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.

  • Review Article
  • Published:

Causal mapping of human brain function

Nature Reviews Neuroscience volume 23, pages 361–375 (2022)Cite this article

Subjects

Abstract

Mapping human brain function is a long-standing goal of neuroscience that promises to inform the development of new treatments for brain disorders. Early maps of human brain function were based on locations of brain damage or brain stimulation that caused a functional change. Over time, this approach was largely replaced by technologies such as functional neuroimaging, which identify brain regions in which activity is correlated with behaviours or symptoms. Despite their advantages, these technologies reveal correlations, not causation. This creates challenges for interpreting the data generated from these tools and using them to develop treatments for brain disorders. A return to causal mapping of human brain function based on brain lesions and brain stimulation is underway. New approaches can combine these causal sources of information with modern neuroimaging and electrophysiology techniques to gain new insights into the functions of specific brain areas. In this Review, we provide a definition of causality for translational research, propose a continuum along which to assess the relative strength of causal information from human brain mapping studies and discuss recent advances in causal brain mapping and their relevance for developing treatments.

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

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Fig. 1: Evolution of brain mapping literature since 1950.
Fig. 2: Appraising causality in human brain mapping studies.
Fig. 3: Heterogeneous lesions causing the same symptom can complicate causal inference.
Fig. 4: Coherence between LNM and iES studies.
Fig. 5: Coherence between TMS, DBS and brain lesions.

Similar content being viewed by others

References

  1. Fox, M. D. & Raichle, M. E. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat. Rev. Neurosci. 8, 700–711 (2007).

    Article  CAS  PubMed  Google Scholar 

  2. Raichle, M. E. A brief history of human brain mapping. Trends Neurosci. 32, 118–126 (2009).

    Article  CAS  PubMed  Google Scholar 

  3. Genon, S., Reid, A., Langner, R., Amunts, K. & Eickhoff, S. B. How to characterize the function of a brain region. Trends Cogn. Sci. 22, 350–364 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Gusnard, D. A. & Raichle, M. E. Searching for a baseline: functional imaging and the resting human brain. Nat. Rev. Neurosci. 2, 685–694 (2001).

    Article  CAS  PubMed  Google Scholar 

  5. Glasser, M. F. et al. A multi-modal parcellation of human cerebral cortex. Nature 536, 171–178 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Power, J. D. et al. Functional network organization of the human brain. Neuron 72, 665–678 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Bullmore, E. & Sporns, O. The economy of brain network organization. Nat. Rev. Neurosci. 13, 336–349 (2012).

    Article  CAS  PubMed  Google Scholar 

  8. Logothetis, N. K. What we can do and what we cannot do with fMRI. Nature 453, 869–878 (2008). This work presents an overview of common uses and pitfalls of correlative neuroimaging.

    Article  CAS  PubMed  Google Scholar 

  9. Jonas, E. & Kording, K. P. Could a neuroscientist understand a microprocessor? PLoS Comput. Biol. 13, e1005268 (2017). This work illustrates that conventional neuroscience tools are unable to explain the function of a microprocessor (a device that we understand completely), raising questions about whether they can explain anything meaningful about the brain.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Reid, A. T. et al. Advancing functional connectivity research from association to causation. Nat. Neurosci. 22, 1751–1760 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Laumann, T. O. & Snyder, A. Z. Brain activity is not only for thinking. Curr. Opin. Behav. Sci. 40, 130–136 (2021).

    Article  Google Scholar 

  12. Etkin, A. A reckoning and research agenda for neuroimaging in psychiatry. Am. J. Psychiatry 176, 507–511 (2019).

    Article  PubMed  Google Scholar 

  13. Weichwald, S. & Peters, J. Causality in cognitive neuroscience: concepts, challenges, and distributional robustness. J. Cogn. Neurosci. 33, 226–247 (2021).

    Article  PubMed  Google Scholar 

  14. Etkin, A. Addressing the causality gap in human psychiatric neuroscience. JAMA Psychiatry 75, 3–4 (2018).

    Article  PubMed  Google Scholar 

  15. Angrist, J. D. & Pischke, J.-S. The credibility revolution in empirical economics: how better research design is taking the con out of econometrics. J. Econ. Perspect. 24, 3–30 (2010).

    Article  Google Scholar 

  16. Leamer, E. E. Let’s take the con out of econometrics. Am. Econ. Rev. 73, 31–43 (1983).

    Google Scholar 

  17. Etkin, A. Mapping causal circuitry in human depression. Biol. Psychiatry 86, 732–733 (2019).

    Article  PubMed  Google Scholar 

  18. Bergmann, T. O. & Hartwigsen, G. Inferring causality from noninvasive brain stimulation in cognitive neuroscience. J. Cogn. Neurosci. 33, 195–225 (2021).

    Article  PubMed  Google Scholar 

  19. Pycroft, L., Stein, J. & Aziz, T. Deep brain stimulation: an overview of history, methods, and future developments. Brain Neurosci. Adv. 2, 2398212818816017 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lozano, A. M. et al. Effect of GPi pallidotomy on motor function in Parkinson’s disease. Lancet 346, 1383–1387 (1995).

