Search results for "anger"

showing 10 items of 929 documents

Assessing Frequency Domain Causality in Cardiovascular Time Series with Instantaneous Interactions

2009

Summary Background: The partial directed coherence (PDC) is commonly used to assess in the frequency domain the existence of causal relations between two time series measured in conjunction with a set of other time series. Although the multivariate autoregressive (MVAR) model traditionally used for PDC computation accounts only for lagged effects, instantaneous effects cannot be neglected in the analysis of cardiovascular time series. Objectives: We propose the utilization of an extended MVAR model for PDC computation, in order to improve the evaluation of frequency domain causality in the presence of zero-lag correlations among multivariate time series. Methods: A procedure for the identif…

Multivariate statisticsComputationDiagnostic Techniques CardiovascularHealth InformaticsHealth Information ManagementExtended modelGranger causalityReference ValuesEconometricsCardiovascular interactionHumansCoherence (signal processing)MathematicsHealth InformaticAdvanced and Specialized NursingPartial directed coherenceModels CardiovascularAC powerCausalityAutoregressive modelFrequency domainSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaMultivariate AnalysisGranger causalityLinear ModelsRegression AnalysisAlgorithmMethods of Information in Medicine
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Information Dynamics Analysis: A new approach based on Sparse Identification of Linear Parametric Models*

2020

The framework of information dynamics allows to quantify different aspects of the statistical structure of multivariate processes reflecting the temporal dynamics of a complex network. The information transfer from one process to another can be quantified through Transfer Entropy, and under the assumption of joint Gaussian variables it is strictly related to the concept of Granger Causality (GC). According to the most recent developments in the field, the computation of GC entails representing the processes through a Vector Autoregressive (VAR) model and a state space (SS) model typically identified by means of the Ordinary Least Squares (OLS). In this work, we propose a new identification …

Multivariate statisticsComputer scienceEntropyGaussian0206 medical engineeringNormal Distribution02 engineering and technology01 natural sciencesLASSO regression010305 fluids & plasmassymbols.namesakeinformation TransferState Space modelsGranger causalityLasso (statistics)0103 physical sciencesStatistics::MethodologyState spaceLeast-Squares AnalysisShrinkageSparse matrixElectroencephalography020601 biomedical engineeringinformation Transfer; LASSO regression; State Space models; Granger causalityAutoregressive modelstate space modelParametric modelOrdinary least squaresLinear ModelssymbolsGranger causalityTransfer entropyAlgorithmInformation dyancamic analysi
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Decomposing the transfer entropy to quantify lag-specific Granger causality in cardiovascular variability.

2013

We present a modification of the well known transfer entropy (TE) which makes it able to detect, besides the direction and strength of the information transfer between coupled processes, its exact timing. The approach follows a decomposition strategy which identifies--according to a lag-specific formulation of the concept of Granger causality--the set of time delays carrying significant information, and then assigns to each of these delays an amount of information transfer such that the total contribution yields the overall TE. We propose also a procedure for the practical estimation from time series data of the relevant delays and lag-specific TE in both bivariate and multivariate settings…

Multivariate statisticsMathematical optimizationInformation transferMedicine (all)LagEntropyBivariate analysisCardiovascular Physiological PhenomenaGranger causalitySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaMultivariate AnalysisEntropy (information theory)HumansTransfer entropyComputer SimulationTime seriesAlgorithmsMathematicsAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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Algorithms for the inference of causality in dynamic processes: Application to cardiovascular and cerebrovascular variability

2015

This study faces the problem of causal inference in multivariate dynamic processes, with specific regard to the detection of instantaneous and time-lagged directed interactions. We point out the limitations of the traditional Granger causality analysis, showing that it leads to false detection of causality when instantaneous and time-lagged effects coexist in the process structure. Then, we propose an improved algorithm for causal inference that combines the Granger framework with the approach proposed by Pearl for the study of causality among multiple random variables. This new approach is compared with the traditional one in theoretical and simulated examples of interacting processes, sho…

Multivariate statisticsProcess (engineering)Computer scienceBiomedical EngineeringInferenceHealth InformaticsMachine learningcomputer.software_genreHeart RateEconometricsHumansArterial PressureComputer Simulation1707Granger causality analysisSeries (mathematics)business.industryBrainHeartCausalityCausalityCerebrovascular CirculationCausal inferenceSignal ProcessingSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaArtificial intelligencebusinesscomputerRandom variableAlgorithms2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
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Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series

2012

The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respira…

Multivariate statisticsSupine positionMultivariate analysisQuantitative Biology::Tissues and OrgansTime delay embeddingPhysics::Medical PhysicsPostureBlood PressureHealth InformaticsCardiovascular Physiological PhenomenaGranger causalityPosition (vector)StatisticsHumansCardiovascular interactionMathematicsConditional entropySeries (mathematics)RespirationModels CardiovascularReproducibility of ResultsSignal Processing Computer-AssistedComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsNonlinear systemNonlinear DynamicsMultivariate AnalysisSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityMultivariate time serieConditional entropyAlgorithmAlgorithms
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Measuring frequency domain granger causality for multiple blocks of interacting time series

