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Identifying neural patterns of functional dyspepsia using multivariate pattern analysis: a resting-state FMRI study.

Peng Liu1, Wei Qin, Jingjing Wang

  • 1Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, People's Republic of China.

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Summary

Resting-state brain activity differs significantly between functional dyspepsia (FD) patients and healthy individuals. These brain function differences in FD may aid in developing new diagnostic tools.

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Area of Science:

  • Neuroscience
  • Gastroenterology
  • Medical Imaging

Background:

  • Previous functional dyspepsia (FD) research focused on task-based brain activity.
  • Resting-state brain function in FD patients remains under-explored.
  • Understanding resting-state abnormalities is crucial for identifying the neural basis of FD.

Purpose of the Study:

  • To identify distinct resting-state functional patterns in FD patients compared to healthy controls (HCs).
  • To explore the neural underpinnings of FD during a resting state.

Main Methods:

  • Thirty FD patients and thirty HCs underwent 5-minute resting-state fMRI scans.
  • Multivariate pattern analysis (MVPA) using support vector machine (SVM) was applied to regional homogeneity (ReHo) data.
  • Principal component analysis (PCA) and permutation testing were used for classifier design and validation.

Main Results:

  • The classifier achieved 86.67% accuracy in distinguishing FD patients from HCs.
  • Key discriminative brain regions included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), and insula.
  • FD symptom severity and duration correlated significantly with ReHo values in specific brain regions like the medial PFC and anterior cingulate cortex (ACC).

Conclusions:

  • Distinct resting-state functional patterns differentiate FD patients from HCs.
  • These findings enhance the understanding of the neural basis of FD.
  • Resting-state fMRI shows potential as a diagnostic tool for FD.