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Sample records for cd99 inhibits neural

  1. CD99 regulates neural differentiation of Ewing sarcoma cells through miR-34a-Notch-mediated control of NF-κB signaling.

    Science.gov (United States)

    Ventura, S; Aryee, D N T; Felicetti, F; De Feo, A; Mancarella, C; Manara, M C; Picci, P; Colombo, M P; Kovar, H; Carè, A; Scotlandi, K

    2016-07-28

    Sarcomas are mesenchymal tumors characterized by blocked differentiation process. In Ewing sarcoma (EWS) both CD99 and EWS-FLI1 concur to oncogenesis and inhibition of differentiation. Here, we demonstrate that uncoupling CD99 from EWS-FLI1 by silencing the former, nuclear factor-κB (NF-κB) signaling is inhibited and the neural differentiation program is re-established. NF-κB inhibition passes through miR-34a-mediated repression of Notch pathway. CD99 counteracts EWS-FLI1 in controlling NF-κB signaling through the miR-34a, which is increased and secreted into exosomes released by CD99-silenced EWS cells. Delivery of exosomes from CD99-silenced cells was sufficient to induce neural differentiation in recipient EWS cells through miR-34a inhibition of Notch-NF-κB signaling. Notably, even the partial delivery of CD99 small interfering RNA may have a broad effect on the entire tumor cell population owing to the spread operated by their miR-34a-enriched exosomes, a feature opening to a new therapeutic option. PMID:26616853

  2. CD99 and CD99L2 act at the same site as, but independently of, PECAM-1 during leukocyte diapedesis.

    Science.gov (United States)

    Bixel, M Gabriele; Li, Hang; Petri, Bjoern; Khandoga, Alexander G; Khandoga, Andrej; Zarbock, Alexander; Wolburg-Buchholz, Karen; Wolburg, Hartwig; Sorokin, Lydia; Zeuschner, Dagmar; Maerz, Sigrid; Butz, Stefan; Krombach, Fritz; Vestweber, Dietmar

    2010-08-19

    Leukocyte extravasation depends on various adhesion receptors at endothelial cell contacts. Here we have analyzed how mouse CD99 and CD99L2 cooperate with PECAM-1. We found that antibodies against mouse CD99 and PECAM-1 trap neutrophils between endothelial cells in in vitro transmigration assays. A sequential function, as has been suggested for human PECAM-1 and CD99, could not be demonstrated. In contrast to these in vitro results, blocking CD99 or CD99L2 or gene disruption of PECAM-1 trapped neutrophils in vivo between endothelial cells and the underlying basement membrane as revealed by electron microscopy and by 3-dimensional confocal fluorescence microscopy in the inflamed cremaster tissue. Leukocyte extravasation was inhibited in interleukin-1beta-inflamed peritoneum and in the cremaster by PECAM-1 gene disruption and was further attenuated by blocking antibodies against CD99 and CD99L2. In addition, CD99 and CD99L2 were required for leukocyte extravasation in the cremaster after stimulation with tumor necrosis factor-alpha, where the need for PECAM-1 is known to be bypassed. We conclude that CD99 and CD99L2 act independently of PECAM-1 in leukocyte extravasation and cooperate in an independent way to help neutrophils overcome the endothelial basement membrane. PMID:20479283

  3. SEPTIN2 and STATHMIN Regulate CD99-Mediated Cellular Differentiation in Hodgkin's Lymphoma.

    Directory of Open Access Journals (Sweden)

    Wenjing Jian

    Full Text Available Hodgkin's lymphoma (HL is a lymphoid neoplasm characterized by Hodgkin's and Reed-Sternberg (H/RS cells, which is regulated by CD99. We previously reported that CD99 downregulation led to the transformation of murine B lymphoma cells (A20 into cells with an H/RS phenotype, while CD99 upregulation induced differentiation of classical Hodgkin's lymphoma (cHL cells (L428 into terminal B-cells. However, the molecular mechanism remains unclear. In this study, using fluorescence two-dimensional differential in-gel electrophoresis and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS, we have analyzed the alteration of protein expression following CD99 upregulation in L428 cells as well as downregulation of mouse CD99 antigen-like 2 (mCD99L2 in A20 cells. Bioinformatics analysis showed that SEPTIN2 and STATHMIN, which are cytoskeleton proteins, were significantly differentially expressed, and chosen for further validation and functional analysis. Differential expression of SEPTIN2 was found in both models and was inversely correlated with CD99 expression. STATHMIN was identified in the A20 cell line model and its expression was positively correlated with that of CD99. Importantly, silencing of SEPTIN2 with siRNA substantially altered the cellular cytoskeleton in L428 cells. The downregulation of STATHMIN by siRNA promoted the differentiation of H/RS cells toward terminal B-cells. These results suggest that SEPTIN2-mediated cytoskeletal rearrangement and STATHMIN-mediated differentiation may contribute to changes in cell morphology and differentiation of H/RS cells with CD99 upregulation in HL.

  4. Analysis of CD99 expression in chondroblastoma by immunohistochemistry%CD99在软骨母细胞瘤中的表达及其意义

    Institute of Scientific and Technical Information of China (English)

    螘国铮; 丁敏; 王晓秋; 邢晓皖; 吴红阳

    2004-01-01

    目的探讨CD99在软骨母细胞瘤的表达.方法应用免疫组织化学S-P法,观察12例软骨母细胞瘤的病理形态.结果 12例软骨母细胞瘤中9例CD99阳性,在无基质的软骨母细胞和部分网状基质内软骨母细胞处表达,基质明显区和钙盐沉积处的软骨母细胞和软骨细胞均阴性.S-100蛋白、Vim、NSE弥漫强阳性,多核巨细胞CD68阳性.结论 CD99对软骨母细胞瘤阳性无特异性诊断价值.联合应用CD99、S-100蛋白和Vim等标记,进一步说明软骨母细胞瘤是由胚胎性软骨母细胞发生.

  5. CD99 and CD106 (VCAM—1) in human testis

    Institute of Scientific and Technical Information of China (English)

    VeraE; LaatoM

    2002-01-01

    Aim:The expression of the cytokines Il-2,IL-6,IL-10,IFN-γ and TNF-α and the adhesion proteins CD99 and CD106 was studied in the human testis at the protein level.Methods:The expression of the cytokines and the adhesion proteins was assessed using immunohistochemistry and immunoblotting.Results:None of the cytokines studied was present in the human testis,but CD99 and CD106(VCAM-1) strongly were expressed in all the testes investigated.CD99 was present in the interstitial tissue of the human testis as well as in the Sertoli cells.The identity of the CD99+ interstitial cells is unclear.CD106(VCAM-1) was present in Leydig cells as well as the basal parts of the Sertoli cells in the seminiferous tubules.In immunoblotting,CD99 was demonstrated at molecular ratios of 46-57(kD).This is a novel isoform of the molecule.Conclusion:The human testis produces both CD99 and CD106 and as CD106 mediates cell binding to lymphocytes,it is possible that the human Leydig cells adhere to lymphocytes like the rodent Leydig cells.

  6. Stat3 inhibition in neural lineage cells.

    Science.gov (United States)

    Chiba, Tomohiro; Mack, Laura; Delis, Natalia; Brill, Boris; Groner, Bernd

    2012-06-01

    Abstract Deregulation of signal transducer and activator of transcription 3 (Stat3) is attracting attentions in neurological disorders of elderly populations, e.g., Stat3 is inactivated in hippocampal neurons of Alzheimer's disease (AD) brains, whereas it is often constitutively activated in glioblastoma multiforme (GBM), correlating with poor prognosis. Stat3-inhibiting drugs have been intensively developed for chemotherapy based on the fact that GBM, in many cases, are "addicted" to Stat3 activation. Stat3 inhibitors, however, potentially have unfavorable side effects on postmitotic neurons, normal permanent residents in the central nervous system. It is, therefore, of great importance to address detailed cellular responses of neural lineage cells including normal neurons, astrocytes, and neuronal/glial cancer cell lines to several classes of Stat3 inhibitors focusing on their effective concentrations. Here, we picked up five human and mouse cancer cell lines (Neuro-2a and SH-SY5Y neuroblastoma cell lines and Tu-9648, U-87MG, and U-373MG glioblastoma cell lines) and treated with various Stat3 inhibitors. Among them, Stattic, FLLL31, and resveratrol potently suppressed P-Stat3 and cell viability in all the tested cell lines. Stat3 knockdown or expression of dominant-negative Stat3 further sensitized cells to the inhibitors. Expression of familial AD-related mutant amyloid precursor protein sensitized neuronal cells, not glial cells, to Stat3 inhibitors by reducing P-Stat3 levels. Primary neurons and astrocytes also responded to Stat3 inhibitors with similar sensitivities to those observed in cancer cell lines. Thus, Stat3 inhibitors should be carefully targeted to GBM cells to avoid potential neurotoxicity leading to AD-like neuropsychiatric dysfunctions. PMID:25436682

  7. Neural correlates of central inhibition during physical fatigue.

    Directory of Open Access Journals (Sweden)

    Masaaki Tanaka

    Full Text Available Central inhibition plays a pivotal role in determining physical performance during physical fatigue. Classical conditioning of central inhibition is believed to be associated with the pathophysiology of chronic fatigue. We tried to determine whether classical conditioning of central inhibition can really occur and to clarify the neural mechanisms of central inhibition related to classical conditioning during physical fatigue using magnetoencephalography (MEG. Eight right-handed volunteers participated in this study. We used metronome sounds as conditioned stimuli and maximum handgrip trials as unconditioned stimuli to cause central inhibition. Participants underwent MEG recording during imagery of maximum grips of the right hand guided by metronome sounds for 10 min. Thereafter, fatigue-inducing maximum handgrip trials were performed for 10 min; the metronome sounds were started 5 min after the beginning of the handgrip trials. The next day, neural activities during imagery of maximum grips of the right hand guided by metronome sounds were measured for 10 min. Levels of fatigue sensation and sympathetic nerve activity on the second day were significantly higher relative to those of the first day. Equivalent current dipoles (ECDs in the posterior cingulated cortex (PCC, with latencies of approximately 460 ms, were observed in all the participants on the second day, although ECDs were not identified in any of the participants on the first day. We demonstrated that classical conditioning of central inhibition can occur and that the PCC is involved in the neural substrates of central inhibition related to classical conditioning during physical fatigue.

  8. Infrared neural stimulation (INS) inhibits electrically evoked neural responses in the deaf white cat

    Science.gov (United States)

    Richter, Claus-Peter; Rajguru, Suhrud M.; Robinson, Alan; Young, Hunter K.

    2014-03-01

    Infrared neural stimulation (INS) has been used in the past to evoke neural activity from hearing and partially deaf animals. All the responses were excitatory. In Aplysia californica, Duke and coworkers demonstrated that INS also inhibits neural responses [1], which similar observations were made in the vestibular system [2, 3]. In deaf white cats that have cochleae with largely reduced spiral ganglion neuron counts and a significant degeneration of the organ of Corti, no cochlear compound action potentials could be observed during INS alone. However, the combined electrical and optical stimulation demonstrated inhibitory responses during irradiation with infrared light.

  9. Intimate Partner Violence PTSD and Neural Correlates of Inhibition.

    Science.gov (United States)

    Aupperle, Robin L; Stillman, Ashley N; Simmons, Alan N; Flagan, Taru; Allard, Carolyn B; Thorp, Steven R; Norman, Sonya B; Paulus, Martin P; Stein, Murray B

    2016-02-01

    Posttraumatic stress disorder (PTSD) has been linked to deficits in response inhibition, and neuroimaging research suggests this may be due to differences in prefrontal cortex recruitment. The current study examined relationships between PTSD from intimate partner violence (IPV) and neural responses during inhibition. There were 10 women with PTSD from IPV and 12 female control subjects without trauma history who completed the stop signal task during functional magnetic resonance imaging. Linear mixed models were used to investigate group differences in activation (stop-nonstop and hard-easy trials). Those with PTSD exhibited greater differential activation to stop-nonstop trials in the right dorsolateral prefrontal cortex and the anterior insula and less differential activation in several default mode regions (d = 1.12-1.22). Subjects with PTSD exhibited less differential activation to hard-easy trials in the lateral frontal and the anterior insula regions (driven by less activation to hard trials) and several default mode regions (i.e., medial prefrontal cortex, posterior cingulate; driven by greater activation to easy trials; d = 1.23-1.76). PTSD was associated with difficulties disengaging default mode regions during cognitive tasks with relatively low cognitive demand, as well as difficulties modulating executive control and salience processing regions with increasing cognitive demand. Together, these results suggest that PTSD may relate to decreased neural flexibility during inhibition. PMID:26748991

  10. PTEN inhibition and axon regeneration and neural repair

    Institute of Scientific and Technical Information of China (English)

    Yosuke Ohtake; Umar Hayat; Shuxin Li

    2015-01-01

    The intrinsic growth ability of all the neurons declines during development although some may grow better than others. Numerous intracellular signaling proteins and transcription factors have been shown to regulate the intrinsic growth capacity in mature neurons. Among them, PI3 kinase/Akt pathway is important for controlling axon elongation. As a negative regulator of this pathway, the tumor suppressor phosphatase and tensin homolog (PTEN) appears critical to con-trol the regenerative ability of young and adult neurons. This review will focus on recent research progress in axon regeneration and neural repair by PTEN inhibition and therapeutic potential of blocking this phosphatase for neurological disorders. Inhibition of PTEN by deletion in con-ditional knockout mice, knockdown by short-hairpin RNA, or blockade by pharmacological approaches, including administration of selective PTEN antagonist peptides, stimulates various degrees of axon regrowth in juvenile or adult rodents with central nervous system injuries. Im-portantly, post-injury PTEN suppression could enhance axonal growth and functional recovery in adult central nervous system after injury.

  11. Neural correlates of intentional and stimulus-driven inhibition: a comparison

    OpenAIRE

    Schel, Margot A.; Kühn, Simone; Brass, Marcel; Haggard, Patrick; Ridderinkhof, K Richard; Crone, Eveline A.

    2014-01-01

    People can inhibit an action because of an instruction by an external stimulus, or because of their own internal decision. The similarities and differences between these two forms of inhibition are not well understood. Therefore, in the present study the neural correlates of intentional and stimulus-driven inhibition were tested in the same subjects. Participants performed two inhibition tasks while lying in the scanner: the marble task in which they had to choose for themselves between inten...

  12. Neural correlates of intentional and stimulus-driven inhibition: A comparison

    OpenAIRE

    Schel, Margot A.; Simone eKühn; Marcel eBrass; Patrick eHaggard; K Richard eRidderinkhof; Crone, Eveline A.

    2014-01-01

    People can inhibit an action because of an instruction by an external stimulus, or because of their own internal decision. The similarities and differences between these two forms of inhibition are not well understood. Therefore, in the present study the neural correlates of intentional and stimulus-driven inhibition were tested in the same subjects. Participants performed two inhibition tasks while lying in the scanner: the marble task in which they had to choose for themselves between inten...

  13. Neural correlates of intentional and stimulus-driven inhibition: a comparison

    NARCIS (Netherlands)

    M.A. Schel; S. Kühn; M. Brass; P. Haggard; K.R. Ridderinkhof; E.A. Crone

    2014-01-01

    People can inhibit an action because of an instruction by an external stimulus, or because of their own internal decision. The similarities and differences between these two forms of inhibition are not well understood. Therefore, in the present study the neural correlates of intentional and stimulus

  14. Solid-pseudopapillary neoplasm of the pancreas: A classical presentation with unique paranuclear dot like immunostaining with CD 99.

    Science.gov (United States)

    Nair Anila, Kunjulekshmi Amma Raveendran; Nayak, Nileena; Muralee, Madhu; Venugopal, Bhaskaran Pillai; Mony, Rari P

    2015-01-01

    A 32-year-old lady presented with a history of abdominal pain and upper abdominal discomfort of 3 months duration. Her imaging studies done at a local hospital showed a solid-cystic mass involving head of the pancreas. The patient was referred to our surgical oncology department. On examination, there was a nontender mass in the epigastrium. An ultrasound scan guided fine-needle aspiration (FNA) was done which was showing classical features of solid-pseudo papillary neoplasm of the pancreas. With this preoperative diagnosis patient was taken up for surgery. Per operatively, there was a solid-cystic mass in the head of the pancreas. Pancreaticoduodenectomy was done. Histopathology and immunohistochemistry (IHC) confirmed the diagnosis of solid-pseudo papillary neoplasm of the pancreas. Apart from the routine IHC panel, CD 99 immunostain was also done which demonstrated the characteristic paranuclear dot-like staining observed in previous studies in the literature.

  15. Downregulation of CD99 and upregulation of human leukocyte antigen class II promote tumor aggravation and poor survival in patients with osteosarcomas

    OpenAIRE

    Zhou Q; Xu J; Zhao J; Zhang S; Pan W

    2014-01-01

    Quan Zhou,* Jin Xu,* Jiali Zhao, Shaoxian Zhang, Wei PanDepartment of Orthopaedics, the second Hospital of Huai'an city Affiliated to Xuzhou Medical College and the second Hospital of Huai'an city, Huai'an, People's Republic of China *These authors contributed equally to this workBackground: CD99 is involved in the intracellular transport of human leukocyte antigen class II (HLA-II) protein. The aim of this study was to clarify the clinical value of CD99 and HL...

  16. Characterization of the feeding inhibition and neural activation produced by dorsomedial hypothalamic cholecystokinin administration

    OpenAIRE

    Chen, Jie; Scott, Karen A.; Zhao, Zhengyan; Moran, Timothy H.; BI, Sheng

    2008-01-01

    Within the dorsomedial hypothalamus (DMH), cholecystokinin (CCK) has been proposed to modulate neuropeptide Y (NPY) signaling to affect food intake. However, the neural circuitry underlying the actions of this CCK-NPY signaling system in the controls of food intake has yet to be determined. We sought to characterize the feeding inhibition and brain neural activation produced by CCK administration into the DMH of rats. We determined the time course of feeding inhibitory effects of exogenous DM...

  17. The neural basis of inhibition in cognitive control.

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    Aron, Adam R

    2007-06-01

    The concept of "inhibition" is widely used in synaptic, circuit, and systems neuroscience, where it has a clear meaning because it is clearly observable. The concept is also ubiquitous in psychology. One common use is to connote an active/willed process underlying cognitive control. Many authors claim that subjects execute cognitive control over unwanted stimuli, task sets, responses, memories, and emotions by inhibiting them, and that frontal lobe damage induces distractibility, impulsivity, and perseveration because of damage to an inhibitory mechanism. However, with the exception of the motor domain, the notion of an active inhibitory process underlying cognitive control has been heavily challenged. Alternative explanations have been provided that explain cognitive control without recourse to inhibition as concept, mechanism, or theory. This article examines the role that neuroscience can play when examining whether the psychological concept of active inhibition can be meaningfully applied in cognitive control research.

  18. ROCK inhibition enhances neurite outgrowth in neural stem cells by upregulating YAP expressionin vitro

    Institute of Scientific and Technical Information of China (English)

    Xu-feng Jia; Fei Ye; Yan-bo Wang; Da-xiong Feng

    2016-01-01

    Spontaneous axonal regeneration of neurons does not occur after spinal cord injury because of inhibition by myelin and other inhibitory factors. Studies have demonstrated that blocking the Rho/Rho-kinase (ROCK) pathway can promote neurite outgrowth in spinal cord injury models. In the present study, we investigated neurite outgrowth and neuronal differentiation in neural stem cells from the mouse subventricular zone after inhibition of ROCK in vitro. Inhibition of ROCK with Y-27632 increased neurite length, enhanced neuronal differentiation, and upregulated the expression of two major signaling pathway effectors, phospho-Akt and phospho-mitogen-activated protein kinase, and the Hippo pathway effector YAP. These results suggest that inhibition of ROCK mediates neurite outgrowth in neural stem cells by activating the Hippo signaling pathway.

  19. ROCK inhibition enhances neurite outgrowth in neural stem cells by upregulating YAP expression in vitro

    Science.gov (United States)

    Jia, Xu-feng; Ye, Fei; Wang, Yan-bo; Feng, Da-xiong

    2016-01-01

    Spontaneous axonal regeneration of neurons does not occur after spinal cord injury because of inhibition by myelin and other inhibitory factors. Studies have demonstrated that blocking the Rho/Rho-kinase (ROCK) pathway can promote neurite outgrowth in spinal cord injury models. In the present study, we investigated neurite outgrowth and neuronal differentiation in neural stem cells from the mouse subventricular zone after inhibition of ROCK in vitro. Inhibition of ROCK with Y-27632 increased neurite length, enhanced neuronal differentiation, and upregulated the expression of two major signaling pathway effectors, phospho-Akt and phospho-mitogen-activated protein kinase, and the Hippo pathway effector YAP. These results suggest that inhibition of ROCK mediates neurite outgrowth in neural stem cells by activating the Hippo signaling pathway. PMID:27482229

  20. Neural mechanisms of impaired fear inhibition in posttraumatic stress disorder

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    Tanja eJovanovic

    2011-07-01

    Full Text Available Posttraumatic stress disorder (PTSD can develop in some individuals who are exposed to an event that causes extreme fear, horror, or helplessness (APA, 1994. PTSD is a complex and heterogeneous disorder, which is often co-morbid with depression, substance abuse, and anxiety disorders such as panic or social phobia. Given this complexity, progress in the field can be greatly enhanced by focusing on phenotypes that are more proximal to the neurobiology of the disorder. Such neurobiological intermediate phenotypes can provide investigative tools to increase our understanding of the roots of the disorder and develop better prevention or intervention programs. In the present paper, we argue that the inhibition of fear responses is an intermediate phenotype that is related to both the neurocircuitry associated with the disorder, and is linked to its clinical symptoms. An advantage of focusing on fear inhibition is that the neurobiology of fear has been well investigated in animal models providing the necessary groundwork in understanding alterations. Furthermore, because many paradigms can be tested across species, fear inhibition is an ideal translational tool. Here we review both the behavioral tests and measures of fear inhibition and the related neurocircuitry in neuroimaging studies with both healthy and clinical samples.

  1. Modular neural network and classical reinforcement learning for autonomous robot navigation: inhibiting undesirable behaviors

    OpenAIRE

    Antonelo, Eric; Baerveldt, Albert-Jan; Rögnvaldsson, Thorsteinn; Figueiredo, Mauricio

    2006-01-01

    Classical reinforcement learning mechanisms and a modular neural network are unified for conceiving an intelligent autonomous system for mobile robot navigation. The conception aims at inhibiting two common navigation deficiencies: generation of unsuitable cyclic trajectories and ineffectiveness in risky configurations. Distinct design apparatuses are considered for tackling these navigation difficulties, for instance: 1) neuron parameter for memorizing neuron activities (also functioning as ...

  2. Neural correlates of inhibition and contextual cue processing related to treatment response in PTSD

    NARCIS (Netherlands)

    van Rooij, Sanne J H; Geuze, Elbert; Kennis, Mitzy; Rademaker, Arthur R; Vink, Matthijs

    2015-01-01

    Thirty to fifty percent of posttraumatic stress disorder (PTSD) patients do not respond to treatment. Understanding the neural mechanisms underlying treatment response could contribute to improve response rates. PTSD is often associated with decreased inhibition of fear responses in a safe environme

  3. Comparative sensitivity of human and rat neural cultures to chemical-induced inhibition of neurite outgrowth

    International Nuclear Information System (INIS)

    There is a need for rapid, efficient and cost-effective alternatives to traditional in vivo developmental neurotoxicity testing. In vitro cell culture models can recapitulate many of the key cellular processes of nervous system development, including neurite outgrowth, and may be used as screening tools to identify potential developmental neurotoxicants. The present study compared primary rat cortical cultures and human embryonic stem cell-derived neural cultures in terms of: 1) reproducibility of high content image analysis based neurite outgrowth measurements, 2) dynamic range of neurite outgrowth measurements and 3) sensitivity to chemicals which have been shown to inhibit neurite outgrowth. There was a large increase in neurite outgrowth between 2 and 24 h in both rat and human cultures. Image analysis data collected across multiple cultures demonstrated that neurite outgrowth measurements in rat cortical cultures were more reproducible and had higher dynamic range as compared to human neural cultures. Human neural cultures were more sensitive than rat cortical cultures to chemicals previously shown to inhibit neurite outgrowth. Parallel analysis of morphological (neurite count, neurite length) and cytotoxicity (neurons per field) measurements were used to detect selective effects on neurite outgrowth. All chemicals which inhibited neurite outgrowth in rat cortical cultures did so at concentrations which did not concurrently affect the number of neurons per field, indicating selective effects on neurite outgrowth. In contrast, more than half the chemicals which inhibited neurite outgrowth in human neural cultures did so at concentrations which concurrently decreased the number of neurons per field, indicating that effects on neurite outgrowth were secondary to cytotoxicity. Overall, these data demonstrate that the culture models performed differently in terms of reproducibility, dynamic range and sensitivity to neurite outgrowth inhibitors. While human neural

  4. Comparative sensitivity of human and rat neural cultures to chemical-induced inhibition of neurite outgrowth

    Energy Technology Data Exchange (ETDEWEB)

    Harrill, Joshua A.; Freudenrich, Theresa M.; Robinette, Brian L.; Mundy, William R., E-mail: mundy.william@epa.gov

    2011-11-15

    There is a need for rapid, efficient and cost-effective alternatives to traditional in vivo developmental neurotoxicity testing. In vitro cell culture models can recapitulate many of the key cellular processes of nervous system development, including neurite outgrowth, and may be used as screening tools to identify potential developmental neurotoxicants. The present study compared primary rat cortical cultures and human embryonic stem cell-derived neural cultures in terms of: 1) reproducibility of high content image analysis based neurite outgrowth measurements, 2) dynamic range of neurite outgrowth measurements and 3) sensitivity to chemicals which have been shown to inhibit neurite outgrowth. There was a large increase in neurite outgrowth between 2 and 24 h in both rat and human cultures. Image analysis data collected across multiple cultures demonstrated that neurite outgrowth measurements in rat cortical cultures were more reproducible and had higher dynamic range as compared to human neural cultures. Human neural cultures were more sensitive than rat cortical cultures to chemicals previously shown to inhibit neurite outgrowth. Parallel analysis of morphological (neurite count, neurite length) and cytotoxicity (neurons per field) measurements were used to detect selective effects on neurite outgrowth. All chemicals which inhibited neurite outgrowth in rat cortical cultures did so at concentrations which did not concurrently affect the number of neurons per field, indicating selective effects on neurite outgrowth. In contrast, more than half the chemicals which inhibited neurite outgrowth in human neural cultures did so at concentrations which concurrently decreased the number of neurons per field, indicating that effects on neurite outgrowth were secondary to cytotoxicity. Overall, these data demonstrate that the culture models performed differently in terms of reproducibility, dynamic range and sensitivity to neurite outgrowth inhibitors. While human neural

  5. A mechanism for the inhibition of neural progenitor cell proliferation by cocaine.

    Directory of Open Access Journals (Sweden)

    Chun-Ting Lee

    2008-06-01

    Full Text Available BACKGROUND: Prenatal exposure of the developing brain to cocaine causes morphological and behavioral abnormalities. Recent studies indicate that cocaine-induced proliferation inhibition and/or apoptosis in neural progenitor cells may play a pivotal role in causing these abnormalities. To understand the molecular mechanism through which cocaine inhibits cell proliferation in neural progenitors, we sought to identify the molecules that are responsible for mediating the effect of cocaine on cell cycle regulation. METHODS AND FINDINGS: Microarray analysis followed by quantitative real-time reverse transcription PCR was used to screen cocaine-responsive and cell cycle-related genes in a neural progenitor cell line where cocaine exposure caused a robust anti-proliferative effect by interfering with the G1-to-S transition. Cyclin A2, among genes related to the G1-to-S cell cycle transition, was most strongly down-regulated by cocaine. Down-regulation of cyclin A was also found in cocaine-treated human primary neural and A2B5+ progenitor cells, as well as in rat fetal brains exposed to cocaine in utero. Reversing cyclin A down-regulation by gene transfer counteracted the proliferation inhibition caused by cocaine. Further, we found that cocaine-induced accumulation of reactive oxygen species, which involves N-oxidation of cocaine via cytochrome P450, promotes cyclin A down-regulation by causing an endoplasmic reticulum (ER stress response, as indicated by increased phosphorylation of eIF2alpha and expression of ATF4. In the developing rat brain, the P450 inhibitor cimetidine counteracted cocaine-induced inhibition of neural progenitor cell proliferation as well as down-regulation of cyclin A. CONCLUSIONS: Our results demonstrate that down-regulation of cyclin A underlies cocaine-induced proliferation inhibition in neural progenitors. The down-regulation of cyclin A is initiated by N-oxidative metabolism of cocaine and consequent ER stress. Inhibition of

  6. Psychosis-proneness and neural correlates of self-inhibition in theory of mind.

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    Lisette van der Meer

    Full Text Available Impaired Theory of Mind (ToM has been repeatedly reported as a feature of psychotic disorders. ToM is crucial in social interactions and for the development of social behavior. It has been suggested that reasoning about the belief of others, requires inhibition of the self-perspective. We investigated the neural correlates of self-inhibition in nineteen low psychosis prone (PP and eighteen high PP subjects presenting with subclinical features. High PP subjects have a more than tenfold increased risk of developing a schizophrenia-spectrum disorder. Brain activation was measured with functional Magnetic Resonance Imaging during a ToM task differentiating between self-perspective inhibition and belief reasoning. Furthermore, to test underlying inhibitory mechanisms, we included a stop-signal task. We predicted worse behavioral performance for high compared to low PP subjects on both tasks. Moreover, based on previous neuroimaging results, different activation patterns were expected in the inferior frontal gyrus (IFG in high versus low PP subjects in self-perspective inhibition and simple response inhibition. Results showed increased activation in left IFG during self-perspective inhibition, but not during simple response inhibition, for high PP subjects as compared to low PP subjects. High and low PP subjects showed equal behavioral performance. The results suggest that at a neural level, high PP subjects need more resources for inhibiting the self-perspective, but not for simple motor response inhibition, to equal the performance of low PP subjects. This may reflect a compensatory mechanism, which may no longer be available for patients with schizophrenia-spectrum disorders resulting in ToM impairments.

  7. ETOH inhibits embryonic neural stem/precursor cell proliferation via PLD signaling

    International Nuclear Information System (INIS)

    While a mother's excessive alcohol consumption during pregnancy is known to have adverse effects on fetal neural development, little is known about the underlying mechanism of these effects. In order to investigate these mechanisms, we investigated the toxic effect of ethanol (ETOH) on neural stem/precursor cell (NSC) proliferation. In cultures of NSCs, phospholipase D (PLD) is activated following stimulation with epidermal growth factor (EGF) and fibroblast growth factor 2 (FGF2). Exposure of NSCs to ETOH suppresses cell proliferation, while it has no effect on cell death. Phosphatidic acid (PA), which is a signaling messenger produced by PLD, reverses ETOH inhibition of NSC proliferation. Blocking the PLD signal by 1-butanol suppresses the proliferation. ETOH-induced suppression of NSC proliferation and the protective effect of PA for ETOH-induced suppression are mediated through extracellular signal-regulated kinase signaling. These results indicate that exposure to ETOH impairs NSC proliferation by altering the PLD signaling pathway

  8. Axon guidance factor SLIT2 inhibits neural invasion and metastasis in pancreatic cancer.

    Science.gov (United States)

    Göhrig, Andreas; Detjen, Katharina M; Hilfenhaus, Georg; Körner, Jan L; Welzel, Martina; Arsenic, Ruza; Schmuck, Rosa; Bahra, Marcus; Wu, Jane Y; Wiedenmann, Bertram; Fischer, Christian

    2014-03-01

    Pancreatic ductal adenocarcinoma (PDAC) metastasizes by neural, vascular, and local invasion routes, which limit patient survival. In nerves and vessels, SLIT2 and its ROBO receptors constitute repellent guidance cues that also direct epithelial branching. Thus, the SLIT2-ROBO system may represent a key pinch point to regulate PDAC spread. In this study, we examined the hypothesis that escaping from repellent SLIT2-ROBO signaling is essential to enable PDAC cells to appropriate their local stromal infrastructure for dissemination. Through immunohistochemical analysis, we detected SLIT2 receptors ROBO1 and ROBO4 on epithelia, nerves, and vessels in healthy pancreas and PDAC specimens, respectively. SLIT2 mRNA expression was reduced in PDAC compared with nontransformed pancreatic tissues and cell lines, suggesting a reduction in SLIT2-ROBO pathway activity in PDAC. In support of this interpretation, restoring the SLIT2 expression in SLIT2-deficient PDAC cells inhibited their bidirectional chemoattraction with neural cells, and more specifically, impaired unidirectional PDAC cell navigation along outgrowing neurites in models of neural invasion. Restoring autocrine/paracrine SLIT2 signaling was also sufficient to inhibit the directed motility of PDAC cells, but not their random movement. Conversely, RNA interference-mediated silencing of ROBO1 stimulated the motility of SLIT2-competent PDAC cells. Furthermore, culture supernatants from SLIT2-competent PDAC cells impaired migration of endothelial cells (human umbilical vein endothelial cells), whereas an N-terminal SLIT2 cleavage fragment stimulated such migration. In vivo investigations of pancreatic tumors with restored SLIT2 expression demonstrated reduced invasion, metastasis, and vascularization, with opposing effects produced by ROBO1 silencing in tumor cells or sequestration of endogenous SLIT2. Analysis of clinical specimens of PDAC showed that those with low SLIT2 mRNA expression exhibited a higher incidence

  9. Neural mechanism of central inhibition during physical fatigue: a magnetoencephalography study.

    Science.gov (United States)

    Tanaka, Masaaki; Ishii, Akira; Watanabe, Yasuyoshi

    2013-11-01

    Central inhibition plays an important role in physical performance during physical fatigue. We tried to clarify the neural mechanism of central inhibition during physical fatigue using the magnetoencephalography (MEG) and a classical conditioning technique. Twelve right-handed volunteers participated in this study. Participants underwent MEG recording during the imagery of maximum grips of the right hand guided by metronome sounds for 10 min. Thereafter, fatigue-inducing maximum handgrip trials were performed for 10 min; the metronome sounds were started 5 min after the beginning of the handgrip trials. We used metronome sounds as conditioned stimuli and maximum handgrip trials as unconditioned stimuli to cause central inhibition. The next day, MEG recording during the imagery of maximum grips of the right hand guided by metronome sounds were measured for 10 min. Levels of the fatigue sensation in the right hand and sympathetic nerve activity on the second day were significantly higher than those on the first day. In the right dorsolateral prefrontal cortex (Brodmann's area 46), the alpha-band event-related desynchronization (ERD) of the second MEG session relative to the first session with the time window of 200 to 300 ms after the onset of handgrip cue sounds was identified. The ERD level in this brain region was positively associated with the change in subjective level of right hand fatigue after the conditioning session and was negatively associated with that of the sympathetic nerve activity. We demonstrated that the right dorsolateral prefrontal cortex is involved in the neural substrates of central inhibition during physical fatigue.

  10. RhoA inhibits neural differentiation in murine stem cells through multiple mechanisms.

    Science.gov (United States)

    Yang, Junning; Wu, Chuanshen; Stefanescu, Ioana; Jakobsson, Lars; Chervoneva, Inna; Horowitz, Arie

    2016-01-01

    Spontaneous neural differentiation of embryonic stem cells is induced by Noggin-mediated inhibition of bone morphogenetic protein 4 (BMP4) signaling. RhoA is a guanosine triphosphatase (GTPase) that regulates cytoskeletal dynamics and gene expression, both of which control stem cell fate. We found that disruption of Syx, a gene encoding a RhoA-specific guanine nucleotide exchange factor, accelerated retinoic acid-induced neural differentiation in murine embryonic stem cells aggregated into embryoid bodies. Cells from Syx(+/+) and Syx(-/-) embryoid bodies had different abundances of proteins implicated in stem cell pluripotency. The differentiation-promoting proteins Noggin and RARγ (a retinoic acid receptor) were more abundant in cells of Syx(-/-) embryoid bodies, whereas the differentiation-suppressing proteins SIRT1 (a protein deacetylase) and the phosphorylated form of SMAD1 (the active form of this transcription factor) were more abundant in cells of Syx(+/+) embryoid bodies. These differences were blocked by the overexpression of constitutively active RhoA, indicating that the abundance of these proteins was maintained, at least in part, by RhoA activity. The peripheral stress fibers in cells from Syx(-/-) embryoid bodies were thinner than those in Syx(+/+) cells. Furthermore, less Noggin and fewer vesicles containing Rab3d, a GTPase that mediates Noggin trafficking, were detected in cells from Syx(-/-) embryoid bodies, which could result from increased Noggin exocytosis. These results suggested that, in addition to inhibiting Noggin transcription, RhoA activity in wild-type murine embryonic stem cells also prevented neural differentiation by limiting Noggin secretion. PMID:27460990

  11. Inhibition of Gli1 mobilizes endogenous neural stem cells for remyelination

    Science.gov (United States)

    Samanta, Jayshree; Grund, Ethan M.; Silva, Hernandez M.; Lafaille, Juan J.; Fishell, Gord; Salzer, James L.

    2016-01-01

    Summary Enhancing repair of myelin is an important, but still elusive therapeutic goal in many neurological disorders1. In Multiple Sclerosis (MS), an inflammatory demyelinating disease, endogenous remyelination does occur but is frequently insufficient to restore function. Both parenchymal oligodendrocyte progenitor cells (OPCs) and endogenous adult neural stem cells (NSCs) resident within the subventricular zone (SVZ) are known sources of remyelinating cells2. Here, we characterize the contribution to remyelination of a subset of adult NSCs, identified by their expression of Gli1, a transcriptional effector of the Sonic Hedgehog (Shh) pathway. We show that these cells are recruited from the SVZ to populate demyelinated lesions in the forebrain but never enter healthy, white matter tracts. Unexpectedly, recruitment of this pool of NSCs, and their differentiation into oligodendrocytes, is significantly enhanced by genetic or pharmacological inhibition of Gli1. Importantly, complete inhibition of canonical hedgehog signaling was ineffective indicating that Gli1’s role in both augmenting hedgehog signaling and retarding myelination is specialized. Indeed, inhibition of Gli1 improves the functional outcome in a relapsing/remitting model of experimental autoimmune encephalomyelitis (RR-EAE) and is neuroprotective. Thus, endogenous NSCs can be mobilized for the repair of demyelinated lesions by inhibiting Gli1, identifying a new therapeutic avenue for the treatment of demyelinating disorders. PMID:26416758

  12. Behavioural and neural interaction between spatial inhibition of return and the Simon effect

    Directory of Open Access Journals (Sweden)

    Pengfei eWang

    2013-09-01

    Full Text Available It has been well documented that the anatomically independent attention networks in the human brain interact functionally to achieve goal-directed behaviours. By combining spatial inhibition of return (IOR which implicates the orienting network with some executive function tasks (e.g., the Stroop and the flanker effects which implicate the executive network, researchers consistently found that the interference effects are significantly reduced at cued compared to uncued locations, indicating the functional interaction between the two attention networks. However, a unique, but consistent, effect is observed when spatial IOR is combined with the Simon effect: the Simon effect is significantly higher at the cued than uncued locations. To investigate the neural substrates underlying this phenomenon, we orthogonally combined the spatial IOR with the Simon effect in the present event-related fMRI study. Our behavioural data replicated previous results by showing larger Simon effect at the cued location. At the neural level, we found shared spatial representation system between spatial IOR and the Simon effect in bilateral posterior parietal cortex; spatial IOR specifically activated bilateral superior parietal cortex while the Simon effect specifically activated bilateral middle frontal cortex. Moreover, left precentral gyrus was involved in the neural interaction between spatial IOR and the Simon effect by showing significantly higher neural activity in the ‘Cued_Congruent’ condition. Taken together, our results suggest that due to the shared spatial representation system in the posterior parietal cortex, responses were significantly facilitated when spatial IOR and the Simon effect relied on the same spatial representations, i.e., in the ‘Cued_Congruent’ condition. Correspondingly, the sensorimotor system was significantly involved in the ‘Cued_Congruent’ condition to fasten the responses, which indirectly resulted in the enhanced Simon

  13. Inhibition of glycogen synthase kinase-3 enhances the differentiation and reduces the proliferation of adult human olfactory epithelium neural precursors

    International Nuclear Information System (INIS)

    The olfactory epithelium (OE) contains neural precursor cells which can be easily harvested from a minimally invasive nasal biopsy, making them a valuable cell source to study human neural cell lineages in health and disease. Glycogen synthase kinase-3 (GSK-3) has been implicated in the etiology and treatment of neuropsychiatric disorders and also in the regulation of murine neural precursor cell fate in vitro and in vivo. In this study, we examined the impact of decreased GSK-3 activity on the fate of adult human OE neural precursors in vitro. GSK-3 inhibition was achieved using ATP-competitive (6-bromoindirubin-3'-oxime and CHIR99021) or substrate-competitive (TAT-eIF2B) inhibitors to eliminate potential confounding effects on cell fate due to off-target kinase inhibition. GSK-3 inhibitors decreased the number of neural precursor cells in OE cell cultures through a reduction in proliferation. Decreased proliferation was not associated with a reduction in cell survival but was accompanied by a reduction in nestin expression and a substantial increase in the expression of the neuronal differentiation markers MAP1B and neurofilament (NF-M) after 10 days in culture. Taken together, these results suggest that GSK-3 inhibition promotes the early stages of neuronal differentiation in cultures of adult human neural precursors and provide insights into the mechanisms by which alterations in GSK-3 signaling affect adult human neurogenesis, a cellular process strongly suspected to play a role in the etiology of neuropsychiatric disorders.

  14. Inhibition of glycogen synthase kinase-3 enhances the differentiation and reduces the proliferation of adult human olfactory epithelium neural precursors

    Energy Technology Data Exchange (ETDEWEB)

    Manceur, Aziza P. [Institute of Biomaterials and Biomedical Engineering (IBBME), University of Toronto, Toronto, Ontario (Canada); Donnelly Centre, University of Toronto, Toronto, Ontario (Canada); Tseng, Michael [Laboratory of Cellular and Molecular Pathophysiology, Centre for Addiction and Mental Health (CAMH), University of Toronto, Toronto, Ontario (Canada); Department of Psychiatry, University of Toronto, Toronto, ON (Canada); Institute of Medical Science, University of Toronto, Toronto, ON (Canada); Holowacz, Tamara [Donnelly Centre, University of Toronto, Toronto, Ontario (Canada); Witterick, Ian [Institute of Medical Science, University of Toronto, Toronto, ON (Canada); Department of Otolaryngology, Head and Neck Surgery, University of Toronto, ON (Canada); Weksberg, Rosanna [Institute of Medical Science, University of Toronto, Toronto, ON (Canada); The Hospital for Sick Children, Research Institute, Program in Genetics and Genomic Biology, Toronto, Ontario Canada (Canada); McCurdy, Richard D. [The Hospital for Sick Children, Research Institute, Program in Genetics and Genomic Biology, Toronto, Ontario Canada (Canada); Warsh, Jerry J. [Laboratory of Cellular and Molecular Pathophysiology, Centre for Addiction and Mental Health (CAMH), University of Toronto, Toronto, Ontario (Canada); Department of Psychiatry, University of Toronto, Toronto, ON (Canada); Institute of Medical Science, University of Toronto, Toronto, ON (Canada); Audet, Julie, E-mail: julie.audet@utoronto.ca [Institute of Biomaterials and Biomedical Engineering (IBBME), University of Toronto, Toronto, Ontario (Canada); Donnelly Centre, University of Toronto, Toronto, Ontario (Canada)

    2011-09-10

    The olfactory epithelium (OE) contains neural precursor cells which can be easily harvested from a minimally invasive nasal biopsy, making them a valuable cell source to study human neural cell lineages in health and disease. Glycogen synthase kinase-3 (GSK-3) has been implicated in the etiology and treatment of neuropsychiatric disorders and also in the regulation of murine neural precursor cell fate in vitro and in vivo. In this study, we examined the impact of decreased GSK-3 activity on the fate of adult human OE neural precursors in vitro. GSK-3 inhibition was achieved using ATP-competitive (6-bromoindirubin-3'-oxime and CHIR99021) or substrate-competitive (TAT-eIF2B) inhibitors to eliminate potential confounding effects on cell fate due to off-target kinase inhibition. GSK-3 inhibitors decreased the number of neural precursor cells in OE cell cultures through a reduction in proliferation. Decreased proliferation was not associated with a reduction in cell survival but was accompanied by a reduction in nestin expression and a substantial increase in the expression of the neuronal differentiation markers MAP1B and neurofilament (NF-M) after 10 days in culture. Taken together, these results suggest that GSK-3 inhibition promotes the early stages of neuronal differentiation in cultures of adult human neural precursors and provide insights into the mechanisms by which alterations in GSK-3 signaling affect adult human neurogenesis, a cellular process strongly suspected to play a role in the etiology of neuropsychiatric disorders.

  15. Influence of DAT1 and COMT variants on neural activation during response inhibition in adolescents with attention-deficit/hyperactivity disorder and healthy controls

    NARCIS (Netherlands)

    van Rooij, D.; Hoekstra, P. J.; Bralten, J.; Hakobjan, M.; Oosterlaan, J.; Franke, B.; Rommelse, N.; Buitelaar, J. K.; Hartman, C. A.

    2015-01-01

    Background. Impairment of response inhibition has been implicated in attention-deficit/hyperactivity disorder (ADHD). Dopamine neurotransmission has been linked to the behavioural and neural correlates of response inhibition. The current study aimed to investigate the relationship of polymorphisms i

  16. The frequency of p53, Ki67, CD99 and Fli-1 protein expression in paraffin-embedded tissue blocks in Ewing’s sarcoma

    Directory of Open Access Journals (Sweden)

    Bagheri Hossein-Abadi Z

    2011-06-01

    Full Text Available "n Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;} Background: Ewing sarcoma family tumors (ESFTs are among the most malignant tumors in children and young adults. ESFTs include Ewing sarcoma (ES and peripheral primitive neuroectodermal tumors (pPNETs. As there seemed to be few studies on the molecular biology of ESFTs, we investigated the frequency of CD99, Ki67, p53 and Fli-1 protein expression in 15 Iranian patients with ESFTs. In addition, the correlation between expression rate of these proteins and various clinical factors, including age, sex and survival was computed."n"nMethods: The expression of the aforesaid proteins was studied by immunohisto-chemistry in formalin-fixed and paraffin-embedded blocks of 15 ESFTs specimens. Stained sections were classified according to the percentage of stained tumor cells."n"nResults: The results showed the membrane expression of CD99 protein in all of the specimens. The nuclear expression of Fli-1 protein was observed in 86.7% and the over-expression of p53 nuclear protein was seen in 53.3% of the specimens. The expression rate of Ki67 protein was 60%. Although a significant correlation was not shown between the expression levels of Ki67, p53 or Fli-1 proteins with age, sex or survival of the patients, there was a significant

  17. Regulation of neural gene transcription by optogenetic inhibition of the RE1-silencing transcription factor.

    Science.gov (United States)

    Paonessa, Francesco; Criscuolo, Stefania; Sacchetti, Silvio; Amoroso, Davide; Scarongella, Helena; Pecoraro Bisogni, Federico; Carminati, Emanuele; Pruzzo, Giacomo; Maragliano, Luca; Cesca, Fabrizia; Benfenati, Fabio

    2016-01-01

    Optogenetics provides new ways to activate gene transcription; however, no attempts have been made as yet to modulate mammalian transcription factors. We report the light-mediated regulation of the repressor element 1 (RE1)-silencing transcription factor (REST), a master regulator of neural genes. To tune REST activity, we selected two protein domains that impair REST-DNA binding or recruitment of the cofactor mSin3a. Computational modeling guided the fusion of the inhibitory domains to the light-sensitive Avena sativa light-oxygen-voltage-sensing (LOV) 2-phototrophin 1 (AsLOV2). By expressing AsLOV2 chimeras in Neuro2a cells, we achieved light-dependent modulation of REST target genes that was associated with an improved neural differentiation. In primary neurons, light-mediated REST inhibition increased Na(+)-channel 1.2 and brain-derived neurotrophic factor transcription and boosted Na(+) currents and neuronal firing. This optogenetic approach allows the coordinated expression of a cluster of genes impinging on neuronal activity, providing a tool for studying neuronal physiology and correcting gene expression changes taking place in brain diseases.

  18. Inhibition of neurosphere formation in neural stem/progenitor cells by acrylamide.

    Science.gov (United States)

    Chen, Jong-Hang; Lee, Don-Ching; Chen, Mei-Shu; Ko, Ying-Chin; Chiu, Ing-Ming

    2015-01-01

    Previous studies showed that transplantation of cultured neural stem/progenitor cells (NSPCs) could improve functional recovery for various neurological diseases. This study aims to develop a stem cell-based model for predictive toxicology of development in the neurological system after acrylamide exposure. Treatment of mouse (KT98/F1B-GFP) and human (U-1240 MG/F1B-GFP) NSPCs with 0.5 mM acrylamide resulted in the inhibition of neurosphere formation (definition of self-renewal ability in NSPCs), but not inhibition of cell proliferation. Apoptosis and differentiation of KT98 (a precursor of KT98/F1B-GFP) and KT98/F1B-GFP are not observed in acrylamide-treated neurospheres. Analysis of secondary neurosphere formation and differentiation of neurons and glia illustrated that acrylamide-treated KT98 and KT98/F1B-GFP neurospheres retain the NSPC properties, such as self-renewal and differentiation capacity. Correlation of acrylamide-inhibited neurosphere formation with cell-cell adhesion was observed in mouse NSPCs by live cell image analysis and the presence of acrylamide. Protein expression levels of cell adhesion molecules [neural cell adhesion molecule (NCAM) and N-cadherin] and extracellular signal-regulated kinases (ERK) in acrylamide-treated KT98/F1B-GFP and U-1240 MG/F1B-GFP neurospheres demonstrated that NCAM decreased and phospho-ERK (pERK) increased, whereas expression of N-cadherin remained unchanged. Analysis of AKT (protein kinase B, PKB)/β-catenin pathway showed decrease in phospho-AKT (p-AKT) and cyclin D1 expression in acrylamide-treated neurospheres of KT98/F1B-GFP. Furthermore, PD98059, an ERK phosphorylation inhibitor, attenuated acrylamide-induced ERK phosphorylation, indicating that pERK contributed to the cell proliferation, but not in neurosphere formation in mouse NSPCs. Coimmunoprecipitation results of KT98/F1B-GFP cell lysates showed that the complex of NCAM and fibroblast growth factor receptor 1 (FGFR1) is present in the neurosphere, and the

  19. Process development of a human recombinant diabody expressed in E. coli: engagement of CD99-induced apoptosis for target therapy in Ewing's sarcoma.

    Science.gov (United States)

    Moricoli, Diego; Carbonella, Damiano Cosimo; Dominici, Sabrina; Fiori, Valentina; Balducci, Maria Cristina; Guerzoni, Clara; Manara, Maria Cristina; Pasello, Michela; Laguardia, Maria Elena; Cianfriglia, Maurizio; Scotlandi, Katia; Magnani, Mauro

    2016-05-01

    Ewing's sarcoma (EWS) is the second most common primary bone tumor in pediatric patients characterized by over expression of CD99. Current management consists in extensive chemotherapy in addition to surgical resection and/or radiation. Recent improvements in treatment are still overshadowed by severe side effects such as toxicity and risk of secondary malignancies; therefore, more effective strategies are urgently needed. The goal of this work was to develop a rapid, inexpensive, and "up-scalable" process of a novel human bivalent single-chain fragment variable diabody (C7 dAbd) directed against CD99, as a new therapeutic approach for EWS. We first investigated different Escherichia coli constructs of C7 dAbd in small-scale studies. Starting from 60 % soluble fraction, we obtained a yield of 25 mg C7 dAbd per liter of bacterial culture with the construct containing pelB signal sequence. In contrast, a low recovery of C7 dAbd was achieved starting from periplasmic inclusion bodies. In order to maximize the yield of C7 dAbd, large-scale fermentation was optimized. We obtained from 75 % soluble fraction 35 mg C7 dAbd per L of cell culture grown in a synthetic media containing 3 g/L of vegetable peptone and 1 g/L of yeast extract. Furthermore, we demonstrated the better efficacy of the cell lysis by homogenization versus periplasmic extraction, in reducing endotoxin level of the C7 dAbd. For gram-scale purification, a direct aligned two-step chromatography cascade based on binding selectivity was developed. Finally, we recovered C7 dAbd with low residual process-related impurities, excellent reactivity, and apoptotic ability against EWS cells. PMID:26685854

  20. Neural circuits containing olfactory neurons are involved in prepulse inhibition of the startle reflex in rats

    Directory of Open Access Journals (Sweden)

    Haichen eNiu

    2015-03-01

    Full Text Available Many neuropsychiatric disorders, such as schizophrenia, have been associated with abnormalities in the function of the olfactory system and prepulse inhibition (PPI of the startle reflex. However, whether these two abnormalities are related is unclear. The present study was designed to determine whether inhibiting olfactory sensory input via the infusion of zinc sulfate (ZnE, 0.17 M, 0.5 ml into the olfactory naris disrupts PPI. Furthermore, lidocaine/MK801 was bilaterally microinjected into the olfactory bulb (OB to examine whether the blockade of olfactory sensory input impairs PPI. To identify the neural projections that connect the olfaction- and PPI-related areas of the CNS, trans-synaptic retrograde tracing using a recombinant pseudorabies virus (PRV was performed. Our results demonstrated that blocking olfactory sensory input altered olfaction-related behavior. At the functional level, we demonstrated that the inhibition of olfactory sensory input impaired PPI of the startle response subsequent to a decrease in c-fos expression in relevant brain regions. Furthermore, the results of a similar and more robust experiment indicated that blocking olfactory sensory input via the microinjection of lidocaine/MK801 into the OB impaired PPI. At the circuit level, based on trans-synaptic retrograde tracing using PRV, we demonstrated that a large portion of the labeled neurons in several regions of the olfactory cortices connected to the pedunculopontine tegmental nucleus (PPTg. Thus, these data suggest that the olfactory system participates in the regulation of PPI and plays a role in the effect of PPI on the startle response in rats.

  1. Contrasting neural effects of aging on proactive and reactive response inhibition

    NARCIS (Netherlands)

    Bloemendaal, Mirjam; Zandbelt, Bram; Wegman, Joost; Nieuwerth-van de Rest, Ondine; Cools, Roshan; Aarts, Esther

    2016-01-01

    Two distinct forms of response inhibition may underlie observed deficits in response inhibition in aging. We assessed whether age-related neurocognitive impairments in response inhibition reflect deficient reactive inhibition (outright stopping) or also deficient proactive inhibition (anticipator

  2. Inhibition of Sirt1 promotes neural progenitors toward motoneuron differentiation from human embryonic stem cells

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yun; Wang, Jing [Department of Neurology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191 (China); Clinical Stem Cell Center, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191 (China); Chen, Guian [Clinical Stem Cell Center, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191 (China); Reproductive Medical Center, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191 (China); Fan, Dongsheng, E-mail: dsfan@yahoo.cn [Department of Neurology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191 (China); Clinical Stem Cell Center, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191 (China); Deng, Min, E-mail: dengmin1706@yahoo.com.cn [Department of Neurology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191 (China); Clinical Stem Cell Center, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191 (China)

    2011-01-14

    Research highlights: {yields} Nicotinamide inhibit Sirt1. {yields} MASH1 and Ngn2 activation. {yields} Increase the expression of HB9. {yields} Motoneurons formation increases significantly. -- Abstract: Several protocols direct human embryonic stem cells (hESCs) toward differentiation into functional motoneurons, but the efficiency of motoneuron generation varies based on the human ESC line used. We aimed to develop a novel protocol to increase the formation of motoneurons from human ESCs. In this study, we tested a nuclear histone deacetylase protein, Sirt1, to promote neural precursor cell (NPC) development during differentiation of human ESCs into motoneurons. A specific inhibitor of Sirt1, nicotinamide, dramatically increased motoneuron formation. We found that about 60% of the cells from the total NPCs expressed HB9 and {beta}III-tubulin, commonly used motoneuronal markers found in neurons derived from ESCs following nicotinamide treatment. Motoneurons derived from ESC expressed choline acetyltransferase (ChAT), a positive marker of mature motoneuron. Moreover, we also examined the transcript levels of Mash1, Ngn2, and HB9 mRNA in the differentiated NPCs treated with the Sirt1 activator resveratrol (50 {mu}M) or inhibitor nicotinamide (100 {mu}M). The levels of Mash1, Ngn2, and HB9 mRNA were significantly increased after nicotinamide treatment compared with control groups, which used the traditional protocol. These results suggested that increasing Mash1 and Ngn2 levels by inhibiting Sirt1 could elevate HB9 expression, which promotes motoneuron differentiation. This study provides an alternative method for the production of transplantable motoneurons, a key requirement in the development of hESC-based cell therapy in motoneuron disease.

