Int J Neural Syst - Singular spectrum analysis and adaptive filtering enhance the functional connectivity analysis of resting state fMRI data.

Tópicos

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Resumo

Sources of noise in resting-state fMRI experiments include instrumental and physiological noises, which need to be filtered before a functional connectivity analysis of brain regions is performed. These noisy components show autocorrelated and nonstationary properties that limit the efficacy of standard techniques (i.e. time filtering and general linear model). Herein we describe a novel approach based on the combination of singular spectrum analysis and adaptive filtering, which allows a greater noise reduction and yields better connectivity estimates between regions at rest, providing a new feasible procedure to analyze fMRI data.

Resumo Limpo

sourc nois restingst fmri experi includ instrument physiolog nois need filter function connect analysi brain region perform noisi compon show autocorrel nonstationari properti limit efficaci standard techniqu ie time filter general linear model herein describ novel approach base combin singular spectrum analysi adapt filter allow greater nois reduct yield better connect estim region rest provid new feasibl procedur analyz fmri data

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