Science.gov

Sample records for model neurons nt2

  1. Integration of human model neurons (NT2) into embryonic chick nervous system.

    PubMed

    Podrygajlo, Grzegorz; Wiegreffe, Christoph; Scaal, Martin; Bicker, Gerd

    2010-02-01

    Postmitotic neurons were generated from the human NT2 teratocarcinoma cell line in a novel cell aggregate differentiation procedure. Approximately a third of the differentiated neurons expressed cell markers related to cholinergic neurotransmission. To examine whether this human cell model system can be directed toward a motoneuronal fate, postmitotic neurons were co-cultured with mouse myotubes. Outgrowing neuronal processes established close contact with the myotubes and formed neuromuscular junction-like structures that bound alpha-bungarotoxin. To determine how grafted precursor cells and neurons respond to embryonic nerve tissue, NT2 cells at different stages of neural development were injected into chick embryo neural tube and brain. Grafted NT2 neurons populated both parts of the nervous system, sometimes migrating away from the site of injection. The neural tube appeared to be more permissive for neurite extensions than the brain. Moreover, extending neurites of spinal grafts were approaching the ventral roots, thus resembling motoneuronal projections.

  2. 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

  3. 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

  4. 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.

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

    PubMed

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

    2013-12-01

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

  6. 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.

  7. Cyanide preconditioning protects brain endothelial and NT2 neuron-like cells against glucotoxicity: role of mitochondrial reactive oxygen species and HIF-1α.

    PubMed

    Correia, Sónia C; Santos, Renato X; Cardoso, Sandra M; Santos, Maria S; Oliveira, Catarina R; Moreira, Paula I

    2012-01-01

    The current study was undertaken to address the role of mitochondrial reactive oxygen species (ROS), and hypoxia inducible factor-1 alpha (HIF-1α) signaling pathway in the protection against high glucose levels in brain endothelial and NT2 neuron-like cells. Rat brain endothelial cells (RBE4) treated with non-toxic concentrations of cyanide (≤1 μM; 1h) exhibited an increase in ROS levels, particularly hydrogen peroxide (H(2)O(2)). Cyanide also induced a modest mitochondrial depolarization, an increase in oxygen consumption and a structural (smaller mitochondria) and spatial (perinuclear region) reorganization of mitochondrial network. The stabilization and nuclear activation of HIF-1α in the presence of cyanide were also observed, which resulted in an increase in vascular endothelial growth factor (VEGF), endothelial nitric oxide synthase (eNOS) and erythropoietin (EPO) protein levels reflecting an adaptive response. Importantly, preconditioning induced by cyanide protected brain endothelial cells against high glucose-mediated damage by the prevention of apoptotic cell death. In mitochondrial DNA-depleted NT2 (NT2 ρ0) cells, cyanide (0.1 μM) was unable to stimulate ROS production and, consequently, protect against glucotoxicity. Conversely, in NT2 cells, the parental cells with functional mitochondria, cyanide significantly increased ROS levels protecting against high glucose-induced neuronal cell loss and activation of caspase-3. The free radical scavenger N-acetyl-L-cysteine and the specific HIF-1α inhibitor 2-methoxyestradiol completely abolished the protective effects of cyanide preconditioning. Altogether our results demonstrate that mitochondrial preconditioning induced by cyanide triggers a protective response mediated by mitochondrial ROS and HIF-1α activation and signaling, which render brain endothelial and neuronal cells resistant against glucotoxicity.

  8. Transcriptional activation of the human brain-derived neurotrophic factor gene promoter III by dopamine signaling in NT2/N neurons.

    PubMed

    Fang, Hung; Chartier, Joanne; Sodja, Caroline; Desbois, Angele; Ribecco-Lutkiewicz, Maria; Walker, P Roy; Sikorska, Marianna

    2003-07-18

    We have identified a functional cAMP-response element (CRE) in the human brain-derived neurotrophic factor (BDNF) gene promoter III and established that it participated in the modulation of BDNF expression in NT2/N neurons via downstream signaling from the D1 class of dopamine (DA) receptors. The up-regulation of BDNF expression, in turn, produced neuroprotective signals through receptor tyrosine kinase B (TrkB) and promoted cell survival under the conditions of oxygen and glucose deprivation. To our knowledge this is the first evidence showing the presence of a functional CRE in the human BDNF gene and the role of DA signaling in establishing transcriptional competence of CRE in post-mitotic NT2/N neurons. This ability of DA to regulate the expression of the BDNF survival factor has a profound significance for the nigrostriatal pathway, because it indicates the existence of a feedback loop between the neutrophin, which promotes both the maturation and survival of dopaminergic neurons, and the neurotransmitter, which the mature neurons ultimately produce and release.

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

    PubMed Central

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

    2013-01-01

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

  10. 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

    DTIC Science & Technology

    2012-01-01

    eliminate experimental bias; the data were analyzed and unblinded by the statistician at the end of the experiment . 2.5.3. Excitotoxic Spinal Cord...conditions to eliminate experimental bias; the data were analyzed and un-blinded by the statistician at the end of the experiment . 2.6. Sensory Behavioral...buffer, pH 7.4. All immunohistochemistry experiments included the use of a negative control, sub- stitution of specific primary antibody with species IgG

  11. SOX2 overexpression affects neural differentiation of human pluripotent NT2/D1 cells.

    PubMed

    Klajn, A; Drakulic, D; Tosic, M; Pavkovic, Z; Schwirtlich, M; Stevanovic, M

    2014-11-01

    SOX2 is one of the key transcription factors involved in maintenance of neural progenitor identity. However, its function during the process of neural differentiation, including phases of lineage-specification and terminal differentiation, is still poorly understood. Considering growing evidence indicating that SOX2 expression level must be tightly controlled for proper neural development, the aim of this research was to analyze the effects of constitutive SOX2 overexpression on outcome of retinoic acid-induced neural differentiation of pluripotent NT2/D1 cells. We demonstrated that in spite of constitutive SOX2 overexpression, NT2/D1 cells were able to reach final phases of neural differentiation yielding both neuronal and glial cells. However, SOX2 overexpression reduced the number of mature MAP2-positive neurons while no difference in the number of GFAP-positive astrocytes was detected. In-depth analysis at single-cell level showed that SOX2 downregulation was in correlation with both neuronal and glial phenotype acquisitions. Interestingly, while in mature neurons SOX2 was completely downregulated, astrocytes with low level of SOX2 expression were detected. Nevertheless, cells with high level of SOX2 expression were incapable of entering in either of two differentiation pathways, neurogenesis or gliogenesis. Accordingly, our results indicate that fine balance between undifferentiated state and neural differentiation depends on SOX2 expression level. Unlike neurons, astrocytes could maintain low level of SOX2 expression after they acquired glial fate. Further studies are needed to determine whether differences in the level of SOX2 expression in GFAP-positive astrocytes are in correlation with their self-renewal capacity, differentiation status, and/or their phenotypic characteristics.

  12. Crosstalk between SOXB1 proteins and WNT/β-catenin signaling in NT2/D1 cells.

    PubMed

    Mojsin, Marija; Topalovic, Vladanka; Vicentic, Jelena Marjanovic; Schwirtlich, Marija; Stanisavljevic, Danijela; Drakulic, Danijela; Stevanovic, Milena

    2015-11-01

    During early vertebrate embryogenesis, the expression of SOXB1 proteins is precisely regulated by a number of different mechanisms, including Wnt/β-catenin signaling. This is essential for controlling the balance between stemness and differentiation in embryonic stem cells. In the present study, we analyzed the molecular mechanism of LiCl action in NT2/D1 cells and examined the crosstalk between SOXB1 proteins and Wnt signaling in this model system. We have shown that LiCl increases β-catenin level, induces its translocation to the nucleus and consequently up-regulates β-catenin/Tcf-dependent transcription in NT2/D1 cells. Our results also suggest that LiCl treatment leads to increased expression of SOX2 and SOX3 proteins in NT2/D1 cells through activation of canonical Wnt signaling. Finally, we have detected a negative feedback loop between β-catenin and SOX2 expression in NT2/D1 cells. Since β-catenin and SOX2 have been linked to processes of self-renewal and pluripotency, our results have implications for future research on the maintenance of stemness and lineage commitment of embryonic stem cells.

  13. Evaluation of Human and Nonhuman Primate Antibody Binding to Pig Cells Lacking GGTA1/CMAH/β4GalNT2 Genes

    PubMed Central

    Estrada, J; Martens, G; Li, P; Adams, AB; Newell, KA; Ford, ML; Butler, JR; Sidner, RA; Tector, M; Tector, AJ

    2015-01-01

    Background Simultaneous inactivation of pig GGTA1 and CMAH genes eliminates carbohydrate xenoantigens recognized by human antibodies. The β4GalNT2 glycosyltransferase may also synthesize xenoantigens. To further characterize glycan-based species incompatibilities, we examined human and non-human primate antibody binding to cells derived from genetically modified pigs lacking these carbohydrate-modifying genes. Methods The Cas9 endonuclease and gRNA were used to create pigs lacking GGTA1, GGTA1/CMAH, or GGTA1/CMAH/β4GalNT2 genes. Peripheral blood mononuclear cells were isolated from these animals and examined for binding to IgM and IgG from humans, rhesus macaques, and baboons. Results Cells from GGTA1/CMAH/β4GalNT2 deficient pigs exhibited reduced human IgM and IgG binding compared to cells lacking both GGTA1 and CMAH. Nonhuman primate antibody reactivity with cells from the various pigs exhibited a slightly different pattern of reactivity than that seen in humans. Simultaneous inactivation of the GGTA1 and CMAH genes increased nonhuman primate antibody binding compared to cells lacking either GGTA1 only or to those deficient in GGTA1/CMAH/β4GalNT2. Conclusions Inactivation of the β4GalNT2 gene reduces human and nonhuman primate antibody binding resulting in diminished porcine xenoantigenicity. The increased humoral immunity of nonhuman primates towards GGTA1/CMAH-deficient cells compared to pigs lacking either GGTA1 or GGTA1/CMAH/β4GalNT2 highlights the complexities of carbohydrate xenoantigens and suggests potential limitations of the nonhuman primate model for examining some genetic modifications. The progressive reduction of swine xenoantigens recognized by human immunoglobulin through inactivation of pig GGTA1/CMAH/β4GalNT2 genes demonstrates that the antibody barrier to xenotransplantation can be minimized by genetic engineering. PMID:25728481

  14. Energy Model of Neuron Activation.

    PubMed

    Romanyshyn, Yuriy; Smerdov, Andriy; Petrytska, Svitlana

    2017-02-01

    On the basis of the neurophysiological strength-duration (amplitude-duration) curve of neuron activation (which relates the threshold amplitude of a rectangular current pulse of neuron activation to the pulse duration), as well as with the use of activation energy constraint (the threshold curve corresponds to the energy threshold of neuron activation by a rectangular current pulse), an energy model of neuron activation by a single current pulse has been constructed. The constructed model of activation, which determines its spectral properties, is a bandpass filter. Under the condition of minimum-phase feature of the neuron activation model, on the basis of Hilbert transform, the possibilities of phase-frequency response calculation from its amplitude-frequency response have been considered. Approximation to the amplitude-frequency response by the response of the Butterworth filter of the first order, as well as obtaining the pulse response corresponding to this approximation, give us the possibility of analyzing the efficiency of activating current pulses of various shapes, including analysis in accordance with the energy constraint.

  15. Expression of a novel splice variant of FRMD7 in developing human fetal brains that is upregulated upon the differentiation of NT2 cells

    PubMed Central

    LI, YINGZHI; PU, JIALI; ZHANG, BAORONG

    2014-01-01

    FRMD7 mutations are associated with X-linked idiopathic congenital nystagmus (ICN); however, the underlying mechanisms whereby mutations of FRMD7 lead to ICN remain unclear. In a previous study, the first FRMD7 splice variant (FRMD7-S) was cloned and identified, and FRMD7-S was hypothesized to play a significant role in neuronal differentiation and development. The present study investigated a novel multiple exon-skipping mRNA splice variant of FRMD7, termed FRMD7_SV2, which was detected in NT2 cells using northern blotting. The mRNA expression levels of FRMD7_SV2 in the developing human fetal brain were examined using reverse transcription polymerase chain reaction (PCR), while the expression levels in NT2 cells treated with retinoid acid (RA) or bone morphogenetic protein-2 were investigated using quantitative PCR. The results revealed that the expression of FRMD7_SV2 was spatially and temporally restricted in human fetal brain development, and was upregulated upon RA-induced neuronal differentiation of the NT2 cells. These results indicated that as a novel splice variant of FRMD7, FRMD7_SV2 may play a role in neuronal development. PMID:25187810

  16. 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

  17. Establishment and initial characterization of SOX2-overexpressing NT2/D1 cell clones.

    PubMed

    Drakulic, D; Krstic, A; Stevanovic, M

    2012-05-15

    SOX2, a universal marker of pluripotent stem cells, is a transcription factor that helps control embryonic development in vertebrates; its expression persists in neural stem/progenitor cells into adulthood. Considering the critical role of the SOX2 transcription factor in the regulation of genes required for self-renewal and pluripotency of stem cells, we developed and characterized SOX2-overexpressing NT2/D1 cell clones. Using Southern blot and semi-quantitative RT-PCR, we confirmed integration and expression of exogenous SOX2 in three NT2/D1 cell clones. Overexpression of the SOX2 gene was detected in two of these clones. SOX2 overexpression in NT2/D1 cell clones resulted in altered expression of key pluripotency genes OCT4 and NANOG. Furthermore, SOX2-overexpressing NT2/D1 cell clones entered into retinoic acid-dependent neural differentiation, even when there was elevated SOX2 expression. After 21 days of induction by retinoic acid, expression of neural markers (neuroD1 and synaptophysin) was higher in induced cell clones than in induced parental cells. The cell clone with SOX2 overexpression had an approximately 1.3-fold higher growth rate compared to parental cells. SOX2 overexpression did not increase the population of cells undergoing apoptosis. Taken together, we developed two SOX2-overexpressing cell clones, with constitutive SOX2 expression after three weeks of retinoic acid treatment. SOX2 overexpression resulted in altered expression of pluripotency-related genes, increased proliferation, and altered expression of neural markers after three weeks of retinoic acid treatment.

  18. Results on a binding neuron model and their implications for modified hourglass model for neuronal network.

    PubMed

    Arunachalam, Viswanathan; Akhavan-Tabatabaei, Raha; Lopez, Cristina

    2013-01-01

    The classical models of single neuron like Hodgkin-Huxley point neuron or leaky integrate and fire neuron assume the influence of postsynaptic potentials to last till the neuron fires. Vidybida (2008) in a refreshing departure has proposed models for binding neurons in which the trace of an input is remembered only for a finite fixed period of time after which it is forgotten. The binding neurons conform to the behaviour of real neurons and are applicable in constructing fast recurrent networks for computer modeling. This paper develops explicitly several useful results for a binding neuron like the firing time distribution and other statistical characteristics. We also discuss the applicability of the developed results in constructing a modified hourglass network model in which there are interconnected neurons with excitatory as well as inhibitory inputs. Limited simulation results of the hourglass network are presented.

  19. MRI of neuronal plasticity in rodent models.

    PubMed

    Pelled, Galit

    2011-01-01

    Modifications in the behavior and architecture of neuronal networks are well documented to occur in association with learning and memory, as well as following injury. These plasticity mechanisms are crucial to ensure adequate processing of stimuli, and they also dictate the degree of recovery following peripheral or central nervous system injury. Nevertheless, the underlying neuronal mechanisms that determine the degree of plasticity of neuronal pathways are not fully understood. Recent developments in animal-dedicated magnetic resonance imaging (MRI) scanners and related hardware afford a high spatial and temporal resolution, making functional MRI and manganese-enhanced MRI emerging tools for studying reorganization of neuronal pathways in rodent models. Many of the observed changes in neuronal functions in rodent's brains following injury discussed here agree with clinical human fMRI findings. This demonstrates that animal model imaging can have a significant clinical impact in the neuronal plasticity and rehabilitation arenas.

  20. 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

  1. 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.

  2. 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.

  3. Fractional Cable Models for Spiny Neuronal Dendrites

    NASA Astrophysics Data System (ADS)

    Henry, B. I.; Langlands, T. A. M.; Wearne, S. L.

    2008-03-01

    Cable equations with fractional order temporal operators are introduced to model electrotonic properties of spiny neuronal dendrites. These equations are derived from Nernst-Planck equations with fractional order operators to model the anomalous subdiffusion that arises from trapping properties of dendritic spines. The fractional cable models predict that postsynaptic potentials propagating along dendrites with larger spine densities can arrive at the soma faster and be sustained at higher levels over longer times. Calibration and validation of the models should provide new insight into the functional implications of altered neuronal spine densities, a hallmark of normal aging and many neurodegenerative disorders.

  4. 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.

  5. Dressed Neurons: Modeling the Tripartite Synapse

    NASA Astrophysics Data System (ADS)

    Jung, Peter

    2004-03-01

    The vast majority of cells in the brain are glial cells, of which astrocytes are the most numerous. Besides providing structural and metabolic support for the neurons, they listen to the neuronal chatter and modulate synaptic transmission at the synapse through extended processes that enwrap partially or fully neuronal synapses. The interaction of neurons with astrocytes involves metabolic pathways that are much slower than neuronal processes, typically of the order of seconds to minutes, resulting in complex neural-glial circuits that are at the forefront of research in neurobiology. In this talk I will give a brief introduction into the neurobiology of neural-glial circuitry and then discuss first attempts to mould these into mathematical models. One of the main signaling mechanisms within the astrocytes is through calcium release from internal stores. Neurotransmitter, released at synapses triggers astrocytic calcium events that can travel intra- and intercellularly to modify nearby or remote synapses through co-released glutamate. We discuss a few simple neural-glial circuits and the fingerprints of the astrocytic environment on neuronal dynamics. We further explore extreme parameter ranges that are consistent with conditions found in epileptic tissue and discuss the possible role of astrocytes for epilepsy.

  6. A stochastic model for interconnected neurons.

    PubMed

    Cottrell, M; Piat, F; Rospars, J P

    1997-01-01

    A model is proposed to describe the collective behavior of a biologically plausible neural network, composed of interconnected spiking neurons which separately receive external stationary stimulations. The spiking dynamics of each neuron is represented by an hourglass metaphor. This network model was first studied in a special case where the connections are only inhibitory (Cottrell, 1988, 1992). We study the network dynamics as a function of the parameters which quantify the strengths of both inhibitory and excitatory connections. We show that the model exhibits two kinds of limit states. In the first states (convergent case), the system is ergodic and all neurons have a positive mean firing rate. In the other states (divergent case), some neurons become definitively inactive while the sub-network of the active neurons is ergodic. The patterns which result from these divergent states can be seen as a neural coding of the external stimulation by the network. This property is applied to the olfactory system to produce a code for an odor. The role of inhibitory connections in odor discrimination is studied.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. Modeling autism spectrum disorders with human neurons.

    PubMed

    Beltrão-Braga, Patricia C B; Muotri, Alysson R

    2017-02-01

    Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by impaired social communication and interactions and by restricted and repetitive behaviors. Although ASD is suspected to have a heritable or sporadic genetic basis, its underlying etiology and pathogenesis are not well understood. Therefore, viable human neurons and glial cells produced using induced pluripotent stem cells (iPSC) to reprogram cells from individuals affected with ASD provide an unprecedented opportunity to elucidate the pathophysiology of these disorders, providing novel insights regarding ASD and a potential platform to develop and test therapeutic compounds. Herein, we discuss the state of art with regards to ASD modeling, including limitations of this technology, as well as potential future directions. This article is part of a Special Issue entitled SI: Exploiting human neurons.

  14. 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

  15. 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.

  16. The overexpression of SOX2 affects the migration of human teratocarcinoma cell line NT2/D1.

    PubMed

    Drakulic, Danijela; Vicentic, Jelena Marjanovic; Schwirtlich, Marija; Tosic, Jelena; Krstic, Aleksandar; Klajn, Andrijana; Stevanovic, Milena

    2015-03-01

    The altered expression of the SOX2 transcription factor is associated with oncogenic or tumor suppressor functions in human cancers. This factor regulates the migration and invasion of different cancer cells. In this study we investigated the effect of constitutive SOX2 overexpression on the migration and adhesion capacity of embryonal teratocarcinoma NT2/D1 cells derived from a metastasis of a human testicular germ cell tumor. We detected that increased SOX2 expression changed the speed, mode and path of cell migration, but not the adhesion ability of NT2/D1 cells. Additionally, we demonstrated that SOX2 overexpression increased the expression of the tumor suppressor protein p53 and the HDM2 oncogene. Our results contribute to the better understanding of the effect of SOX2 on the behavior of tumor cells originating from a human testicular germ cell tumor. Considering that NT2/D1 cells resemble cancer stem cells in many features, our results could contribute to the elucidation of the role of SOX2 in cancer stem cells behavior and the process of metastasis.

  17. Functionalized Anatomical Models for EM-Neuron Interaction Modeling

    PubMed Central

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

    2017-01-01

    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. PMID:27224508

  18. 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.

  19. 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.

  20. Role of Transmembrane Domain 4 in Ligand Permeation by Crithidia fasciculata Equilibrative Nucleoside Transporter 2 (CfNT2)*

    PubMed Central

    Arendt, Cassandra S.; Ullman, Buddy

    2010-01-01

    Equilibrative nucleoside transporters play essential roles in nutrient uptake, cardiovascular and renal function, and purine analog drug chemotherapies. Limited structural information is available for this family of transporters; however, residues in transmembrane domains 1, 2, 4, and 5 appear to be important for ligand and inhibitor binding. In order to identify regions of the transporter that are important for ligand specificity, a genetic selection for mutants of the inosine-guanosine-specific Crithidia fasciculata nucleoside transporter 2 (CfNT2) that had gained the ability to transport adenosine was carried out in the yeast Saccharomyces cerevisiae. Nearly all positive clones from the genetic selection carried mutations at lysine 155 in transmembrane domain 4, highlighting lysine 155 as a pivotal residue governing the ligand specificity of CfNT2. Mutation of lysine 155 to asparagine conferred affinity for adenosine on the mutant transporter at the expense of inosine and guanosine affinity due to weakened contacts to the purine ring of the ligand. Following systematic cysteine-scanning mutagenesis, thiol-specific modification of several positions within transmembrane domain 4 was found to interfere with inosine transport capability, indicating that this helix lines the water-filled ligand translocation channel. Additionally, the pattern of modification of transmembrane domain 4 suggested that it may deviate from helicity in the vicinity of residue 155. Position 155 was also protected from modification in the presence of ligand, suggesting that lysine 155 is in or near the ligand binding site. Transmembrane domain 4 and particularly lysine 155 appear to play key roles in ligand discrimination and translocation by CfNT2. PMID:20037157

  1. From spiking neuron models to linear-nonlinear models.

    PubMed

    Ostojic, Srdjan; Brunel, Nicolas

    2011-01-20

    Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

  2. 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.

  3. Evaluation of the importance of astrocytes when screening for acute toxicity in neuronal cell systems.

    PubMed

    Woehrling, E K; Hill, E J; Coleman, M D

    2010-02-01

    Reliable, high throughput, in vitro preliminary screening batteries have the potential to greatly accelerate the rate at which regulatory neurotoxicity data is generated. This study evaluated the importance of astrocytes when predicting acute toxic potential using a neuronal screening battery of pure neuronal (NT2.N) and astrocytic (NT2.A) and integrated neuronal/astrocytic (NT2.N/A) cell systems derived from the human NT2.D1 cell line, using biochemical endpoints (mitochondrial membrane potential (MMP) depolarisation and ATP and GSH depletion). Following exposure for 72 h, the known acute human neurotoxicants trimethyltin-chloride, chloroquine and 6-hydroxydopamine were frequently capable of disrupting biochemical processes in all of the cell systems at non-cytotoxic concentrations. Astrocytes provide key metabolic and protective support to neurons during toxic challenge in vivo and generally the astrocyte containing cell systems showed increased tolerance to toxicant insult compared with the NT2.N mono-culture in vitro. Whilst there was no consistent relationship between MMP, ATP and GSH log IC(50) values for the NT2.N/A and NT2.A cell systems, these data did provide preliminary evidence of modulation of the acute neuronal toxic response by astrocytes. In conclusion, the suitability of NT2 neurons and astrocytes as cell systems for acute toxicity screening deserves further investigation.

  4. Modelling small-patterned neuronal networks coupled to microelectrode arrays

    NASA Astrophysics Data System (ADS)

    Massobrio, Paolo; Martinoia, Sergio

    2008-09-01

    Cultured neurons coupled to planar substrates which exhibit 'well-defined' two-dimensional network architectures can provide valuable insights into cell-to-cell communication, network dynamics versus topology, and basic mechanisms of synaptic plasticity and learning. In the literature several approaches were presented to drive neuronal growth, such as surface modification by silane chemistry, photolithographic techniques, microcontact printing, microfluidic channel flow patterning, microdrop patterning, etc. This work presents a computational model fit for reproducing and explaining the dynamics exhibited by small-patterned neuronal networks coupled to microelectrode arrays (MEAs). The model is based on the concept of meta-neuron, i.e., a small spatially confined number of actual neurons which perform single macroscopic functions. Each meta-neuron is characterized by a detailed morphology, and the membrane channels are modelled by simple Hodgkin-Huxley and passive kinetics. The two main findings that emerge from the simulations can be summarized as follows: (i) the increasing complexity of meta-neuron morphology reflects the variations of the network dynamics as a function of network development; (ii) the dynamics displayed by the patterned neuronal networks considered can be explained by hypothesizing the presence of several short- and a few long-term distance interactions among small assemblies of neurons (i.e., meta-neurons).

  5. Chaotic Resonance in Coupled Inferior Olive Neurons with the Llinás Approach Neuron Model.

    PubMed

    Nobukawa, Sou; Nishimura, Haruhiko

    2016-09-14

    It is well known that cerebellar motor control is fine-tuned by the learning process adjusted according to rich error signals from inferior olive (IO) neurons. Schweighofer and colleagues proposed that these signals can be produced by chaotic irregular firing in the IO neuron assembly; such chaotic resonance (CR) was replicated in their computer demonstration of a Hodgkin-Huxley (HH)-type compartment model. In this study, we examined the response of CR to a periodic signal in the IO neuron assembly comprising the Llinás approach IO neuron model. This system involves empirically observed dynamics of the IO membrane potential and is simpler than the HH-type compartment model. We then clarified its dependence on electrical coupling strength, input signal strength, and frequency. Furthermore, we compared the physiological validity for IO neurons such as low firing rate and sustaining subthreshold oscillation between CR and conventional stochastic resonance (SR) and examined the consistency with asynchronous firings indicated by the previous model-based studies in the cerebellar learning process. In addition, the signal response of CR and SR was investigated in a large neuron assembly. As the result, we confirmed that CR was consistent with the above IO neuron's characteristics, but it was not as easy for SR.

  6. 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

    2016-02-07

    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.

  7. 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

  8. Small is beautiful: models of small neuronal networks

    PubMed Central

    Lamb, Damon G; Calabrese, Ronald L

    2013-01-01

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

  9. 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.

  10. Unsupervised learnable neuron model with nonlinear interaction on dendrites.

    PubMed

    Todo, Yuki; Tamura, Hiroki; Yamashita, Kazuya; Tang, Zheng

    2014-12-01

    Recent researches have provided strong circumstantial support to dendrites playing a key and possibly essential role in computations. In this paper, we propose an unsupervised learnable neuron model by including the nonlinear interactions between excitation and inhibition on dendrites. The model neuron self-adjusts its synaptic parameters, so that the synapse to dendrite, according to a generalized delta-rule-like algorithm. The model is used to simulate directionally selective cells by the unsupervised learning algorithm. In the simulations, we initialize the interaction and dendrite of the neuron randomly and use the generalized delta-rule-like unsupervised learning algorithm to learn the two-dimensional multi-directional selectivity problem without an external teacher's signals. Simulation results show that the directionally selective cells can be formed by unsupervised learning, acquiring the required number of dendritic branches, and if needed, enhanced and if not, eliminated. Further, the results show whether a synapse exists; if it exists, where and what type (excitatory or inhibitory) of synapse it is. This leads us to believe that the proposed neuron model may be considerably more powerful on computations than the McCulloch-Pitts model because theoretically a single neuron or a single layer of such neurons is capable of solving any complex problem. These may also lead to a completely new technique for analyzing the mechanisms and principles of neurons, dendrites, and synapses.

  11. A spiking neuron model for synchronous flashing of fireflies.

    PubMed

    Kim, DaeEun

    2004-01-01

    Certain species of fireflies show a group behavior of synchronous flashing. Their synchronized and rhythmic flashing has received much attention among many researchers, and there has been a study of biological models for their entrainment of flashing. The synchronous behavior of fireflies resembles the firing synchrony of integrate-and-fire neurons with excitatory or inhibitory connections. This paper shows an analysis of spiking neurons specialized for a firefly flashing model, and provides simulation results of multiple neurons with various transmission delays and coupling strengths. It also explains flashing patterns of some firefly species and examines the synchrony conditions depending on transmission delays and coupling strengths.

  12. A bi-stable neuronal model of Gibbs distribution

    NASA Astrophysics Data System (ADS)

    Gross, Eitan

    2015-07-01

    In this paper we present a bi-stable neuronal model consistent with the Gibbs distribution. Our approach utilizes a formalism used in stochastic (Boltzmann) machines with a bistable-neuron algorithm in which each neuron can exist in either an ON or an OFF state. The transition between the system's states is composed of two random processes, the first one decides which state transition should be attempted and the second one decides if the transition is accepted or not. Our model can be easily extended to systems with asymmetrical weight matrices.

  13. GABAergic pathway in a rat model of chronic neuropathic pain: modulation after intrathecal transplantation of a human neuronal cell line.

    PubMed

    Vaysse, L; Sol, J C; Lazorthes, Y; Courtade-Saidi, M; Eaton, M J; Jozan, S

    2011-02-01

    Current understanding of chronic pain points a decrease in level of the inhibitory neurotransmitter GABA, in the spinal dorsal horn, leading to an imbalance between excitatory and inhibitory pathways. A subcloned derivative of the human NT2 cell line (hNT2.17) which, after neuronal differentiation, secretes different inhibitory neurotransmitters such as GABA and glycine has been recently isolated. In this study, we have investigated the effect of this new cell line on peripheral nerve injury induced by chronic constriction (CCI) and notably the effect on the cellular GABAergic pathway. Our data show that the decrease in GABA expression in the spinal dorsal horn of injured animals is concomitant with a decline of its synthetic enzyme GAD67-Ir and mRNA but not GAD65. Interestingly, in transplanted animals we observed a strong induction of GAD67 mRNA with one week after graft, which is followed by a recovery of GAD67 and GABA Ir. This effect paralleled a reduction of hindpaw hypersensitivity and thermal hyperalgesia induced by CCI. These results suggest that hNT2.17 GABA cells can modulate neuropathic pain after CCI certainly by minimizing the imbalance and restoring the cellular GABAergic pathway.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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

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

    PubMed Central

    Duan, Haibin; Wang, Xiaohua

    2015-01-01

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

  4. 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.