    Article  CAS  PubMed  Google Scholar 

  21. Groiss, S. J., Wojtecki, L., Sudmeyer, M. & Schnitzler, A. Deep brain stimulation in Parkinson’s disease. Ther. Adv. Neurol. Disord. 2, 20–28 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Benabid, A. L. et al. Long-term suppression of tremor by chronic stimulation of the ventral intermediate thalamic nucleus. Lancet 337, 403–406 (1991). This work is an early example of successful therapeutic use of DBS, using a target for tremor based partly on prior studies using brain lesions.

    Article  CAS  PubMed  Google Scholar 

  23. George, M. S. et al. A controlled trial of daily left prefrontal cortex TMS for treating depression. Biol. Psychiatry 48, 962–970 (2000).

    Article  CAS  PubMed  Google Scholar 

  24. Pascual-Leone, A., Rubio, B., Pallardó, F. & Catalá, M. D. Rapid-rate transcranial magnetic stimulation of left dorsolateral prefrontal cortex in drug-resistant depression. Lancet 348, 233–237 (1996). This example of successful therapeutic use of TMS uses a target for depression based, in part, on depression-causing lesions — later confirmed in larger trials, including.

    Article  CAS  PubMed  Google Scholar 

  25. Harlow, J. M. Passage of an iron rod through the head. Boston Med. Surg. J. 39, 389–393 (1848).

    Article  Google Scholar 

  26. Scoville, W. B. & Milner, B. Loss of recent memory after bilateral hippocampal lesions. J. Neurol. Neurosurg. Psychiatry 20, 11 (1957).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Penfield, W. & Jasper, H. Epilepsy and the Functional Anatomy of the Human Brain (Little, Brown and Co., 1954).

  28. Penfield, W. & Perot, P. The brain’s record of auditory and visual experience: a final summary and discussion. Brain 86, 595–696 (1963).

    Article  CAS  PubMed  Google Scholar 

  29. Penfield, W. & Boldrey, E. Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain 60, 389–443 (1937).

    Article  Google Scholar 

  30. Rorden, C. & Karnath, H.-O. Using human brain lesions to infer function: a relic from a past era in the fMRI age? Nat. Rev. Neurosci. 5, 812–819 (2004).

    Article  CAS  Google Scholar 

  31. Michel, J.-B. et al. Quantitative analysis of culture using millions of digitized books. Science 331, 176–182 (2011).

    Article  CAS  PubMed  Google Scholar 

  32. Gaillard, R. et al. Direct intracranial, FMRI, and lesion evidence for the causal role of left inferotemporal cortex in reading. Neuron 50, 191–204 (2006).

    Article  CAS  PubMed  Google Scholar 

  33. Petersen, S. E., Fox, P. T., Posner, M. I., Mintun, M. & Raichle, M. E. Positron emission tomographic studies of the cortical anatomy of single-word processing. Nature 331, 585–589 (1988). This classic study uses correlative neuroimaging to illustrate features of language processing in healthy individuals.

    Article  CAS  PubMed  Google Scholar 

  34. Dolan, R. J. & Fletcher, P. Dissociating prefrontal and hippocampal function in episodic memory encoding. Nature 388, 582–585 (1997).

    Article  CAS  PubMed  Google Scholar 

  35. Zalesky, A., Fornito, A. & Bullmore, E. On the use of correlation as a measure of network connectivity. Neuroimage 60, 2096–2106 (2012).

    Article  PubMed  Google Scholar 

  36. Uttal, W. R. The New Phrenology: The Limits of Localizing Cognitive Processes in the Brain (MIT Press, 2001).

  37. Pearl, J. Causality (Cambridge Univ. Press, 2009).

  38. Angrist, J. D. & Pischke, J.-S. Mostly Harmless Econometrics: An Empiricist’s Companion (Princeton Univ. Press, 2008).

  39. Holland, P. W. Statistics and causal inference. J. Am. Stat. Assoc. 81, 945–960 (1986).

    Article  Google Scholar 

  40. Pearl, J. & Mackenzie, D. The Book of Why: The New Science of Cause and Effect (Basic Books, 2018). This book details the basic principles of causal reasoning across disciplines.

  41. Gotthelf, A. Aristotle’s Conception of Final Causality Thesis (Columbia Univ., 1975).

  42. Black, D. L. Mental existence in Thomas Aquinas and Avicenna. Mediaev. Stud. 61, 45–79 (1999).

    Article  Google Scholar 

  43. Taylor, R. in The Routledge Companion to Islamic Philosophy (eds Taylor, R. C. & Lopez-Farjeat, L. X.) 225–235 (Routledge, 2016).

  44. Smith, N. K. The Philosophy of David Hume: A Critical Study of Its Origins and Central Doctrines (Macmillan, 1941).

  45. Koch, R. An address on bacteriological research. BMJ 2, 380 (1890).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Bradford Hill, A. The environment and disease: association or causation? Proc. R. Soc. Med. 58, 295–300 (1965). This work introduces the Bradford Hill criteria, which have been used to understand causal relationships across multiple disciplines.

