| Literature DB >> 17892596 |
Taiki Takahashi1, Koki Ikeda, Toshikazu Hasegawa.
Abstract
BACKGROUND: Hyperbolic discounting of delayed and probabilistic outcomes has drawn attention in psychopharmacology and neuroeconomics. Sozou's evolutionary theory proposed that hyperbolic delay discounting may be totally attributable to aversion to a decrease in subjective probability of obtaining delayed rewards (SP) which follows a hyperbolic decay function. However, to date, no empirical study examined the hypothesis, although this investigation is important for elucidating the roles of impatience, precaution, and uncertainty aversion in delay discounting processes.Entities:
Year: 2007 PMID: 17892596 PMCID: PMC2072955 DOI: 10.1186/1744-9081-3-52
Source DB: PubMed Journal: Behav Brain Funct ISSN: 1744-9081 Impact factor: 3.759
Figure 1The solid (red) and dotted (blue) curves are the hyperbolic and exponential functions respectively, best fitted to the experimental data in delay and probability discounting tasks (a-b) (see Methods). Fig. 1a: Vertical axis indicates group median of indifference point in delay discounting task (discounted present value) and horizontal axis indicates delay (days). Data points are represented by the black diamonds. Fig. 1b: Vertical axis indicates group median of indifference point in probability discounting task (certainty equivalent discounted value) and horizontal axis indicates odds-against = (1/probability)-1 (an average waiting time in Rachlin's virtually-repeated gambling [17]). Note that hyperbolic models (red) better fit than exponential models (blue) (see Table 1 for AICc for each model).
AICc (Akaike Information Criterion with small sample correction) for exponential and hyperbolic functions in delay and probability discounting, and SP (subjective probability of obtaining delayed rewards)
| Exponential | Hyperbolic | |
| Delay discounting | 92.33 | 86.49 |
| Probability discounting | 90.59 | 82.33 |
| SP (subjective probability) | -6.7 | - 14.37 |
Hyperbolic functions better fit behavioral data in delay and probability discounting and SP. Note that smaller AICc indicates better fitting.
Each subject's delay (k) and probability (k) discount rates and decay rate kof subjective probability of obtaining delayed rewards (SP).
| Subject's ID | Subject's ID | ||||||
| 1 | 0.000620 | 1.3047 | 16 | 0.001757 | 0.9972 | 0.012409 | |
| 2 | 0.000320 | 1.5601 | 0.025945 | 17 | 0.000455 | 1.0612 | 0.027894 |
| 3 | 0.002862 | 1.3140 | 0.007099 | 18 | 0.000928 | 1.0243 | 0.000631 |
| 4 | 0.000385 | 1.1339 | 19 | 0.4244 | 0.000116 | ||
| 5 | 0.004214 | 1.1543 | 0.025158 | 20 | 0.000144 | 1.4166 | |
| 6 | 0.000388 | 0.3495 | 0.022878 | 21 | 0.000053 | 0.6046 | 0.000333 |
| 7 | 0.000645 | 1.6229 | 0.002207 | 22 | 0.000378 | 0.5443 | 0.013914 |
| 8 | 0.004837 | 2.8802 | 0.002156 | 23 | 0.000224 | 24.9100 | 0.225340 |
| 9 | 0.001377 | 0.5892 | 0.000737 | 24 | 0.000115 | 0.8915 | 0.000031 |
| 10 | 0.021098 | 1.4429 | 0.000059 | 25 | 0.000170 | 1.3478 | 0.000002 |
| 11 | 0.008886 | 1.1245 | 0.017660 | 26 | 0.001646 | 3.4975 | 0.000026 |
| 12 | 0.035444 | 1.5373 | 0.028255 | 27 | 0.054930 | 0.9969 | 0.027064 |
| 13 | 0.000131 | 2.1120 | 0.000030 | 28 | 0.000052 | 0.7414 | 0.000347 |
| 14 | 0.000035 | 0.6274 | 0.000038 | 29 | 0.004808 | 0.0337 | 0.312700 |
| 15 | 0.000000062 | 0.5930 | 0.000640 | 30 | 0.001757 | 1.0714 | 0.015360 |
| Median | 0.000489 | 1.0170 | 0.001395 | ||||
Note that all k parameters were estimated with hyperbolic functions (not with exponential functions). n.a. indicates failure in estimating parameters in nonlinear regression [20].
Spearman's correlations between the discount rates in delay discounting (k), probability discounting (k), and decay rate of SP (k)
| Probability discounting ( | Decay rate of SP ( | |
| Delay discounting ( | ||
| Probability discounting ( |
A significant correlation between delay discounting and decay rate of SP was observed (Spearman's rank-order correlation, *:p < 0.05). Note that a (hyperbolic) decay rate of SP (subjective probability of obtaining a delayed reward) as a function of delay (k) is defined in SP(D) = 1/(1+kD) (see [13]).
Figure 2Vertical axis indicates group median of SP(D) (i.e., subjective probability of obtaining a reward at delay D) and horizontal axis indicates delay (days). The solid (red) and dotted (blue) curves are the hyperbolic and exponential functions respectively, best fitted to the SP(D) obtained in SPQ (see Methods). Note that hyperbolic decay model (red) proposed by Sozou [13] better fit data than exponential decay model (blue) (see Table 1 for AICc for each model).