Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Stomach–brain coupling indexes a dimensional signature of mental health

Nature Mental Health volume 3, pages 899–908 (2025) Cite this article

Subjects

Abstract

Visceral rhythms orchestrate the physiological states underlying human emotion. Chronic aberrations in these brain–body interactions are implicated in a broad spectrum of mental health disorders. However, the relationship between gastric–brain coupling and affective symptoms remains poorly understood. Here we investigated the relationship between this novel interoceptive axis and mental health in 243 participants, using a cross-validated machine learning approach. We find that increased frontoparietal brain coupling to the gastric rhythm indexes a dimensional signature of poorer mental health, spanning anxiety, depression, stress and well-being. Control analyses confirm the specificity of these interactions to the gastric–brain axis. Our study proposes coupling between the stomach and brain as a factor in mental health and offers potential new targets for interventions remediating aberrant brain–body coupling.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: CCA of stomach–brain coupling and mental health.
The alternative text for this image may have been generated using AI.
Fig. 2: Mental health functional correlate of stomach–brain coupling.
The alternative text for this image may have been generated using AI.
Fig. 3: CCA loadings averaged summary.
The alternative text for this image may have been generated using AI.

Similar content being viewed by others

Data availability

Deidentified participant data (EGG, control neurological and stomach–brain coupling) implemented in this article are available via GitHub at https://github.com/embodied-computation-group/StomachBrain-MentalHealth. Due to Danish privacy law, mental health data and raw neurological data are available upon reasonable request, with the formation of a data sharing agreement. Researchers who wish to access these data may contact M.A. (micah@cfin.au.dk) at The Center of Functionally Integrative Neuroscience, Aarhus University, Denmark. The complete dataset (Visceral Mind Project) will be released as a data publication upon completion of the full anonymization process.

Code availability

Code for this article is available via GitHub at https://github.com/embodied-computation-group/StomachBrain-MentalHealth.

References

  1. Thompson, E. Mind in Life: Biology, Phenomenology, and the Sciences of Mind (Harvard Univ. Press, 2010).

  2. Engelen, T., Solcà, M. & Tallon-Baudry, C. Interoceptive rhythms in the brain. Nat. Neurosci. 26, 1670–1684 (2023).

    Article  PubMed  Google Scholar 

  3. Allen, M. Unravelling the neurobiology of interoceptive inference. Trends Cogn. Sci. 24, 265–266 (2020).

    Article  PubMed  Google Scholar 

  4. Critchley, H. D. & Garfinkel, S. N. Interoception and emotion. Curr. Opin. Psychol. 17, 7–14 (2017).

    Article  PubMed  Google Scholar 

  5. Nord, C. L. & Garfinkel, S. N. Interoceptive pathways to understand and treat mental health conditions. Trends Cogn. Sci. 26, 499–513 (2022).

    Article  PubMed  Google Scholar 

  6. Hsueh, B. et al. Cardiogenic control of affective behavioural state. Nature 615, 292–299 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Teed, A. R. et al. Association of generalized anxiety disorder with autonomic hypersensitivity and blunted ventromedial prefrontal cortex activity during peripheral adrenergic stimulation: a randomized clinical trial. JAMA Psychiatry 79, 323–332 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Cryan, J. F. & Dinan, T. G. Mind-altering microorganisms: the impact of the gut microbiota on brain and behaviour. Nat. Rev. Neurosci. 13, 701–712 (2012).

    Article  PubMed  Google Scholar 

  9. Kolobaric, A. et al. Gut microbiome predicts cognitive function and depressive symptoms in late life. Mol. Psychiatry https://doi.org/10.1038/s41380-024-02551-3 (2024).

  10. Allen, M., Varga, S. & Heck, D. H. Respiratory rhythms of the predictive mind. Psychol. Rev. https://doi.org/10.1037/rev0000391 (2022).

