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.

  • Opinion
  • Published:

The cortex as a central pattern generator

Abstract

Vertebrate spinal cord and brainstem central pattern generator (CPG) circuits share profound similarities with neocortical circuits. CPGs can produce meaningful functional output in the absence of sensory inputs. Neocortical circuits could be considered analogous to CPGs as they have rich spontaneous dynamics that, similar to CPGs, are powerfully modulated or engaged by sensory inputs, but can also generate output in their absence. We find compelling evidence for this argument at the anatomical, biophysical, developmental, dynamic and pathological levels of analysis. Although it is possible that cortical circuits are particularly plastic types of CPG ('learning CPGs'), we argue that present knowledge about CPGs is likely to foretell the basic principles of the organization and dynamic function of cortical circuits.

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

Access options

Buy this article

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

Figure 1: Similarities between vertebrate central pattern generators and neocortical circuits.

Similar content being viewed by others

References

  1. Sherrington, C. S. The Integrative Action of the Nervous System (Yale Univ. Press, New York, 1948).

    Google Scholar 

  2. Hartline, H. K. The response of single optic nerve fibres of the vertebrate eye to illumination of the retina. Am. J. Physiol. 121, 400–415 (1938).

    Article  Google Scholar 

  3. Llinás, R. I of the Vortex: From Neurons to Self (MIT Press, Cambridge, Massachusetts, 2002).

    Google Scholar 

  4. Brown, G. On the nature of the fundamental activity of the nervous centres; together with an analysis of the conditioning of rhythmic activity in progression, and a theory of the evolution of function in the nervous system. J. Physiol. (Lond.) 49, 18–46 (1914).

    Article  Google Scholar 

  5. Sherrington, C. S. Inhibition as a Coordinative Factor (Nobel Lecture) [online] http://nobelprize.org/medicine/laureates/1932/sherrington-lecture.html (12 December 1932).

    Google Scholar 

  6. Grillner, S. & Zangger, P. How detailed is the central pattern generation for locomotion? Brain Res. 88, 367–371 (1975).

    Article  CAS  PubMed  Google Scholar 

  7. Selverston, A. General principles of rhythmic motor pattern generation derived from invertebrate CPGs. Prog. Brain Res. 123, 247–257 (1999).

    Article  CAS  PubMed  Google Scholar 

  8. Harris-Warrick, R. M. & Marder, E. Modulation of neural networks for behavior. Annu. Rev. Neurosci. 14, 39–57 (1991).

    Article  CAS  PubMed  Google Scholar 

  9. Marder, E. & Calabrese, R. L. Principles of rhythmic motor pattern generation. Physiol. Rev. 76, 687–717 (1996).

    Article  CAS  PubMed  Google Scholar 

  10. Kiehn, O. & Butt, S. J. Physiological, anatomical and genetic identification of CPG neurons in the developing mammalian spinal cord. Prog. Neurobiol. 70, 347–361 (2003).

    Article  CAS  PubMed  Google Scholar 

  11. Grillner, S. The motor infrastructure: from ion channels to neuronal networks. Nature Rev. Neurosci. 4, 573–586 (2003).

    Article  CAS  Google Scholar 

  12. Lansner, A., Ekeberg, Ö. & Grillner, S. in Neurons, Networks, and Motor Behavior (eds Stein, P. S. G., Grillner, S., Selverston, A. I. & Stuart, D. G.) 165–171 (MIT Press, Cambridge, Massachusetts, 1997).

    Google Scholar 

  13. Smith, J. C. in Neurons, Networks, and Motor Behavior (eds Stein, P. S. G., Grillner, S., Selverston, A. I. & Stuart, D. G.) 97–104 (MIT Press, Cambridge, Massachusetts, 1997).

    Google Scholar 

  14. Smith, J. C., Ellenberger, H. H., Ballanyi, K., Richter, D. W. & Feldman, J. L. Pre-Bötzinger complex: a brainstem region that may generate respiratory rhythm in mammals. Science 254, 726–729 (1991).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Reckling, J. C. & Feldman, J. L. PreBötzinger complex: hypothetical site and kernel for respiratory rhythm generation. Ann. Rev. Physiol. 60, 385–405 (1998).

    Article  Google Scholar 

  16. Koshiya, N. & Smith, J. C. Neuronal pacemaker for breathing visualized in vitro. Nature 400, 360–363 (1999).

    Article  CAS  PubMed  Google Scholar 

  17. Richter, D. W. & Spyer, M. Studying rhythmogenesis of breathing: comparison of in vivo and in vitro models. Trends Neurosci. 24, 464–472 (2001).

    Article  CAS  PubMed  Google Scholar 

  18. Ramón y Cajal, S. La Textura del Sistema Nerviosa del Hombre y los Vertebrados 1st edn (Moya, Madrid, 1899).

    Google Scholar 

  19. Lorente de Nó, R. La corteza cerebral del ratón. Trab. Lab. Invest. Bio. (Madrid) 20, 41–78 (1922).

    Google Scholar 

  20. Douglas, R. J., Martin, K. A. C. & Markram, H. in The Synaptic Organization of the Brain (ed. Shepherd, G. M.) 499–558 (Oxford Univ. Press, Oxford, UK, 2004).

    Book  Google Scholar 

  21. Kalisman, N., Silberberg, G. & Markram, H. The neocortical microcircuit as a tabula rasa. Proc. Natl Acad. Sci. USA 102, 880–885 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Gilbert, C. & Wiesel, T. N. Morphology and intracortical projections of functionally characterised neurons in the cat visual cortex. Nature 280, 120–125 (1979).

    Article  CAS  PubMed  Google Scholar 

  23. Somogyi, P., Tamas, G., Lujan, R. & Buhl, E. Salient features of synaptic organisation in the cerebral cortex. Brain Res. Brain Res. Rev. 26, 113–135 (1998).

    Article  CAS  PubMed  Google Scholar 

  24. Kozloski, J., Hamzei-Sichani, F. & Yuste, R. Stereotyped position of local synaptic targets in neocortex. Science 293, 868–872 (2001).

    Article  CAS  PubMed  Google Scholar 

  25. Silberberg, G., Gupta, A. & Markram, H. Stereotypy in neocortical microcircuits. Trends Neurosci. 25, 227–230 (2002).

    Article  CAS  PubMed  Google Scholar 

  26. Lorente de Nó, R. Studies on the structure of the cerebral cortex. J. Psychol. Neurol. 45, 381–438 (1932).

    Google Scholar 

  27. Lorente de Nó, R. in Physiology of the Nervous System (ed. Fulton, J. F.) 228–330 (Oxford Univ. Press, New York, 1949).

    Google Scholar 

  28. Douglas, R. J. & Martin, K. A. C. Neuronal circuits in the neocortex. Annu. Rev. Neurosci. 27, 419–451 (2004).

    Article  CAS  PubMed  Google Scholar 

  29. Ahmed, B., Anderson, J. C., Douglas, R. J., Martin, K. A. C. & Nelson, J. C. Polyneuronal innervation of spiny stellate neurons in cat visual cortex. J. Comp. Neurol. 341, 39–49 (1994).

    Article  CAS  PubMed  Google Scholar 

  30. Lorente de Nó, R. Analysis of the activity of the chains of internuncial neurons. J. Neurophysiol. 1, 207–244 (1938).

    Article  Google Scholar 

  31. Butera, R. J., Rinzel, J. & Smith, J. C. Models of respiratory rhythm generation in the pre-Bötzinger complex. II. Populations of coupled pacemaker neurons. J. Neurophysiol. 82, 398–415 (1999).

    Article  PubMed  Google Scholar 

  32. Butera, R. J., Rinzel, J. & Smith, J. C. Models of respiratory rhythm generation in the pre-Bötzinger complex. I. Bursting pacemaker neurons. J. Neurophysiol. 82, 382–397 (1999).

