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Research ArticleResearch Article: New Research, Cognition and Behavior

Discounting of Future Rewards and Punishments in Rats

Maurice-Philipp Zech, Sandra Schäble and Tobias Kalenscher
eNeuro 21 November 2022, 9 (6) ENEURO.0452-21.2022; DOI: https://doi.org/10.1523/ENEURO.0452-21.2022
Maurice-Philipp Zech
Comparative Psychology, Institute of Experimental Psychology, Heinrich-Heine Universität Düsseldorf, Düsseldorf, 40225, Germany
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Sandra Schäble
Comparative Psychology, Institute of Experimental Psychology, Heinrich-Heine Universität Düsseldorf, Düsseldorf, 40225, Germany
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Tobias Kalenscher
Comparative Psychology, Institute of Experimental Psychology, Heinrich-Heine Universität Düsseldorf, Düsseldorf, 40225, Germany
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  • Figure 1.
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    Figure 1.

    Overview of the customized T-maze. The start arm starts on the right side with the start box, which can be closed by an automatic door. Two identical decision arms were connected to the start arm. Additionally, the decision arms could be closed by automatic down sliding doors. Pellet dispensers were placed at the end of the start arm and each decision arm. Finally, the pellets were delivered into Petri dishes, and above the Petri dishes, reward lights were placed.

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    Figure 2.

    Overview of the shock and reward timings for each experiment. After an animal entered a decision arm (0 s), the doors were closed. Afterwards, the rewards and shocks were delivered. In general, an early reward had a delay of 2 s and a late reward of 21 s. The early shock was administered after 1 s (relative to entering) and the late shock after 20 s.

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    Figure 3.

    Overview of the shock and reward contingencies in the two arms of the T-maze for each experiment and the predictions for each theory. For the shocks and rewards, each column represents one arm of the T-maze (early reward + late reward [EE]; late shock + late reward [LL]; early shock + early reward [EE]). In the first experiment, the entry-to-reward contingencies are identical in both arms, but the entry-to-shock delays differ between both arms. The second experiment tested constant shock-to-reward delays with different entry-to-shock delays. The third experiment used constant entry-to-shock delays, but the shock-to-reward contingencies differ between arms. In the predictions, “∼” represents no predictions. Note that the assignment of shock/reward contingencies to the left or right arm of the T-maze will be pseudo-randomized across sessions for all experiments. The left side is always the condition for which the percentage of decisions was calculated.

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    Figure 4.

    Depicted is the used Bayesian hierarchy model. As the likelihood function for the decisions, a Bernoulli distribution was used. Each estimation of θ followed a β function with μθ(κ−2)+1,(1−μθ)(κ−2)+1 . For μθ , an uninformed β prior was used, and κ used a gamma(0.01,0.01) function (for prior predictions, see Extended Data Figs. 4-1, 4-2, 4-3).

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    Figure 5.

    Mean parameter estimation with simulated data for all predictions according to the Bayesian hierarchy model. The predictions of both models are color coded, and on the top left corner are the specific experiments (EL: early shock + late rerwad; LL: late shock + late reward; EE: early shock + early reward). The y-axis shows the posterior distribution of μθ . The vertical gray lines represent the upper and lower bound for the 95% highest density interval. Experiment 1 is in the top row, and the utility from anticipation model is on the left side (upper bound = 0.42, lower bound = 0.38). On the other side is the prediction for the aversive discounting model (upper bound = 0.62, lower bound = 0.589). In the second row is experiment 2, and the prediction for the utility from anticipation model is displayed (upper bound = 0.42, lower bound = 0.38). Finally, in the bottom row, experiment 3 can be seen, and both models have the same predictions (upper bound = 0.42, lower bound = 0.38).

  • Figure 6.
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    Figure 6.

    A, Mean percentage of decisions for each experiment. In each experiment, animals performed 10 sessions and up to 21 trials per session (6 forced trials and 16 free trials). The timings of the reward and shocks are displayed on the x-axis as well as the experiment. Specifically, for experiment 1, the percentage of decisions are calculated for early shock + late reward (EL) versus late shock + late reward (LL). For experiments 2 and 3, the percentage is calculated for early shock + early reward (EE) versus late shock + late reward (LL) and early shock + early reward (EE) versus early shock + early shock + late reward (EL), respectively. The vertical lines represent the SEM, and each dot represents a single animal. For all experiments, we calculated one-sample t tests (two-tailed). In the first experiment, animals showed a significant preference above chance level. The second experiment failed to yield any significant results; and in the third experiment, animals revealed a significant preference below chance level. The black horizontal line represents chance level. B, Mean parameter estimation for the Bayesian hierarchy model. On the top left corner are the specific experiments. On the y-axis is the posterior distribution of μθ . Additionally, the conditions are displayed again. The vertical gray lines show the upper and lower bound for the 95% highest density interval. From top to bottom is experiment 1 (upper bound = 0.57, lower bound = 0.52), experiment 2 (upper bound = 0,55, lower bound = 0.49), and experiment 3 (upper bound = 0.48, lower bound = 0.42). See the extended data for the posterior θ distribution for all experiments (Extended Data Fig. 6-1); ***p < 0.00.

  • Figure 7.
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    Figure 7.

    Mean percentage choice (experiment 1: early shock, late reward vs late shock, late reward, EL vs LL; experiment 2: early shock, early reward vs late shock, late reward, EE vs LL; experiment 3: early shock, early reward vs early shock, late reward, EE vs EL) for the first and second blocks of trials (trials 1–8 vs trial 9–16; left panels) and for the first and second block of sessions (sessions 1–5 vs sessions 6–10; right panels) in all experiments. Repeated-measured ANOVAs revealed significant main effects of block of trials for experiments 2 and 3. Additionally, there was a significant main effect of block of sessions on percentage choice in experiment 3, but not in experiment 1 or 2. Additionally, there were significant main effects of session order within a block on choice in experiments 1 and 2 but not in 3; *p < 0.05.

Tables

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    Table 1

    Statistical table

    Data structureType of testPower
    Experiment 1
    Normal distribution
    One-sample two-tailed t tests95% confidence interval
    Experiment 1
    Bernoulli
    Bayesian parameter estimate95% highest density Interval
    Experiment 2
    Normal distribution
    One-sample two-tailed t tests95% confidence interval
    Experiment 2
    Bernoulli
    Bayesian parameter estimate95% highest density Interval
    Experiment 3
    Normal distribution
    One-sample two-tailed t tests95% confidence interval
    Experiment 3
    Bernoulli
    Bayesian parameter estimate95% highest density Interval
    • Listed are all performed tests in the same order as the text.

Extended Data

  • Figures
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  • Extended Data Figure 4-1

    Prior distribution for the κ parameter. The y-axis represents the κ density and the x-axis the κ parameter. Download Figure 4-1, TIF file.

  • Extended Data Figure 4-2

    Prior distribution for the omega parameter. The y-axis represents the omega density and the x-axis the omega parameter. Download Figure 4-2, TIF file.

  • Extended Data Figure 4-3

    Prior distribution for the θ parameter. The y-axis represents the θ density and the x-axis the θ parameter. Download Figure 4-3, TIF file.

  • Extended Data 1

    Data and scripts for all calculations. Folders are separated for the data extraction (Data), null hypothesis testing (NHST), and bayesian hierarchical models (Bayes). Download Extended Data 1, ZIP file

  • Extended Data Figure 6-1

    Posterior θ distribution for all experiments. Displayed are violin plots where the width the density represents. Additionally, boxplots are added to the violins. Download Figure 6-1, TIF file.

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eneuro: 9 (6)
eNeuro
Vol. 9, Issue 6
November/December 2022
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Discounting of Future Rewards and Punishments in Rats
Maurice-Philipp Zech, Sandra Schäble, Tobias Kalenscher
eNeuro 21 November 2022, 9 (6) ENEURO.0452-21.2022; DOI: 10.1523/ENEURO.0452-21.2022

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Discounting of Future Rewards and Punishments in Rats
Maurice-Philipp Zech, Sandra Schäble, Tobias Kalenscher
eNeuro 21 November 2022, 9 (6) ENEURO.0452-21.2022; DOI: 10.1523/ENEURO.0452-21.2022
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Keywords

  • aversive discounting
  • delay discounting
  • intertemporal choice
  • reward
  • shock
  • utility from anticipation

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