The Effects of Reward Quality on Risk-sensitive Foraging Craft*, B.B., Church, A.C., Rohrbach, C.M., & Bennett, J

1. The Effects of Reward Quality on Risk-sensitive Foraging Craft*, B.B., Church, A.C., Rohrbach, C.M., & Bennett, J.M. Introduction Method Results • Subjects • Male, Sprague Dawley (a laboratory strain of Rattusnorvegicus) rats; n=20 • Apparatus • The experimental procedure was conducted in Lafayette operant conditioning chambers housed in a sound attenuating box. • The chambers (27.94 x 21.59 x 21.59 cm) had stainless steel grid flooring, stainless steel front and back walls, and a Plexiglas door, ceiling, and side walls. • Two bar presses, equidistant to the feeding tray, corresponded with either a variable (risk-prone) or constant (risk-averse) reward option. • Experimental Session • The Sugar Group (SG, n=10) chose between a risk-prone (1 or 5 pellets, p=0.5) and a risk-averse (3 pellets, p=1.0) option that delivered a calorically rich reward (45 mg BioServe sugar pellets) • The Grain Group (GG, n=10) chose between a risk-prone (1 or 5 pellets, p=0.5) and risk-averse (3 pellets, p=1.0) option that delivered a calorically poor reward (45 mg BioServe grain pellets). • Delay to reward was held constant at .1s. • Subjects were deprived to 90% of their free-feeding body weight. • Once subjects reached the target weight, choice preference was measured using operant conditioning chambers. • Risk-sensitive Foraging Theory • Risk-sensitive Foraging Theory (RSFT) was developed to explain a forager’s shift in choice between a variable (risk-prone) or constant (risk-averse) option. In typical RSFT studies, a risk-averse choice yields a constant return, whereas a risk-prone choice yields a variable return. If an organism displays a risk-prone or risk-averse choice bias, the organism is said to be risk-sensitive. • Daily Energy Budget Rule • The Daily Energy Budget (DEB) rule was developed to describe qualitative shifts in risk-sensitivity and makes the following assumptions: first, there is a non-linear relationship between a forager’s fitness and the rate of gain, and second, risk-sensitivity is contingent on the relationship between a metabolic reference and the rate of caloric return from a food source. For example, as a forager reaches a negative energy budget, the DEB rule describes the organism as seeking a reward with the greatest amount of return despite the variability of the reward. • Past studies, primarily with insects, have manipulated reward quality by changing the mean reward amount or the concentration of calories in rewards, but support for the DEB rule in these experiments differs across species and procedures used. Contrary to insect studies, past experiments using rats have observed shifts in risk-sensitivity that are consistent with the DEB rule when the mean reward amount and response effort was manipulated. • Given that rats displayed shifts in choice as the result of fluctuations in the mean reward amount, it is possible that changes in the rate of caloric return could result in differences in risk-sensitivity that are consistent with the DEB rule. However, no studies have been conducted using mammalian species where the mean reward amount and response effort was controlled and caloric return was manipulated. Figure 1.The mean number of choices for the variable option during the final three sessions of the experiment. Conclusion • The results of the present study confirmed that subjects’ risk-sensitive choices were influenced by reward quality. In addition, these results are interesting in that they indicate that differences in the rate of caloric gain from a particular food source resulted in qualitative differences in risk-sensitivity in rats when the mean reward amount, delay to reward, response effort, and body mass were held constant. • Choice preferences in the current experiment are consistent with the predictions of the DEB rule. The DEB rule describes qualitative changes in risk-sensitivity as being the result of a forager’s fitness and the rate of gain from a food source. In the current experiment, subjects in the SG received rewards with a higher rate of caloric gain and displayed a risk-averse strategy. However, subjects that received rewards with a lower rate of calorie gain made more variable option choices than the GG and were risk-indifferent. • One potential limitation of the current study was in regard to the type of rewards used. For instance, although the rate of caloric gain was different for the sugar and grain rewards, subjects in the current experiment could have been responding to the sweetness of the sugar pellets instead of the caloric value. Future studies should examine the potential effects of taste on risk-sensitivity by employing a sweet, nonnutritive option (i.e. saccharin or sucralose) along with a sugar and grain option. Results • All data were analyzed using an alpha level of .05. • An Independent Samples t-Test was conducted to determine the difference between the frequency of risk-prone choices made by the SG (M=4.76, SD=4) and GG (M=11.83, SD=4.88) groups over the last five days of data collection. • The Independent Samples t-Test revealed a statistically significant difference between the group’s risk-prone choices, t(18)=3.54, p=.002, r 2=.41; see Figure1. • Furthermore, a One-Sample t-Test was used to determine if the group’s risk-prone responses deviate from chance alone. The test revealed a statistically significant choice preference for the SG, t(9)= 4.14, p= .003, r 2=.66.As for the GG, no statistically significant difference was observed, t(9)= 1.19, p=.27, r 2=.14. Purpose • We hypothesized that  subjects in receiving grain pellets would become more risk-prone due to the low caloric gain of the grain pellets, whereas subjects in the receiving sugar pellets would become more risk-averse due to the high caloric return of the sugar pellets. • Furthermore, we hypothesized that subjects in both groups would display a risk-sensitive choice bias. *Contact information: craftb@spu.edu