Do rats represent time logarithmically or linearly?

Yi, Linlin

doi:10.1016/j.beproc.2008.10.004

Cited by 22 publications

(32 citation statements)

References 15 publications

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“…For instance, there has been a persistent discussion on whether the timing of learned events is encoded on a linear or logarithmic scale (Gibbon and Church, 1981; Machado and Vasconcelos, 2006; Yi 2009). The model of timing advanced here does not resolve this dispute but suggests an important consideration so far neglected: that the scale on which time is encoded, whichever it may be, must be flexible.…”

Section: Discussionmentioning

confidence: 99%

Adaptation of timing behavior to a regular change in criterion

Sanabria

Oldenburg

2014

Behavioural Processes

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This study examined how operant behavior adapted to an abrupt but regular change in the timing of reinforcement. Pigeons were trained on a fixed interval (FI) 15-s schedule of reinforcement during half of each experimental session, and on an FI 45-s (Experiment 1), FI 60-s (Experiment 2), or extinction schedule (Experiment 3) during the other half. FI performance was well characterized by a mixture of two gamma-shaped distributions of responses. When a longer FI schedule was in effect in the first half of the session (Experiment 1), a constant interference by the shorter FI was observed. When a shorter FI schedule was in effect in the first half of the session (Experiments 1, 2, and 3), the transition between schedules involved a decline in responding and a progressive rightward shift in the mode of the response distribution initially centered around the short FI. These findings are discussed in terms of the constraints they impose to quantitative models of timing, and in relation to the implications for information-based models of associative learning.

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Section: Discussionmentioning

confidence: 99%

Adaptation of timing behavior to a regular change in criterion

Sanabria

Oldenburg

2014

Behavioural Processes

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“…However, if these findings hold under further experimental tests, the fact that responding was most accurately predicted using reinforcement probability-weighted, logarithmically-scaled durations provides a modicum of support that time is subjectively perceived on a logarithmic scale, rather than a linear scale. The question of linear versus logarithmic timing is a long debated topic (Gibbon, 1977; Staddon & Higa, 1999) and support for both subjective scales has been obtained (Gibbon & Church, 1981; Yi, 2009). One of the most consistent findings related to this debate comes from the temporal bisection task in which the point of subjective equality occurs at the geometric mean (e.g., a 2s vs. 8s bisection yields the point of subjective equality at the geometric mean of 4s) (Allan & Gibbon, 1991; Church & Deluty, 1977).…”

Section: Discussionmentioning

confidence: 99%

Stimulus compounding in interval timing: The modality–duration relationship of the anchor durations results in qualitatively different response patterns to the compound cue.

Swanton

Matell

2011

Journal of Experimental Psychology: Animal Behavior Processes

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We have previously demonstrated that rats trained on a two-duration peak procedure in which 2 different modal signals (i.e., tone and houselight) predicted probabilistic reinforcement availability at 2 different times (10s and 20s), would respond in a scalar manner at a time between the trained durations in response to the simultaneous compound cue (tone + houselight). The present experiments evaluated whether this scalar response pattern would remain with greater relative separation between the anchor durations. Results revealed an effect of the modality-duration relationship, such that scalar responding was seen on compound trials in rats trained that the auditory stimulus signaled the shorter duration, while the visual stimulus signaled the longer duration, but not in the reverse condition. In those rats showing scalar responding on compound trials, post-hoc analyses demonstrated that the peak time of compound responding was most accurately predicted by the reinforcement probability weighted average of anchor peak times. In contrast, rats trained that the visual stimulus signaled the shorter duration, while the auditory stimulus signaled the longer duration, responded in a highly rightward skewed manner. In these subjects, initiation of responding to the compound stimulus appeared to be controlled by the visual stimulus only, while response terminations reflected control by both modal stimuli. These latter data provide evidence of separate determinants of response initiation and termination.

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“…Moreover, the subjective midpoint between two different time intervals lies near the geometric rather than the arithmetic mean (Gallistel, 1990;Gibbon et al, 1997;Buhusi and Meck, 2005). These findings are well accounted for by assuming that time is represented on a logarithmic scale in the nervous system (Church and Deluty, 1977;Staddon and Higa, 1999;Roberts, 2006;Yi, 2009). However, they can also be accounted for by assuming that time is represented on a linear scale, but with proportionally increasing variability (Gibbon, 1977;Gibbon and Church, 1981;Roberts, 1981;Church and Gibbon, 1982;Gallistel, 1999;Wearden and Jones, 2007;scalar variability).…”

Section: Introductionmentioning

confidence: 99%

Neural Correlates of Interval Timing in Rodent Prefrontal Cortex

et al. 2013

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Time interval estimation is involved in numerous behavioral processes, but its underlying neural mechanisms remain unclear. In particular, it has been controversial whether time is encoded on a linear or logarithmic scale. Based on our previous finding that inactivation of the medial prefrontal cortex (mPFC) profoundly impairs rat's ability to discriminate time intervals, we investigated how the mPFC processes temporal information by examining activity of mPFC neurons in rats performing a temporal bisection task. Many mPFC neurons conveyed temporal information based on monotonically changing activity profiles over time with negative accelerations, so that their activity profiles were better described by logarithmic than linear functions. Moreover, the precision of time-interval discrimination based on neural activity was lowered in proportion to the elapse of time, but without proportional increase in neural variability, which is well accounted for by logarithmic, but not by linear functions. As a population, mPFC neurons conveyed precise information about the elapse of time with their activity tightly correlated with the animal's choice of target. These results suggest that the mPFC might be part of an internal clock in charge of controlling interval-timing behavior, and that linearly changing neuronal activity on a logarithmic time scale might be one way of representing the elapse of time in the brain.

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Do rats represent time logarithmically or linearly?

Cited by 22 publications

References 15 publications

Adaptation of timing behavior to a regular change in criterion

Adaptation of timing behavior to a regular change in criterion

Stimulus compounding in interval timing: The modality–duration relationship of the anchor durations results in qualitatively different response patterns to the compound cue.

Neural Correlates of Interval Timing in Rodent Prefrontal Cortex

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