Adaptive Optimal Basis Set for BCG Artifact Removal in Simultaneous EEG-fMRI

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F18%3A00490810" target="_blank" >RIV/67985807:_____/18:00490810 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00023752:_____/18:43919417

Výsledek na webu

<a href="http://dx.doi.org/10.1038/s41598-018-27187-6" target="_blank" >http://dx.doi.org/10.1038/s41598-018-27187-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-018-27187-6" target="_blank" >10.1038/s41598-018-27187-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Adaptive Optimal Basis Set for BCG Artifact Removal in Simultaneous EEG-fMRI

Popis výsledku v původním jazyce

Electroencephalography (EEG) signals recorded during simultaneous functional magnetic resonance imaging (fMRI) are contaminated by strong artifacts. Among these, the ballistocardiographic (BCG) artifact is the most challenging, due to its complex spatio-temporal dynamics associated with ongoing cardiac activity. The presence of BCG residuals in EEG data may hide true, or generate spurious correlations between EEG and fMRI time-courses. Here, we propose an adaptive Optimal Basis Set (aOBS) method for BCG artifact removal. Our method is adaptive, as it can estimate the delay between cardiac activity and BCG occurrence on a beat-to-beat basis. The efective creation of an optimal basis set by principal component analysis (PCA) is therefore ensured by a more accurate alignment of BCG occurrences. Furthermore, aOBS can automatically estimate which components produced by PCA are likely to be BCG artifact-related and therefore need to be removed. The aOBS performance was evaluated on high-density EEG data acquired with simultaneous fMRI in healthy subjects during visual stimulation. As aOBS enables efective reduction of BCG residuals while preserving brain signals, we suggest it may fnd wide application in simultaneous EEG-fMRI studies.

Název v anglickém jazyce

Adaptive Optimal Basis Set for BCG Artifact Removal in Simultaneous EEG-fMRI

Popis výsledku anglicky

Electroencephalography (EEG) signals recorded during simultaneous functional magnetic resonance imaging (fMRI) are contaminated by strong artifacts. Among these, the ballistocardiographic (BCG) artifact is the most challenging, due to its complex spatio-temporal dynamics associated with ongoing cardiac activity. The presence of BCG residuals in EEG data may hide true, or generate spurious correlations between EEG and fMRI time-courses. Here, we propose an adaptive Optimal Basis Set (aOBS) method for BCG artifact removal. Our method is adaptive, as it can estimate the delay between cardiac activity and BCG occurrence on a beat-to-beat basis. The efective creation of an optimal basis set by principal component analysis (PCA) is therefore ensured by a more accurate alignment of BCG occurrences. Furthermore, aOBS can automatically estimate which components produced by PCA are likely to be BCG artifact-related and therefore need to be removed. The aOBS performance was evaluated on high-density EEG data acquired with simultaneous fMRI in healthy subjects during visual stimulation. As aOBS enables efective reduction of BCG residuals while preserving brain signals, we suggest it may fnd wide application in simultaneous EEG-fMRI studies.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Scientific Reports

ISSN

2045-2322

e-ISSN

—

Svazek periodika

8

Číslo periodika v rámci svazku

June

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

11

Strana od-do

—

Kód UT WoS článku

000434779300010

EID výsledku v databázi Scopus

2-s2.0-85048415416