  3. Kuwanon V inhibits proliferation, promotes cell survival and increases neurogenesis of neural stem cells.

    Directory of Open Access Journals (Sweden)

    Sun-Young Kong

    Full Text Available Neural stem cells (NSCs have the ability to proliferate and differentiate into neurons and glia. Regulation of NSC fate by small molecules is important for the generation of a certain type of cell. The identification of small molecules that can induce new neurons from NSCs could facilitate regenerative medicine and drug development for neurodegenerative diseases. In this study, we screened natural compounds to identify molecules that are effective on NSC cell fate determination. We found that Kuwanon V (KWV, which was isolated from the mulberry tree (Morus bombycis root, increased neurogenesis in rat NSCs. In addition, during NSC differentiation, KWV increased cell survival and inhibited cell proliferation as shown by 5-bromo-2-deoxyuridine pulse experiments, Ki67 immunostaining and neurosphere forming assays. Interestingly, KWV enhanced neuronal differentiation and decreased NSC proliferation even in the presence of mitogens such as epidermal growth factor and fibroblast growth factor 2. KWV treatment of NSCs reduced the phosphorylation of extracellular signal-regulated kinase 1/2, increased mRNA expression levels of the cyclin-dependent kinase inhibitor p21, down-regulated Notch/Hairy expression levels and up-regulated microRNA miR-9, miR-29a and miR-181a. Taken together, our data suggest that KWV modulates NSC fate to induce neurogenesis, and it may be considered as a new drug candidate that can regenerate or protect neurons in neurodegenerative diseases.

  4. Negative stereotype activation alters interaction between neural correlates of arousal, inhibition and cognitive control.

    Science.gov (United States)

    Forbes, Chad E; Cox, Christine L; Schmader, Toni; Ryan, Lee

    2012-10-01

    Priming negative stereotypes of African Americans can bias perceptions toward novel Black targets, but less is known about how these perceptions ultimately arise. Examining how neural regions involved in arousal, inhibition and control covary when negative stereotypes are activated can provide insight into whether individuals attempt to downregulate biases. Using fMRI, White egalitarian-motivated participants were shown Black and White faces at fast (32 ms) or slow (525 ms) presentation speeds. To create a racially negative stereotypic context, participants listened to violent and misogynistic rap (VMR) in the background. No music (NM) and death metal (DM) were used as control conditions in separate blocks. Fast exposure of Black faces elicited amygdala activation in the NM and VMR conditions (but not DM), that also negatively covaried with activation in prefrontal regions. Only in VMR, however, did amygdala activation for Black faces persist during slow exposure and positively covary with activation in dorsolateral prefrontal cortex while negatively covarying with activation in orbitofrontal cortex. Findings suggest that contexts that prime negative racial stereotypes seem to hinder the downregulation of amygdala activation that typically occurs when egalitarian perceivers are exposed to Black faces. PMID:21954239

  5. Neural correlates of attention biases, behavioral inhibition, and social anxiety in children: An ERP study.

    Science.gov (United States)

    Thai, Nhi; Taber-Thomas, Bradley C; Pérez-Edgar, Koraly E

    2016-06-01

    Behavioral inhibition (BI) is a biologically-based temperament characterized by vigilance toward threat. Over time, many children with BI increasingly fear social circumstances and display maladaptive social behavior. BI is also one of the strongest individual risk factors for developing social anxiety disorder. Although research has established a link between BI and anxiety, its causal mechanism remains unclear. Attention biases may underlie this relation. The current study examined neural markers of the BI-attention-anxiety link in children ages 9-12 years (N=99, Mean=9.97, SD=0.97). ERP measures were collected as children completed an attention-bias (dot-probe) task with neutral and angry faces. P2 and N2 amplitudes were associated with social anxiety and attention bias, respectively. Specifically, augmented P2 was related to decreased symptoms of social anxiety and moderated the relation between BI and social anxiety, suggesting that increasing attention mobilization may serve as a compensatory mechanism that attenuates social anxiety in individuals with high BI. The BI by N2 interaction found that larger N2 related to threat avoidance with increasing levels of BI, consistent with over-controlled socio-emotional functioning. Lastly, children without BI (BN) showed an augmented P1 to probes replacing angry faces, suggesting maintenance of attentional resources in threat-related contexts. PMID:27061248

  6. Stimulation of Neural Stem Cell Proliferation by Inhibition of Phosphodiesterase 5

    Directory of Open Access Journals (Sweden)

    Ana I. Santos

    2014-01-01

    Full Text Available The involvement of nitric oxide (NO and cyclic GMP (cGMP in neurogenesis has been progressively unmasked over the last decade. Phosphodiesterase 5 (PDE5 specifically degrades cGMP and is highly abundant in the mammalian brain. Inhibition of cGMP hydrolysis by blocking PDE5 is a possible strategy to enhance the first step of neurogenesis, proliferation of neural stem cells (NSC. In this work, we have studied the effect on cell proliferation of 3 inhibitors with different selectivity and potency for PDE5, T0156, sildenafil, and zaprinast, using subventricular zone-(SVZ- derived NSC cultures. We observed that a short- (6 h or a long-term (24 h treatment with PDE5 inhibitors increased SVZ-derived NSC proliferation. Cell proliferation induced by PDE5 inhibitors was dependent on the activation of the mitogen-activated protein kinase (MAPK and was abolished by inhibitors of MAPK signaling, soluble guanylyl cyclase, and protein kinase G. Moreover, sildenafil neither activated ERK1/2 nor altered p27Kip1 levels, suggesting the involvement of pathways different from those activated by T0156 or zaprinast. In agreement with the present results, PDE5 inhibitors may be an interesting therapeutic approach for enhancing the proliferation stage of adult neurogenesis.

  7. Nitric oxide from inflammatory origin impairs neural stem cell proliferation by inhibiting epidermal growth factor receptor signaling

    OpenAIRE

    Bruno Pereira Carreira; Maria Inês Morte; Ana Isabel Santos; Ana Sofia Lourenço; António Francisco Ambrósio; Carvalho, Caetana M.; Araújo, Inês M.

    2014-01-01

    Neuroinflammation is characterized by activation of microglial cells, followed by production of nitric oxide (NO), which may have different outcomes on neurogenesis, favoring or inhibiting this process. In the present study, we investigated how the inflammatory mediator NO can affect proliferation of neural stem cells (NSCs), and explored possible mechanisms underlying this effect. We investigated which mechanisms are involved in the regulation of NSC proliferation following treatment with an...

  8. Buffering social influence: neural correlates of response inhibition predict driving safety in the presence of a peer.

    Science.gov (United States)

    Cascio, Christopher N; Carp, Joshua; O'Donnell, Matthew Brook; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G; Falk, Emily B

    2015-01-01

    Adolescence is a period characterized by increased sensitivity to social cues, as well as increased risk-taking in the presence of peers. For example, automobile crashes are the leading cause of death for adolescents, and driving with peers increases the risk of a fatal crash. Growing evidence points to an interaction between neural systems implicated in cognitive control and social and emotional context in predicting adolescent risk. We tested such a relationship in recently licensed teen drivers. Participants completed an fMRI session in which neural activity was measured during a response inhibition task, followed by a separate driving simulator session 1 week later. Participants drove alone and with a peer who was randomly assigned to express risk-promoting or risk-averse social norms. The experimentally manipulated social context during the simulated drive moderated the relationship between individual differences in neural activity in the hypothesized cognitive control network (right inferior frontal gyrus, BG) and risk-taking in the driving context a week later. Increased activity in the response inhibition network was not associated with risk-taking in the presence of a risky peer but was significantly predictive of safer driving in the presence of a cautious peer, above and beyond self-reported susceptibility to peer pressure. Individual differences in recruitment of the response inhibition network may allow those with stronger inhibitory control to override risky tendencies when in the presence of cautious peers. This relationship between social context and individual differences in brain function expands our understanding of neural systems involved in top-down cognitive control during adolescent development. PMID:25100217

  9. Leptin reverses corticosterone-induced inhibition of neural stem cell proliferation through activating the NR2B subunits of NMDA receptors

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Wen-Zhu [Anesthesia and Operation Center, Hainan Branch of Chinese PLA General Hospital, Hainan 572013 (China); Anesthesia and Operation Center, Chinese PLA General Hospital, Beijing 100853 (China); Miao, Yu-Liang [Department of Anesthesiology, PLA No. 306 Hospital, Beijing 100101 (China); Guo, Wen-Zhi [Department of Anesthesiology, Beijing Military General Hospital of Chinese People’s Liberation Army, Beijing 100700 (China); Wu, Wei, E-mail: wwzwgk@163.com [Department of Head and Neck Surgery of Otolaryngology, PLA No. 306 Hospital, Beijing 100101 (China); Li, Bao-Wei [Department of Head and Neck Surgery of Otolaryngology, PLA No. 306 Hospital, Beijing 100101 (China); An, Li-Na [Department of Anesthesiology, Armed Police General Hospital, Beijing 100039 (China); Fang, Wei-Wu [Department of Anesthesiology, PLA No. 306 Hospital, Beijing 100101 (China); Mi, Wei-Dong, E-mail: elite2005gg@163.com [Anesthesia and Operation Center, Chinese PLA General Hospital, Beijing 100853 (China)

    2014-04-25

    Highlights: • Leptin promotes the proliferation of neural stem cells isolated from embryonic mouse hippocampus. • Leptin reverses corticosterone-induced inhibition of neural stem cell proliferation. • The effects of leptin are partially mediated by upregulating NR2B subunits. - Abstract: Corticosterone inhibits the proliferation of hippocampal neural stem cells (NSCs). The removal of corticosterone-induced inhibition of NSCs proliferation has been reported to contribute to neural regeneration. Leptin has been shown to regulate brain development, improve angiogenesis, and promote neural regeneration; however, its effects on corticosterone-induced inhibition of NSCs proliferation remain unclear. Here we reported that leptin significantly promoted the proliferation of hippocampal NSCs in a concentration-dependent pattern. Also, leptin efficiently reversed the inhibition of NSCs proliferation induced by corticosterone. Interestingly, pre-treatment with non-specific NMDA antagonist MK-801, specific NR2B antagonist Ro 25-6981, or small interfering RNA (siRNA) targeting NR2B, significantly blocked the effect of leptin on corticosterone-induced inhibition of NSCs proliferation. Furthermore, corticosterone significantly reduced the protein expression of NR2B, whereas pre-treatment with leptin greatly reversed the attenuation of NR2B expression caused by corticosterone in cultured hippocampal NSCs. Our findings demonstrate that leptin reverses the corticosterone-induced inhibition of NSCs proliferation. This process is, at least partially mediated by increased expression of NR2B subunits of NMDA receptors.

  10. Leptin reverses corticosterone-induced inhibition of neural stem cell proliferation through activating the NR2B subunits of NMDA receptors

    International Nuclear Information System (INIS)

    Highlights: • Leptin promotes the proliferation of neural stem cells isolated from embryonic mouse hippocampus. • Leptin reverses corticosterone-induced inhibition of neural stem cell proliferation. • The effects of leptin are partially mediated by upregulating NR2B subunits. - Abstract: Corticosterone inhibits the proliferation of hippocampal neural stem cells (NSCs). The removal of corticosterone-induced inhibition of NSCs proliferation has been reported to contribute to neural regeneration. Leptin has been shown to regulate brain development, improve angiogenesis, and promote neural regeneration; however, its effects on corticosterone-induced inhibition of NSCs proliferation remain unclear. Here we reported that leptin significantly promoted the proliferation of hippocampal NSCs in a concentration-dependent pattern. Also, leptin efficiently reversed the inhibition of NSCs proliferation induced by corticosterone. Interestingly, pre-treatment with non-specific NMDA antagonist MK-801, specific NR2B antagonist Ro 25-6981, or small interfering RNA (siRNA) targeting NR2B, significantly blocked the effect of leptin on corticosterone-induced inhibition of NSCs proliferation. Furthermore, corticosterone significantly reduced the protein expression of NR2B, whereas pre-treatment with leptin greatly reversed the attenuation of NR2B expression caused by corticosterone in cultured hippocampal NSCs. Our findings demonstrate that leptin reverses the corticosterone-induced inhibition of NSCs proliferation. This process is, at least partially mediated by increased expression of NR2B subunits of NMDA receptors

  11. Electroacupuncture in the repair of spinal cord injury: inhibiting the Notch signaling pathway and promoting neural stem cell proliferation

    Directory of Open Access Journals (Sweden)

    Xin Geng

    2015-01-01

    Full Text Available Electroacupuncture for the treatment of spinal cord injury has a good clinical curative effect, but the underlying mechanism is unclear. In our experiments, the spinal cord of adult Sprague-Dawley rats was clamped for 60 seconds. Dazhui (GV14 and Mingmen (GV4 acupoints of rats were subjected to electroacupuncture. Enzyme-linked immunosorbent assay revealed that the expression of serum inflammatory factors was apparently downregulated in rat models of spinal cord injury after electroacupuncture. Hematoxylin-eosin staining and immunohistochemistry results demonstrated that electroacupuncture contributed to the proliferation of neural stem cells in rat injured spinal cord, and suppressed their differentiation into astrocytes. Real-time quantitative PCR and western blot assays showed that electroacupuncture inhibited activation of the Notch signaling pathway induced by spinal cord injury. These findings indicate that electroacupuncture repaired the injured spinal cord by suppressing the Notch signaling pathway and promoting the proliferation of endogenous neural stem cells.

  12. Electroacupuncture in the repair of spinal cord injury:inhibiting the Notch signaling pathway and promoting neural stem cell proliferation

    Institute of Scientific and Technical Information of China (English)

    Xin Geng; Tao Sun; Jing-hui Li; Ning Zhao; Yong Wang; Hua-lin Yu

    2015-01-01

    Electroacupuncture for the treatment of spinal cord injury has a good clinical curative effect, but the underlying mechanism is unclear. In our experiments, the spinal cord of adult Sprague-Daw-ley rats was clamped for 60 seconds.Dazhui (GV14) andMingmen (GV4) acupoints of rats were subjected to electroacupuncture. Enzyme-linked immunosorbent assay revealed that the expres-sion of serum inlfammatory factors was apparently downregulated in rat models of spinal cord injury after electroacupuncture. Hematoxylin-eosin staining and immunohistochemistry results demonstrated that electroacupuncture contributed to the proliferation of neural stem cells in rat injured spinal cord, and suppressed their differentiation into astrocytes. Real-time quantitative PCR and western blot assays showed that electroacupuncture inhibited activation of the Notch signaling pathway induced by spinal cord injury. These ifndings indicate that electroacupuncture repaired the injured spinal cord by suppressing the Notch signaling pathway and promoting the proliferation of endogenous neural stem cells.

  13. Dissociable Patterns of Neural Activity during Response Inhibition in Depressed Adolescents with and without Suicidal Behavior

    Science.gov (United States)

    Pan, Lisa A.; Batezati-Alves, Silvia C.; Almeida, Jorge R. C.; Segreti, AnnaMaria; Akkal, Dalila; Hassel, Stefanie; Lakdawala, Sara; Brent, David A.; Phillips, Mary L.

    2011-01-01

    Objectives: Impaired attentional control and behavioral control are implicated in adult suicidal behavior. Little is known about the functional integrity of neural circuitry supporting these processes in suicidal behavior in adolescence. Method: Functional magnetic resonance imaging was used in 15 adolescent suicide attempters with a history of…

  14. Effects of histone deacetylation inhibition on neuronal differentiation of embryonic mouse neural stem cells

    NARCIS (Netherlands)

    Balasubramaniyan, V.; Boddeke, E.; Bakels, R.; Kust, B.; Kooistra, S.; Veneman, A.; Copray, S.

    2006-01-01

    Neural stem cells (NSCs) are multipotent cells that have the capacity for self-renewal and for differentiation into the major cell types of the nervous system, i.e. neurons, astrocytes and oligodendrocytes. The molecular mechanisms regulating gene transcription resulting in NSC differentiation and c

  15. Genomic DNA hypomethylation is associated with neural tube defects induced by methotrexate inhibition of folate metabolism.

    Directory of Open Access Journals (Sweden)

    Xiuwei Wang

    Full Text Available DNA methylation is thought to be involved in the etiology of neural tube defects (NTDs. However, the exact mechanism between DNA methylation and NTDs remains unclear. Herein, we investigated the change of methylation in mouse model of NTDs associated with folate dysmetabolism by use of ultraperformance liquid chromatography tandem mass spectrometry (UPLC/MS/MS, liquid chromatography-electrospray ionization tandem mass spectrometry (LC-MS/MS, microarray, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and Real time quantitative PCR. Results showed that NTD neural tube tissues had lower concentrations of 5-methyltetrahydrofolate (5-MeTHF, P = 0.005, 5-formyltetrahydrofolate (5-FoTHF, P = 0.040, S-adenosylmethionine (SAM, P = 0.004 and higher concentrations of folic acid (P = 0.041, homocysteine (Hcy, P = 0.006 and S-adenosylhomocysteine (SAH, P = 0.045 compared to control. Methylation levels of genomic DNA decreased significantly in the embryonic neural tube tissue of NTD samples. 132 differentially methylated regions (35 low methylated regions and 97 high methylated regions were selected by microarray. Two genes (Siah1b, Prkx in Wnt signal pathway demonstrated lower methylated regions (peak and higher expression in NTDs (P<0.05; P<0.05. Results suggest that DNA hypomethylation was one of the possible epigenetic variations correlated with the occurrence of NTDs induced by folate dysmetabolism and that Siah1b, Prkx in Wnt pathway may be candidate genes for NTDs.

  16. Genomic DNA hypomethylation is associated with neural tube defects induced by methotrexate inhibition of folate metabolism.

    Science.gov (United States)

    Wang, Xiuwei; Guan, Zhen; Chen, Yan; Dong, Yanting; Niu, Yuhu; Wang, Jianhua; Zhang, Ting; Niu, Bo

    2015-01-01

    DNA methylation is thought to be involved in the etiology of neural tube defects (NTDs). However, the exact mechanism between DNA methylation and NTDs remains unclear. Herein, we investigated the change of methylation in mouse model of NTDs associated with folate dysmetabolism by use of ultraperformance liquid chromatography tandem mass spectrometry (UPLC/MS/MS), liquid chromatography-electrospray ionization tandem mass spectrometry (LC-MS/MS), microarray, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and Real time quantitative PCR. Results showed that NTD neural tube tissues had lower concentrations of 5-methyltetrahydrofolate (5-MeTHF, P = 0.005), 5-formyltetrahydrofolate (5-FoTHF, P = 0.040), S-adenosylmethionine (SAM, P = 0.004) and higher concentrations of folic acid (P = 0.041), homocysteine (Hcy, P = 0.006) and S-adenosylhomocysteine (SAH, P = 0.045) compared to control. Methylation levels of genomic DNA decreased significantly in the embryonic neural tube tissue of NTD samples. 132 differentially methylated regions (35 low methylated regions and 97 high methylated regions) were selected by microarray. Two genes (Siah1b, Prkx) in Wnt signal pathway demonstrated lower methylated regions (peak) and higher expression in NTDs (P<0.05; P<0.05). Results suggest that DNA hypomethylation was one of the possible epigenetic variations correlated with the occurrence of NTDs induced by folate dysmetabolism and that Siah1b, Prkx in Wnt pathway may be candidate genes for NTDs.

  17. Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model

    OpenAIRE

    Papasavvas, Christoforos A.; Wang, Yujiang; Trevelyan, Andrew J; Kaiser, Marcus

    2015-01-01

    Experimental results suggest that there are two distinct mechanisms of inhibition in cortical neuronal networks: subtractive and divisive inhibition. They modulate the input-output function of their target neurons either by increasing the input that is needed to reach maximum output or by reducing the gain and the value of maximum output itself, respectively. However, the role of these mechanisms on the dynamics of the network is poorly understood. We introduce a novel population model and nu...

  18. Intraportal Infusion of Ghrelin Could Inhibit Glucose-Stimulated GLP-1 Secretion by Enteric Neural Net in Wistar Rat

    Directory of Open Access Journals (Sweden)

    Xiyao Zhang

    2014-01-01

    Full Text Available As a regulator of food intake and energy metabolism, the role of ghrelin in glucose metabolism is still not fully understood. In this study, we determined the in vivo effect of ghrelin on incretin effect. We demonstrated that ghrelin inhibited the glucose-stimulated release of glucagon-like peptide-1 (GLP-1 when infused into the portal vein of Wistar rat. Hepatic vagotomy diminished the inhibitory effect of ghrelin on glucose-stimulated GLP-1 secretion. In addition, phentolamine, a nonselective α receptor antagonist, could recover the decrease of GLP-1 release induced by ghrelin infusion. Pralmorelin (an artificial growth hormone release peptide infusion into the portal vein could also inhibit the glucose-stimulated release of GLP-1. And growth hormone secretagogue receptor antagonist, [D-lys3]-GHRP-6, infusion showed comparable increases of glucose stimulated GLP-1 release compared to ghrelin infusion into the portal vein. The data showed that intraportal infusion of ghrelin exerted an inhibitory effect on GLP-1 secretion through growth hormone secretagogue receptor 1α (GHS1α receptor, which indicated that the downregulation of ghrelin secretion after food intake was necessary for incretin effect. Furthermore, our results suggested that the enteric neural net involved hepatic vagal nerve and sympathetic nerve mediated inhibition effect of ghrelin on incretin effect.

  19. Effects of acute aerobic exercise on neural correlates of attention and inhibition in adolescents with bipolar disorder.

    Science.gov (United States)

    Metcalfe, A W S; MacIntosh, B J; Scavone, A; Ou, X; Korczak, D; Goldstein, B I

    2016-05-17

    Executive dysfunction is common during and between mood episodes in bipolar disorder (BD), causing social and functional impairment. This study investigated the effect of acute exercise on adolescents with BD and healthy control subjects (HC) to test for positive or negative consequences on neural response during an executive task. Fifty adolescents (mean age 16.54±1.47 years, 56% female, 30 with BD) completed an attention and response inhibition task before and after 20 min of recumbent cycling at ~70% of age-predicted maximum heart rate. 3 T functional magnetic resonance imaging data were analyzed in a whole brain voxel-wise analysis and as regions of interest (ROI), examining Go and NoGo response events. In the whole brain analysis of Go trials, exercise had larger effect in BD vs HC throughout ventral prefrontal cortex, amygdala and hippocampus; the profile of these effects was of greater disengagement after exercise. Pre-exercise ROI analysis confirmed this 'deficit in deactivation' for BDs in rostral ACC and found an activation deficit on NoGo errors in accumbens. Pre-exercise accumbens NoGo error activity correlated with depression symptoms and Go activity with mania symptoms; no correlations were present after exercise. Performance was matched to controls and results survived a series of covariate analyses. This study provides evidence that acute aerobic exercise transiently changes neural response during an executive task among adolescents with BD, and that pre-exercise relationships between symptoms and neural response are absent after exercise. Acute aerobic exercise constitutes a biological probe that may provide insights regarding pathophysiology and treatment of BD.

  20. Effects of acute aerobic exercise on neural correlates of attention and inhibition in adolescents with bipolar disorder.

    Science.gov (United States)

    Metcalfe, A W S; MacIntosh, B J; Scavone, A; Ou, X; Korczak, D; Goldstein, B I

    2016-01-01

    Executive dysfunction is common during and between mood episodes in bipolar disorder (BD), causing social and functional impairment. This study investigated the effect of acute exercise on adolescents with BD and healthy control subjects (HC) to test for positive or negative consequences on neural response during an executive task. Fifty adolescents (mean age 16.54±1.47 years, 56% female, 30 with BD) completed an attention and response inhibition task before and after 20 min of recumbent cycling at ~70% of age-predicted maximum heart rate. 3 T functional magnetic resonance imaging data were analyzed in a whole brain voxel-wise analysis and as regions of interest (ROI), examining Go and NoGo response events. In the whole brain analysis of Go trials, exercise had larger effect in BD vs HC throughout ventral prefrontal cortex, amygdala and hippocampus; the profile of these effects was of greater disengagement after exercise. Pre-exercise ROI analysis confirmed this 'deficit in deactivation' for BDs in rostral ACC and found an activation deficit on NoGo errors in accumbens. Pre-exercise accumbens NoGo error activity correlated with depression symptoms and Go activity with mania symptoms; no correlations were present after exercise. Performance was matched to controls and results survived a series of covariate analyses. This study provides evidence that acute aerobic exercise transiently changes neural response during an executive task among adolescents with BD, and that pre-exercise relationships between symptoms and neural response are absent after exercise. Acute aerobic exercise constitutes a biological probe that may provide insights regarding pathophysiology and treatment of BD. PMID:27187236

  1. Neural crest migration: interplay between chemorepellents, chemoattractants, contact inhibition, epithelial-mesenchymal transition, and collective cell migration.

    Science.gov (United States)

    Theveneau, Eric; Mayor, Roberto

    2012-01-01

    Neural crest (NC) cells are induced at the border of the neural plate and subsequently leave the neuroepithelium during a delamination phase. This delamination involves either a complete or partial epithelium-to-mesenchyme transition, which is directly followed by an extensive cell migration. During migration, NC cells are exposed to a wide variety of signals controlling their polarity and directionality, allowing them to colonize specific areas or preventing them from invading forbidden zones. For instance, NC cells are restricted to very precise pathways by the presence of inhibitory signals at the borders of each route, such as Semaphorins, Ephrins, and Slit/Robo. Although specific NC chemoattractants have been recently identified, there is evidence that repulsive interactions between the cells, in a process called contact inhibition of locomotion, is one of the major driving forces behind directional migration. Interestingly, in cellular and molecular terms, the invasive behavior of NC is similar to the invasion of cancer cells during metastasis. NC cells eventually settle in various places and make an immense contribution to the vertebrate body. They form the major constituents of the skull, the peripheral nervous system, and the pigment cells among others, which show the remarkable diversity and importance of this embryonic-stem cell like cell population. Consequently, several birth defects and craniofacial disorders, such as Treacher Collins syndrome, are due to improper NC cell migration. PMID:23801492

  2. Blockade of microglial KATP -channel abrogates suppression of inflammatory-mediated inhibition of neural precursor cells.

    Science.gov (United States)

    Ortega, Francisco J; Vukovic, Jana; Rodríguez, Manuel J; Bartlett, Perry F

    2014-02-01

    Microglia positively affect neural progenitor cell physiology through the release of inflammatory mediators or trophic factors. We demonstrated previously that reactive microglia foster K(ATP) -channel expression and that blocking this channel using glibenclamide administration enhances striatal neurogenesis after stroke. In this study, we investigated whether the microglial K(ATP) -channel directly influences the activation of neural precursor cells (NPCs) from the subventricular zone using transgenic Csf1r-GFP mice. In vitro exposure of NPCs to lipopolysaccharide and interferon-gamma resulted in a significant decrease in precursor cell number. The complete removal of microglia from the culture or exposure to enriched microglia culture also decreased the precursor cell number. The addition of glibenclamide rescued the negative effects of enriched microglia on neurosphere formation and promoted a ∼20% improvement in precursor cell number. Similar results were found using microglial-conditioned media from isolated microglia. Using primary mixed glial and pure microglial cultures, glibenclamide specifically targeted reactive microglia to restore neurogenesis and increased the microglial production of the chemokine monocyte chemoattractant protein-1 (MCP-1). These findings provide the first direct evidence that the microglial K(ATP) -channel is a regulator of the proliferation of NPCs under inflammatory conditions.

  3. Inhibit yourself and understand the other : Neural basis of distinct processes underlying Theory of Mind

    NARCIS (Netherlands)

    van der Meer, Lisette; Groenewold, Nynke A.; Nolen, Willem A.; Pijnenborg, Marieke; Aleman, Andre

    2011-01-01

    Taking the perspective of somebody else (Theory of Mind; ToM) is an essential human ability depending on a large cerebral network comprising prefrontal and temporo-parietal regions. Recently, ToM was suggested to consist of two processes: (1) self-perspective inhibition and (2) belief reasoning. Mor

  4. Psychosis-Proneness and Neural Correlates of Self-Inhibition in Theory of Mind

    NARCIS (Netherlands)

    van der Meer, Lisette; Groenewold, Nynke A.; Pijnenborg, Marieke; Aleman, Andre

    2013-01-01

    Impaired Theory of Mind (ToM) has been repeatedly reported as a feature of psychotic disorders. ToM is crucial in social interactions and for the development of social behavior. It has been suggested that reasoning about the belief of others, requires inhibition of the self-perspective. We investiga

  5. Increased nuclear sphingoid base-1-phosphates and HDAC inhibition after fumonisin and FTY720-treatment: the link between epigenomic modifications and neural tube defects?

    Science.gov (United States)

    Introduction: Fumonisin B1 (FB1) is a mycotoxin produced by a common fungal contaminant of corn. Ingestion of FB1-contaminated food during early pregnancy is associated with increased risk for neural tube defects (NTDs). FB1 inhibits the enzyme ceramide synthase in de novo sphingolipid biosynthes...

  6. Zika Virus NS4A and NS4B Proteins Deregulate Akt-mTOR Signaling in Human Fetal Neural Stem Cells to Inhibit Neurogenesis and Induce Autophagy

    DEFF Research Database (Denmark)

    Liang, Qiming; Luo, Zhifei; Zeng, Jianxiong;

    2016-01-01

    development and autophagy regulation. Here, we show that ZIKV infection of human fetal neural stem cells (fNSCs) causes inhibition of the Akt-mTOR pathway, leading to defective neurogenesis and aberrant activation of autophagy. By screening the three structural proteins and seven nonstructural proteins...

  7. Positron Emission Tomography with [18F]FLT Revealed Sevoflurane-induced Inhibition of Neural Progenitor Cell Expansion in vivo

    Directory of Open Access Journals (Sweden)

    Shuliang eLiu

    2014-11-01

    Full Text Available Neural progenitor cell expansion is critical for normal brain development and an appropriate response to injury. During the brain growth spurt, exposures to general anesthetics which either block the N-methyl D-aspartate receptor or enhance the γ-aminobutyric acid receptor type A can disturb neuronal transduction. This effect can be detrimental to brain development. Until now, the effects of anesthetic exposure on neural progenitor cell expansion in vivo had seldom been reported. Here, minimally invasive micro positron emission tomography (microPET coupled with 3'-deoxy-3' [18F] fluoro-L-thymidine ([18F]FLT was utilized to assess the effects of sevoflurane exposure on neural progenitor cell proliferation. FLT, a thymidine analogue, is taken up by proliferating cells and phosphorylated in the cytoplasm, leading to its intracellular trapping. Intracellular retention of [18F]FLT, thus, represents an observable in vivo marker of cell proliferation. Here, postnatal day (PND 7 rats (n = 11/ group were exposed to 2.5% sevoflurane or room air for 9 hr. For up to two weeks following the exposure, standard uptake values (SUVs for [18F]-FLT in the hippocampal formation were significantly attenuated in the sevoflurane-exposed rats (p <0.0001, suggesting decreased uptake and retention of [18F]FLT (decreased proliferation in these regions. Four weeks following exposure, SUVs for [18F]FLT were comparable in the sevoflurane-exposed rats and in controls. Co-administration of 7-nitroindazole (7-NI, 30 mg/kg, n = 5, a selective inhibitor of neuronal nitric oxide synthase, significantly attenuated the SUVs for [18F]FLT in both the air-exposed (p = 0.00006 and sevoflurane-exposed rats (p = 0.0427 in the first week following the exposure. These findings suggested that microPET in couple with [18F]FLT as cell proliferation marker could be used as a non-invasive modality to monitor the sevoflurane-induced inhibition of neural progenitor cell proliferation in vivo.

  8. Prolonged propagation of rat neural stem cells relies on inhibiting autocrine/paracrine bone morphogenetic protein and platelet derived growth factor signals

    Institute of Scientific and Technical Information of China (English)

    Yirui Sun; Liangfu Zhou; Xing Wu; Hua Liu; Qiang Yuan; Ying Mao; Jin Hu

    2011-01-01

    Continuous expansion of rat neural stem cell lines has not been achieved due to proliferation arrest and spontaneous differentiation in vitro. In the current study, neural precursor cells derived from the subventricular zone of adult rats spontaneously underwent astroglial and oligodendroglial differentiation after limited propagation. This differentiation was largely induced by autocrine or paracrine bone morphogenetic protein and platelet derived growth factor signals. The results showed that, by inhibiting bone morphogenetic protein and platelet derived growth factor signals, adult rat neural precursor cells could be extensively cultured in vitro as tripotent stem cell lines. In addition to adult rat neural stem cells, we found that bone morphogenetic protein antagonists can promote the proliferation of human neural stem cells. Therefore, the present findings illustrated the role of autocrine or paracrine bone morphogenetic protein and platelet derived growth factor signaling in determining neural stem cell self-renewal and differentiation. By antagonizing both signals, the long-term propagation of rat neural stem cell lines can be achieved.

  9. Basic fibroblast growth factor increases the number of endogenous neural stem cells and inhibits the expression of amino methyl isoxazole propionic acid receptors in amyotrophic lateral sclerosis mice

    Institute of Scientific and Technical Information of China (English)

    Weihui Huang; Dawei Zang; Yi Lu; Ping Jiang

    2012-01-01

    This study aimed to investigate the number of amino methyl isoxazole propionic acid (AMPA) re-ceptors and production of endogenous neural stem cells in the SOD1G93AG1H transgenic mouse model of amyotrophic lateral sclerosis, at postnatal day 60 following administration of basic fibroblast growth factor (FGF-2). A radioligand binding assay and immunohistochemistry were used to estimate the number of AMPA receptors and endogenous neural stem cells respectively. Results showed that the number of AMPA receptors and endogenous neural stem cells in the brain stem and sensorimotor cortex were significantly increased, while motor function was significantly decreased at postnatal days 90 and 120. After administration of FGF-2 into mice, numbers of endogenous neural stem cells increased, while expression of AMPA receptors decreased, whilst motor functions were recovered. At postnatal day 120, the number of AMPA receptors was negatively correlated with the number of endogenous neural stem cells in model mice and FGF-2-treated mice. Our experimental findings indicate that FGF-2 can inhibit AMPA receptors and increase the number of endogenous neural stem cells, thus repairing neural injury in amyotrophic lateral sclerosis mice.

  10. The neural correlates of belief-bias inhibition: the impact of logic training.

    Science.gov (United States)

    Luo, Junlong; Tang, Xiaochen; Zhang, Entao; Stupple, Edward J N

    2014-12-01

    Functional Magnetic Resonance Imaging (fMRI) was used to investigate the brain activity associated with response change in a belief bias paradigm before and after logic training. Participants completed two sets of belief biased reasoning tasks. In the first set they were instructed to respond based on their empirical beliefs, and in the second - following logic training - they were instructed to respond logically. The comparison between conflict problems in the second scan versus in the first scan revealed differing activation for the left inferior frontal gyrus, left middle frontal gyrus, cerebellum, and precuneus. The scan was time locked to the presentation of the minor premise, and thus demonstrated effects of belief-logic conflict on neural activation earlier in the time course than has previously been shown in fMRI. These data, moreover, indicated that logical training results in changes in brain activity associated with cognitive control processing.

  11. HB-GAM (pleiotrophin) reverses inhibition of neural regeneration by the CNS extracellular matrix

    Science.gov (United States)

    Paveliev, Mikhail; Fenrich, Keith K.; Kislin, Mikhail; Kuja-Panula, Juha; Kulesskiy, Evgeny; Varjosalo, Markku; Kajander, Tommi; Mugantseva, Ekaterina; Ahonen-Bishopp, Anni; Khiroug, Leonard; Kulesskaya, Natalia; Rougon, Geneviève; Rauvala, Heikki

    2016-01-01

    Chondroitin sulfate (CS) glycosaminoglycans inhibit regeneration in the adult central nervous system (CNS). We report here that HB-GAM (heparin-binding growth-associated molecule; also known as pleiotrophin), a CS-binding protein expressed at high levels in the developing CNS, reverses the role of the CS chains in neurite growth of CNS neurons in vitro from inhibition to activation. The CS-bound HB-GAM promotes neurite growth through binding to the cell surface proteoglycan glypican-2; furthermore, HB-GAM abrogates the CS ligand binding to the inhibitory receptor PTPσ (protein tyrosine phosphatase sigma). Our in vivo studies using two-photon imaging of CNS injuries support the in vitro studies and show that HB-GAM increases dendrite regeneration in the adult cerebral cortex and axonal regeneration in the adult spinal cord. Our findings may enable the development of novel therapies for CNS injuries. PMID:27671118

  12. Prestimulus neural oscillations inhibit visual perception via modulation of response gain.

    Science.gov (United States)

    Chaumon, Maximilien; Busch, Niko A

    2014-11-01

    The ongoing state of the brain radically affects how it processes sensory information. How does this ongoing brain activity interact with the processing of external stimuli? Spontaneous oscillations in the alpha range are thought to inhibit sensory processing, but little is known about the psychophysical mechanisms of this inhibition. We recorded ongoing brain activity with EEG while human observers performed a visual detection task with stimuli of different contrast intensities. To move beyond qualitative description, we formally compared psychometric functions obtained under different levels of ongoing alpha power and evaluated the inhibitory effect of ongoing alpha oscillations in terms of contrast or response gain models. This procedure opens the way to understanding the actual functional mechanisms by which ongoing brain activity affects visual performance. We found that strong prestimulus occipital alpha oscillations-but not more anterior mu oscillations-reduce performance most strongly for stimuli of the highest intensities tested. This inhibitory effect is best explained by a divisive reduction of response gain. Ongoing occipital alpha oscillations thus reflect changes in the visual system's input/output transformation that are independent of the sensory input to the system. They selectively scale the system's response, rather than change its sensitivity to sensory information.

  13. Inhibition of glycogen synthase kinase-3 (GSK3) promotes the neural differentiation of full-term amniotic fluid-derived stem cells towards neural progenitor cells.

    Science.gov (United States)

    Gao, Liyang; Zhao, Mingyan; Ye, Wei; Huang, Jinzhi; Chu, Jiaqi; Yan, Shouquan; Wang, Chaojun; Zeng, Rong

    2016-08-01

    The amniotic fluid has a heterogeneous population of cells. Some human amniotic fluid-derived stem (hAFS) cells have been shown to harbor the potential to differentiate into neural cells. However, the neural differentiation efficiency of hAFS cells remains low. In this study, we isolated CD117-positive hAFS cells from amniotic fluid and then examined the pluripotency of these cells through the formation of embryoid bodies (EBs). Additionally, we induced the neural differentiation of these cells using neuroectodermal medium. This study revealed that the GSK3-beta inhibitor SB216763 was able to stimulate the proliferation of CD117-positive hAFS cells without influencing their undifferentiated state. Moreover, SB216763 can efficiently promote the neural differentiation of CD117-positive hAFS cells towards neural progenitor cells in the presence of DMEM/F12 and N2 supplement. These findings provide an easy and low-cost method to maintain the proliferation of hAFS cells, as well as induce an efficacious generation of neural progenitor cells from hAFS cells. Such induction of the neural commitment of hAFS cells may provide an option for the treatment of neurodegenerative diseases by hAFS cells-based therapies.

  14. Neural Inhibition of Dopaminergic Signaling Enhances Immunity in a Cell-Non-autonomous Manner.

    Science.gov (United States)

    Cao, Xiou; Aballay, Alejandro

    2016-09-12

    The innate immune system is the front line of host defense against microbial infections, but its rapid and uncontrolled activation elicits microbicidal mechanisms that have deleterious effects [1, 2]. Increasing evidence indicates that the metazoan nervous system, which responds to stimuli originating from both the internal and the external environment, functions as a modulatory apparatus that controls not only microbial killing pathways but also cellular homeostatic mechanisms [3-5]. Here we report that dopamine signaling controls innate immune responses through a D1-like dopamine receptor, DOP-4, in Caenorhabditis elegans. Chlorpromazine inhibition of DOP-4 in the nervous system activates a microbicidal PMK-1/p38 mitogen-activated protein kinase signaling pathway that enhances host resistance against bacterial infections. The immune inhibitory function of dopamine originates in CEP neurons and requires active DOP-4 in downstream ASG neurons. Our findings indicate that dopamine signaling from the nervous system controls immunity in a cell-non-autonomous manner and identifies the dopaminergic system as a potential therapeutic target for not only infectious diseases but also a range of conditions that arise as a consequence of malfunctioning immune responses.

  15. Minocycline inhibited the pro-apoptotic effect of microglia on neural progenitor cells and protected their neuronal differentiation in vitro.

    Science.gov (United States)

    Liu, Xuqing; Su, Huanxing; Chu, Tak-Ho; Guo, Anchen; Wu, Wutian

    2013-05-10

    Neural progenitor cell (NPC) transplantation offers great potential to treat spinal cord injury (SCI), but their efficiency is limited by poor survival and neuronal differentiation after transplantation. In the injury site, microglia may become activated and participate in the inflammation reaction. In vitro studies indicated that activated microglia might impair NPC survival and neuronal differentiation, but resting microglia did not. This study investigated the potential of minocycline to modify the negative effects of activated microglia on NPCs in vitro. First, the direct effects of minocycline on NPCs were tested. The results showed that at the concentration of 10μg/ml or lower, minocycline did not affect NPC survival and proliferation, but impaired neuronal differentiation. Then microglia were activated with lipopolysaccharide (LPS) or treated with LPS plus minocycline (LPSMC), and the effects of conditioned media on NPC apoptosis and differentiation were studied. The results showed that, compared with LPS treatment group, the microglia conditioned media of LPSMC treatment group resulted in a significantly lower apoptotic rate of NPCs, and increased the neuronal differentiation of NPCs. This suggested that minocycline might inhibit the negative effects of microglia on NPCs, and have the potential to support the survival and neuronal differentiation of transplanted NPCs for SCI.

  16. The neural substrates of response inhibition to negative information across explicit and implicit tasks in GAD patients: Electrophysiological evidence from an ERP study

    Directory of Open Access Journals (Sweden)

    Fengqiong eYu

    2015-03-01

    Full Text Available Background: It has been established that the inability to inhibit a response to negative stimuli is the genesis of anxiety. However, the neural substrates of response inhibition to sad faces across explicit and implicit tasks in general anxiety disorder (GAD patients remain unclear.Methods: Electrophysiological data were recorded when subjects performed two modified emotional go/no-go tasks in which neutral and sad faces were presented: one task was explicit (emotion categorization, and the other task was implicit (gender categorization.Results: In the explicit task, electrophysiological evidence showed decreased amplitudes of no-go/go difference waves at the N2 interval in the GAD group compared to the control group. However, in the implicit task, the amplitudes of no-go/go difference waves at the N2 interval showed a reversed trend. Source localization analysis on no-go/N2 components revealed a decreased current source density (CSD in the right dorsal lateral prefrontal cortex in GAD individuals relative to controls. In the implicit task, the left superior temporal gyrus and the left inferior parietal lobe showed enhanced activation in GAD individuals and may compensate for the dysfunction of the right dorsal lateral prefrontal cortex.Conclusions: These findings indicated that the processing of response inhibition to socially sad faces in GAD individuals was interrupted in the explicit task. However, this processing was preserved in the implicit task. The neural substrates of response inhibition to sad faces were dissociated between implicit and explicit tasks.

  17. Altered neural connectivity during response inhibition in adolescents with attention-deficit/hyperactivity disorder and their unaffected siblings

    Directory of Open Access Journals (Sweden)

    Daan van Rooij

    2015-01-01

    Discussion: Subjects with ADHD fail to integrate activation within the response inhibition network and to inhibit connectivity with task-irrelevant regions. Unaffected siblings show similar alterations only during failed stop trials, as well as unique suppression of motor areas, suggesting compensatory strategies. These findings support the role of altered functional connectivity in understanding the neurobiology and familial transmission of ADHD.

  18. Buffering Social Influence: Neural Correlates of Response Inhibition Predict Driving Safety in the Presence of a Peer

    OpenAIRE

    Cascio, Christopher N.; Carp, Joshua; O'Donnell, Matthew Brook; Tinney, Francis J.; Bingham, C. Raymond; Shope, Jean T.; Ouimet, Marie Claude; Pradhan, Anuj K.; Simons-Morton, Bruce G.; Falk, Emily B.

    2015-01-01

    Adolescence is a period characterized by increased sensitivity to social cues, as well as increased risk-taking in the presence of peers. For example, automobile crashes are the leading cause of death for adolescents, and driving with peers increases the risk of a fatal crash. Growing evidence points to an interaction between neural systems implicated in cognitive control and social and emotional context in predicting adolescent risk. We tested such a relationship in recently licensed teen dr...

  19. Dynamin-related Protein 1 Inhibition Mitigates Bisphenol A-mediated Alterations in Mitochondrial Dynamics and Neural Stem Cell Proliferation and Differentiation.

    Science.gov (United States)

    Agarwal, Swati; Yadav, Anuradha; Tiwari, Shashi Kant; Seth, Brashket; Chauhan, Lalit Kumar Singh; Khare, Puneet; Ray, Ratan Singh; Chaturvedi, Rajnish Kumar

    2016-07-29

    The regulatory dynamics of mitochondria comprises well orchestrated distribution and mitochondrial turnover to maintain the mitochondrial circuitry and homeostasis inside the cells. Several pieces of evidence suggested impaired mitochondrial dynamics and its association with the pathogenesis of neurodegenerative disorders. We found that chronic exposure of synthetic xenoestrogen bisphenol A (BPA), a component of consumer plastic products, impaired autophagy-mediated mitochondrial turnover, leading to increased oxidative stress, mitochondrial fragmentation, and apoptosis in hippocampal neural stem cells (NSCs). It also inhibited hippocampal derived NSC proliferation and differentiation, as evident by the decreased number of BrdU- and β-III tubulin-positive cells. All these effects were reversed by the inhibition of oxidative stress using N-acetyl cysteine. BPA up-regulated the levels of Drp-1 (dynamin-related protein 1) and enhanced its mitochondrial translocation, with no effect on Fis-1, Mfn-1, Mfn-2, and Opa-1 in vitro and in the hippocampus. Moreover, transmission electron microscopy studies suggested increased mitochondrial fission and accumulation of fragmented mitochondria and decreased elongated mitochondria in the hippocampus of the rat brain. Impaired mitochondrial dynamics by BPA resulted in increased reactive oxygen species and malondialdehyde levels, disruption of mitochondrial membrane potential, and ATP decline. Pharmacological (Mdivi-1) and genetic (Drp-1siRNA) inhibition of Drp-1 reversed BPA-induced mitochondrial dysfunctions, fragmentation, and apoptosis. Interestingly, BPA-mediated inhibitory effects on NSC proliferation and neuronal differentiations were also mitigated by Drp-1 inhibition. On the other hand, Drp-1 inhibition blocked BPA-mediated Drp-1 translocation, leading to decreased apoptosis of NSC. Overall, our studies implicate Drp-1 as a potential therapeutic target against BPA-mediated impaired mitochondrial dynamics and

  20. Valproic acid induces differentiation and inhibition of proliferation in neural progenitor cells via the beta-catenin-Ras-ERK-p21Cip/WAF1 pathway

    Directory of Open Access Journals (Sweden)

    Arenas Ernest

    2008-12-01

    Full Text Available Abstract Background Valproic acid (VPA, a commonly used mood stabilizer that promotes neuronal differentiation, regulates multiple signaling pathways involving extracellular signal-regulated kinase (ERK and glycogen synthase kinase3β (GSK3β. However, the mechanism by which VPA promotes differentiation is not understood. Results We report here that 1 mM VPA simultaneously induces differentiation and reduces proliferation of basic fibroblast growth factor (bFGF-treated embryonic day 14 (E14 rat cerebral cortex neural progenitor cells (NPCs. The effects of VPA on the regulation of differentiation and inhibition of proliferation occur via the ERK-p21Cip/WAF1 pathway. These effects, however, are not mediated by the pathway involving the epidermal growth factor receptor (EGFR but via the pathway which stabilizes Ras through β-catenin signaling. Stimulation of differentiation and inhibition of proliferation in NPCs by VPA occur independently and the β-catenin-Ras-ERK-p21Cip/WAF1 pathway is involved in both processes. The independent regulation of differentiation and proliferation in NPCs by VPA was also demonstrated in vivo in the cerebral cortex of developing rat embryos. Conclusion We propose that this mechanism of VPA action may contribute to an explanation of its anti-tumor and neuroprotective effects, as well as elucidate its role in the independent regulation of differentiation and inhibition of proliferation in the cerebral cortex of developing rat embryos.

  1. Inhibition of the histone demethylase Kdm5b promotes neurogenesis and derepresses Reln (reelin) in neural stem cells from the adult subventricular zone of mice.

    Science.gov (United States)

    Zhou, Qiong; Obana, Edwin A; Radomski, Kryslaine L; Sukumar, Gauthaman; Wynder, Christopher; Dalgard, Clifton L; Doughty, Martin L

    2016-02-15

    The role of epigenetic regulators in the control of adult neurogenesis is largely undefined. We show that the histone demethylase enzyme Kdm5b (Jarid1b) negatively regulates neurogenesis from adult subventricular zone (SVZ) neural stem cells (NSCs) in culture. shRNA-mediated depletion of Kdm5b in proliferating adult NSCs decreased proliferation rates and reduced neurosphere formation in culture. When transferred to differentiation culture conditions, Kdm5b-depleted adult NSCs migrated from neurospheres with increased velocity. Whole-genome expression screening revealed widespread transcriptional changes with Kdm5b depletion, notably the up-regulation of reelin (Reln), the inhibition of steroid biosynthetic pathway component genes and the activation of genes with intracellular transport functions in cultured adult NSCs. Kdm5b depletion increased extracellular reelin concentration in the culture medium and increased phosphorylation of the downstream reelin signaling target Disabled-1 (Dab1). Sequestration of extracellular reelin with CR-50 reelin-blocking antibodies suppressed the increase in migratory velocity of Kdm5b-depleted adult NSCs. Chromatin immunoprecipitation revealed that Kdm5b is present at the proximal promoter of Reln, and H3K4me3 methylation was increased at this locus with Kdm5b depletion in differentiating adult NSCs. Combined the data suggest Kdm5b negatively regulates neurogenesis and represses Reln in neural stem cells from the adult SVZ. PMID:26739753

  2. GABAA receptor-mediated feedforward and feedback inhibition differentially modulate the gain and the neural code transformation in hippocampal CA1 pyramidal cells.

    Science.gov (United States)

    Jang, Hyun Jae; Park, Kyerl; Lee, Jaedong; Kim, Hyuncheol; Han, Kyu Hun; Kwag, Jeehyun

    2015-12-01

    Diverse variety of hippocampal interneurons exists in the CA1 area, which provides either feedforward (FF) or feedback (FB) inhibition to CA1 pyramidal cell (PC). However, how the two different inhibitory network architectures modulate the computational mode of CA1 PC is unknown. By investigating the CA3 PC rate-driven input-output function of CA1 PC using in vitro electrophysiology, in vitro-simulation of inhibitory network, and in silico computational modeling, we demonstrated for the first time that GABAA receptor-mediated FF and FB inhibition differentially modulate the gain, the spike precision, the neural code transformation and the information capacity of CA1 PC. Recruitment of FF inhibition buffered the CA1 PC spikes to theta-frequency regardless of the input frequency, abolishing the gain and making CA1 PC insensitive to its inputs. Instead, temporal variability of the CA1 PC spikes was increased, promoting the rate-to-temporal code transformation to enhance the information capacity of CA1 PC. In contrast, the recruitment of FB inhibition sub-linearly transformed the input rate to spike output rate with high gain and low spike temporal variability, promoting the rate-to-rate code transformation. These results suggest that GABAA receptor-mediated FF and FB inhibitory circuits could serve as network mechanisms for differentially modulating the gain of CA1 PC, allowing CA1 PC to switch between different computational modes using rate and temporal codes ad hoc. Such switch will allow CA1 PC to efficiently respond to spatio-temporally dynamic inputs and expand its computational capacity during different behavioral and neuromodulatory states in vivo.

  3. Acute Stressors Reduce Neural Inhibition to Food Cues and Increase Eating Among Binge Eating Disorder Symptomatic Women

    Science.gov (United States)

    Lyu, Zhenyong; Jackson, Todd

    2016-01-01

    Stressors can trigger binge-eating but researchers have yet to consider their effects on both neural responses to food cues and food consumption among those at risk. In this experiment, we examined the impact of acute stressors on neural activation to food images and subsequent food consumption within binge-eating disorder (BED) and non-eating disordered control groups. Eighteen women meeting DSM-IV BED criteria and 26 women serving as non-eating disordered controls were randomly assigned to unpleasant stressor (painful cold pressor test (CPT) followed by negative performance feedback) or less unpleasant stressor (non-painful sensory discrimination task followed by positive performance feedback) conditions. Subsequently, they were scanned with functional magnetic resonance imaging (fMRI) while viewing food and neutral images. After the scans, participants completed a self-report battery in an environment conducive to snacking. During exposure to food images, BED-symptomatic women in the unpleasant stressor condition reported more liking of high calorie food images and showed less activation in one inhibitory area, the hippocampus, compared to controls in this condition. BED-symptomatic women exposed to unpleasant stressors also consumed more chocolate than any other group during the post-scan questionnaire completion. Crucially, reduced hippocampal activation to high calorie food images predicted more chocolate consumption following fMRI scans within the entire sample. This experiment provides initial evidence suggesting unpleasant acute stressors contribute to reduced inhibitory region responsiveness in relation to external food cues and later food consumption among BED-symptomatic women. PMID:27790097

  4. Dissociable identity- and modality-specific neural representations as revealed by cross-modal nonspatial inhibition of return.

    Science.gov (United States)

    Chi, Yukai; Yue, Zhenzhu; Liu, Yupin; Mo, Lei; Chen, Qi

    2014-08-01

    There are ongoing debates on whether object concepts are coded as supramodal identity-based or modality-specific representations in the human brain. In this fMRI study, we adopted a cross-modal "prime-neutral cue-target" semantic priming paradigm, in which the prime-target relationship was manipulated along both the identity and the modality dimensions. The prime and the target could refer to either the same or different semantic identities, and could be delivered via either the same or different sensory modalities. By calculating the main effects and interactions of this 2 (identity cue validity: "Identity_Cued" vs. "Identity_Uncued") × 2 (modality cue validity: "Modality_Cued" vs. "Modality_Uncued") factorial design, we aimed at dissociating three neural networks involved in creating novel identity-specific representations independent of sensory modality, in creating modality-specific representations independent of semantic identity, and in evaluating changes of an object along both the identity and the modality dimensions, respectively. Our results suggested that bilateral lateral occipital cortex was involved in creating a new supramodal semantic representation irrespective of the input modality, left dorsal premotor cortex, and left intraparietal sulcus were involved in creating a new modality-specific representation irrespective of its semantic identity, and bilateral superior temporal sulcus was involved in creating a representation when the identity and modality properties were both cued or both uncued. In addition, right inferior frontal gyrus showed enhanced neural activity only when both the identity and the modality of the target were new, indicating its functional role in novelty detection.

  5. Protective Effect of Electroacupuncture on Neural Myelin Sheaths is Mediated via Promotion of Oligodendrocyte Proliferation and Inhibition of Oligodendrocyte Death After Compressed Spinal Cord Injury.

    Science.gov (United States)

    Huang, Siqin; Tang, Chenglin; Sun, Shanquan; Cao, Wenfu; Qi, Wei; Xu, Jin; Huang, Juan; Lu, Weitian; Liu, Qian; Gong, Biao; Zhang, Yi; Jiang, Jin

    2015-12-01

    Electroacupuncture (EA) has been used worldwide to treat demyelinating diseases, but its therapeutic mechanism is poorly understood. In this study, a custom-designed model of compressed spinal cord injury (CSCI) was used to induce demyelination. Zusanli (ST36) and Taixi (KI3) acupoints of adult rats were stimulated by EA to demonstrate its protective effect. At 14 days after EA, both locomotor skills and ultrastructural features of myelin sheath were significantly improved. Phenotypes of proliferating cells were identified by double immunolabeling of 5-ethynyl-2'-deoxyuridine with antibodies to cell markers: NG2 [oligodendrocyte precursor cell (OPC) marker], 2',3'-cyclic-nucleotide 3'-phosphodiesterase (CNPase) (oligodendrocyte marker), and glial fibrillary acidic protein (GFAP) (astrocyte marker). EA enhanced the proliferation of OPCs and CNPase, as well as the differentiation of OPCs by promoting Olig2 (the basic helix-loop-helix protein) and attenuating Id2 (the inhibitor of DNA binding 2). EA could also improve myelin basic protein (MBP) and protect existing oligodendrocytes from apoptosis by inhibiting caspase-12 (a representative of endoplasmic reticulum stress) and cytochrome c (an apoptotic factor and hallmark of mitochondria). Therefore, our results indicate that the protective effect of EA on neural myelin sheaths is mediated via promotion of oligodendrocyte proliferation and inhibition of oligodendrocyte death after CSCI.

  6. Dopamine-signalled reward predictions generated by competitive excitation and inhibition in a spiking neural network model

    Directory of Open Access Journals (Sweden)

    Paul eChorley

    2011-05-01

    Full Text Available Dopaminergic neurons in the mammalian substantia nigra displaycharacteristic phasic responses to stimuli which reliably predict thereceipt of primary rewards. These responses have been suggested toencode reward prediction-errors similar to those used in reinforcementlearning. Here, we propose a model of dopaminergic activity in whichprediction error signals are generated by the joint action ofshort-latency excitation and long-latency inhibition, in a networkundergoing dopaminergic neuromodulation of both spike-timing dependentsynaptic plasticity and neuronal excitability. In contrast toprevious models, sensitivity to recent events is maintained by theselective modification of specific striatal synapses, efferent tocortical neurons exhibiting stimulus-specific, temporally extendedactivity patterns. Our model shows, in the presence of significantbackground activity, (i a shift in dopaminergic response from rewardto reward predicting stimuli, (ii preservation of a response tounexpected rewards, and (iii a precisely-timed below-baseline dip inactivity observed when expected rewards are omitted.

