A modular theory of learning and performance

Guilhardi, Paulo; Yi, Linlin; Church, Russell M.

doi:10.3758/bf03196805

Cited by 43 publications

(61 citation statements)

References 35 publications

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“…This latter model is in keeping with an abrupt switch between responding and not responding that is typically assumed by timing models (Gibbon, 1977;Guilhardi et al, 2007). It is also consistent with the assumption made by these models that the relative weight of each component to the bimodal frequency distribution changes at different time points within the trial.…”

Section: Discussionsupporting

confidence: 82%

“…How might timing theories of conditioning, or theories based on associative strength, accommodate the present evidence that changes in responding during a trial reflect a shift in both the probability of being in a response state and the strength of responding in that state? A combination of these factors has been incorporated in the modular extension of packet theory (Guilhardi et al, 2007). In this theory, bouts of responding are initiated as the output of a decision process.…”

Section: Discussionmentioning

confidence: 99%

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Changes in the distribution of response rates across the CS-US interval: Evidence that responding switches between two distinct states.

Harris

2015

Journal of Experimental Psychology: Animal Learning and Cogniti

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Two experiments used the peak procedure to examine timing of conditioned responses in a magazine approach paradigm with rats. A conditioned stimulus (CS) was reinforced with food on 50% of trials. Food was delivered at a fixed time, either 20 s, 30 s or 40 s into the CS presentation. Response rates were recorded during non-reinforced CS presentations that extended well beyond the scheduled time of food delivery. The mean response rate (averaged over many trials) increased during the CS, peaking at the expected time of reinforcement, and decreased again. Detailed analyses of the frequency distribution of response rates showed that responding was described by two distinct distributions, consistent with the rat being in a low response state on some trials and in a high response state on other trials. Modeling of these frequency distributions showed that the systematic rise and fall in response rate across a trial was primarily explained by a change in the proportion of time that the rat spent in the low versus high response state. However, the change in responding was also explained in part by a continuous shift in the high response state, such that responding in that state increased and then decreased gradually across the trial. These results support accounts that describe response timing as an abrupt change from low to high responding during the CS, but also provide evidence for a continuous change in conditioning strength across the duration of the CS. The implications of these findings for timing and associative theories of conditioning are discussed.

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Section: Discussionsupporting

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Changes in the distribution of response rates across the CS-US interval: Evidence that responding switches between two distinct states.

Harris

2015

Journal of Experimental Psychology: Animal Learning and Cogniti

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“…The present generative performance model is also consistent, to some extent, with the Packet theory of timing Guilhardi, Keen, MacInnis, & Church, 2005;Guilhardi, Yi, & Church, 2007;Kirkpatrick, 2002;Kirkpatrick & Church, 2003 also see Dragoi et al, 2003, for an alternative to Packet theory). Packet theory is the only theory of timing that operates on the assumption of bout-like behavior; it stipulates that responding in interval schedules of reinforcement is a composite of the temporal structure of bouts and the rate at which bouts are generated.…”

Section: Implications For Timing Researchsupporting

confidence: 84%

Interval timing under a behavioral microscope: Dissociating motivational and timing processes in fixed-interval performance

Daniels

Sanabria

2016

Learn Behav

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The distribution of latencies and interresponse times (IRTs) of rats was compared between two fixedinterval (FI) schedules of food reinforcement (FI 30 s and FI 90 s), and between two levels of food deprivation. Computational modeling revealed that latencies and IRTs were well described by mixture probability distributions embodying two-state Markov chains. Analysis of these models revealed that only a subset of latencies is sensitive to the periodicity of reinforcement, and prefeeding only reduces the size of this subset. The distribution of IRTs suggests that behavior in FI schedules is organized in bouts that lengthen and ramp up in frequency with proximity to reinforcement. Prefeeding slowed down the lengthening of bouts and increased the time between bouts. When concatenated, latency and IRT models adequately reproduced sigmoidal FI response functions. These findings suggest that behavior in FI schedules fluctuates in and out of schedule control; an account of such fluctuation suggests that timing and motivation are dissociable components of FI performance. These mixturedistribution models also provide novel insights on the motivational, associative, and timing processes expressed in FI performance. These processes may be obscured, however, when performance in timing tasks is analyzed in terms of mean response rates.

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“…These theories include packet theory (Kirkpatrick, 2002;Kirkpatrick & Church, 2003) and the closely related modular theory of learning and performance (Guilhardi, Yi, & Church, 2007). In the fixed condition of Experiment 1, both the stimulus and the expected time from stimulus onset to reinforcement were reliable cues; in the varied condition, only the temporal cues provided a basis for differential responding.…”

Section: Discussionmentioning

confidence: 99%

Stimulus control in multiple temporal discriminations

2012

Self Cite

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In multiple fixed interval (FI) schedules, rats are trained to discriminate different FIs that are signaled by different stimuli. After extensive training, the different stimuli often acquire control over performance, observed by an earlier increase in responding for stimuli that signal shorter FIs, as compared with stimuli that signal longer FIs. The order in which the different FIs are trained, either intermixed across cycles or in blocks of several cycles, may seem irrelevant given that average performance at asymptote may be similar. In this study, rats were trained in two procedures with multiple FIs presented intermixed within sessions or in blocks of one interval per session. Similar performance was observed at asymptote, but an inspection of early cycles in each session revealed that different stimuli acquired control over performance only when trained intermixed within each session. Although the stimuli reliably signaled the upcoming FI, when trained in successive blocks of 60 cycles, rats rapidly adjusted performance early in the sessions on the basis of the temporal aspects of the task, and not on the basis of the stimulus presented in the current cycle. These results are discussed in terms of overshadowing of the stimuli by temporal cues and in terms of conditions under which a stimulus acquires control over performance.

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A modular theory of learning and performance

Cited by 43 publications

References 35 publications

Changes in the distribution of response rates across the CS-US interval: Evidence that responding switches between two distinct states.

Changes in the distribution of response rates across the CS-US interval: Evidence that responding switches between two distinct states.

Interval timing under a behavioral microscope: Dissociating motivational and timing processes in fixed-interval performance

Stimulus control in multiple temporal discriminations

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