essay on classical and operant conditioning

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Essay On Compare And Contrast Classical And Operant Conditioning Essay

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Topic: Psychology , Pets , Dog , Sound , Operant Conditioning , Behavior , Training , Food

Published: 01/30/2020

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Classical conditioning and operant conditioning are two concepts of learning that are integral to behavioral psychology. Although the processes differ to quite an extent, they tend to complement one another, and the ultimate result of both concepts is learning. Although both conditioning practices were pioneered by different individuals, both believed in the general principle that investigating behaviors through experiments should be the basis of psychology. Ivan Pavlov, a Russian psychologist, was the one who unintentionally discovered the concept of classical conditioning while carrying out research on canine digestive patterns. According to his findings, His findings supported the idea that we may develop unnatural responses to some stimuli (Pavlov, 1927). B. F. Skinner, an American psychologist coined the term operant conditioning based on his belief that examining at the causes and consequences of an action reveal a lot about behavior (Skinner, 1953). Thus, in classical conditioning a neutral stimuli is placed before a reflex and it focuses on automatic, involuntary behaviors, while in operant conditioning punishment or reinforcement is applied after a behavior and it focuses on voluntary behaviors.

How Does Classical Conditioning Work?

In Pavlov’s famous experiment, Pavlov observed that repeatedly pairing the sound of bell while presenting his dogs with food caused them to salivate (Pavlov, 1927). In classical conditioning, a stimulus in the learning process that was previously neutral is paired with a stimulus that is unconditioned. The unconditioned stimulus triggers a natural response, for instance, the dog had always salivated whenever the food was presented to them. However, when the neutral and unconditioned response is paired, it triggers an unnatural response; for instance, eventually the dogs began salivating merely to the sound of the bell.

How Does Operant Conditioning Work?

In operant conditioning a behavior is encouraged or discouraged by using either punishment or reinforcement. This process ends up establishing a bond between the behavior and its consequences. For instance, a trainer who is trying to teach a dog how to fetch a ball praises the dog as a reward whenever it successfully chases and brings back the ball. The trainer does not praise the dog whenever it is unsuccessful in bringing back the ball. Ultimately, the dog understands that the praise it is receiving is somehow associated with its behavior of fetching the ball successfully.

How Are Classical Conditioning and Operant Conditioning Different From Each Other?

Whether the behavior is involuntary or voluntary is the major aspect that distinguishes classical and operant conditioning from each other. According to classical conditioning, we tend to pair certain stimuli (Pavlov, 1927), for instance, a song to a person or a situation, and listening to the song may trigger unintentional response, in the form of perhaps happiness or sadness, merely based on the person or situation it was associated with. According to operant conditioning, we learn from our consequences in our everyday life and they shape our voluntary behavior (Skinner, 1953). For instance, we often make mistakes in life, but we usually do not voluntarily make the same mistake again because of the consequence that had occurred as a result of that mistake. These days, classical and operant conditioning are employed for numerous purposes, such as animal training, parenting, psychology, teaching, etc. While training an animal, a trainer may make use of classical conditioning by pairing the taste of food with the sound of a clicker, almost like Pavlov did. Eventually, the dog will began responding to the clicker just as it would to the taste of food. In a classroom, a teacher may use operant conditioning reward students that behave well by giving them tokens. Students will learn that they can earn behavior by behaving properly and will be encouraged to do so. A recent breakthrough in classical conditioning include that animals, especially invertebrates such as fish, use classical conditioning for reproduction and survival ("Psychologist Karen Hollis"). A major breakthrough in operant conditioning is the discovery that affective disorders, such as borderline personality disorder and reactive attachment disorder, can be treated using operant conditioning (Othmer, 2002). Despite their differences, both classical conditioning and operant conditioning are psychological theories that are often used in behavioral therapy. In both theories, the focus is to learn associations to behaviors, whether involuntary or voluntary. Certain stimuli in the environment always control the responses. Reinforcement of both types of conditioning is necessary because neither is capable of lasting forever. Both classical and operant conditioning allows new behaviors to be built on ones that are previously established.

Othmer, S. (2002, Feb). On the use of EEG operant conditioning as a treatment for affective disorders, including reactive attachment disorder and borderline personality disorder. Retrieved from http://www.eeginfo.com/research/articles/general_12.htm Pavlov, I. P. (1927). Conditioned reflexes. Mineola, New York: Courier Dover Publications. Psychologist Karen Hollis "goes fishing" and nets a research breakthrough. (n.d.). Retrieved from https://www.mtholyoke.edu/offices/comm/csj/970221/hollis.html Skinner, B. F. (1953). Science and human behavior. New York, NY: Free Press.

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Classical vs. Operant Conditioning

How Classical Conditioning Differs from Operant Conditioning

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Comparing Classical and Operant Conditioning

Classical conditioning, operant conditioning.

Classical conditioning and operant conditioning are two important concepts central to behavioral psychology. There are similarities between classical and operant conditioning. Both types of conditioning result in learning and both suggest that a subject can adapt to their environment.

However, the processes are also quite different. What are the main differences between classical vs. operant conditioning? To understand how each of these behavior modification techniques can be used, it is also essential to understand how classical and operant conditioning differ from one another.

Let's take a look at some of the most basic differences.

First described by Ivan Pavlov, a Russian physiologist

Focuses on involuntary, automatic behaviors

Involves placing a neutral signal before a reflex

First described by B. F. Skinner, an American psychologist

Involves applying reinforcement or punishment after a behavior

Focuses on strengthening or weakening voluntary behaviors

Even if you are not a psychology student, you have probably at least heard about  Pavlov's dogs . In his famous experiment ,  Ivan Pavlov  noticed dogs began to salivate in response to a tone after the sound had repeatedly been paired with presenting food. Pavlov quickly realized that this was a learned response and set out to further investigate the conditioning process.

Classical conditioning is a process that involves creating an association between a naturally existing stimulus and a previously neutral one. Sounds confusing, but let's break it down:

The classical conditioning process involves pairing a previously neutral stimulus (such as the sound of a bell) with an unconditioned stimulus (the taste of food).

This unconditioned stimulus naturally and automatically triggers salivating as a response to the food, which is known as the unconditioned response . After associating the neutral stimulus and the unconditioned stimulus, the sound of the bell alone will start to evoke salivating as a response.

The sound of the bell is now known as the conditioned stimulus and salivating in response to the bell is known as the conditioned response .

A dog doesn't need to be trained to salivate when it sees food; this occurs naturally. The food is the naturally occurring stimulus. If you ring a bell every time you presented the dog with food, an association would be formed between the food and the bell. Eventually, the bell alone, a.k.a. the conditioned stimulus would come to evoke the salivation response.

Classical conditioning is much more than just a basic term used to describe a method of learning; it can also explain how many behaviors form that can impact your health. Consider how a bad habit might form. Even though you have been working out and eating healthy, nighttime overeating keeps tripping up your dieting efforts.

Thanks to classical conditioning, you might have developed the habit of heading to the kitchen for a snack every time a commercial comes on while you are watching your favorite television program.

While commercial breaks were once a neutral stimulus, repeated pairing with an unconditioned stimulus (having a delicious snack) has turned the commercials into a conditioned stimulus. Now every time you see a commercial, you crave a sweet treat.

Operant conditioning (or instrumental conditioning ) focuses on using either reinforcement or punishment to increase or decrease a behavior. Through this process, an association is formed between the behavior and the consequences of that behavior.

Imagine that a trainer is trying to teach a dog to fetch a ball. When the dog successfully chases and picks up the ball, the dog receives praise as a reward. When the animal fails to retrieve the ball, the trainer withholds the praise. Eventually, the dog forms an association between the behavior of fetching the ball and receiving the desired reward.

For example, imagine that a schoolteacher punishes a student for talking out of turn by not letting the student go outside for recess. As a result, the student forms an association between the behavior (talking out of turn) and the consequence (not being able to go outside for recess). As a result, the problematic behavior decreases.

A number of factors can influence how quickly a response is learned and the strength of the response. How often the response is reinforced, known as a schedule of reinforcement , can play an important role in how quickly the behavior is learned and how strong the response becomes. The type of reinforcer used can also have an impact on the response.

For example, while a variable-ratio schedule will result in a high and steady rate of response, a variable-interval schedule will lead to a slow and steady response rate.

In addition to being used to train people and animals to engage in new behaviors, operant conditioning can also be used to help people eliminate unwanted ones. Using a system of rewards and punishments, people can learn to overcome bad habits that might have a negative impact on their health such as smoking or overeating.

One of the simplest ways to remember the differences between classical and operant conditioning is to focus on whether the behavior is involuntary or voluntary.

The main difference between classical and operant conditioning is that classical conditioning involves associating an involuntary response and a stimulus, while operant conditioning is about associating a voluntary behavior and a consequence.

In operant conditioning, the learner is also rewarded with incentives, while classical conditioning involves no such enticements. Also, remember that classical conditioning is passive on the part of the learner, while operant conditioning requires the learner to actively participate and perform some type of action in order to be rewarded or punished.

For operant conditioning to work, the subject must first display a behavior that can then be either rewarded or punished. Classical conditioning, on the other hand, involves forming an association with some sort of already naturally occurring event.  

Classical vs. Operant Conditioning Examples

Today, both classical and operant conditioning are utilized for a variety of purposes by teachers, parents, psychologists, animal trainers, and many others.

• Example of classical conditioning : In animal conditioning, a trainer might utilize classical conditioning by repeatedly pairing the sound of a clicker with the taste of food. Eventually, the sound of the clicker alone will begin to produce the same response that the taste of food would.
• Example of operant conditioning : In a classroom setting, a teacher might utilize operant conditioning by offering tokens as rewards for good behavior. Students can then turn in these tokens to receive some type of reward, such as a treat or extra playtime. In each of these instances, the goal of conditioning is to produce some sort of change in behavior.

A Word From Verywell

Classical conditioning and operant conditioning are both important learning concepts that originated in behavioral psychology. While these two types of conditioning share some similarities, it is important to understand some of the key differences in order to best determine which approach is best for certain learning situations.

