0000000000107897

AUTHOR

Qing Zhang

showing 6 related works from this author

Tensor clustering on outer-product of coefficient and component matrices of independent component analysis for reliable functional magnetic resonance…

2019

Background. Stability of spatial components is frequently used as a post-hoc selection criteria for choosing the dimensionality of an independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data. Although the stability of the ICA temporal courses differs from that of spatial components, temporal stability has not been considered during dimensionality decisions. New method. The current study aims to (1) develop an algorithm to incorporate temporal course stability into dimensionality selection and (2) test the impact of temporal course on the stability of the ICA decomposition of fMRI data via tensor clustering. Resting state fMRI data were analyzed with two popu…

model ordertoiminnallinen magneettikuvaustensor clusteringfMRIsignaalianalyysistabilityindependent component analysis (ICA)
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Consistency of Independent Component Analysis for FMRI

2021

Background Independent component analysis (ICA) has been widely used for blind source separation in the field of medical imaging. However, despite of previous substantial efforts, the stability of ICA components remains a critical issue which has not been adequately addressed, despite numerous previous efforts. Most critical is the inconsistency of some of the extracted components when ICA is run with different model orders (MOs). New Method In this study, a novel method of determining the consistency of component analysis (CoCA) is proposed to evaluate the consistency of extracted components with different model orders. In the method, “consistent components” (CCs) are defined as those whic…

model ordertoiminnallinen magneettikuvausconsistencysignaalinkäsittelyfMRIsignaalianalyysiICA
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Experimental determination of single molecule toroic behaviour in a Dy8 single molecule magnet

2019

The enhancement of toroic motifs through coupling toroidal moments within molecular nanomagnets is a new, interesting and relevant approach for both fundamental research and potential quantum computation applications. We investigate a Dy8 molecular cluster and discover it has a antiferrotoroic ground state with slow magnetic relaxation. The experimental characterization of the magnetic anisotropy axes of each magnetic center and their exchange interactions represents a considerable challenge due to the non-magnetic nature of the toroidal motif. To overcome this and obtain access to the low energy states of Dy8 we establish a multi-orientation single-crystal micro Hall sensor magnetometry ap…

PhysicsMagnetometerUNESCO::QUÍMICA02 engineering and technologySpin structure010402 general chemistry021001 nanoscience & nanotechnology01 natural sciencesMolecular physics:QUÍMICA [UNESCO]0104 chemical scienceslaw.inventionIonCoupling (physics)Magnetic anisotropylawMoleculeGeneral Materials ScienceSingle-molecule magnet0210 nano-technologyGround state
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Shared and Unshared Feature Extraction in Major Depression During Music Listening Using Constrained Tensor Factorization

2021

Ongoing electroencephalography (EEG) signals are recorded as a mixture of stimulus-elicited EEG, spontaneous EEG and noises, which poses a huge challenge to current data analyzing techniques, especially when different groups of participants are expected to have common or highly correlated brain activities and some individual dynamics. In this study, we proposed a data-driven shared and unshared feature extraction framework based on nonnegative and coupled tensor factorization, which aims to conduct group-level analysis for the EEG signals from major depression disorder (MDD) patients and healthy controls (HC) when freely listening to music. Constrained tensor factorization not only preserve…

masennusmajor depressive disordersignaalinkäsittelymusiikkinaturalistic music stimulisignaalianalyysiNeurosciences. Biological psychiatry. NeuropsychiatryHuman Neuroscienceconstrained tensor factorizationbehavioral disciplines and activitiesBehavioral NeurosciencePsychiatry and Mental healthNeuropsychology and Physiological PsychologyNeurologyCANDECOMP/PARAFACaivotutkimusEEGärsykkeetBiological PsychiatryRC321-571Original ResearchFrontiers in Human Neuroscience
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The role of motor system in action-related language comprehension in L1 and L2: An fMRI study

2018

The framework of embodied cognition has challenged the modular view of a language-cognition divide by suggesting that meaning-retrieval critically involves the sensory-motor system. Despite extensive research into the neural mechanisms underlying language-motor coupling, it remains unclear how the motor system might be differentially engaged by different levels of linguistic abstraction and language proficiency. To address this issue, we used fMRI to quantify neural activations in brain regions underlying motor and language processing in Chinese-English speakers’ processing of literal, metaphorical, and abstract language in their L1 and L2. Results overall revealed a response in motor ROIs …

toinen kieliAdultMaleLinguistics and Languagemetaphorical languagefirst/second languageCognitive NeuroscienceMultilingualismExperimental and Cognitive PsychologyäidinkieliAbstract languagegradation050105 experimental psychologyLanguage and Linguistics03 medical and health sciencesSpeech and Hearingtoiminnallinen magneettikuvaus0302 clinical medicineMotor systemConnectomeHumans0501 psychology and cognitive sciencesLanguage proficiencyAbstractionmotoriikkaluetun ymmärtäminenfMRI05 social sciencesMotor CortexContrast (statistics)linguistic abstractionkognitiiviset prosessitMagnetic Resonance ImagingComprehensionembodied cognitionAction (philosophy)Embodied cognitiontekstinymmärtäminenFemaleComprehensionPsychology030217 neurology & neurosurgeryCognitive psychologyBrain and Language
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Examining stability of independent component analysis based on coefficient and component matrices for voxel-based morphometry of structural magnetic …

2018

Independent component analysis (ICA) on group-level voxel-based morphometry (VBM) produces the coefficient matrix and the component matrix. The former contains variability among multiple subjects for further statistical analysis, and the latter reveals spatial maps common for all subjects. ICA algorithms converge to local optimization points in practice and the mostly applied stability investigation approach examines the stability of the extracted components. We found that the practically stable components do not guarantee to produce the practically stable coefficients of ICA decomposition for the further statistical analysis. Consequently, we proposed a novel approach including two steps: …

back-projectioncomponent matrixaivokuoridiabetescoefficient matrixvoxel-based morphometrysignaalianalyysimagneettitutkimusriippumattomien komponenttien analyysiMontreal cognitive assessmentstability
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