Search results for "Neural"

showing 10 items of 2783 documents

How many sites of action for endocannabinoids to control energy metabolism?

2006

The promising results obtained by clinical trials using Rimonabant to tackle visceral obesity and related disorders recently promoted a remarkable impulse to carry out detailed investigations into the mechanisms of action of endocannabinoids in regulating food intake and energy metabolism. The endocannabinoid system has been known for many years to play an important role in the modulation of the neuronal pathways mediating the rewarding properties of food. However, in the last few years, with the advanced understanding of the crucial role of the hypothalamic neuronal network in the regulation of appetite, several studies have also directed attention to the orexigenic role of the endocannabi…

Leptinmedicine.medical_specialtyCannabinoid receptorEndocrinology Diabetes and Metabolismmedicine.medical_treatmentmedia_common.quotation_subjectHypothalamusEnergy metabolismMedicine (miscellaneous)BiologyCannabis sativaReceptor Cannabinoid CB1RimonabantOrexigenicInternal medicineCannabinoid Receptor ModulatorsmedicineAnimalsHumansmedia_commonNutrition and DieteticsAppetite Regulationmusculoskeletal neural and ocular physiologyFatty AcidsBrainAppetiteEndocannabinoid systemEndocrinologyAdipose TissueLivernervous systemlipids (amino acids peptides and proteins)CannabinoidEnergy MetabolismNeurosciencepsychological phenomena and processesEndocannabinoidsmedicine.drugInternational Journal of Obesity
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An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension

2020

Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still be brought in simplifying the experimental setup and in employing an easier to use data processing procedure for the acquired time-series. A DLS time series processing procedure based on an artificial neural network is presented with details regarding the design, training procedure and error analysis, working over an extended particle size range. The procedure proved to be much faster regarding time-series processing and easier to use than fitti…

LightComputer sciencesimulated time-series02 engineering and technologySaccharomyces cerevisiaelcsh:Chemical technology01 natural sciencesBiochemistryArticleAnalytical Chemistry010309 optics<i>Saccharomyces cerevisiae</i>Dynamic light scatteringSuspensions0103 physical sciencesRange (statistics)Scattering Radiationlcsh:TP1-1185Electrical and Electronic EngineeringParticle SizeSuspension (vehicle)InstrumentationfermentationCell SizeAqueous solutionArtificial neural networkdynamic light scatteringFunction (mathematics)021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsParticle sizeNeural Networks Computer0210 nano-technologyBiological systemartificial neural networkSensors
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Modifications in Evoked Activity in the Visual Cortex Induced by the Caudate Nucleus

1971

The visual system, like the other sensorial systems, is subjected to intrinsic, complex control, originating both in the retina (CHANG et al., 1959; ARDUINI and HIRAO, 1960; STERIADE, 1967) and in the visual cortex (BUSER et a/., 1963; JASSIK-GERSCHENFELD and ASCHER, 1963; MEULDERS, 1965), which regulates its input at various levels of the specific pathways. However, the visual system is also influenced by subcortical structures which, though not exerting on it a strictly selective control, determine notable modifications in the level of excitability of the cortical sensorial neurons. It is in fact we11 known that activation of the mesencephalic reticular formation, by increasing the level …

LightPhysiologyCaudate nucleusStimulationInhibitory postsynaptic potentialReticular formationBiochemistryMidbrainMesencephalonNeural PathwaysmedicineAnimalsEvoked PotentialsVisual CortexChemistryReticular FormationGeniculate BodiesOptic NerveParamedian pontine reticular formationElectric StimulationRadiation EffectsVisual cortexmedicine.anatomical_structureCerebral cortexCatsCaudate NucleusNeuroscienceArchives Internationales de Physiologie et de Biochimie
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Effects of high power ultrasound treatments on the phenolic, chromatic and aroma composition of young and aged red wine

2019

Abstract In this study, the effects of both ultrasonic bath and probe treatments on the phenolic, chromatic and aroma composition of young red wine Cabernet Sauvignon were studied and modeled by artificial neural networks (ANNs). Moreover, the effect of high power ultrasound (HPU) along with antioxidants addition (sulfur dioxide and glutathione) was investigated during 6 months of aging in bottles. Lower amplitude and temperature, shorter treatment duration and particularly lower frequency showed a more favorable and milder effect on the chemical composition of wine. In the case of the ultrasonic probe treatment, similar effect was achieved primarily by a larger probe diameter as well as lo…