Dunsmoor JE, Murphy GL. Categories, concepts, and conditioning: how humans generalize fear. Trends Cogn Sci (Regul Ed). 2015;19(2):73-7.  doi:10.1016/j.tics.2014.12.003

Segers E, Beckers T, Geurts H, Claes L, Danckaerts M, Van der oord S. Working memory and reinforcement schedule jointly determine reinforcement learning in children: Potential implications for behavioral parent training. Front Psychol . 2018;9:394.  doi:10.3389/fpsyg.2018.00394

Franzoi S. Psychology: A Discovery Experience. South-Western CENGAGE Learning. 2015.

Boutelle KN, Bouton ME. Implications of learning theory for developing programs to decrease overeating. Appetite . 2015;93:62-74.  doi:10.1016/j.appet.2015.05.013

Silverman K, Jarvis BP, Jessel J, Lopez AA. Incentives and Motivation. Transl Issues Psychol Sci . 2016;2(2):97-100.  doi:10.1037/tps0000073

Hulac D, Benson N, et al. Using variable interval reinforcement schedules to support students in the classroom: An introduction with illustrative examples. Journal of Educational Research and Practice . 2016;6(1):90–96.

• McSweeney, FK & Murphy, ES. The Wiley Blackwell Handbook of Operant and Classical Conditioning. Oxford: John Wiley & Sons; 2014.
• Nevid, JS. Essentials of Psychology: Concepts and Applications. Belmont, CA: Wadsworth; 2012.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Ai or not ai a student suspects one of their peer reviewer was a bot, how to summarize a research article, loose vs lose, how to cite a blog, apa paraphrasing, classical vs operant conditioning.

The following review example can serve as a guide for students trying to find inspiration when writing an assignment on “Classical and operant conditioning”.

Classical and operant conditioning are two core concepts in behavioral psychology, each playing a crucial role in understanding how humans and animals adapt to their environments. Despite some similarities, these forms of conditioning have distinct differences. Understanding these differences is key to utilizing them effectively in various settings, including education, parenting, and animal training.

Behavioral psychology has significantly advanced our understanding of learning and behavior. Central to this field are the concepts of classical and operant conditioning, each offering a unique perspective on how behavior is learned and modified. While they share the common goal of facilitating learning and adaptation, their approaches and mechanisms differ significantly. This article delves into these differences, providing definitions, explanations, and examples to illustrate their distinct roles in behavior modification.

Operant vs Classical conditioning

Ever wonder if our actions are more like an echo or a choice? This question opens the door to understanding operant and classical conditioning. Classical conditioning is like an echo – an automatic response to a familiar sound. It’s a natural reaction, not chosen but developed through repeated experiences, like jumping at the sound of thunder. Operant conditioning, however, is about choices, like navigating a maze. It’s learning through trial and error, guided by the rewards and consequences of our actions, akin to choosing a path based on the signs of success or warning.

Classical Conditioning

Classical conditioning, first described by Ivan Pavlov, focuses on involuntary, automatic behaviors. It involves creating an association between a naturally occurring stimulus and a previously neutral one. In Pavlov’s famous experiment, dogs were conditioned to salivate in response to a bell, a neutral stimulus, after it was repeatedly paired with food, an unconditioned stimulus. This form of conditioning underlines how an involuntary response (salivation) can be elicited by a previously neutral stimulus (bell sound).

Examples of classical conditioning in everyday life

Classical conditioning occurs in everyday scenarios, often without our conscious awareness. For instance, if a person feels anxious every time they enter a doctor’s office due to past painful experiences, the doctor’s office (neutral stimulus) has become associated with discomfort (unconditioned stimulus), eliciting anxiety (conditioned response).

Operant Conditioning

Operant conditioning, introduced by B. F. Skinner, is centered around voluntary behaviors and their consequences. It involves the use of reinforcement or punishment to either increase or decrease a behavior. Unlike classical conditioning, operant conditioning requires active participation from the learner. For example, a dog is rewarded for fetching a ball, thereby increasing the likelihood of the behavior being repeated.

Examples of operant conditioning in everyday life 

Operant conditioning is widely used in educational settings, such as teachers rewarding students for good behavior to encourage its repetition. Similarly, parents might use time-outs (a form of punishment) to reduce undesirable behaviors in children.

Comparing Classical and Operant Conditioning

While both classical and operant conditioning are forms of associative learning, they differ in key aspects:

• Nature of Behavior: Classical conditioning deals with involuntary responses (e.g., salivating), while operant conditioning involves voluntary behaviors (e.g., fetching a ball).
• Role of the Learner: In classical conditioning, the learner is passive, responding to the association between stimuli. In contrast, operant conditioning requires active participation from the learner.
• Stimulus-Response Relationship: Classical conditioning links an involuntary response with a stimulus. Operant conditioning, however, associates a voluntary behavior with a consequence (reinforcement or punishment).

Final Thoughts

Understanding the nuances between classical and operant conditioning is essential for effectively applying these principles in various fields, from education to behavioral therapy. While they share similarities in their associative learning processes, their differences in addressing involuntary versus voluntary behaviors, the learner’s role, and the nature of stimulus-response relationships set them apart. This knowledge not only aids in practical applications but also enriches our understanding of the complex nature of learning and behavior modification.

What is an example of classical and operant conditioning?

An example of classical conditioning is Pavlov’s dogs, where dogs were conditioned to salivate at the sound of a bell, which initially had no relevance to salivation. This was achieved by repeatedly pairing the bell sound with the presentation of food. An example of operant conditioning is training a dog to sit. When the dog sits on command, it receives a treat (positive reinforcement), increasing the likelihood of the dog sitting on command in the future.

What is the difference between classical and operant conditioning extinction?

Extinction in classical conditioning occurs when the conditioned stimulus (e.g., a bell in Pavlov’s experiment) is repeatedly presented without the unconditioned stimulus (e.g., food), leading to a decrease in the conditioned response (e.g., salivation). In operant conditioning, extinction happens when a behavior (e.g., pressing a lever) is no longer reinforced (e.g., by removing a food reward), which gradually reduces the frequency of that behavior. Essentially, classical conditioning extinction is the breaking of an association between two stimuli, while operant conditioning extinction involves the ceasing of reinforcement or punishment.

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Behaviorism

Explaining behaviorism: operant & classical conditioning, simple and easy to digest explanations of behaviorism, take 1..

Posted February 28, 2014 | Reviewed by Ekua Hagan

There are many explanations that can be used to help people understand the Behaviorist Point of View. Some are very factual, others argue towards practical concerns, and still others are highly philosophical.

This is the first in a series of posts trying to show these styles of explanation in a compact and easy-to-digest form. Feedback is welcome. Because of a guest lecture that I must give soon, the first post will focus on outlining operant and classical conditioning . The order is not meant to imply that this should be the first thing you tell someone about behaviorism, nor to imply that it is the most convincing line of explanation.

How to Explain Behaviorism, version 1: Operant and Classical Conditioning

Operant and classical conditioning are two different ways in which organisms come to reflect the order of the environment around them. They are not perfect processes and they certainly cannot explain facet of human and non-human behavior.

That said, they are surprisingly reliable processes, and they can explain much, much , more about human and non-human behavior than anyone would have thought before extensive study of those processes began.

It is probably best to think about operant and classical conditioning as offering two different types of developmental stories. They are not stories about what a behavior is , now, but rather stories about how that behavior got to be that way.

Classical conditioning stories are about things happening around the animal, no matter what the animal does. Operant conditioning stories involve consequences of the animal's action, i.e., what happens when the animal operates upon the world as an active agent.

There is some debate about whether we need two types of stories. There are good reasons to go either way, including some recent genetic evidence that they can be disentangled. None of that really matters here; all that matters is that you understand the two types of stories and their consequences for future behavior.

Note below that "stimulus" can refer to any object, event, or situation that an organism could potentially respond to. Note also that "response" can be anything the organism does . For now, a "response" could be an overt action (such as jumping up and down), a covert action (such as tensing your leg without moving it), or even thinking or feeling, so long as we conceiving of those as active, rather than passive.

Operant Conditioning

Operant conditioning stories involve an animal doing something that changes the world in a way that produces, crudely speaking, a good or a bad outcome. When an organism does something that is followed by a good outcome, that behavior will become more likely in the future. When an organism does something that is followed by a bad outcome, that behavior will become less likely in the future.

The action and outcome could coincide because of natural laws or social conventions, because someone purposely set it up that way, or it could be that the events followed due to random chance in this animal's life history.

For example, in pretty much any animal's experience, it is good to stop touching overly-hot objects (natural law); in some worlds telling a parent you love them results in good outcomes (social convention); and in some worlds tapping a baseball bat five times on the left corner of the mound is followed by a home run (random chance).

Operant conditioning stories require that the outcome be reinforcing or punitive to the particular animal in question. (There are ways to specify that so it does not involve circular reasoning, but we don't need to go that deep.)

For example, candy might reinforce one person, but not another; some might find a graphic kill-sequence in a violent video game punishing, while others find it reinforcing; etc.

Over time, the story goes, if a certain type of outcome consistently follows a particular behavior, this will affect the rate of future behaviors.

Example Traditional Story : A cat is put in a "puzzle box." It performs a wide range of behaviors because cats don't like to be in cages. Eventually one of its flailing limbs pulls a lever that opens the cage door. This happens many times, and each time the lever gets pulled a little bit quicker (there is no "aha!" moment).

Tradition vs. Necessity : Traditionally operant conditioning stories start with a relatively "random" behavior, but they could start with any behavior. Traditionally, the story then introduces an arbitrary consequence, but in real-life situations, we usually care about socially-mediated consequences. Traditionally it takes many cycles for the consequence to make big changes in the frequency of future behavior, but sometimes the changes can be quite quick and others it can take a very long time. In the traditional story, the consequence always follows the behavior, but there are many cool effects that we know about when it does not the consequence is intermittent (i.e., the "schedule of reinforcement"). Traditionally the consequence has to be immediately following the behavior, though there are some exceptions, you probably want to stick with the traditional version here.

