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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. Enhanced Neurite Outgrowth of Human Model (NT2) Neurons by Small-Molecule Inhibitors of Rho/ROCK Signaling

    PubMed Central

    Roloff, Frank; Scheiblich, Hannah; Dewitz, Carola; Dempewolf, Silke; Stern, Michael; Bicker, Gerd

    2015-01-01

    Axonal injury in the adult human central nervous system often results in loss of sensation and motor functions. Promoting regeneration of severed axons requires the inactivation of growth inhibitory influences from the tissue environment and stimulation of the neuron intrinsic growth potential. Especially glial cell derived factors, such as chondroitin sulfate proteoglycans, Nogo-A, myelin-associated glycoprotein, and myelin in general, prevent axon regeneration. Most of the glial growth inhibiting factors converge onto the Rho/ROCK signaling pathway in neurons. Although conditions in the injured nervous system are clearly different from those during neurite outgrowth in vitro, here we use a chemical approach to manipulate Rho/ROCK signalling with small-molecule agents to encourage neurite outgrowth in cell culture. The development of therapeutic treatments requires drug testing not only on neurons of experimental animals, but also on human neurons. Using human NT2 model neurons, we demonstrate that the pain reliever Ibuprofen decreases RhoA (Ras homolog gene family, member A GTPase) activation and promotes neurite growth. Inhibition of the downstream effector Rho kinase by the drug Y-27632 results in a strong increase in neurite outgrowth. Conversely, activation of the Rho pathway by lysophosphatidic acid results in growth cone collapse and eventually to neurite retraction. Finally, we show that blocking of Rho kinase, but not RhoA results in an increase in neurons bearing neurites. Due to its anti-inflammatory and neurite growth promoting action, the use of a pharmacological treatment of damaged neural tissue with Ibuprofen should be explored. PMID:25714396

  3. 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

  4. Highly efficient generation of glutamatergic/cholinergic NT2-derived postmitotic human neurons by short-term treatment with the nucleoside analogue cytosine β-D-arabinofuranoside.

    PubMed

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

    2016-03-01

    The human NTERA2/D1 (NT2) cells generate postmitotic neurons (NT2N cells) upon retinoic acid (RA) treatment and are functionally integrated in the host tissue following grafting into the rodent and human brain, thus representing a promising source for neuronal replacement therapy. Yet the major limitations of this model are the lengthy differentiation procedure and its low efficiency, although recent studies suggest that the differentiation process can be shortened to less than 1 week using nucleoside analogues. To explore whether short-term exposure of NT2 cells to the nucleoside analogue cytosine β-d-arabinofuranoside (AraC) could be a suitable method to efficiently generate mature neurons, we conducted a neurochemical and morphometric characterization of AraC-differentiated NT2N (AraC/NT2N) neurons and improved the differentiation efficiency by modifying the cell culture schedule. Moreover, we analyzed the neurotransmitter phenotypes of AraC/NT2N neurons. Cultures obtained by treatment with AraC were highly enriched in postmitotic neurons and essentially composed of dual glutamatergic/cholinergic neurons, which contrasts with the preferential GABAergic phenotype that we found after RA differentiation. Taken together, our results further reinforce the notion NT2 cells are a versatile source of neuronal phenotypes and provide a new encouraging platform for studying mechanisms of neuronal differentiation and for exploring neuronal replacement strategies. PMID:26985738

  5. Differentiation-specific effects of LHON mutations introduced into neuronal NT2 cells.

    PubMed

    Wong, Alice; Cavelier, Lucia; Collins-Schramm, Heather E; Seldin, Michael F; McGrogan, Michael; Savontaus, Marja-Liisa; Cortopassi, Gino A

    2002-02-15

    Inheritance of one of three primary mutations at positions 11778, 3460 or 14484 of the mitochondrial genome in subunits of Complex I causes Leber's Hereditary Optic Neuropathy (LHON), a specific degeneration of the optic nerve, resulting in bilateral blindness. It has been unclear why inheritance of a systemic mitochondrial mutation would result in a specific neurodegeneration. To address the neuron-specific degenerative phenotype of the LHON genotype, we have created cybrids using a neuronal precursor cell line, Ntera 2/D1 (NT2), containing mitochondria from patient lymphoblasts bearing the most common LHON mutation (11778) and the most severe LHON mutation (3460). The undifferentiated LHON-NT2 mutant cells were not significantly different from the parental cell control in terms of mtDNA/nDNA ratio, mitochondrial membrane potential, reactive oxygen species (ROS) production or the ability to reduce Alamar Blue. Differentiation of NT2s resulted in a neuronal morphology and neuron-specific pattern of gene expression, and a 3-fold reduction in mtDNA/nDNA ratio in both mutant and control cells; however, the differentiation protocol yielded significantly less LHON cells than controls, by 30%, indicating either a decreased proliferative potential or increased cell death of the LHON-NT2 cells. Differentiation of the cells to the neuronal form also resulted in significant increases in ROS production in the LHON-NT2 neurons versus controls, which is abolished by rotenone, a specific inhibitor of Complex I. We infer that the LHON genotype requires a differentiated neuronal environment in order to induce increased mitochondrial ROS, which may be the cause of the reduced NT2 yield; and suggest that the LHON degenerative phenotype may be the result of an increase in mitochondrial superoxide which is caused by the LHON mutations, possibly mediated through neuron-specific alterations in Complex I structure.

  6. 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

  7. 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

  8. A not cytotoxic nickel concentration alters the expression of neuronal differentiation markers in NT2 cells.

    PubMed

    Ceci, Claudia; Barbaccia, Maria Luisa; Pistritto, Giuseppa

    2015-03-01

    Nickel, a known occupational/environmental hazard, may cross the placenta and reach appreciable concentrations in various fetal organs, including the brain. The aim of this study was to investigate whether nickel interferes with the process of neuronal differentiation. Following a 4 week treatment with retinoic acid (10μM), the human teratocarcinoma-derived NTera2/D1 cell line (NT2 cells) terminally differentiate into neurons which recapitulate many features of human fetal neurons. The continuous exposure of the differentiating NT2 cells to a not cytotoxic nickel concentration (10μM) increased the expression of specific neuronal differentiation markers such as neural cell adhesion molecule (NCAM) and microtubule associated protein 2 (MAP2). Furthermore, nickel exposure increased the expression of hypoxia-inducible-factor-1α (HIF-1α) and induced the activation of the AKT/PKB kinase pathway, as shown by the increase of P(Ser-9)-GSK-3β, the inactive form of glycogen synthase kinase-3β (GSK-3β). Intriguingly, by the end of the fourth week the expression of tyrosine hydroxylase (TH) protein, a marker of dopaminergic neurons, was lower in nickel-treated than in control cultures. Thus, likely by partially mimicking hypoxic conditions, a not-cytotoxic nickel concentration appears to alter the process of neuronal differentiation and hinder the expression of the dopaminergic neuronal phenotype. Taken together, these results suggest that nickel, by altering normal brain development, may increase susceptibility to neuro-psychopathology later in life.

  9. 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

  10. ER-mediated stress induces mitochondrial-dependent caspases activation in NT2 neuron-like cells.

    PubMed

    Arduino, Daniela M; Esteves, A Raquel; Domingues, A Filipa; Pereira, Claudia M F; Cardoso, Sandra M; Oliveira, Catarina R

    2009-11-30

    Recent studies have revealed that endoplasmic reticulum (ER) disturbance is involved in the pathophysiology of neurodegenerative disorders, contributing to the activation of the ER stress-mediated apoptotic pathway. Therefore, we investigated here the molecular mechanisms underlying the ER-mitochondria axis, focusing on calcium as a potential mediator of cell death signals. Using NT2 cells treated with brefeldin A or tunicamycin, we observed that ER stress induces changes in the mitochondrial function, impairing mitochondrial membrane potential and distressing mitochondrial respiratory chain complex Moreover, stress stimuli at ER level evoked calcium fluxes between ER and mitochondria. Under these conditions, ER stress activated the unfolded protein response by an overexpression of GRP78, and also caspase-4 and-2, both involved upstream of caspase-9. Our findings show that ER and mitochondria interconnection plays a prominent role in the induction of neuronal cell death under particular stress circumstances.

  11. 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.

  12. 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.

  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. Effects of Lithium and Valproic Acid on Gene Expression and Phenotypic Markers in an NT2 Neurosphere Model of Neural Development

    PubMed Central

    Hill, Eric J.; Nagel, David A.; O’Neil, John D.; Torr, Elizabeth; Woehrling, Elizabeth K.; Devitt, Andrew; Coleman, Michael D.

    2013-01-01

    Mood stabilising drugs such as lithium (LiCl) and valproic acid (VPA) are the first line agents for treating conditions such as Bipolar disorder and Epilepsy. However, these drugs have potential developmental effects that are not fully understood. This study explores the use of a simple human neurosphere-based in vitro model to characterise the pharmacological and toxicological effects of LiCl and VPA using gene expression changes linked to phenotypic alterations in cells. Treatment with VPA and LiCl resulted in the differential expression of 331 and 164 genes respectively. In the subset of VPA targeted genes, 114 were downregulated whilst 217 genes were upregulated. In the subset of LiCl targeted genes, 73 were downregulated and 91 were upregulated. Gene ontology (GO) term enrichment analysis was used to highlight the most relevant GO terms associated with a given gene list following toxin exposure. In addition, in order to phenotypically anchor the gene expression data, changes in the heterogeneity of cell subtype populations and cell cycle phase were monitored using flow cytometry. Whilst LiCl exposure did not significantly alter the proportion of cells expressing markers for stem cells/undifferentiated cells (Oct4, SSEA4), neurons (Neurofilament M), astrocytes (GFAP) or cell cycle phase, the drug caused a 1.4-fold increase in total cell number. In contrast, exposure to VPA resulted in significant upregulation of Oct4, SSEA, Neurofilament M and GFAP with significant decreases in both G2/M phase cells and cell number. This neurosphere model might provide the basis of a human-based cellular approach for the regulatory exploration of developmental impact of potential toxic chemicals. PMID:23527032

  15. 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

  16. 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.

  17. Dataset of differentially expressed genes from SOX9 over-expressing NT2/D1 cells.

    PubMed

    Ludbrook, Louisa; Alankarage, Dimuthu; Bagheri-Fam, Stefan; Harley, Vincent

    2016-12-01

    The data presents the genes that are differentially up-regulated or down-regulated in response to SOX9 in a human Sertoli-like cell line, NT2/D1. The dataset includes genes that may be implicated in gonad development and are further explored in our associated article, "SOX9 Regulates Expression of the Male Fertility Gene Ets Variant Factor 5 (ETV5) during Mammalian Sex Development" (D. lankarage, R. Lavery, T. Svingen, S. Kelly, L.M. Ludbrook, S. Bagheri-Fam, et al., 2016) [1]. The necessity of SOX9 for male sex development is evident in instances where SOX9 is lost, as in 46, XY DSD where patients are sex reversed or in mouse knock-out models, where mice lacking Sox9 are sex reversed. Despite the crucial nature of this transcriptional activator, downstream target genes of SOX9 remain largely undiscovered. Here, we have utilized NT2/D1 cells to transiently over-express SOX9 and performed microarray analysis of the RNA. Microarray data are available in the ArrayExpress database (www.ebi.ac.uk/arrayexpress) under accession number E-MTAB-3378. PMID:27656672

  18. 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.

  19. Neuronal models of cognitive functions.

    PubMed

    Changeux, J P; Dehaene, S

    1989-11-01

    Understanding the neural bases of cognition has become a scientifically tractable problem, and neurally plausible models are proposed to establish a causal link between biological structure and cognitive function. To this end, levels of organization have to be defined within the functional architecture of neuronal systems. Transitions from any one of these interacting levels to the next are viewed in an evolutionary perspective. They are assumed to involve: (1) the production of multiple transient variations and (2) the selection of some of them by higher levels via the interaction with the outside world. The time-scale of these "evolutions" is expected to differ from one level to the other. In the course of development and in the adult this internal evolution is epigenetic and does not require alteration of the structure of the genome. A selective stabilization (and elimination) of synaptic connections by spontaneous and/or evoked activity in developing neuronal networks is postulated to contribute to the shaping of the adult connectivity within an envelope of genetically encoded forms. At a higher level, models of mental representations, as states of activity of defined populations of neurons, are discussed in terms of statistical physics, and their storage is viewed as a process of selection among variable and transient pre-representations. Theoretical models illustrate that cognitive functions such as short-term memory and handling of temporal sequences may be constrained by "microscopic" physical parameters. Finally, speculations are offered about plausible neuronal models and selectionist implementations of intentions. PMID:2691185

  20. Modeling Neuronal Current MRI Signal with Human Neuron

    PubMed Central

    Luo, Qingfei; Jiang, Xia; Chen, Bin; Zhu, Yi; Gao, Jia-Hong

    2010-01-01

    Up to date, no consensus has been achieved regarding the possibility of detecting neuronal currents by MRI (ncMRI) in human brain. To evaluate the detectability of ncMRI, an effective way is to simulate ncMRI signal with the realistic neuronal geometry and electrophysiological processes. Unfortunately, previous realistic ncMRI models are based on rat and monkey neurons. The species difference in neuronal morphology and physiology would prevent these models from simulating the ncMRI signal accurately in human subjects. The aim of the present study is to bridge this gap by establishing a realistic ncMRI model specifically for human cerebral cortex. In this model, the ncMRI signal was simulated using anatomically reconstructed human pyramidal neurons and their biophysical properties. The modeling results showed that the amplitude of ncMRI signal significantly depends on the density of synchronously firing neurons and imaging conditions such as position of imaging voxel, direction of main magnetic field (B0) relative to the cortical surface and echo time. The results indicated that physiologically-evoked ncMRI signal is too weak to be detected (magnitude/phase change ≤ -1.4×10−6/0.02°), but the phase signal induced by spontaneous activity may reach a detectable level (up to 0.2°) in favorable conditions. PMID:21254209

  1. 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.

  2. 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

  3. Neuron model-free PID control

    NASA Astrophysics Data System (ADS)

    Wang, Ning; Zhang, Li; Wang, Shuqing

    2001-09-01

    Based on the neuron model and learning strategy, the neuron intelligent PID control system is set up in this paper. The neuron model-free PID control method is posed. The simulation tests with an example of a hydraulic turbine generator unit are made. The result show that god control performances are obtained. This new intelligent controller is very simple and has very strong adaptability and robustness. It can be used directly in practice.

  4. 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

  5. Fitting neuron models to spike trains.

    PubMed

    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

  6. 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.

  7. 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.

  8. 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

  9. A computational model of motor neuron degeneration.

    PubMed

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

    2014-08-20

    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.

  10. Mirror neurons: functions, mechanisms and models.

    PubMed

    Oztop, Erhan; Kawato, Mitsuo; Arbib, Michael A

    2013-04-12

    Mirror neurons for manipulation fire both when the animal manipulates an object in a specific way and when it sees another animal (or the experimenter) perform an action that is more or less similar. Such neurons were originally found in macaque monkeys, in the ventral premotor cortex, area F5 and later also in the inferior parietal lobule. Recent neuroimaging data indicate that the adult human brain is endowed with a "mirror neuron system," putatively containing mirror neurons and other neurons, for matching the observation and execution of actions. Mirror neurons may serve action recognition in monkeys as well as humans, whereas their putative role in imitation and language may be realized in human but not in monkey. This article shows the important role of computational models in providing sufficient and causal explanations for the observed phenomena involving mirror systems and the learning processes which form them, and underlines the need for additional circuitry to lift up the monkey mirror neuron circuit to sustain the posited cognitive functions attributed to the human mirror neuron system.

  11. Oxidative stress induces increase in intracellular amyloid beta-protein production and selective activation of betaI and betaII PKCs in NT2 cells.

    PubMed

    Paola, D; Domenicotti, C; Nitti, M; Vitali, A; Borghi, R; Cottalasso, D; Zaccheo, D; Odetti, P; Strocchi, P; Marinari, U M; Tabaton, M; Pronzato, M A

    2000-02-16

    Amyloid beta-protein (Abeta) aggregation produces an oxidative stress in neuronal cells that, in turn, may induce an amyloidogenic shift of neuronal metabolism. To investigate this hypothesis, we analyzed intra- and extracellular Abeta content in NT2 differentiated cells incubated with 4-hydroxy-2,3-nonenal (HNE), a major product of lipid peroxidation. In parallel, we evaluated protein kinase C (PKC) isoenzymes activity, a signaling system suspected to modulate amyloid precursor protein (APP) processing. Low HNE concentrations (0.1-1 microM) induced a 2-6 fold increase of intracellular Abeta production that was concomitant with selective activation of betaI and betaII PKC isoforms, without affecting either cell viability or APP full-length expression. Selective activation of the same PKC isoforms was observed following NT2 differentiation. Our findings suggest that PKC beta isoenzymes are part of cellular mechanisms that regulate production of the intracellular Abeta pool. Moreover, they indicate that lipid peroxidation fosters intracellular Abeta accumulation, creating a vicious neurodegenerative loop. PMID:10679257

  12. 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

  13. Activity-Dependent Model for Neuronal Avalanches

    NASA Astrophysics Data System (ADS)

    de Arcangelis, L.

    Networks of living neurons represent one of the most fascinating systems of modern biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behavior of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behavior is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. This fundamental problem in neurobiology has recently shown a number of features in common to other complex systems. These features mainly concern the morphology of the network, namely the spatial organization of the established connections, and a novel kind of neuronal activity. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. Both features have been found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behavior. In this contribution, we apply a statistical mechanical model to describe the complex activity in a neuronal network. The network is chosen to have a number of connections in long range, as found for neurons in vitro. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. The numerical power spectra for electrical activity reproduces also the power law behavior measured in an EEG of man resting with the eyes closed.

  14. 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

  15. Modeling Molecular Pathways of Neuronal Ischemia

    PubMed Central

    Taxin, Zachary H.; Neymotin, Samuel A.; Mohan, Ashutosh; Lipton, Peter; Lytton, William W.

    2014-01-01

    Neuronal ischemia, the consequence of a stroke (cerebrovascular accident), is a condition of reduced delivery of nutrients to brain neurons. The brain consumes more energy per gram of tissue than any other organ, making continuous blood flow critical. Loss of nutrients, most critically glucose and O2, triggers a large number of interacting molecular pathways in neurons and astrocytes. The dynamics of these pathways take place over multiple temporal scales and occur in multiple interacting cytosolic and organelle compartments: in mitochondria, endoplasmic reticulum, and nucleus. The complexity of these relationships suggests the use of computer simulation to understand the interplay between pathways leading to reversible or irreversible damage, the forms of damage, and interventions that could reduce damage at different stages of stroke. We describe a number of models and simulation methods that can be used to further our understanding of ischemia. PMID:24560148

  16. 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

  17. 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.

  18. 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.

  19. 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

  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. A computational model of cuneothalamic projection neurons.

    PubMed

    Sánchez, Eduardo; Barro, Senén; Mariño, Jorge; Canedo, Antonio

    2003-05-01

    The dorsal column nuclei, cuneatus and gracilis, play a fundamental role in the processing and integration of somesthetic ascending information. Intracellular and patch-clamp recordings obtained in cat in vivo have shown that cuneothalamic projection neurons present two modes of activity: oscillatory and tonic (Canedo et al 1998 Neuroscience 84 603-17). The former is the basis of generating, in sleep and anaesthetized states, slow, delta and spindle rhythms under the control of the cerebral cortex (Mariño et al 2000 Neuroscience 95 657-73). The latter is needed, during wakefulness, to process somesthetic information in real time. To study this behaviour we have developed the first realistic computational model of the cuneothalamic projection neurons. The modelling was guided by experimental recordings, which suggest the existence of hyperpolarization-activated inward currents, transient low- and high-threshold calcium currents, and calcium-activated potassium currents. The neuronal responses were simulated during (1) sleep, (2) transition from sleep to wakefulness and (3) wakefulness under both excitatory and inhibitory synaptic input. In wakefulness the model predicts a set of synaptically driven firing modes that could be associated with information processing strategies in the middle cuneate nucleus.

  2. 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.

  3. 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

  4. A neuron-astrocyte transistor-like model for neuromorphic dressed neurons.

    PubMed

    Valenza, G; Pioggia, G; Armato, A; Ferro, M; Scilingo, E P; De Rossi, D

    2011-09-01

    Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology.

  5. 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.

  6. Aggregate input-output models of neuronal populations.

    PubMed

    Saxena, Shreya; Schieber, Marc H; Thakor, Nitish V; Sarma, Sridevi V

    2012-07-01

    An extraordinary amount of electrophysiological data has been collected from various brain nuclei to help us understand how neural activity in one region influences another region. In this paper, we exploit the point process modeling (PPM) framework and describe a method for constructing aggregate input-output (IO) stochastic models that predict spiking activity of a population of neurons in the "output" region as a function of the spiking activity of a population of neurons in the "input" region. We first build PPMs of each output neuron as a function of all input neurons, and then cluster the output neurons using the model parameters. Output neurons that lie within the same cluster have the same functional dependence on the input neurons. We first applied our method to simulated data, and successfully uncovered the predetermined relationship between the two regions. We then applied our method to experimental data to understand the input-output relationship between motor cortical neurons and 1) somatosensory and 2) premotor cortical neurons during a behavioral task. Our aggregate IO models highlighted interesting physiological dependences including relative effects of inhibition/excitation from input neurons and extrinsic factors on output neurons.

  7. Stein's neuronal model with pooled renewal input.

    PubMed

    Rajdl, Kamil; Lansky, Petr

    2015-06-01

    The input of Stein's model of a single neuron is usually described by using a Poisson process, which is assumed to represent the behaviour of spikes pooled from a large number of presynaptic spike trains. However, such a description of the input is not always appropriate as the variability cannot be separated from the intensity. Therefore, we create and study Stein's model with a more general input, a sum of equilibrium renewal processes. The mean and variance of the membrane potential are derived for this model. Using these formulas and numerical simulations, the model is analyzed to study the influence of the input variability on the properties of the membrane potential and the output spike trains. The generalized Stein's model is compared with the original Stein's model with Poissonian input using the relative difference of variances of membrane potential at steady state and the integral square error of output interspike intervals. Both of the criteria show large differences between the models for input with high variability. PMID:25910437

  8. Stochastic resonance in models of neuronal ensembles

    SciTech Connect

    Chialvo, D.R. Longtin, A.; Mueller-Gerkin, J.

    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 {open_quotes}resonance curve{close_quotes} in the multineuron {ital 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. {copyright} {ital 1997} {ital The American Physical Society}

  9. 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.

  10. A diffusion model of a neuron and neural nets.

    PubMed

    Dabrowski, L

    1993-01-01

    In the paper a diffusion model of a neuron is treated. A new, less restrictive than usually, condition of applicability of a diffusion model is presented. As a result the point-process-to-point-process model of a neuron is obtained, which produces an output signal of the same kind as the accepted input signals.

  11. 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.

  12. Mathematical modeling of the neuron morphology using two dimensional images.

    PubMed

    Rajković, Katarina; Marić, Dušica L; Milošević, Nebojša T; Jeremic, Sanja; Arsenijević, Valentina Arsić; Rajković, Nemanja

    2016-02-01

    In this study mathematical analyses such as the analysis of area and length, fractal analysis and modified Sholl analysis were applied on two dimensional (2D) images of neurons from adult human dentate nucleus (DN). Using mathematical analyses main morphological properties were obtained including the size of neuron and soma, the length of all dendrites, the density of dendritic arborization, the position of the maximum density and the irregularity of dendrites. Response surface methodology (RSM) was used for modeling the size of neurons and the length of all dendrites. However, the RSM model based on the second-order polynomial equation was only possible to apply to correlate changes in the size of the neuron with other properties of its morphology. Modeling data provided evidence that the size of DN neurons statistically depended on the size of the soma, the density of dendritic arborization and the irregularity of dendrites. The low value of mean relative percent deviation (MRPD) between the experimental data and the predicted neuron size obtained by RSM model showed that model was suitable for modeling the size of DN neurons. Therefore, RSM can be generally used for modeling neuron size from 2D images.

  13. 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

  14. 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

  15. 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.

  16. Biodegradation of 4-nitrotoluene with biosurfactant production by Rhodococcus pyridinivorans NT2: metabolic pathway, cell surface properties and toxicological characterization.

    PubMed

    Kundu, Debasree; Hazra, Chinmay; Dandi, Navin; Chaudhari, Ambalal

    2013-11-01

    A novel 4-nitrotoluene-degrading bacterial strain was isolated from pesticides contaminated effluent-sediment and identified as Rhodococcus pyridinivorans NT2 based on morphological and biochemical properties and 16S rDNA sequencing. The strain NT2 degraded 4-NT (400 mg l(-1)) with rapid growth at the end of 120 h, reduced surface tension of the media from 71 to 29 mN m(-1) and produced glycolipidic biosurfactants (45 mg l(-1)). The biosurfactant was purified and characterized as trehalose lipids. The biosurfactant was stable in high salinity (10 % w/v NaCl), elevated temperatures (120 °C for 15 min) and a wide pH range (2.0-10.0). The noticeable changes during biodegradation were decreased hydrophobicity; an increase in degree of fatty acid saturation, saturated/unsaturated ratio and cyclopropane fatty acid. Biodegradation of 4-NT was accompanied by the accumulation of ammonium (NH4 (+)) and negligible amount of nitrite ion (NO2 (-)). Product stoichiometry showed a carbon (C) and nitrogen (N) mass balance of 37 and 35 %, respectively. Biodegradation of 4-NT proceeded by oxidation at the methyl group to form 4-nitrobenzoate, followed by reduction and hydrolytic deamination yielding protocatechuate, which was metabolized through β-ketoadipate pathway. In vitro and in vivo acute toxicity assays in adult rat (Rattus norvegicus) showed sequential detoxification and the order of toxicity was 4-NT >4-nitrobenzyl alcohol >4-nitrobenzaldehyde >4-nitrobenzoate > protocatechuate. Taken together, the strain NT2 could be used as a potential bioaugmentation candidate for the bioremediation of contaminated sites.

  17. An algorithmic method for reducing conductance-based neuron models.

    PubMed

    Sorensen, Michael E; DeWeerth, Stephen P

    2006-08-01

    Although conductance-based neural models provide a realistic depiction of neuronal activity, their complexity often limits effective implementation and analysis. Neuronal model reduction methods provide a means to reduce model complexity while retaining the original model's realism and relevance. Such methods, however, typically include ad hoc components that require that the modeler already be intimately familiar with the dynamics of the original model. We present an automated, algorithmic method for reducing conductance-based neuron models using the method of equivalent potentials (Kelper et al., Biol Cybern 66(5):381-387, 1992) Our results demonstrate that this algorithm is able to reduce the complexity of the original model with minimal performance loss, and requires minimal prior knowledge of the model's dynamics. Furthermore, by utilizing a cost function based on the contribution of each state variable to the total conductance of the model, the performance of the algorithm can be significantly improved.

