WorldWideScience

Sample records for cd99 inhibits neural

  1. Endothelial CD99 signals through soluble adenylyl cyclase and PKA to regulate leukocyte transendothelial migration

    Science.gov (United States)

    Watson, Richard L.; Buck, Jochen; Levin, Lonny R.; Winger, Ryan C.; Wang, Jing; Arase, Hisashi

    2015-01-01

    CD99 is a critical regulator of leukocyte transendothelial migration (TEM). How CD99 signals during this process remains unknown. We show that during TEM, endothelial cell (EC) CD99 activates protein kinase A (PKA) via a signaling complex formed with the lysine-rich juxtamembrane cytoplasmic tail of CD99, the A-kinase anchoring protein ezrin, and soluble adenylyl cyclase (sAC). PKA then stimulates membrane trafficking from the lateral border recycling compartment to sites of TEM, facilitating the passage of leukocytes across the endothelium. Pharmacologic or genetic inhibition of EC sAC or PKA, like CD99 blockade, arrests neutrophils and monocytes partway through EC junctions, in vitro and in vivo, without affecting leukocyte adhesion or the expression of relevant cellular adhesion molecules. This is the first description of the CD99 signaling pathway in TEM as well as the first demonstration of a role for sAC in leukocyte TEM. PMID:26101266

  2. CD99 triggering induces methuosis of Ewing sarcoma cells through IGF-1R/RAS/Rac1 signaling.

    Science.gov (United States)

    Manara, Maria Cristina; Terracciano, Mario; Mancarella, Caterina; Sciandra, Marika; Guerzoni, Clara; Pasello, Michela; Grilli, Andrea; Zini, Nicoletta; Picci, Piero; Colombo, Mario P; Morrione, Andrea; Scotlandi, Katia

    2016-11-29

    CD99 is a cell surface molecule that has emerged as a novel target for Ewing sarcoma (EWS), an aggressive pediatric bone cancer. This report provides the first evidence of methuosis in EWS, a non-apoptotic form of cell death induced by an antibody directed against the CD99 molecule. Upon mAb triggering, CD99 induces an IGF-1R/RAS/Rac1 complex, which is internalized into RAB5-positive endocytic vacuoles. This complex is then dissociated, with the IGF-1R recycling to the cell membrane while CD99 and RAS/Rac1 are sorted into immature LAMP-1-positive vacuoles, whose excessive accumulation provokes methuosis. This process, which is not detected in CD99-expressing normal mesenchymal cells, is inhibited by disruption of the IGF-1R signaling, whereas enhanced by IGF-1 stimulation. Induction of IGF-1R/RAS/Rac1 was also observed in the EWS xenografts that respond to anti-CD99 mAb, further supporting the role of the IGF/RAS/Rac1 axis in the hyperstimulation of macropinocytosis and selective death of EWS cells. Thus, we describe a vulnerability of EWS cells, including those resistant to standard chemotherapy, to a treatment with anti-CD99 mAb, which requires IGF-1R/RAS signaling but bypasses the need for their direct targeting. Overall, we propose CD99 targeting as new opportunity to treat EWS patients resistant to canonical apoptosis-inducing agents.

  3. CD99 at the crossroads of physiology and pathology.

    Science.gov (United States)

    Pasello, Michela; Manara, Maria Cristina; Scotlandi, Katia

    2018-03-01

    CD99 is a cell surface protein with unique features and only partly defined mechanisms of action. This molecule is involved in crucial biological processes, including cell adhesion, migration, death, differentiation and diapedesis, and it influences processes associated with inflammation, immune responses and cancer. CD99 is frequently overexpressed in many types of tumors, particularly pediatric tumors including Ewing sarcoma and specific subtypes of leukemia. Engagement of CD99 induces the death of malignant cells through non-conventional mechanisms. In Ewing sarcoma, triggering of CD99 by specific monoclonal antibodies activates hyperstimulation of micropinocytosis and leads to cancer cells killing through a caspase-independent, non-apoptotic pathway resembling methuosis. This process is characterized by extreme accumulation of vacuoles in the cytoplasmic space, which compromises cell viability, requires the activation of RAS-Rac1 downstream signaling and appears to be rather specific for tumor cells. In addition, anti-CD99 monoclonal antibodies exhibit antitumor activities in xenografts in the absence of immune effector cells or complement proteins. Overall, these data establish CD99 as a new opportunity to treat patients with high expression of CD99, particularly those that are resistant to canonical apoptosis-inducing agents.

  4. Optimal Decision Making in Neural Inhibition Models

    Science.gov (United States)

    van Ravenzwaaij, Don; van der Maas, Han L. J.; Wagenmakers, Eric-Jan

    2012-01-01

    In their influential "Psychological Review" article, Bogacz, Brown, Moehlis, Holmes, and Cohen (2006) discussed optimal decision making as accomplished by the drift diffusion model (DDM). The authors showed that neural inhibition models, such as the leaky competing accumulator model (LCA) and the feedforward inhibition model (FFI), can mimic the…

  5. Optimal decision making in neural inhibition models

    NARCIS (Netherlands)

    van Ravenzwaaij, D.; van der Maas, H.L.J.; Wagenmakers, E.-J.

    2012-01-01

    In their influential Psychological Review article, Bogacz, Brown, Moehlis, Holmes, and Cohen (2006) discussed optimal decision making as accomplished by the drift diffusion model (DDM). The authors showed that neural inhibition models, such as the leaky competing accumulator model (LCA) and the

  6. 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.

  7. Neural synchrony during response production and inhibition.

    Directory of Open Access Journals (Sweden)

    Viktor Müller

    Full Text Available Inhibition of irrelevant information (conflict monitoring and/or of prepotent actions is an essential component of adaptive self-organized behavior. Neural dynamics underlying these functions has been studied in humans using event-related brain potentials (ERPs elicited in Go/NoGo tasks that require a speeded motor response to the Go stimuli and withholding a prepotent response when a NoGo stimulus is presented. However, averaged ERP waveforms provide only limited information about the neuronal mechanisms underlying stimulus processing, motor preparation, and response production or inhibition. In this study, we examine the cortical representation of conflict monitoring and response inhibition using time-frequency analysis of electroencephalographic (EEG recordings during continuous performance Go/NoGo task in 50 young adult females. We hypothesized that response inhibition would be associated with a transient boost in both temporal and spatial synchronization of prefrontal cortical activity, consistent with the role of the anterior cingulate and lateral prefrontal cortices in cognitive control. Overall, phase synchronization across trials measured by Phase Locking Index and phase synchronization between electrode sites measured by Phase Coherence were the highest in the Go and NoGo conditions, intermediate in the Warning condition, and the lowest under Neutral condition. The NoGo condition was characterized by significantly higher fronto-central synchronization in the 300-600 ms window, whereas in the Go condition, delta- and theta-band synchronization was higher in centro-parietal regions in the first 300 ms after the stimulus onset. The present findings suggest that response production and inhibition is supported by dynamic functional networks characterized by distinct patterns of temporal and spatial synchronization of brain oscillations.

  8. Neural inhibition during maximal eccentric and concentric quadriceps contraction: effects of resistance training

    DEFF Research Database (Denmark)

    Aagaard, Per; Simonsen, E.B.; Andersen, J.L.

    2000-01-01

    neuromuscular activation, muscle strength, neural efferent drive, eccentric activation deficiency, force inhibition......neuromuscular activation, muscle strength, neural efferent drive, eccentric activation deficiency, force inhibition...

  9. CD99 is upregulated in placenta and astrocytomas with a differential subcellular distribution according to the malignancy stage.

    Science.gov (United States)

    Úrias, Ursula; Marie, Suely K N; Uno, Miyuki; da Silva, Roseli; Evagelinellis, Mariá M; Caballero, Otavia L; Stevenson, Brian J; Silva, Wilson A; Simpson, Andrew J; Oba-Shinjo, Sueli M

    2014-08-01

    In the present study, we searched for genes highly expressed in placenta and that could contribute to the establishment and maintenance of a malignant phenotype in different types of tumours, and in astrocytomas in particular. We employed a strategy based on the integration of in silico data from previously generated massively parallel signature sequencing and public serial analysis of gene expression databases. Among 12 selected genes, CD99 exhibited the highest relative mRNA expression in GBM compared to non-neoplastic brain tissues. In a larger cohort of astrocytic tumours, we further demonstrated increased CD99 expression in all malignant grades, with GBMs showing the highest values. These findings were confirmed at the protein level by Western blotting and immunohistochemistry. Additionally, we demonstrated the CD99 localisation profile in astrocytic tumours. Interestingly, CD99 expression was confined to the cytoplasm or membrane in more malignant astrocytomas, in contrast to non-neoplastic brain tissue or non-infiltrative pilocytic astrocytoma, which showed no obvious staining in these structures. Comparison of three GBM cell lines revealed higher CD99 expression at the membrane and higher migratory capacity in the A172 and U87MG lines, but lower CD99 expression and no migratory ability in the T98 line. Knocking down CD99 expression by siRNA decreased significantly the migration of both cell lines. These integrated CD99 gene and protein expression results suggest that CD99 expression in astrocytomas of different malignant grades might contribute to the infiltrative ability and support the importance of CD99 as a potential target to reduce infiltrative astrocytoma capacity in migration and invasion.

  10. Inhibition delay increases neural network capacity through Stirling transform

    Science.gov (United States)

    Nogaret, Alain; King, Alastair

    2018-03-01

    Inhibitory neural networks are found to encode high volumes of information through delayed inhibition. We show that inhibition delay increases storage capacity through a Stirling transform of the minimum capacity which stabilizes locally coherent oscillations. We obtain both the exact and asymptotic formulas for the total number of dynamic attractors. Our results predict a (ln2) -N-fold increase in capacity for an N -neuron network and demonstrate high-density associative memories which host a maximum number of oscillations in analog neural devices.

  11. 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.

  12. CD99 triggering induces methuosis of Ewing sarcoma cells through IGF-1R/RAS/Rac1 signaling

    OpenAIRE

    Manara, Maria Cristina; Terracciano, Mario; Mancarella, Caterina; Sciandra, Marika; Guerzoni, Clara; Pasello, Michela; Grilli, Andrea; Zini, Nicoletta; Picci, Piero; Colombo, Mario P.; Morrione, Andrea; Scotlandi, Katia

    2016-01-01

    CD99 is a cell surface molecule that has emerged as a novel target for Ewing sarcoma (EWS), an aggressive pediatric bone cancer. This report provides the first evidence of methuosis in EWS, a non-apoptotic form of cell death induced by an antibody directed against the CD99 molecule. Upon mAb triggering, CD99 induces an IGF-1R/RAS/Rac1 complex, which is internalized into RAB5-positive endocytic vacuoles. This complex is then dissociated, with the IGF-1R recycling to the cell membrane while CD9...

  13. 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.

  14. Common neural substrates for inhibition of spoken and manual responses.

    Science.gov (United States)

    Xue, Gui; Aron, Adam R; Poldrack, Russell A

    2008-08-01

    The inhibition of speech acts is a critical aspect of human executive control over thought and action, but its neural underpinnings are poorly understood. Using functional magnetic resonance imaging and the stop-signal paradigm, we examined the neural correlates of speech control in comparison to manual motor control. Initiation of a verbal response activated left inferior frontal cortex (IFC: Broca's area). Successful inhibition of speech (naming of letters or pseudowords) engaged a region of right IFC (including pars opercularis and anterior insular cortex) as well as presupplementary motor area (pre-SMA); these regions were also activated by successful inhibition of a hand response (i.e., a button press). Moreover, the speed with which subjects inhibited their responses, stop-signal reaction time, was significantly correlated between speech and manual inhibition tasks. These findings suggest a functional dissociation of left and right IFC in initiating versus inhibiting vocal responses, and that manual responses and speech acts share a common inhibitory mechanism localized in the right IFC and pre-SMA.

  15. Neural signature of behavioural inhibition in women with bulimia nervosa.

    Science.gov (United States)

    Skunde, Mandy; Walther, Stephan; Simon, Joe J; Wu, Mudan; Bendszus, Martin; Herzog, Wolfgang; Friederich, Hans-Christoph

    2016-08-01

    Impaired inhibitory control is considered a behavioural phenotype in patients with bulimia nervosa. However, the underlying neural correlates of impaired general and food-specific behavioural inhibition are largely unknown. Therefore, we investigated brain activation during the performance of behavioural inhibition to general and food-related stimuli in adults with bulimia nervosa. Women with bulimia and healthy control women underwent event-related fMRI while performing a general and a food-specific no-go task. We included 28 women with bulimia nervosa and 29 healthy control women in our study. On a neuronal level, we observed significant group differences in response to general no-go stimuli in women with bulimia nervosa with high symptom severity; compared with healthy controls, the patients showed reduced activation in the right sensorimotor area (postcentral gyrus, precentral gyrus) and right dorsal striatum (caudate nucleus, putamen). The present results are limited to adult women with bulimia nervosa. Furthermore, it remains unclear whether impaired behavioural inhibition in patients with this disorder are a cause or consequence of chronic illness. Our findings suggest that diminished frontostriatal brain activation in patients with bulimia nervosa contribute to the severity of binge eating symptoms. Gaining further insight into the neural mechanisms of behavioural inhibition problems in individuals with this disorder may inform brain-directed treatment approaches and the development of response inhibition training approaches to improve inhibitory control in patients with bulimia nervosa. The present study does not support greater behavioural and neural impairments to food-specific behavioural inhibition in these patients.

  16. Immune function genes CD99L2, JARID2 and TPO show association with autism spectrum disorder

    Directory of Open Access Journals (Sweden)

    Ramos Paula S

    2012-06-01

    Full Text Available Abstract Background A growing number of clinical and basic research studies have implicated immunological abnormalities as being associated with and potentially responsible for the cognitive and behavioral deficits seen in autism spectrum disorder (ASD children. Here we test the hypothesis that immune-related gene loci are associated with ASD. Findings We identified 2,012 genes of known immune-function via Ingenuity Pathway Analysis. Family-based tests of association were computed on the 22,904 single nucleotide polymorphisms (SNPs from the 2,012 immune-related genes on 1,510 trios available at the Autism Genetic Resource Exchange (AGRE repository. Several SNPs in immune-related genes remained statistically significantly associated with ASD after adjusting for multiple comparisons. Specifically, we observed significant associations in the CD99 molecule-like 2 region (CD99L2, rs11796490, P = 4.01 × 10-06, OR = 0.68 (0.58-0.80, in the jumonji AT rich interactive domain 2 (JARID2 gene (rs13193457, P = 2.71 × 10-06, OR = 0.61 (0.49-0.75, and in the thyroid peroxidase gene (TPO (rs1514687, P = 5.72 × 10-06, OR = 1.46 (1.24-1.72. Conclusions This study suggests that despite the lack of a general enrichment of SNPs in immune function genes in ASD children, several novel genes with known immune functions are associated with ASD.

  17. Determination of inhibition in the enzymatic hydrolysis of cellobiose using hybrid neural modeling

    Directory of Open Access Journals (Sweden)

    F. C. Corazza

    2005-03-01

    Full Text Available Neural networks and hybrid models were used to study substrate and product inhibition observed in the enzymatic hydrolysis of cellobiose at 40ºC, 50ºC and 55ºC, pH 4.8, using cellobiose solutions with or without the addition of exogenous glucose. Firstly, the initial velocity method and nonlinear fitting with StatisticaÒ were used to determine the kinetic parameters for either the uncompetitive or the competitive substrate inhibition model at a negligible product concentration and cellobiose from 0.4 to 2.0 g/L. Secondly, for six different models of substrate and product inhibitions and data for low to high cellobiose conversions in a batch reactor, neural networks were used for fitting the product inhibition parameter to the mass balance equations derived for each model. The two models found to be best were: 1 noncompetitive inhibition by substrate and competitive by product and 2 uncompetitive inhibition by substrate and competitive by product; however, these models’ correlation coefficients were quite close. To distinguish between them, hybrid models consisting of neural networks and first principle equations were used to select the best inhibition model based on the smallest norm observed, and the model with noncompetitive inhibition by substrate and competitive inhibition by product was shown to be the best predictor of cellobiose hydrolysis reactor behavior.

  18. The neural markers of an imminent failure of response inhibition

    NARCIS (Netherlands)

    Bengson, Jesse J.; Mangun, George R.; Mazaheri, Ali

    2012-01-01

    In his novel Ulysses, James Joyce wrote that mistakes are the "...portals of discovery". The present study investigated the pre-stimulus oscillatory EEG signatures of selective attention and motor preparation that predicted failures of overt response inhibition. We employed a trial-by-trial spatial

  19. Speaking Two Languages Enhances an Auditory but Not a Visual Neural Marker of Cognitive Inhibition

    Directory of Open Access Journals (Sweden)

    Mercedes Fernandez

    2014-09-01

    Full Text Available The purpose of the present study was to replicate and extend our original findings of enhanced neural inhibitory control in bilinguals. We compared English monolinguals to Spanish/English bilinguals on a non-linguistic, auditory Go/NoGo task while recording event-related brain potentials. New to this study was the visual Go/NoGo task, which we included to investigate whether enhanced neural inhibition in bilinguals extends from the auditory to the visual modality. Results confirmed our original findings and revealed greater inhibition in bilinguals compared to monolinguals. As predicted, compared to monolinguals, bilinguals showed increased N2 amplitude during the auditory NoGo trials, which required inhibitory control, but no differences during the Go trials, which required a behavioral response and no inhibition. Interestingly, during the visual Go/NoGo task, event related brain potentials did not distinguish the two groups, and behavioral responses were similar between the groups regardless of task modality. Thus, only auditory trials that required inhibitory control revealed between-group differences indicative of greater neural inhibition in bilinguals. These results show that experience-dependent neural changes associated with bilingualism are specific to the auditory modality and that the N2 event-related brain potential is a sensitive marker of this plasticity.

  20. The neural markers of an imminent failure of response inhibition.

    Science.gov (United States)

    Bengson, Jesse J; Mangun, George R; Mazaheri, Ali

    2012-01-16

    In his novel Ulysses, James Joyce wrote that mistakes are the "…portals of discovery". The present study investigated the pre-stimulus oscillatory EEG signatures of selective attention and motor preparation that predicted failures of overt response inhibition. We employed a trial-by-trial spatial cueing task using a go/no-go response paradigm with bilateral target stimuli. Subjects were required to covertly attend to the spatial location cued on each trial and respond to most of the number targets (go trials) at that location while withholding responses for one designated number (no-go trials). We analyzed the post-cue/pre-target spectral patterns comparing no-go trials in which a response occurred in error (False Alarms, FA) with trials in which participants correctly withheld a response (Correct Rejections, CR). We found that cue-induced occipital alpha (8-12 Hz) lateralization and inter-frequency anti-correlations between the motor beta (18-24 Hz) and pre-frontal theta (3-5 Hz) bands each independently predicted subsequent failures of response inhibition. Based on these findings, we infer that independent perceptual and motor mechanisms operate in parallel to contribute to failures of response inhibition. Copyright © 2011 Elsevier Inc. All rights reserved.

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

    International Nuclear Information System (INIS)

    Harrill, Joshua A.; Freudenrich, Theresa M.; Robinette, Brian L.; Mundy, William R.

    2011-01-01

    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

  2. Effects of modafinil on neural correlates of response inhibition in alcohol-dependent patients.

    Science.gov (United States)

    Schmaal, Lianne; Joos, Leen; Koeleman, Marte; Veltman, Dick J; van den Brink, Wim; Goudriaan, Anna E

    2013-02-01

    Impaired response inhibition is a key feature of patients with alcohol dependence. Improving impulse control is a promising target for the treatment of alcohol dependence. The pharmacologic agent modafinil enhances cognitive control functions in both healthy subjects and in patients with various psychiatric disorders. However, very little is known about the underlying neural correlates of improvements in response inhibition following modafinil. We conducted a randomized, double-blind, placebo-controlled, crossover study using functional magnetic resonance imaging with a stop signal task to examine effects of a single dose of modafinil (200 mg) on response inhibition and underlying neural correlates in abstinent alcohol-dependent patients (AD) (n = 16) and healthy control subjects (n = 16). Within the AD group modafinil administration improved response inhibition (reflected by the stop signal reaction time [SSRT]) in subjects with initial poor response inhibition, whereas response inhibition was diminished in better performing subjects. In AD patients with initial poor response inhibition, modafinil-induced SSRT improvement was accompanied by greater activation in the thalamus and supplementary motor area (SMA) and reduced connectivity between the thalamus and the primary motor cortex. In addition, the relationship between baseline response inhibition and modafinil-induced SSRT improvement was mediated by these changes in thalamus and SMA activation. These findings indicate that modafinil can improve response inhibition in alcohol-dependent patients through its effect on thalamus and SMA function but only in subjects with poor baseline response inhibition. Therefore, baseline levels of response inhibition should be taken into account when considering treatment with modafinil in AD. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  3. 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

  4. The response of early neural genes to FGF signaling or inhibition of BMP indicate the absence of a conserved neural induction module

    Directory of Open Access Journals (Sweden)

    Rogers Crystal D

    2011-12-01

    Full Text Available Abstract Background The molecular mechanism that initiates the formation of the vertebrate central nervous system has long been debated. Studies in Xenopus and mouse demonstrate that inhibition of BMP signaling is sufficient to induce neural tissue in explants or ES cells respectively, whereas studies in chick argue that instructive FGF signaling is also required for the expression of neural genes. Although additional signals may be involved in neural induction and patterning, here we focus on the roles of BMP inhibition and FGF8a. Results To address the question of necessity and sufficiency of BMP inhibition and FGF signaling, we compared the temporal expression of the five earliest genes expressed in the neuroectoderm and determined their requirements for induction at the onset of neural plate formation in Xenopus. Our results demonstrate that the onset and peak of expression of the genes vary and that they have different regulatory requirements and are therefore unlikely to share a conserved neural induction regulatory module. Even though all require inhibition of BMP for expression, some also require FGF signaling; expression of the early-onset pan-neural genes sox2 and foxd5α requires FGF signaling while other early genes, sox3, geminin and zicr1 are induced by BMP inhibition alone. Conclusions We demonstrate that BMP inhibition and FGF signaling induce neural genes independently of each other. Together our data indicate that although the spatiotemporal expression patterns of early neural genes are similar, the mechanisms involved in their expression are distinct and there are different signaling requirements for the expression of each gene.

  5. Neural correlates of working memory deficits and associations to response inhibition in obsessive compulsive disorder.

    Science.gov (United States)

    Heinzel, Stephan; Kaufmann, Christian; Grützmann, Rosa; Hummel, Robert; Klawohn, Julia; Riesel, Anja; Bey, Katharina; Lennertz, Leonhard; Wagner, Michael; Kathmann, Norbert

    2018-01-01

    Previous research in patients with obsessive-compulsive disorder (OCD) has indicated performance decrements in working memory (WM) and response inhibition. However, underlying neural mechanisms of WM deficits are not well understood to date, and empirical evidence for a proposed conceptual link to inhibition deficits is missing. We investigated WM performance in a numeric n-back task with four WM load conditions during functional Magnetic Resonance Imaging (fMRI) in 51 patients with OCD and 49 healthy control participants who were matched for age, sex, and education. Additionally, a stop signal task was performed outside the MRI scanner in a subsample. On the behavioral level, a significant WM load by group interaction was found for both accuracy (p neural correlates of a load-dependent WM decrement in OCD in the supplementary motor area (SMA) and the inferior parietal lobule (IPL). Within the OCD sample, SMA-activity as well as n-back performance were correlated with stop signal task performance. Results from behavioral and fMRI-analyses indicate a reduced WM load-dependent modulation of neural activity in OCD and suggest a common neural mechanism for inhibitory dysfunction and WM decrements in OCD.

  6. Anything goes? Regulation of the neural processes underlying response inhibition in TBI patients.

    Science.gov (United States)

    Moreno-López, Laura; Manktelow, Anne E; Sahakian, Barbara J; Menon, David K; Stamatakis, Emmanuel A

    2017-02-01

    Despite evidence for beneficial use of methylphenidate in response inhibition, no studies so far have investigated the effects of this drug in the neurobiology of inhibitory control in traumatic brain injury (TBI), even though impulsive behaviours are frequently reported in this patient group. We investigated the neural basis of response inhibition in a group of TBI patients using functional magnetic resonance imaging and a stop-signal paradigm. In a randomised double-blinded crossover study, the patients received either a single 30mg dose of methylphenidate or placebo and performed the stop-signal task. Activation in the right inferior frontal gyrus (RIFG), an area associated with response inhibition, was significantly lower in patients compared to healthy controls. Poor response inhibition in this group was associated with greater connectivity between the RIFG and a set of regions considered to be part of the default mode network (DMN), a finding that suggests the interplay between DMN and frontal executive networks maybe compromised. A single dose of methylphenidate rendered activity and connectivity profiles of the patients RIFG near normal. The results of this study indicate that the neural circuitry involved in response inhibition in TBI patients may be partially restored with methylphenidate. Given the known mechanisms of action of methylphenidate, the effect we observed may be due to increased dopamine and noradrenaline levels. Copyright © 2016 Elsevier B.V. and ECNP. All rights reserved.

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

    NARCIS (Netherlands)

    van Rooij, Daan; Hartman, Catharina A.; Mennes, Maarten; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Heslenfeld, Dirk; Faraone, Stephen V.; Buitelaar, Jan K.; Hoekstra, Pieter J.

    2015-01-01

    Introduction: Response inhibition is one of the executive functions impaired in attention-deficit/hyperactivity disorder (ADHD). Increasing evidence indicates that altered functional and structural neural connectivity are part of the neurobiological basis of ADHD. Here, we investigated if

  8. Distinct Neural Correlates for Two Types of Inhibition in Bilinguals: Response Inhibition versus Interference Suppression

    Science.gov (United States)

    Luk, Gigi; Anderson, John A. E.; Craik, Fergus I. M.; Grady, Cheryl; Bialystok, Ellen

    2010-01-01

    To examine the effects of bilingualism on cognitive control, we studied monolingual and bilingual young adults performing a flanker task with functional MRI. The trial types of primary interest for this report were incongruent and no-go trials, representing interference suppression and response inhibition, respectively. Response times were similar…

  9. The neural correlates of tic inhibition in Gilles de la Tourette syndrome.

    Science.gov (United States)

    Ganos, Christos; Kahl, Ursula; Brandt, Valerie; Schunke, Odette; Bäumer, Tobias; Thomalla, Götz; Roessner, Veit; Haggard, Patrick; Münchau, Alexander; Kühn, Simone

    2014-12-01

    Tics in Gilles de la Tourette syndrome (GTS) resemble fragments of normal motor behaviour but appear in an intrusive, repetitive and context-inappropriate manner. Although tics can be voluntarily inhibited on demand, the neural correlates of this process remain unclear. 14 GTS adults without relevant comorbidities participated in this study. First, tic severity and voluntary tic inhibitory capacity were evaluated outside the scanner. Second, patients were examined with resting state functional magnetic resonance imaging (RS-fMRI) in two states, free ticcing and voluntary tic inhibition. Local synchronization of spontaneous fMRI-signal was analysed with regional homogeneity (ReHo) and differences between both states (free ticcingtic inhibition) were contrasted. Clinical correlations of the resulting differential ReHo parameters between both states and clinical measures of tic frequency, voluntary tic inhibition and premonitory urges were also performed. ReHo of the left inferior frontal gyrus (IFG) was increased during voluntary tic inhibition compared to free ticcing. ReHo increases were positively correlated with participants׳ ability to inhibit their tics during scanning sessions but also outside the scanner. There was no correlation with ratings of premonitory urges. Voluntary tic inhibition is associated with increased ReHo of the left IFG. Premonitory urges are unrelated to this process. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. dNTP deficiency induced by HU via inhibiting ribonucleotide reductase affects neural tube development

    International Nuclear Information System (INIS)

    Guan, Zhen; Wang, Xiuwei; Dong, Yanting; Xu, Lin; Zhu, Zhiqiang; Wang, Jianhua; Zhang, Ting; Niu, Bo

    2015-01-01

    Highlights: • Murine NTDs were successfully induced by means of hydroxyurea (HU). • The impairment of dNTP was induced via inhibition of ribonucleotide reductase. • dNTP deficiency induced by HU caused defective DNA synthesis and repair. • Abnormal apoptosis and proliferation induced by HU affected neural tube development. - Abstract: Exposure to environmental toxic chemicals in utero during the neural tube development period can cause developmental disorders. To evaluate the disruption of neural tube development programming, the murine neural tube defects (NTDs) model was induced by interrupting folate metabolism using methotrexate in our previous study. The present study aimed to examine the effects of dNTP deficiency induced by hydroxyurea (HU), a specific ribonucleotide reductase (RNR) inhibitor, during murine neural tube development. Pregnant C57BL/6J mice were intraperitoneally injected with various doses of HU on gestation day (GD) 7.5, and the embryos were checked on GD 11.5. RNR activity and deoxynucleoside triphosphate (dNTP) levels were measured in the optimal dose. Additionally, DNA damage was examined by comet analysis and terminal deoxynucleotidyl transferase mediated dUTP nick end-labeling (TUNEL) assay. Cellular behaviors in NTDs embryos were evaluated with phosphorylation of histone H3 (PH-3) and caspase-3 using immunohistochemistry and western blot analysis. The results showed that NTDs were observed mostly with HU treatment at an optimal dose of 225 mg/kg b/w. RNR activity was inhibited and dNTP levels were decreased in HU-treated embryos with NTDs. Additionally, increased DNA damage, decreased proliferation, and increased caspase-3 were significant in NTDs embryos compared to the controls. Results indicated that HU induced murine NTDs model by disturbing dNTP metabolism and further led to the abnormal cell balance between proliferation and apoptosis

  11. Neural Differentiation Is Inhibited through HIF1α/β-Catenin Signaling in Embryoid Bodies

    Directory of Open Access Journals (Sweden)

    Josef Večeřa

    2017-01-01

    Full Text Available Extensive research in the field of stem cells and developmental biology has revealed evidence of the role of hypoxia as an important factor regulating self-renewal and differentiation. However, comprehensive information about the exact hypoxia-mediated regulatory mechanism of stem cell fate during early embryonic development is still missing. Using a model of embryoid bodies (EBs derived from murine embryonic stem cells (ESC, we here tried to encrypt the role of hypoxia-inducible factor 1α (HIF1α in neural fate during spontaneous differentiation. EBs derived from ESC with the ablated gene for HIF1α had abnormally increased neuronal characteristics during differentiation. An increased neural phenotype in Hif1α−/− EBs was accompanied by the disruption of β-catenin signaling together with the increased cytoplasmic degradation of β-catenin. The knock-in of Hif1α, as well as β-catenin ectopic overexpression in Hif1α−/− EBs, induced a reduction in neural markers to the levels observed in wild-type EBs. Interestingly, direct interaction between HIF1α and β-catenin was demonstrated by immunoprecipitation analysis of the nuclear fraction of wild-type EBs. Together, these results emphasize the regulatory role of HIF1α in β-catenin stabilization during spontaneous differentiation, which seems to be a crucial mechanism for the natural inhibition of premature neural differentiation.

  12. Neural Differentiation Is Inhibited through HIF1α/β-Catenin Signaling in Embryoid Bodies.

    Science.gov (United States)

    Večeřa, Josef; Kudová, Jana; Kučera, Jan; Kubala, Lukáš; Pacherník, Jiří

    2017-01-01

    Extensive research in the field of stem cells and developmental biology has revealed evidence of the role of hypoxia as an important factor regulating self-renewal and differentiation. However, comprehensive information about the exact hypoxia-mediated regulatory mechanism of stem cell fate during early embryonic development is still missing. Using a model of embryoid bodies (EBs) derived from murine embryonic stem cells (ESC), we here tried to encrypt the role of hypoxia-inducible factor 1 α (HIF1 α ) in neural fate during spontaneous differentiation. EBs derived from ESC with the ablated gene for HIF1 α had abnormally increased neuronal characteristics during differentiation. An increased neural phenotype in Hif1α -/- EBs was accompanied by the disruption of β -catenin signaling together with the increased cytoplasmic degradation of β -catenin. The knock-in of Hif1α , as well as β -catenin ectopic overexpression in Hif1α -/- EBs, induced a reduction in neural markers to the levels observed in wild-type EBs. Interestingly, direct interaction between HIF1 α and β -catenin was demonstrated by immunoprecipitation analysis of the nuclear fraction of wild-type EBs. Together, these results emphasize the regulatory role of HIF1 α in β -catenin stabilization during spontaneous differentiation, which seems to be a crucial mechanism for the natural inhibition of premature neural differentiation.

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

    International Nuclear Information System (INIS)

    Fujita, Yuko; Hiroyama, Masami; Sanbe, Atsushi; Yamauchi, Junji; Murase, Shoko; Tanoue, Akito

    2008-01-01

    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

  14. Neural correlates of response inhibition in pediatric bipolar disorder and attention deficit hyperactivity disorder.

    Science.gov (United States)

    Passarotti, Alessandra M; Sweeney, John A; Pavuluri, Mani N

    2010-01-30

    Impulsivity, inattention and poor behavioral inhibition are common deficits in pediatric bipolar disorder (PBD) and attention deficit hyperactivity disorder (ADHD). This study aimed to identify similarities and differences in the neural substrate of response inhibition deficits that are associated with these disorders. A functional magnetic resonance imaging (fMRI) study was conducted on 15 unmedicated PBD patients (Type I, manic/mixed), 11 unmedicated ADHD patients, and 15 healthy controls (HC) (mean age = 13.5 years; S.D. = 3.5). A response inhibition task examined the ability to inhibit a motor response to a target when a stop cue appeared shortly after. The PBD and ADHD groups did not differ on behavioral performance, although both groups were less accurate than the HC group. fMRI findings showed that for trials requiring response inhibition, the ADHD group, relative to the PBD and HC groups, demonstrated reduced activation in both ventrolateral (VLPFC) and dorsolateral (DLPFC) prefrontal cortex, and increased bilateral caudate activation compared with HC. The PBD group, relative to HC, showed decreased activation in the left VLPFC, at the junction of the inferior and middle frontal gyri, and in the right anterior cingulate cortex (ACC). Prefrontal dysfunction was observed in both the ADHD and PBD groups relative to HC, although it was more extensive and accompanied by subcortical overactivity in ADHD.

  15. Radial glial neural progenitors regulate nascent brain vascular network stabilization via inhibition of Wnt signaling.

    Directory of Open Access Journals (Sweden)

    Shang Ma

    Full Text Available The cerebral cortex performs complex cognitive functions at the expense of tremendous energy consumption. Blood vessels in the brain are known to form stereotypic patterns that facilitate efficient oxygen and nutrient delivery. Yet little is known about how vessel development in the brain is normally regulated. Radial glial neural progenitors are well known for their central role in orchestrating brain neurogenesis. Here we show that, in the late embryonic cortex, radial glial neural progenitors also play a key role in brain angiogenesis, by interacting with nascent blood vessels and regulating vessel stabilization via modulation of canonical Wnt signaling. We find that ablation of radial glia results in vessel regression, concomitant with ectopic activation of Wnt signaling in endothelial cells. Direct activation of Wnt signaling also results in similar vessel regression, while attenuation of Wnt signaling substantially suppresses regression. Radial glial ablation and ectopic Wnt pathway activation leads to elevated endothelial expression of matrix metalloproteinases, while inhibition of metalloproteinase activity significantly suppresses vessel regression. These results thus reveal a previously unrecognized role of radial glial progenitors in stabilizing nascent brain vascular network and provide novel insights into the molecular cascades through which target neural tissues regulate vessel stabilization and patterning during development and throughout life.

  16. Intrinsic lens potential of neural retina inhibited by Notch signaling as the cause of lens transdifferentiation.

    Science.gov (United States)

    Iida, Hideaki; Ishii, Yasuo; Kondoh, Hisato

    2017-01-15

    Embryonic neural retinas of avians produce lenses under spreading culture conditions. This phenomenon has been regarded as a paradigm of transdifferentiation due to the overt change in cell type. Here we elucidated the underlying mechanisms. Retina-to-lens transdifferentiation occurs in spreading cultures, suggesting that it is triggered by altered cell-cell interactions. Thus, we tested the involvement of Notch signaling based on its role in retinal neurogenesis. Starting from E8 retina, a small number of crystallin-expressing lens cells began to develop after 20 days in control spreading cultures. By contrast, addition of Notch signal inhibitors to cultures after day 2 strongly promoted lens development beginning at day 11, and a 10-fold increase in δ-crystallin expression level. After Notch signal inhibition, transcription factor genes that regulate the early stage of eye development, Prox1 and Pitx3, were sequentially activated. These observations indicate that the lens differentiation potential is intrinsic to the neural retina, and this potential is repressed by Notch signaling during normal embryogenesis. Therefore, Notch suppression leads to lens transdifferentiation by disinhibiting the neural retina-intrinsic program of lens development. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. High glucose environment inhibits cranial neural crest survival by activating excessive autophagy in the chick embryo

    Science.gov (United States)

    Wang, Xiao-Yu; Li, Shuai; Wang, Guang; Ma, Zheng-Lai; Chuai, Manli; Cao, Liu; Yang, Xuesong

    2015-01-01

    High glucose levels induced by maternal diabetes could lead to defects in neural crest development during embryogenesis, but the cellular mechanism is still not understood. In this study, we observed a defect in chick cranial skeleton, especially parietal bone development in the presence of high glucose levels, which is derived from cranial neural crest cells (CNCC). In early chick embryo, we found that inducing high glucose levels could inhibit the development of CNCC, however, cell proliferation was not significantly involved. Nevertheless, apoptotic CNCC increased in the presence of high levels of glucose. In addition, the expression of apoptosis and autophagy relevant genes were elevated by high glucose treatment. Next, the application of beads soaked in either an autophagy stimulator (Tunicamycin) or inhibitor (Hydroxychloroquine) functionally proved that autophagy was involved in regulating the production of CNCC in the presence of high glucose levels. Our observations suggest that the ERK pathway, rather than the mTOR pathway, most likely participates in mediating the autophagy induced by high glucose. Taken together, our observations indicated that exposure to high levels of glucose could inhibit the survival of CNCC by affecting cell apoptosis, which might result from the dysregulation of the autophagic process. PMID:26671447

  18. Attention Alters Neural Responses to Evocative Faces in Behaviorally Inhibited Adolescents

    Science.gov (United States)

    Pérez-Edgar, Koraly; Roberson-Nay, Roxann; Hardin, Michael G.; Poeth, Kaitlin; Guyer, Amanda E.; Nelson, Eric E.; McClure, Erin B.; Henderson, Heather A.; Fox, Nathan A.; Pine, Daniel S.; Ernst, Monique

    2007-01-01

    Behavioral inhibition (BI) is a risk factor for anxiety disorders. While the two constructs bear behavioral similarities, previous work has not extended these parallels to the neural level. This study examined amygdala reactivity during a task previously used with clinically anxious adolescents. Adolescents were selected for enduring patterns of BI or non-inhibition (BN). We examined amygdala response to evocative emotion faces in BI (N=10, mean 12.8 years) and BN (N=17, mean 12.5 years) adolescents while systematically manipulating attention. Analyses focused on amygdala response during subjective ratings of internal fear (constrained attention) and passive viewing (unconstrained attention) during the presentation of emotion faces (Happy, Angry, Fearful, and Neutral). BI adolescents, relative to BN adolescents, showed exaggerated amygdala response during subjective fear ratings and deactivation during passive viewing, across all emotion faces. In addition, the BI group showed an abnormally high amygdala response to a task condition marked by novelty and uncertainty (i.e., rating fear state to a Happy face). Perturbations in amygdala function are evident in adolescents temperamentally at risk for anxiety. Attention state alters the underlying pattern of neural processing, potentially mediating the observed behavioral patterns across development. BI adolescents also show a heightened sensitivity to novelty and uncertainty, which has been linked to anxiety. These patterns of reactivity may help sustain early temperamental biases over time and contribute to the observed relation between BI and anxiety. PMID:17376704

  19. Study of GABAergic extra-synaptic tonic inhibition in single neurons and neural populations by traversing neural scales: application to propofol-induced anaesthesia.