  5. Tunable Neuromimetic Integrated System for Emulating Cortical Neuron Models

    PubMed Central

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

    2011-01-01

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

  6. 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.

  7. Selective loss of alpha motor neurons with sparing of gamma motor neurons and spinal cord cholinergic neurons in a mouse model of spinal muscular atrophy.

    PubMed

    Powis, Rachael A; Gillingwater, Thomas H

    2016-03-01

    Spinal muscular atrophy (SMA) is a neuromuscular disease characterised primarily by loss of lower motor neurons from the ventral grey horn of the spinal cord and proximal muscle atrophy. Recent experiments utilising mouse models of SMA have demonstrated that not all motor neurons are equally susceptible to the disease, revealing that other populations of neurons can also be affected. Here, we have extended investigations of selective vulnerability of neuronal populations in the spinal cord of SMA mice to include comparative assessments of alpha motor neuron (α-MN) and gamma motor neuron (γ-MN) pools, as well as other populations of cholinergic neurons. Immunohistochemical analyses of late-symptomatic SMA mouse spinal cord revealed that numbers of α-MNs were significantly reduced at all levels of the spinal cord compared with controls, whereas numbers of γ-MNs remained stable. Likewise, the average size of α-MN cell somata was decreased in SMA mice with no change occurring in γ-MNs. Evaluation of other pools of spinal cord cholinergic neurons revealed that pre-ganglionic sympathetic neurons, central canal cluster interneurons, partition interneurons and preganglionic autonomic dorsal commissural nucleus neuron numbers all remained unaffected in SMA mice. Taken together, these findings indicate that α-MNs are uniquely vulnerable among cholinergic neuron populations in the SMA mouse spinal cord, with γ-MNs and other cholinergic neuronal populations being largely spared.

  8. 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.

  9. 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

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

    PubMed

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

    2015-01-01

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

  11. Comparison of single neuron models in terms of synchronization propensity

    NASA Astrophysics Data System (ADS)

    Sungar, N.; Allaria, E.; Leyva, I.; Arecchi, F. T.

    2008-09-01

    A plausible model for coherent perception is the synchronization of chaotically distributed neural spike trains over wide cortical areas. A recently introduced propensity criterion provides a tool for a quantitative comparison of different neuron models in terms of their ability to synchronize to an applied perturbation. We explore the propensity of several systems and indicate the requirements to be satisfied by a plausible candidate for modeling neuronal activity. Our results show that the conflicting requirements of stability and sensitivity leading to high propensity to synchronization can be satisfied by a strongly nonuniform attractor made of two distinct regions: a saddle focus plus a sufficiently separated saddle node.

  12. Modeling ALS and FTD with iPSC-derived neurons.

    PubMed

    Lee, Sebum; Huang, Eric J

    2017-02-01

    Recent advances in genetics and neuropathology support the idea that amyotrophic lateral sclerosis (ALS) and frontotemporal lobar dementia (FTD) are two ends of a disease spectrum. Although several animal models have been developed to investigate the pathogenesis and disease progression in ALS and FTD, there are significant limitations that hamper our ability to connect these models with the neurodegenerative processes in human diseases. With the technical breakthrough in reprogramming biology, it is now possible to generate patient-specific induced pluripotent stem cells (iPSCs) and disease-relevant neuron subtypes. This review provides a comprehensive summary of studies that use iPSC-derived neurons to model ALS and FTD. We discuss the unique capabilities of iPSC-derived neurons that capture some key features of ALS and FTD, and underscore their potential roles in drug discovery. There are, however, several critical caveats that require improvements before iPSC-derived neurons can become highly effective disease models. This article is part of a Special Issue entitled SI: Exploiting human neurons.

  13. Generative modelling of regulated dynamical behavior in cultured neuronal networks

    NASA Astrophysics Data System (ADS)

    Volman, Vladislav; Baruchi, Itay; Persi, Erez; Ben-Jacob, Eshel

    2004-04-01

    The spontaneous activity of cultured in vitro neuronal networks exhibits rich dynamical behavior. Despite the artificial manner of their construction, the networks’ activity includes features which seemingly reflect the action of underlying regulating mechanism rather than arbitrary causes and effects. Here, we study the cultured networks dynamical behavior utilizing a generative modelling approach. The idea is to include the minimal required generic mechanisms to capture the non-autonomous features of the behavior, which can be reproduced by computer modelling, and then, to identify the additional features of biotic regulation in the observed behavior which are beyond the scope of the model. Our model neurons are composed of soma described by the two Morris-Lecar dynamical variables (voltage and fraction of open potassium channels), with dynamical synapses described by the Tsodyks-Markram three variables dynamics. The model neuron satisfies our self-consistency test: when fed with data recorded from a real cultured networks, it exhibits dynamical behavior very close to that of the networks’ “representative” neuron. Specifically, it shows similar statistical scaling properties (approximated by similar symmetric Lévy distribution with finite mean). A network of such M-L elements spontaneously generates (when weak “structured noise” is added) synchronized bursting events (SBEs) similar to the observed ones. Both the neuronal statistical scaling properties within the bursts and the properties of the SBEs time series show generative (a new discussed concept) agreement with the recorded data. Yet, the model network exhibits different structure of temporal variations and does not recover the observed hierarchical temporal ordering, unless fed with recorded special neurons (with much higher rates of activity), thus indicating the existence of self-regulation mechanisms. It also implies that the spontaneous activity is not simply noise-induced. Instead, the

  14. Leaders of neuronal cultures in a quorum percolation model.

    PubMed

    Eckmann, Jean-Pierre; Moses, Elisha; Stetter, Olav; Tlusty, Tsvi; Zbinden, Cyrille

    2010-01-01

    We present a theoretical framework using quorum percolation for describing the initiation of activity in a neural culture. The cultures are modeled as random graphs, whose nodes are excitatory neurons with k(in) inputs and k(out) outputs, and whose input degrees k(in) = k obey given distribution functions p(k). We examine the firing activity of the population of neurons according to their input degree (k) classes and calculate for each class its firing probability Φ(k)(t) as a function of t. The probability of a node to fire is found to be determined by its in-degree k, and the first-to-fire neurons are those that have a high k. A small minority of high-k-classes may be called "Leaders," as they form an interconnected sub-network that consistently fires much before the rest of the culture. Once initiated, the activity spreads from the Leaders to the less connected majority of the culture. We then use the distribution of in-degree of the Leaders to study the growth rate of the number of neurons active in a burst, which was experimentally measured to be initially exponential. We find that this kind of growth rate is best described by a population that has an in-degree distribution that is a Gaussian centered around k = 75 with width σ = 31 for the majority of the neurons, but also has a power law tail with exponent -2 for 10% of the population. Neurons in the tail may have as many as k = 4,700 inputs. We explore and discuss the correspondence between the degree distribution and a dynamic neuronal threshold, showing that from the functional point of view, structure and elementary dynamics are interchangeable. We discuss possible geometric origins of this distribution, and comment on the importance of size, or of having a large number of neurons, in the culture.

  15. 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.

  16. 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

  17. 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

  18. Optical Computing Based on Neuronal Models

    DTIC Science & Technology

    1988-05-01

    walking, and cognition are far too complex for existing sequential digital computers. Therefore new architectures, hardware, and algorithms modeled...collective behavior, and iterative processing into optical processing and artificial neurodynamical systems. Another intriguing promise of neural nets is...with architectures, implementations, and programming; and material research s -7- called for. Our future research in neurodynamics will continue to

  19. Complex Parameter Landscape for a Complex Neuron Model

    PubMed Central

    Achard, Pablo; De Schutter, Erik

    2006-01-01

    The electrical activity of a neuron is strongly dependent on the ionic channels present in its membrane. Modifying the maximal conductances from these channels can have a dramatic impact on neuron behavior. But the effect of such modifications can also be cancelled out by compensatory mechanisms among different channels. We used an evolution strategy with a fitness function based on phase-plane analysis to obtain 20 very different computational models of the cerebellar Purkinje cell. All these models produced very similar outputs to current injections, including tiny details of the complex firing pattern. These models were not completely isolated in the parameter space, but neither did they belong to a large continuum of good models that would exist if weak compensations between channels were sufficient. The parameter landscape of good models can best be described as a set of loosely connected hyperplanes. Our method is efficient in finding good models in this complex landscape. Unraveling the landscape is an important step towards the understanding of functional homeostasis of neurons. PMID:16848639

  20. Modeling Huntington׳s disease with patient-derived neurons.

    PubMed

    Mattis, Virginia B; Svendsen, Clive N

    2017-02-01

    Huntington׳s Disease (HD) is a fatal neurodegenerative disorder caused by expanded polyglutamine repeats in the Huntingtin (HTT) gene. While the gene was identified over two decades ago, it remains poorly understood why mutant HTT (mtHTT) is initially toxic to striatal medium spiny neurons (MSNs). Models of HD using non-neuronal human patient cells and rodents exhibit some characteristic HD phenotypes. While these current models have contributed to the field, they are limited in disease manifestation and may vary in their response to treatments. As such, human HD patient MSNs for disease modeling could greatly expand the current understanding of HD and facilitate the search for a successful treatment. It is now possible to use pluripotent stem cells, which can generate any tissue type in the body, to study and potentially treat HD. This review covers disease modeling in vitro and, via chimeric animal generation, in vivo using human HD patient MSNs differentiated from embryonic stem cells or induced pluripotent stem cells. This includes an overview of the differentiation of pluripotent cells into MSNs, the established phenotypes found in cell-based models and transplantation studies using these cells. This review not only outlines the advancements in the rapidly progressing field of HD modeling using neurons derived from human pluripotent cells, but also it highlights several remaining controversial issues such as the 'ideal' series of pluripotent lines, the optimal cell types to use and the study of a primarily adult-onset disease in a developmental model. This article is part of a Special Issue entitled SI: Exploiting human neurons.

  1. 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.

  2. 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.

  3. Activity-Dependent Neuronal Model on Complex Networks

    PubMed Central

    de Arcangelis, Lucilla; Herrmann, Hans J.

    2012-01-01

    Neuronal avalanches are a novel mode of activity in neuronal networks, experimentally found in vitro and in vivo, and exhibit a robust critical behavior: these avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems. We present a recent model inspired in self-organized criticality, which consists of an electrical network with threshold firing, refractory period, and activity-dependent synaptic plasticity. The model reproduces the critical behavior of the distribution of avalanche sizes and durations measured experimentally. Moreover, the power spectra of the electrical signal reproduce very robustly the power law behavior found in human electroencephalogram (EEG) spectra. We implement this model on a variety of complex networks, i.e., regular, small-world, and scale-free and verify the robustness of the critical behavior. PMID:22470347

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Estimation of the input parameters in the Feller neuronal model

    NASA Astrophysics Data System (ADS)

    Ditlevsen, Susanne; Lansky, Petr

    2006-06-01

    The stochastic Feller neuronal model is studied, and estimators of the model input parameters, depending on the firing regime of the process, are derived. Closed expressions for the first two moments of functionals of the first-passage time (FTP) through a constant boundary in the suprathreshold regime are derived, which are used to calculate moment estimators. In the subthreshold regime, the exponentiality of the FTP is utilized to characterize the input parameters. The methods are illustrated on simulated data. Finally, approximations of the first-passage-time moments are suggested, and biological interpretations and comparisons of the parameters in the Feller and the Ornstein-Uhlenbeck models are discussed.

  10. Stress exacerbates neuron loss and microglia proliferation in a rat model of excitotoxic lower motor neuron injury

    PubMed Central

    Puga, Denise A.; Tovar, C. Amy; Guan, Zhen; C.Gensel, John; Lyman, Matthew S.; McTigue, Dana M.; Popovich, Phillip G.

    2015-01-01

    All individuals experience stress and hormones (e.g., glucocorticoids/GCs) released during stressful events can affect the structure and function of neurons. These effects of stress are best characterized for brain neurons; however, the mechanisms controlling the expression and binding affinity of glucocorticoid receptors in the spinal cord are different than those in the brain. Accordingly, whether stress exerts unique effects on spinal cord neurons, especially in the context of pathology, is unknown. Using a controlled model of focal excitotoxic lower motor neuron injury in rats, we examined the effects of acute or chronic variable stress on spinal cord motor neuron survival and glial activation. New data indicate that stress exacerbates excitotoxic spinal cord motor neuron loss and associated activation of microglia. In contrast, hypertrophy and hyperplasia of astrocytes and NG2+ glia were unaffected or were modestly suppressed by stress. Although excitotoxic lesions cause significant motor neuron loss and stress exacerbates this pathology, overt functional impairment did not develop in the relevant forelimb up to one week post-lesion. These data indicate that stress is a disease-modifying factor capable of altering neuron and glial responses to pathological challenges in the spinal cord. PMID:26100488

  11. Digital hardware implementation of a stochastic two-dimensional neuron model.

    PubMed

    Grassia, F; Kohno, T; Levi, T

    2017-02-22

    This study explores the feasibility of stochastic neuron simulation in digital systems (FPGA), which realizes an implementation of a two-dimensional neuron model. The stochasticity is added by a source of current noise in the silicon neuron using an Ornstein-Uhlenbeck process. This approach uses digital computation to emulate individual neuron behavior using fixed point arithmetic operation. The neuron model's computations are performed in arithmetic pipelines. It was designed in VHDL language and simulated prior to mapping in the FPGA. The experimental results confirmed the validity of the developed stochastic FPGA implementation, which makes the implementation of the silicon neuron more biologically plausible for future hybrid experiments.

  12. 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.

  13. Micropatterned bioimplant with guided neuronal cells to promote tissue reconstruction and improve functional recovery after primary motor cortex insult.

    PubMed

    Vaysse, L; Beduer, A; Sol, J C; Vieu, C; Loubinoux, I

    2015-07-01

    With the ever increasing incidence of brain injury, developing new tissue engineering strategies to promote neural tissue regeneration is an enormous challenge. The goal of this study was to design and evaluate an implantable scaffold capable of directing neurite and axonal growth for neuronal brain tissue regeneration. We have previously shown in cell culture conditions that engineered micropatterned PDMS surface with straight microchannels allow directed neurite growth without perturbing cell differentiation and neurite outgrowth. In this study, the micropatterned PDMS device pre-seeded with hNT2 neuronal cells were implanted in rat model of primary motor cortex lesion which induced a strong motor deficit. Functional recovery was assessed by the forelimb grip strength test during 3 months post implantation. Results show a more rapid and efficient motor recovery with the hNT2 neuroimplants associated with an increase of neuronal tissue reconstruction and cell survival. This improvement is also hastened when compared to a direct cell graft of ten times more cells. Histological analyses showed that the implant remained structurally intact and we did not see any evidence of inflammatory reaction. In conclusion, PDMS bioimplants with guided neuronal cells seem to be a promising approach for supporting neural tissue reconstruction after central brain injury.

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

    PubMed

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

    2013-11-01

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

  15. Novel model for the mechanisms of glutamate-dependent excitotoxicity: Role of neuronal gap junctions

    PubMed Central

    Belousov, Andrei B.

    2012-01-01

    In the mammalian central nervous system (CNS), coupling of neurons by gap junctions (electrical synapses) increases during early postnatal development, then decreases, but increases in the mature CNS following neuronal injury, such as ischemia, traumatic brain injury and epilepsy. Glutamate-dependent neuronal death also occurs in the CNS during development and neuronal injury, i.e., at the time when neuronal gap junction coupling is increased. Here, we review our recent studies on regulation of neuronal gap junction coupling by glutamate during development and injury and on the role of gap junctions in neuronal cell death. A novel model of the mechanisms of glutamate-dependent neuronal death is discussed, which includes neuronal gap junction coupling as a critical part of these mechanisms. PMID:22771704

  16. From in silico astrocyte cell models to neuron-astrocyte network models: A review.

    PubMed

    Oschmann, Franziska; Berry, Hugues; Obermayer, Klaus; Lenk, Kerstin

    2017-02-08

    The idea that astrocytes may be active partners in synaptic information processing has recently emerged from abundant experimental reports. Because of their spatial proximity to neurons and their bidirectional communication with them, astrocytes are now considered as an important third element of the synapse. Astrocytes integrate and process synaptic information and by doing so generate cytosolic calcium signals that are believed to reflect neuronal transmitter release. Moreover, they regulate neuronal information transmission by releasing gliotransmitters into the synaptic cleft affecting both pre- and postsynaptic receptors. Concurrent with the first experimental reports of the astrocytic impact on neural network dynamics, computational models describing astrocytic functions have been developed. In this review, we give an overview over the published computational models of astrocytic functions, from single-cell dynamics to the tripartite synapse level and network models of astrocytes and neurons.

  17. Dynamics in the Parameter Space of a Neuron Model

    NASA Astrophysics Data System (ADS)

    Paulo, C. Rech

    2012-06-01

    Some two-dimensional parameter-space diagrams are numerically obtained by considering the largest Lyapunov exponent for a four-dimensional thirteen-parameter Hindmarsh—Rose neuron model. Several different parameter planes are considered, and it is shown that depending on the combination of parameters, a typical scenario can be preserved: for some choice of two parameters, the parameter plane presents a comb-shaped chaotic region embedded in a large periodic region. It is also shown that there exist regions close to these comb-shaped chaotic regions, separated by the comb teeth, organizing themselves in period-adding bifurcation cascades.

  18. 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

  19. A role for the anterior insular cortex in the global neuronal workspace model of consciousness.

    PubMed

    Michel, Matthias

    2017-03-01

    According to the global neuronal workspace model of consciousness, consciousness results from the global broadcast of information throughout the brain. The global neuronal workspace is mainly constituted by a fronto-parietal network. The anterior insular cortex is part of this global neuronal workspace, but the function of this region has not yet been defined within the global neuronal workspace model of consciousness. In this review, I hypothesize that the anterior insular cortex implements a cross-modal priority map, the function of which is to determine priorities for the processing of information and subsequent entrance in the global neuronal workspace.

  20. Nonlinear Maps for Design of Discrete Time Models of Neuronal Network Dynamics

    DTIC Science & Technology

    2016-02-29

    network activity. D· 1S. SUBJECT TERMS Map-based neuronal model , Discrete time spiking dynamics, Synapses, Neurons, Neurobiological Networks 16...N00014-16-1-2252 Report #1 Performance/Technical Monthly Report Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics...research of network dynamics utilizing the conductance-based models will be done in collaboration Dr. M. Bazhenov who will support the remaining 50% of

  1. The composite neuron: a realistic one-compartment Purkinje cell model suitable for large-scale neuronal network simulations.

    PubMed

    Coop, A D; Reeke, G N

    2001-01-01

    We present a simple method for the realistic description of neurons that is well suited to the development of large-scale neuronal network models where the interactions within and between neural circuits are the object of study rather than the details of dendritic signal propagation in individual cells. Referred to as the composite approach, it combines in a one-compartment model elements of both the leaky integrator cell and the conductance-based formalism of Hodgkin and Huxley (1952). Composite models treat the cell membrane as an equivalent circuit that contains ligand-gated synaptic, voltage-gated, and voltage- and concentration-dependent conductances. The time dependences of these various conductances are assumed to correlate with their spatial locations in the real cell. Thus, when viewed from the soma, ligand-gated synaptic and other dendritically located conductances can be modeled as either single alpha or double exponential functions of time, whereas, with the exception of discharge-related conductances, somatic and proximal dendritic conductances can be well approximated by simple current-voltage relationships. As an example of the composite approach to neuronal modeling we describe a composite model of a cerebellar Purkinje neuron.

  2. Estimating the electrotonic structure of neurons with compartmental models.

    PubMed

    Holmes, W R; Rall, W

    1992-10-01

    1. A procedure based on compartmental modeling called the "constrained inverse computation" was developed for estimating the electrotonic structure of neurons. With the constrained inverse computation, a set of N electrotonic parameters are estimated iteratively with use of a Newton-Raphson algorithm given values of N parameters that can be measured or estimated from experimental data. 2. The constrained inverse computation is illustrated by several applications to the basic example of a neuron represented as one cylinder coupled to a soma. The number of unknown parameters estimated was different (ranging from 2 to 6) when different sets of constraints were chosen. The unknowns were chosen from the following: dendritic membrane resistivity Rmd, soma membrane resistivity Rms, intracellular resistivity Ri, membrane capacity Cm, dendritic membrane area AD, soma membrane area As, electrotonic length L, and resistivity-free length, rfl (rfl = 2l/d1/2 where l and d are length and diameter of the cylinder). The values of the unknown parameters were estimated from the values of an equal number of known parameters, which were chosen from the following: the time constants and coefficients of a voltage transient tau 0, tau 1, ..., C0, C1, ..., voltage-clamp time constants tau vc1, tau vc2, ..., and input resistance RN. Note that initially, morphological data were treated as unknown, rather than known. 3. When complete morphology was not known, parameters from voltage and current transients, combined with the input resistance were not sufficient to completely specify the electrotonic structure of the neuron. For a neuron represented as a cylinder coupled to a soma, there were an infinite number of combinations of Rmd, Rms, Ri, Cm, AS, AD, and L that could be fitted to the same voltage and current transients and input resistance. 4. One reason for the nonuniqueness when complete morphology was not specified is that the Ri estimate is intrinsically bound to the morphology. Ri

  3. 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

  4. Modeling neuron selectivity over simple midlevel features for image classification.

    PubMed

    Shu Kong; Zhuolin Jiang; Qiang Yang

    2015-08-01

    We now know that good mid-level features can greatly enhance the performance of image classification, but how to efficiently learn the image features is still an open question. In this paper, we present an efficient unsupervised midlevel feature learning approach (MidFea), which only involves simple operations, such as k-means clustering, convolution, pooling, vector quantization, and random projection. We show this simple feature can also achieve good performance in traditional classification task. To further boost the performance, we model the neuron selectivity (NS) principle by building an additional layer over the midlevel features prior to the classifier. The NS-layer learns category-specific neurons in a supervised manner with both bottom-up inference and top-down analysis, and thus supports fast inference for a query image. Through extensive experiments, we demonstrate that this higher level NS-layer notably improves the classification accuracy with our simple MidFea, achieving comparable performances for face recognition, gender classification, age estimation, and object categorization. In particular, our approach runs faster in inference by an order of magnitude than sparse coding-based feature learning methods. As a conclusion, we argue that not only do carefully learned features (MidFea) bring improved performance, but also a sophisticated mechanism (NS-layer) at higher level boosts the performance further.

  5. 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.

  6. 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

    2016-05-18

    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.

  7. 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

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

    PubMed

    Pyka, Martin; Klatt, Sebastian; Cheng, Sen

    2014-01-01

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

  9. 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.

  10. Electrophysiological properties of inferior olive neurons: A compartmental model.

    PubMed

    Schweighofer, N; Doya, K; Kawato, M

    1999-08-01

    As a step in exploring the functions of the inferior olive, we constructed a biophysical model of the olivary neurons to examine their unique electrophysiological properties. The model consists of two compartments to represent the known distribution of ionic currents across the cell membrane, as well as the dendritic location of the gap junctions and synaptic inputs. The somatic compartment includes a low-threshold calcium current (I(Ca_l)), an anomalous inward rectifier current (I(h)), a sodium current (I(Na)), and a delayed rectifier potassium current (I(K_dr)). The dendritic compartment contains a high-threshold calcium current (I(Ca_h)), a calcium-dependent potassium current (I(K_Ca)), and a current flowing into other cells through electrical coupling (I(c)). First, kinetic parameters for these currents were set according to previously reported experimental data. Next, the remaining free parameters were determined to account for both static and spiking properties of single olivary neurons in vitro. We then performed a series of simulated pharmacological experiments using bifurcation analysis and extensive two-parameter searches. Consistent with previous studies, we quantitatively demonstrated the major role of I(Ca_l) in spiking excitability. In addition, I(h) had an important modulatory role in the spike generation and period of oscillations, as previously suggested by Bal and McCormick. Finally, we investigated the role of electrical coupling in two coupled spiking cells. Depending on the coupling strength, the hyperpolarization level, and the I(Ca_l) and I(h) modulation, the coupled cells had four different synchronization modes: the cells could be in-phase, phase-shifted, or anti-phase or could exhibit a complex desynchronized spiking mode. Hence these simulation results support the counterintuitive hypothesis that electrical coupling can desynchronize coupled inferior olive cells.

  11. Slow motor neuron stimulation of locust skeletal muscle: model and measurement.

    PubMed

    Wilson, Emma; Rustighi, Emiliano; Newland, Philip L; Mace, Brian R

    2013-06-01

    The isometric force response of the locust hind leg extensor tibia muscle to stimulation of a slow extensor tibia motor neuron is experimentally investigated, and a mathematical model describing the response presented. The measured force response was modelled by considering the ability of an existing model, developed to describe the response to the stimulation of a fast extensor tibia motor neuron and to also model the response to slow motor neuron stimulation. It is found that despite large differences in the force response to slow and fast motor neuron stimulation, which could be accounted for by the differing physiology of the fibres they innervate, the model is able to describe the response to both fast and slow motor neuron stimulation. Thus, the presented model provides a potentially generally applicable, robust, simple model to describe the isometric force response of a range of muscles.

  12. Linear and Nonlinear Electrical Models of Neurons for Hopfield Neural Network

    NASA Astrophysics Data System (ADS)

    Sarwar, Farah; Iqbal, Shaukat; Hussain, Muhammad Waqar

    2016-11-01

    A novel electrical model of neuron is proposed in this presentation. The suggested neural network model has linear/nonlinear input-output characteristics. This new deterministic model has joint biological properties in excellent agreement with the earlier deterministic neuron model of Hopfield and Tank and to the stochastic neuron model of McCulloch and Pitts. It is an accurate portrayal of differential equation presented by Hopfield and Tank to mimic neurons. Operational amplifiers, resistances, capacitor, and diodes are used to design this system. The presented biological model of neurons remains to be advantageous for simulations. Impulse response is studied and conferred to certify the stability and strength of this innovative model. A simple illustration is mapped to demonstrate the exactness of the intended system. Precisely mapped illustration exhibits 100 % accurate results.

  13. 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.

  14. Temporal structure of neuronal population oscillations with empirical model decomposition

    NASA Astrophysics Data System (ADS)

    Li, Xiaoli

    2006-08-01

    Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

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

    PubMed

    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.

  16. 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

  17. A computational model for the loss of neuronal organization in microcolumns.

    PubMed

    Henderson, Maxwell; Urbanc, Brigita; Cruz, Luis

    2014-05-20

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

  18. 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

  19. On the simulation of nonlinear bidimensional spiking neuron models.

    PubMed

    Touboul, Jonathan

    2011-07-01

    Bidimensional spiking models are garnering a lot of attention for their simplicity and their ability to reproduce various spiking patterns of cortical neurons and are used particularly for large network simulations. These models describe the dynamics of the membrane potential by a nonlinear differential equation that blows up in finite time, coupled to a second equation for adaptation. Spikes are emitted when the membrane potential blows up or reaches a cutoff θ. The precise simulation of the spike times and of the adaptation variable is critical, for it governs the spike pattern produced and is hard to compute accurately because of the exploding nature of the system at the spike times. We thoroughly study the precision of fixed time-step integration schemes for this type of model and demonstrate that these methods produce systematic errors that are unbounded, as the cutoff value is increased, in the evaluation of the two crucial quantities: the spike time and the value of the adaptation variable at this time. Precise evaluation of these quantities therefore involves very small time steps and long simulation times. In order to achieve a fixed absolute precision in a reasonable computational time, we propose here a new algorithm to simulate these systems based on a variable integration step method that either integrates the original ordinary differential equation or the equation of the orbits in the phase plane, and compare this algorithm with fixed time-step Euler scheme and other more accurate simulation algorithms.

  20. Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise

    NASA Astrophysics Data System (ADS)

    Wu, Fuqiang; Wang, Chunni; Jin, Wuyin; Ma, Jun

    2017-03-01

    Complex electrical activities in neuron can induce time-varying electromagnetic field and the effect of various electromagnetic inductions should be considered in dealing with electrical activities of neuron. Based on an improved neuron model, the effect of electromagnetic induction is described by using magnetic flux, and the modulation of magnetic flux on membrane potential is realized by using memristor coupling. Furthermore, additive phase noise is imposed on the neuron to detect the dynamical response of neuron and phase transition in modes. The dynamical properties of electrical activities are detected and discussed, and double coherence resonance behavior is observed, respectively. Furthermore, multiple modes of electrical activities can be observed in the sampled time series for membrane potential of the neuron model.

  1. 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.

  2. Characterization of Kiss1 neurons using transgenic mouse models

    PubMed Central

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

    2010-01-01

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

  3. A modeling approach on why simple central pattern generators are built of irregular neurons.

    PubMed

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

    2015-01-01

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

  4. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

    PubMed

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

    2016-12-01

    With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm(2) patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail.

  5. A distance constrained synaptic plasticity model of C. elegans neuronal network

    NASA Astrophysics Data System (ADS)

    Badhwar, Rahul; Bagler, Ganesh

    2017-03-01

    Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

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

    PubMed Central

    Goeritz, Marie L.; Marder, Eve

    2014-01-01

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

  7. Model of intersegmental coordination in the leech heartbeat neuronal network.

    PubMed

    Hill, Andrew A V; Masino, Mark A; Calabrese, Ronald L

    2002-03-01

    We have created a computational model of the timing network that paces the heartbeat of the medicinal leech, Hirudo medicinalis. The rhythmic activity of this network originates from two segmental oscillators located in the third and fourth midbody ganglia. In the intact nerve cord, these segmental oscillators are mutually entrained to the same cycle period. Although experiments have shown that the segmental oscillators are coupled by inhibitory coordinating interneurons, the underlying mechanisms of intersegmental coordination have not yet been elucidated. To help understand this coordination, we have created a simple computational model with two variants: symmetric and asymmetric. In the symmetric model, neurons within each segmental oscillator called oscillator interneurons, inhibit the coordinating interneurons. In contrast, in the asymmetric model only the oscillator interneurons of one segmental oscillator inhibit the coordinating interneurons. In the symmetric model, when two segmental oscillators with different inherent periods are coupled, the faster one leads in phase, and the period of the coupled system is equal to the period of the faster oscillator. This behavior arises because, during each oscillation cycle, the oscillator interneurons of the faster segmental oscillator begin to burst before those of the slower oscillator, thereby terminating spike activity in the coordinating interneurons. Thus there is a brief period of time in each cycle when the oscillator interneurons of the slower segmental oscillator are relieved of inhibition from the coordinating interneurons. This "removal of synaptic inhibition" allows, within certain limits, the slower segmental oscillator to be sped to the period of the faster one. Thus the symmetric model demonstrates a plausible biophysical mechanism by which one segmental oscillator can entrain the other. In general the asymmetric model, in which only one segmental oscillator has the ability to inhibit the

  8. NeuroGPS: automated localization of neurons for brain circuits using L1 minimization model

    NASA Astrophysics Data System (ADS)

    Quan, Tingwei; Zheng, Ting; Yang, Zhongqing; Ding, Wenxiang; Li, Shiwei; Li, Jing; Zhou, Hang; Luo, Qingming; Gong, Hui; Zeng, Shaoqun

    2013-04-01

    Drawing the map of neuronal circuits at microscopic resolution is important to explain how brain works. Recent progresses in fluorescence labeling and imaging techniques have enabled measuring the whole brain of a rodent like a mouse at submicron-resolution. Considering the huge volume of such datasets, automatic tracing and reconstruct the neuronal connections from the image stacks is essential to form the large scale circuits. However, the first step among which, automated location the soma across different brain areas remains a challenge. Here, we addressed this problem by introducing L1 minimization model. We developed a fully automated system, NeuronGlobalPositionSystem (NeuroGPS) that is robust to the broad diversity of shape, size and density of the neurons in a mouse brain. This method allows locating the neurons across different brain areas without human intervention. We believe this method would facilitate the analysis of the neuronal circuits for brain function and disease studies.

