Dependencies between stimuli and spatially independent fMRI sources: Towards brain correlates of natural stimuli (2009)

AUTHORS:

Ylipaavalniemi Jarkko , Savia Eerika , Malinen Sanna , Hari Riitta , Vigario Ricardo , Kaski Samuel

ABSTRACT:

Natural stimuli are increasingly used in functional magnetic resonance imaging (fMRI) studies to imitate real-life situations. Consequently, challenges are created for novel analysis methods, including new machine learning tools. With natural stimuli it is no longer feasible to assume single features of the experimental design alone to account for the brain activity. Instead, relevant combinations of rich-enough stimulus features could explain the more complex activation patterns. \par We propose a novel two-step approach, where independent component analysis is first used to identify spatially independent brain processes, which we refer to as \emph{functional patterns}. As the second step, temporal dependencies between stimuli and functional patterns are detected using canonical correlation analysis. Our proposed method looks for combinations of stimulus features and the corresponding combinations of functional patterns. \par This two-step approach was used to analyze measurements from a fMRI study during multi-modal stimulation. The detected complex activation patterns were explained as resulting from interactions of multiple brain processes. Our approach seems promising for analysis of data from studies with natural stimuli.

URL:
http://dx.doi.org/10.1016/j.neuroimage.2009.03.056

INTERNAL PDF:
http://research.ics.aalto.fi/publications/bibdb2012/internal_pdfs/JYlipaavalniemi-2009-NIMG.pdf

@article{
    JYlipaavalniemi-2009-NIMG_whyj,
    author = "Ylipaavalniemi, Jarkko and Savia, Eerika and Malinen, Sanna and Hari, Riitta and Vig\'{a}rio, Ricardo and Kaski, Samuel",
    volume = "48",
    title = "{D}ependencies between stimuli and spatially independent f{MRI} sources: {T}owards brain correlates of natural stimuli",
    url = "http://dx.doi.org/10.1016/j.neuroimage.2009.03.056",
    journal = "NeuroImage",
    number = "1",
    month = "October",
    responsibleauthor = "Ylipaavalniemi, Jarkko",
    keywords = "independent component analysis, canonical component analysis, functional magnetic resonance imaging",
    flags = "AIRC",
    pages = "176--185",
    year = "2009",
    internalpdf = "JYlipaavalniemi-2009-NIMG.pdf",
    kay = "NA",
    impactfactor = "A",
    abstract = "Natural stimuli are increasingly used in functional magnetic resonance imaging (fMRI) studies to imitate real-life situations. Consequently, challenges are created for novel analysis methods, including new machine learning tools. With natural stimuli it is no longer feasible to assume single features of the experimental design alone to account for the brain activity. Instead, relevant combinations of rich-enough stimulus features could explain the more complex activation patterns. \par We propose a novel two-step approach, where independent component analysis is first used to identify spatially independent brain processes, which we refer to as \emph{functional patterns}. As the second step, temporal dependencies between stimuli and functional patterns are detected using canonical correlation analysis. Our proposed method looks for combinations of stimulus features and the corresponding combinations of functional patterns. \par This two-step approach was used to analyze measurements from a fMRI study during multi-modal stimulation. The detected complex activation patterns were explained as resulting from interactions of multiple brain processes. Our approach seems promising for analysis of data from studies with natural stimuli."
}

AUTHORS:

ABSTRACT:

URL: http://dx.doi.org/10.1016/j.neuroimage.2009.03.056

INTERNAL PDF: http://research.ics.aalto.fi/publications/bibdb2012/internal_pdfs/JYlipaavalniemi-2009-NIMG.pdf

URL:
http://dx.doi.org/10.1016/j.neuroimage.2009.03.056

INTERNAL PDF:
http://research.ics.aalto.fi/publications/bibdb2012/internal_pdfs/JYlipaavalniemi-2009-NIMG.pdf