  11. Bagur, S. et al. Breathing-driven prefrontal oscillations regulate maintenance of conditioned-fear evoked freezing independently of initiation. Nat. Commun. 12, 2605 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kluger, D. S. et al. Modulatory dynamics of periodic and aperiodic activity in respiration–brain coupling. Nat. Commun. 14, 4699 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Zelano, C. et al. Nasal respiration entrains human limbic oscillations and modulates cognitive function. J. Neurosci. 36, 12448–12467 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Krieger, J.-P. et al. Neural pathway for gut feelings: vagal interoceptive feedback from the gastrointestinal tract is a critical modulator of anxiety-like behavior. Biol. Psychiatry 92, 709–721 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Margolis, K. G., Cryan, J. F. & Mayer, E. A. The microbiota–gut–brain axis: from motility to mood. Gastroenterology 160, 1486–1501 (2021).

    Article  PubMed  Google Scholar 

  16. Foster, J. A. & McVey Neufeld, K.-A. Gut–brain axis: how the microbiome influences anxiety and depression. Trends Neurosci. 36, 305–312 (2013).

    Article  PubMed  Google Scholar 

  17. Mayeli, A. et al. Parieto-occipital ERP indicators of gut mechanosensation in humans. Nat. Commun. 14, 3398 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Rebollo, I., Devauchelle, A.-D., Béranger, B. & Tallon-Baudry, C. Stomach–brain synchrony reveals a novel, delayed-connectivity resting-state network in humans. eLife 7, e33321 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Rebollo, I. & Tallon-Baudry, C. The sensory and motor components of the cortical hierarchy are coupled to the rhythm of the stomach during rest. J. Neurosci. 42, 2202–2220 (2021).

    Google Scholar 

  20. Azzalini, D., Rebollo, I. & Tallon-Baudry, C. Visceral signals shape brain dynamics and cognition. Trends Cogn. Sci. 23, 488–509 (2019).

    Article  PubMed  Google Scholar 

  21. Teckentrup, V. & Kroemer, N. B. Mechanisms for survival: vagal control of goal-directed behavior. Trends Cogn. Sci. 28, 237–251 (2024).

    Article  PubMed  Google Scholar 

  22. Nord, C. L., Dalmaijer, E. S., Armstrong, T., Baker, K. & Dalgleish, T. A causal role for gastric rhythm in human disgust avoidance. Curr. Biol. 31, 629–634 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Inui, A. Ghrelin: an orexigenic and somatotrophic signal from the stomach. Nat. Rev. Neurosci. 2, 551–560 (2001).

    Article  PubMed  Google Scholar 

  24. Sanders, K. M., Ward, S. M. & Koh, S. D. Interstitial cells: regulators of smooth muscle function. Physiol. Rev. 94, 859–907 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Richter, C. G., Babo-Rebelo, M., Schwartz, D. & Tallon-Baudry, C. Phase–amplitude coupling at the organism level: the amplitude of spontaneous alpha rhythm fluctuations varies with the phase of the infra-slow gastric basal rhythm. Neuroimage 146, 951–958 (2017).

    Article  PubMed  Google Scholar 

  26. Cao, J. et al. Gastric stimulation drives fast BOLD responses of neural origin. Neuroimage 197, 200–211 (2019).

    Article  PubMed  Google Scholar 

  27. Alladin, S. N. B., Judson, R., Whittaker, P., Attwood, A. S. & Dalmaijer, E. S. Review of the gastric physiology of disgust: proto-nausea as an under-explored facet of the gut–brain axis. Brain Neurosci. Adv. 8, 23982128241305890 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Müller, S. J., Teckentrup, V., Rebollo, I., Hallschmid, M. & Kroemer, N. B. Vagus nerve stimulation increases stomach-brain coupling via a vagal afferent pathway. Brain Stimul. 15, 1279–1289 (2022).

    Article  PubMed  Google Scholar 

  29. Cao, J., Wang, X., Chen, J., Zhang, N. & Liu, Z. The vagus nerve mediates the stomach–brain coherence in rats. Neuroimage 263, 119628 (2022).