  18. 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

  19. 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.

  20. Transgenic Mouse Models Enabling Photolabeling of Individual Neurons In Vivo

    PubMed Central

    Peter, Manuel; Bathellier, Brice; Fontinha, Bruno; Pliota, Pinelopi; Haubensak, Wulf; Rumpel, Simon

    2013-01-01

    One of the biggest tasks in neuroscience is to explain activity patterns of individual neurons during behavior by their cellular characteristics and their connectivity within the neuronal network. To greatly facilitate linking in vivo experiments with a more detailed molecular or physiological analysis in vitro, we have generated and characterized genetically modified mice expressing photoactivatable GFP (PA-GFP) that allow conditional photolabeling of individual neurons. Repeated photolabeling at the soma reveals basic morphological features due to diffusion of activated PA-GFP into the dendrites. Neurons photolabeled in vivo can be re-identified in acute brain slices and targeted for electrophysiological recordings. We demonstrate the advantages of PA-GFP expressing mice by the correlation of in vivo firing rates of individual neurons with their expression levels of the immediate early gene c-fos. Generally, the mouse models described in this study enable the combination of various analytical approaches to characterize living cells, also beyond the neurosciences. PMID:23626779

  1. 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

  2. A Semiparametric Bayesian Model for Detecting Synchrony Among Multiple Neurons

    PubMed Central

    Shahbaba, Babak; Zhou, Bo; Lan, Shiwei; Ombao, Hernando; Moorman, David; Behseta, Sam

    2015-01-01

    We propose a scalable semiparametric Bayesian model to capture dependencies among multiple neurons by detecting their co-firing (possibly with some lag time) patterns over time. After discretizing time so there is at most one spike at each interval, the resulting sequence of 1’s (spike) and 0’s (silence) for each neuron is modeled using the logistic function of a continuous latent variable with a Gaussian process prior. For multiple neurons, the corresponding marginal distributions are coupled to their joint probability distribution using a parametric copula model. The advantages of our approach are as follows: the nonparametric component (i.e., the Gaussian process model) provides a flexible framework for modeling the underlying firing rates; the parametric component (i.e., the copula model) allows us to make inference regarding both contemporaneous and lagged relationships among neurons; using the copula model, we construct multivariate probabilistic models by separating the modeling of univariate marginal distributions from the modeling of dependence structure among variables; our method is easy to implement using a computationally efficient sampling algorithm that can be easily extended to high dimensional problems. Using simulated data, we show that our approach could correctly capture temporal dependencies in firing rates and identify synchronous neurons. We also apply our model to spike train data obtained from prefrontal cortical areas. PMID:24922500

  3. Automatic fitting of spiking neuron models to electrophysiological recordings.

    PubMed

    Rossant, Cyrille; Goodman, Dan F M; Platkiewicz, Jonathan; Brette, Romain

    2010-01-01

    Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains) that can run in parallel on graphics processing units (GPUs). The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models. PMID:20224819

  4. 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

  5. Iterative learning control algorithm for spiking behavior of neuron model

    NASA Astrophysics Data System (ADS)

    Li, Shunan; Li, Donghui; Wang, Jiang; Yu, Haitao

    2016-11-01

    Controlling neurons to generate a desired or normal spiking behavior is the fundamental building block of the treatment of many neurologic diseases. The objective of this work is to develop a novel control method-closed-loop proportional integral (PI)-type iterative learning control (ILC) algorithm to control the spiking behavior in model neurons. In order to verify the feasibility and effectiveness of the proposed method, two single-compartment standard models of different neuronal excitability are specifically considered: Hodgkin-Huxley (HH) model for class 1 neural excitability and Morris-Lecar (ML) model for class 2 neural excitability. ILC has remarkable advantages for the repetitive processes in nature. To further highlight the superiority of the proposed method, the performances of the iterative learning controller are compared to those of classical PI controller. Either in the classical PI control or in the PI control combined with ILC, appropriate background noises are added in neuron models to approach the problem under more realistic biophysical conditions. Simulation results show that the controller performances are more favorable when ILC is considered, no matter which neuronal excitability the neuron belongs to and no matter what kind of firing pattern the desired trajectory belongs to. The error between real and desired output is much smaller under ILC control signal, which suggests ILC of neuron’s spiking behavior is more accurate.

  6. Modeling the Development of Goal-Specificity in Mirror Neurons.

    PubMed

    Thill, Serge; Svensson, Henrik; Ziemke, Tom

    2011-12-01

    Neurophysiological studies have shown that parietal mirror neurons encode not only actions but also the goal of these actions. Although some mirror neurons will fire whenever a certain action is perceived (goal-independently), most will only fire if the motion is perceived as part of an action with a specific goal. This result is important for the action-understanding hypothesis as it provides a potential neurological basis for such a cognitive ability. It is also relevant for the design of artificial cognitive systems, in particular robotic systems that rely on computational models of the mirror system in their interaction with other agents. Yet, to date, no computational model has explicitly addressed the mechanisms that give rise to both goal-specific and goal-independent parietal mirror neurons. In the present paper, we present a computational model based on a self-organizing map, which receives artificial inputs representing information about both the observed or executed actions and the context in which they were executed. We show that the map develops a biologically plausible organization in which goal-specific mirror neurons emerge. We further show that the fundamental cause for both the appearance and the number of goal-specific neurons can be found in geometric relationships between the different inputs to the map. The results are important to the action-understanding hypothesis as they provide a mechanism for the emergence of goal-specific parietal mirror neurons and lead to a number of predictions: (1) Learning of new goals may mostly reassign existing goal-specific neurons rather than recruit new ones; (2) input differences between executed and observed actions can explain observed corresponding differences in the number of goal-specific neurons; and (3) the percentage of goal-specific neurons may differ between motion primitives.

  7. 3D-printer visualization of neuron models

    PubMed Central

    McDougal, Robert A.; Shepherd, Gordon M.

    2015-01-01

    Neurons come in a wide variety of shapes and sizes. In a quest to understand this neuronal diversity, researchers have three-dimensionally traced tens of thousands of neurons; many of these tracings are freely available through online repositories like NeuroMorpho.Org and ModelDB. Tracings can be visualized on the computer screen, used for statistical analysis of the properties of different cell types, used to simulate neuronal behavior, and more. We introduce the use of 3D printing as a technique for visualizing traced morphologies. Our method for generating printable versions of a cell or group of cells is to expand dendrite and axon diameters and then to transform the tracing into a 3D object with a neuronal surface generating algorithm like Constructive Tessellated Neuronal Geometry (CTNG). We show that 3D printed cells can be readily examined, manipulated, and compared with other neurons to gain insight into both the biology and the reconstruction process. We share our printable models in a new database, 3DModelDB, and encourage others to do the same with cells that they generate using our code or other methods. To provide additional context, 3DModelDB provides a simulatable version of each cell, links to papers that use or describe it, and links to associated entries in other databases. PMID:26175684

  8. 3D-printer visualization of neuron models.

    PubMed

    McDougal, Robert A; Shepherd, Gordon M

    2015-01-01

    Neurons come in a wide variety of shapes and sizes. In a quest to understand this neuronal diversity, researchers have three-dimensionally traced tens of thousands of neurons; many of these tracings are freely available through online repositories like NeuroMorpho.Org and ModelDB. Tracings can be visualized on the computer screen, used for statistical analysis of the properties of different cell types, used to simulate neuronal behavior, and more. We introduce the use of 3D printing as a technique for visualizing traced morphologies. Our method for generating printable versions of a cell or group of cells is to expand dendrite and axon diameters and then to transform the tracing into a 3D object with a neuronal surface generating algorithm like Constructive Tessellated Neuronal Geometry (CTNG). We show that 3D printed cells can be readily examined, manipulated, and compared with other neurons to gain insight into both the biology and the reconstruction process. We share our printable models in a new database, 3DModelDB, and encourage others to do the same with cells that they generate using our code or other methods. To provide additional context, 3DModelDB provides a simulatable version of each cell, links to papers that use or describe it, and links to associated entries in other databases.

  9. Testing Neuronal Accounts of Anisotropic Motion Perception with Computational Modelling

    PubMed Central

    Wong, William; Chiang Price, Nicholas Seow

    2014-01-01

    There is an over-representation of neurons in early visual cortical areas that respond most strongly to cardinal (horizontal and vertical) orientations and directions of visual stimuli, and cardinal- and oblique-preferring neurons are reported to have different tuning curves. Collectively, these neuronal anisotropies can explain two commonly-reported phenomena of motion perception – the oblique effect and reference repulsion – but it remains unclear whether neuronal anisotropies can simultaneously account for both perceptual effects. We show in psychophysical experiments that reference repulsion and the oblique effect do not depend on the duration of a moving stimulus, and that brief adaptation to a single direction simultaneously causes a reference repulsion in the orientation domain, and the inverse of the oblique effect in the direction domain. We attempted to link these results to underlying neuronal anisotropies by implementing a large family of neuronal decoding models with parametrically varied levels of anisotropy in neuronal direction-tuning preferences, tuning bandwidths and spiking rates. Surprisingly, no model instantiation was able to satisfactorily explain our perceptual data. We argue that the oblique effect arises from the anisotropic distribution of preferred directions evident in V1 and MT, but that reference repulsion occurs separately, perhaps reflecting a process of categorisation occurring in higher-order cortical areas. PMID:25409518

  10. 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.

  11. 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

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

    PubMed

    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.

  13. Visual attention model based on statistical properties of neuron responses.

    PubMed

    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

  14. 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

  15. Exploring how extracellular electric field modulates neuron activity through dynamical analysis of a two-compartment neuron model.

    PubMed

    Yi, Guo-Sheng; Wang, Jiang; Wei, Xi-Le; Tsang, Kai-Ming; Chan, Wai-Lok; Deng, Bin; Han, Chun-Xiao

    2014-06-01

    To investigate how extracellular electric field modulates neuron activity, a reduced two-compartment neuron model in the presence of electric field is introduced in this study. Depending on neuronal geometric and internal coupling parameters, the behaviors of the model have been studied extensively. The neuron model can exist in quiescent state or repetitive spiking state in response to electric field stimulus. Negative electric field mainly acts as inhibitory stimulus to the neuron, positive weak electric field could modulate spiking frequency and spike timing when the neuron is already active, and positive electric fields with sufficient intensity could directly trigger neuronal spiking in the absence of other stimulations. By bifurcation analysis, it is observed that there is saddle-node on invariant circle bifurcation, supercritical Hopf bifurcation and subcritical Hopf bifurcation appearing in the obtained two parameter bifurcation diagrams. The bifurcation structures and electric field thresholds for triggering neuron firing are determined by neuronal geometric and coupling parameters. The model predicts that the neurons with a nonsymmetric morphology between soma and dendrite, are more sensitive to electric field stimulus than those with the spherical structure. These findings suggest that neuronal geometric features play a crucial role in electric field effects on the polarization of neuronal compartments. Moreover, by determining the electric field threshold of our biophysical model, we could accurately distinguish between suprathreshold and subthreshold electric fields. Our study highlights the effects of extracellular electric field on neuronal activity from the biophysical modeling point of view. These insights into the dynamical mechanism of electric field may contribute to the investigation and development of electromagnetic therapies, and the model in our study could be further extended to a neuronal network in which the effects of electric fields on

  16. Avalanches in a stochastic model of spiking neurons.

    PubMed

    Benayoun, Marc; Cowan, Jack D; van Drongelen, Wim; Wallace, Edward

    2010-07-08

    Neuronal avalanches are a form of spontaneous activity widely observed in cortical slices and other types of nervous tissue, both in vivo and in vitro. They are characterized by irregular, isolated population bursts when many neurons fire together, where the number of spikes per burst obeys a power law distribution. We simulate, using the Gillespie algorithm, a model of neuronal avalanches based on stochastic single neurons. The network consists of excitatory and inhibitory neurons, first with all-to-all connectivity and later with random sparse connectivity. Analyzing our model using the system size expansion, we show that the model obeys the standard Wilson-Cowan equations for large network sizes ( neurons). When excitation and inhibition are closely balanced, networks of thousands of neurons exhibit irregular synchronous activity, including the characteristic power law distribution of avalanche size. We show that these avalanches are due to the balanced network having weakly stable functionally feedforward dynamics, which amplifies some small fluctuations into the large population bursts. Balanced networks are thought to underlie a variety of observed network behaviours and have useful computational properties, such as responding quickly to changes in input. Thus, the appearance of avalanches in such functionally feedforward networks indicates that avalanches may be a simple consequence of a widely present network structure, when neuron dynamics are noisy. An important implication is that a network need not be "critical" for the production of avalanches, so experimentally observed power laws in burst size may be a signature of noisy functionally feedforward structure rather than of, for example, self-organized criticality.

  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. Multisynaptic activity in a pyramidal neuron model and neural code.

    PubMed

    Ventriglia, Francesco; Di Maio, Vito

    2006-01-01

    The highly irregular firing of mammalian cortical pyramidal neurons is one of the most striking observation of the brain activity. This result affects greatly the discussion on the neural code, i.e. how the brain codes information transmitted along the different cortical stages. In fact it seems to be in favor of one of the two main hypotheses about this issue, named the rate code. But the supporters of the contrasting hypothesis, the temporal code, consider this evidence inconclusive. We discuss here a leaky integrate-and-fire model of a hippocampal pyramidal neuron intended to be biologically sound to investigate the genesis of the irregular pyramidal firing and to give useful information about the coding problem. To this aim, the complete set of excitatory and inhibitory synapses impinging on such a neuron has been taken into account. The firing activity of the neuron model has been studied by computer simulation both in basic conditions and allowing brief periods of over-stimulation in specific regions of its synaptic constellation. Our results show neuronal firing conditions similar to those observed in experimental investigations on pyramidal cortical neurons. In particular, the variation coefficient (CV) computed from the inter-spike intervals (ISIs) in our simulations for basic conditions is close to the unity as that computed from experimental data. Our simulation shows also different behaviors in firing sequences for different frequencies of stimulation. PMID:16870323

  19. A developmental approach to predicting neuronal connectivity from small biological datasets: a gradient-based neuron growth model.

    PubMed

    Borisyuk, Roman; Al Azad, Abul Kalam; 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.

  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. 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

  4. A Neuronal Network Model for Pitch Selectivity and Representation.

    PubMed

    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

  5. Modeling of Auditory Neuron Response Thresholds with Cochlear Implants

    PubMed Central

    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

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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

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

    PubMed

    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.

  12. 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.

  13. Derivation of a neural field model from a network of theta neurons.

    PubMed

    Laing, Carlo R

    2014-07-01

    Neural field models are used to study macroscopic spatiotemporal patterns in the cortex. Their derivation from networks of model neurons normally involves a number of assumptions, which may not be correct. Here we present an exact derivation of a neural field model from an infinite network of theta neurons, the canonical form of a type I neuron. We demonstrate the existence of a "bump" solution in both a discrete network of neurons and in the corresponding neural field model.

  14. 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.

  15. 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

  16. 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.

  17. Regional Differentiation of Retinoic Acid-Induced Human Pluripotent Embryonic Carcinoma Stem Cell Neurons

    PubMed Central

    Coyle, Dennis E.; Li, Jie; Baccei, Mark

    2011-01-01

    The NTERA2 cl D1 (NT2) cell line, derived from human teratocarcinoma, exhibits similar properties as embryonic stem (ES) cells or very early neuroepitheial progenitors. NT2 cells can be induced to become postmitotic central nervous system neurons (NT2N) with retinoic acid. Although neurons derived from pluripotent cells, such as NT2N, have been characterized for their neurotransmitter phenotypes, their potential suitability as a donor source for neural transplantation also depends on their ability to respond to localized environmental cues from a specific region of the CNS. Therefore, our study aimed to characterize the regional transcription factors that define the rostocaudal and dorsoventral identity of NT2N derived from a monolayer differentiation paradigm using quantitative PCR (qPCR). Purified NT2N mainly expressed both GABAergic and glutamatergic phenotypes and were electrically active but did not form functional synapses. The presence of immature astrocytes and possible radial glial cells was noted. The NT2N expressed a regional transcription factor code consistent with forebrain, hindbrain and spinal cord neural progenitors but showed minimal expression of midbrain phenotypes. In the dorsoventral plane NT2N expressed both dorsal and ventral neural progenitors. Of major interest was that even under the influence of retinoic acid, a known caudalization factor, the NT2N population maintained a rostral phenotype subpopulation which expressed cortical regional transcription factors. It is proposed that understanding the regional differentiation bias of neurons derived from pluripotent stem cells will facilitate their successful integration into existing neuronal networks within the CNS. PMID:21283767

  18. 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.

  19. 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.

  20. Neuron type processor modeling using a timed Petri net.

    PubMed

    Habib, M K; Newcomb, R W

    1990-01-01

    The basic operation of a digital neuron is reviewed, and the theory of time Petri nets used for modeling, representation, and analysis of the neuron-type processor (NTP) is reviewed. The timed Petri net is utilized to produce a model for the digital NTP. The neuron-type processor performs input temporal and spatial summation, as well as thresholding. The timed Petri net of the NTP operates asynchronously and sequentially takes on a series of distinct internal states, so that each of these states can concurrently realize a distinct set of steering switching functions depending on the pattern of steering inputs applied to it at the time. This model is structured using several subnets, called essential module units. Depending on the desired number of input dendrites required for the NTP, the essential module units (EMU) are interconnected to produce the required timed Petri net. The timed Petri net and representation facilitates a method of analysis of neural net works containing NTPs prior to hardware implementation.

  1. 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.

  2. A probabilistic model for the establishment of neuron polarity.

    PubMed

    Khanin, K; Khanin, R

    2001-01-01

    The main aim of this paper is to present a simple probabilistic model for the early stage of neuron growth: the specification on an axon out of several initially similar neurites. The model is a Markov process with competition between the growing neurites, wherein longer objects have more chances to grow, and parameter alpha determines the intensity of the competition. For alpha > 1 the model provides results which are qualitatively similar to the experimental ones, i.e. selection of one rapidly elongating axon out of several neurites while other less successful neurites stop growing at some random time. Rigorous mathematical proofs are given.

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

    PubMed

    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.

  4. 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.

  5. [A community model of mutually learning neuronal nets].

    PubMed

    Grosberg, A Iu

    1990-01-01

    A model of a community is suggested whose members are formal neuron nets interacting by signals exchange. As a signal each net can emit an image formed by it when recognising the preceding signal. The emitted signal comes to the inputs of other nets and is used as their initial state for the recognition process. The collective dynamics of such model is discussed for the case of non-learning nets. Possible algorithm of mutual learning of the nets in them course of signals exchange is considered.

  6. Neuronal and glial properties of a murine transgenic retinoblastoma model.

    PubMed Central

    Kivelä, T.; Virtanen, I.; Marcus, D. M.; O'Brien, J. M.; Carpenter, J. L.; Brauner, E.; Tarkkanen, A.; Albert, D. M.

    1991-01-01

    Antigenic properties of a murine transgenic model for hereditary retinoblastoma, induced by a chimeric gene coding for Simian virus 40 large T antigen, an oncogene that inactivates the retinoblastoma susceptibility gene product, were studied by immunohistochemistry. All transgenic mice develop bilateral intraocular retinal tumors in the inner nuclear layer with Homer Wright-like rosettes, and one quarter develop midbrain tumors resembling trilateral retinoblastoma. Cell lines TE-1 and TM-1 were established from intraocular and metastatic tumors, respectively. Intraocular tumors reacted with antibodies to neuron-specific enolase and synaptophysin, while vimentin, glial fibrillary acidic, and S-100 proteins were detected only in reactive glia derived from adjacent retina. The midbrain tumors showed weak reactivity to synaptophysin, and they blended with reactive astrocytes positive for glial markers. The tumors were negative for cytokeratins. Finally both derived cell lines expressed synaptophysin and individual neurofilament triplet proteins in immunofluorescence and Western blotting, supporting their essentially neuronal nature. The antigenic profile resembles human retinoblastoma, but differences in morphology and antigen distribution suggest a more close relationship to neurons of the inner nuclear layer than to photoreceptor cells. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 PMID:1708946

  7. Dynamical properties of neural network model for working memory with Hodgkin-Huxley neurons

    NASA Astrophysics Data System (ADS)

    Omori, Toshiaki; Horiguchi, Tsuyoshi

    2004-03-01

    We propose a neural network model of working memory with one-compartmental neurons and investigate its dynamical properties. We assume that the model consists of excitatory neurons and inhibitory neurons; all the neurons are connected to each other. The excitatory neurons are distinguished as several groups of selective neurons and one group of non-selective neurons. The selective neurons are assumed to form subpopulations in which each selective neuron belongs to only one of subpopulations. The non-selective neurons are assumed not to form any subpopulation. Synaptic strengths between neurons within a subpopulation are assumed to be potentiated. By the numerical simulations, persistent firing of neurons in a subpopulation emerges; the persistent firing corresponds to the retention of memory as one of the functions of working memory. We find that the strength of external input and the strength of N-methyl- D-aspartate synapse are important factors for dynamical behaviors of the network; for example, if we enhance the strength of the external input to a subpopulation while the persistent firing is occurring in other subpopulation, the persistent firing occurs in the subpopulation or is sustained against the external input. These results reveal that the neural network as for the function of the working memory is controlled by the neuromodulation and the external stimuli within the proposed model. We also find that the persistent time of firing of the selective neurons shows a kind of phase transition as a function of the degree of potentiation of synapses.

  8. 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.

  9. Spatiotemporal testing and modeling of catfish retinal neurons.

    PubMed Central

    Krausz, H I; Naka, K

    1980-01-01

    The responses of retinal neurons depend on the interaction of both temporal and spatial aspects of a light stimulus. We developed a linear spatiotemporal model of receptor and horizontal cell layers in the catfish retina based on reciprocal interactions between both layers and coupling within each. Horizontal cell transfer properties were measured experimentally using white-noise intensity modulated light spots of different diameters and were compared with analytical predictions based on the model. Good agreement was obtained with a reasonable choice of model space-constants and feedback parameters. Furthermore, the same set of parameter values determined from spot experiments enabled accurate prediction of experimental horizontal cell responses to traveling gratings. The proposed feedback connections from horizontal cells to receptors quicken the time-course of responses in both layers and sharpen receptive fields. PMID:7260243

  10. Modeling the electric potential across neuronal membranes: the effect of fixed charges on spinal ganglion neurons and neuroblastoma cells.

    PubMed

    Pinto, Thiago M; Wedemann, Roseli S; Cortez, Célia M

    2014-01-01

    We present a model for the electric potential profile across the membranes of neuronal cells. We considered the resting and action potential states, and analyzed the influence of fixed charges of the membrane on its electric potential, based on experimental values of membrane properties of the spinal ganglion neuron and the neuroblastoma cell. The spinal ganglion neuron represents a healthy neuron, and the neuroblastoma cell, which is tumorous, represents a pathological neuron. We numerically solved the non-linear Poisson-Boltzmann equation for the regions of the membrane model we have adopted, by considering the densities of charges dissolved in an electrolytic solution and fixed on both glycocalyx and cytoplasmic proteins. Our model predicts that there is a difference in the behavior of the electric potential profiles of the two types of cells, in response to changes in charge concentrations in the membrane. Our results also describe an insensitivity of the neuroblastoma cell membrane, as observed in some biological experiments. This electrical property may be responsible for the low pharmacological response of the neuroblastoma to certain chemotherapeutic treatments. PMID:24801682

  11. Generation of very slow neuronal rhythms and chaos near the Hopf bifurcation in single neuron models.

    PubMed

    Doi, Shinji; Kumagai, Sadatoshi

    2005-12-01

    We have presented a new generation mechanism of slow spiking or repetitive discharges with extraordinarily long inter-spike intervals using the modified Hodgkin-Huxley equations (Doi and Kumagai, 2001). This generation process of slow firing is completely different from that of the well-known potassium A-current in that the steady-state current-voltage relation of the neuronal model is monotonic rather than the N-shaped one of the A-current. In this paper, we extend the previous results and show that the very slow spiking generically appears in both the three-dimensional Hodgkin-Huxley equations and the three dimensional Bonhoeffer-van der Pol (or FitzHugh-Nagumo) equations. The generation of repetitive discharges or the destabilization of the unique equilibrium point (resting potential) is a simple Hopf bifurcation. We also show that the generation of slow spiking does not depend on the stability of the Hopf bifurcation: supercritical or subcritical. The dynamics of slow spiking is investigated in detail and we demonstrate that the phenomenology of slow spiking can be categorized into two types according to the type of the corresponding bifurcation of a fast subsystem: Hopf or saddle-node bifurcation.

  12. 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

  13. 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

  14. 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

  15. Zebrafish models of human motor neuron diseases: advantages and limitations.

    PubMed

    Babin, Patrick J; Goizet, Cyril; Raldúa, Demetrio

    2014-07-01

    Motor neuron diseases (MNDs) are an etiologically heterogeneous group of disorders of neurodegenerative origin, which result in degeneration of lower (LMNs) and/or upper motor neurons (UMNs). Neurodegenerative MNDs include pure hereditary spastic paraplegia (HSP), which involves specific degeneration of UMNs, leading to progressive spasticity of the lower limbs. In contrast, spinal muscular atrophy (SMA) involves the specific degeneration of LMNs, with symmetrical muscle weakness and atrophy. Amyotrophic lateral sclerosis (ALS), the most common adult-onset MND, is characterized by the degeneration of both UMNs and LMNs, leading to progressive muscle weakness, atrophy, and spasticity. A review of the comparative neuroanatomy of the human and zebrafish motor systems showed that, while the zebrafish was a homologous model for LMN disorders, such as SMA, it was only partially relevant in the case of UMN disorders, due to the absence of corticospinal and rubrospinal tracts in its central nervous system. Even considering the limitation of this model to fully reproduce the human UMN disorders, zebrafish offer an excellent alternative vertebrate model for the molecular and genetic dissection of MND mechanisms. Its advantages include the conservation of genome and physiological processes and applicable in vivo tools, including easy imaging, loss or gain of function methods, behavioral tests to examine changes in motor activity, and the ease of simultaneous chemical/drug testing on large numbers of animals. This facilitates the assessment of the environmental origin of MNDs, alone or in combination with genetic traits and putative modifier genes. Positive hits obtained by phenotype-based small-molecule screening using zebrafish may potentially be effective drugs for treatment of human MNDs.