  7. PANP is a novel O-glycosylated PILRα ligand expressed in neural tissues

    International Nuclear Information System (INIS)

    Research highlights: → A Novel molecule, PANP, was identified to be a PILRα ligand. → Sialylated O-glycan structures on PANP were required for PILRα recognition. → Transcription of PANP was mainly observed in neural tissues. → PANP seems to be involved in immune regulation as a ligand for PILRα. -- Abstract: PILRα is an immune inhibitory receptor possessing an immunoreceptor tyrosine-based inhibitory motif (ITIM) in its cytoplasmic domain enabling it to deliver inhibitory signals. Binding of PILRα to its ligand CD99 is involved in immune regulation; however, whether there are other PILRα ligands in addition to CD99 is not known. Here, we report that a novel molecule, PILR-associating neural protein (PANP), acts as an additional ligand for PILRα. Transcription of PANP was mainly observed in neural tissues. PILRα-Ig fusion protein bound cells transfected with PANP and the transfectants stimulated PILRα reporter cells. Specific O-glycan structures on PANP were found to be required for PILR recognition of this ligand. These results suggest that PANP is involved in immune regulation as a ligand of the PILRα.

  8. Fluoxetine up-regulates expression of cellular FLICE-inhibitory protein and inhibits LPS-induced apoptosis in hippocampus-derived neural stem cell

    International Nuclear Information System (INIS)

    Fluoxetine is a widely used antidepressant compound which inhibits the reuptake of serotonin in the central nervous system. Recent studies have shown that fluoxetine can promote neurogenesis and improve the survival rate of neurons. However, whether fluoxetine modulates the proliferation or neuroprotection effects of neural stem cells (NSCs) needs to be elucidated. In this study, we demonstrated that 20 μM fluoxetine can increase the cell proliferation of NSCs derived from the hippocampus of adult rats by MTT test. The up-regulated expression of Bcl-2, Bcl-xL and the cellular FLICE-inhibitory protein (c-FLIP) in fluoxetine-treated NSCs was detected by real-time RT-PCR. Our results further showed that fluoxetine protects the lipopolysaccharide-induced apoptosis in NSCs, in part, by activating the expression of c-FLIP. Moreover, c-FLIP induction by fluoxetine requires the activation of the c-FLIP promoter region spanning nucleotides -414 to -133, including CREB and SP1 sites. This effect appeared to involve the phosphatidylinositol-3-kinase-dependent pathway. Furthermore, fluoxetine treatment significantly inhibited the induction of proinflammatory factor IL-1β, IL-6, and TNF-α in the culture medium of LPS-treated NSCs (p < 0.01). The results of high performance liquid chromatography coupled to electrochemical detection further confirmed that fluoxentine increased the functional production of serotonin in NSCs. Together, these data demonstrate the specific activation of c-FLIP by fluoxetine and indicate the novel role of fluoxetine for neuroprotection in the treatment of depression

  9. Inhibition of HSP90 Promotes Neural Stem Cell Survival from Oxidative Stress through Attenuating NF-κB/p65 Activation

    Science.gov (United States)

    Jiang, Wenkai; Zhou, Lin

    2016-01-01

    Stem cell survival after transplantation determines the efficiency of stem cell treatment, which develops as a novel potential therapy for several central nervous system (CNS) diseases in recent decades. The engrafted stem cells face the damage of oxidative stress, inflammation, and immune response at the lesion point in host. Among the damaging pathologies, oxidative stress directs stem cells to apoptosis and even death through several signalling pathways and DNA damage. However, the in-detail mechanism of stem cell survival from oxidative stress has not been revealed clearly. Here, in this study, we used hydrogen peroxide (H2O2) to induce the oxidative damage on neural stem cells (NSCs). The damage was in consequence demonstrated involving the activation of heat shock protein 90 (HSP90) and NF-κB/p65 signalling pathways. Further application of the pharmacological inhibitors, respectively, targeting at each signalling indicated an upper-stream role of HSP90 upon NF-κB/p65 on NSCs survival. Preinhibition of HSP90 with the specific inhibitor displayed a significant protection on NSCs against oxidative stress. In conclusion, inhibition of HSP90 would attenuate NF-κB/p65 activation by oxidative induction and promote NSCs survival from oxidative damage. The HSP90/NF-κB mechanism provides a new evidence on rescuing NSCs from oxidative stress and also promotes the stem cell application on CNS pathologies.

  10. 一种基于大脑皮层结构的侧抑制神经网络%A lateral inhibition neural network based on neocortex topology

    Institute of Scientific and Technical Information of China (English)

    杨刚; 乔俊飞; 薄迎春; 韩红桂

    2013-01-01

    借鉴仿生学原理,基于大脑皮层结构提出一种新型侧抑制神经网络(S-LINN)模型。通过模拟大脑皮层内锥体神经元和抑制神经元的连接特点,在多层结构的S-LINN的不同层神经元之间引入跨越连接,同时在隐含层内神经元之间进行信息的侧向抑制传输。引入的两种连接机制有效地提高了网络处理问题的能力,与其他网络相比能够以更精简的结构较好地解决实际问题。通过对乳腺癌诊断数据集和异或问题的求解,表明了S-LINN网络不但能够获得较高的训练精度,而且具有更强的泛化能力。%On the basis of the connective mode and information transmit mechanism of cerebral cortex, a novel lateral inhibition neural network model with span connection(S-LINN) is proposed. Combining the liminar organization of cerebral cortex, and fully considering the lateral inhibition connection between interneurons and the pyramidal neurons, the proposed S-LINN transforms information to other neurons in different layers, which is used to enhance response contrast and advance the network representation, respectively. The effectiveness and superiority of the proposed network is compared with other popular approaches on two benchmark problems in the areas of real-world regression and classification problems. Simulation results show that the proposed S-LINN can achieve the higher accuracy of approximation and generalization with the comparably compact network structure.

  11. [18F]FDG labeling of neural stem cells for in vivo cell tracking with positron emission tomography : inhibition of tracer release by phloretin

    NARCIS (Netherlands)

    Stojanov, Katica; de Vries, Erik F. J.; Hoekstra, Dick; van Waarde, Aren; Dierckx, Rudi A. J. O.; Zuhorn, Inge S.

    2012-01-01

    The introduction of neural stem cells into the brain has promising therapeutic potential for the treatment of neurodegenerative diseases. To monitor the cellular replacement therapy, that is, to determine stem cell migration, survival, and differentiation, in vivo tracking methods are needed. Ideall

  12. Inhibition of Drp1 mitochondrial translocation provides neural protection in dopaminergic system in a Parkinson’s disease model induced by MPTP

    Science.gov (United States)

    Filichia, Emily; Hoffer, Barry; Qi, Xin; Luo, Yu

    2016-01-01

    Accumulating evidence suggest mitochondria-mediated pathways play an important role in dopaminergic neuronal cell death in Parkinson’s disease (PD). Drp1, a key regulator of mitochondrial fission, has been shown to be activated and translocated to mitochondria under stress, leading to excessive mitochondria fission and dopaminergic neuronal death in vitro. However, whether Drp1 inhibition can lead to long term stable preservation of dopaminergic neurons in PD-related mouse models remains unknown. In this study, using a classical MPTP animal PD model, we showed for the first time Drp1 activation and mitochondrial translocation in vivo after MPTP administration. Inhibition of Drp1 activation by a selective peptide inhibitor P110, blocked MPTP-induced Drp1 mitochondrial translocation and attenuated dopaminergic neuronal loss, dopaminergic nerve terminal damage and behavioral deficits caused by MPTP. MPTP-induced microglial activation and astrogliosis were not affected by P110 treatment. Instead, inhibition of Drp1 mitochondrial translocation diminished MPTP-induced p53, BAX and PUMA mitochondrial translocation. This study demonstrates that inhibition of Drp1 hyperactivation by a Drp1 peptide inhibitor P110 is neuroprotective in a MPTP animal model. Our data also suggest that the protective effects of P110 treatment might be mediated by inhibiting the p53 mediated apoptotic pathways in neurons through inhibition of Drp1-dependent p53 mitochondrial translocation. PMID:27619562

  13. Carbon-ion beams effectively induce growth inhibition and apoptosis in human neural stem cells compared with glioblastoma A172 cells

    International Nuclear Information System (INIS)

    Carbon-ion radiotherapy (CIRT) holds promise in the treatment of glioblastoma, an aggressive X-ray–resistant brain tumor. However, since glioblastoma cells show a highly invasive nature, carbon-ion (C-ion) irradiation of normal tissues surrounding the tumor is inevitable. Recent studies have revealed the existence of neural stem cells in the adult brain. Therefore, the damaging effect of C-ion beams on the neural stem cells has to be carefully considered in the treatment planning of CIRT. Here, we investigated the growth and death mode of human neural stem cells (hNSCs) and glioblastoma A172 cells after X-ray or C-ion beam irradiation. The X-ray dose resulting in a 50% growth rate (D50) was 0.8 Gy in hNSCs and 3.0 Gy in A172 cells, while the D50 for C-ion beams was 0.4 Gy in hNSCs and 1.6 Gy in A172 cells; the relative biological effectiveness value of C-ion beams was 2.0 in hNSCs and 1.9 in A172 cells. Importantly, both X-rays and C-ion beams preferentially induced apoptosis, not necrosis, in hNSCs; however, radiation-induced apoptosis was less evident in A172 cells. The apoptosis-susceptible nature of the irradiated hNSCs was associated with prolonged upregulation of phosphorylated p53, whereas the apoptosis-resistant nature of A172 cells was associated with a high basal level of nuclear factor kappa B expression. Taken together, these data indicate that apoptosis is the major cell death pathway in hNSCs after irradiation. The high sensitivity of hNSCs to C-ion beams underscores the importance of careful target volume delineation in the treatment planning of CIRT for glioblastoma. (author)

  14. Impaired TGF-beta induced growth inhibition contributes to the increased proliferation rate of neural stem cells harboring mutant p53

    DEFF Research Database (Denmark)

    Kumar, P.; Naumann, U.; Aigner, L.;

    2015-01-01

    -beta-induced p21 expression could, in contrast, only be detected in p53wt/wt but not in p53mut/mut NPC. Conversely, inhibition of TGF-beta signaling using SB431542 increased proliferation of p53wt/wt but not of p53mut/mut NPC. In conclusion, our data suggest that the TGF-beta induced growth arrest in NPC depends......, NPC derived from p53mut/mut mice were insensitive to TGF-beta induced growth arrest. Still, the canonical TGF-beta signaling pathway remained functional in the absence of p53 signaling and expression of key proteins as well as phosphorylation and nuclear translocation of SMAD2 were unaltered. TGF...

  15. Examining the Neural and Astroglial Protective Effects of Cellular Prion Protein Expression and Cell Death Protease Inhibition in Mouse Cerebrocortical Mixed Cultures.

    Science.gov (United States)

    Wang, Kevin K W; Yang, Zhihui; Chiu, Allen; Lin, Fan; Rubenstein, Richard

    2016-09-01

    Overexpression of cellular prion protein, PrP(C), has cytoprotective effects against neuronal injuries. Inhibition of cell death-associated proteases such as necrosis-linked calpain and apoptosis-linked caspase are also neuroprotective. Here, we systematically studied how PrP(C) expression levels and cell death protease inhibition affect cytotoxic challenges to both neuronal and glial cells in mouse cerebrocortical mixed cultures (CCM). Primary CCM derived from three mouse lines expressing no (PrP(C) knockout mice (PrPKO)), normal (wild-type (wt)), or high (tga20) levels of PrP(C) were subjected to necrotic challenge (calcium ionophore A23187) and apoptotic challenge (staurosporine (STS)). CCM which originated from tga20 mice provided the most robust neuron-astroglia protective effects against necrotic and early apoptotic cell death (lactate dehydrogenase (LDH) release) at 6 h but subsequently lost its cytoprotective effects. In contrast, PrPKO-derived cultures displayed elevated A23187- and STS-induced cell death at 24 h. Calpain inhibitor SNJ-1945 protected against A23187 challenge at 6 h in CCM from all three mouse lines but protected only against A23187 and STS treatments by 24 h in the PrPKO line. In parallel, caspase inhibitor Z-D-DCB protected against pro-apoptotic STS challenge at 6 and 24 h. Furthermore, we also examined αII-spectrin breakdown products (primarily from neurons) and glial fibrillary acidic protein (GFAP) breakdown products (from astroglia) as cytoskeletal proteolytic biomarkers. Overall, it appeared that both neurons and astroglial cells were less vulnerable to proteolytic attack during A23187 and STS challenges in tga20-derived cultures but more vulnerable in PrPKO-derived cultures. In addition, calpain and caspase inhibitors provide further protection against respective protease attacks on these neuronal and glial cytoskeletal proteins in CCM regardless of mouse-line origin. Lastly, some synergistic cytoprotective effects between Pr

  16. Knockdown of α-synuclein in cerebral cortex improves neural behavior associated with apoptotic inhibition and neurotrophin expression in spinal cord transected rats.

    Science.gov (United States)

    Wang, You-Cui; Feng, Guo-Ying; Xia, Qing-Jie; Hu, Yue; Xu, Yang; Xiong, Liu-Lin; Chen, Zhi-Wei; Wang, Hang-Ping; Wang, Ting-Hua; Zhou, Xue

    2016-04-01

    Spinal cord injury (SCI) often causes severe functional impairment with poor recovery. The treatment, however, is far from satisfaction, and the mechanisms remain unclear. By using proteomics and western blot, we found spinal cord transection (SCT) resulted in a significant down-regulation of α-synuclein (SNCA) in the motor cortex of SCT rats at 3 days post-operation. In order to detect the role of SNCA, we used SNCA-ORF/shRNA lentivirus to upregulate or knockdown SNCA expression. In vivo, SNCA-shRNA lentivirus injection into the cerebral cortex motor area not only inhibited SNCA expression, but also significantly enhanced neurons' survival, and attenuated neuronal apoptosis, as well as promoted motor and sensory function recovery in hind limbs. While, overexpression SNCA exhibited the opposite effects. In vitro, cortical neurons transfected with SNCA-shRNA lentivirus gave rise to an optimal neuronal survival and neurite outgrowth, while it was accompanied by reverse efficiency in SNCA-ORF group. In molecular level, SNCA silence induced the upregulation of Bcl-2 and the downregulation of Bax, and the expression of NGF, BDNF and NT3 was substantially upregulated in cortical neurons. Together, endogenous SNCA play a crucial role in motor and sensory function regulation, in which, the underlying mechanism may be linked to the regulation of apoptosis associated with apoptotic gene (Bax, Bcl2) and neurotrophic factors expression (NGF, BDNF and NT3). These finds provide novel insights to understand the role of SNCA in cerebral cortex after SCT, and it may be as a novel treatment target for SCI repair in future clinic trials. PMID:26822976

  17. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  18. 丙戊酸钠通过p21调控大鼠神经干细胞的增殖%Sodium valproate inhibits proliferation in rat neural stem cells through p21 pathway

    Institute of Scientific and Technical Information of China (English)

    黄磊; 储卫华; 袁继超; 赵明月; 陈图南; 蒋周阳; 林江凯; 冯华

    2013-01-01

    Objective To determine the effect of sodium valproate ( VPA ) on the proliferation and cell cycle in adult female rat spinal neural stem cells (NSCs).Methods Cell proliferation was assessed by CCK-8 assay after the cells were treated with VPA at different concentrations of 10-5 , 10-4 , 10-3, 10-2, 10-1, 1 or 10 mmol/L for 0, 24, 48 or 72 h.After NSCs were treated with VPA at a dose of 10-5 and 1 mmol/L for 48 h, cell cycle was analyzed by flow cytometry and the expression of p21 (cyclin-dependent kinase inhibitor) was detected by PCR and Western blot analysis.Results CCK-8 staining colorimetry showed that the proliferation of NSCs was markedly inhibited in a time-dependent manner when the concentration of VPA was more than 10-5mmol/L.Flow cytometry indicated more cultured NSCs were arrested in the G0/G1 phase and fewer at the S phase after being treated with VPA, which indicated that VPA arrested the transition of NSCs from G0/G1 phase to S phase.PCR and Western blot analysis indicated that VPA enhanced the expression of p21 at mRNA and protein levels (P < 0.05).Conclusion VPA may arrest NSCs at G0/G1 by increasing the expression of p21, and then finally inhibit the proliferation of NSCs.%目的 探讨丙戊酸钠(sodium valproate,VPA)对体外培养的成年雌大鼠脊髓神经干细胞(neural stem cells,NSCs)增殖的影响.方法 采用不同浓度的VPA(10-5、10-4、10-3、10-2、10-1、1、10 mmol/L)作用于NSCs,CCK-8法检测在不同时间点(0、24、48、72 h)对细胞增殖的影响;VPA(10-5、l mmol/L)作用于NSCs 48 h后,流式细胞仪测定细胞周期分布,PCR测定p21在基因水平的表达,Western blot测定p21在蛋白质水平的表达.结果 CCK-8检测显示,当VPA浓度> 10-5 mmol/L时,体外培养的成年大鼠脊髓NSCs的增殖受到明显抑制,且具有时间依赖性.流式细胞仪细胞周期检测显示,同样浓度下,VPA可阻滞NSCs由G0/G1期向S期转换,表现为G0/G1期细胞增多,S期细胞减少,G2/M期细胞

  19. ghrelin调控神经生长因子信号途径介导心肌梗死后神经重构%Ghrelin inhibits cardiac neural remodeling after myocardial infarction in rats

    Institute of Scientific and Technical Information of China (English)

    王广丽; 刘磊; 邓笑伟

    2011-01-01

    Objective Ghrelin is a newly discovered peptide as an endogenous ligand for the growth hormone secretagogue receptor,and has been demonstrated to exert beneficial effect in the cardiovascular system.In the present study,we investigated whether ghrelin administration could inhibit cardiac neural remodeling and sympathetic hyperinnervation after myocardial infarction(MI).Methods Sprague-Dawley rats underwent coronary ligation to induce MI and received rat ghrelin(100μg/kg SC BID)or saline(control).Four weeks after treatment,rats were sacrificed.We examined the expression of nerve growth factor and never markers as well as the mRNA expressions of proinflammatory mediators.We also examined the NF-κB p65 protein and IκBα protein levels by western blot analysis.Results Compared to the control group,ghrelin administration significantly decreased the density of nerve fibers with positive immunostaining for GAP43 and TH,and decreased NGF mRNA and protein levels.Ghrelin also significantly suppressed interleukin-1β,tumor necrosis factor-α,and endothelin-1 mRNA expression,and inhibited NF-κB activation.In the MI rats,the mRNA expression of ET-1 at the non-infarcted zones had a significantly positive correlation with the NGF protein levels.Conclusion Treatment with ghrelin inhibited neural remodeling and sympathetic hyperinnervation,the process may be associated with the inhibition of proinflammatory response and NGF signaling.%目的 ghrelin是最近在胃中分离出来的生长激素释放肽受体的内源性配体,在心血管系统显示出了保护效应.本实验探讨了ghrelin对心肌梗死(MI)后大鼠神经重构的影响及其作用机制.方法 SD大鼠结扎冠状动脉制作MI模型作为对照组,干预组在手术后第1天开始给予ghrelin皮下注射,剂量为100μg/kg,每天两次.对照组开胸后在冠状动脉下穿线,但不结扎,给予盐水作皮下注射.经过4个星期治疗后,处死动物.检测梗死区及梗死边缘区神经生长

  20. Curcumin stimulates proIiferation of rat neural stem cells by inhibiting glucocorticoid receptors%姜黄素通过抑制糖皮质激素受体促进大鼠神经干细胞增殖

    Institute of Scientific and Technical Information of China (English)

    马晓晓; 王春满; 张高龙; 左春龙; 黄意湘; 刘劲; 连庆泉; 林函

    2015-01-01

    OBJECTIVE To investigate the effect of curcumin on proliferation of neural stem cells (NSCs) of rats and the mechanism. METHODS NSCs derived from the forebrain of rat E15 embryos were cultured in vitro and identified by neuroepithelial stem cell protein ( nestin and SOX2) staining. NSCs were treated with curcumin 0.1, 0.5, 2.5, 12.5 and 62.5 μmol.L-1 for 24 h, respectively. The cyto-toxicity was estimated by measuring the release of lactate dehydrogenase(LDH). Cell viability and prolif-eration were analyzed respectively by MTT and BrdU assay. The mRNA expression levels of glucocorti-coid receptor (GR), Stat3, Notch1 and p21 were detected by qRT-PCR. The protein expression levels of total GR, Stat3 and phosphorylated Stat3 were measured by Western blotting. RESULTS The primary neural stem cells were identified as NSCs. Curcumin 12.5 and 62.5 μmol.L-1 had cell cytotoxicity( P<0.05). Cell viability assay indicated that curcumin 0.5 and 2.5 μmol.L-1 enhanced NSCs viability( P <0.05), but in 62.5 μmol.L-1 group the cell cytotoxicity was inhibited(P<0.05). Curcumin 0.1, 0.5 and 2.5 μmol.L-1 increased NSCs proliferation ( P < 0. 05), whereas 12. 5 and 62. 5 μmol.L-1 caused a decrease in NSCs proliferation(P<0.05). The mRNA expression level of GR in 0.5 μmol.L-1 group was significantly reduced( P<0.05). Western blotting analysis revealed that the protein expression of GR, Stat3 and p-Stat3 was inhibited by curcumin in 0.5 μmol.L-1 group(P<0.05). CONCLUSION Curcumin stimulates NSCs proliferation, possibly by inhibiting GR mRNA and related protein expression.%目的:探讨姜黄素对大鼠神经干细胞增殖的影响及其可能机制。方法取孕15 d(E15)远交群(SD)大鼠的胎脑皮质,分离培养原代神经干细胞,进行神经干细胞标志蛋白神经上皮干细胞蛋白巢蛋白(nestin)和胚胎干细胞关键蛋白(SOX2)染色鉴定。姜黄素0,0.1,0.5,2.5,12.5和62.5μmolL-1处理大鼠神经干细胞24 h 后,乳酸脱氢酶(LDH)释

  1. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  2. Neural Engineering

    Science.gov (United States)

    He, Bin

    About the Series: Bioelectric Engineering presents state-of-the-art discussions on modern biomedical engineering with respect to applications of electrical engineering and information technology in biomedicine. This focus affirms Springer's commitment to publishing important reviews of the broadest interest to biomedical engineers, bioengineers, and their colleagues in affiliated disciplines. Recent volumes have covered modeling and imaging of bioelectric activity, neural engineering, biosignal processing, bionanotechnology, among other topics.

  3. Neural Network Applications

    NARCIS (Netherlands)

    Vonk, E.; Jain, L.C.; Veelenturf, L.P.J.

    1995-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  4. Normalized neural representations of natural odors

    OpenAIRE

    Zwicker, David

    2016-01-01

    The olfactory system removes correlations in natural odors using a network of inhibitory neurons in the olfactory bulb. It has been proposed that this network integrates the response from all olfactory receptors and inhibits them equally. However, how such global inhibition influences the neural representations of odors is unclear. Here, we study a simple statistical model of this situation, which leads to concentration-invariant, sparse representations of the odor composition. We show that t...

  5. Neural Induction, Neural Fate Stabilization, and Neural Stem Cells

    Directory of Open Access Journals (Sweden)

    Sally A. Moody

    2002-01-01

    Full Text Available The promise of stem cell therapy is expected to greatly benefit the treatment of neurodegenerative diseases. An underlying biological reason for the progressive functional losses associated with these diseases is the extremely low natural rate of self-repair in the nervous system. Although the mature CNS harbors a limited number of self-renewing stem cells, these make a significant contribution to only a few areas of brain. Therefore, it is particularly important to understand how to manipulate embryonic stem cells and adult neural stem cells so their descendants can repopulate and functionally repair damaged brain regions. A large knowledge base has been gathered about the normal processes of neural development. The time has come for this information to be applied to the problems of obtaining sufficient, neurally committed stem cells for clinical use. In this article we review the process of neural induction, by which the embryonic ectodermal cells are directed to form the neural plate, and the process of neural�fate stabilization, by which neural plate cells expand in number and consolidate their neural fate. We will present the current knowledge of the transcription factors and signaling molecules that are known to be involved in these processes. We will discuss how these factors may be relevant to manipulating embryonic stem cells to express a neural fate and to produce large numbers of neurally committed, yet undifferentiated, stem cells for transplantation therapies.

  6. Histone Demethylase LSD1 Regulates Neural Stem Cell Proliferation▿

    OpenAIRE

    Sun, Guoqiang; Alzayady, Kamil; Stewart, Richard; Ye, Peng; Yang, Su; Li, Wendong; Shi, Yanhong

    2010-01-01

    Lysine-specific demethylase 1 (LSD1) functions as a transcriptional coregulator by modulating histone methylation. Its role in neural stem cells has not been studied. We show here for the first time that LSD1 serves as a key regulator of neural stem cell proliferation. Inhibition of LSD1 activity or knockdown of LSD1 expression led to dramatically reduced neural stem cell proliferation. LSD1 is recruited by nuclear receptor TLX, an essential neural stem cell regulator, to the promoters of TLX...

  7. FGF signaling transforms non-neural ectoderm into neural crest.

    Science.gov (United States)

    Yardley, Nathan; García-Castro, Martín I

    2012-12-15

    The neural crest arises at the border between the neural plate and the adjacent non-neural ectoderm. It has been suggested that both neural and non-neural ectoderm can contribute to the neural crest. Several studies have examined the molecular mechanisms that regulate neural crest induction in neuralized tissues or the neural plate border. Here, using the chick as a model system, we address the molecular mechanisms by which non-neural ectoderm generates neural crest. We report that in response to FGF the non-neural ectoderm can ectopically express several early neural crest markers (Pax7, Msx1, Dlx5, Sox9, FoxD3, Snail2, and Sox10). Importantly this response to FGF signaling can occur without inducing ectopic mesodermal tissues. Furthermore, the non-neural ectoderm responds to FGF by expressing the prospective neural marker Sox3, but it does not express definitive markers of neural or anterior neural (Sox2 and Otx2) tissues. These results suggest that the non-neural ectoderm can launch the neural crest program in the absence of mesoderm, without acquiring definitive neural character. Finally, we report that prior to the upregulation of these neural crest markers, the non-neural ectoderm upregulates both BMP and Wnt molecules in response to FGF. Our results provide the first effort to understand the molecular events leading to neural crest development via the non-neural ectoderm in amniotes and present a distinct response to FGF signaling. PMID:23000357

  8. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    changes or to abandon the strong identity thesis altogether. Were one to pursue a theory according to which consciousness is not an epiphenomenon to brain processes, consciousness may in fact affect its own neural basis. The neural correlate of consciousness is often seen as a stable structure, that is......In contemporary consciousness studies the phenomenon of neural plasticity has received little attention despite the fact that neural plasticity is of still increased interest in neuroscience. We will, however, argue that neural plasticity could be of great importance to consciousness studies....... If consciousness is related to neural processes it seems, at least prima facie, that the ability of the neural structures to change should be reflected in a theory of this relationship "Neural plasticity" refers to the fact that the brain can change due to its own activity. The brain is not static but rather...

  9. Neural Tube Defects

    Science.gov (United States)

    Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...

  10. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  11. Holographic neural networks

    OpenAIRE

    Manger, R

    1998-01-01

    Holographic neural networks are a new and promising type of artificial neural networks. This article gives an overview of the holographic neural technology and its possibilities. The theoretical principles of holographic networks are first reviewed. Then, some other papers are presented, where holographic networks have been applied or experimentally evaluated. A case study dealing with currency exchange rate prediction is described in more detail.

  12. Neural tissue-spheres

    DEFF Research Database (Denmark)

    Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten;

    2007-01-01

    By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

  13. READING A NEURAL CODE

    NARCIS (Netherlands)

    BIALEK, W; RIEKE, F; VANSTEVENINCK, RRD; WARLAND, D

    1991-01-01

    Traditional approaches to neural coding characterize the encoding of known stimuli in average neural responses. Organisms face nearly the opposite task - extracting information about an unknown time-dependent stimulus from short segments of a spike train. Here the neural code was characterized from

  14. Normalized neural representations of natural odors

    CERN Document Server

    Zwicker, David

    2016-01-01

    The olfactory system removes correlations in natural odors using a network of inhibitory neurons in the olfactory bulb. It has been proposed that this network integrates the response from all olfactory receptors and inhibits them equally. However, how such global inhibition influences the neural representations of odors is unclear. Here, we study a simple statistical model of this situation, which leads to concentration-invariant, sparse representations of the odor composition. We show that the inhibition strength can be tuned to obtain sparse representations that are still useful to discriminate odors that vary in relative concentration, size, and composition. The model reveals two generic consequences of global inhibition: (i) odors with many molecular species are more difficult to discriminate and (ii) receptor arrays with heterogeneous sensitivities perform badly. Our work can thus help to understand how global inhibition shapes normalized odor representations for further processing in the brain.

  15. Neural crest induction by paraxial mesoderm in Xenopus embryos requires FGF signals.

    Science.gov (United States)

    Monsoro-Burq, Anne-Hélène; Fletcher, Russell B; Harland, Richard M

    2003-07-01

    At the border of the neural plate, the induction of the neural crest can be achieved by interactions with the epidermis, or with the underlying mesoderm. Wnt signals are required for the inducing activity of the epidermis in chick and amphibian embryos. Here, we analyze the molecular mechanisms of neural crest induction by the mesoderm in Xenopus embryos. Using a recombination assay, we show that prospective paraxial mesoderm induces a panel of neural crest markers (Slug, FoxD3, Zic5 and Sox9), whereas the future axial mesoderm only induces a subset of these genes. This induction is blocked by a dominant negative (dn) form of FGFR1. However, neither dnFGFR4a nor inhibition of Wnt signaling prevents neural crest induction in this system. Among the FGFs, FGF8 is strongly expressed by the paraxial mesoderm. FGF8 is sufficient to induce the neural crest markers FoxD3, Sox9 and Zic5 transiently in the animal cap assay. In vivo, FGF8 injections also expand the Slug expression domain. This suggests that FGF8 can initiate neural crest formation and cooperates with other DLMZ-derived factors to maintain and complete neural crest induction. In contrast to Wnts, eFGF or bFGF, FGF8 elicits neural crest induction in the absence of mesoderm induction and without a requirement for BMP antagonists. In vivo, it is difficult to dissociate the roles of FGF and WNT factors in mesoderm induction and neural patterning. We show that, in most cases, effects on neural crest formation were parallel to altered mesoderm or neural development. However, neural and neural crest patterning can be dissociated experimentally using different dominant-negative manipulations: while Nfz8 blocks both posterior neural plate formation and neural crest formation, dnFGFR4a blocks neural patterning without blocking neural crest formation. These results suggest that different signal transduction mechanisms may be used in neural crest induction, and anteroposterior neural patterning. PMID:12783784

  16. Chaotic diagonal recurrent neural network

    Institute of Scientific and Technical Information of China (English)

    Wang Xing-Yuan; Zhang Yi

    2012-01-01

    We propose a novel neural network based on a diagonal recurrent neural network and chaos,and its structure andlearning algorithm are designed.The multilayer feedforward neural network,diagonal recurrent neural network,and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map.The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks.

  17. Balanced feedforward inhibition and dominant recurrent inhibition in olfactory cortex.

    Science.gov (United States)

    Large, Adam M; Vogler, Nathan W; Mielo, Samantha; Oswald, Anne-Marie M

    2016-02-23

    Throughout the brain, the recruitment of feedforward and recurrent inhibition shapes neural responses. However, disentangling the relative contributions of these often-overlapping cortical circuits is challenging. The piriform cortex provides an ideal system to address this issue because the interneurons responsible for feedforward and recurrent inhibition are anatomically segregated in layer (L) 1 and L2/3 respectively. Here we use a combination of optical and electrical activation of interneurons to profile the inhibitory input received by three classes of principal excitatory neuron in the anterior piriform cortex. In all classes, we find that L1 interneurons provide weaker inhibition than L2/3 interneurons. Nonetheless, feedforward inhibitory strength covaries with the amount of afferent excitation received by each class of principal neuron. In contrast, intracortical stimulation of L2/3 evokes strong inhibition that dominates recurrent excitation in all classes. Finally, we find that the relative contributions of feedforward and recurrent pathways differ between principal neuron classes. Specifically, L2 neurons receive more reliable afferent drive and less overall inhibition than L3 neurons. Alternatively, L3 neurons receive substantially more intracortical inhibition. These three features--balanced afferent drive, dominant recurrent inhibition, and differential recruitment by afferent vs. intracortical circuits, dependent on cell class--suggest mechanisms for olfactory processing that may extend to other sensory cortices. PMID:26858458

  18. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  19. Neural Stem Cell Transplant-Induced Effect on Neurogenesis and Cognition in Alzheimer Tg2576 Mice Is Inhibited by Concomitant Treatment with Amyloid-Lowering or Cholinergic α7 Nicotinic Receptor Drugs.

    Science.gov (United States)

    Lilja, Anna M; Malmsten, Linn; Röjdner, Jennie; Voytenko, Larysa; Verkhratsky, Alexei; Ögren, Sven Ove; Nordberg, Agneta; Marutle, Amelia

    2015-01-01

    Stimulating regeneration in the brain has the potential to rescue neuronal networks and counteract progressive pathological changes in Alzheimer's disease (AD). This study investigated whether drugs with different mechanisms of action could enhance neurogenesis and improve cognition in mice receiving human neural stem cell (hNSC) transplants. Six- to nine-month-old AD Tg2576 mice were treated for five weeks with the amyloid-modulatory and neurotrophic drug (+)-phenserine or with the partial α7 nicotinic receptor (nAChR) agonist JN403, combined with bilateral intrahippocampal hNSC transplantation. We observed improved spatial memory in hNSC-transplanted non-drug-treated Tg2576 mice but not in those receiving drugs, and this was accompanied by an increased number of Doublecortin- (DCX-) positive cells in the dentate gyrus, a surrogate marker for newly generated neurons. Treatment with (+)-phenserine did however improve graft survival in the hippocampus. An accumulation of α7 nAChR-expressing astrocytes was observed around the injection site, suggesting their involvement in repair and scarring processes. Interestingly, JN403 treatment decreased the number of α7 nAChR-expressing astrocytes, correlating with a reduction in the number of DCX-positive cells in the dentate gyrus. We conclude that transplanting hNSCs enhances endogenous neurogenesis and prevents further cognitive deterioration in Tg2576 mice, while simultaneous treatments with (+)-phenserine or JN403 result in countertherapeutic effects.

  20. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  1. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

  2. Neural Networks: Implementations and Applications

    OpenAIRE

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  3. Kunstige neurale net

    DEFF Research Database (Denmark)

    Hørning, Annette

    1994-01-01

    Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse.......Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse....

  4. Critical Branching Neural Networks

    Science.gov (United States)

    Kello, Christopher T.

    2013-01-01

    It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

  5. Is neural Darwinism Darwinism?

    Science.gov (United States)

    van Belle, T

    1997-01-01

    Neural Darwinism is a theory of cognition developed by Gerald Edelman along with George Reeke and Olaf Sporns at Rockefeller University. As its name suggests, neural Darwinism is modeled after biological Darwinism, and its authors assert that the two processes are strongly analogous. both operate on variation in a population, amplifying the more adaptive individuals. However, from a computational perspective, neural Darwinism is quite different from other models of natural selection, such as genetic algorithms. The individuals of neural Darwinism do not replicate, thus robbing the process of the capacity to explore new solutions over time and ultimately reducing it to a random search. Because neural Darwinism does not have the computational power of a truly Darwinian process, it is misleading to label it as such. to illustrate this disparity in adaptive power, one of Edelman's early computer experiments, Darwin I, is revisited, and it is shown that adding replication greatly improves the adaptive power of the system.

  6. GDNF基因修饰的神经干细胞抑制脑卒中后大鼠的Caspase-3表达%The grafting neural stem cells modified by GDNF gene inhibits the expression of Caspase-3 in rats subjected to cerebral ischemia reperfusion

    Institute of Scientific and Technical Information of China (English)

    陈贵军; 高小青; 杨朝鲜; 谭树凯; 袁琼兰

    2012-01-01

    目的 研究胶质源性神经营养因子(glial cell line-derived neural factor,GDNF)基因修饰的神经干细胞(neural stem cells,NSCs)移植对脑卒中后大鼠缺血侧脑组织内半胱氨酰天冬氨酸特异性蛋白酶-3(cysteinyl aspartate specific proteinase-3,caspase-3)表达的影响,探讨GDNF基因修饰的神经干细胞(GDNF/NSCs)移植对大鼠脑卒中的神经保护作用机制.方法 取新生大鼠脑组织分离培养NSCs,收集第6代前的NSCs备用.用重组腺病毒GDNF转染神经干细胞,制备GDNF/NSCs.暂时性阻塞大鼠大脑中动脉制备脑卒中模型,3d后,用脑立体定位仪向卒中侧侧脑室分别给予NSCs、GDNF/NSCs和生理盐水.再灌注时间1周、2周、3周、5周、7周后处死大鼠(n=3).裂解卒中侧脑组织,离心后得到脑组织蛋白样品,通过蛋白免疫印迹( Western Blotting)检测Caspase-3表达.结果 GDNF/NSCs、NSCs、NS各组caspase-3的表达在1周、2周、3周、5周、7周各时间点均逐渐降低.NSCs组、GDNF/NSCs组显著低于NS组(P<0.01;P<0.001);GDNF/NSCs组明显低于NSCs组(P<0.01).结论 GDNF/NSCs移植治疗脑卒中的机制可能与抑制caspase-3表达有关.%Objective To study the effects of grafting neural stem cells( NSCs) modified by glial cell line-derived neural factor(GDNF) gene (GDNF/NSCs) on the expression of Caspase-3 in rats subjected to cerebral ischemia reperfusion. Methods NSCs were cultured from newborn rats and NSCs before 6 generation were used for grafting use. NSCs were infected by recombinant GDNF adenovirus to prepare NSCs - overexpressing GDNF( GDNF/NSCs). Rat stroke was performed by occluding the middle cerebral artery occlusion for 2 h and reperfusion. At 3 days after reperfusion, NSCs, GDNF/NSCs and saline was infused into ipsilateral ventricle respectively. According to different reperfusion time, each group was subdivide into 5 groups: 1,2,3,5,7 weeks ( n = 3 ). At each time point, rats were sacrificed and brains were

  7. Dynamics of neural cryptography.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  8. ANT Advanced Neural Tool

    Energy Technology Data Exchange (ETDEWEB)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-07-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.

  9. AUV fuzzy neural BDI

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The typical BDI (belief desire intention) model of agent is not efficiently computable and the strict logic expression is not easily applicable to the AUV (autonomous underwater vehicle) domain with uncertainties. In this paper, an AUV fuzzy neural BDI model is proposed. The model is a fuzzy neural network composed of five layers: input ( beliefs and desires) , fuzzification, commitment, fuzzy intention, and defuzzification layer. In the model, the fuzzy commitment rules and neural network are combined to form intentions from beliefs and desires. The model is demonstrated by solving PEG (pursuit-evasion game), and the simulation result is satisfactory.

  10. ANT Advanced Neural Tool

    International Nuclear Information System (INIS)

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs

  11. The Future of Neural Networks

    OpenAIRE

    Lakra, Sachin; T. V. Prasad; G. Ramakrishna

    2012-01-01

    The paper describes some recent developments in neural networks and discusses the applicability of neural networks in the development of a machine that mimics the human brain. The paper mentions a new architecture, the pulsed neural network that is being considered as the next generation of neural networks. The paper also explores the use of memristors in the development of a brain-like computer called the MoNETA. A new model, multi/infinite dimensional neural networks, are a recent developme...

  12. Neural networks for aircraft control

    Science.gov (United States)

    Linse, Dennis

    1990-01-01

    Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

  13. Neural Networks in Data Mining

    OpenAIRE

    Priyanka Gaur

    2012-01-01

    The application of neural networks in the data mining is very wide. Although neural networks may have complex structure, long training time, and uneasily understandable representation of results, neural networks have high acceptance ability for noisy data and high accuracy and are preferable in data mining. In this paper the data mining based on neural networks is researched in detail, and the key technology and ways to achieve the data mining based on neural networks are also researched.

  14. Neural networks and graph theory

    Institute of Scientific and Technical Information of China (English)

    许进; 保铮

    2002-01-01

    The relationships between artificial neural networks and graph theory are considered in detail. The applications of artificial neural networks to many difficult problems of graph theory, especially NP-complete problems, and the applications of graph theory to artificial neural networks are discussed. For example graph theory is used to study the pattern classification problem on the discrete type feedforward neural networks, and the stability analysis of feedback artificial neural networks etc.

  15. Neural Oscillators Programming Simplified

    Directory of Open Access Journals (Sweden)

    Patrick McDowell

    2012-01-01

    Full Text Available The neurological mechanism used for generating rhythmic patterns for functions such as swallowing, walking, and chewing has been modeled computationally by the neural oscillator. It has been widely studied by biologists to model various aspects of organisms and by computer scientists and robotics engineers as a method for controlling and coordinating the gaits of walking robots. Although there has been significant study in this area, it is difficult to find basic guidelines for programming neural oscillators. In this paper, the authors approach neural oscillators from a programmer’s point of view, providing background and examples for developing neural oscillators to generate rhythmic patterns that can be used in biological modeling and robotics applications.

  16. Hidden neural networks

    DEFF Research Database (Denmark)

    Krogh, Anders Stærmose; Riis, Søren Kamaric

    1999-01-01

    A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

  17. Neural Turing Machines

    OpenAIRE

    Graves, Alex; Wayne, Greg; Danihelka, Ivo

    2014-01-01

    We extend the capabilities of neural networks by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine or Von Neumann architecture but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent. Preliminary results demonstrate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples.

  18. Imaging the Neural Symphony.

    Science.gov (United States)

    Svoboda, Karel

    2016-01-01

    Since the start of the new millennium, a method called two-photon microscopy has allowed scientists to peer farther into the brain than ever before. Our author, one of the pioneers in the development of this new technology, writes that "directly observing the dynamics of neural networks in an intact brain has become one of the holy grails of brain research." His article describes the advances that led to this remarkable breakthrough-one that is helping neuroscientists better understand neural networks.

  19. Neural cryptography with feedback

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  20. Neural cryptography with feedback.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  1. The population firing rate in the presence of GABAergic tonic inhibition in single neurons and application to general anaesthesia.

    Science.gov (United States)

    Hutt, Axel

    2012-06-01

    Tonic inhibition has been found experimentally in single neurons and affects the activity of neural populations. This kind of inhibition is supposed to set the background or resting level of neural activity and plays a role in the brains arousal system, e.g. during general anaesthesia. The work shows how to involve tonic inhibition in population rate-coding models by deriving a novel transfer function. The analytical and numerical study of the novel transfer function reveals the impact of tonic inhibition on the population firing rate. Finally, a first application to a recent neural field model for general anaesthesia discusses the origin of the loss of consciousness during anaesthesia. PMID:23730354

  2. AP2γ regulates neural and epidermal development downstream of the BMP pathway at early stages of ectodermal patterning

    Institute of Scientific and Technical Information of China (English)

    Yunbo Qiao; Yue Zhu; Nengyin Sheng; Jun Chen; Ran Tao; Qingqing Zhu; Ting Zhang; Cheng Qian; Naihe Jing

    2012-01-01

    Bone morphogenetic protein (BMP) inhibits neural specification and induces epidermal differentiation during ectodermal patterning.However,the mechanism of this process is not well understood.Here we show that AP2γ,a transcription factor activator protein (AP)-2 family member,is upregulated by BMP4 during neural differentiation of pluripotent stem cells.Knockdown of AP2γ facilitates mouse embryonic stem cell (ESC) neural fate determination and impairs epidermal differentiation,whereas AP2γ overexpression inhibits neural conversion and promotes epidermal commitment.In the early chick embryo,AP2γ is expressed in the entire epiblast before HH stage 3 and gradually shifts to the putative epidermal ectoderm during HH stage 4.In the future neural plate AP2γ inhibits excessive neural expansion and it also promotes epidermal development in the surface ectoderm.Moreover,AP2γ knockdown in ESCs and chick embryos partially rescued the neural inhibition and epidermal induction effects of BMP4.Mechanistic studies showed that BMP4 directly regulates AP2γ expression through Smad1 binding to the AP2γ promoter.Taken together,we propose that during the early stages of ectodermal patterning in the chick embryo,AP2γ acts downstream of the BMP pathway to restrict precocious neural expansion in the prospective neural plate and initiates epidermal differentiation in the future epidermal ectoderm.

  3. Neural crack identification

    International Nuclear Information System (INIS)

    The inverse, crack identification problem in elasticity can be formulated as an output error minimization problem which, nevertheless, can not be solved without difficulties by classical numerical optimization. A review of all these previous results, where we used neural networks, filter-driven optimization and genetic algorithms is presented and in a companion lecture during this conference. The use of neural networks for the solution of the inverse problem makes possible the on-line solution of the problem. In fact, one usually approximates the inverse mapping (measurements versus crack quantities). Most of the effort is spent for the learning of this relation, while a sufficiently trained neural network provides predictions with, practically, zero computational cost. Potential applications include on-line, in-flight health monitoring systems with applications in civil and mechanical engineering and production control. In this paper we present new developments in the design of specialized neural networks for the solution of the crack identification problem. Emphasis is posed on the effective use of the learning data, which are produced by the boundary element method. Several technical data will be discussed. They include thoughts about the effective choice of the neural network architecture, the number of training examples and of the learning algorithms will be provided, together with the results of our recent numerical investigation. A detailed application for one or more elliptical cracks using static analysis results with the use of back-propagation trained neural networks will be provided. The general methodology follows our previously published results. By using more refined algorithms for the numerical solution of the neural network learning problem, which are based on the MERLIN optimization system developed in the department of the second author, we are able to solve complicated tasks. First results based on dynamic investigations (wave propagation driven

  4. Neural networks in seismic discrimination

    Energy Technology Data Exchange (ETDEWEB)

    Dowla, F.U.

    1995-01-01

    Neural networks are powerful and elegant computational tools that can be used in the analysis of geophysical signals. At Lawrence Livermore National Laboratory, we have developed neural networks to solve problems in seismic discrimination, event classification, and seismic and hydrodynamic yield estimation. Other researchers have used neural networks for seismic phase identification. We are currently developing neural networks to estimate depths of seismic events using regional seismograms. In this paper different types of network architecture and representation techniques are discussed. We address the important problem of designing neural networks with good generalization capabilities. Examples of neural networks for treaty verification applications are also described.

  5. Contextual behavior and neural circuits

    Directory of Open Access Journals (Sweden)

    Inah eLee

    2013-05-01

    Full Text Available Animals including humans engage in goal-directed behavior flexibly in response to items and their background, which is called contextual behavior in this review. Although the concept of context has long been studied, there are differences among researchers in defining and experimenting with the concept. The current review aims to provide a categorical framework within which not only the neural mechanisms of contextual information processing but also the contextual behavior can be studied in more concrete ways. For this purpose, we categorize contextual behavior into three subcategories as follows by considering the types of interactions among context, item, and response: contextual response selection, contextual item selection, and contextual item-response selection. Contextual response selection refers to the animal emitting different types of responses to the same item depending on the context in the background. Contextual item selection occurs when there are multiple items that need to be chosen in a contextual manner. Finally, when multiple items and multiple contexts are involved, contextual item-response selection takes place whereby the animal either choose an item or inhibit such a response depending on item-context paired association. The literature suggests that the rhinal cortical regions and the hippocampal formation play key roles in mnemonically categorizing and recognizing contextual representations and the associated items. In addition, it appears that the fronto-striatal cortical loops in connection with the contextual information-processing areas critically control the flexible deployment of adaptive action sets and motor responses for maximizing goals. We suggest that contextual information processing should be investigated in experimental settings where contextual stimuli and resulting behaviors are clearly defined and measurable, considering the dynamic top-down and bottom-up interactions among the neural systems for

  6. Rule Extraction:Using Neural Networks or for Neural Networks?

    Institute of Scientific and Technical Information of China (English)

    Zhi-Hua Zhou

    2004-01-01

    In the research of rule extraction from neural networks, fidelity describes how well the rules mimic the behavior of a neural network while accuracy describes how well the rules can be generalized. This paper identifies the fidelity-accuracy dilemma. It argues to distinguish rule extraction using neural networks and rule extraction for neural networks according to their different goals, where fidelity and accuracy should be excluded from the rule quality evaluation framework, respectively.

  7. Neural mechanisms of proactive and reactive inhibitory control : Studies in healthy volunteers and schizophrenia patients

    NARCIS (Netherlands)

    Zandbelt, B.B.

    2011-01-01

    The neural underpinnings of our ability to restrain actions in advance (i.e. proactive inhibition) and stop actions in reaction to some event (i.e. reactive inhibition) remain largely unknown. In this thesis we used neuroimaging (functional magnetic resonance imaging, fMRI) and brain stimulation (tr

  8. Introduction to Artificial Neural Networks

    DEFF Research Database (Denmark)

    Larsen, Jan

    1999-01-01

    The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....

  9. Electronic implementation of associative memory based on neural network models

    Science.gov (United States)

    Moopenn, A.; Lambe, John; Thakoor, A. P.

    1987-01-01

    An electronic embodiment of a neural network based associative memory in the form of a binary connection matrix is described. The nature of false memory errors, their effect on the information storage capacity of binary connection matrix memories, and a novel technique to eliminate such errors with the help of asymmetrical extra connections are discussed. The stability of the matrix memory system incorporating a unique local inhibition scheme is analyzed in terms of local minimization of an energy function. The memory's stability, dynamic behavior, and recall capability are investigated using a 32-'neuron' electronic neural network memory with a 1024-programmable binary connection matrix.

  10. Neural circuit dysfunction in schizophrenia: Insights from animal models.

    Science.gov (United States)

    Sigurdsson, T

    2016-05-01

    Despite decades of research, the neural circuit abnormalities underlying schizophrenia remain elusive. Although studies on schizophrenia patients have yielded important insights they have not been able to fully reveal the details of how neural circuits are disrupted in the disease, which is essential for understanding its pathophysiology and developing new treatment strategies. Animal models of schizophrenia are likely to play an important role in this effort. Such models allow neural circuit dysfunction to be investigated in detail and the role of risk factors and pathophysiological mechanisms to be experimentally assessed. The goal of this review is to summarize what we have learned from electrophysiological studies that have examined neural circuit function in animal models of schizophrenia. Although these studies have revealed diverse manifestations of neural circuit dysfunction spanning multiple levels of analysis, common themes have nevertheless emerged across different studies and animal models, revealing a core set of neural circuit abnormalities. These include an imbalance between excitation and inhibition, deficits in synaptic plasticity, disruptions in local and long-range synchrony and abnormalities in dopaminergic signaling. The relevance of these findings to the pathophysiology of the disease is discussed, as well as outstanding questions for future research.

  11. Microgravity effects on neural retina regeneration in the newt

    Science.gov (United States)

    Grigoryan, E. N.; Anton, H. J.; Mitashov, V. I.

    Data on forelimb and eye lens regenerationin in urodeles under spaceflight conditions (SFC) have been obtained in our previous studies. Today, evidence is available that SFC stimulate regeneration in experimental animals rather than inhibit it. The results of control on-ground experiments with simulated microgravity suggest that the stimulatory effect of SFC is due largely to weightlessness. An original experimental model is proposed, which is convenient for comprehensively analyzing neural regeneration under SFC. The initial results described here concern regeneration of neural retina in Pleurodeles waltl newts exposed to microgravity simulated in radial clinostat. After clinorotation for seven days (until postoperation day 16), a positive effect of altered gravity on structural restoration of detached neural retina was confirmed by a number of criteria. Specifically, an increased number of Müllerian glial cells, an increased relative volume of the plexiform layers, reduced cell death, advanced redifferentiation of retinal pigment epithelium, and extended areas of neural retina reattachment were detected in experimental newts. Moreover, cell proliferation in the inner nuclear layer of neural retina increased as compared with control. Thus, low gravity appears to intensify natural cytological and molecular mechanisms of neural retina regeneration in lower vertebrates.

  12. Introduction to neural networks

    International Nuclear Information System (INIS)

    This lecture is a presentation of today's research in neural computation. Neural computation is inspired by knowledge from neuro-science. It draws its methods in large degree from statistical physics and its potential applications lie mainly in computer science and engineering. Neural networks models are algorithms for cognitive tasks, such as learning and optimization, which are based on concepts derived from research into the nature of the brain. The lecture first gives an historical presentation of neural networks development and interest in performing complex tasks. Then, an exhaustive overview of data management and networks computation methods is given: the supervised learning and the associative memory problem, the capacity of networks, the Perceptron networks, the functional link networks, the Madaline (Multiple Adalines) networks, the back-propagation networks, the reduced coulomb energy (RCE) networks, the unsupervised learning and the competitive learning and vector quantization. An example of application in high energy physics is given with the trigger systems and track recognition system (track parametrization, event selection and particle identification) developed for the CPLEAR experiment detectors from the LEAR at CERN. (J.S.). 56 refs., 20 figs., 1 tab., 1 appendix

  13. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  14. Two pore channel 2 differentially modulates neural differentiation of mouse embryonic stem cells.

    Directory of Open Access Journals (Sweden)

    Zhe-Hao Zhang

    Full Text Available Nicotinic acid adenine dinucleotide phosphate (NAADP is an endogenous Ca(2+ mobilizing nucleotide presented in various species. NAADP mobilizes Ca(2+ from acidic organelles through two pore channel 2 (TPC2 in many cell types and it has been previously shown that NAADP can potently induce neuronal differentiation in PC12 cells. Here we examined the role of TPC2 signaling in the neural differentiation of mouse embryonic stem (ES cells. We found that the expression of TPC2 was markedly decreased during the initial ES cell entry into neural progenitors, and the levels of TPC2 gradually rebounded during the late stages of neurogenesis. Correspondingly, TPC2 knockdown accelerated mouse ES cell differentiation into neural progenitors but inhibited these neural progenitors from committing to neurons. Overexpression of TPC2, on the other hand, inhibited mouse ES cell from entering the early neural lineage. Interestingly, TPC2 knockdown had no effect on the differentiation of astrocytes and oligodendrocytes of mouse ES cells. Taken together, our data indicate that TPC2 signaling plays a temporal and differential role in modulating the neural lineage entry of mouse ES cells, in that TPC2 signaling inhibits ES cell entry to early neural progenitors, but is required for late neuronal differentiation.

  15. Echoes in correlated neural systems

    Science.gov (United States)

    Helias, M.; Tetzlaff, T.; Diesmann, M.

    2013-02-01

    Correlations are employed in modern physics to explain microscopic and macroscopic phenomena, like the fractional quantum Hall effect and the Mott insulator state in high temperature superconductors and ultracold atoms. Simultaneously probed neurons in the intact brain reveal correlations between their activity, an important measure to study information processing in the brain that also influences the macroscopic signals of neural activity, like the electroencephalogram (EEG). Networks of spiking neurons differ from most physical systems: the interaction between elements is directed, time delayed, mediated by short pulses and each neuron receives events from thousands of neurons. Even the stationary state of the network cannot be described by equilibrium statistical mechanics. Here we develop a quantitative theory of pairwise correlations in finite-sized random networks of spiking neurons. We derive explicit analytic expressions for the population-averaged cross correlation functions. Our theory explains why the intuitive mean field description fails, how the echo of single action potentials causes an apparent lag of inhibition with respect to excitation and how the size of the network can be scaled while maintaining its dynamical state. Finally, we derive a new criterion for the emergence of collective oscillations from the spectrum of the time-evolution propagator.

  16. Neural mechanisms of proactive and reactive inhibitory control : Studies in healthy volunteers and schizophrenia patients

    OpenAIRE

    Zandbelt, B.B.

    2011-01-01

    The neural underpinnings of our ability to restrain actions in advance (i.e. proactive inhibition) and stop actions in reaction to some event (i.e. reactive inhibition) remain largely unknown. In this thesis we used neuroimaging (functional magnetic resonance imaging, fMRI) and brain stimulation (transcranial magnetic stimulation, TMS) to explore the mechanisms underlying proactive and reactive inhibition in the healthy brain and the brain affected by schizophrenia. In particular, we focused ...

  17. Axial level-dependent molecular and cellular mechanisms underlying the genesis of the embryonic neural plate.

    Science.gov (United States)

    Kondoh, Hisato; Takada, Shinji; Takemoto, Tatsuya

    2016-06-01

    The transcription factor gene Sox2, centrally involved in neural primordial regulation, is activated by many enhancers. During the early stages of embryonic development, Sox2 is regulated by the enhancers N2 and N1 in the anterior neural plate (ANP) and posterior neural plate (PNP), respectively. This differential use of the enhancers reflects distinct regulatory mechanisms underlying the genesis of ANP and PNP. The ANP develops directly from the epiblast, triggered by nodal signal inhibition, and via the combined action of TFs SOX2, OTX2, POU3F1, and ZIC2, which promotes the the ANP development and inhibits other cell lineages. In contrast, the PNP is derived from neuromesodermal bipotential axial stem cells that develop into the neural plate when Sox2 is activated by the N1 enhancer, whereas they develop into the paraxial mesoderm when the N1 enhancer is repressed by the action of TBX6. The axial stem cells are maintained by the activity of WNT3a and T (Brachyury). However, at axial levels more anterior to the 8th somites (cervical levels), the development of both the neural plate and somite proceeds in the absence of WNT3a, T, or TBX6. These observations indicate that distinct molecular and cellular mechanisms determine neural plate genesis based on the axial level, and contradict the classical concept of the term "neural induction," which assumes a pan-neural plate mechanism. PMID:27279156

  18. Axial level-dependent molecular and cellular mechanisms underlying the genesis of the embryonic neural plate.

    Science.gov (United States)

    Kondoh, Hisato; Takada, Shinji; Takemoto, Tatsuya

    2016-06-01

    The transcription factor gene Sox2, centrally involved in neural primordial regulation, is activated by many enhancers. During the early stages of embryonic development, Sox2 is regulated by the enhancers N2 and N1 in the anterior neural plate (ANP) and posterior neural plate (PNP), respectively. This differential use of the enhancers reflects distinct regulatory mechanisms underlying the genesis of ANP and PNP. The ANP develops directly from the epiblast, triggered by nodal signal inhibition, and via the combined action of TFs SOX2, OTX2, POU3F1, and ZIC2, which promotes the the ANP development and inhibits other cell lineages. In contrast, the PNP is derived from neuromesodermal bipotential axial stem cells that develop into the neural plate when Sox2 is activated by the N1 enhancer, whereas they develop into the paraxial mesoderm when the N1 enhancer is repressed by the action of TBX6. The axial stem cells are maintained by the activity of WNT3a and T (Brachyury). However, at axial levels more anterior to the 8th somites (cervical levels), the development of both the neural plate and somite proceeds in the absence of WNT3a, T, or TBX6. These observations indicate that distinct molecular and cellular mechanisms determine neural plate genesis based on the axial level, and contradict the classical concept of the term "neural induction," which assumes a pan-neural plate mechanism.