Enhanced Traditional Story : Often operant conditioning stories are enhanced by adding a "discriminative stimuli," which indicates that a particular contingency (a particular connection between action and outcome) is in effect. For example, an experimenter working with rats might have a light that, when on, means that lever pressing will result in food. Similarly, a special education instructor might have a picture of a hat that, when held up, means that saying "hat" will result in an M&M.

Other Classical Conditioning Stuff : You can do amazing things with discriminative stimuli. You can train people to respond to very specific stimuli, or to very general "categories" of stimuli. For example, we can get pigeons to discriminate early Monet's paintings from Picasso's. Also, by drawing out the "schedule" of reinforcement, you can also train animals to respond for many, many times without getting reinforced. For example, we can get people to pull slot machine levers scores of times without a win.

After Conditioning : After the events of an Operant Conditioning story, a behavior either has an increased or decreased rate of occurrence. Often there is a big increase or decrease specifically when a particular stimulus is present. So, if you know the world that a person has lived in before, you know something about why they respond now in certain ways in the presence of certain objects, events, or situations.

Classical Conditioning

Classical conditioning stories involve (at least) two things that coincide "out there" in an animal's world. Those things could coincide because they are causally related due to natural laws or social conventions, or it could be that the events occur at random in relation to each other and this animal just happens to be the animal that experiences them together.

For example, in pretty much any animal's world, lightning is followed by thunder (natural law); in some worlds hearing "say cheese" might be followed by a camera flash (social convention); and in some worlds eating lamb dinners could coincide with hearing bad news from loved ones (random chance).

Classical conditioning stories also require that the organism already have a developed response to one of the two events. For example, thunder could make you flinch, a bright flash could make you wince, and bad news from loved ones could make you cry.

Over time, the story goes, if two things are repeatedly paired together out there in the world, the organism will come to respond to one as they already respond to the other.

Example Traditional Story : When Mary was a child her father liked to take many pictures of her. He always said, "Say cheese!" before he took the picture, and he always used a flash. Every time the flash hit Mary, she winced slightly. Now, whenever she hears "Say cheese!" she winces.

Tradition vs. Necessity : Traditionally classical conditioning stories start with a response that seems unlearned (an Unconditioned Response to an Unconditioned Stimulus), but they could start with any response the animal already has. Traditionally the story then introduces something the animal has no existing response to (a Neutral Stimulus), but it usually still works for stimuli that already elicit some response. Traditionally the neutral stimulus comes to evoke the response associated with unconditioned stimulus after several pairings (thus becoming a Conditioned Stimulus), but sometimes only a single pairing is required, and sometimes neutral stimuli fail to convert to conditioned stimuli even after many, many pairings. Traditionally the stimuli have to be very close together in time, but sometimes you can create conditioned stimuli when the pairings are far apart.

In many cases, where the traditional story does not hold, there has been a lot of research into the exceptions, and we have a very good understanding of why such exceptions should exist. For example, after a single event, many animals will learn to avoid novel tastes that were associated with becoming sick quite a bit later. This makes a lot of evolutionary sense; poisoned food presents a big risk, and one does not normally experience the full effects until quite a bit after ingestion. On the other hand, when dealing with fairly arbitrary pairings of stimuli, as we get all the time in our modern world, the structure of the traditional story holds. For example, why should anyone ever have become excited by hearing a computerized voice say "You've got mail!"? Because of several pairings, that's why.

Other Classical Conditioning Stuff : You can do amazing things here with generalization and discrimination training, and there are many other interesting phenomena that scientists have discovered.

After Conditioning : After the events of a Classical Conditioning story, the presence of a conditioned stimulus elicits a conditioned response. So, if you know the world that a person has lived in before, you know something about why they respond to certain things in certain ways now.

A Bit of Light Theory

Philosophical behaviorism can be very deep. In this context, all I will say is that most behaviorists believe we can explain a great deal about human behavior using the types of stories above. That is, the preferred style to a run of the mill "Why did he do that?!" question will begin with "Well, in the past history of that person, doing that behavior resulted in...."

Because these explanations are all about the way the world around the person works, and the person's past history in that world, you don't need to include traditional "mental" explanations. That doesn't mean that traditional "mental" stuff doesn't exist, but it does suggest that we can explain an awful lot about human behavior before we would need to start talking about them.

Eric Charles, Ph.D., runs the research lab at CTRL, the Center for Teaching, Research, and Learning, at American University.

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Difference Between Classical and Operant Conditioning

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Both classical conditioning and operant are central to behaviorism , but students often get confused about the differences between the two. Classical and operant conditioning are both types of learning that involve learning by association. However, there are important differences between the two.

The main difference between classical conditioning and operant conditioning is that classical conditioning involves pairing a neutral stimulus with a reflexive response. In contrast, operant conditioning involves reinforcing or punishing voluntary behaviors to either increase or decrease their frequency.

Table of Contents

Classical vs Operant Conditioning: Understanding the Differences

For many students, remembering what makes classical conditioning and operant conditioning different can be a real challenge. Fortunately, there are some handy tricks for remembering and identifying each type of conditioning process.

Classical conditioning:

• Involves involuntary behaviors that occur automatically
• Involves a neutral stimulus that naturally and automatically triggers a response
• Involves placing a previously neutral stimulus before a naturally occurring reflex

Operant conditioning:

• Involves voluntary behaviors
• Requires the use of reinforcement or punishment
• Involves placing a consequence after a behavior

What Is Classical Conditioning?

Classical conditioning is a learning process in which an association is formed between a naturally existing and neutral stimulus. Once an association has been formed, the neutral stimulus will come to evoke the same response as the naturally occurring stimulus.

Sounds confusing, but let’s break it down:

• A dog will salivate when it sees food. The food is a naturally occurring stimulus that automatically triggers a response.
• Now imagine that you begin to wear a white coat every time you present the food to the dog.
• Eventually, the animal forms an association between the natural stimulus (the food) and the previously neutral stimulus (the white coat).
• Once this association has been established, the dog will begin to salivate when it sees the white coat, even in the absence of the food.

This process was discovered by a Russian physiologist named Ivan Pavlov and has become a vital concept within the field of behavioral psychology. The classical conditioning process often occurs in the real world, and can also be used to purposefully alter behaviors and teach new behaviors.

How Does Classical Conditioning Work?

Ivan Pavlov was a Russian physiologist, but his most famous discovery had a significant effect on the field of psychology. If Pavlov’s name rings a bell, then you have probably heard of his famous experiments with dogs. Pavlov experimented on 40 dogs during the course of his experiments.

Pavlov was conducting experiments on the digestive systems of dogs when he noticed something interesting. Whenever a lab assistant would enter the room, the animals would begin to salivate.

Pavlov’s digestive experiments involved introducing both food and non-food items to the animals and then measuring the salivary response. Why were the animals salivating whenever they saw the lab assistant?

Pavlov quickly realized that salivating had actually become a learned response . The animals had grown to associate the sight of the assistant’s white lab coat with the presentation of food. Eventually, simply the sight of the assistant could trigger this response, even in the absence of food.

Pavlov’s discovery became known as classical conditioning. In this process, a previously neutral stimulus is paired with an unconditioned stimulus or something that naturally and automatically triggers a response. In Pavlov’s experiments, he paired the sound of a bell with the presentation of food.

After several pairings, an association is formed and the neutral stimulus will also trigger the response. At this point, the neutral stimulus is known as the conditioned stimulus and the response becomes known as the conditioned response . In Pavlov’s experiments, the sound of the bell eventually began to provoke the drooling response, even when no food was present.

The Influence of Classical Conditioning

The discovery of classical conditioning had an enormous impact on the school of thought known as behaviorism. Advocates of behaviorism included the psychologist John B. Watson, who utilized classical conditioning in an experiment to demonstrate how fear could be a conditioned response.

The behaviorist John B. Watson also utilized this process in his famous Little Albert experiment. In the experiment, a child known as Little Albert was exposed to a white lab rat. The child initially showed no fear of the animal, but Watson and his assistant Rosalie Rayner then paired the presentation of the rat with a loud clanging sound.

After several pairings, the child eventually began to cry whenever he saw the white rat. By associating the sight of a white rat with a loud, clanging sound, Watson was able to classically condition a young boy to fear the white rat. Little Albert’s fear even bled over to other white, furry objects including stuffed toys, Rayner’s white fur coat, and the sight of Watson wearing a Santa Claus beard.

What Is Operant Conditioning?

Another psychologist named B.F. Skinner realized that while classical conditioning was powerful, it could not account for all types of learning. He suggested that intentional behaviors and the consequences that follow were also important.

Skinner described a process known as operant conditioning in which actions followed by reinforcement become more likely to occur again. If a child cleans her room and her parents give her a treat as a reward, she will become more likely to clean her room in the future.

Actions immediately followed by punishment will make the behavior less likely to occur.  If you talk out of turn in class and the teacher reprimands you, chances are you will be less likely to speak out again without first raising your hand.

Operant conditioning is often used by parents, teachers, and behavioral therapists to help teach new behaviors and discourage undesirable ones.

A teacher, for example, might utilize praise and reward systems to encourage good classroom behavior, while also using punishments to minimize disruptive actions. Kids who behave appropriately might be awarded tokens, which they can then turn in to receive a reward. Those who disrupt class, on the other hand, might have to miss recess or some other desired activity.

Operant conditioning utilizes reinforcement and punishment to create associations between behaviors and the consequences for those behaviors.

For example, imagine that a parent punishes a child for throwing a toy. Because of this punishment, the child forms an association between the action (throwing) and a result (getting punished). As a result of this consequence, the child becomes less likely to throw the toy again in the future. Once this association is learned, the problematic behavior decreases.

There are a few different factors that can influence how quickly and how strongly a response is learned.

• The salience of the consequence can play a role, as well as the timing and frequency of the consequence.
• The timing and frequency of consequences in operant conditioning are known as schedules of reinforcement .