  16. Zebrafish models of human motor neuron diseases: advantages and limitations.

    PubMed

    Babin, Patrick J; Goizet, Cyril; Raldúa, Demetrio

    2014-07-01

    Motor neuron diseases (MNDs) are an etiologically heterogeneous group of disorders of neurodegenerative origin, which result in degeneration of lower (LMNs) and/or upper motor neurons (UMNs). Neurodegenerative MNDs include pure hereditary spastic paraplegia (HSP), which involves specific degeneration of UMNs, leading to progressive spasticity of the lower limbs. In contrast, spinal muscular atrophy (SMA) involves the specific degeneration of LMNs, with symmetrical muscle weakness and atrophy. Amyotrophic lateral sclerosis (ALS), the most common adult-onset MND, is characterized by the degeneration of both UMNs and LMNs, leading to progressive muscle weakness, atrophy, and spasticity. A review of the comparative neuroanatomy of the human and zebrafish motor systems showed that, while the zebrafish was a homologous model for LMN disorders, such as SMA, it was only partially relevant in the case of UMN disorders, due to the absence of corticospinal and rubrospinal tracts in its central nervous system. Even considering the limitation of this model to fully reproduce the human UMN disorders, zebrafish offer an excellent alternative vertebrate model for the molecular and genetic dissection of MND mechanisms. Its advantages include the conservation of genome and physiological processes and applicable in vivo tools, including easy imaging, loss or gain of function methods, behavioral tests to examine changes in motor activity, and the ease of simultaneous chemical/drug testing on large numbers of animals. This facilitates the assessment of the environmental origin of MNDs, alone or in combination with genetic traits and putative modifier genes. Positive hits obtained by phenotype-based small-molecule screening using zebrafish may potentially be effective drugs for treatment of human MNDs. PMID:24705136

  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. On learning time delays between the spikes from different input neurons in a biophysical model of a pyramidal neuron.

    PubMed

    Koutsou, Achilleas; Bugmann, Guido; Christodoulou, Chris

    2015-10-01

    Biological systems are able to recognise temporal sequences of stimuli or compute in the temporal domain. In this paper we are exploring whether a biophysical model of a pyramidal neuron can detect and learn systematic time delays between the spikes from different input neurons. In particular, we investigate whether it is possible to reinforce pairs of synapses separated by a dendritic propagation time delay corresponding to the arrival time difference of two spikes from two different input neurons. We examine two subthreshold learning approaches where the first relies on the backpropagation of EPSPs (excitatory postsynaptic potentials) and the second on the backpropagation of a somatic action potential, whose production is supported by a learning-enabling background current. The first approach does not provide a learning signal that sufficiently differentiates between synapses at different locations, while in the second approach, somatic spikes do not provide a reliable signal distinguishing arrival time differences of the order of the dendritic propagation time. It appears that the firing of pyramidal neurons shows little sensitivity to heterosynaptic spike arrival time differences of several milliseconds. This neuron is therefore unlikely to be able to learn to detect such differences.

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. Mimicking human neuronal pathways in silico: an emergent model on the effective connectivity.

    PubMed

    Gürcan, Önder; Türker, Kemal S; Mano, Jean-Pierre; Bernon, Carole; Dikenelli, Oğuz; Glize, Pierre

    2014-04-01

    We present a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication. This poses a great challenge since direct recordings from individual neurons are impossible in the human central nervous system and therefore the underlying neuronal pathway has to be considered as a black box. For tackling this challenge, we used a branch of complex systems modeling called artificial self-organization in which large sets of software entities interacting locally give rise to bottom-up collective behaviors. The result is an emergent model where each software entity represents an integrate-and-fire neuron. We then applied the model to the reflex responses of single motor units obtained from conscious human subjects. Experimental results show that the model recovers functionality of real human neuronal pathways by comparing it to appropriate surrogate data. What makes the model promising is the fact that, to the best of our knowledge, it is the first realistic model to self-wire an artificial neuronal network by efficiently combining neuroscience with artificial self-organization. Although there is no evidence yet of the model's connectivity mapping onto the human connectivity, we anticipate this model will help neuroscientists to learn much more about human neuronal networks, and could also be used for predicting hypotheses to lead future experiments.

  5. 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

  6. 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

  7. Sprouty2 and -4 hypomorphism promotes neuronal survival and astrocytosis in a mouse model of kainic acid induced neuronal damage.

    PubMed

    Thongrong, Sitthisak; Hausott, Barbara; Marvaldi, Letizia; Agostinho, Alexandra S; Zangrandi, Luca; Burtscher, Johannes; Fogli, Barbara; Schwarzer, Christoph; Klimaschewski, Lars

    2016-05-01

    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.

  8. 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

  9. 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.

  10. Delayed-exponential approximation of a linear homogeneous diffusion model of neuron.

    PubMed

    Pacut, A; Dabrowski, L

    1988-01-01

    The diffusion models of neuronal activity are general yet conceptually simple and flexible enough to be useful in a variety of modeling problems. Unfortunately, even simple diffusion models lead to tedious numerical calculations. Consequently, the existing neural net models use characteristics of a single neuron taken from the "pre-diffusion" era of neural modeling. Simplistic elements of neural nets forbid to incorporate a single learning neuron structure into the net model. The above drawback cannot be overcome without the use of the adequate structure of the single neuron as an element of a net. A linear (not necessarily homogeneous) diffusion model of a single neuron is a good candidate for such a structure, it must, however, be simplified. In the paper the structure of the diffusion model of neuron is discussed and a linear homogeneous model with reflection is analyzed. For this model an approximation is presented, which is based on the approximation of the first passage time distribution of the Ornstein-Uhlenbeck process by the delayed (shifted) exponential distribution. The resulting model has a simple structure and has a prospective application in neural modeling and in analysis of neural nets.

  11. On dependency properties of the ISIs generated by a two-compartmental neuronal model.

    PubMed

    Benedetto, Elisa; Sacerdote, Laura

    2013-02-01

    One-dimensional leaky integrate and fire neuronal models describe interspike intervals (ISIs) of a neuron as a renewal process and disregarding the neuron geometry. Many multi-compartment models account for the geometrical features of the neuron but are too complex for their mathematical tractability. Leaky integrate and fire two-compartment models seem a good compromise between mathematical tractability and an improved realism. They indeed allow to relax the renewal hypothesis, typical of one-dimensional models, without introducing too strong mathematical difficulties. Here, we pursue the analysis of the two-compartment model studied by Lansky and Rodriguez (Phys D 132:267-286, 1999), aiming of introducing some specific mathematical results used together with simulation techniques. With the aid of these methods, we investigate dependency properties of ISIs for different values of the model parameters. We show that an increase of the input increases the strength of the dependence between successive ISIs.

  12. Lipid microdomain modification sustains neuronal viability in models of Alzheimer's disease.

    PubMed

    Herzer, Silke; Meldner, Sascha; Rehder, Klara; Gröne, Hermann-Josef; Nordström, Viola

    2016-01-01

    Decreased neuronal insulin receptor (IR) signaling in Alzheimer's disease is suggested to contribute to synaptic loss and neurodegeneration. This work shows that alteration of membrane microdomains increases IR levels and signaling, as well as neuronal viability in AD models in vitro and in vivo. Neuronal membrane microdomains are highly enriched in gangliosides. We found that inhibition of glucosylceramide synthase (GCS), the key enzyme of ganglioside biosynthesis, increases viability of cortical neurons in 5xFAD mice, as well as in cultured neurons exposed to oligomeric amyloid-β-derived diffusible ligands (ADDLs). We furthermore demonstrate a molecular mechanism explaining how gangliosides mediate ADDL-related toxic effects on IR of murine neurons. GCS inhibition increases the levels of functional dendritic IR on the neuronal surface by decreasing caveolin-1-mediated IR internalization. Consequently, IR signaling is increased in neurons exposed to ADDL stress. Thus, we propose that GCS inhibition constitutes a potential target for protecting neurons from ADDL-mediated neurotoxicity and insulin resistance in Alzheimer's disease. PMID:27639375

  13. Modeling ALS using motor neurons derived from human induced pluripotent stem cells

    PubMed Central

    Sances, S; Bruijn, LI; Chandran, S; Eggan, K; Ho, R; Klim, J; Livesey, MR; Lowry, E; Macklis, JD; Rushton, D; Sadegh, C; Sareen, D; Wichterle, H; Zhang, SC; Svendsen, CN

    2016-01-01

    Directing the differentiation of induced pluripotent stem cells into motor neurons has allowed investigators to develop novel models of ALS. However, techniques vary between laboratories and the cells do not appear to mature into fully functional adult motor neurons. Here we discuss common developmental principles of both lower and upper motor neuron development that have led to specific derivation techniques. We then suggest how these motor neurons may be matured further either through direct expression or administration of specific factors or co-culture approaches with other tissues. Ultimately, through a greater understanding of motor neuron biology, it will be possible to establish more reliable models of ALS. These in turn will have a greater chance of validating new drugs that may be effective for the disease. PMID:27021939

  14. 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

  15. 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).

  16. 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

  17. [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

  18. 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…

  19. 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

  20. 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.

  1. A biological plausible Generalized Leaky Integrate-and-Fire neuron model.

    PubMed

    Wang, Zhenzhong; Guo, Lilin; Adjouadi, Malek

    2014-01-01

    This study introduces a new Generalized Leaky Integrate-and-Fire (GLIF) neuron model. Unlike Normal Leaky Integrate-and-Fire (NLIF) models, the leaking resistor in the GLIF model equation is assumed to be variable, and an additional term would have the bias current added to the model equation in order to improve the accuracy. Adjusting the parameters defined for the leaking resistor and bias current, a GLIF model could be accurately matched to any Hodgkin-Huxley (HH) model and be able to reproduce plausible biological neuron behaviors. PMID:25571560

  2. Three-dimensional statistical modeling of neuronal populations: illustration with spatial localization of supernumerary neurons in the locus coeruleus of quaking mutant mice.

    PubMed

    Burguet, Jasmine; Andrey, Philippe; Rampin, Olivier; Maurin, Yves

    2009-04-10

    An algorithm for the three-dimensional statistical representation of neuronal populations was designed and implemented. Using this algorithm a series of 3D models, calculated from repeated histological experiments, can be combined to provide a synthetic vision of a population of neurons taking into account biological and experimental variability. Based on the point process theory, our algorithm allows computation of neuronal density maps from which isodensity surfaces can be readily extracted and visualized as surface models revealing the statistical organization of the neuronal population under study. This algorithm was applied to the spatial distribution of locus coeruleus (LC) neurons of 30- and 90-day-old control and quaking mice. By combining 12 3D models of the LC, a region of the nucleus in which a subpopulation of neurons loses its noradrenergic phenotype between 30 and 90 days postnatally was demonstrated in control mice but not in quaking mice, leading to the hyperplasia previously reported in adult mutants. Altogether, this algorithm allows computation of 3D statistical and graphical models of neuronal populations, providing a contribution to quantitative 3D neuroanatomical modeling. PMID:19226531

  3. 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

  4. Modelling spatiotemporal olfactory data in two steps: from binary to Hodgkin-Huxley neurones.

    PubMed

    Quenet, Brigitte; Dubois, Rémi; Sirapian, Sevan; Dreyfus, Gérard; Horn, David

    2002-01-01

    Network models of synchronously updated McCulloch-Pitts neurones exhibit complex spatiotemporal patterns that are similar to activities of biological neurones in phase with a periodic local field potential, such as those observed experimentally by Wehr and Laurent (1996, Nature 384, 162-166) in the locust olfactory pathway. Modelling biological neural nets with networks of simple formal units makes the dynamics of the model analytically tractable. It is thus possible to determine the constraints that must be satisfied by its connection matrix in order to make its neurones exhibit a given sequence of activity (see, for instance, Quenet et al., 2001, Neurocomputing 38-40, 831-836). In the present paper, we address the following question: how can one construct a formal network of Hodgkin-Huxley (HH) type neurones that reproduces experimentally observed neuronal codes? A two-step strategy is suggested in the present paper: first, a simple network of binary units is designed, whose activity reproduces the binary experimental codes; second, this model is used as a guide to design a network of more realistic formal HH neurones. We show that such a strategy is indeed fruitful: it allowed us to design a model that reproduces the Wehr-Laurent olfactory codes, and to investigate the robustness of these codes to synaptic noise.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. Assignment of Model Amygdala Neurons to the Fear Memory Trace Depends on Competitive Synaptic Interactions

    PubMed Central

    Kim, Dongbeom; Paré, Denis

    2013-01-01

    We used biophysical modeling to examine a fundamental, yet unresolved, question regarding how particular lateral amygdala (LA) neurons are assigned to fear memory traces. This revealed that neurons with high intrinsic excitability are more likely to be integrated into the memory trace, but that competitive synaptic interactions also play a critical role. Indeed, when the ratio of intrinsically excitable cells was increased or decreased, the number of plastic cells remained relatively constant. Analysis of the connectivity of plastic and nonplastic cells revealed that subsets of principal LA neurons effectively band together by virtue of their excitatory interconnections to suppress plasticity in other principal cells via the recruitment of inhibitory interneurons. PMID:24005288

  11. On a Kinetic Fitzhugh-Nagumo Model of Neuronal Network

    NASA Astrophysics Data System (ADS)

    Mischler, S.; Quiñinao, C.; Touboul, J.

    2016-03-01

    We investigate existence and uniqueness of solutions of a McKean-Vlasov evolution PDE representing the macroscopic behaviour of interacting Fitzhugh-Nagumo neurons. This equation is hypoelliptic, nonlocal and has unbounded coefficients. We prove existence of a solution to the evolution equation and non trivial stationary solutions. Moreover, we demonstrate uniqueness of the stationary solution in the weakly nonlinear regime. Eventually, using a semigroup factorisation method, we show exponential nonlinear stability in the small connectivity regime.

  12. Implications of cellular models of dopamine neurons for schizophrenia.

    PubMed

    Yu, Na; Tucker, Kristal R; Levitan, Edwin S; Shepard, Paul D; Canavier, Carmen C

    2014-01-01

    Midbrain dopamine neurons are pacemakers in vitro, but in vivo they fire less regularly and occasionally in bursts that can lead to a temporary cessation in firing produced by depolarization block. The therapeutic efficacy of antipsychotic drugs used to treat the positive symptoms of schizophrenia has been attributed to their ability to induce depolarization block within a subpopulation of dopamine neurons. We summarize the results of experiments characterizing the physiological mechanisms underlying the ability of these neurons to enter depolarization block in vitro, and our computational simulations of those experiments. We suggest that the inactivation of voltage-dependent Na(+) channels, and, in particular, the slower component of this inactivation, is critical in controlling entry into depolarization block. In addition, an ether-a-go-related gene (ERG) K(+) current also appears to be involved by delaying entry into and speeding recovery from depolarization block. Since many antipsychotic drugs share the ability to block this current, ERG channels may contribute to the therapeutic effects of these drugs. PMID:24560140

  13. A synaptic input portal for a mapped clock oscillator model of neuronal electrical rhythmic activity.

    PubMed

    Zariffa, José; Ebden, Mark; Bardakjian, Berj L

    2004-09-01

    Neuronal electrical oscillations play a central role in a variety of situations, such as epilepsy and learning. The mapped clock oscillator (MCO) model is a general model of transmembrane voltage oscillations in excitable cells. In order to be able to investigate the behaviour of neuronal oscillator populations, we present a neuronal version of the model. The neuronal MCO includes an extra input portal, the synaptic portal, which can reflect the biological relationships in a chemical synapse between the frequency of the presynaptic action potentials and the postsynaptic resting level, which in turn affects the frequency of the postsynaptic potentials. We propose that the synaptic input-output relationship must include a power function in order to be able to reproduce physiological behaviour such as resting level saturation. One linear and two power functions (Butterworth and sigmoidal) are investigated, using the case of an inhibitory synapse. The linear relation was not able to produce physiologically plausible behaviour, whereas both the power function examples were appropriate. The resulting neuronal MCO model can be tailored to a variety of neuronal cell types, and can be used to investigate complex population behaviour, such as the influence of network topology and stochastic resonance.

  14. Ciliary neurotrophic factor protects striatal output neurons in an animal model of Huntington disease.

    PubMed Central

    Anderson, K D; Panayotatos, N; Corcoran, T L; Lindsay, R M; Wiegand, S J

    1996-01-01

    Huntington disease is a dominantly inherited, untreatable neurological disorder featuring a progressive loss of striatal output neurons that results in dyskinesia, cognitive decline, and, ultimately, death. Neurotrophic factors have recently been shown to be protective in several animal models of neurodegenerative disease, raising the possibility that such substances might also sustain the survival of compromised striatal output neurons. We determined whether intracerebral administration of brain-derived neurotrophic factor, nerve growth factor, neurotrophin-3, or ciliary neurotrophic factor could protect striatal output neurons in a rodent model of Huntington disease. Whereas treatment with brain-derived neurotrophic factor, nerve growth factor, or neurotrophin-3 provided no protection of striatal output neurons from death induced by intrastriatal injection of quinolinic acid, an N-methyl-D-aspartate glutamate receptor agonist, treatment with ciliary neurotrophic factor afforded marked protection against this neurodegenerative insult. Images Fig. 1 Fig. 2 PMID:8692996

  15. Extending the mirror neuron system model, II: what did I just do? A new role for mirror neurons.

    PubMed

    Bonaiuto, James; Arbib, Michael A

    2010-04-01

    A mirror system is active both when an animal executes a class of actions (self-actions) and when it sees another execute an action of that class. Much attention has been given to the possible roles of mirror systems in responding to the actions of others but there has been little attention paid to their role in self-actions. In the companion article (Bonaiuto et al. Biol Cybern 96:9-38, 2007) we presented MNS2, an extension of the Mirror Neuron System model of the monkey mirror system trained to recognize the external appearance of its own actions as a basis for recognizing the actions of other animals when they perform similar actions. Here we further extend the study of the mirror system by introducing the novel hypotheses that a mirror system may additionally help in monitoring the success of a self-action and may also be activated by recognition of one's own apparent actions as well as efference copy from one's intended actions. The framework for this computational demonstration is a model of action sequencing, called augmented competitive queuing, in which action choice is based on the desirability of executable actions. We show how this "what did I just do?" function of mirror neurons can contribute to the learning of both executability and desirability which in certain cases supports rapid reorganization of motor programs in the face of disruptions.

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

    PubMed

    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

  17. 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

  18. 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.

  19. 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

  20. 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

  1. Sensory neurons do not induce motor neuron loss in a human stem cell model of spinal muscular atrophy.

    PubMed

    Schwab, Andrew J; Ebert, Allison D

    2014-01-01

    Spinal muscular atrophy (SMA) is an autosomal recessive disorder leading to paralysis and early death due to reduced SMN protein. It is unclear why there is such a profound motor neuron loss, but recent evidence from fly and mouse studies indicate that cells comprising the whole sensory-motor circuit may contribute to motor neuron dysfunction and loss. Here, we used induced pluripotent stem cells derived from SMA patients to test whether sensory neurons directly contribute to motor neuron loss. We generated sensory neurons from SMA induced pluripotent stem cells and found no difference in neuron generation or survival, although there was a reduced calcium response to depolarizing stimuli. Using co-culture of SMA induced pluripotent stem cell derived sensory neurons with control induced pluripotent stem cell derived motor neurons, we found no significant reduction in motor neuron number or glutamate transporter boutons on motor neuron cell bodies or neurites. We conclude that SMA sensory neurons do not overtly contribute to motor neuron loss in this human stem cell system.

  2. 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

  3. 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.

  4. 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

  5. Spinal distribution of c-Fos activated neurons expressing enkephalin in acute and chronic pain models.

    PubMed

    Hossaini, Mehdi; Duraku, Liron S; Kohli, Somesh K; Jongen, Joost L M; Holstege, Jan C

    2014-01-16

    The endogenous opioid enkephalin is known to inhibit spinal nociceptive transmission. Here we investigated activation of spinal enkephalinergic neurons by determining the proportions of c-Fos expressing (activated) spinal neurons that were enkephalinergic after different acute and chronic peripheral nociceptive stimuli. The number of c-Fos-activated neurons in the dorsal horn was increased after hind paw injection of capsaicin, formalin or complete Freund's adjuvant (CFA, 1.5 hrs - 4 days). The numbers of these neurons that were enkephalinergic increased after paraformaldehyde, and at 20 hrs, but not 1.5 hrs or 4 days post-CFA as compared to saline. In the spared nerve injury (SNI) model of neuropathic pain, c-Fos expression was increased acutely (2 hrs) and chronically (2 weeks), and a greater number of these were enkephalinergic in the nerve-injured animals acutely compared to controls (sham-SNI). Combining all acute (=2 hrs) versus chronic (≥20 hrs) treatment groups, there was a significant decrease in the percentage of activated neurons that were enkephalinergic in superficial layers, but a significant increase in the deeper layers of the dorsal horn in the chronic treatment group. It is concluded that the overall percentage of c-Fos activated neurons that contained enkephalin was not significantly different between acute and chronic pain phases. However, the shift in localization of these neurons within the spinal dorsal horn indicates a noxious stimulus directed activation pattern.

  6. Modeling Neurological Disease by Rapid Conversion of Human Urine Cells into Functional Neurons.

    PubMed

    Zhang, Shu-Zhen; Ma, Li-Xiang; Qian, Wen-Jing; Li, Hong-Fu; Wang, Zhong-Feng; Wang, Hong-Xia; Wu, Zhi-Ying

    2016-01-01

    Somatic cells can be directly converted into functional neurons by ectopic expression of defined factors and/or microRNAs. Since the first report of conversion mouse embryonic fibroblasts into functional neurons, the postnatal mouse, and human fibroblasts, astroglia, hepatocytes, and pericyte-derived cells have been converted into functional dopaminergic and motor neurons both in vitro and in vivo. However, it is invasive to get all these materials. In the current study, we provide a noninvasive approach to obtain directly reprogrammed functional neurons by overexpression of the transcription factors Ascl1, Brn2, NeuroD, c-Myc, and Myt1l in human urine cells. These induced neuronal (iN) cells could express multiple neuron-specific proteins and generate action potentials. Moreover, urine cells from Wilson's disease (WD) patient could also be directly converted into neurons. In conclusion, generation of iN cells from nonneural lineages is a feasible and befitting approach for neurological disease modeling. PMID:26770203

  7. Physiological Characterization of Vestibular Efferent Brainstem Neurons Using a Transgenic Mouse Model

    PubMed Central

    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

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. Computational modeling of seizure dynamics using coupled neuronal networks: factors shaping epileptiform activity.

    PubMed

    Naze, Sebastien; Bernard, Christophe; Jirsa, Viktor

    2015-05-01

    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

  14. 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.

  15. Squid giant axons. A model for the neuron soma?

    PubMed

    Ramón, F; Moore, J W; Joyner, R W; Westerfield, M

    1976-08-01

    Insertion of electrically floating wires along the axis of a squid giant axon produces an apparent increase in diameter in the region where the wire surface has been treated to give it a low resistance. The shape of action potentials propagating into this region depend upon the surface resistance (and the length) of the wire. As this segment's internal resistance is lowered by reducing the wire's surface resistance, the following characteristic sequence of changes in the action potential is seen at the transition region: (a) the duration increases; (b) two peaks develop, the first one generated in the normal axon region and the second one generated later in the axial wire region, and; (c) blockage occurs (for a very low resistance wire). Action potentials recorded at the membrane region near the tip of the axial wire in (b) resemble those recorded at the initial segment of neurons upon antidromic invasions. Squid axon action potentials propagated from a normal region into that containing the low resistance wire also resemble antidromic invasions recorded in neuron somas. Hyperpolarizing current pulses applied through the wire act as if the wire surface resistance was momentarily reduced. For example, the two components of the action potential recorded at the axial wire membrane region noted in (b) can be sequentially blocked by the application of increasing hyperpolarizing current through the wire. Similar effects are seen when hyperpolarizing currents are injected into motoneuron somas. It is concluded that the geometrical properties of the junction of a neuron axon with its soma may be in themselves sufficient to determine the shape of the action potentials usually recorded by microelectrodes.

  16. 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

  17. 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

  18. 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

  19. 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

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

    PubMed Central

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

    2015-01-01

    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

  1. Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

    PubMed

    Barton, Alan J; Valdés, Julio J; Orchard, Robert

    2009-01-01

    Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.

  2. 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

  3. 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

  4. A Coupled Phase-Temperature Model for Dynamics of Transient Neuronal Signal in Mammals Cold Receptor

    PubMed Central

    Kirana, Firman Ahmad; Husein, Irzaman Sulaiman

    2016-01-01

    We propose a theoretical model consisting of coupled differential equation of membrane potential phase and temperature for describing the neuronal signal in mammals cold receptor. Based on the results from previous work by Roper et al., we modified a nonstochastic phase model for cold receptor neuronal signaling dynamics in mammals. We introduce a new set of temperature adjusted functional parameters which allow saturation characteristic at high and low steady temperatures. The modified model also accommodates the transient neuronal signaling process from high to low temperature by introducing a nonlinear differential equation for the “effective temperature” changes which is coupled to the phase differential equation. This simple model can be considered as a candidate for describing qualitatively the physical mechanism of the corresponding transient process. PMID:27774102

  5. Phase synchronization of coupled bursting neurons and the generalized Kuramoto model.

    PubMed

    Ferrari, F A S; Viana, R L; Lopes, S R; Stoop, R

    2015-06-01

    Bursting neurons fire rapid sequences of action potential spikes followed by a quiescent period. The basic dynamical mechanism of bursting is the slow currents that modulate a fast spiking activity caused by rapid ionic currents. Minimal models of bursting neurons must include both effects. We considered one of these models and its relation with a generalized Kuramoto model, thanks to the definition of a geometrical phase for bursting and a corresponding frequency. We considered neuronal networks with different connection topologies and investigated the transition from a non-synchronized to a partially phase-synchronized state as the coupling strength is varied. The numerically determined critical coupling strength value for this transition to occur is compared with theoretical results valid for the generalized Kuramoto model.

  6. A Possible Role for End-Stopped V1 Neurons in the Perception of Motion: A Computational Model

    PubMed Central

    Zarei Eskikand, Parvin; Kameneva, Tatiana; Ibbotson, Michael R.; Burkitt, Anthony N.; Grayden, David B.

