior in the nematode Caenorhabditis elegans, an organism with a small, well-described nervous system. Here we formulate a mathematical model of random search abstracted from the C. elegans connectome and fit to a large-scale kinematic analysis of C. elegans behavior at submicron resolution. The model predicts behavioral effects of neuronal ablations and genetic perturbations, as well as unexpected aspects of wild type behavior. The predictive success of the model indicates that random search in C. elegans can be understood in terms of a neuronal flip-flop circuit involving reciprocal inhibition between two populations of stochastic neurons. Our findings establish a unified theoretical framework for understanding C. elegans locomotion and a testable neuronal model of random search that can be applied to other organisms. DOI: http://dx.doi.org/10.7554/eLife.12572.001 PMID:26824391

  6. A mathematical model of adult GnRH neurons in mouse brain and its bifurcation analysis.

    PubMed

    Duan, Wen; Lee, Kiho; Herbison, Allan E; Sneyd, James

    2011-05-01

    GnRH neurons are hypothalamic neurons that secrete gonadotropin-releasing hormone (GnRH) which stimulates the release of gonadotropins, one of the crucial hormones for sexual development, fertility and maturation. A mathematical model was built to help elucidate the mechanisms underlying electrical bursting and synchronous [Ca²(+)] transients in GnRH neurons (Lee et al., 2010). The model predicted that bursting in GnRH neurons (at least of the short-bursting type) requires the existence of a [Ca²(+)]-dependent slow after-hyperpolarisation current (sI(AHP-UCL)), and this predicted current was found experimentally. GnRH behaviour under a wide range of conditions (inhibition of Na(+) channels, IP₃ receptors, [Ca²(+)]-dependent K(+) channels, or Ca²(+) pumps, or in the presence of zero extracellular [Ca²(+)]) is successfully reproduced by the model. In this paper, a simplified version of the previous model, with the same qualitative behaviour, is constructed and studied using timescale separation techniques and bifurcation analysis. PMID:21300070

  7. Stochastic Wilson-Cowan models of neuronal network dynamics with memory and delay

    NASA Astrophysics Data System (ADS)

    Goychuk, Igor; Goychuk, Andriy

    2015-04-01

    We consider a simple Markovian class of the stochastic Wilson-Cowan type models of neuronal network dynamics, which incorporates stochastic delay caused by the existence of a refractory period of neurons. From the point of view of the dynamics of the individual elements, we are dealing with a network of non-Markovian stochastic two-state oscillators with memory, which are coupled globally in a mean-field fashion. This interrelation of a higher-dimensional Markovian and lower-dimensional non-Markovian dynamics is discussed in its relevance to the general problem of the network dynamics of complex elements possessing memory. The simplest model of this class is provided by a three-state Markovian neuron with one refractory state, which causes firing delay with an exponentially decaying memory within the two-state reduced model. This basic model is used to study critical avalanche dynamics (the noise sustained criticality) in a balanced feedforward network consisting of the excitatory and inhibitory neurons. Such avalanches emerge due to the network size dependent noise (mesoscopic noise). Numerical simulations reveal an intermediate power law in the distribution of avalanche sizes with the critical exponent around -1.16. We show that this power law is robust upon a variation of the refractory time over several orders of magnitude. However, the avalanche time distribution is biexponential. It does not reflect any genuine power law dependence.

  8. Modeling the Formation Process of Grouping Stimuli Sets through Cortical Columns and Microcircuits to Feature Neurons

    PubMed Central

    Williamson, Adam

    2013-01-01

    A computational model of a self-structuring neuronal net is presented in which repetitively applied pattern sets induce the formation of cortical columns and microcircuits which decode distinct patterns after a learning phase. In a case study, it is demonstrated how specific neurons in a feature classifier layer become orientation selective if they receive bar patterns of different slopes from an input layer. The input layer is mapped and intertwined by self-evolving neuronal microcircuits to the feature classifier layer. In this topical overview, several models are discussed which indicate that the net formation converges in its functionality to a mathematical transform which maps the input pattern space to a feature representing output space. The self-learning of the mathematical transform is discussed and its implications are interpreted. Model assumptions are deduced which serve as a guide to apply model derived repetitive stimuli pattern sets to in vitro cultures of neuron ensembles to condition them to learn and execute a mathematical transform. PMID:24369455

  9. On the dynamical mechanisms of influence of synaptic currents on the neuron model with response differentiation

    NASA Astrophysics Data System (ADS)

    Zakharov, D. G.; Kuznetsov, A. S.

    2015-08-01

    The combined effect of synaptic NMDA, AMPA, and GABA currents on the neuron model with response differentiation has been considered. It has been shown that the GABA and NMDA currents can compensate the effects of each other, whereas the AMPA current not only leads to the suppression of oscillations but also significantly amplifies the high-frequency activity of the neuron induced by the NMDA current. Two bifurcation scenarios underlying these effects have been revealed. It has been predicted which scenario takes place under the combined influence of all three currents.

  10. Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling.

    PubMed

    de Santos-Sierra, Daniel; Sendiña-Nadal, Irene; Leyva, Inmaculada; Almendral, Juan A; Ayali, Amir; Anava, Sarit; Sánchez-Ávila, Carmen; Boccaletti, Stefano

    2015-06-01

    Large scale phase-contrast images taken at high resolution through the life of a cultured neuronal network are analyzed by a graph-based unsupervised segmentation algorithm with a very low computational cost, scaling linearly with the image size. The processing automatically retrieves the whole network structure, an object whose mathematical representation is a matrix in which nodes are identified neurons or neurons' clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocytochemistry techniques, our non invasive measures entitle us to perform a longitudinal analysis during the maturation of a single culture. Such an analysis furnishes the way of individuating the main physical processes underlying the self-organization of the neurons' ensemble into a complex network, and drives the formulation of a phenomenological model yet able to describe qualitatively the overall scenario observed during the culture growth. PMID:25393432

  11. Persistent neuronal Ube3a expression in the suprachiasmatic nucleus of Angelman syndrome model mice.

    PubMed

    Jones, Kelly A; Han, Ji Eun; DeBruyne, Jason P; Philpot, Benjamin D

    2016-01-01

    Mutations or deletions of the maternal allele of the UBE3A gene cause Angelman syndrome (AS), a severe neurodevelopmental disorder. The paternal UBE3A/Ube3a allele becomes epigenetically silenced in most neurons during postnatal development in humans and mice; hence, loss of the maternal allele largely eliminates neuronal expression of UBE3A protein. However, recent studies suggest that paternal Ube3a may escape silencing in certain neuron populations, allowing for persistent expression of paternal UBE3A protein. Here we extend evidence in AS model mice (Ube3a(m-/p+)) of paternal UBE3A expression within the suprachiasmatic nucleus (SCN), the master circadian pacemaker. Paternal UBE3A-positive cells in the SCN show partial colocalization with the neuropeptide arginine vasopressin (AVP) and clock proteins (PER2 and BMAL1), supporting that paternal UBE3A expression in the SCN is often of neuronal origin. Paternal UBE3A also partially colocalizes with a marker of neural progenitors, SOX2, implying that relaxed or incomplete imprinting of paternal Ube3a reflects an overall immature molecular phenotype. Our findings highlight the complexity of Ube3a imprinting in the brain and illuminate a subpopulation of SCN neurons as a focal point for future studies aimed at understanding the mechanisms of Ube3a imprinting. PMID:27306933

  12. Neuronal and astrocytic metabolism in a transgenic rat model of Alzheimer's disease

    PubMed Central

    Nilsen, Linn Hege; Witter, Menno P; Sonnewald, Ursula

    2014-01-01

    Regional hypometabolism of glucose in the brain is a hallmark of Alzheimer's disease (AD). However, little is known about the specific alterations of neuronal and astrocytic metabolism involved in homeostasis of glutamate and GABA in AD. Here, we investigated the effects of amyloid β (Aβ) pathology on neuronal and astrocytic metabolism and glial-neuronal interactions in amino acid neurotransmitter homeostasis in the transgenic McGill-R-Thy1-APP rat model of AD compared with healthy controls at age 15 months. Rats were injected with [1-13C]glucose and [1,2-13C]acetate, and extracts of the hippocampal formation as well as several cortical regions were analyzed using 1H- and 13C nuclear magnetic resonance spectroscopy and high-performance liquid chromatography. Reduced tricarboxylic acid cycle turnover was evident for glutamatergic and GABAergic neurons in hippocampal formation and frontal cortex, and for astrocytes in frontal cortex. Pyruvate carboxylation, which is necessary for de novo synthesis of amino acids, was decreased and affected the level of glutamine in hippocampal formation and those of glutamate, glutamine, GABA, and aspartate in the retrosplenial/cingulate cortex. Metabolic alterations were also detected in the entorhinal cortex. Overall, perturbations in energy- and neurotransmitter homeostasis, mitochondrial astrocytic and neuronal metabolism, and aspects of the glutamate–glutamine cycle were found in McGill-R-Thy1-APP rats. PMID:24594625

  13. Persistent neuronal Ube3a expression in the suprachiasmatic nucleus of Angelman syndrome model mice

    PubMed Central

    Jones, Kelly A.; Han, Ji Eun; DeBruyne, Jason P.; Philpot, Benjamin D.

    2016-01-01

    Mutations or deletions of the maternal allele of the UBE3A gene cause Angelman syndrome (AS), a severe neurodevelopmental disorder. The paternal UBE3A/Ube3a allele becomes epigenetically silenced in most neurons during postnatal development in humans and mice; hence, loss of the maternal allele largely eliminates neuronal expression of UBE3A protein. However, recent studies suggest that paternal Ube3a may escape silencing in certain neuron populations, allowing for persistent expression of paternal UBE3A protein. Here we extend evidence in AS model mice (Ube3am–/p+) of paternal UBE3A expression within the suprachiasmatic nucleus (SCN), the master circadian pacemaker. Paternal UBE3A-positive cells in the SCN show partial colocalization with the neuropeptide arginine vasopressin (AVP) and clock proteins (PER2 and BMAL1), supporting that paternal UBE3A expression in the SCN is often of neuronal origin. Paternal UBE3A also partially colocalizes with a marker of neural progenitors, SOX2, implying that relaxed or incomplete imprinting of paternal Ube3a reflects an overall immature molecular phenotype. Our findings highlight the complexity of Ube3a imprinting in the brain and illuminate a subpopulation of SCN neurons as a focal point for future studies aimed at understanding the mechanisms of Ube3a imprinting. PMID:27306933

  14. Emergent spindle oscillations and intermittent burst firing in a thalamic model: specific neuronal mechanisms.

    PubMed Central

    Wang, X J; Golomb, D; Rinzel, J

    1995-01-01

    The rhythmogenesis of 10-Hz sleep spindles is studied in a large-scale thalamic network model with two cell populations: the excitatory thalamocortical (TC) relay neurons and the inhibitory nucleus reticularis thalami (RE) neurons. Spindle-like bursting oscillations emerge naturally from reciprocal interactions between TC and RE neurons. We find that the network oscillations can be synchronized coherently, even though the RE-TC connections are random and sparse, and even though individual neurons fire rebound bursts intermittently in time. When the fast gamma-aminobutyrate type A synaptic inhibition is blocked, synchronous slow oscillations resembling absence seizures are observed. Near-maximal network synchrony is established with even modest convergence in the RE-to-TC projection (as few as 5-10 RE inputs per TC cell suffice). The hyperpolarization-activated cation current (Ih) is found to provide a cellular basis for the intermittency of rebound bursting that is commonly observed in TC neurons during spindles. Such synchronous oscillations with intermittency can be maintained only with a significant degree of convergence for the TC-to-RE projection. PMID:7777551

  15. Degeneration in Arousal Neurons in Chronic Sleep Disruption Modeling Sleep Apnea

    PubMed Central

    Zhu, Yan; Fenik, Polina; Zhan, Guanxia; Xin, Ryan; Veasey, Sigrid C.

    2015-01-01

    Chronic sleep disruption (CSD) is a cardinal feature of sleep apnea that predicts impaired wakefulness. Despite effective treatment of apneas and sleep disruption, patients with sleep apnea may have persistent somnolence. Lasting wake disturbances in treated sleep apnea raise the possibility that CSD may induce sufficient degeneration in wake-activated neurons (WAN) to cause irreversible wake impairments. Implementing a stereological approach in a murine model of CSD, we found reduced neuronal counts in representative WAN groups, locus coeruleus (LC) and orexinergic neurons, reduced by 50 and 25%, respectively. Mice exposed to CSD showed shortened sleep latencies lasting at least 4 weeks into recovery from CSD. As CSD results in frequent activation of WAN, we hypothesized that CSD promotes mitochondrial metabolic stress in WAN. In support, CSD increased lipofuscin within select WAN. Further, examining the LC as a representative WAN nucleus, we observed increased mitochondrial protein acetylation and down-regulation of anti-oxidant enzyme and brain-derived neurotrophic factor mRNA. Remarkably, CSD markedly increased tumor necrosis factor-alpha within WAN, and not in adjacent neurons or glia. Thus, CSD, as observed in sleep apnea, results in a composite of lasting wake impairments, loss of select neurons, a pro-inflammatory, pro-oxidative mitochondrial stress response in WAN, consistent with a degenerative process with behavioral consequences. PMID:26074865

  16. Progression of Neuronal Damage in an In Vitro Model of the Ischemic Penumbra

    PubMed Central

    le Feber, Joost; Tzafi Pavlidou, Stelina; Erkamp, Niels; van Putten, Michel J. A. M.; Hofmeijer, Jeannette

    2016-01-01

    Improvement of neuronal recovery in the ischemic penumbra around a brain infarct has a large potential to advance clinical recovery of patients with acute ischemic stroke. However, pathophysiological mechanisms leading to either recovery or secondary damage in the penumbra are not completely understood. We studied neuronal dynamics in a model system of the penumbra consisting of networks of cultured cortical neurons exposed to controlled levels and durations of hypoxia. Short periods of hypoxia (pO2≈20mmHg) reduced spontaneous activity, due to impeded synaptic function. After ≈6 hours, activity and connectivity partially recovered, even during continuing hypoxia. If the oxygen supply was restored within 12 hours, changes in network connectivity were completely reversible. For longer periods of hypoxia (12–30 h), activity levels initially increased, but eventually decreased and connectivity changes became partially irreversible. After ≈30 hours, all functional connections disappeared and no activity remained. Since this complete silence seemed unrelated to hypoxic depths, but always followed an extended period of low activity, we speculate that irreversible damage (at least partly) results from insufficient neuronal activation. This opens avenues for therapies to improve recovery by neuronal activation. PMID:26871437

  17. Oral Resveratrol Reduces Neuronal Damage in a Model of Multiple Sclerosis

    PubMed Central

    Shindler, Kenneth S.; Ventura, Elvira; Dutt, Mahasweta; Elliott, Peter; Fitzgerald, Denise C.; Rostami, Abdolmohamad

    2012-01-01

    Background Neuronal loss in multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE), correlates with permanent neurological dysfunction. Current MS therapies have limited ability to prevent neuronal damage. Methods We examined whether oral therapy with SRT501, a pharmaceutical-grade formulation of resveratrol, reduces neuronal loss during relapsing/remitting EAE. Resveratrol activates SIRT1, an NAD+-dependent deacetylase that promotes mitochondrial function. Results Oral SRT501 prevented neuronal loss during optic neuritis, an inflammatory optic nerve lesion in MS and EAE. SRT501 also suppressed neurological dysfunction during EAE remission, and spinal cords from SRT501-treated mice had significantly higher axonal density than vehicle-treated mice. Similar neuroprotection was mediated by SRT1720, another SIRT1-activating compound; and sirtinol, a SIRT1 inhibitor, attenuated SRT501 neuroprotective effects. SIRT1 activators did not prevent inflammation. Conclusions These studies demonstrate SRT501 attenuates neuronal damage and neurological dysfunction in EAE by a mechanism involving SIRT1 activation. SIRT1 activators are a potential oral therapy in MS. PMID:21107122

  18. Genetic manipulation of adult-born hippocampal neurons rescues memory in a mouse model of Alzheimer's disease.

    PubMed

    Richetin, Kevin; Leclerc, Clémence; Toni, Nicolas; Gallopin, Thierry; Pech, Stéphane; Roybon, Laurent; Rampon, Claire

    2015-02-01

    In adult mammals, neural progenitors located in the dentate gyrus retain their ability to generate neurons and glia throughout lifetime. In rodents, increased production of new granule neurons is associated with improved memory capacities, while decreased hippocampal neurogenesis results in impaired memory performance in several memory tasks. In mouse models of Alzheimer's disease, neurogenesis is impaired and the granule neurons that are generated fail to integrate existing networks. Thus, enhancing neurogenesis should improve functional plasticity in the hippocampus and restore cognitive deficits in these mice. Here, we performed a screen of transcription factors that could potentially enhance adult hippocampal neurogenesis. We identified Neurod1 as a robust neuronal determinant with the capability to direct hippocampal progenitors towards an exclusive granule neuron fate. Importantly, Neurod1 also accelerated neuronal maturation and functional integration of new neurons during the period of their maturation when they contribute to memory processes. When tested in an APPxPS1 mouse model of Alzheimer's disease, directed expression of Neurod1 in cycling hippocampal progenitors conspicuously reduced dendritic spine density deficits on new hippocampal neurons, to the same level as that observed in healthy age-matched control animals. Remarkably, this population of highly connected new neurons was sufficient to restore spatial memory in these diseased mice. Collectively our findings demonstrate that endogenous neural stem cells of the diseased brain can be manipulated to become new neurons that could allow cognitive improvement. PMID:25518958

  19. Predicting every spike: a model for the responses of visual neurons.

    PubMed

    Keat, J; Reinagel, P; Reid, R C; Meister, M

    2001-06-01

    In the early visual system, neuronal responses can be extremely precise. Under a wide range of stimuli, cells in the retina and thalamus fire spikes very reproducibly, often with millisecond precision on subsequent stimulus repeats. Here we develop a mathematical description of the firing process that, given the recent visual input, accurately predicts the timing of individual spikes. The formalism is successful in matching the spike trains from retinal ganglion cells in salamander, rabbit, and cat, as well as from lateral geniculate nucleus neurons in cat. It adapts to many different response types, from very precise to highly variable. The accuracy of the model allows a compact description of how these neurons encode the visual stimulus. PMID:11430813

  20. Effects of neuronal loss in the dynamic model of neural networks

    NASA Astrophysics Data System (ADS)

    Yoon, B.-G.; Choi, J.; Choi, M. Y.

    2008-09-01

    We study the phase transitions and dynamic behavior of the dynamic model of neural networks, with an emphasis on the effects of neuronal loss due to external stress. In the absence of loss the overall results obtained numerically are found to agree excellently with the theoretical ones. When the external stress is turned on, some neurons may deteriorate and die; such loss of neurons, in general, weakens the memory in the system. As the loss increases beyond a critical value, the order parameter measuring the strength of memory decreases to zero either continuously or discontinuously, namely, the system loses its memory via a second- or a first-order transition, depending on the ratio of the refractory period to the duration of action potential.

  1. Development of modified cable models to simulate accurate neuronal active behaviors

    PubMed Central

    2014-01-01

    In large network and single three-dimensional (3-D) neuron simulations, high computing speed dictates using reduced cable models to simulate neuronal firing behaviors. However, these models are unwarranted under active conditions and lack accurate representation of dendritic active conductances that greatly shape neuronal firing. Here, realistic 3-D (R3D) models (which contain full anatomical details of dendrites) of spinal motoneurons were systematically compared with their reduced single unbranched cable (SUC, which reduces the dendrites to a single electrically equivalent cable) counterpart under passive and active conditions. The SUC models matched the R3D model's passive properties but failed to match key active properties, especially active behaviors originating from dendrites. For instance, persistent inward currents (PIC) hysteresis, frequency-current (FI) relationship secondary range slope, firing hysteresis, plateau potential partial deactivation, staircase currents, synaptic current transfer ratio, and regional FI relationships were not accurately reproduced by the SUC models. The dendritic morphology oversimplification and lack of dendritic active conductances spatial segregation in the SUC models caused significant underestimation of those behaviors. Next, SUC models were modified by adding key branching features in an attempt to restore their active behaviors. The addition of primary dendritic branching only partially restored some active behaviors, whereas the addition of secondary dendritic branching restored most behaviors. Importantly, the proposed modified models successfully replicated the active properties without sacrificing model simplicity, making them attractive candidates for running R3D single neuron and network simulations with accurate firing behaviors. The present results indicate that using reduced models to examine PIC behaviors in spinal motoneurons is unwarranted. PMID:25277743

  2. A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models.

    PubMed

    Lansky, Petr; Ditlevsen, Susanne

    2008-11-01

    Parameters in diffusion neuronal models are divided into two groups; intrinsic and input parameters. Intrinsic parameters are related to the properties of the neuronal membrane and are assumed to be known throughout the paper. Input parameters characterize processes generated outside the neuron and methods for their estimation are reviewed here. Two examples of the diffusion neuronal model, which are based on the integrate-and-fire concept, are investigated--the Ornstein--Uhlenbeck model as the most common one and the Feller model as an illustration of state-dependent behavior in modeling the neuronal input. Two types of experimental data are assumed-intracellular describing the membrane trajectories and extracellular resulting in knowledge of the interspike intervals. The literature on estimation from the trajectories of the diffusion process is extensive and thus the stress in this review is set on the inference made from the interspike intervals. PMID:18496710

  3. A model for the polarization of neurons by extrinsically applied electric fields.

    PubMed Central

    Tranchina, D; Nicholson, C

    1986-01-01

    A model is presented for the subthreshold polarization of a neuron by an applied electric field. It gives insight into how morphological features of a neuron affect its polarizability. The neuronal model consists of one or more extensively branched dendritic trees, a lumped somatic impedance, and a myelinated axon with nodes of Ranvier. The dendritic trees branch according to the 3/2-power rule of Rall, so that each tree has an equivalent cylinder representation. Equations for the membrane potential at the soma and at the nodes of Ranvier, given an arbitrary specified external potential, are derived. The solutions determine the contributions made by the dendritic tree and the axon to the net polarization at the soma. In the case of a spatially constant electric field, both the magnitude and sign of the polarization depend on simple combinations of parameters describing the neuron. One important combination is given by the ratio of internal resistances for longitudinal current spread along the dendritic tree trunk and along the axon. A second is given by the ratio between the DC space constant for the dendritic tree trunk and the distance between nodes of Ranvier in the axon. A third is given by the product of the electric field and the space constant for the trunk of the dendritic tree. When a neuron with a straight axon is subjected to a constant field, the membrane potential decays exponentially with distance from the soma. Thus, the soma seems to be a likely site for action potential initiation when the field is strong enough to elicit suprathreshold polarization. In a simple example, the way in which orientation of the various parts of the neuron affects its polarization is examined. When an axon with a bend is subjected to a spatially constant field, polarization is focused at the bend, and this is another likely site for action potential initiation. PMID:3801574

  4. Lateral Information Processing by Spiking Neurons: A Theoretical Model of the Neural Correlate of Consciousness

    PubMed Central

    Ebner, Marc; Hameroff, Stuart

    2011-01-01

    Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on “autopilot”). Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the “conscious pilot”) suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious “auto-pilot” cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways “gap junctions” in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of synchrony, within which

  5. Extracellular biosynthesis of zinc oxide nanoparticles using Rhodococcus pyridinivorans NT2: multifunctional textile finishing, biosafety evaluation and in vitro drug delivery in colon carcinoma.

    PubMed

    Kundu, Debasree; Hazra, Chinmay; Chatterjee, Aniruddha; Chaudhari, Ambalal; Mishra, Satyendra

    2014-11-01

    In this study, zinc oxide (ZnO) nanoparticles (NPs) were rapidly synthesized from zinc sulfate solution at room temperature using a metabolically versatile actinobacteria Rhodococcus pyridinivorans NT2. The morphology, structure and stability of the synthesized ZnO NPs were studied using UV-visible absorption spectroscopy, X-ray Diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, field emission scanning electron microscopy (FESEM) with energy dispersive spectroscopy (EDS), transmission electron microscopy (TEM), Zeta potential, and thermogravimetry. The data indicated that the synthesized nanoparticles were moderately stable, hexagonal phase, roughly spherical with average particle diameter in the range of 100-120 nm. Results obtained on examination of protein expression revealed that cell enzymes and extracellular protein systems of Rhodococcus sp. may take part in synthesis process. Furthermore, the ZnO NPs were coated onto textile fabrics to enhance UV-blocking, self-cleaning and antibacterial properties. Ultraviolet protecting factor (UPF) indicating UV-blocking properties of ZnO NPs coated textile fabrics were determined as 65, 88, 121, 172 and 241 for 1, 2, 3, 4 and 5 gm(-2) of ZnO NPs, respectively. Besides, self-cleaning activity was assessed by investigating photocatalytic activity on malachite green as well as antibacterial activity against aerobic Gram-positive Staphylococcus epidermidis NCIM 2493 (ATCC 12228). The antibacterial effects of these textiles were evaluated using ISO 20743 standard. In addition, ZnO NPs exhibited a preferential ability to kill HT-29 cancerous cells as compared with normal peripheral blood mononuclear cells (PBMCs). PMID:25169770

  6. An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites

    PubMed Central

    JADI, MONIKA P.; BEHABADI, BARDIA F.; POLEG-POLSKY, ALON; SCHILLER, JACKIE; MEL, BARTLETT W.

    2014-01-01

    In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based “technology” that underlies the brain’s remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or “neuron,” yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees. PMID:25554708

  7. Silibinin prevents dopaminergic neuronal loss in a mouse model of Parkinson's disease via mitochondrial stabilization.

    PubMed

    Lee, Yujeong; Park, Hee Ra; Chun, Hye Jeong; Lee, Jaewon

    2015-05-01

    Parkinson's disease (PD) is a progressive neurodegenerative disease characterized by the selective loss of dopaminergic neurons in the nigrostriatal pathway. The lipophile 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) can cross the blood-brain barrier and is subsequently metabolized into toxic1-methyl-4-phenylpyridine (MPP(+) ), which causes mitochondrial dysfunction and the selective cell death of dopaminergic neurons. The present article reports the neuroprotective effects of silibinin in a murine MPTP model of PD. The flavonoid silibinin is the major active constituent of silymarin, an extract of milk thistle seeds, and is known to have hepatoprotective, anticancer, antioxidative, and neuroprotective effects. In the present study, silibinin effectively attenuated motor deficit and dopaminergic neuronal loss caused by MPTP. Furthermore, in vitro study confirmed that silibinin protects primary cultured neurons against MPP(+) -induced cell death and mitochondrial membrane disruption. The findings of the present study indicate that silibinin has neuroprotective effects in MPTP-induced models of PD rather than antioxidative or anti-inflammatory effects and that the neuroprotection afforded might be mediated by the stabilization of mitochondrial membrane potential. Furthermore, these findings suggest that silibinin protects mitochondria in MPTP-induced PD models and that it offers a starting point for the development of treatments that ameliorate the symptoms of PD. PMID:25677261

  8. Brain lactate kinetics: Modeling evidence for neuronal lactate uptake upon activation.

    PubMed

    Aubert, Agnès; Costalat, Robert; Magistretti, Pierre J; Pellerin, Luc

    2005-11-01

    A critical issue in brain energy metabolism is whether lactate produced within the brain by astrocytes is taken up and metabolized by neurons upon activation. Although there is ample evidence that neurons can efficiently use lactate as an energy substrate, at least in vitro, few experimental data exist to indicate that it is indeed the case in vivo. To address this question, we used a modeling approach to determine which mechanisms are necessary to explain typical brain lactate kinetics observed upon activation. On the basis of a previously validated model that takes into account the compartmentalization of energy metabolism, we developed a mathematical model of brain lactate kinetics, which was applied to published data describing the changes in extracellular lactate levels upon activation. Results show that the initial dip in the extracellular lactate concentration observed at the onset of stimulation can only be satisfactorily explained by a rapid uptake within an intraparenchymal cellular compartment. In contrast, neither blood flow increase, nor extracellular pH variation can be major causes of the lactate initial dip, whereas tissue lactate diffusion only tends to reduce its amplitude. The kinetic properties of monocarboxylate transporter isoforms strongly suggest that neurons represent the most likely compartment for activation-induced lactate uptake and that neuronal lactate utilization occurring early after activation onset is responsible for the initial dip in brain lactate levels observed in both animals and humans. PMID:16260743

  9. Building a realistic neuronal model that simulates multi-joint arm and hand movements in 3D space.

    PubMed

    Alstermark, Bror; Lan, Ning; Pettersson, Lars-Gunnar

    2007-11-01

    The question as to how the brain controls voluntary movements of the arm and hand still remains largely unsolved despite much research focused on behavioral studies, neurophysiological investigations, and neuronal modeling in computer science. This is because behavioral studies are usually performed without detailed knowledge of the underlying neuronal networks, neurophysiological studies often lack an understanding of the function, and neuronal models are frequently focused on a particular control problem with restricted knowledge of the underlying neuronal networks involved. Therefore, it seems appropriate to start by trying to integrate knowledge of neuronal networks with known function and computer based neuronal models to seek more realistic models that can better control robots or artificial limbs and hands. We propose to combine knowledge of a behavioral model for reaching with the hand toward an object, which is based on detailed knowledge of the underlying neuronal network, and a neuronal model that includes several functional levels, from the planning level via intermediate levels to the final level of control of motoneurons and muscles. PMID:19404420

  10. Application of existing design software to problems in neuronal modeling.

    PubMed

    Vranić-Sowers, S; Fleshman, J W

    1994-03-01

    In this communication, we describe the application of the Valid/Analog Design Tools circuit simulation package called PC Workbench to the problem of modeling the electrical behavior of neural tissue. A nerve cell representation as an equivalent electrical circuit using compartmental models is presented. Several types of nonexcitable and excitable membranes are designed, and simulation results for different types of electrical stimuli are compared to the corresponding analytical data. It is shown that the hardware/software platform and the models developed constitute an accurate, flexible, and powerful way to study neural tissue. PMID:8045583

  11. Neuronal Injury, Gliosis, and Glial Proliferation in Two Models of Temporal Lobe Epilepsy.

    PubMed

    Loewen, Jaycie L; Barker-Haliski, Melissa L; Dahle, E Jill; White, H Steve; Wilcox, Karen S

    2016-04-01

    It is estimated that 30%-40% of epilepsy patients are refractory to therapy and animal models are useful for the identification of more efficacious therapeutic agents. Various well-characterized syndrome-specific models are needed to assess their relevance to human seizure disorders and their validity for testing potential therapies. The corneal kindled mouse model of temporal lobe epilepsy (TLE) allows for the rapid screening of investigational compounds, but there is a lack of information as to the specific inflammatory pathology in this model. Similarly, the Theiler murine encephalomyelitis virus (TMEV) model of TLE may prove to be useful for screening, but quantitative assessment of hippocampal pathology is also lacking. We used immunohistochemistry to characterize and quantitate acute neuronal injury and inflammatory features in dorsal CA1 and dentate gyrus regions and in the directly overlying posterior parietal cortex at 2 time points in each of these TLE models. Corneal kindled mice were observed to have astrogliosis, but not microgliosis or neuron cell death. In contrast, TMEV-injected mice had astrogliosis, microgliosis, neuron death, and astrocyte and microglial proliferation. Our results suggest that these 2 animal models might be appropriate for evaluation of distinct therapies for TLE. PMID:26945036

  12. Dendritic atrophy constricts functional maps in resonance and impedance properties of hippocampal model neurons

    PubMed Central

    Dhupia, Neha; Rathour, Rahul K.; Narayanan, Rishikesh

    2015-01-01

    A gradient in the density of hyperpolarization-activated cyclic-nucleotide gated (HCN) channels is necessary for the emergence of several functional maps within hippocampal pyramidal neurons. Here, we systematically analyzed the impact of dendritic atrophy on nine such functional maps, related to input resistance and local/transfer impedance properties, using conductance-based models of hippocampal pyramidal neurons. We introduced progressive dendritic atrophy in a CA1 pyramidal neuron reconstruction through a pruning algorithm, measured all functional maps in each pruned reconstruction, and arrived at functional forms for the dependence of underlying measurements on dendritic length. We found that, across frequencies, atrophied neurons responded with higher efficiency to incoming inputs, and the transfer of signals across the dendritic tree was more effective in an atrophied reconstruction. Importantly, despite the presence of identical HCN-channel density gradients, spatial gradients in input resistance, local/transfer resonance frequencies and impedance profiles were significantly constricted in reconstructions with dendritic atrophy, where these physiological measurements across dendritic locations converged to similar values. These results revealed that, in atrophied dendritic structures, the presence of an ion channel density gradient alone was insufficient to sustain homologous functional maps along the same neuronal topograph. We assessed the biophysical basis for these conclusions and found that this atrophy-induced constriction of functional maps was mediated by an enhanced spatial spread of the influence of an HCN-channel cluster in atrophied trees. These results demonstrated that the influence fields of ion channel conductances need to be localized for channel gradients to express themselves as homologous functional maps, suggesting that ion channel gradients are necessary but not sufficient for the emergence of functional maps within single neurons

  13. Increased acid responsiveness in vagal sensory neurons in a guinea pig model of eosinophilic esophagitis

    PubMed Central

    Hu, Youtian; Liu, Zhenyu; Yu, Xiaoyun; Pasricha, Pankaj J.; Undem, Bradley J.

    2014-01-01

    Eosinophilic esophagitis (EoE) is characterized with eosinophils and mast cells predominated allergic inflammation in the esophagus and present with esophageal dysfunctions such as dysphagia, food impaction, and heartburn. However, the underlying mechanism of esophageal dysfunctions is unclear. This study aims to determine whether neurons in the vagal sensory ganglia are modulated in a guinea pig model of EoE. Animals were actively sensitized by ovalbumin (OVA) and then challenged with aerosol OVA inhalation for 2 wk. This results in a mild esophagitis with increases in mast cells and eosinophils in the esophageal wall. Vagal nodose and jugular neurons were disassociated, and their responses to acid, capsaicin, and transient receptor potential vanilloid type 1 (TRPV1) antagonist AMG-9810 were studied by calcium imaging and whole cell patch-clamp recording. Compared with naïve animals, antigen challenge significantly increased acid responsiveness in both nodose and jugular neurons. Their responses to capsaicin were also increased after antigen challenge. AMG-9810, at a concentration that blocked capsaicin-evoked calcium influx, abolished the increase in acid-induced activation in both nodose and jugular neurons. Vagotomy strongly attenuated those increased responses of nodose and jugular neurons to both acid and capsaicin induced by antigen challenge. These data for the first time demonstrated that prolonged antigen challenge significantly increases acid responsiveness in vagal nodose and jugular ganglia neurons. This sensitization effect is mediated largely through TRPV1 and initiated at sensory nerve endings in the peripheral tissues. Allergen-induced enhancement of responsiveness to noxious stimulation by acid in sensory nerve may contribute to the development of esophageal dysfunctions such as heartburn in EoE. PMID:24875100

  14. Spike Train Probability Models for Stimulus-Driven Leaky Integrate-and-Fire Neurons

    PubMed Central

    Koyama, Shinsuke; Kass, Robert E.