LightnessAntioxidantAcoustics and Ultrasonicsmedicine.medical_treatmentOrganoleptic02 engineering and technology010402 general chemistry01 natural sciencesInorganic Chemistryhigh power ultrasound ; HPU ; wine quality ; antioxidants ; ultrasonic bath ; ultrasonic probe ; artificial neural network (ANN)medicineChemical Engineering (miscellaneous)Environmental ChemistryRadiology Nuclear Medicine and imagingFood scienceChemical compositionAromaWinebiologyChemistryOrganic ChemistryAging of winefood and beverages021001 nanoscience & nanotechnologybiology.organism_classification0104 chemical sciencesComposition (visual arts)0210 nano-technology
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Learning vector quantization with alternative distance criteria

2003

An adaptive algorithm for training of a nearest neighbour (NN) classifier is developed in this paper. This learning rule has some similarity to the well-known LVQ method, but uses the nearest centroid neighbourhood concept to estimate optimal locations of the codebook vectors. The aim of this approach is to improve the performance of the standard LVQ algorithms when using a very small codebook. The behaviour of the learning technique proposed here is experimentally compared to those of the plain k-NN decision rule and the LVQ algorithms.

Linde–Buzo–Gray algorithmLearning vector quantizationArtificial neural networkAdaptive algorithmbusiness.industryCodebookVector quantizationPattern recognitionDecision ruleMachine learningcomputer.software_genreComputingMethodologies_PATTERNRECOGNITIONLearning ruleArtificial intelligencebusinesscomputerMathematicsProceedings 10th International Conference on Image Analysis and Processing
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Analysis of Complete Neuroblast Cell Lineages in the Drosophila Embryonic Brain via DiI Labeling

2013

Proper functioning of the brain relies on an enormous diversity of neural cells generated by neural stem cell-like neuroblasts (NBs). Each of the about 100 NBs in each side of brain generates a nearly invariant and unique cell lineage, consisting of specific neural cell types that develop in defined time periods. In this chapter we describe a method that labels entire NB lineages in the embryonic brain. Clonal DiI labeling allows us to follow the development of an NB lineage starting from the neuroectodermal precursor cell up to the fully developed cell clone in the first larval instar brain. We also show how to ablate individual cells within an NB clone, which reveals information about the…

Lineage (genetic)Cell divisionNeuroblastPrecursor cellCell CloneBiologyClone (B-cell biology)Molecular biologyNeural cellNeural stem cellCell biology
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Five Ways in Which Computational Modeling Can Help Advance Cognitive Science

2019

Abstract There is a rich tradition of building computational models in cognitive science, but modeling, theoretical, and experimental research are not as tightly integrated as they could be. In this paper, we show that computational techniques—even simple ones that are straightforward to use—can greatly facilitate designing, implementing, and analyzing experiments, and generally help lift research to a new level. We focus on the domain of artificial grammar learning, and we give five concrete examples in this domain for (a) formalizing and clarifying theories, (b) generating stimuli, (c) visualization, (d) model selection, and (e) exploring the hypothesis space.

Linguistics and LanguageArtificial grammar learningComputer scienceCognitive Neuroscience[SHS.PSY]Humanities and Social Sciences/PsychologyExperimental and Cognitive PsychologyBayesian inferenceArtificial grammar learningArticle050105 experimental psychology03 medical and health sciences0302 clinical medicineArtificial IntelligenceHumans0501 psychology and cognitive sciencesCognitive scienceComputational modelPsycholinguisticsArtificial neural networkLift (data mining)Model selection05 social sciencesComputational modelingModels TheoreticalArtificial language learningFormal grammarsExperimental researchBayesian modelingVisualizationHuman-Computer InteractionCognitive ScienceNeural Networks ComputerForthcoming Topic: Learning Grammatical Structures: Developmental Cross‐species and Computational Approaches030217 neurology & neurosurgeryNeural networksTopics in Cognitive Science
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Reconciling time, space and function: a new dorsal-ventral stream model of sentence comprehension.