    2016-01-01

    We present a model of the early stages of processing in the visual cortex, in particular V1 and MT, to investigate the potential role of end-stopped V1 neurons in solving the aperture problem. A hierarchical network is used in which the incoming motion signals provided by complex V1 neurons and end-stopped V1 neurons proceed to MT neurons at the next stage. MT neurons are categorized into two types based on their function: integration and segmentation. The role of integration neurons is to propagate unambiguous motion signals arriving from those V1 neurons that emphasize object terminators (e.g. corners). Segmentation neurons detect the discontinuities in the input stimulus to control the activity of integration neurons. Although the activity of the complex V1 neurons at the terminators of the object accurately represents the direction of the motion, their level of activity is less than the activity of the neurons along the edges. Therefore, a model incorporating end-stopped neurons is essential to suppress ambiguous motion signals along the edges of the stimulus. It is shown that the unambiguous motion signals at terminators propagate over the rest of the object to achieve an accurate representation of motion. PMID:27741307

  7. Conductance-Based Neuron Models and the Slow Dynamics of Excitability

    PubMed Central

    Soudry, Daniel; Meir, Ron

    2012-01-01

    In recent experiments, synaptically isolated neurons from rat cortical culture, were stimulated with periodic extracellular fixed-amplitude current pulses for extended durations of days. The neuron’s response depended on its own history, as well as on the history of the input, and was classified into several modes. Interestingly, in one of the modes the neuron behaved intermittently, exhibiting irregular firing patterns changing in a complex and variable manner over the entire range of experimental timescales, from seconds to days. With the aim of developing a minimal biophysical explanation for these results, we propose a general scheme, that, given a few assumptions (mainly, a timescale separation in kinetics) closely describes the response of deterministic conductance-based neuron models under pulse stimulation, using a discrete time piecewise linear mapping, which is amenable to detailed mathematical analysis. Using this method we reproduce the basic modes exhibited by the neuron experimentally, as well as the mean response in each mode. Specifically, we derive precise closed-form input-output expressions for the transient timescale and firing rates, which are expressed in terms of experimentally measurable variables, and conform with the experimental results. However, the mathematical analysis shows that the resulting firing patterns in these deterministic models are always regular and repeatable (i.e., no chaos), in contrast to the irregular and variable behavior displayed by the neuron in certain regimes. This fact, and the sensitive near-threshold dynamics of the model, indicate that intrinsic ion channel noise has a significant impact on the neuronal response, and may help reproduce the experimentally observed variability, as we also demonstrate numerically. In a companion paper, we extend our analysis to stochastic conductance-based models, and show how these can be used to reproduce the details of the observed irregular and variable neuronal response

  8. Irradiation of Neurons with High-Energy Charged Particles: An In Silico Modeling Approach

    PubMed Central

    Alp, Murat; Parihar, Vipan K.; Limoli, Charles L.; Cucinotta, Francis A.

    2015-01-01

    In this work, a stochastic computational model of microscopic energy deposition events is used to study for the first time damage to irradiated neuronal cells of the mouse hippocampus. An extensive library of radiation tracks for different particle types is created to score energy deposition in small voxels and volume segments describing a neuron’s morphology that later are sampled for given particle fluence or dose. Methods included the construction of in silico mouse hippocampal granule cells from neuromorpho.org with spine and filopodia segments stochastically distributed along the dendritic branches. The model is tested with high-energy 56Fe, 12C, and 1H particles and electrons. Results indicate that the tree-like structure of the neuronal morphology and the microscopic dose deposition of distinct particles may lead to different outcomes when cellular injury is assessed, leading to differences in structural damage for the same absorbed dose. The significance of the microscopic dose in neuron components is to introduce specific local and global modes of cellular injury that likely contribute to spine, filopodia, and dendrite pruning, impacting cognition and possibly the collapse of the neuron. Results show that the heterogeneity of heavy particle tracks at low doses, compared to the more uniform dose distribution of electrons, juxtaposed with neuron morphology make it necessary to model the spatial dose painting for specific neuronal components. Going forward, this work can directly support the development of biophysical models of the modifications of spine and dendritic morphology observed after low dose charged particle irradiation by providing accurate descriptions of the underlying physical insults to complex neuron structures at the nano-meter scale. PMID:26252394

  9. Attention and working memory: a dynamical model of neuronal activity in the prefrontal cortex.

    PubMed

    Deco, Gustavo; Rolls, Edmund T

    2003-10-01

    Cognitive behaviour requires complex context-dependent mapping between sensory stimuli and actions. The same stimulus can lead to different behaviours depending on the situation, or the same behaviour may be elicited by different cueing stimuli. Neurons in the primate prefrontal cortex show task-specific firing activity during working memory delay periods. These neurons provide a neural substrate for mapping stimulus and response in a flexible, context- or rule-dependent, fashion. We describe here an integrate-and-fire network model to explain and investigate the different types of working-memory-related neuronal activity observed. The model contains different populations (or pools) of neurons (as found neurophysiologically) in attractor networks which respond in the delay period to the stimulus object, the stimulus position ('sensory pools'), to combinations of the stimulus sensory properties (e.g. the object identity or object location) and the response ('intermediate pools'), and to the response required (left or right) ('premotor pools'). The pools are arranged hierarchically, are linked by associative synaptic connections, and have global inhibition through inhibitory interneurons to implement competition. It is shown that a biasing attentional input to define the current rule applied to the intermediate pools enables the system to select the correct response in what is a biased competition model of attention. The integrate-and-fire model not only produces realistic spiking dynamicals very similar to the neuronal data but also shows how dopamine could weaken and shorten the persistent neuronal activity in the delay period; and allows us to predict more response errors when dopamine is elevated because there is less different activity in the different pools of competing neurons, resulting in more conflict.

  10. Corresponding decrease in neuronal markers signals progressive parvalbumin neuron loss in MAM schizophrenia model.

    PubMed

    Gill, Kathryn M; Grace, Anthony A

    2014-10-01

    Alteration in normal hippocampal (HPC) function attributed to reduced parvalbumin (PV) expression has been consistently reported in schizophrenia patients and in animal models of schizophrenia. However, it is unclear whether there is an overall loss of interneurons as opposed to a reduction in activity-dependent PV content. Co-expression of PV and the constitutively expressed substance P (SP)-receptor protein has been utilized in other models to ascertain the degree of cell survival, as opposed to reduction in activity-dependent PV content, in the HPC. The present study measured the co-expression of PV and SP-receptors in the dentate and dorsal and ventral CA3 subregions of the HPC in the methylazoymethanol acetate (MAM) rat neurodevelopmental model of schizophrenia. In addition, these changes were compared at the post-natal day 27 (PND27) and post-natal day 240 (PND > 240) time points. Brains from PND27 and PND > 240 MAM (n = 8) and saline (SAL, n = 8) treated offspring were immunohistochemically processed for the co-expression of PV and SP-receptors. The dorsal dentate, dorsal CA3 and ventral CA3 subregions of PND27 and PND > 240 MAM rats demonstrated significant reductions in PV but not SP-receptor expression, signifying a loss of PV-content. In contrast, in the ventral dentate the co-expression of PV and SP-receptors was significantly reduced only in PND > 240 MAM animals, suggesting a reduction in cell number. While MAM-induced reduction of PV content occurs in CA3 of dorsal and ventral HPC, the most substantial loss of interneuron number is localized to the ventral dentate of PND > 240 animals. The disparate loss of PV in HPC subregions likely impacts intra-HPC network activity in MAM rats.

  11. Structure-preserving model reduction of passive and quasi-active neurons.

    PubMed

    Hedrick, Kathryn R; Cox, Steven J

    2013-02-01

    The spatial component of input signals often carries information crucial to a neuron's function, but models mapping synaptic inputs to the transmembrane potential can be computationally expensive. Existing reduced models of the neuron either merge compartments, thereby sacrificing the spatial specificity of inputs, or apply model reduction techniques that sacrifice the underlying electrophysiology of the model. We use Krylov subspace projection methods to construct reduced models of passive and quasi-active neurons that preserve both the spatial specificity of inputs and the electrophysiological interpretation as an RC and RLC circuit, respectively. Each reduced model accurately computes the potential at the spike initiation zone (SIZ) given a much smaller dimension and simulation time, as we show numerically and theoretically. The structure is preserved through the similarity in the circuit representations, for which we provide circuit diagrams and mathematical expressions for the circuit elements. Furthermore, the transformation from the full to the reduced system is straightforward and depends on intrinsic properties of the dendrite. As each reduced model is accurate and has a clear electrophysiological interpretation, the reduced models can be used not only to simulate morphologically accurate neurons but also to examine computations performed in dendrites. PMID:22714391

  12. 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

  13. 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.

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

    PubMed

    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.

  15. Accounting for network effects in neuronal responses using L1 regularized point process models.

    PubMed

    Kelly, Ryan C; Kass, Robert E; Smith, Matthew A; Lee, Tai Sing

    2010-01-01

    Activity of a neuron, even in the early sensory areas, is not simply a function of its local receptive field or tuning properties, but depends on global context of the stimulus, as well as the neural context. This suggests the activity of the surrounding neurons and global brain states can exert considerable influence on the activity of a neuron. In this paper we implemented an L1 regularized point process model to assess the contribution of multiple factors to the firing rate of many individual units recorded simultaneously from V1 with a 96-electrode "Utah" array. We found that the spikes of surrounding neurons indeed provide strong predictions of a neuron's response, in addition to the neuron's receptive field transfer function. We also found that the same spikes could be accounted for with the local field potentials, a surrogate measure of global network states. This work shows that accounting for network fluctuations can improve estimates of single trial firing rate and stimulus-response transfer functions. PMID:22162918

  16. 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.

  17. 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

  18. 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

  19. A compensatory subpopulation of motor neurons in a mouse model of amyotrophic lateral sclerosis.

    PubMed

    Schaefer, Anneliese M; Sanes, Joshua R; Lichtman, Jeff W

    2005-09-26

    Amyotrophic lateral sclerosis is a fatal paralytic disease that targets motor neurons, leading to motor neuron death and widespread denervation atrophy of muscle. Previous electrophysiological data have shown that some motor axon branches attempt to compensate for loss of innervation, resulting in enlarged axonal arbors. Recent histological assays have shown that during the course of the disease some axonal branches die back. We thus asked whether the two types of behavior, die-back and compensatory growth, occur in different branches of single neurons or, alternatively, whether entire motor units are of one type or the other. We used high-resolution in vivo imaging in the G93A SOD1 mouse model, bred to express transgenic yellow fluorescent protein in all or subsets of motor neurons. Time-lapse imaging showed that degenerative axon branches are easily distinguished from those undergoing compensatory reinnervation, showing fragmentation of terminal branches but sparing of the more proximal axon. Reconstruction of entire motor units showed that some were abnormally large. Surprisingly, these large motor units contained few if any degenerating synapses. Some small motor units, however, no longer possessed any neuromuscular contacts at all, giving the appearance of "winter trees." Thus, degenerative versus regenerative changes are largely confined to distinct populations of neurons within the same motor pool. Identification of factors that protect "compensatory" motor neurons from degenerative changes may provide new targets for therapeutic intervention.

  20. 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

  1. Progranulin Gene Delivery Protects Dopaminergic Neurons in a Mouse Model of Parkinson’s Disease

    PubMed Central

    Van Kampen, Jackalina M.; Baranowski, David; Kay, Denis G.

    2014-01-01

    Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by tremor, rigidity and akinesia/bradykinesia resulting from the progressive loss of nigrostriatal dopaminergic neurons. To date, only symptomatic treatment is available for PD patients, with no effective means of slowing or stopping the progression of the disease. Progranulin (PGRN) is a 593 amino acid multifunction protein that is widely distributed throughout the CNS, localized primarily in neurons and microglia. PGRN has been demonstrated to be a potent regulator of neuroinflammation and also acts as an autocrine neurotrophic factor, important for long-term neuronal survival. Thus, enhancing PGRN expression may strengthen the cells resistance to disease. In the present study, we have used the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of PD to investigate the possible use of PGRN gene delivery as a therapy for the prevention or treatment of PD. Viral vector delivery of the PGRN gene was an effective means of elevating PGRN expression in nigrostriatal neurons. When PGRN expression was elevated in the SNC, nigrostriatal neurons were protected from MPTP toxicity in mice, along with a preservation of striatal dopamine content and turnover. Further, protection of nigrostriatal neurons by PGRN gene therapy was accompanied by reductions in markers of MPTP-induced inflammation and apoptosis as well as a complete preservation of locomotor function. We conclude that PGRN gene therapy may have beneficial effects in the treatment of PD. PMID:24804730

  2. The influence of potassium concentration on epileptic seizures in a coupled neuronal model in the hippocampus.

    PubMed

    Du, Mengmeng; Li, Jiajia; Wang, Rong; Wu, Ying

    2016-10-01

    Experiments on hippocampal slices have recorded that a novel pattern of epileptic seizures with alternating excitatory and inhibitory activities in the CA1 region can be induced by an elevated potassium ion (K(+)) concentration in the extracellular space between neurons and astrocytes (ECS-NA). To explore the intrinsic effects of the factors (such as glial K(+) uptake, Na(+)-K(+)-ATPase, the K(+) concentration of the bath solution, and K(+) lateral diffusion) influencing K(+) concentration in the ECS-NA on the epileptic seizures recorded in previous experiments, we present a coupled model composed of excitatory and inhibitory neurons and glia in the CA1 region. Bifurcation diagrams showing the glial K(+) uptake strength with either the Na(+)-K(+)-ATPase pump strength or the bath solution K(+) concentration are obtained for neural epileptic seizures. The K(+) lateral diffusion leads to epileptic seizure in neurons only when the synaptic conductance values of the excitatory and inhibitory neurons are within an appropriate range. Finally, we propose an energy factor to measure the metabolic demand during neuron firing, and the results show that different energy demands for the normal discharges and the pathological epileptic seizures of the coupled neurons.

  3. The influence of potassium concentration on epileptic seizures in a coupled neuronal model in the hippocampus.

    PubMed

    Du, Mengmeng; Li, Jiajia; Wang, Rong; Wu, Ying

    2016-10-01

    Experiments on hippocampal slices have recorded that a novel pattern of epileptic seizures with alternating excitatory and inhibitory activities in the CA1 region can be induced by an elevated potassium ion (K(+)) concentration in the extracellular space between neurons and astrocytes (ECS-NA). To explore the intrinsic effects of the factors (such as glial K(+) uptake, Na(+)-K(+)-ATPase, the K(+) concentration of the bath solution, and K(+) lateral diffusion) influencing K(+) concentration in the ECS-NA on the epileptic seizures recorded in previous experiments, we present a coupled model composed of excitatory and inhibitory neurons and glia in the CA1 region. Bifurcation diagrams showing the glial K(+) uptake strength with either the Na(+)-K(+)-ATPase pump strength or the bath solution K(+) concentration are obtained for neural epileptic seizures. The K(+) lateral diffusion leads to epileptic seizure in neurons only when the synaptic conductance values of the excitatory and inhibitory neurons are within an appropriate range. Finally, we propose an energy factor to measure the metabolic demand during neuron firing, and the results show that different energy demands for the normal discharges and the pathological epileptic seizures of the coupled neurons. PMID:27668019

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

    PubMed

    Liu, Kevin X; Edwards, Benjamin; Lee, Sheena; Finelli, Mattéa J; Davies, Ben; Davies, Kay E; Oliver, Peter L

    2015-05-01

    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 SOD1(G93A) 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 SOD1(G93A) 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 SOD1(G93A) 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.

  5. Phase Resetting and Phase Locking in Hybrid Circuits of One Model and One Biological Neuron

    PubMed Central

    Oprisan, S. A.; Prinz, A. A.; Canavier, C. C.

    2004-01-01

    To determine why elements of central pattern generators phase lock in a particular pattern under some conditions but not others, we tested a theoretical pattern prediction method. The method is based on the tabulated open loop pulsatile interactions of bursting neurons on a cycle-by-cycle basis and was tested in closed loop hybrid circuits composed of one bursting biological neuron and one bursting model neuron coupled using the dynamic clamp. A total of 164 hybrid networks were formed by varying the synaptic conductances. The prediction of 1:1 phase locking agreed qualitatively with the experimental observations, except in three hybrid circuits in which 1:1 locking was predicted but not observed. Correct predictions sometimes required consideration of the second order phase resetting, which measures the change in the timing of the second burst after the perturbation. The method was robust to offsets between the initiation of bursting in the presynaptic neuron and the activation of the synaptic coupling with the postsynaptic neuron. The quantitative accuracy of the predictions fell within the variability (10%) in the experimentally observed intrinsic period and phase resetting curve (PRC), despite changes in the burst duration of the neurons between open and closed loop conditions. PMID:15454430

  6. 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).

  7. 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

  8. High prevalence of multistability of rest states and bursting in a database of a model neuron.

    PubMed

    Marin, Bóris; Barnett, William H; Doloc-Mihu, Anca; Calabrese, Ronald L; Cymbalyuk, Gennady S

    2013-01-01

    Flexibility in neuronal circuits has its roots in the dynamical richness of their neurons. Depending on their membrane properties single neurons can produce a plethora of activity regimes including silence, spiking and bursting. What is less appreciated is that these regimes can coexist with each other so that a transient stimulus can cause persistent change in the activity of a given neuron. Such multistability of the neuronal dynamics has been shown in a variety of neurons under different modulatory conditions. It can play either a functional role or present a substrate for dynamical diseases. We considered a database of an isolated leech heart interneuron model that can display silent, tonic spiking and bursting regimes. We analyzed only the cases of endogenous bursters producing functional half-center oscillators (HCOs). Using a one parameter (the leak conductance (g(leak)) bifurcation analysis, we extended the database to include silent regimes (stationary states) and systematically classified cases for the coexistence of silent and bursting regimes. We showed that different cases could exhibit two stable depolarized stationary states and two hyperpolarized stationary states in addition to various spiking and bursting regimes. We analyzed all cases of endogenous bursters and found that 18% of the cases were multistable, exhibiting coexistences of stationary states and bursting. Moreover, 91% of the cases exhibited multistability in some range of g(leak). We also explored HCOs built of multistable neuron cases with coexisting stationary states and a bursting regime. In 96% of cases analyzed, the HCOs resumed normal alternating bursting after one of the neurons was reset to a stationary state, proving themselves robust against this perturbation.

  9. Computational connectionism within neurons: A model of cytoskeletal automata subserving neural networks

    NASA Astrophysics Data System (ADS)

    Rasmussen, Steen; Karampurwala, Hasnain; Vaidyanath, Rajesh; Jensen, Klaus S.; Hameroff, Stuart

    1990-06-01

    “Neural network” models of brain function assume neurons and their synaptic connections to be the fundamental units of information processing, somewhat like switches within computers. However, neurons and synapses are extremely complex and resemble entire computers rather than switches. The interiors of the neurons (and other eucaryotic cells) are now known to contain highly ordered parallel networks of filamentous protein polymers collectively termed the cytoskeleton. Originally assumed to provide merely structural “bone-like” support, cytoskeletal structures such as microtubules are now recognized to organize cell interiors dynamically. The cytoskeleton is the internal communication network for the eucaryotic cell, both by means of simple transport and by means of coordinating extremely complicated events like cell division, growth and differentiation. The cytoskeleton may therefore be viewed as the cell's “nervous system”. Consequently the neuronal cytoskeleton may be involved in molecular level information processing which subserves higher, collective neuronal functions ultimately relating to cognition. Numerous models of information processing within the cytoskeleton (in particular, microtubules) have been proposed. We have utilized cellular automata as a means to model and demonstrate the potential for information processing in cytoskeletal microtubules. In this paper, we extend previous work and simulate associative learning in a cytoskeletal network as well as assembly and disassembly of microtubules. We also discuss possible relevance and implications of cytoskeletal information processing to cognition.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. Oscillations and spiking pairs: behavior of a neuronal model with STDP learning.

    PubMed

    Shen, Xi; Lin, Xiaobin; De Wilde, Philippe

    2008-08-01

    In a biologically plausible but computationally simplified integrate-and-fire neuronal population, it is observed that transient synchronized spikes can occur repeatedly. However, groups with different properties exhibit different periods and different patterns of synchrony. We include learning mechanisms in these models. The effects of spike-timing-dependent plasticity have been known to play a distinct role in information processing in the central nervous system for several years. In this letter, neuronal models with dynamical synapses are constructed, and we analyze the effect of STDP on collective network behavior, such as oscillatory activity, weight distribution, and spike timing precision. We comment on how information is encoded by the neuronal signaling, when synchrony groups may appear, and what could contribute to the uncertainty in decision making. PMID:18336082

  15. Fast and accurate low-dimensional reduction of biophysically detailed neuron models.

    PubMed

    Marasco, Addolorata; Limongiello, Alessandro; Migliore, Michele

    2012-01-01

    Realistic modeling of neurons are quite successful in complementing traditional experimental techniques. However, their networks require a computational power beyond the capabilities of current supercomputers, and the methods used so far to reduce their complexity do not take into account the key features of the cells nor critical physiological properties. Here we introduce a new, automatic and fast method to map realistic neurons into equivalent reduced models running up to > 40 times faster while maintaining a very high accuracy of the membrane potential dynamics during synaptic inputs, and a direct link with experimental observables. The mapping of arbitrary sets of synaptic inputs, without additional fine tuning, would also allow the convenient and efficient implementation of a new generation of large-scale simulations of brain regions reproducing the biological variability observed in real neurons, with unprecedented advances to understand higher brain functions. PMID:23226594

  16. Fast and accurate low-dimensional reduction of biophysically detailed neuron models.

    PubMed

    Marasco, Addolorata; Limongiello, Alessandro; Migliore, Michele

    2012-01-01

    Realistic modeling of neurons are quite successful in complementing traditional experimental techniques. However, their networks require a computational power beyond the capabilities of current supercomputers, and the methods used so far to reduce their complexity do not take into account the key features of the cells nor critical physiological properties. Here we introduce a new, automatic and fast method to map realistic neurons into equivalent reduced models running up to > 40 times faster while maintaining a very high accuracy of the membrane potential dynamics during synaptic inputs, and a direct link with experimental observables. The mapping of arbitrary sets of synaptic inputs, without additional fine tuning, would also allow the convenient and efficient implementation of a new generation of large-scale simulations of brain regions reproducing the biological variability observed in real neurons, with unprecedented advances to understand higher brain functions.

  17. 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

  18. Disruption of neuronal function by soluble hyperphosphorylated tau in a Drosophila model of tauopathy.

    PubMed

    Cowan, Catherine M; Chee, Francis; Shepherd, David; Mudher, Amritpal

    2010-04-01

    Axonal microtubules are essential for transport of materials to the synapse. Compromised microtubules and synaptic loss have been demonstrated in AD (Alzheimer's disease), which is believed to contribute to cognitive dysfunction before neuronal death in the early stages of the disease. The mechanism by which hyperphosphorylated tau, the building block of neurofibrillary tangles, one of the pathological hallmarks of AD, disrupts neuronal and synaptic function is unclear. There is a theory that hyperphosphorylated tau does not bind effectively to microtubules and is no longer able to function in stabilizing them, thus axonal transport can no longer proceed efficiently. This leads to synaptic dysfunction. We have tested this theory in a Drosophila model of tauopathies in which we expressed human tau (h-tau). Using this model, we have tested all aspects of this hypothesis and have demonstrated that axonal transport does become compromised in the presence of hyperphosphorylated h-tau and this leads to synaptic and behavioural defects. We are currently investigating the mechanism by which hyperphosphorylated h-tau mediates this effect and are preliminary data indicate that this entails phospho-tau-mediated effects that are predicted by the tau-microtubule hypothesis, as well as novel effects. These deleterious effects of h-tau occur in the absence of tau filaments and before neuronal death. This sequence of pathogenic events may constitute the mechanism by which abnormal tau disrupts neuronal and synaptic function and contributes to cognitive impairment before neuronal death in the early stages of tauopathies such as AD. PMID:20298222

  19. 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

  20. Selective degeneration of septal and hippocampal GABAergic neurons in a mouse model of amyloidosis and tauopathy.

    PubMed

    Loreth, Desirée; Ozmen, Laurence; Revel, Florent G; Knoflach, Frédéric; Wetzel, Philine; Frotscher, Michael; Metzger, Friedrich; Kretz, Oliver

    2012-07-01

    Alzheimer's disease (AD) is a neurodegenerative disorder characterized by brain accumulation of amyloid-β peptide and neurofibrillary tangles, which are believed to initiate a pathological cascade that results in progressive impairment of cognitive functions and eventual neuronal death. To obtain a mouse model displaying the typical AD histopathology of amyloidosis and tauopathy, we generated a triple-transgenic mouse line (TauPS2APP) by overexpressing human mutations of the amyloid precursor protein, presenilin2 and tau genes. Stereological analysis of TauPS2APP mice revealed significant neurodegeneration of GABAergic septo-hippocampal projection neurons as well as their target cells, the GABAergic hippocampal interneurons. In contrast, the cholinergic medial septum neurons remained unaffected. Moreover, the degeneration of hippocampal GABAergic interneurons was dependent on the hippocampal subfield and interneuronal subtype investigated, whereby the dentate gyrus and the NPY-positive interneurons, respectively, were most strongly affected. Neurodegeneration was also accompanied by a change in the mRNA expression of markers for inhibitory interneurons. In line with the loss of inhibitory neurons, we observed functional changes in TauPS2APP mice relative to WT mice, with strongly enhanced long-term potentiation in the medial-perforant pathway input to the dentate gyrus, and stereotypic hyperactivity. Our data indicate that inhibitory neurons are the targets of neurodegeneration in a mouse model of amyloidosis and tauopathy, thus pointing to a possible role of the inhibitory network in the pathophysiological and functional cascade of Alzheimer's disease.

  1. 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

  2. Hopf bifurcation of an (n + 1) -neuron bidirectional associative memory neural network model with delays.

    PubMed

    Xiao, Min; Zheng, Wei Xing; Cao, Jinde

    2013-01-01

    Recent studies on Hopf bifurcations of neural networks with delays are confined to simplified neural network models consisting of only two, three, four, five, or six neurons. It is well known that neural networks are complex and large-scale nonlinear dynamical systems, so the dynamics of the delayed neural networks are very rich and complicated. Although discussing the dynamics of networks with a few neurons may help us to understand large-scale networks, there are inevitably some complicated problems that may be overlooked if simplified networks are carried over to large-scale networks. In this paper, a general delayed bidirectional associative memory neural network model with n + 1 neurons is considered. By analyzing the associated characteristic equation, the local stability of the trivial steady state is examined, and then the existence of the Hopf bifurcation at the trivial steady state is established. By applying the normal form theory and the center manifold reduction, explicit formulae are derived to determine the direction and stability of the bifurcating periodic solution. Furthermore, the paper highlights situations where the Hopf bifurcations are particularly critical, in the sense that the amplitude and the period of oscillations are very sensitive to errors due to tolerances in the implementation of neuron interconnections. It is shown that the sensitivity is crucially dependent on the delay and also significantly influenced by the feature of the number of neurons. Numerical simulations are carried out to illustrate the main results.

  3. 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.

