Survey of encoding and decoding of visual stimulus via FMRI: an image analysis perspective.

A variety of exciting scientific achievements have been made in the last few decades in brain encoding and decoding via functional magnetic resonance imaging (fMRI). This trend continues to rise in recent years, as evidenced by the increasing number of published papers in this topic and several publ...

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Publicado en:Brain Imaging & Behavior Vol. 8; no. 1; pp. 7 - 24
Autores principales: Chen, Mo, Han, Junwei, Hu, Xintao, Jiang, Xi, Guo, Lei, Liu, Tianming
Formato: research review Journal Article
Publicado: Springer Nature Mar2014
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: Survey of encoding and decoding of visual stimulus via FMRI: an image analysis perspective.
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          Chen, Mo
          Han, Junwei
          Hu, Xintao
          Jiang, Xi
          Guo, Lei
          Liu, Tianming
        affil: School of Automation, Northwestern Polytechnical University, Xi'an, China.
      sug:
        subj:
          Brain Physiology
          Image Processing, Computer Assisted Methods
          Magnetic Resonance Imaging Methods
          Visual Perception
          Brain Mapping Methods
          Neuroradiography Methods
      ab: A variety of exciting scientific achievements have been made in the last few decades in brain encoding and decoding via functional magnetic resonance imaging (fMRI). This trend continues to rise in recent years, as evidenced by the increasing number of published papers in this topic and several published survey papers addressing different aspects of research issues. Essentially, these survey articles were mainly from cognitive neuroscience and neuroimaging perspectives, although computational challenges were briefly discussed. To complement existing survey articles, this paper focuses on the survey of the variety of image analysis methodologies, such as neuroimage registration, fMRI signal analysis, ROI (regions of interest) selection, machine learning algorithms, reproducibility analysis, structural and functional connectivity, and natural image analysis, which were employed in previous brain encoding/decoding research works. This paper also provides discussions of potential limitations of those image analysis methodologies and possible future improvements. It is hoped that extensive discussions of image analysis issues could contribute to the advancements of the increasingly important brain encoding/decoding field.
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        research
        review
        Journal Article
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    language: English
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