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Sample records for extensive periocular neural

  1. Periocular Scleromyxedema.

    PubMed

    Qureshi, Farhan; Dharmasena, Aruna; Leatherbarrow, Brian

    2015-01-01

    Scleromyxedema is characterized by cutaneous mucinosis and rarely presents to oculoplastic surgeons with bilateral upper and lower eyelid swelling. The authors present 2 case reports with a review of the literature and discuss the ophthalmic manifestations of scleromyxedema and the management of these cases. Both patients were in their early 50s and were fit and well prior to the presentation. They both presented with eyelid swelling and underlying nodularity of the subcutaneous tissue. The skin biopsy confirmed cutaneous manifestations of scleromyxedema. The systemic manifestations responded to intravenous and oral steroids and intravenous infusions of immunoglobulin. The ophthalmic manifestations were managed conservatively. Scleromyxedema is a rare connective tissue disease characterized by cutaneous mucinosis, extracutaneous manifestations, and monoclonal gammopathy. It rarely affects the eyelids and cornea. The authors would like to present 2 cases of periocular scleromyxedema. PMID:24807804

  2. Periocular pilomatrixoma: case report.

    PubMed

    Tvrdi, Ana Bišćan; Elabjer, Kusmanoviċ; Elabjer, Biljana Kuzmanović; Miletić, Daliborka; Bušić, Miladen; Bosnar, Damir; Petrović, Zvonko

    2014-09-01

    The aim is to present a case of pilomatrixoma in the periocular area in a 10-year-old female through retrospective review of medical records of a single patient. A 10-year-old female developed a lesion under her right eyebrow over a period of one year. The rest of the ophthalmic history was unremarkable. On examination, oval, well-defined, subcutaneous tumor measuring 7 x 4 mm was found under the right eyebrow. It gave bluish tint under the firmly adherent overlying skin of normal color and texture. Rocky hard and non-tender, it was mobile over the underlying tissues. Total excision biopsy was performed under general anesthesia. Histopathologic analysis confirmed the diagnosis ofpilomatrixoma. Pilomatrixoma is a rare tumor with head, neck and periocular area being the commonest sites. It is often clinically misdiagnosed and/or missed on differential diagnosis. Although a benign tumor, malignant transformation into pilomatrix carcinoma has been described. Thus, total surgical excision of the mass is recommended. PMID:25509249

  3. Excision of periocular basal cell carcinoma guided by en face frozen section.

    PubMed

    Tullett, Mark; Sagili, Suresh; Barrett, Andrew; Malhotra, Raman

    2013-09-01

    We describe a technique for monitoring excision margins in periocular basal cell carcinoma (BCC) using en face frozen sections and report outcomes. We excised periocular BCC with 3mm margins. An outer 1mm sliver of the perimeter of the specimen was mapped and sent for evaluation by en face frozen section. The central tumour mass was processed using routine paraffin sections. A further 3mm level was excised at the site of any affected margin and the outer 1mm sliver was again evaluated by frozen section. We identified 78 patients from November 2003 to July 2009; 67 had primary tumours and 11 (14%) had recurrent BCC of which 52 (66%) were located on the lower eyelid. Growth patterns were nodular (n=34, 43%), infiltrative (n=25, 32%), micronodular (n=12, 16%), and superficial (n=7, 9%). A third of BCC with a clinically nodular appearance showed additional histological patterns including infiltrative and micronodular growth patterns. Of 30 clinically nodular carcinomas, 29 were excised completely with one level, and one required 2 levels of excision for clearance after evaluation by frozen section. Mean follow-up was 23 months (range 2-60). There was one recurrence (1%). Excision of margins guided by en face frozen section is justified by the low rates of recurrence, and it can easily be taught or imported into hospital practice. Clinically nodular BCC have subclinical extensions that can be missed on bread loaf sectioning, which makes the sampling of margins a standard for periocular BCC. PMID:23219018

  4. Modeling of Corneal and Retinal Pharmacokinetics after Periocular Drug Administration

    PubMed Central

    Amrite, Aniruddha C.; Edelhauser, Henry F.; Kompella, Uday B.

    2012-01-01

    Purpose To develop pharmacokinetics models to describe the disposition of small lipophilic molecules in the cornea and retina after periocular (subconjunctival or posterior subconjunctival) administration. Methods Compartmental pharmacokinetics analysis was performed on the corneal and retinal data obtained after periocular administration of 3 mg of celecoxib (a selective COX-2 inhibitor) to Brown Norway (BN) rats. Berkeley Madonna, a differential and difference equation–based modeling software, was used for the pharmacokinetics modeling. The data were fit to different compartment models with first-order input and disposition, and the best fit was selected on the basis of coefficient of regression and Akaike information criteria (AIC). The models were validated by using the celecoxib data from a prior study in Sprague-Dawley (SD) rats. The corneal model was also fit to the corneal data for prednisolone at a dose of 2.61 mg in albino rabbits, and the model was validated at two other doses of prednisolone (0.261 and 26.1 mg) in these rabbits. Model simulations were performed with the finalized model to understand the effect of formulation on corneal and retinal pharmacokinetics after periocular administration. Results Celecoxib kinetics in the BN rat cornea can be described by a two-compartment (periocular space and cornea, with a dissolution step for periocular formulation) model, with parallel elimination from the cornea and the periocular space. The inclusion of a distribution compartment or a dissolution step for celecoxib suspension did not lead to an overall improvement in the corneal data fit compared with the two-compartment model. The more important parameter for enhanced fit and explaining the apparent lack of an increase phase in the corneal levels is the inclusion of the initial leak-back of the dose from the periocular space into the precorneal area. The predicted celecoxib concentrations from this model also showed very good correlation (r = 0

  5. Periocular granuloma annulare: a case report and review of literature.

    PubMed

    Chiang, Katherine; Bhalla, Rohan; Mesinkovska, Natasha A; Piliang, Melissa P; Tamburro, Joan E

    2014-01-01

    Granuloma annulare (GA) is a granulomatous dermatosis that rarely presents on the face and is extremely uncommon in the periocular region. We report our experience with the presentation and management of GA lesions on the eyelids of a 17-year-old girl. We performed a review of published literature and identified 13 cases of pediatric periocular GA. One additional case was identified upon review of all pediatric GA cases at the Cleveland Clinic Foundation. Review of these cases suggests that periocular GA is a benign condition that spontaneously regresses within a few months. GA nodules have a predilection for the upper eyelids. A greater incidence is noted in African American children. Awareness of the self-resolving nature of this condition can prevent unnecessary surgical excisions in affected children. PMID:23551387

  6. Neural network tracking and extension of positive tracking periods

    NASA Technical Reports Server (NTRS)

    Hanan, Jay C.; Chao, Tien-Hsin; Moreels, Pierre

    2004-01-01

    Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.

  7. An FGF3-BMP Signaling Axis Regulates Caudal Neural Tube Closure, Neural Crest Specification and Anterior-Posterior Axis Extension

    PubMed Central

    Anderson, Matthew J.; Schimmang, Thomas; Lewandoski, Mark

    2016-01-01

    During vertebrate axis extension, adjacent tissue layers undergo profound morphological changes: within the neuroepithelium, neural tube closure and neural crest formation are occurring, while within the paraxial mesoderm somites are segmenting from the presomitic mesoderm (PSM). Little is known about the signals between these tissues that regulate their coordinated morphogenesis. Here, we analyze the posterior axis truncation of mouse Fgf3 null homozygotes and demonstrate that the earliest role of PSM-derived FGF3 is to regulate BMP signals in the adjacent neuroepithelium. FGF3 loss causes elevated BMP signals leading to increased neuroepithelium proliferation, delay in neural tube closure and premature neural crest specification. We demonstrate that elevated BMP4 depletes PSM progenitors in vitro, phenocopying the Fgf3 mutant, suggesting that excessive BMP signals cause the Fgf3 axis defect. To test this in vivo we increased BMP signaling in Fgf3 mutants by removing one copy of Noggin, which encodes a BMP antagonist. In such mutants, all parameters of the Fgf3 phenotype were exacerbated: neural tube closure delay, premature neural crest specification, and premature axis termination. Conversely, genetically decreasing BMP signaling in Fgf3 mutants, via loss of BMP receptor activity, alleviates morphological defects. Aberrant apoptosis is observed in the Fgf3 mutant tailbud. However, we demonstrate that cell death does not cause the Fgf3 phenotype: blocking apoptosis via deletion of pro-apoptotic genes surprisingly increases all Fgf3 defects including causing spina bifida. We demonstrate that this counterintuitive consequence of blocking apoptosis is caused by the increased survival of BMP-producing cells in the neuroepithelium. Thus, we show that FGF3 in the caudal vertebrate embryo regulates BMP signaling in the neuroepithelium, which in turn regulates neural tube closure, neural crest specification and axis termination. Uncovering this FGF3-BMP signaling axis is

  8. An FGF3-BMP Signaling Axis Regulates Caudal Neural Tube Closure, Neural Crest Specification and Anterior-Posterior Axis Extension.

    PubMed

    Anderson, Matthew J; Schimmang, Thomas; Lewandoski, Mark

    2016-05-01

    During vertebrate axis extension, adjacent tissue layers undergo profound morphological changes: within the neuroepithelium, neural tube closure and neural crest formation are occurring, while within the paraxial mesoderm somites are segmenting from the presomitic mesoderm (PSM). Little is known about the signals between these tissues that regulate their coordinated morphogenesis. Here, we analyze the posterior axis truncation of mouse Fgf3 null homozygotes and demonstrate that the earliest role of PSM-derived FGF3 is to regulate BMP signals in the adjacent neuroepithelium. FGF3 loss causes elevated BMP signals leading to increased neuroepithelium proliferation, delay in neural tube closure and premature neural crest specification. We demonstrate that elevated BMP4 depletes PSM progenitors in vitro, phenocopying the Fgf3 mutant, suggesting that excessive BMP signals cause the Fgf3 axis defect. To test this in vivo we increased BMP signaling in Fgf3 mutants by removing one copy of Noggin, which encodes a BMP antagonist. In such mutants, all parameters of the Fgf3 phenotype were exacerbated: neural tube closure delay, premature neural crest specification, and premature axis termination. Conversely, genetically decreasing BMP signaling in Fgf3 mutants, via loss of BMP receptor activity, alleviates morphological defects. Aberrant apoptosis is observed in the Fgf3 mutant tailbud. However, we demonstrate that cell death does not cause the Fgf3 phenotype: blocking apoptosis via deletion of pro-apoptotic genes surprisingly increases all Fgf3 defects including causing spina bifida. We demonstrate that this counterintuitive consequence of blocking apoptosis is caused by the increased survival of BMP-producing cells in the neuroepithelium. Thus, we show that FGF3 in the caudal vertebrate embryo regulates BMP signaling in the neuroepithelium, which in turn regulates neural tube closure, neural crest specification and axis termination. Uncovering this FGF3-BMP signaling axis is

  9. Multilayer neural networks with extensively many hidden units.

    PubMed

    Rosen-Zvi, M; Engel, A; Kanter, I

    2001-08-13

    The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general symmetric Boolean functions, whereas the hidden layer is connected to the output by either discrete or continuous couplings. Introducing an overlap in the space of Boolean functions as order parameter, the storage capacity is found to scale with the logarithm of the number of implementable Boolean functions. The generalization behavior is smooth for continuous couplings and shows a discontinuous transition to perfect generalization for discrete ones. PMID:11497920

  10. Neural Chip SAND in online data processing of extensive air showers

    NASA Astrophysics Data System (ADS)

    Eppler, W.; Fischer, T.; Gemmeke, H.; Chilingarian, A.; Vardanyan, A.

    2000-04-01

    The neural chip SAND (Simple Applicable Neural Device) was designed to accelerate computations of neural networks at a very low cost basis, due to the fact that only few peripheral chips are necessary to use the neural network chip in applications. Four SAND-chips were implemented on one PCI-board. The board is highly usable for hardware triggers in particle physics. The performance of a SAND-PCI-board is 800 Mega Connections per Second due to four neuro-chips, each with four parallel 16 bit multipliers and 40 bit adders. SAND is able to implement feedforward neural networks with a maximum of 512 input neurons and three hidden layers. Kohonen feature maps and radial basis function networks may be also calculated. The application of the SAND-PCI-board is proposed for cosmic ray physics to allow online analysis of extensive air showers.

  11. Management of Periocular Granuloma Annulare Using Topical Dapsone

    PubMed Central

    Patel, Mayha; Shitabata, Paul; Horowitz, David

    2015-01-01

    Granuloma annulare is a disease characterized by granulomatous inflammation of the dermis. Localized granuloma annulare may resolve spontaneously, while generalized granuloma annulare may persist for decades. The authors present the case of a 41-year-old Hispanic man with a two-week history of periocular granuloma annulare. Due to previously reported success in the use of systemic dapsone for the treatment of granuloma annulare, and the periocular proximity of the patient’s lesion, topical dapsone was used for treatment. Various additional therapies for the management of granuloma annulare have been reported, such as topical and systemic steroids, isotretinoin, pentoxifylline, cyclosporine, Interferon gamma, potassium iodide, nicotinamide, niacinamide, salicylic acid, fumaric acid ester, etanercept, infliximab, and hydroxychloroquine. Additional clinical trials are necessary to further evaluate the effectiveness of topical dapsone in the management of granuloma annulare. PMID:26203321

  12. PERIOCULAR CORTICOSTEROID INJECTIONS IN UVEITIS: EFFECTS AND COMPLICATIONS

    PubMed Central

    Sen, H. Nida; Vitale, Susan; Gangaputra, Sapna S.; Nussenblatt, Robert B.; Liesegang, Teresa L.; Levy-Clarke, Grace A.; Rosenbaum, James T.; Suhler, Eric B.; Thorne, Jennifer E.; Foster, C. Stephen; Jabs, Douglas A.; Kempen, John H.

    2014-01-01

    Purpose To evaluate the benefits and complications of periocular depot corticosteroid injections in patients with ocular inflammatory disorders. Design Multicenter retrospective cohort study. Participants A total of 914 patients (1192 eyes) who had received at least one periocular corticosteroid injection at 5 tertiary uveitis clinics in the United States. Methods Patients were identified from the Systemic Immunosuppressive Therapy for Eye Diseases (SITE) Cohort Study. Demographic and clinical characteristics were obtained at every visit via medical record review by trained reviewers. Main Outcome Measures Control of inflammation, improvement of visual acuity to 20/40 or better, improvement of visual acuity loss attributed to macular edema, incident cataract affecting visual acuity, cataract surgery, ocular hypertension and glaucoma surgery. Results Among 914 patients (1192 eyes) who received at least one periocular injection during follow-up, 286 (31.3%) were classified as having anterior uveitis, 303 (33.3%) as intermediate uveitis, 324 (35.4%) as posterior or panuveitis. Cumulatively by ≤6 months, 72.7% [95% confidence interval (95%CI): 69.1-76.3] of the eyes achieved complete control of inflammation and 49.7% [95%CI:45.5-54.1] showed an improvement in visual acuity (VA) from worse than 20/40 to 20/40 or better. Among the subset with VA worse than 20/40 attributed to macular edema, 33.1% [95%CI: 25.2-42.7] improved to 20/40 or better. By 12 months, the cumulative incidence of one or more visits with an intraocular pressure≥24 mmHg and ≥30 mmHg was 34.0% [95%CI: 24.8-45.4] and 15.0% [95%CI: 11.8-19.1] respectively; glaucoma surgery was performed in 2.4% [95%CI: 1.4-3.9] of eyes. Within 12 months, among phakic eyes initially 20/40 or better, the incidence of a reduction in VA to worse than 20/40 attributed to cataract was 20.2% [95%CI: 15.9-25.6]; cataract surgery was performed within 12 months in 13.8 % [95%CI: 11.1-17.2] of the initially phakic eyes

  13. Optical coherence tomography imaging of ocular and periocular tumours

    PubMed Central

    Medina, Carlos A; Plesec, Thomas; Singh, Arun D

    2014-01-01

    Optical coherence tomography (OCT) has become pivotal in the practice of ophthalmology. Similar to other ophthalmic subspecialties, ophthalmic oncology has also incorporated OCT into practice. Anterior segment OCT (AS-OCT), ultra-high resolution OCT (UHR-OCT), spectral domain OCT (SD-OCT) and enhanced depth imaging OCT (EDI-OCT), have all been described to be helpful in the diagnosis, treatment planning and monitoring response of ocular and periocular tumours. Herein we discuss the role of OCT including the advantages and limitations of its use in the setting of common intraocular and adnexal tumours. PMID:24599420

  14. Dynamic causal models of neural system dynamics: current state and future extensions

    PubMed Central

    Stephan, Klaas E.; Harrison, Lee M.; Kiebel, Stefan J.; David, Olivier; Penny, Will D.; Friston, Karl J.

    2009-01-01

    Complex processes resulting from the interaction of multiple elements can rarely be understood by analytical scientific approaches alone; additionally, mathematical models of system dynamics are required. This insight, which disciplines like physics have embraced for a long time already, is gradually gaining importance in the study of cognitive processes by functional neuroimaging. In this field, causal mechanisms in neural systems are described in terms of effective connectivity. Recently, Dynamic Causal Modelling (DCM) was introduced as a generic method to estimate effective connectivity from neuroimaging data in a Bayesian fashion. One of the key advantages of DCM over previous methods is that it distinguishes between neural state equations and modality-specific forward models that translate neural activity into a measured signal. Another strength is its natural relation to Bayesian Model Selection (BMS) procedures. In this article, we review the conceptual and mathematical basis of DCM and its implementation for functional magnetic resonance imaging data and event-related potentials. After introducing the application of BMS in the context of DCM, we conclude with an outlook to future extensions of DCM. These extensions are guided by the long-term goal of using dynamic system models for pharmacological and clinical applications, particularly with regard to synaptic plasticity. PMID:17426386

  15. Short Report: Olfactory Ensheathing Cells Promote Differentiation of Neural Stem Cells and Robust Neurite Extension

    PubMed Central

    Sethi, Rosh; Sethi, Roshan; Redmond, Andy

    2014-01-01

    Aims The goal of this study was to gain insight into the signaling between olfactory ensheathing cells (OECs) and neural stem cells (NSCs). We sought to understand the impact of OECs on NSC differentiation and neurite extension and to begin to elucidate the factors involved in these interactions to provide new targets for therapeutic interventions. Materials and Methods We utilized lines of OECs that have been extremely well characterized in vitro and in vivo along with well studied NSCs in gels to determine the impact of the coculture in three dimensions. To further elucidate the signaling, we used conditioned media from the OECs as well as fractioned components on NSCs to determine the molecular weight range of the soluble factors that was most responsible for the NSC behavior. Results We found that the coculture of NSCs and OECs led to robust NSC differentiation and extremely long neural processes not usually seen with NSCs in three dimensional gels in vitro. Through culture of NSCs with fractioned OEC media, we determined that molecules larger than 30 kDa have the greatest impact on the NSC behavior. Conclusions Overall, our findings suggest that cocultures of NSCs and OECs may be a novel combination therapy for neural injuries including spinal cord injury (SCI). Furthermore, we have identified a class of molecules which plays a substantial role in the behavior that provides new targets for investigating pharmacological therapies. PMID:24996386

  16. Extensive Neuronal Differentiation of Human Neural Stem Cell Grafts in Adult Rat Spinal Cord

    PubMed Central

    Yan, Jun; Xu, Leyan; Welsh, Annie M; Hatfield, Glen; Hazel, Thomas; Johe, Karl; Koliatsos, Vassilis E

    2007-01-01

    Background Effective treatments for degenerative and traumatic diseases of the nervous system are not currently available. The support or replacement of injured neurons with neural grafts, already an established approach in experimental therapeutics, has been recently invigorated with the addition of neural and embryonic stem-derived precursors as inexhaustible, self-propagating alternatives to fetal tissues. The adult spinal cord, i.e., the site of common devastating injuries and motor neuron disease, has been an especially challenging target for stem cell therapies. In most cases, neural stem cell (NSC) transplants have shown either poor differentiation or a preferential choice of glial lineages. Methods and Findings In the present investigation, we grafted NSCs from human fetal spinal cord grown in monolayer into the lumbar cord of normal or injured adult nude rats and observed large-scale differentiation of these cells into neurons that formed axons and synapses and established extensive contacts with host motor neurons. Spinal cord microenvironment appeared to influence fate choice, with centrally located cells taking on a predominant neuronal path, and cells located under the pia membrane persisting as NSCs or presenting with astrocytic phenotypes. Slightly fewer than one-tenth of grafted neurons differentiated into oligodendrocytes. The presence of lesions increased the frequency of astrocytic phenotypes in the white matter. Conclusions NSC grafts can show substantial neuronal differentiation in the normal and injured adult spinal cord with good potential of integration into host neural circuits. In view of recent similar findings from other laboratories, the extent of neuronal differentiation observed here disputes the notion of a spinal cord that is constitutively unfavorable to neuronal repair. Restoration of spinal cord circuitry in traumatic and degenerative diseases may be more realistic than previously thought, although major challenges remain

  17. a Multiscale, Lacunarity and Neural Network Method for γ/h Discrimination in Extensive Air Showers

    NASA Astrophysics Data System (ADS)

    Pagliaro, A.; D'Anna, F.; D'Alí Staiti, G.

    2012-12-01

    This paper presents a new method for the identification of extensive air showers initiated by different primaries. The method uses the multiscale concept and is based on the analysis of multifractal behaviour and lacunarity of secondary particle distributions together with a properly designed and trained artificial neural network. The separation technique is particularly suited for being applied when the topology of the particle distribution in the shower front is as largely detailed as possible. In the present work the method is discussed and applied in the experimental framework of ARGO-YBJ, to obtain hadron to gamma primary separation. We show that the presented approach gives very good results, leading, in the 1 - 10 Tev energy range, to a clear improvement of the discrimination power with respect to the existing figures for extended shower detectors.

  18. Towards online iris and periocular recognition under relaxed imaging constraints.

    PubMed

    Tan, Chun-Wei; Kumar, Ajay

    2013-10-01

    Online iris recognition using distantly acquired images in a less imaging constrained environment requires the development of a efficient iris segmentation approach and recognition strategy that can exploit multiple features available for the potential identification. This paper presents an effective solution toward addressing such a problem. The developed iris segmentation approach exploits a random walker algorithm to efficiently estimate coarsely segmented iris images. These coarsely segmented iris images are postprocessed using a sequence of operations that can effectively improve the segmentation accuracy. The robustness of the proposed iris segmentation approach is ascertained by providing comparison with other state-of-the-art algorithms using publicly available UBIRIS.v2, FRGC, and CASIA.v4-distance databases. Our experimental results achieve improvement of 9.5%, 4.3%, and 25.7% in the average segmentation accuracy, respectively, for the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with most competing approaches. We also exploit the simultaneously extracted periocular features to achieve significant performance improvement. The joint segmentation and combination strategy suggest promising results and achieve average improvement of 132.3%, 7.45%, and 17.5% in the recognition performance, respectively, from the UBIRIS.v2, FRGC, and CASIA.v4-distance databases, as compared with the related competing approaches. PMID:23629856

  19. Significant wave height record extension by neural networks and reanalysis wind data

    NASA Astrophysics Data System (ADS)

    Peres, D. J.; Iuppa, C.; Cavallaro, L.; Cancelliere, A.; Foti, E.

    2015-10-01

    Accuracy of wave climate assessment is related to the length of available observed records of sea state variables of interest (significant wave height, mean direction, mean period, etc.). Data availability may be increased by record extension methods. In the paper, we investigate the use of artificial neural networks (ANNs) fed with reanalysis wind data to extend an observed time series of significant wave heights. In particular, six-hourly 10 m a.s.l. u - and v - wind speed data of the NCEP/NCAR Reanalysis I (NRA1) project are used to perform an extension of observed significant wave height series back to 1948 at the same time resolution. Wind for input is considered at several NRA1 grid-points and at several time lags as well, and the influence of the distance of input points and of the number of lags is analyzed to derive best-performing models, conceptually taking into account wind fetch and duration. Applications are conducted for buoys of the Italian Sea Monitoring Network of different climatic features, for which more than 15 years of observations are available. Results of the ANNs are compared to those of state-of-the-art wave reanalyses NOAA WAVEWATCH III/CFSR and ERA-Interim, and indicate that model performs slightly better than the former, which in turn outperforms the latter. The computational times for model training on a common workstation are typically of few hours, so the proposed method is potentially appealing to engineering practice.

  20. Neural stem cells display extensive tropism for pathology in adult brain: Evidence from intracranial gliomas

    PubMed Central

    Aboody, Karen S.; Brown, Alice; Rainov, Nikolai G.; Bower, Kate A.; Liu, Shaoxiong; Yang, Wendy; Small, Juan E.; Herrlinger, Ulrich; Ourednik, Vaclav; Black, Peter McL.; Breakefield, Xandra O.; Snyder, Evan Y.

    2000-01-01

    One of the impediments to the treatment of brain tumors (e.g., gliomas) has been the degree to which they expand, infiltrate surrounding tissue, and migrate widely into normal brain, usually rendering them “elusive” to effective resection, irradiation, chemotherapy, or gene therapy. We demonstrate that neural stem cells (NSCs), when implanted into experimental intracranial gliomas in vivo in adult rodents, distribute themselves quickly and extensively throughout the tumor bed and migrate uniquely in juxtaposition to widely expanding and aggressively advancing tumor cells, while continuing to stably express a foreign gene. The NSCs “surround” the invading tumor border while “chasing down” infiltrating tumor cells. When implanted intracranially at distant sites from the tumor (e.g., into normal tissue, into the contralateral hemisphere, or into the cerebral ventricles), the donor cells migrate through normal tissue targeting the tumor cells (including human glioblastomas). When implanted outside the CNS intravascularly, NSCs will target an intracranial tumor. NSCs can deliver a therapeutically relevant molecule—cytosine deaminase—such that quantifiable reduction in tumor burden results. These data suggest the adjunctive use of inherently migratory NSCs as a delivery vehicle for targeting therapeutic genes and vectors to refractory, migratory, invasive brain tumors. More broadly, they suggest that NSC migration can be extensive, even in the adult brain and along nonstereotypical routes, if pathology (as modeled here by tumor) is present. PMID:11070094

  1. Safety and efficacy of administering abobotulinumtoxinA through a single injection point when treating lateral periocular rhytides.

    PubMed

    Kiripolsky, Monika G; Goldman, Mitchel P

    2011-09-01

    A retrospective analysis was performed to assess efficacy and patient satisfaction associated with AbobotulinumtoxinA for the treatment of dynamic periocular rhytides. When keeping the total dose of ABA the same for each side of the face, one injection point yielded the same efficacy and safety as three separate injection points into the lateral periocular areas. PMID:21896136

  2. Diagnosis and treatment of a periocular myxosarcoma in a bearded dragon (Pogona vitticeps).

    PubMed

    Gardhouse, Sara; Eshar, David; Lee-Chow, Bridget; Foster, Robert A; Ingrao, Joelle C; Poirier, Valerie J

    2014-07-01

    A 5-year-old male Australian bearded dragon (Pogona vitticeps) was presented with a 2-month history of a periocular mass. The clinical evaluation included a physical examination, hematology, biochemistry, and radiographs. The mass was treated surgically and diagnosed as myxosarcoma. Strontium-90 plesiotherapy was attempted, but the mass recurred 5 mo later. PMID:24982518

  3. Diagnosis and treatment of a periocular myxosarcoma in a bearded dragon (Pogona vitticeps)

    PubMed Central

    Gardhouse, Sara; Eshar, David; Lee-Chow, Bridget; Foster, Robert A.; Ingrao, Joelle C.; Poirier, Valerie J.

    2014-01-01

    A 5-year-old male Australian bearded dragon (Pogona vitticeps) was presented with a 2-month history of a periocular mass. The clinical evaluation included a physical examination, hematology, biochemistry, and radiographs. The mass was treated surgically and diagnosed as myxosarcoma. Strontium-90 plesiotherapy was attempted, but the mass recurred 5 mo later. PMID:24982518

  4. Rn for treatment of periocular fibrous connective tissue sarcomas in the horse

    SciTech Connect

    Frauenfelder, H.C.; Blevins, W.E.; Page, E.H.

    1982-02-01

    Twelve periocular fibrous connective tissue sarcomas in 11 horses were treated with 222Rn. Follow-up periods ranged from 1 to 6 years; the overall nonrecurrence rate at 12 months after therapy was 92%. Two lesions recurred 2 years after treatment, and 1 after 3 years. One of the former lesions has not recurred after a 2nd 222Rn treatment.

  5. Real-time neural network based camera localization and its extension to mobile robot control.

    PubMed

    Choi, D H; Oh, S Y

    1997-06-01

    The feasibility of using neural networks for camera localization and mobile robot control is investigated here. This approach has the advantages of eliminating the laborious and error-prone process of imaging system modeling and calibration procedures. Basically, two different approaches of using neural networks are introduced of which one is a hybrid approach combining neural networks and the pinhole-based analytic solution while the other is purely neural network based. These techniques have been tested and compared through both simulation and real-time experiments and are shown to yield more precise localization than analytic approaches. Furthermore, this neural localization method is also shown to be directly applicable to the navigation control of an experimental mobile robot along the hallway purely guided by a dark wall strip. It also facilitates multi-sensor fusion through the use of multiple sensors of different types for control due to the network's capability of learning without models. PMID:9427102

  6. Neural network modeling of nonlinear systems based on Volterra series extension of a linear model

    NASA Technical Reports Server (NTRS)

    Soloway, Donald I.; Bialasiewicz, Jan T.

    1992-01-01

    A Volterra series approach was applied to the identification of nonlinear systems which are described by a neural network model. A procedure is outlined by which a mathematical model can be developed from experimental data obtained from the network structure. Applications of the results to the control of robotic systems are discussed.

  7. ‘Stalled' periocular necrotising fasciitis: early effective treatment or host genetic determinants?

    PubMed Central

    Mutamba, A; Verity, D H; Rose, G E

    2013-01-01

    Background Necrotising fasciitis (NF) is a devastating disease with considerable mortality and morbidity, and early aggressive surgical debridement of devitalised necrotic tissues has traditionally been advocated. Methods We describe three patients who were referred from other units several weeks after developing periocular necrotising fasciitis; in all the three, the disease had been managed medically without surgical debridement, with apparent ‘stalling' of the inflammatory process despite persistent necrotic periocular tissue. Results Following ‘elective debridement' of the devitalised tissues and reconstruction with local flaps, all achieved a satisfactory aesthetic result. Discussion The role of host genetic determinants, polarised cytokine responses, and early, effective medical treatment in patients with atypical ‘disease phenotypes' in NF are discussed. PMID:23412558

  8. Periocular anterior adnexal anatomy and clinical adnexal examination of the adult Asian elephant (Elephas maximus).

    PubMed

    Wong, Michael A; Isaza, Ramiro; Cuthbert, J Kelly; Brooks, Dennis E; Samuelson, Don A

    2012-12-01

    Formalin preserved ocular-associated anterior adnexa tissues from five necropsied Asian elephants (Elephas maximus) were dissected with attention to the palpebrae, conjunctiva, nictitating membranes, nasolacrimal ducts, and periocular glandular tissues. Gross and histologic examination revealed that lacrimal and tarsal glands were not present. Evidence of the lacrimal drainage apparatus, including lacrimal punctae or any remnant of lacrimal sacs, was also absent. In contrast, well-developed sebaceous glands associated with accessory hairs along the palpebrae were exceptionally abundant. Mixed-secreting accessory lacrimal glands were noted in the deep stroma posterior to the tarsus of both palpebrae and the gland of the nictitating membrane. Apparently, the Asian elephant has developed a novel tear system in the absence of lacrimal and tarsal (meibomian) glands. Clinical examinations and bacterial cultures of the visible periocular tissues were performed on eight living adult Asian elephants to confirm the postmortem anatomic findings and provide guidance to the clinician during examination of the elephant conjunctiva. PMID:23272346

  9. Topical timolol maleate 0.5% solution for the management of deep periocular infantile hemangiomas.

    PubMed

    Painter, Sally L; Hildebrand, Göran Darius

    2016-04-01

    This retrospective, consecutive, clinical case series examined the use of topical timolol in the treatment of 5 children with deep, periocular infantile hemangiomas that caused astigmatism, change in head posture, or ptosis. All patients were treated with timolol maleate solution 0.5% twice daily until the lesions had regressed. All 5 children showed regression of the lesion and improvement in amblyogenic risk factors within 2 weeks. PMID:27079600

  10. Relative contributions of neural mechanisms versus muscle mechanics in promoting finger extension deficits following stroke.

    PubMed

    Kamper, D G; Harvey, R L; Suresh, S; Rymer, W Z

    2003-09-01

    The origins of impaired finger and hand function were examined in 10 stroke survivors with chronic spastic hemiparesis, with the intent of assessing whether mechanical restraint or altered neurophysiological control mechanisms are responsible for the well-known impairment of finger extension. Simultaneous extension of all four metacarpophalangeal (MCP) joints of the impaired hand was either externally imposed using a rotary actuator or attempted voluntarily by the subject. Trials were conducted both before and after administration of a local anesthetic, blocking the median and ulnar nerves at the elbow. The anesthetic was administered to reduce the activity of the muscles flexing the MCP joints, in order to distinguish mechanical from neuronal resistance to imposed MCP rotation. We found that the nerve blockade resulted in a reduction in velocity-dependent torque (P = 0.01), thereby indicating significant joint impedance due to spasticity. Blockade also produced a posture-dependent reduction in static torque in declaratively relaxed subjects (P = 0.04), suggesting some tonic flexor activity for specific hand postures. No change in either extensor isometric (P = 0.33) or isokinetic (0.53) torque was apparent, but 3 of the 10 subjects did exhibit substantial (>10 degrees ) improvement in voluntary MCP extension following the blockade. This improvement seemed largely due to a decrease in inappropriate flexor activity during the movement, rather than an increase in extensor activity. We argue that persistent and inappropriate flexor activation plays a role in limiting voluntary finger extension, and that this activation is potentially a reflection of altered supraspinal control of key spinal pathways. In all cases, this inappropriate activation was compounded by weakness, apparent in both the extensor and flexor muscles. PMID:12929190

  11. In vivo time-lapse imaging reveals extensive neural crest and endothelial cell interactions during neural crest migration and formation of the dorsal root and sympathetic ganglia.

    PubMed

    George, Lynn; Dunkel, Haley; Hunnicutt, Barbara J; Filla, Michael; Little, Charles; Lansford, Rusty; Lefcort, Frances

    2016-05-01

    During amniote embryogenesis the nervous and vascular systems interact in a process that significantly affects the respective morphogenesis of each network by forming a "neurovascular" link. The importance of neurovascular cross-talk in the central nervous system has recently come into focus with the growing awareness that these two systems interact extensively both during development, in the stem-cell niche, and in neurodegenerative conditions such as Alzheimer's Disease and Amyotrophic Lateral Sclerosis. With respect to the peripheral nervous system, however, there have been no live, real-time investigations of the potential relationship between these two developing systems. To address this deficit, we used multispectral 4D time-lapse imaging in a transgenic quail model in which endothelial cells (ECs) express a yellow fluorescent marker, while neural crest cells (NCCs) express an electroporated red fluorescent marker. We monitored EC and NCC migration in real-time during formation of the peripheral nervous system. Our time-lapse recordings indicate that NCCs and ECs are physically juxtaposed and dynamically interact at multiple locations along their trajectories. These interactions are stereotypical and occur at precise anatomical locations along the NCC migratory pathway. NCCs migrate alongside the posterior surface of developing intersomitic vessels, but fail to cross these continuous streams of motile ECs. NCCs change their morphology and migration trajectory when they encounter gaps in the developing vasculature. Within the nascent dorsal root ganglion, proximity to ECs causes filopodial retraction which curtails forward persistence of NCC motility. Overall, our time-lapse recordings support the conclusion that primary vascular networks substantially influence the distribution and migratory behavior of NCCs and the patterned formation of dorsal root and sympathetic ganglia. PMID:26988118

  12. Chaotic Extension Neural Network Theory-Based XXY Stage Collision Fault Detection Using a Single Accelerometer Sensor

    PubMed Central

    Hsieh, Chin-Tsung; Yau, Her-Terng; Wu, Shang-Yi; Lin, Huo-Cheng

    2014-01-01

    The collision fault detection of a XXY stage is proposed for the first time in this paper. The stage characteristic signals are extracted and imported into the master and slave chaos error systems by signal filtering from the vibratory magnitude of the stage. The trajectory diagram is made from the chaos synchronization dynamic error signals E1 and E2. The distance between characteristic positive and negative centers of gravity, as well as the maximum and minimum distances of trajectory diagram, are captured as the characteristics of fault recognition by observing the variation in various signal trajectory diagrams. The matter-element model of normal status and collision status is built by an extension neural network. The correlation grade of various fault statuses of the XXY stage was calculated for diagnosis. The dSPACE is used for real-time analysis of stage fault status with an accelerometer sensor. Three stage fault statuses are detected in this study, including normal status, Y collision fault and X collision fault. It is shown that the scheme can have at least 75% diagnosis rate for collision faults of the XXY stage. As a result, the fault diagnosis system can be implemented using just one sensor, and consequently the hardware cost is significantly reduced. PMID:25405512

  13. Latency of the nictitating membrane response to periocular electrostimulation in unanesthetized rabbits.

    PubMed

    Moore, J W; Desmond, J E

    1982-06-01

    The latency of the nictitating membrane response (NMR) in rabbit (Oryctolagus cuniculus) to periocular electro-stimulation is a negative exponential function of stimulus current with an asymptote of approximately 17 msec. The NMR was recorded by means of a precision low-torque potentiometer like that employed in previous studies of NMR latency, and the criterion of response initiation employed here was similar to that employed in studies of classical conditioning in this preparation. Using estimates from physiological studies on surgically acute preparations, the minimum latency of the NMR of 17 msec can be decomposed as follows: 4 msec to fire motoneurons of the accessory abducens nucleus; 9 msec for conduction, synaptic transmission, and recruitment of retractor bulbi muscle fibers; 4 msec for the nictitating membrane to initiate its sweep after eyeball retraction. The implications of these estimates for chronic unit-recording studies of the conditioned NMR are discussed. PMID:7111447

  14. 5 Years review of periocular basal cell carcinoma and proposed follow-up protocol

    PubMed Central

    Ho, S F; Brown, L; Bamford, M; Sampath, R; Burns, J

    2013-01-01

    Aim (1) To investigate the recurrence of periocular basal cell carcinoma (BCC) reported as completely excised on histology. (2) To identify risks associated with recurrence. (3) To recommend a rational follow-up protocol. Methods This is a cohort study by case note review of consecutive patients undergoing excision of periocular BCC between 2000 and 2006 at University Hospitals of Leicester. All lesions were excised with 3 mm clinical margin and the defect reconstructed only after the excision margin was declared clear. Results A total of 413 episodes of surgical excision were recorded for 270 patients over the 7-year period of 2000–2006. All of them have 5 years follow-up. Mean age 73.7 (±12.5). In all, 67% were nodular BCC and 45.4% located in the lower eyelid. The main outcome measure was the recurrence rate. None of the patients with primary nodular BCC suffered recurrence. The recurrence rate for primary morphoeaform BCC following complete excision is 3.8%. In total, 8.1% of patients had several lesions simultaneously whereas 7.8% patients had BCC in multiple locations subsequently (metachronous). Three patients who had previously recurrent BCC (rBCC) treated elsewhere or not using this method had orbital/lacrimal drainage system involvement requiring exenteration. Conclusion We recommend that patients with a single, completely excised primary solid or nodular BCC can be discharged after one 6-monthly review, although they should be instructed to monitor for the development of further lesions. The incidence of recurrence for primary morphoeaform BCC is 3.8% and for rBCC is 3.6% over 5 years and these patients should stay under review for this period. PMID:23154501

  15. Imiquimod 5% cream as an adjuvant pre-operative treatment for basal cell carcinoma of the periocular area.

    PubMed

    Bonilla, Rosa; Solebo, Ameenat L; Khandwala, Mona A; Jones, Carole A

    2014-12-01

    Despite national guidelines in the UK, patients with low-grade periocular malignancies frequently wait a period of months for their surgery. We have devised a protocol of pre-treatment with an immune modulator in an attempt to reduce the tumour size whilst patients await surgery. We present a case series of 5 patients who used Imiquimod 5% cream (Aldara) for 4 weeks as an adjuvant treatment prior to the excision of periocular nodular basal cell carcinomas. We also assessed tolerability of the cream using a visual analogue scale and recorded adverse events. Our patients had an average 22% reduction in tumour area (range 3.31%-39.64%) whilst awaiting surgery. The medication had a good tolerability profile and there were no ocular adverse events. Due to the promising results, this pilot study demonstrates the feasibility and value of a planned multicentre, prospective research project to further explore these initial findings. PMID:25255050

  16. Periocular cutaneous anthrax in Jimma Zone, Southwest Ethiopia: a case series

    PubMed Central

    2013-01-01

    Background Anthrax is a zoonotic disease caused by Bacillus anthracis. Naturally occurring human infection is rare and is generally the result of contact with anthrax-infected animals or animal products. Case presentation We examined three patients who had contact with presumed anthrax-infected animal and/or its product and presented with preseptal cellulitis with a localized itchy erythematous papule of the eyelid and non-pitting periorbital edema, followed by ulceration and dark eschar formation. All the three patients responded to intravenous antibiotics, and the lesion resolved leaving scars which caused cicatricial ectropion in all cases. Conclusion Anthrax is a rare disease but should be considered in the differential diagnosis of ulcerative (and eschar forming) preseptal cellulitis with a history of contact with anthrax-infected animals or animal products. Furthermore, cicatrization of the eyelids, one of the sequelae of periocular cutaneous anthrax, should be addressed. Urgent case report to the local zoonotic disease and infection control body and other responsible authorities is recommended. PMID:23924443

  17. Expression of p16 and p53 in Intraepithelial Periocular Sebaceous Carcinoma

    PubMed Central

    Bell, W. Robert; Singh, Kamaljeet; Rajan KD, Anand; Eberhart, Charles G.

    2015-01-01

    Purpose Identifying intraepithelial sebaceous carcinoma cells in small periocular biopsies can be difficult, particularly in the conjunctiva. The goal of this study was to evaluate p53 and p16 immunohistochemistry as potential markers of intraepithelial sebaceous carcinoma. Procedures A total of 25 tumors, including 4 recurrent lesions, were stained for p16 and p53, with intensity scored as negative, weak, moderate or strong. Results Expression of p16 was detected in intraepithelial sebaceous carcinoma cells in 24 of the 25 cases (96%), with only 1 case showing weak immunoreactivity. Intraepithelial p53 immunoreactivity was present in 17 of 25 tumors (68%), but was weak in 3 cases. Expression levels remained relatively stable in primary and recurrent tumors, but varied in a few cases between intraepithelial and subepithelial sites. Conclusions Intraepithelial sebaceous carcinomas stained for p53 and p16 demonstrated moderate to strong immunoreactivity in 100% of cases for at least one of these proteins, suggesting that together they are useful markers for determining the extent of tumor spread. Of the two, p16 was immunoreactive in more cases than p53. PMID:27171611

  18. Clinical Assessment of the Safety and Effectiveness of Nonablative Fractional Laser Combined with Transdermal Delivery of Botulinum Toxin A in Treating Periocular Wrinkles.

