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.

Accumbal D2 cells orchestrate innate risk-avoidance according to orexin signals

An Author Correction to this article was published on 05 June 2018

This article has been updated

Abstract

Excitation of accumbal D2 cells governs vital actions, including avoidance of learned risks, but the origins of this excitation and roles of D2 cells in innate risk-avoidance are unclear. Hypothalamic neurons producing orexins (also called hypocretins) enhance innate risk-avoidance via poorly understood neurocircuits. We describe a direct orexin→D2 excitatory circuit and show that D2 cell activity is necessary for orexin-dependent innate risk-avoidance in mice, thus revealing an unsuspected hypothalamus–accumbens interplay in action selection.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Functional evidence for orexinLH→D2NAc excitation.
Fig. 2: Anatomical evidence for a direct orexinLH→D2NAc circuit.
Fig. 3: Combinatorial probing of roles of D2NAc and orexin cells in risk-avoidance.

Change history

  • 05 June 2018

    In the version of this article initially published, a sentence in the third paragraph read, “Suppression of natural orexin signaling by orexin receptor antagonism (Fig. 3b–e) led to increased risk-avoidance behaviors.” “Increased” has been changed to “decreased” in this sentence. The error has been corrected in the HTML and PDF versions of the article.

References

  1. 1.

    Sakurai, T. Nat. Rev. Neurosci. 15, 719–731 (2014).

    Article  PubMed  CAS  Google Scholar 

  2. 2.

    Giardino, W. J. & de Lecea, L. Curr. Opin. Neurobiol. 29, 103–108 (2014).

    Article  PubMed  CAS  Google Scholar 

  3. 3.

    González, J. A., Iordanidou, P., Strom, M., Adamantidis, A. & Burdakov, D. Nat. Commun. 7, 11395 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. 4.

    Peyron, C. et al. J. Neurosci. 18, 9996–10015 (1998).

    Article  PubMed  CAS  Google Scholar 

  5. 5.

    Maner, J. K. & Schmidt, N. B. Behav. Ther. 37, 181–189 (2006).

    Article  PubMed  Google Scholar 

  6. 6.

    Johnson, P. L. et al. Nat. Med. 16, 111–115 (2010).

    Article  PubMed  CAS  Google Scholar 

  7. 7.

    Suzuki, M., Beuckmann, C. T., Shikata, K., Ogura, H. & Sawai, T. Brain Res. 1044, 116–121 (2005).

    Article  PubMed  CAS  Google Scholar 

  8. 8.

    Bonnavion, P., Jackson, A. C., Carter, M. E. & de Lecea, L. Nat. Commun. 6, 6266 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. 9.

    Heydendael, W., Sengupta, A., Beck, S. & Bhatnagar, S. Physiol. Behav. 130, 182–190 (2014).

    Article  PubMed  CAS  Google Scholar 

  10. 10.

    Zalocusky, K. A. et al. Nature 531, 642–646 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. 11.

    Nicola, S. M., Surmeier, J. & Malenka, R. C. Annu. Rev. Neurosci. 23, 185–215 (2000).

    Article  PubMed  CAS  Google Scholar 

  12. 12.

    Kupchik, Y. M. et al. Nat. Neurosci. 18, 1230–1232 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. 13.

    Koós, T. & Tepper, J. M. Nat. Neurosci. 2, 467–472 (1999).

    Article  PubMed  Google Scholar 

  14. 14.

    Harris, G. C., Wimmer, M. & Aston-Jones, G. Nature 437, 556–559 (2005).

    Article  PubMed  CAS  Google Scholar 

  15. 15.

    Mahler, S. V., Moorman, D. E., Smith, R. J., James, M. H. & Aston-Jones, G. Nat. Neurosci. 17, 1298–1303 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. 16.

    Gangarossa, G. et al. Front. Neural Circuits 7, 22 (2013).

    PubMed  PubMed Central  Google Scholar 

  17. 17.

    Mori, A., Shindou, T., Ichimura, M., Nonaka, H. & Kase, H. J. Neurosci. 16, 605–611 (1996).

    Article  PubMed  CAS  Google Scholar 

  18. 18.

    Matsuki, T. et al. Proc. Natl. Acad. Sci. USA 106, 4459–4464 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Schöne, C. et al. J. Neurosci. 32, 12437–12443 (2012).

    Article  PubMed  CAS  Google Scholar 

  20. 20.

    Apergis-Schoute, J. et al. J. Neurosci. 35, 5435–5441 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. 21.

    Planert, H., Berger, T. K. & Silberberg, G. PLoS One 8, e57054 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. 22.