  30. Marso, S. P. et al. Semaglutide and cardiovascular outcomes in patients with type 2 diabetes. N. Engl. J. Med. 375, 1834–1844 (2016).

    Article  PubMed  Google Scholar 

  31. Wilding, J. P. H. et al. Once-weekly semaglutide in adults with overweight or obesity. N. Engl. J. Med. 384, 989–1002 (2021).

    Article  PubMed  Google Scholar 

  32. Nummenmaa, L., Hari, R., Hietanen, J. K. & Glerean, E. Maps of subjective feelings. Proc. Natl Acad. Sci. USA 115, 9198–9203 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Nummenmaa, L., Glerean, E., Hari, R. & Hietanen, J. K. Bodily maps of emotions. Proc. Natl Acad. Sci. USA 111, 646–651 (2014).

    Article  PubMed  Google Scholar 

  34. Insel, T. R. & Cuthbert, B. N. Brain disorders? Precisely. Science 348, 499–500 (2015).

    Article  PubMed  Google Scholar 

  35. Calkins, M. E. et al. The Philadelphia Neurodevelopmental Cohort: constructing a deep phenotyping collaborative. J. Child Psychol. Psychiatry 56, 1356–1369 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Gillan, C. M., Kosinski, M., Whelan, R., Phelps, E. A. & Daw, N. D. Characterizing a psychiatric symptom dimension related to deficits in goal-directed control. eLife 5, e11305 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Smith, S. M. et al. A positive-negative mode of population covariation links brain connectivity, demographics and behavior. Nat. Neurosci. 18, 1565–1567 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Kaczkurkin, A. N. et al. Common and dissociable regional cerebral blood flow differences associate with dimensions of psychopathology across categorical diagnoses. Mol. Psychiatry 23, 1981–1989 (2018).

    Article  PubMed  Google Scholar 

  39. Benwell, C. S. Y., Mohr, G., Wallberg, J., Kouadio, A. & Ince, R. A. A. Psychiatrically relevant signatures of domain-general decision-making and metacognition in the general population. npj Ment. Health Res. 1, 10 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Insel, T. et al. Research Domain Criteria (RDoC): toward a new classification framework for research on mental disorders. Am. J. Psychiatry 167, 748–751 (2010).

    Article  PubMed  Google Scholar 

  41. Schumann, G. et al. Stratified medicine for mental disorders. Eur. Neuropsychopharmacol. 24, 5–50 (2014).

    Article  PubMed  Google Scholar 

  42. Goyal, N., Moraczewski, D., Bandettini, P. A., Finn, E. S. & Thomas, A. G. The positive–negative mode link between brain connectivity, demographics and behaviour: a pre-registered replication of Smith et al. (2015). R. Soc. Open Sci. 9, 201090 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Lachaux, J.-P., Rodriguez, E., Martinerie, J. & Varela, F. J. Measuring phase synchrony in brain signals. Hum. Brain Mapp. 8, 194–208 (1999).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Yeo, B. T. T. et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165 (2011).

    Article  PubMed  Google Scholar 

  45. McTeague, L. M. et al. Identification of common neural circuit disruptions in cognitive control across psychiatric disorders. Am. J. Psychiatry 174, 676–685 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Yang, Y. et al. Common and specific functional activity features in schizophrenia, major depressive disorder, and bipolar disorder. Front. Psychiatry 10, 52 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Seghier, M. L. The angular gyrus. Neuroscientist 19, 43–61 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Gao, Y. et al. Decreased resting-state neural signal in the left angular gyrus as a potential neuroimaging biomarker of schizophrenia: an amplitude of low-frequency fluctuation and support vector machine analysis. Front. Psychiatry 13, 949512 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Su, Q. et al. Decreased interhemispheric functional connectivity in insula and angular gyrus/supramarginal gyrus: significant findings in first-episode, drug-naive somatization disorder. Psychiatry Res. Neuroimaging 248, 48–54 (2016).