    Science.gov (United States)

    Hutt, Axel; Buhry, Laure

    2014-12-01

    Anaesthetic agents are known to affect extra-synaptic GABAergic receptors, which induce tonic inhibitory currents. Since these receptors are very sensitive to small concentrations of agents, they are supposed to play an important role in the underlying neural mechanism of general anaesthesia. Moreover anaesthetic agents modulate the encephalographic activity (EEG) of subjects and hence show an effect on neural populations. To understand better the tonic inhibition effect in single neurons on neural populations and hence how it affects the EEG, the work considers single neurons and neural populations in a steady-state and studies numerically and analytically the modulation of their firing rate and nonlinear gain with respect to different levels of tonic inhibition. We consider populations of both type-I (Leaky Integrate-and-Fire model) and type-II (Morris-Lecar model) neurons. To bridge the single neuron description to the population description analytically, a recently proposed statistical approach is employed which allows to derive new analytical expressions for the population firing rate for type-I neurons. In addition, the work shows the derivation of a novel transfer function for type-I neurons as considered in neural mass models and studies briefly the interaction of synaptic and extra-synaptic inhibition. We reveal a strong subtractive and divisive effect of tonic inhibition in type-I neurons, i.e. a shift of the firing rate to higher excitation levels accompanied by a change of the nonlinear gain. Tonic inhibition shortens the excitation window of type-II neurons and their populations while maintaining the nonlinear gain. The gained results are interpreted in the context of recent experimental findings under propofol-induced anaesthesia.

  20. 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)

    Manceur, Aziza P.; Tseng, Michael; Holowacz, Tamara; Witterick, Ian; Weksberg, Rosanna; McCurdy, Richard D.; Warsh, Jerry J.; Audet, Julie

    2011-01-01

    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.

  1. Large-scale functional neural network correlates of response inhibition: an fMRI meta-analysis.

    Science.gov (United States)

    Zhang, Ruibin; Geng, Xiujuan; Lee, Tatia M C

    2017-12-01

    An influential hypothesis from the last decade proposed that regions within the right inferior frontal cortex of the human brain were dedicated to supporting response inhibition. There is growing evidence, however, to support an alternative model, which proposes that neural areas associated with specific inhibitory control tasks co-exist as common network mechanisms, supporting diverse cognitive processes. This meta-analysis of 225 studies comprising 323 experiments examined the common and distinct neural correlates of cognitive processes for response inhibition, namely interference resolution, action withholding, and action cancellation. Activation coordinates for each subcategory were extracted using multilevel kernel density analysis (MKDA). The extracted activity patterns were then mapped onto the brain functional network atlas to derive the common (i.e., process-general) and distinct (i.e., domain-oriented) neural network correlates of these processes. Independent of the task types, activation of the right hemispheric regions (inferior frontal gyrus, insula, median cingulate, and paracingulate gyri) and superior parietal gyrus was common across the cognitive processes studied. Mapping the activation patterns to a brain functional network atlas revealed that the fronto-parietal and ventral attention networks were the core neural systems that were commonly engaged in different processes of response inhibition. Subtraction analyses elucidated the distinct neural substrates of interference resolution, action withholding, and action cancellation, revealing stronger activation in the ventral attention network for interference resolution than action inhibition. On the other hand, action withholding/cancellation primarily engaged the fronto-striatal circuit. Overall, our results suggest that response inhibition is a multidimensional cognitive process involving multiple neural regions and networks for coordinating optimal performance. This finding has significant

  2. Melatonin antagonizes interleukin-18-mediated inhibition on neural stem cell proliferation and differentiation.

    Science.gov (United States)

    Li, Zheng; Li, Xingye; Chan, Matthew T V; Wu, William Ka Kei; Tan, DunXian; Shen, Jianxiong

    2017-09-01

    Neural stem cells (NSCs) are self-renewing, pluripotent and undifferentiated cells which have the potential to differentiate into neurons, oligodendrocytes and astrocytes. NSC therapy for tissue regeneration, thus, gains popularity. However, the low survivals rate of the transplanted cell impedes its utilities. In this study, we tested whether melatonin, a potent antioxidant, could promote the NSC proliferation and neuronal differentiation, especially, in the presence of the pro-inflammatory cytokine interleukin-18 (IL-18). Our results showed that melatonin per se indeed exhibited beneficial effects on NSCs and IL-18 inhibited NSC proliferation, neurosphere formation and their differentiation into neurons. All inhibitory effects of IL-18 on NSCs were significantly reduced by melatonin treatment. Moreover, melatonin application increased the production of both brain-derived and glial cell-derived neurotrophic factors (BDNF, GDNF) in IL-18-stimulated NSCs. It was observed that inhibition of BDNF or GDNF hindered the protective effects of melatonin on NSCs. A potentially protective mechanism of melatonin on the inhibition of NSC's differentiation caused IL-18 may attribute to the up-regulation of these two major neurotrophic factors, BNDF and GNDF. The findings indicate that melatonin may play an important role promoting the survival of NSCs in neuroinflammatory diseases. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  3. Behavioral and Neural Correlates of Executive Function: Interplay between Inhibition and Updating Processes

    Directory of Open Access Journals (Sweden)

    Na Young Kim

    2017-06-01

    Full Text Available This study investigated the interaction between two executive function processes, inhibition and updating, through analyses of behavioral, neurophysiological, and effective connectivity metrics. Although, many studies have focused on behavioral effects of executive function processes individually, few studies have examined the dynamic causal interactions between these two functions. A total of twenty participants from a local university performed a dual task combing flanker and n-back experimental paradigms, and completed the Operation Span Task designed to measure working memory capacity. We found that both behavioral (accuracy and reaction time and neurophysiological (P300 amplitude and alpha band power metrics on the inhibition task (i.e., flanker task were influenced by the updating load (n-back level and modulated by working memory capacity. Using independent component analysis, source localization (DIPFIT, and Granger Causality analysis of the EEG time-series data, the present study demonstrated that manipulation of cognitive demand in a dual executive function task influenced the causal neural network. We compared connectivity across three updating loads (n-back levels and found that experimental manipulation of working memory load enhanced causal connectivity of a large-scale neurocognitive network. This network contains the prefrontal and parietal cortices, which are associated with inhibition and updating executive function processes. This study has potential applications in human performance modeling and assessment of mental workload, such as the design of training materials and interfaces for those performing complex multitasking under stress.

  4. 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

  5. Neural Stem Cells and Its Derivatives as a New Material for Melanin Inhibition.

    Science.gov (United States)

    Hwang, Insik; Hong, Sunghoi

    2017-12-22

    The pigment molecule, melanin, is produced from melanosomes of melanocytes through melanogenesis, which is a complex process involving a combination of chemical and enzymatically catalyzed reactions. The synthesis of melanin is primarily influenced by tyrosinase (TYR), which has attracted interest as a target molecule for the regulation of pigmentation or depigmentation in skin. Thus, direct inhibitors of TYR activity have been sought from various natural and synthetic materials. However, due to issues with these inhibitors, such as weak or permanent ability for depigmentation, allergy, irritant dermatitis and rapid oxidation, in vitro and in vivo, the development of new materials that inhibit melanin production is essential. A conditioned medium (CM) derived from stem cells contains many cell-secreted factors, such as cytokines, chemokines, growth factors and extracellular vesicles including exosomes. In addition, the secreted factors could negatively regulate melanin production through stimulation of a microenvironment of skin tissue in a paracrine manner, which allows the neural stem cell CM to be explored as a new material for skin depigmentation. In this review, we will summarize the current knowledge regulating depigmentation, and discuss the potential of neural stem cells and their derivatives, as a new material for skin depigmentation.

  6. Comparative Effects of Methylphenidate, Modafinil, and MDMA on Response Inhibition Neural Networks in Healthy Subjects.

    Science.gov (United States)

    Schmidt, André; Müller, Felix; Dolder, Patrick C; Schmid, Yasmin; Zanchi, Davide; Liechti, Matthias E; Borgwardt, Stefan

    2017-09-01

    Psychostimulants such as methylphenidate and modafinil are increasingly used by healthy people for cognitive enhancement purposes, whereas the acute effect of 3,4-methylenedioxymethamphetamine (ecstasy) on cognitive functioning in healthy subjects remains unclear. This study directly compared the acute effects of methylphenidate, modafinil, and 3,4-methylenedioxymethamphetamine on the neural mechanisms underlying response inhibition in healthy subjects. Using a double-blind, within-subject, placebo-controlled, cross-over design, methylphenidate, modafinil, and 3,4-methylenedioxymethamphetamine were administrated to 21 healthy subjects while performing a go/no-go event-related functional magnetic resonance imaging task to assess brain activation during motor response inhibition. Relative to placebo, methylphenidate and modafinil but not 3,4-methylenedioxymethamphetamine improved inhibitory performance. Methylphenidate significantly increased activation in the right middle frontal gyrus, middle/superior temporal gyrus, inferior parietal lobule, presupplementary motor area, and anterior cingulate cortex compared with placebo. Methylphenidate also induced significantly higher activation in the anterior cingulate cortex and presupplementary motor area and relative to modafinil. Relative to placebo, modafinil significantly increased activation in the right middle frontal gyrus and superior/inferior parietal lobule, while 3,4-methylenedioxymethamphetamine significantly increased activation in the right middle/inferior frontal gyrus and superior parietal lobule. Direct comparison of methylphenidate, modafinil, and 3,4-methylenedioxymethamphetamine revealed broad recruitment of fronto-parietal regions but specific effects of methylphenidate on middle/superior temporal gyrus, anterior cingulate cortex, and presupplementary motor area activation, suggesting dissociable modulations of response inhibition networks and potentially the superiority of methylphenidate in the

  7. Perceptual Surprise Improves Action Stopping by Nonselectively Suppressing Motor Activity via a Neural Mechanism for Motor Inhibition.

    Science.gov (United States)

    Dutra, Isabella C; Waller, Darcy A; Wessel, Jan R

    2018-02-07

    Motor inhibition is a cognitive control ability that allows humans to stop actions rapidly even after initiation. Understanding and improving motor inhibition could benefit adaptive behavior in both health and disease. We recently found that presenting surprising, task-unrelated sounds when stopping is necessary improves the likelihood of successful stopping. In the current study, we investigated the neural underpinnings of this effect. Specifically, we tested whether surprise-related stopping improvements are due to a genuine increase in motor inhibition. In Experiment 1, we measured motor inhibition in primary motor cortex of male and female humans by quantifying corticospinal excitability (CSE) via transcranial magnetic stimulation and electromyography during a hybrid surprise-Go/NoGo task. Consistent with prior studies of motor inhibition, successful stopping was accompanied by nonselective suppression of CSE; that is, CSE was suppressed even in task-unrelated motor effectors. Importantly, unexpected sounds significantly increased this motor-system inhibition to a degree that was directly related to behavioral improvements in stopping. In Experiment 2, we then used scalp encephalography to investigate whether unexpected sounds increase motor-inhibition-related activity in the CNS. We used an independent stop-signal localizer task to identify a well characterized frontocentral low-frequency EEG component that indexes motor inhibition. We then investigated the activity of this component in the surprise-Go/NoGo task. Consistent with Experiment 1, this signature of motor inhibition was indeed increased when NoGo signals were followed by unexpected sounds. Together, these experiments provide converging evidence suggesting that unexpected events improve motor inhibition by automatically triggering inhibitory control. SIGNIFICANCE STATEMENT The ability to stop ongoing actions rapidly allows humans to adapt their behavior flexibly and rapidly. Action stopping is

  8. 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.

  9. 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. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. 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.

  11. Cimetidine inhibits salivary gland tumor cell adhesion to neural cells and induces apoptosis by blocking NCAM expression

    Directory of Open Access Journals (Sweden)

    Sakashita Hideaki

    2008-12-01

    Full Text Available Abstract Background Cimetidine, a histamine type-2 receptor antagonist, has been reported to inhibit the growth of glandular tumors such as colorectal cancer, however the mechanism of action underlying this effect is unknown. Adenoid cystic carcinoma is well known as a malignant salivary gland tumor which preferentially invades neural tissues. We demonstrated previously that human salivary gland tumor (HSG cells spontaneously express neural cell adhesion molecule (NCAM, that HSG cell proliferation may be controlled via a homophilic (NCAM-NCAM binding mechanism and that NCAM may be associated with perineural invasion by malignant salivary gland tumors. We further demonstrated that cimetidine inhibited NCAM expression and induced apoptosis in HSG cells. Here, we investigated the effects of cimetidine on growth and perineural/neural invasion of salivary gland tumor cells. Methods In this study, we have examined the effect of cimetidine on cancer cell adhesion to neural cells in vitro, one of the critical steps of cancer invasion and metastasis. We have also used an in vivo carcinogenesis model to confirm the effect of cimetidine. Results We have demonstrated for the first time that cimetidine can block the adhesion of HSG cells to neural cell monolayers and that it can also induce significant apoptosis in the tumor mass in a nude mouse model. We also demonstrated that these apoptotic effects of cimetidine might occur through down-regulation of the cell surface expression of NCAM on HSG cells. Cimetidine-mediated down-regulation of NCAM involved suppression of the nuclear translocation of NF-κB, a transcriptional activator of NCAM gene expression. Conclusion These findings suggest that growth and perineural/neural invasion of salivary gland tumors can be blocked by administration of cimetidine via induction of apoptosis and in which NCAM plays a role.

  12. Zika virus infection dysregulates human neural stem cell growth and inhibits differentiation into neuroprogenitor cells

    Science.gov (United States)

    Devhare, Pradip; Meyer, Keith; Steele, Robert; Ray, Ratna B; Ray, Ranjit

    2017-01-01

    The current outbreak of Zika virus-associated diseases in South America and its threat to spread to other parts of the world has emerged as a global health emergency. A strong link between Zika virus and microcephaly exists, and the potential mechanisms associated with microcephaly are under intense investigation. In this study, we evaluated the effect of Zika virus infection of Asian and African lineages (PRVABC59 and MR766) in human neural stem cells (hNSCs). These two Zika virus strains displayed distinct infection pattern and growth rates in hNSCs. Zika virus MR766 strain increased serine 139 phosphorylation of histone H2AX (γH2AX), a known early cellular response proteins to DNA damage. On the other hand, PRVABC59 strain upregulated serine 15 phosphorylation of p53, p21 and PUMA expression. MR766-infected cells displayed poly (ADP-ribose) polymerase (PARP) and caspase-3 cleavage. Interestingly, infection of hNSCs by both strains of Zika virus for 24 h, followed by incubation in astrocyte differentiation medium, induced rounding and cell death. However, astrocytes generated from hNSCs by incubation in differentiation medium when infected with Zika virus displayed minimal cytopathic effect at an early time point. Infected hNSCs incubated in astrocyte differentiating medium displayed PARP cleavage within 24–36 h. Together, these results showed that two distinct strains of Zika virus potentiate hNSC growth inhibition by different mechanisms, but both viruses strongly induce death in early differentiating neuroprogenitor cells even at a very low multiplicity of infection. Our observations demonstrate further mechanistic insights for impaired neuronal homeostasis during active Zika virus infection. PMID:29022904

  13. 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.

  14. 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.

  15. Neural impact of low-level alcohol use on response inhibition: An fMRI investigation in young adults.

    Science.gov (United States)

    Hatchard, Taylor; Mioduszewski, Ola; Fall, Carley; Byron-Alhassan, Aziza; Fried, Peter; Smith, Andra M

    2017-06-30

    It is widely known that alcohol consumption adversely affects human health, particularly in the immature developing brains of adolescents and young adults, which may also have a long-lasting impact on executive functioning. The present study investigated the neural activity of 28 young adults from the Ottawa Prenatal Prospective Study (OPPS) using functional magnetic resonance imaging (fMRI). The purpose of this study was to discover the impact of regular low-level alcohol consumption on response inhibition as the participants performed a Go/No-Go task. Results indicated that, despite a lack of performance differences, young adults who use alcohol on a regular basis differ significantly from those who do not use alcohol regularly (if at all) with respect to their neural activity as the circuitry engaged in response inhibition is being challenged. Specifically, areas that showed significantly more activation in users compared to controls included the left hippocampus, parahippocampal gyrus, superior frontal gyrus, precentral gyrus, right superior parietal lobule, and the cerebellum. These results suggest that even in low amounts, regular consumption of alcohol may have a significant impact on neurophysiological functioning during response inhibition in the developing brain of youth. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  16. Cannabinoid inhibition of guinea-pig intestinal peristalsis via inhibition of excitatory and activation of inhibitory neural pathways.

    Science.gov (United States)

    Heinemann, A; Shahbazian, A; Holzer, P

    1999-09-01

    Since activation of cannabinoid CB1 receptors inhibits gastrointestinal transit in the mouse, this study analyzed the action of the cannabinoid receptor agonist methanandamide on distension-induced propulsive motility. Peristalsis in luminally perfused segments of the guinea-pig isolated ileum was elicited by a rise of the intraluminal pressure. The pressure threshold at which peristaltic contractions were triggered was used to quantify drug effects. Methanandamide (0.1-3 microM) inhibited peristalsis as deduced from a concentration-related increase in the peristaltic pressure threshold, an action that was prevented by the CB1 receptor antagonist SR141716A (1 microM) per se, which had no effect on peristalsis. The distension-induced ascending reflex contraction of the circular muscle was likewise depressed by methanandamide in a SR141716A-sensitive manner, whereas indomethacin-induced phasic contractions of the circular muscle were left unchanged by methanandamide. The anti-peristaltic action of methanandamide was inhibited by apamin (0.5 microM), attenuated by N-nitro-L-arginine methyl ester (300 microM) and left unaltered by suramin (300 microM), pyridoxal-phosphate-6-azophenyl-2',4'-disulphonic acid (150 microM) and naloxone (0.5 microM). It is concluded that methanandamide depresses intestinal peristalsis via activation of CB1 receptors on enteric neurons, which results in blockade of excitatory motor pathways and facilitation of inhibitory pathways operating via apamin-sensitive K+ channels and nitric oxide.

  17. Effects of a brief mindfulness-meditation intervention on neural measures of response inhibition in cigarette smokers.

    Science.gov (United States)

    Andreu, Catherine I; Cosmelli, Diego; Slagter, Heleen A; Franken, Ingmar H A

    2018-01-01

    Research suggests that mindfulness-practices may aid smoking cessation. Yet, the neural mechanisms underlying the effects of mindfulness-practices on smoking are unclear. Response inhibition is a main deficit in addiction, is associated with relapse, and could therefore be a candidate target for mindfulness-based practices. The current study hence investigated the effects of a brief mindfulness-practice on response inhibition in smokers using behavioral and electroencephalography (EEG) measures. Fifty participants (33 females, mean age 20 years old) underwent a protocol of cigarette exposure to induce craving (cue-exposure) and were then randomly assigned to a group receiving mindfulness-instructions or control-instructions (for 15 minutes approximately). Immediately after this, they performed a smoking Go/NoGo task, while their brain activity was recorded. At the behavioral level, no group differences were observed. However, EEG analyses revealed a decrease in P3 amplitude during NoGo vs. Go trials in the mindfulness versus control group. The lower P3 amplitude might indicate less-effortful response inhibition after the mindfulness-practice, and suggest that enhanced response inhibition underlies observed positive effects of mindfulness on smoking behavior.

  18. Effects of a brief mindfulness-meditation intervention on neural measures of response inhibition in cigarette smokers

    Science.gov (United States)

    Cosmelli, Diego; Slagter, Heleen A.; Franken, Ingmar H. A.

    2018-01-01

    Research suggests that mindfulness-practices may aid smoking cessation. Yet, the neural mechanisms underlying the effects of mindfulness-practices on smoking are unclear. Response inhibition is a main deficit in addiction, is associated with relapse, and could therefore be a candidate target for mindfulness-based practices. The current study hence investigated the effects of a brief mindfulness-practice on response inhibition in smokers using behavioral and electroencephalography (EEG) measures. Fifty participants (33 females, mean age 20 years old) underwent a protocol of cigarette exposure to induce craving (cue-exposure) and were then randomly assigned to a group receiving mindfulness-instructions or control-instructions (for 15 minutes approximately). Immediately after this, they performed a smoking Go/NoGo task, while their brain activity was recorded. At the behavioral level, no group differences were observed. However, EEG analyses revealed a decrease in P3 amplitude during NoGo vs. Go trials in the mindfulness versus control group. The lower P3 amplitude might indicate less-effortful response inhibition after the mindfulness-practice, and suggest that enhanced response inhibition underlies observed positive effects of mindfulness on smoking behavior. PMID:29370256

  19. Effects of a brief mindfulness-meditation intervention on neural measures of response inhibition in cigarette smokers.

    Directory of Open Access Journals (Sweden)

    Catherine I Andreu

    Full Text Available Research suggests that mindfulness-practices may aid smoking cessation. Yet, the neural mechanisms underlying the effects of mindfulness-practices on smoking are unclear. Response inhibition is a main deficit in addiction, is associated with relapse, and could therefore be a candidate target for mindfulness-based practices. The current study hence investigated the effects of a brief mindfulness-practice on response inhibition in smokers using behavioral and electroencephalography (EEG measures. Fifty participants (33 females, mean age 20 years old underwent a protocol of cigarette exposure to induce craving (cue-exposure and were then randomly assigned to a group receiving mindfulness-instructions or control-instructions (for 15 minutes approximately. Immediately after this, they performed a smoking Go/NoGo task, while their brain activity was recorded. At the behavioral level, no group differences were observed. However, EEG analyses revealed a decrease in P3 amplitude during NoGo vs. Go trials in the mindfulness versus control group. The lower P3 amplitude might indicate less-effortful response inhibition after the mindfulness-practice, and suggest that enhanced response inhibition underlies observed positive effects of mindfulness on smoking behavior.

  20. 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…

  1. Transcriptional basis for the inhibition of neural stem cell proliferation and migration by the TGFβ-family member GDF11.

    Directory of Open Access Journals (Sweden)

    Gareth Williams

    Full Text Available Signalling through EGF, FGF and endocannabinoid (eCB receptors promotes adult neurogenesis, and this can be modelled in culture using the Cor-1 neural stem cell line. In the present study we show that Cor-1 cells express a TGFβ receptor complex composed of the ActRIIB/ALK5 subunits and that a natural ligand for this receptor complex, GDF11, activates the canonical Smad2/3 signalling cascade and significantly alters the expression of ∼4700 gene transcripts within a few hours of treatment. Many of the transcripts regulated by GDF11 are also regulated by the EGF, FGF and eCB receptors and by the MAPK pathway - however, in general in the opposite direction. This can be explained to some extent by the observation that GDF11 inhibits expression of, and signalling through, the EGF receptor. GDF11 regulates expression of numerous cell-cycle genes and suppresses Cor-1 cell proliferation; interestingly we found down-regulation of Cyclin D2 rather than p27kip1 to be a good molecular correlate of this. GDF11 also inhibited the expression of numerous genes linked to cytoskeletal regulation including Fascin and LIM and SH3 domain protein 1 (LASP1 and this was associated with an inhibition of Cor-1 cell migration in a scratch wound assay. These data demonstrate GDF11 to be a master regulator of neural stem cell transcription that can suppress cell proliferation and migration by regulating the expression of numerous genes involved in both these processes, and by suppressing transcriptional responses to factors that normally promote proliferation and/or migration.

  2. Effects of selective serotonin reuptake inhibition on neural activity related to risky decisions and monetary rewards in healthy males

    DEFF Research Database (Denmark)

    Macoveanu, Julian; Fisher, Patrick M; Haahr, Mette E

    2014-01-01

    the involvement of the normally functioning 5HT-system in decision-making under risk and processing of monetary rewards. The data suggest that prolonged SSRI treatment might reduce emotional engagement by reducing the impact of risk during decision-making or the impact of reward during outcome evaluation.......Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine are commonly prescribed antidepressant drugs targeting the dysfunctional serotonin (5-HT) system, yet little is known about the functional effects of prolonged serotonin reuptake inhibition in healthy individuals. Here we used...... functional MRI (fMRI) to investigate how a three-week fluoxetine intervention influences neural activity related to risk taking and reward processing. Employing a double-blinded parallel-group design, 29 healthy young males were randomly assigned to receive 3 weeks of a daily dose of 40 mg fluoxetine...

  3. Effects of Modafinil on Neural Correlates of Response Inhibition in Alcohol-Dependent Patients

    NARCIS (Netherlands)

    Schmaal, L.; Joos, L.; Koeleman, M.; Veltman, D.J.; van den Brink, W.; Goudriaan, A.E.

    2013-01-01

    Background: Impaired response inhibition is a key feature of patients with alcohol dependence. Improving impulse control is a promising target for the treatment of alcohol dependence. The pharmacologic agent modafinil enhances cognitive control functions in both healthy subjects and in patients with

  4. Effects of modafinil on neural correlates of response inhibition in alcohol-dependent patients

    NARCIS (Netherlands)

    Schmaal, Lianne; Joos, Leen; Koeleman, Marte; Veltman, Dick J.; van den Brink, Wim; Goudriaan, Anna E.

    2013-01-01

    Impaired response inhibition is a key feature of patients with alcohol dependence. Improving impulse control is a promising target for the treatment of alcohol dependence. The pharmacologic agent modafinil enhances cognitive control functions in both healthy subjects and in patients with various

  5. 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

  6. 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.

  7. Neural Correlates of Rewarded Response Inhibition in Youth at Risk for Problematic Alcohol Use

    Directory of Open Access Journals (Sweden)

    Brenden Tervo-Clemmens

    2017-11-01

    Full Text Available Risk for substance use disorder (SUD is associated with poor response inhibition and heightened reward sensitivity. During adolescence, incentives improve performance on response inhibition tasks and increase recruitment of cortical control areas (Geier et al., 2010 associated with SUD (Chung et al., 2011. However, it is unknown whether incentives moderate the relationship between response inhibition and trait-level psychopathology and personality features of substance use risk. We examined these associations in the current project using a rewarded antisaccade (AS task (Geier et al., 2010 in youth at risk for substance use. Participants were 116 adolescents and young adults (ages 12–21 from the University of Pittsburgh site of the National Consortium on Adolescent Neurodevelopment and Alcohol [NCANDA] study, with neuroimaging data collected at baseline and 1 year follow up visits. Building upon previous work using this task in normative developmental samples (Geier et al., 2010 and adolescents with SUD (Chung et al., 2011, we examined both trial-wise BOLD responses and those associated with individual task-epochs (cue presentation, response preparation, and response and associated them with multiple substance use risk factors (externalizing and internalizing psychopathology, family history of substance use, and trait impulsivity. Results showed that externalizing psychopathology and high levels of trait impulsivity (positive urgency, SUPPS-P were associated with general decreases in antisaccade performance. Accompanying this main effect of poor performance, positive urgency was associated with reduced recruitment of the frontal eye fields (FEF and inferior frontal gyrus (IFG in both a priori regions of interest and at the voxelwise level. Consistent with previous work, monetary incentive improved antisaccade behavioral performance and was associated with increased activation in the striatum and cortical control areas. However, incentives did

  8. 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. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. 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

  10. Acute Stressors Reduce Neural and Behavioral Inhibition to Food Cues among Binge Eating Disorder Symptomatic Women

    Directory of Open Access Journals (Sweden)

    Zhenyong Lyu

    2016-10-01

    Full Text Available 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 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.

  11. MicroRNA-7 Enhances Subventricular Zone Neurogenesis by Inhibiting NLRP3/Caspase-1 Axis in Adult Neural Stem Cells.

    Science.gov (United States)

    Fan, Zheng; Lu, Ming; Qiao, Chen; Zhou, Yan; Ding, Jian-Hua; Hu, Gang

    2016-12-01

    α-Synuclein (α-syn) has been recognized to induce neuroinflammation and to disturb nerve repair process in Parkinson's disease. However, the potential mechanisms underlying α-syn-induced impairment of adult neurogenesis remain unclear. In the present study, A53T mutant α--synuclein transgenic (A53T tg/tg ) mice, caspase-1 knockout mice, and A53T tg/tg ;caspase-1 -/- double transgenic mice were used to prepare adult neural stem cells (ANSCs) and to investigate inflammasome-related mechanism for α-syn-impaired neurogenesis in mouse subventricular zone (SVZ). We showed that α-syn inhibited neurogenesis in the SVZ of A53T tg/tg mice and impaired proliferation and differentiation in ANSCs cultured in vitro, accompanied by reduced microRNA-7 (miR-7) expression levels. We further found that ANSC expressed NLRP3-containing inflammasome and α-syn activated both TLR4/NF-κB and NLRP3/caspase-1 signals in ANSCs. Either Nlrp3 knockdown or Caspase-1 knockout could attenuate the inhibition of proliferation in ANSCs induced by α-syn. Furthermore, we demonstrated that miR-7 post-transcriptionally controlled Nlrp3 expression besides targeting α-syn. Most notably, stereotactic injection of miR-7 mimics into lateral ventricles significantly inhibited NLRP3 inflammasome activation and improved adult neurogenesis in mouse SVZ. Our study provides a direct link between NLRP3 inflammasome activation and α-syn-impaired neurogenesis in the pathogenesis of α-synucleinopathies.

  12. FoxA4 favours notochord formation by inhibiting contiguous mesodermal fates and restricts anterior neural development in Xenopus embryos.

    Directory of Open Access Journals (Sweden)

    Sabrina Murgan

    Full Text Available In vertebrates, the embryonic dorsal midline is a crucial signalling centre that patterns the surrounding tissues during development. Members of the FoxA subfamily of transcription factors are expressed in the structures that compose this centre. Foxa2 is essential for dorsal midline development in mammals, since knock-out mouse embryos lack a definitive node, notochord and floor plate. The related gene foxA4 is only present in amphibians. Expression begins in the blastula -chordin and -noggin expressing centre (BCNE and is later restricted to the dorsal midline derivatives of the Spemann's organiser. It was suggested that the early functions of mammalian foxa2 are carried out by foxA4 in frogs, but functional experiments were needed to test this hypothesis. Here, we show that some important dorsal midline functions of mammalian foxa2 are exerted by foxA4 in Xenopus. We provide new evidence that the latter prevents the respecification of dorsal midline precursors towards contiguous fates, inhibiting prechordal and paraxial mesoderm development in favour of the notochord. In addition, we show that foxA4 is required for the correct regionalisation and maintenance of the central nervous system. FoxA4 participates in constraining the prospective rostral forebrain territory during neural specification and is necessary for the correct segregation of the most anterior ectodermal derivatives, such as the cement gland and the pituitary anlagen. Moreover, the early expression of foxA4 in the BCNE (which contains precursors of the whole forebrain and most of the midbrain and hindbrain is directly required to restrict anterior neural development.

  13. Altering the Balance between Excitation and Inhibition in Cultured Neural Networks

    Science.gov (United States)

    Dzakpasu, Rhonda

    2010-03-01

    How is the network temporal structure altered when the balance between excitation and inhibition is changed? Proper balance is essential for normal brain function, including cognitive processing, the representation of sensory information and motor control. When the balance is compromised, neurological disorders may result. We use a simple reduced experimental system to investigate how manipulating the number of inhibitory neurons in a network of cultured hippocampal neurons affects synchronized bursting activity, the most prominent temporal signature of cultured hippocampal networks. Inhibitory neurons are thought to control spike timing and modulate network excitability and their absence may lead to widespread synchronization. We culture dissociated hippocampal neurons with varying quantities of inhibitory neurons on an 8x8 grid of extracellular electrodes and study how inhibitory neurons modulate network temporal dynamics. We show that as the proportion of inhibitory neurons increase, there is a dramatic transition in the temporal pattern.

  14. A mechanistic study of Toxoplasma gondii ROP18 inhibiting differentiation of C17.2 neural stem cells

    Directory of Open Access Journals (Sweden)

    Xian Zhang

    2017-11-01

    Full Text Available Abstract Background Congenital infection of Toxoplasma gondii is an important factor causing birth defects. The neural stem cells (NSCs are found to be one of the target cells for the parasite during development of the brain. As a key virulence factor of the parasite that hijacks host cellular functions, ROP18 has been demonstrated to mediate the inhibition of host innate and adaptive immune responses through specific binding different host immunity related molecules. However, its pathogenic actions in NSCs remain elusive. Results In the present study, ROP18 recombinant adenovirus (Ad-ROP18 was constructed and used to infect C17.2 NSCs. After 3d- or 5d–culture in differentiation medium, the differentiation of C17.2 NSCs and the activity of the Wnt/β-catenin signaling pathway were detected. The results showed that the protein level of βIII-tubulin, a marker of neurons, in the Ad-ROP18-transfected C17.2 NSCs was significantly decreased, indicating that the differentiation of C17.2 NSCs was inhibited by the ROP18. The β-catenin level in the Ad-ROP18-transfected C17.2 NSCs was found to be lower than that in the Ad group. Also, neurogenin1 (Ngn1 and neurogenin2 (Ngn2 were downregulated significantly (P < 0.05 in the Ad-ROP18-transfected C17.2 NSCs compared to the Ad group. Accordingly, the TOP flash/FOP flash dual-luciferase report system showed that the transfection of Ad-ROP18 decreased the Wnt/β-catenin pathway activity in the C17.2 NSCs. Conclusions The inhibition effect of the ROP18 from T. gondii (TgROP18 on the neuronal differentiation of C17.2 NSCs was at least partly mediated through inhibiting the activity of the Wnt/β-catenin signaling pathway, eventually resulting in the downregulation of Ngn1 and Ngn2. The findings help to better understand potential mechanisms of brain pathology induced by TgROP18.

  15. Environmental CO2 inhibits Caenorhabditis elegans egg-laying by modulating olfactory neurons and evokes widespread changes in neural activity

    Science.gov (United States)

    Fenk, Lorenz A.; de Bono, Mario

    2015-01-01

    Carbon dioxide (CO2) gradients are ubiquitous and provide animals with information about their environment, such as the potential presence of prey or predators. The nematode Caenorhabditis elegans avoids elevated CO2, and previous work identified three neuron pairs called “BAG,” “AFD,” and “ASE” that respond to CO2 stimuli. Using in vivo Ca2+ imaging and behavioral analysis, we show that C. elegans can detect CO2 independently of these sensory pathways. Many of the C. elegans sensory neurons we examined, including the AWC olfactory neurons, the ASJ and ASK gustatory neurons, and the ASH and ADL nociceptors, respond to a rise in CO2 with a rise in Ca2+. In contrast, glial sheath cells harboring the sensory endings of C. elegans’ major chemosensory neurons exhibit strong and sustained decreases in Ca2+ in response to high CO2. Some of these CO2 responses appear to be cell intrinsic. Worms therefore may couple detection of CO2 to that of other cues at the earliest stages of sensory processing. We show that C. elegans persistently suppresses oviposition at high CO2. Hermaphrodite-specific neurons (HSNs), the executive neurons driving egg-laying, are tonically inhibited when CO2 is elevated. CO2 modulates the egg-laying system partly through the AWC olfactory neurons: High CO2 tonically activates AWC by a cGMP-dependent mechanism, and AWC output inhibits the HSNs. Our work shows that CO2 is a more complex sensory cue for C. elegans than previously thought, both in terms of behavior and neural circuitry. PMID:26100886

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

    Directory of Open Access Journals (Sweden)

    Bruno Pereira Carreira

    2014-10-01

    Full Text Available 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 (NSC, and explored possible mechanisms underlying this effect. We investigated which mechanisms are involved in the regulation of NSC proliferation following treatment with an inflammatory stimulus (LPS plus IFN-γ, using a culture system of subventricular zone (SVZ-derived NSC mixed with microglia cells obtained from wild-type mice (iNOS+/+ or from iNOS knockout mice (iNOS-/-. We found an impairment of NSC cell proliferation in iNOS+/+ mixed cultures, which was not observed in iNOS-/- mixed cultures. Furthermore, the increased release of NO by activated iNOS+/+ microglial cells decreased the activation of the ERK/MAPK signaling pathway, which was concomitant with an enhanced nitration of the EGF receptor. Preventing nitrogen reactive species formation with MnTBAP, a scavenger of peroxynitrite, or using the peroxynitrite degradation catalyst FeTMPyP, cell proliferation and ERK signaling were restored to basal levels in iNOS+/+ mixed cultures. Moreover, exposure to the NO donor NOC-18 (100 µM, for 48 h, inhibited SVZ-derived NSC proliferation. Regarding the antiproliferative effect of NO, we found that NOC-18 caused the impairment of signaling through the ERK/MAPK pathway, which may be related to increased nitration of the EGF receptor in NSC. Using MnTBAP nitration was prevented, maintaining ERK signaling, rescuing NSC proliferation. We show that NO from inflammatory origin leads to a decreased function of the EGF receptor, which compromised proliferation of NSC. We also demonstrated that NO-mediated nitration of the EGF receptor caused a decrease in its phosphorylation, thus preventing regular proliferation signaling through the

  17. Neural correlates of endogenous attention, exogenous attention and inhibition of return in touch.

    Science.gov (United States)

    Jones, Alexander; Forster, Bettina

    2014-07-01

    Selective attention helps process the myriad of information constantly touching our body. Both endogenous and exogenous mechanisms are relied upon to effectively process this information; however, it is unclear how they relate in the sense of touch. In three tasks we contrasted endogenous and exogenous event-related potential (ERP) and behavioural effects. Unilateral tactile cues were followed by a tactile target at the same or opposite hand. Clear behavioural effects showed facilitation of expected targets both when the cue predicted targets at the same (endogenous predictive task) and opposite hand (endogenous counter-predictive task), and these effects also correlated with ERP effects of endogenous attention. In an exogenous task, where the cue was non-informative, inhibition of return (IOR) was observed. The electrophysiological results demonstrated early effects of exogenous attention followed by later endogenous attention modulations. These effects were independent in both the endogenous predictive and exogenous tasks. However, voluntarily directing attention away from a cued body part influenced the early exogenous marker (N80). This suggests that the two mechanisms are interdependent, at least when the task requires more demanding shifts of attention. The early marker of exogenous tactile attention, the N80, was not directly related to IOR, which may suggest that exogenous attention and IOR are not necessarily two sides of the same coin. This study adds valuable new insight into how we process and select information presented to our body, showing both independent and interdependent effects of endogenous and exogenous attention in touch. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  18. Different Neural Networks are Involved in Cross-Modal Non-Spatial Inhibition of Return (IOR: The Effect of the Sensory Modality of Behavioral Targets

    Directory of Open Access Journals (Sweden)

    Qi Chen

    2011-10-01

    Full Text Available We employed a novel cross-modal non-spatial inhibition of return (IOR paradigm with fMRI to investigate whether object concept is organized by supramodal or modality-specific systems. A precue-neutral cue-target sequence was presented and participants were asked to discriminate whether the target was a dog or a cat. The precue and the target could be either a picture or vocalization of a dog or a cat. The neutral cue (bird was always from the same modality as the precue. Behaviorally, for both visual and auditory targets, the main effect of cue validity was the only significant effect, p<0.01, with equivalent effects for within- and cross-modal IOR. Neurally, for visual targets, left inferior frontal gyrus and left medial temporal gyrus showed significantly higher neural activity in cued than uncued condition, irrespective of the precue-target relationship, indicating that the two areas are involved in inhibiting a supramodal representation of previously attended object concept. For auditory targets, left lateral occipital gyrus and right postcentral gyrus showed significantly higher neural activity in uncued than cued condition irrespective of the cue-target relationship, indicating that the two areas are involved in creating a new supramodal representation when a novel object concept appears.

