Real-time estimation of dynamic functional connectivity networks.
Hum Brain Mapp
; 38(1): 202-220, 2017 01.
Article
em En
| MEDLINE
| ID: mdl-27600689
ABSTRACT
Two novel and exciting avenues of neuroscientific research involve the study of task-driven dynamic reconfigurations of functional connectivity networks and the study of functional connectivity in real-time. While the former is a well-established field within neuroscience and has received considerable attention in recent years, the latter remains in its infancy. To date, the vast majority of real-time fMRI studies have focused on a single brain region at a time. This is due in part to the many challenges faced when estimating dynamic functional connectivity networks in real-time. In this work, we propose a novel methodology with which to accurately track changes in time-varying functional connectivity networks in real-time. The proposed method is shown to perform competitively when compared to state-of-the-art offline algorithms using both synthetic as well as real-time fMRI data. The proposed method is applied to motor task data from the Human Connectome Project as well as to data obtained from a visuospatial attention task. We demonstrate that the algorithm is able to accurately estimate task-related changes in network structure in real-time. Hum Brain Mapp 38202-220, 2017. © 2016 Wiley Periodicals, Inc.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Encéfalo
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Mapeamento Encefálico
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Modelos Neurológicos
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Vias Neurais
Tipo de estudo:
Prognostic_studies
Limite:
Female
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Humans
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Male
Idioma:
En
Revista:
Hum Brain Mapp
Assunto da revista:
CEREBRO
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Reino Unido