    Google Scholar 

  47. Fedak, K. M., Bernal, A., Capshaw, Z. A. & Gross, S. Applying the Bradford Hill criteria in the 21st century: how data integration has changed causal inference in molecular epidemiology. Emerg. Themes Epidemiol. 12, 14 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Araújo, L., Dalgalarrondo, P. & Banzato, C. On the notion of causality in medicine: addressing Austin Bradford Hill and John L. Mackie. Arch. Clin. Psychiatry 41, 56–61 (2014).

    Article  Google Scholar 

  49. Sajadi, M. M., Mansouri, D. & Sajadi, M. R. Ibn Sina and the clinical trial. Ann. Intern. Med. 150, 640–643 (2009).

    Article  PubMed  Google Scholar 

  50. Bradford Hill, A. Memories of the British streptomycin trial in tuberculosis: the first randomized clinical trial. Controlled Clin. Trials 11, 77–79 (1990).

    Article  Google Scholar 

  51. Gillies, D. Causality, Probability and Medicine (Taylor & Francis, 2018).

  52. Kaplan, R. M. & Irvin, V. L. Likelihood of null effects of large NHLBI clinical trials has increased over time. PLoS ONE 10, e0132382 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Baluku, J. B. et al. Prevalence of malaria and TB coinfection at a national tuberculosis treatment centre in Uganda. J. Tropical Med. 2019, 3741294 (2019).

    Article  Google Scholar 

  54. Koch, R. The etiology of tuberculosis. Mitth. aus dem Kaiserlichen Gesundheitsamte 2, 1–88 (1884).

    Google Scholar 

  55. Hernán, M. A. & Robins, J. M. Using big data to emulate a target trial when a randomized trial is not available. Am. J. Epidemiol. 183, 758–764 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Marinescu, I. E., Lawlor, P. N. & Kording, K. P. Quasi-experimental causality in neuroscience and behavioural research. Nat. Hum. Behav. 2, 891–898 (2018). This work presents an overview of different approaches to investigating causality when a prospective controlled experiment is not possible.

    Article  PubMed  Google Scholar 

  57. Cook, T. D., Shadish, W. R. & Wong, V. C. Three conditions under which experiments and observational studies produce comparable causal estimates: new findings from within-study comparisons. J. Policy Anal. Manag. 27, 724–750 (2008).

    Article  Google Scholar 

  58. Fox, M. D. Mapping symptoms to brain networks with the human connectome. N. Engl. J. Med. 379, 2237–2245 (2018). This work is an introduction to LNM, which can be used to relate different lesion locations causing a symptom to common brain circuits.

    Article  CAS  PubMed  Google Scholar 

  59. Williamson, J. Establishing causal claims in medicine. Int. Stud. Philos. Sci. 32, 33–61 (2019).

    Article  Google Scholar 

  60. Russo, F. & Williamson, J. Interpreting causality in the health sciences. Int. Stud. Philos. Sci. 21, 157–170 (2007).

    Article  Google Scholar 

  61. Evans, A. S. Causation and disease: the Henle–Koch postulates revisited. Yale J. Biol. Med. 49, 175–195 (1976).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Cassidy, J. M., Mark, J. I. & Cramer, S. C. Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation. Brain https://doi.org/10.1093/brain/awab469 (2021).

    Article  PubMed  Google Scholar 

  63. Bates, E. et al. Voxel-based lesion–symptom mapping. Nat. Neurosci. 6, 448–450 (2003).

    Article  CAS  PubMed  Google Scholar 

  64. Wu, O. et al. Role of acute lesion topography in initial ischemic stroke severity and long-term functional outcomes. Stroke 46, 2438–2444 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Corbetta, M. et al. Common behavioral clusters and subcortical anatomy in stroke. Neuron 85, 927–941 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Parvizi, J. & Kastner, S. Promises and limitations of human intracranial electroencephalography. Nat. Neurosci. 21, 474–483 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Fox, K. C. R. et al. Intrinsic network architecture predicts the effects elicited by intracranial electrical stimulation of the human brain. Nat. Hum. Behav. 4, 1039–1052 (2020). This work illustrates how iES can be used to investigate the causal relevance of networks defined using task-free neuroimaging.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Koenigs, M. et al. Focal brain damage protects against post-traumatic stress disorder in combat veterans. Nat. Neurosci. 11, 232–237 (2008).

    Article  CAS  PubMed  Google Scholar 

  69. Knutson, K. M. et al. Injured brain regions associated with anxiety in Vietnam veterans. Neuropsychologia 51, 686–694 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Herbsman, T. et al. More lateral and anterior prefrontal coil location is associated with better repetitive transcranial magnetic stimulation antidepressant response. Biol. Psychiatry 66, 509–515 (2009).

    Article  PubMed  Google Scholar 

  71. Fox, M. D., Buckner, R. L., White, M. P., Greicius, M. D. & Pascual-Leone, A. Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate. Biol. Psychiatry 72, 595–603 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Weigand, A. et al. Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites. Biol. Psychiatry 84, 28–37 (2018).

    Article  CAS  PubMed  Google Scholar 

  73. Gordon, E. M. et al. Individual-specific features of brain systems identified with resting state functional correlations. Neuroimage 146, 918–939 (2017).