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

    PubMed

    Danziger, Zachary; Grill, Warren M

    2015-02-01

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

  10. The impact of neuronal Notch-1/JNK pathway on intracerebral hemorrhage-induced neuronal injury of rat model.

    PubMed

    Chen, Maohua; Sun, Jun; Lu, Chuan; Chen, Xiandong; Ba, Huajun; Lin, Qun; Cai, Jianyong; Dai, Junxia

    2016-11-08

    Notch signaling is a highly conserved pathway that regulates cell fate decisions during embryonic development. Notch activation endangers neurons by modulating NF-κB and HIF-1α pathways, however, the role of Notch signaling in activating JNK/c-Jun following intracerebral hemorrhage (ICH) has not been investigated. In this study, we used rat ICH models and thrombin-induced cell models to investigate the potential role of Notch-1/JNK signals. Our findings revealed that Notch-1 and JNK increased in hematoma-surrounding neurons tissues following ICH during ischemic conditions (all p<0.05). Besides, the expression of active caspase-3 protein was also up-regulated after ICH. According to in-vitro assays, the expression of Notch-1, p-JNK, and active caspase-3 were all up-regulated in cell viability-decreasing ICH cell models (all p<0.05). However, blocking of either Notch-1 or JNK suppressed the phosphorylation of JNK and the expression of active caspase-3, and cell viability was obviously ameliorated. In conclusion, this work suggested Notch-1 activates JNK pathway to induce the active caspase-3, leading to neuronal injury when intracerebral hemorrhage or ischemia occurred. Thus the Notch-1/JNK signal pathway has an important role in ICH process, and may be a therapeutic target to prevent brain injury.

  11. The impact of neuronal Notch-1/JNK pathway on intracerebral hemorrhage-induced neuronal injury of rat model

    PubMed Central

    Chen, Maohua; Sun, Jun; Lu, Chuan; Chen, Xiandong; Ba, Huajun; Lin, Qun; Cai, Jianyong; Dai, Junxia

    2016-01-01

    Notch signaling is a highly conserved pathway that regulates cell fate decisions during embryonic development. Notch activation endangers neurons by modulating NF-κB and HIF-1α pathways, however, the role of Notch signaling in activating JNK/c-Jun following intracerebral hemorrhage (ICH) has not been investigated. In this study, we used rat ICH models and thrombin-induced cell models to investigate the potential role of Notch-1/JNK signals. Our findings revealed that Notch-1 and JNK increased in hematoma-surrounding neurons tissues following ICH during ischemic conditions (all p<0.05). Besides, the expression of active caspase-3 protein was also up-regulated after ICH. According to in-vitro assays, the expression of Notch-1, p-JNK, and active caspase-3 were all up-regulated in cell viability-decreasing ICH cell models (all p<0.05). However, blocking of either Notch-1 or JNK suppressed the phosphorylation of JNK and the expression of active caspase-3, and cell viability was obviously ameliorated. In conclusion, this work suggested Notch-1 activates JNK pathway to induce the active caspase-3, leading to neuronal injury when intracerebral hemorrhage or ischemia occurred. Thus the Notch-1/JNK signal pathway has an important role in ICH process, and may be a therapeutic target to prevent brain injury. PMID:27655677

  12. 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.

  13. Effects of high-rate electrical stimulation upon firing in modelled and real neurons.

    PubMed

    Krauthamer, V; Crosheck, T

    2002-05-01

    Many medical devices use high-rate, low-amplitude currents to affect neural function. This study examined the effect of stimulation rate upon action potential threshold and sustained firing rate for two model neurons, the rabbit myelinated fibre and the unmyelinated leech touch sensory cell. These model neurons were constructed with the NEURON simulator from electrophysiological data. Alternating-phase current pulses (0-1250 Hz), of fixed phase duration (0.2 ms), were used to stimulate the neurons, and propagation success or failure was measured. One effect of the high pulse rates was to cause a net depolarisation, and this was verified by the relief of action potential conduction block by 500 Hz extracellular stimulation in leech neurons. The models also predicted that the neurons would maintain maximum sustained firing at a number of different stimulation rates. For example, at twice threshold, the myelinated model followed the stimulus up to 500 Hz stimulation, half the stimulus rate up to 850 Hz stimulation, and it did not fire at 1250 Hz stimulation. By contrast, the unmyelinated neuron model had a lower maximum firing rate of 190 Hz, and this rate was obtained at a number of stimulation rates, up to 1250 Hz. The myelinated model also predicted sustained firing with 1240 Hz stimulation at threshold current, but no firing when the current level was doubled. Most of these effects are explained by the interaction of stimulus pulses with the cell's refractory period.

  14. Noisy threshold in neuronal models: connections with the noisy leaky integrate-and-fire model.

    PubMed

    Dumont, G; Henry, J; Tarniceriu, C O

    2016-12-01

    Providing an analytical treatment to the stochastic feature of neurons' dynamics is one of the current biggest challenges in mathematical biology. The noisy leaky integrate-and-fire model and its associated Fokker-Planck equation are probably the most popular way to deal with neural variability. Another well-known formalism is the escape-rate model: a model giving the probability that a neuron fires at a certain time knowing the time elapsed since its last action potential. This model leads to a so-called age-structured system, a partial differential equation with non-local boundary condition famous in the field of population dynamics, where the age of a neuron is the amount of time passed by since its previous spike. In this theoretical paper, we investigate the mathematical connection between the two formalisms. We shall derive an integral transform of the solution to the age-structured model into the solution of the Fokker-Planck equation. This integral transform highlights the link between the two stochastic processes. As far as we know, an explicit mathematical correspondence between the two solutions has not been introduced until now.

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

    PubMed Central

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

    2014-01-01

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

  16. Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neurons.

    PubMed

    Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

    2011-12-01

    An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows ("explaining away") and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons.

  17. Modeling ALS with motor neurons derived from human induced pluripotent stem cells.

    PubMed

    Sances, Samuel; Bruijn, Lucie I; Chandran, Siddharthan; Eggan, Kevin; Ho, Ritchie; Klim, Joseph R; Livesey, Matt R; Lowry, Emily; Macklis, Jeffrey D; Rushton, David; Sadegh, Cameron; Sareen, Dhruv; Wichterle, Hynek; Zhang, Su-Chun; Svendsen, Clive N

    2016-04-01

    Directing the differentiation of induced pluripotent stem cells into motor neurons has allowed investigators to develop new models of amyotrophic lateral sclerosis (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 coculture 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.

  18. 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

  19. Qualitative validation of the reduction from two reciprocally coupled neurons to one self-coupled neuron in a respiratory network model.

    PubMed

    Dunmyre, Justin R

    2011-06-01

    The pre-Bötzinger complex of the mammalian brainstem is a heterogeneous neuronal network, and individual neurons within the network have varying strengths of the persistent sodium and calcium-activated nonspecific cationic currents. Individually, these currents have been the focus of modeling efforts. Previously, Dunmyre et al. (J Comput Neurosci 1-24, 2011) proposed a model and studied the interactions of these currents within one self-coupled neuron. In this work, I consider two identical, reciprocally coupled model neurons and validate the reduction to the self-coupled case. I find that all of the dynamics of the two model neuron network and the regions of parameter space where these distinct dynamics are found are qualitatively preserved in the reduction to the self-coupled case.

  20. Quantitative 3D investigation of Neuronal network in mouse spinal cord model.

    PubMed

    Bukreeva, I; Campi, G; Fratini, M; Spanò, R; Bucci, D; Battaglia, G; Giove, F; Bravin, A; Uccelli, A; Venturi, C; Mastrogiacomo, M; Cedola, A

    2017-01-23

    The investigation of the neuronal network in mouse spinal cord models represents the basis for the research on neurodegenerative diseases. In this framework, the quantitative analysis of the single elements in different districts is a crucial task. However, conventional 3D imaging techniques do not have enough spatial resolution and contrast to allow for a quantitative investigation of the neuronal network. Exploiting the high coherence and the high flux of synchrotron sources, X-ray Phase-Contrast multiscale-Tomography allows for the 3D investigation of the neuronal microanatomy without any aggressive sample preparation or sectioning. We investigated healthy-mouse neuronal architecture by imaging the 3D distribution of the neuronal-network with a spatial resolution of 640 nm. The high quality of the obtained images enables a quantitative study of the neuronal structure on a subject-by-subject basis. We developed and applied a spatial statistical analysis on the motor neurons to obtain quantitative information on their 3D arrangement in the healthy-mice spinal cord. Then, we compared the obtained results with a mouse model of multiple sclerosis. Our approach paves the way to the creation of a "database" for the characterization of the neuronal network main features for a comparative investigation of neurodegenerative diseases and therapies.

  1. Quantitative 3D investigation of Neuronal network in mouse spinal cord model

    PubMed Central

    Bukreeva, I.; Campi, G.; Fratini, M.; Spanò, R.; Bucci, D.; Battaglia, G.; Giove, F.; Bravin, A.; Uccelli, A.; Venturi, C.; Mastrogiacomo, M.; Cedola, A.

    2017-01-01

    The investigation of the neuronal network in mouse spinal cord models represents the basis for the research on neurodegenerative diseases. In this framework, the quantitative analysis of the single elements in different districts is a crucial task. However, conventional 3D imaging techniques do not have enough spatial resolution and contrast to allow for a quantitative investigation of the neuronal network. Exploiting the high coherence and the high flux of synchrotron sources, X-ray Phase-Contrast multiscale-Tomography allows for the 3D investigation of the neuronal microanatomy without any aggressive sample preparation or sectioning. We investigated healthy-mouse neuronal architecture by imaging the 3D distribution of the neuronal-network with a spatial resolution of 640 nm. The high quality of the obtained images enables a quantitative study of the neuronal structure on a subject-by-subject basis. We developed and applied a spatial statistical analysis on the motor neurons to obtain quantitative information on their 3D arrangement in the healthy-mice spinal cord. Then, we compared the obtained results with a mouse model of multiple sclerosis. Our approach paves the way to the creation of a “database” for the characterization of the neuronal network main features for a comparative investigation of neurodegenerative diseases and therapies. PMID:28112212

  2. Quantitative 3D investigation of Neuronal network in mouse spinal cord model

    NASA Astrophysics Data System (ADS)

    Bukreeva, I.; Campi, G.; Fratini, M.; Spanò, R.; Bucci, D.; Battaglia, G.; Giove, F.; Bravin, A.; Uccelli, A.; Venturi, C.; Mastrogiacomo, M.; Cedola, A.

    2017-01-01

    The investigation of the neuronal network in mouse spinal cord models represents the basis for the research on neurodegenerative diseases. In this framework, the quantitative analysis of the single elements in different districts is a crucial task. However, conventional 3D imaging techniques do not have enough spatial resolution and contrast to allow for a quantitative investigation of the neuronal network. Exploiting the high coherence and the high flux of synchrotron sources, X-ray Phase-Contrast multiscale-Tomography allows for the 3D investigation of the neuronal microanatomy without any aggressive sample preparation or sectioning. We investigated healthy-mouse neuronal architecture by imaging the 3D distribution of the neuronal-network with a spatial resolution of 640 nm. The high quality of the obtained images enables a quantitative study of the neuronal structure on a subject-by-subject basis. We developed and applied a spatial statistical analysis on the motor neurons to obtain quantitative information on their 3D arrangement in the healthy-mice spinal cord. Then, we compared the obtained results with a mouse model of multiple sclerosis. Our approach paves the way to the creation of a “database” for the characterization of the neuronal network main features for a comparative investigation of neurodegenerative diseases and therapies.

  3. 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…

  4. Molecular model of cannabis sensitivity in developing neuronal circuits.

    PubMed

    Keimpema, Erik; Mackie, Ken; Harkany, Tibor

    2011-09-01

    Prenatal cannabis exposure can complicate in utero development of the nervous system. Cannabis impacts the formation and functions of neuronal circuitries by targeting cannabinoid receptors. Endocannabinoid signaling emerges as a signaling cassette that orchestrates neuronal differentiation programs through the precisely timed interaction of endocannabinoid ligands with their cognate cannabinoid receptors. By indiscriminately prolonging the 'switched-on' period of cannabinoid receptors, cannabis can hijack endocannabinoid signals to evoke molecular rearrangements, leading to the erroneous wiring of neuronal networks. Here, we formulate a hierarchical network design necessary and sufficient to describe the molecular underpinnings of cannabis-induced neural growth defects. We integrate signalosome components, deduced from genome- and proteome-wide arrays and candidate analyses, to propose a mechanistic hypothesis of how cannabis-induced ectopic cannabinoid receptor activity overrides physiological neurodevelopmental endocannabinoid signals, affecting the timely formation of synapses.

  5. A Phase-Locking Analysis of Neuronal Firing Rhythms with Transcranial Magneto-Acoustical Stimulation Based on the Hodgkin-Huxley Neuron Model

    PubMed Central

    Yuan, Yi; Pang, Na; Chen, Yudong; Wang, Yi; Li, Xiaoli

    2017-01-01

    Transcranial magneto-acoustical stimulation (TMAS) uses ultrasonic waves and a static magnetic field to generate electric current in nerve tissues for the purpose of modulating neuronal activities. It has the advantage of high spatial resolution and penetration depth. Neuronal firing rhythms carry and transmit nerve information in neural systems. In this study, we investigated the phase-locking characteristics of neuronal firing rhythms with TMAS based on the Hodgkin-Huxley neuron model. The simulation results indicate that the modulation frequency of ultrasound can affect the phase-locking behaviors. The results of this study may help us to explain the potential firing mechanism of TMAS. PMID:28163679

  6. 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).

  7. The Effects of Guanfacine and Phenylephrine on a Spiking Neuron Model of Working Memory.

    PubMed

    Duggins, Peter; Stewart, Terrence C; Choo, Xuan; Eliasmith, Chris

    2017-01-01

    We use a spiking neural network model of working memory (WM) capable of performing the spatial delayed response task (DRT) to investigate two drugs that affect WM: guanfacine (GFC) and phenylephrine (PHE). In this model, the loss of information over time results from changes in the spiking neural activity through recurrent connections. We reproduce the standard forgetting curve and then show that this curve changes in the presence of GFC and PHE, whose application is simulated by manipulating functional, neural, and biophysical properties of the model. In particular, applying GFC causes increased activity in neurons that are sensitive to the information currently being remembered, while applying PHE leads to decreased activity in these same neurons. Interestingly, these differential effects emerge from network-level interactions because GFC and PHE affect all neurons equally. We compare our model to both electrophysiological data from neurons in monkey dorsolateral prefrontal cortex and to behavioral evidence from monkeys performing the DRT.

  8. 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

  9. [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.

  10. Histologic assessment of neurons in rat models of cerebral ischemia.

    PubMed

    Eke, A; Conger, K A; Anderson, M; Garcia, J H

    1990-02-01

    We describe a method for typing neurons into four progressive stages of ischemic deterioration based on visual characterization of the nucleus in terms of its optical contrast, delineation along the nuclear-cytoplasmic interface, and its shape. Difficulty in assessing nuclear shape required the introduction of an angularity comparator chart to improve the investigator's accuracy. Three investigators typed neurons obtained from normal, ischemic, and ischemic-reperfused rat brains. Accuracy and reproducibility of the investigators' typing decisions with and without the angularity comparator charts were evaluated. The accuracy of subjective shape assessment was compared with objective digitizer measurements of the same. The angularity comparator charts reduced subjective shape classification error by two thirds, and group error (overall performance expressed by the coefficient of variance) decreased from 15.9% to 4.7% for Type I (normal cells), from 33.9% to 17.3% for Type II (cells with angular nuclei), from 15.5% to 14.1% for Type III (cells with smeared nuclei), and from 3.2% to 5.5% for Type IV (dead cells). Thus, Type I and IV neurons can be assessed at a higher reproducibility than the intermediate Types II and III. Our typing method can also be used to evaluate the effect of treatment regimes on ischemic neuronal damage.

  11. Modeling spiking activity of in vitro neuronal networks through non linear methods.

    PubMed

    Maffezzoli, A; Signorini, M G; Gullo, F; Wanke, E

    2008-01-01

    Neuroscience research is even more exploiting technologies developed for electronic engineering use: this is the case of Micro-Electrode Array (MEA) technology, an instrumentation which is able to acquire in vitro neuron spiking activity from a finite number of channels. In this work we present three models of synaptic neuronal network connections, called 'Full-Connected', 'Hierarchical' and 'Closed-Path'. Related to each one we implemented an index giving quantitative measures of similarity and of statistical dependence among neuron activities recorded in different MEA channels. They are based on Information Theory techniques as Mutual and Multi Information: the last one extending the pair-wise information to higher-order connections on the entire MEA neuronal network. We calculated indexes for each model in order to test the presence of self-synchronization among neurons evolving in time, in response to external stimuli such as the application of chemical neuron-inhibitors. The availability of such different models helps us to investigate also how much the synaptic connections are spatially sparse or hierarchically structured and finally how much of the information exchanged on the neuronal network is regulated by higher-order correlations.

  12. 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.

  13. Neuronal Entropy-Rate Feature of Entopeduncular Nucleus in Rat Model of Parkinson's Disease.

    PubMed

    Darbin, Olivier; Jin, Xingxing; Von Wrangel, Christof; Schwabe, Kerstin; Nambu, Atsushi; Naritoku, Dean K; Krauss, Joachim K; Alam, Mesbah

    2016-03-01

    The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus, i.e. the entopeduncular nucleus (EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson's disease (PD). In both control subjects and subjects with 6-OHDA lesion of dopamine (DA) the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15 and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25 Hz. Our data establishes that the nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions such as movement disorders.

  14. Comparative analysis of system identification techniques for nonlinear modeling of the neuron-microelectrode junction.

    PubMed

    Khan, Saad Ahmad; Thakore, Vaibhav; Behal, Aman; Bölöni, Ladislau; Hickman, James J

    2013-03-01

    Applications of non-invasive neuroelectronic interfacing in the fields of whole-cell biosensing, biological computation and neural prosthetic devices depend critically on an efficient decoding and processing of information retrieved from a neuron-electrode junction. This necessitates development of mathematical models of the neuron-electrode interface that realistically represent the extracellular signals recorded at the neuroelectronic junction without being computationally expensive. Extracellular signals recorded using planar microelectrode or field effect transistor arrays have, until now, primarily been represented using linear equivalent circuit models that fail to reproduce the correct amplitude and shape of the signals recorded at the neuron-microelectrode interface. In this paper, to explore viable alternatives for a computationally inexpensive and efficient modeling of the neuron-electrode junction, input-output data from the neuron-electrode junction is modeled using a parametric Wiener model and a Nonlinear Auto-Regressive network with eXogenous input trained using a dynamic Neural Network model (NARX-NN model). Results corresponding to a validation dataset from these models are then employed to compare and contrast the computational complexity and efficiency of the aforementioned modeling techniques with the Lee-Schetzen technique of cross-correlation for estimating a nonlinear dynamic model of the neuroelectronic junction.

  15. Comparative analysis of system identification techniques for nonlinear modeling of the neuron-microelectrode junction

    PubMed Central

    Khan, Saad Ahmad; Thakore, Vaibhav; Behal, Aman; Bölöni, Ladislau; Hickman, James J.

    2016-01-01

    Applications of non-invasive neuroelectronic interfacing in the fields of whole-cell biosensing, biological computation and neural prosthetic devices depend critically on an efficient decoding and processing of information retrieved from a neuron-electrode junction. This necessitates development of mathematical models of the neuron-electrode interface that realistically represent the extracellular signals recorded at the neuroelectronic junction without being computationally expensive. Extracellular signals recorded using planar microelectrode or field effect transistor arrays have, until now, primarily been represented using linear equivalent circuit models that fail to reproduce the correct amplitude and shape of the signals recorded at the neuron-microelectrode interface. In this paper, to explore viable alternatives for a computationally inexpensive and efficient modeling of the neuron-electrode junction, input-output data from the neuron-electrode junction is modeled using a parametric Wiener model and a Nonlinear Auto-Regressive network with eXogenous input trained using a dynamic Neural Network model (NARX-NN model). Results corresponding to a validation dataset from these models are then employed to compare and contrast the computational complexity and efficiency of the aforementioned modeling techniques with the Lee-Schetzen technique of cross-correlation for estimating a nonlinear dynamic model of the neuroelectronic junction.

  16. A learning-enabled neuron array IC based upon transistor channel models of biological phenomena.

    PubMed

    Brink, S; Nease, S; Hasler, P; Ramakrishnan, S; Wunderlich, R; Basu, A; Degnan, B

    2013-02-01

    We present a single-chip array of 100 biologically-based electronic neuron models interconnected to each other and the outside environment through 30,000 synapses. The chip was fabricated in a standard 350 nm CMOS IC process. Our approach used dense circuit models of synaptic behavior, including biological computation and learning, as well as transistor channel models. We use Address-Event Representation (AER) spike communication for inputs and outputs to this IC. We present the IC architecture and infrastructure, including IC chip, configuration tools, and testing platform. We present measurement of small network of neurons, measurement of STDP neuron dynamics, and measurement from a compiled spiking neuron WTA topology, all compiled into this IC.

  17. 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

  18. A neuronal network model with simplified tonotopicity for tinnitus generation and its relief by sound therapy.

    PubMed

    Nagashino, Hirofumi; Kinouchi, Yohsuke; Danesh, Ali A; Pandya, Abhijit S

    2013-01-01

    Tinnitus is the perception of sound in the ears or in the head where no external source is present. Sound therapy is one of the most effective techniques for tinnitus treatment that have been proposed. In order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy, we have proposed conceptual and computational models with plasticity using a neural oscillator or a neuronal network model. In the present paper, we propose a neuronal network model with simplified tonotopicity of the auditory system as more detailed structure. In this model an integrate-and-fire neuron model is employed and homeostatic plasticity is incorporated. The computer simulation results show that the present model can show the generation of oscillation and its cessation by external input. It suggests that the present framework is promising as a modeling for the tinnitus generation and the effects of sound therapy.

  19. Neuronally-directed effects of RXR activation in a mouse model of Alzheimer’s disease

    PubMed Central

    Mariani, M. M.; Malm, T.; Lamb, R.; Jay, T. R.; Neilson, L.; Casali, B.; Medarametla, L.; Landreth, G. E.

    2017-01-01

    Alzheimer’s disease (AD) is characterized by extensive neuron loss that accompanies profound impairments in memory and cognition. We examined the neuronally directed effects of the retinoid X receptor agonist bexarotene in an aggressive model of AD. We report that a two week treatment of 3.5 month old 5XFAD mice with bexarotene resulted in the clearance of intraneuronal amyloid deposits. Importantly, neuronal loss was attenuated by 44% in the subiculum in mice 4 months of age and 18% in layer V of the cortex in mice 8 months of age. Moreover, bexarotene treatment improved remote memory stabilization in fear conditioned mice and improved olfactory cross habituation. These improvements in neuron viability and function were correlated with significant increases in the levels of post-synaptic marker PSD95 and the pre-synaptic marker synaptophysin. Moreover, bexarotene pretreatment improved neuron survival in primary 5XFAD neurons in vitro in response to glutamate-induced excitotoxicity. The salutary effects of bexarotene were accompanied by reduced plaque burden, decreased astrogliosis, and suppression of inflammatory gene expression. Collectively, these data provide evidence that bexarotene treatment reduced neuron loss, elevated levels of markers of synaptic integrity that was linked to improved cognition and in an aggressive model of AD. PMID:28205585

  20. 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.

  1. 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

  2. Lower Motor Control Modeled by Neuron With Fuzzy Synapses

    DTIC Science & Technology

    2007-11-02

    seen in parkinsonism , chorea, cerebellar disorders, and spasticity. In most cases, muscles work in opposing pairs: one muscle opens or extends a joint...performances of predictor schemes based on neurons with fuzzy synapses of order P = 3 in tremor prediction applications. The rules of these particular...Chelaru, A. Kandel, I. Tofan, M. Irimia, “Fuzzy methods in tremor assessment, prediction, and rehabilitation”, Artificial Intelligence in Medicine

  3. The effect of dendritic voltage-gated conductances on the neuronal impedance: a quantitative model.

    PubMed

    Káli, Szabolcs; Zemankovics, Rita

    2012-10-01

    Neuronal impedance characterizes the magnitude and timing of the subthreshold response of a neuron to oscillatory input at a given frequency. It is known to be influenced by both the morphology of the neuron and the presence of voltage-gated conductances in the cell membrane. Most existing theoretical accounts of neuronal impedance considered the effects of voltage-gated conductances but neglected the spatial extent of the cell, while others examined spatially extended dendrites with a passive or spatially uniform quasi-active membrane. We derived an explicit mathematical expression for the somatic input impedance of a model neuron consisting of a somatic compartment coupled to an infinite dendritic cable which contained voltage-gated conductances, in the more general case of non-uniform dendritic membrane potential. The validity and generality of this model was verified through computer simulations of various model neurons. The analytical model was then applied to the analysis of experimental data from real CA1 pyramidal neurons. The model confirmed that the biophysical properties and predominantly dendritic localization of the hyperpolarization-activated cation current I (h) were important determinants of the impedance profile, but also predicted a significant contribution from a depolarization-activated fast inward current. Our calculations also implicated the interaction of I (h) with amplifying currents as the main factor governing the shape of the impedance-frequency profile in two types of hippocampal interneuron. Our results provide not only a theoretical advance in our understanding of the frequency-dependent behavior of nerve cells, but also a practical tool for the identification of candidate mechanisms that determine neuronal response properties.

  4. Dendritic vulnerability in neurodegenerative disease: insights from analyses of cortical pyramidal neurons in transgenic mouse models

    PubMed Central

    Weaver, Christina M.; Rocher, Anne B.; Rodriguez, Alfredo; Crimins, Johanna L.; Dickstein, Dara L.; Wearne, Susan L.; Hof, Patrick R.

    2011-01-01

    In neurodegenerative disorders, such as Alzheimer’s disease, neuronal dendrites and dendritic spines undergo significant pathological changes. Because of the determinant role of these highly dynamic structures in signaling by individual neurons and ultimately in the functionality of neuronal networks that mediate cognitive functions, a detailed understanding of these changes is of paramount importance. Mutant murine models, such as the Tg2576 APP mutant mouse and the rTg4510 tau mutant mouse have been developed to provide insight into pathogenesis involving the abnormal production and aggregation of amyloid and tau proteins, because of the key role that these proteins play in neurodegenerative disease. This review showcases the multidimensional approach taken by our collaborative group to increase understanding of pathological mechanisms in neurodegenerative disease using these mouse models. This approach includes analyses of empirical 3D morphological and electrophysiological data acquired from frontal cortical pyramidal neurons using confocal laser scanning microscopy and whole-cell patch-clamp recording techniques, combined with computational modeling methodologies. These collaborative studies are designed to shed insight on the repercussions of dystrophic changes in neocortical neurons, define the cellular phenotype of differential neuronal vulnerability in relevant models of neurodegenerative disease, and provide a basis upon which to develop meaningful therapeutic strategies aimed at preventing, reversing, or compensating for neurodegenerative changes in dementia. PMID:20177698

  5. Immunohistochemical visualization of hippocampal neuron activity after spatial learning in a mouse model of neurodevelopmental disorders.

    PubMed

    Provenzano, Giovanni; Pangrazzi, Luca; Poli, Andrea; Berardi, Nicoletta; Bozzi, Yuri

    2015-05-12

    Induction of phosphorylated extracellular-regulated kinase (pERK) is a reliable molecular readout of learning-dependent neuronal activation. Here, we describe a pERK immunohistochemistry protocol to study the profile of hippocampal neuron activation following exposure to a spatial learning task in a mouse model characterized by cognitive deficits of neurodevelopmental origin. Specifically, we used pERK immunostaining to study neuronal activation following Morris water maze (MWM, a classical hippocampal-dependent learning task) in Engrailed-2 knockout (En2(-/-)) mice, a model of autism spectrum disorders (ASD). As compared to wild-type (WT) controls, En2(-/-) mice showed significant spatial learning deficits in the MWM. After MWM, significant differences in the number of pERK-positive neurons were detected in specific hippocampal subfields of En2(-/-) mice, as compared to WT animals. Thus, our protocol can robustly detect differences in pERK-positive neurons associated to hippocampal-dependent learning impairment in a mouse model of ASD. More generally, our protocol can be applied to investigate the profile of hippocampal neuron activation in both genetic or pharmacological mouse models characterized by cognitive deficits.

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

    NASA Astrophysics Data System (ADS)

    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.