    PubMed

    Fan, Xing; Yin, Yue; Wang, Shiping; Li, Tong; Xue, Ping; Yang, Qing; Ma, Qiaoxin

    2016-08-01

    The upper and lower eyelids are traditionally contraindicated for subcutaneous botulinum toxin A (BTX) injection because of possible complications. We assessed the clinical safety and effectiveness of nonablative fractional laser (NAFL) combined with transdermal delivery of BTX in the treatment of periocular wrinkles. Thirty patients who had periocular wrinkles were treated with 1,565-nm NAFL in combination in the left periocular area and normal saline in the corresponding area of the right eye. VISIA skin detector was used to photograph and compare the changes induced by treatment. We also recorded the comfort level of the patients. All 28 patients could tolerate the pain caused by the laser treatment and showed no apparent discomfort during percutaneous drug delivery. No chromatosis or ptosis of upper eyelids occurred after the treatment. We used VISIA to detect changes at 1 week, 1 month, 3 months, and 6 months, respectively, after the treatment. The periocular wrinkles decreased, and the flabbiness of eyelids was significantly reduced. The upper and lower eyelids are traditionally contraindicated for subcutaneous BTX injection, as it may cause complications. The treatment combining 1,565-nm NAFL and transdermal delivery of BTX can decrease periocular wrinkles and flabbiness while avoiding complications to the greatest extent. None of the 28 patients who had completed the treatment suffered from complications or adverse effects; all were satisfied with the treatment outcome. PMID:27622085

  19. Clinical Assessment of the Safety and Effectiveness of Nonablative Fractional Laser Combined with Transdermal Delivery of Botulinum Toxin A in Treating Periocular Wrinkles

    PubMed Central

    Yin, Yue; Wang, Shiping; Li, Tong; Xue, Ping; Yang, Qing; Ma, Qiaoxin

    2016-01-01

    Summary: The upper and lower eyelids are traditionally contraindicated for subcutaneous botulinum toxin A (BTX) injection because of possible complications. We assessed the clinical safety and effectiveness of nonablative fractional laser (NAFL) combined with transdermal delivery of BTX in the treatment of periocular wrinkles. Thirty patients who had periocular wrinkles were treated with 1,565-nm NAFL in combination in the left periocular area and normal saline in the corresponding area of the right eye. VISIA skin detector was used to photograph and compare the changes induced by treatment. We also recorded the comfort level of the patients. All 28 patients could tolerate the pain caused by the laser treatment and showed no apparent discomfort during percutaneous drug delivery. No chromatosis or ptosis of upper eyelids occurred after the treatment. We used VISIA to detect changes at 1 week, 1 month, 3 months, and 6 months, respectively, after the treatment. The periocular wrinkles decreased, and the flabbiness of eyelids was significantly reduced. The upper and lower eyelids are traditionally contraindicated for subcutaneous BTX injection, as it may cause complications. The treatment combining 1,565-nm NAFL and transdermal delivery of BTX can decrease periocular wrinkles and flabbiness while avoiding complications to the greatest extent. None of the 28 patients who had completed the treatment suffered from complications or adverse effects; all were satisfied with the treatment outcome. PMID:27622085

  20. Spartans: Single-Sample Periocular-Based Alignment-Robust Recognition Technique Applied to Non-Frontal Scenarios.

    PubMed

    Juefei-Xu, Felix; Luu, Khoa; Savvides, Marios

    2015-12-01

    In this paper, we investigate a single-sample periocular-based alignment-robust face recognition technique that is pose-tolerant under unconstrained face matching scenarios. Our Spartans framework starts by utilizing one single sample per subject class, and generate new face images under a wide range of 3D rotations using the 3D generic elastic model which is both accurate and computationally economic. Then, we focus on the periocular region where the most stable and discriminant features on human faces are retained, and marginalize out the regions beyond the periocular region since they are more susceptible to expression variations and occlusions. A novel facial descriptor, high-dimensional Walsh local binary patterns, is uniformly sampled on facial images with robustness toward alignment. During the learning stage, subject-dependent advanced correlation filters are learned for pose-tolerant non-linear subspace modeling in kernel feature space followed by a coupled max-pooling mechanism which further improve the performance. Given any unconstrained unseen face image, the Spartans can produce a highly discriminative matching score, thus achieving high verification rate. We have evaluated our method on the challenging Labeled Faces in the Wild database and solidly outperformed the state-of-the-art algorithms under four evaluation protocols with a high accuracy of 89.69%, a top score among image-restricted and unsupervised protocols. The advancement of Spartans is also proven in the Face Recognition Grand Challenge and Multi-PIE databases. In addition, our learning method based on advanced correlation filters is much more effective, in terms of learning subject-dependent pose-tolerant subspaces, compared with many well-established subspace methods in both linear and non-linear cases. PMID:26285149

  1. Effect of periocular injection of celecoxib and propranolol on ocular level of vascular endothelial growth factor in a diabetic mouse model

    PubMed Central

    Nassiri, Saman; Houshmand, Gholamreza; Feghhi, Mostafa; Kheirollah, Alireza; Bahadoram, Mohammad; Nassiri, Nariman

    2016-01-01

    AIM To investigate the effects of periocular injection of propranolol and celecoxib on ocular levels of vascular endothelial growth factor (VEGF) in a diabetic mouse model. METHODS Forty 4-6wk BALB-C male mice weighing 20-25 g were used. The study groups included: non-diabetic control (group 1), diabetic control (group 2), diabetic propranolol (group 3), and diabetic celecoxib (group 4). After induction of type 1 diabetes by streptozotocin, propranolol (10 µg) and celecoxib (200 µg dissolved in carboxymethylcellulose 0.5%) were injected periocularly. The ocular level of VEGF was measured in all the study groups using enzyme-linked immuno sorbent assay (ELISA) method. RESULTS Ocular VEGF level was significantly increased (1.25 fold) in the diabetic control group when compared to the non-diabetic group one week after induction with streptozotocin (P=0.002). Both periocular propranolol and celecoxib significantly reduced ocular VEGF levels (P=0.047 and P<0.001, respectively). The effect was more pronounced with celecoxib. CONCLUSION The periocular administration of propranolol and celecoxib can significantly reduce ocular VEGF levels in a diabetic mouse model. PMID:27366681

  2. Periocular and anterior orbital necrosis after upper eyelid gold weight loading: operation-related or self-inflicted?

    PubMed Central

    Schwartz, Roy; Ben Cnaan, Ran; Schein, Ophir; Giladi, Michael; Raz, Michal; Leibovitch, Igal

    2014-01-01

    A 44-year-old woman, who had undergone gold-weight implantation due to facial palsy and lagophthalmos, arrived at the ophthalmology ward with eyelid swelling and erythema, which rapidly deteriorated under intravenous antibiotics to a necrotic process involving the periocular tissues, the eye, and the anterior orbit. Despite prompt removal of the gold weight, the patient’s ocular and systemic condition continued to deteriorate, necessitating evisceration and debridement of necrotic tissue. Cultures showed growth of Staphylococcus epidermidis, Staphylococcus capitis, Candida glabrata, and Candida albicans, and histopathology demonstrated an acute nonspecific necrotizing panophthalmitis. Later on, the patient was admitted to a plastic surgery ward with recurrent severe burns of her thigh, which were highly suggestive of being self-induced, raising the possibility of self-induced damage. PMID:24812491

  3. Hydrologic Record Extension of Water-Level Data in the Everglades Depth Estimation Network (EDEN) Using Artificial Neural Network Models, 2000-2006

    USGS Publications Warehouse

    Conrads, Paul A.; Roehl, Edwin A., Jr.

    2007-01-01

    The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and water-surface models designed to provide scientists, engineers, and water-resource managers with current (2000-present) water-depth information for the entire freshwater portion of the greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystem Science provides support for EDEN and the goal of providing quality assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. To increase the accuracy of the water-surface models, 25 real-time water-level gaging stations were added to the network of 253 established water-level gaging stations. To incorporate the data from the newly added stations to the 7-year EDEN database in the greater Everglades, the short-term water-level records (generally less than 1 year) needed to be simulated back in time (hindcasted) to be concurrent with data from the established gaging stations in the database. A three-step modeling approach using artificial neural network models was used to estimate the water levels at the new stations. The artificial neural network models used static variables that represent the gaging station location and percent vegetation in addition to dynamic variables that represent water-level data from the established EDEN gaging stations. The final step of the modeling approach was to simulate the computed error of the initial estimate to increase the accuracy of the final water-level estimate. The three-step modeling approach for estimating water levels at the new EDEN gaging stations produced satisfactory results. The coefficients of determination (R2) for 21 of the 25 estimates were greater than 0.95, and all of the estimates (25 of 25) were greater than 0.82. The model estimates showed good agreement with the measured data. For some new EDEN stations with limited measured data, the record extension

  4. PlexinD1 is required for proper patterning of the periocular vascular network and for the establishment of corneal avascularity during avian ocular development.

    PubMed

    Kwiatkowski, Sam C; Ojeda, Ana F; Lwigale, Peter Y

    2016-03-01

    The anterior eye is comprised of an avascular cornea surrounded by a dense periocular vascular network and therefore serves as an excellent model for angiogenesis. Although signaling through PlexinD1 underlies various vascular patterning events during embryonic development, its role during the formation of the periocular vascular network is yet to be determined. Our recent study showed that PlexinD1 mRNA is expressed by periocular angioblasts and blood vessels during ocular vasculogenesis in patterns that suggest its involvement with Sema3 ligands that are concurrently expressed in the anterior eye. In this study, we used in vivo knockdown experiments to determine the role of PlexinD1 during vascular patterning in the anterior eye of the developing avian embryos. Knockdown of PlexinD1 in the anterior eye caused mispatterning of the vascular network in the presumptive iris, which was accompanied by lose of vascular integrity and profuse hemorrhaging in the anterior chamber. We also observed ectopic vascularization of the cornea in PlexinD1 knockdown eyes, which coincided with the formation of the limbal vasculature in controls. Finally we show that Sema3E and Sema3C transcripts are expressed in ocular tissue that is devoid of vasculature. These results indicate that PlexinD1 plays a critical role during vascular patterning in the iris and limbus, and is essential for the establishment of corneal avascularity during development. We conclude that PlexinD1 is involved in vascular response to antiangiogenic Sema3 signaling that guides the formation of the iris and limbal blood vessels by inhibiting VEGF signaling. PMID:26783882

  5. Delivery of antifibroblast agents as adjuncts to filtration surgery. Part I--Periocular clearance of cobalt-57 bleomycin in experimental drug delivery: pilot study in the rabbit

    SciTech Connect

    Kay, J.S.; Litin, B.S.; Woolfenden, J.M.; Chvapil, M.; Herschler, J.

    1986-10-01

    Antitumor and antifibroblast agents show promise as adjuncts after glaucoma filtration surgery in reducing postoperative scarring and failure. We used nuclear imaging in rabbits to investigate periocular clearance of one such agent (/sup 57/Co-bleomycin). Sub-Tenon injection was compared to other delivery techniques. Our results showed that a collagen sponge and a silastic disc implant with a microhole prolonged drug delivery when compared to sub-Tenon injection alone or injection with a viscosity enhancing agent (0.5% sodium hyaluronate). We theorize that if an antifibroblast agent can be delivered in small and sustained amounts after filtration surgery, this may prolong bleb longevity and avoid unnecessary drug toxicity.

  6. Contributions of ocular vestibular evoked myogenic potentials and the electrooculogram to periocular potentials produced by whole-body vibration.

    PubMed

    Todd, Neil P M; Bell, Steven L; Paillard, Aurore C; Griffin, Michael J

    2012-11-01

    In this paper we report the results of an experiment to investigate the emergence of ocular vestibular evoked myogenic potentials (OVEMPs) during the linear vestibular ocular reflex (LVOR) evoked by whole-body vibration (WBV). OVEMP and electrooculogram (EOG) montages were employed to record periocular potentials (POPs) from six subjects during WBV in the nasooccipital (NO) axis over a range of frequencies from 0.5 to 64 Hz with approximately constant peak head acceleration of 1.0 ms(-2) (i.e., 0.1 g). Measurements were made in two context conditions: a fixation context to examine the effect of gaze eccentricity (0 vs. 20°), and a visual context, where a target was either head-fixed or earth-fixed. The principal results are that from 0.5 to 2 Hz POP magnitude in the earth-fixed condition is related to head displacement, so with constant acceleration at all frequencies it reduces with increasing frequency, but at frequencies greater than 2 Hz both POP magnitude and POP gain, defined as the ratio of POP magnitude at 20 and 0°, increase with increasing frequency. By exhibiting this high-pass characteristic, a property shared with the LVOR, the results are consistent with the hypothesis that the OVEMP, as commonly employed in the clinical setting, is a high-frequency manifestation of the LVOR. However, we also observed low-frequency acceleration following POPs in head-fixed conditions, consistent with a low-frequency OVEMP, and found evidence of a high-frequency visual context effect, which is also consistent with the OVEMP being a manifestation of the LVOR. PMID:22984251

  7. Contributions of ocular vestibular evoked myogenic potentials and the electrooculogram to periocular potentials produced by whole-body vibration

    PubMed Central

    Bell, Steven L.; Paillard, Aurore C.; Griffin, Michael J.

    2012-01-01

    In this paper we report the results of an experiment to investigate the emergence of ocular vestibular evoked myogenic potentials (OVEMPs) during the linear vestibular ocular reflex (LVOR) evoked by whole-body vibration (WBV). OVEMP and electrooculogram (EOG) montages were employed to record periocular potentials (POPs) from six subjects during WBV in the nasooccipital (NO) axis over a range of frequencies from 0.5 to 64 Hz with approximately constant peak head acceleration of 1.0 ms−2 (i.e., 0.1 g). Measurements were made in two context conditions: a fixation context to examine the effect of gaze eccentricity (0 vs. 20°), and a visual context, where a target was either head-fixed or earth-fixed. The principal results are that from 0.5 to 2 Hz POP magnitude in the earth-fixed condition is related to head displacement, so with constant acceleration at all frequencies it reduces with increasing frequency, but at frequencies greater than 2 Hz both POP magnitude and POP gain, defined as the ratio of POP magnitude at 20 and 0°, increase with increasing frequency. By exhibiting this high-pass characteristic, a property shared with the LVOR, the results are consistent with the hypothesis that the OVEMP, as commonly employed in the clinical setting, is a high-frequency manifestation of the LVOR. However, we also observed low-frequency acceleration following POPs in head-fixed conditions, consistent with a low-frequency OVEMP, and found evidence of a high-frequency visual context effect, which is also consistent with the OVEMP being a manifestation of the LVOR. PMID:22984251

  8. Isolation of Mouse Periocular Tissue for Histological and Immunostaining Analyses of the Extraocular Muscles and Their Satellite Cells.

    PubMed

    Stuelsatz, Pascal; Yablonka-Reuveni, Zipora

    2016-01-01

    The extraocular muscles (EOMs) comprise a group of highly specialized skeletal muscles controlling eye movements. Although a number of unique features of EOMs including their sparing in Duchenne muscular dystrophy have drawn a continuous interest, knowledge about these hard to reach muscles is still limited. The goal of this chapter is to provide detailed methods for the isolation and histological analysis of mouse EOMs. We first introduce in brief the basic anatomy and established nomenclature of the extraocular primary and accessory muscles. We then provide a detailed description with step-by-step images of our procedure for isolating (and subsequently cryosectioning) EOMs while preserving the integrity of their original structural organization. Next, we present several useful histological protocols frequently used by us, including: (1) a method for highlighting the general organization of periocular tissue, using the MyoD(Cre) × R26(mTmG) reporter mouse that elegantly distinguishes muscle (MyoD(Cre)-driven GFP(+)) from the non-myogenic constituents (Tomato(+)); (2) analysis by H&E staining, allowing for example, detection of the pathological features of the dystrophin-null phenotype in affected limb and diaphragm muscles that are absent in EOMs; (3) detection of the myogenic progenitors (i.e., satellite cells) in their native position underneath the myofiber basal lamina using Pax7/laminin double immunostaining. The EOM tissue harvesting procedure described here can also be adapted for isolating and studying satellite cells and other cell types. Overall, the methods described in this chapter should provide investigators the necessary tools for entering the EOM research field and contribute to a better understanding of this highly specialized muscle group and its complex micro-anatomy. PMID:27492169

  9. Leukemia inhibitory factor (LIF) enhances MAP2 + and HUC/D + neurons and influences neurite extension during differentiation of neural progenitors derived from human embryonic stem cells.

    EPA Science Inventory

    Leukemia Inhibitory Factor (L1F), a member of the Interleukin 6 cytokine family, has a role in differentiation of Human Neural Progenitor (hNP) cells in vitro. hNP cells, derived from Human Embryonic Stem (hES) cells, have an unlimited capacity for self-renewal in monolayer cultu...

  10. Generalized Adaptive Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Tawel, Raoul

    1993-01-01

    Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.

  11. Neural control of muscle

    NASA Technical Reports Server (NTRS)

    Max, S. R.; Markelonis, G. J.

    1983-01-01

    Cholinergic innervation regulates the physiological and biochemical properties of skeletal muscle. The mechanisms that appear to be involved in this regulation include soluble, neurally-derived polypeptides, transmitter-evoked muscle activity and the neurotransmitter, acetylcholine, itself. Despite extensive research, the interacting neural mechanisms that control such macromolecules as acetylcholinesterase, the acetylcholine receptor and glucose 6-phosphate dehydrogenase remain unclear. It may be that more simplified in vitro model systems coupled with recent dramatic advances in the molecular biology of neurally-regulated proteins will begin to allow researchers to unravel the mechanisms controlling the expression and maintenance of these macromolecules.

  12. AGRICULTURAL EXTENSION.

    ERIC Educational Resources Information Center

    FARQUHAR, R.N.

    AUSTRALIAN AGRICULTURAL EXTENSION HAS LONG EMPHASIZED TECHNICAL ADVISORY SERVICE AT THE EXPENSE OF THE SOCIOECONOMIC ASPECTS OF FARM PRODUCTION AND FARM LIFE. ONLY IN TASMANIA HAS FARM MANAGEMENT BEEN STRESSED. DEMANDS FOR THE WHOLE-FARM APPROACH HAVE PRODUCED A TREND TOWARD GENERALISM FOR DISTRICT OFFICERS IN MOST STATES. THE FEDERAL GOVERNMENT,…

  13. Viability of full-thickness skin grafts used for correction of cicatricial ectropion of lower eyelid in previously irradiated field in the periocular region

    PubMed Central

    Kim, Hee Joon; Hayek, Brent; Nasser, Qasiem; Esmaeli, Bita

    2013-01-01

    Purpose To evaluate the viability of skin grafts used for correction of cicatricial ectropion resulting from previous ablative surgery and radiotherapy for head and neck cancer and to report overall outcomes of cicatricial ectropion repair. Methods This is a retrospective, non-comparative case series of all consecutive head and neck cancer patients who had been exposed to high-dose radiation therapy in their periocular region and had surgical correction of their lower eyelid cicatricial ectropion through placement of a full-thickness skin graft and a lower eyelid tightening procedure by the same surgeon. The primary outcome measure was skin graft viability. Secondary outcome measures comprised of post-operative complications, the overall outcome of ectropion repair as judged by improvement in symptoms of exposure keratopathy and dependence on lubricating eye drops and ointments, as well as cosmetic improvement measured through a grading scale determined based on the degree of inferior scleral show and/or tarsal conjunctival eversion. Results 25 patients were eligible for the study. 19 men and 6 women had a median age of 63 years (range: 20–84 years). All 25 patients had high-dose radiation therapy for their head and neck cancer. All but 1 patient had major cancer ablative surgery performed prior to radiation therapy. Thirteen of 25 patients also received chemotherapy. There was 100% viability of the skin grafts used for the repair of lower eyelid cicatricial ectropion. There were a few post-operative complications including the need for revision surgery to correct residual ectropion in the lower eyelid in 2 patients and a third patient required a revision surgery due to upper lid retraction and lagophthalmos after harvest of skin graft from the upper eyelid. Improvement was noted in the subjective symptoms in 22 of 25 patients (88%) while 17 patients (68%) were noted to have improvement in their clinical findings on slit lamp examination. All 20 patients for whom

  14. Evolvable synthetic neural system

    NASA Technical Reports Server (NTRS)

    Curtis, Steven A. (Inventor)

    2009-01-01

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

  15. Neural Networks

    SciTech Connect

    Smith, Patrick I.

    2003-09-23

    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

  16. The neural crest: a versatile organ system.

    PubMed

    Zhang, Dongcheng; Ighaniyan, Samiramis; Stathopoulos, Lefteris; Rollo, Benjamin; Landman, Kerry; Hutson, John; Newgreen, Donald

    2014-09-01

    The neural crest is the name given to the strip of cells at the junction between neural and epidermal ectoderm in neurula-stage vertebrate embryos, which is later brought to the dorsal neural tube as the neural folds elevate. The neural crest is a heterogeneous and multipotent progenitor cell population whose cells undergo EMT then extensively and accurately migrate throughout the embryo. Neural crest cells contribute to nearly every organ system in the body, with derivatives of neuronal, glial, neuroendocrine, pigment, and also mesodermal lineages. This breadth of developmental capacity has led to the neural crest being termed the fourth germ layer. The neural crest has occupied a prominent place in developmental biology, due to its exaggerated migratory morphogenesis and its remarkably wide developmental potential. As such, neural crest cells have become an attractive model for developmental biologists for studying these processes. Problems in neural crest development cause a number of human syndromes and birth defects known collectively as neurocristopathies; these include Treacher Collins syndrome, Hirschsprung disease, and 22q11.2 deletion syndromes. Tumors in the neural crest lineage are also of clinical importance, including the aggressive melanoma and neuroblastoma types. These clinical aspects have drawn attention to the selection or creation of neural crest progenitor cells, particularly of human origin, for studying pathologies of the neural crest at the cellular level, and also for possible cell therapeutics. The versatility of the neural crest lends itself to interlinked research, spanning basic developmental biology, birth defect research, oncology, and stem/progenitor cell biology and therapy. PMID:25227568

  17. Neural Engineering

    NASA Astrophysics Data System (ADS)

    He, Bin

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

  18. CT of perineural tumor extension: pterygopalatine fossa

    SciTech Connect

    Curtin, H.D.; Williams, R.; Johnson, J.

    1985-01-01

    Tumors of the oral cavity and paranasal sinuses can spread along nerves to areas apparently removed from the primary tumor. In tumors of the palate, sinuses, and face, this perineural spread usually involves the maxillary division of the trigeminal nerve. The pterygopalatine fossa is a pathway of the maxillary nerve and becomes a key landmark in the detection of neural metastasis by computed tomography (CT). Obliteration of the fat in the fossa suggests pathology. Case material illustrating neural extension is presented and the CT findings are described.

  19. A Neural Model of Mind Wandering.

    PubMed

    Mittner, Matthias; Hawkins, Guy E; Boekel, Wouter; Forstmann, Birte U

    2016-08-01

    The role of the default-mode network (DMN) in the emergence of mind wandering and task-unrelated thought has been studied extensively. In parallel work, mind wandering has been associated with neuromodulation via the locus coeruleus (LC) norepinephrine (LC-NE) system. Here we propose a neural model that links the two systems in an integrative framework. The model attempts to explain how dynamic changes in brain systems give rise to the subjective experience of mind wandering. The model implies a neural and conceptual distinction between an off-focus state and an active mind-wandering state and provides a potential neural grounding for well-known cognitive theories of mind wandering. Finally, the proposed neural model of mind wandering generates precise, testable predictions at neural and behavioral levels. PMID:27353574

  20. Neural crest contributions to the lamprey head

    NASA Technical Reports Server (NTRS)

    McCauley, David W.; Bronner-Fraser, Marianne

    2003-01-01

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

  1. Neural relativity principle

    NASA Astrophysics Data System (ADS)

    Koulakov, Alexei

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

  2. Clustering by Fuzzy Neural Gas and Evaluation of Fuzzy Clusters

    PubMed Central

    Geweniger, Tina; Fischer, Lydia; Kaden, Marika; Lange, Mandy; Villmann, Thomas

    2013-01-01

    We consider some modifications of the neural gas algorithm. First, fuzzy assignments as known from fuzzy c-means and neighborhood cooperativeness as known from self-organizing maps and neural gas are combined to obtain a basic Fuzzy Neural Gas. Further, a kernel variant and a simulated annealing approach are derived. Finally, we introduce a fuzzy extension of the ConnIndex to obtain an evaluation measure for clusterings based on fuzzy vector quantization. PMID:24396342

  3. Neural induction, neural fate stabilization, and neural stem cells.

    PubMed

    Moody, Sally A; Je, Hyun-Soo

    2002-04-28

    The promise of stem cell therapy is expected to greatly benefit the treatment of neurodegenerative diseases. An underlying biological reason for the progressive functional losses associated with these diseases is the extremely low natural rate of self-repair in the nervous system. Although the mature CNS harbors a limited number of self-renewing stem cells, these make a significant contribution to only a few areas of brain. Therefore, it is particularly important to understand how to manipulate embryonic stem cells and adult neural stem cells so their descendants can repopulate and functionally repair damaged brain regions. A large knowledge base has been gathered about the normal processes of neural development. The time has come for this information to be applied to the problems of obtaining sufficient, neurally committed stem cells for clinical use. In this article we review the process of neural induction, by which the embryonic ectodermal cells are directed to form the neural plate, and the process of neural-fate stabilization, by which neural plate cells expand in number and consolidate their neural fate. We will present the current knowledge of the transcription factors and signaling molecules that are known to be involved in these processes. We will discuss how these factors may be relevant to manipulating embryonic stem cells to express a neural fate and to produce large numbers of neurally committed, yet undifferentiated, stem cells for transplantation therapies. PMID:12805974

  4. Improved Adjoint-Operator Learning For A Neural Network

    NASA Technical Reports Server (NTRS)

    Toomarian, Nikzad; Barhen, Jacob

    1995-01-01

    Improved method of adjoint-operator learning reduces amount of computation and associated computational memory needed to make electronic neural network learn temporally varying pattern (e.g., to recognize moving object in image) in real time. Method extension of method described in "Adjoint-Operator Learning for a Neural Network" (NPO-18352).

  5. Advances in Artificial Neural Networks - Methodological Development and Application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other ne...

  6. Electronic Neural Networks

    NASA Technical Reports Server (NTRS)

    Thakoor, Anil

    1990-01-01

    Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

  7. Extensive quantities in thermodynamics

    NASA Astrophysics Data System (ADS)

    Mannaerts, Sebastiaan H.

    2014-05-01

    A literature survey shows little consistency in the definitions of the term ‘extensive quantity’ (a.k.a. extensive property) as used in thermodynamics. A majority assumes that extensive quantities are those that are proportional to mass. Taking the mathematical meaning of proportional and taking the ‘mass’ to be that of the system or subsystem, it is shown that the proportionality assumption is only correct for a few extensive quantities under condition of constant composition. A large subset of extensive quantities are completely independent of mass; for most systems extensive quantities are not proportional to mass, but mass is the (extensive) constant of proportionality. The definition by IUPAC, based on the additivity of extensive quantities, is the preferred baseline for discussing this subject. It is noted however, that two types of additivity need to be distinguished and that a few intensive quantities are also additive. This paper leaves several interesting questions open to further scrutiny.

  8. The Cooperative Extension Service.

    ERIC Educational Resources Information Center

    Sanders, H. C., Ed.

    Designed to stimulate and support training for Extension work and to orient new employees, this book covers the Cooperative Extension Service (CES) and its methods of operation. It begins by describing the status of rural extension in the United States and abroad; the history of the CES and its antecendents; the legal basis, scope, functions, and…

  9. Cooled artery extension

    NASA Technical Reports Server (NTRS)

    Gernert, Nelson J. (Inventor)

    1990-01-01

    An artery vapor trap. A heat pipe artery is constructed with an extension protruding from the evaporator end of the heat pipe beyond the active area of the evaporator. The vapor migrates into the artery extension because of gravity or liquid displacement, and cooling the extension condenses the vapor to liquid, thus preventing vapor lock in the working portion of the artery by removing vapor from within the active artery. The condensed liquid is then transported back to the evaporator by the capillary action of the artery extension itself or by wick located within the extension.

  10. Real-Time Decision Fusion for Multimodal Neural Prosthetic Devices

    PubMed Central

    White, James Robert; Levy, Todd; Bishop, William; Beaty, James D.

    2010-01-01

    Background The field of neural prosthetics aims to develop prosthetic limbs with a brain-computer interface (BCI) through which neural activity is decoded into movements. A natural extension of current research is the incorporation of neural activity from multiple modalities to more accurately estimate the user's intent. The challenge remains how to appropriately combine this information in real-time for a neural prosthetic device. Methodology/Principal Findings Here we propose a framework based on decision fusion, i.e., fusing predictions from several single-modality decoders to produce a more accurate device state estimate. We examine two algorithms for continuous variable decision fusion: the Kalman filter and artificial neural networks (ANNs). Using simulated cortical neural spike signals, we implemented several successful individual neural decoding algorithms, and tested the capabilities of each fusion method in the context of decoding 2-dimensional endpoint trajectories of a neural prosthetic arm. Extensively testing these methods on random trajectories, we find that on average both the Kalman filter and ANNs successfully fuse the individual decoder estimates to produce more accurate predictions. Conclusions Our results reveal that a fusion-based approach has the potential to improve prediction accuracy over individual decoders of varying quality, and we hope that this work will encourage multimodal neural prosthetics experiments in the future. PMID:20209151

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

    PubMed

    Yardley, Nathan; García-Castro, Martín I

    2012-12-15

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

  12. Neural Tube Defects

    MedlinePlus

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

  13. Morphological neural networks

    SciTech Connect

    Ritter, G.X.; Sussner, P.

    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. Optical Neural Interfaces

    PubMed Central

    Warden, Melissa R.; Cardin, Jessica A.; Deisseroth, Karl

    2014-01-01

    Genetically encoded optical actuators and indicators have changed the landscape of neuroscience, enabling targetable control and readout of specific components of intact neural circuits in behaving animals. Here, we review the development of optical neural interfaces, focusing on hardware designed for optical control of neural activity, integrated optical control and electrical readout, and optical readout of population and single-cell neural activity in freely moving mammals. PMID:25014785

  15. Patterns in neural processing

    NASA Astrophysics Data System (ADS)

    Engineer, Sunu

    2012-03-01

    In this paper we propose a model for neural processing that addresses both the evolutionary and functional aspects of neural systems that are observed in nature, from the simplest neural collections to dense large scale associations such as human brains. We propose both an architecture and a process in which these components interact to create the emergent behavior that we define as the 'mind'.

  16. Nested Neural Networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1992-01-01

    Report presents analysis of nested neural networks, consisting of interconnected subnetworks. Analysis based on simplified mathematical models more appropriate for artificial electronic neural networks, partly applicable to biological neural networks. Nested structure allows for retrieval of individual subpatterns. Requires fewer wires and connection devices than fully connected networks, and allows for local reconstruction of damaged subnetworks without rewiring entire network.

  17. Artificial Neural Networks in Policy Research: A Current Assessment.

    ERIC Educational Resources Information Center

    Woelfel, Joseph

    1993-01-01

    Suggests that artificial neural networks (ANNs) exhibit properties that promise usefulness for policy researchers. Notes that ANNs have found extensive use in areas once reserved for multivariate statistical programs such as regression and multiple classification analysis and are developing an extensive community of advocates for processing text…

  18. University of Wisconsin - Extension

    MedlinePlus

    ... Continuing and Online Education About Degree Programs Independent Learning School for Workers UW HELP UW System eCampus Cooperative Extension About Agriculture & Natural Resources Community, Natural Resource & ...

  19. Type Safe Extensible Programming

    NASA Astrophysics Data System (ADS)

    Chae, Wonseok

    2009-10-01

    Software products evolve over time. Sometimes they evolve by adding new features, and sometimes by either fixing bugs or replacing outdated implementations with new ones. When software engineers fail to anticipate such evolution during development, they will eventually be forced to re-architect or re-build from scratch. Therefore, it has been common practice to prepare for changes so that software products are extensible over their lifetimes. However, making software extensible is challenging because it is difficult to anticipate successive changes and to provide adequate abstraction mechanisms over potential changes. Such extensibility mechanisms, furthermore, should not compromise any existing functionality during extension. Software engineers would benefit from a tool that provides a way to add extensions in a reliable way. It is natural to expect programming languages to serve this role. Extensible programming is one effort to address these issues. In this thesis, we present type safe extensible programming using the MLPolyR language. MLPolyR is an ML-like functional language whose type system provides type-safe extensibility mechanisms at several levels. After presenting the language, we will show how these extensibility mechanisms can be put to good use in the context of product line engineering. Product line engineering is an emerging software engineering paradigm that aims to manage variations, which originate from successive changes in software.

  20. Neural Correlates of Predictive Saccades.

    PubMed

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

    2016-08-01

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

  1. Wireless Microstimulators for Neural Prosthetics

    PubMed Central

    Sahin, Mesut; Pikov, Victor

    2016-01-01

    One of the roadblocks in the field of neural prosthetics is the lack of microelectronic devices for neural stimulation that can last a lifetime in the central nervous system. Wireless multi-electrode arrays are being developed to improve the longevity of implants by eliminating the wire interconnects as well as the chronic tissue reactions due to the tethering forces generated by these wires. An area of research that has not been sufficiently investigated is a simple single-channel passive microstimulator that can collect the stimulus energy that is transmitted wirelessly through the tissue and immediately convert it into the stimulus pulse. For example, many neural prosthetic approaches to intraspinal microstimulation require only a few channels of stimulation. Wired spinal cord implants are not practical for human subjects because of the extensive flexions and rotations that the spinal cord experiences. Thus, intraspinal microstimulation may be a pioneering application that can benefit from submillimetersize floating stimulators. Possible means of energizing such a floating microstimulator, such as optical, acoustic, and electromagnetic waves, are discussed. PMID:21488815

  2. Evolvable Neural Software System

    NASA Technical Reports Server (NTRS)

    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.

  3. Signature extension studies

    NASA Technical Reports Server (NTRS)

    Vincent, R. K.; Thomas, G. S.; Nalepka, R. F.

    1974-01-01

    The importance of specific spectral regions to signature extension is explored. In the recent past, the signature extension task was focused on the development of new techniques. Tested techniques are now used to investigate this spectral aspect of the large area survey. Sets of channels were sought which, for a given technique, were the least affected by several sources of variation over four data sets and yet provided good object class separation on each individual data set. Using sets of channels determined as part of this study, signature extension was accomplished between data sets collected over a six-day period and over a range of about 400 kilometers.

  4. Periocular dermatitis artefacta in a child.

    PubMed

    Soong, Terrence Kwong-Weng; Soong, Victor; Samsudin, Amir; Soong, Felicia; Sharma, Vikas; O'Donnell, Niall

    2006-12-01

    Dermatitis artifacta is a factitious dermatological disorder with many forms of presentation in any part of the body. It is commonly documented in dermatological cases but rarely presented as an ophthalmic condition. The diagnosis of dermatitis artifacta is often concluded after rigorous and repeated investigation. Histological sampling of skin lesions is usually required in these cases to exclude masquerading skin lesions such as basal cell carcinoma, vasculitis, or herpetic skin lesions. PMID:17189158

  5. Periocular migration of an intraocular lens.

    PubMed

    Jenkins, C

    1992-11-01

    A woman presented with a painful eye 6 weeks after cataract extraction and intraocular lens implantation. In the past she had had a sector iridectomy for iris bombé caused by chronic anterior uveitis. On examination the three central corneal sutures were absent, whilst the medial and lateral sutures had broken and were protruding from the section. The eye was quiet and the section intact. Combined clinical and ultrasound examination failed to locate the intraocular lens. Four months postoperatively, while being fitted for contact lenses for the correction of aphakia, the intraocular lens appeared from the superior fornix. PMID:1477048

  6. Periocular Reconstruction in Patients with Facial Paralysis.

    PubMed

    Joseph, Shannon S; Joseph, Andrew W; Douglas, Raymond S; Massry, Guy G

    2016-04-01

    Facial paralysis can result in serious ocular consequences. All patients with orbicularis oculi weakness in the setting of facial nerve injury should undergo a thorough ophthalmologic evaluation. The main goal of management in these patients is to protect the ocular surface and preserve visual function. Patients with expected recovery of facial nerve function may only require temporary and conservative measures to protect the ocular surface. Patients with prolonged or unlikely recovery of facial nerve function benefit from surgical rehabilitation of the periorbital complex. Current reconstructive procedures are most commonly intended to improve coverage of the eye but cannot restore blink. PMID:27040589

  7. Improving neural network performance on SIMD architectures

    NASA Astrophysics Data System (ADS)

    Limonova, Elena; Ilin, Dmitry; Nikolaev, Dmitry

    2015-12-01

    Neural network calculations for the image recognition problems can be very time consuming. In this paper we propose three methods of increasing neural network performance on SIMD architectures. The usage of SIMD extensions is a way to speed up neural network processing available for a number of modern CPUs. In our experiments, we use ARM NEON as SIMD architecture example. The first method deals with half float data type for matrix computations. The second method describes fixed-point data type for the same purpose. The third method considers vectorized activation functions implementation. For each method we set up a series of experiments for convolutional and fully connected networks designed for image recognition task.

  8. Exploring neural network technology

    SciTech Connect

    Naser, J.; Maulbetsch, J.

    1992-12-01

    EPRI is funding several projects to explore neural network technology, a form of artificial intelligence that some believe may mimic the way the human brain processes information. This research seeks to provide a better understanding of fundamental neural network characteristics and to identify promising utility industry applications. Results to date indicate that the unique attributes of neural networks could lead to improved monitoring, diagnostic, and control capabilities for a variety of complex utility operations. 2 figs.

  9. Fuzzy and neural control

    NASA Technical Reports Server (NTRS)

    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.

  10. Computing with Neural Synchrony

    PubMed Central

    Brette, Romain

    2012-01-01

    Neurons communicate primarily with spikes, but most theories of neural computation are based on firing rates. Yet, many experimental observations suggest that the temporal coordination of spikes plays a role in sensory processing. Among potential spike-based codes, synchrony appears as a good candidate because neural firing and plasticity are sensitive to fine input correlations. However, it is unclear what role synchrony may play in neural computation, and what functional advantage it may provide. With a theoretical approach, I show that the computational interest of neural synchrony appears when neurons have heterogeneous properties. In this context, the relationship between stimuli and neural synchrony is captured by the concept of synchrony receptive field, the set of stimuli which induce synchronous responses in a group of neurons. In a heterogeneous neural population, it appears that synchrony patterns represent structure or sensory invariants in stimuli, which can then be detected by postsynaptic neurons. The required neural circuitry can spontaneously emerge with spike-timing-dependent plasticity. Using examples in different sensory modalities, I show that this allows simple neural circuits to extract relevant information from realistic sensory stimuli, for example to identify a fluctuating odor in the presence of distractors. This theory of synchrony-based computation shows that relative spike timing may indeed have computational relevance, and suggests new types of neural network models for sensory processing with appealing computational properties. PMID:22719243

  11. A consensual neural network

    NASA Technical Reports Server (NTRS)

    Benediktsson, J. A.; Ersoy, O. K.; Swain, P. H.

    1991-01-01

    A neural network architecture called a consensual neural network (CNN) is proposed for the classification of data from multiple sources. Its relation to hierarchical and ensemble neural networks is discussed. CNN is based on the statistical consensus theory and uses nonlinearly transformed input data. The input data are transformed several times, and the different transformed data are applied as if they were independent inputs. The independent inputs are classified using stage neural networks and outputs from the stage networks are then weighted and combined to make a decision. Experimental results based on remote-sensing data and geographic data are given.

  12. Diagnosing process faults using neural network models

    SciTech Connect

    Buescher, K.L.; Jones, R.D.; Messina, M.J.

    1993-11-01

    In order to be of use for realistic problems, a fault diagnosis method should have the following three features. First, it should apply to nonlinear processes. Second, it should not rely on extensive amounts of data regarding previous faults. Lastly, it should detect faults promptly. The authors present such a scheme for static (i.e., non-dynamic) systems. It involves using a neural network to create an associative memory whose fixed points represent the normal behavior of the system.

  13. What Are Neural Tube Defects?

    MedlinePlus

    ... NICHD Research Information Clinical Trials Resources and Publications Neural Tube Defects (NTDs): Condition Information Skip sharing on ... media links Share this: Page Content What are neural tube defects? Neural (pronounced NOOR-uhl ) tube defects ...

  14. Critical Branching Neural Networks

    ERIC Educational Resources Information Center

    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…

  15. High-performance neural networks. [Neural computers

    SciTech Connect

    Dress, W.B.

    1987-06-01

    The new Forth hardware architectures offer an intermediate solution to high-performance neural networks while the theory and programming details of neural networks for synthetic intelligence are developed. This approach has been used successfully to determine the parameters and run the resulting network for a synthetic insect consisting of a 200-node ''brain'' with 1760 interconnections. Both the insect's environment and its sensor input have thus far been simulated. However, the frequency-coded nature of the Browning network allows easy replacement of the simulated sensors by real-world counterparts.

  16. Is neural Darwinism Darwinism?

    PubMed

    van Belle, T

    1997-01-01

    Neural Darwinism is a theory of cognition developed by Gerald Edelman along with George Reeke and Olaf Sporns at Rockefeller University. As its name suggests, neural Darwinism is modeled after biological Darwinism, and its authors assert that the two processes are strongly analogous. both operate on variation in a population, amplifying the more adaptive individuals. However, from a computational perspective, neural Darwinism is quite different from other models of natural selection, such as genetic algorithms. The individuals of neural Darwinism do not replicate, thus robbing the process of the capacity to explore new solutions over time and ultimately reducing it to a random search. Because neural Darwinism does not have the computational power of a truly Darwinian process, it is misleading to label it as such. to illustrate this disparity in adaptive power, one of Edelman's early computer experiments, Darwin I, is revisited, and it is shown that adding replication greatly improves the adaptive power of the system. PMID:9090158

  17. Mobile Applications for Extension

    ERIC Educational Resources Information Center

    Drill, Sabrina L.

    2012-01-01

    Mobile computing devices (smart phones, tablets, etc.) are rapidly becoming the dominant means of communication worldwide and are increasingly being used for scientific investigation. This technology can further our Extension mission by increasing our power for data collection, information dissemination, and informed decision-making. Mobile…

  18. Extensions of Natural Hamiltonians

    NASA Astrophysics Data System (ADS)

    Rastelli, G.

    2014-03-01

    Given an n-dimensional natural Hamiltonian L on a Riemannian or pseudo-Riemannian manifold, we call "extension" of L the n+1 dimensional Hamiltonian H = ½p2u + α(u)L + β(u) with new canonically conjugated coordinates (u,pu). For suitable L, the functions α and β can be chosen depending on any natural number m such that H admits an extra polynomial first integral in the momenta of degree m, explicitly determined in the form of the m-th power of a differential operator applied to a certain function of coordinates and momenta. In particular, if L is maximally superintegrable (MS) then H is MS also. Therefore, the extension procedure allows the creation of new superintegrable systems from old ones. For m=2, the extra first integral generated by the extension procedure determines a second-order symmetry operator of a Laplace-Beltrami quantization of H, modified by taking in account the curvature of the configuration manifold. The extension procedure can be applied to several Hamiltonian systems, including the three-body Calogero and Wolfes systems (without harmonic term), the Tremblay-Turbiner-Winternitz system and n-dimensional anisotropic harmonic oscillators. We propose here a short review of the known results of the theory and some previews of new ones.

  19. Job Enrichment in Extension.

    ERIC Educational Resources Information Center

    Fourman, Louis S.; Jones, Jo

    1997-01-01

    Interviews with 10 participants in Ohio State University's job enrichment program for midcareer extension agents found that 5 returned to their same jobs after the experience but only 2 felt challenged/renewed. Part-time participation while working made it difficult to balance responsibilities. More information and a structured orientation were…

  20. Identifying High Extension Communicators

    ERIC Educational Resources Information Center

    Lionberger, Herbert F.; Pope, LaVern

    1978-01-01

    Reports results of a survey of social science faculty at the University of Missouri-Columbia to find the extent to which they engaged in communicating information to the public through university extension, with implications for changes in the university rewards system. (MF)

  1. Vocabulary Extension through Poetry.

    ERIC Educational Resources Information Center

    Surajlal, K. C.

    1986-01-01

    Based on the notion that teaching vocabulary extension in isolation makes little impact on students, a three-part exercise, designed to develop students' vocabulary through poetry while providing meaningful enjoyment, uses the poem "The Hawk" by A. C. Benson. In the first class period, students are introduced to both the exercise and the poem and…

  2. Extensive Reading in Japanese

    ERIC Educational Resources Information Center

    Hitosugi, Claire Ikumi; Day, Richard R.

    2004-01-01

    This article discusses how we incorporated an extensive reading (ER) program into a second semester Japanese course at the University of Hawai'i using Japanese children's literature. After summarizing the ten principles of ER, we describe how we addressed six critical issues faced while introducing ER into the course. We also discuss the outcomes…

  3. Extending Extensive Reading

    ERIC Educational Resources Information Center

    Day, Richard R.

    2015-01-01

    The April 2015 issue of "Reading in a Foreign Language" featured a discussion forum on extensive reading (ER). Most of the authors, recognized authorities on ER, discussed their views of the principles of ER, particularly in establishing and conducting ER programs. The purpose of this discussion is to review developments in the practice…

  4. Neural constraints on learning.

    PubMed

    Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

    2014-08-28

    Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already

  5. The homeobox gene Six3 is a potential regulator of anterior segment formation in the chick eye.

    PubMed

    Hsieh, Yi-Wen; Zhang, Xiang-Mei; Lin, Eddie; Oliver, Guillermo; Yang, Xian-Jie

    2002-08-15

    The anterior segment of the vertebrate eye consists of highly organized and specialized ocular tissues critical for normal vision. The periocular mesenchyme, originating from the neural crest, contributes extensively to the anterior segment. During chick eye morphogenesis, the homeobox gene Six3 is expressed in a subset of periocular mesenchymal cells and in differentiating anterior segment tissues. Retrovirus-mediated misexpression of Six3 causes eye anterior segment malformation, including corneal protrusion and opacification, ciliary body and iris hypoplasia, and trabecular meshwork dysgenesis. Histological and molecular marker analyses demonstrate that Six3 misexpression disrupts the integrity of the corneal endothelium and the expression of extracellular matrix components critical for corneal transparency. Six3 misexpression also leads to a reduction of the periocular mesenchymal cell population expressing Lmx1b, Pitx2, and Pax6, transcription factors critical for eye anterior segment morphogenesis. Moreover, elevated levels of Six3 attenuate proliferation of periocular mesenchymal cells in vitro and differentiating anterior segment tissues in vivo. These results suggest that, in addition to its function in eye primordium determination, Six3 plays a role in regulating the development of the vertebrate eye anterior segment. PMID:12167403

  6. Dynamics of neural cryptography

    SciTech Connect

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-15

    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.

