Search results for "neuron"

showing 10 items of 2611 documents

Ergodicity for a stochastic Hodgkin–Huxley model driven by Ornstein–Uhlenbeck type input

2013

We consider a model describing a neuron and the input it receives from its dendritic tree when this input is a random perturbation of a periodic deterministic signal, driven by an Ornstein-Uhlenbeck process. The neuron itself is modeled by a variant of the classical Hodgkin-Huxley model. Using the existence of an accessible point where the weak Hoermander condition holds and the fact that the coefficients of the system are analytic, we show that the system is non-degenerate. The existence of a Lyapunov function allows to deduce the existence of (at most a finite number of) extremal invariant measures for the process. As a consequence, the complexity of the system is drastically reduced in c…

Statistics and ProbabilityDegenerate diffusion processesWeak Hörmander conditionType (model theory)01 natural sciencesPeriodic ergodicity010104 statistics & probability60H0760J25FOS: Mathematics0101 mathematicsComputingMilieux_MISCELLANEOUSMathematical physicsMathematics60J60Quantitative Biology::Neurons and CognitionProbability (math.PR)010102 general mathematicsErgodicityOrnstein–Uhlenbeck processHodgkin–Huxley model[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Hodgkin–Huxley model60J60 60J25 60H07Statistics Probability and UncertaintyTime inhomogeneous diffusion processesMathematics - Probability
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On a set of data for the membrane potential in a neuron

2006

We consider a set of data where the membrane potential in a pyramidal neuron is measured almost continuously in time, under varying experimental conditions. We use nonparametric estimates for the diffusion coefficient and the drift in view to contribute to the discussion which type of diffusion process is suitable to model the membrane potential in a neuron (more exactly: in a particular type of neuron under particular experimental conditions).

Statistics and ProbabilityModels NeurologicalNeural ConductionAction PotentialsTetrodotoxinType (model theory)Statistics NonparametricGeneral Biochemistry Genetics and Molecular BiologyMembrane PotentialsSet (abstract data type)MiceStatisticsAnimalsDiffusion (business)MathematicsCerebral CortexNeuronsMembrane potentialStochastic ProcessesQuantitative Biology::Neurons and CognitionGeneral Immunology and MicrobiologyStochastic processPyramidal CellsApplied MathematicsNonparametric statisticsGeneral MedicineElectrophysiologyElectrophysiologynervous systemDiffusion processModeling and SimulationPotassiumGeneral Agricultural and Biological SciencesBiological systemAlgorithmsMathematical Biosciences
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Energy efficient modulation of dendritic processing functions

1998

The voltage dependent ionic conductances and the passive properties of the neural membrane determine how external inputs are processed by the dendritic tree, and define the computational characteristics of neurons. However, what controls these characteristics and how they are implemented at the single neuron level, in such a way that an external input results in the coding of the appropriate output, is essentially unknown. We show here that a slow inactivation of the Na+ channel, involved in the attenuation and/or failure of APs in the dendrites, acts as an active and energy efficient filter of synaptic input, and results in an activity-dependent control of the properties of individual neur…

Statistics and ProbabilityPhysicsApplied MathematicsAttenuationModels NeurologicalAction PotentialsDendritesGeneral MedicineGeneral Biochemistry Genetics and Molecular Biologymedicine.anatomical_structureFilter (video)ModulationModeling and SimulationLimit (music)medicineNeuronNeuroscienceSodium Channel BlockersEfficient energy useVoltageCommunication channelBiosystems
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A multi-scale approach for testing and detecting peaks in time series

2020

An approach is presented that combines a statistical test for peak detection with the estimation of peak positions in time series. Motivated by empirical observations in neuronal recordings, we aim at investigating peaks of different heights and widths. We use a moving window approach to compare the differences of estimated slope coefficients of local regression models. We combine multiple windows and use the global maximum of all different processes as a test statistic. After rejection, a multiple filter algorithm combines peak positions estimated from multiple windows. Analysing neuronal activity recorded in anaesthetized mice, the procedure could identify significant differences between …

