Overexpectation: Response Loss During Sustained Stimulus Compounding in the Rabbit Nictitating Membrane Preparation

Kehoe, E. James; White, Natasha E.

doi:10.1101/lm.77604

Cited by 17 publications

(12 citation statements)

References 71 publications

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“…Since the first CS would be expected to generate a Purkinje cell CR that disinhibits the cerebellar nucleus and thus inhibits the olive, such blocking is nicely explained by the nucleo-olivary circuit [9,16]. Cerebellar-induced inhibition of the olive might also explain why, when a subject has learned to respond reliably to two independent CSs, presentation of these CSs together, even when paired with the US, causes extinction, the so-called overexpectation [20,21]. Although consistent with the available evidence, these suggestions remain to be rigorously tested.…”

Section: Purkinje Cell Complex Spike Firingmentioning

confidence: 96%

Simple and Complex Spike Firing Patterns in Purkinje Cells During Classical Conditioning

2008

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Classical blink conditioning is known to depend critically on the cerebellum and the relevant circuitry is gradually being unravelled. Several lines of evidence support the theory that the conditioned stimulus is transmitted by mossy fibers to the cerebellar cortex whereas the unconditioned stimulus is transmitted by climbing fibers. This view has been dramatically confirmed by recent Purkinje cell recordings during training with a classical conditioning paradigm. We have tracked the activity of single Purkinje cells with microelectrodes for several hours in decerebrate ferrets during learning, extinction, and relearning. Paired peripheral forelimb and periocular stimulation, as well as paired direct stimulation of cerebellar afferent pathways (mossy and climbing fibers) causes acquisition of a pause response in Purkinje cell simple spike firing. This conditioned Purkinje cell response has temporal properties that match those of the behavioral response. Its latency varies with the interstimulus interval and it responds to manipulations of the conditioned stimulus in the same way that the blink does. Complex spike firing largely mirrors the simple spike behavior. We have previously suggested that cerebellar learning is subject to a negative feedback control via the inhibitory nucleo-olivary pathway. As the Purkinje cell learns to respond to the conditioned stimulus with a suppression of simple spikes, disinhibition of anterior interpositus neurons would be expected to cause inhibition of the inferior olive. Observations of complex spike firing in the Purkinje cells during conditioning and extinction confirm this prediction. Before training, complex spikes are unaffected or facilitated by the conditioned stimulus, but as the simple spike pause response develops, spontaneous and stimulus-evoked complex spikes are also strongly suppressed by the conditioned stimulus. After extinction of the simple spike pause response, the complex spikes reappear.

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Section: Purkinje Cell Complex Spike Firingmentioning

confidence: 96%

Simple and Complex Spike Firing Patterns in Purkinje Cells During Classical Conditioning

2008

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“…Similar to blocking, overexpectation is a robust finding. It has been observed in a number of species and conditioning preparations (e.g., Rescorla 1970Rescorla , 1999Kamin and Gaioni 1974;Kremer 1978;Khallad and Moore 1996;Lattal and Nakajima 1998;Kehoe and White 2004;McNally et al 2004a). …”

Section: Overexpectation and Extinctionmentioning

confidence: 99%

Predicting danger: The nature, consequences, and neural mechanisms of predictive fear learning

McNally¹,

Westbrook²

2006

Learn. Mem.

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The ability to detect and learn about the predictive relations existing between events in the world is essential for adaptive behavior. It allows us to use past events to predict the future and to adjust our behavior accordingly. Pavlovian fear conditioning allows anticipation of sources of danger in the environment. It guides attention away from poorer predictors toward better predictors of danger and elicits defensive behavior appropriate to these threats. This article reviews the differences between learning about predictive relations and learning about contiguous relations in Pavlovian fear conditioning. It then describes behavioral approaches to the study of these differences and to the examination of subtle variations in the nature and consequences of predictive learning. Finally, it reviews recent data from rodent and human studies that have begun to identify the neural mechanisms for direct and indirect predictive fear learning.The ability to detect and learn about predictive relations existing between events in the world is essential for adaptive behavior. Such learning allows us to use past events to predict the future and to adjust our behavior accordingly. Learning about predictive relations depends on what is already known about the events in the relation: If an outcome is unexpected, we learn about cues that predict its occurrence; if the outcome is already expected, information provided by other cues about its occurrence is redundant and our learning about them is impaired. Pavlovian fear conditioning enables learning about, and adaptive responding to, sources of danger in the environment. It involves encoding the predictive relation between a conditioned stimulus (CS) and an aversive unconditioned stimulus (US) stimulus. In this way Pavlovian fear conditioning allows anticipation of sources of danger in the environment. It guides attention away from poorer predictors toward better predictors of danger, and it elicits defensive behavior appropriate to these threats.A wealth of data accumulated over the past Ն20 years has provided significant insights into the neurobiological mechanisms underlying the formation of fear memories in the mammalian brain. These data support the view that the amygdala is essential for encoding, storing, and retrieving fear memories. In contrast to this knowledge of the brain mechanisms for storage of fear memories, the brain mechanisms for predicting danger are only just beginning to be understood. This article begins by reviewing the differences between learning about predictive relations and learning about contiguous relations in Pavlovian fear conditioning. It then describes some behavioral designs that permit differentiation between the neural mechanisms for predictive versus contiguity learning and also permit examination of the nature and consequences of predictive learning. Finally, it considers recent data from rodent and human experiments that reveal the brain mechanisms for predicting danger. Predicting danger: More than just contiguous relations Contingency v...

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“…A central tenet of the model is that the reinforcement value of a paired trial depends on the existing associative strength between the presented stimuli (3,4). Neural mechanisms for several phenomena related to the Rescorla-Wagner model have already been proposed (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16). In this paper, we present evidence from our eyeblink setup that builds on and advances prior thinking regarding the physiological basis of the RescorlaWagner model.…”

mentioning

confidence: 72%

“…This counterintuitive prediction has been confirmed in several learning paradigms including fear conditioning (25,26), appetitive conditioning (27,28), and eyeblink conditioning (10). The phenomenon is known as "overexpectation" because the subject may be said to "expect" a US that is more intense than the one it actually receives.…”

mentioning

confidence: 91%

Purkinje cell activity during classical conditioning with different conditional stimuli explains central tenet of Rescorla–Wagner model

Rasmussen

Zucca

Johansson

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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A central tenet of Rescorla and Wagner’s model of associative learning is that the reinforcement value of a paired trial diminishes as the associative strength between the presented stimuli increases. Despite its fundamental importance to behavioral sciences, the neural mechanisms underlying the model have not been fully explored. Here, we present findings that, taken together, can explain why a stronger association leads to a reduced reinforcement value, within the context of eyeblink conditioning. Specifically, we show that learned pause responses in Purkinje cells, which trigger adaptively timed conditioned eyeblinks, suppress the unconditional stimulus (US) signal in a graded manner. Furthermore, by examining how Purkinje cells respond to two distinct conditional stimuli and to a compound stimulus, we provide evidence that could potentially help explain the somewhat counterintuitive overexpectation phenomenon, which was derived from the Rescorla–Wagner model.

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Overexpectation: Response Loss During Sustained Stimulus Compounding in the Rabbit Nictitating Membrane Preparation

Cited by 17 publications

References 71 publications

Simple and Complex Spike Firing Patterns in Purkinje Cells During Classical Conditioning

Simple and Complex Spike Firing Patterns in Purkinje Cells During Classical Conditioning

Predicting danger: The nature, consequences, and neural mechanisms of predictive fear learning

Purkinje cell activity during classical conditioning with different conditional stimuli explains central tenet of Rescorla–Wagner model

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