  7. WNT/β-catenin signaling mediates human neural crest induction via a pre-neural border intermediate.

    PubMed

    Leung, Alan W; Murdoch, Barbara; Salem, Ahmed F; Prasad, Maneeshi S; Gomez, Gustavo A; García-Castro, Martín I

    2016-02-01

    Neural crest (NC) cells arise early in vertebrate development, migrate extensively and contribute to a diverse array of ectodermal and mesenchymal derivatives. Previous models of NC formation suggested derivation from neuralized ectoderm, via meso-ectodermal, or neural-non-neural ectoderm interactions. Recent studies using bird and amphibian embryos suggest an earlier origin of NC, independent of neural and mesodermal tissues. Here, we set out to generate a model in which to decipher signaling and tissue interactions involved in human NC induction. Our novel human embryonic stem cell (ESC)-based model yields high proportions of multipotent NC cells (expressing SOX10, PAX7 and TFAP2A) in 5 days. We demonstrate a crucial role for WNT/β-catenin signaling in launching NC development, while blocking placodal and surface ectoderm fates. We provide evidence of the delicate temporal effects of BMP and FGF signaling, and find that NC development is separable from neural and/or mesodermal contributions. We further substantiate the notion of a neural-independent origin of NC through PAX6 expression and knockdown studies. Finally, we identify a novel pre-neural border state characterized by early WNT/β-catenin signaling targets that displays distinct responses to BMP and FGF signaling from the traditional neural border genes. In summary, our work provides a fast and efficient protocol for human NC differentiation under signaling constraints similar to those identified in vivo in model organisms, and strengthens a framework for neural crest ontogeny that is separable from neural and mesodermal fates. PMID:26839343

  8. Notch Signaling Maintains Neural Rosette Polarity

    PubMed Central

    Main, Heather; Radenkovic, Jelena; Jin, Shao-bo; Lendahl, Urban; Andersson, Emma R.

    2013-01-01

    Formation of the metazoan body plan requires a complex interplay of morphological changes and patterning, and central to these processes is the establishment of apical/basal cell polarity. In the developing nervous system, apical/basal cell polarity is essential for neural tube closure and maintenance of the neural stem cell population. In this report we explore how a signaling pathway important for nervous system development, Notch signaling, impacts on apical/basal cell polarity in neural differentiation. CSL−/− mouse embryos, which are devoid of canonical Notch signaling, demonstrated a neural tube phenotype consistent with cell polarity and convergent extension defects, including deficiencies in the restricted expression of apical polarity markers in the neuroepithelium. CSL−/− mouse embryonic stem (ES) cells, cultured at low density, behaved as wild-type in the establishment of neural progenitors and apical specification, though progression through rosette formation, an in vitro correlate of neurulation, required CSL for correct maintenance of rosette structure and regulation of neuronal differentiation. Similarly, acute pharmacological inhibition of Notch signaling led to the breakdown of neural rosettes and accelerated neuronal differentiation. In addition to functional Notch signaling, rosette integrity was found to require actin polymerization and Rho kinase (ROCK) activity. Disruption of rosettes through inhibition of actin polymerization or ROCK activity, however, had no effect on neuronal differentiation, indicating that rosette maintenance is not a prerequisite for normal neuronal differentiation. In conclusion, our data indicate that Notch signaling plays a role not only in differentiation, but also in organization and maintenance of polarity during development of the early nervous system. PMID:23675446

  9. Neural networks for aircraft control

    NASA Technical Reports Server (NTRS)

    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.

  10. Geometric neural computing.

    PubMed

    Bayro-Corrochano, E J

    2001-01-01

    This paper shows the analysis and design of feedforward neural networks using the coordinate-free system of Clifford or geometric algebra. It is shown that real-, complex-, and quaternion-valued neural networks are simply particular cases of the geometric algebra multidimensional neural networks and that some of them can also be generated using support multivector machines (SMVMs). Particularly, the generation of radial basis function for neurocomputing in geometric algebra is easier using the SMVM, which allows one to find automatically the optimal parameters. The use of support vector machines in the geometric algebra framework expands its sphere of applicability for multidimensional learning. Interesting examples of nonlinear problems show the effect of the use of an adequate Clifford geometric algebra which alleviate the training of neural networks and that of SMVMs. PMID:18249926

  11. Weakly connected neural nets

    NASA Technical Reports Server (NTRS)

    Zak, Michail

    1990-01-01

    A new neural network architecture is proposed based upon effects of non-Lipschitzian dynamics. The network is fully connected, but these connections are active only during vanishingly short time periods. The advantages of this architecture are discussed.

  12. Neural cryptography with feedback

    NASA Astrophysics Data System (ADS)

    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.

  13. Neural network applications

    NASA Technical Reports Server (NTRS)

    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.

  14. Neural constraints on learning

    PubMed Central

    Sadtler, Patrick T.; Quick, Kristin M.; Golub, Matthew D.; Chase, Steven M.; Ryu, Stephen I.; Tyler-Kabara, Elizabeth C.; Yu, Byron M.; Batista, Aaron P.

    2014-01-01

    Motor, sensory, and cognitive learning require networks of neurons to generate new activity patterns. Because some behaviors are easier to learn than others1,2, we wondered if some neural activity patterns are easier to generate than others. We asked whether the existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define the constraint. We employed a closed-loop intracortical brain-computer interface (BCI) learning paradigm in which Rhesus monkeys controlled a computer cursor by modulating neural activity patterns in primary motor cortex. Using the BCI paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. These patterns comprise a low-dimensional space (termed the intrinsic manifold, or IM) within the high-dimensional neural firing rate space. They presumably reflect constraints imposed by the underlying neural circuitry. We found that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the IM. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the IM. This result suggests that the existing structure of a network can shape learning. On the timescale of hours, it appears to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess3,4. PMID:25164754

  15. Neural alterations from lead exposure in zebrafish.

    PubMed

    Roy, Nicole M; DeWolf, Sarah; Schutt, Alexius; Wright, Ashia; Steele, Latina

    2014-01-01

    Lead was used extensively as a gas additive and pesticide, in paints, batteries, lead shot, pipes, canning and toy manufacturing. Although uses of lead have been restricted, lead persists in our environment especially in older homes, and generally in soil and water. Although extensive studies have determined that fetal and childhood exposures to lead have been associated with childhood and adolescent memory impairments and learning disabilities, there are limited studies investigating early neural and morphological effects that may lead to these behavioral and learning abnormalities. Here we utilize the zebrafish vertebrate model system to study early effects of lead exposure on the brain. We treat embryos with 0.2mM lead for 24, 48 and 72 h and analyze neural structures through live imagery and transgenic approaches. We find structural abnormalities in the hindbrain region as well as changes in branchiomotor neuron development and altered neural vasculature. Additionally, we find areas of increased apoptosis. We conclude that lead is developmentally neurotoxic to a specific region of the brain, the hindbrain and is toxic to branchiomotor neurons residing in rhombomeres 2 through 7 of the hindbrain and hindbrain central artery vasculature. PMID:25242292

  16. Agricultural Extension: Who Uses It?

    ERIC Educational Resources Information Center

    Nolan, Michael; Lasley, Paul

    1979-01-01

    A Missouri study conducted to determine agricultural extension usage patterns found that heavy users of extension publications tended to be younger farmers, those with a relatively large amount of land, and pork producers. Extension meetings were a less frequent source of information than either publications or county extension office visits. (LRA)

  17. LIMB demonstration project extension

    SciTech Connect

    Not Available

    1990-09-21

    The purpose of the DOE limestone injection multistage burner (LIMB) Demonstration Project Extension is to extend the data base on LIMB technology and to expand DOE's list of Clean Coal Technologies by demonstrating the Coolside process as part of the project. The main objectives of this project are: to demonstrate the general applicability of LIMB technology by testing 3 coals and 4 sorbents (total of 12 coal/sorbent combinations) at the Ohio Edison Edgewater plant; and to demonstrate that Coolside is a viable technology for improving precipitator performance and reducing sulfur dioxide emissions while acceptable operability is maintained. Progress is reported. 3 figs.

  18. Portable Extensible Viewer

    NASA Technical Reports Server (NTRS)

    Horowitz, Jay G.

    1997-01-01

    The use of Nonuniform Rational B-Splines (NURBS) to represent geometry and data offers a standard way to facilitate the multidisciplinary analysis and design of aeropropulsion products. Using standard geometry defined by NURBS throughout design, analysis, part definition, manufacture, and test processes saves money and time. The Portable Extensible Viewer (PEV) offers engineers of different disciplines a means to view and manipulate NURBS geometry and associated data. Under the guidance of a team of Lewis, Boeing Company, and Navy personnel, PEV was developed by NASA Lewis Research Center's Computer Services Division for Lewis' Interdisciplinary Technology Office. The aeropropulsion industry provided input to the design requirements.

  19. REVIEW: Optical neural computers based on photorefractive crystals

    NASA Astrophysics Data System (ADS)

    Bel'dyugin, Igor'M.; Zolotarev, M. V.; Sviridov, K. A.

    1992-05-01

    The results are given of recent investigations of the feasibility of using photorefractive crystals in the construction of optical neural computers and of associative memories. The physical basis of the interaction of laser radiation with photorefractive crystals is given and the principles governing the formation of an all-optical neuron and of links (synapses) between neurons in such crystals are discussed. An analysis is made of the learning capabilities of various models of neural networks (Boltzmann machine, perceptron, associatron, neural networks with competition, etc.) and optical systems implementing these models with the aid of photorefractive crystals are described. Extensive experimental data are reported and the results are given of modeling of various tasks (multidimensional optimization, image recognition, etc.) by optical neural computers.

  20. Neural Circuitry and Plasticity Mechanisms Underlying Delay Eyeblink Conditioning

    ERIC Educational Resources Information Center

    Freeman, John H.; Steinmetz, Adam B.

    2011-01-01

    Pavlovian eyeblink conditioning has been used extensively as a model system for examining the neural mechanisms underlying associative learning. Delay eyeblink conditioning depends on the intermediate cerebellum ipsilateral to the conditioned eye. Evidence favors a two-site plasticity model within the cerebellum with long-term depression of…

  1. A Topological Perspective of Neural Network Structure

    NASA Astrophysics Data System (ADS)

    Sizemore, Ann; Giusti, Chad; Cieslak, Matthew; Grafton, Scott; Bassett, Danielle

    The wiring patterns of white matter tracts between brain regions inform functional capabilities of the neural network. Indeed, densely connected and cyclically arranged cognitive systems may communicate and thus perform distinctly. However, previously employed graph theoretical statistics are local in nature and thus insensitive to such global structure. Here we present an investigation of the structural neural network in eight healthy individuals using persistent homology. An extension of homology to weighted networks, persistent homology records both circuits and cliques (all-to-all connected subgraphs) through a repetitive thresholding process, thus perceiving structural motifs. We report structural features found across patients and discuss brain regions responsible for these patterns, finally considering the implications of such motifs in relation to cognitive function.

  2. Endothelial Cells Stimulate Self-Renewal and Expand Neurogenesis of Neural Stem Cells

    NASA Astrophysics Data System (ADS)

    Shen, Qin; Goderie, Susan K.; Jin, Li; Karanth, Nithin; Sun, Yu; Abramova, Natalia; Vincent, Peter; Pumiglia, Kevin; Temple, Sally

    2004-05-01

    Neural stem cells are reported to lie in a vascular niche, but there is no direct evidence for a functional relationship between the stem cells and blood vessel component cells. We show that endothelial cells but not vascular smooth muscle cells release soluble factors that stimulate the self-renewal of neural stem cells, inhibit their differentiation, and enhance their neuron production. Both embryonic and adult neural stem cells respond, allowing extensive production of both projection neuron and interneuron types in vitro. Endothelial coculture stimulates neuroepithelial cell contact, activating Notch and Hes1 to promote self-renewal. These findings identify endothelial cells as a critical component of the neural stem cell niche.

  3. An Improved Transiently Chaotic Neural Network with Application to the Maximum Clique Problems

    NASA Astrophysics Data System (ADS)

    Xu, Xinshun; Tang, Zheng; Wang, Jiahai

    By analyzing the dynamic behaviors of the transiently chaotic neural network, we present a improved transiently chaotic neural network(TCNN) model for combinatorial optimization problems and test it on the maximum clique problem. Extensive simulations are performed and the results show that the improved transiently chaotic neural network model can yield satisfactory results on both some graphs of the DIMACS clique instances in the second DIMACS challenge and p-random graphs. It is superior to other algorithms in light of the solution quality and CPU time. Moreover, the improved model uses fewer steps to converge to saturated states in comparison with the original transiently chaotic neural network.

  4. Non-extensive radiobiology

    SciTech Connect

    Sotolongo-Grau, O.; Rodriguez-Perez, D.; Antoranz, J. C.; Sotolongo-Costa, O.

    2011-03-14

    The expression of survival factors for radiation damaged cells is based on probabilistic assumptions and experimentally fitted for each tumor, radiation and conditions. Here we show how the simplest of these radiobiological models can be derived from the maximum entropy principle of the classical Boltzmann-Gibbs expression. We extend this derivation using the Tsallis entropy and a cutoff hypothesis, motivated by clinical observations. A generalization of the exponential, the logarithm and the product to a non-extensive framework, provides a simple formula for the survival fraction corresponding to the application of several radiation doses on a living tissue. The obtained expression shows a remarkable agreement with the experimental data found in the literature, also providing a new interpretation of some of the parameters introduced anew. It is also shown how the presented formalism may have direct application in radiotherapy treatment optimization through the definition of the potential effect difference, simply calculated between the tumour and the surrounding tissue.

  5. Overlap extension PCR cloning.

    PubMed

    Bryksin, Anton; Matsumura, Ichiro

    2013-01-01

    Rising demand for recombinant proteins has motivated the development of efficient and reliable cloning methods. Here we show how a beginner can clone virtually any DNA insert into a plasmid of choice without the use of restriction endonucleases or T4 DNA ligase. Chimeric primers encoding plasmid sequence at the 5' ends and insert sequence at the 3' ends are designed and synthesized. Phusion(®) DNA polymerase is utilized to amplify the desired insert by PCR. The double-stranded product is subsequently employed as a pair of mega-primers in a PCR-like reaction with circular plasmids. The original plasmids are then destroyed in restriction digests with Dpn I. The product of the overlap extension PCR is used to transform competent Escherichia coli cells. Phusion(®) DNA polymerase is used for both the amplification and fusion reactions, so both steps can be monitored and optimized in the same way. PMID:23996437

  6. Non-extensive radiobiology

    NASA Astrophysics Data System (ADS)

    Sotolongo-Grau, O.; Rodriguez-Perez, D.; Antoranz, J. C.; Sotolongo-Costa, O.

    2011-03-01

    The expression of survival factors for radiation damaged cells is based on probabilistic assumptions and experimentally fitted for each tumor, radiation and conditions. Here we show how the simplest of these radiobiological models can be derived from the maximum entropy principle of the classical Boltzmann-Gibbs expression. We extend this derivation using the Tsallis entropy and a cutoff hypothesis, motivated by clinical observations. A generalization of the exponential, the logarithm and the product to a non-extensive framework, provides a simple formula for the survival fraction corresponding to the application of several radiation doses on a living tissue. The obtained expression shows a remarkable agreement with the experimental data found in the literature, also providing a new interpretation of some of the parameters introduced anew. It is also shown how the presented formalism may have direct application in radiotherapy treatment optimization through the definition of the potential effect difference, simply calculated between the tumour and the surrounding tissue.

  7. Turning an Extension Aide into an Extension Agent

    ERIC Educational Resources Information Center

    Seevers, Brenda; Dormody, Thomas J.

    2010-01-01

    For any organization to remain sustainable, a renewable source of faculty and staff needs to be available. The Extension Internship Program for Juniors and Seniors in High School is a new tool for recruiting and developing new Extension agents. Students get "hands on" experience working in an Extension office and earn college credit while in high…

  8. Neural signatures of autism

    PubMed Central

    Kaiser, Martha D.; Hudac, Caitlin M.; Shultz, Sarah; Lee, Su Mei; Cheung, Celeste; Berken, Allison M.; Deen, Ben; Pitskel, Naomi B.; Sugrue, Daniel R.; Voos, Avery C.; Saulnier, Celine A.; Ventola, Pamela; Wolf, Julie M.; Klin, Ami; Vander Wyk, Brent C.; Pelphrey, Kevin A.

    2010-01-01

    Functional magnetic resonance imaging of brain responses to biological motion in children with autism spectrum disorder (ASD), unaffected siblings (US) of children with ASD, and typically developing (TD) children has revealed three types of neural signatures: (i) state activity, related to the state of having ASD that characterizes the nature of disruption in brain circuitry; (ii) trait activity, reflecting shared areas of dysfunction in US and children with ASD, thereby providing a promising neuroendophenotype to facilitate efforts to bridge genomic complexity and disorder heterogeneity; and (iii) compensatory activity, unique to US, suggesting a neural system–level mechanism by which US might compensate for an increased genetic risk for developing ASD. The distinct brain responses to biological motion exhibited by TD children and US are striking given the identical behavioral profile of these two groups. These findings offer far-reaching implications for our understanding of the neural systems underlying autism. PMID:21078973

  9. Hyperbolic Hopfield neural networks.

    PubMed

    Kobayashi, M

    2013-02-01

    In recent years, several neural networks using Clifford algebra have been studied. Clifford algebra is also called geometric algebra. Complex-valued Hopfield neural networks (CHNNs) are the most popular neural networks using Clifford algebra. The aim of this brief is to construct hyperbolic HNNs (HHNNs) as an analog of CHNNs. Hyperbolic algebra is a Clifford algebra based on Lorentzian geometry. In this brief, a hyperbolic neuron is defined in a manner analogous to a phasor neuron, which is a typical complex-valued neuron model. HHNNs share common concepts with CHNNs, such as the angle and energy. However, HHNNs and CHNNs are different in several aspects. The states of hyperbolic neurons do not form a circle, and, therefore, the start and end states are not identical. In the quantized version, unlike complex-valued neurons, hyperbolic neurons have an infinite number of states. PMID:24808287

  10. Neural tube defects.

    PubMed

    Greene, Nicholas D E; Copp, Andrew J

    2014-01-01

    Neural tube defects (NTDs), including spina bifida and anencephaly, are severe birth defects of the central nervous system that originate during embryonic development when the neural tube fails to close completely. Human NTDs are multifactorial, with contributions from both genetic and environmental factors. The genetic basis is not yet well understood, but several nongenetic risk factors have been identified as have possibilities for prevention by maternal folic acid supplementation. Mechanisms underlying neural tube closure and NTDs may be informed by experimental models, which have revealed numerous genes whose abnormal function causes NTDs and have provided details of critical cellular and morphological events whose regulation is essential for closure. Such models also provide an opportunity to investigate potential risk factors and to develop novel preventive therapies. PMID:25032496

  11. Neural Tube Defects

    PubMed Central

    Greene, Nicholas D.E.; Copp, Andrew J.

    2015-01-01

    Neural tube defects (NTDs), including spina bifida and anencephaly, are severe birth defects of the central nervous system that originate during embryonic development when the neural tube fails to close completely. Human NTDs are multifactorial, with contributions from both genetic and environmental factors. The genetic basis is not yet well understood, but several nongenetic risk factors have been identified as have possibilities for prevention by maternal folic acid supplementation. Mechanisms underlying neural tube closure and NTDs may be informed by experimental models, which have revealed numerous genes whose abnormal function causes NTDs and have provided details of critical cellular and morphological events whose regulation is essential for closure. Such models also provide an opportunity to investigate potential risk factors and to develop novel preventive therapies. PMID:25032496

  12. Cognitive Neural Prosthetics

    PubMed Central

    Andersen, Richard A.; Hwang, Eun Jung; Mulliken, Grant H.

    2010-01-01

    The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations. The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation. We review a number of high-level cortical signals and their application for CNPs, including intention, motor imagery, decision making, forward estimation, executive function, attention, learning, and multi-effector movement planning. CNPs are defined by the cognitive function they extract, not the cortical region from which the signals are recorded. However, some cortical areas may be better than others for particular applications. Signals can also be extracted in parallel from multiple cortical areas using multiple implants, which in many circumstances can increase the range of applications of CNPs. The CNP approach relies on scientific understanding of the neural processes involved in cognition, and many of the decoding algorithms it uses also have parallels to underlying neural circuit functions. PMID:19575625

  13. The ''neural'' phonetic typewriter

    SciTech Connect

    Kohonen, T.

    1988-03-01

    Recently, researchers have placed great hopes on artificial neural networks to perform such ''natural'' tasks as speech recognition. This was indeed one motivation for us to start research in this area many years ago at Helsinki University of Technology. This article describes the result of that research - a complete ''neural'' speech recognition system, which recognizes phonetic units, called phonemes, from a continuous speech signal. Although motivated by neural network principles, the choices in design must be regarded as a compromise of many technical aspects of those principles. As our system is a genuine ''phonetic typewriter'' intended to transcribe orthographically edited text from an unlimited vocabulary, it cannot be directed compared with any more conventional, word-based system that applies classical concepts such as dynamic time warping and hidden Markov models.

  14. Neural Architectures for Control

    NASA Technical Reports Server (NTRS)

    Peterson, James K.

    1991-01-01

    The cerebellar model articulated controller (CMAC) neural architectures are shown to be viable for the purposes of real-time learning and control. Software tools for the exploration of CMAC performance are developed for three hardware platforms, the MacIntosh, the IBM PC, and the SUN workstation. All algorithm development was done using the C programming language. These software tools were then used to implement an adaptive critic neuro-control design that learns in real-time how to back up a trailer truck. The truck backer-upper experiment is a standard performance measure in the neural network literature, but previously the training of the controllers was done off-line. With the CMAC neural architectures, it was possible to train the neuro-controllers on-line in real-time on a MS-DOS PC 386. CMAC neural architectures are also used in conjunction with a hierarchical planning approach to find collision-free paths over 2-D analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The CMAC architectures are trained in real-time for each obstacle field presented. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array. These results are a very good indication of the potential power of the neural architectures in control design. In order to reach as wide an audience as possible, we have run a seminar on neuro-control that has met once per week since 20 May 1991. This seminar has thoroughly discussed the CMAC architecture, relevant portions of classical control, back propagation through time, and adaptive critic designs.

  15. The BGAN extension programme

    NASA Astrophysics Data System (ADS)

    Rivera, Juan J.; Trachtman, Eyal; Richharia, Madhavendra

    2005-11-01

    Mobile satellite telecommunications systems have undergone an enormous evolution in the last decades, with the interest in having advanced telecommunications services available on demand, anywhere and at any time, leading to incredible advances. The demand for braodband data is therefore rapidly gathering pace, but current solutions are finding it increasingly difficult to combine large bandwidth with ubiquitous coverage, reliability and portability. The BGAN (Broadband Global Area Network) system, designed to operate with the Inmarsat-4 satellites, provides breakthrough services that meet all of these requirements. It will enable broadband connection on the move, delivering all the key tools of the modern office. Recognising the great impact that Inmarsat's BGAN system will have on the European satellite communications industry, and the benefits that it will bring to a wide range of European industries, in 2003 ESA initiated the "BGAN Extension" project. Its primary goals are to provide the full range of BGAN services to truly mobile platforms, operating in aeronautical, vehicular and maritime environments, and to introduce a multicast service capability. The project is supported by the ARTES Programme which establishes a collaboration agreement between ESA, Inmarsat and a group of key industrial and academic institutions which includes EMS, Logica, Nera and the University of Surrey (UK).

  16. Extensible Wind Towers

    NASA Astrophysics Data System (ADS)

    Sinagra, Marco; Tucciarelli, Tullio

    The diffusion of wind energy generators is restricted by their strong landscape impact. The PERIMA project is about the development of an extensible wind tower able to support a wind machine for several hundred kW at its optimal working height, up to more than 50 m. The wind tower has a telescopic structure, made by several tubes located inside each other with their axis in vertical direction. The lifting force is given by a jack-up system confined inside a shaft, drilled below the ground level. In the retracted tower configuration, at rest, tower tubes are hidden in the foundation of the telescopic structure, located below the ground surface, and the wind machine is the only emerging part of the system. The lifting system is based on a couple of oleodynamic cylinders that jack-up a central tube connected to the top of the tower by a spring, with a diameter smaller than the minimum tower diameter and with a length a bit greater than the length of the extended telescopic structure. The central tube works as plunger and lifts all telescopic elements. The constraint between the telescopic elements is ensured by special parts, which are kept in traction by the force of the spring and provide the resisting moment. The most evident benefit of the proposed system is attained with the use of a two-blade propeller, which can be kept horizontal in the retracted tower configuration.

  17. Neural Analog Information Processing

    NASA Astrophysics Data System (ADS)

    Hecht-Nielsen, Robert

    1982-07-01

    Neural Analog Information Processing (NAIP) is an effort to develop general purpose pattern classification architectures based upon biological information processing principles. This paper gives an overview of NAIP and its relationship to the previous work in neural modeling from which its fundamental principles are derived. It also presents a theorem concerning the stability of response of a slab (a two dimensional array of identical simple processing units) to time-invariant (spatial) patterns. An experiment (via computer emulation) demonstrating classification of a spatial pattern by a simple, but complete NAIP architecture is described. A concept for hardware implementation of NAIP architectures is briefly discussed.

  18. Imaging the Neural Symphony.

    PubMed

    Svoboda, Karel

    2016-01-01

    Since the start of the new millennium, a method called two-photon microscopy has allowed scientists to peer farther into the brain than ever before. Our author, one of the pioneers in the development of this new technology, writes that "directly observing the dynamics of neural networks in an intact brain has become one of the holy grails of brain research." His article describes the advances that led to this remarkable breakthrough-one that is helping neuroscientists better understand neural networks. PMID:27408677

  19. Nested neural networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1988-01-01

    Nested neural networks, consisting of small interconnected subnetworks, allow for the storage and retrieval of neural state patterns of different sizes. The subnetworks are naturally categorized by layers of corresponding to spatial frequencies in the pattern field. The storage capacity and the error correction capability of the subnetworks generally increase with the degree of connectivity between layers (the nesting degree). Storage of only few subpatterns in each subnetworks results in a vast storage capacity of patterns and subpatterns in the nested network, maintaining high stability and error correction capability.

  20. Neural processing of itch

    PubMed Central

    Akiyama, Tasuku; Carstens, E.

    2013-01-01

    While considerable effort has been made to investigate the neural mechanisms of pain, much less effort has been devoted to itch, at least until recently. However, itch is now gaining increasing recognition as a widespread and costly medical and socioeconomic issue. This is accompanied by increasing interest in the underlying neural mechanisms of itch, which has become a vibrant and rapidly-advancing field of research. The goal of the present forefront review is to describe the recent progress that has been made in our understanding of itch mechanisms. PMID:23891755

  1. Dynamic interactions in neural networks

    SciTech Connect

    Arbib, M.A. ); Amari, S. )

    1989-01-01

    The study of neural networks is enjoying a great renaissance, both in computational neuroscience, the development of information processing models of living brains, and in neural computing, the use of neurally inspired concepts in the construction of intelligent machines. This volume presents models and data on the dynamic interactions occurring in the brain, and exhibits the dynamic interactions between research in computational neuroscience and in neural computing. The authors present current research, future trends and open problems.

  2. Neural nets on the MPP

    NASA Technical Reports Server (NTRS)

    Hastings, Harold M.; Waner, Stefan

    1987-01-01

    The Massively Parallel Processor (MPP) is an ideal machine for computer experiments with simulated neural nets as well as more general cellular automata. Experiments using the MPP with a formal model neural network are described. The results on problem mapping and computational efficiency apply equally well to the neural nets of Hopfield, Hinton et al., and Geman and Geman.

  3. Dissociative States and Neural Complexity

    ERIC Educational Resources Information Center

    Bob, Petr; Svetlak, Miroslav

    2011-01-01

    Recent findings indicate that neural mechanisms of consciousness are related to integration of distributed neural assemblies. This neural integration is particularly vulnerable to past stressful experiences that can lead to disintegration and dissociation of consciousness. These findings suggest that dissociation could be described as a level of…

  4. The Logical Extension

    NASA Technical Reports Server (NTRS)

    2003-01-01

    The same software controlling autonomous and crew-assisted operations for the International Space Station (ISS) is enabling commercial enterprises to integrate and automate manual operations, also known as decision logic, in real time across complex and disparate networked applications, databases, servers, and other devices, all with quantifiable business benefits. Auspice Corporation, of Framingham, Massachusetts, developed the Auspice TLX (The Logical Extension) software platform to effectively mimic the human decision-making process. Auspice TLX automates operations across extended enterprise systems, where any given infrastructure can include thousands of computers, servers, switches, and modems that are connected, and therefore, dependent upon each other. The concept behind the Auspice software spawned from a computer program originally developed in 1981 by Cambridge, Massachusetts-based Draper Laboratory for simulating tasks performed by astronauts aboard the Space Shuttle. At the time, the Space Shuttle Program was dependent upon paper-based procedures for its manned space missions, which typically averaged 2 weeks in duration. As the Shuttle Program progressed, NASA began increasing the length of manned missions in preparation for a more permanent space habitat. Acknowledging the need to relinquish paper-based procedures in favor of an electronic processing format to properly monitor and manage the complexities of these longer missions, NASA realized that Draper's task simulation software could be applied to its vision of year-round space occupancy. In 1992, Draper was awarded a NASA contract to build User Interface Language software to enable autonomous operations of a multitude of functions on Space Station Freedom (the station was redesigned in 1993 and converted into the international venture known today as the ISS)

  5. Neural Tube Defects

    MedlinePlus

    ... The two most common neural tube defects are spina bifida and anencephaly. In spina bifida, the fetal spinal column doesn't close completely. There is usually nerve damage that causes at least some paralysis of the legs. In anencephaly, ... National Institute of Child Health and Human Development

  6. Neural Mechanisms of Cardioprotection

    PubMed Central

    Gourine, Alexander V.

    2014-01-01

    This review highlights the importance of neural mechanisms capable of protecting the heart against lethal ischemia/reperfusion injury. Increased parasympathetic (vagal) activity limits myocardial infarction, and recent data suggest that activation of autonomic reflex pathways contributes to powerful innate mechanisms of cardioprotection underlying the remote ischemic conditioning phenomena. PMID:24583769

  7. Neural Networks and Micromechanics

    NASA Astrophysics Data System (ADS)

    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.

  8. P300 and categorization in brand extension.

    PubMed

    Ma, Qingguo; Wang, Xiaoyi; Shu, Liangchao; Dai, Shenyi

    2008-01-24

    Brand extension is the behavior of applying an established brand to enter new product categories. Its success depends on the perception of attribute similarity between the original brand and the extension product. In this study, 16 participants were required to decide the suitability of extending the brand in stimulus 1 to the product category in stimulus 2 during a S1-S2 paradigm. S1 consists of 15 well-known beverage brands. S2 consists of products in two categories: beverage and non-beverage. P300 - an important component of ERP - was elicited in all probes. The P300 amplitude was larger and distributed over almost all parietal and occipital regions when S2 is a beverage product. The P300 amplitude, however, was smaller and presented predominantly over the right regions when S2 is a non-beverage product. We speculate that the participants' decision process is a categorization process: they tried to classify the product in S2 into brand category in S1. In this process, the brand name in prime evoked the memory of specific products, and the neurons in corresponding cortex areas were activated. The higher similarity and coherence between the brand name in prime and the product name in probe produced an overlap of the similar stimuli in prime and probe, which resulted in larger P300. Otherwise, there is no overlap, resulting in smaller P300. Hence, the P300 may potentially be used in marketing research as an endogenous neural indicator of measuring consumers' attitude towards an intended brand extension. PMID:18155837

  9. Amphioxus and lamprey AP-2 genes: implications for neural crest evolution and migration patterns

    NASA Technical Reports Server (NTRS)

    Meulemans, Daniel; Bronner-Fraser, Marianne

    2002-01-01

    The neural crest is a uniquely vertebrate cell type present in the most basal vertebrates, but not in cephalochordates. We have studied differences in regulation of the neural crest marker AP-2 across two evolutionary transitions: invertebrate to vertebrate, and agnathan to gnathostome. Isolation and comparison of amphioxus, lamprey and axolotl AP-2 reveals its extensive expansion in the vertebrate dorsal neural tube and pharyngeal arches, implying co-option of AP-2 genes by neural crest cells early in vertebrate evolution. Expression in non-neural ectoderm is a conserved feature in amphioxus and vertebrates, suggesting an ancient role for AP-2 genes in this tissue. There is also common expression in subsets of ventrolateral neurons in the anterior neural tube, consistent with a primitive role in brain development. Comparison of AP-2 expression in axolotl and lamprey suggests an elaboration of cranial neural crest patterning in gnathostomes. However, migration of AP-2-expressing neural crest cells medial to the pharyngeal arch mesoderm appears to be a primitive feature retained in all vertebrates. Because AP-2 has essential roles in cranial neural crest differentiation and proliferation, the co-option of AP-2 by neural crest cells in the vertebrate lineage was a potentially crucial event in vertebrate evolution.

  10. Nonlinear signal processing using neural networks: Prediction and system modelling

    SciTech Connect

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  11. Multiple neural network approaches to clinical expert systems

    NASA Astrophysics Data System (ADS)

    Stubbs, Derek F.

    1990-08-01

    We briefly review the concept of computer aided medical diagnosis and more extensively review the the existing literature on neural network applications in the field. Neural networks can function as simple expert systems for diagnosis or prognosis. Using a public database we develop a neural network for the diagnosis of a major presenting symptom while discussing the development process and possible approaches. MEDICAL EXPERTS SYSTEMS COMPUTER AIDED DIAGNOSIS Biomedicine is an incredibly diverse and multidisciplinary field and it is not surprising that neural networks with their many applications are finding more and more applications in the highly non-linear field of biomedicine. I want to concentrate on neural networks as medical expert systems for clinical diagnosis or prognosis. Expert Systems started out as a set of computerized " ifthen" rules. Everything was reduced to boolean logic and the promised land of computer experts was said to be in sight. It never came. Why? First the computer code explodes as the number of " ifs" increases. All the " ifs" have to interact. Second experts are not very good at reducing expertise to language. It turns out that experts recognize patterns and have non-verbal left-brain intuition decision processes. Third learning by example rather than learning by rule is the way natural brains works and making computers work by rule-learning is hideously labor intensive. Neural networks can learn from example. They learn the results

  12. MASPINN: novel concepts for a neuroaccelerator for spiking neural networks

    NASA Astrophysics Data System (ADS)

    Schoenauer, T.; Mehrtash, N.; Jahnke, Andreas; Klar, H.

    1999-03-01

    We present the basic architecture of a Memory Optimized Accelerator for Spiking Neural Networks. The accelerator architecture exploits two novel concepts for an efficient computation of spiking neural networks: weight caching and a compressed memory organization. These concepts allow a further parallelization in processing and reduce bandwidth requirements on accelerator's components. Therefore, they pave the way to dedicated digital hardware for real-time computation of more complex networks of pulse-coded neurons in the order of 106 neurons. The programmable neuron model which the accelerator is based on is described extensively. This shall encourage a discussion and suggestions on features which would be desirable to add to the current model.

  13. Clinical translation of human neural stem cells

    PubMed Central

    2013-01-01

    Human neural stem cell transplants have potential as therapeutic candidates to treat a vast number of disorders of the central nervous system (CNS). StemCells, Inc. has purified human neural stem cells and developed culture conditions for expansion and banking that preserve their unique biological properties. The biological activity of these human central nervous system stem cells (HuCNS-SC®) has been analyzed extensively in vitro and in vivo. When formulated for transplantation, the expanded and cryopreserved banked cells maintain their stem cell phenotype, self-renew and generate mature oligodendrocytes, neurons and astrocytes, cells normally found in the CNS. In this overview, the rationale and supporting data for pursuing neuroprotective strategies and clinical translation in the three components of the CNS (brain, spinal cord and eye) are described. A phase I trial for a rare myelin disorder and phase I/II trial for spinal cord injury are providing intriguing data relevant to the biological properties of neural stem cells, and the early clinical outcomes compel further development. PMID:23987648

  14. Clinical translation of human neural stem cells.

    PubMed

    Tsukamoto, Ann; Uchida, Nobuko; Capela, Alexandra; Gorba, Thorsten; Huhn, Stephen

    2013-01-01

    Human neural stem cell transplants have potential as therapeutic candidates to treat a vast number of disorders of the central nervous system (CNS). StemCells, Inc. has purified human neural stem cells and developed culture conditions for expansion and banking that preserve their unique biological properties. The biological activity of these human central nervous system stem cells (HuCNS-SC®) has been analyzed extensively in vitro and in vivo. When formulated for transplantation, the expanded and cryopreserved banked cells maintain their stem cell phenotype, self-renew and generate mature oligodendrocytes, neurons and astrocytes, cells normally found in the CNS. In this overview, the rationale and supporting data for pursuing neuroprotective strategies and clinical translation in the three components of the CNS (brain, spinal cord and eye) are described. A phase I trial for a rare myelin disorder and phase I/II trial for spinal cord injury are providing intriguing data relevant to the biological properties of neural stem cells, and the early clinical outcomes compel further development. PMID:23987648

  15. The emergent neural modeling system.

    PubMed

    Aisa, Brad; Mingus, Brian; O'Reilly, Randy

    2008-10-01

    Emergent (http://grey.colorado.edu/emergent) is a powerful tool for the simulation of biologically plausible, complex neural systems that was released in August 2007. Inheriting decades of research and experience in network algorithms and modeling principles from its predecessors, PDP++ and PDP, Emergent has been redesigned as an efficient workspace for academic research and an engaging, easy-to-navigate environment for students. The system provides a modern and intuitive interface for programming and visualization centered around hierarchical, tree-based navigation and drag-and-drop reorganization. Emergent contains familiar, high-level simulation constructs such as Layers and Projections, a wide variety of algorithms, general-purpose data handling and analysis facilities and an integrated virtual environment for developing closed-loop cognitive agents. For students, the traditional role of a textbook has been enhanced by wikis embedded in every project that serve to explain, document, and help newcomers engage the interface and step through models using familiar hyperlinks. For advanced users, the software is easily extensible in all respects via runtime plugins, has a powerful shell with an integrated debugger, and a scripting language that is fully symmetric with the interface. Emergent strikes a balance between detailed, computationally expensive spiking neuron models and abstract, Bayesian or symbolic systems. This middle level of detail allows for the rapid development and successful execution of complex cognitive models while maintaining biological plausibility. PMID:18684591

  16. 34. PLAN, PROPOSED EXTENSION OF COAL HOUSE, EXTENSIONS OF ENGINE ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    34. PLAN, PROPOSED EXTENSION OF COAL HOUSE, EXTENSIONS OF ENGINE AND COAL HOUSES, DEER ISLAND PUMPING STATION, METROPOLITAN WATER AND SEWERAGE BOARD, METROPOLITAN SEWARAGE WORKS, JANUARY 1909, SHEET NO. 11. Aperture card 6498-11. - Deer Island Pumping Station, Boston, Suffolk County, MA

  17. 35. WEST END ELEVATION, PROPOSED EXTENSION OF COAL HOUSE, EXTENSIONS ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    35. WEST END ELEVATION, PROPOSED EXTENSION OF COAL HOUSE, EXTENSIONS OF ENGINE AND COAL HOUSES, DEER ISLAND PUMPING STATION, METROPOLITAN WATER AND SEWERAGE BOARD, METROPOLITAN SEWERAGE WORKS, JANUARY 1908, SHEET NO. 7. Aperture card 6498-7. - Deer Island Pumping Station, Boston, Suffolk County, MA

  18. Welding torch gas cup extension

    NASA Technical Reports Server (NTRS)

    Gordon, Stephen S. (Inventor)

    1988-01-01

    The invention relates to a gas shielded electric arc welding torch having a detachable gas cup extension which may be of any desired configuration or length. The gas cup extension assembly is mounted on a standard electric welding torch gas cup to enable welding in areas with limited access. The gas cup assembly has an upper tubular insert that fits within the gas cup such that its lower portion protrudes thereform and has a lower tubular extension that is screwed into the lower portion. The extension has a rim to define the outer perimeter of the seat edge about its entrance opening so a gasket may be placed to effect an airtight seal between the gas cup and extension. The tubular extension may be made of metal or cermaic material that can be machined. The novelty lies in the use of an extension assembly for a standard gas cup of an electric arc welding torch which extension assembly is detachable permitting the use of a number of extensions which may be of different configurations and materials and yet fit the standard gas cup.

  19. Robotic hand with modular extensions

    DOEpatents

    Salisbury, Curt Michael; Quigley, Morgan

    2015-01-20

    A robotic device is described herein. The robotic device includes a frame that comprises a plurality of receiving regions that are configured to receive a respective plurality of modular robotic extensions. The modular robotic extensions are removably attachable to the frame at the respective receiving regions by way of respective mechanical fuses. Each mechanical fuse is configured to trip when a respective modular robotic extension experiences a predefined load condition, such that the respective modular robotic extension detaches from the frame when the load condition is met.

  20. Parallel processing neural networks

    SciTech Connect

    Zargham, M.

    1988-09-01

    A model for Neural Network which is based on a particular kind of Petri Net has been introduced. The model has been implemented in C and runs on the Sequent Balance 8000 multiprocessor, however it can be directly ported to different multiprocessor environments. The potential advantages of using Petri Nets include: (1) the overall system is often easier to understand due to the graphical and precise nature of the representation scheme, (2) the behavior of the system can be analyzed using Petri Net theory. Though, the Petri Net is an obvious choice as a basis for the model, the basic Petri Net definition is not adequate to represent the neuronal system. To eliminate certain inadequacies more information has been added to the Petri Net model. In the model, a token represents either a processor or a post synaptic potential. Progress through a particular Neural Network is thus graphically depicted in the movement of the processor tokens through the Petri Net.

  1. Neural network technologies

    NASA Technical Reports Server (NTRS)

    Villarreal, James A.

    1991-01-01

    A whole new arena of computer technologies is now beginning to form. Still in its infancy, neural network technology is a biologically inspired methodology which draws on nature's own cognitive processes. The Software Technology Branch has provided a software tool, Neural Execution and Training System (NETS), to industry, government, and academia to facilitate and expedite the use of this technology. NETS is written in the C programming language and can be executed on a variety of machines. Once a network has been debugged, NETS can produce a C source code which implements the network. This code can then be incorporated into other software systems. Described here are various software projects currently under development with NETS and the anticipated future enhancements to NETS and the technology.

  2. Implantable microscale neural interfaces.

    PubMed

    Cheung, Karen C

    2007-12-01

    Implantable neural microsystems provide an interface to the nervous system, giving cellular resolution to physiological processes unattainable today with non-invasive methods. Such implantable microelectrode arrays are being developed to simultaneously sample signals at many points in the tissue, providing insight into processes such as movement control, memory formation, and perception. These electrode arrays have been microfabricated on a variety of substrates, including silicon, using both surface and bulk micromachining techniques, and more recently, polymers. Current approaches to achieving a stable long-term tissue interface focus on engineering the surface properties of the implant, including coatings that discourage protein adsorption or release bioactive molecules. The implementation of a wireless interface requires consideration of the necessary data flow, amplification, signal processing, and packaging. In future, the realization of a fully implantable neural microsystem will contribute to both diagnostic and therapeutic applications, such as a neuroprosthetic interface to restore motor functions in paralyzed patients. PMID:17252207

  3. Quantum Neural Nets

    NASA Technical Reports Server (NTRS)

    Zak, Michail; Williams, Colin P.

    1997-01-01

    The capacity of classical neurocomputers is limited by the number of classical degrees of freedom which is roughly proportional to the size of the computer. By Contrast, a Hypothetical quantum neurocomputer can implement an exponentially large number of the degrees of freedom within the same size. In this paper an attempt is made to reconcile linear reversible structure of quantum evolution with nonlinear irreversible dynamics for neural nets.

  4. Neural networks for triggering

    SciTech Connect

    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.