  19. Transcranial Direct Current Stimulation Over the Right Frontal Inferior Cortex Decreases Neural Activity Needed to Achieve Inhibition: A Double-Blind ERP Study in a Male Population.

    Science.gov (United States)

    Campanella, Salvatore; Schroder, Elisa; Monnart, Aurore; Vanderhasselt, Marie-Anne; Duprat, Romain; Rabijns, Mark; Kornreich, Charles; Verbanck, Paul; Baeken, Chris

    2017-05-01

    Inhibitory control refers to the ability to inhibit an action once it has been initiated. Impaired inhibitory control plays a key role in triggering relapse in some pathological states, such as addictions. Therefore, a major challenge of current research is to establish new methods to strengthen inhibitory control in these "high-risk" populations. In this attempt, the right inferior frontal cortex (rIFC), a neural correlate crucial for inhibitory control, was modulated using transcranial direct current stimulation (tDCS). Healthy participants (n = 31) were presented with a "Go/No-go" task, a well-known paradigm to measure inhibitory control. During this task, an event-related potential (ERP) recording (T1; 32 channels) was performed. One subgroup (n = 15) was randomly assigned to a condition with tDCS (anodal electrode was placed on the rIFC and the cathodal on the neck); and the other group (n = 16) to a condition with sham (placebo) tDCS. After one 20- minute neuromodulation session, all participants were confronted again with the same ERP Go/No-go task (T2). To ensure that potential tDCS effects were specific to inhibition, ERPs to a face-detection task were also recorded at T1 and T2 in both subgroups. The rate of commission errors on the Go/No-go task was similar between T1 and T2 in both neuromodulation groups. However, the amplitude of the P3d component, indexing the inhibition function per se, was reduced at T2 as compared with T1. This effect was specific for participants in the tDCS (and not sham) condition for correctly inhibited trials. No difference in the P3 component was observable between both subgroups at T1 and T2 for the face detection task. Overall, the present data indicate that boosting the rIFC specifically enhances inhibitory skills by decreasing the neural activity needed to correctly inhibit a response.

  20. Chronic mild stress impairs latent inhibition and induces region-specific neural activation in CHL1-deficient mice, a mouse model of schizophrenia.

    Science.gov (United States)

    Buhusi, Mona; Obray, Daniel; Guercio, Bret; Bartlett, Mitchell J; Buhusi, Catalin V

    2017-08-30

    Schizophrenia is a neurodevelopmental disorder characterized by abnormal processing of information and attentional deficits. Schizophrenia has a high genetic component but is precipitated by environmental factors, as proposed by the 'two-hit' theory of schizophrenia. Here we compared latent inhibition as a measure of learning and attention, in CHL1-deficient mice, an animal model of schizophrenia, and their wild-type littermates, under no-stress and chronic mild stress conditions. All unstressed mice as well as the stressed wild-type mice showed latent inhibition. In contrast, CHL1-deficient mice did not show latent inhibition after exposure to chronic stress. Differences in neuronal activation (c-Fos-positive cell counts) were noted in brain regions associated with latent inhibition: Neuronal activation in the prelimbic/infralimbic cortices and the nucleus accumbens shell was affected solely by stress. Neuronal activation in basolateral amygdala and ventral hippocampus was affected independently by stress and genotype. Most importantly, neural activation in nucleus accumbens core was affected by the interaction between stress and genotype. These results provide strong support for a 'two-hit' (genes x environment) effect on latent inhibition in CHL1-deficient mice, and identify CHL1-deficient mice as a model of schizophrenia-like learning and attention impairments. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Decreased neural activity and neural connectivity while performing a set-shifting task after inhibiting repetitive transcranial magnetic stimulation on the left dorsal prefrontal cortex

    NARCIS (Netherlands)

    Gerrits, N.J.H.M.; van den Heuvel, O.A.; van der Werf, Y.D.

    2015-01-01

    Background: Sub-optimal functioning of the dorsal prefrontal cortex (PFC) is associated with executive dysfunction, such as set-shifting deficits, in neurological and psychiatric disorders. We tested this hypothesis by investigating the effect of low-frequency 'inhibiting' off-line repetitive

  2. Decreased neural activity and neural connectivity while performing a set-shifting task after inhibiting repetitive transcranial magnetic stimulation on the left dorsal prefrontal cortex

    NARCIS (Netherlands)

    Gerrits, Niels J H M; van den Heuvel, Odile A; van der Werf, Ysbrand D

    2015-01-01

    BACKGROUND: Sub-optimal functioning of the dorsal prefrontal cortex (PFC) is associated with executive dysfunction, such as set-shifting deficits, in neurological and psychiatric disorders. We tested this hypothesis by investigating the effect of low-frequency 'inhibiting' off-line repetitive

  3. Anti-ghrelin Spiegelmer inhibits exogenous ghrelin-induced increases in food intake, hoarding, and neural activation, but not food deprivation-induced increases

    Science.gov (United States)

    Teubner, Brett J. W.

    2013-01-01

    Circulating concentrations of the stomach-derived “hunger-peptide” ghrelin increase in direct proportion to the time since the last meal. Exogenous ghrelin also increases food intake in rodents and humans, suggesting ghrelin may increase post-fast ingestive behaviors. Food intake after food deprivation is increased by laboratory rats and mice, but not by humans (despite dogma to the contrary) or by Siberian hamsters; instead, humans and Siberian hamsters increase food hoarding, suggesting the latter as a model of fasting-induced changes in human ingestive behavior. Exogenous ghrelin markedly increases food hoarding by ad libitum-fed Siberian hamsters similarly to that after food deprivation, indicating sufficiency. Here, we tested the necessity of ghrelin to increase food foraging, food hoarding, and food intake, and neural activation [c-Fos immunoreactivity (c-Fos-ir)] using anti-ghrelin Spiegelmer NOX-B11–2 (SPM), an l-oligonucleotide that specifically binds active ghrelin, inhibiting peptide-receptor interaction. SPM blocked exogenous ghrelin-induced increases in food hoarding the first 2 days after injection, and foraging and food intake at 1–2 h and 2–4 h, respectively, and inhibited hypothalamic c-Fos-ir. SPM given every 24 h across 48-h food deprivation inconsistently inhibited food hoarding after refeeding and c-Fos-ir, similarly to inabilities to do so in laboratory rats and mice. These results suggest that ghrelin may not be necessary for food deprivation-induced foraging and hoarding and neural activation. A possible compensatory response, however, may underlie these findings because SPM treatment led to marked increases in circulating ghrelin concentrations. Collectively, these results show that SPM can block exogenous ghrelin-induced ingestive behaviors, but the necessity of ghrelin for food deprivation-induced ingestive behaviors remains unclear. PMID:23804279

  4. 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

    2016-01-01

    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

  5. HDAC inhibition amplifies gap junction communication in neural progenitors: Potential for cell-mediated enzyme prodrug therapy

    International Nuclear Information System (INIS)

    Khan, Zahidul; Akhtar, Monira; Asklund, Thomas; Juliusson, Bengt; Almqvist, Per M.; Ekstroem, Tomas J.

    2007-01-01

    Enzyme prodrug therapy using neural progenitor cells (NPCs) as delivery vehicles has been applied in animal models of gliomas and relies on gap junction communication (GJC) between delivery and target cells. This study investigated the effects of histone deacetylase (HDAC) inhibitors on GJC for the purpose of facilitating transfer of therapeutic molecules from recombinant NPCs. We studied a novel immortalized midbrain cell line, NGC-407 of embryonic human origin having neural precursor characteristics, as a potential delivery vehicle. The expression of gap junction protein connexin 43 (C x 43) was analyzed by western blot and immunocytochemistry. While C x 43 levels were decreased in untreated differentiating NGC-407 cells, the HDAC inhibitor 4-phenylbutyrate (4-PB) increased C x 43 expression along with increased membranous deposition in both proliferating and differentiating cells. Simultaneously, Ser 279/282-phosphorylated form of C x 43 was declined in both culture conditions by 4-PB. The 4-PB effect in NGC-407 cells was verified by using HNSC.100 human neural progenitors and Trichostatin A. Improved functional GJC is of imperative importance for therapeutic strategies involving intercellular transport of low molecular-weight compounds. We show here an enhancement by 4-PB, of the functional GJC among NGC-407 cells, as well as between NGC-407 and human glioma cells, as indicated by increased fluorescent dye transfer

  6. Neural evidence that inhibition is linked to the affective devaluation of distractors that match the contents of working memory.

    Science.gov (United States)

    De Vito, David; Al-Aidroos, Naseem; Fenske, Mark J

    2017-05-01

    Stimuli appearing as visual distractors subsequently receive more negative affective evaluations than novel items or prior targets of attention. Leading accounts question whether this distractor devaluation effect occurs through evaluative codes that become associated with distractors as a mere artefact of attention-task instructions, or through affective consequences of attentional inhibition when applied to prevent distractor interference. Here we test opposing predictions arising from the evaluative-coding and devaluation-by-inhibition hypotheses using an electrophysiological marker of attentional inhibition in a task that requires participants to avoid interference from abstract-shape distractors presented while maintaining a uniquely-colored stimulus in memory. Consistent with prior research, distractors that matched the colour of the stimulus being held in memory elicited a Pd component of the event-related potential waveform, indicating that their processing was being actively suppressed. Subsequent affective evaluations revealed that memory-matching distractors also received more negative ratings than non-matching distractors or previously-unseen shapes. Moreover, Pd magnitude was greater on trials in which the memory-matching distractors were later rated negatively than on trials preceding positive ratings. These results support the devaluation-by-inhibition hypothesis and strongly suggest that fluctuations in stimulus inhibition are closely associated with subsequent affective evaluations. In contrast, none of the evaluative-coding based predictions were confirmed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. [18F]FDG labeling of neural stem cells for in vivo cell tracking with positron emission tomography: inhibition of tracer release by phloretin.

    Science.gov (United States)

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

    2012-02-01

    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. Ideally, these tracking methods are noninvasive. Noninvasive tracking methods that have been successfully used for the visualization of blood-derived progenitor cells include magnetic resonance imaging and radionuclide imaging using single-photon emission computed tomography (SPECT) and positron emission tomography (PET). The SPECT tracer In-111-oxine is suitable for stem cell labeling, but for studies in small animals, the higher sensitivity and facile quantification that can be obtained with PET are preferred. Here the potential of 2'-[18F]fluoro-2'-deoxy-D-glucose ([18F]-FDG), a PET tracer, for tracking of neural stem cell (NSCs) trafficking toward an inflammation site was investigated. [18F]-FDG turns out to be a poor radiopharmaceutical to label NSCs owing to the low labeling efficiency and substantial release of radioactivity from these cells. Efflux of [18F]-FDG from NSCs can be effectively reduced by phloretin in vitro, but inhibition of tracer release is insufficient in vivo for accurate monitoring of stem cell trafficking.

  8. [18F]FDG Labeling of Neural Stem Cells for in Vivo Cell Tracking with Positron Emission Tomography: Inhibition of Tracer Release by Phloretin

    Directory of Open Access Journals (Sweden)

    Katica Stojanov

    2012-01-01

    Full Text Available 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. Ideally, these tracking methods are noninvasive. Noninvasive tracking methods that have been successfully used for the visualization of blood-derived progenitor cells include magnetic resonance imaging and radionuclide imaging using single-photon emission computed tomography (SPECT and positron emission tomography (PET. The SPECT tracer In-111-oxine is suitable for stem cell labeling, but for studies in small animals, the higher sensitivity and facile quantification that can be obtained with PET are preferred. Here the potential of 2′-[18F]fluoro-2′-deoxy-D-glucose ([18F]-FDG, a PET tracer, for tracking of neural stem cell (NSCs trafficking toward an inflammation site was investigated. [18F]-FDG turns out to be a poor radiopharmaceutical to label NSCs owing to the low labeling efficiency and substantial release of radioactivity from these cells. Efflux of [18F]-FDG from NSCs can be effectively reduced by phloretin in vitro, but inhibition of tracer release is insufficient in vivo for accurate monitoring of stem cell trafficking.

  9. 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.

  10. Inhibition of Myeloperoxidase by N-Acetyl Lysyltyrosylcysteine Amide Reduces Oxidative Stress-Mediated Inflammation, Neuronal Damage, and Neural Stem Cell Injury in a Murine Model of Stroke.

    Science.gov (United States)

    Yu, Guoliang; Liang, Ye; Zheng, Shikan; Zhang, Hao

    2018-02-01

    Recent studies suggest that myeloperoxidase (MPO)-dependent oxidative stress plays a significant role in brain injury in stroke patients. We previously showed that N -acetyl lysyltyrosylcysteine amide (KYC), a novel MPO inhibitor, significantly decreased infarct size, blood-brain barrier leakage, infiltration of myeloid cells, loss of neurons, and apoptosis in the brains of middle cerebral artery occlusion (MCAO) mice. Inhibition of MPO also noticeably reduced neurologic severity scores of MCAO mice. Thus, our data support the idea that MPO-dependent oxidative stress plays a detrimental role in tissue injury in ischemic stroke. However, the mechanisms of MPO-induced injury in stroke are still largely unknown. Here, we present new evidence showing that KYC treatment greatly reduced inflammation by decreasing the number of proinflammatory M1 microglial cells and N1 neutrophils in the brains of MCAO mice. KYC also markedly reduced the expression of high-mobility group box 1, receptor for advanced glycation end products, and nuclear factor- κ B in the brains of MCAO mice. Both neurons and neural stem cells (NSCs) were oxidatively injured by MPO-dependent oxidative stress in MCAO mice. Inhibiting MPO-dependent oxidative stress with KYC significantly reduced oxidative injury and apoptosis in neurons and NSCs. KYC treatment also protected transplanted exogenous NSCs in the brains of MCAO mice. Thus, our studies suggest that MPO-dependent oxidative stress directly injures brain tissues by oxidizing neurons and NSCs and increasing inflammation during stroke. Inhibition of MPO activity with KYC preserves neuronal function and helps the brain recover from injury after stroke. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

  11. Testosterone inhibits facilitating effects of parenting experience on parental behavior and the oxytocin neural system in mice.

    Science.gov (United States)

    Okabe, Shota; Kitano, Kanako; Nagasawa, Miho; Mogi, Kazutaka; Kikusui, Takefumi

    2013-06-13

    Parental behavior in mammals is facilitated by sensory experiences from infant, and by endocrine hormones. However, the interactions between these factors in the parental behavior of nonreproductive adults are not understood. We examined the interactive effects of gonadal hormones and the experience of repeated pup exposure on parental behavior in sexually naive mice. We also compared oxytocin (OT) expression levels in the paraventricular nucleus of the hypothalamus to behavioral outcomes. Clear sex differences were observed in retrieving tests; initial retrieving latency was shorter in females than in males, and 5-time pup exposure shortened retrieving latency in females only. Gonadectomy influenced neither initial retrieving latency nor pup sensitization in females. In contrast, gonadectomy shortened initial retrieving latency and caused pup sensitization in males. Estrogen implants given simultaneously with gonadectomy further shortened the initial retrieving latency in males, but pup sensitization was not affected and occurred in both sexes. In contrast, simultaneous testosterone implants impaired pup sensitization in both sexes. Similar to the results for responsiveness to pups, the number of OT neurons was increased by gonadectomy in males only. In comparison to gonadectomy only, OT neurons were decreased by simultaneous testosterone implants, but were not influenced by estrogen in either sex. Considering the parallel inhibitory effects of testosterone on both pup sensitization and number of OT neurons, we postulate that sex differences in parental responsiveness facilitated by repeated pup exposure were caused by an inhibitory effect of testosterone via the OT neural system in mice. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. In vivo temporal property of GABAergic neural transmission in collateral feed-forward inhibition system of hippocampal-prefrontal pathway.

    Science.gov (United States)

    Takita, Masatoshi; Kuramochi, Masahito; Izaki, Yoshinori; Ohtomi, Michiko

    2007-05-30

    Anatomical evidence suggests that rat CA1 hippocampal afferents collaterally innervate excitatory projecting pyramidal neurons and inhibitory interneurons, creating a disynaptic, feed-forward inhibition microcircuit in the medial prefrontal cortex (mPFC). We investigated the temporal relationship between the frequency of paired synaptic transmission and gamma-aminobutyric acid (GABA)ergic receptor-mediated modulation of the microcircuit in vivo under urethane anesthesia. Local perfusions of a GABAa antagonist (-)-bicuculline into the mPFC via microdialysis resulted in a statistically significant disinhibitory effect on intrinsic GABA action, increasing the first and second mPFC responses following hippocampal paired stimulation at interstimulus intervals of 100-200 ms, but not those at 25-50 ms. This (-)-bicuculline-induced disinhibition was compensated by the GABAa agonist muscimol, which itself did not attenuate the intrinsic oscillation of the local field potentials. The perfusion of a sub-minimal concentration of GABAb agonist (R)-baclofen slightly enhanced the synaptic transmission, regardless of the interstimulus interval. In addition to the tonic control by spontaneous fast-spiking GABAergic neurons, it is clear the sequential transmission of the hippocampal-mPFC pathway can phasically drive the collateral feed-forward inhibition system through activation of a GABAa receptor, bringing an active signal filter to the various types of impulse trains that enter the mPFC from the hippocampus in vivo.

  13. 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.

  14. 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)

    Chiou, S.-H.; Chen, S.-J.; Peng, C-H.; Chang, Y.-L.; Ku, H.-H.; Hsu, W.-M.; Ho, Larry L.-T.; Lee, C.-H.

    2006-01-01

    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

  15. Blockade of spinal nerves inhibits expression of neural growth factor in the myocardium at an early stage of acute myocardial infarction in rats.

    Science.gov (United States)

    Yue, W; Guo, Z

    2012-09-01

    Neural growth factor (NGF) is required for healing and sprouting of cardiac sympathetic and sensory nerves and plays important roles in cardiac protection, sustaining cardiac function and regeneration in ischaemic heart disease. The overexpression or lack of the NGF could be harmful to the heart. In this study, we examined the role of spinal nerves in the modulation of expression of the NGF in the myocardium at risk of ischaemia soon after acute myocardial infarction in rats. Coronary artery occlusion (CAO) was carried out in anaesthetized rats with and without preconditioning of blockade of the spinal nerves. The expression of the NGF protein and mRNA in the myocardium at risk of ischaemia was examined using immunohistochemical assay, enzyme-linked immunosorbent assay, and real-time quantitative reverse transcription polymerase chain reaction assay. In the left ventricle, immunoreactive cells and fibre-like structures were mainly located in the myocardium and in the epicardium. The NGF protein expression was increased by two-fold in the myocardium at risk of ischaemia during the 60 min of CAO, while the NGF mRNA was up-regulated three-fold, at 360 min after acute myocardial infarction. The blockade of the spinal nerves completely abolished the up-regulation of the NGF in the myocardium (Pmyocardial infarction, an effect which can be inhibited by the blockade of these nerves.

  16. Methylprednisolone inhibits the proliferation and affects the differentiation of rat spinal cord-derived neural progenitor cells cultured in low oxygen conditions by inhibiting HIF-1α and Hes1 in vitro.

    Science.gov (United States)

    Wang, Wenhao; Wang, Peng; Li, Shiyuan; Yang, Jiewen; Liang, Xinjun; Tang, Yong; Li, Yuxi; Yang, Rui; Wu, Yanfeng; Shen, Huiyong

    2014-09-01

    Although there is much controversy over the use of methylprednisolone (MP), it is one of the main drugs used in the treatment of acute spinal cord injury (SCI). The induction of the proliferation and differentiation of endogenous neural progenitor cells (NPCs) is considered a promising mode of treatment for SCI. However, the effects of MP on spinal cord-derived endogenous NPCs in a low oxygen enviroment remain to be delineated. Thus, the aim of this study was to investigate the potential effects of MP on NPCs cultured under low oxygen conditions in vitro and to elucidate the molecular mechanisms involved. Fetal rat spinal cord-derived NPCs were harvested and divided into 4 groups: 2 groups of cells cultured under normal oxygen conditions and treated with or without MP, and 2 groups incubated in 3% O2 (low oxygen) treated in a similar manner. We found that MP induced suppressive effects on NPC proliferation even under low oxygen conditions (3% O2). The proportion of nestin-positive NPCs decreased from 51.8±2.46% to 36.17±3.55% following the addition of MP and decreased more significantly to 27.20±2.68% in the cells cultured in 3% O2. In addition, a smaller number of glial fibrillary acidic protein (GFAP)-positive cells and a greater number of microtubule-associated protein 2 (MAP2)-positive cells was observed following the addition of MP under both normal (normoxic) and low oxygen (hypoxic) conditions. In response to MP treatment, hypoxia-inducible factor-1α (HIF-1α) and the Notch signaling pathway downstream protein, Hes1, but not the upstream Notch-1 intracelluar domain (NICD), were inhibited. After blocking NICD with a γ-secretase inhibitor (DAPT) MP still inhibited the expression of Hes1. Our results provide insight into the molecular mechanisms responsible for the MP-induced inhibition of proliferation and its effects on differentiation and suggest that HIF-1α and Hes1 play an important role in this effect.

  17. PANP is a novel O-glycosylated PILR{alpha} ligand expressed in neural tissues

    Energy Technology Data Exchange (ETDEWEB)

    Kogure, Amane [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); Shiratori, Ikuo [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Wang, Jing [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); Lanier, Lewis L. [Department of Microbiology and Immunology and the Cancer Research Institute, University of California San Francisco, San Francisco, CA 94143 (United States); Arase, Hisashi, E-mail: arase@biken.osaka-u.ac.jp [Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka 565-0871 (Japan); Laboratory of Immunochemistry, WPI Immunology Frontier Research Center, Osaka University, Osaka 565-0871 (Japan); JST CREST, Saitama 332-0012 (Japan)

    2011-02-18

    Research highlights: {yields} A Novel molecule, PANP, was identified to be a PILR{alpha} ligand. {yields} Sialylated O-glycan structures on PANP were required for PILR{alpha} recognition. {yields} Transcription of PANP was mainly observed in neural tissues. {yields} PANP seems to be involved in immune regulation as a ligand for PILR{alpha}. -- Abstract: PILR{alpha} 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 PILR{alpha} to its ligand CD99 is involved in immune regulation; however, whether there are other PILR{alpha} 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 PILR{alpha}. Transcription of PANP was mainly observed in neural tissues. PILR{alpha}-Ig fusion protein bound cells transfected with PANP and the transfectants stimulated PILR{alpha} 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 PILR{alpha}.

  18. Neural correlates of correct and failed response inhibition in heavy versus light social drinkers: an fMRI study during a go/no-go task by healthy participants.

    Science.gov (United States)

    Campanella, Salvatore; Absil, Julie; Carbia Sinde, Carina; Schroder, Elisa; Peigneux, Philippe; Bourguignon, Mathieu; Petieau, Mathieu; Metens, Thierry; Nouali, Mustapha; Goldman, Serge; Cheron, Guy; Verbanck, Paul; De Tiège, Xavier

    2017-12-01

    The ability to suppress responses that are inappropriate, as well as the mechanisms monitoring the accuracy of actions in order to compensate for errors, is central to human behavior. Neural alterations that prevent stopping an inaccurate response, combined with a decreased ability of error monitoring, are considered to be prominent features of alcohol abuse. Moreover, (i) alterations of these processes have been reported in heavy social drinkers (i.e. young healthy individuals who do not yet exhibit a state of alcohol dependence); and (ii) through longitudinal studies, these alterations have been shown to underlie subsequent disinhibition that may lead to future alcohol use disorders. In the present functional magnetic resonance imaging study, using a contextual Go/No-Go task, we investigated whether different neural networks subtended correct inhibitions and monitoring mechanisms of failed inhibitory trials in light versus heavy social drinkers. We show that, although successful inhibition did not lead to significant changes, neural networks involved in error monitoring are different in light versus heavy drinkers. Thus, while light drinkers exhibited activations in their right inferior frontal, right middle cingulate and left superior temporal areas; heavy drinkers exhibited activations in their right cerebellum, left caudate nucleus, left superior occipital region, and left amygdala. These data are functionally interpreted as reflecting a "visually-driven emotional strategy" vs. an "executive-based" neural response to errors in heavy and light drinkers, respectively. Such a difference is interpreted as a key-factor that may subtend the transition from a controlled social heavy consumption to a state of clinical alcohol dependence.

  19. [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.

    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.

  20. Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

    Science.gov (United States)

    Takiyama, Ken

    2017-12-01

    How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

  1. Neural networks

    International Nuclear Information System (INIS)

    Denby, Bruce; Lindsey, Clark; Lyons, Louis

    1992-01-01

    The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

  2. Ethanol extracts from Portulaca oleracea L. attenuated ischemia/reperfusion induced rat neural injury through inhibition of HMGB1 induced inflammation

    Science.gov (United States)

    Zheng, Chenggang; Liu, Chen; Wang, Wanyin; Tang, Gusheng; Dong, Liwei; Zhou, Juan; Zhong, Zhengrong

    2016-01-01

    It is well demonstrated that the high mobility group box 1 (HMGB1) mediated inflammation has been implicated as one of the important causes for brain damage induced by cerebral ischemia/reperfusion (I/R). In the present study, we assessed the neuro-protective and anti-inflammation effects of the ethanol extracts from Portulaca oleracea L. (EEPO) against cerebral I/R injury in the rat transient middle cerebral artery occlusion (tMCAO) model. Rats were administrated with their respective treatment for 7 days before the MCA occlusion. After that, rats were intraperitoneal injection with chloral hydrate and sacrificed by decapitation, then the serum and brain tissue were collected. The neurological deficit score, infarct size and brain edema were tested. The levels of serum cytokine as TNF-α, IL-1β, INF-γ, IL-6, and HMGB1 and LDH were detected. The protein level of tissue or nucleus HMGB1, IκB and p-p65 were tested, too. The results showed that pretreatment with EEPO significantly decreased the neurological deficit score, infarct size and brain edema. Moreover, EEPO decreased rat serum cytokine level and rat right cortices p-p65 and IκB protein level. In conclusion all these results suggested that pretreatment with EEFPO provided significant protection against cerebral I/R injury in rats might by virtue of its anti-inflammation property through inhibition of increase of neuleus HMGB1. PMID:27904702

  3. Mir-29b Mediates the Neural Tube versus Neural Crest Fate Decision during Embryonic Stem Cell Neural Differentiation.

    Science.gov (United States)

    Xi, Jiajie; Wu, Yukang; Li, Guoping; Ma, Li; Feng, Ke; Guo, Xudong; Jia, Wenwen; Wang, Guiying; Yang, Guang; Li, Ping; Kang, Jiuhong

    2017-08-08

    During gastrulation, the neuroectoderm cells form the neural tube and neural crest. The nervous system contains significantly more microRNAs than other tissues, but the role of microRNAs in controlling the differentiation of neuroectodermal cells into neural tube epithelial (NTE) cells and neural crest cells (NCCs) remains unknown. Using embryonic stem cell (ESC) neural differentiation systems, we found that miR-29b was upregulated in NTE cells and downregulated in NCCs. MiR-29b promoted the differentiation of ESCs into NTE cells and inhibited their differentiation into NCCs. Accordingly, the inhibition of miR-29b significantly inhibited the differentiation of NTE cells. A mechanistic study revealed that miR-29b targets DNA methyltransferase 3a (Dnmt3a) to regulate neural differentiation. Moreover, miR-29b mediated the function of Pou3f1, a critical neural transcription factor. Therefore, our study showed that the Pou3f1-miR-29b-Dnmt3a regulatory axis was active at the initial stage of neural differentiation and regulated the determination of cell fate. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  4. Neural engineering

    CERN Document Server

    2013-01-01

    Neural Engineering, 2nd Edition, contains reviews and discussions of contemporary and relevant topics by leading investigators in the field. It is intended to serve as a textbook at the graduate and advanced undergraduate level in a bioengineering curriculum. This principles and applications approach to neural engineering is essential reading for all academics, biomedical engineers, neuroscientists, neurophysiologists, and industry professionals wishing to take advantage of the latest and greatest in this emerging field.

  5. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

    Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

  6. Targeted Inhibition of the miR-199a/214 Cluster by CRISPR Interference Augments the Tumor Tropism of Human Induced Pluripotent Stem Cell-Derived Neural Stem Cells under Hypoxic Condition

    Directory of Open Access Journals (Sweden)

    Yumei Luo

    2016-01-01

    Full Text Available The human induced pluripotent stem cell (hiPSC provides a breakthrough approach that helps overcoming ethical and allergenic challenges posed in application of neural stem cells (NSCs in targeted cancer gene therapy. However, the tumor-tropic capacity of hiPSC-derived NSCs (hiPS-NSCs still has much room to improve. Here we attempted to promote the tumor tropism of hiPS-NSCs by manipulating the activity of endogenous miR-199a/214 cluster that is involved in regulation of hypoxia-stimulated cell migration. We first developed a baculovirus-delivered CRISPR interference (CRISPRi system that sterically blocked the E-box element in the promoter of the miR-199a/214 cluster with an RNA-guided catalytically dead Cas9 (dCas9. We then applied this CRISPRi system to hiPS-NSCs and successfully suppressed the expression of miR-199a-5p, miR-199a-3p, and miR-214 in the microRNA gene cluster. Meanwhile, the expression levels of their targets related to regulation of hypoxia-stimulated cell migration, such as HIF1A, MET, and MAPK1, were upregulated. Further migration assays demonstrated that the targeted inhibition of the miR-199a/214 cluster significantly enhanced the tumor tropism of hiPS-NSCs both in vitro and in vivo. These findings suggest a novel application of CRISPRi in NSC-based tumor-targeted gene therapy.

  7. 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.

  8. FGF Signaling Transforms Non-neural Ectoderm into Neural Crest

    OpenAIRE

    Yardley, Nathan; García-Castro, Martín I.

    2012-01-01

    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 respons...

  9. Inhibition of Notch Signaling in Human Embryonic Stem Cell-Derived Neural Stem Cells Delays G1/S Phase Transition and Accelerates Neuronal Differentiation In Vitro and In Vivo

    Czech Academy of Sciences Publication Activity Database

    Borghese, L.; Doležalová, Dáša; Opitz, T.; Haupt, S.; Leinhaas, A.; Steinfarz, B.; Koch, P.; Edenhofer, F.; Hampl, Aleš; Brüstle, O.

    2010-01-01

    Roč. 28, č. 5 (2010), s. 955-964 ISSN 1066-5099 Grant - others:GA MŠk(CZ) 1M0538; EC FP6 project ESTOOLS(XE) LSHG-CT-2006-018739; EC FP7 project NeuroStemcell(XE) HEALTH-2007-B-22943 Program:1M Institutional research plan: CEZ:AV0Z50390703 Keywords : neural stem cells * notch * neuron Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 7.871, year: 2010

  10. Differentiation state determines neural effects on microvascular endothelial cells

    Energy Technology Data Exchange (ETDEWEB)

    Muffley, Lara A., E-mail: muffley@u.washington.edu [University of Washington, Campus Box 359796, 300 9th Avenue, Seattle, WA 98104 (United States); Pan, Shin-Chen, E-mail: pansc@mail.ncku.edu.tw [University of Washington, Campus Box 359796, 300 9th Avenue, Seattle, WA 98104 (United States); Smith, Andria N., E-mail: gnaunderwater@gmail.com [University of Washington, Campus Box 359796, 300 9th Avenue, Seattle, WA 98104 (United States); Ga, Maricar, E-mail: marga16@uw.edu [University of Washington, Campus Box 359796, 300 9th Avenue, Seattle, WA 98104 (United States); Hocking, Anne M., E-mail: ahocking@u.washington.edu [University of Washington, Campus Box 359796, 300 9th Avenue, Seattle, WA 98104 (United States); Gibran, Nicole S., E-mail: nicoleg@u.washington.edu [University of Washington, Campus Box 359796, 300 9th Avenue, Seattle, WA 98104 (United States)

    2012-10-01

    Growing evidence indicates that nerves and capillaries interact paracrinely in uninjured skin and cutaneous wounds. Although mature neurons are the predominant neural cell in the skin, neural progenitor cells have also been detected in uninjured adult skin. The aim of this study was to characterize differential paracrine effects of neural progenitor cells and mature sensory neurons on dermal microvascular endothelial cells. Our results suggest that neural progenitor cells and mature sensory neurons have unique secretory profiles and distinct effects on dermal microvascular endothelial cell proliferation, migration, and nitric oxide production. Neural progenitor cells and dorsal root ganglion neurons secrete different proteins related to angiogenesis. Specific to neural progenitor cells were dipeptidyl peptidase-4, IGFBP-2, pentraxin-3, serpin f1, TIMP-1, TIMP-4 and VEGF. In contrast, endostatin, FGF-1, MCP-1 and thrombospondin-2 were specific to dorsal root ganglion neurons. Microvascular endothelial cell proliferation was inhibited by dorsal root ganglion neurons but unaffected by neural progenitor cells. In contrast, microvascular endothelial cell migration in a scratch wound assay was inhibited by neural progenitor cells and unaffected by dorsal root ganglion neurons. In addition, nitric oxide production by microvascular endothelial cells was increased by dorsal root ganglion neurons but unaffected by neural progenitor cells. -- Highlights: Black-Right-Pointing-Pointer Dorsal root ganglion neurons, not neural progenitor cells, regulate microvascular endothelial cell proliferation. Black-Right-Pointing-Pointer Neural progenitor cells, not dorsal root ganglion neurons, regulate microvascular endothelial cell migration. Black-Right-Pointing-Pointer Neural progenitor cells and dorsal root ganglion neurons do not effect microvascular endothelial tube formation. Black-Right-Pointing-Pointer Dorsal root ganglion neurons, not neural progenitor cells, regulate

  11. A chemical screen in zebrafish embryonic cells establishes that Akt activation is required for neural crest development.

    Science.gov (United States)

    Ciarlo, Christie; Kaufman, Charles K; Kinikoglu, Beste; Michael, Jonathan; Yang, Song; D Amato, Christopher; Blokzijl-Franke, Sasja; den Hertog, Jeroen; Schlaeger, Thorsten M; Zhou, Yi; Liao, Eric; Zon, Leonard I

    2017-08-23

    The neural crest is a dynamic progenitor cell population that arises at the border of neural and non-neural ectoderm. The inductive roles of FGF, Wnt, and BMP at the neural plate border are well established, but the signals required for subsequent neural crest development remain poorly characterized. Here, we conducted a screen in primary zebrafish embryo cultures for chemicals that disrupt neural crest development, as read out by crestin:EGFP expression. We found that the natural product caffeic acid phenethyl ester (CAPE) disrupts neural crest gene expression, migration, and melanocytic differentiation by reducing Sox10 activity. CAPE inhibits FGF-stimulated PI3K/Akt signaling, and neural crest defects in CAPE-treated embryos are suppressed by constitutively active Akt1. Inhibition of Akt activity by constitutively active PTEN similarly decreases crestin expression and Sox10 activity. Our study has identified Akt as a novel intracellular pathway required for neural crest differentiation.

  12. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  13. 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.

  14. 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 ...

  15. 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

  16. artificial neural network (ann)

    African Journals Online (AJOL)

    2004-08-18

    Aug 18, 2004 ... forecasting models and artificial intelligence techniques and have become one of the major research fields (Kher and Joshin, 2003). (a) Artificial Neural Network and Electrical Load. Prediction. Neural network analysis is an Artificial Intelligence. (AI) approach to mathematical modeling. Neural. Networks ...

  17. Neural electrical activity and neural network growth.

    Science.gov (United States)

    Gafarov, F M

    2018-02-09

    The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. Chaotic diagonal recurrent neural network

    International Nuclear Information System (INIS)

    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 and learning 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. (interdisciplinary physics and related areas of science and technology)

  19. 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.

  20. Requirement of mouse BCCIP for neural development and progenitor proliferation.

    Directory of Open Access Journals (Sweden)

    Yi-Yuan Huang

    Full Text Available Multiple DNA repair pathways are involved in the orderly development of neural systems at distinct stages. The homologous recombination (HR pathway is required to resolve stalled replication forks and critical for the proliferation of progenitor cells during neural development. BCCIP is a BRCA2 and CDKN1A interacting protein implicated in HR and inhibition of DNA replication stress. In this study, we determined the role of BCCIP in neural development using a conditional BCCIP knock-down mouse model. BCCIP deficiency impaired embryonic and postnatal neural development, causing severe ataxia, cerebral and cerebellar defects, and microcephaly. These development defects are associated with spontaneous DNA damage and subsequent cell death in the proliferative cell populations of the neural system during embryogenesis. With in vitro neural spheroid cultures, BCCIP deficiency impaired neural progenitor's self-renewal capability, and spontaneously activated p53. These data suggest that BCCIP and its anti-replication stress functions are essential for normal neural development by maintaining an orderly proliferation of neural progenitors.

  1. Methylene blue promotes quiescence of rat neural progenitor cells

    Directory of Open Access Journals (Sweden)

    LUOKUN eXIE

    2014-10-01

    Full Text Available Neural stem cell-based treatment holds a new therapeutic opportunity for neurodegenerative disorders. Here, we investigated the effect of methylene blue on proliferation and differentiation of rat neural progenitor cells (NPCs both in vitro and in vivo. We found that methylene blue inhibited proliferation and promoted quiescence of NPCs in vitro without affecting committed neuronal differentiation. Consistently, intracerebroventricular infusion of methylene blue significantly inhibited neural progenitor cell proliferation at the subventricular zone (SVZ. Methylene blue inhibited mTOR signaling along with down-regulation of cyclins in NPCs in vitro and in vivo. In summary, our study indicates that methylene blue may delay NPC senescence through enhancing NPCs quiescence.

  2. Xenopus reduced folate carrier regulates neural crest development epigenetically.

    Directory of Open Access Journals (Sweden)

    Jiejing Li

    Full Text Available Folic acid deficiency during pregnancy causes birth neurocristopathic malformations resulting from aberrant development of neural crest cells. The Reduced folate carrier (RFC is a membrane-bound receptor for facilitating transfer of reduced folate into the cells. RFC knockout mice are embryonic lethal and develop multiple malformations, including neurocristopathies. Here we show that XRFC is specifically expressed in neural crest tissues in Xenopus embryos and knockdown of XRFC by specific morpholino results in severe neurocristopathies. Inhibition of RFC blocked the expression of a series of neural crest marker genes while overexpression of RFC or injection of 5-methyltetrahydrofolate expanded the neural crest territories. In animal cap assays, knockdown of RFC dramatically reduced the mono- and trimethyl-Histone3-K4 levels and co-injection of the lysine methyltransferase hMLL1 largely rescued the XRFC morpholino phenotype. Our data revealed that the RFC mediated folate metabolic pathway likely potentiates neural crest gene expression through epigenetic modifications.

  3. Fuzzy and neural control

    Science.gov (United States)

    Berenji, Hamid R.

    1992-01-01

    Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

  4. 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...