  19. The neural mechanisms of learning from competitors.

    Science.gov (United States)

    Howard-Jones, Paul A; Bogacz, Rafal; Yoo, Jee H; Leonards, Ute; Demetriou, Skevi

    2010-11-01

    Learning from competitors poses a challenge for existing theories of reward-based learning, which assume that rewarded actions are more likely to be executed in the future. Such a learning mechanism would disadvantage a player in a competitive situation because, since the competitor's loss is the player's gain, reward might become associated with an action the player should themselves avoid. Using fMRI, we investigated the neural activity of humans competing with a computer in a foraging task. We observed neural activity that represented the variables required for learning from competitors: the actions of the competitor (in the player's motor and premotor cortex) and the reward prediction error arising from the competitor's feedback. In particular, regions positively correlated with the unexpected loss of the competitor (which was beneficial to the player) included the striatum and those regions previously implicated in response inhibition. Our results suggest that learning in such contexts may involve the competitor's unexpected losses activating regions of the player's brain that subserve response inhibition, as the player learns to avoid the actions that produced them.

  20. Neural tube defects

    Directory of Open Access Journals (Sweden)

    M.E. Marshall

    1981-09-01

    Full Text Available Neural tube defects refer to any defect in the morphogenesis of the neural tube, the most common types being spina bifida and anencephaly. Spina bifida has been recognised in skeletons found in north-eastern Morocco and estimated to have an age of almost 12 000 years. It was also known to the ancient Greek and Arabian physicians who thought that the bony defect was due to the tumour. The term spina bifida was first used by Professor Nicolai Tulp of Amsterdam in 1652. Many other terms have been used to describe this defect, but spina bifida remains the most useful general term, as it describes the separation of the vertebral elements in the midline.

  1. Analysis of neural data

    CERN Document Server

    Kass, Robert E; Brown, Emery N

    2014-01-01

    Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

  2. Quantum Neural Networks

    CERN Document Server

    Gupta, S; Gupta, Sanjay

    2002-01-01

    This paper initiates the study of quantum computing within the constraints of using a polylogarithmic ($O(\\log^k n), k\\geq 1$) number of qubits and a polylogarithmic number of computation steps. The current research in the literature has focussed on using a polynomial number of qubits. A new mathematical model of computation called \\emph{Quantum Neural Networks (QNNs)} is defined, building on Deutsch's model of quantum computational network. The model introduces a nonlinear and irreversible gate, similar to the speculative operator defined by Abrams and Lloyd. The precise dynamics of this operator are defined and while giving examples in which nonlinear Schr\\"{o}dinger's equations are applied, we speculate on its possible implementation. The many practical problems associated with the current model of quantum computing are alleviated in the new model. It is shown that QNNs of logarithmic size and constant depth have the same computational power as threshold circuits, which are used for modeling neural network...

  3. Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Kapil Nahar

    2012-12-01

    Full Text Available An artificial neural network is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons working in unison to solve specific problems. Ann’s, like people, learn by example.

  4. Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Kapil Nahar

    2012-12-01

    Full Text Available An artificial neural network is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information.The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons working in unison to solve specific problems.Ann’s, like people, learn by example.

  5. Electronic Neural Networks

    Science.gov (United States)

    Lambe, John; Moopen, Alexander; Thakoor, Anilkumar P.

    1988-01-01

    Memory based on neural network models content-addressable and fault-tolerant. System includes electronic equivalent of synaptic network; particular, matrix of programmable binary switching elements over which data distributed. Switches programmed in parallel by outputs of serial-input/parallel-output shift registers. Input and output terminals of bank of high-gain nonlinear amplifiers connected in nonlinear-feedback configuration by switches and by memory-prompting shift registers.

  6. Neural networks for triggering

    Energy Technology Data Exchange (ETDEWEB)

    Denby, B. (Fermi National Accelerator Lab., Batavia, IL (USA)); Campbell, M. (Michigan Univ., Ann Arbor, MI (USA)); Bedeschi, F. (Istituto Nazionale di Fisica Nucleare, Pisa (Italy)); Chriss, N.; Bowers, C. (Chicago Univ., IL (USA)); Nesti, F. (Scuola Normale Superiore, Pisa (Italy))

    1990-01-01

    Two types of neural network beauty trigger architectures, based on identification of electrons in jets and recognition of secondary vertices, have been simulated in the environment of the Fermilab CDF experiment. The efficiencies for B's and rejection of background obtained are encouraging. If hardware tests are successful, the electron identification architecture will be tested in the 1991 run of CDF. 10 refs., 5 figs., 1 tab.

  7. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  8. Progress in neural plasticity

    Institute of Scientific and Technical Information of China (English)

    POO; Mu-Ming

    2010-01-01

    One of the properties of the nervous system is the use-dependent plasticity of neural circuits.The structure and function of neural circuits are susceptible to changes induced by prior neuronal activity,as reflected by short-and long-term modifications of synaptic efficacy and neuronal excitability.Regarded as the most attractive cellular mechanism underlying higher cognitive functions such as learning and memory,activity-dependent synaptic plasticity has been in the spotlight of modern neuroscience since 1973 when activity-induced long-term potentiation(LTP) of hippocampal synapses was first discovered.Over the last 10 years,Chinese neuroscientists have made notable contributions to the study of the cellular and molecular mechanisms of synaptic plasticity,as well as of the plasticity beyond synapses,including activity-dependent changes in intrinsic neuronal excitability,dendritic integration functions,neuron-glia signaling,and neural network activity.This work highlight some of these significant findings.

  9. Two developmentally distinct populations of neural crest cells contribute to the zebrafish heart.

    Science.gov (United States)

    Cavanaugh, Ann M; Huang, Jie; Chen, Jau-Nian

    2015-08-15

    Cardiac neural crest cells are essential for outflow tract remodeling in animals with divided systemic and pulmonary circulatory systems, but their contributions to cardiac development in animals with a single-loop circulatory system are less clear. Here we genetically labeled neural crest cells and examined their contribution to the developing zebrafish heart. We identified two populations of neural crest cells that contribute to distinct compartments of zebrafish cardiovascular system at different developmental stages. A stream of neural crest cells migrating through pharyngeal arches 1 and 2 integrates into the myocardium of the primitive heart tube between 24 and 30 h post fertilization and gives rise to cardiomyocytes. A second wave of neural crest cells migrating along aortic arch 6 envelops the endothelium of the ventral aorta and invades the bulbus arteriosus after three days of development. Interestingly, while inhibition of FGF signaling has no effect on the integration of neural crest cells to the primitive heart tube, it prevents these cells from contributing to the outflow tract, demonstrating disparate responses of neural crest cells to FGF signaling. Furthermore, neural crest ablation in zebrafish leads to multiple cardiac defects, including reduced heart rate, defective myocardial maturation and a failure to recruit progenitor cells from the second heart field. These findings add to our understanding of the contribution of neural crest cells to the developing heart and provide insights into the requirement for these cells in cardiac maturation.

  10. Pattern recognition in field crickets: concepts and neural evidence.

    Science.gov (United States)

    Kostarakos, Konstantinos; Hedwig, Berthold

    2015-01-01

    Since decades the acoustic communication behavior of crickets is in the focus of neurobiology aiming to analyze the neural basis of male singing and female phonotactic behavior. For temporal pattern recognition several different concepts have been proposed to elucidate the possible neural mechanisms underlying the tuning of phonotaxis in females. These concepts encompass either some form of a feature detecting mechanism using cross-correlation processing, temporal filter properties of brain neurons or an autocorrelation processing based on a delay-line and coincidence detection mechanism. Current data based on intracellular recordings of auditory brain neurons indicate a sequential processing by excitation and inhibition in a local auditory network within the protocerebrum. The response properties of the brain neurons point towards the concept of an autocorrelation-like mechanism underlying female pattern recognition in which delay-lines by long lasting inhibition may be involved.

  11. Nanomaterial-enabled neural stimulation

    OpenAIRE

    Yongchen eWang; Liang eGuo

    2016-01-01

    Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a h...

  12. Nanomaterial-Enabled Neural Stimulation

    OpenAIRE

    Wang, Yongchen; Guo, Liang

    2016-01-01

    Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a h...

  13. IMS Algorithm for Learning Representations in Boolean Neural Networks

    OpenAIRE

    Biswas, Nripendra N; Murthy, TVMK; Chandrasekhar, M.

    1991-01-01

    A new algorithm for learning representations in Boolean neural networks, where the inputs and outputs are binary bits, is presented. The algorithm has become feasible because of a newly discovered theorem which states that any non-linearly separable Boolean function can be expressed as a convergent series of linearly separable functions connected by the logical OR (+) and the logical INHIBIT (-) operators. The formation of the series is carried out by many important properties exhibited by th...

  14. Slit/Robo1 signaling regulates neural tube development by balancing neuroepithelial cell proliferation and differentiation

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Guang; Li, Yan; Wang, Xiao-yu [Key Laboratory for Regenerative Medicine of The Ministry of Education, Department of Histology and Embryology, School of Medicine, Jinan University, Guangzhou 510632 (China); Han, Zhe [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Chuai, Manli [College of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH (United Kingdom); Wang, Li-jing [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Ho Lee, Kenneth Ka [Stem Cell and Regeneration Thematic Research Programme, School of Biomedical Sciences, Chinese University of Hong Kong, Shatin (Hong Kong); Geng, Jian-guo, E-mail: jgeng@umich.edu [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Department of Biologic and Materials Sciences, University of Michigan School of Dentistry, Ann Arbor, MI 48109 (United States); Yang, Xuesong, E-mail: yang_xuesong@126.com [Key Laboratory for Regenerative Medicine of The Ministry of Education, Department of Histology and Embryology, School of Medicine, Jinan University, Guangzhou 510632 (China)

    2013-05-01

    Formation of the neural tube is the morphological hallmark for development of the embryonic central nervous system (CNS). Therefore, neural tube development is a crucial step in the neurulation process. Slit/Robo signaling was initially identified as a chemo-repellent that regulated axon growth cone elongation, but its role in controlling neural tube development is currently unknown. To address this issue, we investigated Slit/Robo1 signaling in the development of chick neCollege of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH, UKural tube and transgenic mice over-expressing Slit2. We disrupted Slit/Robo1 signaling by injecting R5 monoclonal antibodies into HH10 neural tubes to block the Robo1 receptor. This inhibited the normal development of the ventral body curvature and caused the spinal cord to curl up into a S-shape. Next, Slit/Robo1 signaling on one half-side of the chick embryo neural tube was disturbed by electroporation in ovo. We found that the morphology of the neural tube was dramatically abnormal after we interfered with Slit/Robo1 signaling. Furthermore, we established that silencing Robo1 inhibited cell proliferation while over-expressing Robo1 enhanced cell proliferation. We also investigated the effects of altering Slit/Robo1 expression on Sonic Hedgehog (Shh) and Pax7 expression in the developing neural tube. We demonstrated that over-expressing Robo1 down-regulated Shh expression in the ventral neural tube and resulted in the production of fewer HNK-1{sup +} migrating neural crest cells (NCCs). In addition, Robo1 over-expression enhanced Pax7 expression in the dorsal neural tube and increased the number of Slug{sup +} pre-migratory NCCs. Conversely, silencing Robo1 expression resulted in an enhanced Shh expression and more HNK-1{sup +} migrating NCCs but reduced Pax7 expression and fewer Slug{sup +} pre-migratory NCCs were observed. In conclusion, we propose that Slit/Robo1 signaling is involved in regulating neural tube

  15. Slit/Robo1 signaling regulates neural tube development by balancing neuroepithelial cell proliferation and differentiation

    International Nuclear Information System (INIS)

    Formation of the neural tube is the morphological hallmark for development of the embryonic central nervous system (CNS). Therefore, neural tube development is a crucial step in the neurulation process. Slit/Robo signaling was initially identified as a chemo-repellent that regulated axon growth cone elongation, but its role in controlling neural tube development is currently unknown. To address this issue, we investigated Slit/Robo1 signaling in the development of chick neCollege of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH, UKural tube and transgenic mice over-expressing Slit2. We disrupted Slit/Robo1 signaling by injecting R5 monoclonal antibodies into HH10 neural tubes to block the Robo1 receptor. This inhibited the normal development of the ventral body curvature and caused the spinal cord to curl up into a S-shape. Next, Slit/Robo1 signaling on one half-side of the chick embryo neural tube was disturbed by electroporation in ovo. We found that the morphology of the neural tube was dramatically abnormal after we interfered with Slit/Robo1 signaling. Furthermore, we established that silencing Robo1 inhibited cell proliferation while over-expressing Robo1 enhanced cell proliferation. We also investigated the effects of altering Slit/Robo1 expression on Sonic Hedgehog (Shh) and Pax7 expression in the developing neural tube. We demonstrated that over-expressing Robo1 down-regulated Shh expression in the ventral neural tube and resulted in the production of fewer HNK-1+ migrating neural crest cells (NCCs). In addition, Robo1 over-expression enhanced Pax7 expression in the dorsal neural tube and increased the number of Slug+ pre-migratory NCCs. Conversely, silencing Robo1 expression resulted in an enhanced Shh expression and more HNK-1+ migrating NCCs but reduced Pax7 expression and fewer Slug+ pre-migratory NCCs were observed. In conclusion, we propose that Slit/Robo1 signaling is involved in regulating neural tube development by tightly

  16. Electrokinetic confinement of axonal growth for dynamically configurable neural networks.

    Science.gov (United States)

    Honegger, Thibault; Scott, Mark A; Yanik, Mehmet F; Voldman, Joel

    2013-02-21

    Axons in the developing nervous system are directed via guidance cues, whose expression varies both spatially and temporally, to create functional neural circuits. Existing methods to create patterns of neural connectivity in vitro use only static geometries, and are unable to dynamically alter the guidance cues imparted on the cells. We introduce the use of AC electrokinetics to dynamically control axonal growth in cultured rat hippocampal neurons. We find that the application of modest voltages at frequencies on the order of 10(5) Hz can cause developing axons to be stopped adjacent to the electrodes while axons away from the electric fields exhibit uninhibited growth. By switching electrodes on or off, we can reversibly inhibit or permit axon passage across the electrodes. Our models suggest that dielectrophoresis is the causative AC electrokinetic effect. We make use of our dynamic control over axon elongation to create an axon-diode via an axon-lock system that consists of a pair of electrode 'gates' that either permit or prevent axons from passing through. Finally, we developed a neural circuit consisting of three populations of neurons, separated by three axon-locks to demonstrate the assembly of a functional, engineered neural network. Action potential recordings demonstrate that the AC electrokinetic effect does not harm axons, and Ca(2+) imaging demonstrated the unidirectional nature of the synaptic connections. AC electrokinetic confinement of axonal growth has potential for creating configurable, directional neural networks. PMID:23314575

  17. Neural Flight Control System

    Science.gov (United States)

    Gundy-Burlet, Karen

    2003-01-01

    The Neural Flight Control System (NFCS) was developed to address the need for control systems that can be produced and tested at lower cost, easily adapted to prototype vehicles and for flight systems that can accommodate damaged control surfaces or changes to aircraft stability and control characteristics resulting from failures or accidents. NFCS utilizes on a neural network-based flight control algorithm which automatically compensates for a broad spectrum of unanticipated damage or failures of an aircraft in flight. Pilot stick and rudder pedal inputs are fed into a reference model which produces pitch, roll and yaw rate commands. The reference model frequencies and gains can be set to provide handling quality characteristics suitable for the aircraft of interest. The rate commands are used in conjunction with estimates of the aircraft s stability and control (S&C) derivatives by a simplified Dynamic Inverse controller to produce virtual elevator, aileron and rudder commands. These virtual surface deflection commands are optimally distributed across the aircraft s available control surfaces using linear programming theory. Sensor data is compared with the reference model rate commands to produce an error signal. A Proportional/Integral (PI) error controller "winds up" on the error signal and adds an augmented command to the reference model output with the effect of zeroing the error signal. In order to provide more consistent handling qualities for the pilot, neural networks learn the behavior of the error controller and add in the augmented command before the integrator winds up. In the case of damage sufficient to affect the handling qualities of the aircraft, an Adaptive Critic is utilized to reduce the reference model frequencies and gains to stay within a flyable envelope of the aircraft.

  18. Chaotic neural control

    Science.gov (United States)

    Potapov, A.; Ali, M. K.

    2001-04-01

    We consider the problem of stabilizing unstable equilibria by discrete controls (the controls take discrete values at discrete moments of time). We prove that discrete control typically creates a chaotic attractor in the vicinity of an equilibrium. Artificial neural networks with reinforcement learning are known to be able to learn such a control scheme. We consider examples of such systems, discuss some details of implementing the reinforcement learning to controlling unstable equilibria, and show that the arising dynamics is characterized by positive Lyapunov exponents, and hence is chaotic. This chaos can be observed both in the controlled system and in the activity patterns of the controller.

  19. via dynamic neural networks

    Directory of Open Access Journals (Sweden)

    J. Reyes-Reyes

    2000-01-01

    Full Text Available In this paper, an adaptive technique is suggested to provide the passivity property for a class of partially known SISO nonlinear systems. A simple Dynamic Neural Network (DNN, containing only two neurons and without any hidden-layers, is used to identify the unknown nonlinear system. By means of a Lyapunov-like analysis the new learning law for this DNN, guarantying both successful identification and passivation effects, is derived. Based on this adaptive DNN model, an adaptive feedback controller, serving for wide class of nonlinear systems with an a priori incomplete model description, is designed. Two typical examples illustrate the effectiveness of the suggested approach.

  20. Neurally augmented sexual function.

    Science.gov (United States)

    Meloy, S

    2007-01-01

    Neurally Augmented Sexual Function (NASF) is a technique utilizing epidural electrodes to restore and improve sexual function. Orgasmic dysfunction is common in adult women, affecting roughly one quarter of populations studied. Many male patients suffering from erectile dysfunction are not candidates for phosphdiesterase therapy due to concomitant nitrate therapy. Positioning the electrodes at roughly the level of the cauda equina allows for stimulation of somatic efferents and afferents as well as modifying sympathetic and parasympathetic activity. Our series of women treated by NASF is described. Our experience shows that the evaluation of potential candidates for both correctable causes and psychological screening are important considerations. PMID:17691397

  1. There Is No Free Won’t: Antecedent Brain Activity Predicts Decisions to Inhibit

    Science.gov (United States)

    Filevich, Elisa; Kühn, Simone; Haggard, Patrick

    2013-01-01

    Inhibition of prepotent action is an important aspect of self-control, particularly in social contexts. Action inhibition and its neural bases have been extensively studied. However, the neural precursors of free decisions to inhibit have hardly been studied. We asked participants to freely choose to either make a rapid key press in response to a visual cue, or to transiently inhibit action, and briefly delay responding. The task required a behavioural response on each trial, so trials involving inhibition could be distinguished from those without inhibition as those showing slower reaction times. We used this criterion to classify free-choice trials as either rapid or inhibited/delayed. For 13 participants, we measured the mean amplitude of the ERP activity at electrode Cz in three subsequent 50 ms time windows prior to the onset of the signal that either instructed to respond or inhibit, or gave participants a free choice. In two of these 50 ms time windows (−150 to −100, and −100 to −50 ms relative to action onset), the amplitude of prestimulus ERP differed between trials where participants ”freely” chose whether to inhibit or to respond rapidly. Larger prestimulus ERP amplitudes were associated with trials in which participants decided to act rapidly as compared to trials in which they decided to delay their responses. Last-moment decisions to inhibit or delay may depend on unconscious preparatory neural activity. PMID:23418420

  2. Space-Time Neural Networks

    Science.gov (United States)

    Villarreal, James A.; Shelton, Robert O.

    1992-01-01

    Concept of space-time neural network affords distributed temporal memory enabling such network to model complicated dynamical systems mathematically and to recognize temporally varying spatial patterns. Digital filters replace synaptic-connection weights of conventional back-error-propagation neural network.

  3. Neural Networks for Optimal Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1995-01-01

    Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....

  4. Neural networks in astronomy.

    Science.gov (United States)

    Tagliaferri, Roberto; Longo, Giuseppe; Milano, Leopoldo; Acernese, Fausto; Barone, Fabrizio; Ciaramella, Angelo; De Rosa, Rosario; Donalek, Ciro; Eleuteri, Antonio; Raiconi, Giancarlo; Sessa, Salvatore; Staiano, Antonino; Volpicelli, Alfredo

    2003-01-01

    In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large astronomical databases which is foreseen in the framework of the astrophysical virtual observatory and national virtual observatory projects, is, however, posing unprecedented data mining and visualization problems which will find a rather natural and user friendly answer in artificial intelligence tools based on NNs, fuzzy sets or genetic algorithms. This review is aimed to both astronomers (who often have little knowledge of the methodological background) and computer scientists (who often know little about potentially interesting applications), and therefore will be structured as follows: after giving a short introduction to the subject, we shall summarize the methodological background and focus our attention on some of the most interesting fields of application, namely: object extraction and classification, time series analysis, noise identification, and data mining. Most of the original work described in the paper has been performed in the framework of the AstroNeural collaboration (Napoli-Salerno).

  5. Analysis of neural networks

    CERN Document Server

    Heiden, Uwe

    1980-01-01

    The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica­ ted throughout the text. However, they are not explored in de­ tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev­ els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be­ havior of neurons or neuron pools. In this respect the essay is writt...

  6. Neural relativity principle

    Science.gov (United States)

    Koulakov, Alexei

    Olfaction is the final frontier of our senses - the one that is still almost completely mysterious to us. Despite extensive genetic and perceptual data, and a strong push to solve the neural coding problem, fundamental questions about the sense of smell remain unresolved. Unlike vision and hearing, where relatively straightforward relationships between stimulus features and neural responses have been foundational to our understanding sensory processing, it has been difficult to quantify the properties of odorant molecules that lead to olfactory percepts. In a sense, we do not have olfactory analogs of ``red'', ``green'' and ``blue''. The seminal work of Linda Buck and Richard Axel identified a diverse family of about 1000 receptor molecules that serve as odorant sensors in the nose. However, the properties of smells that these receptors detect remain a mystery. I will review our current understanding of the molecular properties important to the olfactory system. I will also describe a theory that explains how odorant identity can be preserved despite substantial changes in the odorant concentration.

  7. Inhibition Ability of Food Cues between Successful and Unsuccessful Restrained Eaters: A Two-Choice Oddball Task

    OpenAIRE

    Fanchang Kong; Yan Zhang; Hong Chen

    2015-01-01

    Background Previous studies have presented mixed findings on the inhibition ability in restrained eaters (REs) due to the limited amount of neural evidence and limitations of behavioral measures. The current study explores the neural correlations of the specific inhibition ability among successful restrained eaters (S-REs), unsuccessful restrained eaters (US-REs), and unrestrained eaters (UREs). Methodology and Principal Findings Three groups of females (with 13 participants in each group) co...

  8. Artificial neural networks in NDT

    International Nuclear Information System (INIS)

    Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

  9. Medical diagnosis using neural network

    CERN Document Server

    Kamruzzaman, S M; Siddiquee, Abu Bakar; Mazumder, Md Ehsanul Hoque

    2010-01-01

    This research is to search for alternatives to the resolution of complex medical diagnosis where human knowledge should be apprehended in a general fashion. Successful application examples show that human diagnostic capabilities are significantly worse than the neural diagnostic system. This paper describes a modified feedforward neural network constructive algorithm (MFNNCA), a new algorithm for medical diagnosis. The new constructive algorithm with backpropagation; offer an approach for the incremental construction of near-minimal neural network architectures for pattern classification. The algorithm starts with minimal number of hidden units in the single hidden layer; additional units are added to the hidden layer one at a time to improve the accuracy of the network and to get an optimal size of a neural network. The MFNNCA was tested on several benchmarking classification problems including the cancer, heart disease and diabetes. Experimental results show that the MFNNCA can produce optimal neural networ...

  10. Neural fields theory and applications

    CERN Document Server

    Graben, Peter; Potthast, Roland; Wright, James

    2014-01-01

    With this book, the editors present the first comprehensive collection in neural field studies, authored by leading scientists in the field - among them are two of the founding-fathers of neural field theory. Up to now, research results in the field have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. Starting with a tutorial for novices in neural field studies, the book comprises chapters on emergent patterns, their phase transitions and evolution, on stochastic approaches, cortical development, cognition, robotics and computation, large-scale numerical simulations, the coupling of neural fields to the electroencephalogram and phase transitions in anesthesia. The intended readership are students and scientists in applied mathematics, theoretical physics, theoretical biology, and computational neuroscience. Neural field theory and its applications have a long-standing tradition in the mathematical and computational ...

  11. Neural Progenitor Cells Derived from Human Embryonic Stem Cells as an Origin of Dopaminergic Neurons

    Directory of Open Access Journals (Sweden)

    Parinya Noisa

    2015-01-01

    Full Text Available Human embryonic stem cells (hESCs are able to proliferate in vitro indefinitely without losing their ability to differentiate into multiple cell types upon exposure to appropriate signals. Particularly, the ability of hESCs to differentiate into neuronal subtypes is fundamental to develop cell-based therapies for several neurodegenerative disorders, such as Alzheimer’s disease, Huntington’s disease, and Parkinson’s disease. In this study, we differentiated hESCs to dopaminergic neurons via an intermediate stage, neural progenitor cells (NPCs. hESCs were induced to neural progenitor cells by Dorsomorphin, a small molecule that inhibits BMP signalling. The resulting neural progenitor cells exhibited neural bipolarity with high expression of neural progenitor genes and possessed multipotential differentiation ability. CBF1 and bFGF responsiveness of these hES-NP cells suggested their similarity to embryonic neural progenitor cells. A substantial number of dopaminergic neurons were derived from hES-NP cells upon supplementation of FGF8 and SHH, key dopaminergic neuron inducers. Importantly, multiple markers of midbrain neurons were detected, including NURR1, PITX3, and EN1, suggesting that hESC-derived dopaminergic neurons attained the midbrain identity. Altogether, this work underscored the generation of neural progenitor cells that retain the properties of embryonic neural progenitor cells. These cells will serve as an unlimited source for the derivation of dopaminergic neurons, which might be applicable for treating patients with Parkinson’s disease.

  12. TOX3 regulates neural progenitor identity.

    Science.gov (United States)

    Sahu, Sanjeeb Kumar; Fritz, Alina; Tiwari, Neha; Kovacs, Zsuzsa; Pouya, Alireza; Wüllner, Verena; Bora, Pablo; Schacht, Teresa; Baumgart, Jan; Peron, Sophie; Berninger, Benedikt; Tiwari, Vijay K; Methner, Axel

    2016-07-01

    The human genomic locus for the transcription factor TOX3 has been implicated in susceptibility to restless legs syndrome and breast cancer in genome-wide association studies, but the physiological role of TOX3 remains largely unknown. We found Tox3 to be predominantly expressed in the developing mouse brain with a peak at embryonic day E14 where it co-localizes with the neural stem and progenitor markers Nestin and Sox2 in radial glia of the ventricular zone and intermediate progenitors of the subventricular zone. Tox3 is also expressed in neural progenitor cells obtained from the ganglionic eminence of E15 mice that express Nestin, and it specifically binds the Nestin promoter in chromatin immunoprecipitation assays. In line with this, over-expression of Tox3 increased Nestin promoter activity, which was cooperatively enhanced by treatment with the stem cell self-renewal promoting Notch ligand Jagged and repressed by pharmacological inhibition of Notch signaling. Knockdown of Tox3 in the subventricular zone of E12.5 mouse embryos by in utero electroporation of Tox3 shRNA revealed a reduced Nestin expression and decreased proliferation at E14 and a reduced migration to the cortical plate in E16 embryos in electroporated cells. Together, these results argue for a role of Tox3 in the development of the nervous system. PMID:27080130

  13. Neural Network Model of Memory Retrieval.

    Science.gov (United States)

    Recanatesi, Stefano; Katkov, Mikhail; Romani, Sandro; Tsodyks, Misha

    2015-01-01

    Human memory can store large amount of information. Nevertheless, recalling is often a challenging task. In a classical free recall paradigm, where participants are asked to repeat a briefly presented list of words, people make mistakes for lists as short as 5 words. We present a model for memory retrieval based on a Hopfield neural network where transition between items are determined by similarities in their long-term memory representations. Meanfield analysis of the model reveals stable states of the network corresponding (1) to single memory representations and (2) intersection between memory representations. We show that oscillating feedback inhibition in the presence of noise induces transitions between these states triggering the retrieval of different memories. The network dynamics qualitatively predicts the distribution of time intervals required to recall new memory items observed in experiments. It shows that items having larger number of neurons in their representation are statistically easier to recall and reveals possible bottlenecks in our ability of retrieving memories. Overall, we propose a neural network model of information retrieval broadly compatible with experimental observations and is consistent with our recent graphical model (Romani et al., 2013). PMID:26732491

  14. Interacting neural networks.

    Science.gov (United States)

    Metzler, R; Kinzel, W; Kanter, I

    2000-08-01

    Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbor. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated. Two competitive perceptrons trained on mutually exclusive learning aims and a perceptron which is trained on the opposite of its own output are examined analytically. An ensemble of competitive perceptrons is used as decision-making algorithms in a model of a closed market (El Farol Bar problem or the Minority Game. In this game, a set of agents who have to make a binary decision is considered.); each network is trained on the history of minority decisions. This ensemble of perceptrons relaxes to a stationary state whose performance can be better than random. PMID:11088736

  15. Neural Darwinism and consciousness.

    Science.gov (United States)

    Seth, Anil K; Baars, Bernard J

    2005-03-01

    Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.

  16. Maladaptive neural synchrony in tinnitus: origin and restoration

    Directory of Open Access Journals (Sweden)

    Jos J Eggermont

    2015-02-01

    Full Text Available Tinnitus is the conscious perception of sound heard in the absence of physical sound sources external or internal to the body, reflected in aberrant neural synchrony of spontaneous or resting state brain activity. Neural synchrony is generated by the nearly simultaneous firing of individual neurons, of the synchronization of membrane potential changes in local neural groups as reflected in the local field potentials, resulting in the presence of oscillatory brain waves in the EEG. Noise-induced hearing loss, often resulting in tinnitus, causes a reorganization of the tonotopic map in auditory cortex and increased spontaneous firing rates and neural synchrony. Spontaneous brain rhythms rely on neural synchrony. Abnormal neural synchrony in tinnitus appears to be confined to specific frequency bands of brain rhythms. Increases in delta-band activity are generated by deafferented/deprived neuronal networks resulting from hearing loss. Coordinated reset (CR stimulation was developed in order to specifically counteract such abnormal neuronal synchrony by desynchronization. The goal of acoustic CR neuromodulation is to desynchronize tinnitus-related abnormal delta band oscillations. CR neuromodulation does not require permanent stimulus delivery in order to achieve long-lasting desynchronization or even a full-blown anti-kindling but may have cumulative effects, i.e. the effect of different CR epochs separated by pauses may accumulate. Unlike other approaches, acoustic CR neuromodulation does not intend to reduce tinnitus-related neuronal activity by employing lateral inhibition. The potential efficacy of acoustic CR modulation was shown in a clinical proof of concept trial, where effects achieved in 12 weeks of treatment delivered 4-6h/day persisted through a preplanned 4-week therapy pause and showed sustained long-term effects after 10 months of therapy, leading to 75% responders.

  17. Cooperating attackers in neural cryptography.

    Science.gov (United States)

    Shacham, Lanir N; Klein, Einat; Mislovaty, Rachel; Kanter, Ido; Kinzel, Wolfgang

    2004-06-01

    A successful attack strategy in neural cryptography is presented. The neural cryptosystem, based on synchronization of neural networks by mutual learning, has been recently shown to be secure under different attack strategies. The success of the advanced attacker presented here, called the "majority-flipping attacker," does not decay with the parameters of the model. This attacker's outstanding success is due to its using a group of attackers which cooperate throughout the synchronization process, unlike any other attack strategy known. An analytical description of this attack is also presented, and fits the results of simulations.

  18. Response inhibition and its relation to multidimensional impulsivity.

    Science.gov (United States)

    Wilbertz, Tilmann; Deserno, Lorenz; Horstmann, Annette; Neumann, Jane; Villringer, Arno; Heinze, Hans-Jochen; Boehler, Carsten N; Schlagenhauf, Florian

    2014-12-01

    Impulsivity is a multidimensional construct that has been suggested as a vulnerability factor for several psychiatric disorders, especially addiction disorders. Poor response inhibition may constitute one facet of impulsivity. Trait impulsivity can be assessed by self-report questionnaires such as the widely used Barratt Impulsiveness Scale (BIS-11). However, regarding the multidimensionality of impulsivity different concepts have been proposed, in particular the UPPS self-report questionnaire ('Urgency', 'Lack of Premeditation', 'Lack of Perseverance', 'Sensation Seeking') that is based on a factor analytic approach. The question as to which aspects of trait impulsivity map on individual differences of the behavioral and neural correlates of response inhibition so far remains unclear. In the present study, we investigated 52 healthy individuals that scored either very high or low on the BIS-11 and underwent a reward-modulated Stop-signal task during fMRI. Neither behavioral nor neural differences were observed with respect to high- and low-BIS groups. In contrast, UPPS subdomain Urgency best explained inter-individual variability in SSRT scores and was further negatively correlated to right IFG/aI activation in 'Stop>Go' trials - a key region for response inhibition. Successful response inhibition in rewarded compared to nonrewarded stop trials yielded ventral striatal (VS) activation which might represent a feedback signal. Interestingly, only participants with low Urgency scores were able to use this VS feedback signal for better response inhibition. Our findings indicate that the relationship of impulsivity and response inhibition has to be treated carefully. We propose Urgency as an important subdomain that might be linked to response inhibition as well as to the use of reward-based neural signals. Based on the present results, further studies examining the influence of impulsivity on psychiatric disorders should take into account Urgency as an important

  19. Inhibition Controls Asynchronous States of Neuronal Networks

    Science.gov (United States)

    Treviño, Mario

    2016-01-01

    Computations in cortical circuits require action potentials from excitatory and inhibitory neurons. In this mini-review, I first provide a quick overview of findings that indicate that GABAergic neurons play a fundamental role in coordinating spikes and generating synchronized network activity. Next, I argue that these observations helped popularize the notion that network oscillations require a high degree of spike correlations among interneurons which, in turn, produce synchronous inhibition of the local microcircuit. The aim of this text is to discuss some recent experimental and computational findings that support a complementary view: one in which interneurons participate actively in producing asynchronous states in cortical networks. This requires a proper mixture of shared excitation and inhibition leading to asynchronous activity between neighboring cells. Such contribution from interneurons would be extremely important because it would tend to reduce the spike correlation between neighboring pyramidal cells, a drop in redundancy that could enhance the information-processing capacity of neural networks. PMID:27274721

  20. Inhibition Controls Asynchronous States of Neuronal Networks.

    Science.gov (United States)

    Treviño, Mario

    2016-01-01

    Computations in cortical circuits require action potentials from excitatory and inhibitory neurons. In this mini-review, I first provide a quick overview of findings that indicate that GABAergic neurons play a fundamental role in coordinating spikes and generating synchronized network activity. Next, I argue that these observations helped popularize the notion that network oscillations require a high degree of spike correlations among interneurons which, in turn, produce synchronous inhibition of the local microcircuit. The aim of this text is to discuss some recent experimental and computational findings that support a complementary view: one in which interneurons participate actively in producing asynchronous states in cortical networks. This requires a proper mixture of shared excitation and inhibition leading to asynchronous activity between neighboring cells. Such contribution from interneurons would be extremely important because it would tend to reduce the spike correlation between neighboring pyramidal cells, a drop in redundancy that could enhance the information-processing capacity of neural networks.

  1. 大鼠角膜穿通伤后局部应用 IL-10抑制视网膜炎症和抗神经溃变的研究%Topical application of IL-10 inhibits inflammation and reduces neural degeneration of the retina after corneal penetrating injury in rats

    Institute of Scientific and Technical Information of China (English)

    黄燕; 周月鹏; 肖寿华; 张志坚

    2014-01-01

    -200和血影蛋白,造成神经溃变;局部应用 IL-10可减轻炎症反应,抑制 m-calpain 对骨架蛋白的降解,从而对视网膜细胞产生保护作用。%Objective:To investigate the mechanisms of that IL-1 0 inhibits inflammation and reduces neural degeneration of the retina after corneal penetrating injury in rats.Methods:A total of 50 adult fe-male rats were randomly divided into three groups:A,the normal control group(8 rats);B,the corneal penetrating injury group(21 rats);and C,the IL-1 0 treated group(21 rats ).B and C groups were subdi-vided into the subgroups suffered from corneal penetrating injury for 24 hours,48 hours and 72 hours,re-spectively.The animals of C group suffered from corneal penetrating injury and then were treated with topi-cal application of IL-1 0.Two rats in each group were used to make tissue sections of eyeball.The sections were immunofluorescence stained with antibodies against IL-1 β,IL-6,TNF-α,neurofilament protein-200 (NF200),α-Ⅱ spectrin and m-calpain.The relative contents of activated m-calpain and the degradation products of NF200 and αⅡ spectrin of the retina tissues were detected by western blotting.Results:Theimmunofluorescence staining of IL1 β,IL6,TNFαand mcalpain in normal retina were very weak,andbecame stronger in the retina of corneal penetrating injury groups.After treated with IL1 0,the intensity ofimmunofluorescence staining of IL1 β,IL6,TNFαand mcalpain reduced.The immunofluorescence staining of NF200 and αⅡ spectrin were weaker in the corneal penetrating injury group than those in the normal group;after treated with IL1 0,the intensity of immunofluorescence staining of NF200 and αⅡ spectrin became stronger than those in the corneal penetrating injury group.Western blotting showed that therelative contents of activated mcalpain and the degradation products of NF200 and αⅡ spectrin of the retina tissues in IL1 0 treated

  2. Role of neural modulation in the pathophysiology of atrial fibrillation

    Directory of Open Access Journals (Sweden)

    Shailesh Male

    2014-01-01

    Full Text Available Atrial-fibrillation (AF is the most common clinically encountered arrhythmia affecting over 1 per cent of population in the United States and its prevalence seems to be moving only in forward direction. A recent systemic review estimates global prevalence of AF to be 596.2 and 373.1 per 100,000 population in males and females respectively. Multiple mechanisms have been put forward in the pathogenesis of AF, however; multiple wavelet hypothesis is the most accepted theory so far. Similar to the conduction system of the heart, a neural network exists which surrounds the heart and plays an important role in formation of the substrate of AF and when a trigger is originated, usually from pulmonary vein sleeves, AF occurs. This neural network includes ganglionated plexi (GP located adjacent to pulmonary vein ostia which are under control of higher centers in normal people. When these GP become hyperactive owing to loss of inhibition from higher centers e.g. in elderly, AF can occur. We can control these hyperactive GP either by stimulating higher centers and their connections, e.g. vagus nerve stimulation or simply by ablating these GP. This review provides detailed information about the different proposed mechanisms underlying AF, the exact role of autonomic neural tone in the pathogenesis of AF and the possible role of neural modulation in the treatment of AF.

  3. A model of interval timing by neural integration.

    Science.gov (United States)

    Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

    2011-06-22

    We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

  4. Neural components of altruistic punishment

    Directory of Open Access Journals (Sweden)

    Emily eDu

    2015-02-01

    Full Text Available Altruistic punishment, which occurs when an individual incurs a cost to punish in response to unfairness or a norm violation, may play a role in perpetuating cooperation. The neural correlates underlying costly punishment have only recently begun to be explored. Here we review the current state of research on the neural basis of altruism from the perspectives of costly punishment, emphasizing the importance of characterizing elementary neural processes underlying a decision to punish. In particular, we emphasize three cognitive processes that contribute to the decision to altruistically punish in most scenarios: inequity aversion, cost-benefit calculation, and social reference frame to distinguish self from others. Overall, we argue for the importance of understanding the neural correlates of altruistic punishment with respect to the core computations necessary to achieve a decision to punish.

  5. Complex-Valued Neural Networks

    CERN Document Server

    Hirose, Akira

    2012-01-01

    This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...

  6. Neural components of altruistic punishment

    Science.gov (United States)

    Du, Emily; Chang, Steve W. C.

    2015-01-01

    Altruistic punishment, which occurs when an individual incurs a cost to punish in response to unfairness or a norm violation, may play a role in perpetuating cooperation. The neural correlates underlying costly punishment have only recently begun to be explored. Here we review the current state of research on the neural basis of altruism from the perspectives of costly punishment, emphasizing the importance of characterizing elementary neural processes underlying a decision to punish. In particular, we emphasize three cognitive processes that contribute to the decision to altruistically punish in most scenarios: inequity aversion, cost-benefit calculation, and social reference frame to distinguish self from others. Overall, we argue for the importance of understanding the neural correlates of altruistic punishment with respect to the core computations necessary to achieve a decision to punish. PMID:25709565

  7. Demultiplexer circuit for neural stimulation

    Science.gov (United States)

    Wessendorf, Kurt O; Okandan, Murat; Pearson, Sean

    2012-10-09

    A demultiplexer circuit is disclosed which can be used with a conventional neural stimulator to extend the number of electrodes which can be activated. The demultiplexer circuit, which is formed on a semiconductor substrate containing a power supply that provides all the dc electrical power for operation of the circuit, includes digital latches that receive and store addressing information from the neural stimulator one bit at a time. This addressing information is used to program one or more 1:2.sup.N demultiplexers in the demultiplexer circuit which then route neural stimulation signals from the neural stimulator to an electrode array which is connected to the outputs of the 1:2.sup.N demultiplexer. The demultiplexer circuit allows the number of individual electrodes in the electrode array to be increased by a factor of 2.sup.N with N generally being in a range of 2-4.

  8. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...... in a recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...

  9. Yes-associated protein 65 (YAP expands neural progenitors and regulates Pax3 expression in the neural plate border zone.

    Directory of Open Access Journals (Sweden)

    Stephen T Gee

    Full Text Available Yes-associated protein 65 (YAP contains multiple protein-protein interaction domains and functions as both a transcriptional co-activator and as a scaffolding protein. Mouse embryos lacking YAP did not survive past embryonic day 8.5 and showed signs of defective yolk sac vasculogenesis, chorioallantoic fusion, and anterior-posterior (A-P axis elongation. Given that the YAP knockout mouse defects might be due in part to nutritional deficiencies, we sought to better characterize a role for YAP during early development using embryos that develop externally. YAP morpholino (MO-mediated loss-of-function in both frog and fish resulted in incomplete epiboly at gastrulation and impaired axis formation, similar to the mouse phenotype. In frog, germ layer specific genes were expressed, but they were temporally delayed. YAP MO-mediated partial knockdown in frog allowed a shortened axis to form. YAP gain-of-function in Xenopus expanded the progenitor populations in the neural plate (sox2(+ and neural plate border zone (pax3(+, while inhibiting the expression of later markers of tissues derived from the neural plate border zone (neural crest, pre-placodal ectoderm, hatching gland, as well as epidermis and somitic muscle. YAP directly regulates pax3 expression via association with TEAD1 (N-TEF at a highly conserved, previously undescribed, TEAD-binding site within the 5' regulatory region of pax3. Structure/function analyses revealed that the PDZ-binding motif of YAP contributes to the inhibition of epidermal and somitic muscle differentiation, but a complete, intact YAP protein is required for expansion of the neural plate and neural plate border zone progenitor pools. These results provide a thorough analysis of YAP mediated gene expression changes in loss- and gain-of-function experiments. Furthermore, this is the first report to use YAP structure-function analyzes to determine which portion of YAP is involved in specific gene expression changes and the

  10. Neural Networks Of VLSI Components

    Science.gov (United States)

    Eberhardt, Silvio P.

    1991-01-01

    Concept for design of electronic neural network calls for assembly of very-large-scale integrated (VLSI) circuits of few standard types. Each VLSI chip, which contains both analog and digital circuitry, used in modular or "building-block" fashion by interconnecting it in any of variety of ways with other chips. Feedforward neural network in typical situation operates under control of host computer and receives inputs from, and sends outputs to, other equipment.

  11. Neural models and physiological reality

    OpenAIRE

    Lee, Barry B.

    2008-01-01

    Neural models of retinal processing provide an important tool for analyzing retinal signals and their functional significance. However, it is here argued that in biological reality, retinal connectivity is unlikely to be as specific as ideal neural models might suggest. The retina is thought to provide functionally specific signals, but this specificity is unlikely to be anatomically complete. This is illustrated by examples of cone connectivity to macaque ganglion cells. For example, cells o...

  12. Neural stem cell derived tumourigenesis

    OpenAIRE

    Francesca Froldi; Milán Szuperák; Cheng, Louise Y.

    2015-01-01

    In the developing Drosophila CNS, two pools of neural stem cells, the symmetrically dividing progenitors in the neuroepithelium (NE) and the asymmetrically dividing neuroblasts (NBs) generate the majority of the neurons that make up the adult central nervous system (CNS). The generation of a correct sized brain depends on maintaining the fine balance between neural stem cell self-renewal and differentiation, which are regulated by cell-intrinsic and cell-extrinsic cues. In this review, we wil...

  13. What are artificial neural networks?

    DEFF Research Database (Denmark)

    Krogh, Anders

    2008-01-01

    Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb......Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb...

  14. Neural Networks for Fingerprint Recognition

    OpenAIRE

    Baldi, Pierre; Chauvin, Yves

    1993-01-01

    After collecting a data base of fingerprint images, we design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs an estimate of the probability that the two images originate from the same finger. In one experiment, the neural network is trained using a few hundred pairs of images and its performance is subsequently tested using several thousand pairs of images originated from a subset of the database corresponding to...

  15. Neural Networks and Photometric Redshifts

    OpenAIRE

    Tagliaferri, Roberto; Longo, Giuseppe; Andreon, Stefano; Capozziello, Salvatore; Donalek, Ciro; Giordano, Gerardo

    2002-01-01

    We present a neural network based approach to the determination of photometric redshift. The method was tested on the Sloan Digital Sky Survey Early Data Release (SDSS-EDR) reaching an accuracy comparable and, in some cases, better than SED template fitting techniques. Different neural networks architecture have been tested and the combination of a Multi Layer Perceptron with 1 hidden layer (22 neurons) operated in a Bayesian framework, with a Self Organizing Map used to estimate the accuracy...

  16. Flexibility of neural stem cells

    Directory of Open Access Journals (Sweden)

    Eumorphia eRemboutsika

    2011-04-01

    Full Text Available Embryonic cortical neural stem cells are self-renewing progenitors that can differentiate into neurons and glia. We generated neurospheres from the developing cerebral cortex using a mouse genetic model that allows for lineage selection and found that the self-renewing neural stem cells are restricted to Sox2 expressing cells. Under normal conditions, embryonic cortical neurospheres are heterogeneous with regard to Sox2 expression and contain astrocytes, neural stem cells and neural progenitor cells sufficiently plastic to give rise to neural crest cells when transplanted into the hindbrain of E1.5 chick and E8 mouse embryos. However, when neurospheres are maintained under lineage selection, such that all cells express Sox2, neural stem cells maintain their Pax6+ cortical radial glia identity and exhibit a more restricted fate in vitro and after transplantation. These data demonstrate that Sox2 preserves the cortical identity and regulates the plasticity of self-renewing Pax6+ radial glia cells.

  17. The neural processing of taste

    Directory of Open Access Journals (Sweden)

    Katz Donald B

    2007-09-01

    Full Text Available Abstract Although there have been many recent advances in the field of gustatory neurobiology, our knowledge of how the nervous system is organized to process information about taste is still far from complete. Many studies on this topic have focused on understanding how gustatory neural circuits are spatially organized to represent information about taste quality (e.g., "sweet", "salty", "bitter", etc.. Arguments pertaining to this issue have largely centered on whether taste is carried by dedicated neural channels or a pattern of activity across a neural population. But there is now mounting evidence that the timing of neural events may also importantly contribute to the representation of taste. In this review, we attempt to summarize recent findings in the field that pertain to these issues. Both space and time are variables likely related to the mechanism of the gustatory neural code: information about taste appears to reside in spatial and temporal patterns of activation in gustatory neurons. What is more, the organization of the taste network in the brain would suggest that the parameters of space and time extend to the neural processing of gustatory information on a much grander scale.

  18. Is integration and survival of newborn neurons the bottleneck for effective neural repair by endogenous neural precursor cells?

    Directory of Open Access Journals (Sweden)

    Ann eTurnley

    2014-02-01

    Full Text Available After two decades of research the existence of adult neural precursor cells and the phenomenon of adult neurogenesis is well established. However, there has been little or no effective harnessing of these endogenous cells to promote functional neuronal replacement following neural injury or disease. Neural precursor cells can respond to neural damage by proliferating, migrating to the site of injury and differentiating into neuronal or glial lineages. However, after a month or so, very few or no newborn neurons can be detected, suggesting that even though neuroblasts are generated, they generally fail to survive as mature neurons and contribute to the local circuitry. Is this lack of survival and integration one of the major bottlenecks that inhibits effective neuronal replacement and subsequent repair of the nervous system following injury or disease? In this perspective article the possibility that this bottleneck can be targeted to enhance the integration and subsequent survival of newborn neurons will be explored and will suggest some possible mechanisms that may need to be modulated for this to occur.

  19. Dynamic stability conditions for Lotka-Volterra recurrent neural networks with delays.

    Science.gov (United States)

    Yi, Zhang; Tan, K K

    2002-07-01

    The Lotka-Volterra model of neural networks, derived from the membrane dynamics of competing neurons, have found successful applications in many "winner-take-all" types of problems. This paper studies the dynamic stability properties of general Lotka-Volterra recurrent neural networks with delays. Conditions for nondivergence of the neural networks are derived. These conditions are based on local inhibition of networks, thereby allowing these networks to possess a multistability property. Multistability is a necessary property of a network that will enable important neural computations such as those governing the decision making process. Under these nondivergence conditions, a compact set that globally attracts all the trajectories of a network can be computed explicitly. If the connection weight matrix of a network is symmetric in some sense, and the delays of the network are in L2 space, we can prove that the network will have the property of complete stability.

  20. GABAergic inhibition in visual cortical plasticity

    Directory of Open Access Journals (Sweden)

    Alessandro Sale

    2010-03-01

    Full Text Available Experience is required for the shaping and refinement of developing neural circuits during well defined periods of early postnatal development called critical periods. Many studies in the visual cortex have shown that intracortical GABAergic circuitry plays a crucial role in defining the time course of the critical period for ocular dominance plasticity. With the end of the critical period, neural plasticity wanes and recovery from the effects of visual defects on visual acuity (amblyopia or binocularity is much reduced or absent. Recent results pointed out that intracortical inhibition is a fundamental limiting factor for adult cortical plasticity and that its reduction by means of different pharmacological and environmental strategies makes it possible to greatly enhance plasticity in the adult visual cortex, promoting ocular dominance plasticity and recovery from amblyopia. Here we focus on the role of intracortical GABAergic circuitry in controlling both developmental and adult cortical plasticity. We shall also discuss the potential clinical application of these findings to neurological disorders in which synaptic plasticity is compromised because of excessive intracortical inhibition.

  1. neural control system

    International Nuclear Information System (INIS)

    Automatic power stabilization control is the desired objective for any reactor operation , especially, nuclear power plants. A major problem in this area is inevitable gap between a real plant ant the theory of conventional analysis and the synthesis of linear time invariant systems. in particular, the trajectory tracking control of a nonlinear plant is a class of problems in which the classical linear transfer function methods break down because no transfer function can represent the system over the entire operating region . there is a considerable amount of research on the model-inverse approach using feedback linearization technique. however, this method requires a prices plant model to implement the exact linearizing feedback, for nuclear reactor systems, this approach is not an easy task because of the uncertainty in the plant parameters and un-measurable state variables . therefore, artificial neural network (ANN) is used either in self-tuning control or in improving the conventional rule-based exper system.the main objective of this thesis is to suggest an ANN, based self-learning controller structure . this method is capable of on-line reinforcement learning and control for a nuclear reactor with a totally unknown dynamics model. previously, researches are based on back- propagation algorithm . back -propagation (BP), fast back -propagation (FBP), and levenberg-marquardt (LM), algorithms are discussed and compared for reinforcement learning. it is found that, LM algorithm is quite superior

  2. Correlational Neural Networks.

    Science.gov (United States)

    Chandar, Sarath; Khapra, Mitesh M; Larochelle, Hugo; Ravindran, Balaraman

    2016-02-01

    Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based approaches and autoencoder (AE)-based approaches. CCA-based approaches learn a joint representation by maximizing correlation of the views when projected to the common subspace. AE-based methods learn a common representation by minimizing the error of reconstructing the two views. Each of these approaches has its own advantages and disadvantages. For example, while CCA-based approaches outperform AE-based approaches for the task of transfer learning, they are not as scalable as the latter. In this work, we propose an AE-based approach, correlational neural network (CorrNet), that explicitly maximizes correlation among the views when projected to the common subspace. Through a series of experiments, we demonstrate that the proposed CorrNet is better than AE and CCA with respect to its ability to learn correlated common representations. We employ CorrNet for several cross-language tasks and show that the representations learned using it perform better than the ones learned using other state-of-the-art approaches. PMID:26654210

  3. Homeostatic scaling of excitability in recurrent neural networks.

    Directory of Open Access Journals (Sweden)

    Michiel W H Remme

    Full Text Available Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which neurons reside. However, most neurons are embedded in recurrent networks, which require a delicate balance between excitation and inhibition to maintain network stability. This balance could be disrupted when neurons independently adjust their intrinsic excitability. Here, we study the functioning of activity-dependent homeostatic scaling of intrinsic excitability (HSE in a recurrent neural network. Using both simulations of a recurrent network consisting of excitatory and inhibitory neurons that implement HSE, and a mean-field description of adapting excitatory and inhibitory populations, we show that the stability of such adapting networks critically depends on the relationship between the adaptation time scales of both neuron populations. In a stable adapting network, HSE can keep all neurons functioning within their dynamic range, while the network is undergoing several (pathophysiologically relevant types of plasticity, such as persistent changes in external drive, changes in connection strengths, or the loss of inhibitory cells from the network. However, HSE cannot prevent the unstable network dynamics that result when, due to such plasticity, recurrent excitation in the network becomes too strong compared to feedback inhibition. This suggests that keeping a neural network in a stable and functional state requires the coordination of distinct homeostatic mechanisms that operate not only by adjusting neural excitability, but also by controlling network connectivity.

  4. Brain Plasticity and Disease: A Matter of Inhibition

    OpenAIRE

    Laura Baroncelli; Chiara Braschi; Maria Spolidoro; Tatjana Begenisic; Lamberto Maffei; Alessandro Sale

    2011-01-01

    One major goal in Neuroscience is the development of strategies promoting neural plasticity in the adult central nervous system, when functional recovery from brain disease and injury is limited. New evidence has underscored a pivotal role for cortical inhibitory circuitries in regulating plasticity both during development and in adulthood. This paper summarizes recent findings showing that the inhibition-excitation balance controls adult brain plasticity and is at the core of the pathogenesi...

  5. Inter-hemispheric inhibition is impaired in mirror dystonia

    OpenAIRE

    S. Beck; Shamim, EA; Pirio, Richardson S; Schubert, M.; Hallett, M

    2009-01-01

    Surround inhibition, a neural mechanism relevant for skilled motor behavior, has been shown to be deficient in the affected primary motor cortex (M1) in patients with focal hand dystonia (FHD). Even in unilateral FHD, however, electrophysiological and neuro-imaging studies have provided evidence for bilateral M1 abnormalities. Clinically, the presence of mirror dystonia, dystonic posturing when the opposite hand is moved, also suggests abnormal interhemispheric interaction. To assess whether ...

  6. Neural network regulation driven by autonomous neural firings

    Science.gov (United States)

    Cho, Myoung Won

    2016-07-01

    Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

  7. Multigradient for Neural Networks for Equalizers

    Directory of Open Access Journals (Sweden)

    Chulhee Lee

    2003-06-01

    Full Text Available Recently, a new training algorithm, multigradient, has been published for neural networks and it is reported that the multigradient outperforms the backpropagation when neural networks are used as a classifier. When neural networks are used as an equalizer in communications, they can be viewed as a classifier. In this paper, we apply the multigradient algorithm to train the neural networks that are used as equalizers. Experiments show that the neural networks trained using the multigradient noticeably outperforms the neural networks trained by the backpropagation.

  8. Inhibition in multiclass classification

    OpenAIRE

    Huerta, Ramón; Vembu, Shankar; Amigó, José M.; Nowotny, Thomas; Elkan, Charles

    2012-01-01

    The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and ...

  9. Neural Networks for Flight Control

    Science.gov (United States)

    Jorgensen, Charles C.