  7. Experimentally guided modelling of dendritic excitability in rat neocortical pyramidal neurones

    PubMed Central

    Keren, Naomi; Bar-Yehuda, Dan; Korngreen, Alon

    2009-01-01

    Constructing physiologically relevant compartmental models of neurones is critical for understanding neuronal activity and function. We recently suggested that measurements from multiple locations along the soma, dendrites and axon are necessary as a data set when using a genetic optimization algorithm to constrain the parameters of a compartmental model of an entire neurone. However, recordings from L5 pyramidal neurones can routinely be performed simultaneously from only two locations. Now we show that a data set recorded from the soma and apical dendrite combined with a parameter peeling procedure is sufficient to constrain a compartmental model for the apical dendrite of L5 pyramidal neurones. The peeling procedure was tested on several compartmental models showing that it avoids local minima in parameter space. Based on the requirements of this analysis procedure, we designed and performed simultaneous whole-cell recordings from the soma and apical dendrite of rat L5 pyramidal neurones. The data set obtained from these recordings allowed constraining a simplified compartmental model for the apical dendrite of L5 pyramidal neurones containing four voltage-gated conductances. In agreement with experimental findings, the optimized model predicts that the conductance density gradients of voltage-gated K+ conductances taper rapidly proximal to the soma, while the density gradient of the voltage-gated Na+ conductance tapers slowly along the apical dendrite. The model reproduced the back-propagation of the action potential and the modulation of the resting membrane potential along the apical dendrite. Furthermore, the optimized model provided a mechanistic explanation for the back-propagation of the action potential into the apical dendrite and the generation of dendritic Na+ spikes. PMID:19171651

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

    PubMed Central

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

    2015-01-01

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

  9. Dopamine neuronal loss contributes to memory and reward dysfunction in a model of Alzheimer's disease.

    PubMed

    Nobili, Annalisa; Latagliata, Emanuele Claudio; Viscomi, Maria Teresa; Cavallucci, Virve; Cutuli, Debora; Giacovazzo, Giacomo; Krashia, Paraskevi; Rizzo, Francesca Romana; Marino, Ramona; Federici, Mauro; De Bartolo, Paola; Aversa, Daniela; Dell'Acqua, Maria Concetta; Cordella, Alberto; Sancandi, Marco; Keller, Flavio; Petrosini, Laura; Puglisi-Allegra, Stefano; Mercuri, Nicola Biagio; Coccurello, Roberto; Berretta, Nicola; D'Amelio, Marcello

    2017-04-03

    Alterations of the dopaminergic (DAergic) system are frequently reported in Alzheimer's disease (AD) patients and are commonly linked to cognitive and non-cognitive symptoms. However, the cause of DAergic system dysfunction in AD remains to be elucidated. We investigated alterations of the midbrain DAergic system in the Tg2576 mouse model of AD, overexpressing a mutated human amyloid precursor protein (APPswe). Here, we found an age-dependent DAergic neuron loss in the ventral tegmental area (VTA) at pre-plaque stages, although substantia nigra pars compacta (SNpc) DAergic neurons were intact. The selective VTA DAergic neuron degeneration results in lower DA outflow in the hippocampus and nucleus accumbens (NAc) shell. The progression of DAergic cell death correlates with impairments in CA1 synaptic plasticity, memory performance and food reward processing. We conclude that in this mouse model of AD, degeneration of VTA DAergic neurons at pre-plaque stages contributes to memory deficits and dysfunction of reward processing.

  10. An analytical study of relay neuron's reliability: dependence on input and model parameters.

    PubMed

    Agarwal, Rahul; Sarma, Sridevi V

    2011-01-01

    Relay neurons are widely found in our nervous system, including the Thalamus, spinal cord and lateral geniculate body. They receive a modulating input (background activity) and a reference input. The modulating input modulates relay of the reference input. This modulation is critical for correct functioning of relay neurons, but is poorly understood. In this paper, we use a biophysical-based model and systems theoretic tools to calculate how well a single relay neuron relays a reference input signal as a function of the neuron's electro physiological properties (i.e. model parameters), the modulating signal, and the reference signal parameters. Our analysis is more rigorous than previous related works and is generalizable to all relay cells in the body. Our analytical expression matches relay performance obtained in simulation and suggest that increasing the frequency of a sinusoidal modulating input or decreasing its DC offset increases the relay cell reliability.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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

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

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  18. 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.

  19. 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.

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

    PubMed

    Ebner, Marc; Hameroff, Stuart

    2011-01-01

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

  1. Microglia activation and interaction with neuronal cells in a biochemical model of mevalonate kinase deficiency.

    PubMed

    Tricarico, Paola Maura; Piscianz, Elisa; Monasta, Lorenzo; Kleiner, Giulio; Crovella, Sergio; Marcuzzi, Annalisa

    2015-08-01

    Mevalonate kinase deficiency is a rare disease whose worst manifestation, characterised by severe neurologic impairment, is called mevalonic aciduria. The progressive neuronal loss associated to cell death can be studied in vitro with a simplified model based on a biochemical block of the mevalonate pathway and a subsequent inflammatory trigger. The aim of this study was to evaluate the effect of the mevalonate blocking on glial cells (BV-2) and the following effects on neuronal cells (SH-SY5Y) when the two populations were cultured together. To better understand the cross-talk between glial and neuronal cells, as it happens in vivo, BV-2 and SH-SY5Y were co-cultured in different experimental settings (alone, transwell, direct contact); the effect of mevalonate pathway biochemical block by Lovastatin, followed by LPS inflammatory trigger, were evaluated by analysing programmed cell death and mitochondrial membrane potential, cytokines' release and cells' morphology modifications. In this experimental condition, glial cells underwent an evident activation, confirmed by elevated pro-inflammatory cytokines release, typical of these disorders, and a modification in morphology. Moreover, the activation induced an increase in apoptosis. When glial cells were co-cultured with neurons, their activation caused an increase of programmed cell death also in neuronal cells, but only if the two populations were cultured in direct contact. Our findings, being aware of the limitations related to the cell models used, represent a preliminary step towards understanding the pathological and neuroinflammatory mechanisms occurring in mevalonate kinase diseases. Contact co-culture between neuronal and microglial cells seems to be a good model to study mevalonic aciduria in vitro, and to contribute to the identification of potential drugs able to block microglial activation for this orphan disease. In fact, in such a pathological condition, we demonstrated that microglial cells are

  2. Functional astrocyte-neuron lactate shuttle in a human stem cell-derived neuronal network.

    PubMed

    Tarczyluk, Marta A; Nagel, David A; O'Neil, John D; Parri, H Rheinallt; Tse, Erin H Y; Coleman, Michael D; Hill, Eric J

    2013-09-01

    The NT2.D1 cell line is one of the most well-documented embryocarcinoma cell lines, and can be differentiated into neurons and astrocytes. Great focus has also been placed on defining the electrophysiological properties of the neuronal cells, and more recently we have investigated the functional properties of their associated astrocytes. We now show for the first time that human stem cell-derived astrocytes produce glycogen and that co-cultures of these cells demonstrate a functional astrocyte-neuron lactate shuttle (ANLS). The ANLS hypothesis proposes that during neuronal activity, glutamate released into the synaptic cleft is taken up by astrocytes and triggers glucose uptake, which is converted into lactate and released via monocarboxylate transporters for neuronal use. Using mixed cultures of NT2-derived neurons and astrocytes, we have shown that these cells modulate their glucose uptake in response to glutamate. Additionally, we demonstrate that in response to increased neuronal activity and under hypoglycaemic conditions, co-cultures modulate glycogen turnover and increase lactate production. Similar results were also shown after treatment with glutamate, potassium, isoproterenol, and dbcAMP. Together, these results demonstrate for the first time a functional ANLS in a human stem cell-derived co-culture.

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

    PubMed

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

    2015-03-19

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

  4. Effect of antioxidant treatment on spinal GABA neurons in a neuropathic pain model in the mouse.

    PubMed

    Yowtak, June; Wang, Jigong; Kim, Hee Young; Lu, Ying; Chung, Kyungsoon; Chung, Jin Mo

    2013-11-01

    One feature of neuropathic pain is a reduced spinal gamma-aminobutyric acid (GABA)-ergic inhibitory function. However, the mechanisms behind this attenuation remain to be elucidated. This study investigated the involvement of reactive oxygen species in the spinal GABA neuron loss and reduced GABA neuron excitability in spinal nerve ligation (SNL) model of neuropathic pain in mice. The importance of spinal GABAergic inhibition in neuropathic pain was tested by examining the effects of intrathecally administered GABA receptor agonists and antagonists in SNL and naïve mice, respectively. The effects of SNL and antioxidant treatment on GABA neuron loss and functional changes were examined in transgenic GAD67-enhanced green fluorescent protein positive (EGFP+) mice. GABA receptor agonists transiently reversed mechanical hypersensitivity of the hind paw in SNL mice. On the other hand, GABA receptor antagonists made naïve mice mechanically hypersensitive. Stereological analysis showed that the numbers of enhanced green fluorescent protein positive (EGFP+) GABA neurons were significantly decreased in the lateral superficial laminae (I-II) on the ipsilateral L5 spinal cord after SNL. Repeated antioxidant treatments significantly reduced the pain behaviors and prevented the reduction in EGFP+ GABA neurons. The response rate of the tonic firing GABA neurons recorded from SNL mice increased with antioxidant treatment, whereas no change was seen in those recorded from naïve mice, which suggested that oxidative stress impaired some spinal GABA neuron activity in the neuropathic pain condition. Together the data suggest that neuropathic pain, at least partially, is attributed to oxidative stress, which induces both a GABA neuron loss and dysfunction of surviving GABA neurons.

  5. 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

  6. 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

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

    PubMed

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

    2015-05-22

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

  8. A model for experience-dependent changes in the responses of inferotemporal neurons.

    PubMed

    Sohal, V S; Hasselmo, M E

    2000-08-01

    Neurons in inferior temporal (IT) cortex exhibit selectivity for complex visual stimuli and can maintain activity during the delay following the presentation of a stimulus in delayed match to sample tasks. Experimental work in awake monkeys has shown that the responses of IT neurons decline during presentation of stimuli which have been seen recently (within the past few seconds). In addition, experiments have found that the responses of IT neurons to visual stimuli also decline as the stimuli become familiar, independent of recency. Here a biologically based neural network simulation is used to model these effects primarily through two processes. The recency effects are caused by adaptation due to a calcium-dependent potassium current, and the familiarity effects are caused by competitive self-organization of modifiable feedforward synapses terminating on IT cortex neurons.

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

    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.

  11. 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

  12. Modeling the network dynamics of pulse-coupled neurons

    NASA Astrophysics Data System (ADS)

    Chandra, Sarthak; Hathcock, David; Crain, Kimberly; Antonsen, Thomas M.; Girvan, Michelle; Ott, Edward

    2017-03-01

    We derive a mean-field approximation for the macroscopic dynamics of large networks of pulse-coupled theta neurons in order to study the effects of different network degree distributions and degree correlations (assortativity). Using the ansatz of Ott and Antonsen [Chaos 18, 037113 (2008)], we obtain a reduced system of ordinary differential equations describing the mean-field dynamics, with significantly lower dimensionality compared with the complete set of dynamical equations for the system. We find that, for sufficiently large networks and degrees, the dynamical behavior of the reduced system agrees well with that of the full network. This dimensional reduction allows for an efficient characterization of system phase transitions and attractors. For networks with tightly peaked degree distributions, the macroscopic behavior closely resembles that of fully connected networks previously studied by others. In contrast, networks with highly skewed degree distributions exhibit different macroscopic dynamics due to the emergence of degree dependent behavior of different oscillators. For nonassortative networks (i.e., networks without degree correlations), we observe the presence of a synchronously firing phase that can be suppressed by the presence of either assortativity or disassortativity in the network. We show that the results derived here can be used to analyze the effects of network topology on macroscopic behavior in neuronal networks in a computationally efficient fashion.

  13. 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.

  14. Modeling of multisensory convergence with a network of spiking neurons: a reverse engineering approach.

    PubMed

    Lim, Hun Ki; Keniston, Leslie P; Cios, Krzysztof J

    2011-07-01

    Multisensory processing in the brain underlies a wide variety of perceptual phenomena, but little is known about the underlying mechanisms of how multisensory neurons are formed. This lack of knowledge is due to the difficulty for biological experiments to manipulate and test the parameters of multisensory convergence, the first and definitive step in the multisensory process. Therefore, by using a computational model of multisensory convergence, this study seeks to provide insight into the mechanisms of multisensory convergence. To reverse-engineer multisensory convergence, we used a biologically realistic neuron model and a biology-inspired plasticity rule, but did not make any a priori assumptions about multisensory properties of neurons in the network. The network consisted of two separate projection areas that converged upon neurons in a third area, and stimulation involved activation of one of the projection areas (or the other) or their combination. Experiments consisted of two parts: network training and multisensory simulation. Analyses were performed, first, to find multisensory properties in the simulated networks; second, to reveal properties of the network using graph theoretical approach; and third, to generate hypothesis related to the multisensory convergence. The results showed that the generation of multisensory neurons related to the topological properties of the network, in particular, the strengths of connections after training, was found to play an important role in forming and thus distinguishing multisensory neuron types.

  15. Phase diagrams and dynamics of a computationally efficient map-based neuron model

    PubMed Central

    Gonsalves, Jheniffer J.; Tragtenberg, Marcelo H. R.

    2017-01-01

    We introduce a new map-based neuron model derived from the dynamical perceptron family that has the best compromise between computational efficiency, analytical tractability, reduced parameter space and many dynamical behaviors. We calculate bifurcation and phase diagrams analytically and computationally that underpins a rich repertoire of autonomous and excitable dynamical behaviors. We report the existence of a new regime of cardiac spikes corresponding to nonchaotic aperiodic behavior. We compare the features of our model to standard neuron models currently available in the literature. PMID:28358843

  16. Cofilin inhibition restores neuronal cell death in oxygen glucose deprivation model of ischemia

    PubMed Central

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

    2014-01-01

    Ischemia is a condition associated with decreased blood supply to the brain, eventually leading to death of neurons. It is associated with a diverse cascade of responses involving both degenerative and regenerative mechanisms. At the cellular level, the changes are initiated prominently in the neuronal cytoskeleton. Cofilin, a cytoskeletal actin severing protein, is known to be involved in the early stages of apoptotic cell death. Evidence supports its intervention in the progression of disease states like Alzheimer's and ischemic kidney disease. In the present study, we have hypothesized the possible involvement of cofilin in ischemia. Using PC12 cells and mouse primary cultures of cortical neurons, we investigated the potential role of cofilin in ischemia in two different in vitro ischemic models: chemical induced oxidative stress and oxygen-glucose deprivation/reperfusion (OGD/R). The expression profile studies demonstrated a decrease in phosphocofilin levels in all models of ischemia, implying stress-induced cofilin activation. Furthermore, calcineurin and slingshot 1L (SSH) phosphatases were found to be the signaling mediators of the cofilin activation. In primary cultures of cortical neurons, cofilin was found to be significantly activated after 1 h of OGD. To delineate the role of activated cofilin in ischemia, we knocked down cofilin by siRNA technique and tested the impact of cofilin silencing on neuronal viability. Cofilin siRNA-treated neurons showed a significant reduction of cofilin levels in all treatment groups (control, OGD and OGD/R). Additionally, cofilin siRNA reduced cofilin mitochondrial translocation and caspase 3 cleavage, with a concomitant increase in neuronal viability. These results strongly support the active role of cofilin in ischemia-induced neuronal degeneration and apoptosis. We believe that targeting this protein mediator has a potential for therapeutic intervention in ischemic brain injury and stroke. PMID:25526862

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

    PubMed

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

    2016-03-01

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

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. A psycholinguistic model of natural language parsing implemented in simulated neurons.

    PubMed

    Huyck, Christian R

    2009-12-01

    A natural language parser implemented entirely in simulated neurons is described. It produces a semantic representation based on frames. It parses solely using simulated fatiguing Leaky Integrate and Fire neurons, that are a relatively accurate biological model that is simulated efficiently. The model works on discrete cycles that simulate 10 ms of biological time, so the parser has a simple mapping to psychological parsing time. Comparisons to human parsing studies show that the parser closely approximates this data. The parser makes use of Cell Assemblies and the semantics of lexical items is represented by overlapping hierarchical Cell Assemblies so that semantically related items share neurons. This semantic encoding is used to resolve prepositional phrase attachment ambiguities encountered during parsing. Consequently, the parser provides a neurally-based cognitive model of parsing.

  4. 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.

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

    PubMed Central

    Memelli, Heraldo; Solomon, Irene C.

    2012-01-01

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

  6. Emergent central pattern generator behavior in gap-junction-coupled Hodgkin-Huxley style neuron model.

    PubMed

    Horn, Kyle G; Memelli, Heraldo; Solomon, Irene C

    2012-01-01

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

  7. 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

  8. 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.

  9. 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

  10. Progranulin gene delivery protects dopaminergic neurons in a mouse model of Parkinson's disease.

    PubMed

    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.

  11. High Prevalence of Multistability of Rest States and Bursting in a Database of a Model Neuron

    PubMed Central

    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 ()) 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 . 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. PMID:23505348

  12. Mapping the function of neuronal ion channels in model and experiment

    PubMed Central

    Podlaski, William F; Seeholzer, Alexander; Groschner, Lukas N; Miesenböck, Gero; Ranjan, Rajnish; Vogels, Tim P

    2017-01-01

    Ion channel models are the building blocks of computational neuron models. Their biological fidelity is therefore crucial for the interpretation of simulations. However, the number of published models, and the lack of standardization, make the comparison of ion channel models with one another and with experimental data difficult. Here, we present a framework for the automated large-scale classification of ion channel models. Using annotated metadata and responses to a set of voltage-clamp protocols, we assigned 2378 models of voltage- and calcium-gated ion channels coded in NEURON to 211 clusters. The IonChannelGenealogy (ICGenealogy) web interface provides an interactive resource for the categorization of new and existing models and experimental recordings. It enables quantitative comparisons of simulated and/or measured ion channel kinetics, and facilitates field-wide standardization of experimentally-constrained modeling. DOI: http://dx.doi.org/10.7554/eLife.22152.001 PMID:28267430

  13. Mapping the function of neuronal ion channels in model and experiment.

    PubMed

    Podlaski, William F; Seeholzer, Alexander; Groschner, Lukas N; Miesenböck, Gero; Ranjan, Rajnish; Vogels, Tim P

    2017-03-06

    Ion channel models are the building blocks of computational neuron models. Their biological fidelity is therefore crucial for the interpretation of simulations. However, the number of published models, and the lack of standardization, make the comparison of ion channel models with one another and with experimental data difficult. Here, we present a framework for the automated large-scale classification of ion channel models. Using annotated metadata and responses to a set of voltage-clamp protocols, we assigned 2378 models of voltage- and calcium-gated ion channels coded in NEURON to 211 clusters. The IonChannelGenealogy (ICGenealogy) web interface provides an interactive resource for the categorization of new and existing models and experimental recordings. It enables quantitative comparisons of simulated and/or measured ion channel kinetics, and facilitates field-wide standardization of experimentally-constrained modeling.

  14. 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.

  15. Stability and Hopf Bifurcation Analysis in Hindmarsh-Rose Neuron Model with Multiple Time Delays

    NASA Astrophysics Data System (ADS)

    Hu, Dongpo; Cao, Hongjun

    In this paper, the dynamical behaviors of a single Hindmarsh-Rose neuron model with multiple time delays are investigated. By linearizing the system at equilibria and analyzing the associated characteristic equation, the conditions for local stability and the existence of local Hopf bifurcation are obtained. To discuss the properties of Hopf bifurcation, we derive explicit formulas to determine the direction of Hopf bifurcation and the stability of bifurcated periodic solutions occurring through Hopf bifurcation. The qualitative analyses have demonstrated that the values of multiple time delays can affect the stability of equilibrium and play an important role in determining the properties of Hopf bifurcation. Some numerical simulations are given for confirming the qualitative results. Numerical simulations on the effect of delays show that the delays have different scales when the two delay values are not equal. The physiological basis is most likely that Hindmarsh-Rose neuron model has two different time scales. Finally, the bifurcation diagrams of inter-spike intervals of the single Hindmarsh-Rose neuron model are presented. These bifurcation diagrams show the existence of complex bifurcation structures and further indicate that the multiple time delays are very important parameters in determining the dynamical behaviors of the single neuron. Therefore, these results in this paper could be helpful for further understanding the role of multiple time delays in the information transmission and processing of a single neuron.

  16. 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.

  17. 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

  18. Rescue of neuronal migration deficits in a mouse model of fetal Minamata disease by increasing neuronal Ca2+ spike frequency.

    PubMed

    Fahrion, Jennifer K; Komuro, Yutaro; Li, Ying; Ohno, Nobuhiko; Littner, Yoav; Raoult, Emilie; Galas, Ludovic; Vaudry, David; Komuro, Hitoshi

    2012-03-27

    In the brains of patients with fetal Minamata disease (FMD), which is caused by exposure to methylmercury (MeHg) during development, many neurons are hypoplastic, ectopic, and disoriented, indicating disrupted migration, maturation, and growth. MeHg affects a myriad of signaling molecules, but little is known about which signals are primary targets for MeHg-induced deficits in neuronal development. In this study, using a mouse model of FMD, we examined how MeHg affects the migration of cerebellar granule cells during early postnatal development. The cerebellum is one of the most susceptible brain regions to MeHg exposure, and profound loss of cerebellar granule cells is detected in the brains of patients with FMD. We show that MeHg inhibits granule cell migration by reducing the frequency of somal Ca(2+) spikes through alterations in Ca(2+), cAMP, and insulin-like growth factor 1 (IGF1) signaling. First, MeHg slows the speed of granule cell migration in a dose-dependent manner, independent of the mode of migration. Second, MeHg reduces the frequency of spontaneous Ca(2+) spikes in granule cell somata in a dose-dependent manner. Third, a unique in vivo live-imaging system for cell migration reveals that reducing the inhibitory effects of MeHg on somal Ca(2+) spike frequency by stimulating internal Ca(2+) release and Ca(2+) influxes, inhibiting cAMP activity, or activating IGF1 receptors ameliorates the inhibitory effects of MeHg on granule cell migration. These results suggest that alteration of Ca(2+) spike frequency and Ca(2+), cAMP, and IGF1 signaling could be potential therapeutic targets for infants with MeHg intoxication.

  19. 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.

  20. 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.

  1. Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

    PubMed Central

    Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

    2011-01-01

    An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons. PMID:22219717

  2. 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

  3. Neurons Self-Organize Around Salivary Epithelial Cells in Novel Co-Culture Model

    PubMed Central

    Sommakia, Salah; Baker, Olga J.

    2016-01-01

    Salivary gland bioengineering requires understanding the interaction between salivary epithelium and surrounding tissues. An important component of salivary glands is the presence of neurons. No previous studies have investigated how neurons and salivary epithelial cells interact in an in vitro co-culture model. In this study, we describe the self-organization of neurons around salivary epithelial cells in co-culture, in a similar fashion to what occurs in native tissue. We cultured primary mouse cortical neurons (m-CN) with a salivary epithelial cell line (Par-C10) on growth factor-reduced Matrigel (GFR-MG) for 4 days. After this time, co-cultures were compared with native salivary glands using confocal microscopy. Our findings indicate that m-CN were able to self-organize basolaterally to salivary epithelial cell clusters in a similar manner to what occurs in native tissue. These results indicate that this model can be developed as a potential platform for studying neuron-salivary epithelial cell interactions for bioengineering purposes. PMID:27833941

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. Postnatal Gene Therapy Improves Spatial Learning Despite the Presence of Neuronal Ectopia in a Model of Neuronal Migration Disorder

    PubMed Central

    Hu, Huaiyu; Liu, Yu; Bampoe, Kevin; He, Yonglin; Yu, Miao

    2016-01-01

    Patients with type II lissencephaly, a neuronal migration disorder with ectopic neurons, suffer from severe mental retardation, including learning deficits. There is no effective therapy to prevent or correct the formation of neuronal ectopia, which is presumed to cause cognitive deficits. We hypothesized that learning deficits were not solely caused by neuronal ectopia and that postnatal gene therapy could improve learning without correcting the neuronal ectopia formed during fetal development. To test this hypothesis, we evaluated spatial learning of cerebral cortex-specific protein O-mannosyltransferase 2 (POMT2, an enzyme required for O-mannosyl glycosylation) knockout mice and compared to the knockout mice that were injected with an adeno-associated viral vector (AAV) encoding POMT2 into the postnatal brains with Barnes maze. The data showed that the knockout mice exhibited reduced glycosylation in the cerebral cortex, reduced dendritic spine density on CA1 neurons, and increased latency to the target hole in the Barnes maze, indicating learning deficits. Postnatal gene therapy restored functional glycosylation, rescued dendritic spine defects, and improved performance on the Barnes maze by the knockout mice even though neuronal ectopia was not corrected. These results indicate that postnatal gene therapy improves spatial learning despite the presence of neuronal ectopia. PMID:27916859

  9. Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons

    PubMed Central

    Willmore, Ben D. B.; Cui, Zhanfeng; Schnupp, Jan W. H.; King, Andrew J.

    2016-01-01

    Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1–7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context. PMID:27835647

  10. Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.

    PubMed

    Harper, Nicol S; Schoppe, Oliver; Willmore, Ben D B; Cui, Zhanfeng; Schnupp, Jan W H; King, Andrew J

    2016-11-01

    Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1-7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.

  11. 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

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

    NASA Astrophysics Data System (ADS)

    Goychuk, Igor; Goychuk, Andriy

    2015-04-01

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

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

    PubMed Central

    Williamson, Adam

    2013-01-01

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

  14. Modeling the formation process of grouping stimuli sets through cortical columns and microcircuits to feature neurons.

    PubMed

    Klefenz, Frank; Williamson, Adam

    2013-01-01

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

  15. 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...

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

    PubMed Central

    2014-01-01

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

  17. Testing Brain Overgrowth and Synaptic Models of Autism Using NPC’s and Neurons from Patient-Derived IPS Cells

    DTIC Science & Technology

    2014-10-01

    Models of Autism Using NPC’s and Neurons from Patient- Derived IPS Cells PRINCIPAL INVESTIGATOR: Fred H. Gage, Ph.D...SUBTITLE Testing Brain Overgrowth and Synaptic Models of Autism Using NPC’s and Neurons from Patient- Derived IPS Cells 5a. CONTRACT...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Autism and autism spectrum disorders (ASD) are complex neurodevelopmental

  18. On the applicability of STDP-based learning mechanisms to spiking neuron network models

    NASA Astrophysics Data System (ADS)

    Sboev, A.; Vlasov, D.; Serenko, A.; Rybka, R.; Moloshnikov, I.

    2016-11-01

    The ways to creating practically effective method for spiking neuron networks learning, that would be appropriate for implementing in neuromorphic hardware and at the same time based on the biologically plausible plasticity rules, namely, on STDP, are discussed. The influence of the amount of correlation between input and output spike trains on the learnability by different STDP rules is evaluated. A usability of alternative combined learning schemes, involving artificial and spiking neuron models is demonstrated on the iris benchmark task and on the practical task of gender recognition.

  19. A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons

    PubMed Central

    beim Graben, Peter; Rodrigues, Serafim

    2013-01-01

    We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the “open-field” configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement. PMID:23316157

  20. A biophysical observation model for field potentials of networks of leaky integrate-and-fire neurons.

    PubMed

    Beim Graben, Peter; Rodrigues, Serafim

    2012-01-01

    We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced three-compartment model of a single pyramidal neuron, we derive an observation model for dendritic dipole currents in extracellular space and thereby for the dendritic field potential (DFP) that contributes to the local field potential (LFP) of a neural population. This work aligns and satisfies the widespread dipole assumption that is motivated by the "open-field" configuration of the DFP around cortical pyramidal cells. Our reduced three-compartment scheme allows to derive networks of leaky integrate-and-fire (LIF) models, which facilitates comparison with existing neural network and observation models. In particular, by means of numerical simulations we compare our approach with an ad hoc model by Mazzoni et al. (2008), and conclude that our biophysically motivated approach yields substantial improvement.

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

    PubMed Central

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

    1995-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  3. Nanosecond laser pulse stimulation of spiral ganglion neurons and model cells

    PubMed Central

    Rettenmaier, Alexander; Lenarz, Thomas; Reuter, Günter

    2014-01-01

    Optical stimulation of the inner ear has recently attracted attention, suggesting a higher frequency resolution compared to electrical cochlear implants due to its high spatial stimulation selectivity. Although the feasibility of the effect is shown in multiple in vivo experiments, the stimulation mechanism remains open to discussion. Here we investigate in single-cell measurements the reaction of spiral ganglion neurons and model cells to irradiation with a nanosecond-pulsed laser beam over a broad wavelength range from 420 nm up to 1950 nm using the patch clamp technique. Cell reactions were wavelength- and pulse-energy-dependent but too small to elicit action potentials in the investigated spiral ganglion neurons. As the applied radiant exposure was much higher than the reported threshold for in vivo experiments in the same laser regime, we conclude that in a stimulation paradigm with nanosecond-pulses, direct neuronal stimulation is not the main cause of optical cochlea stimulation. PMID:24761285

  4. Evolution of periodic states and chaos in two types of neuronal models

    NASA Astrophysics Data System (ADS)

    Chay, Teresa R.; Fan, Yinshui

    1993-11-01

    Studies on how chaos theory may be applied to neural disorders is a very challenging theoretical problem. But, to determine the applications of chaos theory cellular functions, it is best to study the genesis of chaos and its characteristics using a minimal model of cellular excitability. In this paper we present two neuronal models which gives rise to interesting types of bursting and chaos. The first model is based on the model of Chay, in which the bursting of neuronal cells is caused by voltage- and time-dependent inactivation of calcium channels. The second model is based on Chay's work in which the bursting is caused by the conformational transformation of the calcium channels that is induced by binding of Ca2+ ion to the receptor site. With these two models, we elucidate how the periodic states and chaos can be evolved when the properties of two types of inward current change. Our bifurcation diagram reveals new types of bifurcations and chaos which were not seen in the other non-linear dynamic models. The predicted chaos from the models closely resembles that observed experimentally in neuronal cells. An implication of our finding is that chaos theory may be used to understand and improve the treatment of certain irregular activities in the brain.

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

    PubMed

    Jadi, Monika P; Behabadi, Bardia F; Poleg-Polsky, Alon; Schiller, Jackie; Mel, Bartlett W

    2014-05-01

    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.