Statistics and Probabilitypeak detection ; multi-scale ; linear regression ; neuronal ensembles ; Brain statesSeries (mathematics)Scale (ratio)business.industry05 social sciencesPattern recognition01 natural sciencesPeak detection010104 statistics & probabilityBrain state0502 economics and businessLinear regressionArtificial intelligence0101 mathematicsStatistics Probability and Uncertaintybusiness050205 econometrics Statistical hypothesis testingMathematics
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Attracted or repelled?--a matter of two neurons, one pheromone binding protein, and a chiral center.

1998

Abstract Two species of scarab beetles, the Osaka beetle (Anomala osakana) and the Japanese beetle (Popillia japonica), utilize the opposite enantiomers of japonilure, (Z)-5-(1-decenyl)oxacyclopentan-2-one, as their sex pheromones. Each species produces only one of the enantiomers that functions as its own sex pheromone and as a very strong behavioral antagonist for the other species. Using an integrated approach we tested whether the discrimination of these two opposite signals is due to selective filtering by pheromone binding proteins or whether it originates in the specificity of ligand–receptor interactions. We found that the antennae of each of these two scarab species contain only a …

StereochemistryProtein ConformationMolecular Sequence DataBiophysicsBiochemistryPheromonesPopilliaBotanymedicineAnimalsPheromone bindingAmino Acid SequenceCloning MolecularMolecular BiologySensillumNeuronsOlfactory receptorBinding SitesbiologyStereoisomerismCell Biologybiology.organism_classificationChemoreceptor CellsColeopteramedicine.anatomical_structureSex pheromonePheromoneEnantiomerPheromone binding proteinSequence AlignmentSignal TransductionBiochemical and biophysical research communications
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Zum Wandel motorischer Einheiten bei Änderung des Aktivitätsmusters durch elektrische Reizung - Elektrostimulation und ihre klinischen Einsatzmöglich…

1989

Motoneuron and muscle fibers interact on the motor unit level, whereby discharge characteristics from the neuron imposed on the muscle seem to play a major role. Within the unit all muscle fibers are biochemically homogeneous and display a high degree of plasticity under different functional demands. To distinguish the existing different units rationals are listed that classify the units by physiological and histochemical parameters. Furthermore the review summarizes the available knowledge on the importance of activity patterns--as a biological principle--involved in the control of phenotypic expression of innervated and denervated muscle. The sequelae are shown of electrical stimulation o…

StimulationPlasticityBiologyMotor unitPsychiatry and Mental healthmedicine.anatomical_structureNeurologyHomogeneousNeuroplasticitymedicineElectric stimulation therapyNeurology (clinical)NeuronNeuroscienceElectric stimulationFortschritte der Neurologie · Psychiatrie
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A Neurocomputational Approach to Trained and Transitive Relations in Equivalence Classes

2017

A stimulus class can be composed of perceptually different but functionally equivalent stimuli. The relations between the stimuli that are grouped in a class can be learned or derived from other stimulus relations. If stimulus A is equivalent to B, and B is equivalent to C, then the equivalence between A and C can be derived without explicit training. In this work we propose, with a neurocomputational model, a basic learning mechanism for the formation of equivalence. We also describe how the relatedness between the members of an equivalence class is developed for both trained and derived stimulus relations. Three classic studies on stimulus equivalence are simulated covering typical and at…

Stimulus equivalencePure mathematicslcsh:BF1-990Stimulus (physiology)Machine learningcomputer.software_genre03 medical and health sciencesBasic learning0302 clinical medicinePsychology0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyNodal distanceEquivalence classGeneral PsychologyOriginal ResearchTransitive relationQuantitative Biology::Neurons and Cognitionbusiness.industryneurocomputational modelequivalence classes05 social sciencestransitive relationscategorizationlcsh:PsychologyHebbian theoryCategorizationArtificial intelligenceHebbian learningbusinessPsychologycomputer030217 neurology & neurosurgeryFrontiers in Psychology
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Stimulant-induced adaptations in neostriatal matrix and striosome systems: Transiting from instrumental responding to habitual behavior in drug addic…