  5. What Is Neural Plasticity?

    Science.gov (United States)

    von Bernhardi, Rommy; Bernhardi, Laura Eugenín-von; Eugenín, Jaime

    2017-01-01

    "Neural plasticity" refers to the capacity of the nervous system to modify itself, functionally and structurally, in response to experience and injury. As the various chapters in this volume show, plasticity is a key component of neural development and normal functioning of the nervous system, as well as a response to the changing environment, aging, or pathological insult. This chapter discusses how plasticity is necessary not only for neural networks to acquire new functional properties, but also for them to remain robust and stable. The article also reviews the seminal proposals developed over the years that have driven experiments and strongly influenced concepts of neural plasticity.

  6. 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...

  7. Neural Networks: Implementations and Applications

    NARCIS (Netherlands)

    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

  8. 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…

  9. Neural Machine Translation

    OpenAIRE

    Koehn, Philipp

    2017-01-01

    Draft of textbook chapter on neural machine translation. a comprehensive treatment of the topic, ranging from introduction to neural networks, computation graphs, description of the currently dominant attentional sequence-to-sequence model, recent refinements, alternative architectures and challenges. Written as chapter for the textbook Statistical Machine Translation. Used in the JHU Fall 2017 class on machine translation.

  10. Cranial and trunk neural crest cells use different mechanisms for attachment to extracellular matrices

    OpenAIRE

    Lallier, Thomas; Leblanc, Gabrielle; Artinger, Kristin B.; Bronner-Fraser, Marianne

    1992-01-01

    We have used a quantitative cell attachment assay to compare the interactions of cranial and trunk neural crest cells with the extracellular matrix (ECM) molecules fibronectin, laminin and collagen types I and IV. Antibodies to the β_1 subunit of integrin inhibited attachment under all conditions tested, suggesting that integrins mediate neural crest cell interactions with these ECM molecules. The HNK-1 antibody against a surface carbohydrate epitope under certain conditions inhibited both cr...

  11. Dynamics of neural cryptography

    International Nuclear Information System (INIS)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-01-01

    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

  12. 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.

  13. 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.

  14. 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.

  15. ANT Advanced Neural Tool

    International Nuclear Information System (INIS)

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

    1996-01-01

    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

  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 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.

  18. Tomography using neural networks

    International Nuclear Information System (INIS)

    Demeter, G.; Zoletnik, S.

    1997-01-01

    Neural networks have been used for fast measurement evaluation in plasma physics, including nonlinear curve fitting to experimental data. Such an approach for fast evaluation of tomographic measurements was utilized on the MT-1M tokamak, especially in the study of impurity injection using laser accelerated pellets and of the transport of these injected impurities. Neural networks were studied for fast processing of tomographic data and large numbers of tomographic data

  19. Neural network applications

    Science.gov (United States)

    Padgett, Mary L.; Desai, Utpal; Roppel, T.A.; White, Charles R.

    1993-01-01

    A design procedure is suggested for neural networks which accommodates the inclusion of such knowledge-based systems techniques as fuzzy logic and pairwise comparisons. The use of these procedures in the design of applications combines qualitative and quantitative factors with empirical data to yield a model with justifiable design and parameter selection procedures. The procedure is especially relevant to areas of back-propagation neural network design which are highly responsive to the use of precisely recorded expert knowledge.

  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. Variational Neural Machine Translation

    OpenAIRE

    Zhang, Biao; Xiong, Deyi; Su, Jinsong; Duan, Hong; Zhang, Min

    2016-01-01

    Models of neural machine translation are often from a discriminative family of encoderdecoders that learn a conditional distribution of a target sentence given a source sentence. In this paper, we propose a variational model to learn this conditional distribution for neural machine translation: a variational encoderdecoder model that can be trained end-to-end. Different from the vanilla encoder-decoder model that generates target translations from hidden representations of source sentences al...

  2. Neurally Mediated Syncope

    OpenAIRE

    Zaqqa, Munir; Massumi, Ali

    2000-01-01

    Neurally mediated syncope is a disorder of the autonomic regulation of postural tone, which results in hypotension, bradycardia, and loss of consciousness. A wide variety of stimuli can trigger this reflex, the most common stimulus being orthostatic stress. Typically, a patient with neurally mediated syncope experiences nausea, lightheadedness, a feeling of warmth, and pallor before abruptly losing consciousness. If the cause of syncope is unclear, a stepwise approach is necessary to arrive a...

  3. Radiation response of rodent neural precursor cells

    International Nuclear Information System (INIS)

    Limoli, C.L.; Fike, J.R.

    2003-01-01

    Full text: Therapeutic irradiation of the brain can cause cognitive dysfunction that is not treatable or well understood. Several lines of evidence from our laboratory suggest that radiation induced inhibition of neurogenesis in the hippocampus may be involved. To understand the mechanisms underlying these observations, we initiated studies using neural precursor cells isolated from the adult rat hippocampus. Cells were cultured exponentially and analyzed for acute (0-24h) and chronic (3-33 day) changes in apoptosis and oxidative stress following exposure to X-rays. Oxidative stress was measured using a dye sensitive to reactive oxygen species (ROS) and apoptosis was measured using annexin V binding; each endpoint was quantified by fluorescent automated cell sorting (FACS). Following exposure to X-rays, neural precursor cells exhibit a dose-responsive increase in the level of ROS and apoptosis over acute and chronic time frames. ROS and apoptosis were maximal at 12h, increasing 35 and 37% respectively over that of unirradiated controls. ROS and apoptosis peaked again at 24h, increasing 31 and 21% respectively over controls. Chronic levels of ROS and apoptosis were persistently elevated in a dose-dependent manner. ROS showed significant increases (34-180%) over a 3-4 week interval, while increases in apoptosis were less dramatic, rising 45% by week one before dropping to background. Irradiation of rat neural precursor cells was associated with an increase in p53 protein levels, and the activation of G1/S and G2/M checkpoints. These data suggest that the apoptotic and ROS responses may be tied to p53 dependent regulation of cell cycle control and stress activated pathways. We propose that oxidative stress plays a critical role in the radiation response of neural precursor cells, and discuss how this might contribute to the inhibition of neurogenesis and the cognitive impairment observed in the irradiated CNS

  4. The Neural Decoding Toolbox

    Directory of Open Access Journals (Sweden)

    Ethan eMeyers

    2013-05-01

    Full Text Available Population decoding is a powerful way to analyze neural data, however currently only a small percentage of systems neuroscience researchers use this method. In order to increase the use of population decoding, we have created the Neural Decoding Toolbox (NDT which is a Matlab package that makes it easy to apply population decoding analyses to neural activity. The design of the toolbox revolves around four abstract object classes which enables users to interchange particular modules in order to try different analyses while keeping the rest of the processing stream intact. The toolbox is capable of analyzing data from many different types of recording modalities, and we give examples of how it can be used to decode basic visual information from neural spiking activity and how it can be used to examine how invariant the activity of a neural population is to stimulus transformations. Overall this toolbox will make it much easier for neuroscientists to apply population decoding analyses to their data, which should help increase the pace of discovery in neuroscience.

  5. The neural decoding toolbox.

    Science.gov (United States)

    Meyers, Ethan M

    2013-01-01

    Population decoding is a powerful way to analyze neural data, however, currently only a small percentage of systems neuroscience researchers use this method. In order to increase the use of population decoding, we have created the Neural Decoding Toolbox (NDT) which is a Matlab package that makes it easy to apply population decoding analyses to neural activity. The design of the toolbox revolves around four abstract object classes which enables users to interchange particular modules in order to try different analyses while keeping the rest of the processing stream intact. The toolbox is capable of analyzing data from many different types of recording modalities, and we give examples of how it can be used to decode basic visual information from neural spiking activity and how it can be used to examine how invariant the activity of a neural population is to stimulus transformations. Overall this toolbox will make it much easier for neuroscientists to apply population decoding analyses to their data, which should help increase the pace of discovery in neuroscience.

  6. Neural Semantic Encoders.

    Science.gov (United States)

    Munkhdalai, Tsendsuren; Yu, Hong

    2017-04-01

    We present a memory augmented neural network for natural language understanding: Neural Semantic Encoders. NSE is equipped with a novel memory update rule and has a variable sized encoding memory that evolves over time and maintains the understanding of input sequences through read , compose and write operations. NSE can also access multiple and shared memories. In this paper, we demonstrated the effectiveness and the flexibility of NSE on five different natural language tasks: natural language inference, question answering, sentence classification, document sentiment analysis and machine translation where NSE achieved state-of-the-art performance when evaluated on publically available benchmarks. For example, our shared-memory model showed an encouraging result on neural machine translation, improving an attention-based baseline by approximately 1.0 BLEU.

  7. The neural crest and neural crest cells: discovery and significance ...

    Indian Academy of Sciences (India)

    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.

  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. Deconvolution using a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, S.K.

    1990-11-15

    Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

  10. Death and rebirth of neural activity in sparse inhibitory networks

    Science.gov (United States)

    Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro

    2017-05-01

    Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.

  11. 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.

  12. 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.

  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. Neural Networks and Micromechanics

    Science.gov (United States)

    Kussul, Ernst; Baidyk, Tatiana; Wunsch, Donald C.

    The title of the book, "Neural Networks and Micromechanics," seems artificial. However, the scientific and technological developments in recent decades demonstrate a very close connection between the two different areas of neural networks and micromechanics. The purpose of this book is to demonstrate this connection. Some artificial intelligence (AI) methods, including neural networks, could be used to improve automation system performance in manufacturing processes. However, the implementation of these AI methods within industry is rather slow because of the high cost of conducting experiments using conventional manufacturing and AI systems. To lower the cost, we have developed special micromechanical equipment that is similar to conventional mechanical equipment but of much smaller size and therefore of lower cost. This equipment could be used to evaluate different AI methods in an easy and inexpensive way. The proved methods could be transferred to industry through appropriate scaling. In this book, we describe the prototypes of low cost microequipment for manufacturing processes and the implementation of some AI methods to increase precision, such as computer vision systems based on neural networks for microdevice assembly and genetic algorithms for microequipment characterization and the increase of microequipment precision.

  15. Neural systems for control

    National Research Council Canada - National Science Library

    Omidvar, Omid; Elliott, David L

    1997-01-01

    ... is reprinted with permission from A. Barto, "Reinforcement Learning," Handbook of Brain Theory and Neural Networks, M.A. Arbib, ed.. The MIT Press, Cambridge, MA, pp. 804-809, 1995. Chapter 4, Figures 4-5 and 7-9 and Tables 2-5, are reprinted with permission, from S. Cho, "Map Formation in Proprioceptive Cortex," International Jour...

  16. Learning from neural control.

    Science.gov (United States)

    Wang, Cong; Hill, David J

    2006-01-01

    One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.

  17. Neural Network Studies

    Science.gov (United States)

    1993-07-01

    simpler linearly separable majority function (Ahmad, Tesauro , 1988), the former has limited applicability to realistic problems and the latter has been...anwered. 6. References Ahmad, S., G. Tesauro , "Scaling and Generalization in Neural Networks: A Case Study", Proceedings of the 1988 Connectionist

  18. Introduction to neural networks

    International Nuclear Information System (INIS)

    Pavlopoulos, P.

    1996-01-01

    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

  19. Neural Expert Systems

    Czech Academy of Sciences Publication Activity Database

    Šíma, Jiří

    1995-01-01

    Roč. 8, č. 2 (1995), s. 261-271 ISSN 0893-6080 R&D Projects: GA ČR GA201/95/0976 Keywords : expert system * knowledge representation * multilayered neural network * back propagation * interval neuron function * incomplete information * explanation Impact factor: 1.262, year: 1995

  20. Echoes in correlated neural systems

    International Nuclear Information System (INIS)

    Helias, M; Tetzlaff, T; Diesmann, M

    2013-01-01

    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. (paper)

  1. Artificial neural/chemical networks

    Science.gov (United States)

    Caulfield, H. John

    2001-11-01

    What strikes the attention of a neural network designer is that the chemicals seem to work not so much on individual neural circuits as on neural cell assemblies. These are large blocks of neural networks that carry out high level tasks using their constituent networks as needed. It follows to us that we might seek ways of achieving that same sort of behavior in an artificial neural network. In what follows, we provide two examples of how that might be done in an artificial system.

  2. Bioprinting for Neural Tissue Engineering.

    Science.gov (United States)

    Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

    2018-01-01

    Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. INHIBITION IN SPEAKING PERFORMANCE

    Directory of Open Access Journals (Sweden)

    Isna Humaera

    2015-09-01

    Full Text Available The most common problem encountered by the learner in the language acquisition process is learner inhibition. Inhibition refers to a temperamental tendency to display wariness, fearfulness, or restrain in response to unfamiliar people, objects, and situations. There are some factors that cause inhibition, such as lack of motivation, shyness, self-confidence, self-esteem, and language ego. There are also levels of inhibition, it refers to kinds of inhibition and caused of inhibition itself. Teacher can support their students to reduce their inhibition effect by many ways, one of them by creating good classroom management including establishing good rapport between teacher and learners.

  4. Spike propagation in driven chain networks with dominant global inhibition

    International Nuclear Information System (INIS)

    Chang Wonil; Jin, Dezhe Z.

    2009-01-01

    Spike propagation in chain networks is usually studied in the synfire regime, in which successive groups of neurons are synaptically activated sequentially through the unidirectional excitatory connections. Here we study the dynamics of chain networks with dominant global feedback inhibition that prevents the synfire activity. Neural activity is driven by suprathreshold external inputs. We analytically and numerically demonstrate that spike propagation along the chain is a unique dynamical attractor in a wide parameter regime. The strong inhibition permits a robust winner-take-all propagation in the case of multiple chains competing via the inhibition.

  5. Response inhibition is associated with white matter microstructure in children

    DEFF Research Database (Denmark)

    Madsen, Kathrine Skak; Baaré, William; Vestergaard, Martin

    2010-01-01

    the relationship between response inhibition, as measured with the stop-signal task, and indices of regional white matter microstructure in typically-developing children. We hypothesized that better response inhibition performance would be associated with higher fractional anisotropy (FA) in fibre tracts within...... to the prediction of performance variability. Observed associations may be related to variation in phase of maturation, to activity-dependent alterations in the network subserving response inhibition, or to stable individual differences in underlying neural system connectivity. (C) 2009 Elsevier Ltd. All rights...... reserved....

  6. 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.

  7. Neural tissue-spheres

    DEFF Research Database (Denmark)

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

    2007-01-01

    maintained their neurogenic potential throughout 77 days of propagation, while the ability of anterior NTS to generate neurons severely declined from day 40. The present procedure describes isolation and long-term expansion of forebrain SVZ tissue with potential preservation of the endogenous cellular......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...... derived from three rostro-caudal levels of the lateral ventricles (anterior, intermediate and posterior) and propagated separately. Explants from all three levels produced proliferating NTS, but "anterior" NTS in general grew to smaller sizes than "intermediate" and "posterior" NTS. Posterior NTS moreover...

  8. 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.

  9. Neurally-mediated sincope.

    Science.gov (United States)

    Can, I; Cytron, J; Jhanjee, R; Nguyen, J; Benditt, D G

    2009-08-01

    Syncope is a syndrome characterized by a relatively sudden, temporary and self-terminating loss of consciousness; the causes may vary, but they have in common a temporary inadequacy of cerebral nutrient flow, usually due to a fall in systemic arterial pressure. However, while syncope is a common problem, it is only one explanation for episodic transient loss of consciousness (TLOC). Consequently, diagnostic evaluation should start with a broad consideration of real or seemingly real TLOC. Among those patients in whom TLOC is deemed to be due to ''true syncope'', the focus may then reasonably turn to assessing the various possible causes; in this regard, the neurally-mediated syncope syndromes are among the most frequently encountered. There are three common variations: vasovagal syncope (often termed the ''common'' faint), carotid sinus syndrome, and the so-called ''situational faints''. Defining whether the cause is due to a neurally-mediated reflex relies heavily on careful history taking and selected testing (e.g., tilt-test, carotid massage). These steps are important. Despite the fact that neurally-mediated faints are usually relatively benign from a mortality perspective, they are nevertheless only infrequently an isolated event; neurally-mediated syncope tends to recur, and physical injury resulting from falls or accidents, diminished quality-of-life, and possible restriction from employment or avocation are real concerns. Consequently, defining the specific form and developing an effective treatment strategy are crucial. In every case the goal should be to determine the cause of syncope with sufficient confidence to provide patients and family members with a reliable assessment of prognosis, recurrence risk, and treatment options.

  10. 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. .

  11. Neural networks for triggering

    International Nuclear Information System (INIS)

    Denby, B.; Campbell, M.; Bedeschi, F.; Chriss, N.; Bowers, C.; Nesti, F.

    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

  12. Deep Neural Yodelling

    OpenAIRE

    Pfäffli, Daniel (Autor/in)

    2018-01-01

    Yodel music differs from most other genres by exercising the transition from chest voice to falsetto with an audible glottal stop which is recognised even by laymen. Yodel often consists of a yodeller with a choir accompaniment. In Switzerland, it is differentiated between the natural yodel and yodel songs. Today's approaches to music generation with machine learning algorithms are based on neural networks, which are best described by stacked layers of neurons which are connected with neurons...

  13. Structured Pyramidal Neural Networks.

    Science.gov (United States)

    Soares, Alessandra M; Fernandes, Bruno J T; Bastos-Filho, Carmelo J A

    2017-02-09

    The Pyramidal Neural Networks (PNN) are an example of a successful recently proposed model inspired by the human visual system and deep learning theory. PNNs are applied to computer vision and based on the concept of receptive fields. This paper proposes a variation of PNN, named here as Structured Pyramidal Neural Network (SPNN). SPNN has self-adaptive variable receptive fields, while the original PNNs rely on the same size for the fields of all neurons, which limits the model since it is not possible to put more computing resources in a particular region of the image. Another limitation of the original approach is the need to define values for a reasonable number of parameters, which can turn difficult the application of PNNs in contexts in which the user does not have experience. On the other hand, SPNN has a fewer number of parameters. Its structure is determined using a novel method with Delaunay Triangulation and k-means clustering. SPNN achieved better results than PNNs and similar performance when compared to Convolutional Neural Network (CNN) and Support Vector Machine (SVM), but using lower memory capacity and processing time.

  14. miR-381 Regulates Neural Stem Cell Proliferation and Differentiation via Regulating Hes1 Expression.

    Directory of Open Access Journals (Sweden)

    Xiaodong Shi

    Full Text Available Neural stem cells are self-renewing, multipotent and undifferentiated precursors that retain the capacity for differentiation into both glial (astrocytes and oligodendrocytes and neuronal lineages. Neural stem cells offer cell-based therapies for neurological disorders such as Alzheimer's disease, Parkinson's disease, Huntington's disease and spinal cord injuries. However, their cellular behavior is poorly understood. MicroRNAs (miRNAs are a class of small noncoding RNAs involved in cell development, proliferation and differentiation through regulating gene expression at post-transcriptional level. The role of miR-381 in the development of neural stem cells remains unknown. In this study, we showed that overexpression of miR-381 promoted neural stem cells proliferation. It induced the neural stem cells differentiation to neurons and inhibited their differentiation to astrocytes. Furthermore, we identified HES1 as a direct target of miR-381 in neural stem cells. Moreover, re-expression of HES1 impaired miR-381-induced promotion of neural stem cells proliferation and induce neural stem cells differentiation to neurons. In conclusion, miR-381 played important role in neural stem cells proliferation and differentiation.

  15. Neural Based Orthogonal Data Fitting The EXIN Neural Networks

    CERN Document Server

    Cirrincione, Giansalvo

    2008-01-01

    Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Wh

  16. Neural Circuitry Based on Single Electron Transistors and Single Electron Memories

    Directory of Open Access Journals (Sweden)

    Aïmen BOUBAKER

    2014-05-01

    Full Text Available In this paper, we propose and explain a neural circuitry based on single electron transistors ‘SET’ which can be used in classification and recognition. We implement, after that, a Winner-Take-All ‘WTA’ neural network with lateral inhibition architecture. The original idea of this work is reflected, first, in the proposed new single electron memory ‘SEM’ design by hybridising two promising Single Electron Memory ‘SEM’ and the MTJ/Ring memory and second, in modeling and simulation results of neural memory based on SET. We prove the charge storage in quantum dot in two types of memories.

  17. The Complexity of Dynamics in Small Neural Circuits.

    Directory of Open Access Journals (Sweden)

    Diego Fasoli

    2016-08-01

    Full Text Available Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing.

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

    International Nuclear Information System (INIS)

    Wang, Guang; Li, Yan; Wang, Xiao-yu; Han, Zhe; Chuai, Manli; Wang, Li-jing; Ho Lee, Kenneth Ka; Geng, Jian-guo; Yang, Xuesong

    2013-01-01

    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 + 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

  19. 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

  20. [Artificial neural networks in Neurosciences].

    Science.gov (United States)

    Porras Chavarino, Carmen; Salinas Martínez de Lecea, José María

    2011-11-01

    This article shows that artificial neural networks are used for confirming the relationships between physiological and cognitive changes. Specifically, we explore the influence of a decrease of neurotransmitters on the behaviour of old people in recognition tasks. This artificial neural network recognizes learned patterns. When we change the threshold of activation in some units, the artificial neural network simulates the experimental results of old people in recognition tasks. However, the main contributions of this paper are the design of an artificial neural network and its operation inspired by the nervous system and the way the inputs are coded and the process of orthogonalization of patterns.

  1. Accelerating Learning By Neural Networks

    Science.gov (United States)

    Toomarian, Nikzad; Barhen, Jacob

    1992-01-01

    Electronic neural networks made to learn faster by use of terminal teacher forcing. Method of supervised learning involves addition of teacher forcing functions to excitations fed as inputs to output neurons. Initially, teacher forcing functions are strong enough to force outputs to desired values; subsequently, these functions decay with time. When learning successfully completed, terminal teacher forcing vanishes, and dynamics or neural network become equivalent to those of conventional neural network. Simulated neural network with terminal teacher forcing learned to produce close approximation of circular trajectory in 400 iterations.

  2. 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.

  3. Differential Protection of Generator by Using Neural Network, Fuzzy Neural and Fuzzy Neural Petri Net

    OpenAIRE

    Prof. Dr. Abduladhem A. Ali; Prof. Dr. Abduladhem A. Ali; Ahmed Thamer Radhi

    2012-01-01

    This paper deals with the applications of Artificial Intelligence techniques for detecting internalfaults in Power generators. Three techniques are used which are Neural Net (NN), FuzzyNeural Net (FNN) and Fuzzy Neural Petri Net (FNPN) to implement differential protection ofgenerator. MATLAB toolbox has been used for simulations and generation of faults data fortraining the programs for different faults cases and to implement the relays. Results ofdifferent fault cases are presented and these...

  4. Optics in neural computation

    Science.gov (United States)

    Levene, Michael John

    In all attempts to emulate the considerable powers of the brain, one is struck by both its immense size, parallelism, and complexity. While the fields of neural networks, artificial intelligence, and neuromorphic engineering have all attempted oversimplifications on the considerable complexity, all three can benefit from the inherent scalability and parallelism of optics. This thesis looks at specific aspects of three modes in which optics, and particularly volume holography, can play a part in neural computation. First, holography serves as the basis of highly-parallel correlators, which are the foundation of optical neural networks. The huge input capability of optical neural networks make them most useful for image processing and image recognition and tracking. These tasks benefit from the shift invariance of optical correlators. In this thesis, I analyze the capacity of correlators, and then present several techniques for controlling the amount of shift invariance. Of particular interest is the Fresnel correlator, in which the hologram is displaced from the Fourier plane. In this case, the amount of shift invariance is limited not just by the thickness of the hologram, but by the distance of the hologram from the Fourier plane. Second, volume holography can provide the huge storage capacity and high speed, parallel read-out necessary to support large artificial intelligence systems. However, previous methods for storing data in volume holograms have relied on awkward beam-steering or on as-yet non- existent cheap, wide-bandwidth, tunable laser sources. This thesis presents a new technique, shift multiplexing, which is capable of very high densities, but which has the advantage of a very simple implementation. In shift multiplexing, the reference wave consists of a focused spot a few millimeters in front of the hologram. Multiplexing is achieved by simply translating the hologram a few tens of microns or less. This thesis describes the theory for how shift

  5. 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).

  6. 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...

  7. Neural networks at the Tevatron

    International Nuclear Information System (INIS)

    Badgett, W.; Burkett, K.; Campbell, M.K.; Wu, D.Y.; Bianchin, S.; DeNardi, M.; Pauletta, G.; Santi, L.; Caner, A.; Denby, B.; Haggerty, H.; Lindsey, C.S.; Wainer, N.; Dall'Agata, M.; Johns, K.; Dickson, M.; Stanco, L.; Wyss, J.L.

    1992-10-01

    This paper summarizes neural network applications at the Fermilab Tevatron, including the first online hardware application in high energy physics (muon tracking): the CDF and DO neural network triggers; offline quark/gluon discrimination at CDF; ND a new tool for top to multijets recognition at CDF

  8. 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...

  9. The Neural Support Vector Machine

    NARCIS (Netherlands)

    Wiering, Marco; van der Ree, Michiel; Embrechts, Mark; Stollenga, Marijn; Meijster, Arnold; Nolte, A; Schomaker, Lambertus

    2013-01-01

    This paper describes a new machine learning algorithm for regression and dimensionality reduction tasks. The Neural Support Vector Machine (NSVM) is a hybrid learning algorithm consisting of neural networks and support vector machines (SVMs). The output of the NSVM is given by SVMs that take a

  10. Cooperative Microsystems and Neural Interfaces

    Science.gov (United States)

    2009-03-04

    Syst Rehab Engin 16: 453-472 (2008) Targeted Reinnervation FINE Approved For Public Release, Distribution Unlimited Peripheral Nerve Microsystems...Outline • Signaling in the Nervous System - Signal sources of cortex and peripheral nerve • Clinically Useful Neural Interfaces • Cortical Recording...Arrays • Peripheral Nerve Interfaces • Challenges and Opportunities for Microsystems in New Neural Interfaces Approved For Public Release

  11. Optoelectronic Implementation of Neural Networks

    Indian Academy of Sciences (India)

    optical neural network using photo refractive crystals and realized interconnection density of 10 8 to. 1010 per cm3. • B Javidi and others designed a correlato.,. based two-layer neural network associated with a supervised perceptron learning algorithm for r~al-time face recognition. electronic wiring altogether and replace it ...

  12. 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....

  13. A neural network model of harmonic detection

    Science.gov (United States)

    Lewis, Clifford F.

    2003-04-01

    Harmonic detection theories postulate that a virtual pitch is perceived when a sufficient number of harmonics is present. The harmonics need not be consecutive, but higher harmonics contribute less than lower harmonics [J. Raatgever and F. A. Bilsen, in Auditory Physiology and Perception, edited by Y. Cazals, K. Horner, and L. Demany (Pergamon, Oxford, 1992), pp. 215-222 M. K. McBeath and J. F. Wayand, Abstracts of the Psychonom. Soc. 3, 55 (1998)]. A neural network model is presented that has the potential to simulate this operation. Harmonics are first passed through a bank of rounded exponential filters with lateral inhibition. The results are used as inputs for an autoassociator neural network. The model is trained using harmonic data for symphonic musical instruments, in order to test whether it can self-organize by learning associations between co-occurring harmonics. It is shown that the trained model can complete the pattern for missing-fundamental sounds. The Performance of the model in harmonic detection will be compared with experimental results for humans.

  14. Adaptive neural network for image enhancement

    Science.gov (United States)

    Perl, Dan; Marsland, T. A.

    1992-09-01

    ANNIE is a neural network that removes noise and sharpens edges in digital images. For noise removal, ANNIE makes a weighted average of the values of the pixels over a certain neighborhood. For edge sharpening, ANNIE detects edges and applies a correction around them. Although averaging is a simple operation and needs only a two-layer neural network, detecting edges is more complex and demands several hidden layers. Based on Marr's theory of natural vision, the edge detection method uses zero-crossings in the image filtered by the ∇2G operator (where ∇2 is the Laplacian operator and G stands for a two- dimensional Gaussian distribution), and uses two channels with different spatial frequencies. Edge detectors are tuned for vertical and horizontal orientations. Lateral inhibition implemented through one-step recursion achieves both edge relaxation and correlation of the two channels. Training by means of the quickprop algorithm determines the shapes of the weighted averaging filter and the edge correction filters, and the rules for edge relaxation and channel interaction. ANNIE uses pairs of pictures as training patterns: one picture is a reference for the output of the network and the same picture deteriorated by noise and/or blur is the input of the network.

  15. Neural retina identity is specified by lens-derived BMP signals.

    Science.gov (United States)

    Pandit, Tanushree; Jidigam, Vijay K; Patthey, Cedric; Gunhaga, Lena

    2015-05-15

    The eye has served as a classical model to study cell specification and tissue induction for over a century. Nevertheless, the molecular mechanisms that regulate the induction and maintenance of eye-field cells, and the specification of neural retina cells are poorly understood. Moreover, within the developing anterior forebrain, how prospective eye and telencephalic cells are differentially specified is not well defined. In the present study, we have analyzed these issues by manipulating signaling pathways in intact chick embryo and explant assays. Our results provide evidence that at blastula stages, BMP signals inhibit the acquisition of eye-field character, but from neural tube/optic vesicle stages, BMP signals from the lens are crucial for the maintenance of eye-field character, inhibition of dorsal telencephalic cell identity and specification of neural retina cells. Subsequently, our results provide evidence that a Rax2-positive eye-field state is not sufficient for the progress to a neural retina identity, but requires BMP signals. In addition, our results argue against any essential role of Wnt or FGF signals during the specification of neural retina cells, but provide evidence that Wnt signals together with BMP activity are sufficient to induce cells of retinal pigment epithelial character. We conclude that BMP activity emanating from the lens ectoderm maintains eye-field identity, inhibits telencephalic character and induces neural retina cells. Our findings link the requirement of the lens ectoderm for neural retina specification with the molecular mechanism by which cells in the forebrain become specified as neural retina by BMP activity. © 2015. Published by The Company of Biologists Ltd.

  16. Neural retina identity is specified by lens-derived BMP signals

    Science.gov (United States)

    Pandit, Tanushree; Jidigam, Vijay K.; Patthey, Cedric; Gunhaga, Lena

    2015-01-01

    The eye has served as a classical model to study cell specification and tissue induction for over a century. Nevertheless, the molecular mechanisms that regulate the induction and maintenance of eye-field cells, and the specification of neural retina cells are poorly understood. Moreover, within the developing anterior forebrain, how prospective eye and telencephalic cells are differentially specified is not well defined. In the present study, we have analyzed these issues by manipulating signaling pathways in intact chick embryo and explant assays. Our results provide evidence that at blastula stages, BMP signals inhibit the acquisition of eye-field character, but from neural tube/optic vesicle stages, BMP signals from the lens are crucial for the maintenance of eye-field character, inhibition of dorsal telencephalic cell identity and specification of neural retina cells. Subsequently, our results provide evidence that a Rax2-positive eye-field state is not sufficient for the progress to a neural retina identity, but requires BMP signals. In addition, our results argue against any essential role of Wnt or FGF signals during the specification of neural retina cells, but provide evidence that Wnt signals together with BMP activity are sufficient to induce cells of retinal pigment epithelial character. We conclude that BMP activity emanating from the lens ectoderm maintains eye-field identity, inhibits telencephalic character and induces neural retina cells. Our findings link the requirement of the lens ectoderm for neural retina specification with the molecular mechanism by which cells in the forebrain become specified as neural retina by BMP activity. PMID:25968316

  17. 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 ...

  18. 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.

  19. Cannabidiol modulates the immunophenotype and inhibits the activation of the inflammasome in human gingival mesenchymal stem cells

    Directory of Open Access Journals (Sweden)

    Rosaliana Libro

    2016-11-01

    Full Text Available Human Gingival Mesenchymal Stem Cells (hGMSC are multipotential cells that can expand and differentiate in culture under specific and standardized conditions. In the present study, we have investigated whether in vitro pre-treatment of hGMCs with Cannabidiol (CBD can influence their expression profile, improving the therapeutic potential of this cell culture. Following CBD treatment (5μM for 24 h, gene expression analysis through Next Generation Sequencing (NGS has revealed several genes differentially expressed between CBD-treated hGMCs (CBD-hGMCs and control cells (CTR-hGMCs that were linked to inflammation and apoptosis. In particular, we have demonstrated that CBD treatment in hGMCs prevented the activation of the NALP3-inflammasome pathway by suppressing the levels of NALP3, CASP1 and IL18, and in parallel, inhibited apoptosis, as demonstrated by the suppression of Bax.CBD treatment was also able to modulate the expression of the well-known mesenchymal stem cell markers (CD13, CD29, CD73, CD44, CD90 and CD166, and other surface antigens. Specifically, CBD led to the downregulation of genes codifying for antigens involved in the activation of the immune system (CD109, CD151, CD40, CD46, CD59, CD68, CD81, CD82, CD99, while it led to the upregulation of those implicated in the inhibition of the immune responses (CD47, CD55, CD276.In conclusion, the present study will provide a new simple and reproducible method for preconditioning hGMSCs with CBD, before transplantation, as an interesting strategy for improving the hGMCs molecular phenotype, reducing the risk of immune or inflammatory reactions in the host, and in parallel, for increasing their survival and thus, their long-term therapeutic efficacy.

  20. Neural mechanisms of aggression.

    Science.gov (United States)

    Nelson, Randy J; Trainor, Brian C

    2007-07-01

    Unchecked aggression and violence exact a significant toll on human societies. Aggression is an umbrella term for behaviours that are intended to inflict harm. These behaviours evolved as adaptations to deal with competition, but when expressed out of context, they can have destructive consequences. Uncontrolled aggression has several components, such as impaired recognition of social cues and enhanced impulsivity. Molecular approaches to the study of aggression have revealed biological signals that mediate the components of aggressive behaviour. These signals may provide targets for therapeutic intervention for individuals with extreme aggressive outbursts. This Review summarizes the complex interactions between genes, biological signals, neural circuits and the environment that influence the development and expression of aggressive behaviour.

  1. Proactive modulation of long-interval intracortical inhibition during response inhibition

    Science.gov (United States)

    Cowie, Matthew J.; MacDonald, Hayley J.; Cirillo, John

    2016-01-01

    Daily activities often require sudden cancellation of preplanned movement, termed response inhibition. When only a subcomponent of a whole response must be suppressed (required here on Partial trials), the ensuing component is markedly delayed. The neural mechanisms underlying partial response inhibition remain unclear. We hypothesized that Partial trials would be associated with nonselective corticomotor suppression and that GABAB receptor-mediated inhibition within primary motor cortex might be responsible for the nonselective corticomotor suppression contributing to Partial trial response delays. Sixteen right-handed participants performed a bimanual anticipatory response inhibition task while single- and paired-pulse transcranial magnetic stimulation was delivered to elicit motor evoked potentials in the left first dorsal interosseous muscle. Lift times, amplitude of motor evoked potentials, and long-interval intracortical inhibition were examined across the different trial types (Go, Stop-Left, Stop-Right, Stop-Both). Go trials produced a tight distribution of lift times around the target, whereas those during Partial trials (Stop-Left and Stop-Right) were substantially delayed. The modulation of motor evoked potential amplitude during Stop-Right trials reflected anticipation, suppression, and subsequent reinitiation of movement. Importantly, suppression was present across all Stop trial types, indicative of a “default” nonselective inhibitory process. Compared with blocks containing only Go trials, inhibition increased when Stop trials were introduced but did not differ between trial types. The amount of inhibition was positively correlated with lift times during Stop-Right trials. Tonic levels of inhibition appear to be proactively modulated by task context and influence the speed at which unimanual responses occur after a nonselective “brake” is applied. PMID:27281744

  2. Program Helps Simulate Neural Networks

    Science.gov (United States)

    Villarreal, James; Mcintire, Gary

    1993-01-01

    Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

  3. Abrogation of Early Apoptosis Does Not Alter Late Inhibition of Hippocampal Neurogenesis After Irradiation

    International Nuclear Information System (INIS)

    Li Yuqing; Aubert, Isabelle; Wong, C. Shun

    2010-01-01

    Purpose: Irradiation of the adult brain results in acute apoptosis of neural progenitors and vascular endothelial cells, as well as late dysfunction of neural progenitors and inhibition of neurogenesis. We sought to determine whether the early apoptotic response has a causative role in late inhibition of neurogenesis after cranial irradiation. Methods and Materials: Using a genetic approach with p53 and smpd1 transgenic mice and a pharmacologic approach with basic fibroblast growth factor (bFGF) to abrogate the early apoptotic response, we evaluated the late inhibition of neurogenesis in the hippocampal dentate gyrus after cranial irradiation. Results: In dentate gyrus, subgranular neural progenitors underwent p53-dependent apoptosis within 24 h after irradiation. Despite a near abrogation of neural progenitor apoptosis in p53-/- mice, the reduction in newborn neurons in dentate gyrus at 9 weeks after irradiation in p53-/- mice was not different from that observed in wildtype controls. Endothelial cell apoptosis after radiation is mediated by membrane damage initiated by activation of acid sphingomyelinase (ASMase). Deletion of the smpd1 gene (which encodes ASMase) attenuated the apoptotic response of endothelial cells. At 9 weeks after irradiation, the inhibition of hippocampal neurogenesis was not rescued by ASMase deficiency. Intravenous administration of bFGF protected both endothelial cells and neural progenitors against radiation-induced apoptosis. There was no protection against inhibition of neurogenesis at 9 weeks after irradiation in bFGF-treated mice. Conclusion: Early apoptotic death of neural progenitors, endothelial cells, or both does not have a causative association with late inhibition of neurogenesis after irradiation.

  4. Noninvasive optical inhibition with a red-shifted microbial rhodopsin

    DEFF Research Database (Denmark)

    Chuong, Amy S; Miri, Mitra L; Busskamp, Volker

    2014-01-01

    Optogenetic inhibition of the electrical activity of neurons enables the causal assessment of their contributions to brain functions. Red light penetrates deeper into tissue than other visible wavelengths. We present a red-shifted cruxhalorhodopsin, Jaws, derived from Haloarcula (Halobacterium......) salinarum (strain Shark) and engineered to result in red light-induced photocurrents three times those of earlier silencers. Jaws exhibits robust inhibition of sensory-evoked neural activity in the cortex and results in strong light responses when used in retinas of retinitis pigmentosa model mice. We also...

  5. Harmine stimulates proliferation of human neural progenitors

    Directory of Open Access Journals (Sweden)

    Vanja Dakic

    2016-12-01

    Full Text Available Harmine is the β-carboline alkaloid with the highest concentration in the psychotropic plant decoction Ayahuasca. In rodents, classical antidepressants reverse the symptoms of depression by stimulating neuronal proliferation. It has been shown that Ayahuasca presents antidepressant effects in patients with depressive disorder. In the present study, we investigated the effects of harmine in cell cultures containing human neural progenitor cells (hNPCs, 97% nestin-positive derived from pluripotent stem cells. After 4 days of treatment, the pool of proliferating hNPCs increased by 71.5%. Harmine has been reported as a potent inhibitor of the dual specificity tyrosine-phosphorylation-regulated kinase (DYRK1A, which regulates cell proliferation and brain development. We tested the effect of analogs of harmine, an inhibitor of DYRK1A (INDY, and an irreversible selective inhibitor of monoamine oxidase (MAO but not DYRK1A (pargyline. INDY but not pargyline induced proliferation of hNPCs similarly to harmine, suggesting that inhibition of DYRK1A is a possible mechanism to explain harmine effects upon the proliferation of hNPCs. Our findings show that harmine enhances proliferation of hNPCs and suggest that inhibition of DYRK1A may explain its effects upon proliferation in vitro and antidepressant effects in vivo.