2013

We present a new dorsal–ventral stream framework for language comprehension which unifies basic neurobiological assumptions (Rauschecker & Scott, 2009) with a cross-linguistic neurocognitive sentence comprehension model (eADM; Bornkessel & Schlesewsky, 2006). The dissociation between (time-dependent)syntactic structure-building and (time-independent) sentence interpretation assumed within thee ADM provides a basis for the division of labour between the dorsal and ventral streams in comprehension.We posit that the ventral stream performs time-independent unifications of conceptual schemata,serving to create auditory objects of increasing complexity. The dorsal stream engages in the time-depe…

Linguistics and LanguageDissociation (neuropsychology)Deep linguistic processingCognitive NeuroscienceModels NeurologicalInferior frontal gyrusExperimental and Cognitive PsychologyHierarchical organisationAnterior temporal lobeStructuringLanguage and LinguisticsTimeSpeech and Hearingventral streaminferior frontal gyrusposterior temporal lobeNeural PathwaysHumansSyntaxcognitive controlanterior temporal lobesyntaxsemanticsLanguageCognitive scienceLanguage comprehensionPosterior temporal lobehierarchical organisationBrainCognitionInferior frontal gyrusSyntaxLinguisticsSemanticsComprehensionDorsal streamdorsal streamCognitive controlVentral streamPsychologyComprehensionSentencelanguage comprehensionBrain and language
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Understanding dynamic scenes

2000

We propose a framework for the representation of visual knowledge in a robotic agent, with special attention to the understanding of dynamic scenes. According to our approach, understanding involves the generation of a high level, declarative description of the perceived world. Developing such a description requires both bottom-up, data driven processes that associate symbolic knowledge representation structures with the data coming out of a vision system, and top-down processes in which high level, symbolic information is in its turn employed to drive and further refine the interpretation of a scene. On the one hand, the computer vision community approached this problem in terms of 2D/3D s…

Linguistics and LanguageKnowledge representation and reasoningComputer scienceMachine visionProcess (engineering)media_common.quotation_subjectRepresentation levelsLanguage and LinguisticsMotion (physics)Data-drivenArtificial IntelligenceHuman–computer interactionPerceptionConceptual spacesArtificial visionLanguage and Linguisticmedia_commonSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniHybrid processingbusiness.industryRepresentation (systemics)RoboticsProcessesAction (philosophy)PerceptionArtificial intelligencebusinessActionsNeural networksArtificial Intelligence
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Stepping into others’ shoes: a cognitive perspective on target audience orientation in written translation

2014

This paper suggests what might allow translators to orient themselves towards their target audience in the translation process. To shed light on translators’ ability to put themselves into their target audience’s shoes, I adopt a cognitive perspective by drawing on current findings from psychology, cognitive science and neuroscience. I depart from the notion of target audience as applied to written translation. Aspects to this concept and the terminology of audience in translation studies are briefly discussed. Then I turn to translation process research to examine two empirical studies and one theoretical paper for insights into researching translators’ target audience orientation. Next, I…

Linguistics and Languagemedia_common.quotation_subjecttarget audience / empathy / translators personality / translator behavior / cognitive and neural processes / translation processTranslator behaviorTarget audienceEmpathyLanguage and LinguisticsEducationTerminologyEmpirical researchZielgruppe / Empathie / Persönlichkeit von ÜbersetzerInnen / Verhalten von ÜbersetzerInnen / Kognitive und neurale Prozesse / ÜbersetzungsprozessSocial cognitionTranslation studiesmedia_commonCognitive scienceTranslators’ personalityUNESCO::CIENCIAS DE LAS ARTES Y LAS LETRASPerspective (graphical)Traducción e InterpretaciónCognitionTarget audienceCognitive and neural processes:CIENCIAS DE LAS ARTES Y LAS LETRAS [UNESCO]Translation processTarget audience; Empathy; Translators’ personality; Translator behavior; Cognitive and neural processes; Translation processEmpathyPsychologySocial psychology
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