    Gertler, T. S., Chan, C. S. & Surmeier, D. J. J. Neurosci. 28, 10814–10824 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. 23.

    Kawaguchi, Y. J. Neurosci. 13, 4908–4923 (1993).

    Article  CAS  Google Scholar 

  24. 24.

    Kawaguchi, Y., Wilson, C. J., Augood, S. J. & Emson, P. C. Trends Neurosci. 18, 527–535 (1995).

    Article  PubMed  CAS  Google Scholar 

  25. 25.

    Saddoris, M. P., Cacciapaglia, F., Wightman, R. M. & Carelli, R. M. J. Neurosci. 35, 11572–11582 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. 26.

    Alderson, H. L., Parkinson, J. A., Robbins, T. W. & Everitt, B. J. Psychopharmacology (Berl.) 153, 455–463 (2001).

    Article  CAS  Google Scholar 

  27. 27.

    van der Plasse, G., Schrama, R., van Seters, S. P., Vanderschuren, L. J. & Westenberg, H. G. PLoS One 7, e33455 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. 28.

    Vélez-Fort, M. et al. Neuron 83, 1431–1443 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. 29.

    Wickersham, I. R. et al. Neuron 53, 639–647 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. 30.

    Wall, N. R., Wickersham, I. R., Cetin, A., De La Parra, M. & Callaway, E. M. Proc. Natl. Acad. Sci. USA 107, 21848–21853 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Schöne, C., Apergis-Schoute, J., Sakurai, T., Adamantidis, A. & Burdakov, D. Cell Rep. 7, 697–704 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. 32.

    Blomeley, C. P., Cains, S. & Bracci, E. Front. Cell. Neurosci. 9, 453 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. 33.

    Smart, D. et al. Br. J. Pharmacol. 132, 1179–1182 (2001).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. 34.

    Adamantidis, A. R., Zhang, F., Aravanis, A. M., Deisseroth, K. & de Lecea, L. Nature 450, 420–424 (2007).

    Article  PubMed  CAS  Google Scholar 

  35. 35.

    Karnani, M. M. et al. Neuron 72, 616–629 (2011).

    Article  PubMed  CAS  Google Scholar 

  36. 36.

    Prut, L. & Belzung, C. Eur. J. Pharmacol. 463, 3–33 (2003).

    Article  PubMed  CAS  Google Scholar 

  37. 37.

    Walsh, R. N. & Cummins, R. A. Psychol. Bull. 83, 482–504 (1976).

    Article  PubMed  CAS  Google Scholar 

  38. 38.

    Dent, C. L., Isles, A. R. & Humby, T. Eur. J. Neurosci. 39, 520–530 (2014).

    Article  PubMed  Google Scholar 

  39. 39.

    Fendt, M., Endres, T., Lowry, C. A., Apfelbach, R. & McGregor, I. S. Neurosci. Biobehav. Rev. 29, 1145–1156 (2005).

    Article  PubMed  CAS  Google Scholar 

  40. 40.

    Yang, H. et al. Nat. Neurosci. 19, 283–289 (2016).

    Article  PubMed  CAS  Google Scholar 

  41. 41.

    Whiddon, B. B. & Palmiter, R. D. J. Neurosci. 33, 2009–2016 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. 42.

    González, J. A. et al. Curr. Biol. 26, 2486–2491 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

This work was funded by The Francis Crick Institute, which receives its core funding from Cancer Research UK, the UK Medical Research Council and the Wellcome Trust.

Author information

Affiliations

Authors

Contributions

C.B. and C.G. (equal contributors) designed and performed experiments and analyzed data; D.B. designed experiments, obtained funding and wrote the paper.

Corresponding author

Correspondence to Denis Burdakov.

Ethics declarations

Competing interests

The authors have no competing interests.