    Article  PubMed  Google Scholar 

  74. Gordon, E. M., Laumann, T. O., Adeyemo, B. & Petersen, S. E. Individual variability of the system-level organization of the human brain. Cereb. Cortex 27, 386–399 (2017).

    PubMed  Google Scholar 

  75. Siddiqi, S. H., Weigand, A., Pascual-Leone, A. & Fox, M. D. Identification of personalized TMS targets based on subgenual cingulate connectivity: an independent replication. Biol. Psychiatry 90, e55–e56 (2021).

    Article  PubMed  Google Scholar 

  76. Cash, R. F. H., Cocchi, L., Lv, J., Fitzgerald, P. B. & Zalesky, A. Functional magnetic resonance imaging-guided personalization of transcranial magnetic stimulation treatment for depression. JAMA Psychiatry 78, 337–339 (2020).

    Article  PubMed Central  Google Scholar 

  77. Howell, B. et al. Quantifying the axonal pathways directly stimulated in therapeutic subcallosal cingulate deep brain stimulation. Hum. Brain Mapp. 40, 889–903 (2019).

    Article  PubMed  Google Scholar 

  78. Siddiqi, S. H. et al. Repetitive transcranial magnetic stimulation with resting-state network targeting for treatment-resistant depression in traumatic brain injury: a randomized, controlled, double-blinded pilot study. J. Neurotrauma 36, 1361–1374 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Parvizi, J., Rangarajan, V., Shirer, W. R., Desai, N. & Greicius, M. D. The will to persevere induced by electrical stimulation of the human cingulate gyrus. Neuron 80, 1359–1367 (2013).

    Article  CAS  PubMed  Google Scholar 

  80. Schrouff, J. et al. Fast temporal dynamics and causal relevance of face processing in the human temporal cortex. Nat. Commun. 11, 656 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Yih, J., Beam, D. E., Fox, K. C. R. & Parvizi, J. Intensity of affective experience is modulated by magnitude of intracranial electrical stimulation in human orbitofrontal, cingulate and insular cortices. Soc. Cogn. Affect. Neurosci. 14, 339–351 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Downar, J. et al. Anhedonia and reward-circuit connectivity distinguish nonresponders from responders to dorsomedial prefrontal repetitive transcranial magnetic stimulation in major depression. Biol. Psychiatry 76, 176–185 (2014).

    Article  PubMed  Google Scholar 

  83. Drysdale, A. T. et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat. Med. 12, 28–38 (2016).

    Google Scholar 

  84. Cash, R. F. H. et al. Using brain imaging to improve spatial targeting of transcranial magnetic stimulation for depression. Biol. Psychiatry 90, 689–700 (2020).

    Article  PubMed  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  86. 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 

  87. Joutsa, J., Horn, A., Hsu, J. & Fox, M. D. Localizing parkinsonism based on focal brain lesions. Brain 141, 2445–2456 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  88. Corp, D. T. et al. Network localization of cervical dystonia based on causal brain lesions. Brain 142, 1660–1674 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  89. Joutsa, J. et al. Identifying therapeutic targets from spontaneous beneficial brain lesions. Ann. Neurol. 84, 153–157 (2018).

    Article  PubMed  Google Scholar 

  90. Irmen, F. et al. Left prefrontal impact links subthalamic stimulation with depressive symptoms. Ann. Neurol. 87, 962–975 (2020).

    Article  PubMed  Google Scholar 

  91. Laganiere, S., Boes, A. D. & Fox, M. D. Network localization of hemichorea-hemiballismus. Neurology 86, 2187–2195 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. 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 

  93. Cotovio, G. et al. Mapping mania symptoms based on focal brain damage. J. Clin. Invest. 130, 5209–5222 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Cash, R. F. H. et al. Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: independent validation and evaluation of personalization. Biol. Psychiatry 86, e5–e7 (2019).

    Article  PubMed  Google Scholar 

  95. 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). This work is a recent test of whether different causal sources of information (lesion locations, non-invasive brain stimulation sites and invasive brain stimulation sites) map to a common brain circuit.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Baldermann, J. C. et al. Connectivity profile predictive of effective deep brain stimulation in obsessive-compulsive disorder. Biol. Psychiatry 85, 735–743 (2019).

    Article  PubMed  Google Scholar 

  97. Li, N. et al. A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nat. Commun. 11, 3364 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. 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 

  99. Kim, N. Y. et al. Lesions causing hallucinations localize to one common brain network. Mol. Psychiatry 26, 1299–1309 (2021).

    Article  PubMed  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  101. Darby, R. R., Laganiere, S., Pascual-Leone, A., Prasad, S. & Fox, M. D. Finding the imposter: brain connectivity of lesions causing delusional misidentifications. Brain 140, 497–507 (2017).