2005

Abstract Converging evidence indicates that repeated exposure to motor stimulants such as cocaine and amphetamine produces marked alterations in network responsiveness of striatal neurons to subsequent challenge with the same stimulant drug. Such alterations, which correlate with persistent patterns of repetitive behavior, associate with distinct compartmental changes in the neostriatum. Striatal matrix system neurons undergo “silencing” following repeated drug challenges, allowing striosome system neurons to exhibit preferential activation. Matrix neurons are innervated by sensory and motor areas of neocortex and are activated in the course of on-going, adaptive behavior. Inactivation of m…

StriosomeCognitive NeuroscienceAmphetamine-Related DisordersExperimental and Cognitive PsychologySensory systemBasal GangliaReceptors DopamineCocaine-Related DisordersBehavioral NeuroscienceCocaineDopamineBasal gangliaLimbic SystemmedicineAnimalsHumansHabituation PsychophysiologicAmphetamineAnterior cingulate cortexCerebral CortexNeuronsNeocortexNeostriatumAmphetaminemedicine.anatomical_structurenervous systemConditioning OperantCentral Nervous System StimulantsNerve NetArousalPsychologyNeuroscienceBasolateral amygdalamedicine.drugNeurobiology of Learning and Memory
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Biomaterials coated by dental pulp cells as substrate for neural stem cell differentiation

2011

[EN] This study is focused on the development of an in vitro hybrid system, consisting in a polymeric biomaterial covered by a dental pulp cellular stroma that acts as a scaffold offering a neurotrophic support for the subsequent survival and differentiation of neural stem Cells. In the first place, the behavior of dental pulp stroma on the polymeric biomaterial based on ethyl acrylate and hydroxy ethyl acrylate copolymer was studied. For this purpose, cells from normal human third molars were grown onto 0.5-mm-diameter biomaterial discs. After cell culture, quantification of neurotrophic factors generated by the stromal cells was performed by means of an ELISA assay. In the second place, s…

Stromal cellMaterials scienceBiomedical EngineeringBiomaterialsCell therapyMiceNerve growth factorCoated Materials BiocompatibleNeural Stem Cellsstomatognathic systemNeurotrophic factorsAnimalsHumansNeural cellCells CulturedDental PulpCell ProliferationNeuronsStem cellBrain-Derived Neurotrophic FactorMetals and AlloysBiomaterialCell adhesionCell DifferentiationNeural stem cellRatsCell biologystomatognathic diseasesCell cultureMAQUINAS Y MOTORES TERMICOSCeramics and CompositesCell cultureStem cellNeural cellBiomedical engineering
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Are Neural Networks Imitations of Mind?

2015

Artificial neural networks are often understood as a good way to imitate mind through the web structure of neurons in brain, but the very high complexity of human brain prevents to consider neural networks as good models for human mind;anyway neural networks are good devices for computation in parallel. The difference between feed-forward and feedback neural networks is introduced; the Hopfield network and the multi-layers Perceptron are discussed. In a very weak isomorphism (not similitude) between brain and neural networks, an artificial form of short term memory and of acknowledgement, in Elman neural networks, is proposed.

Structure (mathematical logic)Artificial neural networkQuantitative Biology::Neurons and CognitionArtificial neural networkComputer sciencebusiness.industryComputationComputer Science::Neural and Evolutionary ComputationAcknowledgementShort-term memoryRecurrent networkBrainFeed-forward networkSettore M-FIL/02 - Logica E Filosofia Della ScienzaPerceptroncomputer.software_genreMindSimilitudeHopfield networkArtificial intelligenceData miningbusinesscomputer
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