  7. Information Processing and Collective Behavior in a Model Neuronal System

    DTIC Science & Technology

    2014-03-28

    at times weekly) telecoms with them and Eli Shlizerman at the University of Washington. In summary, we were happy to work with many groups within...states cause high intracellular calcium concentrations, which could trigger transcription of clock genes . The model also predicts that circadian...phenotypes of mutations or knockdown of clock genes as well as the time courses and relative expression of clock transcripts and proteins. Using this model

  8. Using a hybrid neuron in physiologically inspired models of the basal ganglia

    PubMed Central

    Thibeault, Corey M.; Srinivasa, Narayan

    2013-01-01

    Our current understanding of the basal ganglia (BG) has facilitated the creation of computational models that have contributed novel theories, explored new functional anatomy and demonstrated results complementing physiological experiments. However, the utility of these models extends beyond these applications. Particularly in neuromorphic engineering, where the basal ganglia's role in computation is important for applications such as power efficient autonomous agents and model-based control strategies. The neurons used in existing computational models of the BG, however, are not amenable for many low-power hardware implementations. Motivated by a need for more hardware accessible networks, we replicate four published models of the BG, spanning single neuron and small networks, replacing the more computationally expensive neuron models with an Izhikevich hybrid neuron. This begins with a network modeling action-selection, where the basal activity levels and the ability to appropriately select the most salient input is reproduced. A Parkinson's disease model is then explored under normal conditions, Parkinsonian conditions and during subthalamic nucleus deep brain stimulation (DBS). The resulting network is capable of replicating the loss of thalamic relay capabilities in the Parkinsonian state and its return under DBS. This is also demonstrated using a network capable of action-selection. Finally, a study of correlation transfer under different patterns of Parkinsonian activity is presented. These networks successfully captured the significant results of the originals studies. This not only creates a foundation for neuromorphic hardware implementations but may also support the development of large-scale biophysical models. The former potentially providing a way of improving the efficacy of DBS and the latter allowing for the efficient simulation of larger more comprehensive networks. PMID:23847524

  9. 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.

  10. 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.

  11. Numerical treatment of a mathematical model arising from a model of neuronal variability

    NASA Astrophysics Data System (ADS)

    Kadalbajoo, M. K.; Sharma, K. K.

    2005-07-01

    In this paper, we describe a numerical approach based on finite difference method to solve a mathematical model arising from a model of neuronal variability. The mathematical modelling of the determination of the expected time for generation of action potentials in nerve cells by random synaptic inputs in dendrites includes a general boundary-value problem for singularly perturbed differential-difference equation with small shifts. In the numerical treatment for such type of boundary-value problems, first we use Taylor approximation to tackle the terms containing small shifts which converts it to a boundary-value problem for singularly perturbed differential equation. A rigorous analysis is carried out to obtain priori estimates on the solution of the problem and its derivatives up to third order. Then a parameter uniform difference scheme is constructed to solve the boundary-value problem so obtained. A parameter uniform error estimate for the numerical scheme so constructed is established. Though the convergence of the difference scheme is almost linear but its beauty is that it converges independently of the singular perturbation parameter, i.e., the numerical scheme converges for each value of the singular perturbation parameter (however small it may be but remains positive). Several test examples are solved to demonstrate the efficiency of the numerical scheme presented in the paper and to show the effect of the small shift on the solution behavior.

  12. Recapitulation of spinal motor neuron-specific disease phenotypes in a human cell model of spinal muscular atrophy.

    PubMed

    Wang, Zhi-Bo; Zhang, Xiaoqing; Li, Xue-Jun

    2013-03-01

    Establishing human cell models of spinal muscular atrophy (SMA) to mimic motor neuron-specific phenotypes holds the key to understanding the pathogenesis of this devastating disease. Here, we developed a closely representative cell model of SMA by knocking down the disease-determining gene, survival motor neuron (SMN), in human embryonic stem cells (hESCs). Our study with this cell model demonstrated that knocking down of SMN does not interfere with neural induction or the initial specification of spinal motor neurons. Notably, the axonal outgrowth of spinal motor neurons was significantly impaired and these disease-mimicking neurons subsequently degenerated. Furthermore, these disease phenotypes were caused by SMN-full length (SMN-FL) but not SMN-Δ7 (lacking exon 7) knockdown, and were specific to spinal motor neurons. Restoring the expression of SMN-FL completely ameliorated all of the disease phenotypes, including specific axonal defects and motor neuron loss. Finally, knockdown of SMN-FL led to excessive mitochondrial oxidative stress in human motor neuron progenitors. The involvement of oxidative stress in the degeneration of spinal motor neurons in the SMA cell model was further confirmed by the administration of N-acetylcysteine, a potent antioxidant, which prevented disease-related apoptosis and subsequent motor neuron death. Thus, we report here the successful establishment of an hESC-based SMA model, which exhibits disease gene isoform specificity, cell type specificity, and phenotype reversibility. Our model provides a unique paradigm for studying how motor neurons specifically degenerate and highlights the potential importance of antioxidants for the treatment of SMA.

  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. 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

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

    PubMed

    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.

  16. Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells.

    PubMed

    Masoli, Stefano; Rizza, Martina F; Sgritta, Martina; Van Geit, Werner; Schürmann, Felix; D'Angelo, Egidio

    2017-01-01

    In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (Gi-max) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of Gi-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of Gi-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental Gi-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.

  17. Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells

    PubMed Central

    Masoli, Stefano; Rizza, Martina F.; Sgritta, Martina; Van Geit, Werner; Schürmann, Felix; D'Angelo, Egidio

    2017-01-01

    In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (Gi-max) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of Gi-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of Gi-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental Gi-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models. PMID:28360841

  18. 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

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

    PubMed

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

    2014-01-01

    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.

  20. Neurokinin B and reproductive functions: "KNDy neuron" model in mammals and the emerging story in fish.

    PubMed

    Hu, Guangfu; Lin, Chengyuan; He, Mulan; Wong, Anderson O L

    2014-11-01

    In mammals, neurokinin B (NKB), the gene product of the tachykinin family member TAC3, is known to be a key regulator for episodic release of luteinizing hormone (LH). Its regulatory actions are mediated by a subpopulation of kisspeptin neurons within the arcuate nucleus with co-expression of NKB and dynorphin A (commonly called the "KNDy neurons"). By forming an "autosynaptic feedback loop" within the hypothalamus, the KNDy neurons can modulate gonadotropin-releasing hormone (GnRH) pulsatility and subsequent LH release in the pituitary. NKB regulation of LH secretion has been recently demonstrated in zebrafish, suggesting that the reproductive functions of NKB may be conserved from fish to mammals. Interestingly, the TAC3 genes in fish not only encode the mature peptide of NKB but also a novel tachykinin-like peptide, namely NKB-related peptide (or neurokinin F). Recent studies in zebrafish also reveal that the neuroanatomy of TAC3/kisspeptin system within the fish brain is quite different from that of mammals. In this article, the current ideas of "KNDy neuron" model for GnRH regulation and steroid feedback, other reproductive functions of NKB including its local actions in the gonad and placenta, the revised model of tachykinin evolution from invertebrates to vertebrates, as well as the emerging story of the two TAC3 gene products in fish, NKB and NKB-related peptide, will be reviewed with stress on the areas with interesting questions for future investigations.

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

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

  3. 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

    2016-08-09

    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.

  4. 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

  5. An optimization-based study of equivalent circuit models for representing recordings at the neuron-electrode interface.

    PubMed

    Thakore, V; Molnar, P; Hickman, J J

    2012-08-01

    Extracellular neuroelectronic interfacing is an emerging field with important applications in the fields of neural prosthetics, biological computation, and biosensors. Traditionally, neuron-electrode interfaces have been modeled as linear point or area contact equivalent circuits but it is now being increasingly realized that such models cannot explain the shapes and magnitudes of the observed extracellular signals. Here, results were compared and contrasted from an unprecedented optimization-based study of the point contact models for an extracellular "on-cell" neuron-patch electrode and a planar neuron-microelectrode interface. Concurrent electrophysiological recordings from a single neuron simultaneously interfaced to three distinct electrodes (intracellular, "on-cell" patch, and planar microelectrode) allowed novel insights into the mechanism of signal transduction at the neuron-electrode interface. After a systematic isolation of the nonlinear neuronal contribution to the extracellular signal, a consistent underestimation of the simulated suprathreshold extracellular signals compared to the experimentally recorded signals was observed. This conclusively demonstrated that the dynamics of the interfacial medium contribute nonlinearly to the process of signal transduction at the neuron-electrode interface. Further, an examination of the optimized model parameters for the experimental extracellular recordings from sub- and suprathreshold stimulations of the neuron-electrode junctions revealed that ionic transport at the "on-cell" neuron-patch electrode is dominated by diffusion whereas at the neuron-microelectrode interface the electric double layer (EDL) effects dominate. Based on this study, the limitations of the equivalent circuit models in their failure to account for the nonlinear EDL and ionic electrodiffusion effects occurring during signal transduction at the neuron-electrode interfaces are discussed.

  6. Neuroprotective Role of Gap Junctions in a Neuron Astrocyte Network Model.

    PubMed

    Huguet, Gemma; Joglekar, Anoushka; Messi, Leopold Matamba; Buckalew, Richard; Wong, Sarah; Terman, David

    2016-07-26

    A detailed biophysical model for a neuron/astrocyte network is developed to explore mechanisms responsible for the initiation and propagation of cortical spreading depolarizations and the role of astrocytes in maintaining ion homeostasis, thereby preventing these pathological waves. Simulations of the model illustrate how properties of spreading depolarizations, such as wave speed and duration of depolarization, depend on several factors, including the neuron and astrocyte Na(+)-K(+) ATPase pump strengths. In particular, we consider the neuroprotective role of astrocyte gap junction coupling. The model demonstrates that a syncytium of electrically coupled astrocytes can maintain a physiological membrane potential in the presence of an elevated extracellular K(+) concentration and efficiently distribute the excess K(+) across the syncytium. This provides an effective neuroprotective mechanism for delaying or preventing the initiation of spreading depolarizations.

  7. Analysis of stochastic phenomena in 2D Hindmarsh-Rose neuron model

    NASA Astrophysics Data System (ADS)

    Bashkirtseva, I.; Ryashko, L.; Slepukhina, E.

    2016-10-01

    In mathematical research of neuronal activity, conceptual models play an important role. We consider 2D Hindmarsh-Rose model, which exhibits the fundamental property of neuron, the excitability. We study how random disturbances affect this property. The effects of noise are analysed in the parametric zone where the deterministic model is characterized by the coexistence of two stable equilibria. We show that under random disturbances, noise-induced transitions between the attractors occur, forming a new complex dynamic regime of stochastic bursting. It is confirmed by changes of distribution of random trajectories and interspike intervals. For the analysis of this noise-induced phenomenon, we apply the stochastic sensitivity technique and confidence domains method. We suggest a method for estimation of threshold noise intensity corresponding to the onset of noise-induced bursting. We show that the obtained values are in a good agreement with direct numerical simulations.

  8. 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.

  9. A central neuropathic pain model by DSP-4 induced lesion of noradrenergic neurons: preliminary report.

    PubMed

    Kudo, Takashi; Kushikata, Tetsuya; Kudo, Mihoko; Kudo, Tsuyoshi; Hirota, Kazuyoshi

    2010-09-06

    Neuropathic pain models are classified as central and peripheral pain models. Although various peripheral neuropathic pain models are established, central pain models are based only on spinal cord injury. DSP-4 is a competitive inhibitor of norepinephrine uptake that selectively degenerates the locus coeruleus (LC)-noradrenergic neurons projection to the cerebral cortex and hippocampus. In the present study, we have tested whether lesion of LC-noradrenergic neurons by ip DSP-4 (0, 10, 30, 50 mg/kg, n=7 each) could provide a new central neuropathic pain model in rats using a hot-plate and tail-flick tests. DSP-4 significantly reduced the hot-plate latency and norepinephrine contents especially in the coerulean regions. However, DSP-4 did not change tail-flick latency. There are significant correlations of the latency in the hot-plate test with norepinephrine contents in the cerebral cortex (r=0.432, p=0.022), the hippocampus (r=0.465, p=0.013) and the pons (r=0.400, p=0.035) but not with those in the hypothalamus and the spinal cord. As response to hot-plate and tail-flick implies supra-spinal process and spinal reflex, respectively, central neuropathic pain may be facilitated by DSP-4 depleting LC-noradrenergic neurons although the present data are preliminary.

  10. Mathematical model of bursting in dissociated purkinje neurons.

    PubMed

    Forrest, Michael D

    2013-01-01

    In vitro, Purkinje cell behaviour is sometimes studied in a dissociated soma preparation in which the dendritic projection has been cleaved. A fraction of these dissociated somas spontaneously burst. The mechanism of this bursting is incompletely understood. We have constructed a biophysical Purkinje soma model, guided and constrained by experimental reports in the literature, that can replicate the somatically driven bursting pattern and which hypothesises Persistent Na(+) current (INaP) to be its burst initiator and SK K(+) current (ISK) to be its burst terminator.

  11. The Gamma renewal process as an output of the diffusion leaky integrate-and-fire neuronal model.

    PubMed

    Lansky, Petr; Sacerdote, Laura; Zucca, Cristina

    2016-06-01

    Statistical properties of spike trains as well as other neurophysiological data suggest a number of mathematical models of neurons. These models range from entirely descriptive ones to those deduced from the properties of the real neurons. One of them, the diffusion leaky integrate-and-fire neuronal model, which is based on the Ornstein-Uhlenbeck (OU) stochastic process that is restricted by an absorbing barrier, can describe a wide range of neuronal activity in terms of its parameters. These parameters are readily associated with known physiological mechanisms. The other model is descriptive, Gamma renewal process, and its parameters only reflect the observed experimental data or assumed theoretical properties. Both of these commonly used models are related here. We show under which conditions the Gamma model is an output from the diffusion OU model. In some cases, we can see that the Gamma distribution is unrealistic to be achieved for the employed parameters of the OU process.

  12. 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

  13. A computational model of the respiratory network challenged and optimized by data from optogenetic manipulation of glycinergic neurons.

    PubMed

    Oku, Yoshitaka; Hülsmann, Swen

    2017-04-07

    The topology of the respiratory network in the brainstem has been addressed using different computational models, which help to understand the functional properties of the system. We tested a neural mass model by comparing the result of activation and inhibition of inhibitory neurons in silico with recently published results of optogenetic manipulation of glycinergic neurons [Sherman, et al. (2015) Nat Neurosci 18:408]. The comparison revealed that a five-cell type model consisting of three classes of inhibitory neurons [I-DEC, E-AUG, E-DEC (PI)] and two excitatory populations (pre-I/I) and (I-AUG) neurons can be applied to explain experimental observations made by stimulating or inhibiting inhibitory neurons by light sensitive ion channels.

  14. GSK-3 Mouse Models to Study Neuronal Apoptosis and Neurodegeneration

    PubMed Central

    Gómez-Sintes, Raquel; Hernández, Félix; Lucas, José J.; Avila, Jesús

    2011-01-01

    Increased GSK-3 activity is believed to contribute to the etiology of chronic disorders like Alzheimer’s disease (AD), schizophrenia, diabetes, and some types of cancer, thus supporting therapeutic potential of GSK-3 inhibitors. Numerous mouse models with modified GSK-3 have been generated in order to study the physiology of GSK-3, its implication in diverse pathologies and the potential effect of GSK-3 inhibitors. In this review we have focused on the relevance of these mouse models for the study of the role of GSK-3 in apoptosis. GSK-3 is involved in two apoptotic pathways, intrinsic and extrinsic pathways, and plays opposite roles depending on the apoptotic signaling process that is activated. It promotes cell death when acting through intrinsic pathway and plays an anti-apoptotic role if the extrinsic pathway is occurring. It is important to dissect this duality since, among the diseases in which GSK-3 is involved, excessive cell death is crucial in some illnesses like neurodegenerative diseases, while a deficient apoptosis is occurring in others such as cancer or autoimmune diseases. The clinical application of a classical GSK-3 inhibitor, lithium, is limited by its toxic consequences, including motor side effects. Recently, the mechanism leading to activation of apoptosis following chronic lithium administration has been described. Understanding this mechanism could help to minimize side effects and to improve application of GSK-3 inhibitors to the treatment of AD and to extend the application to other diseases. PMID:22110426

  15. Reduction of stochastic conductance-based neuron models with time-scales separation.

    PubMed

    Wainrib, Gilles; Thieullen, Michèle; Pakdaman, Khashayar

    2012-04-01

    We introduce a method for systematically reducing the dimension of biophysically realistic neuron models with stochastic ion channels exploiting time-scales separation. Based on a combination of singular perturbation methods for kinetic Markov schemes with some recent mathematical developments of the averaging method, the techniques are general and applicable to a large class of models. As an example, we derive and analyze reductions of different stochastic versions of the Hodgkin Huxley (HH) model, leading to distinct reduced models. The bifurcation analysis of one of the reduced models with the number of channels as a parameter provides new insights into some features of noisy discharge patterns, such as the bimodality of interspike intervals distribution. Our analysis of the stochastic HH model shows that, besides being a method to reduce the number of variables of neuronal models, our reduction scheme is a powerful method for gaining understanding on the impact of fluctuations due to finite size effects on the dynamics of slow fast systems. Our analysis of the reduced model reveals that decreasing the number of sodium channels in the HH model leads to a transition in the dynamics reminiscent of the Hopf bifurcation and that this transition accounts for changes in characteristics of the spike train generated by the model. Finally, we also examine the impact of these results on neuronal coding, notably, reliability of discharge times and spike latency, showing that reducing the number of channels can enhance discharge time reliability in response to weak inputs and that this phenomenon can be accounted for through the analysis of the reduced model.

  16. 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

  17. 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

  18. 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

  19. Bone Marrow Mononuclear Cells Protect Neurons and Modulate Microglia in Cell Culture Models of Ischemic Stroke

    PubMed Central

    Sharma, Sushil; Yang, Bing; Strong, Roger; Xi, Xiao Pei; Brenneman, Miranda; Grotta, James C.; Aronowski, Jaroslaw; Savitz, Sean I.

    2010-01-01

    Background Although several studies have provided evidence for the therapeutic potential of bone marrow-derived mononuclear cells (MNCs) in animal models of stroke, the mechanisms underlying their benefits remain largely unknown. We have determined the neuroprotective potential of MNCs in primary neuronal cultures exposed to various injuries in vitro. Methods Cortical neurons in culture were exposed to oxygen-glucose deprivation, hypoxia, or hydrogen peroxide and cell death was assayed by MTT, caspase-3 activation or TUNEL labelling at 24 hrs. Cultures were randomized to co-treatment with MNC-derived supernatants or media before injury exposure. In separate experiments, macrophage or microglial cultures were exposed to lipopolypolysacharide (LPS) in the presence and absence of MNC-derived supernatants. Neuronal cultures were then exposed to conditioned media derived from activated macrophages or microglia. Cytokines from the supernantants of MNC cultures exposed to normoxia or hypoxia were also estimated by enzyme-linked immunosorbant assay (ELISA). Results MNC-derived supernatants attenuated neuronal death induced by OGD, hypoxia, hydrogen peroxide, and conditioned macrophage/microglial media and contain a number of trophic factors including IL-10, IGF-1, VEGF, and SDF-1. Conclusion MNCs provide broad neuroprotection against a variety of injuries relevant to stroke. PMID:20629187

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

    PubMed

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

    2016-02-01

    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.

  1. 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

  2. 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

  3. Models of Neuronal Stimulus-Response Functions: Elaboration, Estimation, and Evaluation

    PubMed Central

    Meyer, Arne F.; Williamson, Ross S.; Linden, Jennifer F.; Sahani, Maneesh

    2017-01-01

    Rich, dynamic, and dense sensory stimuli are encoded within the nervous system by the time-varying activity of many individual neurons. A fundamental approach to understanding the nature of the encoded representation is to characterize the function that relates the moment-by-moment firing of a neuron to the recent history of a complex sensory input. This review provides a unifying and critical survey of the techniques that have been brought to bear on this effort thus far—ranging from the classical linear receptive field model to modern approaches incorporating normalization and other nonlinearities. We address separately the structure of the models; the criteria and algorithms used to identify the model parameters; and the role of regularizing terms or “priors.” In each case we consider benefits or drawbacks of various proposals, providing examples for when these methods work and when they may fail. Emphasis is placed on key concepts rather than mathematical details, so as to make the discussion accessible to readers from outside the field. Finally, we review ways in which the agreement between an assumed model and the neuron's response may be quantified. Re-implemented and unified code for many of the methods are made freely available. PMID:28127278

  4. 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

  5. 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.

  6. Models of Neuronal Stimulus-Response Functions: Elaboration, Estimation, and Evaluation.

    PubMed

    Meyer, Arne F; Williamson, Ross S; Linden, Jennifer F; Sahani, Maneesh

    2016-01-01

    Rich, dynamic, and dense sensory stimuli are encoded within the nervous system by the time-varying activity of many individual neurons. A fundamental approach to understanding the nature of the encoded representation is to characterize the function that relates the moment-by-moment firing of a neuron to the recent history of a complex sensory input. This review provides a unifying and critical survey of the techniques that have been brought to bear on this effort thus far-ranging from the classical linear receptive field model to modern approaches incorporating normalization and other nonlinearities. We address separately the structure of the models; the criteria and algorithms used to identify the model parameters; and the role of regularizing terms or "priors." In each case we consider benefits or drawbacks of various proposals, providing examples for when these methods work and when they may fail. Emphasis is placed on key concepts rather than mathematical details, so as to make the discussion accessible to readers from outside the field. Finally, we review ways in which the agreement between an assumed model and the neuron's response may be quantified. Re-implemented and unified code for many of the methods are made freely available.

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

    PubMed

    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.

  8. 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.

  9. 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.

  10. Channel noise enhances signal detectability in a model of acoustic neuron through the stochastic resonance paradigm.

    PubMed

    Liberti, M; Paffi, A; Maggio, F; De Angelis, A; Apollonio, F; d'Inzeo, G

    2009-01-01

    A number of experimental investigations have evidenced the extraordinary sensitivity of neuronal cells to weak input stimulations, including electromagnetic (EM) fields. Moreover, it has been shown that biological noise, due to random channels gating, acts as a tuning factor in neuronal processing, according to the stochastic resonant (SR) paradigm. In this work the attention is focused on noise arising from the stochastic gating of ionic channels in a model of Ranvier node of acoustic fibers. The small number of channels gives rise to a high noise level, which is able to cause a spike train generation even in the absence of stimulations. A SR behavior has been observed in the model for the detection of sinusoidal signals at frequencies typical of the speech.

  11. A modeling comparison of projection neuron- and neuromodulator-elicited oscillations in a central pattern generating network.

    PubMed

    Kintos, Nickolas; Nusbaum, Michael P; Nadim, Farzan

    2008-06-01

    Many central pattern generating networks are influenced by synaptic input from modulatory projection neurons. The network response to a projection neuron is sometimes mimicked by bath applying the neuronally-released modulator, despite the absence of network interactions with the projection neuron. One interesting example occurs in the crab stomatogastric ganglion (STG), where bath applying the neuropeptide pyrokinin (PK) elicits a gastric mill rhythm which is similar to that elicited by the projection neuron modulatory commissural neuron 1 (MCN1), despite the absence of PK in MCN1 and the fact that MCN1 is not active during the PK-elicited rhythm. MCN1 terminals have fast and slow synaptic actions on the gastric mill network and are presynaptically inhibited by this network in the STG. These local connections are inactive in the PK-elicited rhythm, and the mechanism underlying this rhythm is unknown. We use mathematical and biophysically-realistic modeling to propose potential mechanisms by which PK can elicit a gastric mill rhythm that is similar to the MCN1-elicited rhythm. We analyze slow-wave network oscillations using simplified mathematical models and, in parallel, develop biophysically-realistic models that account for fast, action potential-driven oscillations and some spatial structure of the network neurons. Our results illustrate how the actions of bath-applied neuromodulators can mimic those of descending projection neurons through mathematically similar but physiologically distinct mechanisms.

  12. 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

  13. Efficient and versatile CRISPR engineering of human neurons in culture to model neurological disorders.

    PubMed

    Shah, Ruth R; Cholewa-Waclaw, Justyna; Davies, Faith C J; Paton, Katie M; Chaligne, Ronan; Heard, Edith; Abbott, Catherine M; Bird, Adrian P

    2016-11-15

    The recent identification of multiple new genetic causes of neurological disorders highlights the need for model systems that give experimental access to the underlying biology. In particular, the ability to couple disease-causing mutations with human neuronal differentiation systems would be beneficial. Gene targeting is a well-known approach for dissecting gene function, but low rates of homologous recombination in somatic cells (including neuronal cells) have traditionally impeded the development of robust cellular models of neurological disorders. Recently, however, CRISPR/Cas9 gene editing technologies have expanded the number of systems within which gene targeting is possible. Here we adopt as a model system LUHMES cells, a commercially available diploid human female mesencephalic cell line that differentiates into homogeneous mature neurons in 1-2 weeks. We describe optimised methods for transfection and selection of neuronal progenitor cells carrying targeted genomic alterations using CRISPR/Cas9 technology. By targeting the endogenous X-linked MECP2 locus, we introduced four independent missense mutations that cause the autism spectrum disorder Rett syndrome and observed the desired genetic structure in 3-26% of selected clones, including gene targeting of the inactive X chromosome. Similar efficiencies were achieved by introducing neurodevelopmental disorder-causing mutations at the autosomal EEF1A2 locus on chromosome 20. Our results indicate that efficiency of genetic "knock-in" is determined by the location of the mutation within the donor DNA molecule. Furthermore, we successfully introduced an mCherry tag at the MECP2 locus to yield a fusion protein, demonstrating that larger insertions are also straightforward in this system. We suggest that our optimised methods for altering the genome of LUHMES cells make them an attractive model for the study of neurogenetic disorders.

  14. Efficient and versatile CRISPR engineering of human neurons in culture to model neurological disorders

    PubMed Central

    2016-01-01

    The recent identification of multiple new genetic causes of neurological disorders highlights the need for model systems that give experimental access to the underlying biology. In particular, the ability to couple disease-causing mutations with human neuronal differentiation systems would be beneficial. Gene targeting is a well-known approach for dissecting gene function, but low rates of homologous recombination in somatic cells (including neuronal cells) have traditionally impeded the development of robust cellular models of neurological disorders. Recently, however, CRISPR/Cas9 gene editing technologies have expanded the number of systems within which gene targeting is possible. Here we adopt as a model system LUHMES cells, a commercially available diploid human female mesencephalic cell line that differentiates into homogeneous mature neurons in 1-2 weeks. We describe optimised methods for transfection and selection of neuronal progenitor cells carrying targeted genomic alterations using CRISPR/Cas9 technology. By targeting the endogenous X-linked MECP2 locus, we introduced four independent missense mutations that cause the autism spectrum disorder Rett syndrome and observed the desired genetic structure in 3-26% of selected clones, including gene targeting of the inactive X chromosome. Similar efficiencies were achieved by introducing neurodevelopmental disorder-causing mutations at the autosomal EEF1A2 locus on chromosome 20. Our results indicate that efficiency of genetic “knock-in” is determined by the location of the mutation within the donor DNA molecule. Furthermore, we successfully introduced an mCherry tag at the MECP2 locus to yield a fusion protein, demonstrating that larger insertions are also straightforward in this system. We suggest that our optimised methods for altering the genome of LUHMES cells make them an attractive model for the study of neurogenetic disorders. PMID:27976757

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

    PubMed Central

    Zubler, Frederic; Douglas, Rodney

    2009-01-01

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

  16. 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.

  17. Mathematical models for sleep-wake dynamics: comparison of the two-process model and a mutual inhibition neuronal model.

    PubMed

    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.

  18. A review of methods for identifying stochastic resonance in simulations of single neuron models.

    PubMed

    McDonnell, Mark D; Iannella, Nicolangelo; To, Minh-Son; Tuckwell, Henry C; Jost, Jürgen; Gutkin, Boris S; Ward, Lawrence M

    2015-01-01

    Stochastic resonance (SR) is said to be observed when the presence of noise in a nonlinear system enables an output signal from the system to better represent some feature of an input signal than it does in the absence of noise. The effect has been observed in models of individual neurons, and in experiments performed on real neural systems. Despite the ubiquity of biophysical sources of stochastic noise in the nervous system, however, it has not yet been established whether neuronal computation mechanisms involved in performance of specific functions such as perception or learning might exploit such noise as an integral component, such that removal of the noise would diminish performance of these functions. In this paper we revisit the methods used to demonstrate stochastic resonance in models of single neurons. This includes a previously unreported observation in a multicompartmental model of a CA1-pyramidal cell. We also discuss, as a contrast to these classical studies, a form of 'stochastic facilitation', known as inverse stochastic resonance. We draw on the reviewed examples to argue why new approaches to studying 'stochastic facilitation' in neural systems need to be developed.

  19. Astrocytes and human cognition: modeling information integration and modulation of neuronal activity.

    PubMed

    Pereira, Alfredo; Furlan, Fábio Augusto

    2010-11-01

    Recent research focusing on the participation of astrocytes in glutamatergic tripartite synapses has revealed mechanisms that support cognitive functions common to human and other mammalian species, such as learning, perception, conscious integration, memory formation/retrieval and the control of voluntary behavior. Astrocytes can modulate neuronal activity by means of release of glutamate, d-serine, adenosine triphosphate and other signaling molecules, contributing to sustain, reinforce or depress pre- and post-synaptic membranes. We review molecular mechanisms present in tripartite synapses and model the cognitive role of astrocytes. Single protoplasmic astrocytes operate as a "Local Hub", integrating information patterns from neuronal and glial populations. Two mechanisms, here modeled as the "domino" and "carousel" effects, contribute to the formation of intercellular calcium waves. As waves propagate through gap junctions and reach other types of astrocytes (interlaminar, polarized, fibrous and varicose projection), the active astroglial network functions as a "Master Hub" that integrates results of distributed processing from several brain areas and supports conscious states. Response of this network would define the effect exerted on neuronal plasticity (membrane potentiation or depression), behavior and psychosomatic processes. Theoretical results of our modeling can contribute to the development of new experimental research programs to test cognitive functions of astrocytes.

  20. 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.

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

    PubMed

    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.

  2. 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.

  3. Modeling electromagnetic fields detectability in a HH-like neuronal system: stochastic resonance and window behavior.

    PubMed

    Giannì, Matteo; Liberti, Micaela; Apollonio, Francesca; D'Inzeo, Guglielmo

    2006-02-01

    Noise has already been shown to play a constructive role in neuronal processing and reliability, according to stochastic resonance (SR). Here another issue is addressed, concerning noise role in the detectability of an exogenous signal, here representing an electromagnetic (EM) field. A Hodgkin-Huxley like neuronal model describing a myelinated nerve fiber is proposed and validated, excited with a suprathreshold stimulation. EM field is introduced as an additive voltage input and its detectability in neuronal response is evaluated in terms of the output signal-to-noise ratio. Noise intensities maximizing spiking activity coherence with the exogenous EM signal are clearly shown, indicating a stochastic resonant behavior, strictly connected to the model frequency sensitivity. In this study SR exhibits a window of occurrence in the values of field frequency and intensity, which is a kind of effect long reported in bioelectromagnetic experimental studies. The spatial distribution of the modeled structure also allows to investigate possible effects on action potentials saltatory propagation, which results to be reliable and robust over the presence of an exogenous EM field and biological noise. The proposed approach can be seen as assessing biophysical bases of medical applications funded on electric and magnetic stimulation where the role of noise as a cooperative factor has recently gained growing attention.