    Article  PubMed  Google Scholar 

  102. Snider, S. B. et al. Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem. Hum. Brain Mapp. 41, 1520–1531 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  103. Fischer, D. B. et al. A human brain network derived from coma-causing brainstem lesions. Neurology 87, 2427–2434 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  104. Joutsa, J., Shih, L. C. & Fox, M. D. Mapping Holmes tremor circuit using the human brain connectome. Ann. Neurol. 86, 812–820 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Darby, R. R., Joutsa, J., Burke, M. J. & Fox, M. D. Lesion network localization of free will. Proc. Natl Acad. Sci. USA 115, 10792–10797 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Darby, R. R., Horn, A., Cushman, F. & Fox, M. D. Lesion network localization of criminal behavior. Proc. Natl Acad. Sci. USA 115, 601–606 (2018).

    Article  CAS  PubMed  Google Scholar 

  107. Cohen, A. L. et al. Looking beyond the face area: lesion network mapping of prosopagnosia. Brain 142, 3975–3990 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  108. Cohen, A. L. et al. Tuber locations associated with infantile spasms map to a common brain network. Ann. Neurol. 89, 726–739 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  109. 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  CAS  PubMed  PubMed Central  Google Scholar 

  110. Horn, A. & Fox, M. D. Opportunities of connectomic neuromodulation. Neuroimage 221, 117180 (2020).

    Article  PubMed  Google Scholar 

  111. Bowren, M. et al. Post-stroke cognitive and motor outcomes predicted from lesion location and lesion network mapping. Brain https://doi.org/10.1093/brain/awac010 (2022).

    Article  PubMed  Google Scholar 

  112. Long, M. A. et al. Functional segregation of cortical regions underlying speech timing and articulation. Neuron 89, 1187–1193 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Ibayashi, K. et al. Focal cortical surface cooling is a novel and safe method for intraoperative functional brain mapping. World Neurosurg. 147, e118–e129 (2021).

    Article  PubMed  Google Scholar 

  114. Borchers, S., Himmelbach, M., Logothetis, N. & Karnath, H. O. Direct electrical stimulation of human cortex — the gold standard for mapping brain functions? Nat. Rev. Neurosci. 13, 63–70 (2011).

    Article  PubMed  CAS  Google Scholar 

  115. Winawer, J. & Parvizi, J. Linking electrical stimulation of human primary visual cortex, size of affected cortical area, neuronal responses, and subjective experience. Neuron 92, 1213–1219 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Parvizi, J. et al. Altered sense of self during seizures in the posteromedial cortex. Proc. Natl Acad. Sci. USA 118, e2100522118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Vesuna, S. et al. Deep posteromedial cortical rhythm in dissociation. Nature 586, 87–94 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Knecht, S. et al. Degree of language lateralization determines susceptibility to unilateral brain lesions. Nat. Neurosci. 5, 695–699 (2002).

    Article  CAS  PubMed  Google Scholar 

  119. Pascual-Leone, A., Gates, J. R. & Dhuna, A. Induction of speech arrest and counting errors with rapid-rate transcranial magnetic stimulation. Neurology 41, 697–702 (1991).

    Article  PubMed  Google Scholar 

  120. Lefaucheur, J. P. & Picht, T. The value of preoperative functional cortical mapping using navigated TMS. Neurophysiol. Clin. 46, 125–133 (2016).

    Article  PubMed  Google Scholar 

  121. Riva-Posse, P. et al. Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biol. Psychiatry 76, 963–969 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  122. Riva-Posse, P. et al. A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression. Mol. Psychiatry 23, 843–849 (2018).

    Article  CAS  PubMed  Google Scholar 

  123. Li, N. et al. A unified functional network target for deep brain stimulation in obsessive-compulsive disorder. Biol. Psychiatry 90, 701–713 (2021).

    Article  PubMed  Google Scholar 

  124. Nestor, S. M. & Blumberger, D. M. Mapping symptom clusters to circuits: toward personalizing TMS targets to improve treatment outcomes in depression. Am. J. Psychiatry 177, 373–375 (2020).

    Article  PubMed  Google Scholar 

  125. Robinson, R. G., Kubos, K. L., Starr, L. B., Rao, K. & Price, T. R. Mood disorders in stroke patients. Importance of location of lesion. Brain 107, 81–93 (1984).

    Article  PubMed  Google Scholar 

  126. Robinson, R. G. & Szetela, B. Mood change following left hemispheric brain injury. Ann. Neurol. 9, 447–453 (1981).

    Article  CAS  PubMed  Google Scholar 

  127. Bergman, H., Wichmann, T. & DeLong, M. R. Reversal of experimental parkinsonism by lesions of the subthalamic nucleus. Science 249, 1436–1438 (1990).

    Article  CAS  PubMed  Google Scholar 

  128. Parvizi, J. et al. Electrical stimulation of human fusiform face-selective regions distorts face perception. J. Neurosci. 32, 14915–14920 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Rangarajan, V. et al. Electrical stimulation of the left and right human fusiform gyrus causes different effects in conscious face perception. J. Neurosci. 34, 12828–12836 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Ganos, C. et al. A neural network for tics: insights from causal brain lesions and deep brain stimulation. Brain https://doi.org/10.1093/brain/awac009 (2022).

    Article  PubMed  Google Scholar 

  131. Reich, M. M. et al. A brain network for deep brain stimulation induced cognitive decline in Parkinson’s disease. Brain https://doi.org/10.1093/brain/awac012 (2022).

