0000000001072643

AUTHOR

Reza Mahini

showing 5 related works from this author

Determination of the Time Window of Event-Related Potential Using Multiple-Set Consensus Clustering

2020

Clustering is a promising tool for grouping the sequence of similar time-points aimed to identify the attention blocks in spatiotemporal event-related potentials (ERPs) analysis. It is most likely to elicit the appropriate time window for ERP of interest if a suitable clustering method is applied to spatiotemporal ERP. However, how to reliably estimate a proper time window from entire individual subjects’ data is still challenging. In this study, we developed a novel multiset consensus clustering method in which several clustering results of multiple subjects were combined to retrieve the best fitted clustering for all the subjects within a group. Then, the obtained clustering was processed…

microstates analysiscognitive neurosciencemulti-set consensus clusteringtime windowevent-related potentialslcsh:Neurosciences. Biological psychiatry. Neuropsychiatrylcsh:RC321-571Frontiers in Neuroscience
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Assessment of nonnegative matrix factorization algorithms for electroencephalography spectral analysis.

2020

AbstractBackgroundNonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed. However, the performance of their use in EEG data analysis has not been fully compared. Here, we provide a comparison of four NMF algorithms in terms of accuracy of estimation, stability (repeatability of the results) and time complexity of algorithms with simulated data. In the practical application of NMF algorithms, stability plays an important role, which was an emphasis in the comparison. A Hierarchical clustering algorithm was implemented to evaluate the stability of NM…

lcsh:Medical technologyComputer scienceBiomedical EngineeringStability (learning theory)ElectroencephalographySignal-To-Noise RatioClusteringNon-negative matrix factorizationBiomaterialsNonnegative matrix factorization03 medical and health sciencesklusterit0302 clinical medicineEeg dataalgoritmitmedicineHumansRadiology Nuclear Medicine and imagingSpectral analysisstabiilius (muuttumattomuus)EEGCluster analysisTime complexity030304 developmental biology0303 health sciencesRadiological and Ultrasound Technologymedicine.diagnostic_testResearchnonnegative matrix factorizationElectroencephalographySignal Processing Computer-AssistedGeneral MedicinestabilityModels TheoreticalHierarchical clusteringlcsh:R855-855.5AlgorithmStability030217 neurology & neurosurgeryAlgorithmsclusteringspektrianalyysiBiomedical engineering online
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Cluster Aggregation for Analyzing Event-Related Potentials

2017

Topographic analysis are references independent for Event-Related Potentials (ERPs), and thus render statistically unambiguous results. This drives us to develop an effective clustering approach to finding temporal samples possessing similar topographies for analysing the temporal-spatial ERPs data. The previous study called CARTOOL used single clustering method to cluster ERP data. Indeed, given a clustering method, the quality of clustering varies with data and the number of clusters, motivating us to implement and compare multiple clustering algorithms via using multiple similarity measurements. By finding the minimum distance among the various clustering methods and selecting the most s…

Computer sciencebusiness.industryPattern recognition02 engineering and technology03 medical and health sciences0302 clinical medicineSimilarity (network science)Event-related potential0202 electrical engineering electronic engineering information engineeringCluster (physics)020201 artificial intelligence & image processingArtificial intelligenceCluster analysisbusiness030217 neurology & neurosurgery
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Ensemble deep clustering analysis for time window determination of event-related potentials

2023

Objective Cluster analysis of spatio-temporal event-related potential (ERP) data is a promising tool for exploring the measurement time window of ERPs. However, even after preprocessing, the remaining noise can result in uncertain cluster maps followed by unreliable time windows while clustering via conventional clustering methods. Methods We designed an ensemble deep clustering pipeline to determine a reliable time window for the ERP of interest from temporal concatenated grand average ERP data. The proposed pipeline includes semi-supervised deep clustering methods initialized by consensus clustering and unsupervised deep clustering methods with end-to-end architectures. Ensemble clusterin…

klusteritERP microstatesconsensus clusteringanalyysitutkimusmenetelmätensemble learningtime windowdeep clusteringevent-related potentialskognitiiviset prosessitERP
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Determination of the Time Window of Event-Related Potential Using Multiple-Set Consensus Clustering

2020

Clustering is a promising tool for grouping the sequence of similar time-points aimed to identify the attention blocks in spatiotemporal event-related potentials (ERPs) analysis. It is most likely to elicit the appropriate time window for ERP of interest if a suitable clustering method is applied to spatiotemporal ERP. However, how to reliably estimate a proper time window from entire individual subjects’ data is still challenging. In this study, we developed a novel multiset consensus clustering method in which several clustering results of multiple subjects were combined to retrieve the best fitted clustering for all the subjects within a group. Then, the obtained clustering was processed…

microstates analysiscognitive neurosciencetime-windowsignaalinkäsittelyGeneral Neurosciencesignaalianalyysimulti-set consensus clusteringtime windowklusterianalyysikognitiivinen neurotiedeevent-related potentials
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