    Article  PubMed  Google Scholar 

  33. Shah, M. M. & Haylett, D. G. K+ currents generated by NMDA receptor activation in rat hippocampal pyramidal neurons. J. Neurophysiol. 87, 2983–2989 (2002).

    Article  CAS  PubMed  Google Scholar 

  34. Pena, F., Parkis, M. A. & Ramirez, J. M. Differential contribution of pacemaker properties to the generation of respiratory rhythms during normoxia and hypoxia. Neuron 43, 105–117 (2004).

    Article  CAS  PubMed  Google Scholar 

  35. Steriade, M., Jones, E. G. & Llinás, R. R. Thalamic Oscillations and Signaling 431 (John Wiley & Sons, Somerset, Chichester, 1990).

    Google Scholar 

  36. Gray, C. M., Konig, P., Engel, A. K. & Singer, W. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338, 334–337 (1989).

    Article  CAS  PubMed  Google Scholar 

  37. Crick, F. & Koch, C. Some reflections on visual awareness. Cold Spring Harbor Symp. Quant. Biol. 55, 953–962 (1990).

    Article  CAS  PubMed  Google Scholar 

  38. Jeanmonod, D. et al. Neuropsychiatric thalamocortical dysrhythmia: surgical implications. Neurosurg. Clin. N. Am. 14, 251–265 (2003).

    Article  CAS  PubMed  Google Scholar 

  39. Engel, A. K., Fries, P. & Singer, W. Dynamic predictions: oscillations and synchrony in top-down processing. Nature Rev. Neurosci. 2, 704–716 (2001).

    Article  CAS  Google Scholar 

  40. Parkis, M. A., Feldman, J. L., Robinson, D. M. & Funk, G. D. Oscillations in endogeneous input to neurons affect excitability and signal processing. J. Neurosci. 23, 8152–8158 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Hellgren-Kotaleski, J., Grillner, S. & Lansner, A. Neural mechanisms potentially contributing to the intersegmental phase lag in lamprey. I. Segmental oscillations dependent on reciprocal inhibition. Biol. Cybern. 81, 317–330 (1999).

    Article  Google Scholar 

  42. Cangiano, L. & Grillner, S. Fast and slow locomotor burst generation in the hemispinal cord of the lamprey. J. Neurophysiol. 89, 2931–2942 (2003).

    Article  CAS  PubMed  Google Scholar 

  43. Buzsaki, G. & Chrobak, J. J. Temporal structure in spatially organized neuronal ensembles: a role for interneuron networks. Curr. Opin. Neurobiol. 5, 504–510 (1995).

    Article  CAS  PubMed  Google Scholar 

  44. Klausberger, T. et al. Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature 421, 844–848 (2003).

    Article  CAS  PubMed  Google Scholar 

  45. Fuhrmann, G., Segev, I., Markram, H. & Tsodyks, M. Coding of temporal information by activity dependent synapses. J. Neurophysiol. 87, 140–148 (2002).

    Article  PubMed  Google Scholar 

  46. van Vreeswijk, C. & Hansel, D. Patterns of synchrony in neural networks with spike adaptation. Neural Comput. 13, 959–992 (2001).

    Article  CAS  PubMed  Google Scholar 

  47. Fransén, E. & Lansner, A. Low spiking rates in a population of mutually exciting pyramidal cells. Network Comput. Neural Sys. 6, 271–288 (1995).

    Article  Google Scholar 

  48. Gutnick, M. J., Connors, B. W. & Prince, D. A. Mechanisms of neocortical epileptogenesis in vitro. J. Neurophysiol. 48, 1321–1335 (1982).

    Article  CAS  PubMed  Google Scholar 

  49. Cowley, A. & Schmidt, B. J. Effects of inhibitory amino acid antagonists on reciprocal inhibitory interactions during rhythmic motor activity in the in vitro neonatal rat spinal cord. J. Neurophysiol. 74, 1109–1117 (1995).