    2009-01-01

    Mathematical models of neurons are widely used to improve understanding of neuronal spiking behavior. These models can produce artificial spike trains that resemble actual spike train data in important ways, but they are not very easy to apply to the analysis of spike train data. Instead, statistical methods based on point process models of spike trains provide a wide range of data-analytical techniques. Two simplified point process models have been introduced in the literature: the time-rescaled renewal process (TRRP) and the multiplicative inhomogeneous Markov interval (m-IMI) model. In this letter we investigate the extent to which the TRRP and m-IMI models are able to fit spike trains produced by stimulus-driven leaky integrate-and-fire (LIF) neurons. With a constant stimulus, the LIF spike train is a renewal process, and the m-IMI and TRRP models will describe accurately the LIF spike train variability. With a time-varying stimulus, the probability of spiking under all three of these models depends on both the experimental clock time relative to the stimulus and the time since the previous spike, but it does so differently for the LIF, m-IMI, and TRRP models. We assessed the distance between the LIF model and each of the two empirical models in the presence of a time-varying stimulus. We found that while lack of fit of a Poisson model to LIF spike train data can be evident even in small samples, the m-IMI and TRRP models tend to fit well, and much larger samples are required before there is statistical evidence of lack of fit of the m-IMI or TRRP models. We also found that when the mean of the stimulus varies across time, the m-IMI model provides a better fit to the LIF data than the TRRP, and when the variance of the stimulus varies across time, the TRRP provides the better fit. PMID:18336078

  15. Burst predicting neurons survive an in vitro glutamate injury model of cerebral ischemia.

    PubMed

    Kuebler, Eric S; Tauskela, Joseph S; Aylsworth, Amy; Zhao, Xigeng; Thivierge, Jean-Philippe

    2015-01-01

    Neuronal activity in vitro exhibits network bursts characterized by brief periods of increased spike rates. Recent work shows that a subpopulation of neurons reliably predicts the occurrence of network bursts. Here, we examined the role of burst predictors in cultures undergoing an in vitro model of cerebral ischemia. Dissociated primary cortical neurons were plated on multielectrode arrays and spontaneous activity was recorded at 17 days in vitro (DIV). This activity was characterized by neuronal avalanches where burst statistics followed a power law. We identified burst predictors as channels that consistently fired immediately prior to network bursts. The timing of these predictors relative to bursts followed a skewed distribution that differed sharply from a null model based on branching ratio. A portion of cultures were subjected to an excitotoxic insult (DIV 18). Propidium iodine and fluorescence imaging confirmed cell death in these cultures. While the insult did not alter the distribution of avalanches, it resulted in alterations in overall spike rates. Burst predictors, however, maintained baseline levels of activity. The resilience of burst predictors following excitotoxic insult suggests a key role of these units in maintaining network activity following injury, with implications for the selective effects of ischemia in the brain. PMID:26648112

  16. Burst predicting neurons survive an in vitro glutamate injury model of cerebral ischemia

    PubMed Central

    Kuebler, Eric S.; Tauskela, Joseph S.; Aylsworth, Amy; Zhao, Xigeng; Thivierge, Jean-Philippe

    2015-01-01

    Neuronal activity in vitro exhibits network bursts characterized by brief periods of increased spike rates. Recent work shows that a subpopulation of neurons reliably predicts the occurrence of network bursts. Here, we examined the role of burst predictors in cultures undergoing an in vitro model of cerebral ischemia. Dissociated primary cortical neurons were plated on multielectrode arrays and spontaneous activity was recorded at 17 days in vitro (DIV). This activity was characterized by neuronal avalanches where burst statistics followed a power law. We identified burst predictors as channels that consistently fired immediately prior to network bursts. The timing of these predictors relative to bursts followed a skewed distribution that differed sharply from a null model based on branching ratio. A portion of cultures were subjected to an excitotoxic insult (DIV 18). Propidium iodine and fluorescence imaging confirmed cell death in these cultures. While the insult did not alter the distribution of avalanches, it resulted in alterations in overall spike rates. Burst predictors, however, maintained baseline levels of activity. The resilience of burst predictors following excitotoxic insult suggests a key role of these units in maintaining network activity following injury, with implications for the selective effects of ischemia in the brain. PMID:26648112

  17. Oleuropein Prevents Neuronal Death, Mitigates Mitochondrial Superoxide Production and Modulates Autophagy in a Dopaminergic Cellular Model

    PubMed Central

    Achour, Imène; Arel-Dubeau, Anne-Marie; Renaud, Justine; Legrand, Manon; Attard, Everaldo; Germain, Marc; Martinoli, Maria-Grazia

    2016-01-01

    Parkinson’s disease (PD) is a progressive neurodegenerative disorder, primarily affecting dopaminergic neurons in the substantia nigra. There is currently no cure for PD and present medications aim to alleviate clinical symptoms, thus prevention remains the ideal strategy to reduce the prevalence of this disease. The goal of this study was to investigate whether oleuropein (OLE), the major phenolic compound in olive derivatives, may prevent neuronal degeneration in a cellular dopaminergic model of PD, differentiated PC12 cells exposed to the potent parkinsonian toxin 6-hydroxydopamine (6-OHDA). We also investigated OLE’s ability to mitigate mitochondrial oxidative stress and modulate the autophagic flux. Our results obtained by measuring cytotoxicity and apoptotic events demonstrate that OLE significantly decreases neuronal death. OLE could also reduce mitochondrial production of reactive oxygen species resulting from blocking superoxide dismutase activity. Moreover, quantification of autophagic and acidic vesicles in the cytoplasm alongside expression of specific autophagic markers uncovered a regulatory role for OLE against autophagic flux impairment induced by bafilomycin A1. Altogether, our results define OLE as a neuroprotective, anti-oxidative and autophagy-regulating molecule, in a neuronal dopaminergic cellular model. PMID:27517912

  18. Dynamics of Disordered Network of Coupled Hindmarsh-Rose Neuronal Models

    NASA Astrophysics Data System (ADS)

    Dtchetgnia Djeundam, S. R.; Yamapi, R.; Filatrella, G.; Kofane, T. C.

    We investigate the effects of disorder on the synchronized state of a network of Hindmarsh-Rose neuronal models. Disorder, introduced as a perturbation of the neuronal parameters, destroys the network activity by wrecking the synchronized state. The dynamics of the synchronized state is analyzed through the Kuramoto order parameter, adapted to the neuronal Hindmarsh-Rose model. We find that the coupling deeply alters the dynamics of the single units, thus demonstrating that coupling not only affects the relative motion of the units, but also the dynamical behavior of each neuron; Thus, synchronization results in a structural change of the dynamics. The Kuramoto order parameter allows to clarify the nature of the transition from perfect phase synchronization to the disordered states, supporting the notion of an abrupt, second order-like, dynamical phase transition. We find that the system is resilient up to a certain disorder threshold, after that the network abruptly collapses to a desynchronized state. The loss of perfect synchronization seems to occur even for vanishingly small values of the disorder, but the degree of synchronization (as measured by the Kuramoto order parameter) gently decreases, and the completely disordered state is never reached.

  19. Oleuropein Prevents Neuronal Death, Mitigates Mitochondrial Superoxide Production and Modulates Autophagy in a Dopaminergic Cellular Model.

    PubMed

    Achour, Imène; Arel-Dubeau, Anne-Marie; Renaud, Justine; Legrand, Manon; Attard, Everaldo; Germain, Marc; Martinoli, Maria-Grazia

    2016-01-01

    Parkinson's disease (PD) is a progressive neurodegenerative disorder, primarily affecting dopaminergic neurons in the substantia nigra. There is currently no cure for PD and present medications aim to alleviate clinical symptoms, thus prevention remains the ideal strategy to reduce the prevalence of this disease. The goal of this study was to investigate whether oleuropein (OLE), the major phenolic compound in olive derivatives, may prevent neuronal degeneration in a cellular dopaminergic model of PD, differentiated PC12 cells exposed to the potent parkinsonian toxin 6-hydroxydopamine (6-OHDA). We also investigated OLE's ability to mitigate mitochondrial oxidative stress and modulate the autophagic flux. Our results obtained by measuring cytotoxicity and apoptotic events demonstrate that OLE significantly decreases neuronal death. OLE could also reduce mitochondrial production of reactive oxygen species resulting from blocking superoxide dismutase activity. Moreover, quantification of autophagic and acidic vesicles in the cytoplasm alongside expression of specific autophagic markers uncovered a regulatory role for OLE against autophagic flux impairment induced by bafilomycin A1. Altogether, our results define OLE as a neuroprotective, anti-oxidative and autophagy-regulating molecule, in a neuronal dopaminergic cellular model. PMID:27517912

  20. Modeling the Influence of Ion Channels on Neuron Dynamics in Drosophila

    PubMed Central

    Berger, Sandra D.; Crook, Sharon M.

    2015-01-01

    Voltage gated ion channels play a major role in determining a neuron's firing behavior, resulting in the specific processing of synaptic input patterns. Drosophila and other invertebrates provide valuable model systems for investigating ion channel kinetics and their impact on firing properties. Despite the increasing importance of Drosophila as a model system, few computational models of its ion channel kinetics have been developed. In this study, experimentally observed biophysical properties of voltage gated ion channels from the fruitfly Drosophila melanogaster are used to develop a minimal, conductance based neuron model. We investigate the impact of the densities of these channels on the excitability of the model neuron. Changing the channel densities reproduces different in situ observed firing patterns and induces a switch from integrator to resonator properties. Further, we analyze the preference to input frequency and how it depends on the channel densities and the resulting bifurcation type the system undergoes. An extension to a three dimensional model demonstrates that the inactivation kinetics of the sodium channels play an important role, allowing for firing patterns with a delayed first spike and subsequent high frequency firing as often observed in invertebrates, without altering the kinetics of the delayed rectifier current. PMID:26635592

  1. A Mathematical Model towards Understanding the Mechanism of Neuronal Regulation of Wake-NREMS-REMS States

    PubMed Central

    Kumar, Rupesh; Bose, Amitabha; Mallick, Birendra Nath

    2012-01-01

    In this study we have constructed a mathematical model of a recently proposed functional model known to be responsible for inducing waking, NREMS and REMS. Simulation studies using this model reproduced sleep-wake patterns as reported in normal animals. The model helps to explain neural mechanism(s) that underlie the transitions between wake, NREMS and REMS as well as how both the homeostatic sleep-drive and the circadian rhythm shape the duration of each of these episodes. In particular, this mathematical model demonstrates and confirms that an underlying mechanism for REMS generation is pre-synaptic inhibition from substantia nigra onto the REM-off terminals that project on REM-on neurons, as has been recently proposed. The importance of orexinergic neurons in stabilizing the wake-sleep cycle is demonstrated by showing how even small changes in inputs to or from those neurons can have a large impact on the ensuing dynamics. The results from this model allow us to make predictions of the neural mechanisms of regulation and patho-physiology of REMS. PMID:22905114

  2. The Drive-Reinforcement Neuronal Model: A Real-Time Learning Mechanism For Unsupervised Learning

    NASA Astrophysics Data System (ADS)

    Klopf, A. H.

    1988-05-01

    The drive-reinforcement neuronal model is described as an example of a newly discovered class of real-time learning mechanisms that correlate earlier derivatives of inputs with later derivatives of outputs. The drive-reinforcement neuronal model has been demonstrated to predict a wide range of classical conditioning phenomena in animal learning. A variety of classes of connectionist and neural network models have been investigated in recent years (Hinton and Anderson, 1981; Levine, 1983; Barto, 1985; Feldman, 1985; Rumelhart and McClelland, 1986). After a brief review of these models, discussion will focus on the class of real-time models because they appear to be making the strongest contact with the experimental evidence of animal learning. Theoretical models in physics have inspired Boltzmann machines (Ackley, Hinton, and Sejnowski, 1985) and what are sometimes called Hopfield networks (Hopfield, 1982; Hopfield and Tank, 1986). These connectionist models utilize symmetric connections and adaptive equilibrium processes during which the networks settle into minimal energy states. Networks utilizing error-correction learning mechanisms go back to Rosenblatt's (1962) perception and Widrow's (1962) adaline and currently take the form of back propagation networks (Parker, 1985; Rumelhart, Hinton, and Williams, 1985, 1986). These networks require a "teacher" or "trainer" to provide error signals indicating the difference between desired and actual responses. Networks employing real-time learning mechanisms, in which the temporal association of signals is of fundamental importance, go back to Hebb (1949). Real-time learning mechanisms may require no teacher or trainer and thus may lend themselves to unsupervised learning. Such models have been extended by Klopf (1972, 1982), who introduced the notions of synaptic eligibility and generalized reinforcement. Sutton and Barto (1981) advanced this class of models by proposing that a derivative of the theoretical neuron's out

  3. Human iPSC-Derived Neuronal Model of Tau-A152T Frontotemporal Dementia Reveals Tau-Mediated Mechanisms of Neuronal Vulnerability.

    PubMed

    Silva, M Catarina; Cheng, Chialin; Mair, Waltraud; Almeida, Sandra; Fong, Helen; Biswas, M Helal U; Zhang, Zhijun; Huang, Yadong; Temple, Sally; Coppola, Giovanni; Geschwind, Daniel H; Karydas, Anna; Miller, Bruce L; Kosik, Kenneth S; Gao, Fen-Biao; Steen, Judith A; Haggarty, Stephen J

    2016-09-13

    Frontotemporal dementia (FTD) and other tauopathies characterized by focal brain neurodegeneration and pathological accumulation of proteins are commonly associated with tau mutations. However, the mechanism of neuronal loss is not fully understood. To identify molecular events associated with tauopathy, we studied induced pluripotent stem cell (iPSC)-derived neurons from individuals carrying the tau-A152T variant. We highlight the potential of in-depth phenotyping of human neuronal cell models for pre-clinical studies and identification of modulators of endogenous tau toxicity. Through a panel of biochemical and cellular assays, A152T neurons showed accumulation, redistribution, and decreased solubility of tau. Upregulation of tau was coupled to enhanced stress-inducible markers and cell vulnerability to proteotoxic, excitotoxic, and mitochondrial stressors, which was rescued upon CRISPR/Cas9-mediated targeting of tau or by pharmacological activation of autophagy. Our findings unmask tau-mediated perturbations of specific pathways associated with neuronal vulnerability, revealing potential early disease biomarkers and therapeutic targets for FTD and other tauopathies. PMID:27594585

  4. Energy metabolism in neuronal/glial induction and in iPSC models of brain disorders.

    PubMed

    Mlody, Barbara; Lorenz, Carmen; Inak, Gizem; Prigione, Alessandro

    2016-04-01

    The metabolic switch associated with the reprogramming of somatic cells to pluripotency has received increasing attention in recent years. However, the impact of mitochondrial and metabolic modulation on stem cell differentiation into neuronal/glial cells and related brain disease modeling still remains to be fully addressed. Here, we seek to focus on this aspect by first addressing brain energy metabolism and its inter-cellular metabolic compartmentalization. We then review the findings related to the mitochondrial and metabolic reconfiguration occurring upon neuronal/glial specification from pluripotent stem cells (PSCs). Finally, we provide an update of the PSC-based models of mitochondria-related brain disorders and discuss the challenges and opportunities that may exist on the road to develop a new era of brain disease modeling and therapy. PMID:26877213

  5. Analysis of nonlinear noisy integrate & fire neuron models: blow-up and steady states

    PubMed Central

    2011-01-01

    Nonlinear Noisy Leaky Integrate and Fire (NNLIF) models for neurons networks can be written as Fokker-Planck-Kolmogorov equations on the probability density of neurons, the main parameters in the model being the connectivity of the network and the noise. We analyse several aspects of the NNLIF model: the number of steady states, a priori estimates, blow-up issues and convergence toward equilibrium in the linear case. In particular, for excitatory networks, blow-up always occurs for initial data concentrated close to the firing potential. These results show how critical is the balance between noise and excitatory/inhibitory interactions to the connectivity parameter. AMS Subject Classification: 35K60, 82C31, 92B20. PMID:22657097

  6. A model-based analysis of physiological properties of the striatal medium spiny neuron.

    PubMed

    Wang, Jing; Liu, Shenquan; Wang, Hongchu; Ju, Niansheng; Zeng, Yanjun

    2015-12-01

    As the principal cell of the striatum, medium spiny neurons (MSNs) are closely associated with various motor dysfunctional diseases. In this paper, we describe an electric compartment model constructed in NEURON with a realistic morphology. Based on a 554-compartment computational model, we researched the influence of external current stimuli, different ions conductance, and the removal of partial dendrites on the physiological properties of the MSN. The main results are the following: (1) in the case of external current stimuli, various firing patterns appear in the MSN and the model produces a clear period-adding bifurcation phenomenon; (2) the effect of distinct types of ion channels vary and significant differences in discharge rhythm exist even among ion channels of the same type; (3) the closer the removed dendrite was to the soma, the larger the impact this had on the discharge pattern of the MSN. PMID:26923577

  7. Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons.

    PubMed

    Pospischil, Martin; Toledo-Rodriguez, Maria; Monier, Cyril; Piwkowska, Zuzanna; Bal, Thierry; Frégnac, Yves; Markram, Henry; Destexhe, Alain

    2008-11-01

    We review here the development of Hodgkin-Huxley (HH) type models of cerebral cortex and thalamic neurons for network simulations. The intrinsic electrophysiological properties of cortical neurons were analyzed from several preparations, and we selected the four most prominent electrophysiological classes of neurons. These four classes are "fast spiking", "regular spiking", "intrinsically bursting" and "low-threshold spike" cells. For each class, we fit "minimal" HH type models to experimental data. The models contain the minimal set of voltage-dependent currents to account for the data. To obtain models as generic as possible, we used data from different preparations in vivo and in vitro, such as rat somatosensory cortex and thalamus, guinea-pig visual and frontal cortex, ferret visual cortex, cat visual cortex and cat association cortex. For two cell classes, we used automatic fitting procedures applied to several cells, which revealed substantial cell-to-cell variability within each class. The selection of such cellular models constitutes a necessary step towards building network simulations of the thalamocortical system with realistic cellular dynamical properties. PMID:19011929

  8. Tocilizumab inhibits neuronal cell apoptosis and activates STAT3 in cerebral infarction rat model

    PubMed Central

    Wang, Shaojun; Zhou, Jun; Kang, Weijie; Dong, Zhaoni; Wang, Hezuo

    2016-01-01

    Cerebral infarction is a severe hypoxic ischemic necrosis with accelerated neuronal cell apoptosis in the brain. As a monoclonal antibody against interleukin 6, tocilizumab (TCZ) is widely used in immune diseases, whose function in cerebral infarction has not been studied. This study aims to reveal the role of TCZ in regulating neuronal cell apoptosis in cerebral infarction. The cerebral infarction rat model was constructed by middle cerebral artery occlusion and treated with TCZ. Cell apoptosis in hippocampus and cortex of the brain was examined with TUNEL method. Rat neuronal cells cultured in oxygen-glucose deprivation (OGD) conditions and treated with TCZ were used to compare cell viability and apoptosis. Apoptosis-related factors including B-cell lymphoma extra large (Bcl-xL) and Caspase 3, as well as the phosphorylated signal transducer and activator of transcription 3 (p-STAT3) in brain cortex were analyzed from the protein level. Results indicated that TCZ treatment could significantly prevent the promoted cell apoptosis caused by cerebral infarction or OGD (P < 0.05 or P < 0.01). In brain cortex of the rat model, TCZ up-regulated Bcl-xL and down-regulated Caspase 3, consistent with the inhibited cell apoptosis. It also promoted tyrosine 705 phosphorylation of STAT3, which might be the potential regulatory mechanism of TCZ in neuronal cells. This study provided evidence for the protective role of TCZ against neuronal cell apoptosis in cerebral infarction. Based on these fundamental data, TCZ is a promising option for treating cerebral infarction, but further investigations on related mechanisms are still necessary. PMID:26773188

  9. Modeling the effects of extracellular potassium on bursting properties in pre-Bötzinger complex neurons

    PubMed Central

    Segaran, Joshua; Molkov, Yaroslav I.

    2015-01-01

    There are many types of neurons that intrinsically generate rhythmic bursting activity, even when isolated, and these neurons underlie several specific motor behaviors. Rhythmic neurons that drive the inspiratory phase of respiration are located in the medullary pre-Bötzinger Complex (pre-BötC). However, it is not known if their rhythmic bursting is the result of intrinsic mechanisms or synaptic interactions. In many cases, for bursting to occur, the excitability of these neurons needs to be elevated. This excitation is provided in vitro (e.g. in slices), by increasing extracellular potassium concentration (Kout) well beyond physiologic levels. Elevated Kout shifts the reversal potentials for all potassium currents including the potassium component of leakage to higher values. However, how an increase in Kout, and the resultant changes in potassium currents, induce bursting activity, have yet to be established. Moreover, it is not known if the endogenous bursting induced in vitro is representative of neural behavior in vivo. Our modeling study examines the interplay between Kout, excitability, and selected currents, as they relate to endogenous rhythmic bursting. Starting with a Hodgkin-Huxley formalization of a pre-BötC neuron, a potassium ion component was incorporated into the leakage current, and model behaviors were investigated at varying concentrations of Kout. Our simulations show that endogenous bursting activity, evoked in vitro by elevation of Kout, is the result of a specific relationship between the leakage and voltage-dependent, delayed rectifier potassium currents, which may not be observed at physiological levels of extracellular potassium. PMID:26899961

  10. Cyclooxygenase inhibition targets neurons to prevent early behavioural decline in Alzheimer's disease model mice.

    PubMed

    Woodling, Nathaniel S; Colas, Damien; Wang, Qian; Minhas, Paras; Panchal, Maharshi; Liang, Xibin; Mhatre, Siddhita D; Brown, Holden; Ko, Novie; Zagol-Ikapitte, Irene; van der Hart, Marieke; Khroyan, Taline V; Chuluun, Bayarsaikhan; Priyam, Prachi G; Milne, Ginger L; Rassoulpour, Arash; Boutaud, Olivier; Manning-Boğ, Amy B; Heller, H Craig; Andreasson, Katrin I

    2016-07-01

    Identifying preventive targets for Alzheimer's disease is a central challenge of modern medicine. Non-steroidal anti-inflammatory drugs, which inhibit the cyclooxygenase enzymes COX-1 and COX-2, reduce the risk of developing Alzheimer's disease in normal ageing populations. This preventive effect coincides with an extended preclinical phase that spans years to decades before onset of cognitive decline. In the brain, COX-2 is induced in neurons in response to excitatory synaptic activity and in glial cells in response to inflammation. To identify mechanisms underlying prevention of cognitive decline by anti-inflammatory drugs, we first identified an early object memory deficit in APPSwe-PS1ΔE9 mice that preceded previously identified spatial memory deficits in this model. We modelled prevention of this memory deficit with ibuprofen, and found that ibuprofen prevented memory impairment without producing any measurable changes in amyloid-β accumulation or glial inflammation. Instead, ibuprofen modulated hippocampal gene expression in pathways involved in neuronal plasticity and increased levels of norepinephrine and dopamine. The gene most highly downregulated by ibuprofen was neuronal tryptophan 2,3-dioxygenase (Tdo2), which encodes an enzyme that metabolizes tryptophan to kynurenine. TDO2 expression was increased by neuronal COX-2 activity, and overexpression of hippocampal TDO2 produced behavioural deficits. Moreover, pharmacological TDO2 inhibition prevented behavioural deficits in APPSwe-PS1ΔE9 mice. Taken together, these data demonstrate broad effects of cyclooxygenase inhibition on multiple neuronal pathways that counteract the neurotoxic effects of early accumulating amyloid-β oligomers. PMID:27190010

  11. Electrodiffusive Model for Astrocytic and Neuronal Ion Concentration Dynamics

    PubMed Central

    Halnes, Geir; Østby, Ivar; Pettersen, Klas H.; Omholt, Stig W.; Einevoll, Gaute T.

    2013-01-01

    The cable equation is a proper framework for modeling electrical neural signalling that takes place at a timescale at which the ionic concentrations vary little. However, in neural tissue there are also key dynamic processes that occur at longer timescales. For example, endured periods of intense neural signaling may cause the local extracellular K+-concentration to increase by several millimolars. The clearance of this excess K+ depends partly on diffusion in the extracellular space, partly on local uptake by astrocytes, and partly on intracellular transport (spatial buffering) within astrocytes. These processes, that take place at the time scale of seconds, demand a mathematical description able to account for the spatiotemporal variations in ion concentrations as well as the subsequent effects of these variations on the membrane potential. Here, we present a general electrodiffusive formalism for modeling of ion concentration dynamics in a one-dimensional geometry, including both the intra- and extracellular domains. Based on the Nernst-Planck equations, this formalism ensures that the membrane potential and ion concentrations are in consistency, it ensures global particle/charge conservation and it accounts for diffusion and concentration dependent variations in resistivity. We apply the formalism to a model of astrocytes exchanging ions with the extracellular space. The simulations show that K+-removal from high-concentration regions is driven by a local depolarization of the astrocyte membrane, which concertedly (i) increases the local astrocytic uptake of K+, (ii) suppresses extracellular transport of K+, (iii) increases axial transport of K+ within astrocytes, and (iv) facilitates astrocytic relase of K+ in regions where the extracellular concentration is low. Together, these mechanisms seem to provide a robust regulatory scheme for shielding the extracellular space from excess K+. PMID:24367247

  12. Carbon Monoxide Releasing Molecule-A1 (CORM-A1) Improves Neurogenesis: Increase of Neuronal Differentiation Yield by Preventing Cell Death

    PubMed Central

    Almeida, Ana S.; Soares, Nuno L.; Vieira, Melissa; Gramsbergen, Jan Bert

    2016-01-01

    Cerebral ischemia and neurodegenerative diseases lead to impairment or death of neurons in the central nervous system. Stem cell based therapies are promising strategies currently under investigation. Carbon monoxide (CO) is an endogenous product of heme degradation by heme oxygenase (HO) activity. Administration of CO at low concentrations produces several beneficial effects in distinct tissues, namely anti-apoptotic and anti-inflammatory. Herein the CO role on modulation of neuronal differentiation was assessed. Three different models with increasing complexity were used: human neuroblastoma SH-S5Y5 cell line, human teratocarcinoma NT2 cell line and organotypic hippocampal slice cultures (OHSC). Cell lines were differentiated into post-mitotic neurons by treatment with retinoic acid (RA) supplemented with CO-releasing molecule A1 (CORM-A1). CORM-A1 positively modulated neuronal differentiation, since it increased final neuronal production and enhanced the expression of specific neuronal genes: Nestin, Tuj1 and MAP2. Furthermore, during neuronal differentiation process, there was an increase in proliferative cell number (ki67 mRNA expressing cells) and a decrease in cell death (lower propidium iodide (PI) uptake, limitation of caspase-3 activation and higher Bcl-2 expressing cells). CO supplementation did not increase the expression of RA receptors. In the case of SH-S5Y5 model, small amounts of reactive oxygen species (ROS) generation emerges as important signaling molecules during CO-promoted neuronal differentiation. CO’s improvement of neuronal differentiation yield was validated using OHSC as ex vivo model. CORM-A1 treatment of OHSC promoted higher levels of cells expressing the neuronal marker Tuj1. Still, CORM-A1 increased cell proliferation assessed by ki67 expression and also prevented cell death, which was followed by increased Bcl-2 expression, decreased levels of active caspase-3 and PI uptake. Likewise, ROS signaling emerged as key factors in CO

  13. MND2: A new mouse model of inherited motor neuron disease

    SciTech Connect

    Jones, J.M.; Albin, R.L.; Feldman, E.L.; Simin, K.; Schuster, T.G.; Dunnick, W.A.; Collins, J.T.; Chrisp, C.E.; Meisler, M.H. ); Taylor, B.A. )

    1993-06-01

    The autosomal recessive mutation mnd2 results in early onset motor neuron disease with rapidly progressive paralysis, severe muscle wasting, regression of thymus and spleen, and death before 40 days of age. mnd2 has been mapped to mouse chromosome 6 with the gene order: centromere-Tcrb-Ly-2-Sftp-3-D6Mit4-mnd2-D6Mit6, D6Mit9-D6Rck132-Raf-1, D6Mit11-D6Mit12-D6Mit14. mnd2 is located within a conserved linkage group with homologs on human chromosome 2p12-p13. Spinal motor neurons of homozygous affected animals are swollen and stain weakly, and electromyography revealed spontaneous activity characteristic of muscle denervation. Myelin staining was normal throughout the neuraxis. The clinical observations are consistent with a primary abnormality of lower motor neuron function. This new animal model will be of value for identification of a genetic defect responsible for motor neuron disease and for evaluation of new therapies. 36 refs., 7 figs., 2 tabs.

  14. Chemical Control of Grafted Human PSC-Derived Neurons in a Mouse Model of Parkinson's Disease.

    PubMed

    Chen, Yuejun; Xiong, Man; Dong, Yi; Haberman, Alexander; Cao, Jingyuan; Liu, Huisheng; Zhou, Wenhao; Zhang, Su-Chun

    2016-06-01

    Transplantation of human pluripotent stem cell (hPSC)-derived neurons is a promising avenue for treating disorders including Parkinson's disease (PD). Precise control over engrafted cell activity is highly desired, as cells do not always integrate properly into host circuitry and can cause suboptimal graft function or undesired outcomes. Here, we show tunable rescue of motor function in a mouse model of PD, following transplantation of human midbrain dopaminergic (mDA) neurons differentiated from hPSCs engineered to express DREADDs (designer receptors exclusively activated by designer drug). Administering clozapine-N-oxide (CNO) enabled precise DREADD-dependent stimulation or inhibition of engrafted neurons, revealing D1 receptor-dependent regulation of host neuronal circuitry by engrafted cells. Transplanted cells rescued motor defects, which could be reversed or enhanced by CNO-based control of graft function, and activating engrafted cells drives behavioral changes in transplanted mice. These results highlight the ability to exogenously and noninvasively control and refine therapeutic outcomes following cell transplantation. PMID:27133795

  15. Inferring Neuronal Dynamics from Calcium Imaging Data Using Biophysical Models and Bayesian Inference

    PubMed Central

    Rahmati, Vahid; Kirmse, Knut; Marković, Dimitrije; Holthoff, Knut; Kiebel, Stefan J.

    2016-01-01

    Calcium imaging has been used as a promising technique to monitor the dynamic activity of neuronal populations. However, the calcium trace is temporally smeared which restricts the extraction of quantities of interest such as spike trains of individual neurons. To address this issue, spike reconstruction algorithms have been introduced. One limitation of such reconstructions is that the underlying models are not informed about the biophysics of spike and burst generations. Such existing prior knowledge might be useful for constraining the possible solutions of spikes. Here we describe, in a novel Bayesian approach, how principled knowledge about neuronal dynamics can be employed to infer biophysical variables and parameters from fluorescence traces. By using both synthetic and in vitro recorded fluorescence traces, we demonstrate that the new approach is able to reconstruct different repetitive spiking and/or bursting patterns with accurate single spike resolution. Furthermore, we show that the high inference precision of the new approach is preserved even if the fluorescence trace is rather noisy or if the fluorescence transients show slow rise kinetics lasting several hundred milliseconds, and inhomogeneous rise and decay times. In addition, we discuss the use of the new approach for inferring parameter changes, e.g. due to a pharmacological intervention, as well as for inferring complex characteristics of immature neuronal circuits. PMID:26894748

  16. Altered neuronal network and rescue in a human MECP2 duplication model.

    PubMed

    Nageshappa, S; Carromeu, C; Trujillo, C A; Mesci, P; Espuny-Camacho, I; Pasciuto, E; Vanderhaeghen, P; Verfaillie, C M; Raitano, S; Kumar, A; Carvalho, C M B; Bagni, C; Ramocki, M B; Araujo, B H S; Torres, L B; Lupski, J R; Van Esch, H; Muotri, A R

    2016-02-01

    Increased dosage of methyl-CpG-binding protein-2 (MeCP2) results in a dramatic neurodevelopmental phenotype with onset at birth. We generated induced pluripotent stem cells (iPSCs) from patients with the MECP2 duplication syndrome (MECP2dup), carrying different duplication sizes, to study the impact of increased MeCP2 dosage in human neurons. We show that cortical neurons derived from these different MECP2dup iPSC lines have increased synaptogenesis and dendritic complexity. In addition, using multi-electrodes arrays, we show that neuronal network synchronization was altered in MECP2dup-derived neurons. Given MeCP2 functions at the epigenetic level, we tested whether these alterations were reversible using a library of compounds with defined activity on epigenetic pathways. One histone deacetylase inhibitor, NCH-51, was validated as a potential clinical candidate. Interestingly, this compound has never been considered before as a therapeutic alternative for neurological disorders. Our model recapitulates early stages of the human MECP2 duplication syndrome and represents a promising cellular tool to facilitate therapeutic drug screening for severe neurodevelopmental disorders. PMID:26347316

  17. Deterministic and stochastic bifurcations in the Hindmarsh-Rose neuronal model

    NASA Astrophysics Data System (ADS)

    Dtchetgnia Djeundam, S. R.; Yamapi, R.; Kofane, T. C.; Aziz-Alaoui, M. A.

    2013-09-01

    We analyze the bifurcations occurring in the 3D Hindmarsh-Rose neuronal model with and without random signal. When under a sufficient stimulus, the neuron activity takes place; we observe various types of bifurcations that lead to chaotic transitions. Beside the equilibrium solutions and their stability, we also investigate the deterministic bifurcation. It appears that the neuronal activity consists of chaotic transitions between two periodic phases called bursting and spiking solutions. The stochastic bifurcation, defined as a sudden change in character of a stochastic attractor when the bifurcation parameter of the system passes through a critical value, or under certain condition as the collision of a stochastic attractor with a stochastic saddle, occurs when a random Gaussian signal is added. Our study reveals two kinds of stochastic bifurcation: the phenomenological bifurcation (P-bifurcations) and the dynamical bifurcation (D-bifurcations). The asymptotical method is used to analyze phenomenological bifurcation. We find that the neuronal activity of spiking and bursting chaos remains for finite values of the noise intensity.

  18. Mitochondrial Mislocalization Underlies Aβ42-Induced Neuronal Dysfunction in a Drosophila Model of Alzheimer's Disease

    PubMed Central

    Iijima-Ando, Kanae; Hearn, Stephen A.; Shenton, Christopher; Gatt, Anthony; Zhao, LiJuan; Iijima, Koichi

    2009-01-01

    The amyloid-β 42 (Aβ42) is thought to play a central role in the pathogenesis of Alzheimer's disease (AD). However, the molecular mechanisms by which Aβ42 induces neuronal dysfunction and degeneration remain elusive. Mitochondrial dysfunctions are implicated in AD brains. Whether mitochondrial dysfunctions are merely a consequence of AD pathology, or are early seminal events in AD pathogenesis remains to be determined. Here, we show that Aβ42 induces mitochondrial mislocalization, which contributes to Aβ42-induced neuronal dysfunction in a transgenic Drosophila model. In the Aβ42 fly brain, mitochondria were reduced in axons and dendrites, and accumulated in the somata without severe mitochondrial damage or neurodegeneration. In contrast, organization of microtubule or global axonal transport was not significantly altered at this stage. Aβ42-induced behavioral defects were exacerbated by genetic reductions in mitochondrial transport, and were modulated by cAMP levels and PKA activity. Levels of putative PKA substrate phosphoproteins were reduced in the Aβ42 fly brains. Importantly, perturbations in mitochondrial transport in neurons were sufficient to disrupt PKA signaling and induce late-onset behavioral deficits, suggesting a mechanism whereby mitochondrial mislocalization contributes to Aβ42-induced neuronal dysfunction. These results demonstrate that mislocalization of mitochondria underlies the pathogenic effects of Aβ42 in vivo. PMID:20016833

  19. Altered neuronal network and rescue in a human MECP2 duplication model

    PubMed Central

    Nageshappa, Savitha; Carromeu, Cassiano; Trujillo, Cleber A.; Mesci, Pinar; Espuny-Camacho, Ira; Pasciuto, Emanuela; Vanderhaeghen, Pierre; Verfaillie, Catherine; Raitano, Susanna; Kumar, Anujith; Carvalho, Claudia M.B.; Bagni, Claudia; Ramocki, Melissa B.; Araujo, Bruno H. S.; Torres, Laila B.; Lupski, James R.; Van Esch, Hilde; Muotri, Alysson R.

    2015-01-01

    Increased dosage of MeCP2 results in a dramatic neurodevelopmental phenotype with onset at birth. We generated induced pluripotent stem cells (iPSC) from patients with the MECP2 duplication syndrome (MECP2dup), carrying different duplication sizes, to study the impact of increased MeCP2 dosage in human neurons. We show that cortical neurons derived from these different MECP2dup iPSC lines have increase synaptogenesis and dendritic complexity. Additionally, using multi-electrodes arrays, we show that neuronal network synchronization was altered in MECP2dup-derived neurons. Given MeCP2 function at the epigenetic level, we tested if these alterations were reversible using a library of compounds with defined activity on epigenetic pathways. One histone deacetylase inhibitor, NCH-51, was validated as a potential clinical candidate. Interestingly, this compound has never been considered before as a therapeutic alternative for neurological disorders. Our model recapitulates early stages of the human MECP2 duplication syndrome and represents a promising cellular tool to facilitate therapeutic drug screening for severe neurodevelopmental disorders. PMID:26347316

  20. Phosphodiesterase 7 Inhibition Preserves Dopaminergic Neurons in Cellular and Rodent Models of Parkinson Disease

    PubMed Central

    Morales-Garcia, Jose A.; Redondo, Miriam; Alonso-Gil, Sandra; Gil, Carmen; Perez, Concepción; Martinez, Ana; Santos, Angel; Perez-Castillo, Ana

    2011-01-01

    Background Phosphodiesterase 7 plays a major role in down-regulation of protein kinase A activity by hydrolyzing cAMP in many cell types. This cyclic nucleotide plays a key role in signal transduction in a wide variety of cellular responses. In the brain, cAMP has been implicated in learning, memory processes and other brain functions. Methodology/Principal Findings Here we show a novel function of phosphodiesterase 7 inhibition on nigrostriatal dopaminergic neuronal death. We found that S14, a heterocyclic small molecule inhibitor of phosphodiesterase 7, conferred significant neuronal protection against different insults both in the human dopaminergic cell line SH-SY5Y and in primary rat mesencephalic cultures. S14 treatment also reduced microglial activation, protected dopaminergic neurons and improved motor function in the lipopolysaccharide rat model of Parkinson disease. Finally, S14 neuroprotective effects were reversed by blocking the cAMP signaling pathways that operate through cAMP-dependent protein kinase A. Conclusions/Significance Our findings demonstrate that phosphodiesterase 7 inhibition can protect dopaminergic neurons against different insults, and they provide support for the therapeutic potential of phosphodiesterase 7 inhibitors in the treatment of neurodegenerative disorders, particularly Parkinson disease. PMID:21390306

  1. Metabolic cost of neuronal information in an empirical stimulus-response model.

    PubMed

    Kostal, Lubomir; Lansky, Petr; McDonnell, Mark D

    2013-06-01

    The limits on maximum information that can be transferred by single neurons may help us to understand how sensory and other information is being processed in the brain. According to the efficient-coding hypothesis (Barlow, Sensory Comunication, MIT press, Cambridge, 1961), neurons are adapted to the statistical properties of the signals to which they are exposed. In this paper we employ methods of information theory to calculate, both exactly (numerically) and approximately, the ultimate limits on reliable information transmission for an empirical neuronal model. We couple information transfer with the metabolic cost of neuronal activity and determine the optimal information-to-metabolic cost ratios. We find that the optimal input distribution is discrete with only six points of support, both with and without a metabolic constraint. However, we also find that many different input distributions achieve mutual information close to capacity, which implies that the precise structure of the capacity-achieving input is of lesser importance than the value of capacity. PMID:23467914

  2. Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons.

