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Nucleus accumbens D2R cells signal prior outcomes and control risky decision-making

Abstract

A marked bias towards risk aversion has been observed in nearly every species tested1,2,3,4. A minority of individuals, however, instead seem to prefer risk (repeatedly choosing uncertain large rewards over certain but smaller rewards), and even risk-averse individuals sometimes opt for riskier alternatives2,5. It is not known how neural activity underlies such important shifts in decision-making—either as a stable trait across individuals or at the level of variability within individuals. Here we describe a model of risk-preference in rats, in which stable individual differences, trial-by-trial choices, and responses to pharmacological agents all parallel human behaviour. By combining new genetic targeting strategies with optical recording of neural activity during behaviour in this model, we identify relevant temporally specific signals from a genetically and anatomically defined population of neurons. This activity occurred within dopamine receptor type-2 (D2R)-expressing cells in the nucleus accumbens (NAc), signalled unfavourable outcomes from the recent past at a time appropriate for influencing subsequent decisions, and also predicted subsequent choices made. Having uncovered this naturally occurring neural correlate of risk selection, we then mimicked the temporally specific signal with optogenetic control during decision-making and demonstrated its causal effect in driving risk-preference. Specifically, risk-preferring rats could be instantaneously converted to risk-averse rats with precisely timed phasic stimulation of NAc D2R cells. These findings suggest that individual differences in risk-preference, as well as real-time risky decision-making, can be largely explained by the encoding in D2R-expressing NAc cells of prior unfavourable outcomes during decision-making.

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Figure 1: Trait variability in risk-aversion as loss-sensitivity: rat behavioural model.
Figure 2: D2R agonist in the NAc increases risk-seeking behaviour in rats.
Figure 3: Activity in D2R-expressing cells in the NAc encodes loss-relevant task variables and predicts upcoming choice.
Figure 4: Providing phasic activity in D2-expressing NAc cells during the decision period decreased risky choices in risk-seeking rats.

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References

  1. Barkan, C. P. L. A Field test of risk-sensitive foraging in black-capped chickadees (Parus Atricapillus). Ecology 71, 391–400 (1990)

    Article  Google Scholar 

  2. Kahneman, D. & Tversky, A. Prospect theory: an analysis of decision under risk. Econometrica 47, 263–291 (1979)

    Article  MathSciNet  Google Scholar 

  3. Caraco, T., Martindale, S. & Whittam, T. S. An empirical demonstration of risk-sensitive foraging preferences. Anim. Behav. 28, 820–830 (1980)

    Article  Google Scholar 

  4. Real, L. A. Uncertainty and pollinator–plant interactions: the foraging behavior of bees and wasps on artificial flowers. Ecology 62, 20–26 (1981)

    Article  Google Scholar 

  5. Markowitz, H. Portfolio Selection. J. Finance 7, 77–91 (1952)

    Google Scholar 

  6. Schultz, W. et al. Explicit neural signals reflecting reward uncertainty. Philos. Trans. R. Soc. B Biol. Sci . 363, 3801–3811 (2008)

    Article  Google Scholar 

  7. St Onge, J. R. & Floresco, S. B. Dopaminergic modulation of risk-based decision making. Neuropsychopharmacology 34, 681–697 (2009)

    Article  CAS  Google Scholar 

  8. Nasrallah, N. A. et al. Risk preference following adolescent alcohol use is associated with corrupted encoding of costs but not rewards by mesolimbic dopamine. Proc. Natl Acad. Sci. USA 108, 5466–5471 (2011)

    Article  ADS  CAS  Google Scholar 

  9. Knutson, B., Wimmer, G. E., Kuhnen, C. M. & Winkielman, P. Nucleus accumbens activation mediates the influence of reward cues on financial risk taking. Neuroreport 19, 509–513 (2008)

    Article  Google Scholar 

  10. Tom, S. M., Fox, C. R., Trepel, C. & Poldrack, R. A. The neural basis of loss aversion in decision-making under risk. Science 315, 515–518 (2007)

    Article  ADS  CAS  Google Scholar 

  11. Winstanley, C. A., Theobald, D. E. H., Dalley, J. W. & Robbins, T. W. Interactions between serotonin and dopamine in the control of impulsive choice in rats: therapeutic implications for impulse control disorders. Neuropsychopharmacology 30, 669–682 (2005)

    Article  CAS  Google Scholar 

  12. Bechara, A., Damasio, A. R., Damasio, H. & Anderson, S. W. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50, 7–15 (1994)

    Article  CAS  Google Scholar 

  13. Clark, L. et al. Differential effects of insular and ventromedial prefrontal cortex lesions on risky decision-making. Brain 131, 1311–1322 (2008)

    Article  CAS  Google Scholar 

  14. St Onge, J. R., Abhari, H. & Floresco, S. B. Dissociable contributions by prefrontal D1 and D2 receptors to risk-based decision making. J. Neurosci. 31, 8625–8633 (2011)

    Article  CAS  Google Scholar 

  15. Bechara, A., Damasio, H. & Damasio, A. R. Emotion, decision making and the orbitofrontal cortex. Cereb. Cortex 10, 295–307 (2000)

    Article  CAS  Google Scholar 

  16. O’Neill, M. & Schultz, W. Coding of reward risk by orbitofrontal neurons is mostly distinct from coding of reward value. Neuron 68, 789–800 (2010)

    Article  Google Scholar 

  17. Stopper, C. M., Tse, M. T. L., Montes, D. R., Wiedman, C. R. & Floresco, S. B. Overriding phasic dopamine signals redirects action selection during risk/reward decision making. Neuron 84, 177–189 (2014)

    Article  CAS  Google Scholar 

  18. Hayden, B. Y. & Platt, M. L. Gambling for Gatorade: risk-sensitive decision making for fluid rewards in humans. Anim. Cogn. 12, 201–207 (2009)

    Article  Google Scholar 

  19. Niv, Y., Edlund, J. A., Dayan, P. & O’Doherty, J. P. Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain. J. Neurosci. 32, 551–562 (2012)

    Article  CAS  Google Scholar 

  20. Dodd, M. L. et al. Pathological gambling caused by drugs used to treat parkinson disease. Arch. Neurol. 62, 1377–1381 (2005)

    Article  Google Scholar 

  21. Frank, M. J., Seeberger, L. C. & O’Reilly, R. C. By carrot or by stick: cognitive reinforcement learning in parkinsonism. Science 306, 1940–1943 (2004)

    Article  ADS  CAS  Google Scholar 

  22. van Eimeren, T. et al. Dopamine agonists diminish value sensitivity of the orbitofrontal cortex: a trigger for pathological gambling in Parkinson’s disease? Neuropsychopharmacoly 34, 2758–2766 (2009)

    Article  CAS  Google Scholar 

  23. Kebabian, J. W. et al. A-77636: a potent and selective dopamine D1 receptor agonist with antiparkinsonian activity in marmosets. Eur. J. Pharmacol. 229, 203–209 (1992)

    Article  CAS  Google Scholar 

  24. Dreyer, J. K., Herrik, K. F., Berg, R. W. & Hounsgaard, J. D. Influence of phasic and tonic dopamine release on receptor activation. J. Neurosci. 30, 14273–14283 (2010)

    Article  CAS  Google Scholar 

  25. Porter-Stransky, K. A., Seiler, J. L., Day, J. J. & Aragona, B. J. Development of behavioral preferences for the optimal choice following unexpected reward omission is mediated by a reduction of D2-like receptor tone in the nucleus accumbens. Eur. J. Neurosci. 38, 2572–2588 (2013)

    Article  Google Scholar 

  26. Chen, T.-W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013)

    Article  ADS  CAS  Google Scholar 

  27. Gunaydin, L. A. et al. Natural Neural projection dynamics underlying social behavior. Cell 157, 1535–1551 (2014)

    Article  CAS  Google Scholar 

  28. Lerner, T. N. et al. Intact-brain analyses reveal distinct information carried by SNc dopamine subcircuits. Cell 162, 635–647 (2015)

    Article  CAS  Google Scholar 

  29. Gradinaru, V. et al. Molecular and cellular approaches for diversifying and extending optogenetics. Cell 141, 154–165 (2010)

    Article  CAS  Google Scholar 

  30. Tai, L.-H., Lee, A. M., Benavidez, N., Bonci, A. & Wilbrecht, L. Transient stimulation of distinct subpopulations of striatal neurons mimics changes in action value. Nature Neurosci. 15, 1281–1289 (2012)

    Article  CAS  Google Scholar 

  31. Kepecs, A., Uchida, N., Zariwala, H. A. & Mainen, Z. F. Neural correlates, computation and behavioural impact of decision confidence. Nature 455, 227–231 (2008)

    Article  ADS  CAS  Google Scholar 

  32. Kopec, C. D., Erlich, J. C., Brunton, B. W., Deisseroth, K. & Brody, C. D. Cortical and subcortical contributions to short-term memory for orienting movements. Neuron 88, 367–377 (2015)

    Article  CAS  Google Scholar 

  33. Witten, I. B. et al. Recombinase-driver rat lines: tools, techniques, and optogenetic application to dopamine-mediated reinforcement. Neuron 72, 721–733 (2011)

    Article  CAS  Google Scholar 

  34. Minowa, T., Minowa, M. T. & Mouradian, M. M. Analysis of the promoter region of the rat D2 dopamine receptor gene. Biochemistry 31, 8389–8396 (1992)

    Article  CAS  Google Scholar 

  35. Leong, J. K., Pestilli, F., Wu, C. C., Samanez-Larkin, G. R. & Knutson, B. White-matter tract connecting anterior insula to nucleus accumbens correlates with reduced preference for positively skewed gambles. Neuron 89, 63–69 (2016)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We would like to thank R. Malenka and K. Shenoy for advice on experimental design; A. Andalman for advice on analysis; P. Kalanithi for advice in general; E. Ferenczi, C. Földy, G. Panagiotakos, M. Bennett, A. Bryant, C. Beinat, and M. Palner for preliminary data collection and training in experimental techniques; S. Pak and C. Delacruz for administrative support; and the entire Deisseroth laboratory and Stanford University Neurosciences Program for training and support. All viruses were packaged at the Stanford Viral and Vector Core. K.A.Z. was supported by the NSF Graduate Research Fellowship Program, by the Stanford Neurosciences Program NIH Training Grant, and by an NRSA Predoctoral Fellowship from NIDA (1F31MH105151-01). T.N.L. was supported by a Stanford Dean’s Postdoctoral Fellowship and by an NRSA Postdoctoral Fellowship (1F32MH105053-01). B.K. was supported by a Stanford Neuroscience Institute Big Ideas Grant. K.D. was supported by NIMH, NIDA, NSF, the Wiegers Family Fund, the Nancy and James Grosfeld Foundation, the H.L. Snyder Medical Foundation, the Samuel and Betsy Reeves Fund, and the US Army Research Laboratory and Defense Advanced Research Projects Agency (Cooperative Agreement Number W911NF-14-2-0013); nothing in this material represents official views or policies of our funders. All clones and resources are freely available (http://optogenetics.org, http://clarityresourcecenter.org).

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Authors and Affiliations

Authors

Contributions

K.A.Z. led the design, performance, and analysis of experiments, in collaboration with C.R. for designing and generating the D2SP constructs, with B.K. for behavioural design and analysis, with T.N.L. for characterizing eChR2 and wavelength-dependent responses of GCaMP6m, and with T.J.D. and T.N.L. for photometry methods development and implementation. K.A.Z. and K.D. planned and wrote the paper with editorial input from all authors. K.D. supervised all aspects of the work.

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Correspondence to Karl Deisseroth.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Task validation and behavioural controls.

a, Scale diagram of the behavioural apparatus, showing the relative size and location of the nosepoke, levers, and sucrose port. b, Rats varied the proportion of choices they made to the risky lever as a function of the relative value of the safe and risky options. Subplots were constructed for each rat. The size of the safe reward is displayed as a proportion of the expected value of the risky reward. Red points indicate the proportion of risky choices each rat made to the risky lever given a particular value of the safe reward; blue lines indicate sigmoidal fits to those values. Dashed lines indicate each rat’s indifference point. Data in the centre panel are from a risk-seeking rat (indifference point >1); all other rats were risk-averse. Side bias, in these data, would appear as an upward or downward shift of the sigmoid, such that behaviour would asymptote without spanning the range of risky choices, and 50% would not centre the sigmoid on the ordinate. An additional cohort of rats was trained specifically for this control experiment. These rats do not appear elsewhere in the manuscript. c, Rats reversed their behaviour to track their preferred reward contingency (safe or risky). Each panel displays the behaviour of one rat across several hundred trials. The location of the risky lever is alternated in blocks of trials. Blocks where the right lever is risky are highlighted in yellow. Rats’ choices are smoothed with a 15-trial moving window. The rat in the bottom centre panel displayed risk-seeking behaviour; all others were risk-averse. An additional cohort of rats was trained specifically for this control experiment. These rats do not appear elsewhere in the manuscript.

Extended Data Figure 2 Parameters for logistic regression classifier.

a, Parameter values and goodness-of-fit for single-exponential fits of the form to weights obtained in the logistic regression classifier (Methods) shown in Fig. 1. b, Parameter values and root mean squared error (RMSE) for fits of the form y = b to weights associated with choosing the safe option in the logistic regression classifier (Methods) shown in Fig. 1. c, Model coefficients associated with choosing the safe lever, as obtained from the entire population of rats. d, Model coefficients associated with choosing the safe lever, obtained for risk-seeking and risk-averse rats separately. e, Split-half reliability. Each dot represents a comparison between a rat’s average risk preference on odd days of behaviour and the rat’s average risk preference on even days of behaviour across seven days of testing. Perfect reliability would be represented by each animal’s data falling along the (grey, dashed) unity line. f, A 10,000-fold bootstrap over randomly assigned split halves of each rat’s behaviour generates an average reliability (intraclass correlation (ICC)) of 0.987. Reliability estimates were generated from control animal behavioural data represented in Fig. 4, as this cohort represents the longest test of unmanipulated behaviour in the manuscript.

Extended Data Figure 3 Predictive validity of the logistic regression classifier.

ac, The model was trained on two-thirds of data and tested on the one-third of data that was held-out. The blue histogram indicates the chance distribution, determined by the model’s performance over a 1,000-fold shuffle of the held-out test data. The dashed line indicates cross-validation accuracy (CV) on held-out data. This calculation was performed for data from all rats (a; P < 0.001 by Monte Carlo simulation; CV is 24.3 s.d. outside the chance distribution), a balanced subset of data from risk-averse rats, such that approximately 50% of choices were safe and 50% were risky (b; P < 0.001 by Monte Carlo simulation; CV is 20.6 s.d. outside the chance distribution), and a balanced subset of data from risk-seeking rats (c; P < 0.001 by Monte Carlo simulation; CV is 8.5 s.d. outside the chance distribution). df, Receiver operating characteristic (ROC) curves derived from model performance on held-out test data across all rats (d; area under the curve (AUC) = 0.85), a balanced subset of data from risk-averse rats (e; AUC = 0.76), and a balanced subset of data from risk-seeking rats (f; AUC = 0.78). g, h, Histogram of run lengths for risk-averse rats (g) and risk-seeking rats (h). Blue bars indicate runs on the risky lever. Grey bars indicate runs on the safe lever. Insets show exceptionally long runs.

Extended Data Figure 4 The D1 agonist A-77636 increased intertrial interval without influencing risk preference.

Each rat in this experiment received alternating treatments of intraperitoneal A-77636 and intraperitoneal saline (see Fig. 2d). Each plot represents a different dose of A-77636. On each x axis is the intertrial interval on days receiving saline, and on the y axis is the intertrial interval on days receiving drug. Points above the unity line indicate an increase in intertrial interval with drug administration. a, Vehicle alone does not alter intertrial interval (paired t-test, t17 = 1.088, P = 0.29). b, A 50 μg kg−1 dose of A-77636 does not significantly alter intertrial interval (paired t-test, t14 = 1.598, P = 0.13). c, A 350 μg kg−1 dose of A-77636 significantly increases intertrial interval (paired t-test, t16 = 4.391, P = 0.0005). d, A 700 μg kg−1 dose of A-77636 significantly increases intertrial interval (paired t-test, t16 = 2.738, P = 0.015). e, A 1,000 μg kg−1 dose of A-77636 significantly increases intertrial interval (paired t-test, t13 = 2.948, P = 0.011).

Extended Data Figure 5 The novel D2SP improves expression and specificity over previously published promoters.

a, Expression of eYFP under the novel D2SP. Red shows D2R immunostaining (Methods). Scale bar, 100 μm. b, Expression of eYFP under a D2R promoter based on previously published constructs (D2RE), which included the first exon of the D2 receptor gene30,31. Image taken with settings matched to those used for the D2SP image in a. Scale bar, 100 μm. c, Images are of the same field of view as in b but taken with settings optimized to see the (otherwise dim) eYFP expression. Scale bar, 100 μm. d, Specificity of expression under the D2SP improved from 90.5% to 98.2% under the previously described promoter. Penetrance of expression under the DR2 promoter improved from 69% to 86.8% under the previously described promoter. e, Full sequence of D2SP.

Extended Data Figure 6 Specificity of D2SP.

a, Sagittal sections taken from brains injected with AAV8-hSYN-ChR2-eYFP (top) and AAV8-D2SP-eYFP (bottom). Arrowheads indicate projections expressing eYFP in the hSYN-injected brain that are not expressing eYFP in the D2SP-injected brain. b, Representative injection location, showing minimal overlap of D2SP-eChR2-eYFP with choline acetyltransferase (ChAT)+ cells. Green indicates D2SP-eChR2-eYFP, red indicates ChAT. c, Example of the three ChAT+ cells observed expressing eChR2-eYFP across 6 animals (top) and a ChAT+ cell that does not express eChR2-eYFP (bottom). d, Across NAc sections from the most densely expressing slices from 6 animals, 782 cells expressing eChR2-eYFP, 420 cells expressing ChAT, and 3 cells expressing both ChAT and ChR2-eYFP were observed. e, Within the area of viral infection, 782 cells expressing eChR2-eYFP, 93 cells expressing ChAT, and 3 cells expressing both ChAT and ChR2-eYFP were observed.

Extended Data Figure 7 Characterization of dual-wavelength photometry and eChR2.

a, Images of a GCaMP6m-expressing neuron illuminated at the imaging wavelength (475 nm) and the isosbestic wavelength (400 nm), at baseline (left) and with 10 s of 50 Hz electrical stimulation (right). b, Fluorescence intensity from a representative neuron, illuminated at 475 nm and 400 nm, during 10 s of 50 Hz electrical stimulation. c, Traces from a GCaMP6m-expressing rat (left) and a YFP-expressing rat (right) during the gambling task. Cyan traces are of the imaging wavelength; violet traces are of the isosbestic wavelength; black traces represent the cleaned signal (Methods). d, Expression of D2SP-ChR2-eYFP in rat NAc, showing evidence of opsin accumulations (bright green spots). e, Expression of D2SP-eChR2-eYFP in rat NAc; note greatly reduced accumulation density. f, D2SP-ChR2-eYFP-expressing cells have significantly more aggregates than D2SP-eChR2-eYFP-expressing cells. Quantification is in number of aggregates per expressing cell across ex vivo histological sections (t-test, t7 = 21.25, ***P < 0.0001; n = 168 ChR2-expressing cells in 4 sections, n = 131 eChR2-expressing cells in 5 sections). g, Backbone diagram of pAAV-D2SP-eChR2(H134R)-eYFP showing the membrane trafficking modifications (trafficking signal (TS) and endoplasmic reticulum (ER) export motifs). h, Representative photocurrents evoked by ChR2 and eChR2 in cultured neurons by 1 s 473-nm light. i, Steady-state photocurrents measured from ChR2- and eChR2-expressing cultured neurons. In addition to showing reduced accumulations, photocurrents trended higher with eChR2. j, Peak photocurrents measured from ChR2- and eChR2-expressing cultured neurons; eChR2 trended towards higher peaks as well. k, Expression of eChR2-eYFP in a cultured rat striatal neuron. l, Whole-cell patch-clamp recording from the neuron shown in k. mp, Resting membrane potential, input resistance, membrane capacitance, and membrane resistance measured from ChR2- and eChR2-expressing cultured neurons; no significant differences were observed. All error bars represent s.e.m.

Extended Data Figure 8 D2R+ (but not pan-neuronal) cellular signals are increased during the decision-period leading to risk rejection (safe choice) and encode prior loss.

ah, In all plots, black dashed boxes indicate decision-period activity, and blue dashed boxes indicate subsequent decision-period activity. Traces indicate mean neural activity sorted on trial outcome: safe (black), gain (green) or loss (red). Shaded regions indicate s.e.m. a, Average traces from the most risk-averse cell-specific D2SP-GCaMP6m-expressing rats (n = 3). Note increased neural activity during the decision period preceding a safe choice as compared to a risky (gain or loss) choice, as well as increased activity during the subsequent decision period (blue dashed box) following a loss outcome. b, Average traces from the most risk-averse non-cell-type-specific (hSYN-GCaMP6m-expressing) rats (n = 4). Note the increased activity in these cells during the decision period before making a risky (red/green) as compared to safe (black) choice (contrasting with the opposite D2R+-specific result in a). Also in contrast to the D2R+ case, the pan-neuronal signal did not discriminate immediately-preceding loss (red) from immediately-preceding gain (green) during the subsequent decision period. c, d, These pattern were also consistent in the most risk-seeking animals (D2SP-GCaMP6m-expressing rats, n = 3; hSYN-GCaMP6m-expressing rats, n = 4). eh, This pattern did not depend on the location of the implant relative to the safe lever. Shown are data from D2SP-GCaMP6m-expressing rats with implants ipsilateral to the location of the safe lever (n = 4); hSYN-GCaMP6m-expressing rats with implants ipsilateral to the location of the safe lever (n = 4); D2SP-GCaMP6m-expressing rats with implants contralateral to the location of the safe lever (n = 2); hSYN-GCaMP6m-expressing rats with implants contralateral to the location of the safe lever (n = 4). Data for a, c, e and g are from the rats whose behaviour and neural data are represented in Fig. 3. Data for b, d, f and h are not represented in the main figures of the manuscript. Throughout the figure, traces were analysed as dF/F and z-score normalized before averaging. Scale bars indicate 1 s and 0.25 standard (z-score) units.

Extended Data Figure 9 Pan-neuronal NAc recordings: increased activity associated with risky decisions.

a, Median-normalized dF/F signal during the first second of the outcome period for each hSYN-GCaMP6m-expressing rat, comparing risky outcomes to safe outcomes (n = 8; Wilcoxon matched-pairs test, W = 36, P = 0.008). b, Lack of correlation between the proportion of choices made by each rat to the risky lever and the individual’s risky versus safe outcome signal ((dF/F) during the first 1 s of risky outcome/(dF/F) during safe outcome) (n = 8 rats, Pearson’s r2 = 0.12, P = 0.40). c, Median-normalized dF/F signal during the first second of the outcome period for each D2SP-GCaMP6m-expressing rat, comparing safe outcomes to risky outcomes (n = 6; Wilcoxon matched-pairs test, W = 17, P = 0.04). d, Lack of correlation between the proportion of choices made by each rat to the risky lever and the individual’s risky versus safe outcome signal ((dF/F) during the first 1 s of safe outcome/(dF/F) during risky outcome) (n = 6; Pearson’s r2 = 0.11, P = 0.51). e, Median-normalized dF/F signal at the time of trial initiation for each hSYN-GCaMP6m-expressing rat, sorted on previous trial outcome, comparing risky outcomes to safe outcomes (n = 8; paired t-test, t7 = 7.25, P = 0.0002). f, Lack of correlation between the proportion of choices made by each rat to the risky lever and the individual’s risk signal ((dF/F) at nosepoke trial initiation after risky outcome/(dF/F) after safe outcome) (n = 8; Pearson’s r2 = 0.01, P = 0.78). g, Median-normalized dF/F signal at the time of trial initiation for each D2SP-GCaMP6m-expressing rat, sorted on previous trial outcome, comparing risky outcomes to safe outcomes (n = 6; paired t-test, t5 = 6.901, P = 0.001). h, Correlation between the proportion of choices made by each D2SP-GCaMP6m-expressing rat to the risky lever and the individual’s risk signal ((dF/F) at nosepoke trial initiation after risky outcome/(dF/F) after safe outcome) (n = 6; Pearson’s r2 = 0.97, P = 0.0003). i, Median-normalized dF/F signal at the time of trial initiation for each hSYN-GCaMP6m-expressing rat, sorted on upcoming choice, comparing risky choices to safe choices (n = 8; paired t-test, t7 = 2.11, P = 0.036). j, Lack of correlation between the proportion of choices made by each rat to the risky lever and the individual’s decision period signal ((dF/F) at nosepoke trial initiation before a risky choice/(dF/F) before a safe choice) (n = 8; Pearson’s r2 = 0.17, P = 0.31). k, Median-normalized dF/F signal at the time of trial initiation for each D2SP-GCaMP6m-expressing rat, sorted on upcoming choice, comparing risky choices to safe choices (n = 8; paired t-test, t7 = 2.11, P = 0.036). l, Lack of correlation between the proportion of choices made by each rat to the risky lever and the individual’s safe choice signal ((dF/F) at nosepoke trial initiation before choosing safe/(dF/F) at nosepoke before choosing risky) (n = 6; Pearson’s r2 = 0.12, P = 0.48). Data from k and l also appear in Fig. 3i, o and are reproduced here for ease of comparison. All error bars represent s.e.m.

Extended Data Figure 10 D2SP-eChR2 stimulation during the outcome period produced a small but still detectable effect on risk preference.

a, Stimulation was as in Fig. 4, except delivered during the first second of reward retrieval rather than during the 1-s decision period. b, The effect of this stimulation during the outcome period was smaller than that of stimulation during the decision period (two-way ANOVA, interaction F1,24 = 6.12; *P = 0.02; Bonferroni post-hoc tests revealed a significant effect of stimulation during the decision period, P < 0.001, but no effect of stimulation during the outcome period). ch, As in Fig. 4, 1 s of 20-Hz optical stimulation of NAc DR2+ cells during the outcome period decreased risky choices in risk-seeking, but not risk-averse rats relative to YFP-expressing controls (two-way ANOVA, interaction F1,31 = 4.317, P = 0.046; Bonferroni post-hoc test revealed a significant difference between eChR2-expressing and YFP-expressing risk-seeking rats, but no difference between experimental and control risk-averse rats; *P < 0.05). Grey traces represent individual animals. Black and red traces represent the population average. Error bars represent s.e.m. Blue boxes indicate days on which optical stimulation was delivered during the outcome.

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Zalocusky, K., Ramakrishnan, C., Lerner, T. et al. Nucleus accumbens D2R cells signal prior outcomes and control risky decision-making. Nature 531, 642–646 (2016). https://doi.org/10.1038/nature17400

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