Search results for " mutual information"

showing 10 items of 20 documents

Comparison of discretization strategies for the model-free information-theoretic assessment of short-term physiological interactions

2023

This work presents a comparison between different approaches for the model-free estimation of information-theoretic measures of the dynamic coupling between short realizations of random processes. The measures considered are the mutual information rate (MIR) between two random processes [Formula: see text] and [Formula: see text] and the terms of its decomposition evidencing either the individual entropy rates of [Formula: see text] and [Formula: see text] and their joint entropy rate, or the transfer entropies from [Formula: see text] to [Formula: see text] and from [Formula: see text] to [Formula: see text] and the instantaneous information shared by [Formula: see text] and [Formula: see…

Applied MathematicsSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGeneral Physics and AstronomyStatistical and Nonlinear PhysicsInformation-theoretic measures mutual information rate (MIR) binning permutation time-series analysisMathematical Physics
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Functional connectivity inference from fMRI data using multivariate information measures

2022

Abstract Shannon’s entropy or an extension of Shannon’s entropy can be used to quantify information transmission between or among variables. Mutual information is the pair-wise information that captures nonlinear relationships between variables. It is more robust than linear correlation methods. Beyond mutual information, two generalizations are defined for multivariate distributions: interaction information or co-information and total correlation or multi-mutual information. In comparison to mutual information, interaction information and total correlation are underutilized and poorly studied in applied neuroscience research. Quantifying information flow between brain regions is not explic…

Brain MappingComputer scienceEntropyCognitive NeuroscienceConditional mutual informationBrainMultivariate normal distributionMutual informationcomputer.software_genreMagnetic Resonance ImagingInteraction informationRedundancy (information theory)Artificial IntelligenceEntropy (information theory)Computer SimulationTotal correlationInformation flow (information theory)Data miningcomputerNeural Networks
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Three-dimensional Fuzzy Kernel Regression framework for registration of medical volume data

2013

Abstract In this work a general framework for non-rigid 3D medical image registration is presented. It relies on two pattern recognition techniques: kernel regression and fuzzy c-means clustering. The paper provides theoretic explanation, details the framework, and illustrates its application to implement three registration algorithms for CT/MR volumes as well as single 2D slices. The first two algorithms are landmark-based approaches, while the third one is an area-based technique. The last approach is based on iterative hierarchical volume subdivision, and maximization of mutual information. Moreover, a high performance Nvidia CUDA based implementation of the algorithm is presented. The f…

Computer sciencebusiness.industryImage registrationMutual informationMachine learningcomputer.software_genreFuzzy logicCUDANon-rigid registration Fuzzy regression Mutual information Interpolation GPU computingArtificial IntelligenceSignal ProcessingPattern recognition (psychology)Kernel regressionComputer Vision and Pattern RecognitionArtificial intelligenceData miningGeneral-purpose computing on graphics processing unitsCluster analysisbusinesscomputerSoftwareInterpolationPattern Recognition
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The pragmatics of political messages in twitter communication

2012

The aim of the current paper is to formulate a conception of pragmatic patterns characterizing the construction of individual and collective identities in virtual communities (in our case: the Twitter community). We have explored several theoretical approaches and frameworks and relevant empirical data to show that the agents building virtual communities are 'extended selves' grounded in a highly dynamic and compressed, linguistically mediated virtual network structure. Our empirical evidence consists of a study of discourse related to the Latvian parliamentary elections of 2010. We used a Twitter corpus (in Latvian) harvested and statistically evaluated using the Pointwise Mutual Informati…

Computer sciencebusiness.industryOpinion leadershipLatvianPragmaticsPointwise mutual informationPublic relationslanguage.human_languageWorld Wide WebCollective identityGeneral electionlanguagebusinessEmpirical evidenceVirtual network
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Information decomposition of multichannel EMG to map functional interactions in the distributed motor system

2019

AbstractThe central nervous system needs to coordinate multiple muscles during postural control. Functional coordination is established through the neural circuitry that interconnects different muscles. Here we used multivariate information decomposition of multichannel EMG acquired from 14 healthy participants during postural tasks to investigate the neural interactions between muscles. A set of information measures were estimated from an instantaneous linear regression model and a time-lagged VAR model fitted to the EMG envelopes of 36 muscles. We used network analysis to quantify the structure of functional interactions between muscles and compared them across experimental conditions. Co…

MaleInformation transferMuscle networkNeurologyTransfer entropyComputer scienceSocial SciencesPostural controlFunctional connectivity0302 clinical medicineCONNECTIVITYNeural PathwaysDecomposition (computer science)Medicine and Health Sciencesmotor controlMuscle activityPostural Balance0303 health sciencesMuscle networksConditional mutual information05 social sciencesmedicine.anatomical_structureNeurologySYNCHRONIZATIONFemaleSpinal reflexAdultCORTEXmedicine.medical_specialtyCognitive NeurosciencePostureCentral nervous systemORGANIZATIONCognitive neuroscienceGRANGER CAUSALITY050105 experimental psychology03 medical and health sciencesReflexMotor systemCOHERENCEBiological neural networkmedicineHumans0501 psychology and cognitive sciencesMuscle SkeletalSet (psychology)signal processing030304 developmental biologyIDENTIFICATIONElectromyographyPostural controlMotor controlINPUTSMUSCLE SYNERGIESBRAIN NETWORKSSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaNeuroscience030217 neurology & neurosurgery
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Joint Probability of Shape and Image Similarities to Retrieve 2D TRUS-MR Slice Correspondence for Prostate Biopsy