    PubMed

    Griesi-Oliveira, K; Acab, A; Gupta, A R; Sunaga, D Y; Chailangkarn, T; Nicol, X; Nunez, Y; Walker, M F; Murdoch, J D; Sanders, S J; Fernandez, T V; Ji, W; Lifton, R P; Vadasz, E; Dietrich, A; Pradhan, D; Song, H; Ming, G-L; Gu, X; Haddad, G; Marchetto, M C N; Spitzer, N; Passos-Bueno, M R; State, M W; Muotri, A R

    2015-11-01

    An increasing number of genetic variants have been implicated in autism spectrum disorders (ASDs), and the functional study of such variants will be critical for the elucidation of autism pathophysiology. Here, we report a de novo balanced translocation disruption of TRPC6, a cation channel, in a non-syndromic autistic individual. Using multiple models, such as dental pulp cells, induced pluripotent stem cell (iPSC)-derived neuronal cells and mouse models, we demonstrate that TRPC6 reduction or haploinsufficiency leads to altered neuronal development, morphology and function. The observed neuronal phenotypes could then be rescued by TRPC6 complementation and by treatment with insulin-like growth factor-1 or hyperforin, a TRPC6-specific agonist, suggesting that ASD individuals with alterations in this pathway may benefit from these drugs. We also demonstrate that methyl CpG binding protein-2 (MeCP2) levels affect TRPC6 expression. Mutations in MeCP2 cause Rett syndrome, revealing common pathways among ASDs. Genetic sequencing of TRPC6 in 1041 ASD individuals and 2872 controls revealed significantly more nonsynonymous mutations in the ASD population, and identified loss-of-function mutations with incomplete penetrance in two patients. Taken together, these findings suggest that TRPC6 is a novel predisposing gene for ASD that may act in a multiple-hit model. This is the first study to use iPSC-derived human neurons to model non-syndromic ASD and illustrate the potential of modeling genetically complex sporadic diseases using such cells. PMID:25385366

  3. Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

    PubMed Central

    Pissadaki, Eleftheria Kyriaki; Sidiropoulou, Kyriaki; Reczko, Martin; Poirazi, Panayiota

    2010-01-01

    The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code. PMID:21187899

  4. Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons

    PubMed Central

    Nicola, Wilten; Campbell, Sue Ann

    2013-01-01

    We analytically derive mean-field models for all-to-all coupled networks of heterogeneous, adapting, two-dimensional integrate and fire neurons. The class of models we consider includes the Izhikevich, adaptive exponential and quartic integrate and fire models. The heterogeneity in the parameters leads to different moment closure assumptions that can be made in the derivation of the mean-field model from the population density equation for the large network. Three different moment closure assumptions lead to three different mean-field systems. These systems can be used for distinct purposes such as bifurcation analysis of the large networks, prediction of steady state firing rate distributions, parameter estimation for actual neurons and faster exploration of the parameter space. We use the mean-field systems to analyze adaptation induced bursting under realistic sources of heterogeneity in multiple parameters. Our analysis demonstrates that the presence of heterogeneity causes the Hopf bifurcation associated with the emergence of bursting to change from sub-critical to super-critical. This is confirmed with numerical simulations of the full network for biologically reasonable parameter values. This change decreases the plausibility of adaptation being the cause of bursting in hippocampal area CA3, an area with a sizable population of heavily coupled, strongly adapting neurons. PMID:24416013

  5. Intermittent chaos, self-organization, and learning from synchronous synaptic activity in model neuron networks.

    PubMed Central

    Hoppensteadt, F C

    1989-01-01

    Self-organization of frequencies is studied by using model neurons called VCONs (voltage-controlled oscillator neuron models). These models give direct access to frequency information, in contrast to all-or-none neuron models, and they generate voltage spikes that phase-lock to oscillatory stimulation, similar to phase-locking of action potentials to oscillatory voltage stimulation observed in Hodgkin-Huxley preparations of squid axons. The rotation vector method is described and used to study how networks synchronize, even in the presence of noise or when damaged; the entropy of ratios of phases is used to construct an energy function that characterizes organized behavior. Computer simulations show that rotation numbers (output frequency/input frequency) describe both chaotic and nonchaotic behavior. Learning occurs when synaptic connections strengthen in response to stimulation that is synchronous with cell activity. It is shown that intermittent chaotic firing is suppressed and simple stable responses are enhanced by such learning in VCON networks. This analysis provides a rigorous basis for further investigation of the ideas of Wiener [Wiener, N. (1961) Cybernetics (MIT Press, Cambridge, MA), p. 191] on the origin of slow brain waves due to "the pulling together of frequencies." PMID:2717606

  6. Design of real-time locomotion generator with map-based neuronal models

    NASA Astrophysics Data System (ADS)

    Rulkov, Nikolai; Ayers, Joseph; Hunt, Mark

    2008-03-01

    We are developing an electronic nervous system for a biomimetic robot based on an established neurobiological model system, the Sea Lamprey. Undulatory locomotion of the lamprey is coordinated by a concatenated network of over 100 segmental central pattern generators (CPGs). To achieve real time operation in a DSP chip, we are using simple phenomenological models of neurons and synapses based on the dynamics of nonlinear maps. CPG networks based on known neuronal circuitry have replicated main properties of the dynamical behavior of the animal model. The results of numerical studies of the neuronal activity coordinating various swimming patterns in the reduced model of the CPG are considered. Both ascending and descending connections between segmental CPGs can mediate both forward and backward propagating flexion waves based on anterior or posterior bias by descending premotor commands. Bilaterally asymmetric biases of descending commands can mediate turning. The CPG outputs control 5 shape memory alloy actuators on each side to generate coordinated undulations. Two dorsal and ventral pitch actuators control the angle between the hull and undulator to control dive and climb. Descending commands are modulated by an analog compass, inclinometers, accelerometers and a short baseline sonar array to mediate homing by the vehicle on a sonar beacon.

  7. Bivariate cumulative probit model for the comparison of neuronal encoding hypotheses.

    PubMed

    Hillmann, Julia; Kneib, Thomas; Koepcke, Lena; Juárez Paz, León M; Kretzberg, Jutta

    2014-01-01

    Understanding the way stimulus properties are encoded in the nerve cell responses of sensory organs is one of the fundamental scientific questions in neurosciences. Different neuronal coding hypotheses can be compared by use of an inverse procedure called stimulus reconstruction. Here, based on different attributes of experimentally recorded neuronal responses, the values of certain stimulus properties are estimated by statistical classification methods. Comparison of stimulus reconstruction results then allows to draw conclusions about relative importance of covariate features. Since many stimulus properties have a natural order and can therefore be considered as ordinal, we introduce a bivariate ordinal probit model to obtain classifications for the combination of light intensity and velocity of a visual dot pattern based on different covariates extracted from recorded spike trains. For parameter estimation, we develop a Bayesian Gibbs sampler and incorporate penalized splines to model nonlinear effects. We compare the classification performance of different individual cell covariates and simple features of groups of neurons and find that the combination of at least two covariates increases the classification performance significantly. Furthermore, we obtain a non-linear effect for the first spike latency. The model is compared to a naïve Bayesian stimulus estimation method where it yields comparable misclassification rates for the given dataset. Hence, the bivariate ordinal probit model is shown to be a helpful tool for stimulus reconstruction particularly thanks to its flexibility with respect to the number of covariates as well as their scale and effect type. PMID:24186131

  8. Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

    PubMed Central

    Jolivet, Renaud; Coggan, Jay S.; Allaman, Igor; Magistretti, Pierre J.

    2015-01-01

    Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging. PMID:25719367

  9. Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble.

    PubMed

    Jolivet, Renaud; Coggan, Jay S; Allaman, Igor; Magistretti, Pierre J

    2015-02-01

    Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain's metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging. PMID:25719367

  10. Fast and stable numerical method for neuronal modelling

    NASA Astrophysics Data System (ADS)

    Hashemi, Soheil; Abdolali, Ali

    2016-11-01

    Excitable cell modelling is of a prime interest in predicting and targeting neural activity. Two main limits in solving related equations are speed and stability of numerical method. Since there is a tradeoff between accuracy and speed, most previously presented methods for solving partial differential equations (PDE) are focused on one side. More speed means more accurate simulations and therefore better device designing. By considering the variables in finite differenced equation in proper time and calculating the unknowns in the specific sequence, a fast, stable and accurate method is introduced in this paper for solving neural partial differential equations. Propagation of action potential in giant axon is studied by proposed method and traditional methods. Speed, consistency and stability of the methods are compared and discussed. The proposed method is as fast as forward methods and as stable as backward methods. Forward methods are known as fastest methods and backward methods are stable in any circumstances. Complex structures can be simulated by proposed method due to speed and stability of the method.

  11. MorphML: level 1 of the NeuroML standards for neuronal morphology data and model specification.

    PubMed

    Crook, Sharon; Gleeson, Padraig; Howell, Fred; Svitak, Joseph; Silver, R Angus

    2007-01-01

    Quantitative neuroanatomical data are important for the study of many areas of neuroscience, and the complexity of problems associated with neuronal structure requires that research from multiple groups across many disciplines be combined. However, existing neuron-tracing systems, simulation environments, and tools for the visualization and analysis of neuronal morphology data use a variety of data formats, making it difficult to exchange data in a readily usable way. The NeuroML project was initiated to address these issues, and here we describe an extensible markup language standard, MorphML, which defines a common data format for neuronal morphology data and associated metadata to facilitate data and model exchange, database creation, model publication, and data archiving. We describe the elements of the standard in detail and outline the mappings between this format and those used by a number of popular applications for reconstruction, simulation, and visualization of neuronal morphology. PMID:17873371

  12. Decreased amyloid-β and increased neuronal hyperactivity by immunotherapy in Alzheimer's models.

    PubMed

    Busche, Marc Aurel; Grienberger, Christine; Keskin, Aylin D; Song, Beomjong; Neumann, Ulf; Staufenbiel, Matthias; Förstl, Hans; Konnerth, Arthur

    2015-12-01

    Among the most promising approaches for treating Alzheimer's disease is immunotherapy with amyloid-β (Aβ)-targeting antibodies. Using in vivo two-photon imaging in mouse models, we found that two different antibodies to Aβ used for treatment were ineffective at repairing neuronal dysfunction and caused an increase in cortical hyperactivity. This unexpected finding provides a possible cellular explanation for the lack of cognitive improvement by immunotherapy in human studies. PMID:26551546

  13. A Framework for Modeling the Growth and Development of Neurons and Networks

    PubMed Central

    Zubler, Frederic; Douglas, Rodney

    2009-01-01

    The development of neural tissue is a complex organizing process, in which it is difficult to grasp how the various localized interactions between dividing cells leads relentlessly to global network organization. Simulation is a useful tool for exploring such complex processes because it permits rigorous analysis of observed global behavior in terms of the mechanistic axioms declared in the simulated model. We describe a novel simulation tool, CX3D, for modeling the development of large realistic neural networks such as the neocortex, in a physical 3D space. In CX3D, as in biology, neurons arise by the replication and migration of precursors, which mature into cells able to extend axons and dendrites. Individual neurons are discretized into spherical (for the soma) and cylindrical (for neurites) elements that have appropriate mechanical properties. The growth functions of each neuron are encapsulated in set of pre-defined modules that are automatically distributed across its segments during growth. The extracellular space is also discretized, and allows for the diffusion of extracellular signaling molecules, as well as the physical interactions of the many developing neurons. We demonstrate the utility of CX3D by simulating three interesting developmental processes: neocortical lamination based on mechanical properties of tissues; a growth model of a neocortical pyramidal cell based on layer-specific guidance cues; and the formation of a neural network in vitro by employing neurite fasciculation. We also provide some examples in which previous models from the literature are re-implemented in CX3D. Our results suggest that CX3D is a powerful tool for understanding neural development. PMID:19949465

  14. Complementary processing of haptic information by slowly and rapidly adapting neurons in the trigeminothalamic pathway. Electrophysiology, mathematical modeling and simulations of vibrissae-related neurons

    PubMed Central

    Sanchez-Jimenez, Abel; Torets, Carlos; Panetsos, Fivos

    2013-01-01

    Tonic (slowly adapting) and phasic (rapidly adapting) primary afferents convey complementary aspects of haptic information to the central nervous system: object location and texture the former, shape the latter. Tonic and phasic neural responses are also recorded in all relay stations of the somatosensory pathway, yet it is unknown their role in both, information processing and information transmission to the cortex: we don't know if tonic and phasic neurons process complementary aspects of haptic information and/or if these two types constitute two separate channels that convey complementary aspects of tactile information to the cortex. Here we propose to elucidate these two questions in the fast trigeminal pathway of the rat (PrV-VPM: principal trigeminal nucleus-ventroposteromedial thalamic nucleus). We analyze early and global behavior, latencies and stability of the responses of individual cells in PrV and medial lemniscus under 1–40 Hz stimulation of the whiskers in control and decorticated animals and we use stochastic spiking models and extensive simulations. Our results strongly suggest that in the first relay station of the somatosensory system (PrV): (1) tonic and phasic neurons process complementary aspects of whisker-related tactile information (2) tonic and phasic responses are not originated from two different types of neurons (3) the two responses are generated by the differential action of the somatosensory cortex on a unique type of PrV cell (4) tonic and phasic neurons do not belong to two different channels for the transmission of tactile information to the thalamus (5) trigeminothalamic transmission is exclusively performed by tonically firing neurons and (6) all aspects of haptic information are coded into low-pass, band-pass, and high-pass filtering profiles of tonically firing neurons. Our results are important for both, basic research on neural circuits and information processing, and development of sensory neuroprostheses. PMID:23761732

  15. Alteration of glial-neuronal metabolic interactions in a mouse model of Alexander disease

    PubMed Central

    Meisingset, Tore Wergeland; Risa, Øystein; Brenner, Michael; Messing, Albee; Sonnewald, Ursula

    2010-01-01

    Alexander disease is a rare and usually fatal neurological disorder characterized by the abundant presence of protein aggregates in astrocytes. Most cases result from dominant missense de novo mutations in the gene encoding glial fibrillary acidic protein (GFAP), but how these mutations lead to aggregate formation and compromise function is not known. A transgenic mouse line (Tg73.7) over-expressing human GFAP produces astrocytic aggregates indistinguishable from those seen in the human disease, making them a model of this disorder. To investigate possible metabolic changes associated with Alexander disease Tg73.7 mice and controls were injected simultaneously with [1-13C]glucose to analyze neuronal metabolism and [1,2-13C]acetate to monitor astrocytic metabolism. Brain extracts were analyzed by 1H magnetic resonance spectroscopy (MRS) to quantify amounts of several key metabolites, and by 13C MRS to analyze amino acid neurotransmitter metabolism. In the cerebral cortex, reduced utilization of [1,2-13C]acetate was observed for synthesis of glutamine, glutamate, and GABA, and the concentration of the marker for neuronal mitochondrial metabolism, N-acetylaspartate (NAA), was decreased. This indicates impaired astrocytic and neuronal metabolism and decreased transfer of glutamine from astrocytes to neurons compared to control mice. In the cerebellum, glutamine and GABA content and labeling from [1-13C]glucose were increased. Evidence for brain edema was found in the increased amount of water and of the osmoregulators myo-inositol and taurine. It can be concluded that astrocyte – neuronal interactions were altered differently in distinct regions. PMID:20544858

  16. Plasticity-modulated seizure dynamics for seizure termination in realistic neuronal models

    NASA Astrophysics Data System (ADS)

    Koppert, M. M. J.; Kalitzin, S.; Lopes da Silva, F. H.; Viergever, M. A.

    2011-08-01

    In previous studies we showed that autonomous absence seizure generation and termination can be explained by realistic neuronal models eliciting bi-stable dynamics. In these models epileptic seizures are triggered either by external stimuli (reflex epilepsies) or by internal fluctuations. This scenario predicts exponential distributions of the duration of the seizures and of the inter-ictal intervals. These predictions were validated in rat models of absence epilepsy, as well as in a few human cases. Nonetheless, deviations from the predictions with respect to seizure duration distributions remained unexplained. The objective of the present work is to implement a simple but realistic computational model of a neuronal network including synaptic plasticity and ionic current dynamics and to explore the dynamics of the model with special emphasis on the distributions of seizure and inter-ictal period durations. We use as a basis our lumped model of cortical neuronal circuits. Here we introduce 'activity dependent' parameters, namely post-synaptic voltage-dependent plasticity, as well as a voltage-dependent hyperpolarization-activated current driven by slow and fast activation conductances. We examine the distributions of the durations of the seizure-like model activity and the normal activity, described respectively by the limit cycle and the steady state in the dynamics. We use a parametric γ-distribution fit as a quantifier. Our results show that autonomous, activity-dependent membrane processes can account for experimentally obtained statistical distributions of seizure durations, which were not explainable using the previous model. The activity-dependent membrane processes that display the strongest effect in accounting for these distributions are the hyperpolarization-dependent cationic (Ih) current and the GABAa plastic dynamics. Plastic synapses (NMDA-type) in the interneuron population show only a minor effect. The inter-ictal statistics retain their

  17. CREBBP re-arrangements affect protein function and lead to aberrant neuronal differentiation.

    PubMed

    Sharma, Neeti; Jadhav, Shweta P; Bapat, Sharmila A

    2010-01-01

    Biallelic inactivation of the CREB-binding protein (CREBBP) a transcriptional co-activator produces an embryonic lethal phenotype in mice. In humans, re-arrangements in CREBBP are associated with the Rubinstein-Taybi Syndrome (RSTS) that is characterised by craniofacial, skeletal and neuronal symptoms. Neuronal defects in RSTS can be attributed to genetic re-arrangements in CREBBP, which has been implicated in synaptic plasticity and long-term memory. The present study was designed to investigate the role of CREBBP re-arrangements during neuronal differentiation. Towards this, deletion constructs of pCREBBP, viz. pDeltaCB-HAT and pDeltaHAT-CT were generated and transfected into NT2 cells. Expression profiling of the components of Notch, Wnt, SHH and Retinoid signaling along with screening of the neuronal markers was carried out in the NT2 cells and their mutant derivatives. ChIP-PCRs along with co-immunoprecipitations were also performed in these cells to investigate defects due to inappropriate interaction of mutated CREEBP with the corresponding transcription factor and other transcription regulatory proteins both at steady state as well as during differentiation. Mutant NT2 cells lacking the CREB, BROMO and HAT domains (CB-HAT) were highly proliferative and showed limited differentiation; while mutant NT2 cells expressing CREBBP lacking the HAT and CTAD domains (HAT-CT) are proliferation deficient and differentiate rapidly albeit generating an insufficient number of neurons. Altered CREBBP structure resulted in changes in HAT activity, cell cycle profiles and expression of basal levels of components of Notch, SHH, Wnt and retinoid pathways known to be critical in the proliferation and differentiation of neuronal progenitors. At the chromatin level, aberrant signaling correlated with altered binding affinities of the (CREBBP-transcription factor) complexes to promoter regions of components of these pathways. Thus, differentiation defects are manifested early at

  18. Stability of the synchronized network of Hindmarsh-Rose neuronal models with nearest and global couplings

    NASA Astrophysics Data System (ADS)

    Dtchetgnia Djeundam, S. R.; Yamapi, R.; Filatrella, G.; Kofane, T. C.

    2015-05-01

    We analytically and numerically investigate a set of N identical and non-identical Hindmarsh-Rose neuronal models with nearest-neighbor and global couplings. The stability boundary of the synchronized states is analyzed using the Master Stability Function approach for the case of identical oscillators (complete synchronization) and the Kuramoto order parameter for the disordered case (phase synchronization). We find that, through a linear coupling modeling electrical synapses, complete synchronization occurs in a system of many nearest-neighbor or globally coupled identical oscillators, and in the case of non-identical neurons it is stable even in the presence of a spread of the parameters. We find that the Hindmarsh-Rose neuronal models can synchronize when coupled through the action of potential variable or through the interaction by rapid flows of ions through the membrane. The degree of connectivity of the network favors synchronization: in the global coupling case, the threshold for the in-phase state stabilizes when the number of dynamical units increases. The transition from disordered to the ordered state is a second order dynamical phase transition, although very sharp.

  19. Aminochrome induces dopaminergic neuronal dysfunction: a new animal model for Parkinson's disease.

    PubMed

    Herrera, Andrea; Muñoz, Patricia; Paris, Irmgard; Díaz-Veliz, Gabriela; Mora, Sergio; Inzunza, Jose; Hultenby, Kjell; Cardenas, Cesar; Jaña, Fabián; Raisman-Vozari, Rita; Gysling, Katia; Abarca, Jorge; Steinbusch, Harry W M; Segura-Aguilar, Juan

    2016-09-01

    L-Dopa continues to be the gold drug in Parkinson's disease (PD) treatment from 1967. The failure to translate successful results from preclinical to clinical studies can be explained by the use of preclinical models which do not reflect what happens in the disease since these induce a rapid and extensive degeneration; for example, MPTP induces a severe Parkinsonism in only 3 days in humans contrasting with the slow degeneration and progression of PD. This study presents a new anatomy and develops preclinical model based on aminochrome which induces a slow and progressive dysfunction of dopaminergic neurons. The unilateral injection of aminochrome into rat striatum resulted in (1) contralateral rotation when the animals are stimulated with apomorphine; (2) absence of significant loss of tyrosine hydroxylase-positive neuronal elements both in substantia nigra and striatum; (3) cell shrinkage; (4) significant reduction of dopamine release; (5) significant increase in GABA release; (6) significant decrease in the number of monoaminergic presynaptic vesicles; (7) significant increase of dopamine concentration inside of monoaminergic vesicles; (8) significant increase of damaged mitochondria; (9) significant decrease of ATP level in the striatum (10) significant decrease in basal and maximal mitochondrial respiration. These results suggest that aminochrome induces dysfunction of dopaminergic neurons where the contralateral behavior can be explained by aminochrome-induced ATP decrease required both for anterograde transport of synaptic vesicles and dopamine release. Aminochrome could be implemented as a new model neurotoxin to study Parkinson's disease. PMID:27001668

  20. Acute Neuronal Injury and Blood Genomic Profiles in a Nonhuman Primate Model for Ischemic Stroke

    PubMed Central

    Rodriguez-Mercado, Rafael; Ford, Gregory D; Xu, Zhenfeng; Kraiselburd, Edmundo N; Martinez, Melween I; Eterović, Vesna A; Colon, Edgar; Rodriguez, Idia V; Portilla, Peter; Ferchmin, Pedro A; Gierbolini, Lynette; Rodriguez-Carrasquillo, Maria; Powell, Michael D; Pulliam, John VK; McCraw, Casey O; Gates, Alicia; Ford, Byron D

    2012-01-01

    The goal of this study was to characterize acute neuronal injury in a novel nonhuman primate (NHP) ischemic stroke model by using multiple outcome measures. Silk sutures were inserted into the M1 segment of the middle cerebral artery of rhesus macaques to achieve permanent occlusion of the vessel. The sutures were introduced via the femoral artery by using endovascular microcatheterization techniques. Within hours after middle cerebral artery occlusion (MCAO), infarction was detectable by using diffusion-weighted MRI imaging. The infarcts expanded by 24 h after MCAO and then were detectable on T2-weighted images. The infarcts seen by MRI were consistent with neuronal injury demonstrated histologically. Neurobehavioral function after MCAO was determined by using 2 neurologic testing scales. Neurologic assessments indicated that impairment after ischemia was limited to motor function in the contralateral arm; other neurologic and behavioral parameters were largely unaffected. We also used microarrays to examine gene expression profiles in peripheral blood mononuclear cells after MCAO-induced ischemia. Several genes were altered in a time-dependent manner after MCAO, suggesting that this ischemia model may be suitable for identifying blood biomarkers associated with the presence and severity of ischemia. This NHP stroke model likely will facilitate the elucidation of mechanisms associated with acute neuronal injury after ischemia. In addition, the ability to identify candidate blood biomarkers in NHP after ischemia may prompt the development of new strategies for the diagnosis and treatment of ischemic stroke in humans. PMID:23114047

  1. Using Human iPSC-Derived Neurons to Model TAU Aggregation

    PubMed Central

    Verheyen, An; Diels, Annick; Dijkmans, Joyce; Oyelami, Tutu; Meneghello, Giulia; Mertens, Liesbeth; Versweyveld, Sofie; Borgers, Marianne; Buist, Arjan; Peeters, Pieter; Cik, Miroslav

    2015-01-01

    Alzheimer’s disease and frontotemporal dementia are amongst the most common forms of dementia characterized by the formation and deposition of abnormal TAU in the brain. In order to develop a translational human TAU aggregation model suitable for screening, we transduced TAU harboring the pro-aggregating P301L mutation into control hiPSC-derived neural progenitor cells followed by differentiation into cortical neurons. TAU aggregation and phosphorylation was quantified using AlphaLISA technology. Although no spontaneous aggregation was observed upon expressing TAU-P301L in neurons, seeding with preformed aggregates consisting of the TAU-microtubule binding repeat domain triggered robust TAU aggregation and hyperphosphorylation already after 2 weeks, without affecting general cell health. To validate our model, activity of two autophagy inducers was tested. Both rapamycin and trehalose significantly reduced TAU aggregation levels suggesting that iPSC-derived neurons allow for the generation of a biologically relevant human Tauopathy model, highly suitable to screen for compounds that modulate TAU aggregation. PMID:26720731

  2. Electrical coupling between model midbrain dopamine neurons: effects on firing pattern and synchrony.

    PubMed

    Komendantov, Alexander O; Canavier, Carmen C

    2002-03-01

    The role of gap junctions between midbrain dopamine (DA) neurons in mechanisms of firing pattern generation and synchronization has not been well characterized experimentally. We modified a multi-compartment model of DA neuron by adding a spike-generating mechanism and electrically coupling the dendrites of two such neurons through gap junctions. The burst-generating mechanism in the model neuron results from the interaction of a N-methyl-D-aspartate (NMDA)-induced current and the sodium pump. The firing patterns exhibited by the two model neurons included low frequency (2-7 Hz) spiking, high-frequency (13-20 Hz) spiking, irregular spiking, regular bursting, irregular bursting, and leader/follower bursting, depending on the parameter values used for the permeability for NMDA-induced current and the conductance for electrical coupling. All of these firing patterns have been observed in physiological neurons, but a systematic dependence of the firing pattern on the covariation of these two parameters has not been established experimentally. Our simulations indicate that electrical coupling facilitates NMDA-induced burst firing via two mechanisms. The first can be observed in a pair of identical cells. At low frequencies (low NMDA), as coupling strength was increased, only a transition from asynchronous to synchronous single-spike firing was observed. At high frequencies (high NMDA), increasing the strength of the electrical coupling in an identical pair resulted in a transition from high-frequency single-spike firing to burst firing, and further increases led to synchronous high-frequency spiking. Weak electrical coupling destabilizes the synchronous solution of the fast spiking subsystems, and in the presence of a slowly varying sodium concentration, the desynchronized spiking solution leads to bursts that are approximately in phase with spikes that are not in phase. Thus this transitional mechanism depends critically on action potential dynamics. The second

  3. Effects of Fluvastatin on Characteristics of Stellate Ganglion Neurons in a Rabbit Model of Myocardial Ischemia

    PubMed Central

    Cheng, Li-Jun; Li, Guang-Ping; Li, Jian; Chen, Yan; Wang, Xing-Hua

    2016-01-01

    Background: Stellate ganglion (SG) plays an important role in cardiovascular diseases. The electrical activity of SG neurons is involved in the regulation of the autonomic nervous system. The aim of this research was to evaluate the effects of fluvastatin on the electrophysiological characteristics of SG neurons in a rabbit model of myocardial ischemia (MI). Methods: The MI model was induced by abdominal subcutaneous injections of isoproterenol in rabbits. Using whole-cell patch clamp technique, we studied the characteristic changes of ion channels and action potentials (APs) in isolated SG neurons in control group (n = 20), MI group (n = 20) and fluvastatin pretreated group (fluvastatin group, n = 20), respectively. The protein expression of sodium channel in SG was determined by immunohistochemical analysis. Results: MI and the intervention of fluvastatin did not have significantly influence on the characteristics of delayed rectifier potassium channel currents. The maximal peak current density of sodium channel currents in SG neurons along with the characteristics of activation curves, inactivation curves, and recovery curves after inactivation were changed in the MI group. The peak current densities of control group, MI group, and fluvastatin group (n = 10 in each group) were −71.77 ± 23.22 pA/pF, −126.75 ± 18.90 pA/pF, and −86.42 ± 28.30 pA/pF, respectively (F = 4.862, P = 0.008). Fluvastatin can decrease the current amplitude which has been increased by MI. Moreover, fluvastatin induced the inactivation curves and post-inactive recovery curves moving to the position of the control group. But the expression of sodium channel-associated protein (Nav1.7) had no significantly statistical difference among the three groups. The percentages of Nav1.7 protein in control group, MI group, and fluvastatin group (n = 5 in each group) were 21.49 ± 7.33%, 28.53 ± 8.26%, and 21.64 ± 2.78%, respectively (F = 1.495, P = 0.275). Moreover, MI reduced the electrical

  4. Oscillatory Pattern Generation of the Olfactory Center Using Pulse-Type Hardware Chaotic Neuron Models

    NASA Astrophysics Data System (ADS)

    Saito, Ken; Hatano, Hirokazu; Saito, Minoru; Sekine, Yoshifumi

    Oscillatory patterns of electrical activity are a ubiquitous feature in nervous systems. Oscillatory patterns play an important role in the processing of sensory information pattern recognition. For example, earlier reports describe that the oscillatory patterns in the olfactory center of the land slug are changed by odor stimuli to the tentacles. Olfactory processing has also been studied in relation to rabbits and land slugs through the construction and use of mathematical neural network models. However, a large-scale model is necessary for the study of a model which has sensory information recognition by the oscillatory pattern. Therefore, the construction of a hardware model that can generate oscillatory patterns is desired because nonlinear operations can be processed at higher speeds than the mathematical model. We are studying about the neural network using hardware neuron models to construct the olfactory center model of the living organisms. In the present study, we discuss about the oscillatory pattern generation of the olfactory center using pulse-type hardware chaotic neuron models. Our model shows periodic, quasi-periodic and chaotic oscillations such as the olfactory center of living organisms by changing the synaptic connection weights.

  5. Functional Integration of Grafted Neural Stem Cell-Derived Dopaminergic Neurons Monitored by Optogenetics in an In Vitro Parkinson Model

    PubMed Central

    Tønnesen, Jan; Parish, Clare L.; Sørensen, Andreas T.; Andersson, Angelica; Lundberg, Cecilia; Deisseroth, Karl; Arenas, Ernest; Lindvall, Olle; Kokaia, Merab

    2011-01-01

    Intrastriatal grafts of stem cell-derived dopamine (DA) neurons induce behavioral recovery in animal models of Parkinson's disease (PD), but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral mesencephalon of tyrosine hydroxylase-GFP transgenic mice were expanded as neurospheres and transplanted into organotypic cultures of wild type mouse striatum. Differentiated GFP-labeled DA neurons in the grafts exhibited mature neuronal properties, including spontaneous firing of action potentials, presence of post-synaptic currents, and functional expression of DA D2 autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation or inhibition of grafted cells and host neurons using channelrhodopsin-2 (ChR2) and halorhodopsin (NpHR), respectively, revealed complex, bi-directional synaptic interactions between grafted cells and host neurons and extensive synaptic connectivity within the graft. Our data demonstrate for the first time using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying behavioral recovery as well as adverse effects following stem cell-based DA cell replacement strategies in PD. PMID:21394212

  6. Exploring action potential initiation in neurons exposed to DC electric fields through dynamical analysis of conductance-based model

    NASA Astrophysics Data System (ADS)

    Yi, Guo-Sheng; Wang, Jiang; Han, Chun-Xiao; Deng, Bin; Wei, Xi-Le; Jin, Qi-Tao

    2014-05-01

    Noninvasive direct current (DC) electric stimulation of central nervous system is today a promising therapeutic option to alleviate the symptoms of a number of neurological disorders. Despite widespread use of this noninvasive brain modulation technique, a generalizable explanation of its biophysical basis has not been described which seriously restricts its application and development. This paper investigated the dynamical behaviors of Hodgkin's three classes of neurons exposed to DC electric field based on a conductance-based neuron model. With phase plane and bifurcation analysis, the different responses of each class of neuron to the same stimulation are shown to derive from distinct spike initiating dynamics. Under the effects of negative DC electric field, class 1 neuron generates repetitive spike through a saddle-node on invariant circle (SNIC) bifurcation, while it ceases this repetitive behavior through a Hopf bifurcation; Class 2 neuron generates repetitive spike through a Hopf bifurcation, meanwhile it ceases this repetitive behavior also by a Hopf bifurcation; Class 3 neuron can generate single spike through a quasi-separatrix-crossing (QSC) at first, then it generates repetitive spike through a Hopf bifurcation, while it ceases this repetitive behavior through a SNIC bifurcation. Furthermore, three classes of neurons' spiking frequency f-electric field E (f-E) curves all have parabolic shape. Our results highlight the effects of external DC electric field on neuronal activity from the biophysical modeling point of view. It can contribute to the application and development of noninvasive DC brain modulation technique.

  7. Experimental Models of Status Epilepticus and Neuronal Injury for Evaluation of Therapeutic Interventions

    PubMed Central

    Reddy, Doodipala Samba; Kuruba, Ramkumar

    2013-01-01

    This article describes current experimental models of status epilepticus (SE) and neuronal injury for use in the screening of new therapeutic agents. Epilepsy is a common neurological disorder characterized by recurrent unprovoked seizures. SE is an emergency condition associated with continuous seizures lasting more than 30 min. It causes significant mortality and morbidity. SE can cause devastating damage to the brain leading to cognitive impairment and increased risk of epilepsy. Benzodiazepines are the first-line drugs for the treatment of SE, however, many people exhibit partial or complete resistance due to a breakdown of GABA inhibition. Therefore, new drugs with neuroprotective effects against the SE-induced neuronal injury and degeneration are desirable. Animal models are used to study the pathophysiology of SE and for the discovery of newer anticonvulsants. In SE paradigms, seizures are induced in rodents by chemical agents or by electrical stimulation of brain structures. Electrical stimulation includes perforant path and self-sustaining stimulation models. Pharmacological models include kainic acid, pilocarpine, flurothyl, organophosphates and other convulsants that induce SE in rodents. Neuronal injury occurs within the initial SE episode, and animals exhibit cognitive dysfunction and spontaneous seizures several weeks after this precipitating event. Current SE models have potential applications but have some limitations. In general, the experimental SE model should be analogous to the human seizure state and it should share very similar neuropathological mechanisms. The pilocarpine and diisopropylfluorophosphate models are associated with prolonged, diazepam-insensitive seizures and neurodegeneration and therefore represent paradigms of refractory SE. Novel mechanism-based or clinically relevant models are essential to identify new therapies for SE and neuroprotective interventions. PMID:24013377

  8. Neuronal NOS and cyclooxygenase-2 contribute to DNA damage in a mouse model of Parkinson disease.

    PubMed

    Hoang, Tuan; Choi, Dong-Kug; Nagai, Makiko; Wu, Du-Chu; Nagata, Tetsuya; Prou, Delphine; Wilson, Glenn L; Vila, Miquel; Jackson-Lewis, Vernice; Dawson, Valina L; Dawson, Ted M; Chesselet, Marie-Françoise; Przedborski, Serge

    2009-10-01

    DNA damage is a proposed pathogenic factor in neurodegenerative disorders such as Parkinson disease. To probe the underpinning mechanism of such neuronal perturbation, we sought to produce an experimental model of DNA damage. We thus first assessed DNA damage by in situ nick translation and emulsion autoradiography in the mouse brain after administration of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP; 4 x 20 mg/kg, ip, every 2 h), a neurotoxin known to produce a model of Parkinson disease. Here we show that DNA strand breaks occur in vivo in this mouse model of Parkinson disease with kinetics and a topography that parallel the degeneration of substantia nigra neurons, as assessed by FluoroJade labeling. Previously, nitric oxide synthase and cyclooxygenase-2 (Cox-2) were found to modulate MPTP-induced dopaminergic neuronal death. We thus assessed the contribution of these enzymes to DNA damage in mice lacking neuronal nitric oxide synthase (nNOS), inducible nitric oxide synthase (iNOS), or Cox-2. We found that the lack of Cox-2 and nNOS activities but not of iNOS activity attenuated MPTP-related DNA damage. We also found that not only nuclear, but also mitochondrial, DNA is a target for the MPTP insult. These results suggest that the loss of genomic integrity can be triggered by the concerted actions of nNOS and Cox-2 and provide further support to the view that DNA damage may contribute to the neurodegenerative process in Parkinson disease. PMID:19616617

  9. A computational model to investigate astrocytic glutamate uptake influence on synaptic transmission and neuronal spiking.