  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. 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

  6. Regulation of Firing Frequency in a Computational Model of a Midbrain Dopaminergic Neuron

    PubMed Central

    Kuznetsova, Anna Y; Huertas, Marco A.; Kuznetsov, Alexey S; Paladini, Carlos A; Canavier, Carmen C

    2010-01-01

    Dopaminergic (DA) neurons of the mammalian midbrain exhibit unusually low firing frequencies in vitro. Furthermore, injection of depolarizing current induces depolarization block before high frequencies are achieved. The maximum steady and transient rates are about 10 and 20 Hz, respectively, despite the ability of these neurons to generate bursts at higher frequencies in vivo. We use a three-compartment model calibrated to reproduce DA neuron responses to several pharmacological manipulations to uncover mechanisms of frequency limitation. The model exhibits a slow oscillatory potential (SOP) dependent on the interplay between the L-type Ca2+ current and the small conductance K+ (SK) current that is unmasked by fast Na+ current block. Contrary to previous theoretical work, the SOP does not pace the steady spiking frequency in our model. The main currents that determine the spontaneous firing frequency are the subthreshold L-type Ca2+ and the A-type K+ currents. The model identifies the channel densities for the fast Na+ and the delayed rectifier K+ currents as critical parameters limiting the maximal steady frequency evoked by a depolarizing pulse. We hypothesize that the low maximal steady frequencies result from a low safety factor for action potential generation. In the model, the rate of Ca2+ accumulation in the distal dendrites controls the transient initial frequency in response to a depolarizing pulse. Similar results are obtained when the same model parameters are used in a multi-compartmental model with a realistic reconstructed morphology, indicating that the salient contributions of the dendritic architecture have been captured by the simpler model. PMID:20217204

  7. Regulation of firing frequency in a computational model of a midbrain dopaminergic neuron.

    PubMed

    Kuznetsova, Anna Y; Huertas, Marco A; Kuznetsov, Alexey S; Paladini, Carlos A; Canavier, Carmen C

    2010-06-01

    Dopaminergic (DA) neurons of the mammalian midbrain exhibit unusually low firing frequencies in vitro. Furthermore, injection of depolarizing current induces depolarization block before high frequencies are achieved. The maximum steady and transient rates are about 10 and 20 Hz, respectively, despite the ability of these neurons to generate bursts at higher frequencies in vivo. We use a three-compartment model calibrated to reproduce DA neuron responses to several pharmacological manipulations to uncover mechanisms of frequency limitation. The model exhibits a slow oscillatory potential (SOP) dependent on the interplay between the L-type Ca(2+) current and the small conductance K(+) (SK) current that is unmasked by fast Na(+) current block. Contrary to previous theoretical work, the SOP does not pace the steady spiking frequency in our model. The main currents that determine the spontaneous firing frequency are the subthreshold L-type Ca(2+) and the A-type K(+) currents. The model identifies the channel densities for the fast Na(+) and the delayed rectifier K(+) currents as critical parameters limiting the maximal steady frequency evoked by a depolarizing pulse. We hypothesize that the low maximal steady frequencies result from a low safety factor for action potential generation. In the model, the rate of Ca(2+) accumulation in the distal dendrites controls the transient initial frequency in response to a depolarizing pulse. Similar results are obtained when the same model parameters are used in a multi-compartmental model with a realistic reconstructed morphology, indicating that the salient contributions of the dendritic architecture have been captured by the simpler model.

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  10. Influence of norepinephrine on somatosensory neuronal responses in the rat thalamus: a combined modeling and in vivo multi-channel, multi-neuron recording study.

    PubMed

    Moxon, Karen A; Devilbiss, David M; Chapin, John K; Waterhouse, Barry D

    2007-05-25

    Norepinephrine released within primary sensory circuits from locus coeruleus afferent fibers can produce a spectrum of modulatory actions on spontaneous or sensory-evoked activity of individual neurons. Within the ventral posterior medial thalamus, membrane currents modulated by norepinephrine have been identified. However, the relationship between the cellular effects of norepinephrine and the impact of norepinephrine release on populations of neurons encoding sensory signals is still open to question. To address this lacuna in understanding the net impact of the noradrenergic system on sensory signal processing, a computational model of the rat trigeminal somatosensory thalamus was generated. The effects of independent manipulation of different cellular actions of norepinephrine on simulated afferent input to the computational model were then examined. The results of these simulations aided in the design of in vivo neural ensemble recording experiments where sensory-driven responses of thalamic neurons were measured before and during locus coeruleus activation in waking animals. Together the simulated and experimental results reveal several key insights regarding the regulation of neural network operation by norepinephrine including: 1) cell-specific modulatory actions of norepinephrine, 2) mechanisms of norepinephrine action that can improve the tuning of the network and increase the signal-to-noise ratio of cellular responses in order to enhance network representation of salient stimulus features and 3) identification of the dynamic range of thalamic neuron function through which norepinephrine operates.

  11. Comparison of neuronal network models for tinnitus management by sound therapy.

    PubMed

    Nagashino, Hirofumi; Kinouchi, Yohsuke; Danesh, Ali A; Pandya, Abhijit S

    2009-01-01

    Tinnitus is a condition in which sounds heard in the ear or head without any external sound. There are many therapeutic approaches for tinnitus and sound therapy is one of the techniques for its treatment that have been proposed. In order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy from the viewpoint of neural engineering, we have proposed computational models with plasticity and inhibitory feedback using a neural oscillator or model neurons described by simplified Hodgkin-Huxley equations. By hypothesizing that the oscillation and the non-oscillatory state in the models correspond to generation and inhibition of tinnitus, respectively, we found out that the models could explain the fact that the habituated human auditory system temporarily halts perception of tinnitus following sound therapy. However, a simpler model without inhibitory feedback can exhibit the solutions that exist in the former models. In the present paper, outcomes of the neuronal network model, which is incorporated with inhibitory feedback, are compared with the model without inhibitory feedback. It was revealed that the former is superior since it has a larger parameter region in which the effects of sound therapy can be restored due to synaptic plasticity.

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

    PubMed Central

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

    2014-01-01

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

  13. Neuronal spike timing adaptation described with a fractional leaky integrate-and-fire model.

    PubMed

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

    2014-03-01

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

  14. Phase description of the Huber-Braun neuron model for mammalian cold receptors

    NASA Astrophysics Data System (ADS)

    Freund, J. A.; Finke, C.; Braun, H. A.; Feudel, U.

    2013-10-01

    The spiking activity of mammalian cold receptors is described by the Huber-Braun neuron model. Sweeping temperature as a control parameter across a biologically relevant range this model exhibits a complex bifurcation structure seen in the sequence of interspike intervals. The model's distinctive feature is the interaction between a fast spike generating dynamics and a slow subthreshold oscillation. Viewing the spike generation as a cycle, the dynamics may also be modeled phenomenologically by two phases, one for the spike cycle and the second for the slow subthreshold oscillation. In fact, a phase model of temperature-dependent mammalian cold receptors was already proposed by Roper et al. (2000). Here we follow their approach and investigate to what extent this model is able to reproduce the bifurcation patterns of the Huber-Braun model. Special attention is paid to the tonic firing to bursting transition observed in the low temperature range.

  15. Mathematical Model of Neuronal Morphology: Prenatal Development of the Human Dentate Nucleus

    PubMed Central

    Rajković, Katarina; Bačić, Goran; Ristanović, Dušan; Milošević, Nebojša T.

    2014-01-01

    The aim of the study was to quantify the morphological changes of the human dentate nucleus during prenatal development using mathematical models that take into account main morphometric parameters. The camera lucida drawings of Golgi impregnated neurons taken from human fetuses of gestational ages ranging from 14 to 41 weeks were analyzed. Four morphometric parameters, the size of the neuron, the dendritic complexity, maximum dendritic density, and the position of maximum density, were obtained using the modified Scholl method and fractal analysis. Their increase during the entire prenatal development can be adequately fitted with a simple exponential. The three parameters describing the evolution of branching complexity of the dendritic arbor positively correlated with the increase of the size of neurons, but with different rate constants, showing that the complex development of the dendritic arbor is complete during the prenatal period. The findings of the present study are in accordance with previous crude qualitative data on prenatal development of the human dentate nucleus, but provide much greater amount of fine details. The mathematical model developed here provides a sound foundation enabling further studies on natal development or analyzing neurological disorders during prenatal development. PMID:24995329

  16. Neurodynamics of biased competition and cooperation for attention: a model with spiking neurons.

    PubMed

    Deco, Gustavo; Rolls, Edmund T

    2005-07-01

    Recent neurophysiological experiments have led to a promising "biased competition hypothesis" of the neural basis of attention. According to this hypothesis, attention appears as a sometimes nonlinear property that results from a top-down biasing effect that influences the competitive and cooperative interactions that work both within cortical areas and between cortical areas. In this paper we describe a detailed dynamical analysis of the synaptic and neuronal spiking mechanisms underlying biased competition. We perform a detailed analysis of the dynamical capabilities of the system by exploring the stationary attractors in the parameter space by a mean-field reduction consistent with the underlying synaptic and spiking dynamics. The nonstationary dynamical behavior, as measured in neuronal recording experiments, is studied by an integrate-and-fire model with realistic dynamics. This elucidates the role of cooperation and competition in the dynamics of biased competition and shows why feedback connections between cortical areas need optimally to be weaker by a factor of about 2.5 than the feedforward connections in an attentional network. We modeled the interaction between top-down attention and bottom-up stimulus contrast effects found neurophysiologically and showed that top-down attentional effects can be explained by external attention inputs biasing neurons to move to different parts of their nonlinear activation functions. Further, it is shown that, although NMDA nonlinear effects may be useful in attention, they are not necessary, with nonlinear effects (which may appear multiplicative) being produced in the way just described.

  17. 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.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    Fuwape, Ibiyinka; Neiman, Alexander; Shilnikov, Andrey

    2008-03-01

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

  20. A subthreshold aVLSI implementation of the Izhikevich simple neuron model.

    PubMed

    Rangan, Venkat; Ghosh, Abhishek; Aparin, Vladimir; Cauwenberghs, Gert

    2010-01-01

    We present a circuit architecture for compact analog VLSI implementation of the Izhikevich neuron model, which efficiently describes a wide variety of neuron spiking and bursting dynamics using two state variables and four adjustable parameters. Log-domain circuit design utilizing MOS transistors in subthreshold results in high energy efficiency, with less than 1pJ of energy consumed per spike. We also discuss the effects of parameter variations on the dynamics of the equations, and present simulation results that replicate several types of neural dynamics. The low power operation and compact analog VLSI realization make the architecture suitable for human-machine interface applications in neural prostheses and implantable bioelectronics, as well as large-scale neural emulation tools for computational neuroscience.

  1. Expanded ATXN3 frameshifting events are toxic in Drosophila and mammalian neuron models.

    PubMed

    Stochmanski, Shawn J; Therrien, Martine; Laganière, Janet; Rochefort, Daniel; Laurent, Sandra; Karemera, Liliane; Gaudet, Rebecca; Vyboh, Kishanda; Van Meyel, Don J; Di Cristo, Graziella; Dion, Patrick A; Gaspar, Claudia; Rouleau, Guy A

    2012-05-15

    Spinocerebellar ataxia type 3 is caused by the expansion of the coding CAG repeat in the ATXN3 gene. Interestingly, a -1 bp frameshift occurring within an (exp)CAG repeat would henceforth lead to translation from a GCA frame, generating polyalanine stretches instead of polyglutamine. Our results show that transgenic expression of (exp)CAG ATXN3 led to -1 frameshifting events, which have deleterious effects in Drosophila and mammalian neurons. Conversely, transgenic expression of polyglutamine-encoding (exp)CAA ATXN3 was not toxic. Furthermore, (exp)CAG ATXN3 mRNA does not contribute per se to the toxicity observed in our models. Our observations indicate that expanded polyglutamine tracts in Drosophila and mouse neurons are insufficient for the development of a phenotype. Hence, we propose that -1 ribosomal frameshifting contributes to the toxicity associated with (exp)CAG repeats.

  2. A neuronal network model for context-dependence of pitch change perception

    PubMed Central

    Huang, Chengcheng; Englitz, Bernhard; Shamma, Shihab; Rinzel, John

    2015-01-01

    Many natural stimuli have perceptual ambiguities that can be cognitively resolved by the surrounding context. In audition, preceding context can bias the perception of speech and non-speech stimuli. Here, we develop a neuronal network model that can account for how context affects the perception of pitch change between a pair of successive complex tones. We focus especially on an ambiguous comparison—listeners experience opposite percepts (either ascending or descending) for an ambiguous tone pair depending on the spectral location of preceding context tones. We developed a recurrent, firing-rate network model, which detects frequency-change-direction of successively played stimuli and successfully accounts for the context-dependent perception demonstrated in behavioral experiments. The model consists of two tonotopically organized, excitatory populations, Eup and Edown, that respond preferentially to ascending or descending stimuli in pitch, respectively. These preferences are generated by an inhibitory population that provides inhibition asymmetric in frequency to the two populations; context dependence arises from slow facilitation of inhibition. We show that contextual influence depends on the spectral distribution of preceding tones and the tuning width of inhibitory neurons. Further, we demonstrate, using phase-space analysis, how the facilitated inhibition from previous stimuli and the waning inhibition from the just-preceding tone shape the competition between the Eup and Edown populations. In sum, our model accounts for contextual influences on the pitch change perception of an ambiguous tone pair by introducing a novel decoding strategy based on direction-selective units. The model's network architecture and slow facilitating inhibition emerge as predictions of neuronal mechanisms for these perceptual dynamics. Since the model structure does not depend on the specific stimuli, we show that it generalizes to other contextual effects and stimulus types

  3. Exendin-4 Ameliorates Motor Neuron Degeneration in Cellular and Animal Models of Amyotrophic Lateral Sclerosis

    PubMed Central

    Li, Yazhou; Chigurupati, Srinivasulu; Holloway, Harold W.; Mughal, Mohamed; Tweedie, David; Bruestle, Daniel A.; Mattson, Mark P.; Wang, Yun; Harvey, Brandon K.; Ray, Balmiki; Lahiri, Debomoy K.; Greig, Nigel H.

    2012-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease characterized by a progressive loss of lower motor neurons in the spinal cord. The incretin hormone, glucagon-like peptide-1 (GLP-1), facilitates insulin signaling, and the long acting GLP-1 receptor agonist exendin-4 (Ex-4) is currently used as an anti-diabetic drug. GLP-1 receptors are widely expressed in the brain and spinal cord, and our prior studies have shown that Ex-4 is neuroprotective in several neurodegenerative disease rodent models, including stroke, Parkinson's disease and Alzheimer's disease. Here we hypothesized that Ex-4 may provide neuroprotective activity in ALS, and hence characterized Ex-4 actions in both cell culture (NSC-19 neuroblastoma cells) and in vivo (SOD1 G93A mutant mice) models of ALS. Ex-4 proved to be neurotrophic in NSC-19 cells, elevating choline acetyltransferase (ChAT) activity, as well as neuroprotective, protecting cells from hydrogen peroxide-induced oxidative stress and staurosporine-induced apoptosis. Additionally, in both wild-type SOD1 and mutant SOD1 (G37R) stably transfected NSC-19 cell lines, Ex-4 protected against trophic factor withdrawal-induced toxicity. To assess in vivo translation, SOD1 mutant mice were administered vehicle or Ex-4 at 6-weeks of age onwards to end-stage disease via subcutaneous osmotic pump to provide steady-state infusion. ALS mice treated with Ex-4 showed improved glucose tolerance and normalization of behavior, as assessed by running wheel, compared to control ALS mice. Furthermore, Ex-4 treatment attenuated neuronal cell death in the lumbar spinal cord; immunohistochemical analysis demonstrated the rescue of neuronal markers, such as ChAT, associated with motor neurons. Together, our results suggest that GLP-1 receptor agonists warrant further evaluation to assess whether their neuroprotective potential is of therapeutic relevance in ALS. PMID:22384126

  4. 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

  5. Coupled oscillator model of the dopaminergic neuron of the substantia nigra.

    PubMed

    Wilson, C J; Callaway, J C

    2000-05-01

    Calcium imaging using fura-2 and whole cell recording revealed the effective location of the oscillator mechanism on dopaminergic neurons of the substantia nigra, pars compacta, in slices from rats aged 15-20 days. As previously reported, dopaminergic neurons fired in a slow rhythmic single spiking pattern. The underlying membrane potential oscillation survived blockade of sodium currents with TTX and was enhanced by blockade of voltage-sensitive potassium currents with TEA. Calcium levels increased during the subthreshold depolarizing phase of the membrane potential oscillation and peaked at the onset of the hyperpolarizing phase as expected if the pacemaker potential were due to a low-threshold calcium current and the hyperpolarizing phase to calcium-dependent potassium current. Calcium oscillations were synchronous in the dendrites and soma and were greater in the dendrites than in the soma. Average calcium levels in the dendrites overshot steady-state levels and decayed over the course of seconds after the oscillation was resumed after having been halted by hyperpolarizing currents. Average calcium levels in the soma increased slowly, taking many cycles to achieve steady state. Voltage clamp with calcium imaging revealed the voltage dependence of the somatic calcium current without the artifacts of incomplete spatial voltage control. This showed that the calcium current had little or no inactivation and was half-maximal at -40 to -30 mV. The time constant of calcium removal was measured by the return of calcium to resting levels and depended on diameter. The calcium sensitivity of the calcium-dependent potassium current was estimated by plotting the slow tail current against calcium concentration during the decay of calcium to resting levels at -60 mV. A single compartment model of the dopaminergic neuron consisting of a noninactivating low-threshold calcium current, a calcium-dependent potassium current, and a small leak current reproduced most features of the

  6. Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel.

    PubMed

    Karmeshu; Gupta, Varun; Kadambari, K V

    2011-06-01

    A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.

  7. 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.

  8. 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

  9. Monocarboxylate transporter 8 in neuronal cell growth.

    PubMed

    James, S R; Franklyn, J A; Reaves, B J; Smith, V E; Chan, S Y; Barrett, T G; Kilby, M D; McCabe, C J

    2009-04-01

    Thyroid hormones are essential for the normal growth and development of the fetus, and even small alterations in maternal thyroid hormone status during early pregnancy may be associated with neurodevelopmental abnormalities in childhood. Mutations in the novel and specific thyroid hormone transporter monocarboxylate transporter 8 (MCT8) have been associated with severe neurodevelopmental impairment. However, the mechanism by which MCT8 influences neural development remains poorly defined. We have therefore investigated the effect of wild-type (WT) MCT8, and the previously reported L471P mutant, on the growth and function of human neuronal precursor NT2 cells as well as MCT8-null JEG-3 cells. HA-tagged WT MCT8 correctly localized to the plasma membrane in NT2 cells and increased T(3) uptake in both cell types. In contrast, L471P MCT8 was largely retained in the endoplasmic reticulum and displayed no T(3) transport activity. Transient overexpression of WT and mutant MCT8 proteins failed to induce endoplasmic reticular stress or apoptosis. However, MCT8 overexpression significantly repressed cell proliferation in each cell type in both the presence and absence of the active thyroid hormone T(3) and in a dose-dependent manner. In contrast, L471P MCT8 showed no such influence. Finally, small interfering RNA depletion of endogenous MCT8 resulted in increased cell survival and decreased T(3) uptake. Given that T(3) stimulated proliferation in embryonic neuronal NT2 cells, whereas MCT8 repressed cell growth, these data suggest an entirely novel role for MCT8 in addition to T(3) transport, mediated through the modulation of cell proliferation in the developing brain.

  10. Predictive models of glucose control: roles for glucose-sensing neurones.

    PubMed

    Kosse, C; Gonzalez, A; Burdakov, D

    2015-01-01

    The brain can be viewed as a sophisticated control module for stabilizing blood glucose. A review of classical behavioural evidence indicates that central circuits add predictive (feedforward/anticipatory) control to the reactive (feedback/compensatory) control by peripheral organs. The brain/cephalic control is constructed and engaged, via associative learning, by sensory cues predicting energy intake or expenditure (e.g. sight, smell, taste, sound). This allows rapidly measurable sensory information (rather than slowly generated internal feedback signals, e.g. digested nutrients) to control food selection, glucose supply for fight-or-flight responses or preparedness for digestion/absorption. Predictive control is therefore useful for preventing large glucose fluctuations. We review emerging roles in predictive control of two classes of widely projecting hypothalamic neurones, orexin/hypocretin (ORX) and melanin-concentrating hormone (MCH) cells. Evidence is cited that ORX neurones (i) are activated by sensory cues (e.g. taste, sound), (ii) drive hepatic production, and muscle uptake, of glucose, via sympathetic nerves, (iii) stimulate wakefulness and exploration via global brain projections and (iv) are glucose-inhibited. MCH neurones are (i) glucose-excited, (ii) innervate learning and reward centres to promote synaptic plasticity, learning and memory and (iii) are critical for learning associations useful for predictive control (e.g. using taste to predict nutrient value of food). This evidence is unified into a model for predictive glucose control. During associative learning, inputs from some glucose-excited neurones may promote connections between the 'fast' senses and reward circuits, constructing neural shortcuts for efficient action selection. In turn, glucose-inhibited neurones may engage locomotion/exploration and coordinate the required fuel supply. Feedback inhibition of the latter neurones by glucose would ensure that glucose fluxes they stimulate

  11. Developing Itô stochastic differential equation models for neuronal signal transduction pathways.

    PubMed

    Manninen, Tiina; Linne, Marja-Leena; Ruohonen, Keijo

    2006-08-01

    Mathematical modeling and simulation of dynamic biochemical systems are receiving considerable attention due to the increasing availability of experimental knowledge of complex intracellular functions. In addition to deterministic approaches, several stochastic approaches have been developed for simulating the time-series behavior of biochemical systems. The problem with stochastic approaches, however, is the larger computational time compared to deterministic approaches. It is therefore necessary to study alternative ways to incorporate stochasticity and to seek approaches that reduce the computational time needed for simulations, yet preserve the characteristic behavior of the system in question. In this work, we develop a computational framework based on the Itô stochastic differential equations for neuronal signal transduction networks. There are several different ways to incorporate stochasticity into deterministic differential equation models and to obtain Itô stochastic differential equations. Two of the developed models are found most suitable for stochastic modeling of neuronal signal transduction. The best models give stable responses which means that the variances of the responses with time are not increasing and negative concentrations are avoided. We also make a comparative analysis of different kinds of stochastic approaches, that is the Itô stochastic differential equations, the chemical Langevin equation, and the Gillespie stochastic simulation algorithm. Different kinds of stochastic approaches can be used to produce similar responses for the neuronal protein kinase C signal transduction pathway. The fine details of the responses vary slightly, depending on the approach and the parameter values. However, when simulating great numbers of chemical species, the Gillespie algorithm is computationally several orders of magnitude slower than the Itô stochastic differential equations and the chemical Langevin equation. Furthermore, the chemical

  12. 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.

  13. 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.

  14. 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

  15. Nonlinear Dynamic Modeling of Neuron Action Potential Threshold During Synaptically Driven Broadband Intracellular Activity

    PubMed Central

    Roach, Shane M.; Song, Dong; Berger, Theodore W.

    2012-01-01

    Activity-dependent variation of neuronal thresholds for action potential (AP) generation is one of the key determinants of spike-train temporal-pattern transformations from presynaptic to postsynaptic spike trains. In this study, we model the nonlinear dynamics of the threshold variation during synaptically driven broadband intracellular activity. First, membrane potentials of single CA1 pyramidal cells were recorded under physiologically plausible broadband stimulation conditions. Second, a method was developed to measure AP thresholds from the continuous recordings of membrane potentials. It involves measuring the turning points of APs by analyzing the third-order derivatives of the membrane potentials. Four stimulation paradigms with different temporal patterns were applied to validate this method by comparing the measured AP turning points and the actual AP thresholds estimated with varying stimulation intensities. Results show that the AP turning points provide consistent measurement of the AP thresholds, except for a constant offset. It indicates that 1) the variation of AP turning points represents the nonlinearities of threshold dynamics; and 2) an optimization of the constant offset is required to achieve accurate spike prediction. Third, a nonlinear dynamical third-order Volterra model was built to describe the relations between the threshold dynamics and the AP activities. Results show that the model can predict threshold accurately based on the preceding APs. Finally, the dynamic threshold model was integrated into a previously developed single neuron model and resulted in a 33% improvement in spike prediction. PMID:22156947

  16. 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.

  17. 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.

  18. 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

  19. Impaired Mitochondrial Dynamics and Mitophagy in Neuronal Models of Tuberous Sclerosis Complex.

    PubMed

    Ebrahimi-Fakhari, Darius; Saffari, Afshin; Wahlster, Lara; Di Nardo, Alessia; Turner, Daria; Lewis, Tommy L; Conrad, Christopher; Rothberg, Jonathan M; Lipton, Jonathan O; Kölker, Stefan; Hoffmann, Georg F; Han, Min-Joon; Polleux, Franck; Sahin, Mustafa

    2016-10-18

    Tuberous sclerosis complex (TSC) is a neurodevelopmental disease caused by TSC1 or TSC2 mutations and subsequent activation of the mTORC1 kinase. Upon mTORC1 activation, anabolic metabolism, which requires mitochondria, is induced, yet at the same time the principal pathway for mitochondrial turnover, autophagy, is compromised. How mTORC1 activation impacts mitochondrial turnover in neurons remains unknown. Here, we demonstrate impaired mitochondrial homeostasis in neuronal in vitro and in vivo models of TSC. We find that Tsc1/2-deficient neurons accumulate mitochondria in cell bodies, but are depleted of axonal mitochondria, including those supporting presynaptic sites. Axonal and global mitophagy of damaged mitochondria is impaired, suggesting that decreased turnover may act upstream of impaired mitochondrial metabolism. Importantly, blocking mTORC1 or inducing mTOR-independent autophagy restores mitochondrial homeostasis. Our study clarifies the complex relationship between the TSC-mTORC1 pathway, autophagy, and mitophagy, and defines mitochondrial homeostasis as a therapeutic target for TSC and related diseases.

  20. 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.

  1. Amelioration of toxicity in neuronal models of amyotrophic lateral sclerosis by hUPF1

    PubMed Central

    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

    2015-01-01

    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

  2. The Effect of Neural Noise on Spike Time Precision in a Detailed CA3 Neuron Model

    PubMed Central

    Kuriscak, Eduard; Marsalek, Petr; Stroffek, Julius; Wünsch, Zdenek

    2012-01-01

    Experimental and computational studies emphasize the role of the millisecond precision of neuronal spike times as an important coding mechanism for transmitting and representing information in the central nervous system. We investigate the spike time precision of a multicompartmental pyramidal neuron model of the CA3 region of the hippocampus under the influence of various sources of neuronal noise. We describe differences in the contribution to noise originating from voltage-gated ion channels, synaptic vesicle release, and vesicle quantal size. We analyze the effect of interspike intervals and the voltage course preceding the firing of spikes on the spike-timing jitter. The main finding of this study is the ranking of different noise sources according to their contribution to spike time precision. The most influential is synaptic vesicle release noise, causing the spike jitter to vary from 1 ms to 7 ms of a mean value 2.5 ms. Of second importance was the noise incurred by vesicle quantal size variation causing the spike time jitter to vary from 0.03 ms to 0.6 ms. Least influential was the voltage-gated channel noise generating spike jitter from 0.02 ms to 0.15 ms. PMID:22778784

  3. 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

  4. Investigating spike backpropagation induced Ca2+ influx in models of hippocampal and cortical pyramidal neurons.

    PubMed

    Marsálek, P; Santamaría, F

    1998-01-01

    We modeled the influx of calcium ions into dendrites following active backpropagation of spike trains in a dendritic tree, using compartmental models of anatomically reconstructed pyramidal cells in a GENESIS program. Basic facts of ion channel densities in pyramidal cells were taken into account. The time scale of the backpropagating spike train development was longer than in previous models. We also studied the relationship between intracellular calcium dynamics and membrane voltage. Comparisons were made between two pyramidal cell prototypes and in simplified model. Our results show that: (1) sodium and potassium channels are enough to explain regenerative backpropagating spike trains; (2) intracellular calcium concentration changes are consistent in the range of milliseconds to seconds; (3) the simulations support several experimental observations in both hippocampal and neocortical cells. No additional parameter search optimization was necessary. Compartmental models can be used for investigating the biology of neurons, and then simplified for constructing neural networks.

  5. Analyzing and Modeling the Dysfunction of Inhibitory Neurons in Alzheimer’s Disease

    PubMed Central

    Perez, Carlos; Ziburkus, Jokubas; Ullah, Ghanim

    2016-01-01

    Alzheimer’s disease (AD) is characterized by the abnormal proteolytic processing of amyloid precursor protein, resulting in increased production of a self-aggregating form of beta amyloid (Aβ). Several lines of work on AD patients and transgenic mice with high Aβ levels exhibit altered rhythmicity, aberrant neuronal network activity and hyperexcitability reflected in clusters of hyperactive neurons, and spontaneous epileptic activity. Recent studies highlight that abnormal accumulation of Aβ changes intrinsic properties of inhibitory neurons, which is one of the main reasons underlying the impaired network activity. However, specific cellular mechanisms leading to interneuronal dysfunction are not completely understood. Using extended Hodgkin-Huxley (HH) formalism in conjunction with patch-clamp experiments, we investigate the mechanisms leading to the impaired activity of interneurons. Our detailed analysis indicates that increased Na+ leak explains several observations in inhibitory neurons, including their failure to reliably produce action potentials, smaller action potential amplitude, increased resting membrane potential, and higher membrane depolarization in response to a range of stimuli in a model of APPSWE/PSEN1DeltaE9 (APdE9) AD mice as compared to age-matched control mice. While increasing the conductance of hyperpolarization activated cyclic nucleotide-gated (HCN) ion channel could account for most of the observations, the extent of increase required to reproduce these observations render such changes unrealistic. Furthermore, increasing the conductance of HCN does not account for the observed changes in depolarizability of interneurons from APdE9 mice as compared to those from NTG mice. None of the other pathways tested could lead to all observations about interneuronal dysfunction. Thus we conclude that upregulated sodium leak is the most likely source of impaired interneuronal function. PMID:28036398

  6. Transient high-frequency firing in a coupled-oscillator model of the mesencephalic dopaminergic neuron.

    PubMed

    Kuznetsov, Alexey S; Kopell, Nancy J; Wilson, Charles J

    2006-02-01

    Dopaminergic neurons of the midbrain fire spontaneously at rates <10/s and ordinarily will not exceed this range even when driven with somatic current injection. When driven at higher rates, these cells undergo spike failure through depolarization block. During spontaneous bursting of dopaminergic neurons in vivo, bursts related to reward expectation in behaving animals, and bursts generated by dendritic application of N-methyl-d-aspartate (NMDA) agonists, transient firing attains rates well above this range. We suggest a way such high-frequency firing may occur in response to dendritic NMDA receptor activation. We have extended the coupled oscillator model of the dopaminergic neuron, which represents the soma and dendrites as electrically coupled compartments with different natural spiking frequencies, by addition of dendritic AMPA (voltage-independent) or NMDA (voltage-dependent) synaptic conductance. Both soma and dendrites contain a simplified version of the calcium-potassium mechanism known to be the mechanism for slow spontaneous oscillation and background firing in dopaminergic cells. The compartments differ only in diameter, and this difference is responsible for the difference in natural frequencies. We show that because of its voltage dependence, NMDA receptor activation acts to amplify the effect on the soma of the high-frequency oscillation of the dendrites, which is normally too weak to exert a large influence on the overall oscillation frequency of the neuron. During the high-frequency oscillations that result, sodium inactivation in the soma is removed rapidly after each action potential by the hyperpolarizing influence of the dendritic calcium-dependent potassium current, preventing depolarization block of the spike mechanism, and allowing high-frequency spiking.

