Generalized EEG-fMRI Spectral and Spatiospectral Heuristic Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU118773" target="_blank" >RIV/00216305:26220/16:PU118773 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7493379&newsearch=true&queryText=labounek" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7493379&newsearch=true&queryText=labounek</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISBI.2016.7493379" target="_blank" >10.1109/ISBI.2016.7493379</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Generalized EEG-fMRI Spectral and Spatiospectral Heuristic Models

Popis výsledku v původním jazyce

The aim of the current study is visualization of task-related variability in EEG-fMRI data, performed as a blind-search analysis without stimulus timings, using a methodology that is based on Kilner’s et al. heuristic approach [2]. We show that filters of the relative EEG spectra with different frequency responses visualize different task-related brain networks. The effect is more pronounced within an event-related oddball paradigm (i.e. detecting rare visual targets) than within a block-design semantic decision paradigm (i.e. detecting semantic errors). The mutual information between different EEG-fMRI activation maps calculated with filters of different frequency responses appears stable between the different paradigms. We also introduce preliminary results implementing the heuristic analysis with spatiospectral EEG components, where the filter response has two dimensions and depends on frequency and channels.

Název v anglickém jazyce

Generalized EEG-fMRI Spectral and Spatiospectral Heuristic Models

Popis výsledku anglicky

The aim of the current study is visualization of task-related variability in EEG-fMRI data, performed as a blind-search analysis without stimulus timings, using a methodology that is based on Kilner’s et al. heuristic approach [2]. We show that filters of the relative EEG spectra with different frequency responses visualize different task-related brain networks. The effect is more pronounced within an event-related oddball paradigm (i.e. detecting rare visual targets) than within a block-design semantic decision paradigm (i.e. detecting semantic errors). The mutual information between different EEG-fMRI activation maps calculated with filters of different frequency responses appears stable between the different paradigms. We also introduce preliminary results implementing the heuristic analysis with spatiospectral EEG components, where the filter response has two dimensions and depends on frequency and channels.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the International Symposium on Biomedical Imaging: From Nano to Macro

ISBN

978-1-4799-2350-2

ISSN

1945-7928

e-ISSN

—

Počet stran výsledku

4

Strana od-do

767-770

Název nakladatele

IEEE

Místo vydání

Prague

Místo konání akce

Prague

Datum konání akce

13. 4. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000386377400182