  4. 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

  5. Silencing neuronal mutant androgen receptor in a mouse model of spinal and bulbar muscular atrophy.

    PubMed

    Sahashi, Kentaro; Katsuno, Masahisa; Hung, Gene; Adachi, Hiroaki; Kondo, Naohide; Nakatsuji, Hideaki; Tohnai, Genki; Iida, Madoka; Bennett, C Frank; Sobue, Gen

    2015-11-01

    Spinal and bulbar muscular atrophy (SBMA), an adult-onset neurodegenerative disease that affects males, results from a CAG triplet repeat/polyglutamine expansions in the androgen receptor (AR) gene. Patients develop progressive muscular weakness and atrophy, and no effective therapy is currently available. The tissue-specific pathogenesis, especially relative pathological contributions between degenerative motor neurons and muscles, remains inconclusive. Though peripheral pathology in skeletal muscle caused by toxic AR protein has been recently reported to play a pivotal role in the pathogenesis of SBMA using mouse models, the role of motor neuron degeneration in SBMA has not been rigorously investigated. Here, we exploited synthetic antisense oligonucleotides to inhibit the RNA levels of mutant AR in the central nervous system (CNS) and explore its therapeutic effects in our SBMA mouse model that harbors a mutant AR gene with 97 CAG expansions and characteristic SBMA-like neurogenic phenotypes. A single intracerebroventricular administration of the antisense oligonucleotides in the presymptomatic phase efficiently suppressed the mutant gene expression in the CNS, and delayed the onset and progression of motor dysfunction, improved body weight gain and survival with the amelioration of neuronal histopathology in motor units such as spinal motor neurons, neuromuscular junctions and skeletal muscle. These findings highlight the importance of the neurotoxicity of mutant AR protein in motor neurons as a therapeutic target.

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. 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...

  14. Approaches and tools for modeling signaling pathways and calcium dynamics in neurons

    PubMed Central

    Blackwell, KT

    2013-01-01

    Signaling pathways are cascades of intracellular biochemical reactions that are activated by transmembrane receptors, and ultimately lead to transcription in the nucleus. In neurons, both calcium permeable synaptic and ionic channels as well as G protein coupled receptors initiate activation of signaling pathway molecules that interact with electrical activity at multiple spatial and time scales. At small temporal and spatial scales, calcium modifies the properties of ionic channels, whereas at larger temporal and spatial scales, various kinases and phosphatases modify the properties of ionic channels, producing phenomena such as synaptic plasticity and homeostatic plasticity. The elongated structure of neuronal dendrites and the organization of multi-protein complexes by anchoring proteins implies that the spatial dimension must be explicit. Therefore, modeling signaling pathways in neurons utilizes algorithms for both diffusion and reactions. The small size of spines coupled with small concentrations of some molecules implies that some reactions occur stochastically. The need for stochastic simulation of many reaction and diffusion events coupled with the multiple temporal and spatial scales makes modeling of signaling pathways a difficult problem. Several different software programs have achieved different aspects of these capabilities. This review explains some of the mathematical formulas used for modeling reactions and diffusion. In addition, it briefly presents the simulators used for modeling reaction-diffusion systems in neurons, together with scientific problems addressed. PMID:23743449

  15. 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

  16. 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.

  17. 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

  18. Morphological alterations in neocortical and cerebellar GABAergic neurons in a canine model of juvenile Batten disease.

    PubMed

    March, P A; Wurzelmann, S; Walkley, S U

    1995-06-01

    The pathogenesis of brain dysfunction in a canine model of juvenile Batten disease was studied with techniques designed to determine sequential changes in mitochondrial morphology and cytochrome oxidase (CO) activity, and in neurons and synapses using gamma-aminobutyric acid (GABA) as a neurotransmitter. Histochemical and immunocytochemical methods were employed. Mitochondrial alterations were found in a select population of nonpyramidal neurons in neocortex and claustrum, and in cerebellar basket cells. Proportions of affected neurons at any one time remained constant over the disease course, with morphologically-abnormal mitochondria first being recognized at age 6 months. Enlarged mitochondria were readily identifiable at the light microscope (LM) level as large CO-positive or mitochondrial antibody-positive granular structures. Colabelling with antibodies to GABA or to parvalbumin (PV) indicated that most of these cells were GABAergic. Ultrastructurally, atypical mitochondria were characterized by globular enlargement, intramitochondrial membranous inclusions, and disorganized internal structure. CO activity in all other cell somata and in neuropil was diminished compared with normal, age-matched tissue. Glutamic acid decarboxylase (GAD), PV, and GABA studies demonstrated loss of GABAergic neurons and synapses in cortex and cerebellum of affected dogs. These results indicate that abnormal mitochondria are present in neurons in Batten disease, and suggest that suboptimal mitochondrial function may play a role in the pathogenic mechanisms of brain dysfunction in this disorder.

  19. 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

  20. 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

  1. 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

  2. Dopaminergic neurons generated from monkey embryonic stem cells function in a Parkinson primate model.

    PubMed

    Takagi, Yasushi; Takahashi, Jun; Saiki, Hidemoto; Morizane, Asuka; Hayashi, Takuya; Kishi, Yo; Fukuda, Hitoshi; Okamoto, Yo; Koyanagi, Masaomi; Ideguchi, Makoto; Hayashi, Hideki; Imazato, Takayuki; Kawasaki, Hiroshi; Suemori, Hirofumi; Omachi, Shigeki; Iida, Hidehiko; Itoh, Nobuyuki; Nakatsuji, Norio; Sasai, Yoshiki; Hashimoto, Nobuo

    2005-01-01

    Parkinson disease (PD) is a neurodegenerative disorder characterized by loss of midbrain dopaminergic (DA) neurons. ES cells are currently the most promising donor cell source for cell-replacement therapy in PD. We previously described a strong neuralizing activity present on the surface of stromal cells, named stromal cell-derived inducing activity (SDIA). In this study, we generated neurospheres composed of neural progenitors from monkey ES cells, which are capable of producing large numbers of DA neurons. We demonstrated that FGF20, preferentially expressed in the substantia nigra, acts synergistically with FGF2 to increase the number of DA neurons in ES cell-derived neurospheres. We also analyzed the effect of transplantation of DA neurons generated from monkey ES cells into 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-treated (MPTP-treated) monkeys, a primate model for PD. Behavioral studies and functional imaging revealed that the transplanted cells functioned as DA neurons and attenuated MPTP-induced neurological symptoms.

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

    PubMed

    Elbasiouny, Sherif M

    2014-12-01

    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.

  4. Computational models of neuron-astrocyte interactions lead to improved efficacy in the performance of neural networks.

    PubMed

    Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B

    2012-01-01

    The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem. PMID:22649480

  5. Computational Models of Neuron-Astrocyte Interactions Lead to Improved Efficacy in the Performance of Neural Networks

    PubMed Central

    Alvarellos-González, Alberto; Pazos, Alejandro; Porto-Pazos, Ana B.

    2012-01-01

    The importance of astrocytes, one part of the glial system, for information processing in the brain has recently been demonstrated. Regarding information processing in multilayer connectionist systems, it has been shown that systems which include artificial neurons and astrocytes (Artificial Neuron-Glia Networks) have well-known advantages over identical systems including only artificial neurons. Since the actual impact of astrocytes in neural network function is unknown, we have investigated, using computational models, different astrocyte-neuron interactions for information processing; different neuron-glia algorithms have been implemented for training and validation of multilayer Artificial Neuron-Glia Networks oriented toward classification problem resolution. The results of the tests performed suggest that all the algorithms modelling astrocyte-induced synaptic potentiation improved artificial neural network performance, but their efficacy depended on the complexity of the problem. PMID:22649480

  6. Network dynamics in nociceptive pathways assessed by the neuronal avalanche model

    PubMed Central

    2012-01-01

    Background Traditional electroencephalography provides a critical assessment of pain responses. The perception of pain, however, may involve a series of signal transmission pathways in higher cortical function. Recent studies have shown that a mathematical method, the neuronal avalanche model, may be applied to evaluate higher-order network dynamics. The neuronal avalanche is a cascade of neuronal activity, the size distribution of which can be approximated by a power law relationship manifested by the slope of a straight line (i.e., the α value). We investigated whether the neuronal avalanche could be a useful index for nociceptive assessment. Findings Neuronal activity was recorded with a 4 × 8 multichannel electrode array in the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC). Under light anesthesia, peripheral pinch stimulation increased the slope of the α value in both the ACC and S1, whereas brush stimulation increased the α value only in the S1. The increase in α values was blocked in both regions under deep anesthesia. The increase in α values in the ACC induced by peripheral pinch stimulation was blocked by medial thalamic lesion, but the increase in α values in the S1 induced by brush and pinch stimulation was not affected. Conclusions The neuronal avalanche model shows a critical state in the cortical network for noxious-related signal processing. The α value may provide an index of brain network activity that distinguishes the responses to somatic stimuli from the control state. These network dynamics may be valuable for the evaluation of acute nociceptive processes and may be applied to chronic pathological pain conditions. PMID:22537828

  7. Impact of infralimbic inputs on intercalated amygdala neurons: A biophysical modeling study

    PubMed Central

    Li, Guoshi; Amano, Taiju; Pare, Denis; Nair, Satish S.

    2011-01-01

    Intercalated (ITC) amygdala neurons regulate fear expression by controlling impulse traffic between the input (basolateral amygdala; BLA) and output (central nucleus; Ce) stations of the amygdala for conditioned fear responses. Previously, stimulation of the infralimbic (IL) cortex was found to reduce fear expression and the responsiveness of Ce neurons to BLA inputs. These effects were hypothesized to result from the activation of ITC cells projecting to Ce. However, ITC cells inhibit each other, leading to the question of how IL inputs could overcome the inter-ITC inhibition to regulate the responses of Ce neurons to aversive conditioned stimuli (CSs). To investigate this, we first developed a compartmental model of a single ITC cell that could reproduce their bistable electroresponsive properties, as observed experimentally. Next, we generated an ITC network that implemented the experimentally observed short-term synaptic plasticity of inhibitory inter-ITC connections. Model experiments showed that strongly adaptive CS-related BLA inputs elicited persistent responses in ITC cells despite the presence of inhibitory interconnections. The sustained CS-evoked activity of ITC cells resulted from an unusual slowly deinactivating K+ current. Finally, over a wide range of stimulation strengths, brief IL activation caused a marked increase in the firing rate of ITC neurons, leading to a persistent decrease in Ce output, despite inter-ITC inhibition. Simulations revealed that this effect depended on the bistable properties and synaptic heterogeneity of ITC neurons. These results support the notion that IL inputs are in a strategic position to control extinction of conditioned fear via the activation of ITC neurons. PMID:21436395

  8. 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

  9. Development of a model system for neuronal dysfunction in Fabry disease.

    PubMed

    Kaneski, Christine R; Brady, Roscoe O; Hanover, John A; Schueler, Ulrike H

    2016-09-01

    Fabry disease is a glycosphingolipid storage disorder that is caused by a genetic deficiency of the enzyme alpha-galactosidase A (AGA, EC 3.2.1.22). It is a multisystem disease that affects the vascular, cardiac, renal, and nervous systems. One of the hallmarks of this disorder is neuropathic pain and sympathetic and parasympathetic nervous dysfunction. The exact mechanism by which changes in AGA activity result in change in neuronal function is not clear, partly due to of a lack of relevant model systems. In this study, we report the development of an in vitro model system to study neuronal dysfunction in Fabry disease by using short-hairpin RNA to create a stable knock-down of AGA in the human cholinergic neuronal cell line, LA-N-2. We show that gene-silenced cells show specifically reduced AGA activity and store globotriaosylceramide. In gene-silenced cells, release of the neurotransmitter acetylcholine is significantly reduced, demonstrating that this model may be used to study specific neuronal functions such as neurotransmitter release in Fabry disease. PMID:27471012

  10. Generalized rate-code model for neuron ensembles with finite populations

    SciTech Connect

    Hasegawa, Hideo

    2007-05-15

    We have proposed a generalized Langevin-type rate-code model subjected to multiplicative noise, in order to study stationary and dynamical properties of an ensemble containing a finite number N of neurons. Calculations using the Fokker-Planck equation have shown that, owing to the multiplicative noise, our rate model yields various kinds of stationary non-Gaussian distributions such as {gamma}, inverse-Gaussian-like, and log-normal-like distributions, which have been experimentally observed. The dynamical properties of the rate model have been studied with the use of the augmented moment method (AMM), which was previously proposed by the author from a macroscopic point of view for finite-unit stochastic systems. In the AMM, the original N-dimensional stochastic differential equations (DEs) are transformed into three-dimensional deterministic DEs for the means and fluctuations of local and global variables. The dynamical responses of the neuron ensemble to pulse and sinusoidal inputs calculated by the AMM are in good agreement with those obtained by direct simulation. The synchronization in the neuronal ensemble is discussed. The variabilities of the firing rate and of the interspike interval are shown to increase with increasing magnitude of multiplicative noise, which may be a conceivable origin of the observed large variability in cortical neurons.

  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. Modeling study of the light stimulation of a neuron cell with channelrhodopsin-2 mutants.

    PubMed

    Grossman, Nir; Nikolic, Konstantin; Toumazou, Christofer; Degenaar, Patrick

    2011-06-01

    Channelrhodopsin-2 (ChR2) has become a widely used tool for stimulating neurons with light. Nevertheless, the underlying dynamics of the ChR2-evoked spikes are still not yet fully understood. Here, we develop a model that describes the response of ChR2-expressing neurons to light stimuli and use the model to explore the light-to-spike process. We show that an optimal stimulation yield is achieved when the optical energies are delivered in short pulses. The model allows us to theoretically examine the effects of using various types of ChR2 mutants. We show that while increasing the lifetime and shuttering speed of ChR2 have limited effect, reducing the threshold irradiance by increased conductance will eliminate adaptation and allow constant dynamic range. The model and the conclusion presented in this study can help to interpret experimental results, design illumination protocols, and seek improvement strategies in the nascent optogenetic field.

  13. Selective disruption of acetylcholine synthesis in subsets of motor neurons: a new model of late-onset motor neuron disease.

    PubMed

    Lecomte, Marie-José; Bertolus, Chloé; Santamaria, Julie; Bauchet, Anne-Laure; Herbin, Marc; Saurini, Françoise; Misawa, Hidemi; Maisonobe, Thierry; Pradat, Pierre-François; Nosten-Bertrand, Marika; Mallet, Jacques; Berrard, Sylvie

    2014-05-01

    Motor neuron diseases are characterized by the selective chronic dysfunction of a subset of motor neurons and the subsequent impairment of neuromuscular function. To reproduce in the mouse these hallmarks of diseases affecting motor neurons, we generated a mouse line in which ~40% of motor neurons in the spinal cord and the brainstem become unable to sustain neuromuscular transmission. These mice were obtained by conditional knockout of the gene encoding choline acetyltransferase (ChAT), the biosynthetic enzyme for acetylcholine. The mutant mice are viable and spontaneously display abnormal phenotypes that worsen with age including hunched back, reduced lifespan, weight loss, as well as striking deficits in muscle strength and motor function. This slowly progressive neuromuscular dysfunction is accompanied by muscle fiber histopathological features characteristic of neurogenic diseases. Unexpectedly, most changes appeared with a 6-month delay relative to the onset of reduction in ChAT levels, suggesting that compensatory mechanisms preserve muscular function for several months and then are overwhelmed. Deterioration of mouse phenotype after ChAT gene disruption is a specific aging process reminiscent of human pathological situations, particularly among survivors of paralytic poliomyelitis. These mutant mice may represent an invaluable tool to determine the sequence of events that follow the loss of function of a motor neuron subset as the disease progresses, and to evaluate therapeutic strategies. They also offer the opportunity to explore fundamental issues of motor neuron biology.

  14. Selective disruption of acetylcholine synthesis in subsets of motor neurons: a new model of late-onset motor neuron disease.

    PubMed

    Lecomte, Marie-José; Bertolus, Chloé; Santamaria, Julie; Bauchet, Anne-Laure; Herbin, Marc; Saurini, Françoise; Misawa, Hidemi; Maisonobe, Thierry; Pradat, Pierre-François; Nosten-Bertrand, Marika; Mallet, Jacques; Berrard, Sylvie

    2014-05-01

    Motor neuron diseases are characterized by the selective chronic dysfunction of a subset of motor neurons and the subsequent impairment of neuromuscular function. To reproduce in the mouse these hallmarks of diseases affecting motor neurons, we generated a mouse line in which ~40% of motor neurons in the spinal cord and the brainstem become unable to sustain neuromuscular transmission. These mice were obtained by conditional knockout of the gene encoding choline acetyltransferase (ChAT), the biosynthetic enzyme for acetylcholine. The mutant mice are viable and spontaneously display abnormal phenotypes that worsen with age including hunched back, reduced lifespan, weight loss, as well as striking deficits in muscle strength and motor function. This slowly progressive neuromuscular dysfunction is accompanied by muscle fiber histopathological features characteristic of neurogenic diseases. Unexpectedly, most changes appeared with a 6-month delay relative to the onset of reduction in ChAT levels, suggesting that compensatory mechanisms preserve muscular function for several months and then are overwhelmed. Deterioration of mouse phenotype after ChAT gene disruption is a specific aging process reminiscent of human pathological situations, particularly among survivors of paralytic poliomyelitis. These mutant mice may represent an invaluable tool to determine the sequence of events that follow the loss of function of a motor neuron subset as the disease progresses, and to evaluate therapeutic strategies. They also offer the opportunity to explore fundamental issues of motor neuron biology. PMID:24486622

  15. 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

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

    PubMed

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

    2014-07-15

    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.

  17. An artificial network model for estimating the network structure underlying partially observed neuronal signals.

    PubMed

    Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

    2014-01-01

    Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed.

  18. 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

  19. 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

  20. Hippocampal neuron firing and local field potentials in the in vitro 4-aminopyridine epilepsy model

    PubMed Central

    Wang, Jing; Queenan, Bridget N.; Avoli, Massimo; Vicini, Stefano; Dzakpasu, Rhonda

    2012-01-01

    Excessive synchronous neuronal activity is a defining feature of epileptic activity. We previously characterized the properties of distinct glutamatergic and GABAergic transmission-dependent synchronous epileptiform discharges in mouse hippocampal slices using the 4-aminopyridine model of epilepsy. In the present study, we sought to identify the specific hippocampal neuronal populations that initiate and underlie these local field potentials (LFPs). A perforated multielectrode array was used to simultaneously record multiunit action potential firing and LFPs during spontaneous epileptiform activity. LFPs had distinct components based on the initiation site, extent of propagation, and pharmacological sensitivity. Individual units, located in different hippocampal subregions, fired action potentials during these LFPs. A specific neuron subgroup generated sustained action potential firing throughout the various components of the LFPs. The activity of this subgroup preceded the LFPs observed in the presence of antagonists of ionotropic glutamatergic synaptic transmission. In the absence of ionotropic glutamatergic and GABAergic transmission, LFPs disappeared, but units with shorter spike duration and high basal firing rates were still active. These spontaneously active units had an increased level of activity during LFPs and consistently preceded all LFPs recorded before blockade of synaptic transmission. Our findings reveal that neuronal subpopulations with interneuron properties are likely responsible for initiating synchronous activity in an in vitro model of epileptiform discharges. PMID:22972961

  1. 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

    2015-12-09

    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.

  2. 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

  3. 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

  4. Adaptive control of 2-wheeled balancing robot by cerebellar neuronal network model.

    PubMed

    Tanaka, Yoshiyuki; Ohata, Yohei; Kawamoto, Tomohiro; Hirata, Yutaka

    2010-01-01

    A new adaptive motor controller was constructed, and tested on the control of a 2-wheeled balancing robot in simulation and real world. The controller consists of a feedback (PD) controller and a cerebellar neuronal network model. The structure of the cerebellar model was configured based upon known anatomical neuronal connection in the cerebellar cortex. Namely it consists of 120 granular (Gr) cells, 1 Golgi cell, 6 basket/stellate cells, and 1 Purkinje (Pk) cell. Each cell is described by a typical artificial neuron model that outputs a weighted sum of inputs after a sigmoidal nonlinear transformation. The 2 components of the proposed controller work in parallel, in a way that the cerebellar model adaptively modifies the synaptic weights between Gr and Pk as in the real cerebellum to minimize the output of the PD controller. We demonstrate that the proposed controller successfully controls a 2-wheeled balancing robot, and the cerebellar model rapidly takes over the PD controller in simulation. We also show that an abrupt load change on the robot, which the PD controller alone cannot compensate for, can be adaptively compensated by the cerebellar model. We further confirmed that the proposed controller can be applied to the control of the robot in real world.

  5. A Novel Multiple Objective Optimization Framework for Constraining Conductance-Based Neuron Models by Experimental Data

    PubMed Central

    Druckmann, Shaul; Banitt, Yoav; Gidon, Albert; Schürmann, Felix; Markram, Henry; Segev, Idan

    2007-01-01

    We present a novel framework for automatically constraining parameters of compartmental models of neurons, given a large set of experimentally measured responses of these neurons. In experiments, intrinsic noise gives rise to a large variability (e.g., in firing pattern) in the voltage responses to repetitions of the exact same input. Thus, the common approach of fitting models by attempting to perfectly replicate, point by point, a single chosen trace out of the spectrum of variable responses does not seem to do justice to the data. In addition, finding a single error function that faithfully characterizes the distance between two spiking traces is not a trivial pursuit. To address these issues, one can adopt a multiple objective optimization approach that allows the use of several error functions jointly. When more than one error function is available, the comparison between experimental voltage traces and model response can be performed on the basis of individual features of interest (e.g., spike rate, spike width). Each feature can be compared between model and experimental mean, in units of its experimental variability, thereby incorporating into the fitting this variability. We demonstrate the success of this approach, when used in conjunction with genetic algorithm optimization, in generating an excellent fit between model behavior and the firing pattern of two distinct electrical classes of cortical interneurons, accommodating and fast-spiking. We argue that the multiple, diverse models generated by this method could serve as the building blocks for the realistic simulation of large neuronal networks. PMID:18982116

  6. 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

  7. 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

  8. 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

  9. 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.

  10. Computer Modelling of Functional Aspects of Noise in Endogenously Oscillating Neurons

    NASA Astrophysics Data System (ADS)

    Huber, M. T.; Dewald, M.; Voigt, K.; Braun, H. A.; Moss, F.

    1998-03-01

    Membrane potential oscillations are a widespread feature of neuronal activity. When such oscillations operate close to the spike-triggering threshold, noise can become an essential property of spike-generation. According to that, we developed a minimal Hodgkin-Huxley-type computer model which includes a noise term. This model accounts for experimental data from quite different cells ranging from mammalian cortical neurons to fish electroreceptors. With slight modifications of the parameters, the model's behavior can be tuned to bursting activity, which additionally allows it to mimick temperature encoding in peripheral cold receptors including transitions to apparently chaotic dynamics as indicated by methods for the detection of unstable periodic orbits. Under all conditions, cooperative effects between noise and nonlinear dynamics can be shown which, beyond stochastic resonance, might be of functional significance for stimulus encoding and neuromodulation.

  11. Bayesian Inference for Generalized Linear Models for Spiking Neurons

    PubMed Central

    Gerwinn, Sebastian; Macke, Jakob H.; Bethge, Matthias

    2010-01-01

    Generalized Linear Models (GLMs) are commonly used statistical methods for modelling the relationship between neural population activity and presented stimuli. When the dimension of the parameter space is large, strong regularization has to be used in order to fit GLMs to datasets of realistic size without overfitting. By imposing properly chosen priors over parameters, Bayesian inference provides an effective and principled approach for achieving regularization. Here we show how the posterior distribution over model parameters of GLMs can be approximated by a Gaussian using the Expectation Propagation algorithm. In this way, we obtain an estimate of the posterior mean and posterior covariance, allowing us to calculate Bayesian confidence intervals that characterize the uncertainty about the optimal solution. From the posterior we also obtain a different point estimate, namely the posterior mean as opposed to the commonly used maximum a posteriori estimate. We systematically compare the different inference techniques on simulated as well as on multi-electrode recordings of retinal ganglion cells, and explore the effects of the chosen prior and the performance measure used. We find that good performance can be achieved by choosing an Laplace prior together with the posterior mean estimate. PMID:20577627

  12. Mode locking in a periodically forced integrate-and-fire-or-burst neuron model

    NASA Astrophysics Data System (ADS)

    Coombes, S.; Owen, M. R.; Smith, G. D.

    2001-10-01

    The minimal ``integrate-and-fire-or-burst'' (IFB) neuron model reproduces the salient features of experimentally observed thalamocortical relay neuron response properties, including the temporal tuning of both tonic spiking (i.e., conventional action potentials) and post-inhibitory rebound bursting mediated by the low-threshold Ca2+ current, IT. In previous work focusing on experimental and IFB model responses to sinusoidal current injection, large regions of stimulus parameter space were observed for which the response was entrained to periodic applied current, resulting in repetitive burst, tonic, or mixed (i.e., burst followed by tonic) responses. Here we present an exact analysis of such mode-locking in the integrate-and-fire-or-burst model under the influence of arbitrary periodic forcing that includes sinusoidally driven responses as one case. In this analysis, the instabilities of mode-locked states are identified as both smooth bifurcations of an associated firing time map and nonsmooth bifurcations of the underlying discontinuous flow. The explicit construction of borders in parameter space that define the instabilities of mode-locked zones is used to build up the Arnol'd tongue structure for the model. The zones for mode-locking are shown to be in excellent agreement with numerical simulations and are used to explore the observed stimulus dependence of burst versus tonic response of the IFB neuron model.

  13. 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

  14. 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

  15. Electrodiffusive model for astrocytic and neuronal ion concentration dynamics.

    PubMed

    Halnes, Geir; Ostby, 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

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

    PubMed

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

    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

  17. Analysis of dopaminergic neuronal dysfunction in genetic and toxin-induced models of Parkinson's disease in Drosophila.

    PubMed

    Navarro, Juan A; Heßner, Sabina; Yenisetti, Sarat C; Bayersdorfer, Florian; Zhang, Li; Voigt, Aaron; Schneuwly, Stephan; Botella, Jose A

    2014-11-01

    Drosophila melanogaster has contributed significantly to the understanding of disease mechanisms in Parkinson's disease (PD) as it is one of the very few PD model organisms that allow the study of age-dependent behavioral defects, physiology and histology, and genetic interactions among different PD-related genes. However, there have been contradictory results from a number of recent reports regarding the loss of dopaminergic neurons in different PD fly models. In an attempt to re-evaluate and clarify this issue, we have examined three different genetic (α-synuclein, Pink1, parkin) and two toxin-based (rotenone and paraquat) models of the disease for neuronal cell loss. Our results showed no dopaminergic neuronal loss in all models tested. Despite this surprising result, we found additional phenotypes showing the dysfunctional status of the dopaminergic neurons in most of the models analyzed. A common feature found in most models is a quantifiable decrease in the fluorescence of a green-fluorescent protein reporter gene in dopaminergic neurons that correlates well with other phenotypes found for these models and can be reliably used as a hallmark of the neurodegenerative process when modeling diseases affecting the dopaminergic system in Drosophila. Analyzing three genetic and two toxin-based Drosophila models of Parkinson's disease (PD) through green fluorescent protein reporter and α-tyrosine hydroxylase staining, we have found the number of dopaminergic neurons to remain unchanged. Despite the lack of neuronal loss, we have detected a remarkable decrease in a reporter green-fluorescent protein (GFP) signal in dopaminergic neurons, suggesting an abnormal neuronal status that correlates with the phenotypes associated with those PD fly models.