  6. Frequency-difference-dependent stochastic resonance in neural systems

    Science.gov (United States)

    Guo, Daqing; Perc, Matjaž; Zhang, Yangsong; Xu, Peng; Yao, Dezhong

    2017-08-01

    Biological neurons receive multiple noisy oscillatory signals, and their dynamical response to the superposition of these signals is of fundamental importance for information processing in the brain. Here we study the response of neural systems to the weak envelope modulation signal, which is superimposed by two periodic signals with different frequencies. We show that stochastic resonance occurs at the beat frequency in neural systems at the single-neuron as well as the population level. The performance of this frequency-difference-dependent stochastic resonance is influenced by both the beat frequency and the two forcing frequencies. Compared to a single neuron, a population of neurons is more efficient in detecting the information carried by the weak envelope modulation signal at the beat frequency. Furthermore, an appropriate fine-tuning of the excitation-inhibition balance can further optimize the response of a neural ensemble to the superimposed signal. Our results thus introduce and provide insights into the generation and modulation mechanism of the frequency-difference-dependent stochastic resonance in neural systems.

  7. 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.

  8. 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

  9. (GAGs) in normal and ethanol-induced chick embryo during neural

    African Journals Online (AJOL)

    Administrator

    2011-09-14

    Sep 14, 2011 ... Alcohol as a teratogenic agent inhibits cell growth, function, proliferation and migration by affecting macromolecules, and can induce cell death. Prenatal ethanol exposure causes neural tube defects. (NTD) and growth deficiency in experimental animals. NTDs are a group of malformations that result in.

  10. A model of stimulus-specific neural assemblies in the insect antennal lobe.

    Directory of Open Access Journals (Sweden)

    Dominique Martinez

    2008-08-01

    Full Text Available It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABA(A-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABA(A and GABA(B inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABA(B synapses make the neural response unpredictable. Depending on the balance between GABA(A and GABA(B inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies.

  11. Predictions models with neural nets

    Directory of Open Access Journals (Sweden)

    Vladimír Konečný

    2008-01-01

    Full Text Available The contribution is oriented to basic problem trends solution of economic pointers, using neural networks. Problems include choice of the suitable model and consequently configuration of neural nets, choice computational function of neurons and the way prediction learning. The contribution contains two basic models that use structure of multilayer neural nets and way of determination their configuration. It is postulate a simple rule for teaching period of neural net, to get most credible prediction.Experiments are executed with really data evolution of exchange rate Kč/Euro. The main reason of choice this time series is their availability for sufficient long period. In carry out of experiments the both given basic kind of prediction models with most frequent use functions of neurons are verified. Achieve prediction results are presented as in numerical and so in graphical forms.

  12. Neural complexity, dissociation, and schizophrenia

    Czech Academy of Sciences Publication Activity Database

    Bob, P.; Šusta, M.; Chládek, Jan; Glaslová, K.; Fedor-Ferybergh, P.

    2007-01-01

    Roč. 13, č. 10 (2007), HY1-5 ISSN 1234-1010 Institutional research plan: CEZ:AV0Z20650511 Keywords : neural complexity * dissociation * schizophrenia Subject RIV: FH - Neurology Impact factor: 1.607, year: 2007

  13. 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.

  14. 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.

  15. 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...

  16. 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...

  17. Neural Networks For Robot Control

    National Research Council Canada - National Science Library

    Nasr, Chaiban

    2001-01-01

    ...; and optimization of the architecture; (b) Application of artificial neural networks in controlling closed-loop 2D planar robot arm and comparison with the use of proportional-integral-differential (PID) controllers...

  18. Sequential neural models with stochastic layers

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

    2016-01-01

    How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

  19. Oscillatory neural networks.

    Science.gov (United States)

    Selverston, A I; Moulins, M

    1985-01-01

    Despite the fact that a large number of neuronal oscillators have been described, there are only a few good examples that illustrate how they operate at the cellular level. For most, there is some isolated information about different aspects of the oscillator network, but too little to explain the whole mechanism. Two quite remarkable features do seem to be emerging from ongoing studies, however. One is that there are very few generalizable features common to neural oscillators. Many utilize reciprocal inhibitory circuits and endogenous burst-generating currents to some extent. All that have been well worked out utilize a combination of both cellular and network properties, but little else in the way of common mechanism is noteworthy. Perhaps the most interesting aspect of recent work is the ability of a particular oscillator to produce a large repertoire of different outputs. This is separate and in addition to changes occurring via phasic sensory feedback. It is in fact a radical functional "rewiring" of the network in response to neuromodulators. The CPG circuits represent only the most basic form of a given pattern. Finally, concerning the role of sensory feedback in generating oscillatory patterns, the concept of the CPG as a group of neurons able to produce oscillatory patterns without any sensory feedback is, in our opinion, still valid. There is no doubt that some oscillators may be quite weak when isolated, but they can still produce bursts with firing sequences similar to those seen in vivo. The fact that sensory feedback can both control and enhance the oscillations has never been in doubt. Similarly, entrainment of the pattern by sensory feedback does not mean that the receptor is part of the generator, only that it has access to it (as do command and coordinating fibers). The real question remains: Can a group of cells produce an oscillatory pattern without phasic sensory input? We must answer this affirmatively even for the insect-flight motor CPG

  20. Alternative Routes to Induced Pluripotent Stem Cells Revealed by Reprogramming of the Neural Lineage.

    Science.gov (United States)

    Jackson, Steven A; Olufs, Zachariah P G; Tran, Khoa A; Zaidan, Nur Zafirah; Sridharan, Rupa

    2016-03-08

    During the reprogramming of mouse embryonic fibroblasts (MEFs) to induced pluripotent stem cells, the activation of pluripotency genes such as NANOG occurs after the mesenchymal to epithelial transition. Here we report that both adult stem cells (neural stem cells) and differentiated cells (astrocytes) of the neural lineage can activate NANOG in the absence of cadherin expression during reprogramming. Gene expression analysis revealed that only the NANOG+E-cadherin+ populations expressed stabilization markers, had upregulated several cell cycle genes; and were transgene independent. Inhibition of DOT1L activity enhanced both the numbers of NANOG+ and NANOG+E-cadherin+ colonies in neural stem cells. Expressing SOX2 in MEFs prior to reprogramming did not alter the ratio of NANOG colonies that express E-cadherin. Taken together these results provide a unique pathway for reprogramming taken by cells of the neural lineage. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  1. 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...

  2. Backpropagation neural networks: pattern recognition

    OpenAIRE

    Studenikin, Oleg

    2005-01-01

    In this Master’s degree work artificial neural networks and back propagation learning algorithm for human faces and pattern recognition are analyzed. In the second part of work artificial neural networks and their architecture and structures models are analyzed. In the third part of article the backpropagation procedure and procedures theoretical learning principle are analyzed. In the fourth part different kinds of ANN methods and patterns extracting methods in recognition, learning and ...

  3. Cortical organization of inhibition-related functions and modulation by psychopathology

    Directory of Open Access Journals (Sweden)

    Stacie L. Warren

    2013-06-01

    Full Text Available Individual differences in inhibition-related functions have been implicated as risk factors for a broad range of psychopathology, including anxiety and depression. Delineating neural mechanisms of distinct inhibition-related functions may clarify their role in the development and maintenance of psychopathology. The present study tested the hypothesis that activity in common and distinct brain regions would be associated with an ecologically sensitive, self-report measure of inhibition and a laboratory performance measure of prepotent response inhibition. Results indicated that sub-regions of DLPFC distinguished measures of inhibition, whereas left inferior frontal gyrus and bilateral inferior parietal cortex were associated with both types of inhibition. Additionally, co-occurring anxiety and depression modulated neural activity in select brain regions associated with response inhibition. Results imply that specific combinations of anxiety and depression dimensions are associated with failure to implement top-down attentional control as reflected in inefficient recruitment of posterior DLPFC and increased activation in regions associated with threat (MTG and worry (BA10. Present findings elucidate possible neural mechanisms of interference that could help explain executive control deficits in psychopathology.

  4. 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.

  5. Dissecting neural pathways for forgetting in Drosophila olfactory aversive memory.

    Science.gov (United States)

    Shuai, Yichun; Hirokawa, Areekul; Ai, Yulian; Zhang, Min; Li, Wanhe; Zhong, Yi

    2015-12-01

    Recent studies have identified molecular pathways driving forgetting and supported the notion that forgetting is a biologically active process. The circuit mechanisms of forgetting, however, remain largely unknown. Here we report two sets of Drosophila neurons that account for the rapid forgetting of early olfactory aversive memory. We show that inactivating these neurons inhibits memory decay without altering learning, whereas activating them promotes forgetting. These neurons, including a cluster of dopaminergic neurons (PAM-β'1) and a pair of glutamatergic neurons (MBON-γ4>γ1γ2), terminate in distinct subdomains in the mushroom body and represent parallel neural pathways for regulating forgetting. Interestingly, although activity of these neurons is required for memory decay over time, they are not required for acute forgetting during reversal learning. Our results thus not only establish the presence of multiple neural pathways for forgetting in Drosophila but also suggest the existence of diverse circuit mechanisms of forgetting in different contexts.

  6. Spiking neural network for recognizing spatiotemporal sequences of spikes

    International Nuclear Information System (INIS)

    Jin, Dezhe Z.

    2004-01-01

    Sensory neurons in many brain areas spike with precise timing to stimuli with temporal structures, and encode temporally complex stimuli into spatiotemporal spikes. How the downstream neurons read out such neural code is an important unsolved problem. In this paper, we describe a decoding scheme using a spiking recurrent neural network. The network consists of excitatory neurons that form a synfire chain, and two globally inhibitory interneurons of different types that provide delayed feedforward and fast feedback inhibition, respectively. The network signals recognition of a specific spatiotemporal sequence when the last excitatory neuron down the synfire chain spikes, which happens if and only if that sequence was present in the input spike stream. The recognition scheme is invariant to variations in the intervals between input spikes within some range. The computation of the network can be mapped into that of a finite state machine. Our network provides a simple way to decode spatiotemporal spikes with diverse types of neurons

  7. Neural correlates of hate.

    Directory of Open Access Journals (Sweden)

    Semir Zeki

    Full Text Available In this work, we address an important but unexplored topic, namely the neural correlates of hate. In a block-design fMRI study, we scanned 17 normal human subjects while they viewed the face of a person they hated and also faces of acquaintances for whom they had neutral feelings. A hate score was obtained for the object of hate for each subject and this was used as a covariate in a between-subject random effects analysis. Viewing a hated face resulted in increased activity in the medial frontal gyrus, right putamen, bilaterally in premotor cortex, in the frontal pole and bilaterally in the medial insula. We also found three areas where activation correlated linearly with the declared level of hatred, the right insula, right premotor cortex and the right fronto-medial gyrus. One area of deactivation was found in the right superior frontal gyrus. The study thus shows that there is a unique pattern of activity in the brain in the context of hate. Though distinct from the pattern of activity that correlates with romantic love, this pattern nevertheless shares two areas with the latter, namely the putamen and the insula.

  8. neural control system

    International Nuclear Information System (INIS)

    Elshazly, A.A.E.

    2002-01-01

    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

  9. Surface topography during neural stem cell differentiation regulates cell migration and cell morphology.

    Science.gov (United States)

    Czeisler, Catherine; Short, Aaron; Nelson, Tyler; Gygli, Patrick; Ortiz, Cristina; Catacutan, Fay Patsy; Stocker, Ben; Cronin, James; Lannutti, John; Winter, Jessica; Otero, José Javier

    2016-12-01

    We sought to determine the contribution of scaffold topography to the migration and morphology of neural stem cells by mimicking anatomical features of scaffolds found in vivo. We mimicked two types of central nervous system scaffolds encountered by neural stem cells during development in vitro by constructing different diameter electrospun polycaprolactone (PCL) fiber mats, a substrate that we have shown to be topographically similar to brain scaffolds. We compared the effects of large fibers (made to mimic blood vessel topography) with those of small-diameter fibers (made to mimic radial glial process topography) on the migration and differentiation of neural stem cells. Neural stem cells showed differential migratory and morphological reactions with laminin in different topographical contexts. We demonstrate, for the first time, that neural stem cell biological responses to laminin are dependent on topographical context. Large-fiber topography without laminin prevented cell migration, which was partially reversed by treatment with rock inhibitor. Cell morphology complexity assayed by fractal dimension was inhibited in nocodazole- and cytochalasin-D-treated neural precursor cells in large-fiber topography, but was not changed in small-fiber topography with these inhibitors. These data indicate that cell morphology has different requirements on cytoskeletal proteins dependent on the topographical environment encountered by the cell. We propose that the physical structure of distinct scaffolds induces unique signaling cascades that regulate migration and morphology in embryonic neural precursor cells. J. Comp. Neurol. 524:3485-3502, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  10. Cadherin-6B undergoes macropinocytosis and clathrin-mediated endocytosis during cranial neural crest cell EMT.

    Science.gov (United States)

    Padmanabhan, Rangarajan; Taneyhill, Lisa A

    2015-05-01

    The epithelial-to-mesenchymal transition (EMT) is important for the formation of migratory neural crest cells during development and is co-opted in human diseases such as cancer metastasis. Chick premigratory cranial neural crest cells lose intercellular contacts, mediated in part by Cadherin-6B (Cad6B), migrate extensively, and later form a variety of adult derivatives. Importantly, modulation of Cad6B is crucial for proper neural crest cell EMT. Although Cad6B possesses a long half-life, it is rapidly lost from premigratory neural crest cell membranes, suggesting the existence of post-translational mechanisms during EMT. We have identified a motif in the Cad6B cytoplasmic tail that enhances Cad6B internalization and reduces the stability of Cad6B upon its mutation. Furthermore, we demonstrate for the first time that Cad6B is removed from premigratory neural crest cells through cell surface internalization events that include clathrin-mediated endocytosis and macropinocytosis. Both of these processes are dependent upon the function of dynamin, and inhibition of Cad6B internalization abrogates neural crest cell EMT and migration. Collectively, our findings reveal the significance of post-translational events in controlling cadherins during neural crest cell EMT and migration. © 2015. Published by The Company of Biologists Ltd.

  11. 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.

  12. Relation of cell division to the acquisition of responsiveness to cortisol in the neural retina of the chick embryo

    International Nuclear Information System (INIS)

    Ben-Or, S.; Eshel, M.

    1982-01-01

    Responsiveness of the neural retina to cortisol, as measured by cortisol-induced glutamine synthetase activity, is acquired in the chick embryo during the second week of embryogenesis. The magnitude of the response is inversely related to the growth rate of the neural retina. This developmental event is also acquired by the 8-d-old neural retina under organ culture conditions. The acquisition of competence to respond to the hormonal stimulation can be reversibly abolished by inhibition of DNA synthesis with 0.01 mM cytosine arabinoside; the magnitude of response that resumes after withdrawal of the drug, is characterized by the stage of growth of the neural retina. Responsiveness to cortisol in the embryonic neural retina is apparently coupled to the number of Muller cells (the targets for cortisol action) that have withdrawn from the cell cycle. (author)

  13. Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

    Science.gov (United States)

    Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

    2017-10-01

    This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

  14. Effect of inhibitory firing pattern on coherence resonance in random neural networks

    Science.gov (United States)

    Yu, Haitao; Zhang, Lianghao; Guo, Xinmeng; Wang, Jiang; Cao, Yibin; Liu, Jing

    2018-01-01

    The effect of inhibitory firing patterns on coherence resonance (CR) in random neuronal network is systematically studied. Spiking and bursting are two main types of firing pattern considered in this work. Numerical results show that, irrespective of the inhibitory firing patterns, the regularity of network is maximized by an optimal intensity of external noise, indicating the occurrence of coherence resonance. Moreover, the firing pattern of inhibitory neuron indeed has a significant influence on coherence resonance, but the efficacy is determined by network property. In the network with strong coupling strength but weak inhibition, bursting neurons largely increase the amplitude of resonance, while they can decrease the noise intensity that induced coherence resonance within the neural system of strong inhibition. Different temporal windows of inhibition induced by different inhibitory neurons may account for the above observations. The network structure also plays a constructive role in the coherence resonance. There exists an optimal network topology to maximize the regularity of the neural systems.

  15. Antagonism between the transcription factors NANOG and OTX2 specifies rostral or caudal cell fate during neural patterning transition.

    Science.gov (United States)

    Su, Zhenghui; Zhang, Yanqi; Liao, Baojian; Zhong, Xiaofen; Chen, Xin; Wang, Haitao; Guo, Yiping; Shan, Yongli; Wang, Lihui; Pan, Guangjin

    2018-03-23

    During neurogenesis, neural patterning is a critical step during which neural progenitor cells differentiate into neurons with distinct functions. However, the molecular determinants that regulate neural patterning remain poorly understood. Here we optimized the "dual SMAD inhibition" method to specifically promote differentiation of human pluripotent stem cells (hPSCs) into forebrain and hindbrain neural progenitor cells along the rostral-caudal axis. We report that neural patterning determination occurs at the very early stage in this differentiation. Undifferentiated hPSCs expressed basal levels of the transcription factor orthodenticle homeobox 2 (OTX2) that dominantly drove hPSCs into the "default" rostral fate at the beginning of differentiation. Inhibition of glycogen synthase kinase 3β (GSK3β) through CHIR99021 application sustained transient expression of the transcription factor NANOG at early differentiation stages through Wnt signaling. Wnt signaling and NANOG antagonized OTX2 and, in the later stages of differentiation, switched the default rostral cell fate to the caudal one. Our findings have uncovered a mutual antagonism between NANOG and OTX2 underlying cell fate decisions during neural patterning, critical for the regulation of early neural development in humans. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

  16. Myelin plasticity, neural activity, and traumatic neural injury.

    Science.gov (United States)

    Kondiles, Bethany R; Horner, Philip J

    2018-02-01

    The possibility that adult organisms exhibit myelin plasticity has recently become a topic of great interest. Many researchers are exploring the role of myelin growth and adaptation in daily functions such as memory and motor learning. Here we consider evidence for three different potential categories of myelin plasticity: the myelination of previously bare axons, remodeling of existing sheaths, and the removal of a sheath with replacement by a new internode. We also review evidence that points to the importance of neural activity as a mechanism by which oligodendrocyte precursor cells (OPCs) are cued to differentiate into myelinating oligodendrocytes, which may potentially be an important component of myelin plasticity. Finally, we discuss demyelination in the context of traumatic neural injury and present an argument for altering neural activity as a potential therapeutic target for remyelination following injury. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 108-122, 2018. © 2017 Wiley Periodicals, Inc.

  17. 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.

  18. 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.

  19. Neural recording and modulation technologies

    Science.gov (United States)

    Chen, Ritchie; Canales, Andres; Anikeeva, Polina

    2017-01-01

    In the mammalian nervous system, billions of neurons connected by quadrillions of synapses exchange electrical, chemical and mechanical signals. Disruptions to this network manifest as neurological or psychiatric conditions. Despite decades of neuroscience research, our ability to treat or even to understand these conditions is limited by the capability of tools to probe the signalling complexity of the nervous system. Although orders of magnitude smaller and computationally faster than neurons, conventional substrate-bound electronics do not recapitulate the chemical and mechanical properties of neural tissue. This mismatch results in a foreign-body response and the encapsulation of devices by glial scars, suggesting that the design of an interface between the nervous system and a synthetic sensor requires additional materials innovation. Advances in genetic tools for manipulating neural activity have fuelled the demand for devices that are capable of simultaneously recording and controlling individual neurons at unprecedented scales. Recently, flexible organic electronics and bio- and nanomaterials have been developed for multifunctional and minimally invasive probes for long-term interaction with the nervous system. In this Review, we discuss the design lessons from the quarter-century-old field of neural engineering, highlight recent materials-driven progress in neural probes and look at emergent directions inspired by the principles of neural transduction.

  20. Inductive differentiation of two neural lineages reconstituted in a microculture system from Xenopus early gastrula cells.

    Science.gov (United States)

    Mitani, S; Okamoto, H

    1991-05-01

    Neural induction of ectoderm cells has been reconstituted and examined in a microculture system derived from dissociated early gastrula cells of Xenopus laevis. We have used monoclonal antibodies as specific markers to monitor cellular differentiation from three distinct ectoderm lineages in culture (N1 for CNS neurons from neural tube, Me1 for melanophores from neural crest and E3 for skin epidermal cells from epidermal lineages). CNS neurons and melanophores differentiate when deep layer cells of the ventral ectoderm (VE, prospective epidermis region; 150 cells/culture) and an appropriate region of the marginal zone (MZ, prospective mesoderm region; 5-150 cells/culture) are co-cultured, but not in cultures of either cell type on their own; VE cells cultured alone yield epidermal cells as we have previously reported. The extent of inductive neural differentiation in the co-culture system strongly depends on the origin and number of MZ cells initially added to culture wells. The potency to induce CNS neurons is highest for dorsal MZ cells and sharply decreases as more ventrally located cells are used. The same dorsoventral distribution of potency is seen in the ability of MZ cells to inhibit epidermal differentiation. In contrast, the ability of MZ cells to induce melanophores shows the reverse polarity, ventral to dorsal. These data indicate that separate developmental mechanisms are used for the induction of neural tube and neural crest lineages. Co-differentiation of CNS neurons or melanophores with epidermal cells can be obtained in a single well of co-cultures of VE cells (150) and a wide range of numbers of MZ cells (5 to 100). Further, reproducible differentiation of both neural lineages requires intimate association between cells from the two gastrula regions; virtually no differentiation is obtained when cells from the VE and MZ are separated in a culture well. These results indicate that the inducing signals from MZ cells for both neural tube and neural

  1. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  2. 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...

  3. Refractory neural nets and vision

    Science.gov (United States)

    Fall, Thomas C.

    2014-02-01

    Biological understandings have served as the basis for new computational approaches. A prime example is artificial neural nets which are based on the biological understanding of the trainability of neural synapses. In this paper, we will investigate features of the biological vision system to see if they can also be exploited. These features are 1) the neuron's refractory period - the period of time after the neuron fires before it can fire again and 2) the ocular microtremor which moves the retinal neural array relative to the image. The short term memory due to the refractory period allows the before and after movement views to be compared. This paper will discuss the investigation of the implications of these two features.

  4. 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...

  5. Differences between otolith- and semicircular canal-activated neural circuitry in the vestibular system.

    Science.gov (United States)

    Uchino, Yoshio; Kushiro, Keisuke

    2011-12-01

    In the last two decades, we have focused on establishing a reliable technique for focal stimulation of vestibular receptors to evaluate neural connectivity. Here, we summarize the vestibular-related neuronal circuits for the vestibulo-ocular reflex, vestibulocollic reflex, and vestibulospinal reflex arcs. The focal stimulating technique also uncovered some hidden neural mechanisms. In the otolith system, we identified two hidden neural mechanisms that enhance otolith receptor sensitivity. The first is commissural inhibition, which boosts sensitivity by incorporating inputs from bilateral otolith receptors, the existence of which was in contradiction to the classical understanding of the otolith system but was observed in the utricular system. The second mechanism, cross-striolar inhibition, intensifies the sensitivity of inputs from both sides of receptive cells across the striola in a single otolith sensor. This was an entirely novel finding and is typically observed in the saccular system. We discuss the possible functional meaning of commissural and cross-striolar inhibition. Finally, our focal stimulating technique was applied to elucidate the different constructions of axonal projections from each vestibular receptor to the spinal cord. We also discuss the possible function of the unique neural connectivity observed in each vestibular receptor system. Copyright © 2011 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

  6. BACE inhibition-dependent repair of Alzheimer's pathophysiology.

    Science.gov (United States)

    Keskin, Aylin D; Kekuš, Maja; Adelsberger, Helmuth; Neumann, Ulf; Shimshek, Derya R; Song, Beomjong; Zott, Benedikt; Peng, Tingying; Förstl, Hans; Staufenbiel, Matthias; Nelken, Israel; Sakmann, Bert; Konnerth, Arthur; Busche, Marc Aurel

    2017-08-08

    Amyloid-β (Aβ) is thought to play an essential pathogenic role in Alzheimer´s disease (AD). A key enzyme involved in the generation of Aβ is the β-secretase BACE, for which powerful inhibitors have been developed and are currently in use in human clinical trials. However, although BACE inhibition can reduce cerebral Aβ levels, whether it also can ameliorate neural circuit and memory impairments remains unclear. Using histochemistry, in vivo Ca 2+ imaging, and behavioral analyses in a mouse model of AD, we demonstrate that along with reducing prefibrillary Aβ surrounding plaques, the inhibition of BACE activity can rescue neuronal hyperactivity, impaired long-range circuit function, and memory defects. The functional neuronal impairments reappeared after infusion of soluble Aβ, mechanistically linking Aβ pathology to neuronal and cognitive dysfunction. These data highlight the potential benefits of BACE inhibition for the effective treatment of a wide range of AD-like pathophysiological and cognitive impairments.

  7. [Neural crest and vertebrate evolution].

    Science.gov (United States)

    Le Douarin, Nicole M; Creuzet, Sophie

    2011-01-01

    The neural crest (NC) is a remarkable structure of the Vertebrate embryo, which forms from the lateral borders of the neural plate (designated as neural folds) during neural tube closure. As soon as the NC is formed, its constitutive cells detach and migrate away from the neural primordium along definite pathways and at precise periods of time according to a rostro-caudal progression. The NC cells aggregate in definite places in the developing embryo, where they differentiate into a large variety of cell types including the neurons and glial cells of the peripheral nervous system, the pigment cells dispersed throughout the body and endocrine cells such as the adrenal medulla and the calcitonin producing cells. At the cephalic level only, in higher Vertebrates (but along the whole neural axis in Fishes and Amphibians), the NC is also at the origin of mesenchymal cells differentiating into connective tissue chondrogenic and osteogenic cells. Vertebrates belong to the larger group of Cordates which includes also the Protocordates (Cephalocordates and the Urocordates). All Cordates are characterized by the same body plan with a dorsal neural tube and a notochord which, in Vertebrates, exists only at embryonic stages. The main difference between Protocordates and Vertebrates is the very rudimentary development of cephalic structures in the former. As a result, the process of cephalization is one of the most obvious characteristics of Vertebrates. It was accompanied by the apparition of the NC which can therefore be considered as an innovation of Vertebrates during evolution. The application of a cell marking technique which consists in constructing chimeric embryos between two species of birds, the quail and the chicken, has led to show that the vertebrate head is mainly formed by cells originating from the NC, meaning that this structure was an important asset in Vertebrate evolution. Recent studies, described in this article, have strengthened this view by showing

  8. 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...

  9. Antenna analysis using neural networks

    Science.gov (United States)

    Smith, William T.

    1992-01-01

    Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern

  10. Neural overlap in processing music and speech

    Science.gov (United States)

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L.

    2015-01-01

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. PMID:25646513

  11. 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...

  12. Neural overlap in processing music and speech.

    Science.gov (United States)

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L

    2015-03-19

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  13. The neural crest and neural crest cells: discovery and significance ...

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    ). Le Douarin N M 1986 Cell line segregation during peripheral nervous system ontogeny; Science 231 1515–1522. Le Douarin N M, Dupin E, Baroffio A and Dulac C 1992 New insights into the development of neural crest derivatives; Int. Rev.

  14. Inhibitory control and trait aggression: neural and behavioral insights using the emotional stop signal task.

    Science.gov (United States)

    Pawliczek, Christina M; Derntl, Birgit; Kellermann, Thilo; Kohn, Nils; Gur, Ruben C; Habel, Ute

    2013-10-01

    Deficits in response inhibition and heightened impulsivity have been linked to psychiatric disorders and aggression. They have been investigated in clinical groups as well as individuals with trait characteristics, yielding insights into the underlying neural and behavioral mechanisms of response inhibition and impulsivity. The motor inhibition tasks employed in most studies, however, have lacked an emotional component, which is crucial given that both response inhibition and impulsivity attain salience within a socio-emotional context. For this fMRI study, we selected a group with high trait aggression (HA, n=17) and one with low trait aggression (LA, n=16) from 550 males who had completed an Aggression Questionnaire. Neural activation was compared to an emotional version (including angry and neutral faces) of the stop signal task. Behavioral results revealed impaired response inhibition in HA, associated with higher motor impulsivity. This was accompanied by attenuated activation in brain regions involved in response inhibition, including the pre-supplementary motor area (SMA) and motor cortex. Together, these findings offer evidence that a reduced inhibition capacity is present in HA. Notably, response inhibition improved during anger trials in both groups, suggesting a facilitation effect through heightened activation in the related brain regions. In both groups, inclusion of the anger stimuli enhanced the activation of the motor and somatosensory areas, which modulate executive control, and of limbic regions including the amygdala. In summary, the investigation of response inhibition in individuals with high and low trait characteristics affords useful insights into the underlying distinct processing mechanisms. It can contribute to the investigation of trait markers in a clinical context without having to deal with the complex mechanisms of a clinical disorder itself. In contrast, the mechanisms of emotional response inhibition did not differ between groups

  15. Behavioral inhibition system (BIS), Behavioral activation system (BAS) and schizophrenia : Relationship with psychopathology and physiology

    NARCIS (Netherlands)

    Scholten, Marion R. M.; van Honk, Jack; Aleman, Andre; Kahn, Rene S.

    2006-01-01

    Objective: The Behavioral Inhibition System (BIS) and the Behavioral Activation System (BAS) have been conceptualized as two neural motivational systems that regulate sensitivity to punishment (BIS) and reward (BAS). Imbalance in BIS and BAS levels has been reported to be related to various forms of

  16. Interest Rate Forecasting with Neural Networks

    OpenAIRE

    Jan Täppinen

    1998-01-01

    This paper compares neural networks and linear regression models in interest rate forecasting using US term structure data. The expectations hypothesis gets some extra support from the neural network model as compared to the regression model. A neural network with the whole yield curve spectre from the difference between 1 and 3-month rates to the difference between 5 and 10-year rates predicts changes in interest rates quite well. However, during 1994?1995 the neural networks (as well as the...

  17. Neural network to diagnose lining condition

    Science.gov (United States)

    Yemelyanov, V. A.; Yemelyanova, N. Y.; Nedelkin, A. A.; Zarudnaya, M. V.

    2018-03-01

    The paper presents data on the problem of diagnosing the lining condition at the iron and steel works. The authors describe the neural network structure and software that are designed and developed to determine the lining burnout zones. The simulation results of the proposed neural networks are presented. The authors note the low learning and classification errors of the proposed neural networks. To realize the proposed neural network, the specialized software has been developed.

  18. Notch signaling patterns neurogenic ectoderm and regulates the asymmetric division of neural progenitors in sea urchin embryos.

    Science.gov (United States)

    Mellott, Dan O; Thisdelle, Jordan; Burke, Robert D

    2017-10-01

    We have examined regulation of neurogenesis by Delta/Notch signaling in sea urchin embryos. At gastrulation, neural progenitors enter S phase coincident with expression of Sp-SoxC. We used a BAC containing GFP knocked into the Sp-SoxC locus to label neural progenitors. Live imaging and immunolocalizations indicate that Sp-SoxC-expressing cells divide to produce pairs of adjacent cells expressing GFP. Over an interval of about 6 h, one cell fragments, undergoes apoptosis and expresses high levels of activated Caspase3. A Notch reporter indicates that Notch signaling is activated in cells adjacent to cells expressing Sp-SoxC. Inhibition of γ-secretase, injection of Sp-Delta morpholinos or CRISPR/Cas9-induced mutation of Sp-Delta results in supernumerary neural progenitors and neurons. Interfering with Notch signaling increases neural progenitor recruitment and pairs of neural progenitors. Thus, Notch signaling restricts the number of neural progenitors recruited and regulates the fate of progeny of the asymmetric division. We propose a model in which localized signaling converts ectodermal and ciliary band cells to neural progenitors that divide asymmetrically to produce a neural precursor and an apoptotic cell. © 2017. Published by The Company of Biologists Ltd.

  19. 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. 

  20. 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...

  1. Novel quantum inspired binary neural network algorithm

    Indian Academy of Sciences (India)

    In this paper, a quantum based binary neural network algorithm is proposed, named as novel quantum binary neural network algorithm (NQ-BNN). It forms a neural network structure by deciding weights and separability parameter in quantum based manner. Quantum computing concept represents solution probabilistically ...

  2. Analysis of neural networks through base functions

    NARCIS (Netherlands)

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

    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

  3. Epigenetic learning in non-neural organisms

    Indian Academy of Sciences (India)

    Prakash

    2008-09-19

    Sep 19, 2008 ... learning in neural organisms entail modifications – by inputs and outputs – in the efficiency or strength of existing (reflex) connections between neurons. A neural memory trace can be seen as the result of a temporary pattern of activity (firings) in a neural network, leading to changes in synaptic weights,.

  4. Similarity in gene-regulatory networks suggests that cancer cells share characteristics of embryonic neural cells.

    Science.gov (United States)

    Zhang, Zan; Lei, Anhua; Xu, Liyang; Chen, Lu; Chen, Yonglong; Zhang, Xuena; Gao, Yan; Yang, Xiaoli; Zhang, Min; Cao, Ying

    2017-08-04

    Cancer cells are immature cells resulting from cellular reprogramming by gene misregulation, and redifferentiation is expected to reduce malignancy. It is unclear, however, whether cancer cells can undergo terminal differentiation. Here, we show that inhibition of the epigenetic modification enzyme enhancer of zeste homolog 2 (EZH2), histone deacetylases 1 and 3 (HDAC1 and -3), lysine demethylase 1A (LSD1), or DNA methyltransferase 1 (DNMT1), which all promote cancer development and progression, leads to postmitotic neuron-like differentiation with loss of malignant features in distinct solid cancer cell lines. The regulatory effect of these enzymes in neuronal differentiation resided in their intrinsic activity in embryonic neural precursor/progenitor cells. We further found that a major part of pan-cancer-promoting genes and the signal transducers of the pan-cancer-promoting signaling pathways, including the epithelial-to-mesenchymal transition (EMT) mesenchymal marker genes, display neural specific expression during embryonic neurulation. In contrast, many tumor suppressor genes, including the EMT epithelial marker gene that encodes cadherin 1 ( CDH1 ), exhibited non-neural or no expression. This correlation indicated that cancer cells and embryonic neural cells share a regulatory network, mediating both tumorigenesis and neural development. This observed similarity in regulatory mechanisms suggests that cancer cells might share characteristics of embryonic neural cells. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  5. Phosphofructokinase-1 Negatively Regulates Neurogenesis from Neural Stem Cells.

    Science.gov (United States)

    Zhang, Fengyun; Qian, Xiaodan; Qin, Cheng; Lin, Yuhui; Wu, Haiyin; Chang, Lei; Luo, Chunxia; Zhu, Dongya

    2016-06-01

    Phosphofructokinase-1 (PFK-1), a major regulatory glycolytic enzyme, has been implicated in the functions of astrocytes and neurons. Here, we report that PFK-1 negatively regulates neurogenesis from neural stem cells (NSCs) by targeting pro-neural transcriptional factors. Using in vitro assays, we found that PFK-1 knockdown enhanced, and PFK-1 overexpression inhibited the neuronal differentiation of NSCs, which was consistent with the findings from NSCs subjected to 5 h of hypoxia. Meanwhile, the neurogenesis induced by PFK-1 knockdown was attributed to the increased proliferation of neural progenitors and the commitment of NSCs to the neuronal lineage. Similarly, in vivo knockdown of PFK-1 also increased neurogenesis in the dentate gyrus of the hippocampus. Finally, we demonstrated that the neurogenesis mediated by PFK-1 was likely achieved by targeting mammalian achaete-scute homologue-1 (Mash 1), neuronal differentiation factor (NeuroD), and sex-determining region Y (SRY)-related HMG box 2 (Sox2). All together, our results reveal PFK-1 as an important regulator of neurogenesis.

  6. Sex differences in emotional contexts modulation on response inhibition.

    Science.gov (United States)

    Ramos-Loyo, Julieta; Angulo-Chavira, Armando; Llamas-Alonso, Luis A; González-Garrido, Andrés A

    2016-10-01

    The aim of the present study was to explore sex differences in the effects that emotional contexts exert on the temporal course of response inhibition using event-related potentials (ERP). Participants performed a Go-NoGo response inhibition task under 3 context conditions: with 1) neutral background stimuli, and 2) pleasant, and 3) unpleasant emotional contexts. No sex differences were found in relation to accuracy. Women showed higher N2NoGo amplitudes than men in both emotional contexts; whereas during inhibition men tended to show higher P3NoGo amplitudes than women in the unpleasant context. Both groups experienced a relevant effect of the presence of the unpleasant context during inhibition processing, as shown by the enhancement of the N2NoGo amplitudes in frontal regions compared to results from the neutral and pleasant conditions. In addition, women showed differences between the pleasant and unpleasant contexts, with the latter inducing higher amplitude values. Only in men did inhibition accuracy correlate with higher N2NoGo and lower P3NoGo amplitudes in the emotional context conditions. These findings suggest that when an inhibition task is performed in an emotionally-neutral background context no sex differences are observed in either accuracy or ERP components. However, when the emotional context was introduced -especially the unpleasant one- some gender differences did become evident. The higher N2NoGo amplitude at the presence of the unpleasant context may reflect an effect on attention and conflict monitoring. In addition, results suggest that during earlier processing stages, women invested more resources to process inhibition than men. Furthermore, men who invested more neural resources during earlier stages showed better response inhibition than those who did it during later processing stages, more closely-related to cognitive and motor inhibition processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Numerical experiments with neural networks

    International Nuclear Information System (INIS)

    Miranda, Enrique.

    1990-01-01

    Neural networks are highly idealized models which, in spite of their simplicity, reproduce some key features of the real brain. In this paper, they are introduced at a level adequate for an undergraduate computational physics course. Some relevant magnitudes are defined and evaluated numerically for the Hopfield model and a short term memory model. (Author)

  8. Neural Mechanisms of Conceptual Relations

    Science.gov (United States)

    Lewis, Gwyneth A.

    2017-01-01

    An over-arching goal in neurolinguistic research is to characterize the neural bases of semantic representation. A particularly relevant goal concerns whether we represent features and events (a) together in a generalized semantic hub or (b) separately in distinct but complementary systems. While the left anterior temporal lobe (ATL) is strongly…

  9. Artificial Neural Networks·

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 2. Artificial Neural Networks A Brief Introduction. Jitendra R Raol Sunilkumar S Mankame. General Article Volume 1 Issue 2 February 1996 pp 47-54. Fulltext. Click here to view fulltext PDF. Permanent link:

  10. Classification using Bayesian neural nets

    NARCIS (Netherlands)

    J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)

    1995-01-01

    textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to

  11. Artificial Neural Networks·

    Indian Academy of Sciences (India)

    cial intelligence. However to understand the basics of ANNs, a knowledge of neurobiology is not necessary. Yet, it is a good idea to understand how ANNs have been derived from real biological neural systems (see Figures 1,2 and the accompanying boxes). The soma of the cell body receives inputs from other neurons via.