  5. The neural basis of depth perception from motion parallax.

    PubMed

    Kim, HyunGoo R; Angelaki, Dora E; DeAngelis, Gregory C

    2016-06-19

    In addition to depth cues afforded by binocular vision, the brain processes relative motion signals to perceive depth. When an observer translates relative to their visual environment, the relative motion of objects at different distances (motion parallax) provides a powerful cue to three-dimensional scene structure. Although perception of depth based on motion parallax has been studied extensively in humans, relatively little is known regarding the neural basis of this visual capability. We review recent advances in elucidating the neural mechanisms for representing depth-sign (near versus far) from motion parallax. We examine a potential neural substrate in the middle temporal visual area for depth perception based on motion parallax, and we explore the nature of the signals that provide critical inputs for disambiguating depth-sign.This article is part of the themed issue 'Vision in our three-dimensional world'. PMID:27269599

  6. Neural innovations and the diversification of African weakly electric fishes

    PubMed Central

    Arnegard, Matthew E.

    2011-01-01

    In African mormyrid fishes, evolutionary change in a sensory region of the brain established an ability to detect subtle variation in electric communication signals. In one lineage, this newfound perceptual ability triggered a dramatic increase in the rates of signal evolution and species diversification. This particular neural innovation is just one in a series of nested evolutionary novelties that characterize the sensory and motor systems of mormyrids, the most speciose group of extant osteoglossomorph fishes. Here we discuss the behavioral significance of these neural innovations, relate them to differences in extant species diversity, and outline possible scenarios by which some of these traits may have fueled diversification. We propose that sensory and motor capabilities limit the extent to which signals evolve and, by extension, the role of communication behavior in the process of speciation. By expanding these capabilities, neural innovations increase the potential for signal evolution and species diversification. PMID:22446537

  7. On neural networks in identification and control of dynamic systems

    NASA Technical Reports Server (NTRS)

    Phan, Minh; Juang, Jer-Nan; Hyland, David C.

    1993-01-01

    This paper presents a discussion of the applicability of neural networks in the identification and control of dynamic systems. Emphasis is placed on the understanding of how the neural networks handle linear systems and how the new approach is related to conventional system identification and control methods. Extensions of the approach to nonlinear systems are then made. The paper explains the fundamental concepts of neural networks in their simplest terms. Among the topics discussed are feed forward and recurrent networks in relation to the standard state-space and observer models, linear and nonlinear auto-regressive models, linear, predictors, one-step ahead control, and model reference adaptive control for linear and nonlinear systems. Numerical examples are presented to illustrate the application of these important concepts.

  8. Why Do Extension Agents Resign?

    ERIC Educational Resources Information Center

    Manton, Linda Nunes; van Es, J. C.

    1985-01-01

    Past and current Illinois extension agents were surveyed via mail questionnaires as to reasons for staying or leaving extension programs. Reasons for leaving included family changes, family moves, opportunity to advance, better salary/benefits, dissatisfaction with administration, and too much time away from family. (CT)

  9. GNU Fortran Cray Pointer Extension

    Energy Science and Technology Software Center (ESTSC)

    2005-07-27

    The gfortran compiler is a Fortran front end to the GNU Compiler Collection. The Cray Pointer extension adds to this existing compiler support for Cray-style integer pointers. This non-standard but widely used extension adds the functionality of C-like pointers to the Fortran language.

  10. Extension and the Practicing Veterinarian

    ERIC Educational Resources Information Center

    Meyerholz, G. W.

    1974-01-01

    In order for Extension programs of veterinary medicine to succeed, good relationships are needed among university veterinarians, practicing local veterinarians, county Extension agents and the clientele. This author attempts to define some roles and relationships and offer some suggestions for the improvement of relationships to increase…

  11. Extensive Reading Coursebooks in China

    ERIC Educational Resources Information Center

    Renandya, Willy A.; Hu, Guangwei; Xiang, Yu

    2015-01-01

    This article reports on a principle-based evaluation of eight dedicated extensive reading coursebooks published in mainland China and used in many universities across the country. The aim is to determine the extent to which these coursebooks reflect a core set of nine second language acquisition and extensive reading principles. Our analysis shows…

  12. Repeat Customer Success in Extension

    ERIC Educational Resources Information Center

    Bess, Melissa M.; Traub, Sarah M.

    2013-01-01

    Four multi-session research-based programs were offered by two Extension specialist in one rural Missouri county. Eleven participants who came to multiple Extension programs could be called "repeat customers." Based on the total number of participants for all four programs, 25% could be deemed as repeat customers. Repeat customers had…

  13. Energy Crisis vs. Extension Opportunities

    ERIC Educational Resources Information Center

    Liles, Harold R.

    1978-01-01

    Discusses what steps were taken by the Cooperative Extension Service in Oklahoma, after the energy crisis began, to help landowners make better decisions regarding oil and gas leases. Oklahoma's Extension educational efforts in mineral rights management have been successful because they met the needs of the people. (EM)

  14. A practical guide to neural nets

    SciTech Connect

    Nelson, M.M.; Illingworth, W.T.

    1991-01-01

    The concept of neural networks, their operation, and applications are reviewed. Topics discussed include definitions, terminology, and concepts of neural networks, the principal issues and problems addressed by neural network technology, recent developments in the field of artificial intelligence, characteristics and limitations of neural networks, and various neural network architectures. Other topics covered include the basic learning mechanisms of neural networks, examples of neural network applications, implementations of neural networks, some current problems in neural network research, and suggestions for future research. 126 refs.

  15. A fast, streaming SIMD Extensions 2, logistic squashing function.

    PubMed

    Milner, J J; Grandison, A J

    2008-12-01

    Schraudolph proposed an excellent exponential approximation providing increased performance particularly suited to the logistic squashing function used within many neural networking applications. This note applies Intel's streaming SIMD Extensions 2 (SSE2), where SIMD is single instruction multiple data, of the Pentium IV class processor to Schraudolph's technique, further increasing the performance of the logistic squashing function. It was found that the calculation of the new 32-bit SSE2 logistic squashing function described here was up to 38 times faster than the conventional exponential function and up to 16 times faster than a Schraudolph-style 32-bit method on an Intel Pentium D 3.6 GHz CPU. PMID:18624654

  16. Handbook of neural computing applications

    SciTech Connect

    Parten, C.; Hartson, C.; Maren, A. ); Pap, R. )

    1990-01-01

    Here is a comprehensive guide to architectures, processes, implementation methods, and applications of neural computing systems. Unlike purely theoretical books, this handbook shows how to apply neural processing systems to problems in neurophysiology, control theories, learning theory, pattern recognition, and similar areas. This book discusses neural network theories, and shows where they came from, how they can be used, and how they can be developed for future applications.

  17. Accelerating Learning By Neural Networks

    NASA Technical Reports Server (NTRS)

    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.

  18. Neural networks for calibration tomography

    NASA Technical Reports Server (NTRS)

    Decker, Arthur

    1993-01-01

    Artificial neural networks are suitable for performing pattern-to-pattern calibrations. These calibrations are potentially useful for facilities operations in aeronautics, the control of optical alignment, and the like. Computed tomography is compared with neural net calibration tomography for estimating density from its x-ray transform. X-ray transforms are measured, for example, in diffuse-illumination, holographic interferometry of fluids. Computed tomography and neural net calibration tomography are shown to have comparable performance for a 10 degree viewing cone and 29 interferograms within that cone. The system of tomography discussed is proposed as a relevant test of neural networks and other parallel processors intended for using flow visualization data.

  19. Planar cell polarity links axes of spatial dynamics in neural-tube closure.

    PubMed

    Nishimura, Tamako; Honda, Hisao; Takeichi, Masatoshi

    2012-05-25

    Neural-tube closure is a critical step of embryogenesis, and its failure causes serious birth defects. Coordination of two morphogenetic processes--convergent extension and neural-plate apical constriction--ensures the complete closure of the neural tube. We now provide evidence that planar cell polarity (PCP) signaling directly links these two processes. In the bending neural plates, we find that a PCP-regulating cadherin, Celsr1, is concentrated in adherens junctions (AJs) oriented toward the mediolateral axes of the plates. At these AJs, Celsr1 cooperates with Dishevelled, DAAM1, and the PDZ-RhoGEF to upregulate Rho kinase, causing their actomyosin-dependent contraction in a planar-polarized manner. This planar-polarized contraction promotes simultaneous apical constriction and midline convergence of neuroepithelial cells. Together our findings demonstrate that PCP signals confer anisotropic contractility on the AJs, producing cellular forces that promote the polarized bending of the neural plate. PMID:22632972

  20. What works in auditory working memory? A neural oscillations perspective.

    PubMed

    Wilsch, Anna; Obleser, Jonas

    2016-06-01

    Working memory is a limited resource: brains can only maintain small amounts of sensory input (memory load) over a brief period of time (memory decay). The dynamics of slow neural oscillations as recorded using magneto- and electroencephalography (M/EEG) provide a window into the neural mechanics of these limitations. Especially oscillations in the alpha range (8-13Hz) are a sensitive marker for memory load. Moreover, according to current models, the resultant working memory load is determined by the relative noise in the neural representation of maintained information. The auditory domain allows memory researchers to apply and test the concept of noise quite literally: Employing degraded stimulus acoustics increases memory load and, at the same time, allows assessing the cognitive resources required to process speech in noise in an ecologically valid and clinically relevant way. The present review first summarizes recent findings on neural oscillations, especially alpha power, and how they reflect memory load and memory decay in auditory working memory. The focus is specifically on memory load resulting from acoustic degradation. These findings are then contrasted with contextual factors that benefit neural as well as behavioral markers of memory performance, by reducing representational noise. We end on discussing the functional role of alpha power in auditory working memory and suggest extensions of the current methodological toolkit. This article is part of a Special Issue entitled SI: Auditory working memory. PMID:26556773

  1. Chicken trunk neural crest migration visualized with HNK1

    PubMed Central

    Giovannone, Dion; Ortega, Blanca; Reyes, Michelle; El-Ghali, Nancy; Rabadi, Maes; Sao, Sothy; de Bellard, Maria Elena

    2015-01-01

    The development of the nervous system involves cells remaining within the neural tube (CNS) and a group of cells that delaminate from the dorsal neural tube and migrate extensively throughout the developing embryo called neural crest cells (NCC). These cells are a mesenchymal highly migratory group of cells that give rise to a wide variety of cell derivatives: melanocytes, sensory neurons, bone, Schwann cells, etc. But not all NCC can give rise to all derivatives, they have fate restrictions based on their axial level of origin: cranial, vagal, trunk and sacral. Our aim was to provide a thorough presentation on how does trunk neural crest cell migration looks in the chicken embryo, in wholemount and in sections using the unique chicken marker HNK1. The description presented here makes a good guideline for those interested in viewing trunk NCC migration patterns. We show how before HH14 there are few trunk NCC delaminating and migrating, but between HH15 through HH19 trunk NCC delaminate in large numbers. Melanocytes precursors begin to enter the dorsolateral pathway by HH17. We found that by HH20 HNK1 is not a valid good marker for NCC and that HNK1 is a better marker than Sox10 when looking at neural crest cells morphology and migration details. PMID:25805416

  2. Stimulus-dependent Maximum Entropy Models of Neural Population Codes

    PubMed Central

    Segev, Ronen; Schneidman, Elad

    2013-01-01

    Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME) model—a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population. PMID:23516339

  3. Improved Autoassociative Neural Networks

    NASA Technical Reports Server (NTRS)

    Hand, Charles

    2003-01-01

    Improved autoassociative neural networks, denoted nexi, have been proposed for use in controlling autonomous robots, including mobile exploratory robots of the biomorphic type. In comparison with conventional autoassociative neural networks, nexi would be more complex but more capable in that they could be trained to do more complex tasks. A nexus would use bit weights and simple arithmetic in a manner that would enable training and operation without a central processing unit, programs, weight registers, or large amounts of memory. Only a relatively small amount of memory (to hold the bit weights) and a simple logic application- specific integrated circuit would be needed. A description of autoassociative neural networks is prerequisite to a meaningful description of a nexus. An autoassociative network is a set of neurons that are completely connected in the sense that each neuron receives input from, and sends output to, all the other neurons. (In some instantiations, a neuron could also send output back to its own input terminal.) The state of a neuron is completely determined by the inner product of its inputs with weights associated with its input channel. Setting the weights sets the behavior of the network. The neurons of an autoassociative network are usually regarded as comprising a row or vector. Time is a quantized phenomenon for most autoassociative networks in the sense that time proceeds in discrete steps. At each time step, the row of neurons forms a pattern: some neurons are firing, some are not. Hence, the current state of an autoassociative network can be described with a single binary vector. As time goes by, the network changes the vector. Autoassociative networks move vectors over hyperspace landscapes of possibilities.

  4. Neural Flight Control System

    NASA Technical Reports Server (NTRS)

    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.

  5. Neural wiring optimization.

    PubMed

    Cherniak, Christopher

    2012-01-01

    Combinatorial network optimization theory concerns minimization of connection costs among interconnected components in systems such as electronic circuits. As an organization principle, similar wiring minimization can be observed at various levels of nervous systems, invertebrate and vertebrate, including primate, from placement of the entire brain in the body down to the subcellular level of neuron arbor geometry. In some cases, the minimization appears either perfect, or as good as can be detected with current methods. One question such best-of-all-possible-brains results raise is, what is the map of such optimization, does it have a distinct neural domain? PMID:22230636

  6. Chaotic neural control

    NASA Astrophysics Data System (ADS)

    Potapov, A.; Ali, M. K.

    2001-04-01

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

  7. Neurally augmented sexual function.

    PubMed

    Meloy, S

    2007-01-01

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

  8. Putting Extension on a Spot

    ERIC Educational Resources Information Center

    Lawrence, James E.

    1970-01-01

    Between and during television programs from WNBF-TV, Binghamton, New York, the Extension Service is providing public service announcements giving information on nutrition, food stamps, forage pests, outdoor recreation, farm safety, environmental quality, and many other subjects. (EB)

  9. Decentralizing Agricultural Extension: Alternative Strategies.

    ERIC Educational Resources Information Center

    Rivera, William M.

    1997-01-01

    Examines government strategies for decentralizing agricultural extension, concluding that such changes are largely determined by the country's constitutional status. Reviews decentralization guidelines for structural and fiscal reforms and participatory management systems. (SK)

  10. Incremental evolution of the neural crest, neural crest cells and neural crest-derived skeletal tissues

    PubMed Central

    Hall, Brian K; Gillis, J Andrew

    2013-01-01

    Urochordates (ascidians) have recently supplanted cephalochordates (amphioxus) as the extant sister taxon of vertebrates. Given that urochordates possess migratory cells that have been classified as ‘neural crest-like’– and that cephalochordates lack such cells – this phylogenetic hypothesis may have significant implications with respect to the origin of the neural crest and neural crest-derived skeletal tissues in vertebrates. We present an overview of the genes and gene regulatory network associated with specification of the neural crest in vertebrates. We then use these molecular data – alongside cell behaviour, cell fate and embryonic context – to assess putative antecedents (latent homologues) of the neural crest or neural crest cells in ascidians and cephalochordates. Ascidian migratory mesenchymal cells – non-pigment-forming trunk lateral line cells and pigment-forming ‘neural crest-like cells’ (NCLC) – are unlikely latent neural crest cell homologues. Rather, Snail-expressing cells at the neural plate of border of urochordates and cephalochordates likely represent the extent of neural crest elaboration in non-vertebrate chordates. We also review evidence for the evolutionary origin of two neural crest-derived skeletal tissues – cartilage and dentine. Dentine is a bona fide vertebrate novelty, and dentine-secreting odontoblasts represent a cell type that is exclusively derived from the neural crest. Cartilage, on the other hand, likely has a much deeper origin within the Metazoa. The mesodermally derived cellular cartilages of some protostome invertebrates are much more similar to vertebrate cartilage than is the acellular ‘cartilage-like’ tissue in cephalochordate pharyngeal arches. Cartilage, therefore, is not a vertebrate novelty, and a well-developed chondrogenic program was most likely co-opted from mesoderm to the neural crest along the vertebrate stem. We conclude that the neural crest is a vertebrate novelty, but that neural

  11. Boiler-turbine life extension

    SciTech Connect

    Natzkov, S.; Nikolov, M.

    1995-12-01

    The design life of the main power equipment-boilers and turbines is about 105 working hours. The possibilities for life extension are after normatively regulated control tests. The diagnostics and methodology for Boilers and Turbines Elements Remaining Life Assessment using up to date computer programs, destructive and nondestructive control of metal of key elements of units equipment, metal creep and low cycle fatigue calculations. As well as data for most common damages and some technical decisions for elements life extension are presented.

  12. Intraneural Extension of Synovial Sarcoma: Exceptional, or Simply Underrecognized?

    PubMed

    Ng, Wen; Thway, Khin

    2015-12-01

    Intraneural extension of soft tissue sarcomas is uncommon; it is most frequently seen in malignant peripheral nerve sheath tumor, but its occurrence is exceptional in synovial sarcoma. We describe a case arising extraneurally within the deep soft tissues of the forearm, which recurred and resulted in above-elbow amputation, revealing an unexpected finding of diffuse intraneural extension of tumor within a macroscopically normal major nerve. Despite macroscopic and microscopically clear soft tissue margins, the neoplasm had "traveled" a significant distance intraneurally to involve the neural resection margin. This feature does not appear to have been described before; it highlights the issue of whether intraneural spread of synovial sarcoma might have been previously underrecognized, and we discuss briefly some practical implications. PMID:26215219

  13. Conditional deletion of AP-2β in mouse cranial neural crest results in anterior segment dysgenesis and early-onset glaucoma.

    PubMed

    Martino, Vanessa B; Sabljic, Thomas; Deschamps, Paula; Green, Rebecca M; Akula, Monica; Peacock, Erica; Ball, Alexander; Williams, Trevor; West-Mays, Judith A

    2016-08-01

    Anterior segment dysgenesis (ASD) encompasses a group of developmental disorders in which a closed angle phenotype in the anterior chamber of the eye can occur and 50% of patients develop glaucoma. Many ASDs are thought to involve an inappropriate patterning and migration of the periocular mesenchyme (POM), which is derived from cranial neural crest cells (NCCs) and mesoderm. Although, the mechanism of this disruption is not well understood, a number of transcriptional regulatory molecules have previously been implicated in ASDs. Here, we investigate the function of the transcription factor AP-2β, encoded by Tfap2b, which is expressed in NCCs and their derivatives. Wnt1-Cre-mediated conditional deletion of Tfap2b in NCCs resulted in post-natal ocular defects typified by opacity. Histological data revealed that the conditional AP-2β NCC knockout (KO) mutants exhibited dysgenesis of multiple structures in the anterior segment of the eye including defects in the corneal endothelium, corneal stroma, ciliary body and disruption in the iridocorneal angle with adherence of the iris to the cornea. We further show that this phenotype leads to a significant increase in intraocular pressure and a subsequent loss of retinal ganglion cells and optic nerve degeneration, features indicative of glaucoma. Overall, our findings demonstrate that AP-2β is required in the POM for normal development of the anterior segment of the eye and that the AP-2β NCC KO mice might serve as a new and exciting model of ASD and glaucoma that is fully penetrant and with early post-natal onset. PMID:27483349

  14. Conditional deletion of AP-2β in mouse cranial neural crest results in anterior segment dysgenesis and early-onset glaucoma

    PubMed Central

    Martino, Vanessa B.; Sabljic, Thomas; Deschamps, Paula; Green, Rebecca M.; Akula, Monica; Peacock, Erica; Ball, Alexander

    2016-01-01

    ABSTRACT Anterior segment dysgenesis (ASD) encompasses a group of developmental disorders in which a closed angle phenotype in the anterior chamber of the eye can occur and 50% of patients develop glaucoma. Many ASDs are thought to involve an inappropriate patterning and migration of the periocular mesenchyme (POM), which is derived from cranial neural crest cells (NCCs) and mesoderm. Although, the mechanism of this disruption is not well understood, a number of transcriptional regulatory molecules have previously been implicated in ASDs. Here, we investigate the function of the transcription factor AP-2β, encoded by Tfap2b, which is expressed in NCCs and their derivatives. Wnt1-Cre-mediated conditional deletion of Tfap2b in NCCs resulted in post-natal ocular defects typified by opacity. Histological data revealed that the conditional AP-2β NCC knockout (KO) mutants exhibited dysgenesis of multiple structures in the anterior segment of the eye including defects in the corneal endothelium, corneal stroma, ciliary body and disruption in the iridocorneal angle with adherence of the iris to the cornea. We further show that this phenotype leads to a significant increase in intraocular pressure and a subsequent loss of retinal ganglion cells and optic nerve degeneration, features indicative of glaucoma. Overall, our findings demonstrate that AP-2β is required in the POM for normal development of the anterior segment of the eye and that the AP-2β NCC KO mice might serve as a new and exciting model of ASD and glaucoma that is fully penetrant and with early post-natal onset. PMID:27483349

  15. Neural network applications in telecommunications

    NASA Technical Reports Server (NTRS)

    Alspector, Joshua

    1994-01-01

    Neural network capabilities include automatic and organized handling of complex information, quick adaptation to continuously changing environments, nonlinear modeling, and parallel implementation. This viewgraph presentation presents Bellcore work on applications, learning chip computational function, learning system block diagram, neural network equalization, broadband access control, calling-card fraud detection, software reliability prediction, and conclusions.

  16. Space-Time Neural Networks

    NASA Technical Reports Server (NTRS)

    Villarreal, James A.; Shelton, Robert O.

    1992-01-01

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

  17. Neural Networks for the Beginner.

    ERIC Educational Resources Information Center

    Snyder, Robin M.

    Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…

  18. Neural network committees for finger joint angle estimation from surface EMG signals

    PubMed Central

    Shrirao, Nikhil A; Reddy, Narender P; Kosuri, Durga R

    2009-01-01

    Background In virtual reality (VR) systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG) signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals. PMID:19154615

  19. Agricultural extension and mass media.

    PubMed

    Perraton, H

    1983-12-01

    To learn more about the use of the mass media for agricultural extension, the World Bank has considered the efforts of 2 units: INADES-formation in West Africa and the Extension Aids Branch of Malawi. The INADES-formation study focuses on Cameroon but also considers work in Rwanda and the Ivory Coast. Some general conclusions emerge from a comparison of the 2 organizations. Malawi operates an extension service which reaches farmers through extension agents, through farmer training centers, and through mass media. The Extension Aids Branch (EAB) has responsibility for its media work and broadcasts 4 1/2 hours of radio each week. Its 6 regular radio programs include a general program which interviews farmers, a music request program in which the music is interspersed with farming advice, a farming family serial, and a daily broadcast of agricultural news and information. The 17 cinema vans show some agricultural films, made by EAB, some entertainment films, and some government information films from departments other than the ministry of agriculture. EAB also has a well-developed program of research and evaluation of its own work. INADES-formation, the training section of INADES, works towards social and economic development of the population. It teaches peasant farmers and extension agents and does this through running face-to-face seminars, by publishing a magazine, "Agripromo," and through correspondence courses. In 1978-79 INADES-formation enrolled some 4500 farmers and extension agents as students. Both of these organizations work to teach farmers better agriculture techniques, and both were created in response to the fact that agricultural extension agents cannot meet all the farmers in their area. Despite the similarity of objective, there are differences in methods and philosophy. The EAB works in a single country and uses a variety of mass media, with print playing a minor role. INADES-formation is an international and nongovernmental organization and its

  20. Model neural networks

    SciTech Connect

    Kepler, T.B.

    1989-01-01

    After a brief introduction to the techniques and philosophy of neural network modeling by spin glass inspired system, the author investigates several properties of these discrete models for autoassociative memory. Memories are represented as patterns of neural activity; their traces are stored in a distributed manner in the matrix of synaptic coupling strengths. Recall is dynamic, an initial state containing partial information about one of the memories evolves toward that memory. Activity in each neuron creates fields at every other neuron, the sum total of which determines its activity. By averaging over the space of interaction matrices with memory constraints enforced by the choice of measure, we show that the exist universality classes defined by families of field distributions and the associated network capacities. He demonstrates the dominant role played by the field distribution in determining the size of the domains of attraction and present, in two independent ways, an expression for this size. He presents a class of convergent learning algorithms which improve upon known algorithms for producing such interaction matrices. He demonstrates that spurious states, or unexperienced memories, may be practically suppressed by the inducement of n-cycles and chaos. He investigates aspects of chaos in these systems, and then leave discrete modeling to implement the analysis of chaotic behavior on a continuous valued network realized in electronic hardware. In each section he combine analytical calculation and computer simulations.

  1. Uniformly sparse neural networks

    NASA Astrophysics Data System (ADS)

    Haghighi, Siamack

    1992-07-01

    Application of neural networks to problems with a large number of sensory inputs is severely limited when the processing elements (PEs) need to be fully connected. This paper presents a new network model in which a trade off between the number of connections to a node and the number of processing layers can be made. This trade off is an important issue in the VLSI implementation of neural networks. The performance and capability of a hierarchical pyramidal network architecture of limited fan-in PE layers is analyzed. Analysis of this architecture requires the development of a new learning rule, since each PE has access to limited information about the entire network input. A spatially local unsupervised training rule is developed in which each PE optimizes the fraction of its output variance contributed by input correlations, resulting in PEs behaving as adaptive local correlation detectors. It is also shown that the output of a PE optimally represents the mutual information among the inputs to that PE. Applications of the developed model in image compression and motion detection are presented.

  2. Photosensitive-polyimide based method for fabricating various neural electrode architectures

    PubMed Central

    Kato, Yasuhiro X.; Furukawa, Shigeto; Samejima, Kazuyuki; Hironaka, Naoyuki; Kashino, Makio

    2012-01-01

    An extensive photosensitive-polyimide (PSPI)-based method for designing and fabricating various neural electrode architectures was developed. The method aims to broaden the design flexibility and expand the fabrication capability for neural electrodes to improve the quality of recorded signals and integrate other functions. After characterizing PSPI's properties for micromachining processes, we successfully designed and fabricated various neural electrodes even on a non-flat substrate using only one PSPI as an insulation material and without the time-consuming dry etching processes. The fabricated neural electrodes were an electrocorticogram (ECoG) electrode, a mesh intracortical electrode with a unique lattice-like mesh structure to fixate neural tissue, and a guide cannula electrode with recording microelectrodes placed on the curved surface of a guide cannula as a microdialysis probe. In vivo neural recordings using anesthetized rats demonstrated that these electrodes can be used to record neural activities repeatedly without any breakage and mechanical failures, which potentially promises stable recordings for long periods of time. These successes make us believe that this PSPI-based fabrication is a powerful method, permitting flexible design, and easy optimization of electrode architectures for a variety of electrophysiological experimental research with improved neural recording performance. PMID:22719725

  3. A Neural Link Between Feeling and Hearing

    PubMed Central

    Ro, Tony; Ellmore, Timothy M.; Beauchamp, Michael S.

    2013-01-01

    Hearing and feeling both rely upon the transduction of physical events into frequency-based neural codes, suggesting that the auditory system may be intimately related to the somatosensory system. Here, we provide evidence that the neural substrates for audition and somatosensation are anatomically linked. Using diffusion tensor imaging with both deterministic and probabilistic tractography to measure white matter connectivity, we show that there are extensive ipsilateral connections between the primary auditory cortex and the primary and secondary somatosensory regions in the human cerebral cortex. We further show that these cross-modal connections are exaggerated between the auditory and secondary somatosensory cortex in the lesioned hemisphere of a patient (SR) with acquired auditory-tactile synesthesia, in whom sounds alone produce bodily sensations. These results provide an anatomical basis for multisensory interactions between audition and somatosensation and suggest that cross-talk between these regions may explain why some sounds, such as nails screeching down a chalkboard or an audible mosquito, can induce feelings of touch, especially on the contralesional body surface of patient SR. PMID:22693344

  4. Continuous neural network with windowed Hebbian learning.

    PubMed

    Fotouhi, M; Heidari, M; Sharifitabar, M

    2015-06-01

    We introduce an extension of the classical neural field equation where the dynamics of the synaptic kernel satisfies the standard Hebbian type of learning (synaptic plasticity). Here, a continuous network in which changes in the weight kernel occurs in a specified time window is considered. A novelty of this model is that it admits synaptic weight decrease as well as the usual weight increase resulting from correlated activity. The resulting equation leads to a delay-type rate model for which the existence and stability of solutions such as the rest state, bumps, and traveling fronts are investigated. Some relations between the length of the time window and the bump width is derived. In addition, the effect of the delay parameter on the stability of solutions is shown. Also numerical simulations for solutions and their stability are presented. PMID:25677526

  5. Extension for prevention: margin placement.

    PubMed

    Larson, Thomas D

    2012-01-01

    This article will review the concept of extension for prevention popularized by G.V. Black around the early 1900s. Concepts of extension and prevention have changed over the years with a more informed knowledge of the caries process, improved materials, cutting instruments, and techniques. The reasons for placement of the outline form relative to the tooth morphology, gingival tissue, relationship to adjacent teeth, and the choice of material will be described for all of the materials used in restorative dentistry. Research will be cited to support the scientific basis for outline form placement. PMID:22662468

  6. Fuzzy Neural Networks for water level and discharge forecasting

    NASA Astrophysics Data System (ADS)

    Alvisi, Stefano; Franchini, Marco

    2010-05-01

    A new procedure for water level (or discharge) forecasting under uncertainty using artificial neural networks is proposed: uncertainty is expressed in the form of a fuzzy number. For this purpose, the parameters of the neural network, namely, the weights and biases, are represented by fuzzy numbers rather than crisp numbers. Through the application of the extension principle, the fuzzy number representative of the output variable (water level or discharge) is then calculated at each time step on the basis of a set of crisp inputs and fuzzy parameters of the neural network. The proposed neural network thus allows uncertainty to be taken into account at the forecasting stage not providing only deterministic or crisp predictions, but rather predictions in terms of 'the discharge (or level) will fall between two values, indicated according to the level of credibility considered, whereas it will take on a certain value when the level of credibility is maximum'. The fuzzy parameters of the neural network are estimated using a calibration procedure that imposes a constraint whereby for an assigned h-level the envelope of the corresponding intervals representing the outputs (forecasted levels or discharges, calculated at different points in time) must include a prefixed percentage of observed values. The proposed model is applied to two different case studies. Specifically, the data related to the first case study are used to develop and test a flood event-based water level forecasting model, whereas the data related to the latter are used for continuous discharge forecasting. The results obtained are compared with those provided by other data-driven models - Bayesian neural networks (Neal, R.M. 1992, Bayesian training of backpropagation networks by the hybrid Monte Carlo method. Tech. Rep. CRG-TR-92-1, Dep. of Comput. Sci., Univ. of Toronto, Toronto, Ont., Canada.) and the Local Uncertainty Estimation Model (Shrestha D.L. and Solomatine D.P. 2006, Machine learning

  7. Synchronization in neural nets

    NASA Technical Reports Server (NTRS)

    Vidal, Jacques J.; Haggerty, John

    1988-01-01

    The paper presents an artificial neural network concept (the Synchronizable Oscillator Networks) where the instants of individual firings in the form of point processes constitute the only form of information transmitted between joining neurons. In the model, neurons fire spontaneously and regularly in the absence of perturbation. When interaction is present, the scheduled firings are advanced or delayed by the firing of neighboring neurons. Networks of such neurons become global oscillators which exhibit multiple synchronizing attractors. From arbitrary initial states, energy minimization learning procedures can make the network converge to oscillatory modes that satisfy multi-dimensional constraints. Such networks can directly represent routing and scheduling problems that consist of ordering sequences of events.

  8. Neural circuitry and immunity.

    PubMed

    Pavlov, Valentin A; Tracey, Kevin J

    2015-12-01

    Research during the last decade has significantly advanced our understanding of the molecular mechanisms at the interface between the nervous system and the immune system. Insight into bidirectional neuro-immune communication has characterized the nervous system as an important partner of the immune system in the regulation of inflammation. Neuronal pathways, including the vagus nerve-based inflammatory reflex, are physiological regulators of immune function and inflammation. In parallel, neuronal function is altered in conditions characterized by immune dysregulation and inflammation. Here, we review these regulatory mechanisms and describe the neural circuitry modulating immunity. Understanding these mechanisms reveals possibilities to use targeted neuromodulation as a therapeutic approach for inflammatory and autoimmune disorders. These findings and current clinical exploration of neuromodulation in the treatment of inflammatory diseases define the emerging field of Bioelectronic Medicine. PMID:26512000

  9. Interacting neural networks.

    PubMed

    Metzler, R; Kinzel, W; Kanter, I

    2000-08-01

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

  10. Neural Crest Lineage Segregation

    PubMed Central

    Luan, X.; Dangaria, S.; Ito, Y.; Walker, C.G.; Jin, T.; Schmidt, M.K.; Galang, M.T.; Druzinsky, R.

    2009-01-01

    During the recent decade, the periodontal attachment apparatus has become one of the premier areas of the body for the development of novel tissue-engineering strategies. In the present review, we describe a developmental biology approach to characterize current concepts in periodontal regeneration and to discuss strategies for future applications in periodontal therapies. To decipher the developmental make-up of the periodontal region, we have followed the path of the migratory neural crest, since it gives rise to periodontal progenitor tissues, which in turn are subjected to the influence of diverse craniofacial extracellular matrices and peptide growth factors. Based on this developmental perspective, we have conducted a systematic analysis of the factors, progenitor cells, and matrices used in current periodontal tissue-engineering approaches. We propose that the developmental history of a tissue is a highly instructive design template for the discovery of novel bioengineering tools and approaches. PMID:19767574

  11. Artificial neural superposition eye.

    PubMed

    Brückner, Andreas; Duparré, Jacques; Dannberg, Peter; Bräuer, Andreas; Tünnermann, Andreas

    2007-09-17

    We propose an ultra-thin imaging system which is based on the neural superposition compound eye of insects. Multiple light sensitive pixels in the footprint of each lenslet of this multi-channel configuration enable the parallel imaging of the individual object points. Together with the digital superposition of related signals this multiple sampling enables advanced functionalities for artificial compound eyes. Using this technique, color imaging and a circumvention for the trade-off between resolution and sensitivity of ultra-compact camera devices have been demonstrated in this article. The optical design and layout of such a system is discussed in detail. Experimental results are shown which indicate the attractiveness of microoptical artificial compound eyes for applications in the field of machine vision, surveillance or automotive imaging. PMID:19547555

  12. Deinterlacing using modular neural network

    NASA Astrophysics Data System (ADS)

    Woo, Dong H.; Eom, Il K.; Kim, Yoo S.

    2004-05-01

    Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.

  13. Neural mechanisms in asthma.

    PubMed

    Joos, G F; Germonpré, P R; Pauwels, R A

    2000-06-01

    Advances in the understanding of neural mechanisms in asthma may provide novel therapeutic approaches in the treatment of asthma. Excessive activity of cholinergic nerves may be important in asthma. Dysfunction of M2 muscarinic receptors in asthma may lead to excessive bronchoconstriction and mucus secretion and can be induced in animal models by a range of stimuli including allergen, viral infection, ozone, eosinophil products and cytokines. Cholinergic mechanisms may be especially important in certain types of patients and anticholinergic agents provide protection against bronchospasm due to psychogenic factors or beta2-blockers. Non-adrenergic non-cholinergic (NANC) mechanisms, both inhibitory (i-NANC) and excitatory (e-NANC), may play a significant role in the pathophysiology of asthma. The putative neurotransmitters, vasoactive interstinal polypeptide (VIP) and nitric oxide (NO), mediate neural bronchodilation in human airways. There does not appear to be a defect in the i-NANC system in moderate or severe asthma. e-NANC is mediated by the sensory neuropeptides substance P (SP) and the more potent bronchoconstrictor neurokinin A (NKA). Various studies suggest that the SP content of human airways is increased in asthma. Tachykinins are not only present in sensory nerves, but also are produced by inflammatory cells such as alveolar macrophages, dendritic cells, eosinophils, lymphocytes and neutrophils. They can be released into the airways by stimuli such as allergen and ozone. Evidence suggests that in addition to smooth muscle contraction, which is mediated mainly by NK2 receptors, tachykinins also cause mucus secretion, plasma extravasation and stimulate inflammatory and immune cells. These effects are mediated by NK1 receptors. Recent studies have shown that NK2 receptor antagonists such as saredutant partially inhibit NKA-induced bronchoconstriction in asthmatics. Thus, tachykinin receptor antagonists have potential as therapies for asthma. PMID:10849478

  14. Common and Segregated Neural Substrates for Automatic Conceptual and Affective Priming as Revealed by Event-Related Functional Magnetic Resonance Imaging

    ERIC Educational Resources Information Center

    Liu, Hongyan; Hu, Zhiguo; Peng, Danling; Yang, Yanhui; Li, Kuncheng

    2010-01-01

    The brain activity associated with automatic semantic priming has been extensively studied. Thus far there has been no prior study that directly contrasts the neural mechanisms of semantic and affective priming. The present study employed event-related fMRI to examine the common and distinct neural bases underlying conceptual and affective priming…

  15. Program Helps Simulate Neural Networks

    NASA Technical Reports Server (NTRS)

    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.

  16. Creative-Dynamics Approach To Neural Intelligence

    NASA Technical Reports Server (NTRS)

    Zak, Michail A.

    1992-01-01

    Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

  17. Rule Induction with Extension Matrices.

    ERIC Educational Resources Information Center

    Wu, Xindong

    1998-01-01

    Presents a heuristic, attribute-based, noise-tolerant data mining program, HCV (Version 2.0) based on the newly-developed extension matrix approach. Outlines some techniques implemented in the HCV program for noise handling and discretization of continuous domains; an empirical comparison shows that rules generated by HCV are more compact than the…

  18. Effective Public Relations in Extension.

    ERIC Educational Resources Information Center

    Hogan, Mike

    1994-01-01

    Public relations efforts of the Carroll County (Ohio) extension office included periodic reports to legislators, a toll-free number distributed on refrigerator magnets, annual calendar/report to the public, newspaper supplements, and town meetings. Long-term effects were a 116% increase in funding, used to upgrade staff, programs, and…

  19. Removing the Tension from Extension

    ERIC Educational Resources Information Center

    Bradley, Lucy; Driscoll, Elizabeth; Bardon, Robert

    2012-01-01

    Job burnout and stress begin with day-to-day frustrations, roadblocks, and unmet expectations. These can transform job satisfaction and, ultimately, career choices, affecting the quality of programs, expense to universities, and relationships with the community. A series of innovative statewide workshops involving 97 agents and Extension directors…

  20. Strategic Opportunities for Cooperative Extension

    ERIC Educational Resources Information Center

    National Association of State Universities and Land-Grant Colleges, 2007

    2007-01-01

    In this new century, opportunities exist to help advance America's greatness in the midst of many challenges. Energy, water, food, environment, health, economic productivity, global competitiveness, and the quality of the living environments are all paramount to the future. Extension is, as a part of higher education, prepared to create new…

  1. Slope Extensions to ASL Library

    Energy Science and Technology Software Center (ESTSC)

    2010-03-31

    Extensions to the AMPL/solver interface library (http://netlib.sandia.gov/ampl/solvers) to compute bounds on algebraic expressions, plus a test program. use in uncertainty quantification and global optimization algorithms. This software is not primarily for military applications.

  2. Modular, Hierarchical Learning By Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Baldi, Pierre F.; Toomarian, Nikzad

    1996-01-01

    Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

  3. Neural components of altruistic punishment

    PubMed Central

    Du, Emily; Chang, Steve W. C.

    2015-01-01

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

  4. Genetic Dissection of Neural Circuits

    PubMed Central

    Luo, Liqun; Callaway, Edward M.; Svoboda, Karel

    2009-01-01

    Understanding the principles of information processing in neural circuits requires systematic characterization of the participating cell types and their connections, and the ability to measure and perturb their activity. Genetic approaches promise to bring experimental access to complex neural systems, including genetic stalwarts such as the fly and mouse, but also to nongenetic systems such as primates. Together with anatomical and physiological methods, cell-type-specific expression of protein markers and sensors and transducers will be critical to construct circuit diagrams and to measure the activity of genetically defined neurons. Inactivation and activation of genetically defined cell types will establish causal relationships between activity in specific groups of neurons, circuit function, and animal behavior. Genetic analysis thus promises to reveal the logic of the neural circuits in complex brains that guide behaviors. Here we review progress in the genetic analysis of neural circuits and discuss directions for future research and development. PMID:18341986

  5. Neural variability: friend or foe?

    PubMed

    Dinstein, Ilan; Heeger, David J; Behrmann, Marlene

    2015-06-01

    Although we may not realize it, our brain function varies markedly from moment to moment such that our brain responses exhibit substantial variability across trials even in response to a simple repeating stimulus. Should we care about such within-subject variability? Are there developmental, cognitive, and clinical consequences to having a brain that is more or less variable/noisy? Although neural variability seems to be beneficial for learning, excessive levels of neural variability are apparent in individuals with different clinical disorders. We propose that measuring distinct types of neural variability in autism and other disorders is likely to reveal crucial insights regarding their neuropathology. We further discuss the importance of studying neural variability more generally across development and aging in humans. PMID:25979849

  6. Demultiplexer circuit for neural stimulation

    DOEpatents

    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.

  7. Neural stimulation with optical radiation

    PubMed Central

    Richter, Claus-Peter; Matic, Agnella Izzo; Wells, Jonathon D.; Jansen, E. Duco; Walsh, Joseph T.

    2012-01-01

    This paper reviews the existing research on infrared neural stimulation, a means of artificially stimulating neurons that has been proposed as an alternative to electrical stimulation. Infrared neural stimulation (INS) is defined as the direct induction of an evoked potential in response to a transient targeted deposition of optical energy. The foremost advantage of using optical radiation for neural stimulation is its spatial resolution. Exogenously applied or trans-genetically synthesized fluorophores are not used to achieve stimulation. Here, current work on INS is presented for motor nerves, sensory nerves, central nervous system, and in vitro preparations. A discussion follows addressing the mechanism of INS and its potential use in neuroprostheses. A brief review of neural depolarization involving other optical methods is also presented. Topics covered include optical stimulation concurrent with electrical stimulation, optical stimulation using exogenous fluorophores, and optical stimulation by transgenic induction of light-gated ion channels. PMID:23082105

  8. Neural stimulation with optical radiation.

    PubMed

    Richter, Claus-Peter; Matic, Agnella Izzo; Wells, Jonathon D; Jansen, E Duco; Walsh, Joseph T

    2011-01-01

    This paper reviews the existing research on infrared neural stimulation, a means of artificially stimulating neurons that has been proposed as an alternative to electrical stimulation. Infrared neural stimulation (INS) is defined as the direct induction of an evoked potential in response to a transient targeted deposition of optical energy. The foremost advantage of using optical radiation for neural stimulation is its spatial resolution. Exogenously applied or trans-genetically synthesized fluorophores are not used to achieve stimulation. Here, current work on INS is presented for motor nerves, sensory nerves, central nervous system, and in vitro preparations. A discussion follows addressing the mechanism of INS and its potential use in neuroprostheses. A brief review of neural depolarization involving other optical methods is also presented. Topics covered include optical stimulation concurrent with electrical stimulation, optical stimulation using exogenous fluorophores, and optical stimulation by transgenic induction of light-gated ion channels. PMID:23082105

  9. Neural Networks Of VLSI Components

    NASA Technical Reports Server (NTRS)

    Eberhardt, Silvio P.

    1991-01-01

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

  10. Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks

    SciTech Connect

    Ziaul Huque

    2007-08-31

    This is the final technical report for the project titled 'Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks'. The aim of the project was to develop an efficient chemistry model for combustion simulations. The reduced chemistry model was developed mathematically without the need of having extensive knowledge of the chemistry involved. To aid in the development of the model, Neural Networks (NN) was used via a new network topology known as Non-linear Principal Components Analysis (NPCA). A commonly used Multilayer Perceptron Neural Network (MLP-NN) was modified to implement NPCA-NN. The training rate of NPCA-NN was improved with the GEneralized Regression Neural Network (GRNN) based on kernel smoothing techniques. Kernel smoothing provides a simple way of finding structure in data set without the imposition of a parametric model. The trajectory data of the reaction mechanism was generated based on the optimization techniques of genetic algorithm (GA). The NPCA-NN algorithm was then used for the reduction of Dimethyl Ether (DME) mechanism. DME is a recently discovered fuel made from natural gas, (and other feedstock such as coal, biomass, and urban wastes) which can be used in compression ignition engines as a substitute for diesel. An in-house two-dimensional Computational Fluid Dynamics (CFD) code was developed based on Meshfree technique and time marching solution algorithm. The project also provided valuable research experience to two graduate students.