    PubMed

    Allam, Sushmita L; Ghaderi, Viviane S; Bouteiller, Jean-Marie C; Legendre, Arnaud; Ambert, Nicolas; Greget, Renaud; Bischoff, Serge; Baudry, Michel; Berger, Theodore W

    2012-01-01

    Over the past decades, our view of astrocytes has switched from passive support cells to active processing elements in the brain. The current view is that astrocytes shape neuronal communication and also play an important role in many neurodegenerative diseases. Despite the growing awareness of the importance of astrocytes, the exact mechanisms underlying neuron-astrocyte communication and the physiological consequences of astrocytic-neuronal interactions remain largely unclear. In this work, we define a modeling framework that will permit to address unanswered questions regarding the role of astrocytes. Our computational model of a detailed glutamatergic synapse facilitates the analysis of neural system responses to various stimuli and conditions that are otherwise difficult to obtain experimentally, in particular the readouts at the sub-cellular level. In this paper, we extend a detailed glutamatergic synaptic model, to include astrocytic glutamate transporters. We demonstrate how these glial transporters, responsible for the majority of glutamate uptake, modulate synaptic transmission mediated by ionotropic AMPA and NMDA receptors at glutamatergic synapses. Furthermore, we investigate how these local signaling effects at the synaptic level are translated into varying spatio-temporal patterns of neuron firing. Paired pulse stimulation results reveal that the effect of astrocytic glutamate uptake is more apparent when the input inter-spike interval is sufficiently long to allow the receptors to recover from desensitization. These results suggest an important functional role of astrocytes in spike timing dependent processes and demand further investigation of the molecular basis of certain neurological diseases specifically related to alterations in astrocytic glutamate uptake, such as epilepsy. PMID:23060782

  10. Modeling the electrical behavior of anatomically complex neurons using a network analysis program: passive membrane.

    PubMed

    Segev, I; Fleshman, J W; Miller, J P; Bunow, B

    1985-01-01

    We describe the application of a popular and widely available electrical circuit simulation program called SPICE to modeling the electrical behavior of neurons with passive membrane properties and arbitrarily complex dendritic trees. Transient responses may be calculated at any location in the cell model following current, voltage or conductance perturbations at any point. A numbering method is described for binary trees which is helpful in transforming complex dendritic structures into a coded list of short cylindrical dendritic segments suitable for input to SPICE. Individual segments are modeled as isopotential compartments comprised of a parallel resistor and capacitor, representing the transmembrane impedance, in series with one or two core resistors. Synaptic current is modeled by a current source controlled by the local membrane potential and an "alpha-shaped" voltage, thus simulating a conductance change in series with a driving potential. Extensively branched test cell circuits were constructed which satisfied the equivalent cylinder constraints (Rall 1959). These model neurons were perturbed by independent current sources and by synaptic currents. Responses calculated by SPICE are compared with analytical results. With appropriately chosen model parameters, extremely accurate transient calculations may be obtained. Details of the SPICE circuit elements are presented, along with illustrative examples sufficient to allow implementation of passive nerve cell models on a number of common computers. Methods for modeling excitable membrane are presented in the companion paper (Bunow et al. 1985). PMID:3841013

  11. The locust olfactory system as a case study for modeling dynamics of neurobiological networks: from discrete time neurons to continuous time neurons.

    PubMed

    Quenet, B; Horcholle-Bossavit, G

    2007-11-01

    Both chaotic and periodic activities are observed in networks of the central nervous systems. We choose the locust olfactory system as a good case study to analyze the relationships between networks' structure and the types of dynamics involved in coding mechanisms. In our modeling approach, we first build a fully connected recurrent network of synchronously updated McCulloch and Pitts neurons (MC-P type). In order to measure the use of the temporal dimension in the complex spatio-temporal patterns produced by the networks, we have defined an index the Normalized Euclidian Distance NED. We find that for appropriate parameters of input and connectivity, when adding some strong connections to the initial random synaptic matrices, it was easy to get the emergence of both robust oscillations and distributed synchrony in the spatiotemporal patterns. Then, in order to validate the MC-P model as a tool for analysis for network properties, we examine the dynamic behavior of networks of continuous time model neuron (Izhikevitch Integrate and Fire model -IFI-), implementing the same network characteristics. In both models, similarly to biological PN, the activity of excitatory neurons are phase-locked to different cycles of oscillations which remind the ones of the local field potential (LFP), and nevertheless exhibit dynamic behavior complex enough to be the basis of spatio-temporal codes. PMID:18075120

  12. Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model

    PubMed Central

    Teka, Wondimu; Marinov, Toma M.; Santamaria, Fidel

    2014-01-01

    The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation. PMID:24675903

  13. Activin A Protects Midbrain Neurons in the 6-Hydroxydopamine Mouse Model of Parkinson’s Disease

    PubMed Central

    Li, Kong M.; Vissel, Bryce

    2015-01-01

    Parkinson’s disease (PD) is a chronic neurodegenerative disease characterized by a significant loss of dopaminergic neurons within the substantia nigra pars compacta (SNpc) and a subsequent loss of dopamine (DA) within the striatum. Despite advances in the development of pharmacological therapies that are effective at alleviating the symptoms of PD, the search for therapeutic treatments that halt or slow the underlying nigral degeneration remains a particular challenge. Activin A, a member of the transforming growth factor β superfamily, has been shown to play a role in the neuroprotection of midbrain neurons against 6-hydroxydopamine (6-OHDA) in vitro, suggesting that activin A may offer similar neuroprotective effects in in vivo models of PD. Using robust stereological methods, we found that intrastriatal injections of 6-OHDA results in a significant loss of both TH positive and NeuN positive populations in the SNpc at 1, 2, and 3 weeks post-lesioning in drug naïve mice. Exogenous application of activin A for 7 days, beginning the day prior to 6-OHDA administration, resulted in a significant survival of both dopaminergic and total neuron numbers in the SNpc against 6-OHDA-induced toxicity. However, we found no corresponding protection of striatal DA or dopamine transporter (DAT) expression levels in animals receiving activin A compared to vehicle controls. These results provide the first evidence that activin A exerts potent neuroprotection in a mouse model of PD, however this neuroprotection may be localized to the midbrain. PMID:25902062

  14. Ordering Dynamics in Neuron Activity Pattern Model: An Insight to Brain Functionality

    PubMed Central

    Gundh, Jasleen; Singh, Awaneesh; Singh, R. K. Brojen

    2015-01-01

    We study the domain ordering kinetics in d = 2 ferromagnets which corresponds to populated neuron activities with both long-ranged interactions, V(r) ∼ r−n and short-ranged interactions. We present the results from comprehensive Monte Carlo (MC) simulations for the nonconserved Ising model with n ≥ 2, interaction range considering near and far neighbors. Our model results could represent the long-ranged neuron kinetics (n ≤ 4) in consistent with the same dynamical behaviour of short-ranged case (n ≥ 4) at far below and near criticality. We found that emergence of fast and slow kinetics of long and short ranged case could imitate the formation of connections among near and distant neurons. The calculated characteristic length scale in long-ranged interaction is found to be n independent (L(t) ∼ t1/(n−2)), whereas short-ranged interaction follows L(t) ∼ t1/2 law and approximately preserve universality in domain kinetics. Further, we did the comparative study of phase ordering near the critical temperature which follows different behaviours of domain ordering near and far critical temperature but follows universal scaling law. PMID:26506525

  15. Homoclinic Spike adding in a neuronal model in the presence of noise

    NASA Astrophysics Data System (ADS)

    Fuwape, Ibiyinka; Neiman, Alexander; Shilnikov, Andrey

    2008-03-01

    We study the influence of noise on a spike adding transitions within the bursting activity in a Hodgkin-Huxley-type model of the leech heart interneuron. Spike adding in this model occur via homoclinic bifurcation of a saddle periodic orbit. Although narrow chaotic regions are observed near bifurcation transition, overall bursting dynamics is regular and is characterized by a constant number of spikes per burst. Experimental studies, however, show variability of bursting patterns whereby number of spikes per burst varies randomly. Thus, introduction of external synaptic noise is a necessary step to account for variability of burst durations observed experimentally. We show that near every such transition the neuron is highly sensitive to random perturbations that lead to and enhance broadly the regions of chaotic dynamics of the cell. For each spike adding transition there is a critical noise level beyond which the dynamics of the neuron becomes chaotic throughout the entire region of the given transition. Noise-induced chaotic dynamics is characterized in terms of the Lyapunov exponents and the Shannon entropy and reflects variability of firing patterns with various numbers of spikes per burst, traversing wide range of the neuron's parameters

  16. Mathematical Models for Sleep-Wake Dynamics: Comparison of the Two-Process Model and a Mutual Inhibition Neuronal Model

    PubMed Central

    Skeldon, Anne C.; Dijk, Derk-Jan; Derks, Gianne

    2014-01-01

    Sleep is essential for the maintenance of the brain and the body, yet many features of sleep are poorly understood and mathematical models are an important tool for probing proposed biological mechanisms. The most well-known mathematical model of sleep regulation, the two-process model, models the sleep-wake cycle by two oscillators: a circadian oscillator and a homeostatic oscillator. An alternative, more recent, model considers the mutual inhibition of sleep promoting neurons and the ascending arousal system regulated by homeostatic and circadian processes. Here we show there are fundamental similarities between these two models. The implications are illustrated with two important sleep-wake phenomena. Firstly, we show that in the two-process model, transitions between different numbers of daily sleep episodes can be classified as grazing bifurcations. This provides the theoretical underpinning for numerical results showing that the sleep patterns of many mammals can be explained by the mutual inhibition model. Secondly, we show that when sleep deprivation disrupts the sleep-wake cycle, ostensibly different measures of sleepiness in the two models are closely related. The demonstration of the mathematical similarities of the two models is valuable because not only does it allow some features of the two-process model to be interpreted physiologically but it also means that knowledge gained from study of the two-process model can be used to inform understanding of the behaviour of the mutual inhibition model. This is important because the mutual inhibition model and its extensions are increasingly being used as a tool to understand a diverse range of sleep-wake phenomena such as the design of optimal shift-patterns, yet the values it uses for parameters associated with the circadian and homeostatic processes are very different from those that have been experimentally measured in the context of the two-process model. PMID:25084361

  17. Alzheimer's Proteins, Oxidative Stress, and Mitochondrial Dysfunction Interplay in a Neuronal Model of Alzheimer's Disease

    PubMed Central

    Bobba, Antonella; Petragallo, Vito A.; Marra, Ersilia; Atlante, Anna

    2010-01-01

    In this paper, we discuss the interplay between beta-amyloid (Aβ) peptide, Tau fragments, oxidative stress, and mitochondria in the neuronal model of cerebellar granule neurons (CGNs) in which the molecular events reminiscent of AD are activated. The identification of the death route and the cause/effect relationships between the events leading to death could be helpful to manage the progression of apoptosis in neurodegeneration and to define antiapoptotic treatments acting on precocious steps of the death process. Mitochondrial dysfunction is among the earliest events linked to AD and might play a causative role in disease onset and progression. Recent studies on CGNs have shown that adenine nucleotide translocator (ANT) impairment, due to interaction with toxic N-ter Tau fragment, contributes in a significant manner to bioenergetic failure and mitochondrial dysfunction. These findings open a window for new therapeutic strategies aimed at preserving and/or improving mitochondrial function. PMID:20862336

  18. Effect of spontaneous activity on stimulus detection in a simple neuronal model.

    PubMed

    Levakova, Marie

    2016-06-01

    It is studied what level of a continuous-valued signal is optimally estimable on the basis of first-spike latency neuronal data. When a spontaneous neuronal activity is present, the first spike after the stimulus onset may be caused either by the stimulus itself, or it may be a result of the prevailing spontaneous activity. Under certain regularity conditions, Fisher information is the inverse of the variance of the best estimator. It can be considered as a function of the signal intensity and then indicates accuracy of the estimation for each signal level. The Fisher information is normalized with respect to the time needed to obtain an observation. The accuracy of signal level estimation is investigated in basic discharge patterns modelled by a Poisson and a renewal process and the impact of the complex interaction between spontaneous activity and a delay of the response is shown. PMID:27106186

  19. Modelling the anesthetized brain with ensembles of neuronal and astrocytic oscillators

    NASA Astrophysics Data System (ADS)

    Hansard, T.; Hale, A. C.; Stefanovska, A.

    2013-01-01

    We propose a minimalistic model of the anesthetized brain in order to study the generation of rhythms observed in electroencephalograms (EEGs) recorded from anesthetized humans. We propose that non-neuronal brain cells-astrocytes-play an important role in brain dynamics and that oscillation-based models may provide a simple way to study such dynamics. The model is capable of replicating the main features (i.e. slow and alpha oscillations) observed in EEGs. In addition, this model suggests that astrocytes are integral to the generation of slow EEG (˜0.7 Hz) rhythms. By including astrocytes in the model we take a first step towards investigating the interaction of the brain and cardiovasular system which are primarily connected via astrocytes. The model also illustrates that rich nonlinear dynamics can arise from basic oscillatory "building blocks" and therefore complex systems may be modelled in an uncomplicated way.

  20. Brain-derived neurotrophic factor as an indicator of chemical neurotoxicity: an animal-free CNS cell culture model.

    PubMed

    Woehrling, Elizabeth K; Hill, Eric J; Nagel, David; Coleman, Michael D

    2013-12-01

    Recent changes to the legislation on chemicals and cosmetics testing call for a change in the paradigm regarding the current 'whole animal' approach for identifying chemical hazards, including the assessment of potential neurotoxins. Accordingly, since 2004, we have worked on the development of the integrated co-culture of post-mitotic, human-derived neurons and astrocytes (NT2.N/A), for use as an in vitro functional central nervous system (CNS) model. We have used it successfully to investigate indicators of neurotoxicity. For this purpose, we used NT2.N/A cells to examine the effects of acute exposure to a range of test chemicals on the cellular release of brain-derived neurotrophic factor (BDNF). It was demonstrated that the release of this protective neurotrophin into the culture medium (above that of control levels) occurred consistently in response to sub-cytotoxic levels of known neurotoxic, but not non-neurotoxic, chemicals. These increases in BDNF release were quantifiable, statistically significant, and occurred at concentrations below those at which cell death was measureable, which potentially indicates specific neurotoxicity, as opposed to general cytotoxicity. The fact that the BDNF immunoassay is non-invasive, and that NT2.N/A cells retain their functionality for a period of months, may make this system useful for repeated-dose toxicity testing, which is of particular relevance to cosmetics testing without the use of laboratory animals. In addition, the production of NT2.N/A cells without the use of animal products, such as fetal bovine serum, is being explored, to produce a fully-humanised cellular model. PMID:24512234

  1. Parameter dependence of stochastic resonance in the FitzHugh-Nagumo neuron model driven by trichotomous noise

    NASA Astrophysics Data System (ADS)

    Zhang, Huiqing; Yang, Tingting; Xu, Yong; Xu, Wei

    2015-05-01

    We investigate the stochastic resonance in a FitzHugh-Nagumo neuron model driven by trichotomous noise and periodic signal, focusing on the dependence of properties of stochastic resonance (SR) on system parameters. The stochastic resonance is shown through several different measures: system response, power spectrum and signal-to-noise ratio. Firstly, it is found that whether the neuron can fire regularly depends on the cooperative effect of the signal frequency and the signal amplitude for the deterministic FHN neuron. When the forcing amplitude alone is insufficient to cause the neuron firing, the neuron can fire with the addition of trichotomous noise. Secondly, we show that power spectrum is maximized for an optimal value of the noise correlation time, which is the signature of SR. Finally, from studying SNR, the specific system parameters are found to optimize the SR phenomenon.

  2. Computer Simulations of Loss of Organization of Neurons as a Model for Age-related Cognitive Decline

    NASA Astrophysics Data System (ADS)

    Cruz, Luis; Fengometidis, Elene; Jones, Frank; Jampani, Srinivas

    2011-03-01

    In normal aging, brains suffer from progressive cognitive decline not linked with loss of neurons common in neurodegenerative disorders such as Alzheimer's disease. However, in some brain areas neurons have lost positional organization specifically within microcolumns: arrays of interconnected neurons which may constitute fundamental computational units in the brain. This age-related loss of organization, likely a result of micron-sized random displacements in neuronal positions, is hypothesized to be a by-product of the loss of support from the surrounding medium, including dendrites. Using a dynamical model applied to virtual 3D representation of neuronal arrangements, that previously showed loss of organization in brains of cognitively tested rhesus monkeys, the relationship between these displacements and changes to the surrounding dendrite network are presented. The consequences of these displacements on the structure of the dendritic network, with possible disruptions in signal synchrony important to cognitive function, are discussed. NIH R01AG021133.

  3. Cortical neuron activation induced by electromagnetic stimulation: a quantitative analysis via modelling and simulation.

    PubMed

    Wu, Tiecheng; Fan, Jie; Lee, Kim Seng; Li, Xiaoping

    2016-02-01

    Previous simulation works concerned with the mechanism of non-invasive neuromodulation has isolated many of the factors that can influence stimulation potency, but an inclusive account of the interplay between these factors on realistic neurons is still lacking. To give a comprehensive investigation on the stimulation-evoked neuronal activation, we developed a simulation scheme which incorporates highly detailed physiological and morphological properties of pyramidal cells. The model was implemented on a multitude of neurons; their thresholds and corresponding activation points with respect to various field directions and pulse waveforms were recorded. The results showed that the simulated thresholds had a minor anisotropy and reached minimum when the field direction was parallel to the dendritic-somatic axis; the layer 5 pyramidal cells always had lower thresholds but substantial variances were also observed within layers; reducing pulse length could magnify the threshold values as well as the variance; tortuosity and arborization of axonal segments could obstruct action potential initiation. The dependence of the initiation sites on both the orientation and the duration of the stimulus implies that the cellular excitability might represent the result of the competition between various firing-capable axonal components, each with a unique susceptibility determined by the local geometry. Moreover, the measurements obtained in simulation intimately resemble recordings in physiological and clinical studies, which seems to suggest that, with minimum simplification of the neuron model, the cable theory-based simulation approach can have sufficient verisimilitude to give quantitatively accurate evaluation of cell activities in response to the externally applied field. PMID:26719168

  4. Increased Anandamide Uptake by Sensory Neurons Contributes to Hyperalgesia in a Model of Cancer Pain

    PubMed Central

    Khasabova, Iryna A.; Holman, Michelle; Morse, Tim; Burlakova, Natalya; Coicou, Lia; Harding-Rose, Catherine; Simone, Don A.; Seybold, Virginia S.

    2013-01-01

    Opioids do not effectively manage pain in many patients with advanced cancer. Because anandamide (AEA) activation of cannabinoid type-1 receptors (CB1R) on nociceptors reduces nociception, manipulation of AEA metabolism in the periphery may be an effective alternative or adjuvant therapy in the management of cancer pain. AEA is hydrolyzed by the intracellular enzyme fatty acid amide hydrolase (FAAH), and this enzyme activity contributes to uptake of AEA into neurons and to reduction of AEA available to activate CB1R. We used an in vitro preparation of adult murine dorsal root ganglion (DRG) neurons co-cultured with fibrosarcoma cells to investigate how tumors alter the uptake of AEA into neurons. Evidence that the uptake of [3H]AEA into dissociated DRG cells in the co-culture model mimicked the increase in uptake that occurred in DRG cells from tumor-bearing mice supported the utility of the in vitro model to study AEA uptake. Results with the fluorescent AEA analog CAY10455 confirmed that an increase in uptake in the co-culture model occurred in neurons. One factor that contributed to the increase in [3H]AEA uptake was an increase in total cellular cholesterol in the cancer condition. Treatment with the FAAH inhibitor URB597 reduced CAY10455 uptake in the co-culture model to the level observed in DRG neurons maintained in the control condition (i.e., in the absence of fibrosarcoma cells), and this effect was paralleled by OMDM-1, an inhibitor of AEA uptake, at a concentration that had no effect on FAAH activity. Maximally effective concentrations of the two drugs together produced a greater reduction than was observed with each drug alone. Treatment with BMS309403, which competes for AEA binding to fatty acid binding protein-5, mimicked the effect of OMDM-1 in vitro. Local injection of OMDM-1 reduced hyperalgesia in vivo in mice with unilateral tumors in and around the calcaneous bone. Intraplantar injection of OMDM-1 (5 µg) into the tumor-bearing paw reduced

  5. Integration of Biochemical and Electrical Signaling-Multiscale Model of the Medium Spiny Neuron of the Striatum

    PubMed Central

    Mattioni, Michele; Le Novère, Nicolas

    2013-01-01

    Neuron behavior results from the interplay between networks of biochemical processes and electrical signaling. Synaptic plasticity is one of the neuronal properties emerging from such an interaction. One of the current approaches to study plasticity is to model either its electrical aspects or its biochemical components. Among the chief reasons are the different time scales involved, electrical events happening in milliseconds while biochemical cascades respond in minutes or hours. In order to create multiscale models taking in consideration both aspects simultaneously, one needs to synchronize the two models, and exchange relevant variable values. 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. Our synchronization strategy is general enough to be used in simulations of other models with similar synchronization issues, such as networks of neurons. Moreover, the integration between the electrical and the biochemical models opens up the possibility to investigate multiscale process, like synaptic plasticity, in a more global manner, while taking into account a more realistic description of the underlying mechanisms. PMID:23843966

  6. A Convolutional Subunit Model for Neuronal Responses in Macaque V1

    PubMed Central

    Vintch, Brett; Movshon, J. Anthony

    2015-01-01

    The response properties of neurons in the early stages of the visual system can be described using the rectified responses of a set of self-similar, spatially shifted linear filters. In macaque primary visual cortex (V1), simple cell responses can be captured with a single filter, whereas complex cells combine a set of filters, creating position invariance. These filters cannot be estimated using standard methods, such as spike-triggered averaging. Subspace methods like spike-triggered covariance can recover multiple filters but require substantial amounts of data, and recover an orthogonal basis for the subspace in which the filters reside, rather than the filters themselves. Here, we assume a linear-nonlinear-linear-nonlinear (LN-LN) cascade model in which the first LN stage consists of shifted (“convolutional”) copies of a single filter, followed by a common instantaneous nonlinearity. We refer to these initial LN elements as the “subunits” of the receptive field, and we allow two independent sets of subunits, each with its own filter and nonlinearity. The second linear stage computes a weighted sum of the subunit responses and passes the result through a final instantaneous nonlinearity. We develop a procedure to directly fit this model to electrophysiological data. When fit to data from macaque V1, the subunit model significantly outperforms three alternatives in terms of cross-validated accuracy and efficiency, and provides a robust, biologically plausible account of receptive field structure for all cell types encountered in V1. SIGNIFICANCE STATEMENT We present a new subunit model for neurons in primary visual cortex that significantly outperforms three alternative models in terms of cross-validated accuracy and efficiency, and provides a robust and biologically plausible account of the receptive field structure in these neurons across the full spectrum of response properties. PMID:26538653

  7. A unified model for two modes of bursting in GnRH neurons.

    PubMed

    Moran, Spencer; Moenter, Suzanne M; Khadra, Anmar

    2016-06-01

    Gonadotropin-releasing hormone (GnRH) neurons exhibit at least two intrinsic modes of action potential burst firing, referred to as parabolic and irregular bursting. Parabolic bursting is characterized by a slow wave in membrane potential that can underlie periodic clusters of action potentials with increased interspike interval at the beginning and at the end of each cluster. Irregular bursting is characterized by clusters of action potentials that are separated by varying durations of interburst intervals and a relatively stable baseline potential. Based on recent studies of isolated ionic currents, a stochastic Hodgkin-Huxley (HH)-like model for the GnRH neuron is developed to reproduce each mode of burst firing with an appropriate set of conductances. Model outcomes for bursting are in agreement with the experimental recordings in terms of interburst interval, interspike interval, active phase duration, and other quantitative properties specific to each mode of bursting. The model also shows similar outcomes in membrane potential to those seen experimentally when tetrodotoxin (TTX) is used to block action potentials during bursting, and when estradiol transitions cells exhibiting slow oscillations to irregular bursting mode in vitro. Based on the parameter values used to reproduce each mode of bursting, the model suggests that GnRH neurons can switch between the two through changes in the maximum conductance of certain ionic currents, notably the slow inward Ca(2+) current I s, and the Ca(2+) -activated K(+) current I KCa. Bifurcation analysis of the model shows that both modes of bursting are similar from a dynamical systems perspective despite differences in burst characteristics. PMID:26975615

  8. Sprouty2 and ‐4 hypomorphism promotes neuronal survival and astrocytosis in a mouse model of kainic acid induced neuronal damage

    PubMed Central

    Thongrong, Sitthisak; Hausott, Barbara; Marvaldi, Letizia; Agostinho, Alexandra S.; Zangrandi, Luca; Burtscher, Johannes; Fogli, Barbara

    2015-01-01

    ABSTRACT Sprouty (Spry) proteins play a key role as negative feedback inhibitors of the Ras/Raf/MAPK/ERK pathway downstream of various receptor tyrosine kinases. Among the four Sprouty isoforms, Spry2 and Spry4 are expressed in the hippocampus. In this study, possible effects of Spry2 and Spry4 hypomorphism on neurodegeneration and seizure thresholds in a mouse model of epileptogenesis was analyzed. The Spry2/4 hypomorphs exhibited stronger ERK activation which was limited to the CA3 pyramidal cell layer and to the hilar region. The seizure threshold of Spry2/4+/− mice was significantly reduced at naive state but no difference to wildtype mice was observed 1 month following KA treatment. Histomorphological analysis revealed that dentate granule cell dispersion (GCD) was diminished in Spry2/4+/− mice in the subchronic phase after KA injection. Neuronal degeneration was reduced in CA1 and CA3 principal neuron layers as well as in scattered neurons of the contralateral CA1 and hilar regions. Moreover, Spry2/4 reduction resulted in enhanced survival of somatostatin and neuropeptide Y expressing interneurons. GFAP staining intensity and number of reactive astrocytes markedly increased in lesioned areas of Spry2/4+/− mice as compared with wildtype mice. Taken together, although the seizure threshold is reduced in naive Spry2/4+/− mice, neurodegeneration and GCD is mitigated following KA induced hippocampal lesions, identifying Spry proteins as possible pharmacological targets in brain injuries resulting in neurodegeneration. The present data are consistent with the established functions of the ERK pathway in astrocyte proliferation as well as protection from neuronal cell death and suggest a novel role of Spry proteins in the migration of differentiated neurons. © 2015 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:26540287

  9. Whole-Brain Mapping of Neuronal Activity in the Learned Helplessness Model of Depression

    PubMed Central

    Kim, Yongsoo; Perova, Zinaida; Mirrione, Martine M.; Pradhan, Kith; Henn, Fritz A.; Shea, Stephen; Osten, Pavel; Li, Bo

    2016-01-01

    Some individuals are resilient, whereas others succumb to despair in repeated stressful situations. The neurobiological mechanisms underlying such divergent behavioral responses remain unclear. Here, we employed an automated method for mapping neuronal activity in search of signatures of stress responses in the entire mouse brain. We used serial two-photon tomography to detect expression of c-FosGFP – a marker of neuronal activation – in c-fosGFP transgenic mice subjected to the learned helplessness (LH) procedure, a widely used model of stress-induced depression-like phenotype in laboratory animals. We found that mice showing “helpless” behavior had an overall brain-wide reduction in the level of neuronal activation compared with mice showing “resilient” behavior, with the exception of a few brain areas, including the locus coeruleus, that were more activated in the helpless mice. In addition, the helpless mice showed a strong trend of having higher similarity in whole-brain activity profile among individuals, suggesting that helplessness is represented by a more stereotypic brain-wide activation pattern. This latter effect was confirmed in rats subjected to the LH procedure, using 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography to assess neural activity. Our findings reveal distinct brain activity markings that correlate with adaptive and maladaptive behavioral responses to stress, and provide a framework for further studies investigating the contribution of specific brain regions to maladaptive stress responses. PMID:26869888

  10. Whole-Brain Mapping of Neuronal Activity in the Learned Helplessness Model of Depression.

    PubMed

    Kim, Yongsoo; Perova, Zinaida; Mirrione, Martine M; Pradhan, Kith; Henn, Fritz A; Shea, Stephen; Osten, Pavel; Li, Bo

    2016-01-01

    Some individuals are resilient, whereas others succumb to despair in repeated stressful situations. The neurobiological mechanisms underlying such divergent behavioral responses remain unclear. Here, we employed an automated method for mapping neuronal activity in search of signatures of stress responses in the entire mouse brain. We used serial two-photon tomography to detect expression of c-FosGFP - a marker of neuronal activation - in c-fosGFP transgenic mice subjected to the learned helplessness (LH) procedure, a widely used model of stress-induced depression-like phenotype in laboratory animals. We found that mice showing "helpless" behavior had an overall brain-wide reduction in the level of neuronal activation compared with mice showing "resilient" behavior, with the exception of a few brain areas, including the locus coeruleus, that were more activated in the helpless mice. In addition, the helpless mice showed a strong trend of having higher similarity in whole-brain activity profile among individuals, suggesting that helplessness is represented by a more stereotypic brain-wide activation pattern. This latter effect was confirmed in rats subjected to the LH procedure, using 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography to assess neural activity. Our findings reveal distinct brain activity markings that correlate with adaptive and maladaptive behavioral responses to stress, and provide a framework for further studies investigating the contribution of specific brain regions to maladaptive stress responses. PMID:26869888

  11. Amelioration of toxicity in neuronal models of amyotrophic lateral sclerosis by hUPF1.

    PubMed

    Barmada, Sami J; Ju, Shulin; Arjun, Arpana; Batarse, Anthony; Archbold, Hilary C; Peisach, Daniel; Li, Xingli; Zhang, Yuxi; Tank, Elizabeth M H; Qiu, Haiyan; Huang, Eric J; Ringe, Dagmar; Petsko, Gregory A; Finkbeiner, Steven

    2015-06-23

    Over 30% of patients with amyotrophic lateral sclerosis (ALS) exhibit cognitive deficits indicative of frontotemporal dementia (FTD), suggesting a common pathogenesis for both diseases. Consistent with this hypothesis, neuronal and glial inclusions rich in TDP43, an essential RNA-binding protein, are found in the majority of those with ALS and FTD, and mutations in TDP43 and a related RNA-binding protein, FUS, cause familial ALS and FTD. TDP43 and FUS affect the splicing of thousands of transcripts, in some cases triggering nonsense-mediated mRNA decay (NMD), a highly conserved RNA degradation pathway. Here, we take advantage of a faithful primary neuronal model of ALS and FTD to investigate and characterize the role of human up-frameshift protein 1 (hUPF1), an RNA helicase and master regulator of NMD, in these disorders. We show that hUPF1 significantly protects mammalian neurons from both TDP43- and FUS-related toxicity. Expression of hUPF2, another essential component of NMD, also improves survival, whereas inhibiting NMD prevents rescue by hUPF1, suggesting that hUPF1 acts through NMD to enhance survival. These studies emphasize the importance of RNA metabolism in ALS and FTD, and identify a uniquely effective therapeutic strategy for these disorders. PMID:26056265

  12. Peripheral Mechanosensory Neuron Dysfunction Underlies Tactile and Behavioral Deficits in Mouse Models of ASDs.

    PubMed

    Orefice, Lauren L; Zimmerman, Amanda L; Chirila, Anda M; Sleboda, Steven J; Head, Joshua P; Ginty, David D

    2016-07-14

    Patients with autism spectrum disorders (ASDs) commonly experience aberrant tactile sensitivity, yet the neural alterations underlying somatosensory dysfunction and the extent to which tactile deficits contribute to ASD characteristics are unknown. We report that mice harboring mutations in Mecp2, Gabrb3, Shank3, and Fmr1 genes associated with ASDs in humans exhibit altered tactile discrimination and hypersensitivity to gentle touch. Deletion of Mecp2 or Gabrb3 in peripheral somatosensory neurons causes mechanosensory dysfunction through loss of GABAA receptor-mediated presynaptic inhibition of inputs to the CNS. Remarkably, tactile defects resulting from Mecp2 or Gabrb3 deletion in somatosensory neurons during development, but not in adulthood, cause social interaction deficits and anxiety-like behavior. Restoring Mecp2 expression exclusively in the somatosensory neurons of Mecp2-null mice rescues tactile sensitivity, anxiety-like behavior, and social interaction deficits, but not lethality, memory, or motor deficits. Thus, mechanosensory processing defects contribute to anxiety-like behavior and social interaction deficits in ASD mouse models. PAPERCLIP. PMID:27293187

  13. Interfacing Cultured Neurons to Microtransducers Arrays: A Review of the Neuro-Electronic Junction Models

    PubMed Central

    Massobrio, Paolo; Massobrio, Giuseppe; Martinoia, Sergio

    2016-01-01

    Microtransducer arrays, both metal microelectrodes and silicon-based devices, are widely used as neural interfaces to measure, extracellularly, the electrophysiological activity of excitable cells. Starting from the pioneering works at the beginning of the 70's, improvements in manufacture methods, materials, and geometrical shape have been made. Nowadays, these devices are routinely used in different experimental conditions (both in vivo and in vitro), and for several applications ranging from basic research in neuroscience to more biomedical oriented applications. However, the use of these micro-devices deeply depends on the nature of the interface (coupling) between the cell membrane and the sensitive active surface of the microtransducer. Thus, many efforts have been oriented to improve coupling conditions. Particularly, in the latest years, two innovations related to the use of carbon nanotubes as interface material and to the development of micro-structures which can be engulfed by the cell membrane have been proposed. In this work, we review what can be simulated by using simple circuital models and what happens at the interface between the sensitive active surface of the microtransducer and the neuronal membrane of in vitro neurons. We finally focus our attention on these two novel technological solutions capable to improve the coupling between neuron and micro-nano transducer. PMID:27445657

  14. Interfacing Cultured Neurons to Microtransducers Arrays: A Review of the Neuro-Electronic Junction Models.

    PubMed

    Massobrio, Paolo; Massobrio, Giuseppe; Martinoia, Sergio

    2016-01-01

    Microtransducer arrays, both metal microelectrodes and silicon-based devices, are widely used as neural interfaces to measure, extracellularly, the electrophysiological activity of excitable cells. Starting from the pioneering works at the beginning of the 70's, improvements in manufacture methods, materials, and geometrical shape have been made. Nowadays, these devices are routinely used in different experimental conditions (both in vivo and in vitro), and for several applications ranging from basic research in neuroscience to more biomedical oriented applications. However, the use of these micro-devices deeply depends on the nature of the interface (coupling) between the cell membrane and the sensitive active surface of the microtransducer. Thus, many efforts have been oriented to improve coupling conditions. Particularly, in the latest years, two innovations related to the use of carbon nanotubes as interface material and to the development of micro-structures which can be engulfed by the cell membrane have been proposed. In this work, we review what can be simulated by using simple circuital models and what happens at the interface between the sensitive active surface of the microtransducer and the neuronal membrane of in vitro neurons. We finally focus our attention on these two novel technological solutions capable to improve the coupling between neuron and micro-nano transducer. PMID:27445657

  15. A Hierarchical Neuronal Model for Generation and Online Recognition of Birdsongs

    PubMed Central

    Yildiz, Izzet B.; Kiebel, Stefan J.

    2011-01-01

    The neuronal system underlying learning, generation and recognition of song in birds is one of the best-studied systems in the neurosciences. Here, we use these experimental findings to derive a neurobiologically plausible, dynamic, hierarchical model of birdsong generation and transform it into a functional model of birdsong recognition. The generation model consists of neuronal rate models and includes critical anatomical components like the premotor song-control nucleus HVC (proper name), the premotor nucleus RA (robust nucleus of the arcopallium), and a model of the syringeal and respiratory organs. We use Bayesian inference of this dynamical system to derive a possible mechanism for how birds can efficiently and robustly recognize the songs of their conspecifics in an online fashion. Our results indicate that the specific way birdsong is generated enables a listening bird to robustly and rapidly perceive embedded information at multiple time scales of a song. The resulting mechanism can be useful for investigating the functional roles of auditory recognition areas and providing predictions for future birdsong experiments. PMID:22194676

  16. Transcriptomics analysis of iPSC-derived neurons and modeling of neuropsychiatric disorders.

    PubMed

    Lin, Mingyan; Lachman, Herbert M; Zheng, Deyou

    2016-06-01

    Induced pluripotent stem cell (iPSC)-derived neurons and neural progenitors are great resources for studying neural development and differentiation and their disruptions in disease conditions, and hold the promise of future cell therapy. In general, iPSC lines can be established either specifically from patients with neuropsychiatric disorders or from healthy subjects. The iPSCs can then be induced to differentiate into neural lineages and the iPSC-derived neurons are valuable for various types of cell-based assays that seek to understand disease mechanisms and identify and test novel therapies. In addition, it is an ideal system for gene expression profiling (i.e., transcriptomic analysis), an efficient and cost-effective way to explore the genetic programs regulating neurodevelopment. Moreover, transcriptomic comparison, which can be performed between patient-derived samples and controls, or in control lines in which the expression of specific genes has been disrupted, can uncover convergent gene targets and pathways that are downstream of the hundreds of candidate genes that have been associated with neuropsychiatric disorders. The results, especially after integration with spatiotemporal transcriptomic profiles of normal human brain development, have indeed helped to uncover gene networks, molecular pathways, and cellular signaling that likely play critical roles in disease development and progression. On the other hand, despite the great promise, many challenges remain in the usage of iPSC-derived neurons for modeling neuropsychiatric disorders, for example, how to generate relatively homogenous populations of specific neuronal subtypes that are affected in a particular disorder and how to better address the genetic heterogeneity that exists in the patient population. PMID:26631648

  17. Induction of de novo α-synuclein fibrillization in a neuronal model for Parkinson's disease.

    PubMed

    Fares, Mohamed-Bilal; Maco, Bohumil; Oueslati, Abid; Rockenstein, Edward; Ninkina, Natalia; Buchman, Vladimir L; Masliah, Eliezer; Lashuel, Hilal A

    2016-02-16

    Lewy bodies (LBs) are intraneuronal inclusions consisting primarily of fibrillized human α-synuclein (hα-Syn) protein, which represent the major pathological hallmark of Parkinson's disease (PD). Although doubling hα-Syn expression provokes LB pathology in humans, hα-Syn overexpression does not trigger the formation of fibrillar LB-like inclusions in mice. We hypothesized that interactions between exogenous hα-Syn and endogenous mouse synuclein homologs could be attenuating hα-Syn fibrillization in mice, and therefore, we systematically assessed hα-Syn aggregation propensity in neurons derived from α-Syn-KO, β-Syn-KO, γ-Syn-KO, and triple-KO mice lacking expression of all three synuclein homologs. Herein, we show that hα-Syn forms hyperphosphorylated (at S129) and ubiquitin-positive LB-like inclusions in primary neurons of α-Syn-KO, β-Syn-KO, and triple-KO mice, as well as in transgenic α-Syn-KO mouse brains in vivo. Importantly, correlative light and electron microscopy, immunogold labeling, and thioflavin-S binding established their fibrillar ultrastructure, and fluorescence recovery after photobleaching/photoconversion experiments showed that these inclusions grow in size and incorporate soluble proteins. We further investigated whether the presence of homologous α-Syn species would interfere with the seeding and spreading of α-Syn pathology. Our results are in line with increasing evidence demonstrating that the spreading of α-Syn pathology is most prominent when the injected preformed fibrils and host-expressed α-Syn monomers are from the same species. These findings provide insights that will help advance the development of neuronal and in vivo models for understanding mechanisms underlying hα-Syn intraneuronal fibrillization and its contribution to PD pathogenesis, and for screening pharmacologic and genetic modulators of α-Syn fibrillization in neurons. PMID:26839406

  18. Targeting, Endocytosis, and Lysosomal Delivery of Active Enzymes to Model Human Neurons by ICAM-1-Targeted Nanocarriers

    PubMed Central

    Hsu, Janet; Hoenicka, Janet; Muro, Silvia

    2016-01-01

    Purpose Delivery of therapeutics to neurons is paramount to treat neurological conditions, including many lysosomal storage disorders. However, key aspects of drug-carrier behavior in neurons are relatively unknown: the occurrence of non-canonical endocytic pathways (present in other cells); whether carriers that traverse the blood-brain barrier are, contrarily, retained within neurons; if neuron-surface receptors are accessible to bulky carriers compared to small ligands; or if there are differences regarding neuronal compartments (neuron body vs. neurites) pertaining said parameters. We have explored these questions using model polymer nanocarriers targeting intercellular adhesion molecule-1 (ICAM-1). Methods Differentiated human neuroblastoma cells were incubated with anti-ICAM-coated polystyrene nanocarriers and analyzed by fluorescence microscopy. Results ICAM-1 expression and nanocarrier binding was enhanced in altered (TNFα) vs. control conditions. While small ICAM-1 ligands (anti-ICAM) preferentially accessed the cell body, anti-ICAM nanocarriers bound with faster kinetics to neurites, yet reached similar saturation over time. Anti-ICAM nanocarriers were also endocytosed with faster kinetics and lower saturation levels in neurites. Non-classical cell adhesion molecule (CAM) endocytosis ruled uptake, and neurite-to-cell body transport was inferred. Nanocarriers trafficked to lysosomes, delivering active enzymes (dextranase) with substrate reduction in a lysosomal-storage disease model. Conclusion ICAM-1-targeting holds potential for intracellular delivery of therapeutics to neurons. PMID:25319100

  19. Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons.

