Time-resolved detection of stimulus/task-related networks, via clustering of transient intersubject synchronization.
Hum Brain Mapp
; 36(9): 3404-25, 2015 Sep.
Article
em En
| MEDLINE
| ID: mdl-26095530
ABSTRACT
Several methods are available for the identification of functional networks of brain areas using functional magnetic resonance imaging (fMRI) time-series. These typically assume a fixed relationship between the signal of the areas belonging to the same network during the entire time-series (e.g., positive correlation between the areas belonging to the same network), or require a priori information about when this relationship may change (task-dependent changes of connectivity). We present a fully data-driven method that identifies transient network configurations that are triggered by the external input and that, therefore, include only regions involved in stimulus/task processing. Intersubject synchronization with short sliding time-windows was used to identify if/when any area showed stimulus/task-related responses. Next, a first clustering step grouped together areas that became engaged concurrently and repetitively during the time-series (stimulus/task-related networks). Finally, for each network, a second clustering step grouped together all the time-windows with the same BOLD signal. The final output consists of a set of network configurations that show stimulus/task-related activity at specific time-points during the fMRI time-series. We label these configurations "brain modes" (bModes). The method was validated using simulated datasets and a real fMRI experiment with multiple tasks and conditions. Future applications include the investigation of brain functions using complex and naturalistic stimuli.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Encéfalo
/
Mapeamento Encefálico
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Imageamento por Ressonância Magnética
Tipo de estudo:
Diagnostic_studies
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Evaluation_studies
Limite:
Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Hum Brain Mapp
Assunto da revista:
CEREBRO
Ano de publicação:
2015
Tipo de documento:
Article
País de afiliação:
Itália