Additional information

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

Integrated Supplementary Information

Supplementary Figure 1 Supplementary optogenetic and electrophysiological data

A. Studying electrical properties of NAc D2 neurons. Top: recording schematic. Bottom: classical electrophysiological dynamics (responses to current injections, purple) used to identify NAc D2R neurons (performed in every cell studied). B. Left: effect of bath-application of dopamine (40 mM) on D2 cell membrane potential responses to excitatory current injection (purple). Representative example of n = 8/8 cells (all cells responded). Right: group data (means±sem) illustrating inhibition of the evoked spiking for dopamine, n = 8 cells. C. Top: targeting scheme for studying responses of NAc NPY interneurons to photo-stimulation of LH orexin cells. Bottom: Expression of ChR2 in the LH (typical example of n = 5 brains). D. Top: recording schematic for studying LH orexin-->NAc NPY circuit. Bottom: confirmation that NAc NPY-eGFP neurons display defining electrical signatures of NAc NPY interneurons (response to current injection, purple, performed in every cell studied). E. Effect of orexin axon photostimulation on NAc NPY interneuron membrane potential (left) and current (right), in the presence of orexin receptor antagonists TCS/SB (see Supplementary Methods). Representative responses of n = 11 cells. F. Effect of low-frequency (1 Hz) orexin cell stimulation of NAc D2 cells (individual flash is shown here; this effect is representative of all flashes in the 1 Hz 10 s train), revealing a low-probability (n = 13/64 cells), CNQX-sensitive input.

Supplementary Figure 2 Supplementary data relating to cell-type-specific LH→NAc functional connectivity mapping

A, B. Probing orexin cell→D1 cell interaction. A,Targeting strategy (top) and resulting expression of mCherry (red) in LH (bottom), representative example of n = 5 brains showing expression localization typical of orexin cells. B, Recording scheme (top), and effects of low and high frequency orexin axon photo-stimulation on D1 cells (representative example of n = 48 neurons, 48/48 cells showed no detectable responses). C, D. Probing MCH→D2 cell interaction. C, Targeting strategy (top) and resulting expression of mCherry (red) in LH (bottom), representative example of n = 5 brains showing expression localization typical of MCH cells. D, Recording scheme (top), and effects of low and high frequency MCH axon photo-stimulation on D2 cells (representative example of n = 24 neurons, 24/24 cells showed no detectable responses).

Supplementary Figure 3 Probing sufficiency of NAc orexin for innate risk-avoidance behaviors

A. Experimental paradigm: orexin or control vehicle solutions were infused bilaterally into accumbens via implanted cannulae, followed by behavioral assays, see Supplementary Methods. B. Effect of orexin on center preference in the open-field test. Left and center, examples of spatial exploration heatmaps from the same mouse infused with orexin or vehicle solutions. Right, effect of orexin or vehicle infusion on centre occupancy (% time during the first 15 min of arena exploration) in n = 10 mice. P value is from a two-tailed paired t test, t = 3.545 df = 9. In the same tests, orexin did not significantly affect locomotion velocity (vehicle = 7.24+/-3.5 cm/sec; orexin = 6.04+/-0.96 cm/s; p = 0.176 by two-tailed paired t-test, t=1.468 df=9). C. Effect of orexin on hesitation in the PORT test. Left and center, examples of spatial exploration heatmaps from the same mouse infused with orexin or vehicle solutions. Right, effect of orexin or vehicle infusion on hesitation to entry of middle (odor) chamber in n = 10 mice. P value is from a two-tailed paired t test, t = 4.281 df = 9.

Supplementary Figure 4 Effect of NAc D2 cell chemogenetic excitation on innate risk-avoidance behavior, and control experiments ruling out locomotor sedation as a confounding factor in open field experiments

A. Left, targeting scheme for hM3Dq-mCherry; Right, localization of hM3Dq –mCherry (red); ac = anterior commissure; representative example of n = 4 brains. B. Effect of CNO on membrane potential of a D2–hM3Dq cell (representative example of n = 10 cells; mean+/-sem depolarization = 7.92+/-0.91 mV, p < 0.0001 by two-tailed one-sample t-test; t,df=8.666,9). C. Example of spatial exploration heatmaps from CNO-injected mice expressing ChR2 or hM3Dq in NAc D2 cells. D. Effect of CNO on centre occupancy (% time during the first 15 min of arena exploration) in mice expressing hM3Dq or ChR2 in NAc D2 cells. 4 mice per group, values are individual mice and means ± sem. Two-way repeated measures ANOVA F(1,6) = 9.715, p = 0.0207; numbers above bars are p-values from Sidak’s post tests (ns = > 0.2). E. Effect on drug treatments on measures of sedation (locomotion velocity and immobility) in the open field test used to assess center-border preference. n = 8 mice in each group, values are individual mice and means ± sem. No significant effects were found: Right plot, two-way repeated-measures ANOVA F(3,42) = 0.2342, p = 0.872 (ns); Left plot, two-way repeated-measures ANOVA F(3,42) = 0.6046, p = 0.616 (ns).

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Blomeley, C., Garau, C. & Burdakov, D. Accumbal D2 cells orchestrate innate risk-avoidance according to orexin signals. Nat Neurosci 21, 29–32 (2018). https://doi.org/10.1038/s41593-017-0023-y

Download citation

Further reading

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