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<p>In the rapidly advancing field of neuroscience, sophisticated imaging techniques such as functional magnetic resonance imaging (fMRI) enable detailed analysis of brain activity. Researchers increasingly seek to disentangle distinct brain states, recognizing that fMRI data typically comprise a mixture of these states. To enable independent analysis of individual brain states, numerous methodologies have been proposed, each requiring careful consideration in practical application. This review provides a comprehensive survey of decomposition methods, covering classical, probabilistic, and tensor-based approaches and their applications. Furthermore, the review discusses additional methodological considerations essential for the effective use of these techniques. By comparing decomposition algorithms with other widely used techniques in fMRI data analysis, this review highlights their methodological strengths and limitations, and further demonstrates their broad applicability for extracting brain states from fMRI data.</p>

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A review of decomposition methods for brain states estimation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月18日

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  • Guoqiang Hu,
  • Jinxing Wang,
  • Ziyi Shui,
  • Tianyang Wang,
  • Deqing Wang,
  • Siwen Luo,
  • Hongbo Liu,
  • Xinqiang Xie,
  • Lisa D. Nickerson

摘要

In the rapidly advancing field of neuroscience, sophisticated imaging techniques such as functional magnetic resonance imaging (fMRI) enable detailed analysis of brain activity. Researchers increasingly seek to disentangle distinct brain states, recognizing that fMRI data typically comprise a mixture of these states. To enable independent analysis of individual brain states, numerous methodologies have been proposed, each requiring careful consideration in practical application. This review provides a comprehensive survey of decomposition methods, covering classical, probabilistic, and tensor-based approaches and their applications. Furthermore, the review discusses additional methodological considerations essential for the effective use of these techniques. By comparing decomposition algorithms with other widely used techniques in fMRI data analysis, this review highlights their methodological strengths and limitations, and further demonstrates their broad applicability for extracting brain states from fMRI data.