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:

Heterogeneous neuroimaging findings across substance use disorders localize to a common brain network

Nature Mental Health volume 1, pages 772–781 (2023)Cite this article

Subjects

Abstract

Substance use disorders are associated with neuroimaging abnormalities, but results are heterogeneous across studies and vary across substances, and the causal interpretation of these abnormalities is unknown. We have used network mapping approaches and a functional connectome from a large cohort of healthy participants (n = 1,000) to test whether neuroimaging abnormalities across substance use disorders map to a common brain network. Starting with coordinates of regional brain atrophy from 45 studies (3,791 participants), we found that 91% of the neuroimaging findings mapped to a common brain network. This network was specific to substance use disorder compared to atrophy associated with normal aging and neurodegenerative disease (PFWE < 0.05). Coordinates of functional MRI abnormalities from 99 studies (5,256 participants) mapped to a similar brain network. We found no differences in networks across different substance use categories. We combined all substance use disorder data (144 studies, 9,047 participants) to generate an overall coordinate-based network for substance use disorder, which included positive connectivity to the anterior cingulate, bilateral insulae, dorsolateral prefrontal cortices and thalamus, and negative connectivity to the medial prefrontal and occipital cortices. Lesions resulting in remission from nicotine use disorder (n = 34) intersected this network significantly more than control lesions (n = 69; P < 0.0084). We conclude that neuroimaging abnormalities across substance use disorders map to a common brain network that is similar across imaging modalities, substances and lesion locations that cause remission from substance use disorders.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Locations and connectivity of atrophy in substance use disorders compared to healthy controls.
Fig. 2: Atrophy coordinate network of substance use disorders.
Fig. 3: fMRI coordinate network of substance use disorders.
Fig. 4: Atrophy and fMRI coordinate networks across substance use disorder categories.
Fig. 5: Overall coordinate network of substance use disorders and lesion validation.

Similar content being viewed by others

Data availability

All atrophy and fMRI coordinates used in our study are available in published studies as identified in previous meta-analyses9,10,27. De-identified lesion masks of stroke lesions causing remission from nicotine use disorder are publicly available25,56, and clinical data from the patients may be shared upon request to the corresponding author of the original lesion network mapping study25. A version of the connectome along with preprocessing details is publicly available47. Voxel-wise imaging results were projected onto a publicly available ultrahigh-resolution ex vivo brain aligned to MNI space58.

Code availability

Code to conduct connectivity analyses is available as part of the open-access Lead-DBS software package (https://lead-dbs.org)57, and supporting code for this study is available at https://github.com/nimlab/NMH_Stubbs2023/.

References

  1. Degenhardt, L. & Hall, W. Extent of illicit drug use and dependence, and their contribution to the global burden of disease. Lancet 379, 55–70 (2012).

    Article  PubMed  Google Scholar 

  2. GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 1223–1249 (2020).

    Article  Google Scholar 

  3. Lipari, R. N., Hedden, S. L. & Hughes, A. Substance use and mental health estimates from the 2013 National Survey on Drug Use and Health: overview of findings. In The CBHSQ Report (Substance Abuse and Mental Health Services Administration (US), 2013).

  4. Volkow, N. D., Koob, G. F. & McLellan, A. T. Neurobiologic advances from the brain disease model of addiction. N. Engl. J. Med. 374, 363–371 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Wollman, S. C. et al. Gray matter abnormalities in opioid-dependent patients: a neuroimaging meta-analysis. Am. J. Drug Alcohol Abuse 43, 505–517 (2017).

    Article  PubMed  Google Scholar 

  6. Martín-Santos, R. et al. Neuroimaging in cannabis use: a systematic review of the literature. Psychol. Med. 40, 383–398 (2010).

    Article  PubMed  Google Scholar 

  7. Mackey, S. & Paulus, M. Are there volumetric brain differences associated with the use of cocaine and amphetamine-type stimulants? Neurosci. Biobehav. Rev. 37, 300–316 (2013).

    Article  PubMed  Google Scholar 

  8. Ersche, K. D., Williams, G. B., Robbins, T. W. & Bullmore, E. T. Meta-analysis of structural brain abnormalities associated with stimulant drug dependence and neuroimaging of addiction vulnerability and resilience. Curr. Opin. Neurobiol. 23, 615–624 (2013).