  18. 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

  19. 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

  20. 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

  1. Nonnative SOD1 trimer is toxic to motor neurons in a model of amyotrophic lateral sclerosis

    PubMed Central

    Fee, Lanette; Tao, Yazhong; Redler, Rachel L.; Fay, James M.; Zhang, Yuliang; Lv, Zhengjian; Mercer, Ian P.; Deshmukh, Mohanish; Lyubchenko, Yuri L.; Dokholyan, Nikolay V.

    2016-01-01

    Since the linking of mutations in the Cu,Zn superoxide dismutase gene (sod1) to amyotrophic lateral sclerosis (ALS) in 1993, researchers have sought the connection between SOD1 and motor neuron death. Disease-linked mutations tend to destabilize the native dimeric structure of SOD1, and plaques containing misfolded and aggregated SOD1 have been found in the motor neurons of patients with ALS. Despite advances in understanding of ALS disease progression and SOD1 folding and stability, cytotoxic species and mechanisms remain unknown, greatly impeding the search for and design of therapeutic interventions. Here, we definitively link cytotoxicity associated with SOD1 aggregation in ALS to a nonnative trimeric SOD1 species. We develop methodology for the incorporation of low-resolution experimental data into simulations toward the structural modeling of metastable, multidomain aggregation intermediates. We apply this methodology to derive the structure of a SOD1 trimer, which we validate in vitro and in hybridized motor neurons. We show that SOD1 mutants designed to promote trimerization increase cell death. Further, we demonstrate that the cytotoxicity of the designed mutants correlates with trimer stability, providing a direct link between the presence of misfolded oligomers and neuron death. Identification of cytotoxic species is the first and critical step in elucidating the molecular etiology of ALS, and the ability to manipulate formation of these species will provide an avenue for the development of future therapeutic strategies. PMID:26719414

  2. 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.

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

    PubMed

    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.

  4. 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

  5. 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

  6. 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

  7. Bats use a neuronally implemented computational acoustic model to form sonar images.

    PubMed

    Simmons, James A

    2012-04-01

    This paper reexamines neurophysiological results from echolocating big brown bats to propose a new perspective on FM biosonar processing in the auditory system. Individual auditory neurons are frequency-tuned and respond to brief, 2-10 ms FM sweeps with an average of one spike per sound to register their tuned frequencies, to detect echo arrival, or to register a local null in the echo spectrum. When initiated by the broadcast, these responses comprise a cascade of single spikes distributed across time in neurons tuned to different frequencies that persists for 30-50 ms, long after the sound has ended. Their progress mirrors the broadcast's propagation away from the bat and the return of echoes for distances out to 5-8 m. Each returning echo evokes a similar pattern of single spikes that coincide with ongoing responses to the broadcast to register the target's distance and shape. The hypothesis advanced here is that this flow of responses over time acts as an internal model of sonar acoustics that the bat executes using neuronal computations distributed across many neurons to accumulate a dynamic image of the bat's surroundings.

  8. 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

  9. 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.

  10. Small GSK-3 Inhibitor Shows Efficacy in a Motor Neuron Disease Murine Model Modulating Autophagy

    PubMed Central

    de Munck, Estefanía; Palomo, Valle; Muñoz-Sáez, Emma; Perez, Daniel I.; Gómez-Miguel, Begoña; Solas, M. Teresa; Gil, Carmen; Martínez, Ana; Arahuetes, Rosa M.

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron degenerative disease that has no effective treatment up to date. Drug discovery tasks have been hampered due to the lack of knowledge in its molecular etiology together with the limited animal models for research. Recently, a motor neuron disease animal model has been developed using β-N-methylamino-L-alanine (L-BMAA), a neurotoxic amino acid related to the appearing of ALS. In the present work, the neuroprotective role of VP2.51, a small heterocyclic GSK-3 inhibitor, is analysed in this novel murine model together with the analysis of autophagy. VP2.51 daily administration for two weeks, starting the first day after L-BMAA treatment, leads to total recovery of neurological symptoms and prevents the activation of autophagic processes in rats. These results show that the L-BMAA murine model can be used to test the efficacy of new drugs. In addition, the results confirm the therapeutic potential of GSK-3 inhibitors, and specially VP2.51, for the disease-modifying future treatment of motor neuron disorders like ALS. PMID:27631495

  11. Small GSK-3 Inhibitor Shows Efficacy in a Motor Neuron Disease Murine Model Modulating Autophagy.

    PubMed

    de Munck, Estefanía; Palomo, Valle; Muñoz-Sáez, Emma; Perez, Daniel I; Gómez-Miguel, Begoña; Solas, M Teresa; Gil, Carmen; Martínez, Ana; Arahuetes, Rosa M

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron degenerative disease that has no effective treatment up to date. Drug discovery tasks have been hampered due to the lack of knowledge in its molecular etiology together with the limited animal models for research. Recently, a motor neuron disease animal model has been developed using β-N-methylamino-L-alanine (L-BMAA), a neurotoxic amino acid related to the appearing of ALS. In the present work, the neuroprotective role of VP2.51, a small heterocyclic GSK-3 inhibitor, is analysed in this novel murine model together with the analysis of autophagy. VP2.51 daily administration for two weeks, starting the first day after L-BMAA treatment, leads to total recovery of neurological symptoms and prevents the activation of autophagic processes in rats. These results show that the L-BMAA murine model can be used to test the efficacy of new drugs. In addition, the results confirm the therapeutic potential of GSK-3 inhibitors, and specially VP2.51, for the disease-modifying future treatment of motor neuron disorders like ALS. PMID:27631495

  12. 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.

  13. 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

  14. Small GSK-3 Inhibitor Shows Efficacy in a Motor Neuron Disease Murine Model Modulating Autophagy.

    PubMed

    de Munck, Estefanía; Palomo, Valle; Muñoz-Sáez, Emma; Perez, Daniel I; Gómez-Miguel, Begoña; Solas, M Teresa; Gil, Carmen; Martínez, Ana; Arahuetes, Rosa M

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron degenerative disease that has no effective treatment up to date. Drug discovery tasks have been hampered due to the lack of knowledge in its molecular etiology together with the limited animal models for research. Recently, a motor neuron disease animal model has been developed using β-N-methylamino-L-alanine (L-BMAA), a neurotoxic amino acid related to the appearing of ALS. In the present work, the neuroprotective role of VP2.51, a small heterocyclic GSK-3 inhibitor, is analysed in this novel murine model together with the analysis of autophagy. VP2.51 daily administration for two weeks, starting the first day after L-BMAA treatment, leads to total recovery of neurological symptoms and prevents the activation of autophagic processes in rats. These results show that the L-BMAA murine model can be used to test the efficacy of new drugs. In addition, the results confirm the therapeutic potential of GSK-3 inhibitors, and specially VP2.51, for the disease-modifying future treatment of motor neuron disorders like ALS.

  15. 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.

  16. A system for quantitative morphological measurement and electronic modelling of neurons: three-dimensional reconstruction.

    PubMed

    Stockley, E W; Cole, H M; Brown, A D; Wheal, H V

    1993-04-01

    A system for accurately reconstructing neurones from optical sections taken at high magnification is described. Cells are digitised on a 68000-based microcomputer to form a database consisting of a series of linked nodes each consisting of x, y, z coordinates and an estimate of dendritic diameter. This database is used to generate three-dimensional (3-D) displays of the neurone and allows quantitative analysis of the cell volume, surface area and dendritic length. Images of the cell can be manipulated locally or transferred to an IBM 3090 mainframe where a wireframe model can be displayed on an IBM 5080 graphics terminal and rotated interactively in real time, allowing visualisation of the cell from all angles. Space-filling models can also be produced. Reconstructions can also provide morphological data for passive electrical simulations of hippocampal pyramidal cells.

  17. 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

  18. 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

  19. Neuronal and glial pathological changes during epileptogenesis in the mouse pilocarpine model.

    PubMed

    Borges, Karin; Gearing, Marla; McDermott, Dayna L; Smith, Amy B; Almonte, Antoine G; Wainer, Bruce H; Dingledine, Raymond

    2003-07-01

    The rodent pilocarpine model of epilepsy exhibits hippocampal sclerosis and spontaneous seizures and thus resembles human temporal lobe epilepsy. Use of the many available mouse mutants to study this epilepsy model would benefit from a detailed neuropathology study. To identify new features of epileptogenesis, we characterized glial and neuronal pathologies after pilocarpine-induced status epilepticus (SE) in CF1 and C57BL/6 mice focusing on the hippocampus. All CF1 mice showed spontaneous seizures by 17-27 days after SE. By 6 h there was virtually complete loss of hilar neurons, but the extent of pyramidal cell death varied considerably among mice. In the mossy fiber pathway, neuropeptide Y (NPY) was persistently upregulated beginning 1 day after SE; NPY immunoreactivity in the supragranular layer after 31 days indicated mossy fiber sprouting. beta2 microglobulin-positive activated microglia, normally absent in brains without SE, became abundant over 3-31 days in regions of neuronal loss, including the hippocampus and the amygdala. Astrogliosis developed after 10 days in damaged areas. Amyloid precursor protein immunoreactivity in the thalamus at 10 days suggested delayed axonal degeneration. The mortality after pilocarpine injection was very high in C57BL/6 mice from Jackson Laboratories but not those from Charles River, suggesting that mutant mice in the C57BL/6(JAX) strain will be difficult to study in the pilocarpine model, although their neuropathology was similar to CF1 mice. Major neuropathological changes not previously studied in the rodent pilocarpine model include widespread microglial activation, delayed thalamic axonal death, and persistent NPY upregulation in mossy fibers, together revealing extensive and persistent glial as well as neuronal pathology.

  20. 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.

  1. 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

  2. An ultra-low-voltage electronic implementation of inertial neuron model with nonmonotonous Liao's activation function.

    PubMed

    Kant, Nasir Ali; Dar, Mohamad Rafiq; Khanday, Farooq Ahmad

    2015-01-01

    The output of every neuron in neural network is specified by the employed activation function (AF) and therefore forms the heart of neural networks. As far as the design of artificial neural networks (ANNs) is concerned, hardware approach is preferred over software one because it promises the full utilization of the application potential of ANNs. Therefore, besides some arithmetic blocks, designing AF in hardware is the most important for designing ANN. While attempting to design the AF in hardware, the designs should be compatible with the modern Very Large Scale Integration (VLSI) design techniques. In this regard, the implemented designs should: only be in Metal Oxide Semiconductor (MOS) technology in order to be compatible with the digital designs, provide electronic tunability feature, and be able to operate at ultra-low voltage. Companding is one of the promising circuit design techniques for achieving these goals. In this paper, 0.5 V design of Liao's AF using sinh-domain technique is introduced. Furthermore, the function is tested by implementing inertial neuron model. The performance of the AF and inertial neuron model have been evaluated through simulation results, using the PSPICE software with the MOS transistor models provided by the 0.18-μm Taiwan Semiconductor Manufacturer Complementary Metal Oxide Semiconductor (TSM CMOS) process. PMID:27030660

  3. 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.

  4. 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

  5. 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

  6. 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

  7. An In Silico Agent-Based Model Demonstrates Reelin Function in Directing Lamination of Neurons during Cortical Development

    PubMed Central

    Caffrey, James R.; Hughes, Barry D.; Britto, Joanne M.; Landman, Kerry A.

    2014-01-01

    The characteristic six-layered appearance of the neocortex arises from the correct positioning of pyramidal neurons during development and alterations in this process can cause intellectual disabilities and developmental delay. Malformations in cortical development arise when neurons either fail to migrate properly from the germinal zones or fail to cease migration in the correct laminar position within the cortical plate. The Reelin signalling pathway is vital for correct neuronal positioning as loss of Reelin leads to a partially inverted cortex. The precise biological function of Reelin remains controversial and debate surrounds its role as a chemoattractant or stop signal for migrating neurons. To investigate this further we developed an in silico agent-based model of cortical layer formation. Using this model we tested four biologically plausible hypotheses for neuron motility and four biologically plausible hypotheses for the loss of neuron motility (conversion from migration). A matrix of 16 combinations of motility and conversion rules was applied against the known structure of mouse cortical layers in the wild-type cortex, the Reelin-null mutant, the Dab1-null mutant and a conditional Dab1 mutant. Using this approach, many combinations of motility and conversion mechanisms can be rejected. For example, the model does not support Reelin acting as a repelling or as a stopping signal. In contrast, the study lends very strong support to the notion that the glycoprotein Reelin acts as a chemoattractant for neurons. Furthermore, the most viable proposition for the conversion mechanism is one in which conversion is affected by a motile neuron sensing in the near vicinity neurons that have already converted. Therefore, this model helps elucidate the function of Reelin during neuronal migration and cortical development. PMID:25334023

  8. 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

  9. Functional integration of grafted neural stem cell-derived dopaminergic neurons monitored by optogenetics in an in vitro Parkinson model.

    PubMed

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

    2011-03-04

    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.

  10. 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

  11. 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

  12. 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

  13. Lithium fails to protect dopaminergic neurons in the 6-OHDA model of Parkinson's disease.

    PubMed

    Yong, Yue; Ding, Hanqing; Fan, Zhiqin; Luo, Jia; Ke, Zun-Ji

    2011-03-01

    Lithium has been used for the treatment of bipolar mood disorder and is shown to have neuroprotective properties. Since lithium inhibits the activity of glycogen synthase kinase 3 (GSK3) which is implicated in various human diseases, particularly neurodegenerative diseases, the therapeutic potential of lithium receives great attention. Parkinson's disease (PD) is the second most common neurodegenerative disease, characterized by the pathological loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc). Intranigral injection of the catecholaminergic neurotoxin 6-hydroxydopamine (6-OHDA) causes selective and progressive degeneration of dopaminergic neurons in SNpc, and is a commonly used animal model of PD. The current study was designated to determine whether lithium is effective in alleviating 6-OHDA-induced neurodegeneration in the SNpc of rats. We demonstrated that chronic subcutaneous administration of lithium inhibited GSK3 activity in the SNpc, which was evident by an increase in phosphorylation of GSK3β at serine 9, cyclin D1 expression, and a decrease in tau phosphorylation. 6-OHDA did not affect GSK3 activity in the SNpc. Moreover, lithium was unable to alleviate 6-OHDA-induced degeneration of SNpc dopaminergic neurons. The results suggest that GSK3 is minimally involved in the neurodegeneration in the rat 6-OHDA model of PD.

  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. Altered adult hippocampal neuronal maturation in a rat model of fetal alcohol syndrome.

    PubMed

    Gil-Mohapel, Joana; Boehme, Fanny; Patten, Anna; Cox, Adrian; Kainer, Leah; Giles, Erica; Brocardo, Patricia S; Christie, Brian R

    2011-04-12

    Exposure to ethanol during pregnancy can be devastating to the developing nervous system, leading to significant central nervous system dysfunction. The hippocampus, one of the two brain regions where neurogenesis persists into adulthood, is particularly sensitive to the teratogenic effects of ethanol. In the present study, we tested a rat model of fetal alcohol syndrome (FAS) with ethanol administered via gavage throughout all three trimester equivalents. Subsequently, we assessed cell proliferation, as well as neuronal survival, and differentiation in the dentate gyrus of the hippocampus of adolescent (35 days old), young adult (60 days old) and adult (90 days old) Sprague-Dawley rats. Using both extrinsic (bromodeoxyuridine) and intrinsic (Ki-67) markers, we observed no significant alterations in cell proliferation and survival in ethanol-exposed animals when compared with their pair-fed and ad libitum controls. However, we detected a significant increase in the number of new immature neurons in animals that were exposed to ethanol throughout all three trimester equivalents. This result might reflect a compensatory mechanism to counteract the deleterious effects of prenatal ethanol exposure or an ethanol-induced arrest of the neurogenic process at the early neuronal maturation stages. Taken together these results indicate that exposure to ethanol during the period of brain development causes a long-lasting dysregulation of the neurogenic process, a mechanism that might contribute, at least in part, to the hippocampal deficits that have been reported in rodent models of FAS.

  16. 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

  17. 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.

  18. Response of an ensemble of noisy neuron models to a single input.

    PubMed

    Tanabe, S; Sato, S; Pakdaman, K

    1999-12-01

    Spike timing precision in response to a subthreshold stimulation can be enhanced by noise in ensembles of neurons [X. Pei, L. Wilkens, and F. Moss, Phys. Rev. Lett. 77, 4679 (1996)]. We elucidate the mechanism underlying this phenomenon by computing the membrane potential distributions of ensembles of Hodgkin-Huxley neuron models. For small noise amplitudes, the membrane potential distribution takes on a Gaussian form centered on the resting potential, while for large fluctuations, there is a significant spread to lower potentials. These two regimes are separated by a relatively narrow band where the distributions transit rapidly from the Gaussian-like shapes to the spread ones. We argue that the optimal noise that maximizes the spike timing precision is situated close to this boundary. PMID:11970667

  19. 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

  20. 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.

  1. Dcx reexpression reduces subcortical band heterotopia and seizure threshold in an animal model of neuronal migration disorder.

    PubMed

    Manent, Jean-Bernard; Wang, Yu; Chang, Yoonjeung; Paramasivam, Murugan; LoTurco, Joseph J

    2009-01-01

    Disorders of neuronal migration can lead to malformations of the cerebral neocortex that greatly increase the risk of seizures. It remains untested whether malformations caused by disorders in neuronal migration can be reduced by reactivating cellular migration and whether such repair can decrease seizure risk. Here we show, in a rat model of subcortical band heterotopia (SBH) generated by in utero RNA interference of the Dcx gene, that aberrantly positioned neurons can be stimulated to migrate by reexpressing Dcx after birth. Restarting migration in this way both reduces neocortical malformations and restores neuronal patterning. We further find that the capacity to reduce SBH continues into early postnatal development. Moreover, intervention after birth reduces the convulsant-induced seizure threshold to a level similar to that in malformation-free controls. These results suggest that disorders of neuronal migration may be eventually treatable by reengaging developmental programs both to reduce the size of cortical malformations and to reduce seizure risk.

  2. 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

  3. Active dendrites mediate stratified gamma-range coincidence detection in hippocampal model neurons

    PubMed Central

    Das, Anindita; Narayanan, Rishikesh

    2015-01-01

    Hippocampal pyramidal neurons exhibit gamma-phase preference in their spikes, selectively route inputs through gamma frequency multiplexing and are considered part of gamma-bound cell assemblies. How do these neurons exhibit gamma-frequency coincidence detection capabilities, a feature that is essential for the expression of these physiological observations, despite their slow membrane time constant? In this conductance-based modelling study, we developed quantitative metrics for the temporal window of integration/coincidence detection based on the spike-triggered average (STA) of the neuronal compartment. We employed these metrics in conjunction with quantitative measures for spike initiation dynamics to assess the emergence and dependence of coincidence detection and STA spectral selectivity on various ion channel combinations. We found that the presence of resonating conductances (hyperpolarization-activated cyclic nucleotide-gated or T-type calcium), either independently or synergistically when expressed together, led to the emergence of spectral selectivity in the spike initiation dynamics and a significant reduction in the coincidence detection window (CDW). The presence of A-type potassium channels, along with resonating conductances, reduced the STA characteristic frequency and broadened the CDW, but persistent sodium channels sharpened the CDW by strengthening the spectral selectivity in the STA. Finally, in a morphologically precise model endowed with experimentally constrained channel gradients, we found that somatodendritic compartments expressed functional maps of strong theta-frequency selectivity in spike initiation dynamics and gamma-range CDW. Our results reveal the heavy expression of resonating and spike-generating conductances as the mechanism underlying the robust emergence of stratified gamma-range coincidence detection in the dendrites of hippocampal and cortical pyramidal neurons. PMID:26018187

  4. A mouse model of tuberous sclerosis: neuronal loss of Tsc1 causes dysplastic and ectopic neurons, reduced myelination, seizure activity, and limited survival.

    PubMed

    Meikle, Lynsey; Talos, Delia M; Onda, Hiroaki; Pollizzi, Kristen; Rotenberg, Alexander; Sahin, Mustafa; Jensen, Frances E; Kwiatkowski, David J

    2007-05-23

    Tuberous sclerosis (TSC) is a hamartoma syndrome caused by mutations in TSC1 or TSC2 in which cerebral cortical tubers and seizures are major clinical issues. We have engineered mice in which most cortical neurons lose Tsc1 expression during embryonic development. These Tsc1 mutant mice display several neurological abnormalities beginning at postnatal day 5 with subsequent failure to thrive and median survival of 35 d. The mice also display clinical and electrographic seizures both spontaneously and with physical stimulation, and some seizures end in a fatal tonic phase. Many cortical and hippocampal neurons are enlarged and/or dysplastic in the Tsc1 mutant mice, strongly express phospho-S6, and are ectopic in multiple sites in the cortex and hippocampus. There is a striking delay in myelination in the mutant mice, which appears to be caused by an inductive neuronal defect. This new TSC brain model replicates several features of human TSC brain lesions and implicates an important function of Tsc1/Tsc2 in neuronal development.

  5. 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.

  6. 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

  7. In vivo optical signatures of neuronal death in a mouse model of Alzheimer's disease

    PubMed Central

    Lin, Alexander J; Castello, Nicholas A; Lee, Grace; Green, Kim N; Durkin, Anthony J; Choi, Bernard; LaFerla, Frank; Tromberg, Bruce J

    2014-01-01

    Background There currently is a need for cost-effective, quantitative techniques to evaluate the gradual progression of Alzheimer's disease (AD). Measurement techniques based on diffuse optical spectroscopy can detect blood perfusion and brain cellular composition changes, through measuring the absorption (µa) and reduced scattering (µs′) coefficients, respectively, using non-ionizing near-infrared light. Previous work has shown that brain perfusion deficits in an AD mouse model can be detected. The objective of this study was to determine if µs′ is sensitive to the inflammation and neuron death found in AD. Methods We used spatial frequency domain imaging (SFDI) to form quantitative maps of µa and µs′ in 3-month old male CaM/Tet-DTA mice harboring transgenes for the doxycyline-regulated neuronal expression of diphtheria toxin. When doxycycline is removed from the diet, CaM/Tet-DTA mice develop progressive neuronal loss in forebrain neurons. Mice (n = 5) were imaged longitudinally immediately prior to and after 23 days of lesion induction, and µa and µs′ (30 wavelengths, 650–970 nm) were compared to properties obtained from Tet-DTA controls (n = 5). Neuron death and infiltration of inflammatory cells in brain cortical slices was confirmed with immunohistochemistry. Results No significant difference in baseline scattering and absorption were measured between CaM/Tet-DTA mice and controls. After 23 days of lesion induction, brain cortical µs′ was 11–16% higher in the CaM/Tet-DTA mice than in controls (P < 0.03). Longitudinal imaging showed no significant difference in µs′ between the first and 23rd day of imaging in controls. Removing doxycycline from the diet was associated with a significant decrease in total hemoglobin concentrations (119 ± 9 µM vs. 91 ± 8 µM) (P < 0.05) in controls, but not in CaM/Tet-DTA mice. Conclusions Neuronal death and brain inflammation are associated with increased tissue

  8. 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

  9. Modeling N-methyl-D-aspartate-induced bursting in dopamine neurons.

    PubMed

    Li, Y X; Bertram, R; Rinzel, J

    1996-03-01

    Burst firing of dopaminergic neurons of the substantia nigra pars compacta can be induced in vitro by the glutamate agonist N-methyl-D-aspartate. It has been suggested that the interburst hyperpolarization is due to Na+ extrusion by a ouabain-sensitive pump [Johnson et al. (1992) Science 258, 665-667]. We formulate and explore a theoretical model, with a minimal number of currents, for this novel mechanism of burst generation. This minimal model is further developed into a more elaborate model based on observations of additional currents and hypotheses about their spatial distribution in dopaminergic neurons [Hounsgaard (1992) Neuroscience 50, 513-518; Llinás et al. (1984) Brain Res. 294, 127-132]. Using the minimal model, we confirm that interaction between the regenerative, inward N-methyl-D-aspartate-mediated current and the outward Na(+)-pump current is sufficient to generate the slow oscillation (approximately 0.5 Hz) underlying the burst. The negative-slope region of the N-methyl-D-aspartate channel's current-voltage relation is indispensable for this slow rhythm generation. The time-scale of Na(+)-handling determines the burst's slow frequency. Moreover, we show that, given the constraints of sodium handling, such bursting is best explained mechanistically by using at least two spatial, cable-like compartments: a soma where action potentials are produced and a dendritic compartment where the slow rhythm is generated. Our result is consistent with recent experimental evidence that burst generation originates in distal dendrites [Seutin et al. (1994) Neuroscience 58, 201-206]. Responses of the model to a number of electrophysiological and pharmacological stimuli are consistent with known responses observed under similar conditions. These include the persistence of the slow rhythm when the tetrodotoxin-sensitive Na+ channel is blocked and when the soma is voltage-clamped at -60 mV. Using our more elaborate model, we account for details of the observed

  10. 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

  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. 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

  13. Cerebellar Bergmann glia: an important model to study neuron-glia interactions.

    PubMed

    López-Bayghen, Esther; Rosas, Sandra; Castelán, Francisco; Ortega, Arturo

    2007-05-01

    The biochemical effects triggered by the action of glutamate, the main excitatory amino acid, on a specialized type of glia cells, Bergmann glial cells of the cerebellum, are a model system with which to study glia-neuronal interactions. Neuron to Bergmann glia signaling is involved in early stages of development, mainly in cell migration and synaptogenesis. Later, in adulthood, these cells have an important role in the maintenance and proper function of the synapses that they surround. Major molecular targets of this cellular interplay are glial glutamate receptors and transporters, both of which sense synaptic activity. Glutamate receptors trigger a complex network of signaling cascades that involve Ca(2+) influx and lead to a differential gene-expression pattern. In contrast, Bergmann glia glutamate transporters participate in the removal of the neurotransmitter from the synaptic cleft and act also as signal transducers that regulate, in the short term, their own activity. These exciting findings strengthen the concept of active participation of glial cells in synaptic transmission and the involvement of neuron-glia circuits in the processing of brain information.