    1996-01-01

    Neural networks are being developed at NASA Ames Research Center to permit real-time adaptive control of time varying nonlinear systems, enhance the fault-tolerance of mission hardware, and permit online system reconfiguration. In general, the problem of controlling time varying nonlinear systems with unknown structures has not been solved. Adaptive neural control techniques show considerable promise and are being applied to technical challenges including automated docking of spacecraft, dynamic balancing of the space station centrifuge, online reconfiguration of damaged aircraft, and reducing cost of new air and spacecraft designs. Our experiences have shown that neural network algorithms solved certain problems that conventional control methods have been unable to effectively address. These include damage mitigation in nonlinear reconfiguration flight control, early performance estimation of new aircraft designs, compensation for damaged planetary mission hardware by using redundant manipulator capability, and space sensor platform stabilization. This presentation explored these developments in the context of neural network control theory. The discussion began with an overview of why neural control has proven attractive for NASA application domains. The more important issues in control system development were then discussed with references to significant technical advances in the literature. Examples of how these methods have been applied were given, followed by projections of emerging application needs and directions.

  10. Optogenetic inhibition of neurons by internal light production

    Directory of Open Access Journals (Sweden)

    Benjamin eLand

    2014-04-01

    Full Text Available Optogenetics is an extremely powerful tool for selective neuronal activation/inhibition and dissection of neural circuits. However, a limitation of in vivo optogenetics is that an animal must be tethered to an optical fiber for delivery of light. Here, we describe a new method for in vivo, optogenetic inhibition of neural activity using an internal, animal-generated light source based on firefly luciferase. Two adeno-associated viruses encoding luciferase were tested and both produced concentration-dependent light after administration of the substrate, luciferin. Mice were co-infected with halorhodopsin- and luciferase-expressing viruses in the striatum, and luciferin administration significantly reduced Fos activity compared to control animals infected with halorhodopsin only. Recordings of neuronal activity in behaving animals confirmed that firing was greatly reduced after luciferin administration. Finally, amphetamine-induced locomotor activity was reduced in halorhodopsin/luciferase mice pre-injected with luciferin compared to controls. This demonstrates that virally encoded luciferase is able to generate sufficient light to activate halorhodopsin and suppress neural activity and change behavior. This approach could be used to generate inhibition in response to activation of specific molecular pathways.

  11. Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

    Science.gov (United States)

    Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

    2015-08-01

    A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed

  12. Are newborn rat-derived neural stem cells more sensitive to lead neurotoxicity?

    Institute of Scientific and Technical Information of China (English)

    Yan Ho Chan; Mingyong Gao; Wutian Wu

    2013-01-01

    Lead ion (Pb2+) has been proven to be a neurotoxin due to its neurotoxicity on mammalian nervous system, especially for the developing brains of juveniles. However, many reported studies involved the negative effects of Pb2+ on adult neural cells of humans or other mammals, only few of which have examined the effects of Pb2+ on neural stem cells. The purpose of this study was to reveal the biological effects of Pb2+ from lead acetate [Pb (CH3COO)2] on viability, proliferation and differentiation of neural stem cells derived from the hippocampus of newborn rats aged 7 days and adult rats aged 90 days, respectively. This study was carried out in three parts. In the first part, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay (MTT viability assay) was used to detect the effects of Pb2+ on the cell viability of passage 2 hippocampal neural stem cells after 200 μM Pb2+, followed by immunocytochemical staining with anti-bromodeoxyuridine to demonstrate the effects of Pb2+ on cell proliferation. In the last part, passage 2 hippocampal neural Immunocytochemical staining with anti-microtubule-associated protein 2 (a neuron marker), anti-glial fibrillary acidic protein (an astrocyte marker), and anti-RIP (an oligodendrocyte marker) was performed to detect the differentiation commitment of affected neural stem cells after 6 days. The data showed that Pb2+ inhibited not only the viability and proliferation of rat hippocampal neural stem cells, but also their neuronal and oligodendrocyte differentiation in vitro. Moreover, increased activity of astrocyte differentiation of hippocampal neural stem cells from both newborn and adult rats was observed after exposure to high concentration of lead ion in vitro. These findings suggest that hippocampal neural stem cells of newborn rats were more sensitive than those from adult rats to Pb2+ cytotoxicity.

  13. Anxiety-Like Behavioural Inhibition Is Normative under Environmental Threat-Reward Correlations.

    Directory of Open Access Journals (Sweden)

    Dominik R Bach

    2015-12-01

    Full Text Available Behavioural inhibition is a key anxiety-like behaviour in rodents and humans, distinct from avoidance of danger, and reduced by anxiolytic drugs. In some situations, it is not clear how behavioural inhibition minimises harm or maximises benefit for the agent, and can even appear counterproductive. Extant explanations of this phenomenon make use of descriptive models but do not provide a formal assessment of its adaptive value. This hampers a better understanding of the neural computations underlying anxiety behaviour. Here, we analyse a standard rodent anxiety model, the operant conflict test. We harvest Bayesian Decision Theory to show that behavioural inhibition normatively arises as cost-minimising strategy in temporally correlated environments. Importantly, only if behavioural inhibition is aimed at minimising cost, it depends on probability and magnitude of threat. Harnessing a virtual computer game, we test model predictions in four experiments with human participants. Humans exhibit behavioural inhibition with a strong linear dependence on threat probability and magnitude. Strikingly, inhibition occurs before motor execution and depends on the virtual environment, thus likely resulting from a neural optimisation process rather than a pre-programmed mechanism. Individual trait anxiety scores predict behavioural inhibition, underlining the validity of this anxiety model. These findings put anxiety behaviour into the context of cost-minimisation and optimal inference, and may ultimately pave the way towards a mechanistic understanding of the neural computations gone awry in human anxiety disorder.

  14. Neural networks and statistical learning

    CERN Document Server

    Du, Ke-Lin

    2014-01-01

    Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...

  15. Principles of neural information processing

    CERN Document Server

    Seelen, Werner v

    2016-01-01

    In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework, but also syst...

  16. Video Compression Using Neural Network

    Directory of Open Access Journals (Sweden)

    Sangeeta Mishra

    2012-08-01

    Full Text Available Apart from the existing technology on image compression represented by series of JPEG, MPEG and H.26x standards, new technology such as neural networks and genetic algorithms are being developed to explore the future of image coding. Successful applications of neural networks to basic propagation algorithm have now become well established and other aspects of neural network involvement in this technology. In this paper different algorithms were implemented like gradient descent back propagation, gradient descent with momentum back propagation, gradient descent with adaptive learning back propagation, gradient descent with momentum and adaptive learning back propagation and Levenberg-Marquardt algorithm. The size of original video clip is 25MB and after compression it becomes 21.3MB giving the compression ratio as 85.2% and compression factor of 1.174. It was observed that the size remains same after compression but the difference is in the clarity.

  17. Performance sustaining intracortical neural prostheses

    Science.gov (United States)

    Nuyujukian, Paul; Kao, Jonathan C.; Fan, Joline M.; Stavisky, Sergey D.; Ryu, Stephen I.; Shenoy, Krishna V.

    2014-12-01

    Objective. Neural prostheses, or brain-machine interfaces, aim to restore efficient communication and movement ability to those suffering from paralysis. A major challenge these systems face is robust performance, particularly with aging signal sources. The aim in this study was to develop a neural prosthesis that could sustain high performance in spite of signal instability while still minimizing retraining time. Approach. We trained two rhesus macaques implanted with intracortical microelectrode arrays 1-4 years prior to this study to acquire targets with a neurally-controlled cursor. We measured their performance via achieved bitrate (bits per second, bps). This task was repeated over contiguous days to evaluate the sustained performance across time. Main results. We found that in the monkey with a younger (i.e., two year old) implant and better signal quality, a fixed decoder could sustain performance for a month at a rate of 4 bps, the highest achieved communication rate reported to date. This fixed decoder was evaluated across 22 months and experienced a performance decline at a rate of 0.24 bps yr-1. In the monkey with the older (i.e., 3.5 year old) implant and poorer signal quality, a fixed decoder could not sustain performance for more than a few days. Nevertheless, performance in this monkey was maintained for two weeks without requiring additional online retraining time by utilizing prior days’ experimental data. Upon analysis of the changes in channel tuning, we found that this stability appeared partially attributable to the cancelling-out of neural tuning fluctuations when projected to two-dimensional cursor movements. Significance. The findings in this study (1) document the highest-performing communication neural prosthesis in monkeys, (2) confirm and extend prior reports of the stability of fixed decoders, and (3) demonstrate a protocol for system stability under conditions where fixed decoders would otherwise fail. These improvements to decoder

  18. Ocean wave forecasting using recurrent neural networks

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    , merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off...

  19. Generalization performance of regularized neural network models

    DEFF Research Database (Denmark)

    Larsen, Jan; Hansen, Lars Kai

    1994-01-01

    Architecture optimization is a fundamental problem of neural network modeling. The optimal architecture is defined as the one which minimizes the generalization error. This paper addresses estimation of the generalization performance of regularized, complete neural network models. Regularization...

  20. The neural cell adhesion molecule

    DEFF Research Database (Denmark)

    Berezin, V; Bock, E; Poulsen, F M

    2000-01-01

    During the past year, the understanding of the structure and function of neural cell adhesion has advanced considerably. The three-dimensional structures of several of the individual modules of the neural cell adhesion molecule (NCAM) have been determined, as well as the structure of the complex...... between two identical fragments of the NCAM. Also during the past year, a link between homophilic cell adhesion and several signal transduction pathways has been proposed, connecting the event of cell surface adhesion to cellular responses such as neurite outgrowth. Finally, the stimulation of neurite...

  1. Neural Network Adaptations to Hardware Implementations

    OpenAIRE

    Moerland, Perry,; Fiesler,Emile

    1997-01-01

    In order to take advantage of the massive parallelism offered by artificial neural networks, hardware implementations are essential.However, most standard neural network models are not very suitable for implementation in hardware and adaptations are needed. In this section an overview is given of the various issues that are encountered when mapping an ideal neural network model onto a compact and reliable neural network hardware implementation, like quantization, handling nonuniformities and ...

  2. Neural Network Adaptations to Hardware Implementations

    OpenAIRE

    Moerland, Perry,; Fiesler,Emile; Beale, R

    1997-01-01

    In order to take advantage of the massive parallelism offered by artificial neural networks, hardware implementations are essential. However, most standard neural network models are not very suitable for implementation in hardware and adaptations are needed. In this section an overview is given of the various issues that are encountered when mapping an ideal neural network model onto a compact and reliable neural network hardware implementation, like quantization, handling nonuniformities and...

  3. Building a Chaotic Proved Neural Network

    CERN Document Server

    Bahi, Jacques M; Salomon, Michel

    2011-01-01

    Chaotic neural networks have received a great deal of attention these last years. In this paper we establish a precise correspondence between the so-called chaotic iterations and a particular class of artificial neural networks: global recurrent multi-layer perceptrons. We show formally that it is possible to make these iterations behave chaotically, as defined by Devaney, and thus we obtain the first neural networks proven chaotic. Several neural networks with different architectures are trained to exhibit a chaotical behavior.

  4. Model Of Neural Network With Creative Dynamics

    Science.gov (United States)

    Zak, Michail; Barhen, Jacob

    1993-01-01

    Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.

  5. Analysis of Neural Networks through Base Functions

    NARCIS (Netherlands)

    Zwaag, van der B.J.; Slump, C.H.; Spaanenburg, L.

    2002-01-01

    Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

  6. Simplified LQG Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    A new neural network application for non-linear state control is described. One neural network is modelled to form a Kalmann predictor and trained to act as an optimal state observer for a non-linear process. Another neural network is modelled to form a state controller and trained to produce...

  7. Hybrid neural modelling of an anaerobic digester with respect to biological constraints.

    Science.gov (United States)

    Karama, A; Bernard, O; Gouzé, J L; Benhammou, A; Dochain, D

    2001-01-01

    A hybrid model for an anaerobic digestion process is proposed. The fermentation is assumed to be performed in two steps, acidogenesis and methanogenesis, by two bacterial populations. The model is based on mass balance equations, and the bacterial growth rates are represented by neural networks. In order to guarantee the biological meaning of the hybrid model (positivity of the concentrations, boundedness, saturation or inhibition of the growth rates) outside the training data set, a method that imposes constraints in the neural network is proposed. The method is applied to experimental data from a fixed bed reactor.

  8. Neural chips, neural computers and application in high and superhigh energy physics experiments

    International Nuclear Information System (INIS)

    Architecture peculiarity and characteristics of series of neural chips and neural computes used in scientific instruments are considered. Tendency of development and use of them in high energy and superhigh energy physics experiments are described. Comparative data which characterize the efficient use of neural chips for useful event selection, classification elementary particles, reconstruction of tracks of charged particles and for search of hypothesis Higgs particles are given. The characteristics of native neural chips and accelerated neural boards are considered

  9. Local increase level of chondroitin sulfate induces changes in the rhombencephalic neural crest migration.

    Science.gov (United States)

    Moro Balbás, J A; Gato, A; Alonso, M; Barbosa, E

    1998-03-01

    Numerous studies suggest that chondroitin sulfate proteoglycan (CSPG) inhibits neural crest cells (NCC) migration at the trunk level. However, its action on the cephalic neural crest is not clear. To determine this action, we have microinjected 0.5 nl of different concentrations of chondroitin sulfate (CS) at the anterior rhombencephalon level in 9 stage chick embryos, as well as subgerminally administering beta-D-xyloside to 8 stage chick embryos. Beta-D-xyloside disrupts CSPG synthesis, producing an increase in CS free chains in several embryonal anlages. Chondroitin sulfate microinjected embryos and beta-D xyloside treated embryos were reincubated until attaining 12 stage. Results obtained for both experimental groups were similar. Immunoreactivity with HNK-1 antibody revealed that NCC did not migrate, remaining near the rhombencephalon dorsal wall; in addition, several NCC did not separate from the neural fold, becoming invaginated towards the rhombencephalon cavity. Our findings indicate that an increase in CS free chains in cephalic neural crest migratory routes not only disrupts their migration, but also impedes delamination and detachment of the rhombencephalic neuroepithelium NCC. These data suggest that the inhibitory action upon the neural crest migration attributed to CSPG may rest on its glycosaminoglycan (GAG). We cannot, however, rule out the possibility that increases in other GAGs apart from CS, may produce similar effects on neural crest migration. PMID:9551866

  10. Neural Control of the Circulation

    Science.gov (United States)

    Thomas, Gail D.

    2011-01-01

    The purpose of this brief review is to highlight key concepts about the neural control of the circulation that graduate and medical students should be expected to incorporate into their general knowledge of human physiology. The focus is largely on the sympathetic nerves, which have a dominant role in cardiovascular control due to their effects to…

  11. Neural Network based Consumption Forecasting

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    2016-01-01

    This paper describe a Neural Network based method for consumption forecasting. This work has been financed by the The ENCOURAGE project. The aims of The ENCOURAGE project is to develop embedded intelligence and integration technologies that will directly optimize energy use in buildings and enable...

  12. Nanomaterial-enabled neural stimulation

    Directory of Open Access Journals (Sweden)

    Yongchen eWang

    2016-03-01

    Full Text Available Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a high spatial resolution and cell-type specificity. In these techniques, a nanomaterial converts a remotely transmitted primary stimulus such as a light, magnetic or ultrasonic signal to a localized secondary stimulus such as an electric field or heat to stimulate neurons. The ease of surface modification and bio-conjugation of nanomaterials facilitates cell-type-specific targeting, designated placement and highly localized membrane activation. This review focuses on nanomaterial-enabled neural stimulation techniques primarily involving opto-electric, opto-thermal, magneto-electric, magneto-thermal and acousto-electric transduction mechanisms. Stimulation techniques based on other possible transduction schemes and general consideration for these emerging neurotechnologies are also discussed.

  13. Nanomaterial-Enabled Neural Stimulation.

    Science.gov (United States)

    Wang, Yongchen; Guo, Liang

    2016-01-01

    Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a high spatial resolution and cell-type specificity. In these techniques, a nanomaterial converts a remotely transmitted primary stimulus such as a light, magnetic or ultrasonic signal to a localized secondary stimulus such as an electric field or heat to stimulate neurons. The ease of surface modification and bio-conjugation of nanomaterials facilitates cell-type-specific targeting, designated placement and highly localized membrane activation. This review focuses on nanomaterial-enabled neural stimulation techniques primarily involving opto-electric, opto-thermal, magneto-electric, magneto-thermal and acousto-electric transduction mechanisms. Stimulation techniques based on other possible transduction schemes and general consideration for these emerging neurotechnologies are also discussed.

  14. Nanomaterial-Enabled Neural Stimulation.

    Science.gov (United States)

    Wang, Yongchen; Guo, Liang

    2016-01-01

    Neural stimulation is a critical technique in treating neurological diseases and investigating brain functions. Traditional electrical stimulation uses electrodes to directly create intervening electric fields in the immediate vicinity of neural tissues. Second-generation stimulation techniques directly use light, magnetic fields or ultrasound in a non-contact manner. An emerging generation of non- or minimally invasive neural stimulation techniques is enabled by nanotechnology to achieve a high spatial resolution and cell-type specificity. In these techniques, a nanomaterial converts a remotely transmitted primary stimulus such as a light, magnetic or ultrasonic signal to a localized secondary stimulus such as an electric field or heat to stimulate neurons. The ease of surface modification and bio-conjugation of nanomaterials facilitates cell-type-specific targeting, designated placement and highly localized membrane activation. This review focuses on nanomaterial-enabled neural stimulation techniques primarily involving opto-electric, opto-thermal, magneto-electric, magneto-thermal and acousto-electric transduction mechanisms. Stimulation techniques based on other possible transduction schemes and general consideration for these emerging neurotechnologies are also discussed. PMID:27013938

  15. Memory Storage and Neural Systems.

    Science.gov (United States)

    Alkon, Daniel L.

    1989-01-01

    Investigates memory storage and molecular nature of associative-memory formation by analyzing Pavlovian conditioning in marine snails and rabbits. Presented is the design of a computer-based memory system (neural networks) using the rules acquired in the investigation. Reports that the artificial network recognized patterns well. (YP)

  16. Neural Basis of Visual Distraction

    Science.gov (United States)

    Kim, So-Yeon; Hopfinger, Joseph B.

    2010-01-01

    The ability to maintain focus and avoid distraction by goal-irrelevant stimuli is critical for performing many tasks and may be a key deficit in attention-related problems. Recent studies have demonstrated that irrelevant stimuli that are consciously perceived may be filtered out on a neural level and not cause the distraction triggered by…

  17. Phase Transitions of Neural Networks

    OpenAIRE

    Kinzel, Wolfgang

    1997-01-01

    The cooperative behaviour of interacting neurons and synapses is studied using models and methods from statistical physics. The competition between training error and entropy may lead to discontinuous properties of the neural network. This is demonstrated for a few examples: Perceptron, associative memory, learning from examples, generalization, multilayer networks, structure recognition, Bayesian estimate, on-line training, noise estimation and time series generation.

  18. Artificial neural networks in medicine

    Energy Technology Data Exchange (ETDEWEB)

    Keller, P.E.

    1994-07-01

    This Technology Brief provides an overview of artificial neural networks (ANN). A definition and explanation of an ANN is given and situations in which an ANN is used are described. ANN applications to medicine specifically are then explored and the areas in which it is currently being used are discussed. Included are medical diagnostic aides, biochemical analysis, medical image analysis and drug development.

  19. Medical Imaging with Neural Networks

    International Nuclear Information System (INIS)

    The objective of this paper is to provide an overview of the recent developments in the use of artificial neural networks in medical imaging. The areas of medical imaging that are covered include : ultrasound, magnetic resonance, nuclear medicine and radiological (including computerized tomography). (authors)

  20. Aphasia Classification Using Neural Networks

    DEFF Research Database (Denmark)

    Axer, H.; Jantzen, Jan; Berks, G.;

    2000-01-01

    A web-based software model (http://fuzzy.iau.dtu.dk/aphasia.nsf) was developed as an example for classification of aphasia using neural networks. Two multilayer perceptrons were used to classify the type of aphasia (Broca, Wernicke, anomic, global) according to the results in some subtests...

  1. Investigation of variables influencing cognitive inhibition: from the behavioral to the molecular level

    OpenAIRE

    Dieler, Alica Christina

    2011-01-01

    The present work investigated the neural mechanisms underlying cognitive inhibition/thought suppression in Anderson’s and Green’s Think/No-Think paradigm (TNT), as well as different variables influencing these mechanisms at the cognitive, the neurophysiological, the electrophysiological and the molecular level. Neurophysiological data collected with fNIRS and fMRI have added up to the existing evidence of a fronto-hippocampal network interacting during the inhibition of unwanted thoughts. Som...

  2. The neural crest and neural crest cells: discovery and significance for theories of embryonic organization

    Indian Academy of Sciences (India)

    Brian K Hall

    2008-12-01

    The neural crest has long fascinated developmental biologists, and, increasingly over the past decades, evolutionary and evolutionary developmental biologists. The neural crest is the name given to the fold of ectoderm at the junction between neural and epidermal ectoderm in neurula-stage vertebrate embryos. In this sense, the neural crest is a morphological term akin to head fold or limb bud. This region of the dorsal neural tube consists of neural crest cells, a special population(s) of cell, that give rise to an astonishing number of cell types and to an equally astonishing number of tissues and organs. Neural crest cell contributions may be direct — providing cells — or indirect — providing a necessary, often inductive, environment in which other cells develop. The enormous range of cell types produced provides an important source of evidence of the neural crest as a germ layer, bringing the number of germ layers to four — ectoderm, endoderm, mesoderm, and neural crest. In this paper I provide a brief overview of the major phases of investigation into the neural crest and the major players involved, discuss how the origin of the neural crest relates to the origin of the nervous system in vertebrate embryos, discuss the impact on the germ-layer theory of the discovery of the neural crest and of secondary neurulation, and present evidence of the neural crest as the fourth germ layer. A companion paper (Hall, Evol. Biol. 2008) deals with the evolutionary origins of the neural crest and neural crest cells.

  3. [Neural mechanisms of decision making].

    Science.gov (United States)

    Funahashi, Shintaro

    2008-09-01

    Decision-making plays an important role in the transformation of incoming sensory information to purposeful actions. Many decisions have important biological and social consequences, while others may have a more limited impact on our everyday life. The neural mechanisms of decision-making currently constitute an important subject under intense investigation in the field of cognitive and behavioral neuroscience. Among the investigations, on this topic, those involving sensory discrimination tasks using visual motion have provided a wealth of information about the nature of the neural circuitry required to perform perceptual decision-making. For example, by using a motion discrimination task, Shadlen and Newsome have shown an essential role of area LIP in perceptual decision-making. On the other hand, the importance of reward and reward expectations as determinants of decision-making is increasingly appreciated. In particular, reinforcement learning and economic theories, such as game theory, have provided valuable insights into the brain functions related to decision-making. By using a competitive game analogous to matching pennies against a computer, Lee's group showed that in monkeys, previous selections modulated prefrontal neural activity and that this modulation affected the current choice behavior. The prefrontal cortex has been shown to participate in decision-making in free-choice conditions. By using a task involving the free choice of 1 target from multiple saccade targets, Funahashi's group examined the prefrontal participation in decision-making in a free-choice condition. They compared the activities of prefrontal neurons during an oculomotor delay task with forced-choice conditions and free-choice conditions and identified the neural components reflecting the underlying decision-making processes. Although several attempts have been made to understand the neural mechanisms of decision-making, further investigations are required to fully understand these

  4. Micro- and nanotechnologies for optical neural interfaces

    Directory of Open Access Journals (Sweden)

    Ferruccio ePisanello

    2016-03-01

    Full Text Available In last decade, the possibility to optically interface with the mammalian brain in vivo has allowed unprecedented investigation of functional connectivity of neural circuitry. Together with new genetic and molecular techniques to optically trigger and monitor neural activity, a new generation of optical neural interfaces is being developed, mainly thanks to the exploitation of both bottom-up and top-down nanofabrication approaches. This review discusses the role of nanotechnologies for optical neural interfaces, with particular emphasis on new devices and methodologies for optogenetic control of neural activity and unconventional methods for detection and triggering of action potentials using optically-active colloidal nanoparticles.

  5. Balanced Neural Architecture and the Idling Brain

    Directory of Open Access Journals (Sweden)

    Brent eDoiron

    2014-05-01

    Full Text Available A signature feature of cortical spike trains is their trial-to-trial variability. This variability is large in spontaneous conditions and is reduced when cortex is driven by a stimulus or task. Models of recurrent cortical networks with unstructured, yet balanced, excitation and inhibition generate variability consistent with evoked conditions. However, these models lack the long timescale fluctuations and large variability present in spontaneous conditions. We propose that global network architectures which support a large number of stable states (attractor networks allow balanced networks to capture key features of neural variability in both spontaneous and evoked conditions. We illustrate this using balanced spiking networks with clustered assembly, feedforward chain, and ring structures. By assuming that global network structure is related to stimulus preference, we show that signal correlations are related to the magnitude of correlations in the spontaneous state. In our models, the dynamics of spontaneous activity encompasses much of the possible evoked states, consistent with many experimental reports. Finally, we contrast the impact of stimulation on the trial-to-trial variability in attractor networks with that of strongly coupled spiking networks with chaotic firing rate instabilities, recently investigated by Ostojic (2014. We find that only attractor networks replicate an experimentally observed stimulus-induced quenching of trial-to-trial variability. In total, the comparison of the trial-variable dynamics of single neurons or neuron pairs during spontaneous and evoked activity can be a window into the global structure of balanced cortical networks.

  6. Fuzzy logic systems are equivalent to feedforward neural networks

    Institute of Scientific and Technical Information of China (English)

    李洪兴

    2000-01-01

    Fuzzy logic systems and feedforward neural networks are equivalent in essence. First, interpolation representations of fuzzy logic systems are introduced and several important conclusions are given. Then three important kinds of neural networks are defined, i.e. linear neural networks, rectangle wave neural networks and nonlinear neural networks. Then it is proved that nonlinear neural networks can be represented by rectangle wave neural networks. Based on the results mentioned above, the equivalence between fuzzy logic systems and feedforward neural networks is proved, which will be very useful for theoretical research or applications on fuzzy logic systems or neural networks by means of combining fuzzy logic systems with neural networks.

  7. Long-Lasting Neural Circuit Dysfunction Following Developmental Ethanol Exposure

    Directory of Open Access Journals (Sweden)

    Mariko Saito

    2013-04-01

    Full Text Available Fetal Alcohol Spectrum Disorder (FASD is a general diagnosis for those exhibiting long-lasting neurobehavioral and cognitive deficiencies as a result of fetal alcohol exposure. It is among the most common causes of mental deficits today. Those impacted are left to rely on advances in our understanding of the nature of early alcohol-induced disorders toward human therapies. Research findings over the last decade have developed a model where ethanol-induced neurodegeneration impacts early neural circuit development, thereby perpetuating subsequent integration and plasticity in vulnerable brain regions. Here we review our current knowledge of FASD neuropathology based on discoveries of long-lasting neurophysiological effects of acute developmental ethanol exposure in animal models. We discuss the important balance between synaptic excitation and inhibition in normal neural network function, and relate the significance of that balance to human FASD as well as related disease states. Finally, we postulate that excitation/inhibition imbalance caused by early ethanol-induced neurodegeneration results in perturbed local and regional network signaling and therefore neurobehavioral pathology.

  8. Prediction aluminum corrosion inhibitor efficiency using artificial neural network (ANN)

    Science.gov (United States)

    Ebrahimi, Sh; Kalhor, E. G.; Nabavi, S. R.; Alamiparvin, L.; Pogaku, R.

    2016-06-01

    In this study, activity of some Schiff bases as aluminum corrosion inhibitor was investigated using artificial neural network (ANN). Hence, corrosion inhibition efficiency of Schiff bases (in any type) were gathered from different references. Then these molecules were drawn and optimized in Hyperchem software. Molecular descriptors generating and descriptors selection were fulfilled by Dragon software and principal component analysis (PCA) method, respectively. These structural descriptors along with environmental descriptors (ambient temperature, time of exposure, pH and the concentration of inhibitor) were used as input variables. Furthermore, aluminum corrosion inhibition efficiency was used as output variable. Experimental data were split into three sets: training set (for model building) and test set (for model validation) and simulation (for general model). Modeling was performed by Multiple linear regression (MLR) methods and artificial neural network (ANN). The results obtained in linear models showed poor correlation between experimental and theoretical data. However nonlinear model presented satisfactory results. Higher correlation coefficient of ANN (R > 0.9) revealed that ANN can be successfully applied for prediction of aluminum corrosion inhibitor efficiency of Schiff bases in different environmental conditions.

  9. Multifractal detrended fluctuation analysis of optogenetic modulation of neural activity

    Science.gov (United States)

    Kumar, S.; Gu, L.; Ghosh, N.; Mohanty, S. K.

    2013-02-01

    Here, we introduce a computational procedure to examine whether optogenetically activated neuronal firing recordings could be characterized as multifractal series. Optogenetics is emerging as a valuable experimental tool and a promising approach for studying a variety of neurological disorders in animal models. The spiking patterns from cortical region of the brain of optogenetically-stimulated transgenic mice were analyzed using a sophisticated fluctuation analysis method known as multifractal detrended fluctuation analysis (MFDFA). We observed that the optogenetically-stimulated neural firings are consistent with a multifractal process. Further, we used MFDFA to monitor the effect of chemically induced pain (formalin injection) and optogenetic treatment used to relieve the pain. In this case, dramatic changes in parameters characterizing a multifractal series were observed. Both the generalized Hurst exponent and width of singularity spectrum effectively differentiates the neural activities during control and pain induction phases. The quantitative nature of the analysis equips us with better measures to quantify pain. Further, it provided a measure for effectiveness of the optogenetic stimulation in inhibiting pain. MFDFA-analysis of spiking data from other deep regions of the brain also turned out to be multifractal in nature, with subtle differences in the parameters during pain-induction by formalin injection and inhibition by optogenetic stimulation. Characterization of neuronal firing patterns using MFDFA will lead to better understanding of neuronal response to optogenetic activation and overall circuitry involved in the process.

  10. Metastable dynamics in heterogeneous neural fields.

    Science.gov (United States)

    Schwappach, Cordula; Hutt, Axel; Beim Graben, Peter

    2015-01-01

    We present numerical simulations of metastable states in heterogeneous neural fields that are connected along heteroclinic orbits. Such trajectories are possible representations of transient neural activity as observed, for example, in the electroencephalogram. Based on previous theoretical findings on learning algorithms for neural fields, we directly construct synaptic weight kernels from Lotka-Volterra neural population dynamics without supervised training approaches. We deliver a MATLAB neural field toolbox validated by two examples of one- and two-dimensional neural fields. We demonstrate trial-to-trial variability and distributed representations in our simulations which might therefore be regarded as a proof-of-concept for more advanced neural field models of metastable dynamics in neurophysiological data. PMID:26175671

  11. Effect of midazolam on the proliferation of neural stem cells isolated from rat hippocampus

    Institute of Scientific and Technical Information of China (English)

    Sanjun Zhao; Yajing Zhu; Rui Xue; Yunfeng Li; Hui Lu; Weidong Mi

    2012-01-01

    In many recent studies,the inhibitory transmitter gamma-aminobutyric acid has been shown to modulate the proliferation,differentiation and survival of neural stem cells.Most general anesthetics are partial or allosteric gamma-aminobutyric acid A receptor agonists,suggesting that general anesthetics could alter the behavior of neural stem cells.The neuroprotective efficacy of general anesthetics has been recognized for decades,but their effects on the proliferation of neural stem cells have received little attention.This study investigated the potential effect of midazolam,an extensively used general anesthetic and allosteric gamma-aminobutyric acid A receptor agonist,on the proliferation of neural stem cells in vitro and preliminarily explored the underlying mechanism.The proliferation of neural stem cells was tested using both Cell Counting Kit 8 and bromodeoxyuridine incorporation experiments.Cell distribution analysis was performed to describe changes in the cell cycle distribution in response to midazolam.Calcium imaging was employed to explore the molecular signaling pathways activated by midazolam.Midazolam (30-90 μM) decreased the proliferation of neural stem cells in vitro.Pretreatment with the gamma-aminobutyric acid A receptor antagonist bicuculline or Na-K-2Cl cotransport inhibitor furosemide partially rescued this inhibition.In addition,midazolam triggered a calcium influx into neural stem cells.The suppressive effect of midazolam on the proliferation of neural stem cells can be partly attributed to the activation of gamma-aminobutyric acid A receptor.The calcium influx triggered by midazolam may be a trigger factor leading to further downstream events.

  12. Human neural progenitors express functional lysophospholipid receptors that regulate cell growth and morphology

    Directory of Open Access Journals (Sweden)

    Callihan Phillip

    2008-12-01

    Full Text Available Abstract Background Lysophospholipids regulate the morphology and growth of neurons, neural cell lines, and neural progenitors. A stable human neural progenitor cell line is not currently available in which to study the role of lysophospholipids in human neural development. We recently established a stable, adherent human embryonic stem cell-derived neuroepithelial (hES-NEP cell line which recapitulates morphological and phenotypic features of neural progenitor cells isolated from fetal tissue. The goal of this study was to determine if hES-NEP cells express functional lysophospholipid receptors, and if activation of these receptors mediates cellular responses critical for neural development. Results Our results demonstrate that Lysophosphatidic Acid (LPA and Sphingosine-1-phosphate (S1P receptors are functionally expressed in hES-NEP cells and are coupled to multiple cellular signaling pathways. We have shown that transcript levels for S1P1 receptor increased significantly in the transition from embryonic stem cell to hES-NEP. hES-NEP cells express LPA and S1P receptors coupled to Gi/o G-proteins that inhibit adenylyl cyclase and to Gq-like phospholipase C activity. LPA and S1P also induce p44/42 ERK MAP kinase phosphorylation in these cells and stimulate cell proliferation via Gi/o coupled receptors in an Epidermal Growth Factor Receptor (EGFR- and ERK-dependent pathway. In contrast, LPA and S1P stimulate transient cell rounding and aggregation that is independent of EGFR and ERK, but dependent on the Rho effector p160 ROCK. Conclusion Thus, lysophospholipids regulate neural progenitor growth and morphology through distinct mechanisms. These findings establish human ES cell-derived NEP cells as a model system for studying the role of lysophospholipids in neural progenitors.

  13. Methods of Telomerase Inhibition

    OpenAIRE

    Andrews, Lucy G.; Tollefsbol, Trygve O.

    2008-01-01

    Telomerase is central to cellular immortality and is a key component of most cancer cells although this enzyme is rarely expressed to significant levels in normal cells. Therefore, the inhibition of telomerase has garnered considerable attention as a possible anticancer approach. Many of the methods applied to telomerase inhibition focus on either of the two major components of the ribonucleoprotein holoenzyme, that is, the telomerase reverse transcriptase (TERT) catalytic subunit or the telo...

  14. Altered Inhibition-Related Frontolimbic Connectivity in Obsessive-Compulsive Disorder

    NARCIS (Netherlands)

    van Velzen, Laura S.; de Wit, Stella J.; Curcic-Blake, Branisalava; Cath, Danielle C.; de Vries, Froukje E.; Veltman, Dick J.; van der Werf, Ysbrand D.; van den Heuvel, Odile A.

    2015-01-01

    Background: Recent studies have shown that response inhibition is impaired in patients with obsessive-compulsive disorder and their unaffected siblings, suggesting that these deficits may be considered a cognitive endophenotype of obsessive-compulsive disorder. Structural and functional neural corre

  15. Expressive suppression and neural responsiveness to nonverbal affective cues.

    Science.gov (United States)

    Petrican, Raluca; Rosenbaum, R Shayna; Grady, Cheryl

    2015-10-01

    Optimal social functioning occasionally requires concealment of one's emotions in order to meet one's immediate goals and environmental demands. However, because emotions serve an important communicative function, their habitual suppression disrupts the flow of social exchanges and, thus, incurs significant interpersonal costs. Evidence is accruing that the disruption in social interactions, linked to habitual expressive suppression use, stems not only from intrapersonal, but also from interpersonal causes, since the suppressors' restricted affective displays reportedly inhibit their interlocutors' emotionally expressive behaviors. However, expressive suppression use is not known to lead to clinically significant social impairments. One explanation may be that over the lifespan, individuals who habitually suppress their emotions come to compensate for their interlocutors' restrained expressive behaviors by developing an increased sensitivity to nonverbal affective cues. To probe this issue, the present study used functional magnetic resonance imaging (fMRI) to scan healthy older women while they viewed silent videos of a male social target displaying nonverbal emotional behavior, together with a brief verbal description of the accompanying context, and then judged the target's affect. As predicted, perceivers who reported greater habitual use of expressive suppression showed increased neural processing of nonverbal affective cues. This effect appeared to be coordinated in a top-down manner via cognitive control. Greater neural processing of nonverbal cues among perceivers who habitually suppress their emotions was linked to increased ventral striatum activity, suggestive of increased reward value/personal relevance ascribed to emotionally expressive nonverbal behaviors. These findings thus provide neural evidence broadly consistent with the hypothesized link between habitual use of expressive suppression and compensatory development of increased responsiveness to

  16. Response inhibition signals and miscoding of direction in dorsomedial striatum

    Directory of Open Access Journals (Sweden)

    Daniel W Bryden

    2012-09-01

    Full Text Available The ability to inhibit action is critical for everyday behavior and is affected by a variety of disorders. Behavioral control and response inhibition is thought to depend on a neural circuit that includes the dorsal striatum, yet the neural signals that lead to response inhibition and its failure are unclear. To address this issue, we recorded from neurons in rat dorsomedial striatum (mDS in a novel task in which rats responded to a spatial cue that signaled that reward would be delivered either to the left or to the right. On 80% of trials rats were instructed to respond in the direction cued by the light (GO. On 20% of trials a second light illuminated instructing the rat to refrain from making the cued movement and move in the opposite direction (STOP. Many neurons in mDS encoded direction, firing more or less strongly for GO movements made ipsilateral or contralateral to the recording electrode. Neurons that fired more strongly for contralateral GO responses were more active when rats were faster, showed reduced activity on STOP trials, and miscoded direction on errors, suggesting that when these neurons were overly active, response inhibition failed. Neurons that decreased firing for contralateral movement were excited during trials in which the rat was required to stop the ipsilateral movement. For these neurons activity was reduced when errors were made and was negatively correlated with movement time suggesting that when these neurons were less active on STOP trials, response inhibition failed. Finally, the activity of a significant number of neurons represented a global inhibitory signal, firing more strongly during response inhibition regardless of response direction. Breakdown by cell type suggests that putative medium spiny neurons tended to fire more strongly under STOP trials, whereas putative interneurons exhibited both activity patterns. 

  17. Research on Power Control of Wind Power Generation Based on Neural Network Adaptive Control

    Institute of Scientific and Technical Information of China (English)

    Hai-ying DONG; Chuan-hua SUN

    2010-01-01

    -For the characteristics of wind power generation system is multivariable,nonlinear and random,in this paper the neural network PID adaptive control is adopted.The size of pitch angle is adjusted in time to improve the performance of power control.The PID parameters are corrected by the gradient descent method,and Radial Basis Functinn(RBF)neural network is used as the system identifier in this method.Simulation results shaw that by using neural adaptive PID controller the generator power control can inhibit effectively the speed and affect the output power of generator.The dynamic performance and robustness of the controlled system is good,and the performance of wind power system is improved.

  18. Neural Excitability and Singular Bifurcations.

    Science.gov (United States)

    De Maesschalck, Peter; Wechselberger, Martin

    2015-12-01

    We discuss the notion of excitability in 2D slow/fast neural models from a geometric singular perturbation theory point of view. We focus on the inherent singular nature of slow/fast neural models and define excitability via singular bifurcations. In particular, we show that type I excitability is associated with a novel singular Bogdanov-Takens/SNIC bifurcation while type II excitability is associated with a singular Andronov-Hopf bifurcation. In both cases, canards play an important role in the understanding of the unfolding of these singular bifurcation structures. We also explain the transition between the two excitability types and highlight all bifurcations involved, thus providing a complete analysis of excitability based on geometric singular perturbation theory.

  19. Neural mechanisms of communicative innovation.

    Science.gov (United States)

    Stolk, Arjen; Verhagen, Lennart; Schoffelen, Jan-Mathijs; Oostenveld, Robert; Blokpoel, Mark; Hagoort, Peter; van Rooij, Iris; Toni, Ivan

    2013-09-01

    Human referential communication is often thought as coding-decoding a set of symbols, neglecting that establishing shared meanings requires a computational mechanism powerful enough to mutually negotiate them. Sharing the meaning of a novel symbol might rely on similar conceptual inferences across communicators or on statistical similarities in their sensorimotor behaviors. Using magnetoencephalography, we assess spectral, temporal, and spatial characteristics of neural activity evoked when people generate and understand novel shared symbols during live communicative interactions. Solving those communicative problems induced comparable changes in the spectral profile of neural activity of both communicators and addressees. This shared neuronal up-regulation was spatially localized to the right temporal lobe and the ventromedial prefrontal cortex and emerged already before the occurrence of a specific communicative problem. Communicative innovation relies on neuronal computations that are shared across generating and understanding novel shared symbols, operating over temporal scales independent from transient sensorimotor behavior.

  20. Neural Networks Methodology and Applications

    CERN Document Server

    Dreyfus, Gérard

    2005-01-01

    Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts ands seemlessly edited to present a coherent and comprehensive, yet not redundant, practically-oriented...

  1. Neural Networks and Photometric Redshifts

    CERN Document Server

    Tagliaferri, R; Andreon, S; Capozziello, S; Donalek, C; Giordano, G; Tagliaferri, Roberto; Longo, Giuseppe; Andreon, Stefano; Capozziello, Salvatore; Donalek, Ciro; Giordano, Gerardo

    2002-01-01

    We present a neural network based approach to the determination of photometric redshift. The method was tested on the Sloan Digital Sky Survey Early Data Release (SDSS-EDR) reaching an accuracy comparable and, in some cases, better than SED template fitting techniques. Different neural networks architecture have been tested and the combination of a Multi Layer Perceptron with 1 hidden layer (22 neurons) operated in a Bayesian framework, with a Self Organizing Map used to estimate the accuracy of the results, turned out to be the most effective. In the best experiment, the implemented network reached an accuracy of 0.020 (interquartile error) in the range 0

  2. Genetic attack on neural cryptography.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka; Kanter, Ido

    2006-03-01

    Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size.

  3. Next generation neural mass models

    OpenAIRE

    Coombes, Stephen; Byrne, Áine

    2016-01-01

    Neural mass models have been actively used since the 1970s to model the coarse grained activity of large populations of neurons and synapses. They have proven especially useful in understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. In this chapter we consider the $\\theta$-neuron model that has recently been shown to admi...

  4. Cortical Microstimulation for Neural Prostheses

    OpenAIRE

    Venkatraman, Subramaniam

    2010-01-01

    Brain-controlled prostheses have the potential to improve the quality of life of a large number of paralyzed persons by allowing them to control prosthetic limbs simply by thought. An essential requirement for natural use of such neural prostheses is that the user should be provided with somatosensory feedback from the artificial limb. This can be achieved by electrically stimulating small populations of neurons in the cortex; a process known as cortical microstimulation. This dissertation de...

  5. Learning with heterogeneous neural networks

    OpenAIRE

    Belanche Muñoz, Luis Antonio

    2011-01-01

    This chapter studies a class of neuron models that computes a user-defined similarity function between inputs and weights. The neuron transfer function is formed by composition of an adapted logistic function with the quasi-linear mean of the partial input-weight similarities. The neuron model is capable of dealing directly with mixtures of continuous as well as discrete quantities, among other data types and there is provision for missing values. An artificial neural network using these n...

  6. Neural Prostheses and Brain Plasticity

    OpenAIRE

    Fallon, James B.; Irvine, Dexter R. F.; Shepherd, Robert K.

    2009-01-01

    The success of modern neural prostheses is dependent on a complex interplay between the devices’ hardware and software and the dynamic environment in which the devices operate: the patient’s body or ‘wetware’. Over 110,000 severe/profoundly deaf individuals presently receive information enabling auditory awareness and speech perception from cochlear implants. The cochlear implant therefore provides a useful case study for a review of the complex interactions between hardware, software and wet...

  7. Neural crest migration: trailblazing ahead

    OpenAIRE

    Kulesa, Paul M.; McLennan, Rebecca

    2015-01-01

    Embryonic cell migration patterns are amazingly complex in the timing and spatial distribution of cells throughout the vertebrate landscape. However, advances in in vivo visualization, cell interrogation, and computational modeling are extracting critical features that underlie the mechanistic nature of these patterns. The focus of this review highlights recent advances in the study of the highly invasive neural crest cells and their migratory patterns during embryonic development. We discuss...

  8. Handbook on neural information processing

    CERN Document Server

    Maggini, Marco; Jain, Lakhmi

    2013-01-01

    This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include:                         Deep architectures                         Recurrent, recursive, and graph neural networks                         Cellular neural networks                         Bayesian networks                         Approximation capabilities of neural networks                         Semi-supervised learning                         Statistical relational learning                         Kernel methods for structured data                         Multiple classifier systems                         Self organisation and modal learning                         Applications to ...

  9. Producing Insulin from Neural Cells

    OpenAIRE

    Yuichi Hori; Xueying Gu; Xiaodong Xie; Kim, Seung K.

    2005-01-01

    BACKGROUND: Success in islet-transplantation-based therapies for type 1 diabetes, coupled with a worldwide shortage of transplant-ready islets, has motivated efforts to develop renewable sources of islet-replacement tissue. Islets and neurons share features, including common developmental programs, and in some species brain neurons are the principal source of systemic insulin. METHODS AND FINDINGS: Here we show that brain-derived human neural progenitor cells, exposed to a series of signals t...

  10. Neural substrates of driving behaviour

    OpenAIRE

    Spiers, H. J.; Maguire, E. A.

    2007-01-01

    Driving a vehicle is an indispensable daily behaviour for many people, yet we know little about how it is supported by the brain. Given that driving in the real world involves the engagement of many cognitive systems that rapidly change to meet varying environmental demands, identifying its neural basis presents substantial problems. By employing a unique combination of functional magnetic resonance imaging (fMRI), an accurate interactive virtual simulation of a bustling central London (UK) a...

  11. Neural Stem Cells and Glioblastoma

    OpenAIRE

    Rispoli, Rossella; Conti, Carlo; Celli, Paolo; Caroli, Emanuela; Carletti, Sandro

    2014-01-01

    Glioblastoma multiforme represents one of the most common brain cancers with a rather heterogeneous cellular composition, as indicated by the term “multiforme". Recent reports have described the isolation and identification of cancer neural stem cells from human adult glioblastoma multiforme, which possess the capacity to establish, sustain, and expand these tumours, even under the challenging settings posed by serial transplantation experiments. Our study focused on the distribution of neura...

  12. Niche-dependent development of functional neuronal networks from embryonic stem cell-derived neural populations

    Directory of Open Access Journals (Sweden)

    Siebler Mario

    2009-08-01

    Full Text Available Abstract Background The present work was performed to investigate the ability of two different embryonic stem (ES cell-derived neural precursor populations to generate functional neuronal networks in vitro. The first ES cell-derived neural precursor population was cultivated as free-floating neural aggregates which are known to form a developmental niche comprising different types of neural cells, including neural precursor cells (NPCs, progenitor cells and even further matured cells. This niche provides by itself a variety of different growth factors and extracellular matrix proteins that influence the proliferation and differentiation of neural precursor and progenitor cells. The second population was cultivated adherently in monolayer cultures to control most stringently the extracellular environment. This population comprises highly homogeneous NPCs which are supposed to represent an attractive way to provide well-defined neuronal progeny. However, the ability of these different ES cell-derived immature neural cell populations to generate functional neuronal networks has not been assessed so far. Results While both precursor populations were shown to differentiate into sufficient quantities of mature NeuN+ neurons that also express GABA or vesicular-glutamate-transporter-2 (vGlut2, only aggregate-derived neuronal populations exhibited a synchronously oscillating network activity 2–4 weeks after initiating the differentiation as detected by the microelectrode array technology. Neurons derived from homogeneous NPCs within monolayer cultures did merely show uncorrelated spiking activity even when differentiated for up to 12 weeks. We demonstrated that these neurons exhibited sparsely ramified neurites and an embryonic vGlut2 distribution suggesting an inhibited terminal neuronal maturation. In comparison, neurons derived from heterogeneous populations within neural aggregates appeared as fully mature with a dense neurite network and punctuated

  13. Canonical Wnt activity regulates trunk neural crest delamination linking BMP/noggin signaling with G1/S transition.

    Science.gov (United States)

    Burstyn-Cohen, Tal; Stanleigh, Jonathan; Sela-Donenfeld, Dalit; Kalcheim, Chaya

    2004-11-01

    Delamination of premigratory neural crest cells depends on a balance between BMP/noggin and on successful G1/S transition. Here, we report that BMP regulates G1/S transition and consequent crest delamination through canonical Wnt signaling. Noggin overexpression inhibits G1/S transition and blocking G1/S abrogates BMP-induced delamination; moreover, transcription of Wnt1 is stimulated by BMP and by the developing somites, which concomitantly inhibit noggin production. Interfering with beta-catenin and LEF/TCF inhibits G1/S transition, neural crest delamination and transcription of various BMP-dependent genes, which include Cad6B, Pax3 and Msx1, but not that of Slug, Sox9 or FoxD3. Hence, we propose that developing somites inhibit noggin transcription in the dorsal tube, resulting in activation of BMP and consequent Wnt1 production. Canonical Wnt signaling in turn stimulates G1/S transition and generation of neural crest cell motility independently of its proposed role in earlier neural crest specification. PMID:15456730

  14. Pharmacogenetics of neural injury recovery.

    Science.gov (United States)

    Pearson-Fuhrhop, Kristin M; Cramer, Steven C

    2013-10-01

    Relatively few pharmacological agents are part of routine care for neural injury, although several are used or under consideration in acute stroke, chronic stroke, traumatic brain injury and secondary stroke prevention. Tissue plasminogen activator is approved for the treatment of acute ischemic stroke, and genetic variants may impact the efficacy and safety of this drug. In the chronic phase of stroke, several drugs such as L-dopa, fluoxetine and donepezil are under investigation for enhancing rehabilitation therapy, with varying levels of evidence. One potential reason for the mixed efficacy displayed by these drugs may be the influence of genetic factors that were not considered in prior studies. An understanding of the genetics impacting the efficacy of dopaminergic, serotonergic and cholinergic drugs may allow clinicians to target these potential therapies to those patients most likely to benefit. In the setting of stroke prevention, which is directly linked to neural injury recovery, the most highly studied pharmacogenomic interactions pertain to clopidogrel and warfarin. Incorporating pharmacogenomics into neural injury recovery has the potential to maximize the benefit of several current and potential pharmacological therapies and to refine the choice of pharmacological agent that may be used to enhance benefits from rehabilitation therapy.

  15. Neural prostheses and brain plasticity

    Science.gov (United States)

    Fallon, James B.; Irvine, Dexter R. F.; Shepherd, Robert K.

    2009-12-01

    The success of modern neural prostheses is dependent on a complex interplay between the devices' hardware and software and the dynamic environment in which the devices operate: the patient's body or 'wetware'. Over 120 000 severe/profoundly deaf individuals presently receive information enabling auditory awareness and speech perception from cochlear implants. The cochlear implant therefore provides a useful case study for a review of the complex interactions between hardware, software and wetware, and of the important role of the dynamic nature of wetware. In the case of neural prostheses, the most critical component of that wetware is the central nervous system. This paper will examine the evidence of changes in the central auditory system that contribute to changes in performance with a cochlear implant, and discuss how these changes relate to electrophysiological and functional imaging studies in humans. The relationship between the human data and evidence from animals of the remarkable capacity for plastic change of the central auditory system, even into adulthood, will then be examined. Finally, we will discuss the role of brain plasticity in neural prostheses in general.

  16. Neural Representations of Physics Concepts.

    Science.gov (United States)

    Mason, Robert A; Just, Marcel Adam

    2016-06-01

    We used functional MRI (fMRI) to assess neural representations of physics concepts (momentum, energy, etc.) in juniors, seniors, and graduate students majoring in physics or engineering. Our goal was to identify the underlying neural dimensions of these representations. Using factor analysis to reduce the number of dimensions of activation, we obtained four physics-related factors that were mapped to sets of voxels. The four factors were interpretable as causal motion visualization, periodicity, algebraic form, and energy flow. The individual concepts were identifiable from their fMRI signatures with a mean rank accuracy of .75 using a machine-learning (multivoxel) classifier. Furthermore, there was commonality in participants' neural representation of physics; a classifier trained on data from all but one participant identified the concepts in the left-out participant (mean accuracy = .71 across all nine participant samples). The findings indicate that abstract scientific concepts acquired in an educational setting evoke activation patterns that are identifiable and common, indicating that science education builds abstract knowledge using inherent, repurposed brain systems.

  17. Neural signatures of intransitive preferences

    Directory of Open Access Journals (Sweden)

    Tobias Kalenscher

    2010-06-01

    Full Text Available It is often assumed that decisions are made by rank-ordering and thus comparing the (subjective value of available choice options. Rank-ordering requires that alternatives are mentally represented at least on an ordinal scale. Because one alternative cannot be at the same time better or worse than another alternative, choices should satisfy transitivity (if alternative A is preferred over B, and B is preferred over C, A should be preferred over C. Yet, individuals often demonstrate striking violations of transitivity (preferring C over A. We used functional magnetic resonance imaging to study the neural correlates of intransitive choices between gambles varying in magnitude and probability of financial gains. Behavioral intransitivities were common. They occurred because participants did not evaluate the gambles independently, but in comparison with the alternative gamble presented. Neural value signals in prefrontal and parietal cortex were not ordinal-scaled and transitive, but reflected fluctuations in the gambles’ local, pairing-dependent preference-ranks. Detailed behavioural analysis of gamble preferences showed that, depending on the difference in the offered gambles’ attributes, participants gave variable priority to magnitude or probability and thus shifted between preferring richer or safer gambles. The variable, context-dependent priority given to magnitude and probability was tracked by insula (magnitude and posterior cingulate (probability. Their activation-balance may reflect the individual decision rules leading to intransitivities. Thus, the phenomenon of intransitivity is reflected in the organisation of the neural systems involved in risky decision-making.

  18. [Neural basis of maternal behavior].

    Science.gov (United States)

    Noriuchi, Madoka; Kikuchi, Yoshiaki

    2013-01-01

    Maternal love, which may be the core of maternal behavior, is essential for the mother-infant attachment relationship and is important for the infant's development and mental health. However, little has been known about these neural mechanisms in human mothers. We examined patterns of maternal brain activation in response to infant cues using video clips. We performed functional magnetic resonance imaging (fMRI) measurements while 13 mothers viewed video clips, with no sound, of their own infant and other infants of approximately 16 months of age who demonstrated two different attachment behaviors (smiling at the infant's mother and crying for her). We found that a limited number of the mother's brain areas were specifically involved in recognition of the mother's own infant, namely orbitofrontal cortex (OFC). and periaqueductal gray, anterior insula, and dorsal and ventrolateral parts of putamen. Additionally, we found the strong and specific mother's brain response for the mother's own infant's distress. The differential neural activation pattern was found in the dorsal region of OFC, caudate nucleus, right inferior frontal gyrus, dorsomedial prefrontal cortex (PFC), anterior cingulate, posterior cingulate, posterior superior temporal sulcus, and dorsolateral PFC. Our results showed the highly elaborate neural mechanism mediating maternal love and diverse and complex maternal behaviors for vigilant protectiveness.

