A method for detecting statistically significant differences in EEG data

Nuno Fachada; Janir R. da Cruz; Michael H. Herzog; Patrícia Figueiredo; Agostinho C. Rosa

A method for detecting statistically significant differences in EEG data

Nuno Fachada, Janir R. da Cruz, Michael H. Herzog, Patrícia Figueiredo, Agostinho C. Rosa

ECATI - School of Communication, Arts and Information

Research output: Contribution to conference › Paper

Abstract

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.

Original language	English
Publication status	Published - 2017
Event	OHBM - Duration: 1 Jan 2017 → …

Conference

Conference	OHBM
Period	1/01/17 → …

Bibliographical note

Annual Meeting of the Organization for Human Brain Mapping

Keywords

MULTIVARIATE STATISTICS
PRINCIPAL COMPONENT ANALYSIS
DATA ANALYSIS
ELECTROENCEPHALOGRAPHY

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2017 ohbmFinal published version, 209 KB

Cite this

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title = "A method for detecting statistically significant differences in EEG data",

abstract = "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.",

keywords = "ELETROENCEFALOGRAMA, ESTAT{\'I}STICA MULTIVARIADA, AN{\'A}LISE DE DADOS, MULTIVARIATE STATISTICS, PRINCIPAL COMPONENT ANALYSIS, DATA ANALYSIS, ELECTROENCEPHALOGRAPHY",

author = "Nuno Fachada and Cruz, {Janir R. da} and Herzog, {Michael H.} and Patr{\'i}cia Figueiredo and Rosa, {Agostinho C.}",

note = "Annual Meeting of the Organization for Human Brain Mapping; OHBM ; Conference date: 01-01-2017",

year = "2017",

language = "English",

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TY - CONF

T1 - A method for detecting statistically significant differences in EEG data

AU - Fachada, Nuno

AU - Cruz, Janir R. da

AU - Herzog, Michael H.

AU - Figueiredo, Patrícia

AU - Rosa, Agostinho C.

N1 - Annual Meeting of the Organization for Human Brain Mapping

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - ELETROENCEFALOGRAMA

KW - ESTATÍSTICA MULTIVARIADA

KW - ANÁLISE DE DADOS

KW - MULTIVARIATE STATISTICS

KW - PRINCIPAL COMPONENT ANALYSIS

KW - DATA ANALYSIS

KW - ELECTROENCEPHALOGRAPHY

UR - http://hdl.handle.net/10437/10195

M3 - Paper

T2 - OHBM

Y2 - 1 January 2017

ER -

A method for detecting statistically significant differences in EEG data

Abstract

Conference

Bibliographical note

Keywords

Access to Document

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