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. A hierarchical neuronal model for generation and online recognition of birdsongs.

    PubMed

    Yildiz, Izzet B; Kiebel, Stefan J

    2011-12-01

    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.

  20. A modified cable formalism for modeling neuronal membranes at high frequencies.

    PubMed

    Bédard, Claude; Destexhe, Alain

    2008-02-15

    Intracellular recordings of cortical neurons in vivo display intense subthreshold membrane potential (V(m)) activity. The power spectral density of the V(m) displays a power-law structure at high frequencies (>50 Hz) with a slope of approximately -2.5. This type of frequency scaling cannot be accounted for by traditional models, as either single-compartment models or models based on reconstructed cell morphologies display a frequency scaling with a slope close to -4. This slope is due to the fact that the membrane resistance is short-circuited by the capacitance for high frequencies, a situation which may not be realistic. Here, we integrate nonideal capacitors in cable equations to reflect the fact that the capacitance cannot be charged instantaneously. We show that the resulting nonideal cable model can be solved analytically using Fourier transforms. Numerical simulations using a ball-and-stick model yield membrane potential activity with similar frequency scaling as in the experiments. We also discuss the consequences of using nonideal capacitors on other cellular properties such as the transmission of high frequencies, which is boosted in nonideal cables, or voltage attenuation in dendrites. These results suggest that cable equations based on nonideal capacitors should be used to capture the behavior of neuronal membranes at high frequencies. PMID:17921220

  1. A Modified Cable Formalism for Modeling Neuronal Membranes at High Frequencies

    PubMed Central

    Bédard, Claude; Destexhe, Alain

    2008-01-01

    Intracellular recordings of cortical neurons in vivo display intense subthreshold membrane potential (Vm) activity. The power spectral density of the Vm displays a power-law structure at high frequencies (>50 Hz) with a slope of ∼−2.5. This type of frequency scaling cannot be accounted for by traditional models, as either single-compartment models or models based on reconstructed cell morphologies display a frequency scaling with a slope close to −4. This slope is due to the fact that the membrane resistance is short-circuited by the capacitance for high frequencies, a situation which may not be realistic. Here, we integrate nonideal capacitors in cable equations to reflect the fact that the capacitance cannot be charged instantaneously. We show that the resulting nonideal cable model can be solved analytically using Fourier transforms. Numerical simulations using a ball-and-stick model yield membrane potential activity with similar frequency scaling as in the experiments. We also discuss the consequences of using nonideal capacitors on other cellular properties such as the transmission of high frequencies, which is boosted in nonideal cables, or voltage attenuation in dendrites. These results suggest that cable equations based on nonideal capacitors should be used to capture the behavior of neuronal membranes at high frequencies. PMID:17921220

  2. A hierarchical neuronal model for generation and online recognition of birdsongs.

    PubMed

    Yildiz, Izzet B; Kiebel, Stefan J

    2011-12-01

    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

  3. 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

  4. Enhanced Neuronal Glucose Transporter Expression Reveals Metabolic Choice in a HD Drosophila Model

    PubMed Central

    Besson, Marie Thérèse; Alegría, Karin; Garrido-Gerter, Pamela; Barros, Luis Felipe; Liévens, Jean-Charles

    2015-01-01

    Huntington’s disease is a neurodegenerative disorder caused by toxic insertions of polyglutamine residues in the Huntingtin protein and characterized by progressive deterioration of cognitive and motor functions. Altered brain glucose metabolism has long been suggested and a possible link has been proposed in HD. However, the precise function of glucose transporters was not yet determined. Here, we report the effects of the specifically-neuronal human glucose transporter expression in neurons of a Drosophila model carrying the exon 1 of the human huntingtin gene with 93 glutamine repeats (HQ93). We demonstrated that overexpression of the human glucose transporter in neurons ameliorated significantly the status of HD flies by increasing their lifespan, reducing their locomotor deficits and rescuing eye neurodegeneration. Then, we investigated whether increasing the major pathways of glucose catabolism, glycolysis and pentose-phosphate pathway (PPP) impacts HD. To mimic increased glycolytic flux, we overexpressed phosphofructokinase (PFK) which catalyzes an irreversible step in glycolysis. Overexpression of PFK did not affect HQ93 fly survival, but protected from photoreceptor loss. Overexpression of glucose-6-phosphate dehydrogenase (G6PD), the key enzyme of the PPP, extended significantly the lifespan of HD flies and rescued eye neurodegeneration. Since G6PD is able to synthesize NADPH involved in cell survival by maintenance of the redox state, we showed that tolerance to experimental oxidative stress was enhanced in flies co-expressing HQ93 and G6PD. Additionally overexpressions of hGluT3, G6PD or PFK were able to circumvent mitochondrial deficits induced by specific silencing of genes necessary for mitochondrial homeostasis. Our study confirms the involvement of bioenergetic deficits in HD course; they can be rescued by specific expression of a glucose transporter in neurons. Finally, the PPP and, to a lesser extent, the glycolysis seem to mediate the hGluT3

  5. Enhanced neuronal glucose transporter expression reveals metabolic choice in a HD Drosophila model.

    PubMed

    Besson, Marie Thérèse; Alegría, Karin; Garrido-Gerter, Pamela; Barros, Luis Felipe; Liévens, Jean-Charles

    2015-01-01

    Huntington's disease is a neurodegenerative disorder caused by toxic insertions of polyglutamine residues in the Huntingtin protein and characterized by progressive deterioration of cognitive and motor functions. Altered brain glucose metabolism has long been suggested and a possible link has been proposed in HD. However, the precise function of glucose transporters was not yet determined. Here, we report the effects of the specifically-neuronal human glucose transporter expression in neurons of a Drosophila model carrying the exon 1 of the human huntingtin gene with 93 glutamine repeats (HQ93). We demonstrated that overexpression of the human glucose transporter in neurons ameliorated significantly the status of HD flies by increasing their lifespan, reducing their locomotor deficits and rescuing eye neurodegeneration. Then, we investigated whether increasing the major pathways of glucose catabolism, glycolysis and pentose-phosphate pathway (PPP) impacts HD. To mimic increased glycolytic flux, we overexpressed phosphofructokinase (PFK) which catalyzes an irreversible step in glycolysis. Overexpression of PFK did not affect HQ93 fly survival, but protected from photoreceptor loss. Overexpression of glucose-6-phosphate dehydrogenase (G6PD), the key enzyme of the PPP, extended significantly the lifespan of HD flies and rescued eye neurodegeneration. Since G6PD is able to synthesize NADPH involved in cell survival by maintenance of the redox state, we showed that tolerance to experimental oxidative stress was enhanced in flies co-expressing HQ93 and G6PD. Additionally overexpressions of hGluT3, G6PD or PFK were able to circumvent mitochondrial deficits induced by specific silencing of genes necessary for mitochondrial homeostasis. Our study confirms the involvement of bioenergetic deficits in HD course; they can be rescued by specific expression of a glucose transporter in neurons. Finally, the PPP and, to a lesser extent, the glycolysis seem to mediate the hGluT3

  6. The statistics of repeating patterns of cortical activity can be reproduced by a model network of stochastic binary neurons.

    PubMed

    Roxin, Alex; Hakim, Vincent; Brunel, Nicolas

    2008-10-15

    Calcium imaging of the spontaneous activity in cortical slices has revealed repeating spatiotemporal patterns of transitions between so-called down states and up states (Ikegaya et al., 2004). Here we fit a model network of stochastic binary neurons to data from these experiments, and in doing so reproduce the distributions of such patterns. We use two versions of this model: (1) an unconnected network in which neurons are activated as independent Poisson processes; and (2) a network with an interaction matrix, estimated from the data, representing effective interactions between the neurons. The unconnected model (model 1) is sufficient to account for the statistics of repeating patterns in 11 of the 15 datasets studied. Model 2, with interactions between neurons, is required to account for pattern statistics of the remaining four. Three of these four datasets are the ones that contain the largest number of transitions, suggesting that long datasets are in general necessary to render interactions statistically visible. We then study the topology of the matrix of interactions estimated for these four datasets. For three of the four datasets, we find sparse matrices with long-tailed degree distributions and an overrepresentation of certain network motifs. The remaining dataset exhibits a strongly interconnected, spatially localized subgroup of neurons. In all cases, we find that interactions between neurons facilitate the generation of long patterns that do not repeat exactly.

  7. LFPy: a tool for biophysical simulation of extracellular potentials generated by detailed model neurons

    PubMed Central

    Lindén, Henrik; Hagen, Espen; Łęski, Szymon; Norheim, Eivind S.; Pettersen, Klas H.; Einevoll, Gaute T.

    2014-01-01

    Electrical extracellular recordings, i.e., recordings of the electrical potentials in the extracellular medium between cells, have been a main work-horse in electrophysiology for almost a century. The high-frequency part of the signal (≳500 Hz), i.e., the multi-unit activity (MUA), contains information about the firing of action potentials in surrounding neurons, while the low-frequency part, the local field potential (LFP), contains information about how these neurons integrate synaptic inputs. As the recorded extracellular signals arise from multiple neural processes, their interpretation is typically ambiguous and difficult. Fortunately, a precise biophysical modeling scheme linking activity at the cellular level and the recorded signal has been established: the extracellular potential can be calculated as a weighted sum of all transmembrane currents in all cells located in the vicinity of the electrode. This computational scheme can considerably aid the modeling and analysis of MUA and LFP signals. Here, we describe LFPy, an open source Python package for numerical simulations of extracellular potentials. LFPy consists of a set of easy-to-use classes for defining cells, synapses and recording electrodes as Python objects, implementing this biophysical modeling scheme. It runs on top of the widely used NEURON simulation environment, which allows for flexible usage of both new and existing cell models. Further, calculation of extracellular potentials using the line-source-method is efficiently implemented. We describe the theoretical framework underlying the extracellular potential calculations and illustrate by examples how LFPy can be used both for simulating LFPs, i.e., synaptic contributions from single cells as well a populations of cells, and MUAs, i.e., extracellular signatures of action potentials. PMID:24474916

  8. Chondrolectin affects cell survival and neuronal outgrowth in in vitro and in vivo models of spinal muscular atrophy.

    PubMed

    Sleigh, James N; Barreiro-Iglesias, Antón; Oliver, Peter L; Biba, Angeliki; Becker, Thomas; Davies, Kay E; Becker, Catherina G; Talbot, Kevin

    2014-02-15

    Spinal muscular atrophy (SMA) is characterized by the selective loss of spinal motor neurons owing to reduced levels of survival motor neuron (Smn) protein. In addition to its well-established role in assembling constituents of the spliceosome, diverse cellular functions have been proposed for Smn, but the reason why low levels of this widely expressed protein result in selective motor neuron pathology is still debated. In longitudinal studies of exon-level changes in SMA mouse model tissues, designed to determine the contribution of splicing dysfunction to the disease, we have previously shown that a generalized defect in splicing is unlikely to play a causative role in SMA. Nevertheless, we identified a small subset of genes that were alternatively spliced in the spinal cord compared with control mice before symptom onset, indicating a possible mechanistic role in disease. Here, we have performed functional studies of one of these genes, chondrolectin (Chodl), known to be highly expressed in motor neurons and important for correct motor axon outgrowth in zebrafish. Using in vitro and in vivo models of SMA, we demonstrate altered expression of Chodl in SMA mouse spinal motor neurons, show that Chodl has distinct effects on cell survival and neurite outgrowth and that increasing the expression of chodl can rescue motor neuron outgrowth defects in Smn-depleted zebrafish. Our findings thus link the dysregulation of Chodl to the pathophysiology of motor neuron degeneration in SMA.

  9. 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.

  10. A Model of the Intracellular Response of an Olfactory Neuron in Caenorhabditis elegans to Odor Stimulation

    PubMed Central

    Usuyama, Mamoru; Ushida, Chisato; Shingai, Ryuzo

    2012-01-01

    We developed a mathematical model of a hypothetical neuronal signal transduction pathway to better understand olfactory perception in Caenorhabditis elegans. This worm has only three pairs of olfactory receptor neurons. Intracellular Ca2+ decreases in one pair of olfactory neurons in C. elegans, the AWC neurons, following application of an attractive odor and there is a transient increase in intracellular Ca2+ following removal of odor. The magnitude of this increase is positively correlated with the duration of odor stimulation. Additionally, this Ca2+ transient is induced by a cGMP second messenger system. We identified likely candidates for the signal transduction molecules functioning in this system based on available gene expression and physiological data from AWCs. Our model incorporated a G-protein-coupled odor receptor, a G-protein, a guanylate cyclase as the G-protein effector, and a single phosphodiesterase. Additionally, a cyclic-nucleotide-gated ion channel and a voltage-gated ion channel that mediated calcium influx were incorporated into the model. We posited that, upon odor stimulation, guanylate cyclase was suppressed by the G-protein and that, upon cessation of the stimulus, the G-protein–induced suppression ceased and cGMP synthesis was restored. A key element of our model was a Ca2+-dependent negative feedback loop that ensured that the calcium increases were transient. Two guanylate cyclase-activating proteins acted on the effector guanylate cyclase to negatively regulate cGMP signaling and the resulting calcium influx. Our model was able to closely replicate in silico three important features of the calcium dynamics of AWCs. Specifically, in our simulations, [Ca2+] increased rapidly and reached its peak within 10 s after the odor stimulus was removed, peak [Ca2+] increased with longer odor exposure, and [Ca2+] decreased during a second stimulus that closely followed an initial stimulus. However, application of random background signal (

  11. 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

  12. Modeling Pharmacological Clock and Memory Patterns of Interval Timing in a Striatal Beat-Frequency Model with Realistic, Noisy Neurons

    PubMed Central

    Oprisan, Sorinel A.; Buhusi, Catalin V.

    2011-01-01

    In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing) is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern), whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern). How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an striatal beat frequency (SBF) model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris–Lecar neurons (SBF–ML). Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF–ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise) – which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trials, and in the errors in recording/retrieving stored information related to criterion time – seems to be critical for the time-scale invariance of the clock and memory patterns. PMID:21977014

  13. Synchronization in two neurons: Results for a two-component dynamical model with time-delayed inhibition

    NASA Astrophysics Data System (ADS)

    Renversez, Gilles

    1998-03-01

    We study synchronization in two neurons using two-dimensional neuronal models coupled through threshold delayed inhibition, acting for a fixed duration T. We explain the mechanism of synchronization between the two coupled units by means of phase-plane analysis. Using a piecewise linear approximation, we compute the firing times of two mutually coupled neurons, which allows a quantitative study of synchronization. The results are in good agreement, both quantitatively and qualitatively, with the numerical simulations of the full nonlinear coupled system describing the two neurons. We first show that, with simple inhibition, only phase-lagged synchronization can be achieved except for a particular set of T-values. We then show that coincidence synchronization can rapidly be achieved with an improved coupling model which takes into account the increase of membrane conductance during inhibition.

  14. 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.

  15. 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.

  16. Stimulus-response curves of a neuronal model for noisy subthreshold oscillations and related spike generation.

    PubMed

    Huber, Martin Tobias; Braun, Hans Albert

    2006-04-01

    We investigate the stimulus-dependent tuning properties of a noisy ionic conductance model for intrinsic subthreshold oscillations in membrane potential and associated spike generation. Upon depolarization by an applied current, the model exhibits subthreshold oscillatory activity with an occasional spike generation when oscillations reach the spike threshold. We consider how the amount of applied current, the noise intensity, variation of maximum conductance values, and scaling to different temperature ranges alter the responses of the model with respect to voltage traces, interspike intervals and their statistics, and the mean spike frequency curves. We demonstrate that subthreshold oscillatory neurons in the presence of noise can sensitively and also selectively be tuned by the stimulus-dependent variation of model parameters. PMID:16711858

  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.

  18. 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

  19. 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.

  20. Oxidative Stress Associated with Neuronal Apoptosis in Experimental Models of Epilepsy

    PubMed Central

    Méndez-Armenta, Marisela; Nava-Ruíz, Concepción; Juárez-Rebollar, Daniel; Rodríguez-Martínez, Erika; Yescas Gómez, Petra

    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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. A predictive reinforcement model of dopamine neurons for learning approach behavior.

    PubMed

    Contreras-Vidal, J L; Schultz, W

    1999-01-01

    A neural network model of how dopamine and prefrontal cortex activity guides short- and long-term information processing within the cortico-striatal circuits during reward-related learning of approach behavior is proposed. The model predicts two types of reward-related neuronal responses generated during learning: (1) cell activity signaling errors in the prediction of the expected time of reward delivery and (2) neural activations coding for errors in the prediction of the amount and type of reward or stimulus expectancies. The former type of signal is consistent with the responses of dopaminergic neurons, while the latter signal is consistent with reward expectancy responses reported in the prefrontal cortex. It is shown that a neural network architecture that satisfies the design principles of the adaptive resonance theory of Carpenter and Grossberg (1987) can account for the dopamine responses to novelty, generalization, and discrimination of appetitive and aversive stimuli. These hypotheses are scrutinized via simulations of the model in relation to the delivery of free food outside a task, the timed contingent delivery of appetitive and aversive stimuli, and an asymmetric, instructed delay response task.

  7. Neuropathologic and biochemical changes during disease progression in liver X receptor beta-/- mice, a model of adult neuron disease.

    PubMed

    Bigini, Paolo; Steffensen, Knut R; Ferrario, Anna; Diomede, Luisa; Ferrara, Giovanni; Barbera, Sara; Salzano, Sonia; Fumagalli, Elena; Ghezzi, Pietro; Mennini, Tiziana; Gustafsson, Jan-Ake

    2010-06-01

    In amyotrophic lateral sclerosis (ALS), there is selective degeneration of motor neurons that leads to paralysis and death. Although the etiology of ALS is unclear, its heterogeneity suggests that a combination of factors (endogenous and/or environmental) may induce progressive motor neuron stress that results in the activation of different cell death pathways. Alterations of brain cholesterol homeostasis have recently been considered as possible cofactors in many neurodegenerative disorders, including ALS. The liver X receptor beta (LXRbeta) receptor is involved in lipogenesis and cholesterol metabolism, and we previously found that adult-onset motor neuron pathology occurs in LXRbeta mice. Here, we investigated neuromuscular alterations of LXRbeta mice from ages 3 to 24 months. Increased cholesterol levels, gliosis, and inflammation preceded motor neuron loss and clinical disease onset; the mice showed progressivemotor neuron deficits starting from age 7 months. The numbers ofmotor neurons and neuromuscular junctions were decreased in 24-month-old mice, but neither paralysis nor reduced life span was observed. Moreover, other spinal neurons were also lost in these mice. These results suggest that LXRbeta may inhibit neuroinflammation and maintain cholesterol homeostasis, and that LXRbeta mice represent a potential model for investigating the role of cholesterol in ALS and other neurodegenerative disorders.

  8. Reduced neuronal size and mTOR pathway activity in the Mecp2 A140V Rett syndrome mouse model

    PubMed Central

    Rangasamy, Sampathkumar; Olfers, Shannon; Gerald, Brittany; Hilbert, Alex; Svejda, Sean; Narayanan, Vinodh

    2016-01-01

    Rett syndrome (RTT) is a neurodevelopmental disorder caused by mutation in the X-linked MECP2 gene, encoding methyl-CpG-binding protein 2. We have created a mouse model ( Mecp2 A140V “knock-in” mutant) expressing the recurrent human MECP2 A140V mutation linked to an X-linked mental retardation/Rett syndrome phenotype. Morphological analyses focused on quantifying soma and nucleus size were performed on primary hippocampus and cerebellum granule neuron (CGN) cultures from mutant ( Mecp2 A140V/y) and wild type ( Mecp2 +/y) male mice. Cultured hippocampus and cerebellar granule neurons from mutant animals were significantly smaller than neurons from wild type animals. We also examined soma size in hippocampus neurons from individual female transgenic mice that express both a mutant  (maternal allele) and a wild type Mecp2 gene linked to an eGFP transgene (paternal allele). In cultures from such doubly heterozygous female mice, the size of neurons expressing the mutant (A140V) allele also showed a significant reduction compared to neurons expressing wild type MeCP2, supporting a cell-autonomous role for MeCP2 in neuronal development. IGF-1 (insulin growth factor-1) treatment of neuronal cells from Mecp2 mutant mice rescued the soma size phenotype. We also found that Mecp2   mutation leads to down-regulation of the mTOR signaling pathway, known to be involved in neuronal size regulation. Our results suggest that i) reduced neuronal size is an important in vitro cellular phenotype of Mecp2 mutation in mice, and ii) MeCP2 might play a critical role in the maintenance of neuronal structure by modulation of the mTOR pathway. The definition of a quantifiable cellular phenotype supports using neuronal size as a biomarker in the development of a high-throughput, in vitro assay to screen for compounds that rescue small neuronal phenotype (“phenotypic assay”). PMID:27781091

  9. 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

  10. Increased white matter neuron density in a rat model of maternal immune activation - Implications for schizophrenia.

    PubMed

    Duchatel, Ryan J; Jobling, Phillip; Graham, Brett A; Harms, Lauren R; Michie, Patricia T; Hodgson, Deborah M; Tooney, Paul A

    2016-02-01

    Interstitial neurons are located among white matter tracts of the human and rodent brain. Post-mortem studies have identified increased interstitial white matter neuron (IWMN) density in the fibre tracts below the cortex in people with schizophrenia. The current study assesses IWMN pathology in a model of maternal immune activation (MIA); a risk factor for schizophrenia. Experimental MIA was produced by an injection of polyinosinic:polycytidylic acid (PolyI:C) into pregnant rats on gestational day (GD) 10 or GD19. A separate control group received saline injections. The density of neuronal nuclear antigen (NeuN(+)) and somatostatin (SST(+)) IWMNs was determined in the white matter of the corpus callosum in two rostrocaudally adjacent areas in the 12week old offspring of GD10 (n=10) or GD19 polyI:C dams (n=18) compared to controls (n=20). NeuN(+) IWMN density trended to be higher in offspring from dams exposed to polyI:C at GD19, but not GD10. A subpopulation of these NeuN(+) IWMNs was shown to express SST. PolyI:C treatment of dams induced a significant increase in the density of SST(+) IWMNs in the offspring when delivered at both gestational stages with more regionally widespread effects observed at GD19. A positive correlation was observed between NeuN(+) and SST(+) IWMN density in animals exposed to polyI:C at GD19, but not controls. This is the first study to show that MIA increases IWMN density in adult offspring in a similar manner to that seen in the brain in schizophrenia. This suggests the MIA model will be useful in future studies aimed at probing the relationship between IWMNs and schizophrenia.

  11. Increased white matter neuron density in a rat model of maternal immune activation - Implications for schizophrenia.

    PubMed

    Duchatel, Ryan J; Jobling, Phillip; Graham, Brett A; Harms, Lauren R; Michie, Patricia T; Hodgson, Deborah M; Tooney, Paul A

    2016-02-01

    Interstitial neurons are located among white matter tracts of the human and rodent brain. Post-mortem studies have identified increased interstitial white matter neuron (IWMN) density in the fibre tracts below the cortex in people with schizophrenia. The current study assesses IWMN pathology in a model of maternal immune activation (MIA); a risk factor for schizophrenia. Experimental MIA was produced by an injection of polyinosinic:polycytidylic acid (PolyI:C) into pregnant rats on gestational day (GD) 10 or GD19. A separate control group received saline injections. The density of neuronal nuclear antigen (NeuN(+)) and somatostatin (SST(+)) IWMNs was determined in the white matter of the corpus callosum in two rostrocaudally adjacent areas in the 12week old offspring of GD10 (n=10) or GD19 polyI:C dams (n=18) compared to controls (n=20). NeuN(+) IWMN density trended to be higher in offspring from dams exposed to polyI:C at GD19, but not GD10. A subpopulation of these NeuN(+) IWMNs was shown to express SST. PolyI:C treatment of dams induced a significant increase in the density of SST(+) IWMNs in the offspring when delivered at both gestational stages with more regionally widespread effects observed at GD19. A positive correlation was observed between NeuN(+) and SST(+) IWMN density in animals exposed to polyI:C at GD19, but not controls. This is the first study to show that MIA increases IWMN density in adult offspring in a similar manner to that seen in the brain in schizophrenia. This suggests the MIA model will be useful in future studies aimed at probing the relationship between IWMNs and schizophrenia. PMID:26385575

  12. 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

  13. 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

  14. 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

  15. Optimal design of minimum-power stimuli for phase models of neuron oscillators

    NASA Astrophysics Data System (ADS)

    Dasanayake, Isuru; Li-Shin, Jr.

    2011-06-01

    In this paper, we study optimal control problems of spiking neurons whose dynamics are described by a phase model. We design minimum-power current stimuli (controls) that lead to targeted spiking times. In particular, we consider bounded control amplitude and characterize the range of possible spiking times determined by the bound, which can be chosen sufficiently small within the range where the phase model is valid. We show that for a given bound the corresponding feasible spiking times are optimally achieved by piecewise continuous controls. We present analytic expressions with numerical simulations of the minimum-power stimuli for several phase models. We demonstrate the applicability of our method with an experimentally determined phase response curve.

  16. Irrelevant sensory stimuli interfere with working memory storage: evidence from a computational model of prefrontal neurons.

    PubMed

    Bancroft, Tyler D; Hockley, William E; Servos, Philip

    2013-03-01

    The encoding of irrelevant stimuli into the memory store has previously been suggested as a mechanism of interference in working memory (e.g., Lange & Oberauer, Memory, 13, 333-339, 2005; Nairne, Memory & Cognition, 18, 251-269, 1990). Recently, Bancroft and Servos (Experimental Brain Research, 208, 529-532, 2011) used a tactile working memory task to provide experimental evidence that irrelevant stimuli were, in fact, encoded into working memory. In the present study, we replicated Bancroft and Servos's experimental findings using a biologically based computational model of prefrontal neurons, providing a neurocomputational model of overwriting in working memory. Furthermore, our modeling results show that inhibition acts to protect the contents of working memory, and they suggest a need for further experimental research into the capacity of vibrotactile working memory.

  17. 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).

  18. Enhancement of a robust arcuate GABAergic input to gonadotropin-releasing hormone neurons in a model of polycystic ovarian syndrome.