  7. Modeling the emergence of circadian rhythms in a clock neuron network.

    PubMed

    Diambra, Luis; Malta, Coraci P

    2012-01-01

    Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping) of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i) the control of net entrance of PER into the nucleus and (ii) the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.

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

    PubMed Central

    Thongrong, Sitthisak; Hausott, Barbara; Marvaldi, Letizia; Agostinho, Alexandra S.; Zangrandi, Luca; Burtscher, Johannes; Fogli, Barbara

    2015-01-01

    ABSTRACT Sprouty (Spry) proteins play a key role as negative feedback inhibitors of the Ras/Raf/MAPK/ERK pathway downstream of various receptor tyrosine kinases. Among the four Sprouty isoforms, Spry2 and Spry4 are expressed in the hippocampus. In this study, possible effects of Spry2 and Spry4 hypomorphism on neurodegeneration and seizure thresholds in a mouse model of epileptogenesis was analyzed. The Spry2/4 hypomorphs exhibited stronger ERK activation which was limited to the CA3 pyramidal cell layer and to the hilar region. The seizure threshold of Spry2/4+/− mice was significantly reduced at naive state but no difference to wildtype mice was observed 1 month following KA treatment. Histomorphological analysis revealed that dentate granule cell dispersion (GCD) was diminished in Spry2/4+/− mice in the subchronic phase after KA injection. Neuronal degeneration was reduced in CA1 and CA3 principal neuron layers as well as in scattered neurons of the contralateral CA1 and hilar regions. Moreover, Spry2/4 reduction resulted in enhanced survival of somatostatin and neuropeptide Y expressing interneurons. GFAP staining intensity and number of reactive astrocytes markedly increased in lesioned areas of Spry2/4+/− mice as compared with wildtype mice. Taken together, although the seizure threshold is reduced in naive Spry2/4+/− mice, neurodegeneration and GCD is mitigated following KA induced hippocampal lesions, identifying Spry proteins as possible pharmacological targets in brain injuries resulting in neurodegeneration. The present data are consistent with the established functions of the ERK pathway in astrocyte proliferation as well as protection from neuronal cell death and suggest a novel role of Spry proteins in the migration of differentiated neurons. © 2015 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:26540287

  9. 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. Labeling of neuronal differentiation and neuron cells with biocompatible fluorescent nanodiamonds.

    PubMed

    Hsu, Tzu-Chia; Liu, Kuang-Kai; Chang, Huan-Cheng; Hwang, Eric; Chao, Jui-I

    2014-05-16

    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.

  11. Accurate and fast simulation of channel noise in conductance-based model neurons by diffusion approximation.

    PubMed

    Linaro, Daniele; Storace, Marco; Giugliano, Michele

    2011-03-01

    Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically detailed model neurons calls for the availability of fast numerical methods. In fact, exact techniques employ the microscopic simulation of the random opening and closing of individual ion channels, usually based on Markov models, whose computational loads are prohibitive for next generation massive computer models of the brain. In this work, we operatively define a procedure for translating any Markov model describing voltage- or ligand-gated membrane ion-conductances into an effective stochastic version, whose computer simulation is efficient, without compromising accuracy. Our approximation is based on an improved Langevin-like approach, which employs stochastic differential equations and no Montecarlo methods. As opposed to an earlier proposal recently debated in the literature, our approximation reproduces accurately the statistical properties of the exact microscopic simulations, under a variety of conditions, from spontaneous to evoked response features. In addition, our method is not restricted to the Hodgkin-Huxley sodium and potassium currents and is general for a variety of voltage- and ligand-gated ion currents. As a by-product, the analysis of the properties emerging in exact Markov schemes by standard probability calculus enables us for the first time to analytically identify the sources of inaccuracy of the previous proposal, while providing solid ground for its modification and improvement we present here.

  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. Human Immunodeficiency Virus Type 1 Vpr Induces Apoptosis in Human Neuronal Cells

    PubMed Central

    Patel, Charvi A.; Mukhtar, Muhammad; Pomerantz, Roger J.

    2000-01-01

    Human immunodeficiency virus type 1 (HIV-1) infection of the central nervous system (CNS) causes AIDS dementia complex (ADC) in certain infected individuals. Recent studies have suggested that patients with ADC have an increased incidence of neuronal apoptosis leading to neuronal dropout. Of note, a higher level of the HIV-1 accessory protein Vpr has been detected in the cerebrospinal fluid of AIDS patients with neurological disorders. Moreover, extracellular Vpr has been shown to form ion channels, leading to cell death of cultured rat hippocampal neurons. Based on these previous findings, we first investigated the apoptotic effects of the HIV-1 Vpr protein on the human neuronal precursor NT2 cell line at a range of concentrations. These studies demonstrated that apoptosis induced by both Vpr and the envelope glycoprotein, gp120, occurred in a dose-dependent manner compared to protein treatment with HIV-1 integrase, maltose binding protein (MBP), and MBP-Vpr in the undifferentiated NT2 cells. For mature, differentiated neurons, apoptosis was also induced in a dose-dependent manner by both Vpr and gp120 at concentrations ranging from 1 to 100 ng/ml, as demonstrated by both the terminal deoxynucleotidyltransferase (Tdt)-mediated dUTP-biotin nick end labeling and Annexin V assays for apoptotic cell death. In order to clarify the intracellular pathways and molecular mechanisms involved in Vpr- and gp120-induced apoptosis in the NT2 cell line and differentiated mature human neurons, we then examined the cellular lysates for caspase-8 activity in these studies. Vpr and gp120 treatments exhibited a potent increase in activation of caspase-8 in both mature neurons and undifferentiated NT2 cells. This suggests that Vpr may be exerting selective cytotoxicity in a neuronal precursor cell line and in mature human neurons through the activation of caspase-8. These data represent a characterization of Vpr-induced apoptosis in human neuronal cells, and suggest that extracellular

  14. A three-dimensional spatiotemporal receptive field model explains responses of area MT neurons to naturalistic movies

    PubMed Central

    Nishimoto, Shinji; Gallant, Jack L.

    2012-01-01

    Area MT has been an important target for studies of motion processing. However, previous neurophysiological studies of MT have used simple stimuli that do not contain many of the motion signals that occur during natural vision. In this study we sought to determine whether views of area MT neurons developed using simple stimuli can account for MT responses under more naturalistic conditions. We recorded responses from macaque area MT neurons during stimulation with naturalistic movies. We then used a quantitative modeling framework to discover which specific mechanisms best predict neuronal responses under these challenging conditions. We find that the simplest model that accurately predicts responses of MT neurons consists of a bank of V1-like filters, each followed by a compressive nonlinearity, a divisive nonlinearity and linear pooling. Inspection of the fit models shows that the excitatory receptive fields of MT neurons tend to lie on a single plane within the three-dimensional spatiotemporal frequency domain, and suppressive receptive fields lie off this plane. However, most excitatory receptive fields form a partial ring in the plane and avoid low temporal frequencies. This receptive field organization ensures that most MT neurons are tuned for velocity but do not tend to respond to ambiguous static textures that are aligned with the direction of motion. In sum, MT responses to naturalistic movies are largely consistent with predictions based on simple stimuli. However, models fit using naturalistic stimuli reveal several novel properties of MT receptive fields that had not been shown in prior experiments. PMID:21994372

  15. Sodium MRI in a rat migraine model and a NEURON simulation study support a role for sodium in migraine

    PubMed Central

    Harrington, Michael G; Chekmenev, Eduard Y; Schepkin, Victor; Fonteh, Alfred N; Arakaki, Xianghong

    2012-01-01

    Introduction Increased lumbar cerebrospinal fluid (CSF) sodium has been reported during migraine. We used ultra-high field MRI to investigate cranial sodium in a rat migraine model, and simulated the effects of extracellular sodium on neuronal excitability. Methods Behavioral changes in the nitroglycerin (NTG) rat migraine model were determined from von Frey hair withdrawal response and photography. Central sensitization was measured by counting cFos-immunoreactive cells in the trigeminal nucleus caudalis (TNC). Sodium was quantified in vivo by ultra-high field sodium MRI at 21 Tesla. Effects of extracellular sodium on neuronal excitability were modeled using NEURON software. Results NTG decreased von Frey withdrawal threshold (p=0.0003), decreased eyelid vertical height:width ratio (p<0.0001), increased TNC cFos stain (p<0.0001), and increased sodium between 7.5 and 17% in brain, intracranial CSF, and vitreous humor (p<0.05). Simulated neurons exposed to higher sodium have more frequent and earlier spontaneous action potentials, and corresponding earlier sodium and potassium currents. Conclusions In the rat migraine model, sodium rises to levels that increase neuronal excitability. We propose that rising sodium in CSF surrounding trigeminal nociceptors increases their excitability and causes pain and that rising sodium in vitreous humor increases retinal neuronal excitability and causes photosensitivity. PMID:21816771

  16. A three-dimensional spatiotemporal receptive field model explains responses of area MT neurons to naturalistic movies.

    PubMed

    Nishimoto, Shinji; Gallant, Jack L

    2011-10-12

    Area MT has been an important target for studies of motion processing. However, previous neurophysiological studies of MT have used simple stimuli that do not contain many of the motion signals that occur during natural vision. In this study we sought to determine whether views of area MT neurons developed using simple stimuli can account for MT responses under more naturalistic conditions. We recorded responses from macaque area MT neurons during stimulation with naturalistic movies. We then used a quantitative modeling framework to discover which specific mechanisms best predict neuronal responses under these challenging conditions. We find that the simplest model that accurately predicts responses of MT neurons consists of a bank of V1-like filters, each followed by a compressive nonlinearity, a divisive nonlinearity, and linear pooling. Inspection of the fit models shows that the excitatory receptive fields of MT neurons tend to lie on a single plane within the three-dimensional spatiotemporal frequency domain, and suppressive receptive fields lie off this plane. However, most excitatory receptive fields form a partial ring in the plane and avoid low temporal frequencies. This receptive field organization ensures that most MT neurons are tuned for velocity but do not tend to respond to ambiguous static textures that are aligned with the direction of motion. In sum, MT responses to naturalistic movies are largely consistent with predictions based on simple stimuli. However, models fit using naturalistic stimuli reveal several novel properties of MT receptive fields that had not been shown in prior experiments.

  17. Dysequilibrium of neuronal proliferation and apoptosis in a pharmacological animal model of psychosis.

    PubMed

    Genius, Just; Benninghoff, Jens; Reuter, Nadine; Braun, Isabella; Giegling, Ina; Hartmann, Annette; Möller, Hans-Jürgen; Rujescu, Dan

    2012-04-01

    Growing evidence implicates that abnormal stem cell proliferation and neurodegenerative mechanisms may be involved in the pathogenesis of neuropsychiatric disorders including schizophrenia. Here, we studied the underlying pathomechanisms of psychosis. We are employing a translational approach combining in vivo data with supplementary data from an adult neuronal stem cell-derived cell culture model by generating a large number of analytes in our specimens following a multiplexing strategy. In the animal model the NMDA receptor was chronically antagonized by MK-801 at ultralow doses. As a result of this, we were able to demonstrate a roughly twofold increased density of PCNA positive cells in the germinal zone of the dentate gyrus indicating enhanced neuroproliferative activity. In vitro stem cell experiments additionally pointed to this direction showing an increase both in proliferation and neuronal differentiation after MK-801 treatment. These alterations were partially prevented by coapplication of the dopamine receptor antagonist haloperidol. In addition, apoptotic activity assessed by immunohistochemical demonstration of cleaved caspase-3 stainings was unaffected by MK-801 treatment. These observations were largely supported by microarray gene expression analysis, which permits high-throughput multiplexed assessment of expression data from a comprehensive set of genes and showed parallels with data from human post mortem studies. In conclusion, our data support the notion, that abnormal proliferation due to anti-apoptotic mechanisms may represent a factor in the pathogenesis of psychosis. Thus, research on the exact interplay between glutamatergic neurotransmission and neuronal proliferation deserves more attention. This dual in vivo and in vitro strategy described here may prove as a suitable model for addressing complex neuropsychiatric diseases especially when taking advantage of the potential of multiplex technologies not only in diagnostics but also in

  18. 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.

  19. A new firing paradigm for integrate and fire stochastic neuronal models.

    PubMed

    Sirovich, Roberta; Testa, Luisa

    2016-06-01

    A new definition of firing time is given in the framework of Integrate and Fire neuronal models. The classical absorption condition at the threshold is relaxed and the firing time is defined as the first time the membrane potential process lies above a fixed depolarisation level for a sufficiently long time. The mathematical properties of the new firing time are investigated both for the Perfect Integrator and the Leaky Integrator. In the latter case, a simulation study is presented to complete the analysis where analytical results are not yet achieved.

  20. 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.

  1. 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.

  2. A new glucocerebrosidase-deficient neuronal cell model provides a tool to probe pathophysiology and therapeutics for Gaucher disease.

    PubMed

    Westbroek, Wendy; Nguyen, Matthew; Siebert, Marina; Lindstrom, Taylor; Burnett, Robert A; Aflaki, Elma; Jung, Olive; Tamargo, Rafael; Rodriguez-Gil, Jorge L; Acosta, Walter; Hendrix, An; Behre, Bahafta; Tayebi, Nahid; Fujiwara, Hideji; Sidhu, Rohini; Renvoise, Benoit; Ginns, Edward I; Dutra, Amalia; Pak, Evgenia; Cramer, Carole; Ory, Daniel S; Pavan, William J; Sidransky, Ellen

    2016-07-01

    Glucocerebrosidase is a lysosomal hydrolase involved in the breakdown of glucosylceramide. Gaucher disease, a recessive lysosomal storage disorder, is caused by mutations in the gene GBA1 Dysfunctional glucocerebrosidase leads to accumulation of glucosylceramide and glycosylsphingosine in various cell types and organs. Mutations in GBA1 are also a common genetic risk factor for Parkinson disease and related synucleinopathies. In recent years, research on the pathophysiology of Gaucher disease, the molecular link between Gaucher and Parkinson disease, and novel therapeutics, have accelerated the need for relevant cell models with GBA1 mutations. Although induced pluripotent stem cells, primary rodent neurons, and transfected neuroblastoma cell lines have been used to study the effect of glucocerebrosidase deficiency on neuronal function, these models have limitations because of challenges in culturing and propagating the cells, low yield, and the introduction of exogenous mutant GBA1 To address some of these difficulties, we established a high yield, easy-to-culture mouse neuronal cell model with nearly complete glucocerebrosidase deficiency representative of Gaucher disease. We successfully immortalized cortical neurons from embryonic null allele gba(-/-) mice and the control littermate (gba(+/+)) by infecting differentiated primary cortical neurons in culture with an EF1α-SV40T lentivirus. Immortalized gba(-/-) neurons lack glucocerebrosidase protein and enzyme activity, and exhibit a dramatic increase in glucosylceramide and glucosylsphingosine accumulation, enlarged lysosomes, and an impaired ATP-dependent calcium-influx response; these phenotypical characteristics were absent in gba(+/+) neurons. This null allele gba(-/-) mouse neuronal model provides a much-needed tool to study the pathophysiology of Gaucher disease and to evaluate new therapies.

  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. Gastrodin Protects Apoptotic Dopaminergic Neurons in a Toxin-Induced Parkinson's Disease Model

    PubMed Central

    Kumar, Hemant; Kim, In-Su; More, Sandeep Vasant; Kim, Byung-Wook; Bahk, Young-Yil; Choi, Dong-Kug

    2013-01-01

    Gastrodia elata (GE) Blume is one of the most important traditional plants in Oriental countries and has been used for centuries to improve various conditions. The phenolic glucoside gastrodin is an active constituent of GE. The aim of this study was to investigate the neuroprotective role of gastrodin in 1-methyl-4-phenylpyridinium (MPP+)/1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine- (MPTP) induced human dopaminergic SH-SY5Y cells and mouse model of Parkinson's disease (PD), respectively. Gastrodin significantly and dose dependently protected dopaminergic neurons against neurotoxicity through regulating free radicals, Bax/Bcl-2 mRNA, caspase-3, and cleaved poly(ADP-ribose) polymerase (PARP) in SH-SY5Y cells stressed with MPP+. Gastrodin also showed neuroprotective effects in the subchronic MPTP mouse PD model by ameliorating bradykinesia and motor impairment in the pole and rotarod tests, respectively. Consistent with this finding, gastrodin prevented dopamine depletion and reduced reactive astrogliosis caused by MPTP as assessed by immunohistochemistry and immunoblotting in the substantiae nigrae and striatata of mice. Moreover, gastrodin was also effective in preventing neuronal apoptosis by attenuating antioxidant and antiapoptotic activities in these brain areas. These results strongly suggest that gastrodin has protective effects in experimental PD models and that it may be developed as a clinical candidate to ameliorate PD symptoms. PMID:23533492

  5. A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

    PubMed

    Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P

    2013-01-01

    We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

  6. A model of a rapidly-adapting mechanosensitive current generated by a dorsal root ganglion neuron.

    PubMed

    Fujita, Kazuhisa

    2014-06-01

    I propose a model that replicates the kinetics of a rapidly-adapting mechanosensitive current generated by a dorsal root ganglion (DRG) neuron. When the DRG neuron is mechanically stimulated, an ionic current called a mechanosensitive current flows across its membrane. The kinetics of mechanosensitive currents are broadly classified into three types; rapidly adapting (RA), intermediately adapting, and slowly adapting. The kinetics of RA mechanosensitive currents are particularly intriguing. An RA mechanosensitive current is initially evoked by and rapidly adapts to a mechanical stimulus, but can also respond to an additional stimulus. Furthermore, an antecedent stimulus immediately followed by an additional stimulus suppresses reactivation of the current. The features of the kinetics depend on the characteristics of the mechanotransducer channels. Physiologists have proposed three factors associated with mechanotransducer channels, invoking activation, adaptation, and inactivation. In the present study, these factors are incorporated into an RA mechanosensitive current model. Computer simulations verified that the proposed model replicates the kinetics of real RA DRG mechanosensitive currents. The mechanosensitive current elicited by successive pulse-form stimuli was predominantly desensitized by the inactivating factor. Both the inactivating and adapting factors were involved in desensitization of a double-decker stimulus. The reduction of the sensitivity with decreasing velocity of the stimulus was mainly controlled by the adapting factor.

  7. 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

  8. Optimization behavior of brainstem respiratory neurons. A cerebral neural network model.

    PubMed

    Poon, C S

    1991-01-01

    A recent model of respiratory control suggested that the steady-state respiratory responses to CO2 and exercise may be governed by an optimal control law in the brainstem respiratory neurons. It was not certain, however, whether such complex optimization behavior could be accomplished by a realistic biological neural network. To test this hypothesis, we developed a hybrid computer-neural model in which the dynamics of the lung, brain and other tissue compartments were simulated on a digital computer. Mimicking the "controller" was a human subject who pedalled on a bicycle with varying speed (analog of ventilatory output) with a view to minimize an analog signal of the total cost of breathing (chemical and mechanical) which was computed interactively and displayed on an oscilloscope. In this manner, the visuomotor cortex served as a proxy (homolog) of the brainstem respiratory neurons in the model. Results in 4 subjects showed a linear steady-state ventilatory CO2 response to arterial PCO2 during simulated CO2 inhalation and a nearly isocapnic steady-state response during simulated exercise. Thus, neural optimization is a plausible mechanism for respiratory control during exercise and can be achieved by a neural network with cognitive computational ability without the need for an exercise stimulus.

  9. A Model-Based Spike Sorting Algorithm for Removing Correlation Artifacts in Multi-Neuron Recordings

    PubMed Central

    Chichilnisky, E. J.; Simoncelli, Eero P.

    2013-01-01

    We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call “binary pursuit”. The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth. PMID:23671583

  10. The angiotensin converting enzyme inhibitor captopril protects nigrostriatal dopamine neurons in animal models of parkinsonism.

    PubMed

    Sonsalla, Patricia K; Coleman, Christal; Wong, Lai-Yoong; Harris, Suzan L; Richardson, Jason R; Gadad, Bharathi S; Li, Wenhao; German, Dwight C

    2013-12-01

    Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a prominent loss of nigrostriatal dopamine (DA) neurons with an accompanying neuroinflammation. The peptide angiotensin II (AngII) plays a role in oxidative-stress induced disorders and is thought to mediate its detrimental actions via activation of AngII AT1 receptors. The brain renin-angiotensin system is implicated in neurodegenerative disorders including PD. Blockade of the angiotensin converting enzyme or AT1 receptors provides protection in acute animal models of parkinsonism. We demonstrate here that treatment of mice with the angiotensin converting enzyme inhibitor captopril protects the striatum from acutely administered 1-methyl-4-phenyl-1,2,3,6-tetrahydropyrine (MPTP), and that chronic captopril protects the nigral DA cell bodies from degeneration in a progressive rat model of parkinsonism created by the chronic intracerebral infusion of 1-methyl-4-phenylpyridinium (MPP+). The accompanying activation of microglia in the substantia nigra of MPP+-treated rats was reduced by the chronic captopril treatment. These findings indicate that captopril is neuroprotective for nigrostriatal DA neurons in both acute and chronic rodent PD models. Targeting the brain AngII pathway may be a feasible approach to slowing neurodegeneration in PD.

  11. 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

  12. 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

  13. Neuronal and glial changes in the brain resulting from explosive blast in an experimental model.

    PubMed

    Goodrich, James A; Kim, Jung H; Situ, Robert; Taylor, Wesley; Westmoreland, Ted; Du, Fu; Parks, Steven; Ling, Geoffrey; Hwang, Jung Y; Rapuano, Amedeo; Bandak, Faris A; de Lanerolle, Nihal C

    2016-11-24

    Mild traumatic brain injury (mTBI) is the signature injury in warfighters exposed to explosive blasts. The pathology underlying mTBI is poorly understood, as this condition is rarely fatal and thus postmortem brains are difficult to obtain for neuropathological studies. Here we report on studies of an experimental model with a gyrencephalic brain that is exposed to single and multiple explosive blast pressure waves. To determine injuries to the brain resulting from the primary blast, experimental conditions were controlled to eliminate any secondary or tertiary injury from blasts. We found small but significant levels of neuronal loss in the hippocampus, a brain area that is important for cognitive functions. Furthermore, neuronal loss increased with multiple blasts and the degree of neuronal injury worsened with time post-blast. This is consistent with our findings in the blast-exposed human brain based on magnetic resonance spectroscopic imaging. The studies on this experimental model thus confirm what has been presumed to be the case with the warfighter, namely that exposure to multiple blasts causes increased brain injury. Additionally, as in other studies of both explosive blast as well as closed head mTBI, we found astrocyte activation. Activated microglia were also prominent in white matter tracts, particularly in animals exposed to multiple blasts and at long post-blast intervals, even though injured axons (i.e. β-APP positive) were not found in these areas. Microglial activation appears to be a delayed response, though whether they may contribute to inflammation related injury mechanism at even longer post-blast times than we tested here, remains to be explored. Petechial hemorrhages or other gross signs of vascular injury were not observed in our study. These findings confirm the development of neuropathological changes due to blast exposure. The activation of astrocytes and microglia, cell types potentially involved in inflammatory processes, suggest an

  14. 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

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

    PubMed

    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").

  16. 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

  17. Neuronal mechanisms and circuits underlying repetitive behaviors in mouse models of autism spectrum disorder.

    PubMed

    Kim, Hyopil; Lim, Chae-Seok; Kaang, Bong-Kiun

    2016-01-20

    Autism spectrum disorder (ASD) refers to a broad spectrum of neurodevelopmental disorders characterized by three central behavioral symptoms: impaired social interaction, impaired social communication, and restricted and repetitive behaviors. However, the symptoms are heterogeneous among patients and a number of ASD mouse models have been generated containing mutations that mimic the mutations found in human patients with ASD. Each mouse model was found to display a unique set of repetitive behaviors. In this review, we summarize the repetitive behaviors of the ASD mouse models and variations found in their neural mechanisms including molecular and electrophysiological features. We also propose potential neuronal mechanisms underlying these repetitive behaviors, focusing on the role of the cortico-basal ganglia-thalamic circuits and brain regions associated with both social and repetitive behaviors. Further understanding of molecular and circuitry mechanisms of the repetitive behaviors associated with ASD is necessary to aid the development of effective treatments for these disorders.

  18. 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

  19. The neuron-astrocyte-microglia triad in a rat model of chronic cerebral hypoperfusion: protective effect of dipyridamole

    PubMed Central

    Lana, Daniele; Melani, Alessia; Pugliese, Anna Maria; Cipriani, Sara; Nosi, Daniele; Pedata, Felicita; Giovannini, Maria Grazia

    2014-01-01

    Chronic cerebral hypoperfusion during aging may cause progressive neurodegeneration as ischemic conditions persist. Proper functioning of the interplay between neurons and glia is fundamental for the functional organization of the brain. The aim of our research was to study the pathophysiological mechanisms, and particularly the derangement of the interplay between neurons and astrocytes-microglia with the formation of “triads,” in a model of chronic cerebral hypoperfusion induced by the two-vessel occlusion (2VO) in adult Wistar rats (n = 15). The protective effect of dipyridamole given during the early phases after 2VO (4 mg/kg/day i.v., the first 7 days after 2VO) was verified (n = 15). Sham-operated rats (n = 15) were used as controls. Immunofluorescent triple staining of neurons (NeuN), astrocytes (GFAP), and microglia (IBA1) was performed 90 days after 2VO. We found significantly higher amount of “ectopic” neurons, neuronal debris and apoptotic neurons in CA1 Str. Radiatum and Str. Pyramidale of 2VO rats. In CA1 Str. Radiatum of 2VO rats the amount of astrocytes (cells/mm2) did not increase. In some instances several astrocytes surrounded ectopic neurons and formed a “micro scar” around them. Astrocyte branches could infiltrate the cell body of ectopic neurons, and, together with activated microglia cells formed the “triads.” In the triad, significantly more numerous in CA1 Str. Radiatum of 2VO than in sham rats, astrocytes and microglia cooperated in the phagocytosis of ectopic neurons. These events might be common mechanisms underlying many neurodegenerative processes. The frequency to which they appear might depend upon, or might be the cause of, the burden and severity of neurodegeneration. Dypiridamole significantly reverted all the above described events. The protective effect of chronic administration of dipyridamole might be a consequence of its vasodilatory, antioxidant and anti-inflammatory role during the early phases after 2VO

  20. Arginine vasopressin neuronal loss results from autophagy-associated cell death in a mouse model for familial neurohypophysial diabetes insipidus.

    PubMed

    Hagiwara, D; Arima, H; Morishita, Y; Wenjun, L; Azuma, Y; Ito, Y; Suga, H; Goto, M; Banno, R; Sugimura, Y; Shiota, A; Asai, N; Takahashi, M; Oiso, Y

    2014-03-27

    Familial neurohypophysial diabetes insipidus (FNDI) characterized by progressive polyuria is mostly caused by mutations in the gene encoding neurophysin II (NPII), which is the carrier protein of the antidiuretic hormone, arginine vasopressin (AVP). Although accumulation of mutant NPII in the endoplasmic reticulum (ER) could be toxic for AVP neurons, the precise mechanisms of cell death of AVP neurons, reported in autopsy studies, remain unclear. Here, we subjected FNDI model mice to intermittent water deprivation (WD) in order to promote the phenotypes. Electron microscopic analyses demonstrated that, while aggregates are confined to a certain compartment of the ER in the AVP neurons of FNDI mice with water access ad libitum, they were scattered throughout the dilated ER lumen in the FNDI mice subjected to WD for 4 weeks. It is also demonstrated that phagophores, the autophagosome precursors, emerged in the vicinity of aggregates and engulfed the ER containing scattered aggregates. Immunohistochemical analyses revealed that expression of p62, an adapter protein between ubiquitin and autophagosome, was elicited on autophagosomal membranes in the AVP neurons, suggesting selective autophagy induction at this time point. Treatment of hypothalamic explants of green fluorescent protein (GFP)-microtubule-associated protein 1 light chain 3 (LC3) transgenic mice with an ER stressor thapsigargin increased the number of GFP-LC3 puncta, suggesting that ER stress could induce autophagosome formation in the hypothalamus of wild-type mice as well. The cytoplasm of AVP neurons in FNDI mice was occupied with vacuoles in the mice subjected to WD for 12 weeks, when 30-40% of AVP neurons are lost. Our data thus demonstrated that autophagy was induced in the AVP neurons subjected to ER stress in FNDI mice. Although autophagy should primarily be protective for neurons, it is suggested that the organelles including ER were lost over time through autophagy, leading to autophagy

  1. Dietary restriction delays aging, but not neuronal dysfunction, in Drosophila models of Alzheimer's disease

    PubMed Central

    Kerr, F.; Augustin, H.; Piper, M.D.W.; Gandy, C.; Allen, M.J.; Lovestone, S.; Partridge, L.