    Article  CAS  PubMed  Google Scholar 

  50. Wilson, C. J. & Groves, P. M. Spontaneous firing patterns of identified spiny neurons in the rat neostriatum. Brain Res. 220, 67–80 (1981).

    Article  CAS  PubMed  Google Scholar 

  51. Steriade, M., Nunez, A. & Amzica, F. A novel slow (1Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. J. Neurosci. 13, 3252–3265 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Cowan, R. L. & Wilson, C. J. Spontaneous firing patterns and axonal projections of single corticostriatal neurons in the rat medial agranular cortex. J. Neurophysiol. 71, 17–32 (1994).

    Article  CAS  PubMed  Google Scholar 

  53. Sanchez-Vives, M. & McCormick, D. Cellular and network mechanisms of rhythmic recurrent activity in neocortex. Nature Neurosci. 3, 1027–1034 (2000).

    Article  CAS  PubMed  Google Scholar 

  54. Cossart, R., Aronov, D. & Yuste, R. Attractor dynamics of network UP states in neocortex. Nature 423, 283–289 (2003).

    Article  CAS  PubMed  Google Scholar 

  55. Egorov, A. V., Hamam, B. N., Fransen, E., Hasselmo, M. E. & Alonso, A. A. Graded persistent activity in entorhinal cortex neurons. Nature 420, 173–178 (2002).

    Article  CAS  PubMed  Google Scholar 

  56. Shu, Y., Hasenstaub, A. & McCormick, D. A. Turning on and off recurrent balanced cortical activity. Nature 423, 288–293 (2003).

    Article  CAS  PubMed  Google Scholar 

  57. Anderson, J., Lampl, I., Reichova, I., Carandini, M. & Ferster, D. Stimulus dependence of two-state fluctuations of membrane potential in cat visual cortex. Nature Neurosci. 3, 617–621 (2000).

    Article  CAS  PubMed  Google Scholar 

  58. Del Negro, C. N., Koshiya, N., Butera, R. J. & Smith, J. C. Persistent sodium current, membrane properties, and bursting behavior of pre-Bötzinger complex inspiratory neurons in vitro. J. Neurophysiol. 88, 2242–2250 (2002).

    Article  CAS  PubMed  Google Scholar 

  59. Mao, B. Q., Hamzei-Sichani, F., Aronov, D., Froemke, R. C. & Yuste, R. Dynamics of spontaneous activity in neocortical slices. Neuron 32, 883–898 (2001).

    Article  CAS  PubMed  Google Scholar 

  60. Llinás, R. R. The intrinsic electrophysiological properties of mammalian neurons: insights into central nervous system function. Science 242, 1654–1664 (1988).

    Article  PubMed  Google Scholar 

  61. Raman, I. & Bean, B. P. Ionic currents underlying spontaneous action potentials in isolated cerebellar Purkinje neurons. J. Neurosci. 19, 1663–1674 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Hopfield, J. J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl Acad. Sci. USA 79, 2554–2558 (1982).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Hopfield, J. J. & Tank, D. W. Computing with neural circuits: a model. Science 233, 625–633 (1986).

    Article  CAS  PubMed  Google Scholar 

  64. Ben-Yishai, R., Lev Bar-Or, R. & Sompolinsky, H. Orientation tuning by recurrent neural networks in visual cortex. Proc. Natl Acad. Sci. USA. 92, 3844–3848 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Seung, H. S., Lee, D. D., Reis, B. Y. & Tank, D. W. Stability of the memory of eye position in a recurrent network of conductance-based model neurons. Neuron 26, 259–271 (2000).

    Article  CAS  PubMed  Google Scholar 

  66. Durstewitz, D., Seamans, J. K. & Sejnowski, T. J. Neurocomputational models of working memory. Nature Neurosci. 3 (Suppl.), 1184–1191 (2000).

