Online decoding of object-based attention using real-time fMRI

Adnan M. Niazi, Philip L.C. van den Broek, Stefan Klanke, Markus Barth, Mannes Poel, Peter Desain, Marcel A.J. van Gerven

    Research output: Contribution to journalArticleAcademicpeer-review

    6 Citations (Scopus)

    Abstract

    Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity.
    Original languageUndefined
    Pages (from-to)319-329
    Number of pages11
    JournalEuropean journal of neuroscience
    Volume39
    Issue number2
    DOIs
    Publication statusPublished - Jan 2014

    Keywords

    • EWI-23933
    • multivariate decoding
    • object-based attention
    • Categorization
    • METIS-303970
    • IR-89543
    • real-time fMRI

    Cite this

    Niazi, A. M., van den Broek, P. L. C., Klanke, S., Barth, M., Poel, M., Desain, P., & van Gerven, M. A. J. (2014). Online decoding of object-based attention using real-time fMRI. European journal of neuroscience, 39(2), 319-329. https://doi.org/10.1111/ejn.12405
    Niazi, Adnan M. ; van den Broek, Philip L.C. ; Klanke, Stefan ; Barth, Markus ; Poel, Mannes ; Desain, Peter ; van Gerven, Marcel A.J. / Online decoding of object-based attention using real-time fMRI. In: European journal of neuroscience. 2014 ; Vol. 39, No. 2. pp. 319-329.
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    title = "Online decoding of object-based attention using real-time fMRI",
    abstract = "Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6{\%} accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity.",
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    Niazi, AM, van den Broek, PLC, Klanke, S, Barth, M, Poel, M, Desain, P & van Gerven, MAJ 2014, 'Online decoding of object-based attention using real-time fMRI', European journal of neuroscience, vol. 39, no. 2, pp. 319-329. https://doi.org/10.1111/ejn.12405

    Online decoding of object-based attention using real-time fMRI. / Niazi, Adnan M.; van den Broek, Philip L.C.; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; van Gerven, Marcel A.J.

    In: European journal of neuroscience, Vol. 39, No. 2, 01.2014, p. 319-329.

    Research output: Contribution to journalArticleAcademicpeer-review

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    AU - Klanke, Stefan

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    AU - Poel, Mannes

    AU - Desain, Peter

    AU - van Gerven, Marcel A.J.

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    AB - Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity.

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    Niazi AM, van den Broek PLC, Klanke S, Barth M, Poel M, Desain P et al. Online decoding of object-based attention using real-time fMRI. European journal of neuroscience. 2014 Jan;39(2):319-329. https://doi.org/10.1111/ejn.12405