    Article  PubMed  Google Scholar 

  50. Gao, J. et al. Habenula and left angular gyrus circuit contributes to response of electroconvulsive therapy in major depressive disorder. Brain Imaging Behav. 15, 2246–2253 (2021).

    Article  PubMed  Google Scholar 

  51. Mo, Y. et al. Bifrontal electroconvulsive therapy changed regional homogeneity and functional connectivity of left angular gyrus in major depressive disorder. Psychiatry Res. 294, 113461 (2020).

    Article  PubMed  Google Scholar 

  52. Tozzi, L. et al. Personalized brain circuit scores identify clinically distinct biotypes in depression and anxiety. Nat. Med. 30, 2076–2087 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Menon, V. & Uddin, L. Q. Saliency, switching, attention and control: a network model of insula function. Brain Struct. Funct. 214, 655–667 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Gordon, E. M. et al. A somato-cognitive action network alternates with effector regions in motor cortex. Nature 617, 351–359 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Choe, A. S. et al. Phase-locking of resting-state brain networks with the gastric basal electrical rhythm. PLoS ONE 16, e0244756 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Levakov, G., Ganor, S. & Avidan, G. Reliability and validity of brain–gastric phase synchronization. Hum. Brain Mapp. 44, 4956–4966 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Todd, J., Cardellicchio, P., Swami, V., Cardini, F. & Aspell, J. E. Weaker implicit interoception is associated with more negative body image: evidence from gastric-alpha phase amplitude coupling and the heartbeat evoked potential. Cortex 143, 254–266 (2021).

    Article  PubMed  Google Scholar 

  58. Schürmann-Vengels, J., Troche, S., Victor, P. P., Teismann, T. & Willutzki, U. Multidimensional assessment of strengths and their association with mental health in psychotherapy patients at the beginning of treatment. Clin. Psychol. Eur. 5, e8041 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Mihalik, A. et al. Canonical correlation analysis and partial least squares for identifying brain–behavior associations: a tutorial and a comparative study. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 7, 1055–1067 (2022).

    PubMed  Google Scholar 

  60. Hashimoto, T. et al. Neural correlates of electrointestinography: Insular activity modulated by signals recorded from the abdominal surface. Neuroscience 289, 1–8 (2015).

    Article  PubMed  Google Scholar 

  61. Jeanne, R. et al. Gut-Brain coupling and multilevel physiological response to biofeedback relaxation after a stressful task under virtual reality immersion: a pilot study. Appl. Psychophysiol. Biofeedback 48, 109–125 (2023).

    Article  PubMed  Google Scholar 

  62. Wolpert, N., Rebollo, I. & Tallon-Baudry, C. Electrogastrography for psychophysiological research: practical considerations, analysis pipeline, and normative data in a large sample. Psychophysiology 57, e13599 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Alladin, S. N. B. et al. Children aged 5–13 years show adult-like disgust avoidance, but not proto-nausea. Brain Neurosci. Adv. 8, 23982128241279616 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Chang, L., Wei, Y. & Hashimoto, K. Brain–gut–microbiota axis in depression: a historical overview and future directions. Brain Res. Bull. 182, 44–56 (2022).

    Article  PubMed  Google Scholar 

  65. Vindegaard, N., Speyer, H., Nordentoft, M., Rasmussen, S. & Benros, M. E. Gut microbial changes of patients with psychotic and affective disorders: a systematic review. Schizophr. Res. 234, 41–50 (2021).

    Article  Google Scholar 

  66. Rao, S. S. C., Quigley, E. M. M., Chey, W. D., Sharma, A. & Lembo, A. J. Randomized placebo-controlled phase 3 trial of vibrating capsule for chronic constipation. Gastroenterology 164, 1202–1210.e6 (2023).