  19. Photon spectrometry utilizing neural networks

    International Nuclear Information System (INIS)

    Having in mind the time spent on the uneventful work of characterization of the radiation beams used in a ionizing radiation metrology laboratory, the Metrology Service of the Centro Regional de Ciencias Nucleares do Nordeste - CRCN-NE verified the applicability of artificial intelligence (artificial neural networks) to perform the spectrometry in photon fields. For this, was developed a multilayer neural network, as an application for the classification of patterns in energy, associated with a thermoluminescent dosimetric system (TLD-700 and TLD-600). A set of dosimeters was initially exposed to various well known medium energies, between 40 keV and 1.2 MeV, coinciding with the beams determined by ISO 4037 standard, for the dose of 10 mSv in the quantity Hp(10), on a chest phantom (ISO slab phantom) with the purpose of generating a set of training data for the neural network. Subsequently, a new set of dosimeters irradiated in unknown energies was presented to the network with the purpose to test the method. The methodology used in this work was suitable for application in the classification of energy beams, having obtained 100% of the classification performed. (authors)

  20. Neural Representations of Physics Concepts.

    Science.gov (United States)

    Mason, Robert A; Just, Marcel Adam

    2016-06-01

    We used functional MRI (fMRI) to assess neural representations of physics concepts (momentum, energy, etc.) in juniors, seniors, and graduate students majoring in physics or engineering. Our goal was to identify the underlying neural dimensions of these representations. Using factor analysis to reduce the number of dimensions of activation, we obtained four physics-related factors that were mapped to sets of voxels. The four factors were interpretable as causal motion visualization, periodicity, algebraic form, and energy flow. The individual concepts were identifiable from their fMRI signatures with a mean rank accuracy of .75 using a machine-learning (multivoxel) classifier. Furthermore, there was commonality in participants' neural representation of physics; a classifier trained on data from all but one participant identified the concepts in the left-out participant (mean accuracy = .71 across all nine participant samples). The findings indicate that abstract scientific concepts acquired in an educational setting evoke activation patterns that are identifiable and common, indicating that science education builds abstract knowledge using inherent, repurposed brain systems. PMID:27113732

  1. Neural Correlates of Predictive Saccades.

    Science.gov (United States)

    Lee, Stephen M; Peltsch, Alicia; Kilmade, Maureen; Brien, Donald C; Coe, Brian C; Johnsrude, Ingrid S; Munoz, Douglas P

    2016-08-01

    Every day we generate motor responses that are timed with external cues. This phenomenon of sensorimotor synchronization has been simplified and studied extensively using finger tapping sequences that are executed in synchrony with auditory stimuli. The predictive saccade paradigm closely resembles the finger tapping task. In this paradigm, participants follow a visual target that "steps" between two fixed locations on a visual screen at predictable ISIs. Eventually, the time from target appearance to saccade initiation (i.e., saccadic RT) becomes predictive with values nearing 0 msec. Unlike the finger tapping literature, neural control of predictive behavior described within the eye movement literature has not been well established and is inconsistent, especially between neuroimaging and patient lesion studies. To resolve these discrepancies, we used fMRI to investigate the neural correlates of predictive saccades by contrasting brain areas involved with behavior generated from the predictive saccade task with behavior generated from a reactive saccade task (saccades are generated toward targets that are unpredictably timed). We observed striking differences in neural recruitment between reactive and predictive conditions: Reactive saccades recruited oculomotor structures, as predicted, whereas predictive saccades recruited brain structures that support timing in motor responses, such as the crus I of the cerebellum, and structures commonly associated with the default mode network. Therefore, our results were more consistent with those found in the finger tapping literature. PMID:27054397

  2. miR-21 promotes the differentiation of hair follicle-derived neural crest stem cells into Schwann cells

    Institute of Scientific and Technical Information of China (English)

    Yuxin Ni; Kaizhi Zhang; Xuejuan Liu; Tingting Yang; Baixiang Wang; Li Fu; Lan A; Yanmin Zhou

    2014-01-01

    Hair follicle-derived neural crest stem cells can be induced to differentiate into Schwann cells in vivo and in vitro. However, the underlying regulatory mechanism during cell differentiation remains poorly understood. This study isolated neural crest stem cells from human hair folli-cles and induced them to differentiate into Schwann cells. Quantitative RT-PCR showed that microRNA (miR)-21 expression was gradually increased during the differentiation of neural crest stem cells into Schwann cells. After transfection with the miR-21 agonist (agomir-21), the differentiation capacity of neural crest stem cells was enhanced. By contrast, after transfection with the miR-21 antagonist (antagomir-21), the differentiation capacity was attenuated. Further study results showed that SOX-2 was an effective target of miR-21. Without compromising SOX2 mRNA expression, miR-21 can down-regulate SOX protein expression by binding to the 3′-UTR of miR-21 mRNA. Knocking out the SOX2 gene from the neural crest stem cells significantly reversed the antagomir-21 inhibition of neural crest stem cells differentiating into Schwann cells. The results suggest that miR-21 expression was increased during the differentiation of neural crest stem cells into Schwann cells and miR-21 promoted the differentiation through down-regu-lating SOX protein expression by binding to the 3′-UTR of SOX2 mRNA.

  3. All-trans retinoic acid promotes neural lineage entry by pluripotent embryonic stem cells via multiple pathways

    Directory of Open Access Journals (Sweden)

    Fang Bo

    2009-07-01

    Full Text Available Abstract Background All-trans retinoic acid (RA is one of the most important morphogens with pleiotropic actions. Its embryonic distribution correlates with neural differentiation in the developing central nervous system. To explore the precise effects of RA on neural differentiation of mouse embryonic stem cells (ESCs, we detected expression of RA nuclear receptors and RA-metabolizing enzymes in mouse ESCs and investigated the roles of RA in adherent monolayer culture. Results Upon addition of RA, cell differentiation was directed rapidly and exclusively into the neural lineage. Conversely, pharmacological interference with RA signaling suppressed this neural differentiation. Inhibition of fibroblast growth factor (FGF signaling did not suppress significantly neural differentiation in RA-treated cultures. Pharmacological interference with extracellular signal-regulated kinase (ERK pathway or activation of Wnt pathway effectively blocked the RA-promoted neural specification. ERK phosphorylation was enhanced in RA-treated cultures at the early stage of differentiation. Conclusion RA can promote neural lineage entry by ESCs in adherent monolayer culture systems. This effect depends on RA signaling and its crosstalk with the ERK and Wnt pathways.

  4. Distinct gene expression responses of two anticonvulsant drugs in a novel human embryonic stem cell based neural differentiation assay protocol.

    Science.gov (United States)

    Schulpen, Sjors H W; de Jong, Esther; de la Fonteyne, Liset J J; de Klerk, Arja; Piersma, Aldert H

    2015-04-01

    Hazard assessment of chemicals and pharmaceuticals is increasingly gaining from knowledge about molecular mechanisms of toxic action acquired in dedicated in vitro assays. We have developed an efficient human embryonic stem cell neural differentiation test (hESTn) that allows the study of the molecular interaction of compounds with the neural differentiation process. Within the 11-day differentiation protocol of the assay, embryonic stem cells lost their pluripotency, evidenced by the reduced expression of stem cell markers Pou5F1 and Nanog. Moreover, stem cells differentiated into neural cells, with morphologically visible neural structures together with increased expression of neural differentiation-related genes such as βIII-tubulin, Map2, Neurogin1, Mapt and Reelin. Valproic acid (VPA) and carbamazepine (CBZ) exposure during hESTn differentiation led to concentration-dependent reduced expression of βIII-tubulin, Neurogin1 and Reelin. In parallel VPA caused an increased gene expression of Map2 and Mapt which is possibly related to the neural protective effect of VPA. These findings illustrate the added value of gene expression analysis for detecting compound specific effects in hESTn. Our findings were in line with and could explain effects observed in animal studies. This study demonstrates the potential of this assay protocol for mechanistic analysis of specific compound-induced inhibition of human neural cell differentiation.

  5. Neural heterogeneities determine response characteristics to second-, but not first-order stimulus features.

    Science.gov (United States)

    Metzen, Michael G; Chacron, Maurice J

    2015-02-18

    Neural heterogeneities are seen ubiquitously, but how they determine neural response properties remains unclear. Here we show that heterogeneities can either strongly, or not at all, influence neural responses to a given stimulus feature. Specifically, we recorded from peripheral electroreceptor neurons, which display strong heterogeneities in their resting discharge activity, in response to naturalistic stimuli consisting of a fast time-varying waveform (i.e., first-order) whose amplitude (i.e., second-order or envelope) varied slowly in the weakly electric fish Apteronotus leptorhynchus. Although electroreceptors displayed relatively homogeneous responses to first-order stimulus features, further analysis revealed two subpopulations with similar sensitivities that were excited or inhibited by increases in the envelope, respectively, for stimuli whose frequency content spanned the natural range. We further found that a linear-nonlinear cascade model incorporating the known linear response characteristics to first-order features and a static nonlinearity accurately reproduced experimentally observed responses to both first- and second-order features for all stimuli tested. Importantly, this model correctly predicted that the response magnitude is independent of either the stimulus waveform's or the envelope's frequency content. Further analysis of our model led to the surprising prediction that the mean discharge activity can be used to determine whether a given neuron is excited or inhibited by increases in the envelope. This prediction was validated by our experimental data. Thus, our results provide key insight as to how neural heterogeneities can determine response characteristics to some, but not other, behaviorally relevant stimulus features.

  6. From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

    Science.gov (United States)

    Ross, Muriel D.

    1991-01-01

    The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

  7. Coherence resonance in bursting neural networks

    Science.gov (United States)

    Kim, June Hoan; Lee, Ho Jun; Min, Cheol Hong; Lee, Kyoung J.

    2015-10-01

    Synchronized neural bursts are one of the most noticeable dynamic features of neural networks, being essential for various phenomena in neuroscience, yet their complex dynamics are not well understood. With extrinsic electrical and optical manipulations on cultured neural networks, we demonstrate that the regularity (or randomness) of burst sequences is in many cases determined by a (few) low-dimensional attractor(s) working under strong neural noise. Moreover, there is an optimal level of noise strength at which the regularity of the interburst interval sequence becomes maximal—a phenomenon of coherence resonance. The experimental observations are successfully reproduced through computer simulations on a well-established neural network model, suggesting that the same phenomena may occur in many in vivo as well as in vitro neural networks.

  8. Coherence resonance in bursting neural networks.

    Science.gov (United States)

    Kim, June Hoan; Lee, Ho Jun; Min, Cheol Hong; Lee, Kyoung J

    2015-10-01

    Synchronized neural bursts are one of the most noticeable dynamic features of neural networks, being essential for various phenomena in neuroscience, yet their complex dynamics are not well understood. With extrinsic electrical and optical manipulations on cultured neural networks, we demonstrate that the regularity (or randomness) of burst sequences is in many cases determined by a (few) low-dimensional attractor(s) working under strong neural noise. Moreover, there is an optimal level of noise strength at which the regularity of the interburst interval sequence becomes maximal-a phenomenon of coherence resonance. The experimental observations are successfully reproduced through computer simulations on a well-established neural network model, suggesting that the same phenomena may occur in many in vivo as well as in vitro neural networks.

  9. Criticality of spreading dynamics in hierarchical cluster networks without inhibition

    CERN Document Server

    Kaiser, Marcus; Hilgetag, Claus C

    2008-01-01

    An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable network activations within a limited critical range. In this range, the activity of neural populations in the network persists between the extremes of quickly dying out, or activating the whole network. The nerve fiber network of the mammalian cerebral cortex possesses a modular organization extending across several levels of organization. Using a basic spreading model without inhibition, we investigated how functional activations of nodes propagate through such a hierarchically clustered network. The simulations demonstrated that persistent and scalable activation could be produced in clustered networks, but not in random networks of the same size. Moreover, the parameter range yielding critical activations was substantially larger in hierarchical cluster networks than in small-world networks of the same size. These findings indicate that a hiera...

  10. Multiple roles of Activin/Nodal, bone morphogenetic protein, fibroblast growth factor and Wnt/β-catenin signalling in the anterior neural patterning of adherent human embryonic stem cell cultures

    Science.gov (United States)

    Lupo, Giuseppe; Novorol, Claire; Smith, Joseph R.; Vallier, Ludovic; Miranda, Elena; Alexander, Morgan; Biagioni, Stefano; Pedersen, Roger A.; Harris, William A.

    2013-01-01

    Several studies have successfully produced a variety of neural cell types from human embryonic stem cells (hESCs), but there has been limited systematic analysis of how different regional identities are established using well-defined differentiation conditions. We have used adherent, chemically defined cultures to analyse the roles of Activin/Nodal, bone morphogenetic protein (BMP), fibroblast growth factor (FGF) and Wnt/β-catenin signalling in neural induction, anteroposterior patterning and eye field specification in hESCs. We show that either BMP inhibition or activation of FGF signalling is required for effective neural induction, but these two pathways have distinct outcomes on rostrocaudal patterning. While BMP inhibition leads to specification of forebrain/midbrain positional identities, FGF-dependent neural induction is associated with strong posteriorization towards hindbrain/spinal cord fates. We also demonstrate that Wnt/β-catenin signalling is activated during neural induction and promotes acquisition of neural fates posterior to forebrain. Therefore, inhibition of this pathway is needed for efficient forebrain specification. Finally, we provide evidence that the levels of Activin/Nodal and BMP signalling have a marked influence on further forebrain patterning and that constitutive inhibition of these pathways represses expression of eye field genes. These results show that the key mechanisms controlling neural patterning in model vertebrate species are preserved in adherent, chemically defined hESC cultures and reveal new insights into the signals regulating eye field specification. PMID:23576785

  11. Secure Key Exchange using Neural Network

    OpenAIRE

    Vineeta Soni

    2014-01-01

    Any cryptographic system is used to exchange confidential information securely over the public channel without any leakage of information to the unauthorized users. Neural networks can be used to generate a common secret key because the processes involve in Cryptographic system requires large computational power and very complex. Moreover Diffi hellman key exchange is suffered from man-in –the middle attack. For overcome this problem neural networks can be used.Two neural netwo...

  12. Fast Algorithms for Convolutional Neural Networks

    OpenAIRE

    Lavin, Andrew; Gray, Scott

    2015-01-01

    Deep convolutional neural networks take GPU days of compute time to train on large data sets. Pedestrian detection for self driving cars requires very low latency. Image recognition for mobile phones is constrained by limited processing resources. The success of convolutional neural networks in these situations is limited by how fast we can compute them. Conventional FFT based convolution is fast for large filters, but state of the art convolutional neural networks use small, 3x3 filters. We ...

  13. Introduction to Concepts in Artificial Neural Networks

    Science.gov (United States)

    Niebur, Dagmar

    1995-01-01

    This introduction to artificial neural networks summarizes some basic concepts of computational neuroscience and the resulting models of artificial neurons. The terminology of biological and artificial neurons, biological and machine learning and neural processing is introduced. The concepts of supervised and unsupervised learning are explained with examples from the power system area. Finally, a taxonomy of different types of neurons and different classes of artificial neural networks is presented.

  14. Process Neural Networks Theory and Applications

    CERN Document Server

    He, Xingui

    2010-01-01

    "Process Neural Networks - Theory and Applications" proposes the concept and model of a process neural network for the first time, showing how it expands the mapping relationship between the input and output of traditional neural networks, and enhancing the expression capability for practical problems, with broad applicability to solving problems relating to process in practice. Some theoretical problems such as continuity, functional approximation capability, and computing capability, are strictly proved. The application methods, network construction principles, and optimization alg

  15. Adaptive optimization and control using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  16. Spatiotemporal dynamics of continuum neural fields

    Science.gov (United States)

    Bressloff, Paul C.

    2012-01-01

    We survey recent analytical approaches to studying the spatiotemporal dynamics of continuum neural fields. Neural fields model the large-scale dynamics of spatially structured biological neural networks in terms of nonlinear integrodifferential equations whose associated integral kernels represent the spatial distribution of neuronal synaptic connections. They provide an important example of spatially extended excitable systems with nonlocal interactions and exhibit a wide range of spatially coherent dynamics including traveling waves oscillations and Turing-like patterns.

  17. Information Theory for Analyzing Neural Networks

    OpenAIRE

    Sørngård, Bård

    2014-01-01

    The goal of this thesis was to investigate how information theory could be used to analyze artificial neural networks. For this purpose, two problems, a classification problem and a controller problem were considered. The classification problem was solved with a feedforward neural network trained with backpropagation, the controller problem was solved with a continuous-time recurrent neural network optimized with evolution.Results from the classification problem shows that mutual information ...

  18. Sequential optimizing investing strategy with neural networks

    OpenAIRE

    Ryo Adachi; Akimichi Takemura

    2010-01-01

    In this paper we propose an investing strategy based on neural network models combined with ideas from game-theoretic probability of Shafer and Vovk. Our proposed strategy uses parameter values of a neural network with the best performance until the previous round (trading day) for deciding the investment in the current round. We compare performance of our proposed strategy with various strategies including a strategy based on supervised neural network models and show that our procedure is co...

  19. Neural crest contributions to the lamprey head

    Science.gov (United States)

    McCauley, David W.; Bronner-Fraser, Marianne

    2003-01-01

    The neural crest is a vertebrate-specific cell population that contributes to the facial skeleton and other derivatives. We have performed focal DiI injection into the cranial neural tube of the developing lamprey in order to follow the migratory pathways of discrete groups of cells from origin to destination and to compare neural crest migratory pathways in a basal vertebrate to those of gnathostomes. The results show that the general pathways of cranial neural crest migration are conserved throughout the vertebrates, with cells migrating in streams analogous to the mandibular and hyoid streams. Caudal branchial neural crest cells migrate ventrally as a sheet of cells from the hindbrain and super-pharyngeal region of the neural tube and form a cylinder surrounding a core of mesoderm in each pharyngeal arch, similar to that seen in zebrafish and axolotl. In addition to these similarities, we also uncovered important differences. Migration into the presumptive caudal branchial arches of the lamprey involves both rostral and caudal movements of neural crest cells that have not been described in gnathostomes, suggesting that barriers that constrain rostrocaudal movement of cranial neural crest cells may have arisen after the agnathan/gnathostome split. Accordingly, neural crest cells from a single axial level contributed to multiple arches and there was extensive mixing between populations. There was no apparent filling of neural crest derivatives in a ventral-to-dorsal order, as has been observed in higher vertebrates, nor did we find evidence of a neural crest contribution to cranial sensory ganglia. These results suggest that migratory constraints and additional neural crest derivatives arose later in gnathostome evolution.

  20. Altered neural connectivity in excitatory and inhibitory cortical circuits in autism

    OpenAIRE

    Basilis Zikopoulos

    2013-01-01

    Converging evidence from diverse studies suggests that atypical brain connectivity in autism affects in distinct ways short- and long-range cortical pathways, disrupting neural communication and the balance of excitation and inhibition. This hypothesis is based mostly on functional non-invasive studies that show atypical synchronization and connectivity patterns between cortical areas in children and adults with autism. Indirect methods to study the course and integrity of major brain pathway...

  1. Temperament and Parenting Styles in Early Childhood Differentially Influence Neural Response to Peer Evaluation in Adolescence

    OpenAIRE

    Guyer, Amanda E.; Johanna M. Jarcho; Pérez-Edgar, Koraly; Degnan, Kathryn A.; Pine, Daniel S.; Fox, Nathan A.; Nelson, Eric E.

    2015-01-01

    Behavioral inhibition (BI) is a temperament characterized by social reticence and withdrawal from unfamiliar or novel contexts and conveys risk for social anxiety disorder. Developmental outcomes associated with this temperament can be influenced by children’s caregiving context. The convergence of a child’s temperamental disposition and rearing environment is ultimately expressed at both the behavioral and neural levels in emotional and cognitive response patterns to social challenges. The p...

  2. Chronic multi-electrode neural recording in free-roaming monkeys

    OpenAIRE

    Eliades, Steven J.; Wang, Xiaoqin

    2008-01-01

    Many behaviors of interest to neurophysiologists are difficult to study under laboratory conditions because such behaviors are often inhibited when an animal is restrained and socially isolated. Even under the best conditions, such behaviors may be sparse enough as to require long duration neural recordings or simultaneous recording of multiple neurons to gather a sufficient amount of data for analysis. We have developed a preparation for chronic, multi-electrode recordings in the auditory co...

  3. Dynamic characteristics of multisensory facilitation and inhibition.

    Science.gov (United States)

    Wang, W Y; Hu, L; Valentini, E; Xie, X B; Cui, H Y; Hu, Y

    2012-10-01

    Multimodal integration, which mainly refers to multisensory facilitation and multisensory inhibition, is the process of merging multisensory information in the human brain. However, the neural mechanisms underlying the dynamic characteristics of multimodal integration are not fully understood. The objective of this study is to investigate the basic mechanisms of multimodal integration by assessing the intermodal influences of vision, audition, and somatosensory sensations (the influence of multisensory background events to the target event). We used a timed target detection task, and measured both behavioral and electroencephalographic responses to visual target events (green solid circle), auditory target events (2 kHz pure tone) and somatosensory target events (1.5 ± 0.1 mA square wave pulse) from 20 normal participants. There were significant differences in both behavior performance and ERP components when comparing the unimodal target stimuli with multimodal (bimodal and trimodal) target stimuli for all target groups. Significant correlation among reaction time and P3 latency was observed across all target conditions. The perceptual processing of auditory target events (A) was inhibited by the background events, while the perceptual processing of somatosensory target events (S) was facilitated by the background events. In contrast, the perceptual processing of visual target events (V) remained impervious to multisensory background events. PMID:24082962

  4. NeuroMEMS: Neural Probe Microtechnologies

    Directory of Open Access Journals (Sweden)

    Sam Musallam

    2008-10-01

    Full Text Available Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer’s, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultralong multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

  5. Artificial neural networks in nuclear medicine

    International Nuclear Information System (INIS)

    An analysis of the accessible literature on the diagnostic applicability of artificial neural networks in coronary artery disease and pulmonary embolism appears to be comparative to the diagnosis of experienced doctors dealing with nuclear medicine. Differences in the employed models of artificial neural networks indicate a constant search for the most optimal parameters, which could guarantee the ultimate accuracy in neural network activity. The diagnostic potential within systems containing artificial neural networks proves this calculation tool to be an independent or/and an additional device for supporting a doctor's diagnosis of artery disease and pulmonary embolism. (author)

  6. Fuzzy neural network theory and application

    CERN Document Server

    Liu, Puyin

    2004-01-01

    This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to he

  7. Initial conditions in the neural field model

    CERN Document Server

    Valdes-Hernandez, Pedro A

    2016-01-01

    In spite of the large amount of existing neural models in the literature, there is a lack of a systematic review of the possible effect of choosing different initial conditions on the dynamic evolution of neural systems. In this short review we intend to give insights into this topic by discussing some published examples. First, we briefly introduce the different ingredients of a neural dynamical model. Secondly, we introduce some concepts used to describe the dynamic behavior of neural models, namely phase space and its portraits, time series, spectra, multistability and bifurcations. We end with an analysis of the irreversibility of processes and its implications on the functioning of normal and pathological brains.

  8. Practical neural network recipies in C++

    CERN Document Server

    Masters

    2014-01-01

    This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to produce a working program implementing that network. The book provides guidance along the entire problem-solving path, including designing the training set, preprocessing variables, training and validating the network, and evaluating its performance. Though the book is not intended as a general course in neural networks, no background in neural works is assum

  9. Application of neural networks in coastal engineering

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.

    neural networks, J of computer aided civil and infrastructural engineering, (UK), 13, 113-120. Deo, MC and Naidu, CS (1999) Real time wave forecasting using neural networks, Ocean Engineering, 26, 191-203. Deo, MC, Gondane, DS and Kumar, VS (2002...) An application of artificial neural networks in tide-forecasting. Ocean Engineering, 29, pp 1003-1022 MandaI,S; Subba Rao and Chackraborty, l\\TV (2002) Hindcasting cyclonic waves using neural network. International Conference SHOT 2002, lIT Kharagpur, 18...

  10. Intrinsic Plasticity for Natural Competition in Koniocortex-Like Neural Networks.

    Science.gov (United States)

    Peláez, Francisco Javier Ropero; Aguiar-Furucho, Mariana Antonia; Andina, Diego

    2016-08-01

    In this paper, we use the neural property known as intrinsic plasticity to develop neural network models that resemble the koniocortex, the fourth layer of sensory cortices. These models evolved from a very basic two-layered neural network to a complex associative koniocortex network. In the initial network, intrinsic and synaptic plasticity govern the shifting of the activation function, and the modification of synaptic weights, respectively. In this first version, competition is forced, so that the most activated neuron is arbitrarily set to one and the others to zero, while in the second, competition occurs naturally due to inhibition between second layer neurons. In the third version of the network, whose architecture is similar to the koniocortex, competition also occurs naturally owing to the interplay between inhibitory interneurons and synaptic and intrinsic plasticity. A more complex associative neural network was developed based on this basic koniocortex-like neural network, capable of dealing with incomplete patterns and ideally suited to operating similarly to a learning vector quantization network. We also discuss the biological plausibility of the networks and their role in a more complex thalamocortical model. PMID:27255800

  11. High glucose suppresses embryonic stem cell differentiation into neural lineage cells.

    Science.gov (United States)

    Yang, Penghua; Shen, Wei-bin; Reece, E Albert; Chen, Xi; Yang, Peixin

    2016-04-01

    Abnormal neurogenesis occurs during embryonic development in human diabetic pregnancies and in animal models of diabetic embryopathy. Our previous studies in a mouse model of diabetic embryopathy have implicated that high glucose of maternal diabetes delays neurogenesis in the developing neuroepithelium leading to neural tube defects. However, the underlying process in high glucose-impaired neurogenesis is uncharacterized. Neurogenesis from embryonic stem (ES) cells provides a valuable model for understanding the abnormal neural lineage development under high glucose conditions. ES cells are commonly generated and maintained in high glucose (approximately 25 mM glucose). Here, the mouse ES cell line, E14, was gradually adapted to and maintained in low glucose (5 mM), and became a glucose responsive E14 (GR-E14) line. High glucose induced the endoplasmic reticulum stress marker, CHOP, in GR-E14 cells. Under low glucose conditions, the GR-E14 cells retained their pluripotency and capability to differentiate into neural lineage cells. GR-E14 cell differentiation into neural stem cells (Sox1 and nestin positive cells) was inhibited by high glucose. Neuron (Tuj1 positive cells) and glia (GFAP positive cells) differentiation from GR-E14 cells was also suppressed by high glucose. In addition, high glucose delayed GR-E14 differentiation into neural crest cells by decreasing neural crest markers, paired box 3 (Pax3) and paired box 7 (Pax7). Thus, high glucose impairs ES cell differentiation into neural lineage cells. The low glucose adapted and high glucose responsive GR-E14 cell line is a useful in vitro model for assessing the adverse effect of high glucose on the development of the central nervous system.

  12. Fate of the mammalian cranial neural crest during tooth and mandibular morphogenesis.

    Science.gov (United States)

    Chai, Y; Jiang, X; Ito, Y; Bringas, P; Han, J; Rowitch, D H; Soriano, P; McMahon, A P; Sucov, H M

    2000-04-01

    Neural crest cells are multipotential stem cells that contribute extensively to vertebrate development and give rise to various cell and tissue types. Determination of the fate of mammalian neural crest has been inhibited by the lack of appropriate markers. Here, we make use of a two-component genetic system for indelibly marking the progeny of the cranial neural crest during tooth and mandible development. In the first mouse line, Cre recombinase is expressed under the control of the Wnt1 promoter as a transgene. Significantly, Wnt1 transgene expression is limited to the migrating neural crest cells that are derived from the dorsal CNS. The second mouse line, the ROSA26 conditional reporter (R26R), serves as a substrate for the Cre-mediated recombination. Using this two-component genetic system, we have systematically followed the migration and differentiation of the cranial neural crest (CNC) cells from E9.5 to 6 weeks after birth. Our results demonstrate, for the first time, that CNC cells contribute to the formation of condensed dental mesenchyme, dental papilla, odontoblasts, dentine matrix, pulp, cementum, periodontal ligaments, chondrocytes in Meckel's cartilage, mandible, the articulating disc of temporomandibular joint and branchial arch nerve ganglia. More importantly, there is a dynamic distribution of CNC- and non-CNC-derived cells during tooth and mandibular morphogenesis. These results are a first step towards a comprehensive understanding of neural crest cell migration and differentiation during mammalian craniofacial development. Furthermore, this transgenic model also provides a new tool for cell lineage analysis and genetic manipulation of neural-crest-derived components in normal and abnormal embryogenesis. PMID:10725243

  13. Quorum sensing inhibition

    DEFF Research Database (Denmark)

    Persson, T.; Givskov, Michael Christian; Nielsen, J.

    2005-01-01

    /receptor transcriptional regulator in some clinically relevant Gram-negative bacteria. The present review contains all reported compound types that are currently known to inhibit the QS transcriptional regulator in Gram-negative bacteria. These compounds are sub-divided into two main groups, one comprising structural...

  14. Enzyme inhibition by iminosugars

    DEFF Research Database (Denmark)

    López, Óscar; Qing, Feng-Ling; Pedersen, Christian Marcus;

    2013-01-01

    Imino- and azasugar glycosidase inhibitors display pH dependant inhibition reflecting that both the inhibitor and the enzyme active site have groups that change protonation state with pH. With the enzyme having two acidic groups and the inhibitor one basic group, enzyme-inhibitor complexes...

  15. EDITORIAL: Special issue on applied neurodynamics: from neural dynamics to neural engineering Special issue on applied neurodynamics: from neural dynamics to neural engineering

    Science.gov (United States)

    Chiel, Hillel J.; Thomas, Peter J.

    2011-12-01

    system, the authors use the structure of the phase response curves with and without the synapse present to explain the mechanism underlying this variance-suppressing inhibitory synapse. Their results can be explained at a conceptual level using phase plane analysis to show that inhibitory synaptic input and the intrinsic properties of the neuron act to cancel out the changes in phase induced by perturbations. These results may have intriguing implications for the role of inhibition in stabilizing vertebrate nervous systems, as well as artificial neural networks. The second paper in this special issue uses dynamical analysis to shed light on the dysfunctional activation of peripheral neurons, for instance in paroxysmal attacks of pain or spasticity. Coggan et al (2011) provide insight into changes in axonal excitability through dynamical analysis of conductance-based models. These authors make elegant use of fast/slow analysis to explain the initiation and termination of ectopic spiking that may underlie paroxysmal neurological symptoms. They work both with a multi-compartment conductance-based model and a lower dimensional, single-compartment model based on the Morris-Lecar model mentioned above. They find that axonal susceptibility to after-discharge depends on dynamical properties such as bistability, in which a dynamical system has more than one stable attractor for a given set of parameters (in this case, a 'quiet' stable fixed point and an 'active' stable limit cycle). Moreover, they find that the system's behavior depends on geometrical features of the dynamics, such as the distance between stable and unstable (saddle) fixed points in the phase plane. Based on their models, they make observations that may have clinical relevance: an axon susceptible to paroxysmal discharges due to disease or mutation may be able to operate normally unless an appropriate 'trigger' is encountered, accounting for the intermittency in the phenomenon that is often observed. Moreover

  16. Differentiation of embryonic versus adult rat neural stem cells into dopaminergic neurons in vitro

    Institute of Scientific and Technical Information of China (English)

    Chunlong Ke; Baili Chen; Shaolei Guo; Chao Yang

    2008-01-01

    BACKGROUND: It has been reported that the conversion of neural stem cells into dopaminergic neurons in vitro can be increased through specific cytokine combinations. Such neural stem cell-derived dopaminergic neurons could be used for the treatment of Parkinson's disease. However, little is known about the differences in dopaminergic differentiation between neural stem cells derived from adult and embryonic rats.OBJECTIVE: To study the ability of rat adult and embryonic-derived neural stem cells to differentiate into dopaminergic neurons in vitro.DESIGN: Randomized grouping design.SETTING: Department of Neurosurgery in the First Affiliated Hospital of Sun Yat-sen University.MATERIALS: This experiment was performed at the Surgical Laboratory in the First Affiliated Hospital of Sun Yat-scn University (Guangzhou, Guangdong, China) from June to December 2007. Eight, adult, male,Sprague Dawley rats and eight, pregnant, Sprague Dawley rats (embryonic day 14 or 15) were provided by the Experimental Animal Center of Sun Yat-sen University.METHODS: Neural stem cells derived from adult and embryonic rats were respectively cultivated in serum-free culture medium containing epidermal growth factor and basic fibroblast growth factor. After passaging, neural stem cells were differentiated in medium containing interleukin-1 ct, interleukin-11, human leukemia inhibition factor, and glial cell line-derived neurotrophic factor. Six days later, cells were analyzed by immunocytochemistry and flow cytometry.MAIN OUTCOME MEASURES: Alterations in cellular morphology after differentiation of neural stem cells derived from adult and embryonic rats; and percentage of tyrosine hydroxylase-positive neurons in the differentiated cells.RESULTS: Neural stem cells derived from adult and embryonic rats were cultivated in differentiation medium. Six days later, differentiated cells were immunoreactive for tyrosine hydroxylasc. The percentage of tyrosine hydroxylase positive neurons was (5.6 ± 2

  17. Neural mechanisms underlying breathing complexity.

    Directory of Open Access Journals (Sweden)

    Agathe Hess

    Full Text Available Breathing is maintained and controlled by a network of automatic neurons in the brainstem that generate respiratory rhythm and receive regulatory inputs. Breathing complexity therefore arises from respiratory central pattern generators modulated by peripheral and supra-spinal inputs. Very little is known on the brainstem neural substrates underlying breathing complexity in humans. We used both experimental and theoretical approaches to decipher these mechanisms in healthy humans and patients with chronic obstructive pulmonary disease (COPD. COPD is the most frequent chronic lung disease in the general population mainly due to tobacco smoke. In patients, airflow obstruction associated with hyperinflation and respiratory muscles weakness are key factors contributing to load-capacity imbalance and hence increased respiratory drive. Unexpectedly, we found that the patients breathed with a higher level of complexity during inspiration and expiration than controls. Using functional magnetic resonance imaging (fMRI, we scanned the brain of the participants to analyze the activity of two small regions involved in respiratory rhythmogenesis, the rostral ventro-lateral (VL medulla (pre-Bötzinger complex and the caudal VL pons (parafacial group. fMRI revealed in controls higher activity of the VL medulla suggesting active inspiration, while in patients higher activity of the VL pons suggesting active expiration. COPD patients reactivate the parafacial to sustain ventilation. These findings may be involved in the onset of respiratory failure when the neural network becomes overwhelmed by respiratory overload We show that central neural activity correlates with airflow complexity in healthy subjects and COPD patients, at rest and during inspiratory loading. We finally used a theoretical approach of respiratory rhythmogenesis that reproduces the kernel activity of neurons involved in the automatic breathing. The model reveals how a chaotic activity in

  18. The LILARTI neural network system

    Energy Technology Data Exchange (ETDEWEB)

    Allen, J.D. Jr.; Schell, F.M.; Dodd, C.V.

    1992-10-01

    The material of this Technical Memorandum is intended to provide the reader with conceptual and technical background information on the LILARTI neural network system of detail sufficient to confer an understanding of the LILARTI method as it is presently allied and to facilitate application of the method to problems beyond the scope of this document. Of particular importance in this regard are the descriptive sections and the Appendices which include operating instructions, partial listings of program output and data files, and network construction information.

  19. Physical, neural, and mental timing.

    Science.gov (United States)

    van de Grind, Wim

    2002-06-01

    The conclusions drawn by Benjamin Libet from his work with colleagues on the timing of somatosensorial conscious experiences has met with a lot of praise and criticism. In this issue we find three examples of the latter. Here I attempt to place the divide between the two opponent camps in a broader perspective by analyzing the question of the relation between physical timing, neural timing, and experiential (mental) timing. The nervous system does a sophisticated job of recombining and recoding messages from the sensorial surfaces and if these processes are slighted in a theory, it might become necessary to postulate weird operations, including subjective back-referral. Neuroscientifically inspired theories are of necessity still based on guesses, extrapolations, and philosophically dubious manners of speech. They often assume some neural correlate of consciousness (NCC) as a part of the nervous system that transforms neural activity in reportable experiences. The majority of neuroscientists appear to assume that the NCC can compare and bind activity patterns only if they arrive simultaneously at the NCC. This leads to a search for synchrony or to theories in terms of the compensation of differences in neural delays (latencies). This is the main dimension of the Libet discussion. Examples from vision research, such as "temporal-binding-by-synchrony" and the "flash-lag" effect, are then used to illustrate these reasoning patterns in more detail. Alternatively one could assume symbolic representations of time and space (symbolic "tags") that are not coded in their own dimension (not time in time and space in space). Unless such tags are multiplexed with the quality message (tickle, color, or motion), one gets a binding problem for tags. One of the hidden aspects of the discussion between Libet and opponents appears to be the following. Is the NCC smarter than the rest of the nervous system, so that it can solve the problems of local sign (e.g., "where is the event

  20. Neural correlates of viewing paintings

    DEFF Research Database (Denmark)

    Vartanian, Oshin; Skov, Martin

    2014-01-01

    Many studies involving functional magnetic resonance imaging (fMRI) have exposed participants to paintings under varying task demands. To isolate neural systems that are activated reliably across fMRI studies in response to viewing paintings regardless of variation in task demands, a quantitative...... gyrus) and scene (parahippocampal gyrus) perception, and the anterior insula-a key structure in experience of emotion. In addition, we also observed activation in the posterior cingulate cortex bilaterally-part of the brain's default network. These results suggest that viewing paintings engages not only...

  1. Neural correlates of behavior therapy for Tourette's disorder.

    Science.gov (United States)

    Deckersbach, Thilo; Chou, Tina; Britton, Jennifer C; Carlson, Lindsay E; Reese, Hannah E; Siev, Jedidiah; Scahill, Lawrence; Piacentini, John C; Woods, Douglas W; Walkup, John T; Peterson, Alan L; Dougherty, Darin D; Wilhelm, Sabine

    2014-12-30

    Tourette's disorder, also called Tourette syndrome (TS), is characterized by motor and vocal tics that can cause significant impairment in daily functioning. Tics are believed to be due to failed inhibition of both associative and motor cortico-striato-thalamo-cortical pathways. Comprehensive Behavioral Intervention for Tics (CBIT), which is an extension of Habit Reversal Therapy (HRT), teaches patients to become more aware of sensations that reliably precede tics (premonitory urges) and to initiate competing movements that inhibit the occurrence of tics. In this study, we used functional magnetic resonance imaging (fMRI) to investigate the neural changes associated with CBIT treatment in subjects with TS. Eight subjects with TS were matched with eight healthy controls in gender, education, age, and handedness. Subjects completed the Visuospatial Priming (VSP) task, a measure of response inhibition, during fMRI scanning before and after CBIT treatment (or waiting period for controls). For TS subjects, we found a significant decrease in striatal (putamen) activation from pre- to post-treatment. Change in VSP task-related activation from pre- to post-treatment in Brodmann's area 47 (the inferior frontal gyrus) was negatively correlated with changes in tic severity. CBIT may promote normalization of aberrant cortico-striato-thalamo-cortical associative and motor pathways in individuals with TS. PMID:25444535

  2. Neurons controlling Aplysia feeding inhibit themselves by continuous NO production.

    Directory of Open Access Journals (Sweden)

    Nimrod Miller

    Full Text Available BACKGROUND: Neural activity can be affected by nitric oxide (NO produced by spiking neurons. Can neural activity also be affected by NO produced in neurons in the absence of spiking? METHODOLOGY/PRINCIPAL FINDINGS: Applying an NO scavenger to quiescent Aplysia buccal ganglia initiated fictive feeding, indicating that NO production at rest inhibits feeding. The inhibition is in part via effects on neurons B31/B32, neurons initiating food consumption. Applying NO scavengers or nitric oxide synthase (NOS blockers to B31/B32 neurons cultured in isolation caused inactive neurons to depolarize and fire, indicating that B31/B32 produce NO tonically without action potentials, and tonic NO production contributes to the B31/B32 resting potentials. Guanylyl cyclase blockers also caused depolarization and firing, indicating that the cGMP second messenger cascade, presumably activated by the tonic presence of NO, contributes to the B31/B32 resting potential. Blocking NO while voltage-clamping revealed an inward leak current, indicating that NO prevents this current from depolarizing the neuron. Blocking nitrergic transmission had no effect on a number of other cultured, isolated neurons. However, treatment with NO blockers did excite cerebral ganglion neuron C-PR, a command-like neuron initiating food-finding behavior, both in situ, and when the neuron was cultured in isolation, indicating that this neuron also inhibits itself by producing NO at rest. CONCLUSION/SIGNIFICANCE: Self-inhibitory, tonic NO production is a novel mechanism for the modulation of neural activity. Localization of this mechanism to critical neurons in different ganglia controlling different aspects of a behavior provides a mechanism by which a humeral signal affecting background NO production, such as the NO precursor L-arginine, could control multiple aspects of the behavior.

  3. Impact of preterm birth on inhibition abilities in neutral and emotional contexts in school age children: neuropsychological and brain imaging aspects

    OpenAIRE

    Reveillon, Morgane

    2014-01-01

    Being born preterm is associated with an increased risk of adverse neurodevelopmental functioning, including long-term difficulties in executive functions. Among executive functions, difficulties in major inhibition processes such as response inhibition and interference control have been reported at both brain and behavior levels in preterm samples. However, no consensus exists regarding inhibition difficulties at late school age and information is lacking regarding their underlying neural co...

  4. Brain Plasticity and Disease: A Matter of Inhibition

    Directory of Open Access Journals (Sweden)

    Laura Baroncelli

    2011-01-01

    Full Text Available One major goal in Neuroscience is the development of strategies promoting neural plasticity in the adult central nervous system, when functional recovery from brain disease and injury is limited. New evidence has underscored a pivotal role for cortical inhibitory circuitries in regulating plasticity both during development and in adulthood. This paper summarizes recent findings showing that the inhibition-excitation balance controls adult brain plasticity and is at the core of the pathogenesis of neurodevelopmental disorders like autism, Down syndrome, and Rett syndrome.

  5. Statin therapy inhibits remyelination in the central nervous system

    DEFF Research Database (Denmark)

    Miron, Veronique E; Zehntner, Simone P; Kuhlmann, Tanja;

    2009-01-01

    Remyelination of lesions in the central nervous system contributes to neural repair following clinical relapses in multiple sclerosis. Remyelination is initiated by recruitment and differentiation of oligodendrocyte progenitor cells (OPCs) into myelinating oligodendrocytes. Simvastatin, a blood...... that OPCs were maintained in an immature state (Olig2(strong)/Nkx2.2(weak)). NogoA+ oligodendrocyte numbers were decreased during all simvastatin treatment regimens. Our findings suggest that simvastatin inhibits central nervous system remyelination by blocking progenitor differentiation, indicating...... the need to monitor effects of systemic immunotherapies that can access the central nervous system on brain tissue-repair processes....

  6. Menthol binding and inhibition of α7-nicotinic acetylcholine receptors.

    Directory of Open Access Journals (Sweden)

    Abrar Ashoor

    Full Text Available Menthol is a common compound in pharmaceutical and commercial products and a popular additive to cigarettes. The molecular targets of menthol remain poorly defined. In this study we show an effect of menthol on the α7 subunit of the nicotinic acetylcholine (nACh receptor function. Using a two-electrode voltage-clamp technique, menthol was found to reversibly inhibit α7-nACh receptors heterologously expressed in Xenopus oocytes. Inhibition by menthol was not dependent on the membrane potential and did not involve endogenous Ca(2+-dependent Cl(- channels, since menthol inhibition remained unchanged by intracellular injection of the Ca(2+ chelator BAPTA and perfusion with Ca(2+-free bathing solution containing Ba(2+. Furthermore, increasing ACh concentrations did not reverse menthol inhibition and the specific binding of [(125I] α-bungarotoxin was not attenuated by menthol. Studies of α7- nACh receptors endogenously expressed in neural cells demonstrate that menthol attenuates α7 mediated Ca(2+ transients in the cell body and neurite. In conclusion, our results suggest that menthol inhibits α7-nACh receptors in a noncompetitive manner.

  7. Inhibition of Voltage-Gated Calcium Channels by RGK Proteins.

    Science.gov (United States)

    Buraei, Zafir; Yang, Jian

    2015-01-01

    Due to their essential biological roles, voltage-gated calcium channels (VGCCs) are regulated by a myriad of molecules and mechanisms. Fifteen years ago, RGK proteins were discovered to bind the VGCC β subunit (Cavβ) and potently inhibit high-voltage activated Ca(2+) channels. RGKs (Rad, Rem, Rem2 and Gem/Kir) are a family of monomeric small GTPases belonging to the superfamily of Ras GTPases. They exert dual inhibitory effects on VGCCs, decreasing surface expression and suppressing surface channels through immobilization of the voltage sensor or reduction of channel open probability. While Cavβ is required for all forms of RGK inhibition, not all inhibition is mediated by the RGK-Cavβ interaction. Some RGK proteins also interact directly with the pore-forming α1 subunit of some types of VGCCs (Cavα1). Importantly, RGK proteins tonically inhibit VGCCs in native cells, regulating cardiac and neural functions. This minireview summarizes the mechanisms, molecular determinants, and physiological impact of RGK inhibition of VGCCs. PMID:25966691

  8. Radiation Behavior of Analog Neural Network Chip

    Science.gov (United States)

    Langenbacher, H.; Zee, F.; Daud, T.; Thakoor, A.

    1996-01-01

    A neural network experiment conducted for the Space Technology Research Vehicle (STRV-1) 1-b launched in June 1994. Identical sets of analog feed-forward neural network chips was used to study and compare the effects of space and ground radiation on the chips. Three failure mechanisms are noted.

  9. Heterogeneous scaffold designs for selective neural regeneration

    NARCIS (Netherlands)

    Wieringa, P.A.

    2014-01-01

    Over the past 5 decades, there has been a drive to apply technology to enhance neural regeneration in order to improve patient recovery after disease or injury. This has evolved into the field of Neural Engineering, with the aim to understand, control and exploit the development and function of neur

  10. Adaptive Neurons For Artificial Neural Networks

    Science.gov (United States)

    Tawel, Raoul

    1990-01-01

    Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.

  11. NEURAL METHODS FOR THE FINANCIAL PREDICTION

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2016-06-01

    Full Text Available Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.

  12. Self-organization of neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Clark, J.W.; Winston, J.V.; Rafelski, J.

    1984-05-14

    The plastic development of a neural-network model operating autonomously in discrete time is described by the temporal modification of interneuronal coupling strengths according to momentary neural activity. A simple algorithm (brainwashing) is found which, applied to nets with initially quasirandom connectivity, leads to model networks with properties conducive to the simulation of memory and learning phenomena. 18 references, 2 figures.

  13. Self-organization of neural networks

    Science.gov (United States)

    Clark, John W.; Winston, Jeffrey V.; Rafelski, Johann

    1984-05-01

    The plastic development of a neural-network model operating autonomously in discrete time is described by the temporal modification of interneuronal coupling strengths according to momentary neural activity. A simple algorithm (“brainwashing”) is found which, applied to nets with initially quasirandom connectivity, leads to model networks with properties conductive to the simulation of memory and learning phenomena.

  14. A high-speed analog neural processor

    NARCIS (Netherlands)

    Masa, Peter; Hoen, Klaas; Wallinga, Hans

    1994-01-01

    Targeted at high-energy physics research applications, our special-purpose analog neural processor can classify up to 70 dimensional vectors within 50 nanoseconds. The decision-making process of the implemented feedforward neural network enables this type of computation to tolerate weight discretiza

  15. Neural Control of the Immune System

    Science.gov (United States)

    Sundman, Eva; Olofsson, Peder S.

    2014-01-01

    Neural reflexes support homeostasis by modulating the function of organ systems. Recent advances in neuroscience and immunology have revealed that neural reflexes also regulate the immune system. Activation of the vagus nerve modulates leukocyte cytokine production and alleviates experimental shock and autoimmune disease, and recent data have…

  16. The Elements Of Adaptive Neural Expert Systems

    Science.gov (United States)

    Healy, Michael J.

    1989-03-01

    The generalization properties of a class of neural architectures can be modelled mathematically. The model is a parallel predicate calculus based on pattern recognition and self-organization of long-term memory in a neural network. It may provide the basis for adaptive expert systems capable of inductive learning and rapid processing in a highly complex and changing environment.

  17. Neural networks and MIMD-multiprocessors

    Science.gov (United States)

    Vanhala, Jukka; Kaski, Kimmo

    1990-01-01

    Two artificial neural network models are compared. They are the Hopfield Neural Network Model and the Sparse Distributed Memory model. Distributed algorithms for both of them are designed and implemented. The run time characteristics of the algorithms are analyzed theoretically and tested in practice. The storage capacities of the networks are compared. Implementations are done using a distributed multiprocessor system.

  18. Neural-Network Computer Transforms Coordinates

    Science.gov (United States)

    Josin, Gary M.

    1990-01-01

    Numerical simulation demonstrated ability of conceptual neural-network computer to generalize what it has "learned" from few examples. Ability to generalize achieved with even simple neural network (relatively few neurons) and after exposure of network to only few "training" examples. Ability to obtain fairly accurate mappings after only few training examples used to provide solutions to otherwise intractable mapping problems.

  19. Neural Networks for Non-linear Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1994-01-01

    This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process.......This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process....

  20. Control of Mitral/Tufted Cell Output by Selective Inhibition among Olfactory Bulb Glomeruli.

    Science.gov (United States)

    Economo, Michael N; Hansen, Kyle R; Wachowiak, Matt

    2016-07-20

    Inhibition is fundamental to information processing by neural circuits. In the olfactory bulb (OB), glomeruli are the functional units for odor information coding, but inhibition among glomeruli is poorly characterized. We used two-photon calcium imaging in anesthetized and awake mice to visualize both odorant-evoked excitation and suppression in OB output neurons (mitral and tufted, MT cells). MT cell response polarity mapped uniformly to discrete OB glomeruli, allowing us to analyze how inhibition shapes OB output relative to the glomerular map. Odorants elicited unique patterns of suppression in only a subset of glomeruli in which such suppression could be detected, and excited and suppressed glomeruli were spatially intermingled. Binary mixture experiments revealed that interglomerular inhibition could suppress excitatory mitral cell responses to odorants. These results reveal that inhibitory OB circuits nonlinearly transform odor representations and support a model of selective and nonrandom inhibition among glomerular ensembles. PMID:27346531

  1. Neural network modeling of emotion

    Science.gov (United States)

    Levine, Daniel S.

    2007-03-01

    This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.

  2. Imaging Posture Veils Neural Signals

    Science.gov (United States)

    Thibault, Robert T.; Raz, Amir

    2016-01-01

    Whereas modern brain imaging often demands holding body positions incongruent with everyday life, posture governs both neural activity and cognitive performance. Humans commonly perform while upright; yet, many neuroimaging methodologies require participants to remain motionless and adhere to non-ecological comportments within a confined space. This inconsistency between ecological postures and imaging constraints undermines the transferability and generalizability of many a neuroimaging assay. Here we highlight the influence of posture on brain function and behavior. Specifically, we challenge the tacit assumption that brain processes and cognitive performance are comparable across a spectrum of positions. We provide an integrative synthesis regarding the increasingly prominent influence of imaging postures on autonomic function, mental capacity, sensory thresholds, and neural activity. Arguing that neuroimagers and cognitive scientists could benefit from considering the influence posture wields on both general functioning and brain activity, we examine existing imaging technologies and the potential of portable and versatile imaging devices (e.g., functional near infrared spectroscopy). Finally, we discuss ways that accounting for posture may help unveil the complex brain processes of everyday cognition.

  3. Neural Networks for Emotion Classification

    CERN Document Server

    Sun, Yafei

    2011-01-01

    It is argued that for the computer to be able to interact with humans, it needs to have the communication skills of humans. One of these skills is the ability to understand the emotional state of the person. This thesis describes a neural network-based approach for emotion classification. We learn a classifier that can recognize six basic emotions with an average accuracy of 77% over the Cohn-Kanade database. The novelty of this work is that instead of empirically selecting the parameters of the neural network, i.e. the learning rate, activation function parameter, momentum number, the number of nodes in one layer, etc. we developed a strategy that can automatically select comparatively better combination of these parameters. We also introduce another way to perform back propagation. Instead of using the partial differential of the error function, we use optimal algorithm; namely Powell's direction set to minimize the error function. We were also interested in construction an authentic emotion databases. This...

  4. Artificial neural networks in neurosurgery.

    Science.gov (United States)

    Azimi, Parisa; Mohammadi, Hasan Reza; Benzel, Edward C; Shahzadi, Sohrab; Azhari, Shirzad; Montazeri, Ali

    2015-03-01

    Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review of the relevant published articles that focused on the application of ANNs as a tool for assisting clinical decision-making in neurosurgery. A literature review of all full publications in English biomedical journals (1993-2013) was undertaken. The strategy included a combination of key words 'artificial neural networks', 'prognostic', 'brain', 'tumor tracking', 'head', 'tumor', 'spine', 'classification' and 'back pain' in the title and abstract of the manuscripts using the PubMed search engine. The major findings are summarized, with a focus on the application of ANNs for diagnostic and prognostic purposes. Finally, the future of ANNs in neurosurgery is explored. A total of 1093 citations were identified and screened. In all, 57 citations were found to be relevant. Of these, 50 articles were eligible for inclusion in this review. The synthesis of the data showed several applications of ANN in neurosurgery, including: (1) diagnosis and assessment of disease progression in low back pain, brain tumours and primary epilepsy; (2) enhancing clinically relevant information extraction from radiographic images, intracranial pressure processing, low back pain and real-time tumour tracking; (3) outcome prediction in epilepsy, brain metastases, lumbar spinal stenosis, lumbar disc herniation, childhood hydrocephalus, trauma mortality, and the occurrence of symptomatic cerebral vasospasm in patients with aneurysmal subarachnoid haemorrhage; (4) the use in the biomechanical assessments of spinal disease. ANNs can be effectively employed for diagnosis, prognosis and outcome prediction in neurosurgery.

  5. [Neural basis of procedural memory].

    Science.gov (United States)

    Mochizuki-Kawai, Hiroko

    2008-07-01

    Procedural memory is acquired by trial and error. Our daily life is supported by a number of procedural memories such as those for riding bicycle, typing, reading words, etc. Procedural memory is divided into 3 types; motor, perceptual, and cognitive. Here, the author reviews the cognitive and neural basis of procedural memory according to these 3 types. It is reported that the basal ganglia or cerebellum dysfunction causes deficits in procedural memory. Compared with age-matched healthy participants, patients with Parkinson disease (PD), Huntington disease (HD) or spinocerebellar degeneration (SCD) show deterioration in improvements in motor-type procedural memory tasks. Previous neuroimaging studies have reported that motor-type procedural memory may be supported by multiple brain regions, including the frontal and parietal regions as well as the basal ganglia (cerebellum); this was found with a serial reaction time task (SRT task). Although 2 other types of procedural memory are also maintained by multiple brain regions, the related cerebral areas depend on the type of memory. For example, it was suggested that acquisition of the perceptual type of procedural memory (e.g., ability to read mirror images of words) might be maintained by the bilateral fusiform region, while the acquisition of cognitive procedural memory might be supported by the frontal, parietal, or cerebellar regions as well as the basal ganglia. In the future, we need to cleary understand the neural "network" related to the procedural memory. PMID:18646622

  6. Learning in Artificial Neural Systems

    Science.gov (United States)

    Matheus, Christopher J.; Hohensee, William E.

    1987-01-01

    This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

  7. Miniaturized neural interfaces and implants

    Science.gov (United States)

    Stieglitz, Thomas; Boretius, Tim; Ordonez, Juan; Hassler, Christina; Henle, Christian; Meier, Wolfgang; Plachta, Dennis T. T.; Schuettler, Martin

    2012-03-01

    Neural prostheses are technical systems that interface nerves to treat the symptoms of neurological diseases and to restore sensory of motor functions of the body. Success stories have been written with the cochlear implant to restore hearing, with spinal cord stimulators to treat chronic pain as well as urge incontinence, and with deep brain stimulators in patients suffering from Parkinson's disease. Highly complex neural implants for novel medical applications can be miniaturized either by means of precision mechanics technologies using known and established materials for electrodes, cables, and hermetic packages or by applying microsystems technologies. Examples for both approaches will be introduced and discussed. Electrode arrays for recording of electrocorticograms during presurgical epilepsy diagnosis have been manufactured using approved materials and a marking laser to achieve an integration density that is adequate in the context of brain machine interfaces, e.g. on the motor cortex. Microtechnologies have to be used for further miniaturization to develop polymer-based flexible and light weighted electrode arrays to interface the peripheral and central nervous system. Polyimide as substrate and insulation material will be discussed as well as several application examples for nerve interfaces like cuffs, filament like electrodes and large arrays for subdural implantation.

  8. A new perspective on behavioral inconsistency and neural noise in aging: Compensatory speeding of neural communication

    Directory of Open Access Journals (Sweden)

    S. Lee Hong

    2012-09-01

    Full Text Available This paper seeks to present a new perspective on the aging brain. Here, we make connections between two key phenomena of brain aging: 1 increased neural noise or random background activity; and 2 slowing of brain activity. Our perspective proposes the possibility that the slowing of neural processing due to decreasing nerve conduction velocities leads to a compensatory speeding of neuron firing rates. These increased firing rates lead to a broader distribution of power in the frequency spectrum of neural oscillations, which we propose, can just as easily be interpreted as neural noise. Compensatory speeding of neural activity, as we present, is constrained by the: A availability of metabolic energy sources; and B competition for frequency bandwidth needed for neural communication. We propose that these constraints lead to the eventual inability to compensate for age-related declines in neural function that are manifested clinically as deficits in cognition, affect, and motor behavior.

  9. Plastics for corrosion inhibition

    CERN Document Server

    Goldade, Victor A; Makarevich, Anna V; Kestelman, Vladimir N

    2005-01-01

    The development of polymer composites containing inhibitors of metal corrosion is an important endeavour in modern materials science and technology. Corrosion inhibitors can be located in a polymer matrix in the solid, liquid or gaseous phase. This book details the thermodynamic principles for selecting these components, their compatibility and their effectiveness. The various mechanisms of metal protection – barrier, inhibiting and electromechanical – are considered, as are the conflicting requirements placed on the structure of the combined material. Two main classes of inhibited materials (structural and films/coatings) are described in detail. Examples are given of structural plastics used in friction units subjected to mechano-chemical wear and of polymer films/coatings for protecting metal objects against corrosion.

  10. Neural networks with discontinuous/impact activations

    CERN Document Server

    Akhmet, Marat

    2014-01-01

    This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided. This book also: Explores questions related to the biological underpinning for models of neural networks\\ Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities Provides all necessary mathematical basics for application to the theory of neural networks Neural Networks with Discontinuous/Impact Activations is an ideal book for researchers and professionals in the field of engineering mathematics that have an interest in app...

  11. Video Traffic Prediction Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Miloš Oravec

    2008-10-01

    Full Text Available In this paper, we consider video stream prediction for application in services likevideo-on-demand, videoconferencing, video broadcasting, etc. The aim is to predict thevideo stream for an efficient bandwidth allocation of the video signal. Efficient predictionof traffic generated by multimedia sources is an important part of traffic and congestioncontrol procedures at the network edges. As a tool for the prediction, we use neuralnetworks – multilayer perceptron (MLP, radial basis function networks (RBF networksand backpropagation through time (BPTT neural networks. At first, we briefly introducetheoretical background of neural networks, the prediction methods and the differencebetween them. We propose also video time-series processing using moving averages.Simulation results for each type of neural network together with final comparisons arepresented. For comparison purposes, also conventional (non-neural prediction isincluded. The purpose of our work is to construct suitable neural networks for variable bitrate video prediction and evaluate them. We use video traces from [1].

