Inferring Brain Signals Synchronicity From a Sample of EEG Readings

DOI10.1080/01621459.2018.1518233zbMath1428.62474arXiv1609.09532OpenAlexW2528756367WikidataQ100990347 ScholiaQ100990347MaRDI QIDQ5242445

Catherine Sugar, Shafali Jeste, Joel Frohlich, Qian Li, Charlotte DiStefano, Damla Şentürk, Donatello Telesca

Publication date: 12 November 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1609.09532

zbMATH Keywords

spectral clusteringEEGconsensus clusteringhierarchical mixture models

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Pattern recognition, speech recognition (68T10) Medical applications (general) (92C50)

Related Items (1)

Network modeling in biology: statistical methods for gene and brain networks

Uses Software

• BayesSpec

Cites Work

• Estimating the dimension of a model
• Fitting time series models to nonstationary processes
• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• A simple generalised crossvalidation method of span selection for periodogram smoothing
• Identifying longitudinal trends within EEG experiments
• Computational and Inferential Difficulties with Mixture Posterior Distributions
• AdaptSPEC: Adaptive Spectral Estimation for Nonstationary Time Series
• Bayesian Inference for Gene Expression and Proteomics

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