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Personalized brain decoding of spontaneous pain in individuals with chronic pain

Nature Neuroscience (2026)Cite this article

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Abstract

Spontaneous pain is a hallmark of chronic pain disorders, but its assessment remains limited by the lack of objective biomarkers. Here we used precision functional magnetic resonance imaging data, collected over more than half a year from two individuals with chronic pain, to develop personalized brain-decoding models of spontaneous pain. The personalized decoding models accurately tracked fluctuations in spontaneous pain intensity across sessions, runs and minutes (Participant 1: prediction–outcome correlation, r = 0.40–0.61; Participant 2: r = 0.51–0.65) and effectively discriminated between median-dichotomized high- versus low-pain states (Participant 1: area under the curve = 0.71–0.87; Participant 2: area under the curve = 0.76–0.93). Model performance improved with increased training data, with conventional data quantities failing to achieve significant predictive accuracy. Furthermore, each model relied on individually unique brain features and did not generalize across participants. This study indicates that functional magnetic resonance imaging can assess spontaneous pain, highlighting the need for precise, patient-specific approaches.

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Fig. 1: Study overview.
Fig. 2: Prediction performance.
Fig. 3: Effect of training data size on decoding performance.
Fig. 4: Feature importance maps.
Fig. 5: Cross-testing of personalized decoding models.

Data availability

Raw MRI data are publicly available at https://openneuro.org/datasets/ds006815. All the data to generate the figures are available via figshare at https://doi.org/10.6084/m9.figshare.31064431 (ref. 44). Source data are provided with this paper.

Code availability

Code for the main analyses is available via GitHub at https://github.com/cocoanlab/DEIPP (ref. 45).

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Acknowledgements

We thank all patients for their participation in this study. We thank J. Lee and S.-G. Kim for help with participant recruitment. We thank E.-J. Jeong, J. Han and Y. Park for help with conducting experiments. This work was supported by Institute for Basic Science (grant no. IBS-R015-D2 to C.-W.W.).

Author information

Author notes

  1. Deceased: Seongwoo Jo.

Authors and Affiliations

  1. Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea

    Jae-Joong Lee & Choong-Wan Woo

  2. Department of Psychology, Chungnam National University, Daejeon, South Korea

    Seongwoo Jo & Sungkun Cho

  3. Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea

    Choong-Wan Woo

  4. Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea

    Choong-Wan Woo

  5. Department of Brain Science and Engineering, Sungkyunkwan University, Suwon, South Korea

    Choong-Wan Woo

Authors
  1. Jae-Joong Lee
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  2. Seongwoo Jo
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  3. Sungkun Cho
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  4. Choong-Wan Woo
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Contributions

J.-J.L. and C.-W.W. conceived and designed the experiment. S.J. and S.C. contributed to the experimental design, participant management and psychotherapy. J.-J.L. conducted the data analysis. J.-J.L. and C.-W.W. interpreted the results. J.-J.L. wrote the manuscript. C.-W.W. provided supervision and edited the manuscript. All authors reviewed and approved the final manuscript, except for S.J., who passed away in November 2023.

Corresponding author

Correspondence to Choong-Wan Woo.

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Competing interests

The authors declare no competing interests.

Peer review

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Nature Neuroscience thanks Benjamin Becker, Markus Ploner and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Methods, Figs. 1–17, Table 1 and References.

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Source data for visualization.

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Source data for visualization.

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Source data for visualization.

Source Data Fig. 5

Source data for visualization.

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Lee, JJ., Jo, S., Cho, S. et al. Personalized brain decoding of spontaneous pain in individuals with chronic pain. Nat Neurosci (2026). https://doi.org/10.1038/s41593-026-02221-3

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