  12. Vestibular hearing and neural synchronization.

    Science.gov (United States)

    Emami, Seyede Faranak; Daneshi, Ahmad

    2012-01-01

    Objectives. Vestibular hearing as an auditory sensitivity of the saccule in the human ear is revealed by cervical vestibular evoked myogenic potentials (cVEMPs). The range of the vestibular hearing lies in the low frequency. Also, the amplitude of an auditory brainstem response component depends on the amount of synchronized neural activity, and the auditory nerve fibers' responses have the best synchronization with the low frequency. Thus, the aim of this study was to investigate correlation between vestibular hearing using cVEMPs and neural synchronization via slow wave Auditory Brainstem Responses (sABR). Study Design. This case-control survey was consisted of twenty-two dizzy patients, compared to twenty healthy controls. Methods. Intervention comprised of Pure Tone Audiometry (PTA), Impedance acoustic metry (IA), Videonystagmography (VNG), fast wave ABR (fABR), sABR, and cVEMPs. Results. The affected ears of the dizzy patients had the abnormal findings of cVEMPs (insecure vestibular hearing) and the abnormal findings of sABR (decreased neural synchronization). Comparison of the cVEMPs at affected ears versus unaffected ears and the normal persons revealed significant differences (P < 0.05). Conclusion. Safe vestibular hearing was effective in the improvement of the neural synchronization.

  13. Optoelectronic Implementation of Neural Networks

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 3; Issue 9. Optoelectronic Implementation of Neural Networks - Use of Optics in Computing. R Ramachandran. General Article Volume 3 Issue 9 September 1998 pp 45-55. Fulltext. Click here to view fulltext PDF. Permanent link:

  14. Artificial Neural Networks·

    Indian Academy of Sciences (India)

    works. They have the ability to learn from empirical datal information. They find use in computer science and control engineering fields. In recent years artificial ... However there are vast differences between biological neural networks (BNNs) of the brain and ANN s. A thorough understanding of biologically derived NNs ...

  15. 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…

  16. Medical Imaging with Neural Networks

    International Nuclear Information System (INIS)

    Pattichis, C.; Cnstantinides, A.

    1994-01-01

    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)

  17. Antagonistic neural networks underlying differentiated leadership roles

    Science.gov (United States)

    Boyatzis, Richard E.; Rochford, Kylie; Jack, Anthony I.

    2014-01-01

    The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks – the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success. PMID:24624074

  18. Explicit Logic Circuits Discriminate Neural States

    Science.gov (United States)

    Yoder, Lane

    2009-01-01

    The magnitude and apparent complexity of the brain's connectivity have left explicit networks largely unexplored. As a result, the relationship between the organization of synaptic connections and how the brain processes information is poorly understood. A recently proposed retinal network that produces neural correlates of color vision is refined and extended here to a family of general logic circuits. For any combination of high and low activity in any set of neurons, one of the logic circuits can receive input from the neurons and activate a single output neuron whenever the input neurons have the given activity state. The strength of the output neuron's response is a measure of the difference between the smallest of the high inputs and the largest of the low inputs. The networks generate correlates of known psychophysical phenomena. These results follow directly from the most cost-effective architectures for specific logic circuits and the minimal cellular capabilities of excitation and inhibition. The networks function dynamically, making their operation consistent with the speed of most brain functions. The networks show that well-known psychophysical phenomena do not require extraordinarily complex brain structures, and that a single network architecture can produce apparently disparate phenomena in different sensory systems. PMID:19127299

  19. Explicit logic circuits discriminate neural states.

    Directory of Open Access Journals (Sweden)

    Lane Yoder

    Full Text Available The magnitude and apparent complexity of the brain's connectivity have left explicit networks largely unexplored. As a result, the relationship between the organization of synaptic connections and how the brain processes information is poorly understood. A recently proposed retinal network that produces neural correlates of color vision is refined and extended here to a family of general logic circuits. For any combination of high and low activity in any set of neurons, one of the logic circuits can receive input from the neurons and activate a single output neuron whenever the input neurons have the given activity state. The strength of the output neuron's response is a measure of the difference between the smallest of the high inputs and the largest of the low inputs. The networks generate correlates of known psychophysical phenomena. These results follow directly from the most cost-effective architectures for specific logic circuits and the minimal cellular capabilities of excitation and inhibition. The networks function dynamically, making their operation consistent with the speed of most brain functions. The networks show that well-known psychophysical phenomena do not require extraordinarily complex brain structures, and that a single network architecture can produce apparently disparate phenomena in different sensory systems.

  20. Antagonistic Neural Networks Underlying Differentiated Leadership Roles

    Directory of Open Access Journals (Sweden)

    Richard Eleftherios Boyatzis

    2014-03-01

    Full Text Available The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950’s. Recent research in neuroscience suggests that the division between task oriented and socio-emotional oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks -- the Task Positive Network (TPN and the Default Mode Network (DMN. Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success.

  1. Antagonistic neural networks underlying differentiated leadership roles.

    Science.gov (United States)

    Boyatzis, Richard E; Rochford, Kylie; Jack, Anthony I

    2014-01-01

    The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks - the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success.

  2. 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.

  3. Neural networks and applications tutorial

    Science.gov (United States)

    Guyon, I.

    1991-09-01

    The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

  4. Non-invasive neural stimulation

    Science.gov (United States)

    Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

    2017-05-01

    Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

  5. Roles of chromatin remodelers in maintenance mechanisms of multipotency of mouse trunk neural crest cells in the formation of neural crest-derived stem cells.

    Science.gov (United States)

    Fujita, Kyohei; Ogawa, Ryuhei; Kawawaki, Syunsaku; Ito, Kazuo

    2014-08-01

    We analyzed roles of two chromatin remodelers, Chromodomain Helicase DNA-binding protein 7 (CHD7) and SWItch/Sucrose NonFermentable-B (SWI/SNF-B), and Bone Morphogenetic Protein (BMP)/Wnt signaling in the maintenance of the multipotency of mouse trunk neural crest cells, leading to the formation of mouse neural crest-derived stem cells (mouse NCSCs). CHD7 was expressed in the undifferentiated neural crest cells and in the dorsal root ganglia (DRG) and sciatic nerve, typical tissues containing NCSCs. BMP/Wnt signaling stimulated the expression of CHD7 and participated in maintaining the multipotency of neural crest cells. Furthermore, the promotion of CHD7 expression maintained the multipotency of these cells. The inhibition of CHD7 and SWI/SNF-B expression significantly suppressed the maintenance of the multipotency of these cells. In addition, BMP/Wnt treatment promoted CHD7 expression and caused the increase of the percentage of multipotent cells in DRG. Thus, the present data suggest that the chromatin remodelers as well as BMP/Wnt signaling play essential roles in the maintenance of the multipotency of mouse trunk neural crest cells and in the formation of mouse NCSCs. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  6. Parameterization Of Solar Radiation Using Neural Network

    International Nuclear Information System (INIS)

    Jiya, J. D.; Alfa, B.

    2002-01-01

    This paper presents a neural network technique for parameterization of global solar radiation. The available data from twenty-one stations is used for training the neural network and the data from other ten stations is used to validate the neural model. The neural network utilizes latitude, longitude, altitude, sunshine duration and period number to parameterize solar radiation values. The testing data was not used in the training to demonstrate the performance of the neural network in unknown stations to parameterize solar radiation. The results indicate a good agreement between the parameterized solar radiation values and actual measured values

  7. Micro- and Nanotechnologies for Optical Neural Interfaces

    Science.gov (United States)

    Pisanello, Ferruccio; Sileo, Leonardo; De Vittorio, Massimo

    2016-01-01

    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 highlights 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. PMID:27013939

  8. TV Inhibiting Creative Ideas

    Science.gov (United States)

    Intellect, 1977

    1977-01-01

    Television may be inhibiting our ability to create new ideas, according to Eric Somers, assistant professor of journalism at Drake University. Discusses television's role as facilitator of information and how it should improve to increase organization and the creative process. (Editor/RK)

  9. 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...

  10. 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.

  11. Cell polarity and neurogenesis in embryonic stem cell-derived neural rosettes.

    Science.gov (United States)

    Banda, Erin; McKinsey, Anna; Germain, Noelle; Carter, James; Anderson, Nickesha Camille; Grabel, Laura

    2015-04-15

    Embryonic stem cells (ESCs) undergoing neural differentiation form radial arrays of neural stem cells, termed neural rosettes. These structures manifest many of the properties associated with embryonic and adult neurogenesis, including cell polarization, interkinetic nuclear migration (INM), and a gradient of neuronal differentiation. We now identify novel rosette structural features that serve to localize key regulators of neurogenesis. Cells within neural rosettes have specialized basal as well as apical surfaces, based on localization of the extracellular matrix receptor β1 integrin. Apical processes of cells in mature rosettes terminate at the lumen, where adherens junctions are apparent. Primary cilia are randomly distributed in immature rosettes and tightly associated with the neural stem cell's apical domain as rosettes mature. Components of two signaling pathways known to regulate neurogenesis in vivo and in rosettes, Hedgehog and Notch, are apically localized, with the Hedgehog effector Smoothened (Smo) associated with primary cilia and the Notch pathway γ-secretase subunit Presenilin 2 associated with the adherens junction. Increased neuron production upon treatment with the Notch inhibitor DAPT suggests a major role for Notch signaling in maintaining the neural stem cell state, as previously described. A less robust outcome was observed with manipulation of Hedgehog levels, though consistent with a role in neural stem cell survival or proliferation. Inhibition of both pathways resulted in an additive effect. These data support a model by which cells extending a process to the rosette lumen maintain neural stem cell identity whereas release from this association, either through asymmetric cell division or apical abscission, promotes neuronal differentiation.

  12. Impaired Tuning of Neural Ensembles and the Pathophysiology of Schizophrenia: A Translational and Computational Neuroscience Perspective.

    Science.gov (United States)

    Krystal, John H; Anticevic, Alan; Yang, Genevieve J; Dragoi, George; Driesen, Naomi R; Wang, Xiao-Jing; Murray, John D

    2017-05-15

    The functional optimization of neural ensembles is central to human higher cognitive functions. When the functions through which neural activity is tuned fail to develop or break down, symptoms and cognitive impairments arise. This review considers ways in which disturbances in the balance of excitation and inhibition might develop and be expressed in cortical networks in association with schizophrenia. This presentation is framed within a developmental perspective that begins with disturbances in glutamate synaptic development in utero. It considers developmental correlates and consequences, including compensatory mechanisms that increase intrinsic excitability or reduce inhibitory tone. It also considers the possibility that these homeostatic increases in excitability have potential negative functional and structural consequences. These negative functional consequences of disinhibition may include reduced working memory-related cortical activity associated with the downslope of the "inverted-U" input-output curve, impaired spatial tuning of neural activity and impaired sparse coding of information, and deficits in the temporal tuning of neural activity and its implication for neural codes. The review concludes by considering the functional significance of noisy activity for neural network function. The presentation draws on computational neuroscience and pharmacologic and genetic studies in animals and humans, particularly those involving N-methyl-D-aspartate glutamate receptor antagonists, to illustrate principles of network regulation that give rise to features of neural dysfunction associated with schizophrenia. While this presentation focuses on schizophrenia, the general principles outlined in the review may have broad implications for considering disturbances in the regulation of neural ensembles in psychiatric disorders. Published by Elsevier Inc.

  13. The Growing Hierarchical Neural Gas Self-Organizing Neural Network.

    Science.gov (United States)

    Palomo, Esteban J; Lopez-Rubio, Ezequiel

    2017-09-01

    The growing neural gas (GNG) self-organizing neural network stands as one of the most successful examples of unsupervised learning of a graph of processing units. Despite its success, little attention has been devoted to its extension to a hierarchical model, unlike other models such as the self-organizing map, which has many hierarchical versions. Here, a hierarchical GNG is presented, which is designed to learn a tree of graphs. Moreover, the original GNG algorithm is improved by a distinction between a growth phase where more units are added until no significant improvement in the quantization error is obtained, and a convergence phase where no unit creation is allowed. This means that a principled mechanism is established to control the growth of the structure. Experiments are reported, which demonstrate the self-organization and hierarchy learning abilities of our approach and its performance for vector quantization applications.

  14. Spike Neural Models Part II: Abstract Neural Models

    OpenAIRE

    Johnson, Melissa G.; Chartier, Sylvain

    2018-01-01

    Neurons are complex cells that require a lot of time and resources to model completely. In spiking neural networks (SNN) though, not all that complexity is required. Therefore simple, abstract models are often used. These models save time, use less computer resources, and are easier to understand. This tutorial presents two such models: Izhikevich's model, which is biologically realistic in the resulting spike trains but not in the parameters, and the Leaky Integrate and Fire (LIF) model whic...

  15. Samba, a Xenopus hnRNP expressed in neural and neural crest tissues.

    Science.gov (United States)

    Yan, Chao Yun Irene; Skourides, Paris; Chang, Chenbei; Brivanlou, Ali

    2009-01-01

    RNA binding proteins regulate gene expression at the posttranscriptional level and play important roles in embryonic development. Here, we report the cloning and expression of Samba, a Xenopus hnRNP that is maternally expressed and persists at least until tail bud stages. During gastrula stages, Samba is enriched in the dorsal regions. Subsequently, its expression is elevated only in neural and neural crest tissues. In the latter, Samba expression overlaps with that of Slug in migratory neural crest cells. Thereafter, Samba is maintained in the neural crest derivatives, as well as other neural tissues, including the anterior and posterior neural tube and the eyes. Overexpression of Samba in the animal pole leads to defects in neural crest migration and cranial cartilage development. Thus, Samba encodes a Xenopus hnRNP that is expressed early in neural and neural crest derivatives and may regulate crest cells migratory behavior. Copyright (c) 2008 Wiley-Liss, Inc.

  16. Beta1 integrins activate a MAPK signalling pathway in neural stem cells that contributes to their maintenance

    DEFF Research Database (Denmark)

    Campos, Lia S; Leone, Dino P; Relvas, Joao B

    2004-01-01

    , signalling is required for neural stem cell maintenance, as assessed by neurosphere formation, and inhibition or genetic ablation of beta1 integrin using cre/lox technology reduces the level of MAPK activity. We conclude that integrins are therefore an important part of the signalling mechanisms that control...

  17. Computation within cultured neural networks.

    Science.gov (United States)

    DeMarse, T; Cadotte, A; Douglas, P; He, P; Trinh, V

    2004-01-01

    In this paper we present three related areas of research we are pursuing to study neural computation in vitro. Rat cortical neurons cultured on 60 channel multielectrode array (MEA) allow the researcher to measure from and stimulate sixty different sites across a small population of neurons grown in vitro. Using this system we can send stimulation patterns into the network and study how these living neural networks compute by measuring its outputs. Our first series of studies uses chaotic control techniques to study the dynamics and potentially control the behavior of cortical network. At the same time, we are beginning to apply a model of computation called the liquid state machine or LSM model developed by Wolfgang Maass to provide a firm mathematical framework from which to proceed with our investigations. Each of these components is integrated into a third area investigating the role of computation and feedback using a real-time sensory-motor feedback robotic flight system.

  18. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    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...... concerning canonical, observable state space forms (minimum realizable form) for SISO as wll as MIMO processes. The tests show that all models, after succeeeful training, which is judged by correlation analysis of the prediction errors, are able to perform non-linear system identification, prediction...

  19. 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...

  20. 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.

  1. Genetic attack on neural cryptography

    International Nuclear Information System (INIS)

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

    2006-01-01

    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

  2. Neural plasticity across the lifespan.

    Science.gov (United States)

    Power, Jonathan D; Schlaggar, Bradley L

    2017-01-01

    An essential feature of the brain is its capacity to change. Neuroscientists use the term 'plasticity' to describe the malleability of neuronal connectivity and circuitry. How does plasticity work? A review of current data suggests that plasticity encompasses many distinct phenomena, some of which operate across most or all of the lifespan, and others that operate exclusively in early development. This essay surveys some of the key concepts related to neural plasticity, beginning with how current patterns of neural activity (e.g., as you read this essay) come to impact future patterns of activity (e.g., your memory of this essay), and then extending this framework backward into more development-specific mechanisms of plasticity. WIREs Dev Biol 2017, 6:e216. doi: 10.1002/wdev.216 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

  3. Circadian and ultradian glucocorticoid rhythmicity: Implications for the effects of glucocorticoids on neural stem cells and adult hippocampal neurogenesis.

    Science.gov (United States)

    Fitzsimons, Carlos P; Herbert, Joe; Schouten, Marijn; Meijer, Onno C; Lucassen, Paul J; Lightman, Stafford

    2016-04-01

    Psychosocial stress, and within the neuroendocrine reaction to stress specifically the glucocorticoid hormones, are well-characterized inhibitors of neural stem/progenitor cell proliferation in the adult hippocampus, resulting in a marked reduction in the production of new neurons in this brain area relevant for learning and memory. However, the mechanisms by which stress, and particularly glucocorticoids, inhibit neural stem/progenitor cell proliferation remain unclear and under debate. Here we review the literature on the topic and discuss the evidence for direct and indirect effects of glucocorticoids on neural stem/progenitor cell proliferation and adult neurogenesis. Further, we discuss the hypothesis that glucocorticoid rhythmicity and oscillations originating from the activity of the hypothalamus-pituitary-adrenal axis, may be crucial for the regulation of neural stem/progenitor cells in the hippocampus, as well as the implications of this hypothesis for pathophysiological conditions in which glucocorticoid oscillations are affected. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Inhibiting the inevitable

    DEFF Research Database (Denmark)

    Shashoua, Yvonne

    2006-01-01

    conservation is to ‘buy time’ for the object. Inhibitive conservation of plastics involves the removal or reduction of factors causing or accelerating degradation including light, oxygen, acids, relative humidity and acidic breakdown products. Specific approaches to conservation have been developed......Once plastics objects are registered in museum collections, the institution becomes responsible for their long term preservation, until the end of their useful lifetime. Plastics appear to deteriorate faster than other materials in museum collections and have a useful lifetime between 5 and 25...... years. Preventive or inhibitive conservation involves controlling the environments in which objects are placed during storage and display, with the aim of slowing the major deterioration reactions. Once in progress, degradation of plastics cannot be stopped or reversed, so the aim of preventive...

  5. 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.

  6. 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

  7. Macroscopic Neural Theories of Cognition

    Science.gov (United States)

    2014-03-01

    positive localizations of fMRI brain responses could be recorded from even as unlikely a specimen as a dead salmon . They pointed out that the...with their specific chemistry or genetic properties. However, this powerful technique does not, as sometimes suggested, permit the idiosyncratic...Wolford, G. L. (2011). Neural correlates of interspecies perspective taking in the post-mortem Atlantic Salmon : An argument for proper multiple

  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. [Glutamate signaling and neural plasticity].

    Science.gov (United States)

    Watanabe, Masahiko

    2013-07-01

    Proper functioning of the nervous system relies on the precise formation of neural circuits during development. At birth, neurons have redundant synaptic connections not only to their proper targets but also to other neighboring cells. Then, functional neural circuits are formed during early postnatal development by the selective strengthening of necessary synapses and weakening of surplus connections. Synaptic connections are also modified so that projection fields of active afferents expand at the expense of lesser ones. We have studied the molecular mechanisms underlying these activity-dependent prunings and the plasticity of synaptic circuitry using gene-engineered mice defective in the glutamatergic signaling system. NMDA-type glutamate receptors are critically involved in the establishment of the somatosensory pathway ascending from the brainstem trigeminal nucleus to the somatosensory cortex. Without NMDA receptors, whisker-related patterning fails to develop, whereas lesion-induced plasticity occurs normally during the critical period. In contrast, mice lacking the glutamate transporters GLAST or GLT1 are selectively impaired in the lesion-induced critical plasticity of cortical barrels, although whisker-related patterning itself develops normally. In the developing cerebellum, multiple climbing fibers initially innervating given Purkinje cells are eliminated one by one until mono-innervation is achieved. In this pruning process, P/Q-type Ca2+ channels expressed on Purkinje cells are critically involved by the selective strengthening of single main climbing fibers against other lesser afferents. Therefore, the activation of glutamate receptors that leads to an activity-dependent increase in the intracellular Ca2+ concentration plays a key role in the pruning of immature synaptic circuits into functional circuits. On the other hand, glutamate transporters appear to control activity-dependent plasticity among afferent fields, presumably through adjusting

  10. Artificial Neural Networks for Beginners

    OpenAIRE

    Gershenson, Carlos

    2003-01-01

    The scope of this teaching package is to make a brief induction to Artificial Neural Networks (ANNs) for people who have no previous knowledge of them. We first make a brief introduction to models of networks, for then describing in general terms ANNs. As an application, we explain the backpropagation algorithm, since it is widely used and many other algorithms are derived from it. The user should know algebra and the handling of functions and vectors. Differential calculus is recommendable, ...

  11. Localization and distribution of superoxide dismutase-1 in the neural tube morphogenesis of chick embryo.

    Science.gov (United States)

    Dhage, Prajakta A; Kamble, Lekha K; Bhargava, Shobha Y

    2017-02-01

    Superoxide dismutase 1 (SOD- 1) is an antioxidant enzyme that regulates the levels of Reactive oxygen species (ROS) by catalyzing the conversion of superoxide radical into hydrogen peroxide (H 2 O 2 ) and oxygen. ROS are known to play a significant role in various cellular processes, via redox modification of a variety of molecules that participate in signaling pathways involved in this processes. As the levels of ROS in cells are controlled by the levels of antioxidant enzymes, thus SOD-1 may be indirectly involved in regulating different cellular processes by maintaining the required levels of H 2 O 2. Therefore, in the present study we have investigated the possible involvement of SOD- 1 in the neurulation during the development of chick embryo. During gastrulation, SOD- 1 immunoreactivity was observed throughout the ectoderm and cauda mesoderm areas, however, its presence during neurulation was restricted to certain areas of neural tube particularly in the dorsal neural tube where neural tube closure takes place. Assaying enzyme activity revealed a significant increase in the SOD activity during neurulation. Further, inhibition of SOD- 1 by Diethyldithiocarbamate (DDC) induced abnormalities in the development of the neural tube. SOD- 1 inhibition specifically affected the closure of neural tube in the anterior region. Thus, here we report the presence of SOD- 1 mainly in the ectoderm and tissues of ectodermal origin during gastrulation to neurulation which suggests that it may be involved in the regulating the cellular processes during neural tube morphogenesis. Copyright © 2016 ISDN. Published by Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Nimrod Miller

    2011-03-01

    Full Text Available 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?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.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.

  13. Synchronization and long-time memory in neural networks with inhibitory hubs and synaptic plasticity

    Science.gov (United States)

    Bertolotti, Elena; Burioni, Raffaella; di Volo, Matteo; Vezzani, Alessandro

    2017-01-01

    We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous mean-field approximation to encode the role of network structure and we tune the fraction of inhibitory neurons fI and their connectivity level to investigate the cooperation between hub features and inhibition. We show that, depending on fI, highly connected inhibitory nodes strongly drive the synchronization properties of the overall network through dynamical transitions from synchronous to asynchronous regimes. Furthermore, a metastable regime with long memory of external inputs emerges for a specific fraction of hub inhibitory neurons, underlining the role of inhibition and connectivity also for input processing in neural networks.

  14. Metastable neural dynamics mediates expectation

    Science.gov (United States)

    Mazzucato, Luca; La Camera, Giancarlo; Fontanini, Alfredo

    Sensory stimuli are processed faster when their presentation is expected compared to when they come as a surprise. We previously showed that, in multiple single-unit recordings from alert rat gustatory cortex, taste stimuli can be decoded faster from neural activity if preceded by a stimulus-predicting cue. However, the specific computational process mediating this anticipatory neural activity is unknown. Here, we propose a biologically plausible model based on a recurrent network of spiking neurons with clustered architecture. In the absence of stimulation, the model neural activity unfolds through sequences of metastable states, each state being a population vector of firing rates. We modeled taste stimuli and cue (the same for all stimuli) as two inputs targeting subsets of excitatory neurons. As observed in experiment, stimuli evoked specific state sequences, characterized in terms of `coding states', i.e., states occurring significantly more often for a particular stimulus. When stimulus presentation is preceded by a cue, coding states show a faster and more reliable onset, and expected stimuli can be decoded more quickly than unexpected ones. This anticipatory effect is unrelated to changes of firing rates in stimulus-selective neurons and is absent in homogeneous balanced networks, suggesting that a clustered organization is necessary to mediate the expectation of relevant events. Our results demonstrate a novel mechanism for speeding up sensory coding in cortical circuits. NIDCD K25-DC013557 (LM); NIDCD R01-DC010389 (AF); NSF IIS-1161852 (GL).

  15. Photon spectrometry utilizing neural networks

    International Nuclear Information System (INIS)

    Silveira, R.; Benevides, C.; Lima, F.; Vilela, E.

    2015-01-01

    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)

  16. Central neural pathways for thermoregulation

    Science.gov (United States)

    Morrison, Shaun F.; Nakamura, Kazuhiro

    2010-01-01

    Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction. PMID:21196160

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

    Science.gov (United States)

    Ashoor, Abrar; Nordman, Jacob C; Veltri, Daniel; Yang, Keun-Hang Susan; Al Kury, Lina; Shuba, Yaroslav; Mahgoub, Mohamed; Howarth, Frank C; Sadek, Bassem; Shehu, Amarda; Kabbani, Nadine; Oz, Murat

    2013-01-01

    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 [(125)I] 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.

  18. 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.

  19. Response inhibition deficits in children with Fetal Alcohol Spectrum Disorder: Relationship between diffusion tensor imaging of the corpus callosum and eye movement control

    OpenAIRE

    Angelina Paolozza; Sarah Treit; Christian Beaulieu; James N. Reynolds

    2014-01-01

    Response inhibition is the ability to suppress irrelevant impulses to enable goal-directed behavior. The underlying neural mechanisms of inhibition deficits are not clearly understood, but may be related to white matter connectivity, which can be assessed using diffusion tensor imaging (DTI). The goal of this study was to investigate the relationship between response inhibition during the performance of saccadic eye movement tasks and DTI measures of the corpus callosum in children with or wi...

  20. 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.

  1. Associations Between Behavioral and Neural Correlates of Inhibitory Control and Amphetamine Reward Sensitivity.

    Science.gov (United States)

    Weafer, Jessica; Gorka, Stephanie M; Hedeker, Donald; Dzemidzic, Mario; Kareken, David A; Phan, K Luan; de Wit, Harriet

    2017-08-01

    Poor inhibitory control and sensitivity to drug reward are two significant risk factors for drug abuse. Although the two have been largely viewed as separate and independent risk factors, there is new evidence to suggest that they may be related at both the behavioral and neural level. This study examined associations between behavioral and neural correlates of inhibitory control and sensitivity to the subjective rewarding effects of amphetamine in humans. Healthy volunteers (n=63) first completed the stop signal task, a behavioral measure of inhibitory control. Then they participated in four sessions in which they received amphetamine (20 mg) and placebo in alternating order, providing self-report measures of euphoria and arousal at regular intervals. Finally, a subset of participants (n=38) underwent an fMRI scan to assess neural correlates of inhibitory control. In the first phase of the study, participants with longer stop signal reaction time (SSRT) reported greater amphetamine-induced euphoria and stimulation than those with shorter SSRT. In the second phase, fMRI of response inhibition showed the expected activation in right prefrontal regions. Further, individuals who exhibited less activation in the right middle frontal gyrus during the inhibition task reported more euphoria during the amphetamine sessions. This study is the first to show associations between poor inhibitory control and amphetamine reward sensitivity at both behavioral and neural levels in humans. These findings extend our understanding of risk for drug abuse in individuals with poor inhibitory control and suggest novel targets for prevention efforts.

  2. 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.

  3. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. 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....

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

    OpenAIRE

    Zikopoulos, Basilis; Barbas, Helen

    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...

  6. Prediction of bioactive compounds activity against wood contaminant fungi using artificial neural networks

    OpenAIRE

    Vicente, Henrique; Roseiro, José C.; Arteiro, José M.; Neves, José; Caldeira, A. Teresa

    2013-01-01

    Biopesticides based on natural endophytic bacteria to control plant diseases are an ecological alternative to the chemical treatments. Bacillus species produce a wide variety of metabolites with biological activity like iturinic lipopeptides. This work addresses the production of biopesticides based on natural endophytic bacteria, isolated from Quercus suber. Artificial Neural Networks were used to maximize the percentage of inhibition triggered by antifungal activity of bioactive compounds p...

  7. Neurosecurity: security and privacy for neural devices.

    Science.gov (United States)

    Denning, Tamara; Matsuoka, Yoky; Kohno, Tadayoshi

    2009-07-01

    An increasing number of neural implantable devices will become available in the near future due to advances in neural engineering. This discipline holds the potential to improve many patients' lives dramatically by offering improved-and in some cases entirely new-forms of rehabilitation for conditions ranging from missing limbs to degenerative cognitive diseases. The use of standard engineering practices, medical trials, and neuroethical evaluations during the design process can create systems that are safe and that follow ethical guidelines; unfortunately, none of these disciplines currently ensure that neural devices are robust against adversarial entities trying to exploit these devices to alter, block, or eavesdrop on neural signals. The authors define "neurosecurity"-a version of computer science security principles and methods applied to neural engineering-and discuss why neurosecurity should be a critical consideration in the design of future neural devices.

  8. Rod-Shaped Neural Units for Aligned 3D Neural Network Connection.

    Science.gov (United States)

    Kato-Negishi, Midori; Onoe, Hiroaki; Ito, Akane; Takeuchi, Shoji

    2017-08-01

    This paper proposes neural tissue units with aligned nerve fibers (called rod-shaped neural units) that connect neural networks with aligned neurons. To make the proposed units, 3D fiber-shaped neural tissues covered with a calcium alginate hydrogel layer are prepared with a microfluidic system and are cut in an accurate and reproducible manner. These units have aligned nerve fibers inside the hydrogel layer and connectable points on both ends. By connecting the units with a poly(dimethylsiloxane) guide, 3D neural tissues can be constructed and maintained for more than two weeks of culture. In addition, neural networks can be formed between the different neural units via synaptic connections. Experimental results indicate that the proposed rod-shaped neural units are effective tools for the construction of spatially complex connections with aligned nerve fibers in vitro. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. 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.

  10. First Result on Arabic Neural Machine Translation

    OpenAIRE

    Almahairi, Amjad; Cho, Kyunghyun; Habash, Nizar; Courville, Aaron

    2016-01-01

    Neural machine translation has become a major alternative to widely used phrase-based statistical machine translation. We notice however that much of research on neural machine translation has focused on European languages despite its language agnostic nature. In this paper, we apply neural machine translation to the task of Arabic translation (ArEn) and compare it against a standard phrase-based translation system. We run extensive comparison using various configurations in preprocessing Ara...

  11. Dynamic training algorithm for dynamic neural networks

    International Nuclear Information System (INIS)

    Tan, Y.; Van Cauwenberghe, A.; Liu, Z.

    1996-01-01

    The widely used backpropagation algorithm for training neural networks based on the gradient descent has a significant drawback of slow convergence. A Gauss-Newton method based recursive least squares (RLS) type algorithm with dynamic error backpropagation is presented to speed-up the learning procedure of neural networks with local recurrent terms. Finally, simulation examples concerning the applications of the RLS type algorithm to identification of nonlinear processes using a local recurrent neural network are also included in this paper

  12. Oil reservoir properties estimation using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Toomarian, N.B. [California Inst. of Tech., Pasadena, CA (United States); Barhen, J.; Glover, C.W. [Oak Ridge National Lab., TN (United States). Center for Engineering Systems Advanced Research; Aminzadeh, F. [UNOCAL Corp., Sugarland, TX (United States)

    1997-02-01

    This paper investigates the applicability as well as the accuracy of artificial neural networks for estimating specific parameters that describe reservoir properties based on seismic data. This approach relies on JPL`s adjoint operators general purpose neural network code to determine the best suited architecture. The authors believe that results presented in this work demonstrate that artificial neural networks produce surprisingly accurate estimates of the reservoir parameters.

  13. Neural network monitoring of resistance welding processes

    OpenAIRE

    Quero Reboul, José Manuel; Millán Vázquez de la Torre, Rafael Luis; García Franquelo, Leopoldo; Cañas, J.

    1994-01-01

    Control of weld quality is one of the most important and complex processes to be carried out on production lines. Neural networks have shown good results in fields such as modelling and control of physical processes. It is suggested in this article that a neural classifier should be used to carry out non‐destructive on‐line analysis. This system has been developed and installed at resistance welding stations. Results confirm the validity of neural networks used for this type of application.

  14. 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.

  15. Nonlinear adaptive neural controller for unstable aircraft

    OpenAIRE

    Suresh, S; Omkar, SN; Mani, V; Sundararajan, N

    2005-01-01

    A model reference indirect adaptive neural control scheme that uses both off-line and online learning strategies is proposed for an,unstable nonlinear aircraft controller design. The bounded-input-bounded-output stability requirement for the controller design is circumvented using an off-line, finite interval of time training scheme. The aircraft model is first identified using a neural network with linear filter (also known as time-delayed neural network) with the available input-output data...

  16. GABAergic Neural Activity Involved in Salicylate-Induced Auditory Cortex Gain Enhancement

    Science.gov (United States)

    Lu, Jianzhong; Lobarinas, Edward; Deng, Anchun; Goodey, Ronald; Stolzberg, Daniel; Salvi, Richard J.; Sun, Wei

    2011-01-01

    Although high doses of sodium salicylate impair cochlear function, it paradoxically enhances sound-evoked activity in the auditory cortex (AC) and augments acoustic startle reflex responses, neural and behavioral metrics associated with hyperexcitability and hyperacusis. To explore the neural mechanisms underlying salicylate-induced hyperexcitability and “increased central gain”, we examined the effects of γ-aminobutyric acid (GABA) receptor agonists and antagonists on salicylate-induced hyperexcitability in the AC and startle reflex responses. Consistent with our previous findings, local or systemic application of salicylate significantly increased the amplitude of sound-evoked AC neural activity, but generally reduced spontaneous activity in the AC. Systemic injection of salicylate also significantly increased the acoustic startle reflex. S-baclofen or R-baclofen, GABA-B agonists, which suppressed sound-evoked AC neural firing rate and local field potentials, also suppressed the salicylate-induced enhancement of the AC field potential and the acoustic startle reflex. Local application of vigabatrin, which enhances GABA concentration in the brain, suppressed the salicylate-induced enhancement of AC firing rate. Systemic injection of vigabatrin also reduced the salicylate-induced enhancement of acoustic startle reflex. Collectively, these results suggest that the sound-evoked behavioral and neural hyperactivity induced by salicylate may arise from a salicylate-induced suppression GABAergic inhibition in the AC. PMID:21664433

  17. 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.

  18. Neural Systems Mediating Seasonal Breeding in the Ewe

    Science.gov (United States)

    Goodman, R. L.; Jansen, H.T.; Billings, H. J.; Coolen, L.M.; Lehman, M. N.

    2010-01-01

    Seasonal reproduction in ewes is caused by a dramatic increase in response to oestradiol (E2) negative feedback during the non-breeding (anoestrous) season. Considerable evidence supports the hypothesis that A15 dopaminergic (DA) neurones in the retrochiasmatic area (RCh) play a key role in these seasonal changes. These A15 neurones are stimulated by E2 and inhibit GnRH secretion in anoestrus, but not the breeding season. Because A15 neurones do not contain estrogen receptors-α (ERα), it is likely that E2-responsive afferents stimulate their activity when circulating E2 levels increase during anoestrus. Retrograde tract tracing studies identified a limited set of ERα-containing afferents primarily found in four areas (ventromedial preoptic area, RCh, ventromedial and arcuate [ARC] nuclei). Pharmacological and anatomical data are consistent with γ-aminobutyric acid (GABA)- and glutamate-containing afferents controlling A15 activity in anoestrus, with E2 inhibiting GABA and stimulating glutamate release at this time of year. Tract tracing demonstrated that A15 efferents project posteriorly to the median eminence and the ARC, suggesting possible direct actions on GnRH terminals or indirect actions via kisspeptin neurones in the ARC to inhibit GnRH in anoestrus. Identification of this neural circuitry sets the stage for development of specific hypotheses for morphological or transmitter/receptor expression changes that would account for seasonal breeding in ewes. PMID:20456601

  19. Fast computation with spikes in a recurrent neural network

    International Nuclear Information System (INIS)

    Jin, Dezhe Z.; Seung, H. Sebastian

    2002-01-01

    Neural networks with recurrent connections are sometimes regarded as too slow at computation to serve as models of the brain. Here we analytically study a counterexample, a network consisting of N integrate-and-fire neurons with self excitation, all-to-all inhibition, instantaneous synaptic coupling, and constant external driving inputs. When the inhibition and/or excitation are large enough, the network performs a winner-take-all computation for all possible external inputs and initial states of the network. The computation is done very quickly: As soon as the winner spikes once, the computation is completed since no other neurons will spike. For some initial states, the winner is the first neuron to spike, and the computation is done at the first spike of the network. In general, there are M potential winners, corresponding to the top M external inputs. When the external inputs are close in magnitude, M tends to be larger. If M>1, the selection of the actual winner is strongly influenced by the initial states. If a special relation between the excitation and inhibition is satisfied, the network always selects the neuron with the maximum external input as the winner

  20. 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. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. The neural correlates of impaired inhibitory control in anxiety.

    Science.gov (United States)

    Ansari, Tahereh L; Derakshan, Nazanin

    2011-04-01

    According to Attentional Control Theory (Eysenck et al., 2007) anxiety impairs the inhibition function of working memory by increasing the influence of stimulus-driven processes over efficient top-down control. We investigated the neural correlates of impaired inhibitory control in anxiety using an antisaccade task. Low- and high-anxious participants performed anti- and prosaccade tasks and electrophysiological activity was recorded. Consistent with previous research high-anxious individuals had longer antisaccade latencies in response to the to-be-inhibited target, compared with low-anxious individuals. Central to our predictions, high-anxious individuals showed lower ERP activity, at frontocentral and central recording sites, than low anxious individuals, in the period immediately prior to onset of the to-be-inhibited target on correct antisaccade trials. Our findings indicate that anxiety interferes with the efficient recruitment of top-down mechanisms required for the suppression of prepotent responses. Implications are discussed within current models of attentional control in anxiety (Bishop, 2009; Eysenck et al., 2007). Copyright © 2011 Elsevier Ltd. All rights reserved.

  2. 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

  3. 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

  4. Artificial Neural Networks and Concentration Residual Augmented ...

    African Journals Online (AJOL)

    Artificial Neural Networks and Concentration Residual Augmented Classical Least Squares for the Simultaneous Determination of Diphenhydramine, Benzonatate, Guaifenesin and Phenylephrine in their Quaternary Mixture.

  5. Structured neural networks for pattern recognition.

    Science.gov (United States)

    Murino, V

    1998-01-01

    This paper proposes a novel approach for the design of structures of neural networks for pattern recognition. The basic idea lies in subdividing the whole classification problem in smaller and simpler problems at different levels, each managed by appropriate components of a complex neural architecture. Three neural structures are presented and applied in a surveillance system aimed at monitoring a railway waiting room classifying potential dangerous situations. Each architecture is composed by nodes, which are actual multilayer perceptrons trained to discriminate between subsets of classes until a complete separation among the classes is achieved. This approach showed better performances with respect to a classical statistical classification procedures and to a single neural network.

  6. Neural correlates of consciousness: progress and problems.

    Science.gov (United States)

    Koch, Christof; Massimini, Marcello; Boly, Melanie; Tononi, Giulio

    2016-05-01

    There have been a number of advances in the search for the neural correlates of consciousness--the minimum neural mechanisms sufficient for any one specific conscious percept. In this Review, we describe recent findings showing that the anatomical neural correlates of consciousness are primarily localized to a posterior cortical hot zone that includes sensory areas, rather than to a fronto-parietal network involved in task monitoring and reporting. We also discuss some candidate neurophysiological markers of consciousness that have proved illusory, and measures of differentiation and integration of neural activity that offer more promising quantitative indices of consciousness.

  7. Boolean Factor Analysis by Attractor Neural Network

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.