2011

In the past years, several frequency-domain causality measures based on vector autoregressive time series modeling have been suggested to assess directional connectivity in neural systems. The most followed approaches are based on representing the considered set of multiple time series as a realization of two or three vector-valued processes, yielding the so-called Geweke linear feedback measures, or as a realization of multiple scalar-valued processes, yielding popular measures like the directed coherence (DC) and the partial DC (PDC). In the present study, these two approaches are unified and generalized by proposing novel frequency-domain causality measures which extend the existing meas…

Multivariate statisticsTime FactorsGeneral Computer ScienceLogarithmScalar (mathematics)Complex systemTopologyModels BiologicalNeurophysiological time serieBlock-based connectivity analysiGranger causalityStatisticsHumansComputer SimulationDirected coherenceMathematicsNumerical analysisPartial directed coherenceBrainElectroencephalographyVector autoregressive (VAR) modelBrain WavesCausalityAutoregressive modelFrequency domainComputer ScienceSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityAlgorithmsBiotechnologyBiological Cybernetics
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Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactions.

2010

The Partial Directed Coherence (PDC) and its generalized formulation (gPDC) are popular tools for investigating, in the frequency domain, the concept of Granger causality among multivariate (MV) time series. PDC and gPDC are formalized in terms of the coefficients of an MV autoregressive (MVAR) model which describes only the lagged effects among the time series and forsakes instantaneous effects. However, instantaneous effects are known to affect linear parametric modeling, and are likely to occur in experimental time series. In this study, we investigate the impact on the assessment of frequency domain causality of excluding instantaneous effects from the model underlying PDC evaluation. M…

Multivariate statisticsTime FactorsGeneral Computer ScienceModels NeurologicalPattern Recognition AutomatedCardiovascular Physiological PhenomenaElectrocardiographyGranger causalityArtificial IntelligenceEconometricsCoherence (signal processing)AnimalsHumansComputer SimulationEEGPartial Directed CoherenceMathematicsCausal modelMultivariate autoregressive modelComputer Science (all)Linear modelElectroencephalographySignal Processing Computer-AssistedCardiovascular variabilityAutoregressive modelFrequency domainParametric modelSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityMultivariate time serieLinear ModelsNeural Networks ComputerBiotechnologyBiological cybernetics
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Testing different methodologies for Granger causality estimation: A simulation study

2021

Granger causality (GC) is a method for determining whether and how two time series exert causal influences one over the other. As it is easy to implement through vector autoregressive (VAR) models and can be generalized to the multivariate case, GC has spread in many different areas of research such as neuroscience and network physiology. In its basic formulation, the computation of GC involves two different regressions, taking respectively into account the whole past history of the investigated multivariate time series (full model) and the past of all time series except the putatively causal time series (restricted model). However, the restricted model cannot be represented through a finit…

Multivariate statisticsstate space modelsSeries (mathematics)Computer scienceGranger causality; state space modelsDynamical NetworksMultivariate Time SeriesReduction (complexity)Autoregressive modelGranger causalitySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityState spaceConditioningTime seriesVector Autoregressive ProcessesAlgorithm2020 28th European Signal Processing Conference (EUSIPCO)
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In vitro multiplication ofVella lucentina M. B. crespo (Brassicaceae), a threatened Spanish endemic species

1995

Vella lucentina M. B. Crespo is a threatened Spanish species that is endemic to a small area in eastern Alicante Province (SE Spain). Micropropagation techniques were applied forex situ conservation of this plant. Aseptic epicotyls bearing the apical bud were grown in Murashige and Skoog medium supplemented with 6-furfurylaminopurine (Kin), N6-benzyladenine (BA) or 6-(γ,γ,-dimethilalylamino) purine (2iP). High multiplication rates were obtained with 0.5, 1, or 2 mg·liter−1 BA, or 1 or 2 mg·liter−1 2iP. Indole-3-acetic acid and indole-3-butyric acid were utilized for rooting in half-strength Murashige and Skoog medium. Regenerated plants were transferred to a potting mix and gradually acclim…

Murashige and Skoog mediumbiologyMicropropagationApical dominanceThreatened speciesBotanyEndangered speciesBrassicaceaePlant ScienceEndemismbiology.organism_classificationPotting soilBiotechnologyIn Vitro Cellular & Developmental Biology - Plant
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Adolescents’ expression and perception of emotion in music reflects their broader abilities of emotional communication

2014

Background: Musical behavior has been shown to reflect broader individual differences. However, despite the prevalence of music in the lives of young people little is known about the mechanisms through which adolescents’ musical behavior connects to their general socio-emotional behavior and adjustment. The current study focused on abilities of emotional communication and investigated whether adolescents’ abilities in both perceiving and expressing emotions through music would be reflective of their general abilities of socio-emotional communication and interaction, measured through empathy and conduct problems. Due to the lack of previous research the study was mainly exploratory, but we e…

Music psychologymedia_common.quotation_subjectEmotional intelligencemusiikkiEmpathyGeneral MedicineAngerDevelopmental psychologySadnessemotion expressionMusic and emotionEmotion perceptionempatiaemotion perceptionadolescencePsychologyEmpathic concernmedia_commonCognitive psychology
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