Key Terms and Definitions

The following are a few of the key terms that you should know and understand related to classical conditioning and operant conditioning:

• Conditioned Response
• Conditioned Stimulus
• Discrimination
• Fixed-Interval Schedule
• Fixed Ratio Schedule
• Habituation
• Negative Punishment
• Negative Reinforcement
• Positive Punishment
• Positive Reinforcement
• Stimulus Generalization
• Unconditioned Response
• Unconditioned Stimulus
• Variable-Interval Schedule
• Variable-Ratio Schedule

Classical vs. Operant Conditioning: Study Questions

As you study classical conditioning and operant conditioning, be sure that you are able to answer the following questions.

• What effect do schedules of reinforcement have on acquiring a new behavior?
• What are reinforcement and punishment? How do they differ?
• What are positive reinforcement and negative reinforcement?
• What are positive punishment and negative punishment?
• People often confuse punishment with negative reinforcement. How are they different?
• What are the differences between classical and operant conditioning?

Classical and operant conditioning can be powerful learning tools and have many real-world applications. Pavlov’s discovery may have occurred by accident, but it has influenced our understanding of how behaviors are learned.

Classical Conditioning: How It Works With Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Classical conditioning (also known as Pavlovian or respondent conditioning) is learning through association and was discovered by Pavlov , a Russian physiologist. In simple terms, two stimuli are linked together to produce a new learned response in a person or animal.

John Watson proposed that the process of classical conditioning (based on Pavlov’s observations) was able to explain all aspects of human psychology.

If you pair a neutral stimulus (NS) with an unconditioned stimulus (US) that already triggers an unconditioned response (UR) that neutral stimulus will become a conditioned stimulus (CS), triggering a conditioned response (CR) similar to the original unconditioned response.

Everything from speech to emotional responses was simply patterns of stimulus and response. Watson completely denied the existence of the mind or consciousness. Watson believed that all individual differences in behavior were due to different learning experiences.

Watson (1924, p. 104) famously said:

Give me a dozen healthy infants, well-formed, and my own specified world to bring them up in and I’ll guarantee to take any one at random and train him to become any type of specialist I might select – doctor, lawyer, artist, merchant-chief and, yes, even beggar-man and thief, regardless of his talents, penchants, tendencies, abilities, vocations and the race of his ancestors.

How Classical Conditioning Works

There are three stages of classical conditioning. At each stage, the stimuli and responses are given special scientific terms:

Stage 1: Before Conditioning:

In this stage, the unconditioned stimulus (UCS) produces an unconditioned response (UCR) in an organism.

In basic terms, this means that a stimulus in the environment has produced a behavior/response that is unlearned (i.e., unconditioned) and, therefore, is a natural response that has not been taught. In this respect, no new behavior has been learned yet.

For example, a stomach virus (UCS) would produce a response of nausea (UCR). In another example, a perfume (UCS) could create a response of happiness or desire (UCR).

This stage also involves another stimulus that has no effect on a person and is called the neutral stimulus (NS). The NS could be a person, object, place, etc.

The neutral stimulus in classical conditioning does not produce a response until it is paired with the unconditioned stimulus.

Stage 2: During Conditioning:

During this stage, a stimulus which produces no response (i.e., neutral) is associated with the unconditioned stimulus, at which point it now becomes known as the conditioned stimulus (CS).

For example, a stomach virus (UCS) might be associated with eating a certain food such as chocolate (CS). Also, perfume (UCS) might be associated with a specific person (CS).

For classical conditioning to be effective, the conditioned stimulus should occur before the unconditioned stimulus, rather than after it, or during the same time. Thus, the conditioned stimulus acts as a type of signal or cue for the unconditioned stimulus.

In some cases, conditioning may take place if the NS occurs after the UCS (backward conditioning), but this normally disappears quite quickly. The most important aspect of the conditioning stimulus is the it helps the organism predict the coming of the unconditional stimulus.

Often during this stage, the UCS must be associated with the CS on a number of occasions, or trials, for learning to take place.

However, one trial learning can happen on certain occasions when it is not necessary for an association to be strengthened over time (such as being sick after food poisoning or drinking too much alcohol).

Stage 3: After Conditioning:

The conditioned stimulus (CS) has been associated with the unconditioned stimulus (UCS) to create a new conditioned response (CR).

For example, a person (CS) who has been associated with nice perfume (UCS) is now found attractive (CR). Also, chocolate (CS) which was eaten before a person was sick with a virus (UCS) now produces a response of nausea (CR).

Classical Conditioning Examples

Pavlov’s dogs.

The most famous example of classical conditioning was Ivan Pavlov’s experiment with dogs , who salivated in response to a bell tone. Pavlov showed that when a bell was sounded each time the dog was fed, the dog learned to associate the sound with the presentation of the food.

He first presented the dogs with the sound of a bell; they did not salivate so this was a neutral stimulus. Then he presented them with food, they salivated. The food was an unconditioned stimulus, and salivation was an unconditioned (innate) response.

He then repeatedly presented the dogs with the sound of the bell first and then the food (pairing) after a few repetitions, the dogs salivated when they heard the sound of the bell. The bell had become the conditioned stimulus and salivation had become the conditioned response.

Fear Response

Watson & Rayner (1920) were the first psychologists to apply the principles of classical conditioning to human behavior by looking at how this learning process may explain the development of phobias.

They did this in what is now considered to be one of the most ethically dubious experiments ever conducted – the case of Little Albert . Albert B.’s mother was a wet nurse in a children’s hospital. Albert was described as ‘healthy from birth’ and ‘on the whole stolid and unemotional’.

When he was about nine months old, his reactions to various stimuli (including a white rat, burning newspapers, and a hammer striking a four-foot steel bar just behind his head) were tested.

Only the last of these frightened him, so this was designated the unconditioned stimulus (UCS) and fear the unconditioned response (UCR). The other stimuli were neutral because they did not produce fear.

When Albert was just over eleven months old, the rat and the UCS were presented together: as Albert reached out to stroke the animal, Watson struck the bar behind his head.

This occurred seven times in total over the next seven weeks. By this time, the rat, the conditioned stimulus (CS), on its own frightened Albert, and fear was now a conditioned response (CR).

The CR transferred spontaneously to the rabbit, the dog, and other stimuli that had been previously neutral. Five days after conditioning, the CR produced by the rat persisted. After ten days, it was ‘much less marked’, but it was still evident a month later.

Carter and Tiffany (1999) support the cue reactivity theory, they carried out a meta-analysis reviewing 41 cue-reactivity studies that compared responses of alcoholics, cigarette smokers, cocaine addicts and heroin addicts to drug-related versus neutral stimuli.

They found that dependent individuals reacted strongly to the cues presented and reported craving and physiological arousal.

Panic Disorder

Classical conditioning is thought to play an important role in the development of Pavlov (Bouton et al., 2002).

Panic disorder often begins after an initial “conditioning episode” involving an early panic attack. The panic attack serves as an unconditioned stimulus (US) that gets paired with neutral stimuli (conditioned stimuli or CS), allowing those stimuli to later trigger anxiety and panic reactions (conditioned responses or CRs).

The panic attack US can become associated with interoceptive cues (like increased heart rate) as well as external situational cues that are present during the attack. This allows those cues to later elicit anxiety and possibly panic (CRs).

Through this conditioning process, anxiety becomes focused on the possibility of having another panic attack. This anticipatory anxiety (a CR) is seen as a key step in the development of panic disorder, as it leads to heightened vigilance and sensitivity to bodily cues that can trigger future attacks.

The presence of conditioned anxiety can serve to potentiate or exacerbate future panic attacks. Anxiety cues essentially lower the threshold for panic. This helps explain how panic disorder can spiral after the initial conditioning episode.

Evidence suggests most patients with panic disorder recall an initial panic attack or conditioning event that preceded the disorder. Prospective studies also show conditioned anxiety and panic reactions can develop after an initial panic episode.

Classical conditioning processes are believed to often occur outside of conscious awareness in panic disorder, reflecting the operation of emotional neural systems separate from declarative knowledge systems.

Cue reactivity is the theory that people associate situations (e.g., meeting with friends)/ places (e.g., pub) with the rewarding effects of nicotine, and these cues can trigger a feeling of craving (Carter & Tiffany, 1999).

These factors become smoking-related cues. Prolonged use of nicotine creates an association between these factors and smoking based on classical conditioning.

Nicotine is the unconditioned stimulus (UCS), and the pleasure caused by the sudden increase in dopamine levels is the unconditioned response (UCR). Following this increase, the brain tries to lower the dopamine back to a normal level.

The stimuli that have become associated with nicotine were neutral stimuli (NS) before “learning” took place but they became conditioned stimuli (CS), with repeated pairings. They can produce the conditioned response (CR).

However, if the brain has not received nicotine, the levels of dopamine drop, and the individual experiences withdrawal symptoms therefore is more likely to feel the need to smoke in the presence of the cues that have become associated with the use of nicotine.

Classroom Learning

The implications of classical conditioning in the classroom are less important than those of operant conditioning , but there is still a need for teachers to try to make sure that students associate positive emotional experiences with learning.

If a student associates negative emotional experiences with school, then this can obviously have bad results, such as creating a school phobia.

For example, if a student is bullied at school they may learn to associate the school with fear. It could also explain why some students show a particular dislike of certain subjects that continue throughout their academic career. This could happen if a student is humiliated or punished in class by a teacher.

Principles of Classical Conditioning

Neutral stimulus.

In classical conditioning, a neutral stimulus (NS) is a stimulus that initially does not evoke a response until it is paired with the unconditioned stimulus.

For example, in Pavlov’s experiment, the bell was the neutral stimulus, and only produced a response when paired with food.

Unconditioned Stimulus

Unconditioned response.

In classical conditioning, an unconditioned response is an innate response that occurs automatically when the unconditioned stimulus is presented.

Pavlov showed the existence of the unconditioned response by presenting a dog with a bowl of food and measuring its salivary secretions.

Conditioned Stimulus

Conditioned response.

In classical conditioning, the conditioned response (CR) is the learned response to the previously neutral stimulus.

