Probability of shock in the presence and absence of CS in fear conditioning.
01 Aug 1968-Journal of Comparative and Physiological Psychology (J Comp Physiol Psychol)-Vol. 66, Iss: 1, pp 1-5
TL;DR: 2 experiments indicate that CS-US contingency is an important determinant of fear conditioning and that presentation of US in the absence of CS interferes with fear conditioning.
Abstract: 2 experiments indicate that CS-US contingency is an important determinant of fear conditioning and that presentation of US in the absence of CS interferes with fear conditioning. In Experiment 1, equal probability of a shock US in the presence and absence of a tone CS produced no CER suppression to CS; the same probability of US given only during CS produced substantial conditioning. In Experiment 2, which explored 4 different probabilities of US in the presence and absence of CS, amount of conditioning was higher the greater the probability of US during CS and was lower the greater the probability of US in the absence of CS; when the 2 probabilities were equal, no conditioning resulted. Two conceptions of Pavlovian conditioning have been distinguished by Rescorla (1967). The first, and more traditional, notion emphasizes the role of the number of pairings of CS and US in the formation of a CR. The second notion suggests that it is the contingency between CS and US which is important. The notion of contingency differs from that of pairing in that it includes not only what events are paired but also what events are not paired. As used here, contingency refers to the relative probability of occurrence of US in the presence of CS as contrasted with its probability in the absence of CS. The contingency notion suggests that, in fact, conditioning only occurs when these probabilities differ; when the probability of US is higher during CS than at other times, excitatory conditioning occurs; when the probability is lower, inhibitory conditioning results. Notice that the probability of a US can be the same in the absence and presence of CS and yet there can be a fair number of CS-US pairings. It is this that makes it possible to assess the relative importance of pairing and contingency in the development of a CR. Several experiments have pointed to the usefulness of the contingency notion. Rescorla (1966) reported a Pavlovian 1This research was supported by Grants MH13415-01 from the National Institute of Mental Health and GB-6493 from the National Science Foundation, as well as by funds from Yale University.
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TL;DR: There exists enough physiological data to suggest the overall architecture of a computational model of emotional learning and processing inspired by neurophysiological findings, and emotion plays a clear role in learning the behavior.
Abstract: We describe work in progress with the aim of constructing a computational model of emotional learning and processing inspired by neurophysiological findings. The main brain areas modeled are the amygdala and the orbitofrontal cortex and the interaction between them. We want to show that (1) there exists enough physiological data to suggest the overall architecture of a computational model, (2) emotion plays a clear role in learning the behavior. We review neurophysiological data and present a computational model that is subsequently tested in simulation.
283 citations
Cites background from "Probability of shock in the presenc..."
...Conditioning is sensitive to the statistical dependency between events (Rescorla, 1968; Gallistel, 1990)....
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Book•
27 Apr 2009TL;DR: This book discusses the need to Separate Theory of Memory from Theory of Learning, the nature of learning, and the structure of the Read-Only Biological Memory.