    Article  CAS  PubMed  Google Scholar 

  67. Sandberg, A., Lansner, A., Petersson, K. & Ekeberg, O. A Bayesian attractor network with incremental learning. Network 13, 179–194 (2002).

    Article  CAS  PubMed  Google Scholar 

  68. Hebb, D. O. The Organization of Behaviour (Wiley, New York, 1949).

    Google Scholar 

  69. Lansner, A., Fransén, E. & Sandberg, A. Cell assembly dynamics in detailed and abstract attractor models of cortical associative memory. Theor. Biosci. 122, 19–36 (2003).

    Article  Google Scholar 

  70. Lehmann, D., Strik, W. K., Henggeler, B., Koenig, T. & Koukkou, M. Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: 1. Visual imagery and abstract thoughts. Int. J. Psychophysiol. 29, 1–11 (1998).

    Article  CAS  PubMed  Google Scholar 

  71. Abeles, M., Bergman, H., Margalit, E. & Vaadia, E. Spatiotemporal firing patterns in the frontal cortex of behaving monkeys. J. Neurophysiol. 70, 1629–1638 (1993).

    Article  CAS  PubMed  Google Scholar 

  72. Ikegaya, Y. et al. Synfire chains and cortical songs: temporal modules of cortical activity. Science 304, 559–564 (2004).

    Article  CAS  PubMed  Google Scholar 

  73. Schmidt, B. J. & Jordan, L. M. The role of serotonin in reflex modulation and locomotor rhythm production in the mammalian spinal cord. Brain Res. Bull. 53, 689–710 (2000).

    Article  CAS  PubMed  Google Scholar 

  74. Feldman, J. L., Mitchell, G. S. & Nattie, E. E. Breathing: rhythmicity, plasticity, chemosensitivity. Annu. Rev. Neurosci. 26, 239–266 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Goldman-Rakic, P. S. Cellular basis of working memory. Neuron 14, 477–485 (1995).

    Article  CAS  PubMed  Google Scholar 

  76. McNamara, J. Emerging insights into the genesis of epilepsy. Nature 399, A15–A22 (1999).

    Article  CAS  PubMed  Google Scholar 

  77. Ruscheweyh, R. & Sandkuhler, J. Epileptiform activity in rat spinal dorsal horn in vitro has common features with neuropathic pain. Pain 105, 327–338 (2003).

    Article  PubMed  Google Scholar 

  78. Van Den Pol, A. N., Obrietan, K. & Belousov, A. Glutamate hyperexcitability and seizure-like activity throughout the brain and spinal cord upon relief from chronic glutamate receptor blockade in culture. Neuroscience 74, 653–674 (1996).

    Article  CAS  PubMed  Google Scholar 

  79. Wiesel, T. N. Postnatal development of the visual cortex and the influence of the environment. Nature 299, 583–592 (1982).

    Article  CAS  PubMed  Google Scholar 

  80. Yuste, R. & Majewska, A. On the function of dendritic spines. Neuroscientist 7, 387–395 (2001).

    Article  CAS  PubMed  Google Scholar 

  81. Cameron, W. E., Averill, D. B. & Berger, A. J. Morphology of cat phrenic motoneurons as revealed by intracellular injection of horseradish peroxidase. J. Comp. Neurol. 219, 70–80 (1983).

    Article  CAS  PubMed  Google Scholar 

  82. Semba, K. et al. Ultrastructure of pacinian corpuscle primary afferent terminals in the cat spinal cord. Brain Res. 302, 135–150 (1984).

    Article  CAS  PubMed  Google Scholar 

  83. Maass, W., Natschlager, T. & Markram, H. Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput. 14, 2531–2560 (2003).

    Article  Google Scholar 

  84. Jaeger, H. & Haas, H. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science 304, 78–80 (2004).

    Article  CAS  PubMed  Google Scholar 

  85. Katz, L. C. & Shatz, C. J. Synaptic activity and the construction of cortical circuits. Science 274, 1133–1138 (1996).