In Ivan Pavlov’s experiments in classical conditioning, the dog’s salivation was the conditioned response to the sound of a bell.

Acquisition

The process of pairing a neutral stimulus with an unconditioned stimulus to produce a conditioned response.

In the initial learning period, acquisition describes when an organism learns to connect a neutral stimulus and an unconditioned stimulus.

In psychology, extinction refers to the gradual weakening of a conditioned response by breaking the association between the conditioned and the unconditioned stimuli.

The weakening of a conditioned response occurs when the conditioned stimulus is repeatedly presented without the unconditioned stimulus.

For example, when the bell repeatedly rang, and no food was presented, Pavlov’s dog gradually stopped salivating at the sound of the bell.

Spontaneous Recovery

Spontaneous recovery is a phenomenon of Pavlovian conditioning that refers to the return of a conditioned response (in a weaker form) after a period of time following extinction.

It is the reappearance of an extinguished conditioned response after a rest period when the conditioned stimulus is presented alone.

For example, when Pavlov waited a few days after extinguishing the conditioned response, and then rang the bell once more, the dog salivated again.

Generalization

In psychology, generalization is the tendency to respond in the same way to stimuli similar (but not identical) to the original conditioned stimulus.

For example, in Pavlov’s experiment, if a dog is conditioned to salivate to the sound of a bell, it may later salivate to a higher-pitched bell.

Discrimination

In classical conditioning, discrimination is a process through which individuals learn to differentiate among similar stimuli and respond appropriately to each one.

For example, eventually, Pavlov’s dog learns the difference between the sound of the 2 bells and no longer salivates at the sound of the non-food bell.

Higher-Order Conditioning

Higher-order conditioning is when a conditioned stimulus is paired with a new neutral stimulus to create a second conditioned stimulus. For example, a bell (CS1) is paired with food (UCS) so that the bell elicits salivation (CR). Then, a light (NS) is paired with the bell.

Eventually, the light alone will elicit salivation, even without the presence of food. This demonstrates higher-order conditioning, where the conditioned stimulus (bell) serves as an unconditioned stimulus to condition a new stimulus (light).

Critical Evaluation

Practical applications.

The principles of classical conditioning have been widely and effectively applied in fields like behavioral therapy, education, and advertising. Therapies like systematic desensitization use classical conditioning to help eliminate phobias and anxiety.

The behaviorist approach has been used in the treatment of phobias, and systematic desensitization . The individual with the phobia is taught relaxation techniques and then makes a hierarchy of fear from the least frightening to the most frightening features of the phobic object.

He then is presented with the stimuli in that order and learns to associate (classical conditioning) the stimuli with a relaxation response. This is counter-conditioning.

Explaining involuntary behaviors

Classical conditioning helps explain some reflexive or involuntary behaviors like phobias, emotional reactions, and physiological responses. The model shows how these can be acquired through experience.

The process of classical conditioning can probably account for aspects of certain other mental disorders. For example, in post-traumatic stress disorder (PTSD), sufferers tend to show classically conditioned responses to stimuli present at the time of the traumatizing event (Charney et al., 1993).

However, since not everyone exposed to the traumatic event develops PTSD, other factors must be involved, such as individual differences in people’s appraisal of events as stressors and the recovery environment, such as family and support groups.

Supported by substantial experimental evidence

There is a wealth of experimental support for basic phenomena like acquisition, extinction, generalization, and discrimination. Pavlov’s original experiments on dogs and subsequent studies have demonstrated classical conditioning in animals and humans.

There have been many laboratory demonstrations of human participants acquiring behavior through classical conditioning. It is relatively easy to classically condition and extinguish conditioned responses, such as the eye-blink and galvanic skin responses.

A strength of classical conditioning theory is that it is scientific . This is because it’s based on empirical evidence carried out by controlled experiments . For example, Pavlov (1902) showed how classical conditioning could be used to make a dog salivate to the sound of a bell.

Supporters of a reductionist approach say that it is scientific. Breaking complicated behaviors down into small parts means that they can be scientifically tested. However, some would argue that the reductionist view lacks validity . Thus, while reductionism is useful, it can lead to incomplete explanations.

Ignores biological predispositions

Organisms are biologically prepared to associate certain stimuli over others. However, classical conditioning does not sufficiently account for innate predispositions and biases.

Classical conditioning emphasizes the importance of learning from the environment, and supports nurture over nature.

However, it is limiting to describe behavior solely in terms of either nature or nurture , and attempts to do this underestimate the complexity of human behavior. It is more likely that behavior is due to an interaction between nature (biology) and nurture (environment).

Lacks explanatory power

Classical conditioning provides limited insight into the cognitive processes underlying the associations it describes.

However, applying classical conditioning to our understanding of higher mental functions, such as memory, thinking, reasoning, or problem-solving, has proved more problematic.

Even behavior therapy, one of the more successful applications of conditioning principles to human behavior, has given way to cognitive–behavior therapy (Mackintosh, 1995).

Questionable ecological validity

While lab studies support classical conditioning, some question how well it holds up in natural settings. There is debate about how automatic and inevitable classical conditioning is outside the lab.

In normal adults, the conditioning process can be overridden by instructions: simply telling participants that the unconditioned stimulus will not occur causes an instant loss of the conditioned response, which would otherwise extinguish only slowly (Davey, 1983).

Most participants in an experiment are aware of the experimenter’s contingencies (the relationship between stimuli and responses) and, in the absence of such awareness often fail to show evidence of conditioning (Brewer, 1974).

Evidence indicates that for humans to exhibit classical conditioning, they need to be consciously aware of the connection between the conditioned stimulus (CS) and the unconditioned stimulus (US). This contradicts traditional theories that humans have two separate learning systems – one conscious and one unconscious – that allow conditioning to occur without conscious awareness (Lovibond & Shanks, 2002).

There are also important differences between very young children or those with severe learning difficulties and older children and adults regarding their behavior in a variety of operant conditioning and discrimination learning experiments.

These seem largely attributable to language development (Dugdale & Lowe, 1990). This suggests that people have rather more efficient, language-based forms of learning at their disposal than just the laborious formation of associations between a conditioned stimulus and an unconditioned stimulus.

Ethical concerns

The principles of classical conditioning raise ethical concerns about manipulating behavior without consent. This is especially true in advertising and politics.

• Manipulation of preferences – Classical conditioning can create positive associations with certain brands, products, or political candidates. This can manipulate preferences outside of a person’s rational thought process.
• Encouraging impulsive behaviors – Conditioning techniques may encourage behaviors like impulsive shopping, unhealthy eating, or risky financial choices by forging positive associations with these behaviors.
• Preying on vulnerabilities – Advertisers or political campaigns may exploit conditioning techniques to target and influence vulnerable demographic groups like youth, seniors, or those with mental health conditions.
• Reduction of human agency – At an extreme, the use of classical conditioning techniques reduces human beings to automata reacting predictably to stimuli. This is ethically problematic.

Deterministic theory

A final criticism of classical conditioning theory is that it is deterministic . This means it does not allow the individual any degree of free will. Accordingly, a person has no control over the reactions they have learned from classical conditioning, such as a phobia.

The deterministic approach also has important implications for psychology as a science. Scientists are interested in discovering laws that can be used to predict events.

However, by creating general laws of behavior, deterministic psychology underestimates the uniqueness of human beings and their freedom to choose their destiny.

The Role of Nature in Classical Conditioning

Behaviorists argue all learning is driven by experience, not nature. Classical conditioning exemplifies environmental influence. However, our evolutionary history predisposes us to learn some associations more readily than others. So nature also plays a role.

For example, PTSD develops in part due to strong conditioning during traumatic events. The emotions experienced during trauma lead to neural activity in the amygdala , creating strong associative learning between conditioned and unconditioned stimuli (Milad et al., 2009).

Individuals with PTSD show enhanced fear conditioning, reflected in greater amygdala reactivity to conditioned threat cues compared to trauma-exposed controls. In addition to strong initial conditioning, PTSD patients exhibit slower extinction to conditioned fear stimuli.

During extinction recall tests, PTSD patients fail to show differential skin conductance responses to extinguished versus non-extinguished cues, indicating impaired retention of fear extinction. Deficient extinction retention corresponds to reduced activation in the ventromedial prefrontal cortex and hippocampus and heightened dorsal anterior cingulate cortex response during extinction recall in PTSD patients.

In influential research on food conditioning, John Garcia found that rats easily learned to associate a taste with nausea from drugs, even if illness occurred hours later.

However, conditioning nausea to a sight or sound was much harder. This showed that conditioning does not occur equally for any stimulus pairing. Rather, evolution prepares organisms to learn some associations that aid survival more easily, like linking smells to illness.

The evolutionary significance of taste and nutrition ensures robust and resilient classical conditioning of flavor preferences, making them difficult to reverse (Hall, 2002).

Forming strong and lasting associations between flavors and nutrition aids survival by promoting the consumption of calorie-rich foods. This makes flavor conditioning very robust.

Repeated flavor-nutrition pairings in these studies lead to overlearning of the association, making it more resistant to extinction.

The learning is overtrained, context-specific, and subject to recovery effects that maintain the conditioned behavior despite extinction training.

Classical vs. operant condioning

In summary, classical conditioning is about passive stimulus-response associations, while operant conditioning is about actively connecting behaviors to consequences. Classical works on reflexes and operant on voluntary actions.

• Stimuli vs consequences : Classical conditioning focuses on associating two stimuli together. For example, pairing a bell (neutral stimulus) with food (reflex-eliciting stimulus) creates a conditioned response of salivation to the bell. Operant conditioning is about connecting behaviors with the consequences that follow. If a behavior is reinforced, it will increase. If it’s punished, it will decrease.
• Passive vs. active : In classical conditioning, the organism is passive and automatically responds to the conditioned stimulus. Operant conditioning requires the organism to perform a behavior that then gets reinforced or punished actively. The organism operates on the environment.
• Involuntary vs. voluntary : Classical conditioning works with involuntary, reflexive responses like salivation, blinking, etc. Operant conditioning shapes voluntary behaviors that are controlled by the organism, like pressing a lever.
• Association vs. reinforcement : Classical conditioning relies on associating stimuli in order to create a conditioned response. Operant conditioning depends on using reinforcement and punishment to increase or decrease voluntary behaviors.