    Article  PubMed  Google Scholar 

  9. Pando-Naude, V. et al. Gray and white matter morphology in substance use disorders: a neuroimaging systematic review and meta-analysis. Transl. Psychiatry 11, 29 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Klugah-Brown, B. et al. Common and separable neural alterations in substance use disorders: a coordinate-based meta-analyses of functional neuroimaging studies in humans. Hum. Brain Mapp. 41, 4459–4477 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Spindler, C., Mallien, L., Trautmann, S., Alexander, N. & Muehlhan, M. A coordinate-based meta-analysis of white matter alterations in patients with alcohol use disorder. Transl. Psychiatry 12, 40 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Mackey, S. et al. Mega-analysis of gray matter volume in substance dependence: general and substance-specific regional effects. Am. J. Psychiatry 176, 119–128 (2019).

    Article  PubMed  Google Scholar 

  13. Fox, M. D. Mapping symptoms to brain networks with the human connectome. N. Engl. J. Med. 379, 2237–2245 (2018).

    Article  PubMed  Google Scholar 

  14. Siddiqi, S. H., Kording, K. P., Parvizi, J. & Fox, M. D. Causal mapping of human brain function. Nat. Rev. Neurosci. 23, 361–375 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Siddiqi, S. H. et al. Brain stimulation and brain lesions converge on common causal circuits in neuropsychiatric disease. Nat. Hum. Behav. 5, 1707–1716 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Ferguson, M. A. et al. A human memory circuit derived from brain lesions causing amnesia. Nat. Commun. 10, 3497 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Taylor, J. J., Siddiqi, S. H. & Fox, M. D. Coordinate network mapping: an emerging approach for morphometric meta-analysis. Am. J. Psychiatry 178, 1080–1081 (2021).

    Article  PubMed  Google Scholar 

  18. Weil, R. S., Hsu, J. K., Darby, R. R., Soussand, L. & Fox, M. D. Neuroimaging in Parkinson’s disease dementia: connecting the dots. Brain Commun. 1, fcz006 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Burke, M. J. et al. Mapping migraine to a common brain network. Brain J. Neurol. 143, 541–553 (2020).

    Article  Google Scholar 

  20. Darby, R. R., Joutsa, J. & Fox, M. D. Network localization of heterogeneous neuroimaging findings. Brain J. Neurol. 142, 70–79 (2019).

    Article  Google Scholar 

  21. Zhukovsky, P. et al. Coordinate-based network mapping of brain structure in major depressive disorder in younger and older adults: a systematic review and meta-analysis. Am. J. Psychiatry 178, 1119–1128 (2021).

    Article  PubMed  Google Scholar 

  22. Peng, S., Xu, P., Jiang, Y. & Gong, G. Activation network mapping for integration of heterogeneous fMRI findings. Nat. Hum. Behav. https://doi.org/10.1038/s41562-022-01371-1 (2022).

  23. Neiman, J., Haapaniemi, H. M. & Hillbom, M. Neurological complications of drug abuse: pathophysiological mechanisms. Eur. J. Neurol. 7, 595–606 (2000).

    Article  PubMed  Google Scholar 

  24. Cadet, J. L., Bisagno, V. & Milroy, C. M. Neuropathology of substance use disorders. Acta Neuropathol. (Berl.) 127, 91–107 (2014).

    Article  PubMed  Google Scholar 

  25. Joutsa, J. et al. Brain lesions disrupting addiction map to a common human brain circuit. Nat. Med. 28, 1249–1255 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Taylor, J. et al. A convergent brain network for psychiatric illness. Nat. Hum. Behav. 7, 420–429 (2023).

    Article  PubMed  Google Scholar 

  27. Minkova, L. et al. Gray matter asymmetries in aging and neurodegeneration: a review and meta-analysis. Hum. Brain Mapp. 38, 5890–5904 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Miller, J. M. et al. Anhedonia after a selective bilateral lesion of the globus pallidus. Am. J. Psychiatry 163, 786–788 (2006).

    Article  PubMed  Google Scholar 

  29. Moussawi, K., Kalivas, P. W. & Lee, J. W. Abstinence from drug dependence after bilateral Globus Pallidus hypoxic ischemic injury. Biol. Psychiatry 80, e79–e80 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Muskens, J. B., Schellekens, A. F. A., de Leeuw, F. E., Tendolkar, I. & Hepark, S. Damage in the dorsal striatum alleviates addictive behavior. Gen. Hosp. Psychiatry 34, 702–702 (2012).

    Article  Google Scholar 

  31. Goldstein, R. Z. & Volkow, N. D. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat. Rev. Neurosci. 12, 652–669 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Koob, G. F. & Volkow, N. D. Neurobiology of addiction: a neurocircuitry analysis. Lancet Psychiatry 3, 760–773 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Zhao, Y. et al. Anterior cingulate cortex in addiction: new insights for neuromodulation. Neuromodulation 24, 187–196 (2021).

