Response strength and temporal control in fixed-interval schedules

Grace, Randolph C.; Nevin, John A.

doi:10.3758/bf03200266

Cited by 34 publications

(117 citation statements)

References 33 publications

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“…The finding that the effects of reinforcer magnitude on response rate and rate dependency do not covary stands at odds with the findings of Grace and Nevin (2000) using the peak interval procedure. It is possible that rate dependency is not related to temporal control in the same way as the peak interval procedure.…”

Section: Discussioncontrasting

confidence: 58%

“…Additionally, Grace and Nevin (2000) showed that associative relationships determining resistance to change of overall responding may extend to the temporal organization of behavior. Given that rate dependency may be understood as a loss of temporal organization in schedule-controlled behavior, and our general procedures are similar to those used to examine resistance to change, a resistance-to-change interpretation presents itself as an attractive account for our findings.…”

Section: Discussionmentioning

confidence: 99%

“…Grace and Nevin (2000) examined the relationship between reinforcer magnitude and temporal control using a peak interval procedure. During peak interval procedures, responding is established on regular FI schedules.…”

Section: Introductionmentioning

confidence: 99%

“…Performance on probe trials is characterized by an increasing response rates that peak near the time reinforcers are normally collected and then decrease. Grace and Nevin (2000) found that typical tests of resistance to change shifted the peak response rate to earlier points in the interval; increasing reinforcer magnitude, moreover, attenuated the extent of the shift, which led Grace and Nevin to conclude that the resistance of overall response output and temporal control were affected similarly by variables governing resistance to change (see also Odum et al, 2005). Note also that the results on temporal pattern could be conceptualized in terms of a rate-dependent effect.…”

Section: Introductionmentioning

confidence: 99%

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Reinforcer magnitude and rate dependency

Pinkston

Ginsburg²,

Lamb³

2014

Behavioural Pharmacology

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In many circumstances, reinforcer magnitude appears to modulate the rate-dependent effects of drugs, such that when schedules arrange for relatively larger reinforcer magnitude, rate dependency is attenuated compared to behavior maintained by smaller magnitudes. The current literature on resistance to change suggests that increased reinforcer density strengthens operant behavior, and such strengthening effects appear to extend to the temporal control of behavior. As rate dependency may be understood as a loss of temporal control, the effects of reinforcer magnitude on rate dependency may be due to increased resistance to disruption of temporally controlled behavior. In the present experiments, pigeons earned different magnitudes of grain during signaled components of a multiple fixed-interval schedule. Three drugs, clonidine, haloperidol, and morphine, were examined: all three decreased overall rates of key pecking; however, only the effects of clonidine were attenuated as reinforcer magnitude increased. An analysis of within-interval performance found rate-dependent effects for clonidine and morphine, but those effects were not modulated by reinforcer magnitude. Additionally, we included prefeeding and extinction conditions, standard tests used to measure resistance to change. In general, rate-decreasing effects of prefeeding and extinction were attenuated by increasing reinforcer magnitudes. Rate-dependent analyses of prefeeding showed rate-dependency following those tests, but in no case were these effects modulated by reinforcer magnitude. The results suggest a resistance-to-change interpretation of the effects of reinforcer magnitude on rate dependency is not viable.

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Section: Discussioncontrasting

confidence: 58%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reinforcer magnitude and rate dependency

Pinkston

Ginsburg²,

Lamb³

2014

Behavioural Pharmacology

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“…The mean of the distribution of response rates averaged over empty trials (peak time) is then perhaps a better measure of timing than wait time because motivational variables are assumed to affect only the height and spread of the response-rate distribution, not its mean. This assumption is only partially true (Grace & Nevin 2000, MacEwen & Killeen 1991, Plowright et al 2000.…”

Section: Interval Timingmentioning

confidence: 99%

Operant Conditioning

Staddon

Cerutti

2003

Annu. Rev. Psychol.

343

213

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Operant behavior is behavior "controlled" by its consequences. In practice, operant conditioning is the study of reversible behavior maintained by reinforcement schedules. We review empirical studies and theoretical approaches to two large classes of operant behavior: interval timing and choice. We discuss cognitive versus behavioral approaches to timing, the "gap" experiment and its implications, proportional timing and Weber's law, temporal dynamics and linear waiting, and the problem of simple chain-interval schedules. We review the long history of research on operant choice: the matching law, its extensions and problems, concurrent chain schedules, and self-control. We point out how linear waiting may be involved in timing, choice, and reinforcement schedules generally. There are prospects for a unified approach to all these areas.

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Preference, resistance to change, and the cumulative decision model

Grace

2018

J Exper Analysis Behavior

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According to behavioral momentum theory , preference in concurrent chains and resistance to change in multiple schedules are independent measures of a common construct representing reinforcement history. Here I review the original studies on preference and resistance to change in which reinforcement variables were manipulated parametrically, conducted by Nevin, Grace and colleagues between 1997 and 2002, as well as more recent research. The cumulative decision model proposed by Grace and colleagues for concurrent chains is shown to provide a good account of both preference and resistance to change, and is able to predict the increased sensitivity to reinforcer rate and magnitude observed with constant-duration components. Residuals from fits of the cumulative decision model to preference and resistance to change data were positively correlated, supporting the prediction of behavioral momentum theory. Although some questions remain, the learning process assumed by the cumulative decision model, in which outcomes are compared against a criterion that represents the average outcome value in the current context, may provide a plausible model for the acquisition of differential resistance to change.

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Response strength and temporal control in fixed-interval schedules

Cited by 34 publications

References 33 publications

Reinforcer magnitude and rate dependency

Reinforcer magnitude and rate dependency

Operant Conditioning

Preference, resistance to change, and the cumulative decision model

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