  11. Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks

    SciTech Connect

    Nelson Butuk

    2004-12-01

    This is an annual technical report for the work done over the last year (period ending 9/30/2004) on the project titled ''Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks''. The aim of the project is to develop an efficient chemistry model for combustion simulations. The reduced chemistry model will be developed mathematically without the need of having extensive knowledge of the chemistry involved. To aid in the development of the model, Neural Networks (NN) will be used via a new network topology know as Non-linear Principal Components Analysis (NPCA). We report on the development of a procedure to speed up the training of NPCA. The developed procedure is based on the non-parametric statistical technique of kernel smoothing. When this smoothing technique is implemented as a Neural Network, It is know as Generalized Regression Neural Network (GRNN). We present results of implementing GRNN on a test problem. In addition, we present results of an in house developed 2-D CFD code that will be used through out the project period.

  12. Prediction of beta-turns in proteins using neural networks.

    PubMed

    McGregor, M J; Flores, T P; Sternberg, M J

    1989-05-01

    The use of neural networks to improve empirical secondary structure prediction is explored with regard to the identification of the position and conformational class of beta-turns, a four-residue chain reversal. Recently an algorithm was developed for beta-turn predictions based on the empirical approach of Chou and Fasman using different parameters for three classes (I, II and non-specific) of beta-turns. In this paper, using the same data, an alternative approach to derive an empirical prediction method is used based on neural networks which is a general learning algorithm extensively used in artificial intelligence. Thus the results of the two approaches can be compared. The most severe test of prediction accuracy is the percentage of turn predictions that are correct and the neural network gives an overall improvement from 20.6% to 26.0%. The proportion of correctly predicted residues is 71%, compared to a chance level of about 58%. Thus neural networks provide a method of obtaining more accurate predictions from empirical data than a simpler method of deriving propensities. PMID:2748568

  13. Simulation of dynamic processes with adaptive neural networks.

    SciTech Connect

    Tzanos, C. P.

    1998-02-03

    Many industrial processes are highly non-linear and complex. Their simulation with first-principle or conventional input-output correlation models is not satisfactory, either because the process physics is not well understood, or it is so complex that direct simulation is either not adequately accurate, or it requires excessive computation time, especially for on-line applications. Artificial intelligence techniques (neural networks, expert systems, fuzzy logic) or their combination with simple process-physics models can be effectively used for the simulation of such processes. Feedforward (static) neural networks (FNNs) can be used effectively to model steady-state processes. They have also been used to model dynamic (time-varying) processes by adding to the network input layer input nodes that represent values of input variables at previous time steps. The number of previous time steps is problem dependent and, in general, can be determined after extensive testing. This work demonstrates that for dynamic processes that do not vary fast with respect to the retraining time of the neural network, an adaptive feedforward neural network can be an effective simulator that is free of the complexities introduced by the use of input values at previous time steps.

  14. Mechanical heterogeneities and lithospheric extension

    NASA Astrophysics Data System (ADS)

    Duretz, Thibault; Petri, Benoit; Mohn, Geoffroy; Schenker, Filippo L.; Schmalholz, Stefan

    2016-04-01

    Detailed geological and geophysical studies of passive margins have highlighted the multi-stage and depth-dependent aspect of lithospheric thinning. Lithospheric thinning involves a variety of structures (normal faults, low angle detachments, extensional shear zones, extraction faults) and leads to a complex architecture of passive margins (with e.g. necking zone, mantle exhumation, continental allochthons). The processes controlling the generation and evolution of these structures as well as the impact of pre-rift inheritance are so far incompletely understood. In this study, we investigate the impact of pre-rift inheritance on the development of rifted margins using two-dimensional thermo-mechanical models of lithospheric thinning. To first order, we represent the pre-rift mechanical heterogeneities with lithological layering. The rheologies are kept simple (visco-plastic) and do not involve any strain softening mechanism. Our models show that mechanical layering causes multi-stage and depth-dependent extension. In the initial rifting phase, lithospheric extension is decoupled: as the crust undergoes thinning by brittle (frictional-plastic) faults, the lithospheric mantle accommodates extension by symmetric ductile necking. In a second rifting phase, deformation in the crust and lithospheric mantle is coupled and marks the beginning of an asymmetric extension stage. Low angle extensional shear zones develop across the lithosphere and exhume subcontinental mantle. Furthemore, crustal allochthons and adjacent basins develop coevally. We describe as well the thermal evolution predicted by the numerical models and discuss the first-order implications of our results in the context of the Alpine geological history.

  15. Ductile extension in alpine Corsica

    NASA Astrophysics Data System (ADS)

    Jolivet, Laurent; Dubois, Roland; Fournier, Marc; Goffé, Bruno; Michard, André; Jourdan, Claudie

    1990-10-01

    Ductile deformation in high-pressure (P)-low temperature (T) conditions due to the westward thrusting of oceanic material onto a continental basement in alpine Corsica is overprinted by a late deformation event with a reverse shear sense (eastward) that took place in less severe P-T conditions. We show that the late deformation can be linked to extension during rifting and spreading of the Liguro Provençal basin from late Oligocene to late-middle Miocene time. Major compressive thrust contacts were reactivated as ductile normal faults and, in some units, only a penetrative eastward shear can be observed. This extension following the thickening of the crust brought tectonic units which underwent very different P- T conditions during the earlier stage into close contact. The Balagne nappe, which shows neither significant ductile deformation nor metamorphism, directly overlies the high-P units. The extensional deformation is distributed through the entire thickness of the nappe stack but is more important along the major thrust contacts, which localize the strain. The geometry of the crustal extension is controlled by that of the early compressive thrusts. The latest structures are east-dipping brittle normal faults which bound the early to middle Miocene Saint Florent half graben.

  16. Interval neural networks

    SciTech Connect

    Patil, R.B.

    1995-05-01

    Traditional neural networks like multi-layered perceptrons (MLP) use example patterns, i.e., pairs of real-valued observation vectors, ({rvec x},{rvec y}), to approximate function {cflx f}({rvec x}) = {rvec y}. To determine the parameters of the approximation, a special version of the gradient descent method called back-propagation is widely used. In many situations, observations of the input and output variables are not precise; instead, we usually have intervals of possible values. The imprecision could be due to the limited accuracy of the measuring instrument or could reflect genuine uncertainty in the observed variables. In such situation input and output data consist of mixed data types; intervals and precise numbers. Function approximation in interval domains is considered in this paper. We discuss a modification of the classical backpropagation learning algorithm to interval domains. Results are presented with simple examples demonstrating few properties of nonlinear interval mapping as noise resistance and finding set of solutions to the function approximation problem.

  17. Correlational Neural Networks.

    PubMed

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

    2016-02-01

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

  18. An approximate internal model-based neural control for unknown nonlinear discrete processes.

    PubMed

    Li, Han-Xiong; Deng, Hua

    2006-05-01

    An approximate internal model-based neural control (AIMNC) strategy is proposed for unknown nonaffine nonlinear discrete processes under disturbed environment. The proposed control strategy has some clear advantages in respect to existing neural internal model control methods. It can be used for open-loop unstable nonlinear processes or a class of systems with unstable zero dynamics. Based on a novel input-output approximation, the proposed neural control law can be derived directly and implemented straightforward for an unknown process. Only one neural network needs to be trained and control algorithm can be directly obtained from model identification without further training. The stability and robustness of a closed-loop system can be derived analytically. Extensive simulations demonstrate the superior performance of the proposed AIMNC strategy. PMID:16722170

  19. Coal Combustion Products Extension Program

    SciTech Connect

    Tarunjit S. Butalia; William E. Wolfe

    2004-12-31

    The primary objective of the CCP Extension Program is to promote the responsible uses of Ohio CCPs that are technically sound, environmentally safe, and commercially competitive. A secondary objective is to assist other CCP generating states (particularly neighboring states) in establishing CCP use programs within their states. The goal of the CCP extension program at OSU is to work with CCP stakeholders to increase the overall CCP state utilization rate to more than 30% by the year 2005. The program aims to increase FGD utilization for Ohio to more than 20% by the year 2005. The increased utilization rates are expected to be achieved through increased use of CCPs for highway, mine reclamation, agricultural, manufacturing, and other civil engineering uses. In order to accomplish these objectives and goals, the highly successful CCP pilot extension program previously in place at the university has been expanded and adopted by the university as a part of its outreach and engagement mission. The extension program is an innovative technology transfer program with multiple sponsors. The program is a collaborative effort between The Ohio State University (College of Engineering and University Extension Service), United States Department of Energy's National Energy Technology Laboratory, Ohio Department of Development's Coal Development Office, and trade associations such as the American Coal Ash Association as well as the Midwest Coal Ash Association. Industry co-sponsors include American Electric Power, Dravo Lime Company, and ISG Resources. Implementation of the proposed project results in both direct and indirect as well as societal benefits. These benefits include (1) increased utilization of CCPs instead of landfilling, (2) development of proper construction and installation procedures, (3) education of regulators, specification-writers, designers, construction contractors, and the public, (4) emphasis on recycling and decrease in the need for landfill space, (5

  20. COAL COMBUSTION PRODUCTS EXTENSION PROGRAM

    SciTech Connect

    Tarunjit S. Butalia; William E. Wolfe

    2005-05-15

    The primary objective of the CCP Extension Program is to promote the responsible uses of Ohio CCPs that are technically sound, environmentally safe, and commercially competitive. A secondary objective is to assist other CCP generating states (particularly neighboring states) in establishing CCP use programs within their states. The goal of the CCP extension program at OSU is to work with CCP stakeholders to increase the overall CCP state utilization rate to more than 30% by the year 2005. The program aims to increase FGD utilization for Ohio to more than 20% by the year 2005. The increased utilization rates are expected to be achieved through increased use of CCPs for highway, mine reclamation, agricultural, manufacturing, and other civil engineering uses. In order to accomplish these objectives and goals, the highly successful CCP pilot extension program previously in place at the university has been expanded and adopted by the university as a part of its outreach and engagement mission. The extension program is an innovative technology transfer program with multiple sponsors. The program is a collaborative effort between The Ohio State University (College of Engineering and University Extension Service), United States Department of Energy's National Energy Technology Laboratory, Ohio Department of Development's Coal Development Office, and trade associations such as the American Coal Ash Association as well as the Midwest Coal Ash Association. Industry co-sponsors include American Electric Power, Dravo Lime Company, and ISG Resources. Implementation of the proposed project results in both direct and indirect as well as societal benefits. These benefits include (1) increased utilization of CCPs instead of landfilling, (2) development of proper construction and installation procedures, (3) education of regulators, specification-writers, designers, construction contractors, and the public, (4) emphasis on recycling and decrease in the need for landfill space, (5

  1. Coal Combustion Products Extension Program

    SciTech Connect

    Tarunjit S. Butalia; William E. Wolfe

    2003-12-31

    The primary objective of the CCP Extension Program is to promote the responsible uses of Ohio CCPs that are technically sound, environmentally safe, and commercially competitive. A secondary objective is to assist other CCP generating states (particularly neighboring states) in establishing CCP use programs within their states. The goal of the CCP extension program at OSU is to work with CCP stakeholders to increase the overall CCP state utilization rate to more than 30% by the year 2005. The program aims to increase FGD utilization for Ohio to more than 20% by the year 2005. The increased utilization rates are expected to be achieved through increased use of CCPs for highway, mine reclamation, agricultural, manufacturing, and other civil engineering uses. In order to accomplish these objectives and goals, the highly successful CCP pilot extension program previously in place at the university has been expanded and adopted by the university as a part of its outreach and engagement mission. The extension program is an innovative technology transfer program with multiple sponsors. The program is a collaborative effort between The Ohio State University (College of Engineering and University Extension Service), United States Department of Energy's National Energy Technology Laboratory, Ohio Department of Development's Coal Development Office, and trade associations such as the American Coal Ash Association as well as the Midwest Coal Ash Association. Industry co-sponsors include American Electric Power, Dravo Lime Company, and ISG Resources. Implementation of the proposed project results in both direct and indirect as well as societal benefits. These benefits include (1) increased utilization of CCPs instead of landfilling, (2) development of proper construction and installation procedures, (3) education of regulators, specification-writers, designers, construction contractors, and the public, (4) emphasis on recycling and decrease in the need for landfill space, (5

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

    PubMed Central

    Padmanabhan, Rangarajan; Taneyhill, Lisa A.

    2015-01-01

    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. PMID:25795298

  3. A depictive neural model for the representation of motion verbs.

    PubMed

    Rao, Sunil; Aleksander, Igor

    2011-11-01

    In this paper, we present a depictive neural model for the representation of motion verb semantics in neural models of visual awareness. The problem of modelling motion verb representation is shown to be one of function application, mapping a set of given input variables defining the moving object and the path of motion to a defined output outcome in the motion recognition context. The particular function-applicative implementation and consequent recognition model design presented are seen as arising from a noun-adjective recognition model enabling the recognition of colour adjectives as applied to a set of shapes representing objects to be recognised. The presence of such a function application scheme and a separately implemented position identification and path labelling scheme are accordingly shown to be the primitives required to enable the design and construction of a composite depictive motion verb recognition scheme. Extensions to the presented design to enable the representation of transitive verbs are also discussed. PMID:21468746

  4. Prenatal Music Exposure Induces Long-Term Neural Effects

    PubMed Central

    Partanen, Eino; Kujala, Teija; Tervaniemi, Mari; Huotilainen, Minna

    2013-01-01

    We investigated the neural correlates induced by prenatal exposure to melodies using brains' event-related potentials (ERPs). During the last trimester of pregnancy, the mothers in the learning group played the ‘Twinkle twinkle little star’ -melody 5 times per week. After birth and again at the age of 4 months, we played the infants a modified melody in which some of the notes were changed while ERPs to unchanged and changed notes were recorded. The ERPs were also recorded from a control group, who received no prenatal stimulation. Both at birth and at the age of 4 months, infants in the learning group had stronger ERPs to the unchanged notes than the control group. Furthermore, the ERP amplitudes to the changed and unchanged notes at birth were correlated with the amount of prenatal exposure. Our results show that extensive prenatal exposure to a melody induces neural representations that last for several months. PMID:24205353

  5. Systematic fluctuation expansion for neural network activity equations

    PubMed Central

    Buice, Michael A.; Cowan, Jack D.; Chow, Carson C.

    2009-01-01

    Population rate or activity equations are the foundation of a common approach to modeling for neural networks. These equations provide mean field dynamics for the firing rate or activity of neurons within a network given some connectivity. The shortcoming of these equations is that they take into account only the average firing rate while leaving out higher order statistics like correlations between firing. A stochastic theory of neural networks which includes statistics at all orders was recently formulated. We describe how this theory yields a systematic extension to population rate equations by introducing equations for correlations and appropriate coupling terms. Each level of the approximation yields closed equations, i.e. they depend only upon the mean and specific correlations of interest, without an ad hoc criterion for doing so. We show in an example of an all-to-all connected network how our system of generalized activity equations captures phenomena missed by the mean field rate equations alone. PMID:19852585

  6. Neural circuits underlying the generation of theta oscillations.

    PubMed

    Pignatelli, Michele; Beyeler, Anna; Leinekugel, Xavier

    2012-01-01

    Theta oscillations represent the neural network configuration underlying active awake behavior and paradoxical sleep. This major EEG pattern has been extensively studied, from physiological to anatomical levels, for more than half a century. Nevertheless the cellular and network mechanisms accountable for the theta generation are still not fully understood. This review synthesizes the current knowledge on the circuitry involved in the generation of theta oscillations, from the hippocampus to extra hippocampal structures such as septal complex, entorhinal cortex and pedunculopontine tegmentum, a main trigger of theta state through direct and indirect projections to the septal complex. We conclude with a short overview of the perspectives offered by technical advances for deciphering more precisely the different neural components underlying the emergence of theta oscillations. PMID:21964249

  7. A training algorithm for binary feedforward neural networks.

    PubMed

    Gray, D L; Michel, A N

    1992-01-01

    The authors present a new training algorithm to be used on a four-layer perceptron-type feedforward neural network for the generation of binary-to-binary mappings. This algorithm is called the Boolean-like training algorithm (BLTA) and is derived from original principles of Boolean algebra followed by selected extensions. The algorithm can be implemented on analog hardware, using a four-layer binary feedforward neural network (BFNN). The BLTA does not constitute a traditional circuit building technique. Indeed, the rules which govern the BLTA allow for generalization of data in the face of incompletely specified Boolean functions. When compared with techniques which employ descent methods, training times are greatly reduced in the case of the BLTA. Also, when the BFNN is used in conjunction with A/D converters, the applicability of the present algorithm can be extended to accept real-valued inputs. PMID:18276419

  8. Prenatal music exposure induces long-term neural effects.

    PubMed

    Partanen, Eino; Kujala, Teija; Tervaniemi, Mari; Huotilainen, Minna

    2013-01-01

    We investigated the neural correlates induced by prenatal exposure to melodies using brains' event-related potentials (ERPs). During the last trimester of pregnancy, the mothers in the learning group played the 'Twinkle twinkle little star'-melody 5 times per week. After birth and again at the age of 4 months, we played the infants a modified melody in which some of the notes were changed while ERPs to unchanged and changed notes were recorded. The ERPs were also recorded from a control group, who received no prenatal stimulation. Both at birth and at the age of 4 months, infants in the learning group had stronger ERPs to the unchanged notes than the control group. Furthermore, the ERP amplitudes to the changed and unchanged notes at birth were correlated with the amount of prenatal exposure. Our results show that extensive prenatal exposure to a melody induces neural representations that last for several months. PMID:24205353

  9. General University Extension. Bulletin, 1926, No. 5

    ERIC Educational Resources Information Center

    Shelby, Thomas H.

    1926-01-01

    This report concerns itself with the growth and progress of "general" university extension for the biennial period 1922-1924. By general university extension is meant extension activities of universities and colleges in the fields not covered by agricultural and home economics extension under the Federal subsidy acts through the Federal land-grant…

  10. 48 CFR 570.405 - Lease extensions.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Lease extensions. 570.405... Requirements 570.405 Lease extensions. (a) This section applies to extension of the term of a lease to provide for continued occupancy on a short-term basis. (b) If the value of a lease extension will exceed...

  11. 10 CFR 903.23 - Rate extensions.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Rate Adjustments and Extensions for the Alaska, Southeastern, Southwestern, and Western Area Power Administrations § 903.23 Rate extensions. (a) The following regulations shall apply to the extension of rates... 10 Energy 4 2010-01-01 2010-01-01 false Rate extensions. 903.23 Section 903.23 Energy...

  12. Spreading the Word about Extension's Public Value

    ERIC Educational Resources Information Center

    Kalambokidis, Laura

    2011-01-01

    In recent years, the idea that Extension can build support for its programs by highlighting how they benefit people who have no contact with the programs has taken root in the Extension system. Providing Extension program teams with resources, training, and leadership can lead to a body of public value messages that can infuse Extension's…

  13. Neural network regulation driven by autonomous neural firings

    NASA Astrophysics Data System (ADS)

    Cho, Myoung Won

    2016-07-01

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

  14. Optical neural stimulation modeling on degenerative neocortical neural networks

    NASA Astrophysics Data System (ADS)

    Zverev, M.; Fanjul-Vélez, F.; Salas-García, I.; Arce-Diego, J. L.

    2015-07-01

    Neurodegenerative diseases usually appear at advanced age. Medical advances make people live longer and as a consequence, the number of neurodegenerative diseases continuously grows. There is still no cure for these diseases, but several brain stimulation techniques have been proposed to improve patients' condition. One of them is Optical Neural Stimulation (ONS), which is based on the application of optical radiation over specific brain regions. The outer cerebral zones can be noninvasively stimulated, without the common drawbacks associated to surgical procedures. This work focuses on the analysis of ONS effects in stimulated neurons to determine their influence in neuronal activity. For this purpose a neural network model has been employed. The results show the neural network behavior when the stimulation is provided by means of different optical radiation sources and constitute a first approach to adjust the optical light source parameters to stimulate specific neocortical areas.

  15. Coal Combustion Products Extension Program

    SciTech Connect

    Tarunjit S. Butalia; William E. Wolfe

    2006-01-11

    This final project report presents the activities and accomplishments of the ''Coal Combustion Products Extension Program'' conducted at The Ohio State University from August 1, 2000 to June 30, 2005 to advance the beneficial uses of coal combustion products (CCPs) in highway and construction, mine reclamation, agricultural, and manufacturing sectors. The objective of this technology transfer/research program at The Ohio State University was to promote the increased use of Ohio CCPs (fly ash, FGD material, bottom ash, and boiler slag) in applications that are technically sound, environmentally benign, and commercially competitive. The project objective was accomplished by housing the CCP Extension Program within The Ohio State University College of Engineering with support from the university Extension Service and The Ohio State University Research Foundation. Dr. Tarunjit S. Butalia, an internationally reputed CCP expert and registered professional engineer, was the program coordinator. The program coordinator acted as liaison among CCP stakeholders in the state, produced information sheets, provided expertise in the field to those who desired it, sponsored and co-sponsored seminars, meetings, and speaking at these events, and generally worked to promote knowledge about the productive and proper application of CCPs as useful raw materials. The major accomplishments of the program were: (1) Increase in FGD material utilization rate from 8% in 1997 to more than 20% in 2005, and an increase in overall CCP utilization rate of 21% in 1997 to just under 30% in 2005 for the State of Ohio. (2) Recognition as a ''voice of trust'' among Ohio and national CCP stakeholders (particularly regulatory agencies). (3) Establishment of a national and international reputation, especially for the use of FGD materials and fly ash in construction applications. It is recommended that to increase Ohio's CCP utilization rate from 30% in 2005 to 40% by 2010, the CCP Extension Program be

  16. On the extensible viscoelastic beam

    NASA Astrophysics Data System (ADS)

    Giorgi, Claudio; Pata, Vittorino; Vuk, Elena

    2008-04-01

    This work is focused on the equation \\[ \\begin{eqnarray*}\\fl {\\partial_{tt}} u+\\partial_{xxxx}u +\\int_0^\\infty \\mu(s) \\partial_{xxxx}[u(t)-u(t-s)]\\,\\rmd s\\\\ - \\big(\\beta+\\|\\partial_x u\\|_{L^2(0,1)}^2\\big)\\partial_{xx}u= f\\end{eqnarray*} \\] describing the motion of an extensible viscoelastic beam. Under suitable boundary conditions, the related dynamical system in the history space framework is shown to possess a global attractor of optimal regularity. The result is obtained by exploiting an appropriate decomposition of the solution semigroup, together with the existence of a Lyapunov functional.

  17. Chiral Extensions of the Mssm

    NASA Astrophysics Data System (ADS)

    Ferretti, Gabriele; Karateev, Denis

    2013-03-01

    We present a class of extensions of the MSSM characterized by a fully chiral field content (no μ-terms) and no baryon or lepton number violating term in the superpotential due to an extra U‧(1) gauge symmetry. The minimal model consists of the usual matter sector with family dependent U‧(1) charges, six Higgs weak doublets, and three singlets required to give masses to the Higgsinos and cancel anomalies. We discuss its main features such as the tree level mass spectrum and the constraints on flavor changing processes.

  18. Rhinomaxillary mucormycosis with cerebral extension

    PubMed Central

    Goel, Shikha; Palaskar, Sangeeta; Shetty, Vishwa Parkash; Bhushan, Anju

    2009-01-01

    Mucormycosis is a rare opportunistic infection caused by fungus belonging to the order Mucorales. A case of a controlled diabetic male with rhino maxillary mucormycosis, with cerebral extension, is described. The patient presented with hemifacial swelling, a nasal twang in his voice, fever, ocular signs, gross tissue destruction, and was sluggish. Early recognition of mucormycosis is necessary to limit the spread of infection, which can lead to high morbidity and mortality. Therefore, health practitioners should be familiar with the signs and symptoms of the disease. PMID:21886991

  19. Neural correlates of cognitive ability.

    PubMed

    Brancucci, Alfredo

    2012-07-01

    The challenge to neuroscientists working on intelligence is to discover what neural structures and mechanisms are at the basis of such a complex and variegated capability. Several psychologists agree on the view that behavioral flexibility is a good measure of intelligence, resulting in the appearance of novel solutions that are not part of the animal's normal behavior. This article tries to indicate how the supposed differences in intelligence between species can be related to brain properties and suggests that the best neural indicators may be the ones that convey more information processing capacity to the brain, i.e., high conduction velocity of fibers and small distances between neurons, associated with a high number of neurons and an adequate level of connectivity. The neural bases of human intelligence have been investigated by means of anatomical, neurophysiological, and neuropsychological methods. These investigations have led to two important findings that are briefly discussed: the parietofrontal integration theory of intelligence, which assumes that a distributed network of cortical areas having its main nodes in the frontal and parietal lobes constitutes a probable substrate for smart behavior, and the neural efficiency hypothesis, according to which intelligent people process information more efficiently, showing weaker neural activations in a smaller number of areas than less intelligent people. PMID:22422612

  20. Neural Networks for Flight Control

    NASA Technical Reports Server (NTRS)

    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.

  1. On Harnack's theorem and extensions

    NASA Astrophysics Data System (ADS)

    Costa, Antonio F.; Parlier, Hugo

    Harnack's theorem states that the fixed points of an orientation reversing involution of a compact orientable surface of genus g are a set of k disjoint simple closed geodesic where 0≤ k≤ g+1 . The first goal of this article is to give a purely geometric, complete and self-contained proof of this fact. In the case where the fixed curves of the involution do not separate the surface, we prove an extension of this theorem, by exhibiting the existence of auxiliary invariant curves with interesting properties. Although this type of extension is well known (see, for instance, Comment. Math. Helv. 57(4): 603-626 (1982) and Transl. Math. Monogr., vol. 225, Amer. Math. Soc., Providence, RI, 2004), our method also extends the theorem in the case where the surface has boundary. As a byproduct, we obtain a geometric method on how to obtain these auxiliary curves. As a consequence of these constructions, we obtain results concerning presentations of Non-Euclidean crystallographic groups and a new proof of a result on the set of points corresponding to real algebraic curves in the compactification of the Moduli space of complex curves of genus g , overline{M_{g}} . More concretely, we establish that given two real curves there is a path in overline{M_{g}} which passes through at most two singular curves, a result of M. Seppaelae (Ann. Sci. Ecole Norm. Sup. (4), 24(5), 519-544 (1991)).

  2. Neural crest migration: trailblazing ahead.

    PubMed

    Kulesa, Paul M; McLennan, Rebecca

    2015-01-01

    Embryonic cell migration patterns are amazingly complex in the timing and spatial distribution of cells throughout the vertebrate landscape. However, advances in in vivo visualization, cell interrogation, and computational modeling are extracting critical features that underlie the mechanistic nature of these patterns. The focus of this review highlights recent advances in the study of the highly invasive neural crest cells and their migratory patterns during embryonic development. We discuss these advances within three major themes and include a description of computational models that have emerged to more rapidly integrate and test hypothetical mechanisms of neural crest migration. We conclude with technological advances that promise to reveal new insights and help translate results to human neural crest-related birth defects and metastatic cancer. PMID:25705385

  3. Another look at neural multigrid

    SciTech Connect

    Baeker, M.

    1997-04-01

    We present a new multigrid method called neural multigrid which is based on joining multigrid ideas with concepts from neural nets. The main idea is to use the Greenbaum criterion as a cost functional for the neural net. The algorithm is able to learn efficient interpolation operators in the case of the ordered Laplace equation with only a very small critical slowing down and with a surprisingly small amount of work comparable to that of a Conjugate Gradient solver. In the case of the two-dimensional Laplace equation with SU(2) gauge fields at {beta}=0 the learning exhibits critical slowing down with an exponent of about z {approx} 0.4. The algorithm is able to find quite good interpolation operators in this case as well. Thereby it is proven that a practical true multigrid algorithm exists even for a gauge theory. An improved algorithm using dynamical blocks that will hopefully overcome the critical slowing down completely is sketched.

  4. Multiprocessor Neural Network in Healthcare.

    PubMed

    Godó, Zoltán Attila; Kiss, Gábor; Kocsis, Dénes

    2015-01-01

    A possible way of creating a multiprocessor artificial neural network is by the use of microcontrollers. The RISC processors' high performance and the large number of I/O ports mean they are greatly suitable for creating such a system. During our research, we wanted to see if it is possible to efficiently create interaction between the artifical neural network and the natural nervous system. To achieve as much analogy to the living nervous system as possible, we created a frequency-modulated analog connection between the units. Our system is connected to the living nervous system through 128 microelectrodes. Two-way communication is provided through A/D transformation, which is even capable of testing psychopharmacons. The microcontroller-based analog artificial neural network can play a great role in medical singal processing, such as ECG, EEG etc. PMID:26152990

  5. Neural crest migration: trailblazing ahead

    PubMed Central

    McLennan, Rebecca

    2015-01-01

    Embryonic cell migration patterns are amazingly complex in the timing and spatial distribution of cells throughout the vertebrate landscape. However, advances in in vivo visualization, cell interrogation, and computational modeling are extracting critical features that underlie the mechanistic nature of these patterns. The focus of this review highlights recent advances in the study of the highly invasive neural crest cells and their migratory patterns during embryonic development. We discuss these advances within three major themes and include a description of computational models that have emerged to more rapidly integrate and test hypothetical mechanisms of neural crest migration. We conclude with technological advances that promise to reveal new insights and help translate results to human neural crest-related birth defects and metastatic cancer. PMID:25705385

  6. Refractory neural nets and vision

    NASA Astrophysics Data System (ADS)

    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.

  7. Utilising reinforcement learning to develop strategies for driving auditory neural implants

    NASA Astrophysics Data System (ADS)

    Lee, Geoffrey W.; Zambetta, Fabio; Li, Xiaodong; Paolini, Antonio G.

    2016-08-01

    Objective. In this paper we propose a novel application of reinforcement learning to the area of auditory neural stimulation. We aim to develop a simulation environment which is based off real neurological responses to auditory and electrical stimulation in the cochlear nucleus (CN) and inferior colliculus (IC) of an animal model. Using this simulator we implement closed loop reinforcement learning algorithms to determine which methods are most effective at learning effective acoustic neural stimulation strategies. Approach. By recording a comprehensive set of acoustic frequency presentations and neural responses from a set of animals we created a large database of neural responses to acoustic stimulation. Extensive electrical stimulation in the CN and the recording of neural responses in the IC provides a mapping of how the auditory system responds to electrical stimuli. The combined dataset is used as the foundation for the simulator, which is used to implement and test learning algorithms. Main results. Reinforcement learning, utilising a modified n-Armed Bandit solution, is implemented to demonstrate the model’s function. We show the ability to effectively learn stimulation patterns which mimic the cochlea’s ability to covert acoustic frequencies to neural activity. Time taken to learn effective replication using neural stimulation takes less than 20 min under continuous testing. Significance. These results show the utility of reinforcement learning in the field of neural stimulation. These results can be coupled with existing sound processing technologies to develop new auditory prosthetics that are adaptable to the recipients current auditory pathway. The same process can theoretically be abstracted to other sensory and motor systems to develop similar electrical replication of neural signals.

  8. Convergent evolution of neural systems in ctenophores

    PubMed Central

    Moroz, Leonid L.

    2015-01-01

    Neurons are defined as polarized secretory cells specializing in directional propagation of electrical signals leading to the release of extracellular messengers – features that enable them to transmit information, primarily chemical in nature, beyond their immediate neighbors without affecting all intervening cells en route. Multiple origins of neurons and synapses from different classes of ancestral secretory cells might have occurred more than once during ~600 million years of animal evolution with independent events of nervous system centralization from a common bilaterian/cnidarian ancestor without the bona fide central nervous system. Ctenophores, or comb jellies, represent an example of extensive parallel evolution in neural systems. First, recent genome analyses place ctenophores as a sister group to other animals. Second, ctenophores have a smaller complement of pan-animal genes controlling canonical neurogenic, synaptic, muscle and immune systems, and developmental pathways than most other metazoans. However, comb jellies are carnivorous marine animals with a complex neuromuscular organization and sophisticated patterns of behavior. To sustain these functions, they have evolved a number of unique molecular innovations supporting the hypothesis of massive homoplasies in the organization of integrative and locomotory systems. Third, many bilaterian/cnidarian neuron-specific genes and ‘classical’ neurotransmitter pathways are either absent or, if present, not expressed in ctenophore neurons (e.g. the bilaterian/cnidarian neurotransmitter, γ-amino butyric acid or GABA, is localized in muscles and presumed bilaterian neuron-specific RNA-binding protein Elav is found in non-neuronal cells). Finally, metabolomic and pharmacological data failed to detect either the presence or any physiological action of serotonin, dopamine, noradrenaline, adrenaline, octopamine, acetylcholine or histamine – consistent with the hypothesis that ctenophore neural systems

  9. Convergent evolution of neural systems in ctenophores.

    PubMed

    Moroz, Leonid L

    2015-02-15

    Neurons are defined as polarized secretory cells specializing in directional propagation of electrical signals leading to the release of extracellular messengers - features that enable them to transmit information, primarily chemical in nature, beyond their immediate neighbors without affecting all intervening cells en route. Multiple origins of neurons and synapses from different classes of ancestral secretory cells might have occurred more than once during ~600 million years of animal evolution with independent events of nervous system centralization from a common bilaterian/cnidarian ancestor without the bona fide central nervous system. Ctenophores, or comb jellies, represent an example of extensive parallel evolution in neural systems. First, recent genome analyses place ctenophores as a sister group to other animals. Second, ctenophores have a smaller complement of pan-animal genes controlling canonical neurogenic, synaptic, muscle and immune systems, and developmental pathways than most other metazoans. However, comb jellies are carnivorous marine animals with a complex neuromuscular organization and sophisticated patterns of behavior. To sustain these functions, they have evolved a number of unique molecular innovations supporting the hypothesis of massive homoplasies in the organization of integrative and locomotory systems. Third, many bilaterian/cnidarian neuron-specific genes and 'classical' neurotransmitter pathways are either absent or, if present, not expressed in ctenophore neurons (e.g. the bilaterian/cnidarian neurotransmitter, γ-amino butyric acid or GABA, is localized in muscles and presumed bilaterian neuron-specific RNA-binding protein Elav is found in non-neuronal cells). Finally, metabolomic and pharmacological data failed to detect either the presence or any physiological action of serotonin, dopamine, noradrenaline, adrenaline, octopamine, acetylcholine or histamine - consistent with the hypothesis that ctenophore neural systems evolved

  10. Performance sustaining intracortical neural prostheses

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  11. [Lymphoma of Ocular and Periocular Tissues - Clinicopathological Correlations].

    PubMed

    Schmack, I; Grossniklaus, H E; Hartmann, S

    2016-07-01

    Lymphomas of the ocular adnexa and intraocular tissue include a wide range of lymphoproliferative neoplastic disorders. They are predominantly extranodal non-Hodgkin lymphomas (NHL). The World Health Organization (WHO) classification of lymphoid neoplasm and individual morphological, immunophenotypical, and molecular genetic features, indicate that they may be divided into B-cell (approximately 80 % of all NHL) and T-cell lymphomas (approximately 10-20 % of all NHL). The most common forms of ocular NHL are extranodal marginal zone lymphoma (EMZL) of the mucosa-associated lymphoid tissue (MALT-type), follicular lymphoma (FL), diffuse large B-cell lymphoma, and mantel cell lymphoma. The clinical signs and symptoms are usually very unspecific and depend on the location, size, and extent of the underlying lymphoma subtype. Typical low grade lymphomas have an indolent clinical course and often remain unrecognized for many years. On the other hand, high grade NHLs, such as DLBCL or MCL, are frequently aggressive, with rapid tumour growth and poor prognosis, despite early detection. Histopathology is still the gold standard in the diagnosis of ocular lymphomas. Basic understanding of the principal pathophysiological and clinical aspects of the development and progression of orbital and ocular lymphomas seems to be mandatory for optimal diagnosis and treatment and for improving survival and prognosis. Both residents in training and board certified ophthalmologists should be aware of these problems. PMID:27468099

  12. Plant Growth Models Using Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Bubenheim, David

    1997-01-01

    In this paper, we descrive our motivation and approach to devloping models and the neural network architecture. Initial use of the artificial neural network for modeling the single plant process of transpiration is presented.

  13. Neural overlap in processing music and speech

    PubMed Central

    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

  14. Neural overlap in processing music and speech.

    PubMed

    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. PMID:25646513

  15. MULTIPLE NEURAL FIBROLIPOMAS WITH MACRODACTYLY

    PubMed Central

    Gupta, Aparna; Geetha, V; Monappa, Vidya; Bhat, Sudha S

    2011-01-01

    Neural fibrolipoma is an uncommon tumor-like lesion that involves the upper extremity and usually arises in the median nerve. It is associated with macrodactyly in one-third of the cases. A 3-year-old girl presented with increasing size of fingers of both the hands since birth. Clinical examination revealed macrodactyly of two fingers of the right hand and three fingers of the left. Surgical reduction was performed and microscopy of the biopsy specimen established the diagnosis of neural fibrolipoma. Knowledge of the clinicopathological features is necessary for accurate diagnosis and treatment of this rare entity. PMID:22345793

  16. Neural-Network-Development Program

    NASA Technical Reports Server (NTRS)

    Phillips, Todd A.

    1993-01-01

    NETS, software tool for development and evaluation of neural networks, provides simulation of neural-network algorithms plus computing environment for development of such algorithms. Uses back-propagation learning method for all of networks it creates. Enables user to customize patterns of connections between layers of network. Also provides features for saving, during learning process, values of weights, providing more-precise control over learning process. Written in ANSI standard C language. Machine-independent version (MSC-21588) includes only code for command-line-interface version of NETS 3.0.

  17. Cross interaction of melanocortinergic and dopaminergic systems in neural modulation

    PubMed Central

    He, Zhi-Gang; Liu, Bao-Wen; Xiang, Hong-Bing

    2015-01-01

    Melanocortinergic and dopaminergic systems are widely distributed in the CNS and have been established as a crucial regulatory component in diverse physiological functions. The pharmacology of both melanocortinergic and dopaminergic systems including their individual receptors, signaling mechanisms, agonists and antagonists has been extensively studied. Several lines of evidence showed that there existed a cross interaction between the receptors of melanocortinergic and dopaminergic systems. The data available at present had expanded our understanding of melanocortinergic and dopaminergic system interaction in neural modulation, which will be main discussed in this paper. PMID:26823964

  18. A neural-network approach to robotic control

    NASA Technical Reports Server (NTRS)

    Graham, D. P. W.; Deleuterio, G. M. T.

    1993-01-01

    An artificial neural-network paradigm for the control of robotic systems is presented. The approach is based on the Cerebellar Model Articulation Controller created by James Albus and incorporates several extensions. First, recognizing the essential structure of multibody equations of motion, two parallel modules are used that directly reflect the dynamical characteristics of multibody systems. Second, the architecture of the proposed network is imbued with a self-organizational capability which improves efficiency and accuracy. Also, the networks can be arranged in hierarchical fashion with each subsequent network providing finer and finer resolution.

  19. Neutrons in extensive air showers

    SciTech Connect

    Stenkin, Yu. V.; Djappuev, D. D.; Valdes-Galicia, J. F.

    2007-06-15

    The main properties of the so-called neutron bursts produced by the passage of extensive air showers (EASs) through a detector array and the properties of these EASs are considered using the experiments that are being or have been carried out previously with the Carpet-2 array at Baksan Neutrino Observatory of the Institute for Nuclear Research, Russian Academy of Sciences, and at Cosmic-Ray Station of UNAM in Mexico as examples. We show that no exotic processes are required to explain the nature of neutron bursts. Based on a working prototype of the previously proposed MULTICOM array, we also show that this phenomenon can be successfully used in studying the EAS hadronic component and that adding special thermal neutron detectors can improve significantly the capabilities of the array for EAS study.

  20. Industrial extension, the Oklahoma way

    NASA Astrophysics Data System (ADS)

    Farrell, Edmund J.

    1994-03-01

    Oklahoma has established a customer-driven industrial extension system. A publicly-chartered, private non-profit corporation, the Oklahoma Alliance for Manufacturing Excellence, Inc. (`the Alliance') coordinates the system. The system incorporates principles that Oklahoma manufacturers value: (1) decentralization and local accessibility; (2) coordinated existing resources; (3) comprehensive help; (4) interfirm cooperation; (5) pro-active outreach; (6) self- help and commitment from firms; (7) customer governance; and (8) performance accountability. The Oklahoma system consists of: (1) a network of locally-based broker/agents who work directly with manufacturers to diagnose problems and find appropriate assistance; (2) a group of industry sector specialists who collect and disseminate sector specific technological and market intelligence to the broker/agents and their clients; (3) all the specialized public and private sector resources coordinated by the system; and (4) a customer- driven coordination and evaluation mechanism, the Alliance.

  1. Orbital extension of trigeminal schwannoma.

    PubMed

    Ghosh, Shantanu; Das, Debabrata; Varshney, Rahul; Nandy, Sumit

    2015-01-01

    Schwannomas, also known as neurilemmomas, are benign peripheral nerve sheath tumors. Trigeminal schwannomas are rare intracranial tumors. Here, we report a 35-year-old female presenting with an axial proptosis of right eyeball with right-sided III, IV and VI cranial nerve palsy. Her best corrected visual acuity in the right eye was perception of light absent and in the left eye was 20/20. MRI scan revealed a large right-sided heterogeneous, extra-axial middle cranial fossa mass that extended to the intraconal space of right orbit. A diagnosis of intracranial trigeminal nerve schwannoma with right orbital extension was made. Successful surgical excision of the mass with preservation of the surrounding tissues and orbital exenteration was done. Post-operative period was uneventful. PMID:25552864

  2. Orbital extension of trigeminal schwannoma

    PubMed Central

    Ghosh, Shantanu; Das, Debabrata; Varshney, Rahul; Nandy, Sumit

    2015-01-01

    Schwannomas, also known as neurilemmomas, are benign peripheral nerve sheath tumors. Trigeminal schwannomas are rare intracranial tumors. Here, we report a 35-year-old female presenting with an axial proptosis of right eyeball with right-sided III, IV and VI cranial nerve palsy. Her best corrected visual acuity in the right eye was perception of light absent and in the left eye was 20/20. MRI scan revealed a large right-sided heterogeneous, extra-axial middle cranial fossa mass that extended to the intraconal space of right orbit. A diagnosis of intracranial trigeminal nerve schwannoma with right orbital extension was made. Successful surgical excision of the mass with preservation of the surrounding tissues and orbital exenteration was done. Post-operative period was uneventful. PMID:25552864

  3. Extensibility and limitations of FDDI

    NASA Technical Reports Server (NTRS)

    Game, David; Maly, Kurt J.

    1990-01-01

    Recently two standards for Metropolitan Area Networks (MANs), Fiber Distributed Data Interface (FDDI) and Distributed Queue Dual Bus (DQDB), have emerged as the primary competitors for the MAN arena. Great interest exists in building higher speed networks which support large numbers of node and greater distance, and it is not clear what types of protocols are needed for this type of environment. There is some question as to whether or not these MAN standards can be extended to such environments. The extensibility of FDDI to the Gbps range and a long distance environment is investigated. Specification parameters which affect performance are shown and a measure is provided for predicting utilization of FDDI. A comparison of FDDI at 100 Mbps and 1 Gbps is presented. Some specific problems with FDDI are addressed and modifications which improve the viability of FDDI in such high speed networks are investigated.

  4. How Neural Networks Learn from Experience.

    ERIC Educational Resources Information Center

    Hinton, Geoffrey E.

    1992-01-01

    Discusses computational studies of learning in artificial neural networks and findings that may provide insights into the learning abilities of the human brain. Describes efforts to test theories about brain information processing, using artificial neural networks. Vignettes include information concerning how a neural network represents…

  5. Model Of Neural Network With Creative Dynamics

    NASA Technical Reports Server (NTRS)

    Zak, Michail; Barhen, Jacob

    1993-01-01

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

  6. Competency Modeling in Extension Education: Integrating an Academic Extension Education Model with an Extension Human Resource Management Model

    ERIC Educational Resources Information Center

    Scheer, Scott D.; Cochran, Graham R.; Harder, Amy; Place, Nick T.

    2011-01-01

    The purpose of this study was to compare and contrast an academic extension education model with an Extension human resource management model. The academic model of 19 competencies was similar across the 22 competencies of the Extension human resource management model. There were seven unique competencies for the human resource management model.…

  7. Neural Basis of Visual Distraction

    ERIC Educational Resources Information Center

    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…

  8. Neural Networks For Visual Telephony

    NASA Astrophysics Data System (ADS)

    Gottlieb, A. M.; Alspector, J.; Huang, P.; Hsing, T. R.

    1988-10-01

    By considering how an image is processed by the eye and brain, we may find ways to simplify the task of transmitting complex video images over a telecommunication channel. Just as the retina and visual cortex reduce the amount of information sent to other areas of the brain, electronic systems can be designed to compress visual data, encode features, and adapt to new scenes for video transmission. In this talk, we describe a system inspired by models of neural computation that may, in the future, augment standard digital processing techniques for image compression. In the next few years it is expected that a compact low-cost full motion video telephone operating over an ISDN basic access line (144 KBits/sec) will be shown to be feasible. These systems will likely be based on a standard digital signal processing approach. In this talk, we discuss an alternative method that does not use standard digital signal processing but instead uses eletronic neural networks to realize the large compression necessary for a low bit-rate video telephone. This neural network approach is not being advocated as a near term solution for visual telephony. However, low bit rate visual telephony is an area where neural network technology may, in the future, find a significant application.

