On the Relation Between Preference and Resistance to Change

Grace, Randolph C.; Nevin, John A.

doi:10.1901/jeab.1997.67-43

Cited by 62 publications

(148 citation statements)

References 39 publications

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“…We have measured relative response strength as the difference in log proportion of baseline, log(Bxl/B o 1 ) -log(BjB o2 ) (Grace & Nevin, 1997), plugging in different measures of behavior. Because this measure may be positive or negative (i.e., positive in the case of the richer component's being more resistant to change, but negative for the PREE-type effects in Experiment 2), we can compare the sensitivity of the various measures to differential reinforcement by taking absolute values.…”

Section: Discussionmentioning

confidence: 99%

“…Spetch and Dunn (1987) studied pigeons' preference in concurrent chains for FI schedules that provided reinforcement on either 100% or 33% of the trials and found strong preference for the 100% schedule as long as the no-food trials on the 33% alternative were not differentially signaled. Because reinforcement parameters generally have the same effects on preference and resistance to change (Grace & Nevin, 1997), we expected responding in the rich component to be more resistant to change, again with the possible exception of extinction because the generalization decrement during test for the rich component was greater.…”

Section: Methodsmentioning

confidence: 99%

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Response strength and temporal control in fixed-interval schedules

Grace

Nevin

2000

Animal Learning & Behavior

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Pigeons responded in a two-component peak procedure in which the components differed in terms of reinforcement magnitude (Experiment 1), immediacy (Experiment 2), or probability (Experiment 3). The prediction of behavioral momentum theory that responding in the relatively richer component should be more resistant to change was tested by (1) presenting response-independent food in the intervals between components according to a variable-time (VT) schedule, (2) prefeeding, and (3) extinction. In all the experiments, peak location in baseline occurred earlier, relative to the schedule value in the richer component. Peak response rate was more resistant to change in the richer component during the VT and prefeeding tests, and change in peak rate was more sensitive to differential reinforcement than change in overall response rate. Changes in measures of performance on peak trials during the disruptor tests were partially consistent with predictions of the behavioral theory of timing. The results suggest that peak response rate provides a more sensitive index of resistance to change for fixedinterval schedules than does overall response rate and that reinforcement strengthens both peak responding and temporal control.Nevin and colleagues proposed that response strength can be measured as the resistance to change of behavior when a disruptor, such as prefeeding, response-independent food, or extinction, is applied. In a typical experiment, Nevin (1974) arranged two variable-interval (VI) schedules for pigeons in an operant chamber. The schedules differed in terms of their reinforcement rate (rich or lean) and were signaled by distinctive stimuli (i.e., a two-component multiple schedule). After baseline training, free food was presented independent of responding between the components. Nevin (1974) found that response rate during the rich schedule decreased less, relative to baseline, than did response rate during the lean schedule. These results and others have led to the development of behavioral momentum theory, which assumes that resistance to change and response rate are analogous to the mass and velocity of a moving object in Newtonian mechanics. According to this theory, resistance to change is a measure of response strength, or behavioral mass, which is positively related to the rate, im-

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Response strength and temporal control in fixed-interval schedules

Grace

Nevin

2000

Animal Learning & Behavior

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“…The momentum analysis has been derived and elaborated from work with laboratory animals (e.g., Grace & Nevin, 1997;Nevin, Mandell, & Atak, 1983;Nevin, Tota, Torquato, & Shull, 1990). Three studies with humans have demonstrated momentum effects under laboratory conditions (Cohen, 1996;Dube, Mazzitelli, Lombard, & McIlvane, 2000;Mace et al, 1990; for other applications of the momentum metaphor to human behavior see Mace, 1996;Mace, Lalli, Shea, & Nevin, 1992;Nevin, 1996;Plaud & Gaither, 1996).…”

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Behavioral Momentum in Computer‐presented Discriminations in Individuals With Severe Mental Retardation