Learning Check

• In Ivan Pavlov’s famous experiment, he rang a bell before presenting food powder to dogs. Eventually, the dogs salivated at the mere sound of the bell. Identify the neutral stimulus, unconditioned stimulus, unconditioned response, conditioned stimulus, and conditioned response in Pavlov’s experiment.
• A student loves going out for pizza and beer with friends on Fridays after class. Whenever one friend texts the group about Friday plans, the student immediately feels happy and excited. The friend starts texting the group on Thursdays when she wants the student to feel happier. Explain how this is an example of classical conditioning. Identify the UCS, UCR, CS, and CR.
• A college student is traumatized after a car accident. She now feels fear every time she gets into a car. How could extinction be used to eliminate this acquired fear?
• A professor always slams their book on the lectern right before giving a pop quiz. Students now feel anxiety whenever they hear the book slam. Is this classical conditioning? If so, identify the NS, UCS, UCR, CS, and CR.
• Contrast classical conditioning and operant conditioning. How are they similar and different? Provide an original example of each type of conditioning.
• How could the principles of classical conditioning be applied to help students overcome test anxiety?
• Explain how taste aversion learning is an adaptive form of classical conditioning. Provide an original example.
• What is second-order conditioning? Give an example and identify the stimuli and responses.
• What is the role of extinction in classical conditioning? How could extinction be used in cognitive behavioral therapy for anxiety disorders?

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Brewer, W. F. (1974). There is no convincing evidence for operant or classical conditioning in adult humans.

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Milad, M. R., Pitman, R. K., Ellis, C. B., Gold, A. L., Shin, L. M., Lasko, N. B.,…Rauch, S. L. (2009). Neurobiological basis of failure to recall extinction memory in posttraumatic stress disorder.  Biological Psychiatry, 66 (12), 1075–82.

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O perant C onditioning

Operant behavior is behavior “controlled” by its consequences. In practice, operant conditioning is the study of reversible behavior maintained by reinforcement schedules. We review empirical studies and theoretical approaches to two large classes of operant behavior: interval timing and choice. We discuss cognitive versus behavioral approaches to timing, the “gap” experiment and its implications, proportional timing and Weber's law, temporal dynamics and linear waiting, and the problem of simple chain-interval schedules. We review the long history of research on operant choice: the matching law, its extensions and problems, concurrent chain schedules, and self-control. We point out how linear waiting may be involved in timing, choice, and reinforcement schedules generally. There are prospects for a unified approach to all these areas.

INTRODUCTION

The term operant conditioning 1 was coined by B. F. Skinner in 1937 in the context of reflex physiology, to differentiate what he was interested in—behavior that affects the environment—from the reflex-related subject matter of the Pavlovians. The term was novel, but its referent was not entirely new. Operant behavior , though defined by Skinner as behavior “controlled by its consequences” is in practice little different from what had previously been termed “instrumental learning” and what most people would call habit. Any well-trained “operant” is in effect a habit. What was truly new was Skinner's method of automated training with intermittent reinforcement and the subject matter of reinforcement schedules to which it led. Skinner and his colleagues and students discovered in the ensuing decades a completely unsuspected range of powerful and orderly schedule effects that provided new tools for understanding learning processes and new phenomena to challenge theory.

A reinforcement schedule is any procedure that delivers a reinforcer to an organism according to some well-defined rule. The usual reinforcer is food for a hungry rat or pigeon; the usual schedule is one that delivers the reinforcer for a switch closure caused by a peck or lever press. Reinforcement schedules have also been used with human subjects, and the results are broadly similar to the results with animals. However, for ethical and practical reasons, relatively weak reinforcers must be used—and the range of behavioral strategies people can adopt is of course greater than in the case of animals. This review is restricted to work with animals.

Two types of reinforcement schedule have excited the most interest. Most popular are time-based schedules such as fixed and variable interval, in which the reinforcer is delivered after a fixed or variable time period after a time marker (usually the preceding reinforcer). Ratio schedules require a fixed or variable number of responses before a reinforcer is delivered.

Trial-by-trial versions of all these free-operant procedures exist. For example, a version of the fixed-interval schedule specifically adapted to the study of interval timing is the peak-interval procedure, which adds to the fixed interval an intertrial interval (ITI) preceding each trial and a percentage of extra-long “empty” trials in which no food is given.

For theoretical reasons, Skinner believed that operant behavior ought to involve a response that can easily be repeated, such as pressing a lever, for rats, or pecking an illuminated disk (key) for pigeons. The rate of such behavior was thought to be important as a measure of response strength ( Skinner 1938 , 1966 , 1986 ; Killeen & Hall 2001 ). The current status of this assumption is one of the topics of this review. True or not, the emphasis on response rate has resulted in a dearth of experimental work by operant conditioners on nonrecurrent behavior such as movement in space.

Operant conditioning differs from other kinds of learning research in one important respect. The focus has been almost exclusively on what is called reversible behavior, that is, behavior in which the steady-state pattern under a given schedule is stable, meaning that in a sequence of conditions, XAXBXC…, where each condition is maintained for enough days that the pattern of behavior is locally stable, behavior under schedule X shows a pattern after one or two repetitions of X that is always the same. For example, the first time an animal is exposed to a fixed-interval schedule, after several daily sessions most animals show a “scalloped” pattern of responding (call it pattern A): a pause after each food delivery—also called wait time or latency —followed by responding at an accelerated rate until the next food delivery. However, some animals show negligible wait time and a steady rate (pattern B). If all are now trained on some other procedure—a variable-interval schedule, for example—and then after several sessions are returned to the fixed-interval schedule, almost all the animals will revert to pattern A. Thus, pattern A is the stable pattern. Pattern B, which may persist under unchanging conditions but does not recur after one or more intervening conditions, is sometimes termed metastable ( Staddon 1965 ). The vast majority of published studies in operant conditioning are on behavior that is stable in this sense.

Although the theoretical issue is not a difficult one, there has been some confusion about what the idea of stability (reversibility) in behavior means. It should be obvious that the animal that shows pattern A after the second exposure to procedure X is not the same animal as when it showed pattern A on the first exposure. Its experimental history is different after the second exposure than after the first. If the animal has any kind of memory, therefore, its internal state 2 following the second exposure is likely to be different than after the first exposure, even though the observed behavior is the same. The behavior is reversible; the organism's internal state in general is not. The problems involved in studying nonreversible phenomena in individual organisms have been spelled out elsewhere (e.g., Staddon 2001a , Ch. 1); this review is mainly concerned with the reversible aspects of behavior.

Once the microscope was invented, microorganisms became a new field of investigation. Once automated operant conditioning was invented, reinforcement schedules became an independent subject of inquiry. In addition to being of great interest in their own right, schedules have also been used to study topics defined in more abstract ways such as timing and choice. These two areas constitute the majority of experimental papers in operant conditioning with animal subjects during the past two decades. Great progress has been made in understanding free-operant choice behavior and interval timing. Yet several theories of choice still compete for consensus, and much the same is true of interval timing. In this review we attempt to summarize the current state of knowledge in these two areas, to suggest how common principles may apply in both, and to show how these principles may also apply to reinforcement schedule behavior considered as a topic in its own right.

INTERVAL TIMING

Interval timing is defined in several ways. The simplest is to define it as covariation between a dependent measure such as wait time and an independent measure such as interreinforcement interval (on fixed interval) or trial time-to-reinforcement (on the peak procedure). When interreinforcement interval is doubled, then after a learning period wait time also approximately doubles ( proportional timing ). This is an example of what is sometimes called a time production procedure: The organism produces an approximation to the to-be-timed interval. There are also explicit time discrimination procedures in which on each trial the subject is exposed to a stimulus and is then required to respond differentially depending on its absolute ( Church & Deluty 1977 , Stubbs 1968 ) or even relative ( Fetterman et al. 1989 ) duration. For example, in temporal bisection , the subject (e.g., a rat) experiences either a 10-s or a 2-s stimulus, L or S . After the stimulus goes off, the subject is confronted with two choices. If the stimulus was L , a press on the left lever yields food; if S , a right press gives food; errors produce a brief time-out. Once the animal has learned, stimuli of intermediate duration are presented in lieu of S and L on test trials. The question is, how will the subject distribute its responses? In particular, at what intermediate duration will it be indifferent between the two choices? [Answer: typically in the vicinity of the geometric mean, i.e., √( L.S ) − 4.47 for 2 and 10.]

Wait time is a latency; hence (it might be objected) it may vary on time-production procedures like fixed interval because of factors other than timing—such as degree of hunger (food deprivation). Using a time-discrimination procedure avoids this problem. It can also be mitigated by using the peak procedure and looking at performance during “empty” trials. “Filled” trials terminate with food reinforcement after (say) T s. “Empty” trials, typically 3 T s long, contain no food and end with the onset of the ITI. During empty trials the animal therefore learns to wait, then respond, then stop (more or less) until the end of the trial ( Catania 1970 ). The mean of the distribution of response rates averaged over empty trials ( peak time ) is then perhaps a better measure of timing than wait time because motivational variables are assumed to affect only the height and spread of the response-rate distribution, not its mean. This assumption is only partially true ( Grace & Nevin 2000 , MacEwen & Killeen 1991 , Plowright et al. 2000 ).

There is still some debate about the actual pattern of behavior on the peak procedure in each individual trial. Is it just wait, respond at a constant rate, then wait again? Or is there some residual responding after the “stop” [yes, usually (e.g., Church et al. 1991 )]? Is the response rate between start and stop really constant or are there two or more identifiable rates ( Cheng & Westwood 1993 , Meck et al. 1984 )? Nevertheless, the method is still widely used, particularly by researchers in the cognitive/psychophysical tradition. The idea behind this approach is that interval timing is akin to sensory processes such as the perception of sound intensity (loudness) or luminance (brightness). As there is an ear for hearing and an eye for seeing, so (it is assumed) there must be a (real, physiological) clock for timing. Treisman (1963) proposed the idea of an internal pacemaker-driven clock in the context of human psychophysics. Gibbon (1977) further developed the approach and applied it to animal interval-timing experiments.

