Timing in trace conditioning of the nictitating membrane response of the rabbit (<i>Oryctolagus cuniculus</i>): Scalar, nonscalar, and adaptive features

Kehoe, E. James; Ludvig, Elliot Andrew; Sutton, Richard S.

doi:10.1101/lm.1942210

Cited by 7 publications

(5 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is known from the behavioural literature that the duration of the overt blink CR increases with increasing ISI [1,22], and if we are right in our suggestion that the Purkinje cell CR drives the overt CR, we should expect to see a similar relationship in our recordings. The data provide some support for such a relation.…”

Section: Time Course Of Purkinje Cell Crsupporting

confidence: 66%

Learning Stimulus Intervals—Adaptive Timing of Conditioned Purkinje Cell Responses

Jirenhed

Hesslow

2011

Cerebellum

View full text Add to dashboard Cite

Classical conditioning of motor responses, such as the eyeblink response, is an experimental model of associative learning and of adaptive timing of movements. A conditioned blink will have its maximum amplitude near the expected onset of the unconditioned blink-eliciting stimulus and it adapts to changes in the interval between the conditioned and unconditioned stimuli. Previous studies have shown that an eyeblink conditioning protocol can make cerebellar Purkinje cells learn to pause in response to the conditioned stimulus. According to the cerebellar cortical conditioning model, this conditioned Purkinje cell response drives the overt blink. If so, the model predicts that the temporal properties of the Purkinje cell response reflect the overt behaviour. To test this prediction, in vivo recordings of Purkinje cell activity were performed in decerebrate ferrets during conditioning, using direct stimulation of cerebellar mossy and climbing fibre afferents as conditioned and unconditioned stimuli. The results show that Purkinje cells not only develop a change in responsiveness to the conditioned stimulus. They also learn a particular temporal response profile where the timing, not only of onset and maximum but also of offset, is determined by the temporal interval between the conditioned and unconditioned stimuli.

show abstract

Section: Time Course Of Purkinje Cell Crsupporting

confidence: 66%

Learning Stimulus Intervals—Adaptive Timing of Conditioned Purkinje Cell Responses

Jirenhed

Hesslow

2011

Cerebellum

View full text Add to dashboard Cite

show abstract

“…This optimality property was repeatedly discovered in many experiments. For example, there exist optimal CS duration s CS (Kehoe et al 2009), optimal US intensity A 02 (Oswald et al 2009), optimal arousal A t (Berry and Swain 1989;Shors 2001), optimal ISI (Vogel et al 2004;Kehoe et al 2010). After the ISI change, additional training proved necessary to allow asymptotic responding at the new ISI (Steinmetz et al 2011).…”

Section: Optimal Values Of Trace Conditioning Parametersmentioning

confidence: 99%

“…16b), the falling CV curve is proportional to 1= ffiffiffiffi ffi M p , the other curves are plotted according to Eq. 12. b Experimental CV from Kehoe et al (2010). Note the qualitative agreement of modelpredicted curves with experimental ones, except for the unusual upward concavity of the Onset Latency curve, which is probably due to differences in abscissas in a and b graphs Cogn Neurodyn (2012) 6:377-398 391 a dramatic facilitatory effect on trace conditioning: the animals given theta-contingent training learned several times faster than those given non-theta-contingent training (Griffin et al 2004, Darling et al 2011, with the number of required trials reduced by a factor of up to 4 (Berry and Hoffmann 2011;Griffin et al 2004).…”

Section: The Central Role Of Theta-regulated Attentionmentioning

confidence: 99%

Towards a unified model of pavlovian conditioning: short review of trace conditioning models

Kryukov¹

2012

Cogn Neurodyn

View full text Add to dashboard Cite

There are three basic paradigms of classical conditioning: delay, trace and context conditioning where presentation of a conditioned stimulus (CS) or a context typically predicts an unconditioned stimulus (US). In delay conditioning CS and US normally coterminate, whereas in trace conditioning an interval of time exists between CS termination and US onset. The modeling of trace conditioning is a rather difficult computational problem and is a challenge to the behavior and connectionist approaches mainly due to a time gap between CS and US. To account for trace conditioning, Pavlov (Conditioned reflexes: an investigation of the physiological activity of the cerebral cortex, Oxford University Press, London, 1927) postulated the existence of a stimulus "trace" in the nervous system. Meanwhile, there exist many other options for solving this association problem. There are several excellent reviews of computational models of classical conditioning but none has thus far been devoted to trace conditioning. Eight representative models of trace conditioning aimed at building a prospective model are being reviewed below in a brief form. As a result, one of them, comprising the most important features of its predecessors, can be suggested as a real candidate for a unified model of trace conditioning.

show abstract

“…It is a manifestation of Weber's Law and of time-scale invariance, both of which are quantitatively important aspects of associative learning (Gallistel and Gibbon, 2000). The range covered by the CoVs of the pause offset latencies is the same as that observed in behavioral experiments on the timing of conditional responses (Gallistel and Gibbon, 2000;Kehoe et al, 2010).…”

Section: Pause Statistics Scale With the Training Intervalmentioning

confidence: 72%

Quantitative properties of the creation and activation of a cell-intrinsic duration-encoding engram

Gallistel

Johansson²,

Jirenhed³

et al. 2022

Front. Comput. Neurosci.

View full text Add to dashboard Cite

The engram encoding the interval between the conditional stimulus (CS) and the unconditional stimulus (US) in eyeblink conditioning resides within a small population of cerebellar Purkinje cells. CSs activate this engram to produce a pause in the spontaneous firing rate of the cell, which times the CS-conditional blink. We developed a Bayesian algorithm that finds pause onsets and offsets in the records from individual CS-alone trials. We find that the pause consists of a single unusually long interspike interval. Its onset and offset latencies and their trial-to-trial variability are proportional to the CS-US interval. The coefficient of variation (CoV = σ/μ) are comparable to the CoVs for the conditional eye blink. The average trial-to-trial correlation between the onset latencies and the offset latencies is close to 0, implying that the onsets and offsets are mediated by two stochastically independent readings of the engram. The onset of the pause is step-like; there is no decline in firing rate between the onset of the CS and the onset of the pause. A single presynaptic spike volley suffices to trigger the reading of the engram; and the pause parameters are unaffected by subsequent volleys. The Fano factors for trial-to-trial variations in the distribution of interspike intervals within the intertrial intervals indicate pronounced non-stationarity in the endogenous spontaneous spiking rate, on which the CS-triggered firing pause supervenes. These properties of the spontaneous firing and of the engram read out may prove useful in finding the cell-intrinsic, molecular-level structure that encodes the CS-US interval.

show abstract

Timing in trace conditioning of the nictitating membrane response of the rabbit (Oryctolagus cuniculus): Scalar, nonscalar, and adaptive features

Cited by 7 publications

References 49 publications

Learning Stimulus Intervals—Adaptive Timing of Conditioned Purkinje Cell Responses

Learning Stimulus Intervals—Adaptive Timing of Conditioned Purkinje Cell Responses

Towards a unified model of pavlovian conditioning: short review of trace conditioning models

Quantitative properties of the creation and activation of a cell-intrinsic duration-encoding engram

Contact Info

Product

Resources

About