    PubMed

    Goldwyn, Joshua H; Imennov, Nikita S; Famulare, Michael; Shea-Brown, Eric

    2011-04-01

    The random transitions of ion channels between conducting and nonconducting states generate a source of internal fluctuations in a neuron, known as channel noise. The standard method for modeling the states of ion channels nonlinearly couples continuous-time Markov chains to a differential equation for voltage. Beginning with the work of R. F. Fox and Y.-N. Lu [Phys. Rev. E 49, 3421 (1994)], there have been attempts to generate simpler models that use stochastic differential equation (SDEs) to approximate the stochastic spiking activity produced by Markov chain models. Recent numerical investigations, however, have raised doubts that SDE models can capture the stochastic dynamics of Markov chain models.We analyze three SDE models that have been proposed as approximations to the Markov chain model: one that describes the states of the ion channels and two that describe the states of the ion channel subunits. We show that the former channel-based approach can capture the distribution of channel noise and its effects on spiking in a Hodgkin-Huxley neuron model to a degree not previously demonstrated, but the latter two subunit-based approaches cannot. Our analysis provides intuitive and mathematical explanations for why this is the case. The temporal correlation in the channel noise is determined by the combinatorics of bundling subunits into channels, but the subunit-based approaches do not correctly account for this structure. Our study confirms and elucidates the findings of previous numerical investigations of subunit-based SDE models. Moreover, it presents evidence that Markov chain models of the nonlinear, stochastic dynamics of neural membranes can be accurately approximated by SDEs. This finding opens a door to future modeling work using SDE techniques to further illuminate the effects of ion channel fluctuations on electrically active cells. PMID:21599202

  20. Abrupt and gradual transitions between low and hyperexcited firing frequencies in neuronal models with fast synaptic excitation: A comparative study

    NASA Astrophysics Data System (ADS)

    Rotstein, Horacio G.

    2013-12-01

    Hyperexcitability of neuronal networks is one of the hallmarks of epileptic brain seizure generation, and results from a net imbalance between excitation and inhibition that promotes excessive abnormal firing frequencies. The transition between low and high firing frequencies as the levels of recurrent AMPA excitation change can occur either gradually or abruptly. We used modeling, numerical simulations, and dynamical systems tools to investigate the biophysical and dynamic mechanisms that underlie these two identified modes of transition in recurrently connected neurons via AMPA excitation. We compare our results and demonstrate that these two modes of transition are qualitatively different and can be linked to different intrinsic properties of the participating neurons.

  1. Labeling of neuronal differentiation and neuron cells with biocompatible fluorescent nanodiamonds

    NASA Astrophysics Data System (ADS)

    Hsu, Tzu-Chia; Liu, Kuang-Kai; Chang, Huan-Cheng; Hwang, Eric; Chao, Jui-I.

    2014-05-01

    Nanodiamond is a promising carbon nanomaterial developed for biomedical applications. Here, we show fluorescent nanodiamond (FND) with the biocompatible properties that can be used for the labeling and tracking of neuronal differentiation and neuron cells derived from embryonal carcinoma stem (ECS) cells. The fluorescence intensities of FNDs were increased by treatment with FNDs in both the mouse P19 and human NT2/D1 ECS cells. FNDs were taken into ECS cells; however, FNDs did not alter the cellular morphology and growth ability. Moreover, FNDs did not change the protein expression of stem cell marker SSEA-1 of ECS cells. The neuronal differentiation of ECS cells could be induced by retinoic acid (RA). Interestingly, FNDs did not affect on the morphological alteration, cytotoxicity and apoptosis during the neuronal differentiation. Besides, FNDs did not alter the cell viability and the expression of neuron-specific marker β-III-tubulin in these differentiated neuron cells. The existence of FNDs in the neuron cells can be identified by confocal microscopy and flow cytometry. Together, FND is a biocompatible and readily detectable nanomaterial for the labeling and tracking of neuronal differentiation process and neuron cells from stem cells.

  2. Accurate and Fast Simulation of Channel Noise in Conductance-Based Model Neurons by Diffusion Approximation

    PubMed Central

    Linaro, Daniele; Storace, Marco; Giugliano, Michele

    2011-01-01

    Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically detailed model neurons calls for the availability of fast numerical methods. In fact, exact techniques employ the microscopic simulation of the random opening and closing of individual ion channels, usually based on Markov models, whose computational loads are prohibitive for next generation massive computer models of the brain. In this work, we operatively define a procedure for translating any Markov model describing voltage- or ligand-gated membrane ion-conductances into an effective stochastic version, whose computer simulation is efficient, without compromising accuracy. Our approximation is based on an improved Langevin-like approach, which employs stochastic differential equations and no Montecarlo methods. As opposed to an earlier proposal recently debated in the literature, our approximation reproduces accurately the statistical properties of the exact microscopic simulations, under a variety of conditions, from spontaneous to evoked response features. In addition, our method is not restricted to the Hodgkin-Huxley sodium and potassium currents and is general for a variety of voltage- and ligand-gated ion currents. As a by-product, the analysis of the properties emerging in exact Markov schemes by standard probability calculus enables us for the first time to analytically identify the sources of inaccuracy of the previous proposal, while providing solid ground for its modification and improvement we present here. PMID:21423712

  3. A stochastic mean field model for an excitatory and inhibitory synaptic drive cortical neuronal network.

    PubMed

    Hui, Qing; Haddad, Wassim M; Bailey, James M; Hayakawa, Tomohisa

    2014-04-01

    With the advances in biochemistry, molecular biology, and neurochemistry there has been impressive progress in understanding the molecular properties of anesthetic agents. However, there has been little focus on how the molecular properties of anesthetic agents lead to the observed macroscopic property that defines the anesthetic state, that is, lack of responsiveness to noxious stimuli. In this paper, we develop a mean field synaptic drive firing rate cortical neuronal model and demonstrate how the induction of general anesthesia can be explained using multistability; the property whereby the solutions of a dynamical system exhibit multiple attracting equilibria under asymptotically slowly changing inputs or system parameters. In particular, we demonstrate multistability in the mean when the system initial conditions or the system coefficients of the neuronal connectivity matrix are random variables. Uncertainty in the system coefficients is captured by representing system uncertain parameters by a multiplicative white noise model wherein stochastic integration is interpreted in the sense of Itô. Modeling a priori system parameter uncertainty using a multiplicative white noise model is motivated by means of the maximum entropy principle of Jaynes and statistical analysis. PMID:24807952

  4. Conceptual Network Model From Sensory Neurons to Astrocytes of the Human Nervous System.

    PubMed

    Yang, Yiqun; Yeo, Chai Kiat

    2015-07-01

    From a single-cell animal like paramecium to vertebrates like ape, the nervous system plays an important role in responding to the variations of the environment. Compared to animals, the nervous system in the human body possesses more intricate organization and utility. The nervous system anatomy has been understood progressively, yet the explanation at the cell level regarding complete information transmission is still lacking. Along the signal pathway toward the brain, an external stimulus first activates action potentials in the sensing neuron and these electric pulses transmit along the spinal nerve or cranial nerve to the neurons in the brain. Second, calcium elevation is triggered in the branch of astrocyte at the tripartite synapse. Third, the local calcium wave expands to the entire territory of the astrocyte. Finally, the calcium wave propagates to the neighboring astrocyte via gap junction channel. In our study, we integrate the existing mathematical model and biological experiments in each step of the signal transduction to establish a conceptual network model for the human nervous system. The network is composed of four layers and the communication protocols of each layer could be adapted to entities with different characterizations. We verify our simulation results against the available biological experiments and mathematical models and provide a test case of the integrated network. As the production of conscious episode in the human nervous system is still under intense research, our model serves as a useful tool to facilitate, complement and verify current and future study in human cognition. PMID:25706505

  5. Nanotopography induced contact guidance of the F11 cell line during neuronal differentiation: a neuronal model cell line for tissue scaffold development

    NASA Astrophysics Data System (ADS)

    Wieringa, Paul; Tonazzini, Ilaria; Micera, Silvestro; Cecchini, Marco

    2012-07-01

    The F11 hybridoma, a dorsal root ganglion-derived cell line, was used to investigate the response of nociceptive sensory neurons to nanotopographical guidance cues. This established this cell line as a model of peripheral sensory neuron growth for tissue scaffold design. Cells were seeded on substrates of cyclic olefin copolymer (COC) films imprinted via nanoimprint lithography (NIL) with a grating pattern of nano-scale grooves and ridges. Different ridge widths were employed to alter the focal adhesion formation, thereby changing the cell/substrate interaction. Differentiation was stimulated with forskolin in culture medium consisting of either 1 or 10% fetal bovine serum (FBS). Per medium condition, similar neurite alignment was achieved over the four day period, with the 1% serum condition exhibiting longer, more aligned neurites. Immunostaining for focal adhesions found the 1% FBS condition to also have fewer, less developed focal adhesions. The robust response of the F11 to guidance cues further builds on the utility of this cell line as a sensory neuron model, representing a useful tool to explore the design of regenerative guidance tissue scaffolds.

  6. Thalamocortical neurons display suppressed burst-firing due to an enhanced Ih current in a genetic model of absence epilepsy.

    PubMed

    Cain, Stuart M; Tyson, John R; Jones, Karen L; Snutch, Terrance P

    2015-06-01

    Burst-firing in distinct subsets of thalamic relay (TR) neurons is thought to be a key requirement for the propagation of absence seizures. However, in the well-regarded Genetic Absence Epilepsy Rats from Strasbourg (GAERS) model as yet there has been no link described between burst-firing in TR neurons and spike-and-wave discharges (SWDs). GAERS ventrobasal (VB) neurons are a specific subset of TR neurons that do not normally display burst-firing during absence seizures in the GAERS model, and here, we assessed the underlying relationship of VB burst-firing with Ih and T-type calcium currents between GAERS and non-epileptic control (NEC) animals. In response to 200-ms hyperpolarizing current injections, adult epileptic but not pre-epileptic GAERS VB neurons displayed suppressed burst-firing compared to NEC. In response to longer duration 1,000-ms hyperpolarizing current injections, both pre-epileptic and epileptic GAERS VB neurons required significantly more hyperpolarizing current injection to burst-fire than those of NEC animals. The current density of the Hyperpolarization and Cyclic Nucleotide-activated (HCN) current (Ih) was found to be increased in GAERS VB neurons, and the blockade of Ih relieved the suppressed burst-firing in both pre-epileptic P15-P20 and adult animals. In support, levels of HCN-1 and HCN-3 isoform channel proteins were increased in GAERS VB thalamic tissue. T-type calcium channel whole-cell currents were found to be decreased in P7-P9 GAERS VB neurons, and also noted was a decrease in CaV3.1 mRNA and protein levels in adults. Z944, a potent T-type calcium channel blocker with anti-epileptic properties, completely abolished hyperpolarization-induced VB burst-firing in both NEC and GAERS VB neurons. PMID:24953239

  7. Altered Kv2.1 functioning promotes increased excitability in hippocampal neurons of an Alzheimer's disease mouse model.

    PubMed

    Frazzini, V; Guarnieri, S; Bomba, M; Navarra, R; Morabito, C; Mariggiò, M A; Sensi, S L

    2016-01-01

    Altered neuronal excitability is emerging as an important feature in Alzheimer's disease (AD). Kv2.1 potassium channels are important modulators of neuronal excitability and synaptic activity. We investigated Kv2.1 currents and its relation to the intrinsic synaptic activity of hippocampal neurons from 3xTg-AD (triple transgenic mouse model of Alzheimer's disease) mice, a widely employed preclinical AD model. Synaptic activity was also investigated by analyzing spontaneous [Ca(2+)]i spikes. Compared with wild-type (Non-Tg (non-transgenic mouse model)) cultures, 3xTg-AD neurons showed enhanced spike frequency and decreased intensity. Compared with Non-Tg cultures, 3xTg-AD hippocampal neurons revealed reduced Kv2.1-dependent Ik current densities as well as normalized conductances. 3xTg-AD cultures also exhibited an overall decrease in the number of functional Kv2.1 channels. Immunofluorescence assay revealed an increase in Kv2.1 channel oligomerization, a condition associated with blockade of channel function. In Non-Tg neurons, pharmacological blockade of Kv2.1 channels reproduced the altered pattern found in the 3xTg-AD cultures. Moreover, compared with untreated sister cultures, pharmacological inhibition of Kv2.1 in 3xTg-AD neurons did not produce any significant modification in Ik current densities. Reactive oxygen species (ROS) promote Kv2.1 oligomerization, thereby acting as negative modulator of the channel activity. Glutamate receptor activation produced higher ROS levels in hippocampal 3xTg-AD cultures compared with Non-Tg neurons. Antioxidant treatment with N-Acetyl-Cysteine was found to rescue Kv2.1-dependent currents and decreased spontaneous hyperexcitability in 3xTg-AD neurons. Analogous results regarding spontaneous synaptic activity were observed in neuronal cultures treated with the antioxidant 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox). Our study indicates that AD-related mutations may promote enhanced ROS generation, oxidative

  8. Spatiotemporal pattern of neuronal injury induced by DFP in rats: A model for delayed neuronal cell death following acute OP intoxication

    SciTech Connect

    Li Yonggang; Lein, Pamela J.; Liu Cuimei; Bruun, Donald A.; Tewolde, Teclemichael; Ford, Gregory; Ford, Byron D.

    2011-06-15

    Organophosphate (OP) neurotoxins cause acute cholinergic toxicity and seizures resulting in delayed brain damage and persistent neurological symptoms. Testing novel strategies for protecting against delayed effects of acute OP intoxication has been hampered by the lack of appropriate animal models. In this study, we characterize the spatiotemporal pattern of cellular injury after acute intoxication with the OP diisopropylfluorophosphate (DFP). Adult male Sprague-Dawley rats received pyridostigmine (0.1 mg/kg, im) and atropine methylnitrate (20 mg/kg, im) prior to DFP (9 mg/kg, ip) administration. All DFP-treated animals exhibited moderate to severe seizures within minutes after DFP injection but survived up to 72 h. AChE activity was significantly depressed in the cortex, hippocampus, subcortical brain tissue and cerebellum at 1 h post-DFP injection and this inhibition persisted for up to 72 h. Analysis of neuronal injury by Fluoro-Jade B (FJB) labeling revealed delayed neuronal cell death in the hippocampus, cortex, amygdala and thalamus, but not the cerebellum, starting at 4 h and persisting until 72 h after DFP treatment, although temporal profiles varied between brain regions. At 24 h post-DFP injection, the pattern of FJB labeling corresponded to TUNEL staining in most brain regions, and FJB-positive cells displayed reduced NeuN immunoreactivity but were not immunopositive for astrocytic (GFAP), oligodendroglial (O4) or macrophage/microglial (ED1) markers, demonstrating that DFP causes a region-specific delayed neuronal injury mediated in part by apoptosis. These findings indicate the feasibility of this model for testing neuroprotective strategies, and provide insight regarding therapeutic windows for effective pharmacological intervention following acute OP intoxication. - Research Highlights: > DFP induced neuronal FJB labeling starting at 4-8 h after treatment > The pattern of DFP-induced FJB labeling closely corresponded to TUNEL staining > FJB

  9. The synergistic inhibitory actions of oxcarbazepine on voltage-gated sodium and potassium currents in differentiated NG108-15 neuronal cells and model neurons.

    PubMed

    Huang, Chin-Wei; Huang, Chao-Ching; Lin, Ming-Wei; Tsai, Jing-Jane; Wu, Sheng-Nan

    2008-08-01

    Oxcarbazepine (OXC), one of the newer anti-epileptic drugs, has been demonstrating its efficacy on wide-spectrum neuropsychiatric disorders. However, the ionic mechanism of OXC actions in neurons remains incompletely understood. With the aid of patch-clamp technology, we first investigated the effects of OXC on ion currents in NG108-15 neuronal cells differentiated with cyclic AMP. We found OXC (0.3-30 microm) caused a reversible reduction in the amplitude of voltage-gated Na+ current (INa). The IC50 value required for the inhibition of INa by OXC was 3.1 microm. OXC (3 microm) could shift the steady-state inactivation of INa to a more negative membrane potential by approximately -9 mV with no effect on the slope of the inactivation curve, and produce a significant prolongation in the recovery of INa inactivation. Additionally, OXC was effective in suppressing persistent INa (INa(P)) elicited by long ramp pulses. The blockade of INa by OXC does not simply reduce current magnitude, but alters current kinetics. Moreover, OXC could suppress the amplitude of delayed rectifier K+ current (IK(DR)), with no effect on M-type K+ current (IK(M)). In current-clamp configuration, OXC could reduce the amplitude of action potentials and prolong action-potential duration. Furthermore, the simulations, based on hippocampal pyramidal neurons (Pinsky-Rinzel model) and a network of the Hodgkin-Huxley model, were analysed to investigate the effect of OXC on action potentials. Taken together, our results suggest that the synergistic blocking effects on INa and IK(DR) may contribute to the underlying mechanisms through which OXC affects neuronal function in vivo. PMID:18184444

  10. Oxidative stress associated with neuronal apoptosis in experimental models of epilepsy.

    PubMed

    Méndez-Armenta, Marisela; Nava-Ruíz, Concepción; Juárez-Rebollar, Daniel; Rodríguez-Martínez, Erika; Gómez, Petra Yescas

    2014-01-01

    Epilepsy is considered one of the most common neurological disorders worldwide. Oxidative stress produced by free radicals may play a role in the initiation and progression of epilepsy; the changes in the mitochondrial and the oxidative stress state can lead mechanism associated with neuronal death pathway. Bioenergetics state failure and impaired mitochondrial function include excessive free radical production with impaired synthesis of antioxidants. This review summarizes evidence that suggest what is the role of oxidative stress on induction of apoptosis in experimental models of epilepsy. PMID:25614776

  11. Adaptive Neuron Model: An architecture for the rapid learning of nonlinear topological transformations

    NASA Technical Reports Server (NTRS)

    Tawel, Raoul (Inventor)

    1994-01-01

    A method for the rapid learning of nonlinear mappings and topological transformations using a dynamically reconfigurable artificial neural network is presented. This fully-recurrent Adaptive Neuron Model (ANM) network was applied to the highly degenerate inverse kinematics problem in robotics, and its performance evaluation is bench-marked. Once trained, the resulting neuromorphic architecture was implemented in custom analog neural network hardware and the parameters capturing the functional transformation downloaded onto the system. This neuroprocessor, capable of 10(exp 9) ops/sec, was interfaced directly to a three degree of freedom Heathkit robotic manipulator. Calculation of the hardware feed-forward pass for this mapping was benchmarked at approximately 10 microsec.

  12. Spike patterning of a stochastic phase model neuron given periodic inhibition

    NASA Astrophysics Data System (ADS)

    Nesse, William H.; Clark, Gregory A.; Bressloff, Paul C.

    2007-03-01

    We present a phase model of a repetitively firing neuron possessing a phase-dependent stochastic response to periodic inhibition. We analyze the dynamics in terms of a stochastic phase map and determine the invariant phase distribution. We use the latter to compute both the distribution of interspike intervals (ISIs) and the stochastic winding number (mean firing rate) as a function of the input frequency. We show that only low-order phase locking persists in the presence of weak phase dependence, and is characterized statistically by a multimodal ISI distribution and a nonmonotonic variation in the stochastic winding number as a function of input frequency.

  13. A new firing paradigm for integrate and fire stochastic neuronal models.

    PubMed

    Sirovich, Roberta; Testa, Luisa

    2016-06-01

    A new definition of firing time is given in the framework of Integrate and Fire neuronal models. The classical absorption condition at the threshold is relaxed and the firing time is defined as the first time the membrane potential process lies above a fixed depolarisation level for a sufficiently long time. The mathematical properties of the new firing time are investigated both for the Perfect Integrator and the Leaky Integrator. In the latter case, a simulation study is presented to complete the analysis where analytical results are not yet achieved. PMID:27106182

  14. Arnold tongues and the Devil's Staircase in a discrete-time Hindmarsh-Rose neuron model

    NASA Astrophysics Data System (ADS)

    Felicio, Carolini C.; Rech, Paulo C.

    2015-11-01

    We investigate a three-dimensional discrete-time dynamical system, described by a three-dimensional map derived from a continuous-time Hindmarsh-Rose neuron model by the forward Euler method. For a fixed integration step size, we report a two-dimensional parameter-space for this system, where periodic structures, the so-called Arnold tongues, can be seen with periods organized in a Farey tree sequence. We also report possible modifications in this parameter-space, as a function of the integration step size.

  15. A new glucocerebrosidase-deficient neuronal cell model provides a tool to probe pathophysiology and therapeutics for Gaucher disease.

    PubMed

    Westbroek, Wendy; Nguyen, Matthew; Siebert, Marina; Lindstrom, Taylor; Burnett, Robert A; Aflaki, Elma; Jung, Olive; Tamargo, Rafael; Rodriguez-Gil, Jorge L; Acosta, Walter; Hendrix, An; Behre, Bahafta; Tayebi, Nahid; Fujiwara, Hideji; Sidhu, Rohini; Renvoise, Benoit; Ginns, Edward I; Dutra, Amalia; Pak, Evgenia; Cramer, Carole; Ory, Daniel S; Pavan, William J; Sidransky, Ellen

    2016-07-01

    Glucocerebrosidase is a lysosomal hydrolase involved in the breakdown of glucosylceramide. Gaucher disease, a recessive lysosomal storage disorder, is caused by mutations in the gene GBA1 Dysfunctional glucocerebrosidase leads to accumulation of glucosylceramide and glycosylsphingosine in various cell types and organs. Mutations in GBA1 are also a common genetic risk factor for Parkinson disease and related synucleinopathies. In recent years, research on the pathophysiology of Gaucher disease, the molecular link between Gaucher and Parkinson disease, and novel therapeutics, have accelerated the need for relevant cell models with GBA1 mutations. Although induced pluripotent stem cells, primary rodent neurons, and transfected neuroblastoma cell lines have been used to study the effect of glucocerebrosidase deficiency on neuronal function, these models have limitations because of challenges in culturing and propagating the cells, low yield, and the introduction of exogenous mutant GBA1 To address some of these difficulties, we established a high yield, easy-to-culture mouse neuronal cell model with nearly complete glucocerebrosidase deficiency representative of Gaucher disease. We successfully immortalized cortical neurons from embryonic null allele gba(-/-) mice and the control littermate (gba(+/+)) by infecting differentiated primary cortical neurons in culture with an EF1α-SV40T lentivirus. Immortalized gba(-/-) neurons lack glucocerebrosidase protein and enzyme activity, and exhibit a dramatic increase in glucosylceramide and glucosylsphingosine accumulation, enlarged lysosomes, and an impaired ATP-dependent calcium-influx response; these phenotypical characteristics were absent in gba(+/+) neurons. This null allele gba(-/-) mouse neuronal model provides a much-needed tool to study the pathophysiology of Gaucher disease and to evaluate new therapies. PMID:27482815

  16. A new glucocerebrosidase-deficient neuronal cell model provides a tool to probe pathophysiology and therapeutics for Gaucher disease

    PubMed Central

    Westbroek, Wendy; Nguyen, Matthew; Siebert, Marina; Lindstrom, Taylor; Burnett, Robert A.; Aflaki, Elma; Jung, Olive; Tamargo, Rafael; Rodriguez-Gil, Jorge L.; Acosta, Walter; Hendrix, An; Behre, Bahafta; Tayebi, Nahid; Fujiwara, Hideji; Sidhu, Rohini; Renvoise, Benoit; Ginns, Edward I.; Dutra, Amalia; Pak, Evgenia; Cramer, Carole; Ory, Daniel S.; Pavan, William J.

    2016-01-01

    ABSTRACT Glucocerebrosidase is a lysosomal hydrolase involved in the breakdown of glucosylceramide. Gaucher disease, a recessive lysosomal storage disorder, is caused by mutations in the gene GBA1. Dysfunctional glucocerebrosidase leads to accumulation of glucosylceramide and glycosylsphingosine in various cell types and organs. Mutations in GBA1 are also a common genetic risk factor for Parkinson disease and related synucleinopathies. In recent years, research on the pathophysiology of Gaucher disease, the molecular link between Gaucher and Parkinson disease, and novel therapeutics, have accelerated the need for relevant cell models with GBA1 mutations. Although induced pluripotent stem cells, primary rodent neurons, and transfected neuroblastoma cell lines have been used to study the effect of glucocerebrosidase deficiency on neuronal function, these models have limitations because of challenges in culturing and propagating the cells, low yield, and the introduction of exogenous mutant GBA1. To address some of these difficulties, we established a high yield, easy-to-culture mouse neuronal cell model with nearly complete glucocerebrosidase deficiency representative of Gaucher disease. We successfully immortalized cortical neurons from embryonic null allele gba−/− mice and the control littermate (gba+/+) by infecting differentiated primary cortical neurons in culture with an EF1α-SV40T lentivirus. Immortalized gba−/− neurons lack glucocerebrosidase protein and enzyme activity, and exhibit a dramatic increase in glucosylceramide and glucosylsphingosine accumulation, enlarged lysosomes, and an impaired ATP-dependent calcium-influx response; these phenotypical characteristics were absent in gba+/+ neurons. This null allele gba−/− mouse neuronal model provides a much-needed tool to study the pathophysiology of Gaucher disease and to evaluate new therapies. PMID:27482815

  17. Neuronal synapse as a memristor: modeling pair- and triplet-based STDP rule.

    PubMed

    Cai, Weiran; Ellinger, Frank; Tetzlaff, Ronald

    2015-02-01

    We propose a new memristive model for the neuronal synapse based on the spike-timing-dependent plasticity (STDP) protocol, considering both long-term and short-term plasticity in the synapse. Higher-order behavior is modeled by a memristor with adaptive thresholds, which realizes the well-established suppression principle of Froemke. We assume a mechanism of variable thresholds adapting to synaptic potentiation (LTP) and depression (LTD), which reproduces the refractory time in the weight modification. The corresponding dynamical process is governed by a set of ordinary differential equations. Interestingly, the Froemke's model and our memristive model, based on two completely different mechanisms, are found to be quantitatively equivalent for the 'pre-post-pre' case and 'post-pre-post' case. A relation of the adaptive thresholds to short-term plasticity is addressed. PMID:24960611

  18. Tau-Driven Neuronal and Neurotrophic Dysfunction in a Mouse Model of Early Tauopathy

    PubMed Central

    Mazzaro, Nadia; Barini, Erica; Spillantini, Maria Grazia; Goedert, Michel; Medini, Paolo

    2016-01-01

    Tauopathies are neurodegenerative diseases characterized by intraneuronal inclusions of hyperphosphorylated tau protein and abnormal expression of brain-derived neurotrophic factor (BDNF), a key modulator of neuronal survival and function. The severity of both these pathological hallmarks correlate with the degree of cognitive impairment in patients. However, how tau pathology specifically modifies BDNF signaling and affects neuronal function during early prodromal stages of tauopathy remains unclear. Here, we report that the mild tauopathy developing in retinal ganglion cells (RGCs) of the P301S tau transgenic (P301S) mouse induces functional retinal changes by disrupting BDNF signaling via the TrkB receptor. In adult P301S mice, the physiological visual response of RGCs to pattern light stimuli and retinal acuity decline significantly. As a consequence, the activity-dependent secretion of BDNF in the vitreous is impaired in P301S mice. Further, in P301S retinas, TrkB receptors are selectively upregulated, but uncoupled from downstream extracellular signal-regulated kinase (ERK) 1/2 signaling. We also show that the impairment of TrkB signaling is triggered by tau pathology and mediates the tau-induced dysfunction of visual response. Overall our results identify a neurotrophin-mediated mechanism by which tau induces neuronal dysfunction during prodromal stages of tauopathy and define tau-driven pathophysiological changes of potential value to support early diagnosis and informed therapeutic decisions. SIGNIFICANCE STATEMENT This work highlights the potential molecular mechanisms by which initial tauopathy induces neuronal dysfunction. Combining clinically used electrophysiological techniques (i.e., electroretinography) and molecular analyses, this work shows that in a relevant model of early tauopathy, the retina of the P301S mutant human tau transgenic mouse, mild tau pathology results in functional changes of neuronal activity, likely due to selective impairment

  19. eGFP expression under the Uchl1 promoter labels corticospinal motor neurons and a subpopulation of degeneration resistant spinal motor neurons in ALS mouse models

    NASA Astrophysics Data System (ADS)

    Yasvoina, Marina V.

    Current understanding of basic cellular and molecular mechanisms for motor neuron vulnerability during motor neuron disease initiation and progression is incomplete. The complex cytoarchitecture and cellular heterogeneity of the cortex and spinal cord greatly impedes our ability to visualize, isolate, and study specific neuron populations in both healthy and diseased states. We generated a novel reporter line, the Uchl1-eGFP mouse, in which cortical and spinal components of motor neuron circuitry are genetically labeled with eGFP under the Uchl1 promoter. A series of cellular and anatomical analyses combined with retrograde labeling, molecular marker expression, and electrophysiology were employed to determine identity of eGFP expressing cells in the motor cortex and the spinal cord of novel Uchl1-eGFP reporter mice. We conclude that eGFP is expressed in corticospinal motor neurons (CSMN) in the motor cortex and a subset of S-type alpha and gamma spinal motor neurons (SMN) in the spinal cord. hSOD1G93A and Alsin-/- mice, mouse models for amyotrophic lateral sclerosis (ALS), were bred to Uchl1-eGFP reporter mouse line to investigate the pathophysiology and underlying mechanisms of CSMN degeneration in vivo. Evidence suggests early and progressive degeneration of CSMN and SMN in the hSOD1G93A transgenic mice. We show an early increase of autophagosome formation in the apical dendrites of vulnerable CSMN in hSOD1G93A-UeGFP mice, which is localized to the apical dendrites. In addition, labeling S-type alpha and gamma SMN in the hSOD1G93A-UeGFP mice provide a unique opportunity to study basis of their resistance to degeneration. Mice lacking alsin show moderate clinical phenotype and mild CSMN axon degeneration in the spinal cord, which suggests vulnerability of CSMN. Therefore, we investigated the CSMN cellular and axon defects in aged Alsin-/- mice bred to Uchl1-eGFP reporter mouse line. We show that while CSMN are preserved and lack signs of degeneration, CSMN axons

  20. Transient response in a dendritic neuron model for current injected at one branch.

    PubMed

    Rinzel, J; Rall, W

    1974-10-01

    Mathematical expressions are obtained for the response function corresponding to an instantaneous pulse of current injected to a single dendritic branch in a branched dendritic neuron model. The theoretical model assumes passive membrane properties and the equivalent cylinder constraint on branch diameters. The response function when used in a convolution formula enables one to compute the voltage transient at any specified point in the dendritic tree for an arbitrary current injection at a given input location. A particular numerical example, for a brief current injection at a branch terminal, illustrates the attenuation and delay characteristics of the depolarization peak as it spreads throughout the neuron model. In contrast to the severe attenuation of voltage transients from branch input sites to the soma, the fraction of total input charge actually delivered to the soma and other trees is calculated to be about one-half. This fraction is independent of the input time course. Other numerical examples, which compare a branch terminal input site with a soma input site, demonstrate that, for a given transient current injection, the peak depolarization is not proportional to the input resistance at the injection site and, for a given synaptic conductance transient, the effective synaptic driving potential can be significantly reduced, resulting in less synaptic current flow and charge, for a branch input site. Also, for the synaptic case, the two inputs are compared on the basis of the excitatory post-synaptic potential (EPSP) seen at the soma and the total charge delivered to the soma. PMID:4424185

  1. A Model-Based Spike Sorting Algorithm for Removing Correlation Artifacts in Multi-Neuron Recordings

    PubMed Central

    Chichilnisky, E. J.; Simoncelli, Eero P.

