Search results for "ongoing EEG"

showing 5 items of 5 documents

Functional connectivity of major depression disorder using ongoing EEG during music perception

2020

Abstract Objective The functional connectivity (FC) of major depression disorder (MDD) has not been well studied under naturalistic and continuous stimuli conditions. In this study, we investigated the frequency-specific FC of MDD patients exposed to conditions of music perception using ongoing electroencephalogram (EEG). Methods First, we applied the phase lag index (PLI) method to calculate the connectivity matrices and graph theory-based methods to measure the topology of brain networks across different frequency bands. Then, classification methods were adopted to identify the most discriminate frequency band for the diagnosis of MDD. Results During music perception, MDD patients exhibit…

Adultmasennusmedicine.medical_specialtymusic perceptionFrequency bandmusiikkiElectroencephalographyAudiologybehavioral disciplines and activitiesnaturalistic stimuli050105 experimental psychology03 medical and health sciencesBeta bandYoung Adult0302 clinical medicinePhysiology (medical)mental disordersmedicineHumans0501 psychology and cognitive sciencesEEGDepression (differential diagnoses)AgedDepressive Disorder Majormedicine.diagnostic_testFunctional connectivity05 social sciencesfunctional connectivitymajor depression disorderBrainElectroencephalographyMiddle AgedSensory SystemsPhase lagongoing EEGNeurologyMusic perceptionAuditory PerceptionClassification methodsNeurology (clinical)Psychology030217 neurology & neurosurgeryMusicärsykkeet
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Increasing Stability of EEG Components Extraction Using Sparsity Regularized Tensor Decomposition

2018

Tensor decomposition has been widely employed for EEG signal processing in recent years. Constrained and regularized tensor decomposition often attains more meaningful and interpretable results. In this study, we applied sparse nonnegative CANDECOMP/PARAFAC tensor decomposition to ongoing EEG data under naturalistic music stimulus. Interesting temporal, spectral and spatial components highly related with music features were extracted. We explored the ongoing EEG decomposition results and properties in a wide range of sparsity levels, and proposed a paradigm to select reasonable sparsity regularization parameters. The stability of interesting components extraction from fourteen subjects’ dat…

medicine.diagnostic_testbusiness.industryComputer sciencePattern recognition02 engineering and technologyElectroencephalographystability analysisRegularization (mathematics)ongoing EEG03 medical and health sciences0302 clinical medicinetensor decomposition0202 electrical engineering electronic engineering information engineeringmedicineTensor decompositionsparse regularization020201 artificial intelligence & image processingArtificial intelligencebusiness030217 neurology & neurosurgerynonnegative constraints
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Group analysis of ongoing EEG data based on fast double-coupled nonnegative tensor decomposition

2019

Abstract Background Ongoing EEG data are recorded as mixtures of stimulus-elicited EEG, spontaneous EEG and noises, which require advanced signal processing techniques for separation and analysis. Existing methods cannot simultaneously consider common and individual characteristics among/within subjects when extracting stimulus-elicited brain activities from ongoing EEG elicited by 512-s long modern tango music. New method Aiming to discover the commonly music-elicited brain activities among subjects, we provide a comprehensive framework based on fast double-coupled nonnegative tensor decomposition (FDC-NTD) algorithm. The proposed algorithm with a generalized model is capable of simultaneo…

0301 basic medicineAdultComputer sciencemusiikkiElectroencephalography03 medical and health sciencesYoung Adultcoupled0302 clinical medicinetensor decompositionEeg dataRobustness (computer science)medicineDecomposition (computer science)HumansmusicNonnegative tensorEEGSignal processingmedicine.diagnostic_testbusiness.industryGeneral NeuroscienceFunctional NeuroimagingBrainsignaalianalyysiPattern recognitionElectroencephalographySignal Processing Computer-AssistedMiddle Agedongoing EEGAlpha (programming language)030104 developmental biologyGroup analysisAuditory PerceptionnonnegativeArtificial intelligencebusiness030217 neurology & neurosurgeryAlgorithmsMusicärsykkeet
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Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression

2021

To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscil…

masennusmedicine.medical_specialtyComputer Networks and Communicationsneural oscillationsFeature extractionmusiikkiAlpha (ethology)musiikkipsykologiaMajor depressive disordernaturalistic music listeningAudiologyElectroencephalographyDIAGNOSISbehavioral disciplines and activities050105 experimental psychology03 medical and health sciences0302 clinical medicineSIGNALSmedicine0501 psychology and cognitive sciencesEEGRESTING-STATE NETWORKSmajor depressive disorderINDEPENDENT COMPONENT ANALYSISONGOING EEGmedicine.diagnostic_testsignaalinkäsittely05 social sciences3112 Neuroscienceshermoverkot (biologia)signaalianalyysiFUNCTIONAL CONNECTIVITYADULTSGeneral MedicineMagnetoencephalographymedicine.diseasebrain networksIndependent component analysisongoing EEGhumanitiesElectrophysiologyindependent component analysisFMRI DATAFeature (computer vision)SYNCHRONIZATIONMajor depressive disorderPsychology030217 neurology & neurosurgeryRESPONSESInternational Journal of Neural Systems
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Exploiting ongoing EEG with multilinear partial least squares during free-listening to music

2016

During real-world experiences, determining the stimulus-relevant brain activity is excitingly attractive and is very challenging, particularly in electroencephalography. Here, spectrograms of ongoing electroencephalogram (EEG) of one participant constructed a third-order tensor with three factors of time, frequency and space; and the stimulus data consisting of acoustical features derived from the naturalistic and continuous music formulated a matrix with two factors of time and the number of features. Thus, the multilinear partial least squares (PLS) conforming to the canonical polyadic (CP) model was performed on the tensor and the matrix for decomposing the ongoing EEG. Consequently, we …

ta113Multilinear mapmedicine.diagnostic_testBrain activity and meditationSpeech recognition02 engineering and technologyElectroencephalographyta3112Matrix decomposition03 medical and health sciences0302 clinical medicinetensor decompositionFrequency domainPartial least squares regression0202 electrical engineering electronic engineering information engineeringmedicineSpectrogramOngoing EEG020201 artificial intelligence & image processingmusicTime domain030217 neurology & neurosurgerymultilinear partial least squaresMathematics
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