2012

International audience; This paper presents a novel method to identify the 2D axial Magnetic Resonance (MR) slice from a pre-acquired MR prostate volume that closely corresponds to the 2D axial Transrectal Ultrasound (TRUS) slice obtained during prostate biopsy. The method combines both shape and image intensity information. The segmented prostate contours in both the imaging modalities are described by shape-context representations and matched using the Chi-square distance. Normalized mutual information and correlation coefficient between the TRUS and MR slices are computed to find image similarities. Finally, the joint probability values comprising shape and image similarities are used in…

MaleProstate biopsyBiopsy[INFO.INFO-IM] Computer Science [cs]/Medical Imaging030230 surgeryNormalized mutual information030218 nuclear medicine & medical imagingImage (mathematics)03 medical and health sciences0302 clinical medicineJoint probability distribution[INFO.INFO-IM]Computer Science [cs]/Medical ImagingMedicineHumansComputer visionMR ProstateProbabilitymedicine.diagnostic_test[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industryUltrasoundProstatic NeoplasmsMagnetic resonance imagingImage segmentationMagnetic Resonance ImagingArtificial intelligencebusiness
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Accelerating Causal Inference and Feature Selection Methods through G-Test Computation Reuse

2021

This article presents a novel and remarkably efficient method of computing the statistical G-test made possible by exploiting a connection with the fundamental elements of information theory: by writing the G statistic as a sum of joint entropy terms, its computation is decomposed into easily reusable partial results with no change in the resulting value. This method greatly improves the efficiency of applications that perform a series of G-tests on permutations of the same features, such as feature selection and causal inference applications because this decomposition allows for an intensive reuse of these partial results. The efficiency of this method is demonstrated by implementing it as…

Markov blanketMarkov blanketComputer sciencecomputation reuseConditional mutual informationComputationSciencePhysicsQC1-999QGeneral Physics and AstronomyContext (language use)Feature selectionInformation theoryAstrophysicsJoint entropyArticleG-testQB460-466feature selectionCausal inferencecausal inferenceAlgorithminformation theoryEntropy
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Quantum scrambling via accessible tripartite information

2023

Quantum information scrambling (QIS), from the perspective of quantum information theory, is generally understood as local non-retrievability of information evolved through some dynamical process, and is often quantified via entropic quantities such as the tripartite information. We argue that this approach comes with a number of issues, in large part due to its reliance on quantum mutual informations, which do not faithfully quantify correlations directly retrievable via measurements, and in part due to the specific methodology used to compute tripartite informations of the studied dynamics. We show that these issues can be overcome by using accessible mutual informations, defining corresp…

Paperquantum information scramblingQuantum PhysicsPhysics and Astronomy (miscellaneous)Materials Science (miscellaneous)multipartite entanglementtripartite informationFOS: Physical sciencesaccessible mutual information and quantum discordElectrical and Electronic EngineeringQuantum Physics (quant-ph)Settore FIS/03 - Fisica Della MateriaAtomic and Molecular Physics and Optics
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Transition behavior in the channel capacity of two-quibit channels with memory

2004

We prove that a general upper bound on the maximal mutual information of quantum channels is saturated in the case of Pauli channels with an arbitrary degree of memory. For a subset of such channels we explicitly identify the optimal signal states. We show analytically that for such a class of channels entangled states are indeed optimal above a given memory threshold.

PhysicsData_CODINGANDINFORMATIONTHEORYCoherent informationQuantum channelQuantum capacityTopologyUpper and lower boundsAtomic and Molecular Physics and OpticsClassical capacityQuantum mechanicsQuantum informationAmplitude damping channelQuantum mutual informationComputer Science::Information Theory
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Mutual information and spontaneous symmetry breaking

2015

We show that the metastable, symmetry-breaking ground states of quantum many-body Hamiltonians have vanishing quantum mutual information between macroscopically separated regions, and are thus the most classical ones among all possible quantum ground states. This statement is obvious only when the symmetry-breaking ground states are simple product states, e.g. at the factorization point. On the other hand, symmetry-breaking states are in general entangled along the entire ordered phase, and to show that they actually feature the least macroscopic correlations compared to their symmetric superpositions is highly non trivial. We prove this result in general, by considering the quantum mutual …

PhysicsQuantum discordQuantum PhysicsStrongly Correlated Electrons (cond-mat.str-el)FOS: Physical sciencesQuantum capacityQuantum entanglementCoherent information01 natural sciencesQuantum relative entropyAtomic and Molecular Physics and Optics010305 fluids & plasmasCondensed Matter - Strongly Correlated ElectronsQuantum mechanicsAtomic and Molecular Physics0103 physical sciencesand Optics010306 general physicsQuantum mutual informationAmplitude damping channelmutual informationQuantum Physics (quant-ph)Joint quantum entropy
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