    Article  PubMed  Google Scholar 

  67. Porciello, G., Monti, A., Panasiti, M. S. & Aglioti, S. M. Ingestible pills reveal gastric correlates of emotions. eLife 13, e85567 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Linke, J. O. et al. Shared and anxiety-specific pediatric psychopathology dimensions manifest distributed neural correlates. Biol. Psychiatry 89, 579–587 (2021).

    Article  PubMed  Google Scholar 

  69. Luo, L., Wang, W., Bao, S., Peng, X. & Peng, Y. Robust and sparse canonical correlation analysis for fault detection and diagnosis using training data with outliers. Expert Syst. Appl. 236, 121434 (2024).

    Article  Google Scholar 

  70. Wilms, I. & Croux, C. Robust sparse canonical correlation analysis. BMC Syst. Biol. 10, 72 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Okan Sakar, C. & Kursun, O. A method for combining mutual information and canonical correlation analysis: predictive mutual information and its use in feature selection. Expert Syst. Appl. 39, 3333–3344 (2012).

    Article  Google Scholar 

  72. Mandal, A. & Cichocki, A. Non-linear canonical correlation analysis using alpha–beta divergence. Entropy 15, 2788–2804 (2013).

    Article  Google Scholar 

  73. Critchley, H. D. et al. Human cingulate cortex and autonomic control: converging neuroimaging and clinical evidence. Brain 126, 2139–2152 (2003).

    Article  PubMed  Google Scholar 

  74. Natarajan, A. et al. Measurement of respiratory rate using wearable devices and applications to COVID-19 detection. npj Digit. Med. 4, 136 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Iqbal, T., Elahi, A., Ganly, S., Wijns, W. & Shahzad, A. Photoplethysmography-based respiratory rate estimation algorithm for health monitoring applications. J. Med. Biol. Eng. 42, 242–252 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This research is financially supported by a Lundbeckfonden Fellowship (R272-2017-4345, M.A.) and a European Research Council Grant (ERC-2020-StG-948788, M.A.). I.R. is supported by a Marie Skłodowska-Curie Action (MSCA) BRAINSTOM (101028203). The funding source was not involved in the study design, collection, analysis, interpretation or writing of the manuscript.

Author information

Author notes

  1. These authors contributed equally: Leah Banellis, Ignacio Rebollo.

Authors and Affiliations

  1. Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark

    Leah Banellis, Niia Nikolova & Micah Allen

  2. Department of Decision Neuroscience and Nutrition, German Institute of Human Nutrition, Nuthetal, Germany

    Ignacio Rebollo

  3. Neuroscience Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany

    Ignacio Rebollo

  4. German Center for Diabetes Research (DZD), Neuherberg, Germany

    Ignacio Rebollo

  5. Cambridge Psychiatry, University of Cambridge, Cambridge, UK

    Micah Allen

Authors
  1. Leah Banellis
    View author publications

    Search author on:PubMed Google Scholar

  2. Ignacio Rebollo
    View author publications

    Search author on:PubMed Google Scholar

  3. Niia Nikolova
    View author publications

    Search author on:PubMed Google Scholar

  4. Micah Allen
    View author publications

    Search author on:PubMed Google Scholar

Contributions

L.B. and IR analyzed the data, interpreted the results and wrote the paper. N.N. provided conceptual advice and contributed toward preprocessing of neuroimaging data. M.A. provided supervision, conceptual advice and wrote the paper.

Corresponding author

Correspondence to Leah Banellis.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Mental Health thanks Edwin Dalmaijer, Rebecca Todd and the other, anonymous reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information (download PDF )

Supplementary Tables 1–6, Figs. 1–8 and fMRIprep preprocessing section.

Reporting Summary (download PDF )

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Banellis, L., Rebollo, I., Nikolova, N. et al. Stomach–brain coupling indexes a dimensional signature of mental health. Nat. Mental Health 3, 899–908 (2025). https://doi.org/10.1038/s44220-025-00468-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s44220-025-00468-6

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing