The strength of a rat's eating reflex correlates with hunger level when strength is measured by the response frequency that precedes eating (B. F. Skinner, 1932a, 1932b). On the basis of this finding, Skinner argued response frequency could index reflex strength. Subsequent work documented difficulties with this notion because responding was affected not only by the strengthening properties of the reinforcer but also by the rate-shaping effects of the schedule. This article obviates this problem by measuring strength via methods from behavioral economics. This approach uses demand curves to map how reinforcer consumption changes with changes in the "price" different ratio schedules impose. An exponential equation is used to model these demand curves. The value of this exponential's rate constant is used to scale the strength or essential value of a reinforcer, independent of the scalar dimensions of the reinforcer. Essential value determines the consumption level to be expected at particular prices and the response level that will occur to support that consumption. This approach permits comparing reinforcers that differ in kind, contributing toward the goal of scaling reinforcer value.

Pigeons* key-peck rates under variable-ratio schedules are typically higher than under variable-interval schedules when between-schedule reinforcement rates are equated. Experiment 1 reproduced this between-schedule rate difference in a multiple variable-ratio, variable-interval schedule. However, when the short interresponse times typically reinforced under variable ratios were reqvured for variable-interval reinforcement, between-component rate differences diminished. Experiment 2 replicated Experiment 1 except that the long interresponse times reinforced under variable-interval schedules were,required for variable-ratio reinforcement. This . manipulation eliminated between-sehedule rate differences. In Experiment 3, one multiple-schedule component was at tandem variable-ratio, variable-interval schedule and the other was a tandem variable-interval, variable-ratio schedule. Unlike Experiments 1 and 2, each tandem had the same correlation between response rate and reinforcement rate. Therefore, only between-component differences in interresponse-time reinforcement could account for the higher rates maintained by the tandem terminating with the variable-ratio schedule. In a simulation, Shimp's (1969) interresponse-time response rule was used as an algorithm in a computer simulation to mimic the between-schedule rate difference. The results of the experiments and simulation show that interresponse-time reinforcement (a molecular factor), and not the feedback function between response rate and reinforcement rate (a molar factor), accounts for higher response rates under variable-ratio schedules and suggests that molecular accounts will prove more fruitful than molar accounts in explaining behavioral output. . Skinner (1938) proposed that response rate equivalent reinforcement rates, these schedules should serve as the dependent variable for differ in their reinforcing effectiveness. A secscaling the strength or vigor of schedule-main-ond interpretation remains possible: Responsetained behavior. The consistent interdepen-rate differences might reflect not differences dence he found between rates of responding in the strength of behavior that different and reinforcement spoke for the reasonable* schedules engender, but differences in the reness of this proposition. Nevertheless, the stat-inforcement contingencies characterizing difure'of this measure has been jeopardized in ferent schedules. recent years by the finding that different An exemplar of this problem can be seen schedules providing equal rates of reinforce-in a comparison of behavior maintained under ment produce consistently unequal response variable-interval (VI) and variable-ratio (VR) rates. According to Skinner, despite their schedules of reinforcement. These schedules differ in that the delivery of the reinforcerde-_1 ; '-r-pends on a response after elapsed time in the _,.. ,. . .. .. XT ,. ,-"-•"-VI and on number of responses in the VR.

Ben-Ami Bartal et al. (Science 334:1427-1430, 2011) showed that a rat in an open space (free rat) would touch the front door of a restraining tube to open its rear door, thereby enabling a rat trapped within (trapped rat) to enter a larger space that was farther away from the free rat. Since opening the rear door distanced the trapped rat from the free rat, Ben-Ami Bartal et al. argued free-rat behavior could not be motivated by the pursuit of social contact. Instead, this rat was empathically motivated, its goal being to reduce the presumed distress of the rat trapped in the restraining tube. In two experiments, we show that (a) a free rat will not learn to touch the front door to open the rear door when it is the first condition of the experiment; (b) over time, a trapped rat will often return to a restraining tube despite its presumed aversiveness; and (c) a free rat experienced in touching the front door will continue to touch it even if touching does not free the trapped rat. We explain these results and Ben-Ami Bartal et al.'s in terms of two processes, neophobia and the pursuit of social contact. When first placed in a restraining tube, neophobia causes the trapped rat to escape the tube when the rear door is opened. Across sessions, neophobia diminishes, permitting the rats' pursuit of social contact to emerge and dominate free- and trapped-rat behavior.

Each of 4 female capuchin monkeys ("model") was paired with another female capuchin ("witness") in an adjacent cage. In Phases 1 and 3, a model could remove a grape from the experimenter's hand while the witness watched. The witness was then offered a slice of cucumber, a less preferred food. Trials alternated between subjects 50 times, defining a session. In Phases 2 and 4, both were offered cucumber. Witness rejections of cucumber were infrequent and were not dependent on whether models received grape or cucumber. When models were offered cucumber, they rejected it at higher rates than did witnesses. These results fail to support findings of Brosnan and de Waal. An account based on the frustration effect accommodates these results and those of Brosnan and de Waal.

The exponential model of demand accommodated the data variance for all cocaine and food demand curves. Compared to food, cocaine is a good of lower essential value.