    Article  CAS  PubMed  Google Scholar 

  86. Kandel, E. R., Schwartz, J. H. & Jessell, T. M. Principles of Neural Science (Elsevier, New York, 1991).

    Google Scholar 

  87. Carew, T. J., Hawkins, R. D., Abrams, T. W. & Kandel, E. R. A test of Hebb's postulate at identified synapses which mediate classical conditioning in Aplysia. J. Neurosci. 4, 1217–1224 (1984).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Ji, R., Kohno, T., Moore, K. & Woolf, C. J. Central sensitization and LTP: do pain and memory share similar mechanisms? Trends Neurosci. 26, 696–705 (2003).

    Article  CAS  PubMed  Google Scholar 

  89. Tsuchida, T. et al. Topographic organization of embryonic motor neurons defined by expression of LIM homeobox genes. Cell 79, 957–970 (1994).

    Article  CAS  PubMed  Google Scholar 

  90. Toledo-Rodriguez, M. et al. Correlation maps allow neuronal electrical properties to be predicted from single-cell gene expression profiles in rat neocortex. Cereb. Cortex 14, 1310–1327 (2004).

    Article  PubMed  Google Scholar 

  91. Winfree, A. T. The Geometry of Biological Time (Springer, New York, 2001).

    Book  Google Scholar 

  92. Glass, L. & Mackey, M. C. From Clocks to Chaos. The Rhythms of Life (Princeton Univ. Press, New Jersey, 1988).

    Book  Google Scholar 

  93. Netoff, T. I. et al. Synchronization in hybrid neuronal networks of the hippocampal formation. J. Neurophysiol. 93, 1197–1208 (2005).

    Article  PubMed  Google Scholar 

  94. Fiedler, B. (ed.) Handbook of Dynamical Systems (Elsevier, New York, 2002).

    Google Scholar 

  95. Pinsky, P. F. & Rinzel, J. Intrinsic and network rhythmogenesis in a reduced Traub model for CA3 neurons. J. Comput. Neurosci. 1, 39–60 (1994).

    Article  CAS  PubMed  Google Scholar 

  96. Pinto, D. J., Jones, S. R., Kaper, T. J. & Kopell, N. Analysis of state-dependent transitions in frequency and long-distance coordination in a model oscillatory cortical circuit. J. Comput. Neurosci. 15, 283–298 (2003).

    Article  PubMed  Google Scholar 

  97. Rieke, F., Warland, D., de Ruyter van Steveninck, R. & Bialek, W. Spikes, Exploring the Neural Code (MIT Press, Cambridge, Massachusetts, 1997).

    Google Scholar 

  98. Gold, J. I. & Shadlen, M. N. Banburismus and the brain: decoding the relationship between sensory stimuli, decisions, and reward. Neuron 36, 299–308 (2002).

    Article  CAS  PubMed  Google Scholar 

  99. Barlow, H. Redundancy reduction revisited. Network 12, 241–253 (2001).

    Article  CAS  PubMed  Google Scholar 

  100. Raymond, J. E., Shapiro, K. L. & Arnell, K. M. Temporary suppression of visual processing in an RSVP task: an attentional blink? J. Exp. Psychol. Hum. Percept. Perform. 18, 849–860 (1992).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This review resulted from the 2004 Dahlem Workshop entitled 'Microcircuits: the interface between neurons and global brain function'. We thank the organizers and co-participants in this workshop for their input, and the anonymous reviewers for their constructive criticisms. Work in our laboratories is supported by the Kavli Institute for Brain Science (R.Y.), the National Institutes of Health (R.Y., J.N.M. and J.S.) and the Swedish Science Council (A.L.).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rafael Yuste.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

Related links

FURTHER INFORMATION

Lansner's homepage

Smith's homepage

Yuste's homepage

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yuste, R., MacLean, J., Smith, J. et al. The cortex as a central pattern generator. Nat Rev Neurosci 6, 477–483 (2005). https://doi.org/10.1038/nrn1686

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrn1686

This article is cited by

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