The art and pitfalls of simulatenously measured fMRI and EEG data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU110156" target="_blank" >RIV/00216305:26220/14:PU110156 - isvavai.cz</a>

Výsledek na webu

<a href="https://ww4.aievolution.com/hbm1401/index.cfm?do=abs.viewAbs&abs=3095" target="_blank" >https://ww4.aievolution.com/hbm1401/index.cfm?do=abs.viewAbs&abs=3095</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The art and pitfalls of simulatenously measured fMRI and EEG data

Popis výsledku v původním jazyce

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two most common techniques used in neuroscience research. Currently, there is a growing interest to analyze simultaneously measured data from both modalities. The main motivation is to achieve the best temporal (by EEG) and spatial (by fMRI) resolution for the analyzed data. Another benefit resides in a simultaneous observation of the scene with two independent modalities. However, typical data preprocessing pipelines forboth modalities have to be adjusted to specifics of simultaneous measurement, where acquisition of one modality influences another. Especially EEG data, which are mainly affected, contains strong artifacts. Apart from the techniques for artifacts suppression and other preprocessing steps a several approaches for data analysis will be shown on datasets of patients or healthy controls.

Název v anglickém jazyce

The art and pitfalls of simulatenously measured fMRI and EEG data

Popis výsledku anglicky

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two most common techniques used in neuroscience research. Currently, there is a growing interest to analyze simultaneously measured data from both modalities. The main motivation is to achieve the best temporal (by EEG) and spatial (by fMRI) resolution for the analyzed data. Another benefit resides in a simultaneous observation of the scene with two independent modalities. However, typical data preprocessing pipelines forboth modalities have to be adjusted to specifics of simultaneous measurement, where acquisition of one modality influences another. Especially EEG data, which are mainly affected, contains strong artifacts. Apart from the techniques for artifacts suppression and other preprocessing steps a several approaches for data analysis will be shown on datasets of patients or healthy controls.

Druh

O - Ostatní výsledky

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů