Sensitivity of PPI analysis to differences in noise reduction strategies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F15%3A00080949" target="_blank" >RIV/00216224:14740/15:00080949 - isvavai.cz</a>

Výsledek na webu

<a href="http://ac.els-cdn.com/S0165027015002459/1-s2.0-S0165027015002459-main.pdf?_tid=2b313bc2-4259-11e5-bb7c-00000aab0f26&acdnat=1439538824_bbe2dc8b96cdc663b6ffb54057334360" target="_blank" >http://ac.els-cdn.com/S0165027015002459/1-s2.0-S0165027015002459-main.pdf?_tid=2b313bc2-4259-11e5-bb7c-00000aab0f26&acdnat=1439538824_bbe2dc8b96cdc663b6ffb54057334360</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jneumeth.2015.06.021" target="_blank" >10.1016/j.jneumeth.2015.06.021</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sensitivity of PPI analysis to differences in noise reduction strategies

Popis výsledku v původním jazyce

Background In some fields of fMRI data analysis, using correct methods for dealing with noise is crucial for achieving meaningful results. This paper provides a quantitative assessment of the effects of different preprocessing and noise filtering strategies on psychophysiological interactions (PPI) methods for analyzing fMRI data where noise management has not yet been established. Methods Both real and simulated fMRI data were used to assess these effects. Four regions of interest (ROIs) were chosen for the PPI analysis on the basis of their engagement during two tasks. PPI analysis was performed for 32 different preprocessing and analysis settings, which included data filtering with RETROICOR or no such filtering; different filtering of the ROI ?seed? signal with a nuisance data-driven time series; and the involvement of these data-driven time series in the subsequent PPI GLM analysis.

Název v anglickém jazyce

Sensitivity of PPI analysis to differences in noise reduction strategies

Popis výsledku anglicky

Background In some fields of fMRI data analysis, using correct methods for dealing with noise is crucial for achieving meaningful results. This paper provides a quantitative assessment of the effects of different preprocessing and noise filtering strategies on psychophysiological interactions (PPI) methods for analyzing fMRI data where noise management has not yet been established. Methods Both real and simulated fMRI data were used to assess these effects. Four regions of interest (ROIs) were chosen for the PPI analysis on the basis of their engagement during two tasks. PPI analysis was performed for 32 different preprocessing and analysis settings, which included data filtering with RETROICOR or no such filtering; different filtering of the ROI ?seed? signal with a nuisance data-driven time series; and the involvement of these data-driven time series in the subsequent PPI GLM analysis.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

FH - Neurologie, neurochirurgie, neurovědy

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Journal of Neuroscience Methods

ISSN

0165-0270

e-ISSN

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Svazek periodika

253

Číslo periodika v rámci svazku

September

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

15

Strana od-do

218-232

Kód UT WoS článku

000360867400022

EID výsledku v databázi Scopus

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