    Article  PubMed  Google Scholar 

  132. Hamilton, L. S., Oganian, Y., Hall, J. & Chang, E. F. Parallel and distributed encoding of speech across human auditory cortex. Cell 184, 4626–4639.e13 (2021).

    Article  CAS  PubMed  Google Scholar 

  133. Hamilton, L. S., Edwards, E. & Chang, E. F. A spatial map of onset and sustained responses to speech in the human superior temporal gyrus. Curr. Biol. 28, 1860–1871.e4 (2018).

    Article  CAS  PubMed  Google Scholar 

  134. Zhi, D., King, M. & Diedrichsen, J. Evaluating brain parcellations using the distance controlled boundary coefficient. Preprint at bioRxiv https://doi.org/10.1101/2021.05.11.443151 (2021).

    Article  Google Scholar 

  135. Warren, D. E. et al. Network measures predict neuropsychological outcome after brain injury. Proc. Natl Acad. Sci. USA 111, 14247–14252 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Eldaief, M. C., Halko, M. A., Buckner, R. L. & Pascual-Leone, A. Transcranial magnetic stimulation modulates the brain’s intrinsic activity in a frequency-dependent manner. Proc. Natl Acad. Sci. USA 108, 21229–21234 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Chen, A. C. et al. Causal interactions between fronto-parietal central executive and default-mode networks in humans. Proc. Natl Acad. Sci. USA 110, 19944–19949 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Ozdemir, R. A. et al. Individualized perturbation of the human connectome reveals reproducible biomarkers of network dynamics relevant to cognition. Proc. Natl Acad. Sci. USA 117, 8115–8125 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Gallen, C. L. & D’Esposito, M. Brain modularity: a biomarker of intervention-related plasticity. Trends Cogn. Sci. 23, 293–304 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  140. Chiu, D. et al. Multifocal transcranial stimulation in chronic ischemic stroke: a phase 1/2a randomized trial. J. Stroke Cerebrovasc. Dis. 29, 104816 (2020).

    Article  PubMed  Google Scholar 

  141. Brys, M. et al. Multifocal repetitive TMS for motor and mood symptoms of Parkinson disease: a randomized trial. Neurology 87, 1907–1915 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  142. Magsood, H., Syeda, F., Holloway, K., Carmona, I. C. & Hadimani, R. L. Safety study of combination treatment: deep brain stimulation and transcranial magnetic stimulation. Front. Hum. Neurosci. 14, 123 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Deng, Z., Lisanby, S. H. & Peterchev, A. V. in Annual Int. Conf. IEEE Engineering in Medicine and Biology 6821-6824 (IEEE, 2010).

  144. Tetreault, A. M. et al. Network localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer’s disease. Brain 143, 1249–1260 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  145. Kapur, N. Paradoxical functional facilitation in brain-behaviour research. A critical review. Brain 119, 1775–1790 (1996).

    Article  PubMed  Google Scholar 

  146. Carrera, E. & Tononi, G. Diaschisis: past, present, future. Brain 137, 2408–2422 (2014).

    Article  PubMed  Google Scholar 

  147. Sperber, C. Rethinking causality and data complexity in brain lesion-behaviour inference and its implications for lesion-behaviour modelling. Cortex 126, 49–62 (2020).

    Article  PubMed  Google Scholar 

  148. Griffis, J. C., Metcalf, N. V., Corbetta, M. & Shulman, G. L. Structural disconnections explain brain network dysfunction after stroke. Cell Rep. 28, 2527–2540.e9 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Klomjai, W., Katz, R. & Lackmy-Vallee, A. Basic principles of transcranial magnetic stimulation (TMS) and repetitive TMS (rTMS). Ann. Phys. Rehabil. Med. 58, 208–213 (2015).

    Article  PubMed  Google Scholar 

  150. Su, D. et al. Frequency-dependent effects of subthalamic deep brain stimulation on motor symptoms in Parkinson’s disease: a meta-analysis of controlled trials. Sci. Rep. 8, 14456 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  151. Radman, T., Ramos, R. L., Brumberg, J. C. & Bikson, M. Role of cortical cell type and morphology in subthreshold and suprathreshold uniform electric field stimulation in vitro. Brain Stimul. 2, 215–228 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  152. Feredoes, E., Heinen, K., Weiskopf, N., Ruff, C. & Driver, J. Causal evidence for frontal involvement in memory target maintenance by posterior brain areas during distracter interference of visual working memory. Proc. Natl Acad. Sci. USA 108, 17510–17515 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Duffley, G., Anderson, D. N., Vorwerk, J., Dorval, A. D. & Butson, C. R. Evaluation of methodologies for computing the deep brain stimulation volume of tissue activated. J. Neural Eng. 16, 066024 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  154. Thielscher, A., Antunes, A. & Saturnino, G. B. Field modeling for transcranial magnetic stimulation: a useful tool to understand the physiological effects of TMS? Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2015, 222–225 (2015).

    PubMed  Google Scholar 

  155. Raij, T. et al. Prefrontal cortex stimulation enhances fear extinction memory in humans. Biol. Psychiatry 84, 129–137 (2018).