  12. Auto-programmable impulse neural circuits

    Science.gov (United States)

    Watula, D.; Meador, J.

    1990-01-01

    Impulse neural networks use pulse trains to communicate neuron activation levels. Impulse neural circuits emulate natural neurons at a more detailed level than that typically employed by contemporary neural network implementation methods. An impulse neural circuit which realizes short term memory dynamics is presented. The operation of that circuit is then characterized in terms of pulse frequency modulated signals. Both fixed and programmable synapse circuits for realizing long term memory are also described. The implementation of a simple and useful unsupervised learning law is then presented. The implementation of a differential Hebbian learning rule for a specific mean-frequency signal interpretation is shown to have a straightforward implementation using digital combinational logic with a variation of a previously developed programmable synapse circuit. This circuit is expected to be exploited for simple and straightforward implementation of future auto-adaptive neural circuits.

  13. Reading and writing the neural code.

    Science.gov (United States)

    Stanley, Garrett B

    2013-03-01

    It has been more than 20 years since Bialek and colleagues published a landmark paper asking a seemingly innocuous question: what can we extract about the outside world from the spiking activity of sensory neurons? Can we read the neural code? Although this seemingly simple question has helped us shed light on the neural code, we still do not understand the anatomical and neurophysiological constraints that enable these codes to propagate across synapses and form the basis for computations that we need to interact with our environment. The sensitivity of neuronal activity to the timing of synaptic inputs naturally suggests that synchrony determines the form of the neural code, and, in turn, regulation of synchrony is a critical element in 'writing' the neural code through the artificial control of microcircuits to activate downstream structures. In this way, reading and writing the neural code are inextricably linked.

  14. 22nd Italian Workshop on Neural Nets

    CERN Document Server

    Bassis, Simone; Esposito, Anna; Morabito, Francesco

    2013-01-01

    This volume collects a selection of contributions which has been presented at the 22nd Italian Workshop on Neural Networks, the yearly meeting of the Italian Society for Neural Networks (SIREN). The conference was held in Italy, Vietri sul Mare (Salerno), during May 17-19, 2012. The annual meeting of SIREN is sponsored by International Neural Network Society (INNS), European Neural Network Society (ENNS) and IEEE Computational Intelligence Society (CIS). The book – as well as the workshop-  is organized in three main components, two special sessions and a group of regular sessions featuring different aspects and point of views of artificial neural networks and natural intelligence, also including applications of present compelling interest.

  15. International Conference on Artificial Neural Networks (ICANN)

    CERN Document Server

    Mladenov, Valeri; Kasabov, Nikola; Artificial Neural Networks : Methods and Applications in Bio-/Neuroinformatics

    2015-01-01

    The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new al...

  16. Neural network signal understanding for instrumentation

    DEFF Research Database (Denmark)

    Pau, L. F.; Johansen, F. S.

    1990-01-01

    A report is presented on the use of neural signal interpretation theory and techniques for the purpose of classifying the shapes of a set of instrumentation signals, in order to calibrate devices, diagnose anomalies, generate tuning/settings, and interpret the measurement results. Neural signal...... understanding research is surveyed, and the selected implementation and its performance in terms of correct classification rates and robustness to noise are described. Formal results on neural net training time and sensitivity to weights are given. A theory for neural control using functional link nets is given......, and an explanation facility designed to help neural signal understanding is described. The results are compared to those obtained with a knowledge-based signal interpretation system using the same instrument and data...

  17. Neural scaling laws for an uncertain world

    CERN Document Server

    Howard, Marc W

    2016-01-01

    The Weber-Fechner law describes the form of psychological space in many behavioral experiments involving perception of one-dimensional physical quantities. If the physical quantity is expressed using multiple neural receptors, then placing receptive fields evenly along a logarithmic scale naturally leads to the psychological Weber-Fechner law. In the visual system, the spacing and width of extrafoveal receptive fields are consistent with logarithmic scaling. Other sets of neural "receptors" appear to show the same qualitative properties, suggesting that this form of neural scaling reflects a solution to a very general problem. This paper argues that these neural scaling laws enable the brain to represent information about the world efficiently without making any assumptions about the statistics of the world. This analysis suggests that the organization of neural scales to represent one-dimensional quantities, including more abstract quantities such as numerosity, time, and allocentric space, should have a uni...

  18. Prenatal Tobacco Exposure and Response Inhibition in School-Aged Children: An Event-Related Potential Study

    OpenAIRE

    Boucher, Olivier; Jacobson, Joseph L; Burden, Matthew J.; Dewailly, Éric; Jacobson, Sandra W.; Muckle, Gina

    2014-01-01

    Prenatal cigarette smoke exposure (PCSE) has been linked to problems in behavioral inhibition and attention deficit hyperactivity disorder in children in several epidemiological studies. We used event-related potentials (ERPs) to examine the effects of PCSE on neural correlates of inhibitory control of behavior. In a prospective longitudinal study on child development in the Canadian Arctic, we assessed 186 Inuit children (mean age = 11.3 years) on a visual Go/No-go response inhibition paradi...

  19. A new formulation for feedforward neural networks.

    Science.gov (United States)

    Razavi, Saman; Tolson, Bryan A

    2011-10-01

    Feedforward neural network is one of the most commonly used function approximation techniques and has been applied to a wide variety of problems arising from various disciplines. However, neural networks are black-box models having multiple challenges/difficulties associated with training and generalization. This paper initially looks into the internal behavior of neural networks and develops a detailed interpretation of the neural network functional geometry. Based on this geometrical interpretation, a new set of variables describing neural networks is proposed as a more effective and geometrically interpretable alternative to the traditional set of network weights and biases. Then, this paper develops a new formulation for neural networks with respect to the newly defined variables; this reformulated neural network (ReNN) is equivalent to the common feedforward neural network but has a less complex error response surface. To demonstrate the learning ability of ReNN, in this paper, two training methods involving a derivative-based (a variation of backpropagation) and a derivative-free optimization algorithms are employed. Moreover, a new measure of regularization on the basis of the developed geometrical interpretation is proposed to evaluate and improve the generalization ability of neural networks. The value of the proposed geometrical interpretation, the ReNN approach, and the new regularization measure are demonstrated across multiple test problems. Results show that ReNN can be trained more effectively and efficiently compared to the common neural networks and the proposed regularization measure is an effective indicator of how a network would perform in terms of generalization.

  20. Neural mediator of the schizotypy-antisocial behavior relationship.

    Science.gov (United States)

    Lam, B Y H; Yang, Y; Raine, A; Lee, T M C

    2015-11-03

    Prior studies have established that schizotypal personality traits (schizotypy) were associated with antisocial behavior (crime), but it is unclear what neural factors mediate this relationship. This study assessed the mediating effect that sub-regional prefrontal gray, specifically the orbitofrontal gray matter volume, has on the schizotypy-antisocial behavior relationship. Five prefrontal sub-regional (superior, middle, inferior, orbitofrontal and rectal gyral) gray matter volumes were assessed using structural magnetic resonance imaging in 90 adults from the community, together with schizotypy and antisocial behavior. Among all five prefrontal sub-regions, the orbitofrontal cortex (OFC) was the major region-of-interest in the present study. Mediation analyses showed that orbitofrontal gray fully mediated the association between schizotypy and antisocial behavior. After having controlled the sex, age, socio-economic statuses, whole brain volumes and substance abuse/dependence of test subjects, the orbitofrontal gray still significantly mediated the effect of schizotypy on antisocial behavior by 53.5%. These findings are the first that document a neural mediator of the schizotypy-antisocial behavior relationship. Findings also suggest that functions subserved by the OFC, including impulse control and inhibition, emotion processing and decision-making, may contribute to the above comorbidity.

  1. Neural Correlates of the Cortisol Awakening Response in Humans.

    Science.gov (United States)

    Boehringer, Andreas; Tost, Heike; Haddad, Leila; Lederbogen, Florian; Wüst, Stefan; Schwarz, Emanuel; Meyer-Lindenberg, Andreas

    2015-08-01

    The cortisol rise after awakening (cortisol awakening response, CAR) is a core biomarker of hypothalamic-pituitary-adrenal (HPA) axis regulation related to psychosocial stress and stress-related psychiatric disorders. However, the neural regulation of the CAR has not been examined in humans. Here, we studied neural regulation related to the CAR in a sample of 25 healthy human participants using an established psychosocial stress paradigm together with multimodal functional and structural (voxel-based morphometry) magnetic resonance imaging. Across subjects, a smaller CAR was associated with reduced grey matter volume and increased stress-related brain activity in the perigenual ACC, a region which inhibits HPA axis activity during stress that is implicated in risk mechanisms and pathophysiology of stress-related mental diseases. Moreover, functional connectivity between the perigenual ACC and the hypothalamus, the primary controller of HPA axis activity, was associated with the CAR. Our findings provide support for a role of the perigenual ACC in regulating the CAR in humans and may aid future research on the pathophysiology of stress-related illnesses, such as depression, and environmental risk for illnesses such as schizophrenia. PMID:25781268

  2. Winner-Take-All Neural Network with Massively Optoelectronic Interconnections

    Directory of Open Access Journals (Sweden)

    Wissam H. Ali

    2009-01-01

    Full Text Available The increased interconnection density, bandwidth, nonlocality and fan-out-fan-in offered by optics over conventional electronic technologies make it a very attractive medium for a variety of application particularity in the field of communication system implementation for all types of computing engines is achieved. This is especially true for neural networks in which the demand for communication resources is extremely high. In this study, the implementation of a neural network that exploits an optical interconnect to perform a real task is described. A pnpn semiconductor device has been connected in parallel with a common load resistance for optical switching. When illuminated, only this device with maximum input will turn on. The voltages across the other devices drop and inhibit their switching ability. With suitable biasing, the winning device can be recall at any time. The result shows, a much faster response (<10ns can be obtained from thyristors made of III-V compound semiconductors, because their carrier lifetime is considerably shorter than in silicon. With III-V photothyristor, it is possible to combine light emission (even lasing and photothyristor action in the same unit.

  3. Binocular rivalry waves in a directionally selective neural field model

    Science.gov (United States)

    Carroll, Samuel R.; Bressloff, Paul C.

    2014-10-01

    We extend a neural field model of binocular rivalry waves in the visual cortex to incorporate direction selectivity of moving stimuli. For each eye, we consider a one-dimensional network of neurons that respond maximally to a fixed orientation and speed of a grating stimulus. Recurrent connections within each one-dimensional network are taken to be excitatory and asymmetric, where the asymmetry captures the direction and speed of the moving stimuli. Connections between the two networks are taken to be inhibitory (cross-inhibition). As per previous studies, we incorporate slow adaption as a symmetry breaking mechanism that allows waves to propagate. We derive an analytical expression for traveling wave solutions of the neural field equations, as well as an implicit equation for the wave speed as a function of neurophysiological parameters, and analyze their stability. Most importantly, we show that propagation of traveling waves is faster in the direction of stimulus motion than against it, which is in agreement with previous experimental and computational studies.

  4. Alien hand syndrome: neural correlates of movements without conscious will.

    Directory of Open Access Journals (Sweden)

    Michael Schaefer

    Full Text Available BACKGROUND: The alien hand syndrome is a striking phenomenon characterized by purposeful and autonomous movements that are not voluntarily initiated. This study aimed to examine neural correlates of this rare neurological disorder in a patient with corticobasal degeneration and alien hand syndrome of the left hand. METHODOLOGY/PRINCIPAL FINDINGS: We employed functional magnetic resonance imaging to investigate brain responses associated with unwanted movements in a case study. Results revealed that alien hand movements involved a network of brain activations including the primary motor cortex, premotor cortex, precuneus, and right inferior frontal gyrus. Conscious and voluntary movements of the alien hand elicited a similar network of brain responses but lacked an activation of the inferior frontal gyrus. The results demonstrate that alien and unwanted movements may engage similar brain networks than voluntary movements, but also imply different functional contributions of prefrontal areas. Since the inferior frontal gyrus was uniquely activated during alien movements, the results provide further support for a specific role of this brain region in inhibitory control over involuntary motor responses. CONCLUSIONS/SIGNIFICANCE: We discuss the outcome of this study as providing evidence for a distributed neural network associated with unwanted movements in alien hand syndrome, including brain regions known to be related to movement execution and planning as well as areas that have been linked to inhibition control (inferior frontal gyrus and experience of agency (precuneus.

  5. Neural mediator of the schizotypy-antisocial behavior relationship.

    Science.gov (United States)

    Lam, B Y H; Yang, Y; Raine, A; Lee, T M C

    2015-01-01

    Prior studies have established that schizotypal personality traits (schizotypy) were associated with antisocial behavior (crime), but it is unclear what neural factors mediate this relationship. This study assessed the mediating effect that sub-regional prefrontal gray, specifically the orbitofrontal gray matter volume, has on the schizotypy-antisocial behavior relationship. Five prefrontal sub-regional (superior, middle, inferior, orbitofrontal and rectal gyral) gray matter volumes were assessed using structural magnetic resonance imaging in 90 adults from the community, together with schizotypy and antisocial behavior. Among all five prefrontal sub-regions, the orbitofrontal cortex (OFC) was the major region-of-interest in the present study. Mediation analyses showed that orbitofrontal gray fully mediated the association between schizotypy and antisocial behavior. After having controlled the sex, age, socio-economic statuses, whole brain volumes and substance abuse/dependence of test subjects, the orbitofrontal gray still significantly mediated the effect of schizotypy on antisocial behavior by 53.5%. These findings are the first that document a neural mediator of the schizotypy-antisocial behavior relationship. Findings also suggest that functions subserved by the OFC, including impulse control and inhibition, emotion processing and decision-making, may contribute to the above comorbidity. PMID:26529422

  6. How Tissue Mechanical Properties Affect Enteric Neural Crest Cell Migration

    Science.gov (United States)

    Chevalier, N. R.; Gazguez, E.; Bidault, L.; Guilbert, T.; Vias, C.; Vian, E.; Watanabe, Y.; Muller, L.; Germain, S.; Bondurand, N.; Dufour, S.; Fleury, V.

    2016-02-01

    Neural crest cells (NCCs) are a population of multipotent cells that migrate extensively during vertebrate development. Alterations to neural crest ontogenesis cause several diseases, including cancers and congenital defects, such as Hirschprung disease, which results from incomplete colonization of the colon by enteric NCCs (ENCCs). We investigated the influence of the stiffness and structure of the environment on ENCC migration in vitro and during colonization of the gastrointestinal tract in chicken and mouse embryos. We showed using tensile stretching and atomic force microscopy (AFM) that the mesenchyme of the gut was initially soft but gradually stiffened during the period of ENCC colonization. Second-harmonic generation (SHG) microscopy revealed that this stiffening was associated with a gradual organization and enrichment of collagen fibers in the developing gut. Ex-vivo 2D cell migration assays showed that ENCCs migrated on substrates with very low levels of stiffness. In 3D collagen gels, the speed of the ENCC migratory front decreased with increasing gel stiffness, whereas no correlation was found between porosity and ENCC migration behavior. Metalloprotease inhibition experiments showed that ENCCs actively degraded collagen in order to progress. These results shed light on the role of the mechanical properties of tissues in ENCC migration during development.

  7. EDITORIAL: Special issue on optical neural engineering: advances in optical stimulation technology Special issue on optical neural engineering: advances in optical stimulation technology

    Science.gov (United States)

    Shoham, Shy; Deisseroth, Karl

    2010-08-01

    Neural engineering, itself an 'emerging interdisciplinary research area' [1] has undergone a sea change over the past few years with the emergence of exciting new optical technologies for monitoring, stimulating, inhibiting and, more generally, modulating neural activity. To a large extent, this change is driven by the realization of the promise and complementary strengths that emerging photo-stimulation tools offer to add to the neural engineer's toolbox, which has been almost exclusively based on electrical stimulation technologies. Notably, photo-stimulation is non-contact, can in some cases be genetically targeted to specific cell populations, can achieve high spatial specificity (cellular or even sub-cellular) in two or three dimensions, and opens up the possibility of large-scale spatial-temporal patterned stimulation. It also offers a seamless solution to the problem of cross-talk generated by simultaneous electrical stimulation and recording. As in other biomedical optics phenomena [2], photo-stimulation includes multiple possible modes of interaction between light and the target neurons, including a variety of photo-physical and photo-bio-chemical effects with various intrinsic components or exogenous 'sensitizers' which can be loaded into the tissue or genetically expressed. Early isolated reports of neural excitation with light date back to the late 19th century [3] and to Arvanitaki and Chalazonitis' work five decades ago [4]; however, the mechanism by which these and other direct photo-stimulation, inhibition and modulation events [5-7] took place is yet unclear, as is their short- and long-term safety profile. Photo-chemical photolysis of covalently 'caged' neurotransmitters [8, 9] has been widely used in cellular neuroscience research for three decades, including for exciting or inhibiting neural activity, and for mapping neural circuits. Technological developments now allow neurotransmitters to be uncaged with exquisite spatial specificity (down to

  8. Histone deacetylases control neurogenesis in embryonic brain by inhibition of BMP2/4 signaling.

    Directory of Open Access Journals (Sweden)

    Maya Shakèd

    Full Text Available BACKGROUND: Histone-modifying enzymes are essential for a wide variety of cellular processes dependent upon changes in gene expression. Histone deacetylases (HDACs lead to the compaction of chromatin and subsequent silencing of gene transcription, and they have recently been implicated in a diversity of functions and dysfunctions in the postnatal and adult brain including ocular dominance plasticity, memory consolidation, drug addiction, and depression. Here we investigate the role of HDACs in the generation of neurons and astrocytes in the embryonic brain. PRINCIPAL FINDINGS: As a variety of HDACs are expressed in differentiating neural progenitor cells, we have taken a pharmacological approach to inhibit multiple family members. Inhibition of class I and II HDACs in developing mouse embryos with trichostatin A resulted in a dramatic reduction in neurogenesis in the ganglionic eminences and a modest increase in neurogenesis in the cortex. An identical effect was observed upon pharmacological inhibition of HDACs in in vitro-differentiating neural precursors derived from the same brain regions. A reduction in neurogenesis in ganglionic eminence-derived neural precursors was accompanied by an increase in the production of immature astrocytes. We show that HDACs control neurogenesis by inhibition of the bone morphogenetic protein BMP2/4 signaling pathway in radial glial cells. HDACs function at the transcriptional level by inhibiting and promoting, respectively, the expression of Bmp2 and Smad7, an intracellular inhibitor of BMP signaling. Inhibition of the BMP2/4 signaling pathway restored normal levels of neurogenesis and astrogliogenesis to both ganglionic eminence- and cortex-derived cultures in which HDACs were inhibited. CONCLUSIONS: Our results demonstrate a transcriptionally-based regulation of BMP2/4 signaling by HDACs both in vivo and in vitro that is critical for neurogenesis in the ganglionic eminences and that modulates cortical

  9. Spillover-mediated feedforward-inhibition functionally segregates interneuron activity

    Science.gov (United States)

    Coddington, Luke T.; Rudolph, Stephanie; Lune, Patrick Vande; Overstreet-Wadiche, Linda; Wadiche, Jacques I.

    2013-01-01

    Summary Neurotransmitter spillover represents a form of neural transmission not restricted to morphologically defined synaptic connections. Communication between climbing fibers (CFs) and molecular layer interneurons (MLIs) in the cerebellum is mediated exclusively by glutamate spillover. Here, we show how CF stimulation functionally segregates MLIs based on their location relative to glutamate release. Excitation of MLIs that reside within the domain of spillover diffusion coordinates inhibition of MLIs outside the diffusion limit. CF excitation of MLIs is dependent on extrasynaptic NMDA receptors that enhance the spatial and temporal spread of CF signaling. Activity mediated by functionally segregated MLIs converges onto neighboring Purkinje cells (PCs) to generate a long-lasting biphasic change in inhibition. These data demonstrate how glutamate release from single CFs modulates excitability of neighboring PCs, thus expanding the influence of CFs on cerebellar cortical activity in a manner not predicted by anatomical connectivity. PMID:23707614

  10. The F-box protein Cdc4/Fbxw7 is a novel regulator of neural crest development in Xenopus laevis

    Directory of Open Access Journals (Sweden)

    Hartley Rebecca S

    2010-01-01

    Full Text Available Abstract Background The neural crest is a unique population of cells that arise in the vertebrate ectoderm at the neural plate border after which they migrate extensively throughout the embryo, giving rise to a wide range of derivatives. A number of proteins involved in neural crest development have dynamic expression patterns, and it is becoming clear that ubiquitin-mediated protein degradation is partly responsible for this. Results Here we demonstrate a novel role for the F-box protein Cdc4/Fbxw7 in neural crest development. Two isoforms of Xenopus laevis Cdc4 were identified, and designated xCdc4α and xCdc4β. These are highly conserved with vertebrate Cdc4 orthologs, and the Xenopus proteins are functionally equivalent in terms of their ability to degrade Cyclin E, an established vertebrate Cdc4 target. Blocking xCdc4 function specifically inhibited neural crest development at an early stage, prior to expression of c-Myc, Snail2 and Snail. Conclusions We demonstrate that Cdc4, an ubiquitin E3 ligase subunit previously identified as targeting primarily cell cycle regulators for proteolysis, has additional roles in control of formation of the neural crest. Hence, we identify Cdc4 as a protein with separable but complementary functions in control of cell proliferation and differentiation.

  11. The neural circuit and synaptic dynamics underlying perceptual decision-making

    Science.gov (United States)

    Liu, Feng

    2015-03-01

    Decision-making with several choice options is central to cognition. To elucidate the neural mechanisms of multiple-choice motion discrimination, we built a continuous recurrent network model to represent a local circuit in the lateral intraparietal area (LIP). The network is composed of pyramidal cells and interneurons, which are directionally tuned. All neurons are reciprocally connected, and the synaptic connectivity strength is heterogeneous. Specifically, we assume two types of inhibitory connectivity to pyramidal cells: opposite-feature and similar-feature inhibition. The model accounted for both physiological and behavioral data from monkey experiments. The network is endowed with slow excitatory reverberation, which subserves the buildup and maintenance of persistent neural activity, and predominant feedback inhibition, which underlies the winner-take-all competition and attractor dynamics. The opposite-feature and opposite-feature inhibition have different effects on decision-making, and only their combination allows for a categorical choice among 12 alternatives. Together, our work highlights the importance of structured synaptic inhibition in multiple-choice decision-making processes.

  12. Neural Network Controlled Visual Saccades

    Science.gov (United States)

    Johnson, Jeffrey D.; Grogan, Timothy A.

    1989-03-01

    The paper to be presented will discuss research on a computer vision system controlled by a neural network capable of learning through classical (Pavlovian) conditioning. Through the use of unconditional stimuli (reward and punishment) the system will develop scan patterns of eye saccades necessary to differentiate and recognize members of an input set. By foveating only those portions of the input image that the system has found to be necessary for recognition the drawback of computational explosion as the size of the input image grows is avoided. The model incorporates many features found in animal vision systems, and is governed by understandable and modifiable behavior patterns similar to those reported by Pavlov in his classic study. These behavioral patterns are a result of a neuronal model, used in the network, explicitly designed to reproduce this behavior.

  13. Salience-Affected Neural Networks

    CERN Document Server

    Remmelzwaal, Leendert A; Ellis, George F R

    2010-01-01

    We present a simple neural network model which combines a locally-connected feedforward structure, as is traditionally used to model inter-neuron connectivity, with a layer of undifferentiated connections which model the diffuse projections from the human limbic system to the cortex. This new layer makes it possible to model global effects such as salience, at the same time as the local network processes task-specific or local information. This simple combination network displays interactions between salience and regular processing which correspond to known effects in the developing brain, such as enhanced learning as a result of heightened affect. The cortex biases neuronal responses to affect both learning and memory, through the use of diffuse projections from the limbic system to the cortex. Standard ANNs do not model this non-local flow of information represented by the ascending systems, which are a significant feature of the structure of the brain, and although they do allow associational learning with...

  14. Sunspot prediction using neural networks

    Science.gov (United States)

    Villarreal, James; Baffes, Paul

    1990-01-01

    The earliest systematic observance of sunspot activity is known to have been discovered by the Chinese in 1382 during the Ming Dynasty (1368 to 1644) when spots on the sun were noticed by looking at the sun through thick, forest fire smoke. Not until after the 18th century did sunspot levels become more than a source of wonderment and curiosity. Since 1834 reliable sunspot data has been collected by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Naval Observatory. Recently, considerable effort has been placed upon the study of the effects of sunspots on the ecosystem and the space environment. The efforts of the Artificial Intelligence Section of the Mission Planning and Analysis Division of the Johnson Space Center involving the prediction of sunspot activity using neural network technologies are described.

  15. Subspace learning of neural networks

    CERN Document Server

    Cheng Lv, Jian; Zhou, Jiliu

    2010-01-01

    PrefaceChapter 1. Introduction1.1 Introduction1.1.1 Linear Neural Networks1.1.2 Subspace Learning1.2 Subspace Learning Algorithms1.2.1 PCA Learning Algorithms1.2.2 MCA Learning Algorithms1.2.3 ICA Learning Algorithms1.3 Methods for Convergence Analysis1.3.1 SDT Method1.3.2 DCT Method1.3.3 DDT Method1.4 Block Algorithms1.5 Simulation Data Set and Notation1.6 ConclusionsChapter 2. PCA Learning Algorithms with Constants Learning Rates2.1 Oja's PCA Learning Algorithms2.1.1 The Algorithms2.1.2 Convergence Issue2.2 Invariant Sets2.2.1 Properties of Invariant Sets2.2.2 Conditions for Invariant Sets2.

  16. Primary neural leprosy: systematic review

    Directory of Open Access Journals (Sweden)

    Jose Antonio Garbino

    2013-06-01

    Full Text Available The authors proposed a systematic review on the current concepts of primary neural leprosy by consulting the following online databases: MEDLINE, Lilacs/SciELO, and Embase. Selected studies were classified based on the degree of recommendation and levels of scientific evidence according to the “Oxford Centre for Evidence-based Medicine”. The following aspects were reviewed: cutaneous clinical and laboratorial investigations, i.e. skin clinical exam, smears, and biopsy, and Mitsuda's reaction; neurological investigation (anamnesis, electromyography and nerve biopsy; serological investigation and molecular testing, i.e. serological testing for the detection of the phenolic glycolipid 1 (PGL-I and the polymerase chain reaction (PCR; and treatment (classification criteria for the definition of specific treatment, steroid treatment, and cure criteria.

  17. [The neural mechanisms underlying swallowing].

    Science.gov (United States)

    Inoue, Makoto

    2015-02-01

    Swallowing is regarded as the first step in nutrition; it transports food boluses and liquid from the mouth to the stomach and is a defensive response to prevent aspiration. Swallowing movements are produced by a central pattern generator (CPG) located in the lower brainstem. The swallowing CPG includes two main groups of neurons: one is located within the nucleus tractus solitarii and contains the generator neurons involved in triggering, shaping, and timing the sequential or rhythmic swallowing pattern and the other is located in the ventrolateral medulla and contains switching neurons that distribute the swallowing drive to various pools of related motoneurons. Swallowing movements can be triggered by either central inputs or peripheral inputs from pharyngeal and laryngeal regions, but the precise neural mechanisms of the swallowing CPG remain to be fully elucidated. This review discusses the fundamental knowledge of ingestion behaviors, with a focus on swallowing.

  18. Introduction to artificial neural networks.

    Science.gov (United States)

    Grossi, Enzo; Buscema, Massimo

    2007-12-01

    The coupling of computer science and theoretical bases such as nonlinear dynamics and chaos theory allows the creation of 'intelligent' agents, such as artificial neural networks (ANNs), able to adapt themselves dynamically to problems of high complexity. ANNs are able to reproduce the dynamic interaction of multiple factors simultaneously, allowing the study of complexity; they can also draw conclusions on individual basis and not as average trends. These tools can offer specific advantages with respect to classical statistical techniques. This article is designed to acquaint gastroenterologists with concepts and paradigms related to ANNs. The family of ANNs, when appropriately selected and used, permits the maximization of what can be derived from available data and from complex, dynamic, and multidimensional phenomena, which are often poorly predictable in the traditional 'cause and effect' philosophy. PMID:17998827

  19. Electrode array for neural stimulation

    Energy Technology Data Exchange (ETDEWEB)

    Wessendorf, Kurt O. (Albuquerque, NM); Okandan, Murat (Edgewood, NM); Stein, David J. (Albuquerque, NM); Yang, Pin (Albuquerque, NM); Cesarano, III, Joseph (Albuquerque, NM); Dellinger, Jennifer (Albuquerque, NM)

    2011-08-16

    An electrode array for neural stimulation is disclosed which has particular applications for use in a retinal prosthesis. The electrode array can be formed as a hermetically-sealed two-part ceramic package which includes an electronic circuit such as a demultiplexer circuit encapsulated therein. A relatively large number (up to 1000 or more) of individually-addressable electrodes are provided on a curved surface of a ceramic base portion the electrode array, while a much smaller number of electrical connections are provided on a ceramic lid of the electrode array. The base and lid can be attached using a metal-to-metal seal formed by laser brazing. Electrical connections to the electrode array can be provided by a flexible ribbon cable which can also be used to secure the electrode array in place.

  20. Neural networks for nuclear spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Keller, P.E.; Kangas, L.J.; Hashem, S.; Kouzes, R.T. [Pacific Northwest Lab., Richland, WA (United States)] [and others

    1995-12-31

    In this paper two applications of artificial neural networks (ANNs) in nuclear spectroscopy analysis are discussed. In the first application, an ANN assigns quality coefficients to alpha particle energy spectra. These spectra are used to detect plutonium contamination in the work environment. The quality coefficients represent the levels of spectral degradation caused by miscalibration and foreign matter affecting the instruments. A set of spectra was labeled with quality coefficients by an expert and used to train the ANN expert system. Our investigation shows that the expert knowledge of spectral quality can be transferred to an ANN system. The second application combines a portable gamma-ray spectrometer with an ANN. In this system the ANN is used to automatically identify, radioactive isotopes in real-time from their gamma-ray spectra. Two neural network paradigms are examined: the linear perception and the optimal linear associative memory (OLAM). A comparison of the two paradigms shows that OLAM is superior to linear perception for this application. Both networks have a linear response and are useful in determining the composition of an unknown sample when the spectrum of the unknown is a linear superposition of known spectra. One feature of this technique is that it uses the whole spectrum in the identification process instead of only the individual photo-peaks. For this reason, it is potentially more useful for processing data from lower resolution gamma-ray spectrometers. This approach has been tested with data generated by Monte Carlo simulations and with field data from sodium iodide and Germanium detectors. With the ANN approach, the intense computation takes place during the training process. Once the network is trained, normal operation consists of propagating the data through the network, which results in rapid identification of samples. This approach is useful in situations that require fast response where precise quantification is less important.

  1. Comparing artificial and biological dynamical neural networks

    Science.gov (United States)

    McAulay, Alastair D.

    2006-05-01

    Modern computers can be made more friendly and otherwise improved by making them behave more like humans. Perhaps we can learn how to do this from biology in which human brains evolved over a long period of time. Therefore, we first explain a commonly used biological neural network (BNN) model, the Wilson-Cowan neural oscillator, that has cross-coupled excitatory (positive) and inhibitory (negative) neurons. The two types of neurons are used for frequency modulation communication between neurons which provides immunity to electromagnetic interference. We then evolve, for the first time, an artificial neural network (ANN) to perform the same task. Two dynamical feed-forward artificial neural networks use cross-coupling feedback (like that in a flip-flop) to form an ANN nonlinear dynamic neural oscillator with the same equations as the Wilson-Cowan neural oscillator. Finally we show, through simulation, that the equations perform the basic neural threshold function, switching between stable zero output and a stable oscillation, that is a stable limit cycle. Optical implementation with an injected laser diode and future research are discussed.

  2. Coronary Artery Diagnosis Aided by Neural Network

    Science.gov (United States)

    Stefko, Kamil

    2007-01-01

    Coronary artery disease is due to atheromatous narrowing and subsequent occlusion of the coronary vessel. Application of optimised feed forward multi-layer back propagation neural network (MLBP) for detection of narrowing in coronary artery vessels is presented in this paper. The research was performed using 580 data records from traditional ECG exercise test confirmed by coronary arteriography results. Each record of training database included description of the state of a patient providing input data for the neural network. Level and slope of ST segment of a 12 lead ECG signal recorded at rest and after effort (48 floating point values) was the main component of input data for neural network was. Coronary arteriography results (verified the existence or absence of more than 50% stenosis of the particular coronary vessels) were used as a correct neural network training output pattern. More than 96% of cases were correctly recognised by especially optimised and a thoroughly verified neural network. Leave one out method was used for neural network verification so 580 data records could be used for training as well as for verification of neural network.

  3. Nonequilibrium landscape theory of neural networks.

    Science.gov (United States)

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-11-01

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

  4. Optogenetic dissection of neural circuits underlying emotional valence and motivated behaviors.

    Science.gov (United States)

    Nieh, Edward H; Kim, Sung-Yon; Namburi, Praneeth; Tye, Kay M

    2013-05-20

    The neural circuits underlying emotional valence and motivated behaviors are several synapses away from both defined sensory inputs and quantifiable motor outputs. Electrophysiology has provided us with a suitable means for observing neural activity during behavior, but methods for controlling activity for the purpose of studying motivated behaviors have been inadequate: electrical stimulation lacks cellular specificity and pharmacological manipulation lacks temporal resolution. The recent emergence of optogenetic tools provides a new means for establishing causal relationships between neural activity and behavior. Optogenetics, the use of genetically-encodable light-activated proteins, permits the modulation of specific neural circuit elements with millisecond precision. The ability to control individual cell types, and even projections between distal regions, allows us to investigate functional connectivity in a causal manner. The greatest consequence of controlling neural activity with finer precision has been the characterization of individual neural circuits within anatomical brain regions as defined functional units. Within the mesolimbic dopamine system, optogenetics has helped separate subsets of dopamine neurons with distinct functions for reward, aversion and salience processing, elucidated GABA neuronal effects on behavior, and characterized connectivity with forebrain and cortical structures. Within the striatum, optogenetics has confirmed the opposing relationship between direct and indirect pathway medium spiny neurons (MSNs), in addition to characterizing the inhibition of MSNs by cholinergic interneurons. Within the hypothalamus, optogenetics has helped overcome the heterogeneity in neuronal cell-type and revealed distinct circuits mediating aggression and feeding. Within the amygdala, optogenetics has allowed the study of intra-amygdala microcircuitry as well as interconnections with distal regions involved in fear and anxiety. In this review, we

  5. It's not too late: the onset of the frontocentral P3 indexes successful response inhibition in the stop-signal paradigm.

    Science.gov (United States)

    Wessel, Jan R; Aron, Adam R

    2015-04-01

    The frontocentral P3 event-related potential has been proposed as a neural marker of response inhibition. However, this association is disputed: some argue that P3 latency is too late relative to the timing of action stopping (stop-signal reaction time; SSRT) to index response inhibition. We tested whether P3 onset latency is a marker of response inhibition, and whether it coincides with the timing predicted by neurocomputational models. We measured EEG in 62 participants during the stop-signal task, and used independent component analysis and permutation statistics to measure the P3 onset in each participant. We show that P3 onset latency is shorter when stopping is successful, that it is highly correlated with SSRT, and that it coincides with the purported timing of the inhibition process (towards the end of SSRT). These results demonstrate the utility of P3 onset latency as a noninvasive, temporally precise neural marker of the response inhibition process.

  6. Convolutional Neural Network for Image Recognition

    CERN Document Server

    Seifnashri, Sahand

    2015-01-01

    The aim of this project is to use machine learning techniques especially Convolutional Neural Networks for image processing. These techniques can be used for Quark-Gluon discrimination using calorimeters data, but unfortunately I didn’t manage to get the calorimeters data and I just used the Jet data fromminiaodsim(ak4 chs). The Jet data was not good enough for Convolutional Neural Network which is designed for ’image’ recognition. This report is made of twomain part, part one is mainly about implementing Convolutional Neural Network on unphysical data such as MNIST digits and CIFAR-10 dataset and part 2 is about the Jet data.

  7. Multispectral-image fusion using neural networks

    Science.gov (United States)

    Kagel, Joseph H.; Platt, C. A.; Donaven, T. W.; Samstad, Eric A.

    1990-08-01

    A prototype system is being developed to demonstrate the use of neural network hardware to fuse multispectral imagery. This system consists of a neural network IC on a motherboard a circuit card assembly and a set of software routines hosted by a PC-class computer. Research in support of this consists of neural network simulations fusing 4 to 7 bands of Landsat imagery and fusing (separately) multiple bands of synthetic imagery. The simulations results and a description of the prototype system are presented. 1.

  8. Multispectral image fusion using neural networks

    Science.gov (United States)

    Kagel, J. H.; Platt, C. A.; Donaven, T. W.; Samstad, E. A.

    1990-01-01

    A prototype system is being developed to demonstrate the use of neural network hardware to fuse multispectral imagery. This system consists of a neural network IC on a motherboard, a circuit card assembly, and a set of software routines hosted by a PC-class computer. Research in support of this consists of neural network simulations fusing 4 to 7 bands of Landsat imagery and fusing (separately) multiple bands of synthetic imagery. The simulations, results, and a description of the prototype system are presented.

  9. Optimising the topology of complex neural networks

    CERN Document Server

    Jiang, Fei; Schoenauer, Marc

    2007-01-01

    In this paper, we study instances of complex neural networks, i.e. neural netwo rks with complex topologies. We use Self-Organizing Map neural networks whose n eighbourhood relationships are defined by a complex network, to classify handwr itten digits. We show that topology has a small impact on performance and robus tness to neuron failures, at least at long learning times. Performance may howe ver be increased (by almost 10%) by artificial evolution of the network topo logy. In our experimental conditions, the evolved networks are more random than their parents, but display a more heterogeneous degree distribution.

  10. Handwritten Digits Recognition Using Neural Computing

    OpenAIRE

    Călin Enăchescu; Cristian-Dumitru Miron

    2009-01-01

    In this paper we present a method for the recognition of handwritten digits and a practical implementation of this method for real-time recognition. A theoretical framework for the neural networks used to classify the handwritten digits is also presented.The classification task is performed using a Convolutional Neural Network (CNN). CNN is a special type of multy-layer neural network, being trained with an optimized version of the back-propagation learning algorithm.CNN is designed to recogni...

  11. Optimizing neural network forecast by immune algorithm

    Institute of Scientific and Technical Information of China (English)

    YANG Shu-xia; LI Xiang; LI Ning; YANG Shang-dong

    2006-01-01

    Considering multi-factor influence, a forecasting model was built. The structure of BP neural network was designed, and immune algorithm was applied to optimize its network structure and weight. After training the data of power demand from the year 1980 to 2005 in China, a nonlinear network model was obtained on the relationship between power demand and the factors which had impacts on it, and thus the above proposed method was verified. Meanwhile, the results were compared to those of neural network optimized by genetic algorithm. The results show that this method is superior to neural network optimized by genetic algorithm and is one of the effective ways of time series forecast.

  12. Hidden neural networks: application to speech recognition

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1998-01-01

    We evaluate the hidden neural network HMM/NN hybrid on two speech recognition benchmark tasks; (1) task independent isolated word recognition on the Phonebook database, and (2) recognition of broad phoneme classes in continuous speech from the TIMIT database. It is shown how hidden neural networks...... (HNNs) with much fewer parameters than conventional HMMs and other hybrids can obtain comparable performance, and for the broad class task it is illustrated how the HNN can be applied as a purely transition based system, where acoustic context dependent transition probabilities are estimated by neural...... networks...

  13. Neural network based temporal video segmentation.

    Science.gov (United States)

    Cao, X; Suganthan, P N

    2002-01-01

    The organization of video information in video databases requires automatic temporal segmentation with minimal user interaction. As neural networks are capable of learning the characteristics of various video segments and clustering them accordingly, in this paper, a neural network based technique is developed to segment the video sequence into shots automatically and with a minimum number of user-defined parameters. We propose to employ growing neural gas (GNG) networks and integrate multiple frame difference features to efficiently detect shot boundaries in the video. Experimental results are presented to illustrate the good performance of the proposed scheme on real video sequences. PMID:12370954

  14. Wavelet Neural Networks for Adaptive Equalization

    Institute of Scientific and Technical Information of China (English)

    JIANGMinghu; DENGBeixing; GIELENGeorges; ZHANGBo

    2003-01-01

    A structure based on the Wavelet neural networks (WNNs) is proposed for nonlinear channel equalization in a digital communication system. The construction algorithm of the Minimum error probability (MEP) is presented and applied as a performance criterion to update the parameter matrix of wavelet networks. Our experimental results show that performance of the proposed wavelet networks based on equalizer can significantly improve the neural modeling accuracy, perform quite well in compensating the nonlinear distortion introduced by the channel, and outperform the conventional neural networks in signal to noise ratio and channel non-llnearity.

  15. Estimation of Conditional Quantile using Neural Networks

    DEFF Research Database (Denmark)

    Kulczycki, P.; Schiøler, Henrik

    1999-01-01

    The problem of estimating conditional quantiles using neural networks is investigated here. A basic structure is developed using the methodology of kernel estimation, and a theory guaranteeing con-sistency on a mild set of assumptions is provided. The constructed structure constitutes a basis...... for the design of a variety of different neural networks, some of which are considered in detail. The task of estimating conditional quantiles is related to Bayes point estimation whereby a broad range of applications within engineering, economics and management can be suggested. Numerical results illustrating...... the capabilities of the elaborated neural network are also given....

  16. A COMPREHENSIVE EVOLUTIONARY APPROACH FOR NEURAL NETWORK ENSEMBLES AUTOMATIC DESIGN

    OpenAIRE

    Bukhtoyarov, V.; Semenkin, E.

    2010-01-01

    A new comprehensive approach for neural network ensembles design is proposed. It consists of a method of neural networks automatic design and a method of automatic formation of an ensemble solution on the basis of separate neural networks solutions. It is demonstrated that the proposed approach is not less effective than a number of other approaches for neural network ensembles design.

  17. MicroRNA-765 regulates neural stem cell proliferation and differentiation by modulating Hes1 expression

    Science.gov (United States)

    Li, Siou; Zhao, Weina; Xu, Qing; Yu, Yang; Yin, Changhao

    2016-01-01

    Neural stem cells (NSCs) are multipotent, self-renewing and undifferentiated cells that have the ability to differentiate to both glial and neuronal lineages. miRNAs act a key role in regulating neuronal fate and self-renewal of NSCs. In this study, we found that ectopic expression of miR-765 promoted NSCs proliferation. Moreover, miR-765 overexpression increased the ki-67 and β-tubulin-III expression inNSCs. Overexpression of miR-765 inhibited the expression of GFAP in NSCs. Furthermore, Hes1 was identified as a direct target gene of miR-765 in NSCs. Overexpression of Hes1 decreased miR-765-induced proliferation of NSCs and inhibited NSCs differentiation to neurons in miR-765-treated NSCs. These results demonstrated that miR-765 acted a crucial role in NSCs differentiation and proliferation by inhibiting Hes1 expression. PMID:27508032

  18. Beneficial bacteria inhibit cachexia.

    Science.gov (United States)

    Varian, Bernard J; Goureshetti, Sravya; Poutahidis, Theofilos; Lakritz, Jessica R; Levkovich, Tatiana; Kwok, Caitlin; Teliousis, Konstantinos; Ibrahim, Yassin M; Mirabal, Sheyla; Erdman, Susan E

    2016-03-15

    Muscle wasting, known as cachexia, is a debilitating condition associated with chronic inflammation such as during cancer. Beneficial microbes have been shown to optimize systemic inflammatory tone during good health; however, interactions between microbes and host immunity in the context of cachexia are incompletely understood. Here we use mouse models to test roles for bacteria in muscle wasting syndromes. We find that feeding of a human commensal microbe, Lactobacillus reuteri, to mice is sufficient to lower systemic indices of inflammation and inhibit cachexia. Further, the microbial muscle-building phenomenon extends to normal aging as wild type animals exhibited increased growth hormone levels and up-regulation of transcription factor Forkhead Box N1 [FoxN1] associated with thymus gland retention and longevity. Interestingly, mice with a defective FoxN1 gene (athymic nude) fail to inhibit sarcopenia after L. reuteri therapy, indicating a FoxN1-mediated mechanism. In conclusion, symbiotic bacteria may serve to stimulate FoxN1 and thymic functions that regulate inflammation, offering possible alternatives for cachexia prevention and novel insights into roles for microbiota in mammalian ontogeny and phylogeny. PMID:26933816

  19. Neuroanatomy and sex differences of the lordosis-inhibiting system in the lateral septum

    Directory of Open Access Journals (Sweden)

    Shinji eTsukahara

    2014-09-01

    Full Text Available Female sexual behavior in rodents, termed lordosis, is controlled by facilitatory and inhibitory systems in the brain. It has been well demonstrated that a neural pathway from the ventromedial hypothalamic nucleus (VMN to the midbrain central gray (MCG is essential for facilitatory regulation of lordosis. The neural pathway from the arcuate nucleus to the VMN, via the medial preoptic nucleus, in female rats mediates transient suppression of lordosis, until female sexual receptivity is induced. In addition to this pathway, other regions are involved in inhibitory regulation of lordosis in female rats. The lordosis-inhibiting systems exist not only in the female brain but also in the male brain. The systems contribute to suppression of heterotypical sexual behavior in male rats, although they have the potential ability to display lordosis. The lateral septum (LS exerts an inhibitory influence on lordosis in both female and male rats. This review focuses on the neuroanatomy and sex differences of the lordosis-inhibiting system in the LS. The LS functionally and anatomically links to the MCG to exert suppression of lordosis. Neurons of the intermediate part of the LS (LSi serve as lordosis-inhibiting neurons and project axons to the MCG. The LSi-MCG neural connection is sexually dimorphic, and formation of the male-like LSi-MCG neural connection is affected by aromatized testosterone originating from the testes in the postnatal period. The sexually dimorphic LSi-MCG neural connection may reflect the morphological basis of sex differences in the inhibitory regulation of lordosis in rats.

  20. Maturation of cognitive control: delineating response inhibition and interference suppression.

    Directory of Open Access Journals (Sweden)

    Christopher R Brydges

    Full Text Available Cognitive control is integral to the ability to attend to a relevant task whilst suppressing distracting information or inhibiting prepotent responses. The current study examined the development of these two subprocesses by examining electrophysiological indices elicited during each process. Thirteen 18 year-old adults and thirteen children aged 8-11 years (mean=9.77 years completed a hybrid Go/Nogo flanker task while continuous EEG data were recorded. The N2 topography for both response inhibition and interference suppression changed with increasing age. The neural activation associated with response inhibition became increasingly frontally distributed with age, and showed decreases of both amplitude and peak latency from childhood to adulthood, possibly due to reduced cognitive demands and myelination respectively occurring during this period. Interestingly, a significant N2 effect was apparent in adults, but not observed in children during trials requiring interference suppression. This could be due to more diffuse activation in children, which would require smaller levels of activation over a larger region of the brain than is reported in adults. Overall, these results provide evidence of distinct maturational processes occurring throughout late childhood and adolescence, highlighting the separability of response inhibition and interference suppression.

  1. MLR-induced inhibition of barosensory cells in the NTS.

    Science.gov (United States)

    Degtyarenko, Alexandr M; Kaufman, Marc P

    2005-12-01

    A central motor command arising from the mesencephalic locomotor region (MLR) is widely believed to be one of the neural mechanisms that reset the baroreceptor reflex upward during exercise. The nucleus tractus solitarius (NTS), a dorsal medullary site that receives input from baroreceptors, may be the site where central command inhibits baroreceptor input during exercise. We, therefore, examined the effect of electrical stimulation of the MLR on the impulse activity of cells in the NTS in decerebrate paralyzed cats. Of 129 NTS cells tested for baroreceptor input by injection of phenylephrine (7-25 microg/kg iv) or inflation of a balloon in the carotid sinus, 58 were stimulated and 19 were inhibited. MLR stimulation (80-150 microA) inhibited the discharge of 48 of the 58 cells stimulated by baroreceptor input. MLR stimulation had no effect on the discharge of the remaining 10 cells, each of which displayed no spontaneous activity. In contrast to the 77 NTS cells responsive to baroreceptor input, there was no change in activity of 52 cells when arterial pressure was increased by phenylephrine injection or balloon inflation. MLR stimulation activated each of the 52 NTS cells. For 23 of the cells, the onset latency to MLR stimulation was clearly discernable, averaging 6.4 +/- 0.4 ms. Our findings provide electrophysiological evidence for the hypothesis that the MLR inhibits the baroreceptor reflex by activating NTS interneurons unresponsive to baroreceptor input. In turn, these interneurons may release an inhibitory neurotransmitter onto NTS cells receiving baroreceptor input.

  2. VEGF-mediated angiogenesis stimulates neural stem cell proliferation and differentiation in the premature brain

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Jinqiao, E-mail: jinqiao1977@163.com [Institute of Pediatrics, Children' s Hospital of Fudan University (China); Sha, Bin [Department of Neonatology, Children' s Hospital of Fudan University, 399 Wanyuan Road, Shanghai 201102 (China); Zhou, Wenhao, E-mail: zhou_wenhao@yahoo.com.cn [Department of Neonatology, Children' s Hospital of Fudan University, 399 Wanyuan Road, Shanghai 201102 (China); Yang, Yi [Institute of Pediatrics, Children' s Hospital of Fudan University (China)

    2010-03-26

    This study investigated the effects of angiogenesis on the proliferation and differentiation of neural stem cells in the premature brain. We observed the changes in neurogenesis that followed the stimulation and inhibition of angiogenesis by altering vascular endothelial growth factor (VEGF) expression in a 3-day-old rat model. VEGF expression was overexpressed by adenovirus transfection and down-regulated by siRNA interference. Using immunofluorescence assays, Western blot analysis, and real-time PCR methods, we observed angiogenesis and the proliferation and differentiation of neural stem cells. Immunofluorescence assays showed that the number of vWF-positive areas peaked at day 7, and they were highest in the VEGF up-regulation group and lowest in the VEGF down-regulation group at every time point. The number of neural stem cells, neurons, astrocytes, and oligodendrocytes in the subventricular zone gradually increased over time in the VEGF up-regulation group. Among the three groups, the number of these cells was highest in the VEGF up-regulation group and lowest in the VEGF down-regulation group at the same time point. Western blot analysis and real-time PCR confirmed these results. These data suggest that angiogenesis may stimulate the proliferation of neural stem cells and differentiation into neurons, astrocytes, and oligodendrocytes in the premature brain.

  3. Stromal SLIT2 impacts on pancreatic cancer-associated neural remodeling.

    Science.gov (United States)

    Secq, V; Leca, J; Bressy, C; Guillaumond, F; Skrobuk, P; Nigri, J; Lac, S; Lavaut, M-N; Bui, T-T; Thakur, A K; Callizot, N; Steinschneider, R; Berthezene, P; Dusetti, N; Ouaissi, M; Moutardier, V; Calvo, E; Bousquet, C; Garcia, S; Bidaut, G; Vasseur, S; Iovanna, J L; Tomasini, R

    2015-01-15

    Pancreatic ductal adenocarcinoma (PDA) is a critical health issue in the field of cancer, with few therapeutic options. Evidence supports an implication of the intratumoral microenvironment (stroma) on PDA progression. However, its contribution to the role of neuroplastic changes within the pathophysiology and clinical course of PDA, through tumor recurrence and neuropathic pain, remains unknown, neglecting a putative, therapeutic window. Here, we report that the intratumoral microenvironment is a mediator of PDA-associated neural remodeling (PANR), and we highlight factors such as 'SLIT2' (an axon guidance molecule), which is expressed by cancer-associated fibroblasts (CAFs), that impact on neuroplastic changes in human PDA. We showed that 'CAF-secreted SLIT2' increases neurite outgrowth from dorsal root ganglia neurons as well as from Schwann cell migration/proliferation by modulating N-cadherin/β-catenin signaling. Importantly, SLIT2/ROBO signaling inhibition disrupts this stromal/neural connection. Finally, we revealed that SLIT2 expression and CAFs are correlated with neural remodeling within human and mouse PDA. All together, our data demonstrate the implication of CAFs, through the secretion of axon guidance molecule, in PANR. Furthermore, it provides rationale to investigate the disruption of the stromal/neural compartment connection with SLIT2/ROBO inhibitors for the treatment of pancreatic cancer recurrence and pain.

  4. Neural processing of auditory signals and modular neural control for sound tropism of walking machines

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Pasemann, Frank; Fischer, Joern;

    2005-01-01

    . The parameters of these networks are optimized by an evolutionary algorithm. In addition, a simple modular neural controller then generates the desired different walking patterns such that the machine walks straight, then turns towards a switched-on sound source, and then stops near to it....... and a neural preprocessing system together with a modular neural controller are used to generate a sound tropism of a four-legged walking machine. The neural preprocessing network is acting as a low-pass filter and it is followed by a network which discerns between signals coming from the left or the right...

  5. Deep Learning with Darwin: Evolutionary Synthesis of Deep Neural Networks

    OpenAIRE

    Shafiee, Mohammad Javad; Mishra, Akshaya; Wong, Alexander

    2016-01-01

    Taking inspiration from biological evolution, we explore the idea of "Can deep neural networks evolve naturally over successive generations into highly efficient deep neural networks?" by introducing the notion of synthesizing new highly efficient, yet powerful deep neural networks over successive generations via an evolutionary process from ancestor deep neural networks. The architectural traits of ancestor deep neural networks are encoded using synaptic probability models, which can be view...

  6. Neural bases of accented speech perception

    Directory of Open Access Journals (Sweden)

    Patti eAdank

    2015-10-01

    Full Text Available The recognition of unfamiliar regional and foreign accents represents a challenging task for the speech perception system (Adank, Evans, Stuart-Smith, & Scott, 2009; Floccia, Goslin, Girard, & Konopczynski, 2006. Despite the frequency with which we encounter such accents, the neural mechanisms supporting successful perception of accented speech are poorly understood. Nonetheless, candidate neural substrates involved in processing speech in challenging listening conditions, including accented speech, are beginning to be identified. This review will outline neural bases associated with perception of accented speech in the light of current models of speech perception, and compare these data to brain areas associated with processing other speech distortions. We will subsequently evaluate competing models of speech processing with regards to neural processing of accented speech. See Cristia et al. (2012 for an in-depth overview of behavioural aspects of accent processing.

  7. Drift chamber tracking with neural networks

    International Nuclear Information System (INIS)

    With the very high event rates projected for experiments at the SSC and LHC, it is important to investigate new approaches to on line pattern recognition. The use of neural networks for pattern recognition. The use of neural networks for pattern recognition in high energy physics detectors has been an area of very active research. The authors discuss drift chamber tracking with a commercial analog VLSI neural network chip. Voltages proportional to the drift times in a 4-layer drift chamber were presented to the Intel ETANN chip. The network was trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs were recorded and later compared off line to conventional track fits. Two types of network architectures were studied. Applications of neural network tracking to high energy physics detector triggers is discussed

  8. Rule Extraction using Artificial Neural Networks

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Artificial neural networks have been successfully applied to a variety of business application problems involving classification and regression. Although backpropagation neural networks generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions are not as interpretable as those of decision trees. In many applications, it is desirable to extract knowledge from trained neural networks so that the users can gain a better understanding of the solution. This paper presents an efficient algorithm to extract rules from artificial neural networks. We use two-phase training algorithm for backpropagation learning. In the first phase, the number of hidden nodes of the network is determined automatically in a constructive fashion by adding nodes one after another based on the performance of the network on training data. In the second phase, the number of relevant input units of the network is determined using pruning algorithm. The ...

  9. Optimal neural computations require analog processors

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-12-31

    This paper discusses some of the limitations of hardware implementations of neural networks. The authors start by presenting neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural networks. Further, the focus will be on hardware imposed constraints. They will present recent results for three different alternatives of parallel implementations of neural networks: digital circuits, threshold gate circuits, and analog circuits. The area and the delay will be related to the neurons` fan-in and to the precision of their synaptic weights. The main conclusion is that hardware-efficient solutions require analog computations, and suggests the following two alternatives: (i) cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow the use of the third dimension (e.g. using optical interconnections).

  10. Neural networks for NOx-emission

    International Nuclear Information System (INIS)

    The government wants to restrict nitrogen oxide emissions. However, continuous measurement of these emissions is expensive and maintenance-sensitive. A prediction model based on the use of neural networks might be a reliable and efficient alternative

  11. Neural Networks in Mobile Robot Motion

    Directory of Open Access Journals (Sweden)

    Danica Janglova

    2008-11-01

    Full Text Available This paper deals with a path planning and intelligent control of an autonomous robot which should move safely in partially structured environment. This environment may involve any number of obstacles of arbitrary shape and size; some of them are allowed to move. We describe our approach to solving the motion-planning problem in mobile robot control using neural networks-based technique. Our method of the construction of a collision-free path for moving robot among obstacles is based on two neural networks. The first neural network is used to determine the "free" space using ultrasound range finder data. The second neural network "finds" a safe direction for the next robot section of the path in the workspace while avoiding the nearest obstacles. Simulation examples of generated path with proposed techniques will be presented.

  12. Neural adaptations to electrical stimulation strength training

    NARCIS (Netherlands)

    Hortobagyi, Tibor; Maffiuletti, Nicola A.