  9. Neural Control of the Circulation

    ERIC Educational Resources Information Center

    Thomas, Gail D.

    2011-01-01

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

  10. Nanomaterial-Enabled Neural Stimulation.

    PubMed

    Wang, Yongchen; Guo, Liang

    2016-01-01

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

  11. Neural Network Development Tool (NETS)

    NASA Technical Reports Server (NTRS)

    Baffes, Paul T.

    1990-01-01

    Artificial neural networks formed from hundreds or thousands of simulated neurons, connected in manner similar to that in human brain. Such network models learning behavior. Using NETS involves translating problem to be solved into input/output pairs, designing network configuration, and training network. Written in C.

  12. Artificial neural networks in medicine

    SciTech Connect

    Keller, P.E.

    1994-07-01

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

  13. Serotonin, neural markers, and memory

    PubMed Central

    Meneses, Alfredo

    2015-01-01

    Diverse neuropsychiatric disorders present dysfunctional memory and no effective treatment exits for them; likely as result of the absence of neural markers associated to memory. Neurotransmitter systems and signaling pathways have been implicated in memory and dysfunctional memory; however, their role is poorly understood. Hence, neural markers and cerebral functions and dysfunctions are revised. To our knowledge no previous systematic works have been published addressing these issues. The interactions among behavioral tasks, control groups and molecular changes and/or pharmacological effects are mentioned. Neurotransmitter receptors and signaling pathways, during normal and abnormally functioning memory with an emphasis on the behavioral aspects of memory are revised. With focus on serotonin, since as it is a well characterized neurotransmitter, with multiple pharmacological tools, and well characterized downstream signaling in mammals' species. 5-HT1A, 5-HT4, 5-HT5, 5-HT6, and 5-HT7 receptors as well as SERT (serotonin transporter) seem to be useful neural markers and/or therapeutic targets. Certainly, if the mentioned evidence is replicated, then the translatability from preclinical and clinical studies to neural changes might be confirmed. Hypothesis and theories might provide appropriate limits and perspectives of evidence. PMID:26257650

  14. Neural Networks for Readability Analysis.

    ERIC Educational Resources Information Center

    McEneaney, John E.

    This paper describes and reports on the performance of six related artificial neural networks that have been developed for the purpose of readability analysis. Two networks employ counts of linguistic variables that simulate a traditional regression-based approach to readability. The remaining networks determine readability from "visual snapshots"…

  15. Memory Storage and Neural Systems.

    ERIC Educational Resources Information Center

    Alkon, Daniel L.

    1989-01-01

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

  16. Neural networks for handwriting recognition

    NASA Astrophysics Data System (ADS)

    Kelly, David A.

    1992-09-01

    The market for a product that can read handwritten forms, such as insurance applications, re- order forms, or checks, is enormous. Companies could save millions of dollars each year if they had an effective and efficient way to read handwritten forms into a computer without human intervention. Urged on by the potential gold mine that an adequate solution would yield, a number of companies and researchers have developed, and are developing, neural network-based solutions to this long-standing problem. This paper briefly outlines the current state-of-the-art in neural network-based handwriting recognition research and products. The first section of the paper examines the potential market for this technology. The next section outlines the steps in the recognition process, followed by a number of the basic issues that need to be dealt with to solve the recognition problem in a real-world setting. Next, an overview of current commercial solutions and research projects shows the different ways that neural networks are applied to the problem. This is followed by a breakdown of the current commercial market and the future outlook for neural network-based handwriting recognition technology.

  17. Nanomaterial-Enabled Neural Stimulation

    PubMed Central

    Wang, Yongchen; Guo, Liang

    2016-01-01

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

  18. 78 FR 53135 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-28

    ... available on the Internet at: http://www.eia.gov/survey/#coal . SUPPLEMENTARY INFORMATION: This information... Information Administration Agency Information Collection Extension AGENCY: U.S. Energy Information Administration (EIA), Department of Energy (DOE). ACTION: Information collection extension with change,...

  19. On Design and Implementation of Neural-Machine Interface for Artificial Legs

    PubMed Central

    Zhang, Xiaorong; Liu, Yuhong; Zhang, Fan; Ren, Jin; Sun, Yan (Lindsay); Yang, Qing

    2011-01-01

    The quality of life of leg amputees can be improved dramatically by using a cyber physical system (CPS) that controls artificial legs based on neural signals representing amputees’ intended movements. The key to the CPS is the neural-machine interface (NMI) that senses electromyographic (EMG) signals to make control decisions. This paper presents a design and implementation of a novel NMI using an embedded computer system to collect neural signals from a physical system - a leg amputee, provide adequate computational capability to interpret such signals, and make decisions to identify user’s intent for prostheses control in real time. A new deciphering algorithm, composed of an EMG pattern classifier and a post-processing scheme, was developed to identify the user’s intended lower limb movements. To deal with environmental uncertainty, a trust management mechanism was designed to handle unexpected sensor failures and signal disturbances. Integrating the neural deciphering algorithm with the trust management mechanism resulted in a highly accurate and reliable software system for neural control of artificial legs. The software was then embedded in a newly designed hardware platform based on an embedded microcontroller and a graphic processing unit (GPU) to form a complete NMI for real time testing. Real time experiments on a leg amputee subject and an able-bodied subject have been carried out to test the control accuracy of the new NMI. Our extensive experiments have shown promising results on both subjects, paving the way for clinical feasibility of neural controlled artificial legs. PMID:22389637

  20. Neural networks and applications tutorial

    NASA Astrophysics Data System (ADS)

    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.

  1. Stochastic neural nets and vision

    NASA Astrophysics Data System (ADS)

    Fall, Thomas C.

    1991-03-01

    A stochastic neural net shares with the normally defined neural nets the concept that information is processed by a system consisting of a set of nodes (neurons) connected by weighted links (axons). The normal neural net takes in inputs on an initial layer of neurons which fire appropriately; a neuron of the next layer fires depending on the sum of weights of the axons leading to it from fired neurons of the first layer. The stochastic neural net differs in that the neurons are more complex and that the vision activity is a dynamic process. The first layer (viewing layer) of neurons fires stochastically based on the average brightness of the area it sees and then has a refractory period. The viewing layer looks at the image for several clock cycles. The effect is like those photo sensitive sunglasses that darken in bright light. The neurons over the bright areas are most likely in a refractory period (and this can't fire) and the neurons over the dark areas are not. Now if we move the sensing layer with respect to the image so that a portion of the neurons formerly over the dark are now over the bright, they will likely all fire on that first cycle. Thus, on that cycle, one would see a flash from that portion significantly stronger than surrounding regions. Movement the other direction would produce a patch that is darker, but this effect is not as noticeable. These effects are collected in a collection layer. This paper will discuss the use of the stochastic neural net for edge detection and segmentation of some simple images.

  2. Nozzle Extension for Safety Air Gun

    NASA Technical Reports Server (NTRS)

    Zumbrun, H. N.; Croom, Delwin R., Jr.

    1986-01-01

    New nozzle-extension design overcomes problems and incorporates original commercial nozzle, retaining intrinsic safety features. Components include extension tube, length of which made to suit application; adaptor fitting, and nozzle adaptor repinned to maintain original safety features. Design moves conical airstream to end of extension to blow machine chips away from operator. Nozzle-extension modification allows safe and efficient operation of machine tools while maintaining integrity of orginial safety-air-gun design.

  3. Validation and regulation of medical neural networks.

    PubMed

    Rodvold, D M

    2001-01-01

    Using artificial neural networks (ANNs) in medical applications can be challenging because of the often-experimental nature of ANN construction and the "black box" label that is frequently attached to them. In the US, medical neural networks are regulated by the Food and Drug Administration. This article briefly discusses the documented FDA policy on neural networks and the various levels of formal acceptance that neural network development groups might pursue. To assist medical neural network developers in creating robust and verifiable software, this paper provides a development process model targeted specifically to ANNs for critical applications. PMID:11790274

  4. Micro- and Nanotechnologies for Optical Neural Interfaces

    PubMed Central

    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

  5. Extensively drug-resistant tuberculosis.

    PubMed

    Jassal, Mandeep; Bishai, William R

    2009-01-01

    Extensively drug-resistant (XDR) tuberculosis is defined as disease caused by Mycobacterium tuberculosis with resistance to at least isoniazid and rifampicin, any fluoroquinolone, and at least one of three injectable second-line drugs (amikacin, capreomycin, or kanamycin). The definition has applicable clinical value and has allowed for more uniform surveillance in varied international settings. Recent surveillance data have indicated that the prevalence of tuberculosis drug resistance has risen to the highest rate ever recorded. The gold standard for drug-susceptibility testing has been the agar proportion method; however, this technique requires several weeks for results to be determined. More sensitive and specific diagnostic tests are still unavailable in resource-limited settings. Clinical manifestations, although variable in different settings and among different strains, have in general shown that XDR tuberculosis is associated with greater morbidity and mortality than non-XDR tuberculosis. The treatment of XDR tuberculosis should include agents to which the organism is susceptible, and should continue for a minimum of 18-24 months. However, treatment continues to be limited in tuberculosis-endemic countries largely because of weaknesses in national tuberculosis health-care models. The ultimate strategy to control drug-resistant tuberculosis is one that implements a comprehensive approach incorporating innovation from the political, social, economic, and scientific realms. PMID:18990610

  6. Presentation Extensions of the SOAP

    NASA Technical Reports Server (NTRS)

    Carnright, Robert; Stodden, David; Coggi, John

    2009-01-01

    A set of extensions of the Satellite Orbit Analysis Program (SOAP) enables simultaneous and/or sequential presentation of information from multiple sources. SOAP is used in the aerospace community as a means of collaborative visualization and analysis of data on planned spacecraft missions. The following definitions of terms also describe the display modalities of SOAP as now extended: In SOAP terminology, View signifies an animated three-dimensional (3D) scene, two-dimensional still image, plot of numerical data, or any other visible display derived from a computational simulation or other data source; a) "Viewport" signifies a rectangular portion of a computer-display window containing a view; b) "Palette" signifies a collection of one or more viewports configured for simultaneous (split-screen) display in the same window; c) "Slide" signifies a palette with a beginning and ending time and an animation time step; and d) "Presentation" signifies a prescribed sequence of slides. For example, multiple 3D views from different locations can be crafted for simultaneous display and combined with numerical plots and other representations of data for both qualitative and quantitative analysis. The resulting sets of views can be temporally sequenced to convey visual impressions of a sequence of events for a planned mission.

  7. Nozzle extension design status report

    NASA Technical Reports Server (NTRS)

    Classen, L. B.

    1972-01-01

    Twenty possible concepts of a possible nozzle/nozzle extension interface were originated. Not all of the concepts were considered worthy of analysis time. Six of them were thermally analyzed and three were stress analyzed. These analyses were done to determine which of the concepts would have the best chance of succeeding, that is, they were a screening process which was to allow rating of one concept against another. This was done because adequate material properties to determine absolute stress levels were not available at the time of the analyses. Through all of the concepts still exhibit some areas of negative margin of safety, concept no. 1 shows good promise that, with slight modifications, it could have all positive margins of safety. Another significant question, regarding these designs, has to do with the Grafoil seals and insulators. Some additional data was just recently received on Grafoil properties, but it was too late to incorporate in the analyses. The new data were not significantly different from the properties which were used.

  8. Extensive wetting due to roughness

    SciTech Connect

    Yost, F.G.; Michael, J.R.; Eisenmann, E.T. . Center for Solder Science and Technology)

    1995-01-01

    Typically, a small mass of eutectic Sn-Pb solder wets a copper surface and flows radially outward to form a hemispherical shape with a contact angle of approx. 15--20 deg. When a similar mass of solder wets and thick electroless copper coated substrate, rapid radial flow commences and surprising new effects occur. Thick coats of electroless copper have a nodular surface structure and spreading on it does not subside until all solder is consumed. When the nodular structure is wetted by solder a coastline'' with many nearby islands'' are defined. Photos of regions at the wetting front were taken in the backscatter imaging mode of an SEM. These images show that solder wets the valleys between the surface nodules forming a delicate, lacy arrangement. The geometry of this coastal'' solder structure is described as fractal-like having a dimension D = 1.38 making it similar to drying fronts and cloud configurations. The importance of surface roughness in wetting phenomena is discussed in the light of an extensive history on the subject. It is shown that for spontaneous flow, assisted by roughness, the surface geometry must consist of local angles that are larger than the equilibrium contact angle. Kinetics of the wetting process are demonstrated by image analysis of wetted area taken from videotaped experiments. These experimental kinetics are shown to be similar in form to flow in open channel capillaries.

  9. Extensive Floods in United Kingdom

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Rain continues to fall in the United Kingdom, bringing more water to an already water-logged landscape. Some rivers there are experiencing their worst flooding in more than 50 years. Of particular note, Britain's River Ouse reached its highest levels on record since 1625. Thousands of people have been evacuated from their homes since October 30, when a large low-pressure system brought torrential rains and hurricane-force winds, placing regions around more than 40 rivers across the country on flood alert. Since then, the rains have persisted, keeping water levels high and causing additional rivers to overrun their banks. In all, at least 12 people have been killed and more than 5,000 properties flooded. Some officials estimate damages could reach 500 million pounds (roughly $715 million). These Landsat 7 scenes show a comparison of the region surrounding Exeter, England, before and after the floods. The top image was acquired September 28 and the bottom image was acquired October 30, 2000. Note the extensive flooding along the River Exe in the bottom image (blue pixels). The light bluish-white pixels in the top image are clouds, and the black splotches on the landscape are the clouds' shadows. The reddish-brown shapes are agricultural fields. Image by Robert Simmon and Brian Montgomery, NASA GSFC. Data provided by Ron Beck, USGS EROS Data Center.

  10. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

    PubMed

    Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

    2016-01-01

    Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility. PMID:26752681

  11. Dynamics of a neural system with a multiscale architecture

    PubMed Central

    Breakspear, Michael; Stam, Cornelis J

    2005-01-01

    The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales—neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are ‘slaved’ to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested. PMID:16087448

  12. Associative learning in random environments using neural networks.

    PubMed

    Narendra, K S; Mukhopadhyay, S

    1991-01-01

    Associative learning is investigated using neural networks and concepts based on learning automata. The behavior of a single decision-maker containing a neural network is studied in a random environment using reinforcement learning. The objective is to determine the optimal action corresponding to a particular state. Since decisions have to be made throughout the context space based on a countable number of experiments, generalization is inevitable. Many different approaches can be followed to generate the desired discriminant function. Three different methods which use neural networks are discussed and compared. In the most general method, the output of the network determines the probability with which one of the actions is to be chosen. The weights of the network are updated on the basis of the actions and the response of the environment. The extension of similar concepts to decentralized decision-making in a context space is also introduced. Simulation results are included. Modifications in the implementations of the most general method to make it practically viable are also presented. All the methods suggested are feasible and the choice of a specific method depends on the accuracy desired as well as on the available computational power. PMID:18276348

  13. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields

    PubMed Central

    Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

    2016-01-01

    Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility. PMID:26752681

  14. A constructive algorithm for training cooperative neural network ensembles.

    PubMed

    Islam, Md M; Yao, Xin; Murase, K

    2003-01-01

    Presents a constructive algorithm for training cooperative neural-network ensembles (CNNEs). CNNE combines ensemble architecture design with cooperative training for individual neural networks (NNs) in ensembles. Unlike most previous studies on training ensembles, CNNE puts emphasis on both accuracy and diversity among individual NNs in an ensemble. In order to maintain accuracy among individual NNs, the number of hidden nodes in individual NNs are also determined by a constructive approach. Incremental training based on negative correlation is used in CNNE to train individual NNs for different numbers of training epochs. The use of negative correlation learning and different training epochs for training individual NNs reflect CNNEs emphasis on diversity among individual NNs in an ensemble. CNNE has been tested extensively on a number of benchmark problems in machine learning and neural networks, including Australian credit card assessment, breast cancer, diabetes, glass, heart disease, letter recognition, soybean, and Mackey-Glass time series prediction problems. The experimental results show that CNNE can produce NN ensembles with good generalization ability. PMID:18238062

  15. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields

    NASA Astrophysics Data System (ADS)

    Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

    2016-01-01

    Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

  16. 20 CFR 655.60 - Extensions.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 20 Employees' Benefits 3 2013-04-01 2013-04-01 false Extensions. 655.60 Section 655.60 Employees...) Post Certification Activities § 655.60 Extensions. An employer may apply for extensions of the period... needed and that the need could not have been reasonably foreseen by the employer. The CO will notify...

  17. 20 CFR 655.60 - Extensions.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 20 Employees' Benefits 3 2014-04-01 2014-04-01 false Extensions. 655.60 Section 655.60 Employees...) Post Certification Activities § 655.60 Extensions. An employer may apply for extensions of the period... needed and that the need could not have been reasonably foreseen by the employer. The CO will notify...

  18. 76 FR 53887 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-30

    ... Information Collection Extension AGENCY: U.S. Department of Energy. ACTION: Submission for Office of... information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Legal Collection, OMB...

  19. 77 FR 23469 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-19

    ... Information Collection Extension AGENCY: U.S. Department of Energy. ACTION: Submission for Office of... information collection request to OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Security, OMB Control...

  20. 7 CFR 15b.27 - Extension education.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 7 Agriculture 1 2013-01-01 2013-01-01 false Extension education. 15b.27 Section 15b.27 Agriculture Office of the Secretary of Agriculture NONDISCRIMINATION ON THE BASIS OF HANDICAP IN PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Preschool, Elementary, Secondary, Adult, and Extension Education § 15b.27 Extension education....

  1. 75 FR 37419 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-29

    ... Information Collection Extension AGENCY: U.S. Department of Energy. ACTION: Submission for Office of... information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Financial...

  2. 24 CFR 968.235 - Time extensions.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 24 Housing and Urban Development 4 2011-04-01 2011-04-01 false Time extensions. 968.235 Section... Fewer Than 250 Units) § 968.235 Time extensions. A PHA shall not obligate or expend funds after the... time extension, as follows: (a) Certification. A PHA may extend an obligation or expenditure...

  3. 24 CFR 968.235 - Time extensions.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false Time extensions. 968.235 Section... Fewer Than 250 Units) § 968.235 Time extensions. A PHA shall not obligate or expend funds after the... time extension, as follows: (a) Certification. A PHA may extend an obligation or expenditure...

  4. 77 FR 51791 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-27

    .... Energy Information Administration Agency Information Collection Extension AGENCY: U.S. Energy Information... EIA has submitted an information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of...

  5. 78 FR 38305 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-26

    ... Information Collection Extension AGENCY: Department of Energy. ACTION: Submission for Office of Management and... information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Exchange/Sale Report,...

  6. 76 FR 31598 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-01

    ... Information Collection Extension AGENCY: U.S. Department of Energy. ACTION: Submission for Office of... information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Printing and...

  7. 75 FR 4055 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-01-26

    ... Information Collection Extension AGENCY: Department of Energy. ACTION: Submission for Office of Management and... information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Human Reliability Program...

  8. 77 FR 35366 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-13

    ... of Energy Efficiency and Renewable Energy Agency Information Collection Extension AGENCY: Office of... information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Historic Preservation...

  9. 78 FR 9901 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-12

    ... Information Collection Extension AGENCY: Department of Energy. ACTION: Submission for Office of Management and... information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Human Reliability Program...

  10. 75 FR 54859 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-09

    ... Information Collection Extension AGENCY: U.S. Department of Energy. ACTION: Submission for Office of... information collection request to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The information collection requests a three-year extension of its Contractor Legal...

  11. Improving Disability Awareness among Extension Agents

    ERIC Educational Resources Information Center

    Mahadevan, Lakshmi; Peterson, Rick L.; Grenwelge, Cheryl

    2014-01-01

    Increasing prevalence rates and legislative mandates imply that educators, parents, and Extension agents will need better tools and resources to meet the needs of special populations. The Texas A&M AgriLife Extension Service addresses this issue by using e-learning tools. Extension agents can take advantage of these courses to gain critical…

  12. 7 CFR 15b.27 - Extension education.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 7 Agriculture 1 2011-01-01 2011-01-01 false Extension education. 15b.27 Section 15b.27 Agriculture... Education § 15b.27 Extension education. (a) General. A recipient to which this subpart applies that provides extension education may not, on the basis of handicap, exclude qualified handicapped persons. A...

  13. 7 CFR 15b.27 - Extension education.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 7 Agriculture 1 2012-01-01 2012-01-01 false Extension education. 15b.27 Section 15b.27 Agriculture... Education § 15b.27 Extension education. (a) General. A recipient to which this subpart applies that provides extension education may not, on the basis of handicap, exclude qualified handicapped persons. A...

  14. 7 CFR 15b.27 - Extension education.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 7 Agriculture 1 2014-01-01 2014-01-01 false Extension education. 15b.27 Section 15b.27 Agriculture... Education § 15b.27 Extension education. (a) General. A recipient to which this subpart applies that provides extension education may not, on the basis of handicap, exclude qualified handicapped persons. A...

  15. 20 CFR 655.170 - Extensions.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... seeking extensions of more than 2 weeks may apply to the CO. Such requests must be related to weather... extension is needed and that the need could not have been reasonably foreseen by the employer. The CO will... the decision. The CO will not grant an extension where the total work contract period under...

  16. 20 CFR 655.170 - Extensions.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... seeking extensions of more than 2 weeks may apply to the CO. Such requests must be related to weather... extension is needed and that the need could not have been reasonably foreseen by the employer. The CO will... the decision. The CO will not grant an extension where the total work contract period under...

  17. 20 CFR 655.170 - Extensions.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... seeking extensions of more than 2 weeks may apply to the CO. Such requests must be related to weather... extension is needed and that the need could not have been reasonably foreseen by the employer. The CO will... the decision. The CO will not grant an extension where the total work contract period under...

  18. 20 CFR 655.170 - Extensions.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... seeking extensions of more than 2 weeks may apply to the CO. Such requests must be related to weather... extension is needed and that the need could not have been reasonably foreseen by the employer. The CO will... the decision. The CO will not grant an extension where the total work contract period under...

  19. 20 CFR 655.170 - Extensions.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... seeking extensions of more than 2 weeks may apply to the CO. Such requests must be related to weather... extension is needed and that the need could not have been reasonably foreseen by the employer. The CO will... the decision. The CO will not grant an extension where the total work contract period under...

  20. 7 CFR 15b.27 - Extension education.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 1 2010-01-01 2010-01-01 false Extension education. 15b.27 Section 15b.27 Agriculture... ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Preschool, Elementary, Secondary, Adult, and Extension Education § 15b.27 Extension education. (a) General. A recipient to which this subpart applies that...

  1. 24 CFR 968.235 - Time extensions.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 24 Housing and Urban Development 4 2013-04-01 2013-04-01 false Time extensions. 968.235 Section... Fewer Than 250 Units) § 968.235 Time extensions. A PHA shall not obligate or expend funds after the... time extension, as follows: (a) Certification. A PHA may extend an obligation or expenditure...

  2. 24 CFR 968.235 - Time extensions.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 24 Housing and Urban Development 4 2012-04-01 2012-04-01 false Time extensions. 968.235 Section... Fewer Than 250 Units) § 968.235 Time extensions. A PHA shall not obligate or expend funds after the... time extension, as follows: (a) Certification. A PHA may extend an obligation or expenditure...

  3. Extension Handbook. Processes and Practices. Second Edition.

    ERIC Educational Resources Information Center

    Blackburn, Donald J., Ed.

    This book contains the following papers about processes and practices in extension education in Canada: "Historical Roots" (Blackburn, Flaherty); "Transitions and Directions in Extension" (Blackburn, Flaherty); "Applying Learning Theory in Extension Work" (Griffith); "Understanding and Applying Motivation Research" (Griffith); "Pre-Adult…

  4. Rural Extension Services. Policy Research Working Paper.

    ERIC Educational Resources Information Center

    Anderson, Jock R.; Feder, Gershon

    This paper analyzes the considerations that lead policy makers to undertake extension investments as a key public responsibility, as well as the complex set of factors and intra-agency incentives that explain variations in performance between different extension systems. The goals of extension include transferring knowledge from researchers to…

  5. Improving the Extension Facilities in C+

    SciTech Connect

    Dubois, P F; Scott, B A

    1999-09-24

    CXX is a facility for extending Python using C++. Recently, the authors have substantially revised and improved the way in which you create extension objects and extension modules in C++. The method is now much more natural and has much less overhead, both in the code generated and in the effort needed to create the objects and extensions.

  6. FPNA: interaction between FPGA and neural computation.

    PubMed

    Girau, B

    2000-06-01

    Neural networks are usually considered as naturally parallel computing models. But the number of operators and the complex connection graph of standard neural models can not be directly handled by digital hardware devices. More particularly, several works show that programmable digital hardware is a real opportunity for flexible hardware implementations of neural networks. And yet many area and topology problems arise when standard neural models are implemented onto programmable circuits such as FPGAs, so that the fast FPGA technology improvements can not be fully exploited. Therefore neural network hardware implementations need to reconcile simple hardware topologies with complex neural architectures. The theoretical and practical framework developed, allows this combination thanks to some principles of configurable hardware that are applied to neural computation: Field Programmable Neural Arrays (FPNA) lead to powerful neural architectures that are easy to map onto FPGAs, thanks to a simplified topology and an original data exchange scheme. This paper shows how FPGAs have led to the definition of the FPNA computation paradigm. Then it shows how FPNAs contribute to current and future FPGA-based neural implementations by solving the general problems that are raised by the implementation of complex neural networks onto FPGAs. PMID:11011795

  7. Metastable dynamics in heterogeneous neural fields.

    PubMed

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

    2015-01-01

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

  8. Metastable dynamics in heterogeneous neural fields

    PubMed Central

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

    2015-01-01

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

  9. Towards practical control design using neural computation

    NASA Technical Reports Server (NTRS)

    Troudet, Terry; Garg, Sanjay; Mattern, Duane; Merrill, Walter

    1991-01-01

    The objective is to develop neural network based control design techniques which address the issue of performance/control effort tradeoff. Additionally, the control design needs to address the important issue if achieving adequate performance in the presence of actuator nonlinearities such as position and rate limits. These issues are discussed using the example of aircraft flight control. Given a set of pilot input commands, a feedforward net is trained to control the vehicle within the constraints imposed by the actuators. This is achieved by minimizing an objective function which is the sum of the tracking errors, control input rates and control input deflections. A tradeoff between tracking performance and control smoothness is obtained by varying, adaptively, the weights of the objective function. The neurocontroller performance is evaluated in the presence of actuator dynamics using a simulation of the vehicle. Appropriate selection of the different weights in the objective function resulted in the good tracking of the pilot commands and smooth neurocontrol. An extension of the neurocontroller design approach is proposed to enhance its practicality.

  10. Detection of interplanetary activity using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Gothoskar, Pradeep; Khobragade, Shyam

    1995-12-01

    Early detection of interplanetary activity is important when attempting to associate, with better accuracy, interplanetary phenomena with solar activity and geomagnetic disturbances. However, for a large number of interplanetary observations to be done every day, extensive data analysis is required, leading to a delay in the detection of transient interplanetary activity. In particular, the interplanetary scintillation (IPS) observations done with Ooty Radio Telescope (ORT) need extensive human effort to reduce the data and to model, often subjectively, the scintillation power spectra. We have implemented an artificial neural network (ANN) to detect interplanetary activity using the power spectrum scintillation. The ANN was trained to detect the disturbed power spectra, used as an indicator of the interplanetary activity, and to recognize normal and strong scattering spectra from a large data base of IPS spectra. The coincidence efficiency of classification by the network compared with the experts' judgement to detect the normal, disturbed and strong scattering spectra was found to be greater than 80 per cent. The neural network, when applied during the IPS mapping programme to provide early indication of interplanetary activity, would significantly help the ongoing efforts to predict geomagnetic disturbances.

  11. Axonal Control of the Adult Neural Stem Cell Niche

    PubMed Central

    Tong, Cheuk Ka; Chen, Jiadong; Cebrián-Silla, Arantxa; Mirzadeh, Zaman; Obernier, Kirsten; Guinto, Cristina D.; Tecott, Laurence H.; García-Verdugo, Jose Manuel; Kriegstein, Arnold; Alvarez-Buylla, Arturo

    2014-01-01

    SUMMARY The ventricular-subventricular zone (V-SVZ) is an extensive germinal niche containing neural stem cells (NSC) in the walls of the lateral ventricles of the adult brain. How the adult brain’s neural activity influences the behavior of adult NSCs remains largely unknown. We show that serotonergic (5HT) axons originating from a small group of neurons in the raphe form an extensive plexus on most of the ventricular walls. Electron microscopy revealed intimate contacts between 5HT axons and NSCs (B1) or ependymal cells (E1) and these cells were labeled by a transsynaptic viral tracer injected into the raphe. B1 cells express the 5HT receptors 2C and 5A. Electrophysiology showed that activation of these receptors in B1 cells induced small inward currents. Intraventricular infusion of 5HT2C agonist or antagonist increased or decreased V-SVZ proliferation, respectively. These results indicate that supraependymal 5HT axons directly interact with NSCs to regulate neurogenesis via 5HT2C. PMID:24561083

  12. Axonal control of the adult neural stem cell niche.

    PubMed

    Tong, Cheuk Ka; Chen, Jiadong; Cebrián-Silla, Arantxa; Mirzadeh, Zaman; Obernier, Kirsten; Guinto, Cristina D; Tecott, Laurence H; García-Verdugo, Jose Manuel; Kriegstein, Arnold; Alvarez-Buylla, Arturo

    2014-04-01

    The ventricular-subventricular zone (V-SVZ) is an extensive germinal niche containing neural stem cells (NSCs) in the walls of the lateral ventricles of the adult brain. How the adult brain's neural activity influences the behavior of adult NSCs remains largely unknown. We show that serotonergic (5HT) axons originating from a small group of neurons in the raphe form an extensive plexus on most of the ventricular walls. Electron microscopy revealed intimate contacts between 5HT axons and NSCs (B1) or ependymal cells (E1) and these cells were labeled by a transsynaptic viral tracer injected into the raphe. B1 cells express the 5HT receptors 2C and 5A. Electrophysiology showed that activation of these receptors in B1 cells induced small inward currents. Intraventricular infusion of 5HT2C agonist or antagonist increased or decreased V-SVZ proliferation, respectively. These results indicate that supraependymal 5HT axons directly interact with NSCs to regulate neurogenesis via 5HT2C. PMID:24561083

  13. Neural probes with multi-drug delivery capability.

    PubMed

    Shin, Hyogeun; Lee, Hyunjoo J; Chae, Uikyu; Kim, Huiyoung; Kim, Jeongyeon; Choi, Nakwon; Woo, Jiwan; Cho, Yakdol; Lee, C Justin; Yoon, Eui-Sung; Cho, Il-Joo

    2015-01-01

    Multi-functional neural probes are promising platforms to conduct efficient and effective in-depth studies of brain by recording neural signals as well as modulating the signals with various stimuli. Here we present a neural probe with an embedded microfluidic channel (chemtrode) with multi-drug delivery capability suitable for small animal experiments. We integrated a staggered herringbone mixer (SHM) in a 3-inlet microfluidic chip directly into our chemtrode. This chip, which also serves as a compact interface for the chemtrode, allows for efficient delivery of small volumes of multiple or concentration-modulated drugs via chaotic mixing. We demonstrated the successful infusion of combinatorial inputs of three chemicals with a low flow rate (170 nl min(-1)). By sequentially delivering red, green, and blue inks from each inlet and conducting visual inspections at the tip of the chemtrode, we measured a short residence time of 14 s which corresponds to a small swept volume of 66 nl. Finally, we demonstrated the potential of our proposed chemtrode as an enabling tool through extensive in vivo mice experiments. Through simultaneous infusions of a chemical (pilocarpine or tetrodotoxin (TTX) at inlet 1), a buffer solution (saline at inlet 2), and 4',6-diamidino-2-phenylindole (DAPI at inlet 3) locally into a mouse brain, we not only modulated the neural activities by varying the concentration of the chemical but also locally stained the cells at our target region (CA1 in hippocampus). More specifically, infusion of pilocarpine with a higher concentration resulted in an increase in neural activities while infusion of TTX with a higher concentration resulted in a distinctive reduction. For each chemical, we acquired multiple sets of data using only one mouse through a single implantation of the chemtrode. Our proposed chemtrode offers 1) multiplexed delivery of three drugs through a compact packaging with a small swept volume and 2) simultaneous recording to monitor near

  14. Neural substrates of approach-avoidance conflict decision-making

    PubMed Central

    Aupperle, Robin L.; Melrose, Andrew J.; Francisco, Alex; Paulus, Martin P.; Stein, Murray B.

    2014-01-01

    Animal approach-avoidance conflict paradigms have been used extensively to operationalize anxiety, quantify the effects of anxiolytic agents, and probe the neural basis of fear and anxiety. Results from human neuroimaging studies support that a frontal-striatal-amygdala neural circuitry is important for approach-avoidance learning. However, the neural basis of decision-making is much less clear in this context. Thus, we combined a recently developed human approach-avoidance paradigm with functional magnetic resonance imaging (fMRI) to identify neural substrates underlying approach-avoidance conflict decision-making. Fifteen healthy adults completed the approach-avoidance conflict (AAC) paradigm during fMRI. Analyses of variance were used to compare conflict to non-conflict (avoid-threat and approach-reward) conditions and to compare level of reward points offered during the decision phase. Trial-by-trial amplitude modulation analyses were used to delineate brain areas underlying decision-making in the context of approach/avoidance behavior. Conflict trials as compared to the non-conflict trials elicited greater activation within bilateral anterior cingulate cortex (ACC), anterior insula, and caudate, as well as right dorsolateral prefrontal cortex. Right caudate and lateral PFC activation was modulated by level of reward offered. Individuals who showed greater caudate activation exhibited less approach behavior. On a trial-by-trial basis, greater right lateral PFC activation related to less approach behavior. Taken together, results suggest that the degree of activation within prefrontal-striatal-insula circuitry determines the degree of approach versus avoidance decision-making. Moreover, the degree of caudate and lateral PFC activation is related to individual differences in approach-avoidance decision-making. Therefore, the AAC paradigm is ideally suited to probe anxiety-related processing differences during approach-avoidance decision-making. PMID:25224633

  15. Elastomeric and soft conducting microwires for implantable neural interfaces.

    PubMed

    Kolarcik, Christi L; Luebben, Silvia D; Sapp, Shawn A; Hanner, Jenna; Snyder, Noah; Kozai, Takashi D Y; Chang, Emily; Nabity, James A; Nabity, Shawn T; Lagenaur, Carl F; Cui, X Tracy

    2015-06-28

    Current designs for microelectrodes used for interfacing with the nervous system elicit a characteristic inflammatory response that leads to scar tissue encapsulation, electrical insulation of the electrode from the tissue and ultimately failure. Traditionally, relatively stiff materials like tungsten and silicon are employed which have mechanical properties several orders of magnitude different from neural tissue. This mechanical mismatch is thought to be a major cause of chronic inflammation and degeneration around the device. In an effort to minimize the disparity between neural interface devices and the brain, novel soft electrodes consisting of elastomers and intrinsically conducting polymers were fabricated. The physical, mechanical and electrochemical properties of these materials were extensively characterized to identify the formulations with the optimal combination of parameters including Young's modulus, elongation at break, ultimate tensile strength, conductivity, impedance and surface charge injection. Our final electrode has a Young's modulus of 974 kPa which is five orders of magnitude lower than tungsten and significantly lower than other polymer-based neural electrode materials. In vitro cell culture experiments demonstrated the favorable interaction between these soft materials and neurons, astrocytes and microglia, with higher neuronal attachment and a two-fold reduction in inflammatory microglia attachment on soft devices compared to stiff controls. Surface immobilization of neuronal adhesion proteins on these microwires further improved the cellular response. Finally, in vivo electrophysiology demonstrated the functionality of the elastomeric electrodes in recording single unit activity in the rodent visual cortex. The results presented provide initial evidence in support of the use of soft materials in neural interface applications. PMID:25993261

  16. How to build VLSI-efficient neural chips

    SciTech Connect

    Beiu, V.

    1998-02-01

    This paper presents several upper and lower bounds for the number-of-bits required for solving a classification problem, as well as ways in which these bounds can be used to efficiently build neural network chips. The focus will be on complexity aspects pertaining to neural networks: (1) size complexity and depth (size) tradeoffs, and (2) precision of weights and thresholds as well as limited interconnectivity. They show difficult problems-exponential growth in either space (precision and size) and/or time (learning and depth)-when using neural networks for solving general classes of problems (particular cases may enjoy better performances). The bounds for the number-of-bits required for solving a classification problem represent the first step of a general class of constructive algorithms, by showing how the quantization of the input space could be done in O (m{sup 2}n) steps. Here m is the number of examples, while n is the number of dimensions. The second step of the algorithm finds its roots in the implementation of a class of Boolean functions using threshold gates. It is substantiated by mathematical proofs for the size O (mn/{Delta}), and the depth O [log(mn)/log{Delta}] of the resulting network (here {Delta} is the maximum fan in). Using the fan in as a parameter, a full class of solutions can be designed. The third step of the algorithm represents a reduction of the size and an increase of its generalization capabilities. Extensions by using analogue COMPARISONs, allows for real inputs, and increase the generalization capabilities at the expense of longer training times. Finally, several solutions which can lower the size of the resulting neural network are detailed. The interesting aspect is that they are obtained for limited, or even constant, fan-ins. In support of these claims many simulations have been performed and are called upon.

  17. Identification of Neural Outgrowth Genes using Genome-Wide RNAi

    PubMed Central

    Sepp, Katharine J.; Hong, Pengyu; Lizarraga, Sofia B.; Liu, Judy S.; Mejia, Luis A.; Walsh, Christopher A.; Perrimon, Norbert

    2008-01-01

    While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi) on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new genes that have

  18. Elastomeric and soft conducting microwires for implantable neural interfaces

    PubMed Central

    Kolarcik, Christi L.; Luebben, Silvia D.; Sapp, Shawn A.; Hanner, Jenna; Snyder, Noah; Kozai, Takashi D.Y.; Chang, Emily; Nabity, James A.; Nabity, Shawn T.; Lagenaur, Carl F.; Cui, X. Tracy

    2015-01-01

    Current designs for microelectrodes used for interfacing with the nervous system elicit a characteristic inflammatory response that leads to scar tissue encapsulation, electrical insulation of the electrode from the tissue and ultimately failure. Traditionally, relatively stiff materials like tungsten and silicon are employed which have mechanical properties several orders of magnitude different from neural tissue. This mechanical mismatch is thought to be a major cause of chronic inflammation and degeneration around the device. In an effort to minimize the disparity between neural interface devices and the brain, novel soft electrodes consisting of elastomers and intrinsically conducting polymers were fabricated. The physical, mechanical and electrochemical properties of these materials were extensively characterized to identify the formulations with the optimal combination of parameters including Young’s modulus, elongation at break, ultimate tensile strength, conductivity, impedance and surface charge injection. Our final electrode has a Young’s modulus of 974 kPa which is five orders of magnitude lower than tungsten and significantly lower than other polymer-based neural electrode materials. In vitro cell culture experiments demonstrated the favorable interaction between these soft materials and neurons, astrocytes and microglia, with higher neuronal attachment and a two-fold reduction in inflammatory microglia attachment on soft devices compared to stiff controls. Surface immobilization of neuronal adhesion proteins on these microwires further improved the cellular response. Finally, in vivo electrophysiology demonstrated the functionality of the elastomeric electrodes in recording single unit activity in the rodent visual cortex. The results presented provide initial evidence in support of the use of soft materials in neural interface applications. PMID:25993261

  19. Development of Methodologies for IV and V of Neural Networks

    NASA Technical Reports Server (NTRS)

    Taylor, Brian; Darrah, Marjorie

    2003-01-01

    Non-deterministic systems often rely upon neural network (NN) technology to "lean" to manage flight systems under controlled conditions using carefully chosen training sets. How can these adaptive systems be certified to ensure that they will become increasingly efficient and behave appropriately in real-time situations? The bulk of Independent Verification and Validation (IV&V) research of non-deterministic software control systems such as Adaptive Flight Controllers (AFC's) addresses NNs in well-behaved and constrained environments such as simulations and strict process control. However, neither substantive research, nor effective IV&V techniques have been found to address AFC's learning in real-time and adapting to live flight conditions. Adaptive flight control systems offer good extensibility into commercial aviation as well as military aviation and transportation. Consequently, this area of IV&V represents an area of growing interest and urgency. ISR proposes to further the current body of knowledge to meet two objectives: Research the current IV&V methods and assess where these methods may be applied toward a methodology for the V&V of Neural Network; and identify effective methods for IV&V of NNs that learn in real-time, including developing a prototype test bed for IV&V of AFC's. Currently. no practical method exists. lSR will meet these objectives through the tasks identified and described below. First, ISR will conduct a literature review of current IV&V technology. TO do this, ISR will collect the existing body of research on IV&V of non-deterministic systems and neural network. ISR will also develop the framework for disseminating this information through specialized training. This effort will focus on developing NASA's capability to conduct IV&V of neural network systems and to provide training to meet the increasing need for IV&V expertise in such systems.

  20. Degraded neural and behavioral processing of speech sounds in a rat model of Rett syndrome.

    PubMed

    Engineer, Crystal T; Rahebi, Kimiya C; Borland, Michael S; Buell, Elizabeth P; Centanni, Tracy M; Fink, Melyssa K; Im, Kwok W; Wilson, Linda G; Kilgard, Michael P

    2015-11-01

    Individuals with Rett syndrome have greatly impaired speech and language abilities. Auditory brainstem responses to sounds are normal, but cortical responses are highly abnormal. In this study, we used the novel rat Mecp2 knockout model of Rett syndrome to document the neural and behavioral processing of speech sounds. We hypothesized that both speech discrimination ability and the neural response to speech sounds would be impaired in Mecp2 rats. We expected that extensive speech training would improve speech discrimination ability and the cortical response to speech sounds. Our results reveal that speech responses across all four auditory cortex fields of Mecp2 rats were hyperexcitable, responded slower, and were less able to follow rapidly presented sounds. While Mecp2 rats could accurately perform consonant and vowel discrimination tasks in quiet, they were significantly impaired at speech sound discrimination in background noise. Extensive speech training improved discrimination ability. Training shifted cortical responses in both Mecp2 and control rats to favor the onset of speech sounds. While training increased the response to low frequency sounds in control rats, the opposite occurred in Mecp2 rats. Although neural coding and plasticity are abnormal in the rat model of Rett syndrome, extensive therapy appears to be effective. These findings may help to explain some aspects of communication deficits in Rett syndrome and suggest that extensive rehabilitation therapy might prove beneficial. PMID:26321676

  1. The forces that shape embryos: physical aspects of convergent extension by cell intercalation

    NASA Astrophysics Data System (ADS)

    Keller, Ray; Shook, David; Skoglund, Paul

    2008-03-01

    We discuss the physical aspects of the morphogenic process of convergence (narrowing) and extension (lengthening) of tissues by cell intercalation. These movements, often referred to as 'convergent extension', occur in both epithelial and mesenchymal tissues during embryogenesis and organogenesis of invertebrates and vertebrates, and they play large roles in shaping the body plan during development. Our focus is on the presumptive mesodermal and neural tissues of the Xenopus (frog) embryo, tissues for which some physical measurements have been made. We discuss the physical aspects of how polarized cell motility, oriented along future tissue axes, generate the forces that drive oriented cell intercalation and how this intercalation results in convergence and extension or convergence and thickening of the tissue. Our goal is to identify aspects of these morphogenic movements for further biophysical, molecular and cell biological, and modeling studies.

  2. The Intelligent System of Cardiovascular Disease Diagnosis Based on Extension Data Mining

    NASA Astrophysics Data System (ADS)

    Sun, Baiqing; Li, Yange; Zhang, Lin

    This thesis gives the general definition of the concepts of extension knowledge, extension data mining and extension data mining theorem in high dimension space, and also builds the IDSS integrated system by the rough set, expert system and neural network, develops the relevant computer software. From the diagnosis tests, according to the common diseases of myocardial infarctions, angina pectoris and hypertension, and made the test result with physicians, the results shows that the sensitivity, specific and accuracy diagnosis by the IDSS are all higher than the physicians. It can improve the rate of the accuracy diagnosis of physician with the auxiliary help of this system, which have the obvious meaning in low the mortality, disability rate and high the survival rate, and has strong practical values and further social benefits.

  3. Overview of artificial neural networks.

    PubMed

    Zou, Jinming; Han, Yi; So, Sung-Sau

    2008-01-01

    The artificial neural network (ANN), or simply neural network, is a machine learning method evolved from the idea of simulating the human brain. The data explosion in modem drug discovery research requires sophisticated analysis methods to uncover the hidden causal relationships between single or multiple responses and a large set of properties. The ANN is one of many versatile tools to meet the demand in drug discovery modeling. Compared to a traditional regression approach, the ANN is capable of modeling complex nonlinear relationships. The ANN also has excellent fault tolerance and is fast and highly scalable with parallel processing. This chapter introduces the background of ANN development and outlines the basic concepts crucially important for understanding more sophisticated ANN. Several commonly used learning methods and network setups are discussed briefly at the end of the chapter. PMID:19065803

  4. Neural stimulation and recording electrodes.

    PubMed

    Cogan, Stuart F

    2008-01-01

    Electrical stimulation of nerve tissue and recording of neural electrical activity are the basis of emerging prostheses and treatments for spinal cord injury, stroke, sensory deficits, and neurological disorders. An understanding of the electrochemical mechanisms underlying the behavior of neural stimulation and recording electrodes is important for the development of chronically implanted devices, particularly those employing large numbers of microelectrodes. For stimulation, materials that support charge injection by capacitive and faradaic mechanisms are available. These include titanium nitride, platinum, and iridium oxide, each with certain advantages and limitations. The use of charge-balanced waveforms and maximum electrochemical potential excursions as criteria for reversible charge injection with these electrode materials are described and critiqued. Techniques for characterizing electrochemical properties relevant to stimulation and recording are described with examples of differences in the in vitro and in vivo response of electrodes. PMID:18429704

  5. Genetic attack on neural cryptography

    SciTech Connect

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

    2006-03-15

    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.

  6. Neural mechanisms of communicative innovation.

    PubMed

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

    2013-09-01

    Human referential communication is often thought as coding-decoding a set of symbols, neglecting that establishing shared meanings requires a computational mechanism powerful enough to mutually negotiate them. Sharing the meaning of a novel symbol might rely on similar conceptual inferences across communicators or on statistical similarities in their sensorimotor behaviors. Using magnetoencephalography, we assess spectral, temporal, and spatial characteristics of neural activity evoked when people generate and understand novel shared symbols during live communicative interactions. Solving those communicative problems induced comparable changes in the spectral profile of neural activity of both communicators and addressees. This shared neuronal up-regulation was spatially localized to the right temporal lobe and the ventromedial prefrontal cortex and emerged already before the occurrence of a specific communicative problem. Communicative innovation relies on neuronal computations that are shared across generating and understanding novel shared symbols, operating over temporal scales independent from transient sensorimotor behavior. PMID:23959895

  7. Terminal attractors in neural networks

    NASA Technical Reports Server (NTRS)

    Zak, Michail

    1989-01-01

    A new type of attractor (terminal attractors) for content-addressable memory, associative memory, and pattern recognition in artificial neural networks operating in continuous time is introduced. The idea of a terminal attractor is based upon a violation of the Lipschitz condition at a fixed point. As a result, the fixed point becomes a singular solution which envelopes the family of regular solutions, while each regular solution approaches such an attractor in finite time. It will be shown that terminal attractors can be incorporated into neural networks such that any desired set of these attractors with prescribed basins is provided by an appropriate selection of the synaptic weights. The applications of terminal attractors for content-addressable and associative memories, pattern recognition, self-organization, and for dynamical training are illustrated.

  8. Neural induction and early patterning in vertebrates.

    PubMed

    Ozair, Mohammad Zeeshan; Kintner, Chris; Brivanlou, Ali H

    2013-07-01

    In vertebrates, the development of the nervous system is triggered by signals from a powerful 'organizing' region of the early embryo during gastrulation. This phenomenon--neural induction--was originally discovered and given conceptual definition by experimental embryologists working with amphibian embryos. Work on the molecular circuitry underlying neural induction, also in the same model system, demonstrated that elimination of ongoing transforming growth factor-β (TGFβ) signaling in the ectoderm is the hallmark of anterior neural-fate acquisition. This observation is the basis of the 'default' model of neural induction. Endogenous neural inducers are secreted proteins that act to inhibit TGFβ ligands in the dorsal ectoderm. In the ventral ectoderm, where the signaling ligands escape the inhibitors, a non-neural fate is induced. Inhibition of the TGFβ pathway has now been demonstrated to be sufficient to directly induce neural fate in mammalian embryos as well as pluripotent mouse and human embryonic stem cells. Hence the molecular process that delineates neural from non-neural ectoderm is conserved across a broad range of organisms in the evolutionary tree. The availability of embryonic stem cells from mouse, primates, and humans will facilitate further understanding of the role of signaling pathways and their downstream mediators in neural induction in vertebrate embryos. PMID:24014419

  9. Functional neural anatomy of talent.

    PubMed

    Kalbfleisch, M Layne

    2004-03-01

    The terms gifted, talented, and intelligent all have meanings that suggest an individual's highly proficient or exceptional performance in one or more specific areas of strength. Other than Spearman's g, which theorizes about a general elevated level of potential or ability, more contemporary theories of intelligence are based on theoretical models that define ability or intelligence according to a priori categories of specific performance. Recent studies in cognitive neuroscience report on the neural basis of g from various perspectives such as the neural speed theory and the efficiency of prefrontal function. Exceptional talent is the result of interactions between goal-directed behavior and nonvolitional perceptual processes in the brain that have yet to be fully characterized and understood by the fields of psychology and cognitive neuroscience. Some developmental studies report differences in region-specific neural activation, recruitment patterns, and reaction times in subjects who are identified with high IQ scores according to traditional scales of assessment such as the WISC-III or Stanford-Binet. Although as cases of savants and prodigies illustrate, talent is not synonymous with high IQ. This review synthesizes information from the fields of psychometrics and gifted education, with findings from the neurosciences on the neural basis of intelligence, creativity, profiles of expert performers, cognitive function, and plasticity to suggest a paradigm for investigating talent as the maximal and productive use of either or both of one's high level of general intelligence or domain-specific ability. Anat Rec (Part B: New Anat) 277B:21-36, 2004. PMID:15052651

  10. Ozone Modeling Using Neural Networks.

    NASA Astrophysics Data System (ADS)

    Narasimhan, Ramesh; Keller, Joleen; Subramaniam, Ganesh; Raasch, Eric; Croley, Brandon; Duncan, Kathleen; Potter, William T.

    2000-03-01

    Ozone models for the city of Tulsa were developed using neural network modeling techniques. The neural models were developed using meteorological data from the Oklahoma Mesonet and ozone, nitric oxide, and nitrogen dioxide (NO2) data from Environmental Protection Agency monitoring sites in the Tulsa area. An initial model trained with only eight surface meteorological input variables and NO2 was able to simulate ozone concentrations with a correlation coefficient of 0.77. The trained model was then used to evaluate the sensitivity to the primary variables that affect ozone concentrations. The most important variables (NO2, temperature, solar radiation, and relative humidity) showed response curves with strong nonlinear codependencies. Incorporation of ozone concentrations from the previous 3 days into the model increased the correlation coefficient to 0.82. As expected, the ozone concentrations correlated best with the most recent (1-day previous) values. The model's correlation coefficient was increased to 0.88 by the incorporation of upper-air data from the National Weather Service's Nested Grid Model. Sensitivity analysis for the upper-air variables indicated unusual positive correlations between ozone and the relative humidity from 500 hPa to the tropopause in addition to the other expected correlations with upper-air temperatures, vertical wind velocity, and 1000-500-hPa layer thickness. The neural model results are encouraging for the further use of these systems to evaluate complex parameter cosensitivities, and for the use of these systems in automated ozone forecast systems.

  11. Neural Representations of Physics Concepts.

    PubMed

    Mason, Robert A; Just, Marcel Adam

    2016-06-01

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

  12. Three dimensional living neural networks

    NASA Astrophysics Data System (ADS)

    Linnenberger, Anna; McLeod, Robert R.; Basta, Tamara; Stowell, Michael H. B.

    2015-08-01

    We investigate holographic optical tweezing combined with step-and-repeat maskless projection micro-stereolithography for fine control of 3D positioning of living cells within a 3D microstructured hydrogel grid. Samples were fabricated using three different cell lines; PC12, NT2/D1 and iPSC. PC12 cells are a rat cell line capable of differentiation into neuron-like cells NT2/D1 cells are a human cell line that exhibit biochemical and developmental properties similar to that of an early embryo and when exposed to retinoic acid the cells differentiate into human neurons useful for studies of human neurological disease. Finally induced pluripotent stem cells (iPSC) were utilized with the goal of future studies of neural networks fabricated from human iPSC derived neurons. Cells are positioned in the monomer solution with holographic optical tweezers at 1064 nm and then are encapsulated by photopolymerization of polyethylene glycol (PEG) hydrogels formed by thiol-ene photo-click chemistry via projection of a 512x512 spatial light modulator (SLM) illuminated at 405 nm. Fabricated samples are incubated in differentiation media such that cells cease to divide and begin to form axons or axon-like structures. By controlling the position of the cells within the encapsulating hydrogel structure the formation of the neural circuits is controlled. The samples fabricated with this system are a useful model for future studies of neural circuit formation, neurological disease, cellular communication, plasticity, and repair mechanisms.

  13. Neural mechanisms of social dominance

    PubMed Central

    Watanabe, Noriya; Yamamoto, Miyuki

    2015-01-01

    In a group setting, individuals' perceptions of their own level of dominance or of the dominance level of others, and the ability to adequately control their behavior based on these perceptions are crucial for living within a social environment. Recent advances in neural imaging and molecular technology have enabled researchers to investigate the neural substrates that support the perception of social dominance and the formation of a social hierarchy in humans. At the systems' level, recent studies showed that dominance perception is represented in broad brain regions which include the amygdala, hippocampus, striatum, and various cortical networks such as the prefrontal, and parietal cortices. Additionally, neurotransmitter systems such as the dopaminergic and serotonergic systems, modulate and are modulated by the formation of the social hierarchy in a group. While these monoamine systems have a wide distribution and multiple functions, it was recently found that the Neuropeptide B/W contributes to the perception of dominance and is present in neurons that have a limited projection primarily to the amygdala. The present review discusses the specific roles of these neural regions and neurotransmitter systems in the perception of dominance and in hierarchy formation. PMID:26136644

  14. Neural prostheses and brain plasticity

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  15. Neural models and physiological reality.

    PubMed

    Lee, Barry B

    2008-01-01

    Neural models of retinal processing provide an important tool for analyzing retinal signals and their functional significance. However, it is here argued that in biological reality, retinal connectivity is unlikely to be as specific as ideal neural models might suggest. The retina is thought to provide functionally specific signals, but this specificity is unlikely to be anatomically complete. This is illustrated by examples of cone connectivity to macaque ganglion cells. For example, cells of the magnocellular pathway appear to avoid short-wavelength cone input, so that such input is negligible under normal conditions. However, there is anatomical, physiological, and psychophysical evidence that under special conditions, weak input may be revealed. Second, ideal models of how retinal information is centrally utilized have to take into account the biological reality of retinal signals. The stochastic nature of impulse trains modifies signal-to-noise ratio in unexpected ways. Also, non-linearities in cell responses make, for example, multiplexing of luminance and chromatic signals in the parvocellular pathway impracticable. The purpose of this analysis is to show than ideal neural models must confront an often more complex and nuanced physiological reality. PMID:18321399

  16. Neural network ultrasound image analysis

    NASA Astrophysics Data System (ADS)

    Schneider, Alexander C.; Brown, David G.; Pastel, Mary S.

    1993-09-01

    Neural network based analysis of ultrasound image data was carried out on liver scans of normal subjects and those diagnosed with diffuse liver disease. In a previous study, ultrasound images from a group of normal volunteers, Gaucher's disease patients, and hepatitis patients were obtained by Garra et al., who used classical statistical methods to distinguish from among these three classes. In the present work, neural network classifiers were employed with the same image features found useful in the previous study for this task. Both standard backpropagation neural networks and a recently developed biologically-inspired network called Dystal were used. Classification performance as measured by the area under a receiver operating characteristic curve was generally excellent for the back propagation networks and was roughly comparable to that of classical statistical discriminators tested on the same data set and documented in the earlier study. Performance of the Dystal network was significantly inferior; however, this may be due to the choice of network parameter. Potential methods for enhancing network performance was identified.

  17. Remote sensing-based neural network mapping of tsunami damage in Aceh, Indonesia.

    PubMed

    Aitkenhead, Matthew J; Lumsdon, Parivash; Miller, David R

    2007-09-01

    In addition to the loss of human life, the tsunami event of 26 December 2004 caused extensive damage to coastal areas. The scale of the disaster was such that remote sensing may be the only way to determine its effects on the landscape. This paper presents the results of a neural network-based mapping of part of the region of Aceh, Sumatra. Before-and-after satellite imagery, combined with a novel neural network methodology, enabled a characterisation of landscape change. The neural network technique used a threshold of acceptance for identification, in combination with a bootstrapped identification method for identifying problem pixels. Map analysis allowed identification of urban areas that were inaccessible by road, and which aid agencies could therefore only reach by air or sea. The methods used provide a rapid and effective mapping ability and would be a useful tool for aid agencies, insurance underwriters and environmental monitoring. PMID:17714164

  18. The neural correlates of identity faking and concealment: an FMRI study.

    PubMed

    Ding, Xiao Pan; Du, Xiaoxia; Lei, Du; Hu, Chao Super; Fu, Genyue; Chen, Guopeng

    2012-01-01

    The neural basis of self and identity has received extensive research. However, most of these existing studies have focused on situations where the internal representation of the self is consistent with the external one. The present study used fMRI methodology to examine the neural correlates of two different types of identity conflict: identity faking and concealment. Participants were presented with a sequence of names and asked to either conceal their own identity or fake another one. The results revealed that the right insular cortex and bilaterally inferior frontal gyrus were more active for identity concealment compared to the control condition, whereas identity faking elicited a significantly larger percentage signal increase than the control condition in the right superior frontal gyrus, left calcarine, and right caudate. These results suggest that different neural systems associated with both identity processing and deception were involved in identity concealment and faking. PMID:23144915

  19. Low Density Lipoprotein Receptor Related Proteins as Regulators of Neural Stem and Progenitor Cell Function

    PubMed Central

    Landowski, Lila M.; Young, Kaylene M.

    2016-01-01

    The central nervous system (CNS) is a highly organised structure. Many signalling systems work in concert to ensure that neural stem cells are appropriately directed to generate progenitor cells, which in turn mature into functional cell types including projection neurons, interneurons, astrocytes, and oligodendrocytes. Herein we explore the role of the low density lipoprotein (LDL) receptor family, in particular family members LRP1 and LRP2, in regulating the behaviour of neural stem and progenitor cells during development and adulthood. The ability of LRP1 and LRP2 to bind a diverse and extensive range of ligands, regulate ligand endocytosis, recruit nonreceptor tyrosine kinases for direct signal transduction and signal in conjunction with other receptors, enables them to modulate many crucial neural cell functions. PMID:26949399

  20. Neural organization of spoken language revealed by lesion-symptom mapping.

    PubMed

    Mirman, Daniel; Chen, Qi; Zhang, Yongsheng; Wang, Ze; Faseyitan, Olufunsho K; Coslett, H Branch; Schwartz, Myrna F

    2015-01-01

    Studies of patients with acquired cognitive deficits following brain damage and studies using contemporary neuroimaging techniques form two distinct streams of research on the neural basis of cognition. In this study, we combine high-quality structural neuroimaging analysis techniques and extensive behavioural assessment of patients with persistent acquired language deficits to study the neural basis of language. Our results reveal two major divisions within the language system-meaning versus form and recognition versus production-and their instantiation in the brain. Phonological form deficits are associated with lesions in peri-Sylvian regions, whereas semantic production and recognition deficits are associated with damage to the left anterior temporal lobe and white matter connectivity with frontal cortex, respectively. These findings provide a novel synthesis of traditional and contemporary views of the cognitive and neural architecture of language processing, emphasizing dual routes for speech processing and convergence of white matter tracts for semantic control and/or integration. PMID:25879574

  1. Computer interpretation of thallium SPECT studies based on neural network analysis

    NASA Astrophysics Data System (ADS)

    Wang, David C.; Karvelis, K. C.

    1991-06-01

    A class of artificial intelligence (Al) programs known as neural networks are well suited to pattern recognition. A neural network is trained rather than programmed to recognize patterns. This differs from "expert system" Al programs in that it is not following an extensive set of rules determined by the programmer, but rather bases its decision on a gestalt interpretation of the image. The "bullseye" images from cardiac stress thallium tests performed on 50 male patients, as well as several simulated images were used to train the network. The network was able to accurately classify all patients in the training set. The network was then tested against 50 unknown patients and was able to correctly categorize 77% of the areas of ischemia and 92% of the areas of infarction. While not yet matching the ability of a trained physician, the neural network shows great promise in this area and has potential application in other areas of medical imaging.

  2. Demand forecasting using fuzzy neural computation, with special emphasis on weekend and public holiday forecasting

    SciTech Connect

    Srinivasan, D.; Chang, C.S.; Liew, A.C.

    1995-11-01

    This paper describes the implementation and forecasting results of a hybrid fuzzy neural technique, which combines neural network modeling, and techniques from fuzzy logic and fuzzy set theory for electric load forecasting. The strengths of this powerful technique lie in its ability to forecast accurately on weekdays, as well as, on weekends, public holidays, and days before and after public holidays. Furthermore, use of fuzzy logic effectively handles the load variations due to special events. The Fuzzy-Neural Network (FNN) has been extensively tested on actual data obtained from a power system for 24-hour ahead prediction based on forecast weather information. Very impressive results, with an average error of 0.62% on weekdays, 0.83% on Saturdays and 1.17% on Sundays and public holidays have been obtained. This approach avoids complex mathematical calculations and training on many years of data, and is simple to implement on a personal computer.

  3. Neural field simulator: two-dimensional spatio-temporal dynamics involving finite transmission speed

    PubMed Central

    Nichols, Eric J.; Hutt, Axel

    2015-01-01

    Neural Field models (NFM) play an important role in the understanding of neural population dynamics on a mesoscopic spatial and temporal scale. Their numerical simulation is an essential element in the analysis of their spatio-temporal dynamics. The simulation tool described in this work considers scalar spatially homogeneous neural fields taking into account a finite axonal transmission speed and synaptic temporal derivatives of first and second order. A text-based interface offers complete control of field parameters and several approaches are used to accelerate simulations. A graphical output utilizes video hardware acceleration to display running output with reduced computational hindrance compared to simulators that are exclusively software-based. Diverse applications of the tool demonstrate breather oscillations, static and dynamic Turing patterns and activity spreading with finite propagation speed. The simulator is open source to allow tailoring of code and this is presented with an extension use case. PMID:26539105

  4. Cyclone track forecasting based on satellite images using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Kovordányi, Rita; Roy, Chandan

    Many places around the world are exposed to tropical cyclones and associated storm surges. In spite of massive efforts, a great number of people die each year as a result of cyclone events. To mitigate this damage, improved forecasting techniques must be developed. The technique presented here uses artificial neural networks to interpret NOAA-AVHRR satellite images. A multi-layer neural network, resembling the human visual system, was trained to forecast the movement of cyclones based on satellite images. The trained network produced correct directional forecast for 98% of test images, thus showing a good generalization capability. The results indicate that multi-layer neural networks could be further developed into an effective tool for cyclone track forecasting using various types of remote sensing data. Future work includes extension of the present network to handle a wide range of cyclones and to take into account supplementary information, such as wind speeds, water temperature, humidity, and air pressure.

  5. Neural Organization of Spoken Language Revealed by Lesion-Symptom Mapping

    PubMed Central

    Mirman, Daniel; Chen, Qi; Zhang, Yongsheng; Wang, Ze; Faseyitan, Olufunsho K.; Coslett, H. Branch; Schwartz, Myrna F.

    2015-01-01

    Studies of patients with acquired cognitive deficits following brain damage and studies using contemporary neuroimaging techniques form two distinct streams of research on the neural basis of cognition. In this study, we combine high-quality structural neuroimaging analysis techniques and extensive behavioral assessment of patients with persistent acquired language deficits to study the neural basis of language. Our results reveal two major divisions within the language system – meaning vs. form and recognition vs. production – and their instantiation in the brain. Phonological form deficits are associated with lesions in peri-Sylvian regions, whereas semantic production and recognition deficits are associated with damage to the left anterior temporal lobe and white matter connectivity with frontal cortex, respectively. These findings provide a novel synthesis of traditional and contemporary views of the cognitive and neural architecture of language processing, emphasizing dual-routes for speech processing and convergence of white matter tracts for semantic control and/or integration. PMID:25879574

  6. Neural network application for radionuclide modelling and prediction of radioactivity levels

    NASA Astrophysics Data System (ADS)

    Lynch, Myron Corbett, Jr.

    Existing applications of artificial neural networks in physics research and development have been analyzed as a basis for proposing new opportunities using that AI technology for data analysis in physics. A taxonomy was developed, based on an extensive literature search, for physics problems where neural network applications have been useful. Then, a particular use of neural networks was carried out to study ways to predict normal concentrations of radioactivity measured at monitoring stations in different geographic locations. The purpose of the data collection and analysis was to establish background levels that would serve as bases for detecting unusual levels of radioactivity, for example due to nuclear weapons testing, in these physical environments. Useful data sets were developed in this area and a process was discovered for modeling the background levels.

  7. Facial expression recognition using constructive neural networks

    NASA Astrophysics Data System (ADS)

    Ma, Liying; Khorasani, Khashayar

    2001-08-01

    The computer-based recognition of facial expressions has been an active area of research for quite a long time. The ultimate goal is to realize intelligent and transparent communications between human beings and machines. The neural network (NN) based recognition methods have been found to be particularly promising, since NN is capable of implementing mapping from the feature space of face images to the facial expression space. However, finding a proper network size has always been a frustrating and time consuming experience for NN developers. In this paper, we propose to use the constructive one-hidden-layer feed forward neural networks (OHL-FNNs) to overcome this problem. The constructive OHL-FNN will obtain in a systematic way a proper network size which is required by the complexity of the problem being considered. Furthermore, the computational cost involved in network training can be considerably reduced when compared to standard back- propagation (BP) based FNNs. In our proposed technique, the 2-dimensional discrete cosine transform (2-D DCT) is applied over the entire difference face image for extracting relevant features for recognition purpose. The lower- frequency 2-D DCT coefficients obtained are then used to train a constructive OHL-FNN. An input-side pruning technique previously proposed by the authors is also incorporated into the constructive OHL-FNN. An input-side pruning technique previously proposed by the authors is also incorporated into the constructive learning process to reduce the network size without sacrificing the performance of the resulting network. The proposed technique is applied to a database consisting of images of 60 men, each having the resulting network. The proposed technique is applied to a database consisting of images of 60 men, each having 5 facial expression images (neutral, smile, anger, sadness, and surprise). Images of 40 men are used for network training, and the remaining images are used for generalization and

  8. Neural dynamics during repetitive visual stimulation

    NASA Astrophysics Data System (ADS)

    Tsoneva, Tsvetomira; Garcia-Molina, Gary; Desain, Peter

    2015-12-01

    Objective. Steady-state visual evoked potentials (SSVEPs), the brain responses to repetitive visual stimulation (RVS), are widely utilized in neuroscience. Their high signal-to-noise ratio and ability to entrain oscillatory brain activity are beneficial for their applications in brain-computer interfaces, investigation of neural processes underlying brain rhythmic activity (steady-state topography) and probing the causal role of brain rhythms in cognition and emotion. This paper aims at analyzing the space and time EEG dynamics in response to RVS at the frequency of stimulation and ongoing rhythms in the delta, theta, alpha, beta, and gamma bands. Approach.We used electroencephalography (EEG) to study the oscillatory brain dynamics during RVS at 10 frequencies in the gamma band (40-60 Hz). We collected an extensive EEG data set from 32 participants and analyzed the RVS evoked and induced responses in the time-frequency domain. Main results. Stable SSVEP over parieto-occipital sites was observed at each of the fundamental frequencies and their harmonics and sub-harmonics. Both the strength and the spatial propagation of the SSVEP response seem sensitive to stimulus frequency. The SSVEP was more localized around the parieto-occipital sites for higher frequencies (>54 Hz) and spread to fronto-central locations for lower frequencies. We observed a strong negative correlation between stimulation frequency and relative power change at that frequency, the first harmonic and the sub-harmonic components over occipital sites. Interestingly, over parietal sites for sub-harmonics a positive correlation of relative power change and stimulation frequency was found. A number of distinct patterns in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz) and beta (15-30 Hz) bands were also observed. The transient response, from 0 to about 300 ms after stimulation onset, was accompanied by increase in delta and theta power over fronto-central and occipital sites, which returned to baseline

  9. Ror2 signaling is required for local upregulation of GFD6 and activation of BMP signaling at the neural plate border.

    PubMed

    Schille, Carolin; Bayerlová, Michaela; Bleckmann, Annalen; Schambony, Alexandra

    2016-09-01

    The receptor tyrosine kinase Ror2 is a major Wnt receptor that activates β-catenin-independent signaling and plays a conserved role in the regulation of convergent extension movements and planar cell polarity in vertebrates. Mutations in the ROR2 gene cause recessive Robinow syndrome in humans, a short-limbed dwarfism associated with craniofacial malformations. Here, we show that Ror2 is required for local upregulation of gdf6 at the neural plate border in Xenopus embryos. Ror2 morphant embryos fail to upregulate neural plate border genes and show defects in the induction of neural crest cell fate. These embryos lack the spatially restricted activation of BMP signaling at the neural plate border at early neurula stages, which is required for neural crest induction. Ror2-dependent planar cell polarity signaling is required in the dorsolateral marginal zone during gastrulation indirectly to upregulate the BMP ligand Gdf6 at the neural plate border and Gdf6 is sufficient to rescue neural plate border specification in Ror2 morphant embryos. Thereby, Ror2 links Wnt/planar cell polarity signaling to BMP signaling in neural plate border specification and neural crest induction. PMID:27578181

  10. Adolescents' Neural Processing of Risky Decisions: Effects of Sex and Behavioral Disinhibition

    PubMed Central

    Crowley, Thomas J.; Dalwani, Manish S.; Mikulich-Gilbertson, Susan K.; Young, Susan E.; Sakai, Joseph T.; Raymond, Kristen M.; McWilliams, Shannon K.; Roark, Melissa J.; Banich, Marie T.

    2015-01-01

    Background Accidental injury and homicide, relatively common among adolescents, often follow risky behaviors; those are done more by boys and by adolescents with greater behavioral disinhibition (BD). Hypothesis Neural processing during adolescents' risky decision-making will differ in youths with greater BD severity, and in males vs. females, both before cautious behaviors and before risky behaviors. Methodology/Principal Findings 81 adolescents (Patients with substance and conduct problems, and comparison youths (Comparisons)), assessed in a 2 x 2 design (Patients:Comparisons x Male:Female) repeatedly decided between doing a cautious behavior that earned 1 cent, or a risky one that either won 5 or lost 10 cents. Odds of winning after risky responses gradually decreased. Functional magnetic resonance imaging captured brain activity during 4-sec deliberation periods preceding responses. Most neural activation appeared in known decision-making structures. Patients, who had more severe BD scores and clinical problems than Comparisons, also had extensive neural hypoactivity. Comparisons' greater activation before cautious responses included frontal pole, medial prefrontal cortex, striatum, and other regions; and before risky responses, insula, temporal, and parietal regions. Males made more risky and fewer cautious responses than females, but before cautious responses males activated numerous regions more than females. Before risky behaviors female-greater activation was more posterior, and male-greater more anterior. Conclusions/Significance Neural processing differences during risky-cautious decision-making may underlie group differences in adolescents' substance-related and antisocial risk-taking. Patients reported harmful real-life decisions and showed extensive neural hypoactivity during risky-or-cautious decision-making. Males made more risky responses than females; apparently biased toward risky decisions, males (compared with females) utilized many more neural

  11. Satellite image analysis using neural networks

    NASA Technical Reports Server (NTRS)

    Sheldon, Roger A.

    1990-01-01

    The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

  12. Coherence resonance in bursting neural networks

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  13. A Case of Extensive Pityriasis Alba

    PubMed Central

    Kang, Ju Hyun; Kim, Sang Hyun; Seo, Jong Keun; Sung, Ho Suk; Hwang, Seon Wook

    2008-01-01

    Pityriasis alba (PA) is a common benign disease, characterized by hypopigmented macules or patches on the face, usually seen in children. However, two uncommon variants exist, a pigmenting type and an extensive type. Extensive PA is rare. The lesions tend to be less scaly, more persistent, more generalized, more symmetrical, and more frequently seen over the trunk and less so over the face. We report a child who had extensive PA lesions. PMID:27303180

  14. Introduction to Concepts in Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    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. NASA JSC neural network survey results

    NASA Technical Reports Server (NTRS)

    Greenwood, Dan

    1987-01-01

    A survey of Artificial Neural Systems in support of NASA's (Johnson Space Center) Automatic Perception for Mission Planning and Flight Control Research Program was conducted. Several of the world's leading researchers contributed papers containing their most recent results on artificial neural systems. These papers were broken into categories and descriptive accounts of the results make up a large part of this report. Also included is material on sources of information on artificial neural systems such as books, technical reports, software tools, etc.

  16. Spatiotemporal dynamics of continuum neural fields

    NASA Astrophysics Data System (ADS)

    Bressloff, Paul C.

    2012-01-01

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

  17. Adaptive optimization and control using neural networks

    SciTech Connect

    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.

  18. Applying the multivariate time-rescaling theorem to neural population models

    PubMed Central

    Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

    2011-01-01

    Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

  19. Advances in neural networks research: an introduction.

    PubMed

    Kozma, Robert; Bressler, Steven; Perlovsky, Leonid; Venayagamoorthy, Ganesh Kumar

    2009-01-01

    The present Special Issue "Advances in Neural Networks Research: IJCNN2009" provides a state-of-art overview of the field of neural networks. It includes 39 papers from selected areas of the 2009 International Joint Conference on Neural Networks (IJCNN2009). IJCNN2009 took place on June 14-19, 2009 in Atlanta, Georgia, USA, and it represents an exemplary collaboration between the International Neural Networks Society and the IEEE Computational Intelligence Society. Topics in this issue include neuroscience and cognitive science, computational intelligence and machine learning, hybrid techniques, nonlinear dynamics and chaos, various soft computing technologies, intelligent signal processing and pattern recognition, bioinformatics and biomedicine, and engineering applications. PMID:19632811

  20. Emerging Neural Stimulation Technologies for Bladder Dysfunctions

    PubMed Central

    Lee, Jee Woong; Kim, Daejeong; Yoo, Sangjin; Lee, Hyungsup; Lee, Gu-Haeng; Nam, Yoonkey

    2015-01-01

    In the neural engineering field, physiological dysfunctions are approached by identifying the target nerves and providing artificial stimulation to restore the function. Neural stimulation and recording technologies play a central role in this approach, and various engineering devices and stimulation techniques have become available to the medical community. For bladder control problems, electrical stimulation has been used as one of the treatments, while only a few emerging neurotechnologies have been used to tackle these problems. In this review, we introduce some recent developments in neural stimulation technologies including microelectrode array, closed-loop neural stimulation, optical stimulation, and ultrasound stimulation. PMID:25833475

  1. Neural repair in the adult brain

    PubMed Central

    Jessberger, Sebastian

    2016-01-01

    Acute or chronic injury to the adult brain often results in substantial loss of neural tissue and subsequent permanent functional impairment. Over the last two decades, a number of approaches have been developed to harness the regenerative potential of neural stem cells and the existing fate plasticity of neural cells in the nervous system to prevent tissue loss or to enhance structural and functional regeneration upon injury. Here, we review recent advances of stem cell-associated neural repair in the adult brain, discuss current challenges and limitations, and suggest potential directions to foster the translation of experimental stem cell therapies into the clinic. PMID:26918167

  2. Neural network based system for equipment surveillance

    DOEpatents

    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.

  3. Neural network based system for equipment surveillance

    DOEpatents

    Vilim, Richard B.; Gross, Kenneth C.; Wegerich, Stephan W.

    1998-01-01

    A method and system 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.

  4. Nonlinear PLS modeling using neural networks

    SciTech Connect

    Qin, S.J.; McAvoy, T.J.

    1994-12-31

    This paper discusses the embedding of neural networks into the framework of the PLS (partial least squares) modeling method resulting in a neural net PLS modeling approach. By using the universal approximation property of neural networks, the PLS modeling method is genealized to a nonlinear framework. The resulting model uses neural networks to capture the nonlinearity and keeps the PLS projection to attain robust generalization property. In this paper, the standard PLS modeling method is briefly reviewed. Then a neural net PLS (NNPLS) modeling approach is proposed which incorporates feedforward networks into the PLS modeling. A multi-input-multi-output nonlinear modeling task is decomposed into linear outer relations and simple nonlinear inner relations which are performed by a number of single-input-single-output networks. Since only a small size network is trained at one time, the over-parametrized problem of the direct neural network approach is circumvented even when the training data are very sparse. A conjugate gradient learning method is employed to train the network. It is shown that, by analyzing the NNPLS algorithm, the global NNPLS model is equivalent to a multilayer feedforward network. Finally, applications of the proposed NNPLS method are presented with comparison to the standard linear PLS method and the direct neural network approach. The proposed neural net PLS method gives better prediction results than the PLS modeling method and the direct neural network approach.

  5. Neural network modeling of distillation columns

    SciTech Connect

    Baratti, R.; Vacca, G.; Servida, A.

    1995-06-01

    Neural network modeling (NNM) was implemented for monitoring and control applications on two actual distillation columns: the butane splitter tower and the gasoline stabilizer. The two distillation columns are in operation at the SARAS refinery. Results show that with proper implementation techniques NNM can significantly improve column operation. The common belief that neural networks can be used as black-box process models is not completely true. Effective implementation always requires a minimum degree of process knowledge to identify the relevant inputs to the net. After background and generalities on neural network modeling, the paper describes efforts on the development of neural networks for the two distillation units.

  6. Screening for Open Neural Tube Defects.

    PubMed

    Krantz, David A; Hallahan, Terrence W; Carmichael, Jonathan B

    2016-06-01

    Biochemical prenatal screening was initiated with the use of maternal serum alpha fetoprotein to screen for open neural tube defects. Screening now includes multiple marker and sequential screening protocols involving serum and ultrasound markers to screen for aneuploidy. Recently cell-free DNA screening for aneuploidy has been initiated, but does not screen for neural tube defects. Although ultrasound is highly effective in identifying neural tube defects in high-risk populations, in decentralized health systems maternal serum screening still plays a significant role. Abnormal maternal serum alpha fetoprotein alone or in combination with other markers may indicate adverse pregnancy outcome in the absence of open neural tube defects. PMID:27235920

  7. Stochastic cellular automata model of neural networks.

    PubMed

    Goltsev, A V; de Abreu, F V; Dorogovtsev, S N; Mendes, J F F

    2010-06-01

    We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers, and spontaneous activity. This model has a complex phase diagram with self-organized active neural states, hybrid phase transitions, and a rich array of behaviors. We show that if spontaneous activity (noise) reaches a threshold level then global neural oscillations emerge. Stochastic resonance is a precursor of this dynamical phase transition. These oscillations are an intrinsic property of even small groups of 50 neurons. PMID:20866454

  8. NeuroMEMS: Neural Probe Microtechnologies

    PubMed Central

    HajjHassan, Mohamad; Chodavarapu, Vamsy; Musallam, Sam

    2008-01-01

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

  9. Electronic neural networks for global optimization

    NASA Technical Reports Server (NTRS)

    Thakoor, A. P.; Moopenn, A. W.; Eberhardt, S.

    1990-01-01

    An electronic neural network with feedback architecture, implemented in analog custom VLSI is described. Its application to problems of global optimization for dynamic assignment is discussed. The convergence properties of the neural network hardware are compared with computer simulation results. The neural network's ability to provide optimal or near optimal solutions within only a few neuron time constants, a speed enhancement of several orders of magnitude over conventional search methods, is demonstrated. The effect of noise on the circuit dynamics and the convergence behavior of the neural network hardware is also examined.

  10. Load forecasting using artificial neural networks

    SciTech Connect

    Pham, K.D.

    1995-12-31

    Artificial neural networks, modeled after their biological counterpart, have been successfully applied in many diverse areas including speech and pattern recognition, remote sensing, electrical power engineering, robotics and stock market forecasting. The most commonly used neural networks are those that gained knowledge from experience. Experience is presented to the network in form of the training data. Once trained, the neural network can recognized data that it has not seen before. This paper will present a fundamental introduction to the manner in which neural networks work and how to use them in load forecasting.

  11. Neural learning of constrained nonlinear transformations

    NASA Technical Reports Server (NTRS)

    Barhen, Jacob; Gulati, Sandeep; Zak, Michail

    1989-01-01

    Two issues that are fundamental to developing autonomous intelligent robots, namely, rudimentary learning capability and dexterous manipulation, are examined. A powerful neural learning formalism is introduced for addressing a large class of nonlinear mapping problems, including redundant manipulator inverse kinematics, commonly encountered during the design of real-time adaptive control mechanisms. Artificial neural networks with terminal attractor dynamics are used. The rapid network convergence resulting from the infinite local stability of these attractors allows the development of fast neural learning algorithms. Approaches to manipulator inverse kinematics are reviewed, the neurodynamics model is discussed, and the neural learning algorithm is presented.

  12. The Neural Crest in Cardiac Congenital Anomalies

    PubMed Central

    Keyte, Anna; Hutson, Mary Redmond

    2012-01-01

    This review discusses the function of neural crest as they relate to cardiovascular defects. The cardiac neural crest cells are a subpopulation of cranial neural crest discovered nearly 30 years ago by ablation of premigratory neural crest. The cardiac neural crest cells are necessary for normal cardiovascular development. We begin with a description of the crest cells in normal development, including their function in remodeling the pharyngeal arch arteries, outflow tract septation, valvulogenesis, and development of the cardiac conduction system. The cells are also responsible for modulating signaling in the caudal pharynx, including the second heart field. Many of the molecular pathways that are known to influence specification, migration, patterning and final targeting of the cardiac neural crest cells are reviewed. The cardiac neural crest cells play a critical role in the pathogenesis of various human cardiocraniofacial syndromes such as DiGeorge, Velocardiofacial, CHARGE, Fetal Alcohol, Alagille, LEOPARD, and Noonan syndromes, as well as Retinoic Acid Embryopathy. The loss of neural crest cells or their dysfunction may not always directly cause abnormal cardiovascular development, but are involved secondarily because crest cells represent a major component in the complex tissue interactions in the head, pharynx and outflow tract. Thus many of the human syndromes linking defects in the heart, face and brain can be better understood when considered within the context of a single cardiocraniofacial developmental module with the neural crest being a key cell type that interconnects the regions. PMID:22595346

  13. Stage-dependent plasticity of the anterior neural folds to form neural crest.

    PubMed

    Ezin, Maxellende; Barembaum, Meyer; Bronner, Marianne E

    2014-01-01

    The anterior neural fold (ANF) is the only region of the neural tube that does not produce neural crest cells. Instead, ANF cells contribute to the olfactory and lens placodes, as well as to the forebrain and epidermis. Here, we test the ability of the ANF to form neural crest by performing heterotopic transplantation experiments in the chick embryo. We find that, at the neurula stage (HH stage 7), the chick ANF retains the ability to form migrating neural crest cells when transplanted caudally to rostral hindbrain levels. This ability is gradually lost, such that by HH9, this tissue appears to no longer have the potential to form neural crest. In contrast to the ANF, hindbrain dorsal neural folds transplanted rostrally fail to contribute to the olfactory placode but instead continue to generate neural crest cells. The transcription factor GANF is expressed in the ANF and its morpholino-mediated knock-down expands the neural crest domain rostrally and results in the production of migratory cells emerging from the ANF; however, these cells fail to express the HNK1 neural crest marker, suggesting only partial conversion. Our results show that environmental factors can imbue the chick anterior neural folds to assume a neural crest cell fate via a mechanism that partially involves loss of GANF. PMID:25264214

  14. Higher-order neural network software for distortion invariant object recognition

    NASA Technical Reports Server (NTRS)

    Reid, Max B.; Spirkovska, Lilly

    1991-01-01

    The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

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

    PubMed

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

    2000-04-01

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

  16. Spin-mediated consciousness theory: possible roles of neural membrane nuclear spin ensembles and paramagnetic oxygen.

    PubMed

    Hu, Huping; Wu, Maoxin

    2004-01-01

    A novel theory of consciousness is proposed in this paper. We postulate that consciousness is intrinsically connected to quantum spin since the latter is the origin of quantum effects in both Bohm and Hestenes quantum formulism and a fundamental quantum process associated with the structure of space-time. That is, spin is the "mind-pixel". The unity of mind is achieved by entanglement of the mind-pixels. Applying these ideas to the particular structures and dynamics of the brain, we theorize that human brain works as follows: through action potential modulated nuclear spin interactions and paramagnetic O2/NO driven activations, the nuclear spins inside neural membranes and proteins form various entangled quantum states some of which survive decoherence through quantum Zeno effects or in decoherence-free subspaces and then collapse contextually via irreversible and non-computable means producing consciousness and, in turn, the collective spin dynamics associated with said collapses have effects through spin chemistry on classical neural activities thus influencing the neural networks of the brain. Our proposal calls for extension of associative encoding of neural memories to the dynamical structures of neural membranes and proteins. Thus, according our theory, the nuclear spin ensembles are the "mind-screen" with nuclear spins as its pixels, the neural membranes and proteins are the mind-screen and memory matrices, and the biologically available paramagnetic species such as O2 and NO are pixel-activating agents. Together, they form the neural substrates of consciousness. We also present supporting evidence and make important predictions. We stress that our theory is experimentally verifiable with present technologies. Further, experimental realizations of intra-/inter-molecular nuclear spin coherence and entanglement, macroscopic entanglement of spin ensembles and NMR quantum computation, all in room temperatures, strongly suggest the possibility of a spin

  17. Multimodal optogenetic neural interfacing device fabricated by scalable optical fiber drawing technique.

    PubMed

    Davey, Christopher J; Argyros, Alexander; Fleming, Simon C; Solomon, Samuel G

    2015-12-01

    We present a novel approach to the design and manufacture of optrodes for use in the biomedical research field of optogenetic neural interfacing. Using recently developed optical fiber drawing techniques that involve co-drawing metal/polymer composite fiber, we have assembled and characterized a novel optrode with promising optical and electrical functionality. The fabrication technique is flexible, scalable, and amenable to extension to implantable optrodes with high-density arrays of multiple electrodes, waveguides, and drug delivery channels. PMID:26836662

  18. Automated neural network-based instrument validation system

    NASA Astrophysics Data System (ADS)

    Xu, Xiao

    2000-10-01

    In a complex control process, instrument calibration is periodically performed to maintain the instruments within the calibration range, which assures proper control and minimizes down time. Instruments are usually calibrated under out-of-service conditions using manual calibration methods, which may cause incorrect calibration or equipment damage. Continuous in-service calibration monitoring of sensors and instruments will reduce unnecessary instrument calibrations, give operators more confidence in instrument measurements, increase plant efficiency or product quality, and minimize the possibility of equipment damage during unnecessary manual calibrations. In this dissertation, an artificial neural network (ANN)-based instrument calibration verification system is designed to achieve the on-line monitoring and verification goal for scheduling maintenance. Since an ANN is a data-driven model, it can learn the relationships among signals without prior knowledge of the physical model or process, which is usually difficult to establish for the complex non-linear systems. Furthermore, the ANNs provide a noise-reduced estimate of the signal measurement. More importantly, since a neural network learns the relationships among signals, it can give an unfaulted estimate of a faulty signal based on information provided by other unfaulted signals; that is, provide a correct estimate of a faulty signal. This ANN-based instrument verification system is capable of detecting small degradations or drifts occurring in instrumentation, and preclude false control actions or system damage caused by instrument degradation. In this dissertation, an automated scheme of neural network construction is developed. Previously, the neural network structure design required extensive knowledge of neural networks. An automated design methodology was developed so that a network structure can be created without expert interaction. This validation system was designed to monitor process sensors plant

  19. Creating Teams Increases Extension Educator Productivity

    ERIC Educational Resources Information Center

    Chalker-Scott, Linda; Daniels, Catherine H.; Martini, Nicole

    2016-01-01

    The Garden Team at Washington State University is a transdisciplinary group of faculty, staff, and students with expertise in applied plant and soil sciences and an interest in Extension education. The team's primary mission is to create current, relevant, and peer-reviewed materials as Extension publications for home gardeners. The average yearly…

  20. Extension Specialists: A Self-Analysis.

    ERIC Educational Resources Information Center

    Gerber, John M.

    1985-01-01

    To document perceived changes in the role of the extension horticulture specialist, a national survey of state horticulture specialists was conducted in 1983. Extension specialists in horticulture appear to be moving away from the traditional activities of farm visits and personal interaction with individual producers. (CT)

  1. 36 CFR 251.89 - Time extensions.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 36 Parks, Forests, and Public Property 2 2010-07-01 2010-07-01 false Time extensions. 251.89... Appeal of Decisions Relating to Occupancy and Use of National Forest System Lands § 251.89 Time extensions. (a) Filing of notice of appeal. Time for filing a notice of appeal is not extendable. (b)...

  2. Plagiarism within Extension: Origin and Current Effects

    ERIC Educational Resources Information Center

    Rollins, Dora

    2011-01-01

    Extension publication editors from around the United States are finding cases of plagiarism within manuscripts that Extension educators submit as new public education materials. When editors confront such educators with the problem, some don't understand it as such, rationalizing that reproducing published information for a new purpose qualifies…

  3. A New Funding Model for Extension

    ERIC Educational Resources Information Center

    Brown, Paul W.; Otto, Daniel M.; Ouart, Michael D.

    2006-01-01

    The traditional funding model of the Cooperative Extension System has been stretched to its limits by increasing demand for information and programs without concurrent increases in funding by the public sector. As the social, economic, and political environments have evolved and become more complex, extension is often asked to apply the expertise…

  4. 78 FR 57790 - Extension of Time Limits

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-20

    ... Regulation Regarding the Extension of Time Limits, 78 FR 3367 (January 16, 2013) (Proposed Rule). The... Information and Time Limits for Submission of Factual Information, 78 FR 21246 (April 10, 2013). As to the... International Trade Administration 19 CFR Part 351 RIN 0625-AA94 Extension of Time Limits AGENCY:...

  5. 77 FR 33453 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-06

    .... Energy Information Administration Agency Information Collection Extension AGENCY: U.S. Energy Information... public comment on the proposed collection of information involving a three-year extension of the.... Comments are invited on: (a) Whether the proposed extended collection of information is necessary for...

  6. 78 FR 13656 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-28

    ... Information Administration Agency Information Collection Extension AGENCY: U.S. Energy Information... Act of 1995, an information collection request to the OMB for a three-year extension, with changes, of... should be sent to the: DOE Desk Officer, Office of Information and Regulatory Affairs, Office...

  7. Taxonomy for Assessing Evaluation Competencies in Extension

    ERIC Educational Resources Information Center

    Rodgers, Michelle S.; Hillaker, Barbara D.; Haas, Bruce E.; Peters, Cheryl

    2012-01-01

    Evaluation of public service programming is becoming increasingly important with current funding realities. The taxonomy of evaluation competencies compiled by Ghere et al. (2006) provided the starting place for Taxonomy for Assessing Evaluation Competencies in Extension. The Michigan State University Extension case study described here presents a…

  8. Farmer Experience of Pluralistic Agricultural Extension, Malawi

    ERIC Educational Resources Information Center

    Chowa, Clodina; Garforth, Chris; Cardey, Sarah

    2013-01-01

    Purpose: Malawi's current extension policy supports pluralism and advocates responsiveness to farmer demand. We investigate whether smallholder farmers' experience supports the assumption that access to multiple service providers leads to extension and advisory services that respond to the needs of farmers. Design/methodology/approach: Within a…

  9. 78 FR 15034 - Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-08

    ....S. Geological Survey Information Collection Extension AGENCY: U.S. Geological Survey, Interior. ACTION: Notice of an extension of an information collection (1028- 0090). SUMMARY: We (the U.S... this information collection to the Information Collection Clearance Officer, U.S. Geological...

  10. Anticommutative extension of the Adler map

    NASA Astrophysics Data System (ADS)

    Konstantinou-Rizos, S.; Mikhailov, A. V.

    2016-07-01

    We construct a noncommutative (Grassmann) extension of the well-known Adler Yang–Baxter map. It satisfies the Yang–Baxter equation, it is reversible and birational. Our extension preserves all the properties of the original map except the involutivity.

  11. Colour octet extension of 2HDM

    NASA Astrophysics Data System (ADS)

    Valencia, German

    2016-07-01

    In this paper we consider some aspects of the Manohar-Wise extension of the SM with a colour-octet electroweak-doublet scalar applied to 2HDM. We present theoretical constraints on the parameters of this extension to both the SM and the 2HDM and discuss related phenomenology at LHC.

  12. Extensive Reading: Students' Performance and Perception

    ERIC Educational Resources Information Center

    Fernandez de Morgado, Nelly

    2009-01-01

    Reading is thought to be a crucial skill in the EFL learning process, and Extensive Reading a very useful strategy. However, very few teachers implement it on a regular basis. The process of introducing Extensive Reading (ER) is considered far too expensive, complicated, and time-consuming. One way to encourage its use would be to more deeply…

  13. Effective Use of Facebook for Extension Professionals

    ERIC Educational Resources Information Center

    Mains, Mark; Jenkins-Howard, Brooke; Stephenson, Laura

    2013-01-01

    As the use of social media increases, Extension is challenged to stay relevant with cliental by using digital tools. This article illustrates how Facebook can be part of Extension's repertoire of methods for communication, program implementation, education, and marketing. This allows professionals to build social networking capacity with…

  14. 40 CFR 52.1078 - Extensions.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 4 2010-07-01 2010-07-01 false Extensions. 52.1078 Section 52.1078 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS (CONTINUED) Maryland § 52.1078 Extensions. (a) (b) The Administrator hereby extends by six-months...

  15. 36 CFR 251.89 - Time extensions.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 36 Parks, Forests, and Public Property 2 2011-07-01 2011-07-01 false Time extensions. 251.89... Appeal of Decisions Relating to Occupancy and Use of National Forest System Lands § 251.89 Time extensions. (a) Filing of notice of appeal. Time for filing a notice of appeal is not extendable. (b)...

  16. 14 CFR 1260.23 - Extensions.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Extensions. 1260.23 Section 1260.23.... A copy of the extension must also be forwarded to cognizant Office of Naval Research office. NASA... NASA Grant Officer. Copies are to be forwarded to the cognizant Office of Naval Research office....

  17. 14 CFR 1260.23 - Extensions.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Extensions. 1260.23 Section 1260.23.... A copy of the extension must also be forwarded to cognizant Office of Naval Research office. NASA... NASA Grant Officer. Copies are to be forwarded to the cognizant Office of Naval Research office....

  18. Graduate Students Serve Extension as Evaluation Consultants

    ERIC Educational Resources Information Center

    McClure, Megan; Fuhrman, Nicholas E.

    2011-01-01

    In an effort to provide graduate students at a distance with field-based learning experiences and evaluation resources to statewide Extension programs, 24 Master's students participating in a distance-delivered program evaluation course served as evaluation consultants for Extension programs. State evaluation specialists unable to conduct…

  19. An extension theorem for conformal gauge singularities

    SciTech Connect

    Luebbe, Christian; Tod, Paul

    2009-11-15

    We analyze conformal gauge, or isotropic, singularities in cosmological models in general relativity. Using the calculus of tractors, we find conditions in terms of tractor curvature for a local extension of the conformal structure through a cosmological singularity and prove a local extension theorem along a congruence of timelike conformal geodesics.

  20. 10 CFR 905.33 - Extension formula.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 10 Energy 4 2013-01-01 2013-01-01 false Extension formula. 905.33 Section 905.33 Energy DEPARTMENT OF ENERGY ENERGY PLANNING AND MANAGEMENT PROGRAM Power Marketing Initiative § 905.33 Extension formula. (a) The amount of power to be extended to an existing customer shall be determined according...

  1. 10 CFR 905.33 - Extension formula.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 4 2014-01-01 2014-01-01 false Extension formula. 905.33 Section 905.33 Energy DEPARTMENT OF ENERGY ENERGY PLANNING AND MANAGEMENT PROGRAM Power Marketing Initiative § 905.33 Extension formula. (a) The amount of power to be extended to an existing customer shall be determined according...

  2. 10 CFR 905.33 - Extension formula.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 4 2012-01-01 2012-01-01 false Extension formula. 905.33 Section 905.33 Energy DEPARTMENT OF ENERGY ENERGY PLANNING AND MANAGEMENT PROGRAM Power Marketing Initiative § 905.33 Extension formula. (a) The amount of power to be extended to an existing customer shall be determined according...

  3. 10 CFR 905.33 - Extension formula.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Extension formula. 905.33 Section 905.33 Energy DEPARTMENT OF ENERGY ENERGY PLANNING AND MANAGEMENT PROGRAM Power Marketing Initiative § 905.33 Extension formula. (a) The amount of power to be extended to an existing customer shall be determined according...

  4. 10 CFR 905.33 - Extension formula.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 4 2011-01-01 2011-01-01 false Extension formula. 905.33 Section 905.33 Energy DEPARTMENT OF ENERGY ENERGY PLANNING AND MANAGEMENT PROGRAM Power Marketing Initiative § 905.33 Extension formula. (a) The amount of power to be extended to an existing customer shall be determined according...

  5. Developing a Roadmap for Excellence in Extension

    ERIC Educational Resources Information Center

    Saunders, Kristine S.; Reese, Diane

    2011-01-01

    Trying to figure out the promotion and tenure system is one of the major stressors for new Extension faculty. To help new county-based Extension faculty, their supervisors, committee chairs, and other mentors evaluate progress in the probationary years, a Roadmap with specific guideposts delineating expectations for pre-tenure years was developed.…

  6. Kentucky's Urban Extension Focus

    ERIC Educational Resources Information Center

    Young, Jeffery; Vavrina, Charles

    2014-01-01

    Defining the success of Urban Extension units is sometimes challenging. For those Extension agents, specialists, administrators, and others who have worked to bring solid, research-based programming to urban communities, it is no surprise that working in these communities brings its own unique and sometimes difficult challenges. Kentucky's…

  7. Community Leadership Development: Implications for Extension.

    ERIC Educational Resources Information Center

    Northeast Regional Center for Rural Development, University Park, PA.

    Designed for extension personnel who are involved in community leadership (CL) programs, this publication summarizes recent national efforts that could be useful in developing and conducting CL programs, and current leadership theory and literature. Part 1 reports the results of the national survey, initiated in April 1985, of extension staff…

  8. Extensive Reading in Enhancing Lexical Chunks Acquisition

    ERIC Educational Resources Information Center

    Pereyra, Nilsa

    2015-01-01

    The purpose of this action research was to investigate the effect of extensive reading and related activities on the acquisition of lexical chunks in EFL students. Seven adult EFL learners with an Intermediate level volunteered to take part in the 16 week project following Extensive Reading principles combined with tasks based on the Lexical…

  9. Extension Sustainability Camp: Design, Implementation, and Evaluation

    ERIC Educational Resources Information Center

    Brain, Roslynn; Upton, Sally; Tingey, Brett

    2015-01-01

    Sustainability Camps provide an opportunity for Extension educators to be in the forefront of sustainability outreach and to meet the growing demand for sustainability education. This article shares development, implementation, and evaluation of an Extension Sustainability Camp for youth, grades 4-6. Camp impact was measured via daily pre-and…

  10. 75 FR 4359 - Agency Information Collection Extension

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-01-27

    ...The Department of Energy (DOE) has submitted an information collection package to the OMB for extension under the provisions of the Paperwork Reduction Act of 1995. The package requests a three-year extension of its ``Annual Alternative Fuel Vehicle Acquisition Report for State and Alternative Fuel Provider Fleets,'' OMB Control Number 1910-5101. This information collection package covers......

  11. Extension Is Unpopular--On the Internet

    ERIC Educational Resources Information Center

    Rader, Heidi B.

    2011-01-01

    The first Extension-authored link in Google Search (2011a) for "how to garden" was ranked an abysmal 82nd. Worse, Internet users selected the top-ranked site significantly more often than they selected the second-ranked one, and they rarely selected any site ranked lower than #10 (Granka, Joachims, & Gay, 2004). An Extension-commissioned poll in…

  12. Bendable Extension For Abrasive-Jet Cleaning

    NASA Technical Reports Server (NTRS)

    Mayer, Walter

    1989-01-01

    Hard-to-reach places cleaned more easily. Extension for abrasive-jet apparatus bent to provide controlled abrasive cleaning of walls in deep cavities or other hard-to-reach places. Designed for controlled removal of penetrant inspection dyes from inside castings, extension tube also used for such general grit-blasting work as removal of scratches.

  13. Extension Learners' Use of Electronic Technology

    ERIC Educational Resources Information Center

    Guenthner, Joseph F.; Swan, Benjamin G.

    2011-01-01

    Extension clientele use electronic technology for entertainment, communication, and business. Educational programs that use electronic technology can enhance learning. To learn more about use of electronic technology among Extension clientele, we surveyed 80 university students and 135 potato farmers. We found that the farmers were likely to use…

  14. 1890 Institutions' Extension Program and Rural Development.

    ERIC Educational Resources Information Center

    Brown, Adell, Jr.

    The extension role of Tuskegee Institute and the 16 black land grant colleges established by the Morrill Act of 1890 has been to diffuse among the non-university citizens of America useful and practical information on agriculture, home economics, and related areas. Tuskegee's extension efforts began in 1880 and flourished under the leadership of…

  15. 36 CFR 251.89 - Time extensions.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 36 Parks, Forests, and Public Property 2 2012-07-01 2012-07-01 false Time extensions. 251.89... Appeal of Decisions Relating to Occupancy and Use of National Forest System Lands § 251.89 Time extensions. (a) Filing of notice of appeal. Time for filing a notice of appeal is not extendable. (b)...

  16. 75 FR 77663 - Information Collection Extension Request

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-13

    ... of the Secretary Information Collection Extension Request ACTION: Notice. SUMMARY: The Department of... comment on information collection extension request in accordance with the Paperwork Reduction Act of 1995... Information Report--29 CFR part 31 (Title VI of the Civil Rights Act), Nondiscrimination--Disability--29...

  17. Extensive Reading Quizzes and Reading Attitudes

    ERIC Educational Resources Information Center

    Stoeckel, Tim; Reagan, Nevitt; Hann, Fergus

    2012-01-01

    Extensive reading (ER) has become a common feature of many English as a second or foreign language (ESL/EFL) programs. There is evidence that reading large amounts of easy, interesting material may improve foreign language skills, most notably in vocabulary, reading rates, and overall proficiency. However, teacher evaluation of extensive reading…

  18. PERCEPTIONS OF EXTENSION WORK IN MEXICO.

    ERIC Educational Resources Information Center

    CHENA-GONZALEZ, RODOLFO

    THE STUDY EXPLORED BASIC PATTERNS OF PERCEPTIONS AMONG PROFESSIONAL AGRICULTURAL WORKERS IN MEXICO ABOUT THE IMPORTANCE OF POSSIBLE NEW OBJECTIVES, KINDS OF FUNCTIONS, AND TYPES OF TRAINING FOR ITS EXTENSION AGENTS. DATA WERE COLLECTED FROM 147 EXTENSION AGENTS AND SUPERVISORS, EXPERIMENTALISTS, RESEARCH LEADERS, AND PROFESSORS, BY A MAILED…

  19. Neural network and letter recognition

    SciTech Connect

    Lee, Hue Yeon.

    1989-01-01

    Neural net architectures and learning algorithms that recognize hand written 36 alphanumeric characters are studied. The thin line input patterns written in 32 x 32 binary array are used. The system is comprised of two major components, viz. a preprocessing unit and a Recognition unit. The preprocessing unit in turn consists of three layers of neurons; the U-layer, the V-layer, and the C-layer. The functions of the U-layer is to extract local features by template matching. The correlation between the detected local features are considered. Through correlating neurons in a plane with their neighboring neurons, the V-layer would thicken the on-cells or lines that are groups of on-cells of the previous layer. These two correlations would yield some deformation tolerance and some of the rotational tolerance of the system. The C-layer then compresses data through the Gabor transform. Pattern dependent choice of center and wavelengths of Gabor filters is the cause of shift and scale tolerance of the system. Three different learning schemes had been investigated in the recognition unit, namely; the error back propagation learning with hidden units, a simple perceptron learning, and a competitive learning. Their performances were analyzed and compared. Since sometimes the network fails to distinguish between two letters that are inherently similar, additional ambiguity resolving neural nets are introduced on top of the above main neural net. The two dimensional Fourier transform is used as the preprocessing and the perceptron is used as the recognition unit of the ambiguity resolver. One hundred different person's handwriting sets are collected. Some of these are used as the training sets and the remainders are used as the test sets.

  20. Neural mechanisms for voice recognition.

    PubMed

    Andics, Attila; McQueen, James M; Petersson, Karl Magnus; Gál, Viktor; Rudas, Gábor; Vidnyánszky, Zoltán

    2010-10-01

    We investigated neural mechanisms that support voice recognition in a training paradigm with fMRI. The same listeners were trained on different weeks to categorize the mid-regions of voice-morph continua as an individual's voice. Stimuli implicitly defined a voice-acoustics space, and training explicitly defined a voice-identity space. The pre-defined centre of the voice category was shifted from the acoustic centre each week in opposite directions, so the same stimuli had different training histories on different tests. Cortical sensitivity to voice similarity appeared over different time-scales and at different representational stages. First, there were short-term adaptation effects: increasing acoustic similarity to the directly preceding stimulus led to haemodynamic response reduction in the middle/posterior STS and in right ventrolateral prefrontal regions. Second, there were longer-term effects: response reduction was found in the orbital/insular cortex for stimuli that were most versus least similar to the acoustic mean of all preceding stimuli, and, in the anterior temporal pole, the deep posterior STS and the amygdala, for stimuli that were most versus least similar to the trained voice-identity category mean. These findings are interpreted as effects of neural sharpening of long-term stored typical acoustic and category-internal values. The analyses also reveal anatomically separable voice representations: one in a voice-acoustics space and one in a voice-identity space. Voice-identity representations flexibly followed the trained identity shift, and listeners with a greater identity effect were more accurate at recognizing familiar voices. Voice recognition is thus supported by neural voice spaces that are organized around flexible 'mean voice' representations. PMID:20553895

  1. Transcriptomic Approaches to Neural Repair

    PubMed Central

    Antunes-Martins, Ana; Chandran, Vijayendran; Costigan, Michael; Lerch, Jessica K.; Willis, Dianna E.; Tuszynski, Mark H.

    2015-01-01

    Understanding why adult CNS neurons fail to regenerate their axons following injury remains a central challenge of neuroscience research. A more complete appreciation of the biological mechanisms shaping the injured nervous system is a crucial prerequisite for the development of robust therapies to promote neural repair. Historically, the identification of regeneration associated signaling pathways has been impeded by the limitations of available genetic and molecular tools. As we progress into an era in which the high-throughput interrogation of gene expression is commonplace and our knowledge base of interactome data is rapidly expanding, we can now begin to assemble a more comprehensive view of the complex biology governing axon regeneration. Here, we highlight current and ongoing work featuring transcriptomic approaches toward the discovery of novel molecular mechanisms that can be manipulated to promote neural repair. SIGNIFICANCE STATEMENT Transcriptional profiling is a powerful technique with broad applications in the field of neuroscience. Recent advances such as single-cell transcriptomics, CNS cell type-specific and developmental stage-specific expression libraries are rapidly enhancing the power of transcriptomics for neuroscience applications. However, extracting biologically meaningful information from large transcriptomic datasets remains a formidable challenge. This mini-symposium will highlight current work using transcriptomic approaches to identify regulatory networks in the injured nervous system. We will discuss analytical strategies for transcriptomics data, the significance of noncoding RNA networks, and the utility of multiomic data integration. Though the studies featured here specifically focus on neural repair, the approaches highlighted in this mini-symposium will be of broad interest and utility to neuroscientists working in diverse areas of the field. PMID:26468186

  2. Neural Mechanisms Underlying Breathing Complexity

    PubMed Central

    Hess, Agathe; Yu, Lianchun; Klein, Isabelle; De Mazancourt, Marine; Jebrak, Gilles; Mal, Hervé; Brugière, Olivier; Fournier, Michel; Courbage, Maurice; Dauriat, Gaelle; Schouman-Clayes, Elisabeth; Clerici, Christine; Mangin, Laurence

    2013-01-01

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

  3. Aerodynamic Design Using Neural Networks

    NASA Technical Reports Server (NTRS)

    Rai, Man Mohan; Madavan, Nateri K.

    2003-01-01

    The design of aerodynamic components of aircraft, such as wings or engines, involves a process of obtaining the most optimal component shape that can deliver the desired level of component performance, subject to various constraints, e.g., total weight or cost, that the component must satisfy. Aerodynamic design can thus be formulated as an optimization problem that involves the minimization of an objective function subject to constraints. A new aerodynamic design optimization procedure based on neural networks and response surface methodology (RSM) incorporates the advantages of both traditional RSM and neural networks. The procedure uses a strategy, denoted parameter-based partitioning of the design space, to construct a sequence of response surfaces based on both neural networks and polynomial fits to traverse the design space in search of the optimal solution. Some desirable characteristics of the new design optimization procedure include the ability to handle a variety of design objectives, easily impose constraints, and incorporate design guidelines and rules of thumb. It provides an infrastructure for variable fidelity analysis and reduces the cost of computation by using less-expensive, lower fidelity simulations in the early stages of the design evolution. The initial or starting design can be far from optimal. The procedure is easy and economical to use in large-dimensional design space and can be used to perform design tradeoff studies rapidly. Designs involving multiple disciplines can also be optimized. Some practical applications of the design procedure that have demonstrated some of its capabilities include the inverse design of an optimal turbine airfoil starting from a generic shape and the redesign of transonic turbines to improve their unsteady aerodynamic characteristics.

  4. From Classical Neural Networks to Quantum Neural Networks

    NASA Astrophysics Data System (ADS)

    Tirozzi, B.

    2013-09-01

    First I give a brief description of the classical Hopfield model introducing the fundamental concepts of patterns, retrieval, pattern recognition, neural dynamics, capacity and describe the fundamental results obtained in this field by Amit, Gutfreund and Sompolinsky,1 using the non rigorous method of replica and the rigorous version given by Pastur, Shcherbina, Tirozzi2 using the cavity method. Then I give a formulation of the theory of Quantum Neural Networks (QNN) in terms of the XY model with Hebbian interaction. The problem of retrieval and storage is discussed. The retrieval states are the states of the minimum energy. I apply the estimates found by Lieb3 which give lower and upper bound of the free-energy and expectation of the observables of the quantum model. I discuss also some experiment and the search of ground state using Monte Carlo Dynamics applied to the equivalent classical two dimensional Ising model constructed by Suzuki et al.6 At the end there is a list of open problems.

  5. Braided Multi-Electrode Probes (BMEPs) for Neural Interfaces

    NASA Astrophysics Data System (ADS)

    Kim, Tae Gyo

    Although clinical use of invasive neural interfaces is very limited, due to safety and reliability concerns, the potential benefits of their use in brain machine interfaces (BMIs) seem promising and so they have been widely used in the research field. Microelectrodes as invasive neural interfaces are the core tool to record neural activities and their failure is a critical issue for BMI systems. Possible sources of this failure are neural tissue motions and their interactions with stiff electrode arrays or probes fixed to the skull. To overcome these tissue motion problems, we have developed novel braided multi-electrode probes (BMEPs). By interweaving ultra-fine wires into a tubular braid structure, we obtained a highly flexible multi-electrode probe. In this thesis we described BMEP designs and how to fabricate BMEPs, and explore experiments to show the advantages of BMEPs through a mechanical compliance comparison and a chronic immunohistological comparison with single 50microm nichrome wires used as a reference electrode type. Results from the mechanical compliance test showed that the bodies of BMEPs have 4 to 21 times higher compliance than the single 50microm wire and the tethers of BMEPs were 6 to 96 times higher compliance, depending on combinations of the wire size (9.6microm or 12.7microm), the wire numbers (12 or 24), and the length of tether (3, 5 or 10 mm). Results from the immunohistological comparison showed that both BMEPs and 50microm wires anchored to the skull caused stronger tissue reactions than unanchored BMEPs and 50microm wires, and 50microm wires caused stronger tissue reactions than BMEPs. In in-vivo tests with BMEPs, we succeeded in chronic recordings from the spinal cord of freely jumping frogs and in acute recordings from the spinal cord of decerebrate rats during air stepping which was evoked by mesencephalic locomotor region (MLR) stimulation. This technology may provide a stable and reliable neural interface to spinal cord

  6. Enteric Neurospheres Are Not Specific to Neural Crest Cultures: Implications for Neural Stem Cell Therapies

    PubMed Central

    Cooper, Julie; Kronfli, Rania; Cananzi, Mara; Delalande, Jean-Marie; McCann, Conor; Burns, Alan J.; Thapar, Nikhil

    2015-01-01

    Objectives Enteric neural stem cells provide hope of curative treatment for enteric neuropathies. Current protocols for their harvesting from humans focus on the generation of ‘neurospheres’ from cultures of dissociated gut tissue. The study aims to better understand the derivation, generation and composition of enteric neurospheres. Design Gut tissue was obtained from Wnt1-Cre;Rosa26Yfp/Yfp transgenic mice (constitutively labeled neural crest cells) and paediatric patients. Gut cells were cultured either unsorted (mixed neural crest/non-neural crest), or following FACS selection into neural crest (murine-YFP+ve/human-p75+ve) or non-neural crest (YFP-ve/p75-ve) populations. Cultures and resultant neurospheres were characterized using immunolabelling in vitro and following transplantation in vivo. Results Cultures of (i) unsorted, (ii) neural crest, and (iii) non-neural crest cell populations generated neurospheres similar in numbers, size and morphology. Unsorted neurospheres were highly heterogeneous for neural crest content. Neural crest-derived (YFP+ve/p75+ve) neurospheres contained only neural derivatives (neurons and glia) and were devoid of non-neural cells (i.e. negative for SMA, c-Kit), with the converse true for non-neural crest-derived (YFP-ve/p75-ve) ‘neurospheres’. Under differentiation conditions only YFP+ve cells gave rise to neural derivatives. Both YFP+ve and YFP-ve cells displayed proliferation and spread upon transplantation in vivo, but YFP-ve cells did not locate or integrate within the host ENS. Conclusions Spherical accumulations of cells, so-called ‘neurospheres’ forming in cultures of dissociated gut contain variable proportions of neural crest-derived cells. If they are to be used for ENS cell replacement therapy then improved protocols for their generation, including cell selection, should be sought in order to avoid inadvertent transplantation of non-therapeutic, non-ENS cells. PMID:25799576

  7. The LILARTI neural network system

    SciTech Connect

    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.

  8. Centroid calculation using neural networks

    NASA Astrophysics Data System (ADS)

    Himes, Glenn S.; Inigo, Rafael M.

    1992-01-01

    Centroid calculation provides a means of eliminating translation problems, which is useful for automatic target recognition. a neural network implementation of centroid calculation is described that used a spatial filter and a Hopfield network to determine the centroid location of an object. spatial filtering of a segmented window creates a result whose peak vale occurs at the centroid of the input data set. A Hopfield network then finds the location of this peak and hence gives the location of the centroid. Hardware implementations of the networks are described and simulation results are provided.

  9. Chemotaxis during neural crest migration.

    PubMed

    Shellard, Adam; Mayor, Roberto

    2016-07-01

    Chemotaxis refers to the directional migration of cells towards external, soluble factors along their gradients. It is a process that is used by many different cell types during development for tissue organisation and the formation of embryonic structures, as well as disease like cancer metastasis. The neural crest (NC) is a multipotent, highly migratory cell population that contribute to a range of tissues. It has been hypothesised that NC migration, at least in part, is reliant on chemotactic signals. This review will explore the current evidence for proposed chemoattractants of NC cells, and outline mechanisms for the chemotactic response of the NC to them. PMID:26820523

  10. Physical, neural, and mental timing.

    PubMed

    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

  11. Neural processing of natural sounds.

    PubMed

    Theunissen, Frédéric E; Elie, Julie E

    2014-06-01

    We might be forced to listen to a high-frequency tone at our audiologist's office or we might enjoy falling asleep with a white-noise machine, but the sounds that really matter to us are the voices of our companions or music from our favourite radio station. The auditory system has evolved to process behaviourally relevant natural sounds. Research has shown not only that our brain is optimized for natural hearing tasks but also that using natural sounds to probe the auditory system is the best way to understand the neural computations that enable us to comprehend speech or appreciate music. PMID:24840800

  12. The hysteretic Hopfield neural network.

    PubMed

    Bharitkar, S; Mendel, J M

    2000-01-01

    A new neuron activation function based on a property found in physical systems--hysteresis--is proposed. We incorporate this neuron activation in a fully connected dynamical system to form the hysteretic Hopfield neural network (HHNN). We then present an analog implementation of this architecture and its associated dynamical equation and energy function.We proceed to prove Lyapunov stability for this new model, and then solve a combinatorial optimization problem (i.e., the N-queen problem) using this network. We demonstrate the advantages of hysteresis by showing increased frequency of convergence to a solution, when the parameters associated with the activation function are varied. PMID:18249816

  13. Neural Network Classifies Teleoperation Data

    NASA Technical Reports Server (NTRS)

    Fiorini, Paolo; Giancaspro, Antonio; Losito, Sergio; Pasquariello, Guido

    1994-01-01

    Prototype artificial neural network, implemented in software, identifies phases of telemanipulator tasks in real time by analyzing feedback signals from force sensors on manipulator hand. Prototype is early, subsystem-level product of continuing effort to develop automated system that assists in training and supervising human control operator: provides symbolic feedback (e.g., warnings of impending collisions or evaluations of performance) to operator in real time during successive executions of same task. Also simplifies transition between teleoperation and autonomous modes of telerobotic system.

  14. Neural Regulation of Mucosal Function

    PubMed Central

    Baraniuk, James N.

    2009-01-01

    Nociceptive, parasympathetic and sympathetic nerves play critical roles in regulating glandular, vascular and other processes in airway mucosa. These functions are vital for cleaning and humidifying ambient air before it is inhaled into the lungs. Recent identification of subsets of nociceptive nerves has tipped the donkey cart of dogma and led to the discovery of new receptor and ion channel families that respond to culinary odorants (“aromatherapy”), inhaled irritants, temperature and other “humors”; a new interpretation of airway nociceptive nerve axon responses; and an understanding of the neural plasticity induced by inflammation and different neurotrophic factors. PMID:17707667

  15. Phantom limbs and neural plasticity.

    PubMed

    Ramachandran, V S; Rogers-Ramachandran, D

    2000-03-01

    The study of phantom limbs has received tremendous impetus from recent studies linking changes in cortical topography with perceptual experience. Systematic psychophysical testing and functional imaging studies on patients with phantom limbs provide 2 unique opportunities. First, they allow us to demonstrate neural plasticity in the adult human brain. Second, by tracking perceptual changes (such as referred sensations) and changes in cortical topography in individual patients, we can begin to explore how the activity of sensory maps gives rise to conscious experience. Finally, phantom limbs also allow us to explore intersensory effects and the manner in which the brain constructs and updates a "body image" throughout life. PMID:10714655

  16. Canine hip extension range during gait.

    PubMed

    van der Walt, A M; Stewart, A V; Joubert, K E; Bekker, P

    2008-12-01

    Assessment of canine gait is frequently used by veterinary clinicians to establish the presence of orthopaedic pain. As up to 30% of canine orthopaedic conditions affect the pelvic limb, knowledge of pelvic limb biomechanics during gait is very important. Previous studies have investigated the biomechanics at the tarsus and stifle, but little information is available regarding hip motion during gait. The aim of this study was to determine the maximum hip extension range achieved during the stance phase of gait in normal canines. In addition, this study aimed to determine the difference between maximum passive hip extension and maximum hip extension during gait. Using a sample of 30 morphologically similar normal dogs, mean maximum passive hip extension was measured using a goniometer and mean maximum hip extension range during gait was determined videographically. Inter- and intra-assessor reliability studies performed at the start of the study showed that the measurement tools and techniques used in this study were valid and reliable. The goniometric data showed that mean maximum passive hip extension range was 162.44 degrees (+/-3.94) with no significant difference between the left and the right hind limbs. The videographic data showed that mean maximum hip extension range during gait was 119.9 degrees (+/-9.26) with no significant difference between the left and right hind limbs. The results of this study provided reference values for active and passive hip extension range and showed that the degree of hip extension range required for normal gait is significantly less than maximum passive hip extension range. PMID:19496317

  17. Acute effects of neural mobilization and infrared on the mechanics of the median nerve

    PubMed Central

    Nunes, Monara Kedma; Fontenele dos Santos, Gabrielly; Martins e Silva, Diandra Caroline; Mota de Freitas, Ana Cláudia; Henriques, Isadora Ferreira; Andrade, Peterson Marco; Machado, Dionis de Castro; Teixeira, Silmar; Neves, Marco Orsini; Dias, Gildário; Silva-Júnior, Fernando; Bastos, Victor Hugo

    2016-01-01

    [Purpose] This study analyzed the acute effects of infrared and neural mobilization on the median nerve on the range of elbow extension of the dominant limb. [Subjects and Methods] Forty participants from university, neurologically asymptomatic, 12 males and 28 females (22.8 ± 1.9 years), were randomly divided into four groups: Group 1 (control) rested for 25 minutes in the supine position; Group 2 received the specific neural mobilization for the median nerve; Group 3 received an application of infrared for 15 minutes on the forearm; Group 4 received the same application of infrared followed by neural mobilization. The goniometric parameters of elbow extension were evaluated after the intervention. [Results] Significant differences of extension value were observed between Group 1 and Group 3 (15.75 degrees), and between Group 1 and Group 4 (14.60 degrees), and the average higher in Group 3 (26.35 degrees). [Conclusion] This research provides new experimental evidence that NM in relation to superficial heat produces an immediate effect on elbow range of motion versus NM isolated. PMID:27390402

  18. Acute effects of neural mobilization and infrared on the mechanics of the median nerve.

    PubMed

    Nunes, Monara Kedma; Fontenele Dos Santos, Gabrielly; Martins E Silva, Diandra Caroline; Mota de Freitas, Ana Cláudia; Henriques, Isadora Ferreira; Andrade, Peterson Marco; Machado, Dionis de Castro; Teixeira, Silmar; Neves, Marco Orsini; Dias, Gildário; Silva-Júnior, Fernando; Bastos, Victor Hugo

    2016-06-01

    [Purpose] This study analyzed the acute effects of infrared and neural mobilization on the median nerve on the range of elbow extension of the dominant limb. [Subjects and Methods] Forty participants from university, neurologically asymptomatic, 12 males and 28 females (22.8 ± 1.9 years), were randomly divided into four groups: Group 1 (control) rested for 25 minutes in the supine position; Group 2 received the specific neural mobilization for the median nerve; Group 3 received an application of infrared for 15 minutes on the forearm; Group 4 received the same application of infrared followed by neural mobilization. The goniometric parameters of elbow extension were evaluated after the intervention. [Results] Significant differences of extension value were observed between Group 1 and Group 3 (15.75 degrees), and between Group 1 and Group 4 (14.60 degrees), and the average higher in Group 3 (26.35 degrees). [Conclusion] This research provides new experimental evidence that NM in relation to superficial heat produces an immediate effect on elbow range of motion versus NM isolated. PMID:27390402

  19. NeuralWISP: A Wirelessly Powered Neural Interface With 1-m Range.

    PubMed

    Yeager, D J; Holleman, J; Prasad, R; Smith, J R; Otis, B P

    2009-12-01

    We present the NeuralWISP, a wireless neural interface operating from far-field radio-frequency RF energy. The NeuralWISP is compatible with commercial RF identification readers and operates at a range up to 1 m. It includes a custom low-noise, low-power amplifier integrated circuit for processing the neural signal and an analog spike detection circuit for reducing digital computational requirements and communications bandwidth. Our system monitors the neural signal and periodically transmits the spike density in a user-programmable time window. The entire system draws an average 20 muA from the harvested 1.8-V supply. PMID:23853285

  20. The neural basis of human tool use.

    PubMed

    Orban, Guy A; Caruana, Fausto

    2014-01-01

    In this review, we propose that the neural basis for the spontaneous, diversified human tool use is an area devoted to the execution and observation of tool actions, located in the left anterior supramarginal gyrus (aSMG). The aSMG activation elicited by observing tool use is typical of human subjects, as macaques show no similar activation, even after an extensive training to use tools. The execution of tool actions, as well as their observation, requires the convergence upon aSMG of inputs from different parts of the dorsal and ventral visual streams. Non-semantic features of the target object may be provided by the posterior parietal cortex (PPC) for tool-object interaction, paralleling the well-known PPC input to anterior intraparietal (AIP) for hand-object interaction. Semantic information regarding tool identity, and knowledge of the typical manner of handling the tool, could be provided by inferior and middle regions of the temporal lobe. Somatosensory feedback and technical reasoning, as well as motor and intentional constraints also play roles during the planning of tool actions and consequently their signals likewise converge upon aSMG. We further propose that aSMG may have arisen though duplication of monkey AIP and invasion of the duplicate area by afferents from PPC providing distinct signals depending on the kinematics of the manipulative action. This duplication may have occurred when Homo Habilis or Homo Erectus emerged, generating the Oldowan or Acheulean Industrial complexes respectively. Hence tool use may have emerged during hominid evolution between bipedalism and language. We conclude that humans have two parietal systems involved in tool behavior: a biological circuit for grasping objects, including tools, and an artifactual system devoted specifically to tool use. Only the latter allows humans to understand the causal relationship between tool use and obtaining the goal, and is likely to be the basis of all technological developments. PMID

  1. The neural basis of human tool use

    PubMed Central

    Orban, Guy A.; Caruana, Fausto

    2014-01-01

    In this review, we propose that the neural basis for the spontaneous, diversified human tool use is an area devoted to the execution and observation of tool actions, located in the left anterior supramarginal gyrus (aSMG). The aSMG activation elicited by observing tool use is typical of human subjects, as macaques show no similar activation, even after an extensive training to use tools. The execution of tool actions, as well as their observation, requires the convergence upon aSMG of inputs from different parts of the dorsal and ventral visual streams. Non-semantic features of the target object may be provided by the posterior parietal cortex (PPC) for tool-object interaction, paralleling the well-known PPC input to anterior intraparietal (AIP) for hand-object interaction. Semantic information regarding tool identity, and knowledge of the typical manner of handling the tool, could be provided by inferior and middle regions of the temporal lobe. Somatosensory feedback and technical reasoning, as well as motor and intentional constraints also play roles during the planning of tool actions and consequently their signals likewise converge upon aSMG. We further propose that aSMG may have arisen though duplication of monkey AIP and invasion of the duplicate area by afferents from PPC providing distinct signals depending on the kinematics of the manipulative action. This duplication may have occurred when Homo Habilis or Homo Erectus emerged, generating the Oldowan or Acheulean Industrial complexes respectively. Hence tool use may have emerged during hominid evolution between bipedalism and language. We conclude that humans have two parietal systems involved in tool behavior: a biological circuit for grasping objects, including tools, and an artifactual system devoted specifically to tool use. Only the latter allows humans to understand the causal relationship between tool use and obtaining the goal, and is likely to be the basis of all technological developments. PMID

  2. Neural Network Algorithm for Particle Loading

    SciTech Connect

    J. L. V. Lewandowski

    2003-04-25

    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.

  3. Adaptive Neurons For Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    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.

  4. Neural networks for aircraft system identification

    NASA Technical Reports Server (NTRS)

    Linse, Dennis J.

    1991-01-01

    Artificial neural networks offer some interesting possibilities for use in control. Our current research is on the use of neural networks on an aircraft model. The model can then be used in a nonlinear control scheme. The effectiveness of network training is demonstrated.

  5. The Elements Of Adaptive Neural Expert Systems

    NASA Astrophysics Data System (ADS)

    Healy, Michael J.

    1989-03-01

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

  6. Radiation Behavior of Analog Neural Network Chip

    NASA Technical Reports Server (NTRS)

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

    1996-01-01

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

  7. The Neural Substrates of Spoken Idiom Comprehension

    ERIC Educational Resources Information Center

    Hillert, Dieter G.; Buracas, Giedrius T.

    2009-01-01

    To examine the neural correlates of spoken idiom comprehension, we conducted an event-related functional MRI study with a "rapid sentence decision" task. The spoken sentences were equally familiar but varied in degrees of "idiom figurativeness". Our results show that "figurativeness" co-varied with neural activity in the left ventral dorsolateral…

  8. Medical image analysis with artificial neural networks.

    PubMed

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

    Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. PMID:20713305

  9. Modeling neural circuits in Parkinson's disease.

    PubMed

    Psiha, Maria; Vlamos, Panayiotis

    2015-01-01

    Parkinson's disease (PD) is caused by abnormal neural activity of the basal ganglia which are connected to the cerebral cortex in the brain surface through complex neural circuits. For a better understanding of the pathophysiological mechanisms of PD, it is important to identify the underlying PD neural circuits, and to pinpoint the precise nature of the crucial aberrations in these circuits. In this paper, the general architecture of a hybrid Multilayer Perceptron (MLP) network for modeling the neural circuits in PD is presented. The main idea of the proposed approach is to divide the parkinsonian neural circuitry system into three discrete subsystems: the external stimuli subsystem, the life-threatening events subsystem, and the basal ganglia subsystem. The proposed model, which includes the key roles of brain neural circuit in PD, is based on both feed-back and feed-forward neural networks. Specifically, a three-layer MLP neural network with feedback in the second layer was designed. The feedback in the second layer of this model simulates the dopamine modulatory effect of compacta on striatum. PMID:25416983

  10. Identifying Bilingual Semantic Neural Representations across Languages

    ERIC Educational Resources Information Center

    Buchweitz, Augusto; Shinkareva, Svetlana V.; Mason, Robert A.; Mitchell, Tom M.; Just, Marcel Adam

    2012-01-01

    The goal of the study was to identify the neural representation of a noun's meaning in one language based on the neural representation of that same noun in another language. Machine learning methods were used to train classifiers to identify which individual noun bilingual participants were thinking about in one language based solely on their…

  11. Creativity in design and artificial neural networks

    SciTech Connect

    Neocleous, C.C.; Esat, I.I.; Schizas, C.N.

    1996-12-31

    The creativity phase is identified as an integral part of the design phase. The characteristics of creative persons which are relevant to designing artificial neural networks manifesting aspects of creativity, are identified. Based on these identifications, a general framework of artificial neural network characteristics to implement such a goal are proposed.

  12. Self-organization of neural networks

    NASA Astrophysics Data System (ADS)

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

    1984-05-01

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

  13. Advanced telerobotic control using neural networks

    NASA Technical Reports Server (NTRS)

    Pap, Robert M.; Atkins, Mark; Cox, Chadwick; Glover, Charles; Kissel, Ralph; Saeks, Richard

    1993-01-01

    Accurate Automation is designing and developing adaptive decentralized joint controllers using neural networks. We are then implementing these in hardware for the Marshall Space Flight Center PFMA as well as to be usable for the Remote Manipulator System (RMS) robot arm. Our design is being realized in hardware after completion of the software simulation. This is implemented using a Functional-Link neural network.

  14. Neural networks and MIMD-multiprocessors

    NASA Technical Reports Server (NTRS)

    Vanhala, Jukka; Kaski, Kimmo

    1990-01-01

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

  15. Neural network based architectures for aerospace applications

    NASA Technical Reports Server (NTRS)

    Ricart, Richard

    1987-01-01

    A brief history of the field of neural networks research is given and some simple concepts are described. In addition, some neural network based avionics research and development programs are reviewed. The need for the United States Air Force and NASA to assume a leadership role in supporting this technology is stressed.

  16. Applications of Neural Networks in Finance.

    ERIC Educational Resources Information Center

    Crockett, Henry; Morrison, Ronald

    1994-01-01

    Discusses research with neural networks in the area of finance. Highlights include bond pricing, theoretical exposition of primary bond pricing, bond pricing regression model, and an example that created networks with corporate bonds and NeuralWare Neuralworks Professional H software using the back-propagation technique. (LRW)

  17. Neural Events in the Reinforcement Contingency

    ERIC Educational Resources Information Center

    Silva, Maria Teresa Araujo; Goncalves, Fabio Leyser; Garcia-Mijares, Miriam

    2007-01-01

    When neural events are analyzed as stimuli and responses, functional relations among them and among overt stimuli and responses can be unveiled. The integration of neuroscience and the experimental analysis of behavior is beginning to provide empirical evidence of involvement of neural events in the three-term contingency relating discriminative…

  18. Neural-Network Computer Transforms Coordinates

    NASA Technical Reports Server (NTRS)

    Josin, Gary M.

    1990-01-01

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

  19. Neural Plasticity in Speech Acquisition and Learning

    ERIC Educational Resources Information Center

    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…

  20. Neural Control of the Immune System

    ERIC Educational Resources Information Center

    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…