    Article  PubMed  Google Scholar 

  156. Curot, J. et al. Awake craniotomy and memory induction through electrical stimulation: why are Penfield’s findings not replicated in the modern era? Neurosurgery 87, E130–E137 (2020).

    Article  PubMed  Google Scholar 

  157. Cole, E. J. et al. Stanford accelerated intelligent neuromodulation therapy for treatment-resistant depression. Am. J. Psychiatry 177, 716–726 (2020).

    Article  PubMed  Google Scholar 

  158. Maeda, F., Keenan, J. P., Tormos, J. M., Topka, H. & Pascual-Leone, A. Interindividual variability of the modulatory effects of repetitive transcranial magnetic stimulation on cortical excitability. Exp. Brain Res. 133, 425–430 (2000).

    Article  CAS  PubMed  Google Scholar 

  159. Brown, J. C. et al. NMDA receptor partial agonist, d-cycloserine, enhances 10 Hz rTMS-induced motor plasticity, suggesting long-term potentiation (LTP) as underlying mechanism. Brain Stimul. 13, 530–532 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  160. Minzenberg, M. J. & Leuchter, A. F. The effect of psychotropic drugs on cortical excitability and plasticity measured with transcranial magnetic stimulation: implications for psychiatric treatment. J. Affect. Disord. 253, 126–140 (2019).

    Article  CAS  PubMed  Google Scholar 

  161. Schaefer, A. et al. Local–global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cereb. Cortex 28, 3095–3114 (2018).

    Article  PubMed  Google Scholar 

  162. Yeo, B. 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 

  163. Gordon, E. M. et al. Generation and evaluation of a cortical area parcellation from resting-state correlations. Cereb. Cortex 26, 288–303 (2016).

    Article  PubMed  Google Scholar 

  164. Destrieux, C., Fischl, B., Dale, A. & Halgren, E. Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage 53, 1–15 (2010).

    Article  PubMed  Google Scholar 

  165. Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C. & Wager, T. D. Large-scale automated synthesis of human functional neuroimaging data. Nat. Methods 8, 665–670 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Laumann, T. O. et al. Functional system and areal organization of a highly sampled individual human brain. Neuron 87, 657–670 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  167. Gordon, E. M. et al. Precision functional mapping of individual human brains. Neuron 95, 791–807.e7 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Wang, D. et al. Parcellating cortical functional networks in individuals. Nat. Neurosci. 18, 1853–1860 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Hacker, C. D. et al. Resting state network estimation in individual subjects. Neuroimage 82, 616–633 (2013).

    Article  PubMed  Google Scholar 

  170. Cohen, A. L. & Fox, M. D. Reply: The influence of sample size and arbitrary statistical thresholds in lesion-network mapping. Brain 143, e41 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  171. Botvinik-Nezer, R. et al. Variability in the analysis of a single neuroimaging dataset by many teams. Nature 582, 84–88 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Salvalaggio, A. et al. Reply: Lesion network mapping predicts post-stroke behavioural deficits and improves localization. Brain 144, e36 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  173. Bergmann, T. O. et al. Concurrent TMS–fMRI for causal network perturbation and proof of target engagement. Neuroimage 237, 118093 (2021).

    Article  PubMed  Google Scholar 

  174. Golay, X., Hendrikse, J. & Lim, T. C. Perfusion imaging using arterial spin labeling. Top. Magn. Reson. Imaging 15, 10–27 (2004).

    Article  PubMed  Google Scholar 

  175. Fischl, B. FreeSurfer. Neuroimage 62, 774–781 (2012).

    Article  PubMed  Google Scholar 

  176. MacInnes, J. J., Dickerson, K. C., Chen, N. K. & Adcock, R. A. Cognitive neurostimulation: learning to volitionally sustain ventral tegmental area activation. Neuron 89, 1331–1342 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Bauer, C. C. C. et al. Real-time fMRI neurofeedback reduces auditory hallucinations and modulates resting state connectivity of involved brain regions: part 2: default mode network — preliminary evidence. Psychiatry Res. 284, 112770 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  178. Tarakad, A. & Jankovic, J. Anosmia and ageusia in Parkinson’s disease. Int. Rev. Neurobiol. 133, 541–556 (2017).

    Article  PubMed  Google Scholar 

  179. Williams, Z. M., Bush, G., Rauch, S. L., Cosgrove, G. R. & Eskandar, E. N. Human anterior cingulate neurons and the integration of monetary reward with motor responses. Nat. Neurosci. 7, 1370–1375 (2004).

    Article  CAS  PubMed  Google Scholar 

  180. Sheth, S. A. et al. Human dorsal anterior cingulate cortex neurons mediate ongoing behavioural adaptation. Nature 488, 218–221 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  181. Shine, J. M. et al. Distinct patterns of temporal and directional connectivity among intrinsic networks in the human brain. J. Neurosci. 37, 9667–9674 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Rafiei, F., Safrin, M., Wokke, M. E., Lau, H. & Rahnev, D. Transcranial magnetic stimulation alters multivoxel patterns in the absence of overall activity changes. Hum. Brain Mapp. 42, 3804–3820 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  183. Buzsáki, G., Anastassiou, C. A. & Koch, C. The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes. Nat. Rev. Neurosci. 13, 407–420 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  184. Granger, C. W. J. & Newbold, P. Forecasting Economic Time Series (Academic, 1977).