    2011-01-01

    Dietary restriction (DR) extends lifespan in diverse organisms and, in animal and cellular models, can delay a range of aging-related diseases including Alzheimer's disease (AD). A better understanding of the mechanisms mediating these interactions, however, may reveal novel pathways involved in AD pathogenesis, and potential targets for disease-modifying treatments and biomarkers for disease progression. Drosophila models of AD have recently been developed and, due to their short lifespan and susceptibility to genetic manipulation, we have used the fly to investigate the molecular connections among diet, aging and AD pathology. DR extended lifespan in both Arctic mutant Aβ42 and WT 4R tau over-expressing flies, but the underlying molecular pathology was not altered and neuronal dysfunction was not prevented by dietary manipulation. Our data suggest that DR may alter aging through generalised mechanisms independent of the specific pathways underlying AD pathogenesis in the fly, and hence that lifespan-extending manipulations may have varying effects on aging and functional declines in aging-related diseases. Alternatively, our analysis of the specific effects of DR on neuronal toxicity downstream of Aβ and tau pathologies with negative results may simply confirm that the neuro-protective effects of DR are upstream of the initiating events involved in the pathogenesis of AD. PMID:19969390

  2. The costs of ignoring high-order correlations in populations of model neurons.

    PubMed

    Michel, Melchi M; Jacobs, Robert A

    2006-03-01

    Investigators debate the extent to which neural populations use pair-wise and higher-order statistical dependencies among neural responses to represent information about a visual stimulus. To study this issue, three statistical decoders were used to extract the information in the responses of model neurons about the binocular disparities present in simulated pairs of left-eye and right-eye images: (1) the full joint probability decoder considered all possible statistical relations among neural responses as potentially important; (2) the dependence tree decoder also considered all possible relations as potentially important, but it approximated high-order statistical correlations using a computationally tractable procedure; and (3) the independent response decoder, which assumed that neural responses are statistically independent, meaning that all correlations should be zero and thus can be ignored. Simulation results indicate that high-order correlations among model neuron responses contain significant information about binocular disparities and that the amount of this high-order information increases rapidly as a function of neural population size. Furthermore, the results highlight the potential importance of the dependence tree decoder to neuroscientists as a powerful but still practical way of approximating high-order correlations among neural responses.

  3. 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

  4. 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.

  5. Lychee Seed Saponins Improve Cognitive Function and Prevent Neuronal Injury via Inhibiting Neuronal Apoptosis in a Rat Model of Alzheimer’s Disease

    PubMed Central

    Wang, Xiuling; Wu, Jianming; Yu, Chonglin; Tang, Yong; Liu, Jian; Chen, Haixia; Jin, Bingjin; Mei, Qibing; Cao, Shousong; Qin, Dalian

    2017-01-01

    Lychee seed is a traditional Chinese medicine and possesses many activities, including hypoglycemia, liver protection, antioxidation, antivirus, and antitumor. However, its effect on neuroprotection is still unclear. The present study investigated the effects of lychee seed saponins (LSS) on neuroprotection and associated mechanisms. We established a rat model of Alzheimer’s disease (AD) by injecting Aβ25–35 into the lateral ventricle of rats and evaluated the effect of LSS on spatial learning and memory ability via the Morris water maze. Neuronal apoptosis was analyzed by hematoxylin and eosin stain and terminal deoxynucleotidyl transferase (Tdt)-mediated dUTP nick-end labeling analysis, and mRNA expression of caspase-3 and protein expressions of Bax and Bcl-2 by reverse transcription-polymerase chain reaction (RT-PCR) and Western blotting, respectively. The results showed that LSS remarkably improved cognitive function and alleviated neuronal injury by inhibiting apoptosis in the hippocampus of AD rats. Furthermore, the mRNA expression of caspase-3 and the protein expression of Bax were downregulated, while the protein expression of Bcl-2 and the ratio of Bcl-2/Bax were increased by LSS. We demonstrate that LSS significantly improves cognitive function and prevent neuronal injury in the AD rats via regulation of the apoptosis pathway. Therefore, LSS may be developed as a nutritional supplement and sold as a drug for AD prevention and/or treatment. PMID:28165366

  6. Biochanin A protects dopaminergic neurons against lipopolysaccharide-induced damage and oxidative stress in a rat model of Parkinson's disease.

    PubMed

    Wang, Jun; He, Can; Wu, Wang-Yang; Chen, Feng; Wu, Yang-Yang; Li, Wei-Zu; Chen, Han-Qing; Yin, Yan-Yan

    2015-11-01

    Parkinson's disease (PD) is the second most common neurodegenerative disease, which is characterized by loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc). Accumulated evidences have suggested that oxidative stress is closely associated with the dopaminergic neurodegeneration of PD that can be protected by antioxidants. Biochanin A that is an O-methylated isoflavone in chickpea is investigated to explore its protective mechanism on dopaminergic neurons of the unilateral lipopolysaccharide (LPS)-injected rat. The results showed that biochanin A significantly improved the animal model's behavioral symptoms, prevented the loss of dopaminergic neurons and inhibited the deleterious microglia activation in the LPS-induced rats. Moreover, biochanin A inhibited nicotinamide adenine dinucleotide phosphate oxidase (NADPH oxidase) activation and malondialdehyde (MDA) production, increased superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities in the rat brain. These results suggested that biochanin A might be a natural candidate with protective properties on dopaminergic neurons against the PD.

  7. Astrocytes show reduced support of motor neurons with aging that is accelerated in a rodent model of ALS.

    PubMed

    Das, Melanie M; Svendsen, Clive N

    2015-02-01

    Astrocytes play a crucial role in supporting motor neurons in health and disease. However, there have been few attempts to understand how aging may influence this effect. Here, we report that rat astrocytes show an age-dependent senescence phenotype and a significant reduction in their ability to support motor neurons. In a rodent model of familial amyotrophic lateral sclerosis (ALS) overexpressing mutant superoxide dismutase 1 (SOD1), the rate of astrocytes acquiring a senescent phenotype is accelerated and they subsequently provide less support to motor neurons. This can be partially reversed by glial cell line-derived neurotrophic factor (GDNF). Replacing aging astrocytes with young ones producing GDNF may therefore have a significant survival promoting affect on aging motor neurons and those lost through diseases such as ALS.

  8. Experimental evidence and modeling studies support a synchronizing role for electrical coupling in the cat thalamic reticular neurons in vivo

    PubMed Central

    Fuentealba, Pablo; Crochet, Sylvain; Timofeev, Igor; Bazhenov, Maxim; Sejnowski, Terrence J.; Steriade, Mircea

    2010-01-01

    Thalamic reticular (RE) neurons are crucially implicated in brain rhythms. Here, we report that RE neurons of adult cats, recorded and stained intracellularly in vivo, displayed spontaneously occurring spikelets, which are characteristic of central neurons that are coupled electrotonically via gap junctions. Spikelets occurred spontaneously during spindles, an oscillation in which RE neurons play a leading role, as well as during interspindle lulls. They were significantly different from excitatory postsynaptic potentials and also distinct from fast prepotentials that are presumably dendritic spikes generated synaptically. Spikelets were strongly reduced by halothane, a blocker of gap junctions. Multi-site extracellular recordings performed before, during and after administration of halothane demonstrated a role for electrical coupling in the synchronization of spindling activity within the RE nucleus. Finally, computational models of RE neurons predicted that gap junctions between these neurons could mediate the spread of low-frequency activity at great distances. These experimental and modeling data suggest that electrotonic coupling within the RE nucleus plays an important role in the generation and synchronization of low-frequency (spindling) activities in the thalamus. PMID:15245484

  9. Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings.

    PubMed

    Pinotsis, D A; Geerts, J P; Pinto, L; FitzGerald, T H B; Litvak, V; Auksztulewicz, R; Friston, K J

    2017-02-01

    Neural models describe brain activity at different scales, ranging from single cells to whole brain networks. Here, we attempt to reconcile models operating at the microscopic (compartmental) and mesoscopic (neural mass) scales to analyse data from microelectrode recordings of intralaminar neural activity. Although these two classes of models operate at different scales, it is relatively straightforward to create neural mass models of ensemble activity that are equipped with priors obtained after fitting data generated by detailed microscopic models. This provides generative (forward) models of measured neuronal responses that retain construct validity in relation to compartmental models. We illustrate our approach using cross spectral responses obtained from V1 during a visual perception paradigm that involved optogenetic manipulation of the basal forebrain. We find that the resulting neural mass model can distinguish between activity in distinct cortical layers - both with and without optogenetic activation - and that cholinergic input appears to enhance (disinhibit) superficial layer activity relative to deep layers. This is particularly interesting from the perspective of predictive coding, where neuromodulators are thought to boost prediction errors that ascend the cortical hierarchy.

  10. 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.

  11. 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.

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

    PubMed Central

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

    2015-01-01

    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 3 h induced dose-dependent cell death with an EC50 of 3.98 μM and 3.77 μM, respectively. Also, tebufenpyrad and pyridaben (3 μM) 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

  13. 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

  14. 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.

  15. 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.

  16. Modeling the attenuation and failure of action potentials in the dendrites of hippocampal neurons.

    PubMed Central

    Migliore, M

    1996-01-01

    We modeled two different mechanisms, a shunting conductance and a slow sodium inactivation, to test whether they could modulate the active propagation of a train of action potentials in a dendritic tree. Computer simulations, using a compartmental model of a pyramidal neuron, suggest that each of these two mechanisms could account for the activity-dependent attenuation and failure of the action potentials in the dendrites during the train. Each mechanism is shown to be in good qualitative agreement with experimental findings on somatic or dendritic stimulation and on the effects of hyperpolarization. The conditions under which branch point failures can be observed, and a few experimentally testable predictions, are presented and discussed. PMID:8913580

  17. 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

  18. Estimating input parameters from intracellular recordings in the Feller neuronal model

    NASA Astrophysics Data System (ADS)

    Bibbona, Enrico; Lansky, Petr; Sirovich, Roberta

    2010-03-01

    We study the estimation of the input parameters in a Feller neuronal model from a trajectory of the membrane potential sampled at discrete times. These input parameters are identified with the drift and the infinitesimal variance of the underlying stochastic diffusion process with multiplicative noise. The state space of the process is restricted from below by an inaccessible boundary. Further, the model is characterized by the presence of an absorbing threshold, the first hitting of which determines the length of each trajectory and which constrains the state space from above. We compare, both in the presence and in the absence of the absorbing threshold, the efficiency of different known estimators. In addition, we propose an estimator for the drift term, which is proved to be more efficient than the others, at least in the explored range of the parameters. The presence of the threshold makes the estimates of the drift term biased, and two methods to correct it are proposed.

  19. 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.

  20. 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.

  1. 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

    2014-10-06

    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.

  2. 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

  3. 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.

  4. 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.

  5. Defining and Modeling Known Adverse Outcome Pathways: Domoic Acid and Neuronal Signaling as a Case Study

    SciTech Connect

    Watanabe, Karen H.; Andersen, Melvin E.; Basu, Nil; Carvan, Michael J.; Crofton, Kevin M.; King, Kerensa A.; Sunol, Cristina; Tiffany-Castiglioni, Evelyn; Schultz, Irvin R.

    2011-01-01

    An adverse outcome pathway (AOP) is a sequence of key events from a molecular-level initiating event and an ensuing cascade of steps to an adverse outcome with population level significance. To implement a predictive strategy for ecotoxicology, the multiscale nature of an AOP requires computational models to link salient processes (e.g., in chemical uptake, toxicokinetics, toxicodynamics, and population dynamics). A case study with domoic acid was used to demonstrate strategies and enable generic recommendations for developing computational models in an effort to move toward a toxicity testing paradigm focused on toxicity pathway perturbations applicable to ecological risk assessment. Domoic acid, an algal toxin with adverse effects on both wildlife and humans, is a potent agonist for kainate receptors (ionotropic glutamate receptors whose activation leads to the influx of Na+ and Ca2+). Increased Ca2+ concentrations result in neuronal excitotoxicity and cell death primarily in the hippocampus, which produces seizures, impairs learning and memory, and alters behavior in some species. Altered neuronal Ca2+ is a key process in domoic acid toxicity which can be evaluated in vitro. Further, results of these assays would be amenable to mechanistic modeling for identifying domoic acid concentrations and Ca2+ perturbations that are normal, adaptive, or clearly toxic. In vitro assays with outputs amenable to measurement in exposed populations can link in vitro to in vivo conditions, and toxicokinetic information will aid in linking in vitro results to the individual organism. Development of an AOP required an iterative process with three important outcomes: (1) a critically reviewed, stressor-specific AOP; (2) identification of key processes suitable for evaluation with in vitro assays; and (3) strategies for model development.

  6. Reinforcement Learning of Targeted Movement in a Spiking Neuronal Model of Motor Cortex

    PubMed Central

    Chadderdon, George L.; Neymotin, Samuel A.; Kerr, Cliff C.; Lytton, William W.

    2012-01-01

    Sensorimotor control has traditionally been considered from a control theory perspective, without relation to neurobiology. In contrast, here we utilized a spiking-neuron model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint “forearm” to a target. Learning was based on a reinforcement mechanism analogous to that of the dopamine system. This provided a global reward or punishment signal in response to decreasing or increasing distance from hand to target, respectively. Output was partially driven by Poisson motor babbling, creating stochastic movements that could then be shaped by learning. The virtual forearm consisted of a single segment rotated around an elbow joint, controlled by flexor and extensor muscles. The model consisted of 144 excitatory and 64 inhibitory event-based neurons, each with AMPA, NMDA, and GABA synapses. Proprioceptive cell input to this model encoded the 2 muscle lengths. Plasticity was only enabled in feedforward connections between input and output excitatory units, using spike-timing-dependent eligibility traces for synaptic credit or blame assignment. Learning resulted from a global 3-valued signal: reward (+1), no learning (0), or punishment (−1), corresponding to phasic increases, lack of change, or phasic decreases of dopaminergic cell firing, respectively. Successful learning only occurred when both reward and punishment were enabled. In this case, 5 target angles were learned successfully within 180 s of simulation time, with a median error of 8 degrees. Motor babbling allowed exploratory learning, but decreased the stability of the learned behavior, since the hand continued moving after reaching the target. Our model demonstrated that a global reinforcement signal, coupled with eligibility traces for synaptic plasticity, can train a spiking sensorimotor network to perform goal-directed motor behavior. PMID:23094042

  7. A point-process response model for spike trains from single neurons in neural circuits under optogenetic stimulation.

    PubMed

    Luo, X; Gee, S; Sohal, V; Small, D

    2016-02-10

    Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from these experiments present a statistical challenge of modeling a high-frequency point process (neuronal spikes) while the input is another high-frequency point process (light flashes). We further develop a generalized linear model approach to model the relationships between two point processes, employing additive point-process response functions. The resulting model, point-process responses for optogenetics (PRO), provides explicit nonlinear transformations to link the input point process with the output one. Such response functions may provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation. We validate and compare the PRO model using a real dataset and simulations, and our model yields a superior area-under-the-curve value as high as 93% for predicting every future spike. For our experiment on the recurrent layer V circuit in the prefrontal cortex, the PRO model provides evidence that neurons integrate their inputs in a sophisticated manner. Another use of the model is that it enables understanding how neural circuits are altered under various disease conditions and/or experimental conditions by comparing the PRO parameters.

  8. Presynaptic learning and memory with a persistent firing neuron and a habituating synapse: a model of short term persistent habituation.

    PubMed

    Ramanathan, Kiruthika; Ning, Ning; Dhanasekar, Dhiviya; Li, Guoqi; Shi, Luping; Vadakkepat, Prahlad

    2012-08-01

    Our paper explores the interaction of persistent firing axonal and presynaptic processes in the generation of short term memory for habituation. We first propose a model of a sensory neuron whose axon is able to switch between passive conduction and persistent firing states, thereby triggering short term retention to the stimulus. Then we propose a model of a habituating synapse and explore all nine of the behavioral characteristics of short term habituation in a two neuron circuit. We couple the persistent firing neuron to the habituation synapse and investigate the behavior of short term retention of habituating response. Simulations show that, depending on the amount of synaptic resources, persistent firing either results in continued habituation or maintains the response, both leading to longer recovery times. The effectiveness of the model as an element in a bio-inspired memory system is discussed.

  9. 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.

  10. 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.

  11. 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

  12. Imaging gene delivery in a mouse model of congenital neuronal ceroid lipofuscinosis.

    PubMed

    Pike, L S; Tannous, B A; Deliolanis, N C; Hsich, G; Morse, D; Tung, C-H; Sena-Esteves, M; Breakefield, X O

    2011-12-01

    Adeno-associated virus (AAV)-mediated gene replacement for lysosomal disorders have been spurred by the ability of some serotypes to efficiently transduce neurons in the brain and by the ability of lysosomal enzymes to cross-correct among cells. Here, we explored enzyme replacement therapy in a knock-out mouse model of congenital neuronal ceroid lipofuscinosis (NCL), the most severe of the NCLs in humans. The missing protease in this disorder, cathepsin D (CathD) has high levels in the central nervous system. This enzyme has the potential advantage for assessing experimental therapy in that it can be imaged using a near-infrared fluorescence (NIRF) probe activated by CathD. Injections of an AAV2/rh8 vector-encoding mouse CathD (mCathD) into both cerebral ventricles and peritoneum of newborn knock-out mice resulted in a significant increase in lifespan. Successful delivery of active CathD by the AAV2/rh8-mCathD vector was verified by NIRF imaging of mouse embryonic fibroblasts from knock-out mice in culture, as well as by ex vivo NIRF imaging of the brain and liver after gene transfer. These studies support the potential effectiveness and imaging evaluation of enzyme replacement therapy to the brain and other organs in CathD null mice via AAV-mediated gene delivery in neonatal animals.

  13. 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.

  14. Organization of left–right coordination of neuronal activity in the mammalian spinal cord: Insights from computational modelling

    PubMed Central

    Shevtsova, Natalia A; Talpalar, Adolfo E; Markin, Sergey N; Harris-Warrick, Ronald M; Kiehn, Ole; Rybak, Ilya A

    2015-01-01

    Different locomotor gaits in mammals, such as walking or galloping, are produced by coordinated activity in neuronal circuits in the spinal cord. Coordination of neuronal activity between left and right sides of the cord is provided by commissural interneurons (CINs), whose axons cross the midline. In this study, we construct and analyse two computational models of spinal locomotor circuits consisting of left and right rhythm generators interacting bilaterally via several neuronal pathways mediated by different CINs. The CIN populations incorporated in the models include the genetically identified inhibitory (V0D) and excitatory (V0V) subtypes of V0 CINs and excitatory V3 CINs. The model also includes the ipsilaterally projecting excitatory V2a interneurons mediating excitatory drive to the V0V CINs. The proposed network architectures and CIN connectivity allow the models to closely reproduce and suggest mechanistic explanations for several experimental observations. These phenomena include: different speed-dependent contributions of V0D and V0V CINs and V2a interneurons to left–right alternation of neural activity, switching gaits between the left–right alternating walking-like activity and the left–right synchronous hopping-like pattern in mutants lacking specific neuron classes, and speed-dependent asymmetric changes of flexor and extensor phase durations. The models provide insights into the architecture of spinal network and the organization of parallel inhibitory and excitatory CIN pathways and suggest explanations for how these pathways maintain alternating and synchronous gaits at different locomotor speeds. The models propose testable predictions about the neural organization and operation of mammalian locomotor circuits. Key points Coordination of neuronal activity between left and right sides of the mammalian spinal cord is provided by several sets of commissural interneurons (CINs) whose axons cross the midline. Genetically identified inhibitory V

  15. Dual sensitivity of inferior colliculus neurons to ITD in the envelopes of high-frequency sounds: experimental and modeling study

    PubMed Central

    Wang, Le; Devore, Sasha; Delgutte, Bertrand

    2013-01-01

    Human listeners are sensitive to interaural time differences (ITDs) in the envelopes of sounds, which can serve as a cue for sound localization. Many high-frequency neurons in the mammalian inferior colliculus (IC) are sensitive to envelope-ITDs of sinusoidally amplitude-modulated (SAM) sounds. Typically, envelope-ITD-sensitive IC neurons exhibit either peak-type sensitivity, discharging maximally at the same delay across frequencies, or trough-type sensitivity, discharging minimally at the same delay across frequencies, consistent with responses observed at the primary site of binaural interaction in the medial and lateral superior olives (MSO and LSO), respectively. However, some high-frequency IC neurons exhibit dual types of envelope-ITD sensitivity in their responses to SAM tones, that is, they exhibit peak-type sensitivity at some modulation frequencies and trough-type sensitivity at other frequencies. Here we show that high-frequency IC neurons in the unanesthetized rabbit can also exhibit dual types of envelope-ITD sensitivity in their responses to SAM noise. Such complex responses to SAM stimuli could be achieved by convergent inputs from MSO and LSO onto single IC neurons. We test this hypothesis by implementing a physiologically explicit, computational model of the binaural pathway. Specifically, we examined envelope-ITD sensitivity of a simple model IC neuron that receives convergent inputs from MSO and LSO model neurons. We show that dual envelope-ITD sensitivity emerges in the IC when convergent MSO and LSO inputs are differentially tuned for modulation frequency. PMID:24155013

  16. Time-course of neuronal death in the mouse pilocarpine model of chronic epilepsy using Fluoro-Jade C staining.

    PubMed

    Wang, Lian; Liu, Yong-Hong; Huang, Yuan-Gui; Chen, Liang-Wei

    2008-11-19

    Epilepsy is a serious neurological disorder in human beings and the long-term pathological events remain largely obscure. We are interested in elucidating long-term brain injury that may occur in the temporal lobe epilepsy, and time-course of neuronal death was examined in a mouse pilocarpine model of chronic epilepsy by Fluoro-Jade C (FJC) dye that can specifically stain the degenerative neurons in the central nervous system. The FJC stain combined with immunohistochemistry to neuronal nuclear specific protein revealed that pilocarpine-induced status epilepticus (SE) resulted in massive degenerative death of neuronal cells in brains with their dense distribution in the cerebral cortex and hippocampus. The FJC-positive degenerating neurons, most of them also expressed apoptosis signaling molecules such as caspase-9 and activated caspase-3, occurred at 4h, increased into peak levels at 12h-3d, and then gradually went down at 7d-14d after onset of SE. More interestingly, a large percentage (about 88%) of FJC-positive degenerative neurons were GABAergic as indicated with their immunoreactivity to glutamic acid decarboxylase-67, implying that inhibitory function of GABAergic neural system might by seriously damaged in brains subject to SE attack in this mouse pilocarpine model. Taken together with previous studies, time-course of degenerative neurons in the mouse pilocarpine model by Fluoro-Jade C staining further benefits understanding of long-term brain pathological changes and recurrent seizure mechanism, and may also result in finding the most suitable time-window in therapeutic manipulation of the chronic epilepsy in human beings.

  17. 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

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

    PubMed Central

    Andrew, David

    2009-01-01

    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°C vs. 46.7 ± 2.6°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. PMID:19289544

  19. Faithful SGCE imprinting in iPSC-derived cortical neurons: an endogenous cellular model of myoclonus-dystonia

    PubMed Central

    Grütz, Karen; Seibler, Philip; Weissbach, Anne; Lohmann, Katja; Carlisle, Francesca A.; Blake, Derek J.; Westenberger, Ana; Klein, Christine; Grünewald, Anne

    2017-01-01

    In neuropathology research, induced pluripotent stem cell (iPSC)-derived neurons are considered a tool closely resembling the patient brain. Albeit in respect to epigenetics, this concept has been challenged. We generated iPSC-derived cortical neurons from myoclonus-dystonia patients with mutations (W100G and R102X) in the maternally imprinted ε-sarcoglycan (SGCE) gene and analysed properties such as imprinting, mRNA and protein expression. Comparison of the promoter during reprogramming and differentiation showed tissue-independent differential methylation. DNA sequencing with methylation-specific primers and cDNA analysis in patient neurons indicated selective expression of the mutated paternal SGCE allele. While fibroblasts only expressed the ubiquitous mRNA isoform, brain-specific SGCE mRNA and ε-sarcoglycan protein were detected in iPSC-derived control neurons. However, neuronal protein levels were reduced in both mutants. Our phenotypic characterization highlights the suitability of iPSC-derived cortical neurons with SGCE mutations for myoclonus-dystonia research and, in more general terms, prompts the use of iPSC-derived cellular models to study epigenetic mechanisms impacting on health and disease. PMID:28155872

  20. A spatially resolved network spike in model neuronal cultures reveals nucleation centers, circular traveling waves and drifting spiral waves

    NASA Astrophysics Data System (ADS)

    Paraskevov, A. V.; Zendrikov, D. K.

    2017-04-01

    We show that in model neuronal cultures, where the probability of interneuronal connection formation decreases exponentially with increasing distance between the neurons, there exists a small number of spatial nucleation centers of a network spike, from where the synchronous spiking activity starts propagating in the network typically in the form of circular traveling waves. The number of nucleation centers and their spatial locations are unique and unchanged for a given realization of neuronal network but are different for different networks. In contrast, if the probability of interneuronal connection formation is independent of the distance between neurons, then the nucleation centers do not arise and the synchronization of spiking activity during a network spike occurs spatially uniform throughout the network. Therefore one can conclude that spatial proximity of connections between neurons is important for the formation of nucleation centers. It is also shown that fluctuations of the spatial density of neurons at their random homogeneous distribution typical for the experiments in vitro do not determine the locations of the nucleation centers. The simulation results are qualitatively consistent with the experimental observations.

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

    PubMed Central

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

    2011-01-01

    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

  2. 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.

  3. 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.

  4. Alterations in the motor neuron-Renshaw cell circuit in the Sod1G93A mouse model

    PubMed Central

    Wootz, Hanna; FitzSimons-Kantamneni, Eileen; Larhammar, Martin; Rotterman, Travis M.; Enjin, Anders; Patra, Kalicharan; Andre, Elodie; van Zundert, Brigitte; Kullander, Klas; Alvarez, Francisco J.

    2012-01-01

    Motor neurons become hyperexcitable during progression of amyotrophic lateral sclerosis (ALS). This abnormal firing behavior has been explained by changes in their membrane properties, but more recently it has been suggested that changes in premotor circuits may also contribute to this abnormal activity. The specific circuits that may be altered during development of ALS have not been investigated. Here we examined the Renshaw cell recurrent circuit that exerts inhibitory feedback control on motor neuron firing. Using two markers for Renshaw cells (calbindin and Chrna2 , cholinergic nicotinic receptor subunit alpha2), two general markers for motor neurons (NeuN and VAChT, vesicular acethylcholine transporter ) and two markers for fast motor neurons (Chondrolectin and Calca, calcitonin-related polypeptide alpha), we analyzed the survival and connectivity of these cells during disease progression in the Sod1G93A mouse model. Most calbindin-immunoreactive (IR) Renshaw cells survive to end-stage but downregulate postsynaptic Chrna2 in presymptomatic animals. In motor neurons, some markers are downregulated early (NeuN, VAChT, Chondrolectin) and others at end-stage(Calca). Early downregulation of presynaptic VAChT and Chrna2 was correlated with disconnection from Renshaw cells as well as major structural abnormalities of motor axon synapses inside the spinal cord. Renshaw cell synapses on motor neurons underwent more complex changes, including transitional sprouting preferentially over remaining NeuN-IR motor neurons. We conclude that the loss of presynaptic motor axon input on Renshaw cells occurs at early stages of ALS and disconnects the recurrent inhibitory circuit, presumably resulting in a diminished control of motor neuron firing. PMID:23172249

  5. Th17 Cells Induce Dopaminergic Neuronal Death via LFA-1/ICAM-1 Interaction in a Mouse Model of Parkinson's Disease.

    PubMed

    Liu, Zhan; Huang, Yan; Cao, Bei-Bei; Qiu, Yi-Hua; Peng, Yu-Ping

    2016-11-14

    T helper (Th)17 cells, a subset of CD4(+) T lymphocytes, have strong pro-inflammatory property and appear to be essential in the pathogenesis of many inflammatory diseases. However, the involvement of Th17 cells in Parkinson's disease (PD) that is characterized by a progressive degeneration of dopaminergic (DAergic) neurons in the nigrostriatal system is unclear. Here, we aimed to demonstrate that Th17 cells infiltrate into the brain parenchyma and induce neuroinflammation and DAergic neuronal death in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)- or 1-methyl-4-phenylpyridinium (MPP(+))-induced PD models. Blood-brain barrier (BBB) disruption in the substantia nigra (SN) was assessed by the signal of FITC-labeled albumin that was injected into blood circulation via the ascending aorta. Live cell imaging system was used to observe a direct contact of Th17 cells with neurons by staining these cells using the two adhesion molecules, leukocyte function-associated antigen (LFA)-1 and intercellular adhesion molecule (ICAM)-1, respectively. Th17 cells invaded into the SN where BBB was disrupted in MPTP-induced PD mice. Th17 cells exacerbated DAergic neuronal loss and pro-inflammatory/neurotrophic factor disorders in MPP(+)-treated ventral mesencephalic (VM) cell cultures. A direct contact of LFA-1-stained Th17 cells with ICAM-1-stained VM neurons was dynamically captured. Either blocking LFA-1 in Th17 cells or blocking ICAM-1 in VM neurons with neutralizing antibodies abolished Th17-induced DAergic neuronal death. These results establish that Th17 cells infiltrate into the brain parenchyma of PD mice through lesioned BBB and exert neurotoxic property by promoting glial activation and importantly by a direct damage to neurons depending on LFA-1/ICAM-1 interaction.

  6. 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

  7. A Codimension-2 Bifurcation Controlling Endogenous Bursting Activity and Pulse-Triggered Responses of a Neuron Model

    PubMed Central

    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

  8. The maintained discharge of neurons in the cat lateral geniculate nucleus: spectral analysis and computational modeling.

    PubMed

    Mukherjee, P; Kaplan, E

    1998-01-01

    The maintained discharge of neurons along the early visual pathway in mammals constitutes the "noise" from which the visual signal must be discriminated. The statistics of this background noise in cat retinal ganglion cells (RGCs) have been shown to conform to that of a gamma-distributed renewal process (Kuffler et al., 1957; Barlow & Levick, 1969), and power spectrum analysis reveals that this property allows for low noise levels at the temporal-frequency range (0-10 Hz) most important for visual performance (Troy & Robson, 1992). In this study, we compare the statistics of the maintained discharge of cat lateral geniculate neurons with those of its RGC input by simultaneous recordings of spikes and S-potentials in single relay cells of the cat lateral geniculate nucleus (LGN). We demonstrate that, during primarily tonic spiking activity, the LGN maintained discharge preserves the renewal process statistics of its RGC input and also generates relatively little noise at the temporal frequencies important for vision. However, during burst spiking activity, the renewal process model breaks down and increased noise is generated at 2-10 Hz. This suggests that optimization of the visual signal/noise ratio is not a prime consideration in the behavioral states associated with bursting activity in the LGN. The occurrence of burst spikes in LGN relay cells is dependent on the activity of T-type calcium channels in their plasma membranes (Jahnsen & Llinas, 1984a,b). We show that a computational model of LGN relay cells that incorporates T-channel kinetics (Mukherjee & Kaplan, 1995) can correctly simulate LGN maintained discharge statistics during both tonic and bursty firing conditions, and indicates an essential role for this ion channel in determining the dynamic noise properties of the LGN. We also use the computational model to predict how the burstiness of the LGN maintained discharge is affected by the statistics of its RGC input.

  9. 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.

  10. 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

    2014-05-07

    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.

  11. 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

  12. 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 propo