    2013-01-01

    We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call “binary pursuit”. The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth. PMID:23671583

  2. A new simple /spl infin/OH neuron model as a biologically plausible principal component analyzer.

    PubMed

    Jankovic, M V

    2003-01-01

    A new approach to unsupervised learning in a single-layer neural network is discussed. An algorithm for unsupervised learning based upon the Hebbian learning rule is presented. A simple neuron model is analyzed. A dynamic neural model, which contains both feed-forward and feedback connections between the input and the output, has been adopted. The, proposed learning algorithm could be more correctly named self-supervised rather than unsupervised. The solution proposed here is a modified Hebbian rule, in which the modification of the synaptic strength is proportional not to pre- and postsynaptic activity, but instead to the presynaptic and averaged value of postsynaptic activity. It is shown that the model neuron tends to extract the principal component from a stationary input vector sequence. Usually accepted additional decaying terms for the stabilization of the original Hebbian rule are avoided. Implementation of the basic Hebbian scheme would not lead to unrealistic growth of the synaptic strengths, thanks to the adopted network structure. PMID:18238065

  3. Multiscale analysis of slow-fast neuronal learning models with noise

    PubMed Central

    2012-01-01

    This paper deals with the application of temporal averaging methods to recurrent networks of noisy neurons undergoing a slow and unsupervised modification of their connectivity matrix called learning. Three time-scales arise for these models: (i) the fast neuronal dynamics, (ii) the intermediate external input to the system, and (iii) the slow learning mechanisms. Based on this time-scale separation, we apply an extension of the mathematical theory of stochastic averaging with periodic forcing in order to derive a reduced deterministic model for the connectivity dynamics. We focus on a class of models where the activity is linear to understand the specificity of several learning rules (Hebbian, trace or anti-symmetric learning). In a weakly connected regime, we study the equilibrium connectivity which gathers the entire ‘knowledge’ of the network about the inputs. We develop an asymptotic method to approximate this equilibrium. We show that the symmetric part of the connectivity post-learning encodes the correlation structure of the inputs, whereas the anti-symmetric part corresponds to the cross correlation between the inputs and their time derivative. Moreover, the time-scales ratio appears as an important parameter revealing temporal correlations. PMID:23174307

  4. Automatic Generation of Connectivity for Large-Scale Neuronal Network Models through Structural Plasticity.

    PubMed

    Diaz-Pier, Sandra; Naveau, Mikaël; Butz-Ostendorf, Markus; Morrison, Abigail

    2016-01-01

    With the emergence of new high performance computation technology in the last decade, the simulation of large scale neural networks which are able to reproduce the behavior and structure of the brain has finally become an achievable target of neuroscience. Due to the number of synaptic connections between neurons and the complexity of biological networks, most contemporary models have manually defined or static connectivity. However, it is expected that modeling the dynamic generation and deletion of the links among neurons, locally and between different regions of the brain, is crucial to unravel important mechanisms associated with learning, memory and healing. Moreover, for many neural circuits that could potentially be modeled, activity data is more readily and reliably available than connectivity data. Thus, a framework that enables networks to wire themselves on the basis of specified activity targets can be of great value in specifying network models where connectivity data is incomplete or has large error margins. To address these issues, in the present work we present an implementation of a model of structural plasticity in the neural network simulator NEST. In this model, synapses consist of two parts, a pre- and a post-synaptic element. Synapses are created and deleted during the execution of the simulation following local homeostatic rules until a mean level of electrical activity is reached in the network. We assess the scalability of the implementation in order to evaluate its potential usage in the self generation of connectivity of large scale networks. We show and discuss the results of simulations on simple two population networks and more complex models of the cortical microcircuit involving 8 populations and 4 layers using the new framework. PMID:27303272

  5. Automatic Generation of Connectivity for Large-Scale Neuronal Network Models through Structural Plasticity

    PubMed Central

    Diaz-Pier, Sandra; Naveau, Mikaël; Butz-Ostendorf, Markus; Morrison, Abigail

    2016-01-01

    With the emergence of new high performance computation technology in the last decade, the simulation of large scale neural networks which are able to reproduce the behavior and structure of the brain has finally become an achievable target of neuroscience. Due to the number of synaptic connections between neurons and the complexity of biological networks, most contemporary models have manually defined or static connectivity. However, it is expected that modeling the dynamic generation and deletion of the links among neurons, locally and between different regions of the brain, is crucial to unravel important mechanisms associated with learning, memory and healing. Moreover, for many neural circuits that could potentially be modeled, activity data is more readily and reliably available than connectivity data. Thus, a framework that enables networks to wire themselves on the basis of specified activity targets can be of great value in specifying network models where connectivity data is incomplete or has large error margins. To address these issues, in the present work we present an implementation of a model of structural plasticity in the neural network simulator NEST. In this model, synapses consist of two parts, a pre- and a post-synaptic element. Synapses are created and deleted during the execution of the simulation following local homeostatic rules until a mean level of electrical activity is reached in the network. We assess the scalability of the implementation in order to evaluate its potential usage in the self generation of connectivity of large scale networks. We show and discuss the results of simulations on simple two population networks and more complex models of the cortical microcircuit involving 8 populations and 4 layers using the new framework. PMID:27303272

  6. Protein carbonylation, protein aggregation and neuronal cell death in a murine model of multiple sclerosis

    NASA Astrophysics Data System (ADS)

    Dasgupta, Anushka

    Many studies have suggested that oxidative stress plays an important role in the pathophysiology of both multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE). Yet, the mechanism by which oxidative stress leads to tissue damage in these disorders is unclear. Recent work from our laboratory has revealed that protein carbonylation, a major oxidative modification caused by severe and/or chronic oxidative stress conditions, is elevated in MS and EAE. Furthermore, protein carbonylation has been shown to alter protein structure leading to misfolding/aggregation. These findings prompted me to hypothesize that carbonylated proteins, formed as a consequence of oxidative stress and/or decreased proteasomal activity, promote protein aggregation to mediate neuronal apoptosis in vitro and in EAE. To test this novel hypothesis, I first characterized protein carbonylation, protein aggregation and apoptosis along the spinal cord during the course of myelin-oligodendrocyte glycoprotein (MOG)35-55 peptide-induced EAE in C57BL/6 mice [Chapter 2]. The results show that carbonylated proteins accumulate throughout the course of the disease, albeit by different mechanisms: increased oxidative stress in acute EAE and decreased proteasomal activity in chronic EAE. I discovered not only that there is a temporal correlation between protein carbonylation and apoptosis but also that carbonyl levels are significantly higher in apoptotic cells. A high number of juxta-nuclear and cytoplasmic protein aggregates containing the majority of the oxidized proteins are also present during the course of EAE, which seems to be due to reduced autophagy. In chapter 3, I show that when gluthathione levels are reduced to those in EAE spinal cord, both neuron-like PC12 (nPC12) cells and primary neuronal cultures accumulate carbonylated proteins and undergo cell death (both by necrosis and apoptosis). Immunocytochemical and biochemical studies also revealed a temporal

  7. Arginine vasopressin neuronal loss results from autophagy-associated cell death in a mouse model for familial neurohypophysial diabetes insipidus.

    PubMed

    Hagiwara, D; Arima, H; Morishita, Y; Wenjun, L; Azuma, Y; Ito, Y; Suga, H; Goto, M; Banno, R; Sugimura, Y; Shiota, A; Asai, N; Takahashi, M; Oiso, Y

    2014-01-01

    Familial neurohypophysial diabetes insipidus (FNDI) characterized by progressive polyuria is mostly caused by mutations in the gene encoding neurophysin II (NPII), which is the carrier protein of the antidiuretic hormone, arginine vasopressin (AVP). Although accumulation of mutant NPII in the endoplasmic reticulum (ER) could be toxic for AVP neurons, the precise mechanisms of cell death of AVP neurons, reported in autopsy studies, remain unclear. Here, we subjected FNDI model mice to intermittent water deprivation (WD) in order to promote the phenotypes. Electron microscopic analyses demonstrated that, while aggregates are confined to a certain compartment of the ER in the AVP neurons of FNDI mice with water access ad libitum, they were scattered throughout the dilated ER lumen in the FNDI mice subjected to WD for 4 weeks. It is also demonstrated that phagophores, the autophagosome precursors, emerged in the vicinity of aggregates and engulfed the ER containing scattered aggregates. Immunohistochemical analyses revealed that expression of p62, an adapter protein between ubiquitin and autophagosome, was elicited on autophagosomal membranes in the AVP neurons, suggesting selective autophagy induction at this time point. Treatment of hypothalamic explants of green fluorescent protein (GFP)-microtubule-associated protein 1 light chain 3 (LC3) transgenic mice with an ER stressor thapsigargin increased the number of GFP-LC3 puncta, suggesting that ER stress could induce autophagosome formation in the hypothalamus of wild-type mice as well. The cytoplasm of AVP neurons in FNDI mice was occupied with vacuoles in the mice subjected to WD for 12 weeks, when 30-40% of AVP neurons are lost. Our data thus demonstrated that autophagy was induced in the AVP neurons subjected to ER stress in FNDI mice. Although autophagy should primarily be protective for neurons, it is suggested that the organelles including ER were lost over time through autophagy, leading to autophagy

  8. The neuron-astrocyte-microglia triad in a rat model of chronic cerebral hypoperfusion: protective effect of dipyridamole

    PubMed Central

    Lana, Daniele; Melani, Alessia; Pugliese, Anna Maria; Cipriani, Sara; Nosi, Daniele; Pedata, Felicita; Giovannini, Maria Grazia

    2014-01-01

    Chronic cerebral hypoperfusion during aging may cause progressive neurodegeneration as ischemic conditions persist. Proper functioning of the interplay between neurons and glia is fundamental for the functional organization of the brain. The aim of our research was to study the pathophysiological mechanisms, and particularly the derangement of the interplay between neurons and astrocytes-microglia with the formation of “triads,” in a model of chronic cerebral hypoperfusion induced by the two-vessel occlusion (2VO) in adult Wistar rats (n = 15). The protective effect of dipyridamole given during the early phases after 2VO (4 mg/kg/day i.v., the first 7 days after 2VO) was verified (n = 15). Sham-operated rats (n = 15) were used as controls. Immunofluorescent triple staining of neurons (NeuN), astrocytes (GFAP), and microglia (IBA1) was performed 90 days after 2VO. We found significantly higher amount of “ectopic” neurons, neuronal debris and apoptotic neurons in CA1 Str. Radiatum and Str. Pyramidale of 2VO rats. In CA1 Str. Radiatum of 2VO rats the amount of astrocytes (cells/mm2) did not increase. In some instances several astrocytes surrounded ectopic neurons and formed a “micro scar” around them. Astrocyte branches could infiltrate the cell body of ectopic neurons, and, together with activated microglia cells formed the “triads.” In the triad, significantly more numerous in CA1 Str. Radiatum of 2VO than in sham rats, astrocytes and microglia cooperated in the phagocytosis of ectopic neurons. These events might be common mechanisms underlying many neurodegenerative processes. The frequency to which they appear might depend upon, or might be the cause of, the burden and severity of neurodegeneration. Dypiridamole significantly reverted all the above described events. The protective effect of chronic administration of dipyridamole might be a consequence of its vasodilatory, antioxidant and anti-inflammatory role during the early phases after 2VO

  9. Processing of odor stimuli by neuronal network models of the olfactory bulb

    NASA Astrophysics Data System (ADS)

    Wick, Stuart; Wiechert, Martin; Riecke, Hermann; Friedrich, Rainer

    2007-03-01

    The space of perceptable odors is high-dimensional and its representation in the various brain structures is still poorly understood. We focus on the olfactory bulb, which constitutes the first processing stage for odor stimuli after they have been sensed by receptor neurons. Experimentally it is found that the correlations between the outputs of the bulb are significantly reduced relative to those of the corresponding inputs, thus enhancing the discriminability of similar odors. We have generated a firing-rate-based network model with parameters derived from experimental data that reproduces decorrelation. Here we use this model to investigate the dependence of stimulus representations on odor concentration. We address the possibility of a change in perceived odor identity with changing concentration and the dependence of odor discriminability on odor concentration. We interpret some of our results within a simple mean-field model for the neural activity.

  10. Neuronal mechanisms and circuits underlying repetitive behaviors in mouse models of autism spectrum disorder.

    PubMed

    Kim, Hyopil; Lim, Chae-Seok; Kaang, Bong-Kiun

    2016-01-01

    Autism spectrum disorder (ASD) refers to a broad spectrum of neurodevelopmental disorders characterized by three central behavioral symptoms: impaired social interaction, impaired social communication, and restricted and repetitive behaviors. However, the symptoms are heterogeneous among patients and a number of ASD mouse models have been generated containing mutations that mimic the mutations found in human patients with ASD. Each mouse model was found to display a unique set of repetitive behaviors. In this review, we summarize the repetitive behaviors of the ASD mouse models and variations found in their neural mechanisms including molecular and electrophysiological features. We also propose potential neuronal mechanisms underlying these repetitive behaviors, focusing on the role of the cortico-basal ganglia-thalamic circuits and brain regions associated with both social and repetitive behaviors. Further understanding of molecular and circuitry mechanisms of the repetitive behaviors associated with ASD is necessary to aid the development of effective treatments for these disorders. PMID:26790724

  11. An analog circuit implementation of a Huber-Braun cold receptor neuron model.

    PubMed

    Hermida, Raul; Patrone, Martin; Pijuan, Martin; Monzon, Pablo; Oreggioni, Julián

    2012-01-01

    We present the design and implementation of an electronic device that, using off the shelf discrete analog components, implements the mathematical model of a cold receptor neuron called Huber-Braun. This model describes the electrical behavior of certain kinds of receptors when interacting with their environment, and it consists of a set of differential equations that has only been solved by numeric simulations. By these means a chaotic behavior has been found. An analog computer can be relevant for further analysis and validation of the model. The results obtained by means of numeric simulations and through our analog circuit simulator are consistent. In particular, temperature and external current bifurcation diagrams were successfully built. Finally, the electronic device allows the observation of all relevant variables and most of the expected behavior (tonic firing, chaotic, burst discharge, subthreshold oscillation and steady state). PMID:23366650

  12. Mixed-mode oscillations in a three time-scale model for the dopaminergic neuron

    NASA Astrophysics Data System (ADS)

    Krupa, Martin; Popović, Nikola; Kopell, Nancy; Rotstein, Horacio G.

    2008-03-01

    Mixed-mode dynamics is a complex type of dynamical behavior that has been observed both numerically and experimentally in numerous prototypical systems in the natural sciences. The compartmental Wilson-Callaway model for the dopaminergic neuron is an example of a system that exhibits a wide variety of mixed-mode patterns upon variation of a control parameter. One characteristic feature of this system is the presence of multiple time scales. In this article, we study the Wilson-Callaway model from a geometric point of view. We show that the observed mixed-mode dynamics is caused by a slowly varying canard structure. By appropriately transforming the model equations, we reduce them to an underlying three-dimensional canonical form that can be analyzed via a slight adaptation of the approach developed by M. Krupa, N. Popović, and N. Kopell (unpublished).

  13. Biochanin A protects dopaminergic neurons against lipopolysaccharide-induced damage and oxidative stress in a rat model of Parkinson's disease.

    PubMed

    Wang, Jun; He, Can; Wu, Wang-Yang; Chen, Feng; Wu, Yang-Yang; Li, Wei-Zu; Chen, Han-Qing; Yin, Yan-Yan

    2015-11-01

    Parkinson's disease (PD) is the second most common neurodegenerative disease, which is characterized by loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc). Accumulated evidences have suggested that oxidative stress is closely associated with the dopaminergic neurodegeneration of PD that can be protected by antioxidants. Biochanin A that is an O-methylated isoflavone in chickpea is investigated to explore its protective mechanism on dopaminergic neurons of the unilateral lipopolysaccharide (LPS)-injected rat. The results showed that biochanin A significantly improved the animal model's behavioral symptoms, prevented the loss of dopaminergic neurons and inhibited the deleterious microglia activation in the LPS-induced rats. Moreover, biochanin A inhibited nicotinamide adenine dinucleotide phosphate oxidase (NADPH oxidase) activation and malondialdehyde (MDA) production, increased superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities in the rat brain. These results suggested that biochanin A might be a natural candidate with protective properties on dopaminergic neurons against the PD. PMID:26394281

  14. Dynamic neuronal ensembles: Issues in representing structure change in object-oriented, biologically-based brain models

    SciTech Connect

    Vahie, S.; Zeigler, B.P.; Cho, H.

    1996-12-31

    This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological systems, using a neural circuit from a snail is presented and discussed. This paper provides an insight into the DNE paradigm using models developed and simulated in DEVS.

  15. Soman and glutamate toxicity in cultured cortical and hippocampal neurons: An in vitro model for testing neuroprotective drugs

    SciTech Connect

    Deshpande, S.S.; Filbert, M.G.; Cann, F.J.

    1993-05-13

    An in vitro mammalian model neuronal system to evaluate intrinsic toxicity of soman and other neurotoxicants and the efficacy of potential countermeasures was developed. Primary dissociated cell cultures from rat hippocampus and cerebral neocortex have been established. The link between soman toxicity, glutamate hyperactivity and neuronal death in the central nervous system was investigated. The cytotoxicity was assessed by trypan blue dye exclusion and also from the measurement of LDH released by damaged cells in the extracellular fluid 24 hr after exposure. Cortical or hippocampal cells exposed to glutamate for 15 min caused neuronal death in almost 80 % of the cells examined at 24 hr. when cortical cells were exposed to soman alone for 15 to 120 min, washed to remove excess ChE inhibitor and incubated for 24 hr, no damage was evident as assessed by trypan blue exclusion or LDH assay. Soman does not appear to have direct toxic effect on the cerebral cortical neurons.

  16. Model-based iterative learning control of Parkinsonian state in thalamic relay neuron

    NASA Astrophysics Data System (ADS)

    Liu, Chen; Wang, Jiang; Li, Huiyan; Xue, Zhiqin; Deng, Bin; Wei, Xile

    2014-09-01

    Although the beneficial effects of chronic deep brain stimulation on Parkinson's disease motor symptoms are now largely confirmed, the underlying mechanisms behind deep brain stimulation remain unclear and under debate. Hence, the selection of stimulation parameters is full of challenges. Additionally, due to the complexity of neural system, together with omnipresent noises, the accurate model of thalamic relay neuron is unknown. Thus, the iterative learning control of the thalamic relay neuron's Parkinsonian state based on various variables is presented. Combining the iterative learning control with typical proportional-integral control algorithm, a novel and efficient control strategy is proposed, which does not require any particular knowledge on the detailed physiological characteristics of cortico-basal ganglia-thalamocortical loop and can automatically adjust the stimulation parameters. Simulation results demonstrate the feasibility of the proposed control strategy to restore the fidelity of thalamic relay in the Parkinsonian condition. Furthermore, through changing the important parameter—the maximum ionic conductance densities of low-threshold calcium current, the dominant characteristic of the proposed method which is independent of the accurate model can be further verified.

  17. Functional Neurons Generated from T Cell-Derived Induced Pluripotent Stem Cells for Neurological Disease Modeling.

    PubMed

    Matsumoto, Takuya; Fujimori, Koki; Andoh-Noda, Tomoko; Ando, Takayuki; Kuzumaki, Naoko; Toyoshima, Manabu; Tada, Hirobumi; Imaizumi, Kent; Ishikawa, Mitsuru; Yamaguchi, Ryo; Isoda, Miho; Zhou, Zhi; Sato, Shigeto; Kobayashi, Tetsuro; Ohtaka, Manami; Nishimura, Ken; Kurosawa, Hiroshi; Yoshikawa, Takeo; Takahashi, Takuya; Nakanishi, Mahito; Ohyama, Manabu; Hattori, Nobutaka; Akamatsu, Wado; Okano, Hideyuki

    2016-03-01

    Modeling of neurological diseases using induced pluripotent stem cells (iPSCs) derived from the somatic cells of patients has provided a means of elucidating pathogenic mechanisms and performing drug screening. T cells are an ideal source of patient-specific iPSCs because they can be easily obtained from samples. Recent studies indicated that iPSCs retain an epigenetic memory relating to their cell of origin that restricts their differentiation potential. The classical method of differentiation via embryoid body formation was not suitable for T cell-derived iPSCs (TiPSCs). We developed a neurosphere-based robust differentiation protocol, which enabled TiPSCs to differentiate into functional neurons, despite differences in global gene expression between TiPSCs and adult human dermal fibroblast-derived iPSCs. Furthermore, neurons derived from TiPSCs generated from a juvenile patient with Parkinson's disease exhibited several Parkinson's disease phenotypes. Therefore, we conclude that TiPSCs are a useful tool for modeling neurological diseases. PMID:26905201

  18. Functional Neurons Generated from T Cell-Derived Induced Pluripotent Stem Cells for Neurological Disease Modeling

    PubMed Central

    Matsumoto, Takuya; Fujimori, Koki; Andoh-Noda, Tomoko; Ando, Takayuki; Kuzumaki, Naoko; Toyoshima, Manabu; Tada, Hirobumi; Imaizumi, Kent; Ishikawa, Mitsuru; Yamaguchi, Ryo; Isoda, Miho; Zhou, Zhi; Sato, Shigeto; Kobayashi, Tetsuro; Ohtaka, Manami; Nishimura, Ken; Kurosawa, Hiroshi; Yoshikawa, Takeo; Takahashi, Takuya; Nakanishi, Mahito; Ohyama, Manabu; Hattori, Nobutaka; Akamatsu, Wado; Okano, Hideyuki

    2016-01-01

    Summary Modeling of neurological diseases using induced pluripotent stem cells (iPSCs) derived from the somatic cells of patients has provided a means of elucidating pathogenic mechanisms and performing drug screening. T cells are an ideal source of patient-specific iPSCs because they can be easily obtained from samples. Recent studies indicated that iPSCs retain an epigenetic memory relating to their cell of origin that restricts their differentiation potential. The classical method of differentiation via embryoid body formation was not suitable for T cell-derived iPSCs (TiPSCs). We developed a neurosphere-based robust differentiation protocol, which enabled TiPSCs to differentiate into functional neurons, despite differences in global gene expression between TiPSCs and adult human dermal fibroblast-derived iPSCs. Furthermore, neurons derived from TiPSCs generated from a juvenile patient with Parkinson's disease exhibited several Parkinson's disease phenotypes. Therefore, we conclude that TiPSCs are a useful tool for modeling neurological diseases. PMID:26905201

  19. Spontaneous dynamics and response properties of a Hodgkin-Huxley-type neuron model driven by harmonic synaptic noise

    PubMed Central

    Nguyen, Hoai; Neiman, Alexander B.

    2010-01-01

    We study statistical properties, response dynamics, and information transmission in a Hodgkin-Huxley–type neuron system, modeling peripheral electroreceptors in paddlefish. In addition to sodium and potassium currents, the neuron model includes fast calcium and slow afterhyperpolarization (AHP) potassium currents. The synaptic transmission from sensory epithelium is modeled by a Poission process with a rate modulated by narrow-band noise, mimicking stochastic epithelial oscillations observed experimentally. We study how the interplay of parameters of AHP current and synaptic noise affects the statistics of spontaneous dynamics and response properties of the system. In particular, we confirm predictions made earlier with perfect integrate and fire and phase neuron models that epithelial oscillations enhance stimulus–response coherence and thus information transmission in electroreceptor system. In addition, we consider a strong stimulus regime and show that coherent epithelial oscillations may reduce variability of electroreceptor responses to time-varying stimuli. PMID:20975925

  20. Transient Exposure to Ethanol during Zebrafish Embryogenesis Results in Defects in Neuronal Differentiation: An Alternative Model System to Study FASD

    PubMed Central

    Joya, Xavier; Garcia-Algar, Oscar; Vall, Oriol; Pujades, Cristina

    2014-01-01

    Background The exposure of the human embryo to ethanol results in a spectrum of disorders involving multiple organ systems, including the impairment of the development of the central nervous system (CNS). In spite of the importance for human health, the molecular basis of prenatal ethanol exposure remains poorly understood, mainly to the difficulty of sample collection. Zebrafish is now emerging as a powerful organism for the modeling and the study of human diseases. In this work, we have assessed the sensitivity of specific subsets of neurons to ethanol exposure during embryogenesis and we have visualized the sensitive embryonic developmental periods for specific neuronal groups by the use of different transgenic zebrafish lines. Methodology/Principal Findings In order to evaluate the teratogenic effects of acute ethanol exposure, we exposed zebrafish embryos to ethanol in a given time window and analyzed the effects in neurogenesis, neuronal differentiation and brain patterning. Zebrafish larvae exposed to ethanol displayed small eyes and/or a reduction of the body length, phenotypical features similar to the observed in children with prenatal exposure to ethanol. When neuronal populations were analyzed, we observed a clear reduction in the number of differentiated neurons in the spinal cord upon ethanol exposure. There was a decrease in the population of sensory neurons mainly due to a decrease in cell proliferation and subsequent apoptosis during neuronal differentiation, with no effect in motoneuron specification. Conclusion Our investigation highlights that transient exposure to ethanol during early embryonic development affects neuronal differentiation although does not result in defects in early neurogenesis. These results establish the use of zebrafish embryos as an alternative research model to elucidate the molecular mechanism(s) of ethanol-induced developmental toxicity at very early stages of embryonic development. PMID:25383948

  1. Lemon Odor Reduces Stress-induced Neuronal Activation in the Emotion Expression System: An Animal Model Study

    NASA Astrophysics Data System (ADS)

    Sanada, Kazue; Sugimoto, Koji; Shutoh, Fumihiro; Hisano, Setsuji

    Perception of particular sensory stimuli from the surroundings can influence emotion in individuals. In an uncomfortable situation, humans protect themselves from some aversive stimulus by acutely evoking a stress response. Animal model studies have contributed to an understanding of neuronal mechanisms underlying the stress response in humans. To study a possible anti-stressful effect of lemon odor, an excitation of neurons secreting corticotropin-releasing hormone (CRH) as a primary factor of the hypothalamic-pituitary-adrenal axis (HPA) was analyzed in animal model experiments, in which rats are restrained in the presence or absence of the odor. The effect was evaluated by measuring expression of c-Fos (an excited neuron marker) in the hypothalamic paraventricular nucleus (PVN), a key structure of the HPA in the brain. We prepared 3 animal groups: Groups S, L and I. Groups S and L were restrained for 30 minutes while being blown by air and being exposed to the lemon odor, respectively. Group I was intact without any treatment. Two hours later of the onset of experiments, brains of all groups were sampled and processed for microscopic examination. Brain sections were processed for c-Fos immunostaining and/or in situ hybridization for CRH. In Group S but not in Group I, c-Fos expression was found in the PVN. A combined in situ hybridization-immunohistochemical dual labeling revealed that CRH mRNA-expressing neurons express c-Fos. In computer-assisted automatic counting, the incidence of c-Fos-expressing neurons in the entire PVN was statistically lower in Group L than in Group S. Detailed analysis of PVN subregions demonstrated that c-Fos-expressing neurons are fewer in Group L than in Group S in the dorsal part of the medial parvocellular subregion. These results may suggest that lemon odor attenuates the restraint stress-induced neuronal activation including CRH neurons, presumably mimicking an aspect of stress responses in humans.

  2. A Computational Model of the Dendron of the GnRH Neuron.

    PubMed

    Chen, Xingjiang; Sneyd, James

    2015-06-01

    Gonadotropin-releasing hormone (GnRH) neurons have two major processes that have properties of both dendrites (they receive synaptic input from other neurons) and axons (they actively propagate action potentials to the synaptic terminal). These processes have thus been termed dendrons. We construct a stochastic spatiotemporal model of the dendron of the GnRH neuron, with the goal of studying how stochastic synaptic input along the length of the dendron affects the initiation and propagation of action potentials. We show (1) that synaptic inputs closer to the soma are effective controllers of action potential initiation and electrical bursting and (2) that although the effects on the amplitude and width of propagating action potentials are critically dependent on the timing and location of synaptic input addition, the effects remain small. We conclude that although stochastic synaptic input along the length of the dendron is likely to be a major determinant of action potential initiation, it is an unlikely mechanism for controlling whether or not action potentials reach the synaptic terminal. Thus, the role of synaptic inputs situated along the dendron a long way from the site of action potential initiation remains unclear. We also show that the actions of kisspeptin can result in significant modulation of the amount of calcium released by an action potential at the synaptic terminal. Furthermore, we show that the actions of kisspeptin are greatest when multiple effects operate together and that a kisspeptin-induced increase in firing rate is, by itself, less effective at increasing Ca2+ release than is a combination of an increased firing rate, an increase in Ca2+ influx, and an increase in inositol trisphosphate (IP3) production. We conclude that the inherent synergies in the various actions of kisspeptin make it a likely candidate for the precise control of Ca2+ transients at the synaptic terminal. PMID:25503424

  3. Hypothalamic Dopaminergic Neurons in an Animal Model of Seasonal Affective Disorder

    PubMed Central

    Deats, Sean P.; Adidharma, Widya; Yan, Lily

    2015-01-01

    Light has profound effects on mood regulation as exemplified in Seasonal Affective Disorder (SAD) and the therapeutic benefits of light therapy. However, the underlying neural pathways through which light regulates mood are not well understood. Our previous work has developed the diurnal grass rat, Arvicanthis niloticus, as an animal model of SAD. Following housing conditions of either 12:12hr Dim Light:Dark (DLD) or 8:16hr Short Photoperiod (SP), which mimic the lower light intensity or short day-length of winter, respectively, grass rats exhibit an increase in depression-like behavior compared to those housed in a 12:12hr Bright Light:Dark (BLD) condition. Furthermore, we revealed that the orexinergic system is involved in mediating the effects of light on mood and anxiety. To explore other potential neural substrates involved in the depressive phenotype, the present study examined hypothalamic dopaminergic (DA) and somatostatin (SST) neurons in the brains of grass rats housed in DLD, SP and BLD. Using immunostaining for tyrosine hydroxylase (TH) and SST, we found that the number of TH- and SST-ir cells in the hypothalamus was significantly lower in the DLD and SP groups compared to the BLD group. We also found that treating BLD animals with a selective orexin receptor 1 (OX1R) antagonist SB-334867 significantly reduced the number of hypothalamic TH-ir cells. The present study suggests that the hypothalamic DA neurons are sensitive to daytime light deficiency and are regulated by an orexinergic pathway. The results support the hypothesis that the orexinergic pathways mediate the effects of light on other neuronal systems that collectively contribute to light-dependent changes in the affective state. PMID:26116821

  4. Interdisciplinary approaches of transcranial magnetic stimulation applied to a respiratory neuronal circuitry model.

    PubMed

    Vinit, Stéphane; Keomani, Emilie; Deramaudt, Thérèse B; Spruance, Victoria M; Bezdudnaya, Tatiana; Lane, Michael A; Bonay, Marcel; Petitjean, Michel

    2014-01-01

    Respiratory related diseases associated with the neuronal control of breathing represent life-threatening issues and to date, no effective therapeutics are available to enhance the impaired function. The aim of this study was to determine whether a preclinical respiratory model could be used for further studies to develop a non-invasive therapeutic tool applied to rat diaphragmatic neuronal circuitry. Transcranial magnetic stimulation (TMS) was performed on adult male Sprague-Dawley rats using a human figure-of-eight coil. The largest diaphragmatic motor evoked potentials (MEPdia) were recorded when the center of the coil was positioned 6 mm caudal from Bregma, involving a stimulation of respiratory supraspinal pathways. Magnetic shielding of the coil with mu metal reduced magnetic field intensities and improved focality with increased motor threshold and lower amplitude recruitment curve. Moreover, transynaptic neuroanatomical tracing with pseudorabies virus (applied to the diaphragm) suggest that connections exist between the motor cortex, the periaqueductal grey cell regions, several brainstem neurons and spinal phrenic motoneurons (distributed in the C3-4 spinal cord). These results reveal the anatomical substrate through which supraspinal stimulation can convey descending action potential volleys to the spinal motoneurons (directly or indirectly). We conclude that MEPdia following a single pulse of TMS can be successfully recorded in the rat and may be used in the assessment of respiratory supraspinal plasticity. Supraspinal non-invasive stimulations aimed to neuromodulate respiratory circuitry will enable new avenues of research into neuroplasticity and the development of therapies for respiratory dysfunction associated with neural injury and disease (e.g. spinal cord injury, amyotrophic lateral sclerosis). PMID:25406091

  5. Iron-induced neuronal damage in a rat model of post-traumatic stress disorder.

    PubMed

    Zhao, Ming; Yu, Zhibo; Zhang, Yang; Huang, Xueling; Hou, Jingming; Zhao, YanGang; Luo, Wei; Chen, Lin; Ou, Lan; Li, Haitao; Zhang, Jiqiang

    2016-08-25

    Previous studies have shown that iron redistribution and deposition in the brain occurs in some neurodegenerative diseases, and oxidative damage due to abnormal iron level is a primary cause of neuronal death. In the present study, we used the single prolonged stress (SPS) model to mimic post-traumatic stress disorder (PTSD), and examined whether iron was involved in the progression of PTSD. The anxiety-like behaviors of the SPS group were assessed by the elevated plus maze (EPM) and open field tests, and iron levels were measured by inductively coupled plasma optical emission spectrometer (ICP-OES). Expression of glucocorticoid receptors and transferrin receptor 1 (TfR1) and ferritin (Fn) was detected by Western blot and immunohistochemistry in selected brain areas; TfR1 and Fn mRNA expression were detected by quantitative-polymerase chain reaction (Q-PCR). Ultrastructures of the hippocampus were observed under a transmission electron microscope. Our results showed that SPS exposure induced anxiety-like symptoms and increased the level of serum cortisol and the concentration of iron in key brain areas such as the hippocampus, prefrontal cortex, and striatum. The stress induced region-specific changes in both protein and mRNA levels of TfR1 and Fn. Moreover, swelling mitochondria and cell apoptosis were observed in neurons in brain regions with iron accumulation. We concluded that SPS stress increased iron in some cognition-related brain regions and subsequently cause neuronal injury, indicating that the iron may function in the pathology of PTSD. PMID:27208615

  6. Interdisciplinary Approaches of Transcranial Magnetic Stimulation Applied to a Respiratory Neuronal Circuitry Model

    PubMed Central

    Vinit, Stéphane; Keomani, Emilie; Deramaudt, Thérèse B.; Spruance, Victoria M.; Bezdudnaya, Tatiana; Lane, Michael A.

    2014-01-01

    Respiratory related diseases associated with the neuronal control of breathing represent life-threatening issues and to date, no effective therapeutics are available to enhance the impaired function. The aim of this study was to determine whether a preclinical respiratory model could be used for further studies to develop a non-invasive therapeutic tool applied to rat diaphragmatic neuronal circuitry. Transcranial magnetic stimulation (TMS) was performed on adult male Sprague-Dawley rats using a human figure-of-eight coil. The largest diaphragmatic motor evoked potentials (MEPdia) were recorded when the center of the coil was positioned 6 mm caudal from Bregma, involving a stimulation of respiratory supraspinal pathways. Magnetic shielding of the coil with mu metal reduced magnetic field intensities and improved focality with increased motor threshold and lower amplitude recruitment curve. Moreover, transynaptic neuroanatomical tracing with pseudorabies virus (applied to the diaphragm) suggest that connections exist between the motor cortex, the periaqueductal grey cell regions, several brainstem neurons and spinal phrenic motoneurons (distributed in the C3-4 spinal cord). These results reveal the anatomical substrate through which supraspinal stimulation can convey descending action potential volleys to the spinal motoneurons (directly or indirectly). We conclude that MEPdia following a single pulse of TMS can be successfully recorded in the rat and may be used in the assessment of respiratory supraspinal plasticity. Supraspinal non-invasive stimulations aimed to neuromodulate respiratory circuitry will enable new avenues of research into neuroplasticity and the development of therapies for respiratory dysfunction associated with neural injury and disease (e.g. spinal cord injury, amyotrophic lateral sclerosis). PMID:25406091

  7. Automated evolutionary optimization of ion channel conductances and kinetics in models of young and aged rhesus monkey pyramidal neurons.

    PubMed

    Rumbell, Timothy H; Draguljić, Danel; Yadav, Aniruddha; Hof, Patrick R; Luebke, Jennifer I; Weaver, Christina M

    2016-08-01

    Conductance-based compartment modeling requires tuning of many parameters to fit the neuron model to target electrophysiological data. Automated parameter optimization via evolutionary algorithms (EAs) is a common approach to accomplish this task, using error functions to quantify differences between model and target. We present a three-stage EA optimization protocol for tuning ion channel conductances and kinetics in a generic neuron model with minimal manual intervention. We use the technique of Latin hypercube sampling in a new way, to choose weights for error functions automatically so that each function influences the parameter search to a similar degree. This protocol requires no specialized physiological data collection and is applicable to commonly-collected current clamp data and either single- or multi-objective optimization. We applied the protocol to two representative pyramidal neurons from layer 3 of the prefrontal cortex of rhesus monkeys, in which action potential firing rates are significantly higher in aged compared to young animals. Using an idealized dendritic topology and models with either 4 or 8 ion channels (10 or 23 free parameters respectively), we produced populations of parameter combinations fitting the target datasets in less than 80 hours of optimization each. Passive parameter differences between young and aged models were consistent with our prior results using simpler models and hand tuning. We analyzed parameter values among fits to a single neuron to facilitate refinement of the underlying model, and across fits to multiple neurons to show how our protocol will lead to predictions of parameter differences with aging in these neurons. PMID:27106692

  8. A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models

    PubMed Central

    Hanuschkin, A.; Ganguli, S.; Hahnloser, R. H. R.

    2013-01-01

    Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli. PMID

  9. Sertoli cells improve survival of motor neurons in SOD1 transgenic mice, a model of amyotrophic lateral sclerosis.

    PubMed

    Hemendinger, Richelle; Wang, Jay; Malik, Saafan; Persinski, Rafal; Copeland, Jane; Emerich, Dwaine; Gores, Paul; Halberstadt, Craig; Rosenfeld, Jeffrey

    2005-12-01

    Cell replacement therapy has been widely suggested as a treatment for multiple diseases including motor neuron disease. A variety of donor cells have been tested for treatment including isolated preparations from bone marrow and embryonic spinal cord. Another cell source, Sertoli cells, have been successfully used in models of diabetes, Parkinson's disease and Huntington's disease. The ability of these cells to secrete cytoprotective proteins and their role as 'nurse cells' supporting the function of other cell types in the testes suggest their potential use as neuroprotective cells. The current study examines the ability of Sertoli cells injected into the parenchyma of the spinal cord to protect motor neurons in a mouse model for amyotrophic lateral sclerosis. Seventy transgenic mice expressing the mutant (G93A) human Cu-Zn superoxide dismutase (SOD1) received a unilateral spinal injection of Sertoli-enriched testicular cells into the L4-L5 ventral horn (1 x 10(5) cells total) prior to the onset of clinical symptoms. The animals were euthanized at the end stage of the disease. Histological and morphometric analyses of the transplant site were performed. A significant increase in the number of surviving ChAT positive motor neurons was found ipsilateral to the injection compared with contralateral and uninjected spinal cord. The ipsilateral increase in motor neuron density was dependent upon proximity to the injection site. Sections rostral or caudal to the injection site did not display a similar difference in motor neuron density. Implantation of a Sertoli-cell-enriched preparation has a significant neuroprotective benefit to vulnerable motor neurons in the SOD1 transgenic model. The therapeutic benefit may be the result of secreted neurotrophic factors present at a critical stage of motor neuron degeneration in this model. PMID:16242126

  10. A Motion Detection Model Inspired by the Neuronal Propagation in the Hippocampus

    NASA Astrophysics Data System (ADS)

    Liang, Haichao; Morie, Takashi

    We propose a motion detection model, which is suitable for higher speed operation than the video rate, inspired by the neuronal propagation in the hippocampus in the brain. The model detects motion of edges, which are extracted from monocular image sequences, on specified 2D maps without image matching. We introduce gating units into a CA3-CA1 model, where CA3 and CA1 are the names of hippocampal regions. We use the function of gating units to reduce mismatching for applying our model in complicated situations. We also propose a map-division method to achieve accurate detection. We have evaluated the performance of the proposed model by using artificial and real image sequences. The results show that the proposed model can run up to 1.0ms/frame if using a resolution of 64 × 60 units division of 320 × 240 pixels image. The detection rate of moving edges is achieved about 99% under a complicated situation. We have also verified that the proposed model can achieve accurate detection of approaching objects at high frame rate (> 100fps), which is better than conventional models, provided we can obtain accurate positions of image features and filter out the origins of false positive results in the post-processing.

  11. Respiratory pattern generator model using Ca++-induced Ca++ release in neurons shows both pacemaker and reciprocal network properties.