  185. Friston, K. J., Harrison, L. & Penny, W. Dynamic causal modelling. Neuroimage 19, 1273–1302 (2003).

    Article  CAS  PubMed  Google Scholar 

  186. Barnett, L., Barrett, A. B. & Seth, A. K. Misunderstandings regarding the application of Granger causality in neuroscience. Proc. Natl Acad. Sci. USA 115, E6676–E6677 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  187. Friston, K. Causal modelling and brain connectivity in functional magnetic resonance imaging. PLoS Biol. 7, e33 (2009).

    Article  PubMed  CAS  Google Scholar 

  188. Webb, J. T., Ferguson, M. A., Nielsen, J. A. & Anderson, J. S. BOLD granger causality reflects vascular anatomy. PLoS ONE 8, e84279 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  189. Granger, C. W. Time series analysis, cointegration, and applications. Am. Econ. Rev. 94, 421–425 (2004).

    Article  Google Scholar 

  190. Mehler, D. & Kording, K. The lure of causal statements: rampant mis-inference of causality in estimated connectivity. Preprint at https://arxiv.org/abs/1812.03363 (2018).

Download references

Acknowledgements

The authors thank the National Institute of Mental Health, the Brain and Behaviour Research Foundation, Brigham and Women’s Hospital, and Stanford University BioX for funding the present work.

Author information

Authors and Affiliations

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

    Shan H. Siddiqi & Michael D. Fox

  2. Department of Psychiatry, Harvard Medical School, Boston, MA, USA

    Shan H. Siddiqi

  3. Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA

    Konrad P. Kording

  4. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA, USA

    Josef Parvizi

  5. Department of Neurology, Harvard Medical School, Boston, MA, USA

    Michael D. Fox

Authors
  1. Shan H. Siddiqi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Konrad P. Kording
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Josef Parvizi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michael D. Fox
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.H.S and M.D.F. wrote the manuscript. The authors all researched data for the article, provided substantial contributions to discussion of its content, and reviewed and edited the manuscript before submission.

Corresponding author

Correspondence to Shan H. Siddiqi.

Ethics declarations

Competing interests

S.H.S. serves as a consultant for Kaizen Brain Center, Acacia Mental Health and Magnus Medical, and owns stock in Brainsway Inc. (publicly traded) and Magnus Medical (not publicly traded). S.H.S. and M.D.F. have jointly received investigator-initiated research support from Neuronetics Inc. None of these organizations were involved in the present work. S.H.S. and M.D.F. each own independent intellectual property on the use of brain network mapping to target neuromodulation. The present work did not utilize any of this intellectual property. The authors report no other conflicts of interest related to the present work.

Peer review

Peer review information

Nature Reviews Neuroscience thanks G. Hartwigsen, A. Kiyonaga 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.

Glossary

Causality gap

The missing logical link between correlation and causation, particularly as it relates to identifying treatment targets.

Deep brain stimulation

(DBS). An invasive technique for modulating brain activity using surgically implanted depth electrodes, commonly used as a treatment for Parkinson disease.

Transcranial magnetic stimulation

(TMS). A non-invasive technique for modulating brain activity via magnetic pulses applied over the scalp, commonly used as a treatment for major depressive disorder.

Functional neuroimaging

A non-invasive technique for measuring changes in brain activity, commonly based on changes in blood oxygenation or metabolic activity.

Causal inference

The process of assessing whether one event directly contributed to the occurrence of another event.

Counterfactual

The hypothetical outcome if a causal event had not occurred.

Causal chain

A sequence of events leading to a particular outcome.

Bradford Hill criteria

A widely used framework for objectively appraising the strength of causal inference based on observed data.

Randomized controlled trials

Research studies that randomly allocate clinical participants to active or control interventions.

Natural experiments

Observed situations in which an intervention was incidentally assigned in a near-random manner.

Symptom localization

The process by which a neurological or psychiatric problem is linked to a specific brain region.

Effective connectivity

The influence that one neural unit exerts over another.

Probabilistic causality

An approach that assesses whether an event modifies the probability of an outcome, even if it is not necessary or sufficient to induce the outcome.

Voxel lesion symptom mapping

(VLSM). A probabilistic technique that analyses the relationship between tissue damage and behaviour on a voxel-by-voxel basis.

Diaschisis

The phenomenon by which damage to one brain region can cause a change in function of distant regions.

Brain circuit

Any interconnected network of units, potentially including monosynaptic structural connections and/or polysynaptic functional connections.

Lesion network mapping

(LNM). A technique that identifies shared connectivity patterns among lesions associated with a specific symptom or behaviour.

Intracranial electrical stimulation

(iES). Invasive technique for modulating brain activity using depth electrodes or subdural electrodes, commonly used for mapping brain function prior to brain surgery.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Siddiqi, S.H., Kording, K.P., Parvizi, J. et al. Causal mapping of human brain function. Nat Rev Neurosci 23, 361–375 (2022). https://doi.org/10.1038/s41583-022-00583-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41583-022-00583-8

This article is cited by

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