    2011-01-01

    This review provides evidence for the hypothesis that electrostimulation strength training (EST) increases the force of a maximal voluntary contraction (MVC) through neural adaptations in healthy skeletal muscle. Although electrical stimulation and voluntary effort activate muscle differently, there

  13. Evolutionary induction of sparse neural trees

    Science.gov (United States)

    Zhang; Ohm; Muhlenbein

    1997-01-01

    This paper is concerned with the automatic induction of parsimonious neural networks. In contrast to other program induction situations, network induction entails parametric learning as well as structural adaptation. We present a novel representation scheme called neural trees that allows efficient learning of both network architectures and parameters by genetic search. A hybrid evolutionary method is developed for neural tree induction that combines genetic programming and the breeder genetic algorithm under the unified framework of the minimum description length principle. The method is successfully applied to the induction of higher order neural trees while still keeping the resulting structures sparse to ensure good generalization performance. Empirical results are provided on two chaotic time series prediction problems of practical interest. PMID:10021759

  14. Wandering bumps in stochastic neural fields

    CERN Document Server

    Kilpatrick, Zachary P

    2012-01-01

    We study the effects of noise on stationary pulse solutions (bumps) in spatially extended neural fields. The dynamics of a neural field is described by an integrodifferential equation whose integral term characterizes synaptic interactions between neurons in different spatial locations of the network. Translationally symmetric neural fields support a continuum of stationary bump solutions, which may be centered at any spatial location. Random fluctuations are introduced by modeling the system as a spatially extended Langevin equation whose noise term we take to be multiplicative or additive. For nonzero noise, these bumps are shown to wander about the domain in a purely diffusive way. We can approximate the effective diffusion coefficient using a small noise expansion. Upon breaking the (continuous) translation symmetry of the system using a spatially heterogeneous inputs or synapses, bumps in the stochastic neural field can become temporarily pinned to a finite number of locations in the network. In the case...

  15. Neural Network Based 3D Surface Reconstruction

    Directory of Open Access Journals (Sweden)

    Vincy Joseph

    2009-11-01

    Full Text Available This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pixel values of the two-dimensional images to be reconstructed. The normal vectors of the surface can then be obtained from the output of the neural network after supervised learning, where the illuminant direction does not have to be known in advance. Finally, the obtained normal vectors can be applied to integration method when reconstructing 3-D objects. Facial images were used for training in the proposed approach

  16. TIME SERIES FORECASTING USING NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    BOGDAN OANCEA

    2013-05-01

    Full Text Available Recent studies have shown the classification and prediction power of the Neural Networks. It has been demonstrated that a NN can approximate any continuous function. Neural networks have been successfully used for forecasting of financial data series. The classical methods used for time series prediction like Box-Jenkins or ARIMA assumes that there is a linear relationship between inputs and outputs. Neural Networks have the advantage that can approximate nonlinear functions. In this paper we compared the performances of different feed forward and recurrent neural networks and training algorithms for predicting the exchange rate EUR/RON and USD/RON. We used data series with daily exchange rates starting from 2005 until 2013.

  17. Neural network for sonogram gap filling

    DEFF Research Database (Denmark)

    Klebæk, Henrik; Jensen, Jørgen Arendt; Hansen, Lars Kai

    1995-01-01

    a neural network for predicting mean frequency of the velocity signal and its variance. The neural network then predicts the evolution of the mean and variance in the gaps, and the sonogram and audio signal are reconstructed from these. The technique is applied on in-vivo data from the carotid artery....... The neural network is trained on part of the data and the network is pruned by the optimal brain damage procedure in order to reduce the number of parameters in the network, and thereby reduce the risk of overfitting. The neural predictor is compared to using a linear filter for the mean and variance time......In duplex imaging both an anatomical B-mode image and a sonogram are acquired, and the time for data acquisition is divided between the two images. This gives problems when rapid B-mode image display is needed, since there is not time for measuring the velocity data. Gaps then appear...

  18. Estimates on compressed neural networks regression.

    Science.gov (United States)

    Zhang, Yongquan; Li, Youmei; Sun, Jianyong; Ji, Jiabing

    2015-03-01

    When the neural element number n of neural networks is larger than the sample size m, the overfitting problem arises since there are more parameters than actual data (more variable than constraints). In order to overcome the overfitting problem, we propose to reduce the number of neural elements by using compressed projection A which does not need to satisfy the condition of Restricted Isometric Property (RIP). By applying probability inequalities and approximation properties of the feedforward neural networks (FNNs), we prove that solving the FNNs regression learning algorithm in the compressed domain instead of the original domain reduces the sample error at the price of an increased (but controlled) approximation error, where the covering number theory is used to estimate the excess error, and an upper bound of the excess error is given.

  19. Additive Feed Forward Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1999-01-01

    This paper demonstrates a method to control a non-linear, multivariable, noisy process using trained neural networks. The basis for the method is a trained neural network controller acting as the inverse process model. A training method for obtaining such an inverse process model is applied....... A suitable 'shaped' (low-pass filtered) reference is used to overcome problems with excessive control action when using a controller acting as the inverse process model. The control concept is Additive Feed Forward Control, where the trained neural network controller, acting as the inverse process model......, is placed in a supplementary pure feed-forward path to an existing feedback controller. This concept benefits from the fact, that an existing, traditional designed, feedback controller can be retained without any modifications, and after training the connection of the neural network feed-forward controller...

  20. Neural regulation of the stress response: glucocorticoid feedback mechanisms

    Directory of Open Access Journals (Sweden)

    J.P. Herman

    2012-04-01

    Full Text Available The mammalian stress response is an integrated physiological and psychological reaction to real or perceived adversity. Glucocorticoids are an important component of this response, acting to redistribute energy resources to both optimize survival in the face of challenge and to restore homeostasis after the immediate challenge has subsided. Release of glucocorticoids is mediated by the hypothalamo-pituitary-adrenal (HPA axis, driven by a neural signal originating in the paraventricular nucleus (PVN. Stress levels of glucocorticoids bind to glucocorticoid receptors in multiple body compartments, including the brain, and consequently have wide-reaching actions. For this reason, glucocorticoids serve a vital function in negative feedback inhibition of their own secretion. Negative feedback inhibition is mediated by a diverse collection of mechanisms, including fast, non-genomic feedback at the level of the PVN, stress-shut-off at the level of the limbic system, and attenuation of ascending excitatory input through destabilization of mRNAs encoding neuropeptide drivers of the HPA axis. In addition, there is evidence that glucocorticoids participate in stress activation via feed-forward mechanisms at the level of the amygdala. Feedback deficits are associated with numerous disease states, underscoring the necessity for adequate control of glucocorticoid homeostasis. Thus, rather than having a single, defined feedback ‘switch’, control of the stress response requires a wide-reaching feedback ‘network’ that coordinates HPA activity to suit the overall needs of multiple body systems.

  1. Central neural control of thermoregulation and brown adipose tissue.

    Science.gov (United States)

    Morrison, Shaun F

    2016-04-01

    Central neural circuits orchestrate the homeostatic repertoire that maintains body temperature during environmental temperature challenges and alters body temperature during the inflammatory response. This review summarizes the experimental underpinnings of our current model of the CNS pathways controlling the principal thermoeffectors for body temperature regulation: cutaneous vasoconstriction controlling heat loss, and shivering and brown adipose tissue for thermogenesis. The activation of these effectors is regulated by parallel but distinct, effector-specific, core efferent pathways within the CNS that share a common peripheral thermal sensory input. Via the lateral parabrachial nucleus, skin thermal afferent input reaches the hypothalamic preoptic area to inhibit warm-sensitive, inhibitory output neurons which control heat production by inhibiting thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to thermogenesis-controlling premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation of spinal circuits necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus sympathetic premotor neurons controlling cutaneous vasoconstriction. The model proposed for central thermoregulatory control provides a useful platform for further understanding of the functional organization of central thermoregulation and elucidating the hypothalamic circuitry and neurotransmitters involved in body temperature regulation. PMID:26924538

  2. SAR ATR Based on Convolutional Neural Network

    OpenAIRE

    Tian Zhuangzhuang; Zhan Ronghui; Hu Jiemin; Zhang Jun

    2016-01-01

    This study presents a new method of Synthetic Aperture Radar (SAR) image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network’s ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recogni...

  3. Drift chamber tracking with neural networks

    International Nuclear Information System (INIS)

    We discuss drift chamber tracking with a commercial log VLSI neural network chip. Voltages proportional to the drift times in a 4-layer drift chamber were presented to the Intel ETANN chip. The network was trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs were recorded and later compared off line to conventional track fits. Two types of network architectures were studied. Applications of neural network tracking to high energy physics detector triggers is discussed

  4. Exponential Stability for Delayed Cellular Neural Networks

    Institute of Scientific and Technical Information of China (English)

    YANG Jin-xiang; ZHONG Shou-ming; YAN Ke-yu

    2005-01-01

    The exponential stability of the delayed cellular neural networks (DCNN's) is investigated. By dividing the network state variables into some parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Liapunov function. It is shown that the conditions differ from previous ones. The new conditions, which are associated with some initial value, are represented by some blocks of the interconnection matrix.

  5. Neural Boundary Conditions in Optic Guides

    OpenAIRE

    Özkan-Bakbak, Pınar

    2015-01-01

    In this study, the boundary coefficients of Transverse Electric (TE) and Transverse Magnetic (TM) modes at a planar slab optic guides are modeled by Neural Networks (NN). After modal analysis, train and test files are prepared for NN. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks are performed and compared with each other. NNs are expected to be capable of modeling optical fiber technology in industry based on the same approaches as a result of this study.

  6. Applications of Pulse-Coupled Neural Networks

    CERN Document Server

    Ma, Yide; Wang, Zhaobin

    2011-01-01

    "Applications of Pulse-Coupled Neural Networks" explores the fields of image processing, including image filtering, image segmentation, image fusion, image coding, image retrieval, and biometric recognition, and the role of pulse-coupled neural networks in these fields. This book is intended for researchers and graduate students in artificial intelligence, pattern recognition, electronic engineering, and computer science. Prof. Yide Ma conducts research on intelligent information processing, biomedical image processing, and embedded system development at the School of Information Sci

  7. Neural networks, D0, and the SSC

    International Nuclear Information System (INIS)

    We outline several exploratory studies involving neural network simulations applied to pattern recognition in high energy physics. We describe the D0 data acquisition system and a natual means by which algorithms derived from neural networks techniques may be incorporated into recently developed hardware associated with the D0 MicroVAX farm nodes. Such applications to the event filtering needed by SSC detectors look interesting. 10 refs., 11 figs

  8. Radioactive fallout and neural tube defects

    Directory of Open Access Journals (Sweden)

    Nejat Akar

    2015-10-01

    Full Text Available Possible link between radioactivity and the occurrence of neural tube defects is a long lasting debate since the Chernobyl nuclear fallout in 1986. A recent report on the incidence of neural defects in the west coast of USA, following Fukushima disaster, brought another evidence for effect of radioactive fallout on the occurrence of NTD’s. Here a literature review was performed focusing on this special subject.

  9. Learning Processes of Layered Neural Networks

    OpenAIRE

    Fujiki, Sumiyoshi; Fujiki, Nahomi M.

    1995-01-01

    A positive reinforcement type learning algorithm is formulated for a stochastic feed-forward neural network, and a learning equation similar to that of the Boltzmann machine algorithm is obtained. By applying a mean field approximation to the same stochastic feed-forward neural network, a deterministic analog feed-forward network is obtained and the back-propagation learning rule is re-derived.

  10. An Introduction to Convolutional Neural Networks

    OpenAIRE

    O'Shea, Keiron; Nash, Ryan

    2015-01-01

    The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of artificial intelligence in common machine learning tasks. One of the most impressive forms of ANN architecture is that of the Convolutional Neural Network (CNN). CNNs are primarily used to solve difficult image-driven pattern recognition tasks and with their p...

  11. Neural differentiation of human embryonic stem cells

    OpenAIRE

    Dhara, Sujoy K.; Stice, Steven L.

    2008-01-01

    Availability of human embryonic stem cells (hESC) has enhanced human neural differentiation research. The derivation of neural progenitor (NP) cells from hESC facilitates the integration of human embryonic development through the generation of neuronal subtypes and supporting glial cells. These cells will likely lead to new and novel drug screening and cell therapy uses. This review will discuss the current status of derivation, maintenance and further differentiation of NP cells with special...

  12. Multilingual Image Description with Neural Sequence Models

    OpenAIRE

    Elliott, Desmond; Frank, Stella; Hasler, Eva

    2015-01-01

    In this paper we present an approach to multi-language image description bringing together insights from neural machine translation and neural image description. To create a description of an image for a given target language, our sequence generation models condition on feature vectors from the image, the description from the source language, and/or a multimodal vector computed over the image and a description in the source language. In image description experiments on the IAPR-TC12 dataset o...

  13. Parameterizing Stellar Spectra Using Deep Neural Networks

    OpenAIRE

    Li, Xiangru; Pan, Ruyang

    2016-01-01

    This work investigates the spectrum parameterization problem using deep neural networks (DNNs). The proposed scheme consists of the following procedures: first, the configuration of a DNN is initialized using a series of autoencoder neural networks; second, the DNN is fine-tuned using a gradient descent scheme; third, stellar parameters ($T_{eff}$, log$~g$, and [Fe/H]) are estimated using the obtained DNN. This scheme was evaluated on both real spectra from SDSS/SEGUE and synthetic spectra ca...

  14. Immunological control of adult neural stem cells

    OpenAIRE

    Gonzalez-Perez, Oscar; Quiñones-Hinojosa, Alfredo; Garcia-Verdugo, Jose Manuel

    2010-01-01

    Adult neurogenesis occurs only in discrete regions of adult central nervous system: the subventricular zone and the subgranular zone. These areas are populated by adult neural stem cells (aNSC) that are regulated by a number of molecules and signaling pathways, which control their cell fate choices, survival and proliferation rates. For a long time, it was believed that the immune system did not exert any control on neural proliferative niches. However, it has been observed that many patholog...

  15. Can neural machine translation do simultaneous translation?

    OpenAIRE

    Cho, KyungHyun; Esipova, Masha

    2016-01-01

    We investigate the potential of attention-based neural machine translation in simultaneous translation. We introduce a novel decoding algorithm, called simultaneous greedy decoding, that allows an existing neural machine translation model to begin translating before a full source sentence is received. This approach is unique from previous works on simultaneous translation in that segmentation and translation are done jointly to maximize the translation quality and that translating each segmen...

  16. The neural basis of bounded rational behavior

    OpenAIRE

    Coricelli, Giorgio; Nagel, Rosemarie

    2010-01-01

    Bounded rational behaviour is commonly observed in experimental games and in real life situations. Neuroeconomics can help to understand the mental processing underlying bounded rationality and out-of-equilibrium behaviour. Here we report results from recent studies on the neural basis of limited steps of reasoning in a competitive setting —the beauty contest game. We use functional magnetic resonance imaging (fMRI) to study the neural correlates of human mental processes in strategic games. ...

  17. Drift chamber tracking with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Lindsey, C.S.; Denby, B.; Haggerty, H.

    1992-10-01

    We discuss drift chamber tracking with a commercial log VLSI neural network chip. Voltages proportional to the drift times in a 4-layer drift chamber were presented to the Intel ETANN chip. The network was trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs were recorded and later compared off line to conventional track fits. Two types of network architectures were studied. Applications of neural network tracking to high energy physics detector triggers is discussed.

  18. Hindcasting cyclonic waves using neural networks

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Rao, S.; Chakravarty, N.V.

    for computing extreme wave conditions or design wave statistics. As far as Indian seas are concerned recorded wave data are available for short periods for some places along the coasts. Estimation of wave parameters by numerical wave forecasting schemes.... Some applications of neural network (NN) in wave forecasting are carried out by Deo and Naidu (1999), and Prabaharan (2001). Londhe and Deo (2001) have worked on wave propagation using neural network. This paper describes about hindcasting of wave...

  19. The neural correlates of social connection

    OpenAIRE

    Hutcherson, Cendri A.; Seppala, Emma M.; James J Gross

    2015-01-01

    Cultivating social connection has long been a goal of psychology, philosophy, religion, and public policy. Yet the psychological and neural responses that accompany a feeling of connection to others remain unclear. In the present study, we used functional neuroimaging to shed light on the neural correlates of self- and other-focused processes during the successful self-generation of feelings of social connection. To do this, we used a trait judgment task to localize functional activation rela...

  20. Density functional and neural network analysis

    DEFF Research Database (Denmark)

    Jalkanen, K. J.; Suhai, S.; Bohr, Henrik

    1997-01-01

    dichroism (VCD) intensities. The large changes due to hydration on the structures, relative stability of conformers, and in the VA and VCD spectra observed experimentally are reproduced by the DFT calculations. Furthermore a neural network was constructed for reproducing the inverse scattering data (infer...... the structural coordinates from spectroscopic data) that the DFT method could produce. Finally the neural network performances are used to monitor a sensitivity or dependence analysis of the importance of secondary structures....

  1. Diagnosis method utilizing neural networks

    International Nuclear Information System (INIS)

    Studies have been made on the technique of neural networks, which will be used to identify a cause of a small anomalous state in the reactor coolant system of the ATR (Advance Thermal Reactor). Three phases of analyses were carried out in this study. First, simulation for 100 seconds was made to determine how the plant parameters respond after the occurence of a transient decrease in reactivity, flow rate and temperature of feed water and increase in the steam flow rate and steam pressure, which would produce a decrease of water level in a steam drum of the ATR. Next, the simulation data was analysed utilizing an autoregressive model. From this analysis, a total of 36 coherency functions up to 0.5 Hz in each transient were computed among nine important and detectable plant parameters: neutron flux, flow rate of coolant, steam or feed water, water level in the steam drum, pressure and opening area of control valve in a steam pipe, feed water temperature and electrical power. Last, learning of neural networks composed of 96 input, 4-9 hidden and 5 output layer units was done by use of the generalized delta rule, namely a back-propagation algorithm. These convergent computations were continued as far as the difference between the desired outputs, 1 for direct cause or 0 for four other ones and actual outputs reached less than 10%. (1) Coherency functions were not governed by decreasing rate of reactivity in the range of 0.41x10-2dollar/s to 1.62x10-2dollar /s or by decreasing depth of the feed water temperature in the range of 3 deg C to 10 deg C or by a change of 10% or less in the three other causes. Change in coherency functions only depended on the type of cause. (2) The direct cause from the other four ones could be discriminated with 0.94+-0.01 of output level. A maximum of 0.06 output height was found among the other four causes. (3) Calculation load which is represented as products of learning times and numbers of the hidden units did not depend on the numbers

  2. Chemical Inhibition of Autophagy

    DEFF Research Database (Denmark)

    Baek, Eric; Lin Kim, Che; Gyeom Kim, Mi;

    2016-01-01

    Chinese hamster ovary (CHO) cells activate and undergo apoptosis and autophagy for various environmental stresses. Unlike apoptosis, studies on increasing the production of therapeutic proteins in CHO cells by targeting the autophagy pathway are limited. In order to identify the effects of chemical...... autophagy inhibitors on the specific productivity (qp), nine chemical inhibitors that had been reported to target three different phases of autophagy (metformin, dorsomorphin, resveratrol, and SP600125 against initiation and nucleation; 3-MA, wortmannin, and LY294002 against elongation, and chloroquine...... significantly increased the qp of DG44-Fc and DUKX-Fc. In contrast, for DG44-Ab, only 3-MA significantly increased the qp. The autophagy-inhibiting activity of the nine chemical inhibitors on the rCHO cell lines was evaluated through Western blot analysis and flow cytometry. Unexpectedly, some chemical...

  3. Fcγ receptor-mediated inflammation inhibits axon regeneration.

    Directory of Open Access Journals (Sweden)

    Gang Zhang

    Full Text Available Anti-glycan/ganglioside antibodies are the most common immune effectors found in patients with Guillain-Barré Syndrome, which is a peripheral autoimmune neuropathy. We previously reported that disease-relevant anti-glycan autoantibodies inhibited axon regeneration, which echo the clinical association of these antibodies and poor recovery in Guillain-Barré Syndrome. However, the specific molecular and cellular elements involved in this antibody-mediated inhibition of axon regeneration are not previously defined. This study examined the role of Fcγ receptors and macrophages in the antibody-mediated inhibition of axon regeneration. A well characterized antibody passive transfer sciatic nerve crush and transplant models were used to study the anti-ganglioside antibody-mediated inhibition of axon regeneration in wild type and various mutant and transgenic mice with altered expression of specific Fcγ receptors and macrophage/microglia populations. Outcome measures included behavior, electrophysiology, morphometry, immunocytochemistry, quantitative real-time PCR, and western blotting. We demonstrate that the presence of autoantibodies, directed against neuronal/axonal cell surface gangliosides, in the injured mammalian peripheral nerves switch the proregenerative inflammatory environment to growth inhibitory milieu by engaging specific activating Fcγ receptors on recruited monocyte-derived macrophages to cause severe inhibition of axon regeneration. Our data demonstrate that the antibody orchestrated Fcγ receptor-mediated switch in inflammation is one mechanism underlying inhibition of axon regeneration. These findings have clinical implications for nerve repair and recovery in antibody-mediated immune neuropathies. Our results add to the complexity of axon regeneration in injured peripheral and central nervous systems as adverse effects of B cells and autoantibodies on neural injury and repair are increasingly recognized.

  4. Brain and language: evidence for neural multifunctionality.

    Science.gov (United States)

    Cahana-Amitay, Dalia; Albert, Martin L

    2014-01-01

    This review paper presents converging evidence from studies of brain damage and longitudinal studies of language in aging which supports the following thesis: the neural basis of language can best be understood by the concept of neural multifunctionality. In this paper the term "neural multifunctionality" refers to incorporation of nonlinguistic functions into language models of the intact brain, reflecting a multifunctional perspective whereby a constant and dynamic interaction exists among neural networks subserving cognitive, affective, and praxic functions with neural networks specialized for lexical retrieval, sentence comprehension, and discourse processing, giving rise to language as we know it. By way of example, we consider effects of executive system functions on aspects of semantic processing among persons with and without aphasia, as well as the interaction of executive and language functions among older adults. We conclude by indicating how this multifunctional view of brain-language relations extends to the realm of language recovery from aphasia, where evidence of the influence of nonlinguistic factors on the reshaping of neural circuitry for aphasia rehabilitation is clearly emerging.

  5. The Laplacian spectrum of neural networks

    Directory of Open Access Journals (Sweden)

    Siemon ede Lange

    2014-01-01

    Full Text Available The brain is a complex network of neural interactions, both at the microscopic and macroscopic level. Graph theory is well suited to examine the global network architecture of these neural networks. Many popular graph metrics, however, encode average properties of individual network elements. Complementing these ‘conventional’ graph metrics, the eigenvalue spectrum of the normalized Laplacian describes a network’s structure directly at a systems level, without referring to individual nodes or connections. In this paper, the Laplacian spectra of the macroscopic anatomical neuronal networks of the macaque and cat, and the microscopic network of the Caenorhabditis elegans were examined. Consistent with conventional graph metrics, analysis of the Laplacian spectra revealed an integrative community structure in neural brain networks. Extending previous findings of overlap of network attributes across species, similarity of the Laplacian spectra across the cat, macaque and C. elegans neural networks suggests a certain level of consistency in the overall architecture of the anatomical neural networks of these species. Our results further suggest a specific network class for neural networks, distinct from conceptual small-world and scale-free models as well as several empirical networks.

  6. Applying neural networks in autonomous systems

    Science.gov (United States)

    Thornbrugh, Allison L.; Layne, J. D.; Wilson, James M., III

    1992-03-01

    Autonomous and teleautonomous operations have been defined in a variety of ways by different groups involved with remote robotic operations. For example, Conway describes architectures for producing intelligent actions in teleautonomous systems. Applying neural nets in such systems is similar to applying them in general. However, for autonomy, learning or learned behavior may become a significant system driver. Thus, artificial neural networks are being evaluated as components in fully autonomous and teleautonomous systems. Feed- forward networks may be trained to perform adaptive signal processing, pattern recognition, data fusion, and function approximation -- as in control subsystems. Certain components of particular autonomous systems become more amenable to implementation using a neural net due to a match between the net's attributes and desired attributes of the system component. Criteria have been developed for distinguishing such applications and then implementing them. The success of hardware implementation is a crucial part of this application evaluation process. Three basic applications of neural nets -- autoassociation, classification, and function approximation -- are used to exemplify this process and to highlight procedures that are followed during the requirements, design, and implementation phases. This paper assumes some familiarity with basic neural network terminology and concentrates upon the use of different neural network types while citing references that cover the underlying mathematics and related research.

  7. Microtubules, polarity and vertebrate neural tube morphogenesis.

    Science.gov (United States)

    Cearns, Michael D; Escuin, Sarah; Alexandre, Paula; Greene, Nicholas D E; Copp, Andrew J

    2016-07-01

    Microtubules (MTs) are key cellular components, long known to participate in morphogenetic events that shape the developing embryo. However, the links between the cellular functions of MTs, their effects on cell shape and polarity, and their role in large-scale morphogenesis remain poorly understood. Here, these relationships were examined with respect to two strategies for generating the vertebrate neural tube: bending and closure of the mammalian neural plate; and cavitation of the teleost neural rod. The latter process has been compared with 'secondary' neurulation that generates the caudal spinal cord in mammals. MTs align along the apico-basal axis of the mammalian neuroepithelium early in neural tube closure, participating functionally in interkinetic nuclear migration, which indirectly impacts on cell shape. Whether MTs play other functional roles in mammalian neurulation remains unclear. In the zebrafish, MTs are important for defining the neural rod midline prior to its cavitation, both by localizing apical proteins at the tissue midline and by orienting cell division through a mirror-symmetric MT apparatus that helps to further define the medial localization of apical polarity proteins. Par proteins have been implicated in centrosome positioning in neuroepithelia as well as in the control of polarized morphogenetic movements in the neural rod. Understanding of MT functions during early nervous system development has so far been limited, partly by techniques that fail to distinguish 'cause' from 'effect'. Future developments will likely rely on novel ways to selectively impair MT function in order to investigate the roles they play.

  8. Research of The Deeper Neural Networks

    Directory of Open Access Journals (Sweden)

    Xiao You Rong

    2016-01-01

    Full Text Available Neural networks (NNs have powerful computational abilities and could be used in a variety of applications; however, training these networks is still a difficult problem. With different network structures, many neural models have been constructed. In this report, a deeper neural networks (DNNs architecture is proposed. The training algorithm of deeper neural network insides searching the global optimal point in the actual error surface. Before the training algorithm is designed, the error surface of the deeper neural network is analyzed from simple to complicated, and the features of the error surface is obtained. Based on these characters, the initialization method and training algorithm of DNNs is designed. For the initialization, a block-uniform design method is proposed which separates the error surface into some blocks and finds the optimal block using the uniform design method. For the training algorithm, the improved gradient-descent method is proposed which adds a penalty term into the cost function of the old gradient descent method. This algorithm makes the network have a great approximating ability and keeps the network state stable. All of these improve the practicality of the neural network.

  9. Recent Advances in Neural Recording Microsystems

    Directory of Open Access Journals (Sweden)

    Benoit Gosselin

    2011-04-01

    Full Text Available The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

  10. Sensory gating, inhibition control and gamma oscillations in the human somatosensory cortex

    OpenAIRE

    Chia-Hsiung Cheng; Chan, Pei-Ying S.; Niddam, David M.; Shang-Yueh Tsai; Shih-Chieh Hsu; Chia-Yih Liu

    2016-01-01

    Inhibiting the responses to irrelevant stimuli is an essential component of human cognitive function. Pre-attentive auditory sensory gating (SG), an attenuated neural activation to the second identical stimulus, has been found to be related to the performance of higher-hierarchical brain function. However, it remains unclear whether other cortical regions, such as somatosensory cortex, also possess similar characteristics, or if such a relationship is modality-specific. This study used magnet...

  11. The activity-dependent transcription factor NPAS4 regulates domain-specific inhibition

    OpenAIRE

    Bloodgood, Brenda L.; Sharma, Nikhil; Browne, Heidi Adlman; Trepman, Alissa Z.; Greenberg, Michael E.

    2013-01-01

    A heterogeneous population of inhibitory neurons controls the flow of information through a neural circuit1–3. Inhibitory synapses that form on pyramidal neuron dendrites modulate the summation of excitatory synaptic potentials4–6 and prevent the generation of dendritic calcium spikes7,8. Precisely timed somatic inhibition limits both the number of action potentials and the time window during which firing can occur8,9. The activity-dependent transcription factor NPAS4 regulates inhibitory syn...

  12. Impaired response inhibition and excess cortical thickness as candidate endophenotypes for trichotillomania

    DEFF Research Database (Denmark)

    Odlaug, Brian Lawrence; Chamberlain, Samuel R; Derbyshire, Katie L;

    2014-01-01

    Trichotillomania is characterized by repetitive pulling out of one's own hair. Impaired response inhibition has been identified in patients with trichotillomania, along with gray matter density changes in distributed neural regions including frontal cortex. The objective of this study was to...... evaluate impaired response inhibition and abnormal cortical morphology as candidate endophenotypes for the disorder. Subjects with trichotillomania (N = 12), unaffected first-degree relatives of these patients (N = 10), and healthy controls (N = 14), completed the Stop Signal Task (SST), a measure of...

  13. Neural correlates of rhythmic expectancy

    Directory of Open Access Journals (Sweden)

    Theodore P. Zanto

    2006-01-01

    Full Text Available Temporal expectancy is thought to play a fundamental role in the perception of rhythm. This review summarizes recent studies that investigated rhythmic expectancy by recording neuroelectric activity with high temporal resolution during the presentation of rhythmic patterns. Prior event-related brain potential (ERP studies have uncovered auditory evoked responses that reflect detection of onsets, offsets, sustains,and abrupt changes in acoustic properties such as frequency, intensity, and spectrum, in addition to indexing higher-order processes such as auditory sensory memory and the violation of expectancy. In our studies of rhythmic expectancy, we measured emitted responses - a type of ERP that occurs when an expected event is omitted from a regular series of stimulus events - in simple rhythms with temporal structures typical of music. Our observations suggest that middle-latency gamma band (20-60 Hz activity (GBA plays an essential role in auditory rhythm processing. Evoked (phase-locked GBA occurs in the presence of physically presented auditory events and reflects the degree of accent. Induced (non-phase-locked GBA reflects temporally precise expectancies for strongly and weakly accented events in sound patterns. Thus far, these findings support theories of rhythm perception that posit temporal expectancies generated by active neural processes.

  14. Neural architectures for stereo vision.

    Science.gov (United States)

    Parker, Andrew J; Smith, Jackson E T; Krug, Kristine

    2016-06-19

    Stereoscopic vision delivers a sense of depth based on binocular information but additionally acts as a mechanism for achieving correspondence between patterns arriving at the left and right eyes. We analyse quantitatively the cortical architecture for stereoscopic vision in two areas of macaque visual cortex. For primary visual cortex V1, the result is consistent with a module that is isotropic in cortical space with a diameter of at least 3 mm in surface extent. This implies that the module for stereo is larger than the repeat distance between ocular dominance columns in V1. By contrast, in the extrastriate cortical area V5/MT, which has a specialized architecture for stereo depth, the module for representation of stereo is about 1 mm in surface extent, so the representation of stereo in V5/MT is more compressed than V1 in terms of neural wiring of the neocortex. The surface extent estimated for stereo in V5/MT is consistent with measurements of its specialized domains for binocular disparity. Within V1, we suggest that long-range horizontal, anatomical connections form functional modules that serve both binocular and monocular pattern recognition: this common function may explain the distortion and disruption of monocular pattern vision observed in amblyopia.This article is part of the themed issue 'Vision in our three-dimensional world'. PMID:27269604

  15. Pattern Recognition Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Santaji Ghorpade

    2010-12-01

    Full Text Available Face Recognition has been identified as one of the attracting research areas and it has drawn the attention of many researchers due to its varying applications such as security systems, medical systems,entertainment, etc. Face recognition is the preferred mode of identification by humans: it is natural,robust and non-intrusive. A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else.Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor.In this paper we have developed and illustrated a recognition system for human faces using a novel Kohonen self-organizing map (SOM or Self-Organizing Feature Map (SOFM based retrieval system.SOM has good feature extracting property due to its topological ordering. The Facial Analytics results for the 400 images of AT&T database reflects that the face recognition rate using one of the neural network algorithm SOM is 85.5% for 40 persons.

  16. Backward semantic inhibition in toddlers

    OpenAIRE

    Chow, J.; Aimola Davies, AM; Fuentes, LJ; Plunkett, KR

    2016-01-01

    Attention-switching is a crucial ability required in our everyday life, from toddlerhood to adulthood. In adults, shifting attention from one word (e.g., dog) to another (e.g., sea) results in backward semantic inhibition, i.e., the inhibition of the initial word (dog). This study examines whether attention-switching is accompanied by backward semantic inhibition in toddlers using the preferential looking paradigm. The findings demonstrate that a backward inhibitory mechanism operates during ...

  17. Role of neural NO synthase (nNOS uncoupling in the dysfunctional nitrergic vasorelaxation of penile arteries from insulin-resistant obese Zucker rats.

    Directory of Open Access Journals (Sweden)

    Ana Sánchez

    Full Text Available OBJECTIVE: Erectile dysfunction (ED is considered as an early sign of vascular disease due to its high prevalence in patients with cardiovascular risk factors. Endothelial and neural dysfunction involving nitric oxide (NO are usually implicated in the pathophysiology of the diabetic ED, but the underlying mechanisms are unclear. The present study assessed the role of oxidative stress in the dysfunctional neural vasodilator responses of penile arteries in the obese Zucker rat (OZR, an experimental model of metabolic syndrome/prediabetes. METHODS AND RESULTS: Electrical field stimulation (EFS under non-adrenergic non-cholinergic (NANC conditions evoked relaxations that were significantly reduced in penile arteries of OZR compared with those of lean Zucker rats (LZR. Blockade of NO synthase (NOS inhibited neural relaxations in both LZR and OZR, while saturating concentrations of the NOS substrate L-arginine reversed the inhibition and restored relaxations in OZR to levels in arteries from LZR. nNOS expression was unchanged in arteries from OZR compared to LZR and nNOS selective inhibition decreased the EFS relaxations in LZR but not in OZR, while endothelium removal did not alter these responses in either strain. Superoxide anion production and nitro-tyrosine immunostaining were elevated in the erectile tissue from OZR. Treatment with the NADPH oxidase inhibitor apocynin or acute incubation with the NOS cofactor tetrahydrobiopterin (BH4 restored neural relaxations in OZR to levels in control arteries, while inhibition of the enzyme of BH4 synthesis GTP-cyclohydrolase (GCH reduced neural relaxations in arteries from LZR but not OZR. The NO donor SNAP induced decreases in intracellular calcium that were impaired in arteries from OZR compared to controls. CONCLUSIONS: The present study demonstrates nitrergic dysfunction and impaired neural NO signalling due to oxidative stress and nNOS uncoupling in penile arteries under conditions of insulin

  18. Neural signal transduction aided by noise in multisynaptic excitatory and inhibitory pathways with saturation

    Science.gov (United States)

    Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek

    2011-08-01

    We study the stochastic resonance phenomenon in saturating dynamical models of neural signal transduction, at the synaptic stage, wherein the noise in multipathways enhances the processing of neuronal information integrated by excitatory and inhibitory synaptic currents. For an excitatory synaptic pathway, the additive intervention of an inhibitory pathway reduces the stochastic resonance effect. However, as the number of synaptic pathways increases, the signal transduction is greatly improved for parallel multipathways that feature both excitation and inhibition. The obtained results lead us to the realization that the collective property of inhibitory synapses assists neural signal transmission, and a parallel array of neurons can enhance their responses to multiple synaptic currents by adjusting the contributions of excitatory and inhibitory currents.

  19. Neural circuitry underlying the regulation of conditioned fear and its relation to extinction.

    Science.gov (United States)

    Delgado, Mauricio R; Nearing, Katherine I; Ledoux, Joseph E; Phelps, Elizabeth A

    2008-09-11

    Recent efforts to translate basic research to the treatment of clinical disorders have led to a growing interest in exploring mechanisms for diminishing fear. This research has emphasized two approaches: extinction of conditioned fear, examined across species; and cognitive emotion regulation, unique to humans. Here, we sought to examine the similarities and differences in the neural mechanisms underlying these two paradigms for diminishing fear. Using an emotion regulation strategy, we examine the neural mechanisms of regulating conditioned fear using fMRI and compare the resulting activation pattern with that observed during classic extinction. Our results suggest that the lateral PFC regions engaged by cognitive emotion regulation strategies may influence the amygdala, diminishing fear through similar vmPFC connections that are thought to inhibit the amygdala during extinction. These findings further suggest that humans may have developed complex cognition that can aid in regulating emotional responses while utilizing phylogenetically shared mechanisms of extinction.

  20. The neural ring: an algebraic tool for analyzing the intrinsic structure of neural codes.

    Science.gov (United States)

    Curto, Carina; Itskov, Vladimir; Veliz-Cuba, Alan; Youngs, Nora

    2013-09-01

    Neurons in the brain represent external stimuli via neural codes. These codes often arise from stereotyped stimulus-response maps, associating to each neuron a convex receptive field. An important problem confronted by the brain is to infer properties of a represented stimulus space without knowledge of the receptive fields, using only the intrinsic structure of the neural code. How does the brain do this? To address this question, it is important to determine what stimulus space features can--in principle--be extracted from neural codes. This motivates us to define the neural ring and a related neural ideal, algebraic objects that encode the full combinatorial data of a neural code. Our main finding is that these objects can be expressed in a "canonical form" that directly translates to a minimal description of the receptive field structure intrinsic to the code. We also find connections to Stanley-Reisner rings, and use ideas similar to those in the theory of monomial ideals to obtain an algorithm for computing the primary decomposition of pseudo-monomial ideals. This allows us to algorithmically extract the canonical form associated to any neural code, providing the groundwork for inferring stimulus space features from neural activity alone.

  1. Neural transcription factors bias cleavage stage blastomeres to give rise to neural ectoderm.

    Science.gov (United States)

    Gaur, Shailly; Mandelbaum, Max; Herold, Mona; Majumdar, Himani Datta; Neilson, Karen M; Maynard, Thomas M; Mood, Kathy; Daar, Ira O; Moody, Sally A

    2016-06-01

    The decision by embryonic ectoderm to give rise to epidermal versus neural derivatives is the result of signaling events during blastula and gastrula stages. However, there also is evidence in Xenopus that cleavage stage blastomeres contain maternally derived molecules that bias them toward a neural fate. We used a blastomere explant culture assay to test whether maternally deposited transcription factors bias 16-cell blastomere precursors of epidermal or neural ectoderm to express early zygotic neural genes in the absence of gastrulation interactions or exogenously supplied signaling factors. We found that Foxd4l1, Zic2, Gmnn, and Sox11 each induced explants made from ventral, epidermis-producing blastomeres to express early neural genes, and that at least some of the Foxd4l1 and Zic2 activities are required at cleavage stages. Similarly, providing extra Foxd4l1 or Zic2 to explants made from dorsal, neural plate-producing blastomeres significantly increased the expression of early neural genes, whereas knocking down either significantly reduced them. These results show that maternally delivered transcription factors bias cleavage stage blastomeres to a neural fate. We demonstrate that mouse and human homologs of Foxd4l1 have similar functional domains compared to the frog protein, as well as conserved transcriptional activities when expressed in Xenopus embryos and blastomere explants. genesis 54:334-349, 2016. © 2016 Wiley Periodicals, Inc. PMID:27092474

  2. FGF signalling regulates chromatin organisation during neural differentiation via mechanisms that can be uncoupled from transcription.

    Directory of Open Access Journals (Sweden)

    Nishal S Patel

    Full Text Available Changes in higher order chromatin organisation have been linked to transcriptional regulation; however, little is known about how such organisation alters during embryonic development or how it is regulated by extrinsic signals. Here we analyse changes in chromatin organisation as neural differentiation progresses, exploiting the clear spatial separation of the temporal events of differentiation along the elongating body axis of the mouse embryo. Combining fluorescence in situ hybridisation with super-resolution structured illumination microscopy, we show that chromatin around key differentiation gene loci Pax6 and Irx3 undergoes both decompaction and displacement towards the nuclear centre coincident with transcriptional onset. Conversely, down-regulation of Fgf8 as neural differentiation commences correlates with a more peripheral nuclear position of this locus. During normal neural differentiation, fibroblast growth factor (FGF signalling is repressed by retinoic acid, and this vitamin A derivative is further required for transcription of neural genes. We show here that exposure to retinoic acid or inhibition of FGF signalling promotes precocious decompaction and central nuclear positioning of differentiation gene loci. Using the Raldh2 mutant as a model for retinoid deficiency, we further find that such changes in higher order chromatin organisation are dependent on retinoid signalling. In this retinoid deficient condition, FGF signalling persists ectopically in the elongating body, and importantly, we find that inhibiting FGF receptor (FGFR signalling in Raldh2-/- embryos does not rescue differentiation gene transcription, but does elicit both chromatin decompaction and nuclear position change. These findings demonstrate that regulation of higher order chromatin organisation during differentiation in the embryo can be uncoupled from the machinery that promotes transcription and, for the first time, identify FGF as an extrinsic signal that

  3. Implantable neurotechnologies: a review of integrated circuit neural amplifiers.

    Science.gov (United States)

    Ng, Kian Ann; Greenwald, Elliot; Xu, Yong Ping; Thakor, Nitish V

    2016-01-01

    Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

  4. Meditation reduces pain-related neural activity in the anterior cingulate cortex, insula, secondary somatosensory cortex, and thalamus.

    OpenAIRE

    Hiroki eNakata; Kiwako eSakamoto; Ryusuke eKakigi

    2014-01-01

    Recent studies have shown that meditation inhibits or relieves pain perception. To clarify the underlying mechanisms for this phenomenon, neuroimaging methods, such as functional magnetic resonance imaging (fMRI), and neurophysiological methods, such as magnetoencephalography (MEG) and electroencephalography (EEG), have been used. However, it has been difficult to interpret the results, because there is some paradoxical evidence. For example, some studies reported increased neural response...

  5. Phenothiourea sensitizes zebrafish cranial neural crest and extraocular muscle development to changes in retinoic acid and IGF signaling.

    Directory of Open Access Journals (Sweden)

    Brenda L Bohnsack

    Full Text Available 1-Phenyl 2-thiourea (PTU is a tyrosinase inhibitor commonly used to block pigmentation and aid visualization of zebrafish development. At the standard concentration of 0.003% (200 µM, PTU inhibits melanogenesis and reportedly has minimal other effects on zebrafish embryogenesis. We found that 0.003% PTU altered retinoic acid and insulin-like growth factor (IGF regulation of neural crest and mesodermal components of craniofacial development. Reduction of retinoic acid synthesis by the pan-aldehyde dehydrogenase inhibitor diethylbenzaldehyde, only when combined with 0.003% PTU, resulted in extraocular muscle disorganization. PTU also decreased retinoic acid-induced teratogenic effects on pharyngeal arch and jaw cartilage despite morphologically normal appearing PTU-treated controls. Furthermore, 0.003% PTU in combination with inhibition of IGF signaling through either morpholino knockdown or pharmacologic inhibition of tyrosine kinase receptor phosphorylation, disrupted jaw development and extraocular muscle organization. PTU in and of itself inhibited neural crest development at higher concentrations (0.03% and had the greatest inhibitory effect when added prior to 22 hours post fertilization (hpf. Addition of 0.003% PTU between 4 and 20 hpf decreased thyroxine (T4 in thyroid follicles in the nasopharynx of 96 hpf embryos. Treatment with exogenous triiodothyronine (T3 and T4 improved, but did not completely rescue, PTU-induced neural crest defects. Thus, PTU should be used with caution when studying zebrafish embryogenesis as it alters the threshold of different signaling pathways important during craniofacial development. The effects of PTU on neural crest development are partially caused by thyroid hormone signaling.

  6. EDITORIAL: Focus on the neural interface Focus on the neural interface

    Science.gov (United States)

    Durand, Dominique M.

    2009-10-01

    The possibility of an effective connection between neural tissue and computers has inspired scientists and engineers to develop new ways of controlling and obtaining information from the nervous system. These applications range from `brain hacking' to neural control of artificial limbs with brain signals. Notwithstanding the significant advances in neural prosthetics in the last few decades and the success of some stimulation devices such as cochlear prosthesis, neurotechnology remains below its potential for restoring neural function in patients with nervous system disorders. One of the reasons for this limited impact can be found at the neural interface and close attention to the integration between electrodes and tissue should improve the possibility of successful outcomes. The neural interfaces research community consists of investigators working in areas such as deep brain stimulation, functional neuromuscular/electrical stimulation, auditory prostheses, cortical prostheses, neuromodulation, microelectrode array technology, brain-computer/machine interfaces. Following the success of previous neuroprostheses and neural interfaces workshops, funding (from NIH) was obtained to establish a biennial conference in the area of neural interfaces. The first Neural Interfaces Conference took place in Cleveland, OH in 2008 and several topics from this conference have been selected for publication in this special section of the Journal of Neural Engineering. Three `perspectives' review the areas of neural regeneration (Corredor and Goldberg), cochlear implants (O'Leary et al) and neural prostheses (Anderson). Seven articles focus on various aspects of neural interfacing. One of the most popular of these areas is the field of brain-computer interfaces. Fraser et al, report on a method to generate robust control with simple signal processing algorithms of signals obtained with electrodes implanted in the brain. One problem with implanted electrode arrays, however, is that

  7. Neural-networks-based Modelling and a Fuzzy Neural Networks Controller of MCFC

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Molten Carbonate Fuel Cells (MCFC) are produced with a highly efficient and clean power generation technology which will soon be widely utilized. The temperature characters of MCFC stack are briefly analyzed. A radial basis function (RBF) neural networks identification technology is applied to set up the temperature nonlinear model of MCFC stack, and the identification structure, algorithm and modeling training process are given in detail. A fuzzy controller of MCFC stack is designed. In order to improve its online control ability, a neural network trained by the I/O data of a fuzzy controller is designed. The neural networks can memorize and expand the inference rules of the fuzzy controller and substitute for the fuzzy controller to control MCFC stack online. A detailed design of the controller is given. The validity of MCFC stack modelling based on neural networks and the superior performance of the fuzzy neural networks controller are proved by Simulations.

  8. Stability analysis of discrete-time BAM neural networks based on standard neural network models

    Institute of Scientific and Technical Information of China (English)

    ZHANG Sen-lin; LIU Mei-qin

    2005-01-01

    To facilitate stability analysis of discrete-time bidirectional associative memory (BAM) neural networks, they were converted into novel neural network models, termed standard neural network models (SNNMs), which interconnect linear dynamic systems and bounded static nonlinear operators. By combining a number of different Lyapunov functionals with S-procedure, some useful criteria of global asymptotic stability and global exponential stability of the equilibrium points of SNNMs were derived. These stability conditions were formulated as linear matrix inequalities (LMIs). So global stability of the discrete-time BAM neural networks could be analyzed by using the stability results of the SNNMs. Compared to the existing stability analysis methods, the proposed approach is easy to implement, less conservative, and is applicable to other recurrent neural networks.

  9. Neural Net Safety Monitor Design

    Science.gov (United States)

    Larson, Richard R.

    2007-01-01

    The National Aeronautics and Space Administration (NASA) at the Dryden Flight Research Center (DFRC) has been conducting flight-test research using an F-15 aircraft (figure 1). This aircraft has been specially modified to interface a neural net (NN) controller as part of a single-string Airborne Research Test System (ARTS) computer with the existing quad-redundant flight control system (FCC) shown in figure 2. The NN commands are passed to FCC channels 2 and 4 and are cross channel data linked (CCDL) to the other computers as shown. Numerous types of fault-detection monitors exist in the FCC when the NN mode is engaged; these monitors would cause an automatic disengagement of the NN in the event of a triggering fault. Unfortunately, these monitors still may not prevent a possible NN hard-over command from coming through to the control laws. Therefore, an additional and unique safety monitor was designed for a single-string source that allows authority at maximum actuator rates but protects the pilot and structural loads against excessive g-limits in the case of a NN hard-over command input. This additional monitor resides in the FCCs and is executed before the control laws are computed. This presentation describes a floating limiter (FL) concept1 that was developed and successfully test-flown for this program (figure 3). The FL computes the rate of change of the NN commands that are input to the FCC from the ARTS. A window is created with upper and lower boundaries, which is constantly floating and trying to stay centered as the NN command rates are changing. The limiter works by only allowing the window to move at a much slower rate than those of the NN commands. Anywhere within the window, however, full rates are allowed. If a rate persists in one direction, it will eventually hit the boundary and be rate-limited to the floating limiter rate. When this happens, a persistent counter begins and after a limit is reached, a NN disengage command is generated. The

  10. Can Arousal Modulate Response Inhibition?

    Science.gov (United States)

    Weinbach, Noam; Kalanthroff, Eyal; Avnit, Amir; Henik, Avishai

    2015-01-01

    The goal of the present study was to examine if and how arousal can modulate response inhibition. Two competing hypotheses can be drawn from previous literature. One holds that alerting cues that elevate arousal should result in an impulsive response and therefore impair response inhibition. The other suggests that alerting enhances processing of…

  11. Forcing contact inhibition of locomotion

    OpenAIRE

    Roycroft, A.; Mayor, R.

    2015-01-01

    Contact inhibition of locomotion drives a variety of biological phenomenon, from cell dispersion to collective cell migration and cancer invasion. New imaging techniques have allowed contact inhibition of locomotion to be visualised in vivo for the first time, helping to elucidate some of the molecules and forces involved in this phenomenon.

  12. The equilibrium of neural firing: A mathematical theory

    Energy Technology Data Exchange (ETDEWEB)

    Lan, Sizhong, E-mail: lsz@fuyunresearch.org [Fuyun Research, Beijing, 100055 (China)

    2014-12-15

    Inspired by statistical thermodynamics, we presume that neuron system has equilibrium condition with respect to neural firing. We show that, even with dynamically changeable neural connections, it is inevitable for neural firing to evolve to equilibrium. To study the dynamics between neural firing and neural connections, we propose an extended communication system where noisy channel has the tendency towards fixed point, implying that neural connections are always attracted into fixed points such that equilibrium can be reached. The extended communication system and its mathematics could be useful back in thermodynamics.

  13. Kernel Temporal Differences for Neural Decoding

    Directory of Open Access Journals (Sweden)

    Jihye Bae

    2015-01-01

    Full Text Available We study the feasibility and capability of the kernel temporal difference (KTD(λ algorithm for neural decoding. KTD(λ is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm’s convergence can be guaranteed for policy evaluation. The algorithm’s nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement. KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey’s neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm’s capabilities in reinforcement learning brain machine interfaces.

  14. Migrating into Genomics with the Neural Crest

    Directory of Open Access Journals (Sweden)

    Marianne E. Bronner

    2014-01-01

    Full Text Available Neural crest cells are a fascinating embryonic cell type, unique to vertebrates, which arise within the central nervous system but emigrate soon after its formation and migrate to numerous and sometimes distant locations in the periphery. Following their migratory phase, they differentiate into diverse derivatives ranging from peripheral neurons and glia to skin melanocytes and craniofacial cartilage and bone. The molecular underpinnings underlying initial induction of prospective neural crest cells at the neural plate border to their migration and differentiation have been modeled in the form of a putative gene regulatory network. This review describes experiments performed in my laboratory in the past few years aimed to test and elaborate this gene regulatory network from both an embryonic and evolutionary perspective. The rapid advances in genomic technology in the last decade have greatly expanded our knowledge of important transcriptional inputs and epigenetic influences on neural crest development. The results reveal new players and new connections in the neural crest gene regulatory network and suggest that it has an ancient origin at the base of the vertebrate tree.

  15. Exploring neural code in natural environments

    Science.gov (United States)

    Nemenman, Ilya

    2010-03-01

    Neurons communicate by means of stereotyped pulses, called action potentials or spikes, and a central issue in systems neuroscience is to understand this neural coding. We study how sensory information is encoded in sequences of spikes, using motion detection in the blowfly as a model system. To emphasize the importance of the environment, and specifically the statistics of its dynamics, on shaping the animal's response, we perform experiments in an environment maximally similar to the natural one. This results in a number of unexpected, striking observations about the structure of the neural code in this system, typically unseen in simpler, more traditional experimental setups. First, the timing of spikes is important with a precision roughly two orders of magnitude greater than the temporal dynamics of the stimulus, which is behaviorally controlled in the natural settings. Second, the fly goes a long way to utilize the redundancy in the stimulus in order to optimize the neural code and encode efficiently more refined features than would be possible otherwise, providing sufficient information about the stimulus in time for behavioral decision making. This implies that the neural code, even in low-level vision, may be significantly context (that is, environment and behavior) dependent. The presentation is based on: I Nemenman, GD Lewen, W Bialek, RR de Ruyter van Steveninck. Neural Coding of Natural Stimuli: Information at Sub-Millisecond Resolution. PLoS Comput Biol 4 (3): e1000025, 2008.

  16. Neural network segmentation of magnetic resonance images

    Science.gov (United States)

    Frederick, Blaise

    1990-07-01

    Neural networks are well adapted to the task of grouping input patterns into subsets which share some similarity. Moreover once trained they can generalize their classification rules to classify new data sets. Sets of pixel intensities from magnetic resonance (MR) images provide a natural input to a neural network by varying imaging parameters MR images can reflect various independent physical parameters of tissues in their pixel intensities. A neural net can then be trained to classify physically similar tissue types based on sets of pixel intensities resulting from different imaging studies on the same subject. A neural network classifier for image segmentation was implemented on a Sun 4/60 and was tested on the task of classifying tissues of canine head MR images. Four images of a transaxial slice with different imaging sequences were taken as input to the network (three spin-echo images and an inversion recovery image). The training set consisted of 691 representative samples of gray matter white matter cerebrospinal fluid bone and muscle preclassified by a neuroscientist. The network was trained using a fast backpropagation algorithm to derive the decision criteria to classify any location in the image by its pixel intensities and the image was subsequently segmented by the classifier. The classifier''s performance was evaluated as a function of network size number of network layers and length of training. A single layer neural network performed quite well at

  17. Using neural networks to describe tracer correlations

    Directory of Open Access Journals (Sweden)

    D. J. Lary

    2004-01-01

    Full Text Available Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and methane volume mixing ratio (v.m.r.. In this study a neural network using Quickprop learning and one hidden layer with eight nodes was able to reproduce the CH4-N2O correlation with a correlation coefficient between simulated and training values of 0.9995. Such an accurate representation of tracer-tracer correlations allows more use to be made of long-term datasets to constrain chemical models. Such as the dataset from the Halogen Occultation Experiment (HALOE which has continuously observed CH4  (but not N2O from 1991 till the present. The neural network Fortran code used is available for download.

  18. Neural crest: The fourth germ layer

    Directory of Open Access Journals (Sweden)

    K Shyamala

    2015-01-01

    Full Text Available The neural crest cells (NCCs, a transient group of cells that emerges from the dorsal aspect of the neural tube during early vertebrate development has been a fascinating group of cells because of its multipotency, long range migration through embryo and its capacity to generate a prodigious number of differentiated cell types. For these reasons, although derived from the ectoderm, the neural crest (NC has been called the fourth germ layer. The non neural ectoderm, the neural plate and the underlying mesoderm are needed for the induction and formation of NC cells. Once formed, NC cells start migrating as a wave of cells, moving away from the neuroepithelium and quickly splitting into distinct streams. These migrating NCCs home in to different regions and give rise to plethora of tissues. Umpteen number of signaling molecules are essential for formation, epithelial mesenchymal transition, delamination, migration and localization of NCC. Authors believe that a clear understanding of steps and signals involved in NC formation, migration, etc., may help in understanding the pathogenesis behind cancer metastasis and many other diseases. Hence, we have taken this review to discuss the various aspects of the NC cells.

  19. Embryonic stem cell neurogenesis and neural specification.

    Science.gov (United States)

    Germain, Noélle; Banda, Erin; Grabel, Laura

    2010-10-15

    The prospect of using embryonic stem cell (ESC)-derived neural progenitors and neurons to treat neurological disorders has led to great interest in defining the conditions that guide the differentiation of ESCs, and more recently induced pluripotent stem cells (iPSCs), into neural stem cells (NSCs) and a variety of neuronal and glial subtypes. Over the past decade, researchers have looked to the embryo to guide these studies, applying what we know about the signaling events that direct neural specification during development. This has led to the design of a number of protocols that successfully promote ESC neurogenesis, terminating with the production of neurons and glia with diverse regional addresses and functional properties. These protocols demonstrate that ESCs undergo neural specification in two, three, and four dimensions, mimicking the cell-cell interactions, patterning, and timing that characterizes the in vivo process. We therefore propose that these in vitro systems can be used to examine the molecular regulation of neural specification. PMID:20589755

  20. Weight discretization paradigm for optical neural networks

    Science.gov (United States)

    Fiesler, Emile; Choudry, Amar; Caulfield, H. John

    1990-08-01

    Neural networks are a primary candidate architecture for optical computing. One of the major problems in using neural networks for optical computers is that the information holders: the interconnection strengths (or weights) are normally real valued (continuous), whereas optics (light) is only capable of representing a few distinguishable intensity levels (discrete). In this paper a weight discretization paradigm is presented for back(ward error) propagation neural networks which can work with a very limited number of discretization levels. The number of interconnections in a (fully connected) neural network grows quadratically with the number of neurons of the network. Optics can handle a large number of interconnections because of the fact that light beams do not interfere with each other. A vast amount of light beams can therefore be used per unit of area. However the number of different values one can represent in a light beam is very limited. A flexible, portable (machine independent) neural network software package which is capable of weight discretization, is presented. The development of the software and some experiments have been done on personal computers. The major part of the testing, which requires a lot of computation, has been done using a CRAY X-MP/24 super computer.