A method for detecting statistically significant differences in EEG data
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Data
2017
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OHBM
Resumo
The highly multivariate nature of EEG data often limits the search for statistically significant differences in data collected from two or more groups of subjects. We have recently developed a new technique for assessing whether two or more multidimensional samples are drawn from the same distribution. Here, we apply this to EEG data collected from schizophrenia patients and healthy controls while performing a Visual Backward Masking (VBM) task.
Descrição
Annual Meeting of the Organization for Human Brain Mapping
Palavras-chave
ELETROENCEFALOGRAMA, ANÁLISE DE DADOS, PRINCIPAL COMPONENT ANALYSIS, MULTIVARIATE STATISTICS, ELECTROENCEPHALOGRAPHY, ESTATÍSTICA MULTIVARIADA, DATA ANALYSIS
Citação
Fachada, N., da Cruz, J.R., Herzog, M.H., Figueiredo, P. & Rosa, A.C. (2017). A method for detecting statistically significant differences in EEG data. Annual Meeting of the Organization for Human Brain Mapping, OHBM 2017, Vancouver, Canada