Dube

McIlvane

2001

J Exper Analysis Behavior

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Behavioral momentum was examined in 2 individuals with severe mental retardation via withinsubject manipulations of obtained reinforcer rates. Subjects performed self-paced discrimination problems presented on a touch screen computer monitor. Two different problems, Tasks A and B, alternated in blocks of 15 trials on a multiple schedule. Reinforcers were snack foods. The reinforcement schedule for Task A was continuous (fixed-ratio 1), and the schedule for Task B was continuous in some conditions and variable ratio in other conditions. Behavioral momentum was assessed in test sessions by prefeeding, presenting response-independent food, and making available alternatives to the tasks. When the obtained reinforcer rate for Task A was at least twice that for Task B, resistance to change was greater for Task A. When both reinforcer rates and response rates were approximately equal for the two tasks, resistance to change was approximately equal. These results are consistent with behavioral momentum effects. They extend previous findings with humans by examining momentum in self-initiated discrete-trial discrimination tasks with ratio schedules, and by isolating relative reinforcer rates as a controlling variable via within-subject manipulations.

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“…On the basis of these results, Nevin has proposed behavioral momentum theory, which assumes that resistance to change provides a measure of "behavioral mass," or response strength that is independent of response rate (see Nevin & Grace, 2000, for a review). Grace and Nevin (1997) showed that resistance to change and preference in concurrent chains are correlated, leading Nevin and Grace (2000) to propose that "behavioral mass" and "value" are different labels for the same construct that represents what is learned about the conditions of reinforcement associated with a particular stimulus.…”

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Contrast and value: Beyond the work ethic effect. A reply to Zentall (2008)

Arantes

Grace

2008

Learning & Behavior

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Zentall (2008) challenges Arantes and Grace's (2008) failure to replicate Clement, Feltus, Kaiser, and Zentall (2000) Learning & Behavior 2008, 36 (1), 26-28 doi: 10.3758/LB.36.1.26 J. Arantes, joana.arantes@canterbury.ac.nz; R. C. Grace, randolph.grace@canterbury.ac.nz Arantes and Grace (2008) report two experiments that attempted to (1) replicate the work ethic effect reported by Clement, Feltus, Kaiser, and Zentall (2000); (2) determine whether the results were similar for simultaneous and successive discrimination training; and (3) analyze the effects of amount of training on the preference for the high-effort stimulus. However, both experiments failed to replicate Clement et al.'s results. Instead of a consistent preference for the high-effort stimuli, we found that for both S and S test trials, preference for the FR20 stimulus depended on the initiating event that preceded the choice stimuli. Specifically, pigeons preferred the FR20 stimulus on trials preceded by FR1 or by no response requirement and preferred the FR1 stimulus on trials preceded by FR20. We also found that preferences on test trials became more extreme as amount of training increased and were generally stronger on S than on S trials.In his commentary, Zentall (2008) argues that our failures to replicate Clement et al. (2000) should not be taken as evidence that the work ethic effect is unreliable. He suggests that our results may be due to methodological shortcomings such as insufficient training or subjects' experimental histories, and that they are actually consistent with those of Clement et al. when examined closely. However, we do not find these arguments convincing.We are puzzled by Zentall's comment that we trained the pigeons to criterion and then tested them in Experiment 1, and consequently failed to replicate the work ethic effect because of the "minimal amount of training provided" (p. 20). This is incorrect; our pigeons received more training than did those of Clement et al. (2000). In Experiment 1, our pigeons completed an average of 37.2 baseline sessions prior to test. Given that the average number of sessions to reach criterion in the simultaneous condition was 2.1, our pigeons had an average of 35.1 sessions of overtraining prior to test, as compared with Clement et al.'s, which had a total of 23.0 sessions (3.0 sessions to reach criterion plus 20.0 sessions of overtraining). Overall, the training our pigeons received was comparable to the amount that Singer, Berry, and Zentall (2007) found was necessary for a reliable within-contrast effect to emerge. Thus, it is unlikely that our failure to replicate Clement et al. in Experiment 1 was due to insufficient training.Regarding our Experiment 2, Zentall claims that the preference for the stimuli that followed the greater response requirement in baseline trials increased as more training was provided. He calculates the overall average preferences in the S and S trials for the subgroup of 4 pigeons that received extended training as 56% and 65%, respectively, concludin...

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On the Relation Between Preference and Resistance to Change

Cited by 62 publications

References 39 publications

Response strength and temporal control in fixed-interval schedules

Response strength and temporal control in fixed-interval schedules

Behavioral Momentum in Computer‐presented Discriminations in Individuals With Severe Mental Retardation

Contrast and value: Beyond the work ethic effect. A reply to Zentall (2008)

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