    Article  Google Scholar 

  34. Uddin, L. Q., Nomi, J. S., Hebert-Seropian, B., Ghaziri, J. & Boucher, O. Structure and function of the human insula. J. Clin. Neurophysiol. 34, 300–306 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Huang, A. S., Mitchell, J. A., Haber, S. N., Alia-Klein, N. & Goldstein, R. Z. The thalamus in drug addiction: from rodents to humans. Philos. Trans. R. Soc. Lond. B Biol. Sci. 373, 20170028 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Steele, J. D., Christmas, D., Eljamel, M. S. & Matthews, K. Anterior cingulotomy for major depression: clinical outcome and relationship to lesion characteristics. Biol. Psychiatry 63, 670–677 (2008).

    Article  PubMed  Google Scholar 

  37. Sharim, J. & Pouratian, N. Anterior cingulotomy for the treatment of chronic intractable pain: a systematic review. Pain Physician 19, 537–550 (2016).

    PubMed  Google Scholar 

  38. Leong, S. L. et al. Anterior cingulate cortex implants for alcohol addiction: a feasibility study. Neurother. J. Am. Soc. Exp. Neurother. 17, 1287–1299 (2020).

    Google Scholar 

  39. Patel, S. R., Aronson, J. P., Sheth, S. A. & Eskandar, E. N. Lesion procedures in psychiatric neurosurgery. World Neurosurg. 80, S31.e9–16 (2013).

    Article  PubMed  Google Scholar 

  40. Naqvi, N. H., Rudrauf, D., Damasio, H. & Bechara, A. Damage to the insula disrupts addiction to cigarette smoking. Science 315, 531–534 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Jiang, J., Ferguson, M. A., Grafman, J., Cohen, A. L. & Fox, M. D. A lesion-derived brain network for emotion regulation. Biol. Psychiatry https://doi.org/10.1016/j.biopsych.2023.02.007 (2023).

  42. Lees, B. et al. Promising vulnerability markers of substance use and misuse: a review of human neurobehavioral studies. Neuropharmacology 187, 108500 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Fox, M. D. et al. Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases. Proc. Natl Acad. Sci. USA 111, E4367–E4375 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Boes, A. D. et al. Network localization of neurological symptoms from focal brain lesions. Brain J. Neurol. 138, 3061–3075 (2015).

    Article  Google Scholar 

  45. Horn, A. et al. Connectivity predicts deep brain stimulation outcome in Parkinson disease. Ann. Neurol. 82, 67–78 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Lancaster, J. L. et al. Bias between MNI and Talairach coordinates analyzed using the ICBM-152 brain template. Hum. Brain Mapp. 28, 1194–1205 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Cohen, A., Soussand, L., McManus, P. & Fox, M. GSP1000 Preprocessed Connectome (Harvard Dataverse, 2020); https://doi.org/10.7910/DVN/ILXIKS

  48. Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M. & Nichols, T. E. Permutation inference for the general linear model. NeuroImage 92, 381–397 (2014).

    Article  PubMed  Google Scholar 

  49. Bachi, K., Sierra, S., Volkow, N. D., Goldstein, R. Z. & Alia-Klein, N. Is biological aging accelerated in drug addiction? Curr. Opin. Behav. Sci. 13, 34–39 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Büttner, A. Neuropathology of Drug Abuse (Springer, 2021).

  51. Byars, J. A., Beglinger, L. J., Moser, D. J., Gonzalez-Alegre, P. & Nopoulos, P. Substance abuse may be a risk factor for earlier onset of Huntington disease. J. Neurol. 259, 1824–1831 (2012).

    Article  PubMed  Google Scholar 

  52. Livingston, G. et al. Dementia prevention, intervention and care: 2020 report of the Lancet Commission. Lancet 396, 413–446 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  53. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).

  54. Siddiqi, S. H. et al. Distinct symptom-specific treatment targets for circuit-based neuromodulation. Am. J. Psychiatry 177, 435–446 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Padmanabhan, J. L. et al. A human depression circuit derived from focal brain lesions. Biol. Psychiatry 86, 749–758 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Joutsa, J. Smoking Lesion Datasets (2022); https://doi.org/10.7910/DVN/8BHHRS

  57. Horn, A. et al. Lead-DBS v2: towards a comprehensive pipeline for deep brain stimulation imaging. NeuroImage 184, 293–316 (2019).