    PubMed

    Dunin-Barkowski, W L; Escobar, A L; Lovering, A T; Orem, J M

    2003-10-01

    There are two contradictory explanations for central respiratory rhythmogenesis. One suggests that respiratory rhythm emerges from interaction between inspiratory and expiratory neural semicenters that inhibit each other and thereby provide reciprocal rhythmic activity (Brown 1914). The other uses bursting pacemaker activity of individual neurons to produce the rhythm (Feldman and Cleland 1982). Hybrid models have been developed to reconcile these two seemingly conflicting mechanisms (Smith et al. 2000; Rybak et al. 2001). Here we report computer simulations that demonstrate a unified mechanism of the two types of oscillator. In the model, we use the interaction of Ca(++)-dependent K+ channels (Mifflin et al. 1985) with Ca(++)-induced Ca++ release from intracellular stores (McPherson and Campbell 1993), which was recently revealed in neurons (Hernandez-Cruz et al. 1997; Mitra and Slaughter 2002a,b; Scornik et al. 2001). Our computations demonstrate that uncoupled neurons with these intracellular mechanisms show conditional pacemaker properties (Butera et al. 1999) when exposed to steady excitatory inputs. Adding weak inhibitory synapses (based on increased K+ conductivity) between two model neural pools surprisingly synchronizes the activity of both neural pools. As inhibitory synaptic connections between the two pools increase from zero to higher values, the model produces first dissociated pacemaker activity of individual neurons, then periodic synchronous bursts of all neurons (inspiratory and expiratory), and finally reciprocal rhythmic activity of the neural pools. PMID:14605892

  12. Bifurcation of synchronous oscillations into torus in a system of two reciprocally inhibitory silicon neurons: experimental observation and modeling.

    PubMed

    Bondarenko, Vladimir E; Cymbalyuk, Gennady S; Patel, Girish; Deweerth, Stephen P; Calabrese, Ronald L

    2004-12-01

    Oscillatory activity in the central nervous system is associated with various functions, like motor control, memory formation, binding, and attention. Quasiperiodic oscillations are rarely discussed in the neurophysiological literature yet they may play a role in the nervous system both during normal function and disease. Here we use a physical system and a model to explore scenarios for how quasiperiodic oscillations might arise in neuronal networks. An oscillatory system of two mutually inhibitory neuronal units is a ubiquitous network module found in nervous systems and is called a half-center oscillator. Previously we created a half-center oscillator of two identical oscillatory silicon (analog Very Large Scale Integration) neurons and developed a mathematical model describing its dynamics. In the mathematical model, we have shown that an in-phase limit cycle becomes unstable through a subcritical torus bifurcation. However, the existence of this torus bifurcation in experimental silicon two-neuron system was not rigorously demonstrated or investigated. Here we demonstrate the torus predicted by the model for the silicon implementation of a half-center oscillator using complex time series analysis, including bifurcation diagrams, mapping techniques, correlation functions, amplitude spectra, and correlation dimensions, and we investigate how the properties of the quasiperiodic oscillations depend on the strengths of coupling between the silicon neurons. The potential advantages and disadvantages of quasiperiodic oscillations (torus) for biological neural systems and artificial neural networks are discussed. PMID:15568913

  13. Multiscale Coupling of Transcranial Direct Current Stimulation to Neuron Electrodynamics: Modeling the Influence of the Transcranial Electric Field on Neuronal Depolarization

    PubMed Central

    Dougherty, Edward T.; Turner, James C.; Vogel, Frank

    2014-01-01

    Transcranial direct current stimulation (tDCS) continues to demonstrate success as a medical intervention for neurodegenerative diseases, psychological conditions, and traumatic brain injury recovery. One aspect of tDCS still not fully comprehended is the influence of the tDCS electric field on neural functionality. To address this issue, we present a mathematical, multiscale model that couples tDCS administration to neuron electrodynamics. We demonstrate the model's validity and medical applicability with computational simulations using an idealized two-dimensional domain and then an MRI-derived, three-dimensional human head geometry possessing inhomogeneous and anisotropic tissue conductivities. We exemplify the capabilities of these simulations with real-world tDCS electrode configurations and treatment parameters and compare the model's predictions to those attained from medical research studies. The model is implemented using efficient numerical strategies and solution techniques to allow the use of fine computational grids needed by the medical community. PMID:25404950

  14. The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity

    PubMed Central

    Ward, Jamie

    2016-01-01

    Synaesthesia is an unusual perceptual experience in which an inducer stimulus triggers a percept in a different domain in addition to its own. To explore the conditions under which synaesthesia evolves, we studied a neuronal network model that represents two recurrently connected neural systems. The interactions in the network evolve according to learning rules that optimize sensory sensitivity. We demonstrate several scenarios, such as sensory deprivation or heightened plasticity, under which synaesthesia can evolve even though the inputs to the two systems are statistically independent and the initial cross-talk interactions are zero. Sensory deprivation is the known causal mechanism for acquired synaesthesia and increased plasticity is implicated in developmental synaesthesia. The model unifies different causes of synaesthesia within a single theoretical framework and repositions synaesthesia not as some quirk of aberrant connectivity, but rather as a functional brain state that can emerge as a consequence of optimising sensory information processing. PMID:27392215

  15. Edaravone Guards Dopamine Neurons in a Rotenone Model for Parkinson's Disease

    PubMed Central

    Chen, Chunnuan; Huang, Jinsha; Zhao, Ying; Zhang, Zhentao; Qiao, Xian; Feng, Yuan; Reesaul, Harrish; Zhang, Yongxue; Sun, Shenggang; Lin, Zhicheng; Wang, Tao

    2011-01-01

    3-methyl-1-phenyl-2-pyrazolin-5-one (edaravone), an effective free radical scavenger, provides neuroprotection in stroke models and patients. In this study, we investigated its neuroprotective effects in a chronic rotenone rat model for Parkinson's disease. Here we showed that a five-week treatment with edaravone abolished rotenone's activity to induce catalepsy, damage mitochondria and degenerate dopamine neurons in the midbrain of rotenone-treated rats. This abolishment was attributable at least partly to edaravone's inhibition of rotenone-induced reactive oxygen species production or apoptotic promoter Bax expression and its up-regulation of the vesicular monoamine transporter 2 (VMAT2) expression. Collectively, edaravone may provide novel clinical therapeutics for PD. PMID:21677777

  16. The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity.

    PubMed

    Shriki, Oren; Sadeh, Yaniv; Ward, Jamie

    2016-07-01

    Synaesthesia is an unusual perceptual experience in which an inducer stimulus triggers a percept in a different domain in addition to its own. To explore the conditions under which synaesthesia evolves, we studied a neuronal network model that represents two recurrently connected neural systems. The interactions in the network evolve according to learning rules that optimize sensory sensitivity. We demonstrate several scenarios, such as sensory deprivation or heightened plasticity, under which synaesthesia can evolve even though the inputs to the two systems are statistically independent and the initial cross-talk interactions are zero. Sensory deprivation is the known causal mechanism for acquired synaesthesia and increased plasticity is implicated in developmental synaesthesia. The model unifies different causes of synaesthesia within a single theoretical framework and repositions synaesthesia not as some quirk of aberrant connectivity, but rather as a functional brain state that can emerge as a consequence of optimising sensory information processing. PMID:27392215

  17. Homoclinic bifurcation in a Hodgkin-Huxley model of thermally sensitive neurons

    SciTech Connect

    Feudel, Ulrike; Neiman, Alexander; Pei, Xing; Wojtenek, Winfried; Braun, Hans; Huber, Martin; Moss, Frank

    2000-03-01

    We study global bifurcations of the chaotic attractor in a modified Hodgkin-Huxley model of thermally sensitive neurons. The control parameter for this model is the temperature. The chaotic behavior is realized over a wide range of temperatures and is visualized using interspike intervals. We observe an abrupt increase of the interspike intervals in a certain temperature region. We identify this as a homoclinic bifurcation of a saddle-focus fixed point which is embedded in the chaotic attractors. The transition is accompanied by intermittency, which obeys a universal scaling law for the average length of trajectory segments exhibiting only short interspike intervals with the distance from the onset of intermittency. We also present experimental results of interspike interval measurements taken from the crayfish caudal photoreceptor, which qualitatively demonstrate the same bifurcation structure. (c) 2000 American Institute of Physics.

  18. A stochastic model for automatic extraction of 3D neuronal morphology.

    PubMed

    Basu, Sreetama; Kulikova, Maria; Zhizhina, Elena; Ooi, Wei Tsang; Racoceanu, Daniel

    2013-01-01

    Tubular structures are frequently encountered in bio-medical images. The center-lines of these tubules provide an accurate representation of the topology of the structures. We introduce a stochastic Marked Point Process framework for fully automatic extraction of tubular structures requiring no user interaction or seed points for initialization. Our Marked Point Process model enables unsupervised network extraction by fitting a configuration of objects with globally optimal associated energy to the centreline of the arbors. For this purpose we propose special configurations of marked objects and an energy function well adapted for detection of 3D tubular branches. The optimization of the energy function is achieved by a stochastic, discrete-time multiple birth and death dynamics. Our method finds the centreline, local width and orientation of neuronal arbors and identifies critical nodes like bifurcations and terminals. The proposed model is tested on 3D light microscopy images from the DIADEM data set with promising results. PMID:24505691

  19. Dynamical analysis of periodic bursting in piece-wise linear planar neuron model.

    PubMed

    Ji, Ying; Zhang, Xiaofang; Liang, Minjie; Hua, Tingting; Wang, Yawei

    2015-12-01

    A piece-wise linear planar neuron model, namely, two-dimensional McKean model with periodic drive is investigated in this paper. Periodical bursting phenomenon can be observed in the numerical simulations. By assuming the formal solutions associated with different intervals of this non-autonomous system and introducing the generalized Jacobian matrix at the non-smooth boundaries, the bifurcation mechanism for the bursting solution induced by the slowly varying periodic drive is presented. It is shown that, the discontinuous Hopf bifurcation occurring at the non-smooth boundaries, i.e., the bifurcation taking place at the thresholds of the stimulation, leads the alternation between the rest state and spiking state. That is, different oscillation modes of this non-autonomous system convert periodically due to the non-smoothness of the vector field and the slow variation of the periodic drive as well. PMID:26557927

  20. Numerical study of a cylinder model of the diffusion MRI signal for neuronal dendrite trees.

    PubMed

    Van Nguyen, Dang; Grebenkov, Denis; Le Bihan, Denis; Li, Jing-Rebecca

    2015-03-01

    We study numerically how the neuronal dendrite tree structure can affect the diffusion magnetic resonance imaging (dMRI) signal in brain tissue. For a large set of randomly generated dendrite trees, synthetic dMRI signals are computed and fitted to a cylinder model to estimate the effective longitudinal diffusivity D(L) in the direction of neurites. When the dendrite branches are short compared to the diffusion length, D(L) depends significantly on the ratio between the average branch length and the diffusion length. In turn, D(L) has very weak dependence on the distribution of branch lengths and orientations of a dendrite tree, and the number of branches per node. We conclude that the cylinder model which ignores the connectivity of the dendrite tree, can still be adapted to describe the apparent diffusion coefficient in brain tissue. PMID:25681802

  1. Numerical study of a cylinder model of the diffusion MRI signal for neuronal dendrite trees

    NASA Astrophysics Data System (ADS)

    Van Nguyen, Dang; Grebenkov, Denis; Le Bihan, Denis; Li, Jing-Rebecca

    2015-03-01

    We study numerically how the neuronal dendrite tree structure can affect the diffusion magnetic resonance imaging (dMRI) signal in brain tissue. For a large set of randomly generated dendrite trees, synthetic dMRI signals are computed and fitted to a cylinder model to estimate the effective longitudinal diffusivity DL in the direction of neurites. When the dendrite branches are short compared to the diffusion length, DL depends significantly on the ratio between the average branch length and the diffusion length. In turn, DL has very weak dependence on the distribution of branch lengths and orientations of a dendrite tree, and the number of branches per node. We conclude that the cylinder model which ignores the connectivity of the dendrite tree, can still be adapted to describe the apparent diffusion coefficient in brain tissue.

  2. Dipeptide Piracetam Analogue Noopept Improves Viability of Hippocampal HT-22 Neurons in the Glutamate Toxicity Model.

    PubMed

    Antipova, T A; Nikolaev, S V; Ostrovskaya, P U; Gudasheva, T A; Seredenin, S B

    2016-05-01

    Effect of noopept (N-phenylacetyl-prolylglycine ethyl ester) on viability of neurons exposed to neurotoxic action of glutamic acid (5 mM) was studied in vitro in immortalized mouse hippocampal HT-22 neurons. Noopept added to the medium before or after glutamic acid improved neuronal survival in a concentration range of 10-11-10-5 M. Comparison of the effective noopept concentrations determined in previous studies on cultured cortical and cerebellar neurons showed that hippocampal neurons are more sensitive to the protective effect of noopept. PMID:27265136

  3. Drosophila as a Model for MECP2 Gain of Function in Neurons

    PubMed Central

    Vonhoff, Fernando; Williams, Alison; Ryglewski, Stefanie; Duch, Carsten

    2012-01-01

    Methyl-CpG-binding protein 2 (MECP2) is a multi-functional regulator of gene expression. In humans loss of MECP2 function causes classic Rett syndrome, but gain of MECP2 function also causes mental retardation. Although mouse models provide valuable insight into Mecp2 gain and loss of function, the identification of MECP2 genetic targets and interactors remains time intensive and complicated. This study takes a step toward utilizing Drosophila as a model to identify genetic targets and cellular consequences of MECP2 gain-of function mutations in neurons, the principle cell type affected in patients with Rett-related mental retardation. We show that heterologous expression of human MECP2 in Drosophila motoneurons causes distinct defects in dendritic structure and motor behavior, as reported with MECP2 gain of function in humans and mice. Multiple lines of evidence suggest that these defects arise from specific MECP2 function. First, neurons with MECP2-induced dendrite loss show normal membrane currents. Second, dendritic phenotypes require an intact methyl-CpG-binding domain. Third, dendritic defects are amended by reducing the dose of the chromatin remodeling protein, osa, indicating that MECP2 may act via chromatin remodeling in Drosophila. MECP2-induced motoneuron dendritic defects cause specific motor behavior defects that are easy to score in genetic screening. In sum, our data show that some aspects of MECP2 function can be studied in the Drosophila model, thus expanding the repertoire of genetic reagents that can be used to unravel specific neural functions of MECP2. However, additional genes and signaling pathways identified through such approaches in Drosophila will require careful validation in the mouse model. PMID:22363746

  4. Defining and Modeling Known Adverse Outcome Pathways: Domoic Acid and Neuronal Signaling as a Case Study

    SciTech Connect

    Watanabe, Karen H.; Andersen, Melvin E.; Basu, Nil; Carvan, Michael J.; Crofton, Kevin M.; King, Kerensa A.; Sunol, Cristina; Tiffany-Castiglioni, Evelyn; Schultz, Irvin R.

    2011-01-01

    An adverse outcome pathway (AOP) is a sequence of key events from a molecular-level initiating event and an ensuing cascade of steps to an adverse outcome with population level significance. To implement a predictive strategy for ecotoxicology, the multiscale nature of an AOP requires computational models to link salient processes (e.g., in chemical uptake, toxicokinetics, toxicodynamics, and population dynamics). A case study with domoic acid was used to demonstrate strategies and enable generic recommendations for developing computational models in an effort to move toward a toxicity testing paradigm focused on toxicity pathway perturbations applicable to ecological risk assessment. Domoic acid, an algal toxin with adverse effects on both wildlife and humans, is a potent agonist for kainate receptors (ionotropic glutamate receptors whose activation leads to the influx of Na+ and Ca2+). Increased Ca2+ concentrations result in neuronal excitotoxicity and cell death primarily in the hippocampus, which produces seizures, impairs learning and memory, and alters behavior in some species. Altered neuronal Ca2+ is a key process in domoic acid toxicity which can be evaluated in vitro. Further, results of these assays would be amenable to mechanistic modeling for identifying domoic acid concentrations and Ca2+ perturbations that are normal, adaptive, or clearly toxic. In vitro assays with outputs amenable to measurement in exposed populations can link in vitro to in vivo conditions, and toxicokinetic information will aid in linking in vitro results to the individual organism. Development of an AOP required an iterative process with three important outcomes: (1) a critically reviewed, stressor-specific AOP; (2) identification of key processes suitable for evaluation with in vitro assays; and (3) strategies for model development.

  5. Reinforcement Learning of Targeted Movement in a Spiking Neuronal Model of Motor Cortex

    PubMed Central

    Chadderdon, George L.; Neymotin, Samuel A.; Kerr, Cliff C.; Lytton, William W.

    2012-01-01

    Sensorimotor control has traditionally been considered from a control theory perspective, without relation to neurobiology. In contrast, here we utilized a spiking-neuron model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint “forearm” to a target. Learning was based on a reinforcement mechanism analogous to that of the dopamine system. This provided a global reward or punishment signal in response to decreasing or increasing distance from hand to target, respectively. Output was partially driven by Poisson motor babbling, creating stochastic movements that could then be shaped by learning. The virtual forearm consisted of a single segment rotated around an elbow joint, controlled by flexor and extensor muscles. The model consisted of 144 excitatory and 64 inhibitory event-based neurons, each with AMPA, NMDA, and GABA synapses. Proprioceptive cell input to this model encoded the 2 muscle lengths. Plasticity was only enabled in feedforward connections between input and output excitatory units, using spike-timing-dependent eligibility traces for synaptic credit or blame assignment. Learning resulted from a global 3-valued signal: reward (+1), no learning (0), or punishment (−1), corresponding to phasic increases, lack of change, or phasic decreases of dopaminergic cell firing, respectively. Successful learning only occurred when both reward and punishment were enabled. In this case, 5 target angles were learned successfully within 180 s of simulation time, with a median error of 8 degrees. Motor babbling allowed exploratory learning, but decreased the stability of the learned behavior, since the hand continued moving after reaching the target. Our model demonstrated that a global reinforcement signal, coupled with eligibility traces for synaptic plasticity, can train a spiking sensorimotor network to perform goal-directed motor behavior. PMID:23094042

  6. Tau loss attenuates neuronal network hyperexcitability in mouse and Drosophila genetic models of epilepsy

    PubMed Central

    Holth, Jerrah K.; Bomben, Valerie C.; Reed, J. Graham; Inoue, Taeko; Younkin, Linda; Younkin, Steven G.; Pautler, Robia G.; Botas, Juan; Noebels, Jeffrey L.

    2013-01-01

    Neuronal network hyperexcitability underlies the pathogenesis of seizures and is a component of some degenerative neurological disorders such as Alzheimer’s disease (AD). Recently, the microtubule binding protein tau has been implicated in the regulation of network synchronization. Genetic removal of Mapt, the gene encoding tau, in AD models overexpressing amyloid-beta (Aβ) decreases hyperexcitability and normalizes the excitation/inhibition imbalance. Whether this effect of tau removal is specific to Aβ mouse models remains to be determined. Here we examined tau as an excitability modifier in the non-AD nervous system using genetic deletion of tau in mouse and Drosophila models of hyperexcitability. Kcna1−/− mice lack Kv1.1 delayed rectifier currents and exhibit severe spontaneous seizures, early lethality, and megencephaly. Young Kcna1−/− mice retained wild-type levels of Aβ, tau, and tau phospho-Thr231. Decreasing tau in Kcna1−/− mice reduced hyperexcitability and alleviated seizure-related comorbidities. Tau reduction decreased Kcna1−/− video-EEG recorded seizure frequency and duration as well as normalized Kcna1−/− hippocampal network hyperexcitability in vitro. Additionally, tau reduction increased Kcna1−/− survival and prevented megencephaly and hippocampal hypertrophy, as determined by MRI. Bang-sensitive Drosophila mutants display paralysis and seizures in response to mechanical stimulation, providing a complementary excitability assay for epistatic interactions. We found that tau reduction significantly decreased seizure sensitivity in two independent bang-sensitive mutant models, kcc and eas. Our results indicate that tau plays a general role in regulating intrinsic neuronal network hyperexcitability independently of Aβ overexpression and suggest that reducing tau function could be a viable target for therapeutic intervention in seizure disorders and antiepileptogenesis. PMID:23345237

  7. Dysregulation of coordinated neuronal firing patterns in striatum of freely behaving transgenic rats that model Huntington's disease.

    PubMed

    Miller, Benjamin R; Walker, Adam G; Fowler, Stephen C; von Hörsten, Stephan; Riess, Olaf; Johnson, Michael A; Rebec, George V

    2010-01-01

    Altered neuronal activity in the striatum appears to be a key component of Huntington's disease (HD), a fatal, neurodegenerative condition. To assess this hypothesis in freely behaving transgenic rats that model HD (tgHDs), we used chronically implanted micro-wires to record the spontaneous activity of striatal neurons. We found that relative to wild-type controls, HD rats suffer from population-level deficits in striatal activity characterized by a loss of correlated firing and fewer episodes of coincident spike bursting between simultaneously recorded neuronal pairs. These results are in line with our previous report of marked alterations in the pattern of striatal firing in mouse models of HD that vary in background strain, genetic construct, and symptom severity. Thus, loss of coordinated spike activity in striatum appears to be a common feature of HD pathophysiology, regardless of HD model variability. PMID:19818852

  8. A point-process response model for spike trains from single neurons in neural circuits under optogenetic stimulation.

    PubMed

    Luo, X; Gee, S; Sohal, V; Small, D

    2016-02-10

    Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from these experiments present a statistical challenge of modeling a high-frequency point process (neuronal spikes) while the input is another high-frequency point process (light flashes). We further develop a generalized linear model approach to model the relationships between two point processes, employing additive point-process response functions. The resulting model, point-process responses for optogenetics (PRO), provides explicit nonlinear transformations to link the input point process with the output one. Such response functions may provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation. We validate and compare the PRO model using a real dataset and simulations, and our model yields a superior area-under-the-curve value as high as 93% for predicting every future spike. For our experiment on the recurrent layer V circuit in the prefrontal cortex, the PRO model provides evidence that neurons integrate their inputs in a sophisticated manner. Another use of the model is that it enables understanding how neural circuits are altered under various disease conditions and/or experimental conditions by comparing the PRO parameters. PMID:26411923

  9. Ongoing Spontaneous Activity Controls Access to Consciousness: A Neuronal Model for Inattentional Blindness

    PubMed Central

    2005-01-01

    Even in the absence of sensory inputs, cortical and thalamic neurons can show structured patterns of ongoing spontaneous activity, whose origins and functional significance are not well understood. We use computer simulations to explore the conditions under which spontaneous activity emerges from a simplified model of multiple interconnected thalamocortical columns linked by long-range, top-down excitatory axons, and to examine its interactions with stimulus-induced activation. Simulations help characterize two main states of activity. First, spontaneous gamma-band oscillations emerge at a precise threshold controlled by ascending neuromodulator systems. Second, within a spontaneously active network, we observe the sudden “ignition” of one out of many possible coherent states of high-level activity amidst cortical neurons with long-distance projections. During such an ignited state, spontaneous activity can block external sensory processing. We relate those properties to experimental observations on the neural bases of endogenous states of consciousness, and particularly the blocking of access to consciousness that occurs in the psychophysical phenomenon of “inattentional blindness,” in which normal subjects intensely engaged in mental activity fail to notice salient but irrelevant sensory stimuli. Although highly simplified, the generic properties of a minimal network may help clarify some of the basic cerebral phenomena underlying the autonomy of consciousness. PMID:15819609

  10. Using Chick Forebrain Neurons to Model Neurodegeneration and Protection in an Undergraduate Neuroscience Laboratory Course

    PubMed Central

    Burdo, Joseph R.

    2013-01-01

    Since 2009 at Boston College, we have been offering a Research in Neuroscience course using cultured neurons in an in vitro model of stroke. The students work in groups to learn how to perform sterile animal cell culture and run several basic bioassays to assess cell viability. They are then tasked with analyzing the scientific literature in an attempt to identify and predict the intracellular pathways involved in neuronal death, and identify dietary antioxidant compounds that may provide protection based on their known effects in other cells. After each group constructs a hypothesis pertaining to the potential neuroprotection, we purchase one compound per group and the students test their hypotheses using a commonly performed viability assay. The groups generate quantitative data and perform basic statistics on that data to analyze it for statistical significance. Finally, the groups compile their data and other elements of their research experience into a poster for our departmental research celebration at the end of the spring semester. PMID:23805059

  11. The Chihuahua dog: A new animal model for neuronal ceroid lipofuscinosis CLN7 disease?

    PubMed

    Faller, Kiterie M E; Bras, Jose; Sharpe, Samuel J; Anderson, Glenn W; Darwent, Lee; Kun-Rodrigues, Celia; Alroy, Joseph; Penderis, Jacques; Mole, Sara E; Gutierrez-Quintana, Rodrigo; Guerreiro, Rita J

    2016-04-01

    Neuronal ceroid lipofuscinoses (NCLs) are a group of incurable lysosomal storage disorders characterized by neurodegeneration and accumulation of lipopigments mainly within the neurons. We studied two littermate Chihuahua dogs presenting with progressive signs of blindness, ataxia, pacing, and cognitive impairment from 1 year of age. Because of worsening of clinical signs, both dogs were euthanized at about 2 years of age. Postmortem examination revealed marked accumulation of autofluorescent intracellular inclusions within the brain, characteristic of NCL. Whole-genome sequencing was performed on one of the affected dogs. After sequence alignment and variant calling against the canine reference genome, variants were identified in the coding region or splicing regions of four previously known NCL genes (CLN6, ARSG, CLN2 [=TPP1], and CLN7 [=MFSD8]). Subsequent segregation analysis within the family (two affected dogs, both parents, and three relatives) identified MFSD8:p.Phe282Leufs13*, which had previously been identified in one Chinese crested dog with no available ancestries, as the causal mutation. Because of the similarities of the clinical signs and histopathological changes with the human form of the disease, we propose that the Chihuahua dog could be a good animal model of CLN7 disease. PMID:26762174

  12. Scanning electrochemical microscopy of model neurons: imaging and real-time detection of morphological changes.

    PubMed

    Liebetrau, Johanna M; Miller, Heather M; Baur, John E; Takacs, Sara A; Anupunpisit, Vipavee; Garris, Paul A; Wipf, David O

    2003-02-01

    Living PC12 cells, a model cell type for studying neuronal function, were imaged using the negative feedback mode of a scanning electrochemical microscope (SECM). Six biocompatible redox mediators were successfully identified from a large pool of candidates and were then used for imaging PC12 cells before and after exposure to nerve growth factor (NGF). When exposed to NGF, cells differentiate into a neuron phenotype by growing narrow neurites (1-2 microm wide) that can extend > 100 microm from the cell proper. We demonstrate that carbon fiber electrodes with reduced tip diameters can be used for imaging both the cell proper and these neurites. Regions of decreased current, possibly resulting from raised features not identifiable by light microscopy, are clearly evident in the SECM images. Changes in the morphology of undifferentiated PC12 cells could be detected in real time with the SECM. After exposure to hypotonic and hypertonic solutions, reversible changes in cell height of <2 microm were measured. PMID:12585485

  13. A small-molecule scaffold induces autophagy in primary neurons and protects against toxicity in a Huntington disease model

    PubMed Central

    Tsvetkov, Andrey S.; Miller, Jason; Arrasate, Montserrat; Wong, Jinny S.; Pleiss, Michael A.; Finkbeiner, Steven

    2010-01-01

    Autophagy is an intracellular turnover pathway. It has special relevance for neurodegenerative proteinopathies, such as Alzheimer disease, Parkinson disease, and Huntington disease (HD), which are characterized by the accumulation of misfolded proteins. Although induction of autophagy enhances clearance of misfolded protein and has therefore been suggested as a therapy for proteinopathies, neurons appear to be less responsive to classic autophagy inducers than nonneuronal cells. Searching for improved inducers of neuronal autophagy, we discovered an N10-substituted phenoxazine that, at proper doses, potently and safely up-regulated autophagy in neurons in an Akt- and mTOR-independent fashion. In a neuron model of HD, this compound was neuroprotective and decreased the accumulation of diffuse and aggregated misfolded protein. A structure/activity analysis with structurally similar compounds approved by the US Food and Drug Administration revealed a defined pharmacophore for inducing neuronal autophagy. This pharmacophore should prove useful in studying autophagy in neurons and in developing therapies for neurodegenerative proteinopathies. PMID:20833817

  14. An In Vitro Model of Latency and Reactivation of Varicella Zoster Virus in Human Stem Cell-Derived Neurons

    PubMed Central

    Markus, Amos; Lebenthal-Loinger, Ilana; Yang, In Hong; Kinchington, Paul R.; Goldstein, Ronald S.

    2015-01-01

    Varicella zoster virus (VZV) latency in sensory and autonomic neurons has remained enigmatic and difficult to study, and experimental reactivation has not yet been achieved. We have previously shown that human embryonic stem cell (hESC)-derived neurons are permissive to a productive and spreading VZV infection. We now demonstrate that hESC-derived neurons can also host a persistent non-productive infection lasting for weeks which can subsequently be reactivated by multiple experimental stimuli. Quiescent infections were established by exposing neurons to low titer cell-free VZV either by using acyclovir or by infection of axons in compartmented microfluidic chambers without acyclovir. VZV DNA and low levels of viral transcription were detectable by qPCR for up to seven weeks. Quiescently-infected human neuronal cultures were induced to undergo renewed viral gene and protein expression by growth factor removal or by inhibition of PI3-Kinase activity. Strikingly, incubation of cultures induced to reactivate at a lower temperature (34°C) resulted in enhanced VZV reactivation, resulting in spreading, productive infections. Comparison of VZV genome transcription in quiescently-infected to productively-infected neurons using RNASeq revealed preferential transcription from specific genome regions, especially the duplicated regions. These experiments establish a powerful new system for modeling the VZV latent state, and reveal a potential role for temperature in VZV reactivation and disease. PMID:26042814

  15. Deep brain stimulation of the subthalamic nucleus reestablishes neuronal information transmission in the 6-OHDA rat model of parkinsonism

    PubMed Central

    Grill, Warren M.

    2014-01-01

    Pathophysiological activity of basal ganglia neurons accompanies the motor symptoms of Parkinson's disease. High-frequency (>90 Hz) deep brain stimulation (DBS) reduces parkinsonian symptoms, but the mechanisms remain unclear. We hypothesize that parkinsonism-associated electrophysiological changes constitute an increase in neuronal firing pattern disorder and a concomitant decrease in information transmission through the ventral basal ganglia, and that effective DBS alleviates symptoms by decreasing neuronal disorder while simultaneously increasing information transfer through the same regions. We tested these hypotheses in the freely behaving, 6-hydroxydopamine-lesioned rat model of hemiparkinsonism. Following the onset of parkinsonism, mean neuronal firing rates were unchanged, despite a significant increase in firing pattern disorder (i.e., neuronal entropy), in both the globus pallidus and substantia nigra pars reticulata. This increase in neuronal entropy was reversed by symptom-alleviating DBS. Whereas increases in signal entropy are most commonly indicative of similar increases in information transmission, directed information through both regions was substantially reduced (>70%) following the onset of parkinsonism. Again, this decrease in information transmission was partially reversed by DBS. Together, these results suggest that the parkinsonian basal ganglia are rife with entropic activity and incapable of functional information transmission. Furthermore, they indicate that symptom-alleviating DBS works by lowering the entropic noise floor, enabling more information-rich signal propagation. In this view, the symptoms of parkinsonism may be more a default mode, normally overridden by healthy basal ganglia information. When that information is abolished by parkinsonian pathophysiology, hypokinetic symptoms emerge. PMID:24554786

  16. Deep brain stimulation of the subthalamic nucleus reestablishes neuronal information transmission in the 6-OHDA rat model of parkinsonism.

    PubMed

    Dorval, Alan D; Grill, Warren M

    2014-05-01

    Pathophysiological activity of basal ganglia neurons accompanies the motor symptoms of Parkinson's disease. High-frequency (>90 Hz) deep brain stimulation (DBS) reduces parkinsonian symptoms, but the mechanisms remain unclear. We hypothesize that parkinsonism-associated electrophysiological changes constitute an increase in neuronal firing pattern disorder and a concomitant decrease in information transmission through the ventral basal ganglia, and that effective DBS alleviates symptoms by decreasing neuronal disorder while simultaneously increasing information transfer through the same regions. We tested these hypotheses in the freely behaving, 6-hydroxydopamine-lesioned rat model of hemiparkinsonism. Following the onset of parkinsonism, mean neuronal firing rates were unchanged, despite a significant increase in firing pattern disorder (i.e., neuronal entropy), in both the globus pallidus and substantia nigra pars reticulata. This increase in neuronal entropy was reversed by symptom-alleviating DBS. Whereas increases in signal entropy are most commonly indicative of similar increases in information transmission, directed information through both regions was substantially reduced (>70%) following the onset of parkinsonism. Again, this decrease in information transmission was partially reversed by DBS. Together, these results suggest that the parkinsonian basal ganglia are rife with entropic activity and incapable of functional information transmission. Furthermore, they indicate that symptom-alleviating DBS works by lowering the entropic noise floor, enabling more information-rich signal propagation. In this view, the symptoms of parkinsonism may be more a default mode, normally overridden by healthy basal ganglia information. When that information is abolished by parkinsonian pathophysiology, hypokinetic symptoms emerge. PMID:24554786

  17. A kinetic model of the transient phase in the response of olfactory receptor neurons.

    PubMed

    Getz, W M

    1999-10-01

    A model is presented that predicts the instantaneous spike rate of an olfactory receptor neuron (ORN) in response to the quality and concentration of an odor stimulus. The model accounts for the chemical kinetics of ligand-receptor binding and activation processes, and implicitly the initiation of second messenger cascades that lead to depolarization and/or hyperpolarization of the ORN membrane. Both of these polarizing processes are included in the most general form of the model, as well as a process that restores the voltage to its negative resting state. The spike rate is assumed to be linearly proportional to the level of voltage depolarization above a critical negative voltage level. The model includes the simplifying assumption that activation of bound ligand-receptor complexes by G-proteins and other enabling molecules follows a Monod function that has the ratio of enabling molecules to bound unactivated ligand-receptor complexes as its argument. Parameters are selected that provide an excellent fit of the model to previously published empirical data on the response of cockroach ORNs to pulsed 1-hexanol stimuli. The sensitivity of model output to various model parameters is investigated and changes to parameters are discussed that would improve the ability of ORNs to follow rapidly pulsed stimuli. PMID:10576257

  18. Dopaminergic neuron-specific deletion of p53 gene is neuroprotective in an experimental Parkinson's disease model.

    PubMed

    Qi, Xin; Davis, Brandon; Chiang, Yung-Hsiao; Filichia, Emily; Barnett, Austin; Greig, Nigel H; Hoffer, Barry; Luo, Yu

    2016-09-01

    p53, a stress response gene, is involved in diverse cell death pathways and its activation has been implicated in the pathogenesis of Parkinson's disease (PD). However, whether the neuronal p53 protein plays a direct role in regulating dopaminergic (DA) neuronal cell death is unknown. In this study, in contrast to the global inhibition of p53 function by pharmacological inhibitors and in traditional p53 knock-out (KO) mice, we examined the effect of DA specific p53 gene deletion in DAT-p53KO mice. These DAT-p53KO mice did not exhibit apparent changes in the general structure and neuronal density of DA neurons during late development and in aging. However, in DA-p53KO mice treated with the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), we found that the induction of Bax and p53 up-regulated modulator of apoptosis (PUMA) mRNA and protein levels by MPTP were diminished in both striatum and substantia nigra of these mice. Notably, deletion of the p53 gene in DA neurons significantly reduced dopaminergic neuronal loss in substantia nigra, dopaminergic neuronal terminal loss at striatum and, additionally, decreased motor deficits in mice challenged with MPTP. In contrast, there was no difference in astrogliosis between WT and DAT-p53KO mice in response to MPTP treatment. These findings demonstrate a specific contribution of p53 activation in DA neuronal cell death by MPTP challenge. Our results further support the role of programmed cell death mediated by p53 in this animal model of PD and identify Bax, BAD and PUMA genes as downstream targets of p53 in modulating DA neuronal death in the in vivo MPTP-induced PD model. We deleted p53 gene in dopaminergic neurons in late developmental stages and found that DA specific p53 deletion is protective in acute MPTP animal model possibly through blocking MPTP-induced BAX and PUMA up-regulation. Astrocyte activation measured by GFAP positive cells and GFAP gene up-regulation in the striatum shows no difference

  19. Ablation of sensory neurons in a genetic model of pancreatic ductal adenocarcinoma slows initiation and progression of cancer

    PubMed Central

    Saloman, Jami L.; Albers, Kathryn M.; Li, Dongjun; Hartman, Douglas J.; Crawford, Howard C.; Muha, Emily A.; Rhim, Andrew D.; Davis, Brian M.

    2016-01-01

    Pancreatic ductal adenocarcinoma (PDAC) is characterized by an exuberant inflammatory desmoplastic response. The PDAC microenvironment is complex, containing both pro- and antitumorigenic elements, and remains to be fully characterized. Here, we show that sensory neurons, an under-studied cohort of the pancreas tumor stroma, play a significant role in the initiation and progression of the early stages of PDAC. Using a well-established autochthonous model of PDAC (PKC), we show that inflammation and neuronal damage in the peripheral and central nervous system (CNS) occurs as early as the pancreatic intraepithelial neoplasia (PanIN) 2 stage. Also at the PanIN2 stage, pancreas acinar-derived cells frequently invade along sensory neurons into the spinal cord and migrate caudally to the lower thoracic and upper lumbar regions. Sensory neuron ablation by neonatal capsaicin injection prevented perineural invasion (PNI), astrocyte activation, and neuronal damage, suggesting that sensory neurons convey inflammatory signals from Kras-induced pancreatic neoplasia to the CNS. Neuron ablation in PKC mice also significantly delayed PanIN formation and ultimately prolonged survival compared with vehicle-treated controls (median survival, 7.8 vs. 4.5 mo; P = 0.001). These data establish a reciprocal signaling loop between the pancreas and nervous system, including the CNS, that supports inflammation associated with oncogenic Kras-induced neoplasia. Thus, pancreatic sensory neurons comprise an important stromal cell population that supports the initiation and progression of PDAC and may represent a potential target for prevention in high-risk populations. PMID:26929329

  20. Ablation of sensory neurons in a genetic model of pancreatic ductal adenocarcinoma slows initiation and progression of cancer.

    PubMed

    Saloman, Jami L; Albers, Kathryn M; Li, Dongjun; Hartman, Douglas J; Crawford, Howard C; Muha, Emily A; Rhim, Andrew D; Davis, Brian M

    2016-03-15

    Pancreatic ductal adenocarcinoma (PDAC) is characterized by an exuberant inflammatory desmoplastic response. The PDAC microenvironment is complex, containing both pro- and antitumorigenic elements, and remains to be fully characterized. Here, we show that sensory neurons, an under-studied cohort of the pancreas tumor stroma, play a significant role in the initiation and progression of the early stages of PDAC. Using a well-established autochthonous model of PDAC (PKC), we show that inflammation and neuronal damage in the peripheral and central nervous system (CNS) occurs as early as the pancreatic intraepithelial neoplasia (PanIN) 2 stage. Also at the PanIN2 stage, pancreas acinar-derived cells frequently invade along sensory neurons into the spinal cord and migrate caudally to the lower thoracic and upper lumbar regions. Sensory neuron ablation by neonatal capsaicin injection prevented perineural invasion (PNI), astrocyte activation, and neuronal damage, suggesting that sensory neurons convey inflammatory signals from Kras-induced pancreatic neoplasia to the CNS. Neuron ablation in PKC mice also significantly delayed PanIN formation and ultimately prolonged survival compared with vehicle-treated controls (median survival, 7.8 vs. 4.5 mo; P = 0.001). These data establish a reciprocal signaling loop between the pancreas and nervous system, including the CNS, that supports inflammation associated with oncogenic Kras-induced neoplasia. Thus, pancreatic sensory neurons comprise an important stromal cell population that supports the initiation and progression of PDAC and may represent a potential target for prevention in high-risk populations. PMID:26929329

  1. A codimension-2 bifurcation controlling endogenous bursting activity and pulse-triggered responses of a neuron model.

    PubMed

    Barnett, William H; Cymbalyuk, Gennady S

    2014-01-01

    The dynamics of individual neurons are crucial for producing functional activity in neuronal networks. An open question is how temporal characteristics can be controlled in bursting activity and in transient neuronal responses to synaptic input. Bifurcation theory provides a framework to discover generic mechanisms addressing this question. We present a family of mechanisms organized around a global codimension-2 bifurcation. The cornerstone bifurcation is located at the intersection of the border between bursting and spiking and the border between bursting and silence. These borders correspond to the blue sky catastrophe bifurcation and the saddle-node bifurcation on an invariant circle (SNIC) curves, respectively. The cornerstone bifurcation satisfies the conditions for both the blue sky catastrophe and SNIC. The burst duration and interburst interval increase as the inverse of the square root of the difference between the corresponding bifurcation parameter and its bifurcation value. For a given set of burst duration and interburst interval, one can find the parameter values supporting these temporal characteristics. The cornerstone bifurcation also determines the responses of silent and spiking neurons. In a silent neuron with parameters close to the SNIC, a pulse of current triggers a single burst. In a spiking neuron with parameters close to the blue sky catastrophe, a pulse of current temporarily silences the neuron. These responses are stereotypical: the durations of the transient intervals-the duration of the burst and the duration of latency to spiking-are governed by the inverse-square-root laws. The mechanisms described here could be used to coordinate neuromuscular control in central pattern generators. As proof of principle, we construct small networks that control metachronal-wave motor pattern exhibited in locomotion. This pattern is determined by the phase relations of bursting neurons in a simple central pattern generator modeled by a chain of

  2. Dual sensitivity of inferior colliculus neurons to ITD in the envelopes of high-frequency sounds: experimental and modeling study

    PubMed Central

    Wang, Le; Devore, Sasha; Delgutte, Bertrand

    2013-01-01

    Human listeners are sensitive to interaural time differences (ITDs) in the envelopes of sounds, which can serve as a cue for sound localization. Many high-frequency neurons in the mammalian inferior colliculus (IC) are sensitive to envelope-ITDs of sinusoidally amplitude-modulated (SAM) sounds. Typically, envelope-ITD-sensitive IC neurons exhibit either peak-type sensitivity, discharging maximally at the same delay across frequencies, or trough-type sensitivity, discharging minimally at the same delay across frequencies, consistent with responses observed at the primary site of binaural interaction in the medial and lateral superior olives (MSO and LSO), respectively. However, some high-frequency IC neurons exhibit dual types of envelope-ITD sensitivity in their responses to SAM tones, that is, they exhibit peak-type sensitivity at some modulation frequencies and trough-type sensitivity at other frequencies. Here we show that high-frequency IC neurons in the unanesthetized rabbit can also exhibit dual types of envelope-ITD sensitivity in their responses to SAM noise. Such complex responses to SAM stimuli could be achieved by convergent inputs from MSO and LSO onto single IC neurons. We test this hypothesis by implementing a physiologically explicit, computational model of the binaural pathway. Specifically, we examined envelope-ITD sensitivity of a simple model IC neuron that receives convergent inputs from MSO and LSO model neurons. We show that dual envelope-ITD sensitivity emerges in the IC when convergent MSO and LSO inputs are differentially tuned for modulation frequency. PMID:24155013

  3. Compartmental models of electrotonic structure and synaptic integration in an identified neurone.

    PubMed Central

    Edwards, D H; Mulloney, B

    1984-01-01

    A three-compartment model of the electrotonic structure of an identified motoneurone, the median gastric (m.g.) neurone of the stomatogastric ganglion of the spiny lobster (Panulirus interruptus) was constructed, based on the passive response of the cell to a step of injected current. While its structure is only remotely related to that of the cell, the model is able to predict the passive response of the cell to any wave form of injected current. The shape of the m.g. neurone provided the basis for the development of a multicompartment model of the cell from the simple compartment model. Unlike the three-compartment model, the multicompartment model has a structure that corresponds closely to that of the cell while it retains the ability to predict the passive response of the cell to any wave form of injected current. The multicompartment model was used to analyse the electrotonic structure and synaptic integration of the cell. The axon acts as a current sink, causing steady-state voltage attenuation between the tips of different dendrites and the integrating segment to range between 26 and 89%. Steady-state voltage attenuation in the distal direction is 2% or less. Synaptic inhibition of m.g. by Interneurone 1 was simulated with simultaneously activated conductance-increase synapses located on all dendritic end-compartments of the model. Inhibitory post-synaptic potential (i.p.s.p.) wave forms recorded in the cell soma were duplicated in the soma compartment when the synaptic conductance change in each of the twenty-eight end-compartments was set equal to 5 nS for 8 ms. I.p.s.p. wave forms in dendritic end-compartments were 30% larger than the soma compartment i.p.s.p., while i.p.s.p.s in the integrating segment compartment were intermediate in size. Charge from a 92 mV, 1 ms action potential in the model axon was passively conducted from axonal compartments to the soma compartment of the model, where it reproduced the attenuated, broadened voltage wave forms of

  4. Structural versus dynamical origins of mean-field behavior in a self-organized critical model of neuronal avalanches.

    PubMed

    Moosavi, S Amin; Montakhab, Afshin

    2015-11-01

    Critical dynamics of cortical neurons have been intensively studied over the past decade. Neuronal avalanches provide the main experimental as well as theoretical tools to consider criticality in such systems. Experimental studies show that critical neuronal avalanches show mean-field behavior. There are structural as well as recently proposed [Phys. Rev. E 89, 052139 (2014)] dynamical mechanisms that can lead to mean-field behavior. In this work we consider a simple model of neuronal dynamics based on threshold self-organized critical models with synaptic noise. We investigate the role of high-average connectivity, random long-range connections, as well as synaptic noise in achieving mean-field behavior. We employ finite-size scaling in order to extract critical exponents with good accuracy. We conclude that relevant structural mechanisms responsible for mean-field behavior cannot be justified in realistic models of the cortex. However, strong dynamical noise, which can have realistic justifications, always leads to mean-field behavior regardless of the underlying structure. Our work provides a different (dynamical) origin than the conventionally accepted (structural) mechanisms for mean-field behavior in neuronal avalanches. PMID:26651741

  5. NSC-34 Motor Neuron-Like Cells Are Unsuitable as Experimental Model for Glutamate-Mediated Excitotoxicity.

    PubMed

    Madji Hounoum, Blandine; Vourc'h, Patrick; Felix, Romain; Corcia, Philippe; Patin, Franck; Guéguinou, Maxime; Potier-Cartereau, Marie; Vandier, Christophe; Raoul, Cédric; Andres, Christian R; Mavel, Sylvie; Blasco, Hélène

    2016-01-01

    Glutamate-induced excitotoxicity is a major contributor to motor neuron degeneration in the pathogenesis of amyotrophic lateral sclerosis (ALS). The spinal cord × Neuroblastoma hybrid cell line (NSC-34) is often used as a bona fide cellular model to investigate the physiopathological mechanisms of ALS. However, the physiological response of NSC-34 to glutamate remains insufficiently described. In this study, we evaluated the relevance of differentiated NSC-34 (NSC-34D) as an in vitro model for glutamate excitotoxicity studies. NSC-34D showed morphological and physiological properties of motor neuron-like cells and expressed glutamate receptor subunits GluA1-4, GluN1 and GluN2A/D. Despite these diverse characteristics, no specific effect of glutamate was observed on cultured NSC-34D survival and morphology, in contrast to what has been described in primary culture of motor neurons (MN). Moreover, a small non sustained increase in the concentration of intracellular calcium was observed in NSC-34D after exposure to glutamate compared to primary MN. Our findings, together with the inability to obtain cultures containing only differentiated cells, suggest that the motor neuron-like NSC-34 cell line is not a suitable in vitro model to study glutamate-induced excitotoxicity. We suggest that the use of primary cultures of MN is more suitable than NSC-34 cell line to explore the pathogenesis of glutamate-mediated excitotoxicity at the cellular level in ALS and other motor neuron diseases. PMID:27242431

  6. Conditional Ablation of Orexin/Hypocretin Neurons: A New Mouse Model for the Study of Narcolepsy and Orexin System Function

    PubMed Central

    Tabuchi, Sawako; Tsunematsu, Tomomi; Black, Sarah W.; Tominaga, Makoto; Maruyama, Megumi; Takagi, Kazuyo; Minokoshi, Yasuhiko; Sakurai, Takeshi

    2014-01-01

    The sleep disorder narcolepsy results from loss of hypothalamic orexin/hypocretin neurons. Although narcolepsy onset is usually postpubertal, current mouse models involve loss of either orexin peptides or orexin neurons from birth. To create a model of orexin/hypocretin deficiency with closer fidelity to human narcolepsy, diphtheria toxin A (DTA) was expressed in orexin neurons under control of the Tet-off system. Upon doxycycline removal from the diet of postpubertal orexin-tTA;TetO DTA mice, orexin neurodegeneration was rapid, with 80% cell loss within 7 d, and resulted in disrupted sleep architecture. Cataplexy, the pathognomic symptom of narcolepsy, occurred by 14 d when ∼5% of the orexin neurons remained. Cataplexy frequency increased for at least 11 weeks after doxycycline. Temporary doxycycline removal followed by reintroduction after several days enabled partial lesion of orexin neurons. DTA-induced orexin neurodegeneration caused a body weight increase without a change in food consumption, mimicking metabolic aspects of human narcolepsy. Because the orexin/hypocretin system has been implicated in the control of metabolism and addiction as well as sleep/wake regulation, orexin-tTA; TetO DTA mice are a novel model in which to study these functions, for pharmacological studies of cataplexy, and to study network reorganization as orexin input is lost. PMID:24806676

  7. Structural versus dynamical origins of mean-field behavior in a self-organized critical model of neuronal avalanches

    NASA Astrophysics Data System (ADS)

    Moosavi, S. Amin; Montakhab, Afshin

    2015-11-01

    Critical dynamics of cortical neurons have been intensively studied over the past decade. Neuronal avalanches provide the main experimental as well as theoretical tools to consider criticality in such systems. Experimental studies show that critical neuronal avalanches show mean-field behavior. There are structural as well as recently proposed [Phys. Rev. E 89, 052139 (2014), 10.1103/PhysRevE.89.052139] dynamical mechanisms that can lead to mean-field behavior. In this work we consider a simple model of neuronal dynamics based on threshold self-organized critical models with synaptic noise. We investigate the role of high-average connectivity, random long-range connections, as well as synaptic noise in achieving mean-field behavior. We employ finite-size scaling in order to extract critical exponents with good accuracy. We conclude that relevant structural mechanisms responsible for mean-field behavior cannot be justified in realistic models of the cortex. However, strong dynamical noise, which can have realistic justifications, always leads to mean-field behavior regardless of the underlying structure. Our work provides a different (dynamical) origin than the conventionally accepted (structural) mechanisms for mean-field behavior in neuronal avalanches.

  8. Efficient derivation of cortical glutamatergic neurons from human pluripotent stem cells: a model system to study neurotoxicity in Alzheimer's disease.

    PubMed

    Vazin, Tandis; Ball, K Aurelia; Lu, Hui; Park, Hyungju; Ataeijannati, Yasaman; Head-Gordon, Teresa; Poo, Mu-ming; Schaffer, David V

    2014-02-01

    Alzheimer's disease (AD) is among the most prevalent forms of dementia affecting the aging population, and pharmacological therapies to date have not been successful in preventing disease progression. Future therapeutic efforts may benefit from the development of models that enable basic investigation of early disease pathology. In particular, disease-relevant models based on human pluripotent stem cells (hPSCs) may be promising approaches to assess the impact of neurotoxic agents in AD on specific neuronal populations and thereby facilitate the development of novel interventions to avert early disease mechanisms. We implemented an efficient paradigm to convert hPSCs into enriched populations of cortical glutamatergic neurons emerging from dorsal forebrain neural progenitors, aided by modulating Sonic hedgehog (Shh) signaling. Since AD is generally known to be toxic to glutamatergic circuits, we exposed glutamatergic neurons derived from hESCs to an oligomeric pre-fibrillar forms of Aβ known as "globulomers", which have shown strong correlation with the level of cognitive deficits in AD. Administration of such Aβ oligomers yielded signs of the disease, including cell culture age-dependent binding of Aβ and cell death in the glutamatergic populations. Furthermore, consistent with previous findings in postmortem human AD brain, Aβ-induced toxicity was selective for glutamatergic rather than GABAeric neurons present in our cultures. This in vitro model of cortical glutamatergic neurons thus offers a system for future mechanistic investigation and therapeutic development for AD pathology using human cell types specifically affected by this disease. PMID:24055772

  9. NSC-34 Motor Neuron-Like Cells Are Unsuitable as Experimental Model for Glutamate-Mediated Excitotoxicity

    PubMed Central

    Madji Hounoum, Blandine; Vourc’h, Patrick; Felix, Romain; Corcia, Philippe; Patin, Franck; Guéguinou, Maxime; Potier-Cartereau, Marie; Vandier, Christophe; Raoul, Cédric; Andres, Christian R.; Mavel, Sylvie; Blasco, Hélène

    2016-01-01

    Glutamate-induced excitotoxicity is a major contributor to motor neuron degeneration in the pathogenesis of amyotrophic lateral sclerosis (ALS). The spinal cord × Neuroblastoma hybrid cell line (NSC-34) is often used as a bona fide cellular model to investigate the physiopathological mechanisms of ALS. However, the physiological response of NSC-34 to glutamate remains insufficiently described. In this study, we evaluated the relevance of differentiated NSC-34 (NSC-34D) as an in vitro model for glutamate excitotoxicity studies. NSC-34D showed morphological and physiological properties of motor neuron-like cells and expressed glutamate receptor subunits GluA1–4, GluN1 and GluN2A/D. Despite these diverse characteristics, no specific effect of glutamate was observed on cultured NSC-34D survival and morphology, in contrast to what has been described in primary culture of motor neurons (MN). Moreover, a small non sustained increase in the concentration of intracellular calcium was observed in NSC-34D after exposure to glutamate compared to primary MN. Our findings, together with the inability to obtain cultures containing only differentiated cells, suggest that the motor neuron-like NSC-34 cell line is not a suitable in vitro model to study glutamate-induced excitotoxicity. We suggest that the use of primary cultures of MN is more suitable than NSC-34 cell line to explore the pathogenesis of glutamate-mediated excitotoxicity at the cellular level in ALS and other motor neuron diseases. PMID:27242431

  10. Spike propagation through the dorsal root ganglia in an unmyelinated sensory neuron: a modeling study.

    PubMed

    Sundt, Danielle; Gamper, Nikita; Jaffe, David B

    2015-12-01

    Unmyelinated C-fibers are a major type of sensory neurons conveying pain information. Action potential conduction is regulated by the bifurcation (T-junction) of sensory neuron axons within the dorsal root ganglia (DRG). Understanding how C-fiber signaling is influenced by the morphology of the T-junction and the local expression of ion channels is important for understanding pain signaling. In this study we used biophysical computer modeling to investigate the influence of axon morphology within the DRG and various membrane conductances on the reliability of spike propagation. As expected, calculated input impedance and the amplitude of propagating action potentials were both lowest at the T-junction. Propagation reliability for single spikes was highly sensitive to the diameter of the stem axon and the density of voltage-gated Na(+) channels. A model containing only fast voltage-gated Na(+) and delayed-rectifier K(+) channels conducted trains of spikes up to frequencies of 110 Hz. The addition of slowly activating KCNQ channels (i.e., KV7 or M-channels) to the model reduced the following frequency to 30 Hz. Hyperpolarization produced by addition of a much slower conductance, such as a Ca(2+)-dependent K(+) current, was needed to reduce the following frequency to 6 Hz. Attenuation of driving force due to ion accumulation or hyperpolarization produced by a Na(+)-K(+) pump had no effect on following frequency but could influence the reliability of spike propagation mutually with the voltage shift generated by a Ca(2+)-dependent K(+) current. These simulations suggest how specific ion channels within the DRG may contribute toward therapeutic treatments for chronic pain. PMID:26334005

  11. Spike propagation through the dorsal root ganglia in an unmyelinated sensory neuron: a modeling study

    PubMed Central

    Sundt, Danielle; Gamper, Nikita

    2015-01-01

    Unmyelinated C-fibers are a major type of sensory neurons conveying pain information. Action potential conduction is regulated by the bifurcation (T-junction) of sensory neuron axons within the dorsal root ganglia (DRG). Understanding how C-fiber signaling is influenced by the morphology of the T-junction and the local expression of ion channels is important for understanding pain signaling. In this study we used biophysical computer modeling to investigate the influence of axon morphology within the DRG and various membrane conductances on the reliability of spike propagation. As expected, calculated input impedance and the amplitude of propagating action potentials were both lowest at the T-junction. Propagation reliability for single spikes was highly sensitive to the diameter of the stem axon and the density of voltage-gated Na+ channels. A model containing only fast voltage-gated Na+ and delayed-rectifier K+ channels conducted trains of spikes up to frequencies of 110 Hz. The addition of slowly activating KCNQ channels (i.e., KV7 or M-channels) to the model reduced the following frequency to 30 Hz. Hyperpolarization produced by addition of a much slower conductance, such as a Ca2+-dependent K+ current, was needed to reduce the following frequency to 6 Hz. Attenuation of driving force due to ion accumulation or hyperpolarization produced by a Na+-K+ pump had no effect on following frequency but could influence the reliability of spike propagation mutually with the voltage shift generated by a Ca2+-dependent K+ current. These simulations suggest how specific ion channels within the DRG may contribute toward therapeutic treatments for chronic pain. PMID:26334005

  12. Intracellular calcium dynamics permit a Purkinje neuron model to perform toggle and gain computations upon its inputs

    PubMed Central

    Forrest, Michael D.

    2014-01-01

    Without synaptic input, Purkinje neurons can spontaneously fire in a repeating trimodal pattern that consists of tonic spiking, bursting and quiescence. Climbing fiber input (CF) switches Purkinje neurons out of the trimodal firing pattern and toggles them between a tonic firing and a quiescent state, while setting the gain of their response to Parallel Fiber (PF) input. The basis to this transition is unclear. We investigate it using a biophysical Purkinje cell model under conditions of CF and PF input. The model can replicate these toggle and gain functions, dependent upon a novel account of intracellular calcium dynamics that we hypothesize to be applicable in real Purkinje cells. PMID:25191262

  13. Membrane resistivity estimated for the Purkinje neuron by means of a passive computer model.

    PubMed

    Shelton, D P

    1985-01-01

    A multicompartment passive electrotonic computer model is constructed for the cerebellar Purkinje cell of the guinea-pig. The model has 1089 coupled compartments to accurately represent the morphology of the Purkinje cell. In order that the calculated behavior of the model fit the published electrophysiological observations of somatic and dendritic input conductance, the neural membrane resistivity must be spatially non-uniform. The passive electrical parameter values for which the model best fits the observations of input conductances, pulse attenuation and current-clamp voltage transients are rm,dend = 45,740 omega cm2, rm,soma = 760 omega cm2, ri = 225 omega cm and cm = 1.16 microF/cm2 (the membrane and cytoplasm specific resistivities and membrane specific capacitance, respectively). The model with these parameter values is electrically compact, with electrotonic length X = 0.33 and dendritic dominance ratio p = 0.44. Analysis of the calculated voltage transient of the multicompartment model by the methods of equivalent-cylinder cable theory is shown to result in very different and unreliable conclusions. The significance for neuronal function of the estimated electrical parameter values is discussed. The possible effect of active conductances on these conclusions is assessed. PMID:2579350

  14. A normalized contrast-encoding model exhibits bright/dark asymmetries similar to early visual neurons.

    PubMed

    Cooper, Emily A

    2016-04-01

    Biological sensory systems share a number of organizing principles. One such principle is the formation of parallel streams. In the visual system, information about bright and dark features is largely conveyed via two separate streams: theONandOFFpathways. While brightness and darkness can be considered symmetric and opposite forms of visual contrast, the response properties of cells in theONandOFFpathways are decidedly asymmetric. Here, we ask whether a simple contrast-encoding model predicts asymmetries for brights and darks that are similar to the asymmetries found in theONandOFFpathways. Importantly, this model does not include any explicit differences in how the visual system represents brights and darks, but it does include a common normalization mechanism. The phenomena captured by the model include (1) nonlinear contrast response functions, (2) greater nonlinearities in the responses to darks, and (3) larger responses to dark contrasts. We report a direct, quantitative comparison between these model predictions and previously published electrophysiological measurements from the retina and thalamus (guinea pig and cat, respectively). This work suggests that the simple computation of visual contrast may account for a range of early visual processing nonlinearities. Assessing explicit models of sensory representations is essential for understanding which features of neuronal activity these models can and cannot predict, and for investigating how early computations may reverberate through the sensory pathways. PMID:27044852

  15. Macro- and micro-chaotic structures in the Hindmarsh-Rose model of bursting neurons

    SciTech Connect

    Barrio, Roberto Serrano, Sergio; Angeles Martínez, M.; Shilnikov, Andrey

    2014-06-01

    We study a plethora of chaotic phenomena in the Hindmarsh-Rose neuron model with the use of several computational techniques including the bifurcation parameter continuation, spike-quantification, and evaluation of Lyapunov exponents in bi-parameter diagrams. Such an aggregated approach allows for detecting regions of simple and chaotic dynamics, and demarcating borderlines—exact bifurcation curves. We demonstrate how the organizing centers—points corresponding to codimension-two homoclinic bifurcations—along with fold and period-doubling bifurcation curves structure the biparametric plane, thus forming macro-chaotic regions of onion bulb shapes and revealing spike-adding cascades that generate micro-chaotic structures due to the hysteresis.

  16. Finite volume and asymptotic methods for stochastic neuron models with correlated inputs.

    PubMed

    Rosenbaum, Robert; Marpeau, Fabien; Ma, Jianfu; Barua, Aditya; Josić, Krešimir

    2012-07-01

    We consider a pair of stochastic integrate and fire neurons receiving correlated stochastic inputs. The evolution of this system can be described by the corresponding Fokker-Planck equation with non-trivial boundary conditions resulting from the refractory period and firing threshold. We propose a finite volume method that is orders of magnitude faster than the Monte Carlo methods traditionally used to model such systems. The resulting numerical approximations are proved to be accurate, nonnegative and integrate to 1. We also approximate the transient evolution of the system using an Ornstein-Uhlenbeck process, and use the result to examine the properties of the joint output of cell pairs. The results suggests that the joint output of a cell pair is most sensitive to changes in input variance, and less sensitive to changes in input mean and correlation. PMID:21717104

  17. Modeling the electrical behavior of anatomically complex neurons using a network analysis program: excitable membrane.

    PubMed

    Bunow, B; Segev, I; Fleshman, J W

    1985-01-01

    We present methods for using the general-purpose network analysis program, SPICE, to construct computer models of excitable membrane displaying Hodgkin-Huxley-like kinetics. The four non-linear partial differential equations of Hodgkin and Huxley (H-H; 1952) are implemented using electrical circuit elements. The H-H rate constants, alpha and beta, are approximated by polynomial functions rather than exponential functions, since the former are handled more efficiently by SPICE. The process of developing code to implement the H-H sodium conductance is described in detail. The Appendix contains a complete listing of the code required to simulate an H-H action potential. The behavior of models so constructed is validated by comparison with the space-clamped and propagating action potentials of Hodgkin and Huxley. SPICE models of multiply branched axons were tested and found to behave as predicted by previous numerical solutions for propagation in inhomogeneous axons. New results are presented for two cases. First, a detailed, anatomically based model is constructed of group Ia input to an alpha-motoneuron with an excitable soma, a myelinated axon and passive dendrites. Second, we simulate interactions among clusters of mixed excitable and passive dendritic spines on an idealized neuron. The methods presented in this paper and its companion (Segev et al. 1985) should permit neurobiologists to construct and explore models which simulate much more closely the real morphological and physiological characteristics of nerve cells. PMID:3841014

  18. FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model.

    PubMed

    Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid

    2014-01-01

    A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well. PMID:25484854

  19. Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons.

    PubMed

    Glaze, Tera A; Lewis, Scott; Bahar, Sonya

    2016-08-01

    Chimera states occur when identically coupled groups of nonlinear oscillators exhibit radically different dynamics, with one group exhibiting synchronized oscillations and the other desynchronized behavior. This dynamical phenomenon has recently been studied in computational models and demonstrated experimentally in mechanical, optical, and chemical systems. The theoretical basis of these states is currently under active investigation. Chimera behavior is of particular relevance in the context of neural synchronization, given the phenomenon of unihemispheric sleep and the recent observation of asymmetric sleep in human patients with sleep apnea. The similarity of neural chimera states to neural "bump" states, which have been suggested as a model for working memory and visual orientation tuning in the cortex, adds to their interest as objects of study. Chimera states have been demonstrated in the FitzHugh-Nagumo model of excitable cells and in the Hindmarsh-Rose neural model. Here, we demonstrate chimera states and chimera-like behaviors in a Hodgkin-Huxley-type model of thermally sensitive neurons both in a system with Abrams-Strogatz (mean field) coupling and in a system with Kuramoto (distance-dependent) coupling. We map the regions of parameter space for which chimera behavior occurs in each of the two coupling schemes. PMID:27586615

  20. FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model

    PubMed Central

    Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid

    2014-01-01

    A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well. PMID:25484854

  1. Analog low-power hardware implementation of a Laguerre-Volterra model of intracellular subthreshold neuronal activity.

    PubMed

    Ghaderi, Viviane S; Roach, Shane; Song, Dong; Marmarelis, Vasilis Z; Choma, John; Berger, Theodore W

    2012-01-01

    The right level of abstraction for a model mimicking a neural function is often difficult to determine. There are trade-offs between capturing biological complexities on one hand and the scalability and efficiency of the model on the other. In this work, we describe a nonlinear Laguerre-Volterra model of the synaptic temporal integration of input spikes to postsynaptic potentials. This model is then efficiently implemented using analog subthreshold circuits and can serve as a foundation for future large-scale hardware systems that can emulate multi-input multi-output (MIMO) spike transformations in populations of neurons. The normalized mean square error in estimating real data using the circuit implementation of this model is less than 15%. The model components are modular and its parameters are adjustable for modeling temporal integration by neurons in other brain regions. The total power consumption of this nonlinear Laguerre-Volterra system is less than 5nW. PMID:23366005

  2. Implementation of an integrated op-amp based chaotic neuron model and observation of its chaotic dynamics

    SciTech Connect

    Jung, Jinwoo; Lee, Jewon; Song, Hanjung

    2011-03-15

    This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performed simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-{mu}m single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with {+-}2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.

  3. Hippocampal Neuron Loss Exceeds Amyloid Plaque Load in a Transgenic Mouse Model of Alzheimer’s Disease

    PubMed Central

    Schmitz, Christoph; Rutten, Bart P. F.; Pielen, Andrea; Schäfer, Stephanie; Wirths, Oliver; Tremp, Günter; Czech, Christian; Blanchard, Veronique; Multhaup, Gerd; Rezaie, Payam; Korr, Hubert; Steinbusch, Harry W. M.; Pradier, Laurent; Bayer, Thomas A.

    2004-01-01

    According to the “amyloid hypothesis of Alzheimer’s disease,” β-amyloid is the primary driving force in Alzheimer’s disease pathogenesis. Despite the development of many transgenic mouse lines developing abundant β-amyloid-containing plaques in the brain, the actual link between amyloid plaques and neuron loss has not been clearly established, as reports on neuron loss in these models have remained controversial. We investigated transgenic mice expressing human mutant amyloid precursor protein APP751 (KM670/671NL and V717I) and human mutant presenilin-1 (PS-1 M146L). Stereologic and image analyses revealed substantial age-related neuron loss in the hippocampal pyramidal cell layer of APP/PS-1 double-transgenic mice. The loss of neurons was observed at sites of Aβ aggregation and surrounding astrocytes but, most importantly, was also clearly observed in areas of the parenchyma distant from plaques. These findings point to the potential involvement of more than one mechanism in hippocampal neuron loss in this APP/PS-1 double-transgenic mouse model of Alzheimer’s disease. PMID:15039236

  4. A novel mouse model of pediatric cardiac arrest and cardiopulmonary resuscitation reveals age-dependent neuronal sensitivities to ischemic injury

    PubMed Central

    Deng, G; Yonchek, JC; Quillinan, N; Strnad, FA; Exo, J; Herson, PS; Traystman, RJ

    2014-01-01

    Background Pediatric sudden cardiac arrest (CA) is an unfortunate and devastating condition, often leading to poor neurologic outcomes. However, little experimental data on the pathophysiology of pediatric CA is currently available due to the scarcity of animal models. New Method We developed a novel experimental model of pediatric cardiac arrest and cardiopulmonary resuscitation (CA/CPR) using postnatal day 20–25 mice. Adult (8–12 weeks) and pediatric (P20–25) mice were subjected to 6 min CA/CPR. Hippocampal CA1 and striatal neuronal injury were quantified 3 days after resuscitation by hematoxylin and eosin (H&E) and Fluoro-Jade B staining, respectively. Results Pediatric mice exhibited less neuronal injury in both CA1 hippocampal and striatal neurons compared to adult mice. Increasing ischemia time to 8 min CA/CPR resulted in an increase in hippocampal injury in pediatric mice, resulting in similar damage in adult and pediatric brains. In contrast, striatal injury in the pediatric brain following 6 or 8 min CA/CPR remained extremely low. As observed in adult mice, cardiac arrest causes delayed neuronal death in pediatric mice, with hippocampal CA1 neuronal damage maturing at 72 hours after insult. Finally, mild therapeutic hypothermia reduced hippocampal CA1 neuronal injury after pediatric CA/CPR. Comparison with Existing Method This is the first report of a cardiac arrest and CPR model of global cerebral ischemia in mice Conclusions Therefore, the mouse pediatric CA/CPR model we developed is unique and will provide an important new tool to the research community for the study of pediatric brain injury. PMID:24192226

  5. Foundational dendritic processing that is independent of the cell type-specific structure in model primary neurons.

    PubMed

    Kim, Hojeong; Heckman, C J

    2015-11-16

    It has long been known that primary neurons in the brain and spinal cord exhibit very distinctive dendritic structures. However, it remains unclear whether dendritic processing for signal propagation and channel activation over dendrites is a function of the cell type-specific dendritic structure. By applying an extended analysis of signal attenuation for the physiological distributions of synaptic inputs and active channels on dendritic branches, we first demonstrate that regardless of their specific structure, all anatomically reconstructed models of primary neurons display a similar pattern of directional signal attenuation and locational channel activation over their dendrites. Then, using a novel modeling approach that allows direct comparison of the anatomically reconstructed primary neurons with their reduced models that exclusively retain anatomical dendritic signaling without being associated with structural specificity, we show that the reduced model can accurately predict dendritic excitability of the anatomical model in both passive and active mode. These results indicate that the directional signaling, locational excitability and their relationship are foundational features of dendritic processing that are independent of the cell type-specific structure across primary neurons. PMID:26463670

  6. Vestibular Neuronitis

    MedlinePlus

    ... Prevent Painful Swimmer's Ear Additional Content Medical News Vestibular Neuronitis By Lawrence R. Lustig, MD NOTE: This ... Drugs Herpes Zoster Oticus Meniere Disease Purulent Labyrinthitis Vestibular Neuronitis Vestibular neuronitis is a disorder characterized by ...

  7. Existence and stability of limit cycles in a macroscopic neuronal population model

    NASA Astrophysics Data System (ADS)

    Rodrigues, Serafim; Gonçalves, Jorge; Terry, John R.

    2007-09-01

    We present rigorous results concerning the existence and stability of limit cycles in a macroscopic model of neuronal activity. The specific model we consider is developed from the Ki set methodology, popularized by Walter Freeman. In particular we focus on a specific reduction of the KII sets, denoted RKII sets. We analyse the unfolding of supercritical Hopf bifurcations via consideration of the normal forms and centre manifold reductions. Subsequently we analyse the global stability of limit cycles on a region of parameter space and this is achieved by applying a new methodology termed Global Analysis of Piecewise Linear Systems. The analysis presented may also be used to consider coupled systems of this type. A number of macroscopic mean-field approaches to modelling human EEG may be considered as coupled RKII networks. Hence developing a theoretical understanding of the onset of oscillations in models of this type has important implications in clinical neuroscience, as limit cycle oscillations have been demonstrated to be critical in the onset of certain types of epilepsy.

  8. Enhanced GABAergic synaptic transmission at VLPAG neurons and potent modulation by oxycodone in a bone cancer pain model

    PubMed Central

    Takasu, Keiko; Ogawa, Koichi; Nakamura, Atsushi; Kanbara, Tomoe; Ono, Hiroko; Tomii, Takako; Morioka, Yasuhide; Hasegawa, Minoru; Shibasaki, Masahiro; Mori, Tomohisa; Suzuki, Tsutomu; Sakaguchi, Gaku

    2015-01-01

    Background and Purpose We demonstrated previously that oxycodone has potent antinociceptive effects at supraspinal sites. In this study, we investigated changes in neuronal function and antinociceptive mechanisms of oxycodone at ventrolateral periaqueductal gray (VLPAG) neurons, which are a major site of opioid action, in a femur bone cancer (FBC) model with bone cancer-related pain. Experimental Approach We characterized the supraspinal antinociceptive profiles of oxycodone and morphine on mechanical hypersensitivity in the FBC model. Based on the disinhibition mechanism underlying supraspinal opioid antinociception, the effects of oxycodone and morphine on GABAA receptor-mediated inhibitory postsynaptic currents (IPSCs) in VLPAG neurons were evaluated in slices from the FBC model. Key Results The supraspinal antinociceptive effects of oxycodone, but not morphine, were abolished by blocking G protein-gated inwardly rectifying potassium1 (Kir3.1) channels. In slices from the FBC model, GABAergic synaptic transmission at VLPAG neurons was enhanced, as indicated by a leftward shift of the input–output relationship curve of evoked IPSCs, the increased paired-pulse facilitation and the enhancement of miniature IPSC frequency. Following treatment with oxycodone and morphine, IPSCs were reduced in the FBC model, and the inhibition of presynaptic GABA release by oxycodone, but not morphine was enhanced and dependent on Kir3.1 channels. Conclusion and Implications Our results demonstrate that Kir3.1 channels are important for supraspinal antinociception and presynaptic GABA release inhibition by oxycodone in the FBC model. Enhanced GABAergic synaptic transmission at VLPAG neurons in the FBC model is an important site of supraspinal antinociception by oxycodone via Kir3.1 channel activation. PMID:25521524

  9. A working memory model for serial order that stores information in the intrinsic excitability properties of neurons.

    PubMed

    Conde-Sousa, Eduardo; Aguiar, Paulo

    2013-10-01

    Models for temporary information storage in neuronal populations are dominated by mechanisms directly dependent on synaptic plasticity. There are nevertheless other mechanisms available that are well suited for creating short-term memories. Here we present a model for working memory which relies on the modulation of the intrinsic excitability properties of neurons, instead of synaptic plasticity, to retain novel information for periods of seconds to minutes. We show that it is possible to effectively use this mechanism to store the serial o