Impact of analysis methods on the reproducibility and reliability of resting-state networks.
Brain Connect
; 3(4): 363-74, 2013.
Article
em En
| MEDLINE
| ID: mdl-23705789
ABSTRACT
Though previous examinations of intrinsic resting-state networks (RSNs) in healthy populations have consistently identified several RSNs that represent connectivity patterns evoked by cognitive and sensory tasks, the effects of different analytic approaches on the reliability and reproducibility of these RSNs have yet to be fully explored. Thus, the primary aim of the current study was to investigate the effect of method (independent component analyses [ICA] vs. seed-based analyses) on RSN reproducibility (independent datasets) for ICA and reliability (independent time points) in both methods using functional magnetic resonance imaging. Good to excellent reproducibility was observed in 9 out of 10 commonly identified RSNs, indicating the robustness of these intrinsic fluctuations at the group level. Reliability analyses showed that results were dependent on three main methodological factors (1) group versus subject-level analyses (group>subject); (2) whether data from different visits were analyzed separately or jointly with ICA (combined>separate ICA); and (3) whether ICA output was used to directly assess reliability or to inform seed-based analyses (seed-based>ICA). These results suggest that variations in the analytic technique have a significant impact on individual reliability measurements, but do not significantly affect the reproducibility or reliability of RSNs at the group level. Further investigation into the effect of the analytic technique on RSN quantification is warranted to increase the utility of RSN analyses in clinical studies.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Encéfalo
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Interpretação de Imagem Assistida por Computador
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Estatística como Assunto
/
Rede Nervosa
Tipo de estudo:
Prognostic_studies
Limite:
Adolescent
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Adult
/
Female
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Humans
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Male
Idioma:
En
Revista:
Brain Connect
Ano de publicação:
2013
Tipo de documento:
Article
País de afiliação:
Brasil