    Article  PubMed  Google Scholar 

  58. Edlow, B. L. et al. 7 Tesla MRI of the ex vivo human brain at 100 micron resolution. Sci. Data 6, 244 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Drs. A. Boes, J. Bruss and E. van Wijngaarden for sharing the lesion and clinical data included in the lesion validation analysis and Fig. 5, and we thank Dr. J. Joutsa for sharing the lesion case study data included in Supplementary Fig. 5. J.L.S. was supported by a Canadian Institutes of Health Research Vanier Scholarship and a University of British Columbia Friedman Award for Scholars in Health. J.J.T. was supported by the National Institute of Mental Health (K23MH129829), the Brain and Behavior Research Foundation, Sidney R. Baer Foundation, the Baszucki Brain Research Fund and Harvard Medical School. F.L.W.V.J.S. was supported by the NIH (R01NS127892). A.C. was supported by the NIH (K23MH120510), the Child Neurology Foundation and the Simons Foundation. Data from the Rochester cohort was supported in part by the National Heart, Lung and Blood Institute Preventive Cardiology Training (grant no. T32 HL007937) and by the Clinical and Translational Science Institute (grant no. UL1 RR024160) from the National Institutes of Health. W.G.H. was supported by the Jack Bell Chair in Schizophrenia. M.D.F. was supported by grants from the NIH (R01MH113929, R21MH126271, R56AG069086, R21NS123813 and R01NS127892), the Kaye Family Research Endowment, the Ellison/Baszucki Family Foundation and the Manley Family.

Author information

Authors and Affiliations

  1. Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Boston, MA, USA

    Jacob L. Stubbs, Joseph J. Taylor, Shan H. Siddiqi, Frederic L. W. V. J. Schaper, Alexander L. Cohen, William Drew & Michael D. Fox

  2. Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Jacob L. Stubbs, Frederic L. W. V. J. Schaper, William Drew & Michael D. Fox

  3. Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada

    Jacob L. Stubbs, William G. Honer & William J. Panenka

  4. Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Joseph J. Taylor, Shan H. Siddiqi & Michael D. Fox

  5. Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

    Alexander L. Cohen

  6. Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA

    Colleen A. Hanlon

  7. Clinical Affairs, Philips Healthcare, Cambridge, MA, USA

    Amir Abdolahi

  8. Department of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, USA

    Henry Z. Wang

  9. British Columbia Mental Health and Substance Use Services Research Institute, Vancouver, British Columbia, Canada

    William G. Honer & William J. Panenka

  10. British Columbia Provincial Neuropsychiatry Program, Vancouver, British Columbia, Canada

    William J. Panenka

Authors
  1. Jacob L. Stubbs
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joseph J. Taylor
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shan H. Siddiqi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Frederic L. W. V. J. Schaper
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alexander L. Cohen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. William Drew
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Colleen A. Hanlon
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Amir Abdolahi
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Henry Z. Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. William G. Honer
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. William J. Panenka
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Michael D. Fox
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.L.S., J.J.T. and M.D.F. designed the study. J.L.S. and W.D. processed the data. J.L.S., J.J.T., S.H.S., F.L.W.V.J.S., A.L.C., W.D. and M.D.F. conducted and interpreted analyses. J.L.S., J.J.T., S.H.S., F.L.W.V.J.S., A.L.C., W.D., C.A.H., A.A., H.Z.W., W.G.H., W.J.P. and M.D.F. contributed to the interpretation of the results and writing of the manuscript.

Corresponding author

Correspondence to Jacob L. Stubbs.

Ethics declarations

Competing interests

C.H. is employed by BrainsWay and has financial interest in the company. S.H.S. is a scientific consultant for Magnus Medical, and a clinical consultant for Acacia Mental Health, Kaizen Brain Center and Boston Precision Neurotherapeutics. S.H.S. has received investigator-initiated research funding from Neuronetics and BrainsWay. S.H.S. has served as a speaker for BrainsWay (branded) and PsychU.org (unbranded, sponsored by Otsuka). S.H.S. owns stock in BrainsWay (publicly traded) and Magnus Medical (not publicly traded). S.H.S. owns intellectual property involving the use of functional connectivity to target TMS. M.D.F. is a consultant for Magnus Medical, Solaris and Boston Scientific, and has intellectual property using connectivity imaging to guide brain stimulation. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Mental Health thanks Tianye Jia and the other, anonymous, reviewers for their contributions 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

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

Stubbs, J.L., Taylor, J.J., Siddiqi, S.H. et al. Heterogeneous neuroimaging findings across substance use disorders localize to a common brain network. Nat. Mental Health 1, 772–781 (2023). https://doi.org/10.1038/s44220-023-00128-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s44220-023-00128-7

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research