    2007-01-01

    Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007

  8. Neural network based system for equipment surveillance

    Science.gov (United States)

    Vilim, R.B.; Gross, K.C.; Wegerich, S.W.

    1998-04-28

    A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

  9. 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

  10. Time-course of motor inhibition during hypnotic paralysis: EEG topographical and source analysis.

    Science.gov (United States)

    Cojan, Yann; Archimi, Aurélie; Cheseaux, Nicole; Waber, Lakshmi; Vuilleumier, Patrik

    2013-02-01

    Cognitive hypotheses of hypnotic phenomena have proposed that executive attentional systems may be either inhibited or overactivated to produce a selective alteration or disconnection of some mental operations. Recent brain imaging studies have reported changes in activity in both medial (anterior cingulate) and lateral (inferior) prefrontal areas during hypnotically induced paralysis, overlapping with areas associated with attentional control as well as inhibitory processes. To compare motor inhibition mechanisms responsible for paralysis during hypnosis and those recruited by voluntary inhibition, we used electroencephalography (EEG) to record brain activity during a modified bimanual Go-Nogo task, which was performed either in a normal baseline condition or during unilateral paralysis caused by hypnotic suggestion or by simulation (in two groups of participants, each tested once with both hands valid and once with unilateral paralysis). This paradigm allowed us to identify patterns of neural activity specifically associated with hypnotically induced paralysis, relative to voluntary inhibition during simulation or Nogo trials. We used a topographical EEG analysis technique to investigate both the spatial organization and the temporal sequence of neural processes activated in these different conditions, and to localize the underlying anatomical generators through minimum-norm methods. We found that preparatory activations were similar in all conditions, despite left hypnotic paralysis, indicating preserved motor intentions. A large P3-like activity was generated by voluntary inhibition during voluntary inhibition (Nogo), with neural sources in medial prefrontal areas, while hypnotic paralysis was associated with a distinctive topography activity during the same time-range and specific sources in right inferior frontal cortex. These results add support to the view that hypnosis might act by enhancing executive control systems mediated by right prefrontal areas, but

  11. Cultured neural networks: Optimisation of patterned network adhesiveness and characterisation of their neural activity

    NARCIS (Netherlands)

    Rutten, Wim; Ruardij, T.G.; Marani, Enrico; Roelofsen, B.H.

    2006-01-01

    One type of future, improved neural interface is the "cultured probe"?. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA) on a planar substrate, each electrode being covered and

  12. 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

    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...

  13. 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

  14. 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.

    2016-01-01

    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

  15. 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...... of the Aachen Aphasia Test (AAT). First a coarse classification was achieved by using an assessment of spontaneous speech of the patient. This classifier produced correct results in 87% of the test cases. For a second test, data analysis tools were used to select four features out of the 30 available test...

  16. Finite connectivity attractor neural networks

    International Nuclear Information System (INIS)

    Wemmenhove, B; Coolen, A C C

    2003-01-01

    We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous

  17. Finite connectivity attractor neural networks

    Science.gov (United States)

    Wemmenhove, B.; Coolen, A. C. C.

    2003-09-01

    We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous.

  18. 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

  19. 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.

  20. Clustering: a neural network approach.

    Science.gov (United States)

    Du, K-L

    2010-01-01

    Clustering is a fundamental data analysis method. It is widely used for pattern recognition, feature extraction, vector quantization (VQ), image segmentation, function approximation, and data mining. As an unsupervised classification technique, clustering identifies some inherent structures present in a set of objects based on a similarity measure. Clustering methods can be based on statistical model identification (McLachlan & Basford, 1988) or competitive learning. In this paper, we give a comprehensive overview of competitive learning based clustering methods. Importance is attached to a number of competitive learning based clustering neural networks such as the self-organizing map (SOM), the learning vector quantization (LVQ), the neural gas, and the ART model, and clustering algorithms such as the C-means, mountain/subtractive clustering, and fuzzy C-means (FCM) algorithms. Associated topics such as the under-utilization problem, fuzzy clustering, robust clustering, clustering based on non-Euclidean distance measures, supervised clustering, hierarchical clustering as well as cluster validity are also described. Two examples are given to demonstrate the use of the clustering methods.

  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

    Directory of Open Access Journals (Sweden)

    Robert T Thibault

    2016-10-01

    Full Text Available 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. 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.

  4. Disruption prediction with adaptive neural networks for ASDEX Upgrade

    International Nuclear Information System (INIS)

    Cannas, B.; Fanni, A.; Pautasso, G.; Sias, G.

    2011-01-01

    In this paper, an adaptive neural system has been built to predict the risk of disruption at ASDEX Upgrade. The system contains a Self Organizing Map, which determines the 'novelty' of the input of a Multi Layer Perceptron predictor module. The answer of the MLP predictor will be inhibited whenever a novel sample is detected. Furthermore, it is possible that the predictor produces a wrong answer although it is fed with known samples. In this case, a retraining procedure will be performed to update the MLP predictor in an incremental fashion using data coming from both the novelty detection, and from wrong predictions. In particular, a new update is performed whenever a missed alarm is triggered by the predictor. The performance of the adaptive predictor during the more recent experimental campaigns until November 2009 has been evaluated.

  5. 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...

  6. 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....

  7. Vitamin E in neural and visual function.

    Science.gov (United States)

    Hayton, S M; Muller, D P R

    2004-12-01

    A rat model of vitamin E (alpha-tocopherol) deficiency with similar "clinical," electrophysiological, and neuropathological abnormalities to those seen in man was used to investigate the effects of various amounts and forms of alpha-tocopheryl acetate (alphaTA) on neural and visual function. Electrophysiological techniques provide an objective, non-invasive measure of neural and visual function. These techniques were used in the animal model to determine the minimum dietary requirement of vitamin E necessary to prevent neural and visual abnormalities. They were also used to compare the biological activities of the natural (RRR-) and synthetic (all-rac-) forms of alpha-tocopherol in neural tissues. The results were as follows: (1) Significant differences in neural and visual function were observed between deficient and control rats after approximately 8 months. (2) An intake of 1.0 mg/kg all-rac- or 0.75 mg/kg RRR-alphaTA was observed to marginally protect nerves from vitamin E deficiency. (3) The biological activity of all-rac-alpha-tocopherol in neural tissues was approximately 75% of RRR-alpha-tocopherol. (4) The concentration of free malondialdehyde (an indicator of lipid peroxidation) was significantly increased in tissues from the deficient compared to the control animals. These results are consistent with a deficiency of alpha-tocopherol causing increased lipid peroxidation leading to abnormal neural electrophysiology. They could also be explained by more specific but as yet undefined function(s) of alpha-tocopherol in neural tissues.

  8. Neural Networks in Nonlinear Aircraft Control

    Science.gov (United States)

    Linse, Dennis J.

    1990-01-01

    Recent research indicates that artificial neural networks offer interesting learning or adaptive capabilities. The current research focuses on the potential for application of neural networks in a nonlinear aircraft control law. The current work has been to determine which networks are suitable for such an application and how they will fit into a nonlinear control law.

  9. Neural Network Algorithm for Particle Loading

    International Nuclear Information System (INIS)

    Lewandowski, J.L.V.

    2003-01-01

    An artificial neural network algorithm for continuous minimization is developed and applied to the case of numerical particle loading. It is shown that higher-order moments of the probability distribution function can be efficiently renormalized using this technique. A general neural network for the renormalization of an arbitrary number of moments is given

  10. Neural Network to Solve Concave Games

    OpenAIRE

    Liu, Zixin; Wang, Nengfa

    2014-01-01

    The issue on neural network method to solve concave games is concerned. Combined with variational inequality, Ky Fan inequality, and projection equation, concave games are transformed into a neural network model. On the basis of the Lyapunov stable theory, some stability results are also given. Finally, two classic games’ simulation results are given to illustrate the theoretical results.

  11. A Fuzzy Neural Tree for Possibilistic Reliability

    NARCIS (Netherlands)

    Ciftcioglu, O.

    2008-01-01

    An innovative neural fuzzy system is considered for possibilistic reliability using a neural tree structure with nodes of neuronal type. The total tree structure works effectively as a fuzzy logic system where the possibility theory plays important role with Gaussian possibility distribution at the

  12. A high-speed analog neural processor

    NARCIS (Netherlands)

    Masa, P.; Masa, Peter; Hoen, Klaas; 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

  13. Neural network classification - A Bayesian interpretation

    Science.gov (United States)

    Wan, Eric A.

    1990-01-01

    The relationship between minimizing a mean squared error and finding the optimal Bayesian classifier is reviewed. This provides a theoretical interpretation for the process by which neural networks are used in classification. A number of confidence measures are proposed to evaluate the performance of the neural network classifier within a statistical framework.

  14. Neural Network Classifier Based on Growing Hyperspheres

    Czech Academy of Sciences Publication Activity Database

    Jiřina Jr., Marcel; Jiřina, Marcel

    2000-01-01

    Roč. 10, č. 3 (2000), s. 417-428 ISSN 1210-0552. [Neural Network World 2000. Prague, 09.07.2000-12.07.2000] Grant - others:MŠMT ČR(CZ) VS96047; MPO(CZ) RP-4210 Institutional research plan: AV0Z1030915 Keywords : neural network * classifier * hyperspheres * big -dimensional data Subject RIV: BA - General Mathematics

  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. Neurophysiology and neural engineering: a review.

    Science.gov (United States)

    Prochazka, Arthur

    2017-08-01

    Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight. Copyright © 2017 the American Physiological Society.

  17. 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.

  18. Windowed active sampling for reliable neural learning

    NARCIS (Netherlands)

    Barakova, E.I; Spaanenburg, L

    The composition of the example set has a major impact on the quality of neural learning. The popular approach is focused on extensive pre-processing to bridge the representation gap between process measurement and neural presentation. In contrast, windowed active sampling attempts to solve these

  19. Improved transformer protection using probabilistic neural network ...

    African Journals Online (AJOL)

    user

    secure and dependable protection for power transformers. Owing to its superior learning and generalization capabilities Artificial. Neural Network (ANN) can considerably enhance the scope of WI method. ANN approach is faster, robust and easier to implement than the conventional waveform approach. The use of neural ...

  20. Deciphering the Cognitive and Neural Mechanisms Underlying ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Deciphering the Cognitive and Neural Mechanisms Underlying Auditory Learning. This project seeks to understand the brain mechanisms necessary for people to learn to perceive sounds. Neural circuits and learning. The research team will test people with and without musical training to evaluate their capacity to learn ...

  1. Learning from large scale neural simulations

    DEFF Research Database (Denmark)

    Serban, Maria

    2017-01-01

    -possibly explanations of neural and cognitive phenomena, or they can be used to test explanatory hypotheses and identify sufficient causal factors in specific neurobiological mechanisms, or yet again they can be deployed exploratorily to evaluate the hierarchy of multiple neural and cognitive models that are put...

  2. Neural plasticity in pancreatitis and pancreatic cancer.

    Science.gov (United States)

    Demir, Ihsan Ekin; Friess, Helmut; Ceyhan, Güralp O

    2015-11-01

    Pancreatic nerves undergo prominent alterations during the evolution and progression of human chronic pancreatitis and pancreatic cancer. Intrapancreatic nerves increase in size (neural hypertrophy) and number (increased neural density). The proportion of autonomic and sensory fibres (neural remodelling) is switched, and are infiltrated by perineural inflammatory cells (pancreatic neuritis) or invaded by pancreatic cancer cells (neural invasion). These neuropathic alterations also correlate with neuropathic pain. Instead of being mere histopathological manifestations of disease progression, pancreatic neural plasticity synergizes with the enhanced excitability of sensory neurons, with Schwann cell recruitment toward cancer and with central nervous system alterations. These alterations maintain a bidirectional interaction between nerves and non-neural pancreatic cells, as demonstrated by tissue and neural damage inducing neuropathic pain, and activated neurons releasing mediators that modulate inflammation and cancer growth. Owing to the prognostic effects of pain and neural invasion in pancreatic cancer, dissecting the mechanism of pancreatic neuroplasticity holds major translational relevance. However, current in vivo models of pancreatic cancer and chronic pancreatitis contain many discrepancies from human disease that overshadow their translational value. The present Review discusses novel possibilities for mechanistically uncovering the role of the nervous system in pancreatic disease progression.

  3. Neural Plasticity in Speech Acquisition and Learning

    Science.gov (United States)

    Zhang, Yang; Wang, Yue

    2007-01-01

    Neural plasticity in speech acquisition and learning is concerned with the timeline trajectory and the mechanisms of experience-driven changes in the neural circuits that support or disrupt linguistic function. In this selective review, we discuss the role of phonetic learning in language acquisition, the "critical period" of learning, the agents…

  4. Neural plasticity: the biological substrate for neurorehabilitation.

    Science.gov (United States)

    Warraich, Zuha; Kleim, Jeffrey A

    2010-12-01

    Decades of basic science have clearly demonstrated the capacity of the central nervous system (CNS) to structurally and functionally adapt in response to experience. The field of neurorehabilitation has begun to use this body of work to develop neurobiologically informed therapies that harness the key behavioral and neural signals that drive neural plasticity. The present review describes how neural plasticity supports both learning in the intact CNS and functional improvement in the damaged or diseased CNS. A pragmatic, interdisciplinary definition of neural plasticity is presented that may be used by both clinical and basic scientists studying neurorehabilitation. Furthermore, a description of how neural plasticity may act to drive different neural strategies underlying functional improvement after CNS injury or disease is provided. The understanding of the relationship between these different neural strategies, mechanisms of neural plasticity, and changes in behavior may facilitate the development of novel, more effective rehabilitation interventions. Copyright © 2010 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

  5. Recognizing changing seasonal patterns using neural networks

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); G. Draisma (Gerrit)

    1997-01-01

    textabstractIn this paper we propose a graphical method based on an artificial neural network model to investigate how and when seasonal patterns in macroeconomic time series change over time. Neural networks are useful since the hidden layer units may become activated only in certain seasons or

  6. Neural constructivism or self-organization?

    NARCIS (Netherlands)

    van der Maas, H.L.J.; Molenaar, P.C.M.

    2000-01-01

    Comments on the article by S. R. Quartz et al (see record 1998-00749-001) which discussed the constructivist perspective of interaction between cognition and neural processes during development and consequences for theories of learning. Three arguments are given to show that neural constructivism

  7. A Survey of Neural Network Publications.

    Science.gov (United States)

    Vijayaraman, Bindiganavale S.; Osyk, Barbara

    This paper is a survey of publications on artificial neural networks published in business journals for the period ending July 1996. Its purpose is to identify and analyze trends in neural network research during that period. This paper shows which topics have been heavily researched, when these topics were researched, and how that research has…

  8. Some Examples of Identification with Neural Networks

    OpenAIRE

    Sjöberg, Jonas

    1994-01-01

    In this report some examples on system identification of non-linear systems with neural networks are presented. The systems being identified all have different kinds of non-linearities, more or less known. The examples in this paper show that these non-linearities can be successfully modeled by non-linear models based on neural networks.

  9. 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.

  10. A Chip for an Implantable Neural Stimulator

    DEFF Research Database (Denmark)

    Gudnason, Gunnar; Bruun, Erik; Haugland, Morten

    2000-01-01

    This paper describes a chip for a multichannel neural stimulator for functional electrical stimulation (FES). The purpose of FES is to restore muscular control in disabled patients. The chip performs all the signal processing required in an implanted neural stimulator. The power and digital data...

  11. [Penicillium-inhibiting yeasts].

    Science.gov (United States)

    Benítez Ahrendts, M R; Carrillo, L

    2004-01-01

    The objective of this work was to establish the in vitro and in vivo inhibition of post-harvest pathogenic moulds by yeasts in order to make a biocontrol product. Post-harvest pathogenic moulds Penicillium digitatum, P. italicum, P. ulaiense, Phyllosticta sp., Galactomyces geotrichum and yeasts belonging to genera Brettanomyces, Candida, Cryptococcus, Kloeckera, Pichia, Rhodotorula were isolated from citrus fruits. Some yeasts strains were also isolated from other sources. The yeasts were identified by their macro and micro-morphology and physiological tests. The in vitro and in vivo activities against P. digitatum or P. ulaiense were different. Candida cantarellii and one strain of Pichia subpelliculosa produced a significant reduction of the lesion area caused by the pathogenic moulds P. digitatum and P. ulaiense, and could be used in a biocontrol product formulation.

  12. Lying in the scanner: localized inhibition predicts lying skill.

    Science.gov (United States)

    Vartanian, Oshin; Kwantes, Peter; Mandel, David R

    2012-10-31

    Recent literature suggests that lying may be revealed by elevated cognitive effort. A functional magnetic resonance imaging experiment using a match-mismatch detection task was conducted that found support for this hypothesis in two ways. First, compared to truthful reporting, lying (i.e., responding that matches were mismatches or vice versa) triggered greater activation of the working memory network in the brain. This was especially true for lying about a match, where activation in the WM network was found to be greater than when lying about a mismatch. Lying also activated the right rostrolateral prefrontal cortex (BA 10)-a key cognitive control region that regulates the interplay between stimulus-oriented and internally-generated schemas. Second, activation in the right inferior frontal gyrus (BA 44) - a brain region underpinning inhibition - predicted lying skill. The findings show that the neural correlates of cognitive effort and control can be used to detect lying, and that a specific neural marker of inhibition can predict how well one lies. Crown Copyright © 2012. Published by Elsevier Ireland Ltd. All rights reserved.

  13. 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.

  14. 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.

  15. Proactive inhibition: An element of inhibitory control in eating disorders.

    Science.gov (United States)

    Bartholdy, Savani; Campbell, Iain C; Schmidt, Ulrike; O'Daly, Owen G

    2016-12-01

    The aetiology of eating disorders (EDs) is unclear, but many hypotheses implicate alterations in behavioural control. Specifically and because of its relevance to symptomatology, there has been much interest in inhibitory control, i.e., the ability to inhibit inappropriate/unwanted behaviours. This has been studied in relation to reactive motor inhibition (withholding a response in reaction to a signal), reward-based inhibition (e.g., temporal discounting paradigms) and to reversal learning (e.g., set shifting tasks assessing cognitive flexibility and compulsivity). However, there has been less explicit exploration of proactive inhibitory control, i.e., a preparatory form of inhibitory control where responses are pre-emptively suppressed to improve performance either in terms of a dynamic strategy (e.g., post-error slowing) or as a more general suppression in the context of uncertainty (e.g., when the appropriateness of a response is less certain). This review considers proactive inhibition within the context of broader conceptual considerations of inhibitory control in EDs, discusses the existing behavioural and neural evidence, and concludes that this is a construct worthy of further exploration. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. 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.

  17. 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.

  18. Neural evidence of motivational conflict between social values.

    Science.gov (United States)

    Leszkowicz, Emilia; Linden, David E J; Maio, Gregory R; Ihssen, Niklas

    2017-10-01

    Motivational interdependence is an organizing principle in Schwartz's circumplex model of social values, which has received abundant cross-cultural support. We used fMRI to test whether motivational relations between social values predict different brain responses in a situation of choice between values. We hypothesized that differences in brain responses would become evident when the more important value had to be selected in pairs of congruent (e.g., wealth and success) as opposed to incongruent (e.g., curiosity and stability) values as they are described in Schwartz's model, because the former serve mutually facilitating motives, whereas the latter serve mutually inhibiting motives. Consistent with the model, choosing between congruent values led to longer response times and more activation in conflict-related brain regions (e.g., the supplementary motor area, dorsolateral prefrontal cortex) than selecting between incongruent values. These results provide novel neural evidence supporting the circumplex model's predictions about motivational interdependence between social values. In particular, our results show that the neural networks underlying social values are organized in a way that allows activation patterns related to motivational similarity between congruent values to be dissociated from those related to incongruent values.

  19. 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.

  20. Flexible body control using neural networks

    Science.gov (United States)

    Mccullough, Claire L.

    1992-01-01

    Progress is reported on the control of Control Structures Interaction suitcase demonstrator (a flexible structure) using neural networks and fuzzy logic. It is concluded that while control by neural nets alone (i.e., allowing the net to design a controller with no human intervention) has yielded less than optimal results, the neural net trained to emulate the existing fuzzy logic controller does produce acceptible system responses for the initial conditions examined. Also, a neural net was found to be very successful in performing the emulation step necessary for the anticipatory fuzzy controller for the CSI suitcase demonstrator. The fuzzy neural hybrid, which exhibits good robustness and noise rejection properties, shows promise as a controller for practical flexible systems, and should be further evaluated.

  1. 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...

  2. 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...

  3. 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.

  4. Decentralized neural control application to robotics

    CERN Document Server

    Garcia-Hernandez, Ramon; Sanchez, Edgar N; Alanis, Alma y; Ruz-Hernandez, Jose A

    2017-01-01

    This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network. The third control scheme applies a decentralized neural i...

  5. 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...

  6. Neural correlates of phonetic convergence and speech imitation

    Directory of Open Access Journals (Sweden)

    Maeva eGarnier

    2013-09-01

    Full Text Available Speakers unconsciously tend to mimic their interlocutor’s speech during communicative interaction. This study aims at examining the neural correlates of phonetic convergence and deliberate imitation, in order to explore whether imitation of phonetic features, deliberate or unconscious, might reflect a sensory-motor recalibration process.Sixteen participants listened to vowels with pitch varying around the average pitch of their own voice, and then produced the identified vowels, while their speech was recorded and their brain activity was imaged using fMRI. Three degrees and types of imitation were compared (unconscious, deliberate and inhibited using a go-nogo paradigm, which enabled the comparison of brain activations during the whole imitation process, its active perception step, and its production. Speakers followed the pitch of voices they were exposed to, even unconsciously, without being instructed to do so. After being informed about this phenomenon, fourteen participants were able to inhibit it, at least partially. The results of whole brain and ROI analyses support the fact that both deliberate and unconscious imitations are based on similar neural mechanisms and networks, involving regions of the dorsal stream, during both perception and production steps of the imitation process. While no significant difference in brain activation was found between unconscious and deliberate imitations, the degree of imitation however appears to be determined by processes occurring during the perception step. Four regions of the dorsal stream: bilateral auditory cortex, bilateral supramarginal gyrus, and left Wernicke’s area, indeed showed an activity that correlated significantly with the degree of imitation during the perception step.

  7. Cortical Neural Activity Predicts Sensory Acuity Under Optogenetic Manipulation.

    Science.gov (United States)

    Briguglio, John J; Aizenberg, Mark; Balasubramanian, Vijay; Geffen, Maria N

    2018-02-21

    Excitatory and inhibitory neurons in the mammalian sensory cortex form interconnected circuits that control cortical stimulus selectivity and sensory acuity. Theoretical studies have predicted that suppression of inhibition in such excitatory-inhibitory networks can lead to either an increase or, paradoxically, a decrease in excitatory neuronal firing, with consequent effects on stimulus selectivity. We tested whether modulation of inhibition or excitation in the auditory cortex of male mice could evoke such a variety of effects in tone-evoked responses and in behavioral frequency discrimination acuity. We found that, indeed, the effects of optogenetic manipulation on stimulus selectivity and behavior varied in both magnitude and sign across subjects, possibly reflecting differences in circuitry or expression of optogenetic factors. Changes in neural population responses consistently predicted behavioral changes for individuals separately, including improvement and impairment in acuity. This correlation between cortical and behavioral change demonstrates that, despite the complex and varied effects that these manipulations can have on neuronal dynamics, the resulting changes in cortical activity account for accompanying changes in behavioral acuity. SIGNIFICANCE STATEMENT Excitatory and inhibitory interactions determine stimulus specificity and tuning in sensory cortex, thereby controlling perceptual discrimination acuity. Modeling has predicted that suppressing the activity of inhibitory neurons can lead to increased or, paradoxically, decreased excitatory activity depending on the architecture of the network. Here, we capitalized on differences between subjects to test whether suppressing/activating inhibition and excitation can in fact exhibit such paradoxical effects for both stimulus sensitivity and behavioral discriminability. Indeed, the same optogenetic manipulation in the auditory cortex of different mice could improve or impair frequency discrimination

  8. 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.

  9. Andrographolide Promotes Neural Differentiation of Rat Adipose Tissue-Derived Stromal Cells through Wnt/β-Catenin Signaling Pathway

    Directory of Open Access Journals (Sweden)

    Yan Liang

    2017-01-01

    Full Text Available Adipose tissue-derived stromal cells (ADSCs are a high-yield source of pluripotent stem cells for use in cell-based therapies. We explored the effect of andrographolide (ANDRO, one of the ingredients of the medicinal herb extract on the neural differentiation of rat ADSCs and associated molecular mechanisms. We observed that rat ADSCs were small and spindle-shaped and expressed multiple stem cell markers including nestin. They were multipotent as evidenced by adipogenic, osteogenic, chondrogenic, and neural differentiation under appropriate conditions. The proportion of cells exhibiting neural-like morphology was higher, and neurites developed faster in the ANDRO group than in the control group in the same neural differentiation medium. Expression levels of the neural lineage markers MAP2, tau, GFAP, and β-tubulin III were higher in the ANDRO group. ANDRO induced a concentration-dependent increase in Wnt/β-catenin signaling as evidenced by the enhanced expression of nuclear β-catenin and the inhibited form of GSK-3β (pSer9. Thus, this study shows for the first time how by enhancing the neural differentiation of ADSCs we expect that ANDRO pretreatment may increase the efficacy of adult stem cell transplantation in nervous system diseases, but more exploration is needed.

  10. Transmitters and pathways mediating inhibition of spinal itch-signaling neurons by scratching and other counterstimuli.

    Directory of Open Access Journals (Sweden)

    Tasuku Akiyama

    Full Text Available Scratching relieves itch, but the underlying neural mechanisms are poorly understood. We presently investigated a role for the inhibitory neurotransmitters GABA and glycine in scratch-evoked inhibition of spinal itch-signaling neurons in a mouse model of chronic dry skin itch. Superficial dorsal horn neurons ipsilateral to hindpaw dry skin treatment exhibited a high level of spontaneous firing that was significantly attenuated by cutaneous scratching, pinch and noxious heat. Scratch-evoked inhibition was nearly abolished by spinal delivery of the glycine antagonist, strychnine, and was markedly attenuated by respective GABA(A and GABA(B antagonists bicuculline and saclofen. Scratch-evoked inhibition was also significantly attenuated (but not abolished by interruption of the upper cervical spinal cord, indicating the involvement of both segmental and suprasegmental circuits that engage glycine- and GABA-mediated inhibition of spinal itch-signaling neurons by noxious counterstimuli.

  11. Modulation of recurrent inhibition from knee extensors to ankle motoneurones during human walking

    DEFF Research Database (Denmark)

    Lamy, Jean-Charles; Iglesias, Caroline; Lackmy, Alexandra

    2008-01-01

    The neural control for muscle coordination during human locomotion involves spinal and supraspinal networks, but little is known about the exact mechanisms implicated. The present study focused on modulation of heteronymous recurrent inhibition from knee extensors to ankle motoneurones at different...... times in the gait cycle, when quadriceps (Quad) muscle activity overlaps that in tibialis anterior (TA) and soleus (Sol). The effects of femoral nerve stimulation on ankle motoneurones were investigated during treadmill walking and during tonic co-contraction of Quad and TA/Sol while standing. Recurrent...... inhibition of TA motoneurones depended on the level of background EMG, and was similar during walking and standing for matched background EMG levels. On the other hand, recurrent inhibition in Sol was reduced in early stance, with respect to standing, and enhanced in late stance. Reduced inhibition in Sol...

  12. Asynchronous Cholinergic Drive Correlates with Excitation-Inhibition Imbalance via a Neuronal Ca2+ Sensor Protein

    Directory of Open Access Journals (Sweden)

    Keming Zhou

    2017-05-01

    Full Text Available Excitation-inhibition imbalance in neural networks is widely linked to neurological and neuropsychiatric disorders. However, how genetic factors alter neuronal activity, leading to excitation-inhibition imbalance, remains unclear. Here, using the C. elegans locomotor circuit, we examine how altering neuronal activity for varying time periods affects synaptic release pattern and animal behavior. We show that while short-duration activation of excitatory cholinergic neurons elicits a reversible enhancement of presynaptic strength, persistent activation results to asynchronous and reduced cholinergic drive, inducing imbalance between endogenous excitation and inhibition. We find that the neuronal calcium sensor protein NCS-2 is required for asynchronous cholinergic release in an activity-dependent manner and dampens excitability of inhibitory neurons non-cell autonomously. The function of NCS-2 requires its Ca2+ binding and membrane association domains. These results reveal a synaptic mechanism implicating asynchronous release in regulation of excitation-inhibition balance.

  13. Some neural effects of adenosin.

    Science.gov (United States)

    Haulică, I; Brănişteanu, D D; Petrescu, G H

    1978-01-01

    The possible neural effects of adenosine were investigated by using electrophysiological techniques at the level of some central and peripheral synapses. The evoked potentials in the somatosensorial cerebral cortex are influenced according to both the type of administration and the level of the electrical stimulation. While the local application does not induce significant alterations, the intrathalamic injections and the perfusion of the IIIrd cerebral ventricle do change the distribution of activated units at the level of different cortical layers especially during the peripheral stimulation. The frequency of spontaneous miniature discharges intracellularly recorded in the neuromuscular junction (mepp) is significantly depressed by adenosine. This effect is calcium- and dose-dependent. The end plate potentials (EPP) were also depressed. The statistical binomial analysis of the phenomenon indicated that adenosine induces a decrease if the presynaptic pool of the available transmitter. The data obtained demonstrate a presynaptic inhibitory action of adenosine beside its known vascular and metaholic effects.

  14. 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.

  15. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    concerning canonical, observable state space forms (minimum realizable form) for SISO as wll as MIMO processes. The tests show that all models, after succeeeful training, which is judged by correlation analysis of the prediction errors, are able to perform non-linear system identification, prediction......, simulation and filtering of dynamic, non-linear, multi-variable and noisy processes in a very satisfactory manner. The further examinations mainly concentrate on two models, the Non-linear ARMAX (NARMAX) model representing input/output description, and the Non-linear Innovation state Space (NISS) model (a...... Kalmann filter) representing state space description. The potentials of neural networks for control of non-linear processes are also examined, focusing on three different groups of control concepts, all considered as generalizations of known linear control concepts to handle also non-linear processes...

  16. 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...... meta-analysis of fifteen experiments using the activation likelihood estimation (ALE) method was conducted. As predicted, viewing paintings was correlated with activation in a distributed system including the occipital lobes, temporal lobe structures in the ventral stream involved in object (fusiform...... 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...

  17. The neural correlates of dreaming.

    Science.gov (United States)

    Siclari, Francesca; Baird, Benjamin; Perogamvros, Lampros; Bernardi, Giulio; LaRocque, Joshua J; Riedner, Brady; Boly, Melanie; Postle, Bradley R; Tononi, Giulio

    2017-06-01

    Consciousness never fades during waking. However, when awakened from sleep, we sometimes recall dreams and sometimes recall no experiences. Traditionally, dreaming has been identified with rapid eye-movement (REM) sleep, characterized by wake-like, globally 'activated', high-frequency electroencephalographic activity. However, dreaming also occurs in non-REM (NREM) sleep, characterized by prominent low-frequency activity. This challenges our understanding of the neural correlates of conscious experiences in sleep. Using high-density electroencephalography, we contrasted the presence and absence of dreaming in NREM and REM sleep. In both NREM and REM sleep, reports of dream experience were associated with local decreases in low-frequency activity in posterior cortical regions. High-frequency activity in these regions correlated with specific dream contents. Monitoring this posterior 'hot zone' in real time predicted whether an individual reported dreaming or the absence of dream experiences during NREM sleep, suggesting that it may constitute a core correlate of conscious experiences in sleep.

  18. Impaired response inhibition and excess cortical thickness as candidate endophenotypes for trichotillomania.

    Science.gov (United States)

    Odlaug, Brian L; Chamberlain, Samuel R; Derbyshire, Katie L; Leppink, Eric W; Grant, Jon E

    2014-12-01

    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 response inhibition, and structural magnetic resonance imaging scans. Group differences in SST performance and cortical thickness were explored using permutation testing. Groups differed significantly in response inhibition, with patients demonstrating impaired performance versus controls, and relatives occupying an intermediate position. Permutation cluster analysis revealed significant excesses of cortical thickness in patients and their relatives compared to controls, in right inferior/middle frontal gyri (Brodmann Area, BA 47 & 11), right lingual gyrus (BA 18), left superior temporal cortex (BA 21), and left precuneus (BA 7). No significant differences emerged between groups for striatum or cerebellar volumes. Impaired response inhibition and an excess of cortical thickness in neural regions germane to inhibitory control, and action monitoring, represent vulnerability markers for trichotillomania. Future work should explore genetic and environmental associations with these biological markers. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Feedforward inhibition and synaptic scaling--two sides of the same coin?

    Directory of Open Access Journals (Sweden)

    Christian Keck

    Full Text Available Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

  20. 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. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  1. Forming competing fear learning and extinction memories in adolescence makes fear difficult to inhibit

    OpenAIRE

    Baker, Kathryn D.; Richardson, Rick

    2015-01-01

    Fear inhibition is markedly impaired in adolescent rodents and humans. The present experiments investigated whether this impairment is critically determined by the animal's age at the time of fear learning or their age at fear extinction. Male rats (n = 170) were tested for extinction retention after conditioning and extinction at different ages. We examined neural correlates of impaired extinction retention by detection of phosphorylated mitogen-activated protein kinase immunoreactivity (pMA...

  2. Nonequilibrium landscape theory of neural networks

    Science.gov (United States)

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

    2013-01-01

    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. PMID:24145451

  3. Application of neural network to CT

    International Nuclear Information System (INIS)

    Ma, Xiao-Feng; Takeda, Tatsuoki

    1999-01-01

    This paper presents a new method for two-dimensional image reconstruction by using a multilayer neural network. Multilayer neural networks are extensively investigated and practically applied to solution of various problems such as inverse problems or time series prediction problems. From learning an input-output mapping from a set of examples, neural networks can be regarded as synthesizing an approximation of multidimensional function (that is, solving the problem of hypersurface reconstruction, including smoothing and interpolation). From this viewpoint, neural networks are well suited to the solution of CT image reconstruction. Though a conventionally used object function of a neural network is composed of a sum of squared errors of the output data, we can define an object function composed of a sum of residue of an integral equation. By employing an appropriate line integral for this integral equation, we can construct a neural network that can be used for CT. We applied this method to some model problems and obtained satisfactory results. As it is not necessary to discretized the integral equation using this reconstruction method, therefore it is application to the problem of complicated geometrical shapes is also feasible. Moreover, in neural networks, interpolation is performed quite smoothly, as a result, inverse mapping can be achieved smoothly even in case of including experimental and numerical errors, However, use of conventional back propagation technique for optimization leads to an expensive computation cost. To overcome this drawback, 2nd order optimization methods or parallel computing will be applied in future. (J.P.N.)

  4. Flight control with adaptive critic neural network

    Science.gov (United States)

    Han, Dongchen

    2001-10-01

    In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.

  5. Neural dynamics underlying emotional transmissions between individuals.

    Science.gov (United States)

    Golland, Yulia; Levit-Binnun, Nava; Hendler, Talma; Lerner, Yulia

    2017-08-01

    Emotional experiences are frequently shaped by the emotional responses of co-present others. Research has shown that people constantly monitor and adapt to the incoming social-emotional signals, even without face-to-face interaction. And yet, the neural processes underlying such emotional transmissions have not been directly studied. Here, we investigated how the human brain processes emotional cues which arrive from another, co-attending individual. We presented continuous emotional feedback to participants who viewed a movie in the scanner. Participants in the social group (but not in the control group) believed that the feedback was coming from another person who was co-viewing the same movie. We found that social-emotional feedback significantly affected the neural dynamics both in the core affect and in the medial pre-frontal regions. Specifically, the response time-courses in those regions exhibited increased similarity across recipients and increased neural alignment with the timeline of the feedback in the social compared with control group. Taken in conjunction with previous research, this study suggests that emotional cues from others shape the neural dynamics across the whole neural continuum of emotional processing in the brain. Moreover, it demonstrates that interpersonal neural alignment can serve as a neural mechanism through which affective information is conveyed between individuals. © The Author (2017). Published by Oxford University Press.

  6. 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....

  7. Genetic algorithm for neural networks optimization

    Science.gov (United States)

    Setyawati, Bina R.; Creese, Robert C.; Sahirman, Sidharta

    2004-11-01

    This paper examines the forecasting performance of multi-layer feed forward neural networks in modeling a particular foreign exchange rates, i.e. Japanese Yen/US Dollar. The effects of two learning methods, Back Propagation and Genetic Algorithm, in which the neural network topology and other parameters fixed, were investigated. The early results indicate that the application of this hybrid system seems to be well suited for the forecasting of foreign exchange rates. The Neural Networks and Genetic Algorithm were programmed using MATLAB«.

  8. Byte-based neural machine translation

    OpenAIRE

    Ruiz Costa-Jussà, Marta; Escolano Peinado, Carlos; Rodríguez Fonollosa, José Adrián

    2017-01-01

    This paper presents experiments compar- ing character-based and byte-based neural machine translation systems. The main motivation of the byte-based neural ma- chine translation system is to build multi- lingual neural machine translation systems that can share the same vocabulary. We compare the performance of both systems in several language pairs and we see that the performance in test is similar for most language pairs while the training time is slightly reduced in the case of byte-based ...

  9. Applications of neural network to numerical analyses

    International Nuclear Information System (INIS)

    Takeda, Tatsuoki; Fukuhara, Makoto; Ma, Xiao-Feng; Liaqat, Ali

    1999-01-01

    Applications of a multi-layer neural network to numerical analyses are described. We are mainly concerned with the computed tomography and the solution of differential equations. In both cases as the objective functions for the training process of the neural network we employed residuals of the integral equation or the differential equations. This is different from the conventional neural network training where sum of the squared errors of the output values is adopted as the objective function. For model problems both the methods gave satisfactory results and the methods are considered promising for some kind of problems. (author)

  10. Application of neural networks in coastal engineering

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.

    /plain; charset=UTF-8 ~lffE~fSTE?rS'ponsoredShort-Term Training Programme on EtiStal Erosion Areas (CEA) - Protection & Management ~_.Jai_ .........~••_ •. 06 - 18, January, 2003 II LECTURE VOLUME II Dr. A. Vittal Hegde Co-ordinator Dr. Subba Rao Co...Clion & Management " 6-18, Jal1uory 2003 at NlTK. Suralhkal 227 NEURAL·NETWORK The word 'Neural Network' is used to normally describe the "Artificial Neural Network"(ANN). Biological neural networks are much more complicated in their elementary structures than...

  11. Neural retinal regeneration with pluripotent stem cells.

    Science.gov (United States)

    Ramsden, Conor M; Powner, Michael B; Carr, Amanda-Jayne F; Smart, Matthew J K; da Cruz, Lyndon; Coffey, Peter J

    2014-01-01

    Retinal degeneration represents a huge burden of blinding disease, and currently there are no effective treatments that reverse the most common causes of neural retinal degeneration. Stem cell biology has the potential to significantly ease this burden, not only through the development of disease models of retinal degeneration but also in the manufacture of a replacement for the neural retinal tissue. This review summarizes the major advancements in the last decade in the field of neural retinal regeneration with an emphasis on the differentiation of embryonic and induced pluripotent stem cells into cells with retinal and specifically photoreceptor characteristics. © 2014 S. Karger AG, Basel.

  12. Decision boundary feature extraction for neural networks

    Science.gov (United States)

    Lee, Chulhee; Landgrebe, David A.