    PubMed

    Moore, Aleisha M; Prescott, Mel; Marshall, Christopher J; Yip, Siew Hoong; Campbell, Rebecca E

    2015-01-13

    Polycystic ovarian syndrome (PCOS), the leading cause of female infertility, is associated with an increase in luteinizing hormone (LH) pulse frequency, implicating abnormal steroid hormone feedback to gonadotropin-releasing hormone (GnRH) neurons. This study investigated whether modifications in the synaptically connected neuronal network of GnRH neurons could account for this pathology. The PCOS phenotype was induced in mice following prenatal androgen (PNA) exposure. Serial blood sampling confirmed that PNA elicits increased LH pulse frequency and impaired progesterone negative feedback in adult females, mimicking the neuroendocrine abnormalities of the clinical syndrome. Imaging of GnRH neurons revealed greater dendritic spine density that correlated with increased putative GABAergic but not glutamatergic inputs in PNA mice. Mapping of steroid hormone receptor expression revealed that PNA mice had 59% fewer progesterone receptor-expressing cells in the arcuate nucleus of the hypothalamus (ARN). To address whether increased GABA innervation to GnRH neurons originates in the ARN, a viral-mediated Cre-lox approach was taken to trace the projections of ARN GABA neurons in vivo. Remarkably, projections from ARN GABAergic neurons heavily contacted and even bundled with GnRH neuron dendrites, and the density of fibers apposing GnRH neurons was even greater in PNA mice (56%). Additionally, this ARN GABA population showed significantly less colocalization with progesterone receptor in PNA animals compared with controls. Together, these data describe a robust GABAergic circuit originating in the ARN that is enhanced in a model of PCOS and may underpin the neuroendocrine pathophysiology of the syndrome.

  19. 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.

  20. VMAT2 and dopamine neuron loss in a primate model of Parkinson’s disease

    PubMed Central

    Chen, Ming-Kai; Kuwabara, Hiroto; Zhou, Yun; Adams, Robert J.; Brašić, James R.; McGlothan, Jennifer L.; Verina, Tatyana; Burton, Neal C.; Alexander, Mohab; Kumar, Anil; Wong, Dean F.; Guilarte, Tomás R.

    2014-01-01

    We used positron emission tomography (PET) to measure the earliest change in dopaminergic synapses and glial cell markers in a chronic, low-dose MPTP non-human primate model of Parkinson’s disease (PD). In vivo levels of dopamine transporters (DAT), vesicular monoamine transporter-type 2 (VMAT2), amphetamine-induced dopamine release (AMPH-DAR), D2-dopamine receptors (D2R) and translocator protein 18 kDa (TSPO) were measured longitudinally in the striatum of MPTP-treated animals. We report an early (2 months) decrease (46%) of striatal VMAT2 in asymptomatic MPTP animals that preceded changes in DAT, D2R, and AMPH-DAR and was associated with increased TSPO levels indicative of a glial response. Subsequent PET studies showed progressive loss of all pre-synaptic dopamine markers in the striatum with expression of parkinsonism. However, glial cell activation did not track disease progression. These findings indicate that decreased VMAT2 is a key pathogenic event that precedes nigrostriatal dopamine neuron degeneration. The loss of VMAT2 may result from an association with α-synuclein aggregation induced by oxidative stress. Disruption of dopamine sequestration by reducing VMAT2 is an early pathogenic event in the dopamine neuron degeneration that occurs in the MPTP non-human primate model of PD. Genetic or environmental factors that decrease VMAT2 function may be important determinants of PD. PMID:17988241

  1. 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

  2. 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

  3. 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.

  4. Alterations in mitochondrial dynamics induced by tebufenpyrad and pyridaben in a dopaminergic neuronal cell culture model.

    PubMed

    Charli, Adhithiya; Jin, Huajun; Anantharam, Vellareddy; Kanthasamy, Arthi; Kanthasamy, Anumantha G

    2016-03-01

    Tebufenpyrad and pyridaben are two agro-chemically important acaricides that function like the known mitochondrial toxicant rotenone. Although these two compounds have been commonly used to kill populations of mites and ticks in commercial greenhouses, their neurotoxic profiles remain largely unknown. Therefore, we investigated the effects of these two pesticides on mitochondrial structure and function in an in vitro cell culture model using the Seahorse bioanalyzer and confocal fluorescence imaging. The effects were compared with rotenone. Exposing rat dopaminergic neuronal cells (N27 cells) to tebufenpyrad and pyridaben for 3h induced dose-dependent cell death with an EC50 of 3.98μM and 3.77μM, respectively. Also, tebufenpyrad and pyridaben (3μM) exposure induced reactive oxygen species (ROS) generation and m-aconitase damage, suggesting that the pesticide toxicity is associated with oxidative damage. Morphometric image analysis with the MitoTracker red fluorescent probe indicated that tebufenpyrad and pyridaben, as well as rotenone, caused abnormalities in mitochondrial morphology, including reduced mitochondrial length and circularity. Functional bioenergetic experiments using the Seahorse XF96 analyzer revealed that tebufenpyrad and pyridaben very rapidly suppressed the basal mitochondrial oxygen consumption rate similar to that of rotenone. Further analysis of bioenergetic curves also revealed dose-dependent decreases in ATP-linked respiration and respiratory capacity. The luminescence-based ATP measurement further confirmed that pesticide-induced mitochondrial inhibition of respiration is accompanied by the loss of cellular ATP. Collectively, our results suggest that exposure to the pesticides tebufenpyrad and pyridaben induces neurotoxicity by rapidly initiating mitochondrial dysfunction and oxidative damage in dopaminergic neuronal cells. Our findings also reveal that monitoring the kinetics of mitochondrial respiration with Seahorse could be used as an

  5. Hypothalamic dopaminergic neurons in an animal model of seasonal affective disorder.

    PubMed

    Deats, Sean P; Adidharma, Widya; Yan, Lily

    2015-08-18

    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 12:12 h dim light:dark (DLD) or 8:16 h 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 12:12 h bright light:dark (BLD) condition. Furthermore, we have shown 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.

  6. 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.

  7. 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

  8. A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.

    PubMed

    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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. Neuronal periodicity detection as a basis for the perception of consonance: a mathematical model of tonal fusion.

    PubMed

    Ebeling, Martin

    2008-10-01

    A mathematical model is presented here to explain the sensation of consonance and dissonance on the basis of neuronal coding and the properties of a neuronal periodicity detection mechanism. This mathematical model makes use of physiological data from a neuronal model of periodicity analysis in the midbrain, whose operation can be described mathematically by autocorrelation functions with regard to time windows. Musical intervals produce regular firing patterns in the auditory nerve that depend on the vibration ratio of the two tones. The mathematical model makes it possible to define a measure for the degree of these regularities for each vibration ratio. It turns out that this measure value is in line with the degree of tonal fusion as described by Stumpf [Tonpsychologie (Psychology of Tones) (Knuf, Hilversum), reprinted 1965]. This finding makes it probable that tonal fusion is a consequence of certain properties of the neuronal periodicity detection mechanism. Together with strong roughness resulting from interval tones with fundamentals close together or close to the octave, this neuronal mechanism may be regarded as the basis of consonance and dissonance.

  16. M-type potassium conductance controls the emergence of neural phase codes: a combined experimental and neuron modelling study.

    PubMed

    Kwag, Jeehyun; Jang, Hyun Jae; Kim, Mincheol; Lee, Sujeong

    2014-10-01

    Rate and phase codes are believed to be important in neural information processing. Hippocampal place cells provide a good example where both coding schemes coexist during spatial information processing. Spike rate increases in the place field, whereas spike phase precesses relative to the ongoing theta oscillation. However, what intrinsic mechanism allows for a single neuron to generate spike output patterns that contain both neural codes is unknown. Using dynamic clamp, we simulate an in vivo-like subthreshold dynamics of place cells to in vitro CA1 pyramidal neurons to establish an in vitro model of spike phase precession. Using this in vitro model, we show that membrane potential oscillation (MPO) dynamics is important in the emergence of spike phase codes: blocking the slowly activating, non-inactivating K+ current (IM), which is known to control subthreshold MPO, disrupts MPO and abolishes spike phase precession. We verify the importance of adaptive IM in the generation of phase codes using both an adaptive integrate-and-fire and a Hodgkin-Huxley (HH) neuron model. Especially, using the HH model, we further show that it is the perisomatically located IM with slow activation kinetics that is crucial for the generation of phase codes. These results suggest an important functional role of IM in single neuron computation, where IM serves as an intrinsic mechanism allowing for dual rate and phase coding in single neurons.

  17. 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

  18. Multiscale coupling of transcranial direct current stimulation to neuron electrodynamics: modeling the influence of the transcranial electric field on neuronal depolarization.

    PubMed

    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.

  19. 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

  20. 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

  1. Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex.

    PubMed

    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.

  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. Primary cultures of cerebellar neurons: A unique model for studying benzodiazepine receptors

    SciTech Connect

    Allen, A.J.

    1988-01-01

    The binding of ({sup 3}H)flunitrazepam to intact cultures of cerebellar neurons was studied at 24{degree}C. Association of 1 nM ({sup 3}H)flunitrazepam was monophasic, k{sub +1} = 1.41 pmole{sup {minus}1} sec{sup {minus}1}. Dissociation was approximately monophasic, k{sub {minus}1} = 0.0145 sec{sup {minus}1}. The presence of 1 {mu}M diazepam in the diluting buffer significantly accelerated initial dissociation of ({sup 3}H)flunitrazepam. Saturation binding studies revealed a nonlinear Scatchard plot with a Hill coefficient (n{sub H}) of 0.81 and K{sub 0.5} = 28.7 nM. The data fit equally well a model with two independent binding sites, and a stoichiometric equation utilizing pairwise interactions between four sites. A newly developed HPLC method was used for rapid, sensitive, and quantitative detection of amino acid neutrotransmitters and adenosine released from cerebellar neurons in culture. In preliminary studies, this technique was coupled with a specially designed perfusion chamber to demonstrate that flunitrazepam enhances potassium-stimulated release of glutamate and GABA, and may inhibit basal release of taurine.

  4. 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

  5. Possible effects of depolarizing GABAA conductance on the neuronal input-output relationship: a modeling study.

    PubMed

    Morita, Kenji; Tsumoto, Kunichika; Aihara, Kazuyuki

    2005-06-01

    Recent in vitro experiments revealed that the GABAA reversal potential is about 10 mV higher than the resting potential in mature mammalian neocortical pyramidal cells; thus GABAergic inputs could have facilitatory, rather than inhibitory, effects on action potential generation under certain conditions. However, how the relationship between excitatory input conductances and the output firing rate is modulated by such depolarizing GABAergic inputs under in vivo circumstances has not yet been understood. We examine herewith the input-output relationship in a simple conductance-based model of cortical neurons with the depolarized GABAA reversal potential, and show that a tonic depolarizing GABAergic conductance up to a certain amount does not change the relationship between a tonic glutamatergic driving conductance and the output firing rate, whereas a higher GABAergic conductance prevents spike generation. When the tonic glutamatergic and GABAergic conductances are replaced by in vivo-like highly fluctuating inputs, on the other hand, the effect of depolarizing GABAergic inputs on the input-output relationship critically depends on the degree of coincidence between glutamatergic input events and GABAergic ones. Although a wide range of depolarizing GABAergic inputs hardly changes the firing rate of a neuron driven by noncoincident glutamatergic inputs, a certain range of these inputs considerably decreases the firing rate if a large number of driving glutamatergic inputs are coincident with them. These results raise the possibility that the depolarized GABAA reversal potential is not a paradoxical mystery, but is instead a sophisticated device for discriminative firing rate modulation.

  6. 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

  7. An integrate-and-fire model of prefrontal cortex neuronal activity during performance of goal-directed decision making.

    PubMed

    Koene, Randal A; Hasselmo, Michael E

    2005-12-01

    The orbital frontal cortex appears to be involved in learning the rules of goal-directed behavior necessary to perform the correct actions based on perception to accomplish different tasks. The activity of orbitofrontal neurons changes dependent upon the specific task or goal involved, but the functional role of this activity in performance of specific tasks has not been fully determined. Here we present a model of prefrontal cortex function using networks of integrate-and-fire neurons arranged in minicolumns. This network model forms associations between representations of sensory input and motor actions, and uses these associations to guide goal-directed behavior. The selection of goal-directed actions involves convergence of the spread of activity from the goal representation with the spread of activity from the current state. This spiking network model provides a biological implementation of the action selection process used in reinforcement learning theory. The spiking activity shows properties similar to recordings of orbitofrontal neurons during task performance.

  8. 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

  9. 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

  10. Sensitization of lamina I spinoparabrachial neurons parallels heat hyperalgesia in the chronic constriction injury model of neuropathic pain.

    PubMed

    Andrew, David

    2009-05-01

    It has been proposed that spinal lamina I neurons with ascending axons that project to the midbrain play a crucial role in hyperalgesia. To test this hypothesis the quantitative properties of lamina I spinoparabrachial neurons in the chronic constriction injury (CCI) model of neuropathic pain were compared to those of unoperated and sham-operated controls. Behavioural testing showed that animals with a CCI exhibited heat hyperalgesia within 4 days of the injury, and this hyperalgesia persisted throughout the 14-day post-operative testing period. In the CCI, nociceptive lamina I spinoparabrachial neurons had heat thresholds that were significantly lower than controls (43.0 +/- 2.8 degrees C vs. 46.7 +/- 2.6 degrees C; P < 10(-4), ANOVA). Nociceptive lamina I spinoparabrachial neurons were also significantly more responsive to graded heat stimuli in the CCI, compared to controls (P < 0.02, 2-factor repeated-measures ANOVA), and increased after-discharges were also observed. Furthermore, the heat-evoked stimulus-response functions of lamina I spinoparabrachial neurons in CCI animals co-varied significantly (P < 0.03, ANCOVA) with the amplitude of heat hyperalgesia determined behaviourally. Taken together these results are consistent with the hypothesis that lamina I spinoparabrachial neurons have an important mechanistic role in the pathophysiology of neuropathic pain.

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. A Novel Protocol to Differentiate Induced Pluripotent Stem Cells by Neuronal microRNAs to Provide a Suitable Cellular Model.

    PubMed

    Zare, Mehrak; Soleimani, Masoud; Akbarzadeh, Abolfazl; Bakhshandeh, Behnaz; Aghaee-Bakhtiari, Seyed Hamid; Zarghami, Nosratollah

    2015-08-01

    Neurodegenerative diseases are one of the most challenging subjects in medicine. Investigation of their underlying genetic or epigenetic factors is hampered by lack of suitable models. Patient-specific induced pluripotent stem cells (iPS cells) represent a valuable approach to provide a proper model for poorly understood mechanisms of neuronal diseases and the related drug screenings. miR-124 and miR-128 are the two brain-enriched miRNAs with different time-points of expression during neuronal development. Herein, we transduced human iPS cells with miR-124 and miR-128 harboring lentiviruses sequentially. The transduced plasmids contained GFP and puromycin antibiotic-resistant genes for easier selection and identification. Morphological assessment and immunocytochemistry (overexpressions of beta-tubulin and neuron-specific enolase) confirmed that induced hiPS cells by miR-124 and miR-128 represent similar characteristics to those of mature neurons. In addition, the upregulation of neuron-specific enolase, beta-tubulin, Map2, GFAP, and BDNF was detected by quantitative real-time PCR. In conclusion, it seems that our novel protocol remarks the combinatorial effect of miR-124 and miR-128 on neural differentiation in the absence of any extrinsic factor. Moreover, such cellular models could be used in personalized drug screening and applied for more effective therapies.

  18. 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

  19. Conditional ablation of orexin/hypocretin neurons: a new mouse model for the study of narcolepsy and orexin system function.

    PubMed

    Tabuchi, Sawako; Tsunematsu, Tomomi; Black, Sarah W; Tominaga, Makoto; Maruyama, Megumi; Takagi, Kazuyo; Minokoshi, Yasuhiko; Sakurai, Takeshi; Kilduff, Thomas S; Yamanaka, Akihiro

    2014-05-01

    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.

  20. Structural versus dynamical origins of mean-field behavior in a self-organized critical model of neuronal avalanches.

    PubMed

    Moosavi, S Amin; Montakhab, Afshin

    2015-01-01

    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.

  1. 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.

  2. Structural versus dynamical origins of mean-field behavior in a self-organized critical model of neuronal avalanches.

    PubMed

    Moosavi, S Amin; Montakhab, Afshin

    2015-01-01

    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

  3. 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

  4. Detailed numerical investigation of the dissipative stochastic mechanics based neuron model.

    PubMed

    Güler, Marifi

    2008-10-01

    Recently, a physical approach for the description of neuronal dynamics under the influence of ion channel noise was proposed in the realm of dissipative stochastic mechanics (Güler, Phys Rev E 76:041918, 2007). Led by the presence of a multiple number of gates in an ion channel, the approach establishes a viewpoint that ion channels are exposed to two kinds of noise: the intrinsic noise, associated with the stochasticity in the movement of gating particles between the inner and the outer faces of the membrane, and the topological noise, associated with the uncertainty in accessing the permissible topological states of open gates. Renormalizations of the membrane capacitance and of a membrane voltage dependent potential function were found to arise from the mutual interaction of the two noisy systems. The formalism therein was scrutinized using a special membrane with some tailored properties giving the Rose-Hindmarsh dynamics in the deterministic limit. In this paper, the resultant computational neuron model of the above approach is investigated in detail numerically for its dynamics using time-independent input currents. The following are the major findings obtained. The intrinsic noise gives rise to two significant coexisting effects: it initiates spiking activity even in some range of input currents for which the corresponding deterministic model is quiet and causes bursting in some other range of input currents for which the deterministic model fires tonically. The renormalization corrections are found to augment the above behavioral transitions from quiescence to spiking and from tonic firing to bursting, and, therefore, the bursting activity is found to take place in a wider range of input currents for larger values of the correction coefficients. Some findings concerning the diffusive behavior in the voltage space are also reported.

  5. Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering.

    PubMed

    Havlicek, Martin; Friston, Karl J; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D

    2011-06-15

    This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain. PMID:21396454

  6. 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

  7. Improved survival with an ambulatory model of non-invasive ventilation implementation in motor neuron disease.

    PubMed

    Sheers, Nicole; Berlowitz, David J; Rautela, Linda; Batchelder, Ian; Hopkinson, Kim; Howard, Mark E

    2014-06-01

    Non-invasive ventilation (NIV) increases survival and quality of life in motor neuron disease (MND). NIV implementation historically occurred during a multi-day inpatient admission at this institution; however, increased demand led to prolonged waiting times. The aim of this study was to evaluate the introduction of an ambulatory model of NIV implementation. A prospective cohort study was performed. Inclusion criteria were referral for NIV implementation six months pre- or post-commencement of the Day Admission model. This model involved a 4-h stay to commence ventilation with follow-up in-laboratory polysomnography titration and outpatient attendance. Outcome measures included waiting time, hospital length of stay, adverse events and polysomnography data. Results indicated that after changing to the Day Admission model the median waiting time fell from 30 to 13.5 days (p < 0.04) and adverse events declined (4/17 pre- (three deaths, one acute admission) vs. 0/12 post-). Survival was also prolonged (median (IQR) 278 (51-512) days pre- vs 580 (306-1355) days post-introduction of the Day Admission model; hazard ratio 0.41, p = 0.04). Daytime PaCO2 was no different. In conclusion, reduced waiting time to commence ventilation and improved survival were observed following introduction of an ambulatory model of NIV implementation in people with MND, with no change in the effectiveness of ventilation.

  8. The advantage of flexible neuronal tunings in neural network models for motor learning

    PubMed Central

    Marongelli, Ellisha N.; Thoroughman, Kurt A.

    2013-01-01

    Human motor adaptation to novel environments is often modeled by a basis function network that transforms desired movement properties into estimated forces. This network employs a layer of nodes that have fixed broad tunings that generalize across the input domain. Learning is achieved by updating the weights of these nodes in response to training experience. This conventional model is unable to account for rapid flexibility observed in human spatial generalization during motor adaptation. However, added plasticity in the widths of the basis function tunings can achieve this flexibility, and several neurophysiological experiments have revealed flexibility in tunings of sensorimotor neurons. We found a model, Locally Weighted Projection Regression (LWPR), which uniquely possesses the structure of a basis function network in which both the weights and tuning widths of the nodes are updated incrementally during adaptation. We presented this LWPR model with training functions of different spatial complexities and monitored incremental updates to receptive field widths. An inverse pattern of dependence of receptive field adaptation on experienced error became evident, underlying both a relationship between generalization and complexity, and a unique behavior in which generalization always narrows after a sudden switch in environmental complexity. These results implicate a model that is flexible in both basis function widths and weights, like LWPR, as a viable alternative model for human motor adaptation that can account for previously observed plasticity in spatial generalization. This theory can be tested by using the behaviors observed in our experiments as novel hypotheses in human studies. PMID:23888141

  9. 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.

  10. One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death III: diffusion pulse death zones.

    PubMed

    Lomasko, Tatiana; Lumsden, Charles J

    2009-01-01

    This is the third of three papers in which we study a mathematical model of cytoskeleton-induced neuron death. In the first two papers of this suite [Lomasko, T., Clarke, G., Lumsden, C., 2007a. One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death I: cell fate arrival times. J. Theor. Biol. 249, 1-17, doi:10.1016/j.jtbi.2007.05.031; Lomasko, T., Clarke, G., Lumsden, C., 2007b. One-hit stochastic decline in a mechanochemical model of cytoskeleton-induced neuron death II: transition state metastability. J. Theor. Biol. 249, 18-28, doi:10.1016/j.jtbi.2007.05.032], we established that the mean-field limit of our model relates the known patterns of neuron decline to specific scales of cytoskeleton reorganization and cell-cell interaction by diffusible death factors. In the mean-field limit, the spatially variable concentration of diffusing death factor is replaced by a constant average value. Recent empirical advances now permit the actual diffusion of such factors to be followed in intact neuropil. In this paper we therefore extend the model beyond the mean-field limit, to include the diffusion dynamics of death factor bursts released from dying neurons. A range of novel tissue degeneration patterns is observed, for which we confirm and extend the mean-field prediction that sigmoidal patterns of neuron population decay are a principal hallmark of cell death in the presence of death factor release.

  11. 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.

  12. Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons

    NASA Astrophysics Data System (ADS)

    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.

  13. Neuronal dynamics during the learning of trace conditioning in a CA3 model of hippocampal function.

    PubMed

    Thomas, Blake T; Levy, William B

    2014-04-01

    The present article develops quantitative behavioral and neurophysiological predictions for rabbits trained on an air-puff version of the trace-interval classical conditioning paradigm. Using a minimal hippocampal model, consisting of 8,000 primary cells sparsely and randomly interconnected as a model of hippocampal region CA-3, the simulations identify conditions which produce a clear split in the number of trials individual animals should need to learn a criterion response. A trace interval that is difficult to learn, but still learnable by half the experimental population, produces a bimodal population of learners: an early learner group and a late learner group. The model predicts that late learners are characterized by two kinds of CA-3 neuronal activity fluctuations that are not seen in the early learners. As is typical in our minimal hippocampal models, the off-rate constant of the N-methyl-d-aspartate receptor receptor gives a timescale to the model that leads to a temporally quantifiable behavior, the learnable trace interval.

  14. 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.

  15. 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

  16. 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.

  17. Macro- and micro-chaotic structures in the Hindmarsh-Rose model of bursting neurons.

    PubMed

    Barrio, Roberto; Martínez, M Angeles; Serrano, Sergio; 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.

  18. 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

  19. Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

    PubMed

    Ponzi, Adam; Wickens, Jeff

    2012-01-01

    The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

  20. Input Dependent Cell Assembly Dynamics in a Model of the Striatal Medium Spiny Neuron Network

    PubMed Central

    Ponzi, Adam; Wickens, Jeff

    2012-01-01

    The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior. PMID:22438838

  1. Implementation of an integrated op-amp based chaotic neuron model and observation of its chaotic dynamics.

    PubMed

    Jung, Jinwoo; Lee, Jewon; Song, Hanjung

    2011-03-01

    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-μm 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.

  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. Reduced survival of motor neuron (SMN) protein in motor neuronal progenitors functions cell autonomously to cause spinal muscular atrophy in model mice expressing the human centromeric (SMN2) gene.

    PubMed

    Park, Gyu-Hwan; Maeno-Hikichi, Yuka; Awano, Tomoyuki; Landmesser, Lynn T; Monani, Umrao R

    2010-09-01

    Spinal muscular atrophy (SMA) is a common (approximately 1:6400) autosomal recessive neuromuscular disorder caused by a paucity of the survival of motor neuron (SMN) protein. Although widely recognized to cause selective spinal motor neuron loss when deficient, the precise cellular site of action of the SMN protein in SMA remains unclear. In this study we sought to determine the consequences of selectively depleting SMN in the motor neurons of model mice. Depleting but not abolishing the protein in motor neuronal progenitors causes an SMA-like phenotype. Neuromuscular weakness in the model mice is accompanied by peripheral as well as central synaptic defects, electrophysiological abnormalities of the neuromuscular junctions, muscle atrophy, and motor neuron degeneration. However, the disease phenotype is more modest than that observed in mice expressing ubiquitously low levels of the SMN protein, and both symptoms as well as early electrophysiological abnormalities that are readily apparent in neonates were attenuated in an age-dependent manner. We conclude that selective knock-down of SMN in motor neurons is sufficient but may not be necessary to cause a disease phenotype and that targeting these cells will be a requirement of any effective therapeutic strategy. This realization is tempered by the relatively mild SMA phenotype in our model mice, one explanation for which is the presence of normal SMN levels in non-neuronal tissue that serves to modulate disease severity.

  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. 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.

  7. A Transgenic Mouse Model Reveals Fast Nicotinic Transmission in Hippocampal Pyramidal Neurons

    PubMed Central

    Grybko, Michael J.; Hahm, Eu-teum; Perrine, Wesley; Parnes, Jason A.; Chick, Wallace S.; Sharma, Geeta; Finger, Thomas E.; Vijayaraghavan, Sukumar

    2011-01-01

    The relative contribution, to brain cholinergic signaling, by synaptic- and diffusion-based mechanisms remains to be elucidated. In this study, we examined the prevalence of fast nicotinic signaling in the hippocampus. We describe a mouse model where cholinergic axons are labeled with the tauGFP fusion protein driven by the choline acetyltransferase (ChAT) promoter. The model provides for the visualization of individual cholinergic axons at greater resolution than other available models and techniques, even in thick, live, slices. Combining calcium imaging and electrophysiology, we demonstrate that local stimulation of visualized cholinergic fibers results in rapid EPSCs mediated by the activation of α7-subunit containing nicotinic receptors (α7-nAChRs) on CA3 pyramidal neurons. These responses were blocked by the α7-nAChR antagonist methyllycaconitine (MLA) and potentiated by the receptor specific allosteric modulator 1-(5-chloro-2,4- dimethoxy-phenyl)-3-(5-methyl-isoxanol-3-yl)-urea (PNU-120596). Our results suggest, for the first time, that synaptic nAChRs can modulate pyrami