Abstract: Preface. 1. Information. Shannon's Theory of Communication. Measuring Information. Efficient Coding. Information and the Brain. Digital and Analog Signals. Appendix: The Information Content of Rare Versus Common Events and Signals. 2. Bayesian Updating. Bayes' Theorem and Our Intuitions About Evidence. Using Bayes' Rule. Summary. 3. Functions. Functions of One Argument. Composition and Decomposition of Functions. Functions of More than One Argument. The Limits to Functional Decomposition. Functions Can Map to Multi-Part Outputs. Mapping to Multiple-Element Outputs Does Not Increase Expressive Power. Defining Particular Functions. Summary: Physical/Neurobiological Implications of Facts about Functions. 4. Representations. Some Simple Examples. Notation. The Algebraic Representation of Geometry. 5. Symbols. Physical Properties of Good Symbols. Symbol Taxonomy. Summary. 6. Procedures. Algorithms. Procedures, Computation, and Symbols. Coding and Procedures. Two Senses of Knowing. A Geometric Example. 7. Computation. Formalizing Procedures. The Turing Machine. Turing Machine for the Successor Function. Turing Machines for f is -even Turing Machines for f + Minimal Memory Structure. General Purpose Computer. Summary. 8. Architectures. One-Dimensional Look-Up Tables (If-Then Implementation). Adding State Memory: Finite-State Machines. Adding Register Memory. Summary. 9. Data Structures. Finding Information in Memory. An Illustrative Example. Procedures and the Coding of Data Structures. The Structure of the Read-Only Biological Memory. 10. Computing with Neurons. Transducers and Conductors. Synapses and the Logic Gates. The Slowness of It All. The Time-Scale Problem. Synaptic Plasticity. Recurrent Loops in Which Activity Reverberates. 11. The Nature of Learning. Learning As Rewiring. Synaptic Plasticity and the Associative Theory of Learning. Why Associations Are Not Symbols. Distributed Coding. Learning As the Extraction and Preservation of Useful Information. Updating an Estimate of One's Location. 12. Learning Time and Space. Computational Accessibility. Learning the Time of Day. Learning Durations. Episodic Memory. 13. The Modularity of Learning. Example 1: Path Integration. Example 2: Learning the Solar Ephemeris. Example 3: "Associative" Learning. Summary. 14. Dead Reckoning in a Neural Network. Reverberating Circuits as Read/Write Memory Mechanisms. Implementing Combinatorial Operations by Table-Look-Up. The Full Model. The Ontogeny of the Connections? How Realistic is the Model? Lessons to be Drawn. Summary. 15. Neural Models of Interval Timing. Timing an Interval on First Encounter. Dworkin's Paradox. Neurally Inspired Models. The Deeper Problems. 16. The Molecular Basis of Memory. The Need to Separate Theory of Memory from Theory of Learning. The Coding Question. A Cautionary Tale. Why Not Synaptic Conductance? A Molecular or Sub-Molecular Mechanism? Bringing the Data to the Computational Machinery. Is It Universal? References. Glossary. Index.
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TL;DR: Magical thinking is an expansion of a universal disinclination of normal adults to draw correlational lessons from their experiences as discussed by the authors, which is an alternative, cognitive-processing, account of magical thinking.
Abstract: Magical thinking has perplexed anthropological theorists for nearly a century. At least three perspectives are extant: (1) Magic is a form of science, a relatively effective set of canons and procedures for acquiring knowledge and exercising control (see, e. g., Levi-Strauss 1966); (2) magic is a form of fantasy, an irrational symbolic attempt to influence uncontrollable events (see, e.g., Malinowski 1954); (3) magic is a form of rhetoric, a persuasive communication designed to arouse sentiments rather than make truth claims about what goes with what in experience (see, e.g., Tambiah 1973). This study presents an alternative, cognitive-processing, account of magical thinking. Magical thinking is an expansion of a universal disinclination of normal adults to draw correlational lessons from their experiences. Correlation and contingency are relatively complex concepts that are not spontaneously available to human thought and are not to be found in the reasoning of most normal adults in all cultures. In the ...
277 citations
TL;DR: Root mean square contingency, Ø, is proposed as a measure of contingency characterizing classical conditioning effects at asymptote, and further analysis of instrumental contingencies yields a surprising result.
Abstract: The contingency between conditional and unconditional stimuli in classical conditioning paradigms, and between responses and consequences in instrumental conditioning paradigms, is analyzed. The results are represented in two- and three-dimensional spaces in which points correspond to procedures, or procedures and outcomes. Traditional statistical and psychological measures of association are applied to data in classical conditioning. Root mean square contingency, o, is proposed as a measure of contingency characterizing classical conditioning effects at asymptote. In instrumental training procedures, traditional measures of association are inappropriate, since one degree of freedom—response probability—is yielded to the subject. Further analysis of instrumental contingencies yields a surprising result. The well established “Matching Law” in free-operant concurrent schedules subsumes the “Probability Matching” finding of mathematical learning theory, and both are equivalent to zero contingency between responses and consequences.
251 citations
TL;DR: The scientific study of associative learning began nearly 100 years ago with the pioneering studies of Thorndike and Pavlov, and it continues today as an active area of research and theory.
Abstract: The scientific study of associative learning began nearly 100 years ago with the pioneering studies of Thorndike and Pavlov, and it continues today as an active area of research and theory. Associative learning should be the foundation for our understanding of other forms of behavior and cognition in human and nonhuman animals. The laws of associative learning are complex, and many modern theorists posit the involvement of attention, memory, and information processing in such basic conditioning phenomena as overshadowing and blocking, and the effects of stimulus preexposure on later conditioning. An unresolved problem for learning theory is distinguishing the formation of associations from their behavioral expression. This and other problems will occupy future generations of behavioral scientists interested in the experimental investigation of associative learning. Neuroscientists and cognitive scientists will both contribute to and benefit from that effort in the next 100 years of inquiry.
249 citations
Cites background or methods from "Probability of shock in the presenc..."
...Modern interest in the role of contingency in learning was rekindled by observations that presenting the US without the CS during training decreased CRs to the CS (Rescorla 1968)....
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...A second technique (the method of negative contingency) for producing conditioned inhibition consists of presenting the target stimulus and the US in an explicitly unpaired fashion (Rescorla 1968)....
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...Thanks largely to the efforts of Rescorla (1968), we now know that animals learn about negative CS-US contingencies as well as about positive ones....
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References
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TL;DR: This "truly random" control procedure leads to a new conception of Pavlovian conditioning postulating that the contingency between CS and US, rather than the pairing of CS andUS, is the important event in conditioning.
Abstract: The traditional control procedures for Pavlovian conditioning are examined and each is found wanting. Some procedures introduce nonassociative factors not present in the experimental procedure while others transform the excitatory, experimental CS-US contingency into an inhibitory contingency. An alternative control procedure is suggested in which there is no contingency whatsoever between CS and US. This \"truly random\" control procedure leads to a new conception of Pavlovian conditioning postulating that the contingency between CS and US, rather than the pairing of CS and US, is the important event in conditioning. The fruitfulness of this new conception of Pavlovian conditioning is illustrated by 2 experimental results.
1,328 citations
301 citations
TL;DR: In this paper, three groups of dogs were trained with different kinds of Pavlovian fear conditioning for three different types of dogs: randomly and independently; for a second group, CSs predicted the occurrence of USs; and for a third group, S predicted the absence of the USs.
Abstract: Three groups of dogs were Sidman avoidance trained They then received different kinds of Pavlovian fear conditioning For one group CSs and USs occurred randomly and independently; for a second group, CSs predicted the occurrence of USs; for a third group, CSs predicted the absence of the USs The CSs were subsequently presented while S performed the avoidance response CSs which had predicted the occurrence or the absence of USs produced, respectively, increases and decreases in avoidance rate For the group with random CSs and USs in conditioning, the CS had no effect upon avoidance
160 citations
64 citations
TL;DR: Rats in an experimental group were given 30 trials of differential CER and then the CS+ and CS− were combined during CER extinction, resulting in less suppression for the experimental group than shown by a control group, interpreted as a demonstration of the active inhibitory properties of CS−.
Abstract: Rats in an experimental group were given 30 trials of differential CER and then the CS+ and CS− were combined during CER extinction. The combination resulted in less suppression for the experimental group than shown by a control group which had a CS+ and a formerly random stimulus combined during extinction. This was interpreted as a demonstration of the active inhibitory properties of CS−.
44 citations
"Probability of shock in the presenc..." refers background in this paper
...Although such an account is plausible for the present data, it fails to explain the active inhibition of fear found by Rescorla and LoLordo (1965), Rescorla (1966), and Hammond (1967)....
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