    1992-01-01

    We propose a new feature extraction method for neural networks. The method is based on the recently published decision boundary feature extraction algorithm. It has been shown that all the necessary features for classification can be extracted from the decision boundary. To apply the decision boundary feature extraction method, we first define the decision boundary in neural networks. Next, we propose a procedure for extracting all the necessary features for classification from the decision boundary. The proposed algorithm preserves the characteristics of neural networks, which can define arbitrary decision boundary. Experiments show promising results.

  13. 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.

  14. Neural correlates of deception in social contexts in normally developing children

    Directory of Open Access Journals (Sweden)

    Susumu eYokota

    2013-05-01

    Full Text Available Deception is related to the ability to inhibit prepotent responses and to engage in mental tasks such as anticipating responses and inferring what another person knows, especially in social contexts. However, the neural correlates of deception processing, which requires mentalizing, remain unclear. Using functional magnetic resonance imaging (fMRI, we examined the neural correlates of deception, including mentalization, in social contexts in normally developing children. Healthy right-handed children (aged 8–9 years were scanned while performing interactive games involving deception. The games varied along two dimensions: the type of reply (deception and truth and the type of context (social and less social. Participants were instructed to deceive a witch and to tell the truth to a girl. Under the social-context conditions, participants were asked to consider what they inferred about protagonists’ preferences from their facial expressions when responding to questions. Under the less-social-context conditions, participants did not need to consider others’ preferences. We found a significantly greater response in the right precuneus under the social-context than under less-social-context conditions. Additionally, we found substantially greater activation in the right inferior parietal lobule (IPL under the deception than under the truth condition. These results suggest that deception in a social context requires not only inhibition of prepotent responses but also engagement in mentalizing processes. This study provides the first evidence of the neural correlates of the mentalizing processes involved in deception in normally developing children.

  15. Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making.

    Science.gov (United States)

    Huk, Alexander C; Meister, Miriam L R

    2012-01-01

    A recent line of work has found remarkable success in relating perceptual decision-making and the spiking activity in the macaque lateral intraparietal area (LIP). In this review, we focus on questions about the neural computations in LIP that are not answered by demonstrations of neural correlates of psychological processes. We highlight three areas of limitations in our current understanding of the precise neural computations that might underlie neural correlates of decisions: (1) empirical questions not yet answered by existing data; (2) implementation issues related to how neural circuits could actually implement the mechanisms suggested by both extracellular neurophysiology and psychophysics; and (3) ecological constraints related to the use of well-controlled laboratory tasks and whether they provide an accurate window on sensorimotor computation. These issues motivate the adoption of a more general "encoding-decoding framework" that will be fruitful for more detailed contemplation of how neural computations in LIP relate to the formation of perceptual decisions.

  16. 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. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. A Neural Circuit for Auditory Dominance over Visual Perception.

    Science.gov (United States)

    Song, You-Hyang; Kim, Jae-Hyun; Jeong, Hye-Won; Choi, Ilsong; Jeong, Daun; Kim, Kwansoo; Lee, Seung-Hee

    2017-02-22

    When conflicts occur during integration of visual and auditory information, one modality often dominates the other, but the underlying neural circuit mechanism remains unclear. Using auditory-visual discrimination tasks for head-fixed mice, we found that audition dominates vision in a process mediated by interaction between inputs from the primary visual (VC) and auditory (AC) cortices in the posterior parietal cortex (PTLp). Co-activation of the VC and AC suppresses VC-induced PTLp responses, leaving AC-induced responses. Furthermore, parvalbumin-positive (PV+) interneurons in the PTLp mainly receive AC inputs, and muscimol inactivation of the PTLp or optogenetic inhibition of its PV+ neurons abolishes auditory dominance in the resolution of cross-modal sensory conflicts without affecting either sensory perception. Conversely, optogenetic activation of PV+ neurons in the PTLp enhances the auditory dominance. Thus, our results demonstrate that AC input-specific feedforward inhibition of VC inputs in the PTLp is responsible for the auditory dominance during cross-modal integration. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Model study of combined electrical and near-infrared neural stimulation on the bullfrog sciatic nerve.

    Science.gov (United States)

    You, Mengxian; Mou, Zongxia

    2017-07-01

    This paper implemented a model study of combined electrical and near-infrared (808 nm) neural stimulation (NINS) on the bullfrog sciatic nerve. The model includes a COMSOL model to calculate the electric-field distribution of the surrounding area of the nerve, a Monte Carlo model to simulate light transport and absorption in the bullfrog sciatic nerve during NINS, and a NEURON model to simulate the neural electrophysiology changes under electrical stimulus and laser irradiation. The optical thermal effect is considered the main mechanism during NINS. Therefore, thermal change during laser irradiation was calculated by the Monte Carlo method, and the temperature distribution was then transferred to the NEURON model to stimulate the sciatic nerve. The effects on thermal response by adjusting the laser spot size, energy of the beam, and the absorption coefficient of the nerve are analyzed. The effect of the ambient temperature on the electrical stimulation or laser stimulation and the interaction between laser irradiation and electrical stimulation are also studied. The results indicate that the needed stimulus threshold for neural activation or inhibition is reduced by laser irradiation. Additionally, the needed laser energy for blocking the action potential is reduced by electrical stimulus. Both electrical and laser stimulation are affected by the ambient temperature. These results provide references for subsequent animal experiments and could be of great help to future basic and applied studies of infrared neural stimulation (INS).

  19. Amigo adhesion protein regulates development of neural circuits in zebrafish brain.

    Science.gov (United States)

    Zhao, Xiang; Kuja-Panula, Juha; Sundvik, Maria; Chen, Yu-Chia; Aho, Vilma; Peltola, Marjaana A; Porkka-Heiskanen, Tarja; Panula, Pertti; Rauvala, Heikki

    2014-07-18

    The Amigo protein family consists of three transmembrane proteins characterized by six leucine-rich repeat domains and one immunoglobulin-like domain in their extracellular moieties. Previous in vitro studies have suggested a role as homophilic adhesion molecules in brain neurons, but the in vivo functions remain unknown. Here we have cloned all three zebrafish amigos and show that amigo1 is the predominant family member expressed during nervous system development in zebrafish. Knockdown of amigo1 expression using morpholino oligonucleotides impairs the formation of fasciculated tracts in early fiber scaffolds of brain. A similar defect in fiber tract development is caused by mRNA-mediated expression of the Amigo1 ectodomain that inhibits adhesion mediated by the full-length protein. Analysis of differentiated neural circuits reveals defects in the catecholaminergic system. At the behavioral level, the disturbed formation of neural circuitry is reflected in enhanced locomotor activity and in the inability of the larvae to perform normal escape responses. We suggest that Amigo1 is essential for the development of neural circuits of zebrafish, where its mechanism involves homophilic interactions within the developing fiber tracts and regulation of the Kv2.1 potassium channel to form functional neural circuitry that controls locomotion. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

  20. Convergence of inhibitory neural inputs regulate motor activity in the murine and monkey stomach.

    Science.gov (United States)

    Shaylor, Lara A; Hwang, Sung Jin; Sanders, Kenton M; Ward, Sean M

    2016-11-01

    Inhibitory motor neurons regulate several gastric motility patterns including receptive relaxation, gastric peristaltic motor patterns, and pyloric sphincter opening. Nitric oxide (NO) and purines have been identified as likely candidates that mediate inhibitory neural responses. However, the contribution from each neurotransmitter has received little attention in the distal stomach. The aims of this study were to identify the roles played by NO and purines in inhibitory motor responses in the antrums of mice and monkeys. By using wild-type mice and mutants with genetically deleted neural nitric oxide synthase (Nos1 -/- ) and P2Y1 receptors (P2ry1 -/- ) we examined the roles of NO and purines in postjunctional inhibitory responses in the distal stomach and compared these responses to those in primate stomach. Activation of inhibitory motor nerves using electrical field stimulation (EFS) produced frequency-dependent inhibitory junction potentials (IJPs) that produced muscle relaxations in both species. Stimulation of inhibitory nerves during slow waves terminated pacemaker events and associated contractions. In Nos1 -/- mice IJPs and relaxations persisted whereas in P2ry1 -/- mice IJPs were absent but relaxations persisted. In the gastric antrum of the non-human primate model Macaca fascicularis, similar NO and purine neural components contributed to inhibition of gastric motor activity. These data support a role of convergent inhibitory neural responses in the regulation of gastric motor activity across diverse species. Copyright © 2016 the American Physiological Society.

  1. All competition is not alike: Neural mechanisms for resolving underdetermined and prepotent competition

    Science.gov (United States)

    Snyder, Hannah R.; Banich, Marie T.; Munakata, Yuko

    2014-01-01

    People must constantly select among potential thoughts and actions in the face of competition from (a) multiple task-relevant options (underdetermined competition) and (b) strongly dominant options that are not appropriate in the current context (prepotent competition). These types of competition are ubiquitous during language production. In this work, we investigate the neural mechanisms that allow individuals to effectively manage these cognitive control demands and to quickly choose words with few errors. Using fMRI, we directly contrast underdetermined and prepotent competition within the same task (verb generation) for the first time, allowing localization of the neural substrates supporting the resolution of these two types of competition. Using a neural network model, we investigate the possible mechanisms by which these brain regions support selection. Together, our findings demonstrate that all competition is not alike: resolving prepotent competition and resolving underdetermined competition rely on partly dissociable neural substrates and mechanisms. Specifically, activation of left ventrolateral prefrontal cortex is specific to resolving underdetermined competition between multiple appropriate responses, most likely via competitive lateral inhibition. In contrast, activation of left dorsolateral prefrontal cortex is sensitive to both underdetermined competition and prepotent competition from response options that are inappropriate in the current context. This region likely provides top-down support for task-relevant responses, which enables them to out-compete prepotent responses in the selection process that occurs in left ventrolateral prefrontal cortex. PMID:24742155

  2. Neural underpinnings of divergent production of rules in numerical analogical reasoning.

    Science.gov (United States)

    Wu, Xiaofei; Jung, Rex E; Zhang, Hao

    2016-05-01

    Creativity plays an important role in numerical problem solving. Although the neural underpinnings of creativity have been studied over decades, very little is known about neural mechanisms of the creative process that relates to numerical problem solving. In the present study, we employed a numerical analogical reasoning task with functional Magnetic Resonance Imaging (fMRI) to investigate the neural correlates of divergent production of rules in numerical analogical reasoning. Participants performed two tasks: a multiple solution analogical reasoning task and a single solution analogical reasoning task. Results revealed that divergent production of rules involves significant activations at Brodmann area (BA) 10 in the right middle frontal cortex, BA 40 in the left inferior parietal lobule, and BA 8 in the superior frontal cortex. The results suggest that right BA 10 and left BA 40 are involved in the generation of novel rules, and BA 8 is associated with the inhibition of initial rules in numerical analogical reasoning. The findings shed light on the neural mechanisms of creativity in numerical processing. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Effects of Acute Alcohol Intoxication on Empathic Neural Responses for Pain

    Directory of Open Access Journals (Sweden)

    Yang Hu

    2018-01-01

    Full Text Available The questions whether and how empathy for pain can be modulated by acute alcohol intoxication in the non-dependent population remain unanswered. To address these questions, a double-blind, placebo-controlled, within-subject study design was adopted in this study, in which healthy social drinkers were asked to complete a pain-judgment task using pictures depicting others' body parts in painful or non-painful situations during fMRI scanning, either under the influence of alcohol intoxication or placebo conditions. Empathic neural activity for pain was reduced by alcohol intoxication only in the dorsal anterior cingulate cortex (dACC. More interestingly, we observed that empathic neural activity for pain in the right anterior insula (rAI was significantly correlated with trait empathy only after alcohol intoxication, along with impaired functional connectivity between the rAI and the fronto-parietal attention network. Our results reveal that alcohol intoxication not only inhibits empathic neural responses for pain but also leads to trait empathy inflation, possibly via impaired top-down attentional control. These findings help to explain the neural mechanism underlying alcohol-related social problems.

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

    International Nuclear Information System (INIS)

    Sun, Jinqiao; Sha, Bin; Zhou, Wenhao; Yang, Yi

    2010-01-01

    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.

  5. Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

    Directory of Open Access Journals (Sweden)

    Chernoded Andrey

    2017-01-01

    Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

  6. Recurrent Neural Network Identification and Adaptive Neural Control of Hydrocarbon Biodegradation Processes

    OpenAIRE

    Baruch, Ieroham; Mariaca-Gaspar, Carlos; Barrera-Cortes, Josefina

    2008-01-01

    The chapter proposes a new Kalman filter closed loop topology of recurrent neural network for identification and modeling of an unknown hydrocarbon degradation process carried out in a biopile system and a rotating drum. The proposed KF RNN contained a recurrent neural plant model, a recurrent neural output plant filter and posses global and local feedbacks. The learning algorithm is a modified version of the dynamic Backpropagation one derived using the adjoint KF RNN topology by means of th...

  7. The neural cell adhesion molecule L1 is distinct from the N-CAM related group of surface antigens BSP-2 and D2

    DEFF Research Database (Denmark)

    Faissner, A; Kruse, J; Goridis, C

    1984-01-01

    The neural cell adhesion molecule L1 and the group of N-CAM related molecules, BSP-2 and D2 antigen, are immunochemically distinct molecular species. The two groups of surface molecules are also functionally distinct entities, since inhibition of Ca2+-independent adhesion among early post-natal m...

  8. 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

    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....... 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....

  9. Neural Architecture of Selective Stopping Strategies: Distinct Brain Activity Patterns Are Associated with Attentional Capture But Not with Outright Stopping.

    Science.gov (United States)

    Sebastian, Alexandra; Rössler, Kora; Wibral, Michael; Mobascher, Arian; Lieb, Klaus; Jung, Patrick; Tüscher, Oliver

    2017-10-04

    In stimulus-selective stop-signal tasks, the salient stop signal needs attentional processing before genuine response inhibition is completed. Differential prefrontal involvement in attentional capture and response inhibition has been linked to the right inferior frontal junction (IFJ) and ventrolateral prefrontal cortex (VLPFC), respectively. Recently, it has been suggested that stimulus-selective stopping may be accomplished by the following different strategies: individuals may selectively inhibit their response only upon detecting a stop signal (independent discriminate then stop strategy) or unselectively whenever detecting a stop or attentional capture signal (stop then discriminate strategy). Alternatively, the discrimination process of the critical signal (stop vs attentional capture signal) may interact with the go process (dependent discriminate then stop strategy). Those different strategies might differentially involve attention- and stopping-related processes that might be implemented by divergent neural networks. This should lead to divergent activation patterns and, if disregarded, interfere with analyses in neuroimaging studies. To clarify this crucial issue, we studied 87 human participants of both sexes during a stimulus-selective stop-signal task and performed strategy-dependent functional magnetic resonance imaging analyses. We found that, regardless of the strategy applied, outright stopping displayed indistinguishable brain activation patterns. However, during attentional capture different strategies resulted in divergent neural activation patterns with variable activation of right IFJ and bilateral VLPFC. In conclusion, the neural network involved in outright stopping is ubiquitous and independent of strategy, while different strategies impact on attention-related processes and underlying neural network usage. Strategic differences should therefore be taken into account particularly when studying attention-related processes in stimulus

  10. Artificial neural networks a practical course

    CERN Document Server

    da Silva, Ivan Nunes; Andrade Flauzino, Rogerio; Liboni, Luisa Helena Bartocci; dos Reis Alves, Silas Franco

    2017-01-01

    This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.

  11. 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).

  12. 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.

  13. 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

  14. Memory pattern analysis of cellular neural networks

    International Nuclear Information System (INIS)

    Zeng Zhigang; Huang Deshuang; Wang Zengfu

    2005-01-01

    In this Letter, we have shown that the n-dimensional cellular neural network and delay cellular neural network can have not more than 3 n memory patterns, can have 2 n memory patterns which are locally exponentially stable. And we have obtained the estimates of attractive domain of such 2 n locally exponentially stable memory patterns. In addition, we have derived the conditions that the equilibrium point is locally exponentially stable when the equilibrium point locate the designated position. Some sufficient conditions have been obtained to guarantee the global exponential stability for the cellular neural networks. Those conditions can be directly derived from the parameters of the neural networks, are very easy to verified. The results presented in this Letter are the improvement and extension of the existed ones. Finally, the validity and performance of the results are illustrated by two simulation results

  15. Control Augmentation Using Adaptive Fuzzy Neural Networks

    Science.gov (United States)

    Kato, Akio; Wada, Yoshihisa

    Control to improve control characteristics of aircraft, CA (Control Augmentation), is used to realize the desirable motion of aircraft corresponding to pilot's control action. When the control laws using fuzzy inference were designed, trial and error was repeated for optimization of the parameter. Here, in designing control laws using fuzzy neural networks, the systematic optimization of the parameter was possible using the learning algorithm usually used in neural networks, by expressing the fuzzy inference in the form of neural networks. Here, the control laws, which learned the characteristics of the aircraft for one flight condition only, were used in all flight conditions without changing any parameter. Evaluation of the designed control laws showed good performance in all flight conditions. This proves that fuzzy neural networks are an effective and flexible method when applied to control laws for control augmentation of aircraft.

  16. Visualizing Neural Machine Translation Attention and Confidence

    Directory of Open Access Journals (Sweden)

    Rikters Matīss

    2017-10-01

    Full Text Available In this article, we describe a tool for visualizing the output and attention weights of neural machine translation systems and for estimating confidence about the output based on the attention.

  17. Imbibition well stimulation via neural network design

    Science.gov (United States)

    Weiss, William

    2007-08-14

    A method for stimulation of hydrocarbon production via imbibition by utilization of surfactants. The method includes use of fuzzy logic and neural network architecture constructs to determine surfactant use.

  18. Neural Networks in Mobile Robot Motion

    Directory of Open Access Journals (Sweden)

    Danica Janglová

    2004-03-01

    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.

  19. Stable Neural Control of Uncertain Multivariable Systems

    National Research Council Canada - National Science Library

    Mears, Mark

    2001-01-01

    ... that the trajectories remain bonded. Lyapunov analysis is used to derive equations for the sliding mode control, neural network training, and to show uniform ultimate boundedness of the closed loop systems...

  20. Local Dynamics in Trained Recurrent Neural Networks

    Science.gov (United States)

    Rivkind, Alexander; Barak, Omri

    2017-06-01

    Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.

  1. NEURAL NETWORKS FOR STOCK MARKET OPTION PRICING

    Directory of Open Access Journals (Sweden)

    Sergey A. Sannikov

    2017-03-01

    Full Text Available Introduction: The use of neural networks for non-linear models helps to understand where linear model drawbacks, coused by their specification, reveal themselves. This paper attempts to find this out. The objective of research is to determine the meaning of “option prices calculation using neural networks”. Materials and Methods: We use two kinds of variables: endogenous (variables included in the model of neural network and variables affecting on the model (permanent disturbance. Results: All data are divided into 3 sets: learning, affirming and testing. All selected variables are normalised from 0 to 1. Extreme values of income were shortcut. Discussion and Conclusions: Using the 33-14-1 neural network with direct links we obtained two sets of forecasts. Optimal criteria of strategies in stock markets’ option pricing were developed.

  2. Neural plasticity after spinal cord injury.

    Science.gov (United States)

    Liu, Jian; Yang, Xiaoyu; Jiang, Lianying; Wang, Chunxin; Yang, Maoguang

    2012-02-15

    Plasticity changes of uninjured nerves can result in a novel neural circuit after spinal cord injury, which can restore sensory and motor functions to different degrees. Although processes of neural plasticity have been studied, the mechanism and treatment to effectively improve neural plasticity changes remain controversial. The present study reviewed studies regarding plasticity of the central nervous system and methods for promoting plasticity to improve repair of injured central nerves. The results showed that synaptic reorganization, axonal sprouting, and neurogenesis are critical factors for neural circuit reconstruction. Directed functional exercise, neurotrophic factor and transplantation of nerve-derived and non-nerve-derived tissues and cells can effectively ameliorate functional disturbances caused by spinal cord injury and improve quality of life for patients.

  3. Local Dynamics in Trained Recurrent Neural Networks.

    Science.gov (United States)

    Rivkind, Alexander; Barak, Omri

    2017-06-23

    Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.

  4. Machine Learning Topological Invariants with Neural Networks

    Science.gov (United States)

    Zhang, Pengfei; Shen, Huitao; Zhai, Hui

    2018-02-01

    In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.

  5. Using Neural Networks in Diagnosing Breast Cancer

    National Research Council Canada - National Science Library

    Fogel, David

    1997-01-01

    .... In the current study, evolutionary programming is used to train neural networks and linear discriminant models to detect breast cancer in suspicious and microcalcifications using radiographic features and patient age...

  6. Control of autonomous robot using neural networks

    Science.gov (United States)

    Barton, Adam; Volna, Eva

    2017-07-01

    The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.

  7. PREDIKSI FOREX MENGGUNAKAN MODEL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. Hadapiningradja Kusumodestoni

    2015-11-01

    Full Text Available ABSTRAK Prediksi adalah salah satu teknik yang paling penting dalam menjalankan bisnis forex. Keputusan dalam memprediksi adalah sangatlah penting, karena dengan prediksi dapat membantu mengetahui nilai forex di waktu tertentu kedepan sehingga dapat mengurangi resiko kerugian. Tujuan dari penelitian ini dimaksudkan memprediksi bisnis fores menggunakan model neural network dengan data time series per 1 menit untuk mengetahui nilai akurasi prediksi sehingga dapat mengurangi resiko dalam menjalankan bisnis forex. Metode penelitian pada penelitian ini meliputi metode pengumpulan data kemudian dilanjutkan ke metode training, learning, testing menggunakan neural network. Setelah di evaluasi hasil penelitian ini menunjukan bahwa penerapan algoritma Neural Network mampu untuk memprediksi forex dengan tingkat akurasi prediksi 0.431 +/- 0.096 sehingga dengan prediksi ini dapat membantu mengurangi resiko dalam menjalankan bisnis forex. Kata kunci: prediksi, forex, neural network.

  8. Isolated Speech Recognition Using Artificial Neural Networks

    National Research Council Canada - National Science Library

    Polur, Prasad

    2001-01-01

    .... A small size vocabulary containing the words YES and NO is chosen. Spectral features using cepstral analysis are extracted per frame and imported to a feedforward neural network which uses a backpropagation with momentum training algorithm...

  9. Neural Correlates of Craving in Methamphetamine Abuse

    Directory of Open Access Journals (Sweden)

    Fanak Shahmohammadi

    2016-07-01

    Conclusion: This study presented a novel and noninvasive method based on neural correlates to discriminate healthy individuals from methamphetamine drug abusers. This method can be employed in treatment and monitoring of the methamphetamine abuse.

  10. 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.

  11. Hardware Acceleration of Adaptive Neural Algorithms.

    Energy Technology Data Exchange (ETDEWEB)

    James, Conrad D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-11-01

    As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - world conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.

  12. Neural Elements for Predictive Coding

    Directory of Open Access Journals (Sweden)

    Stewart SHIPP

    2016-11-01

    Full Text Available Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backwards in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many ‘illusory’ instances of perception where what is seen (heard, etc is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forwards and backwards pathways should be completely separate, given their functional distinction; this aspect of circuitry – that neurons with extrinsically bifurcating axons do not project in both directions – has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy formulation of predictive coding is combined with the classic ‘canonical microcircuit’ and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a updates in the microcircuitry of primate visual cortex, and (b rapid technical advances made

  13. Neural Elements for Predictive Coding.

    Science.gov (United States)

    Shipp, Stewart

    2016-01-01

    Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backward in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many 'illusory' instances of perception where what is seen (heard, etc.) is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forward and backward pathways should be completely separate, given their functional distinction; this aspect of circuitry - that neurons with extrinsically bifurcating axons do not project in both directions - has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy) formulation of predictive coding is combined with the classic 'canonical microcircuit' and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a) updates in the microcircuitry of primate visual cortex, and (b) rapid technical advances made possible by transgenic neural

  14. Neural networks and orbit control in accelerators

    International Nuclear Information System (INIS)

    Bozoki, E.; Friedman, A.

    1994-01-01

    An overview of the architecture, workings and training of Neural Networks is given. We stress the aspects which are important for the use of Neural Networks for orbit control in accelerators and storage rings, especially its ability to cope with the nonlinear behavior of the orbit response to 'kicks' and the slow drift in the orbit response during long-term operation. Results obtained for the two NSLS storage rings with several network architectures and various training methods for each architecture are given

  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. Chronux: A Platform for Analyzing Neural Signals

    OpenAIRE

    Bokil, Hemant; Andrews, Peter; Kulkarni, Jayant E.; Mehta, Samar; Mitra, Partha

    2010-01-01

    Chronux is an open-source software package developed for the analysis of neural data. The current version of Chronux includes software for signal processing of neural time-series data including several specialized mini-packages for spike sorting, local regression, audio segmentation, and other data-analysis tasks typically encountered by a neuroscientist. Chronux is freely available along with user tutorials, sample data, and extensive documentation from http://chronux.org/.

  17. Chronux: a platform for analyzing neural signals.

    Science.gov (United States)

    Bokil, Hemant; Andrews, Peter; Kulkarni, Jayant E; Mehta, Samar; Mitra, Partha P

    2010-09-30

    Chronux is an open-source software package developed for the analysis of neural data. The current version of Chronux includes software for signal processing of neural time-series data including several specialized mini-packages for spike-sorting, local regression, audio segmentation, and other data-analysis tasks typically encountered by a neuroscientist. Chronux is freely available along with user tutorials, sample data, and extensive documentation from http://chronux.org/. Copyright 2010 Elsevier B.V. All rights reserved.

  18. Learning Maneuvers Using Neural Network Models

    Science.gov (United States)

    1994-08-07

    parametric function approximators such as neural networks ( Tesauro 1991). The prediction process runs in a series of epochs. Each epoch ends when a...function approximator such as a neural network. This technique has recently been used successfully on a large complex problem, Backgammon, by Tesauro (1991...Morgan Kaufman. Tesauro , G. J. (1991). Practical Issues in Temporal Difference Learning. Report RC 17223 (76307), IBM T. J. Watson Research Center

  19. Neural Photo Editing with Introspective Adversarial Networks

    OpenAIRE

    Brock, Andrew; Lim, Theodore; Ritchie, J. M.; Weston, Nick

    2016-01-01

    The increasingly photorealistic sample quality of generative image models suggests their feasibility in applications beyond image generation. We present the Neural Photo Editor, an interface that leverages the power of generative neural networks to make large, semantically coherent changes to existing images. To tackle the challenge of achieving accurate reconstructions without loss of feature quality, we introduce the Introspective Adversarial Network, a novel hybridization of the VAE and GA...

  20. Novel LDPC Decoder via MLP Neural Networks

    OpenAIRE

    Karami, Alireza; Attari, Mahmoud Ahmadian

    2014-01-01

    In this paper, a new method for decoding Low Density Parity Check (LDPC) codes, based on Multi-Layer Perceptron (MLP) neural networks is proposed. Due to the fact that in neural networks all procedures are processed in parallel, this method can be considered as a viable alternative to Message Passing Algorithm (MPA), with high computational complexity. Our proposed algorithm runs with soft criterion and concurrently does not use probabilistic quantities to decide what the estimated codeword i...

  1. Culture of Mouse Neural Stem Cell Precursors

    OpenAIRE

    Currle, D. Spencer; Hu, Jia Sheng; Kolski-Andreaco, Aaron; Monuki, Edwin S.

    2007-01-01

    Primary neural stem cell cultures are useful for studying the mechanisms underlying central nervous system development. Stem cell research will increase our understanding of the nervous system and may allow us to develop treatments for currently incurable brain diseases and injuries. In addition, stem cells should be used for stem cell research aimed at the detailed study of mechanisms of neural differentiation and transdifferentiation and the genetic and environmental signals that direct the...

  2. VLSI Cells Placement Using the Neural Networks

    International Nuclear Information System (INIS)

    Azizi, Hacene; Zouaoui, Lamri; Mokhnache, Salah

    2008-01-01

    The artificial neural networks have been studied for several years. Their effectiveness makes it possible to expect high performances. The privileged fields of these techniques remain the recognition and classification. Various applications of optimization are also studied under the angle of the artificial neural networks. They make it possible to apply distributed heuristic algorithms. In this article, a solution to placement problem of the various cells at the time of the realization of an integrated circuit is proposed by using the KOHONEN network

  3. Robust Planning and Control Using Neural Networks

    Science.gov (United States)

    1990-06-30

    hyperspace . We have been investigating CMAC neural networks with tapered, rather than rectangular, receptive fields. Such networks promise better (continuous...CMOS Logic Cell Arrays.’ UNH Intelligent Structures Group Report ECE.IS.90.01, Feb. 6,1990. Miller, W. T., Box, B. A., Whitney, E. C., and Glynn, J...M., ’Design and Implementation of a High Speed CMAC Neural Network Using Logic Programmable CMOS Logic Cell Arrays." To be presented at the Naval

  4. Pattern recognition using chaotic neural networks

    OpenAIRE

    Tan, Z.; Hepburn, B. S.; Tucker, C.; Ali, M. K.

    1998-01-01

    Pattern recognition by chaotic neural networks is studied using a hyperchaotic neural network as model. Virtual basins of attraction are introduced around unstable periodic orbits which are then used as patterns. Search for periodic orbits in dynamical systems is treated as a process of pattern recognition. The role of synapses on patterns in chaotic networks is discussed. It is shown that distorted states having only limited information of the patterns are successfully recognized.

  5. Pattern recognition using chaotic neural networks

    Directory of Open Access Journals (Sweden)

    Z. Tan

    1998-01-01

    Full Text Available Pattern recognition by chaotic neural networks is studied using a hyperchaotic neural network as model. Virtual basins of attraction are introduced around unstable periodic orbits which are then used as patterns. Search for periodic orbits in dynamical systems is treated as a process of pattern recognition. The role of synapses on patterns in chaotic networks is discussed. It is shown that distorted states having only limited information of the patterns are successfully recognized.

  6. Drift chamber tracking with neural networks

    International Nuclear Information System (INIS)

    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

  7. Using neural networks in software repositories

    Science.gov (United States)

    Eichmann, David (Editor); Srinivas, Kankanahalli; Boetticher, G.

    1992-01-01

    The first topic is an exploration of the use of neural network techniques to improve the effectiveness of retrieval in software repositories. The second topic relates to a series of experiments conducted to evaluate the feasibility of using adaptive neural networks as a means of deriving (or more specifically, learning) measures on software. Taken together, these two efforts illuminate a very promising mechanism supporting software infrastructures - one based upon a flexible and responsive technology.

  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. Genetic Algorithms for Evolving Deep Neural Networks

    OpenAIRE

    David, Eli; Greental, Iddo

    2017-01-01

    In recent years, deep learning methods applying unsupervised learning to train deep layers of neural networks have achieved remarkable results in numerous fields. In the past, many genetic algorithms based methods have been successfully applied to training neural networks. In this paper, we extend previous work and propose a GA-assisted method for deep learning. Our experimental results indicate that this GA-assisted approach improves the performance of a deep autoencoder, producing a sparser...

  10. Neural networks, D0, and the SSC

    International Nuclear Information System (INIS)

    Barter, C.; Cutts, D.; Hoftun, J.S.; Partridge, R.A.; Sornborger, A.T.; Johnson, C.T.; Zeller, R.T.

    1989-01-01

    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

  11. Motor Inhibition during Overt and Covert Actions: An Electrical Neuroimaging Study.

    Directory of Open Access Journals (Sweden)

    Monica Angelini

    Full Text Available Given ample evidence for shared cortical structures involved in encoding actions, whether or not subsequently executed, a still unsolved problem is the identification of neural mechanisms of motor inhibition, preventing "covert actions" as motor imagery from being performed, in spite of the activation of the motor system. The principal aims of the present study were the evaluation of: 1 the presence in covert actions as motor imagery of putative motor inhibitory mechanisms; 2 their underlying cerebral sources; 3 their differences or similarities with respect to cerebral networks underpinning the inhibition of overt actions during a Go/NoGo task. For these purposes, we performed a high density EEG study evaluating the cerebral microstates and their related sources elicited during two types of Go/NoGo tasks, requiring the execution or withholding of an overt or a covert imagined action, respectively. Our results show for the first time the engagement during motor imagery of key nodes of a putative inhibitory network (including pre-supplementary motor area and right inferior frontal gyrus partially overlapping with those activated for the inhibition of an overt action during the overt NoGo condition. At the same time, different patterns of temporal recruitment in these shared neural inhibitory substrates are shown, in accord with the intended overt or covert modality of action performance. The evidence that apparently divergent mechanisms such as controlled inhibition of overt actions and contingent automatic inhibition of covert actions do indeed share partially overlapping neural substrates, further challenges the rigid dichotomy between conscious, explicit, flexible and unconscious, implicit, inflexible forms of motor behavioral control.

  12. Inhibition does not affect the timing code for vocalizations in the mouse auditory midbrain

    Directory of Open Access Journals (Sweden)

    Alexander G Dimitrov

    2014-04-01

    Full Text Available Many animals use a diverse repertoire of complex acoustic signals to convey different types of information to other animals. The information in each vocalization therefore must be coded by neurons in the auditory system. One way in which the auditory system may discriminate among different vocalizations is by having highly selective neurons, where only one or two different vocalizations evoke a strong response from a single neuron. Another strategy is to have specific spike timing patterns for particular vocalizations such that each neural response can be matched to a specific vocalization. Both of these strategies may occur in the auditory midbrain of mice. However, the neural mechanisms underlying rate and time coding are unclear, but it is likely that inhibition plays a role. Here, we examined whether inhibition is involved in creating neural selectivity to vocalizations via rate and/or time coding in the mouse inferior colliculus. We examined extracellular single unit responses to vocalizations before and after iontophoretically blocking GABA_A and glycine receptors in the IC of awake mice. In general, we found that pharmacologically blocking inhibitory receptors in the IC increased response rate to vocalizations but did not dramatically affect spike timing. We observed two main effects when inhibition was locally blocked: 1 Highly selective neurons maintained their selectivity and the information about the stimuli did not change, but response rate increased slightly. 2 Neurons that responded to vocalizations in the control condition, also responded to the same stimuli in the test condition, with similar timing and pattern, but with a greater number of spikes, and, in some cases, greater reliability. Interestingly, in some neurons, blocking inhibition had no effect on vocalization-evoked responses. Overall, we found that inhibition in the IC does not play a substantial role in creating the reliable neuronal temporal patterns in response to

  13. The Laplacian spectrum of neural networks

    Science.gov (United States)

    de Lange, Siemon C.; de Reus, Marcel A.; van den Heuvel, Martijn P.

    2014-01-01

    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. PMID:24454286

  14. Modular representation of layered neural networks.

    Science.gov (United States)

    Watanabe, Chihiro; Hiramatsu, Kaoru; Kashino, Kunio

    2018-01-01

    Layered neural networks have greatly improved the performance of various applications including image processing, speech recognition, natural language processing, and bioinformatics. However, it is still difficult to discover or interpret knowledge from the inference provided by a layered neural network, since its internal representation has many nonlinear and complex parameters embedded in hierarchical layers. Therefore, it becomes important to establish a new methodology by which layered neural networks can be understood. In this paper, we propose a new method for extracting a global and simplified structure from a layered neural network. Based on network analysis, the proposed method detects communities or clusters of units with similar connection patterns. We show its effectiveness by applying it to three use cases. (1) Network decomposition: it can decompose a trained neural network into multiple small independent networks thus dividing the problem and reducing the computation time. (2) Training assessment: the appropriateness of a trained result with a given hyperparameter or randomly chosen initial parameters can be evaluated by using a modularity index. And (3) data analysis: in practical data it reveals the community structure in the input, hidden, and output layers, which serves as a clue for discovering knowledge from a trained neural network. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. 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.

  16. 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.

  17. Application of neural networks in CRM systems

    Directory of Open Access Journals (Sweden)

    Bojanowska Agnieszka

    2017-01-01

    Full Text Available The central aim of this study is to investigate how to apply artificial neural networks in Customer Relationship Management (CRM. The paper presents several business applications of neural networks in software systems designed to aid CRM, e.g. in deciding on the profitability of building a relationship with a given customer. Furthermore, a framework for a neural-network based CRM software tool is developed. Building beneficial relationships with customers is generating considerable interest among various businesses, and is often mentioned as one of the crucial objectives of enterprises, next to their key aim: to bring satisfactory profit. There is a growing tendency among businesses to invest in CRM systems, which together with an organisational culture of a company aid managing customer relationships. It is the sheer amount of gathered data as well as the need for constant updating and analysis of this breadth of information that may imply the suitability of neural networks for the application in question. Neural networks exhibit considerably higher computational capabilities than sequential calculations because the solution to a problem is obtained without the need for developing a special algorithm. In the majority of presented CRM applications neural networks constitute and are presented as a managerial decision-taking optimisation tool.

  18. Recent advances in neural recording microsystems.

    Science.gov (United States)

    Gosselin, Benoit

    2011-01-01

    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.

  19. A Rotational Motion Perception Neural Network Based on Asymmetric Spatiotemporal Visual Information Processing.

    Science.gov (United States)

    Hu, Bin; Yue, Shigang; Zhang, Zhuhong

    All complex motion patterns can be decomposed into several elements, including translation, expansion/contraction, and rotational motion. In biological vision systems, scientists have found that specific types of visual neurons have specific preferences to each of the three motion elements. There are computational models on translation and expansion/contraction perceptions; however, little has been done in the past to create computational models for rotational motion perception. To fill this gap, we proposed a neural network that utilizes a specific spatiotemporal arrangement of asymmetric lateral inhibited direction selective neural networks (DSNNs) for rotational motion perception. The proposed neural network consists of two parts-presynaptic and postsynaptic parts. In the presynaptic part, there are a number of lateral inhibited DSNNs to extract directional visual cues. In the postsynaptic part, similar to the arrangement of the directional columns in the cerebral cortex, these direction selective neurons are arranged in a cyclic order to perceive rotational motion cues. In the postsynaptic network, the delayed excitation from each direction selective neuron is multiplied by the gathered excitation from this neuron and its unilateral counterparts depending on which rotation, clockwise (cw) or counter-cw (ccw), to perceive. Systematic experiments under various conditions and settings have been carried out and validated the robustness and reliability of the proposed neural network in detecting cw or ccw rotational motion. This research is a critical step further toward dynamic visual information processing.All complex motion patterns can be decomposed into several elements, including translation, expansion/contraction, and rotational motion. In biological vision systems, scientists have found that specific types of visual neurons have specific preferences to each of the three motion elements. There are computational models on translation and expansion

  20. Direct behavioral and neural evidence for an offset-triggered conscious perception.

    Science.gov (United States)

    Noguchi, Yasuki; Kimijima, Shintaro; Kakigi, Ryusuke

    2015-04-01

    Many previous theories of perceptual awareness assume that a conscious representation of a stimulus is created from sensory information carried by an onset (appearance) of the stimulus. In contrast, here we provide behavioral and neural evidence for a new phenomenon in which conscious perception is directly triggered by an offset (disappearance) of a stimulus. When a stimulus made invisible by inter-ocular suppression physically disappeared from a screen, subjects reported an appearance (not disappearance) of that stimulus, correctly reporting a color of the disappeared stimulus. Measurements of brain activity further confirmed that the physical offset of an invisible stimulus evoked neural activity reflecting conscious perception of that stimulus. Those results indicate a new role of a stimulus offset to facilitate (rather than inhibit) an emergence of consciousness. Copyright © 2015 Elsevier Ltd. All rights reserved.