WEBER'S LAW, PROPORTIONAL TIMING AND TIMESCALE INVARIANCE

The major similarity between acknowledged sensory processes, such as brightness perception, and interval timing is Weber's law . Peak time on the peak procedure is not only proportional to time-to-food ( T ), its coefficient of variation (standard deviation divided by mean) is approximately constant, a result similar to Weber's law obeyed by most sensory dimensions. This property has been called scalar timing ( Gibbon 1977 ). Most recently, Gallistel & Gibbon (2000) have proposed a grand principle of timescale invariance , the idea that the frequency distribution of any given temporal measure (the idea is assumed to apply generally, though in fact most experimental tests have used peak time) scales with the to-be-timed-interval. Thus, given the normalized peak-time distribution for T =60 s, say; if the x -axis is divided by 2, it will match the distribution for T = 30 s. In other words, the frequency distribution for the temporal dependent variable, normalized on both axes, is asserted to be invariant.

Timescale invariance is in effect a combination of Weber's law and proportional timing. Like those principles, it is only approximately true. There are three kinds of evidence that limit its generality. The simplest is the steady-state pattern of responding (key-pecking or lever-pressing) observed on fixed-interval reinforcement schedules. This pattern should be the same at all fixed-interval values, but it is not. Gallistel & Gibbon wrote, “When responding on such a schedule, animals pause after each reinforcement and then resume responding after some interval has elapsed. It was generally supposed that the animals' rate of responding accelerated throughout the remainder of the interval leading up to reinforcement. In fact, however, conditioned responding in this paradigm … is a two-state variable (slow, sporadic pecking vs. rapid, steady pecking), with one transition per interreinforcement interval ( Schneider 1969 )” (p. 293).

This conclusion over-generalizes Schneider's result. Reacting to reports of “break-and-run” fixed-interval performance under some conditions, Schneider sought to characterize this feature more objectively than the simple inspection of cumulative records. He found a way to identify the point of maximum acceleration in the fixed-interval “scallop” by using an iterative technique analogous to attaching an elastic band to the beginning of an interval and the end point of the cumulative record, then pushing a pin, representing the break point, against the middle of the band until the two resulting straight-line segments best fit the cumulative record (there are other ways to achieve the same result that do not fix the end points of the two line-segments). The postreinforcement time ( x -coordinate) of the pin then gives the break point for that interval. Schneider showed that the break point is an orderly dependent measure: Break point is roughly 0.67 of interval duration, with standard deviation proportional to the mean (the Weber-law or scalar property).

This finding is by no means the same as the idea that the fixed-interval scallop is “a two-state variable” ( Hanson & Killeen 1981 ). Schneider showed that a two-state model is an adequate approximation; he did not show that it is the best or truest approximation. A three- or four-line approximation (i.e., two or more pins) might well have fit significantly better than the two-line version. To show that the process is two-state, Schneider would have had to show that adding additional segments produced negligibly better fit to the data.

The frequent assertion that the fixed-interval scallop is always an artifact of averaging flies in the face of raw cumulative-record data“the many nonaveraged individual fixed-interval cumulative records in Ferster & Skinner (1957 , e.g., pp. 159, 160, 162), which show clear curvature, particularly at longer fixed-interval values (> ∼2 min). The issue for timescale invariance, therefore, is whether the shape, or relative frequency of different-shaped records, is the same at different absolute intervals.

The evidence is that there is more, and more frequent, curvature at longer intervals. Schneider's data show this effect. In Schneider's Figure 3, for example, the time to shift from low to high rate is clearly longer at longer intervals than shorter ones. On fixed-interval schedules, apparently, absolute duration does affect the pattern of responding. (A possible reason for this dependence of the scallop on fixed-interval value is described in Staddon 2001a , p. 317. The basic idea is that greater curvature at longer fixed-interval values follows from two things: a linear increase in response probability across the interval, combined with a nonlinear, negatively accelerated, relation between overall response rate and reinforcement rate.) If there is a reliable difference in the shape, or distribution of shapes, of cumulative records at long and short fixed-interval values, the timescale-invariance principle is violated.

A second dataset that does not agree with timescale invariance is an extensive set of studies on the peak procedure by Zeiler & Powell (1994 ; see also Hanson & Killeen 1981) , who looked explicitly at the effect of interval duration on various measures of interval timing. They conclude, “Quantitative properties of temporal control depended on whether the aspect of behavior considered was initial pause duration, the point of maximum acceleration in responding [break point], the point of maximum deceleration, the point at which responding stopped, or several different statistical derivations of a point of maximum responding … . Existing theory does not explain why Weber's law [the scalar property] so rarely fit the results …” (p. 1; see also Lowe et al. 1979 , Wearden 1985 for other exceptions to proportionality between temporal measures of behavior and interval duration). Like Schneider (1969) and Hanson & Killeen (1981) , Zeiler & Powell found that the break point measure was proportional to interval duration, with scalar variance (constant coefficient of variation), and thus consistent with timescale invariance, but no other measure fit the rule.

Moreover, the fit of the breakpoint measure is problematic because it is not a direct measure of behavior but is itself the result of a statistical fitting procedure. It is possible, therefore, that the fit of breakpoint to timescale invariance owes as much to the statistical method used to arrive at it as to the intrinsic properties of temporal control. Even if this caveat turns out to be false, the fact that every other measure studied by Zeiler & Powell failed to conform to timescale invariance surely rules it out as a general principle of interval timing.

The third and most direct test of the timescale invariance idea is an extensive series of time-discrimination experiments carried out by Dreyfus et al. (1988) and Stubbs et al. (1994) . The usual procedure in these experiments was for pigeons to peck a center response key to produce a red light of one duration that is followed immediately by a green light of another duration. When the green center-key light goes off, two yellow side-keys light up. The animals are reinforced with food for pecking the left side-key if the red light was longer, the right side-key if the green light was longer.

The experimental question is, how does discrimination accuracy depend on relative and absolute duration of the two stimuli? Timescale invariance predicts that accuracy depends only on the ratio of red and green durations: For example, accuracy should be the same following the sequence red:10, green:20 as the sequence red:30, green:60, but it is not. Pigeons are better able to discriminate between the two short durations than the two long ones, even though their ratio is the same. Dreyfus et al. and Stubbs et al. present a plethora of quantitative data of the same sort, all showing that time discrimination depends on absolute as well as relative duration.

Timescale invariance is empirically indistinguishable from Weber's law as it applies to time, combined with the idea of proportional timing: The mean of a temporal dependent variable is proportional to the temporal independent variable. But Weber's law and proportional timing are dissociable—it is possible to have proportional timing without conforming to Weber's law and vice versa (cf. Hanson & Killeen 1981 , Zeiler & Powell 1994 ), and in any case both are only approximately true. Timescale invariance therefore does not qualify as a principle in its own right.

Cognitive and Behavioral Approaches to Timing

The cognitive approach to timing dates from the late 1970s. It emphasizes the psychophysical properties of the timing process and the use of temporal dependent variables as measures of (for example) drug effects and the effects of physiological interventions. It de-emphasizes proximal environmental causes. Yet when timing (then called temporal control; see Zeiler 1977 for an early review) was first discovered by operant conditioners (Pavlov had studied essentially the same phenomenon— delay conditioning —many years earlier), the focus was on the time marker , the stimulus that triggered the temporally correlated behavior. (That is one virtue of the term control : It emphasizes the fact that interval timing behavior is usually not free-running. It must be cued by some aspect of the environment.) On so-called spaced-responding schedules, for example, the response is the time marker: The subject must learn to space its responses more than T s apart to get food. On fixed-interval schedules the time marker is reinforcer delivery; on the peak procedure it is the stimulus events associated with trial onset. This dependence on a time marker is especially obvious on time-production procedures, but on time-discrimination procedures the subject's choice behavior must also be under the control of stimuli associated with the onset and offset of the sample duration.

Not all stimuli are equally effective as time markers. For example, an early study by Staddon & Innis (1966a ; see also 1969) showed that if, on alternate fixed intervals, 50% of reinforcers (F) are omitted and replaced by a neutral stimulus (N) of the same duration, wait time following N is much shorter than after F (the reinforcement-omission effect ). Moreover, this difference persists indefinitely. Despite the fact that F and N have the same temporal relationship to the reinforcer, F is much more effective as a time marker than N. No exactly comparable experiment has been done using the peak procedure, partly because the time marker there involves ITI offset/trial onset rather than the reinforcer delivery, so that there is no simple manipulation equivalent to reinforcement omission.

These effects do not depend on the type of behavior controlled by the time marker. On fixed-interval schedules the time marker is in effect inhibitory: Responding is suppressed during the wait time and then occurs at an accelerating rate. Other experiments ( Staddon 1970 , 1972 ), however, showed that given the appropriate schedule, the time marker can control a burst of responding (rather than a wait) of a duration proportional to the schedule parameters ( temporal go–no-go schedules) and later experiments have shown that the place of responding can be controlled by time since trial onset in the so-called tri-peak procedure ( Matell & Meck 1999 ).

A theoretical review ( Staddon 1974 ) concluded, “Temporal control by a given time marker depends on the properties of recall and attention, that is, on the same variables that affect attention to compound stimuli and recall in memory experiments such as delayed matching-to-sample.” By far the most important variable seems to be “the value of the time-marker stimulus—Stimuli of high value … are more salient …” (p. 389), although the full range of properties that determine time-marker effectiveness is yet to be explored.

Reinforcement omission experiments are transfer tests , that is, tests to identify the effective stimulus. They pinpoint the stimulus property controlling interval timing—the effective time marker—by selectively eliminating candidate properties. For example, in a definitive experiment, Kello (1972) showed that on fixed interval the wait time is longest following standard reinforcer delivery (food hopper activated with food, hopper light on, house light off, etc.). Omission of any of those elements caused the wait time to decrease, a result consistent with the hypothesis that reinforcer delivery acquires inhibitory temporal control over the wait time. The only thing that makes this situation different from the usual generalization experiment is that the effects of reinforcement omission are relatively permanent. In the usual generalization experiment, delivery of the reinforcer according to the same schedule in the presence of both the training stimulus and the test stimuli would soon lead all to be responded to in the same way. Not so with temporal control: As we just saw, even though N and F events have the same temporal relationship to the next food delivery, animals never learn to respond similarly after both. The only exception is when the fixed-interval is relatively short, on the order of 20 s or less ( Starr & Staddon 1974 ). Under these conditions pigeons are able to use a brief neutral stimulus as a time marker on fixed interval.

The Gap Experiment

The closest equivalent to fixed-interval reinforcement–omission using the peak procedure is the so-called gap experiment ( Roberts 1981 ). In the standard gap paradigm the sequence of stimuli in a training trial (no gap stimulus) consists of three successive stimuli: the intertrial interval stimulus (ITI), the fixed-duration trial stimulus (S), and food reinforcement (F), which ends each training trial. The sequence is thus ITI, S, F, ITI. Training trials are typically interspersed with empty probe trials that last longer than reinforced trials but end with an ITI only and no reinforcement. The stimulus sequence on such trials is ITI, S, ITI, but the S is two or three times longer than on training trials. After performance has stabilized, gap trials are introduced into some or all of the probe trials. On gap trials the ITI stimulus reappears for a while in the middle of the trial stimulus. The sequence on gap trials is therefore ITI, S, ITI, S, ITI. Gap trials do not end in reinforcement.

What is the effective time marker (i.e., the stimulus that exerts temporal control) in such an experiment? ITI offset/trial onset is the best temporal predictor of reinforcement: Its time to food is shorter and less variable than any other experimental event. Most but not all ITIs follow reinforcement, and the ITI itself is often variable in duration and relatively long. So reinforcer delivery is a poor temporal predictor. The time marker therefore has something to do with the transition between ITI and trial onset, between ITI and S. Gap trials also involve presentation of the ITI stimulus, albeit with a different duration and within-trial location than the usual ITI, but the similarities to a regular trial are obvious. The gap experiment is therefore a sort of generalization (of temporal control) experiment. Buhusi & Meck (2000) presented gap stimuli more or less similar to the ITI stimulus during probe trials and found results resembling generalization decrement, in agreement with this analysis.

However, the gap procedure was not originally thought of as a generalization test, nor is it particularly well designed for that purpose. The gap procedure arose directly from the cognitive idea that interval timing behavior is driven by an internal clock ( Church 1978 ). From this point of view it is perfectly natural to inquire about the conditions under which the clock can be started or stopped. If the to-be-timed interval is interrupted—a gap—will the clock restart when the trial stimulus returns (reset)? Will it continue running during the gap and afterwards? Or will it stop and then restart (stop)?

“Reset” corresponds to the maximum rightward shift (from trial onset) of the response-rate peak from its usual position t s after trial onset to t + G E , where G E is the offset time (end) of the gap stimulus. Conversely, no effect (clock keeps running) leaves the peak unchanged at t , and “stop and restart” is an intermediate result, a peak shift to G E − G B + t , where G B is the time of onset (beginning) of the gap stimulus.

Both gap duration and placement within a trial have been varied. The results that have been obtained so far are rather complex (cf. Buhusi & Meck 2000 , Cabeza de Vaca et al. 1994 , Matell & Meck 1999 ). In general, the longer the gap and the later it appears in the trial, the greater the rightward peak shift. All these effects can be interpreted in clock terms, but the clock view provides no real explanation for them, because it does not specify which one will occur under a given set of conditions. The results of gap experiments can be understood in a qualitative way in terms of the similarity of the gap presentation to events associated with trial onset; the more similar, the closer the effect will be to reset, i.e., the onset of a new trial. Another resemblance between gap results and the results of reinforcement-omission experiments is that the effects of the gap are also permanent: Behavior on later trials usually does not differ from behavior on the first few ( Roberts 1981 ). These effects have been successfully simulated quantitatively by a neural network timing model ( Hopson 1999 , 2002 ) that includes the assumption that the effects of time-marker presentation decay with time ( Cabeza de Vaca et al. 1994 ).

The original temporal control studies were strictly empirical but tacitly accepted something like the psychophysical view of timing. Time was assumed to be a sensory modality like any other, so the experimental task was simply to explore the different kinds of effect, excitatory, inhibitory, discriminatory, that could come under temporal control. The psychophysical view was formalized by Gibbon (1977) in the context of animal studies, and this led to a static information-processing model, scalar expectancy theory (SET: Gibbon & Church 1984 , Meck 1983 , Roberts 1983 ), which comprised a pacemaker-driven clock, working and reference memories, a comparator, and various thresholds. A later dynamic version added memory for individual trials (see Gallistel 1990 for a review). This approach led to a long series of experimental studies exploring the clocklike properties of interval timing (see Gallistel & Gibbon 2000 , Staddon & Higa 1999 for reviews), but none of these studies attempted to test the assumptions of the SET approach in a direct way.

SET was for many years the dominant theoretical approach to interval timing. In recent years, however, its limitations, of parsimony and predictive range, have become apparent and there are now a number of competitors such as the behavioral theory of timing ( Killeen & Fetterman 1988 , MacEwen & Killeen 1991 , Machado 1997 ), spectral timing theory ( Grossberg & Schmajuk 1989 ), neural network models ( Church & Broadbent 1990 , Hopson 1999 , Dragoi et al. 2002 ), and the habituation-based multiple time scale theory (MTS: Staddon & Higa 1999 , Staddon et al. 2002 ). There is as yet no consensus on the best theory.

Temporal Dynamics: Linear Waiting

A separate series of experiments in the temporal-control tradition, beginning in the late 1980s, studied the real-time dynamics of interval timing (e.g., Higa et al. 1991 , Lejeune et al. 1997 , Wynne & Staddon 1988 ; see Staddon 2001a for a review). These experiments have led to a simple empirical principle that may have wide application. Most of these experiments used the simplest possible timing schedule, a response-initiated delay (RID) schedule 3 . In this schedule the animal (e.g., a pigeon) can respond at any time, t , after food. The response changes the key color and food is delivered after a further T s. Time t is under the control of the animal; time T is determined by the experimenter. These experiments have shown that wait time on these and similar schedules (such as fixed interval) is strongly determined by the duration of the previous interfood interval (IFI). For example, wait time will track a cyclic sequence of IFIs, intercalated at a random point in a sequence of fixed ( t + T =constant) intervals, with a lag of one interval; a single short IFI is followed by a short wait time in the next interval (the effect of a single long interval is smaller), and so on (see Staddon et al. 2002 for a review and other examples of temporal tracking). To a first approximation, these results are consistent with a linear relation between wait time in IFI N + 1 and the duration of IFI N :

where I is the IFI, a is a constant less than one, and b is usually negligible. This relation has been termed linear waiting ( Wynne & Staddon 1988 ). The principle is an approximation: an expanded model, incorporating the multiple time scale theory, allows the principle to account for the slower effects of increases as opposed to decreases in IFI (see Staddon et al. 2002 ).

Most importantly for this discussion, the linear waiting principle appears to be obligatory. That is, organisms seem to follow the linear waiting rule even if they delay or even prevent reinforcer delivery by doing so. The simplest example is the RID schedule itself. Wynne & Staddon (1988) showed that it makes no difference whether the experimenter holds delay time T constant or the sum of t + T constant ( t + T = K ): Equation 1 holds in both cases, even though the optimal (reinforcement-rate-maximizing) strategy in the first case is for the animal to set t equal to zero, whereas in the second case reinforcement rate is maximized so long as t < K . Using a version of RID in which T in interval N + 1 depended on the value of t in the preceding interval, Wynne & Staddon also demonstrated two kinds of instability predicted by linear waiting.

The fact that linear waiting is obligatory allows us to look for its effects on schedules other than the simple RID schedule. The most obvious application is to ratio schedules. The time to emit a fixed number of responses is approximately constant; hence the delay to food after the first response in each interval is also approximately constant on fixed ratio (FR), as on fixed- T RID ( Powell 1968 ). Thus, the optimal strategy on FR, as on fixed- T RID, is to respond immediately after food. However, in both cases animals wait before responding and, as one might expect based on the assumption of a roughly constant interresponse time on all ratio schedules, the duration of the wait on FR is proportional to the ratio requirement ( Powell 1968 ), although longer than on a comparable chain-type schedule with the same interreinforcement time ( Crossman et al. 1974 ). The phenomenon of ratio strain —the appearance of long pauses and even extinction on high ratio schedules ( Ferster & Skinner 1957 )—may also have something to do with obligatory linear waiting.

Chain Schedules

A chain schedule is one in which a stimulus change, rather than primary reinforcement, is scheduled. Thus, a chain fixed-interval–fixed-interval schedule is one in which, for example, food reinforcement is followed by the onset of a red key light in the presence of which, after a fixed interval, a response produces a change to green. In the presence of green, food delivery is scheduled according to another fixed interval. RID schedules resemble two-link chain schedules. The first link is time t , before the animal responds; the second link is time T , after a response. We may expect, therefore, that waiting time in the first link of a two-link schedule will depend on the duration of the second link. We describe two results consistent with this conjecture and then discuss some exceptions.

Davison (1974) studied a two-link chain fixed-interval–fixed-interval schedule. Each cycle of the schedule began with a red key. Responding was reinforced, on fixed-interval I 1 s, by a change in key color from red to white. In the presence of white, food reinforcement was delivered according to fixed-interval I 2 s, followed by reappearance of the red key. Davison varied I 1 and I 2 and collected steady-state rate, pause, and link-duration data. He reported that when programmed second-link duration was long in relation to the first-link duration, pause in the first link sometimes exceeded the programmed link duration. The linear waiting predictions for this procedure can therefore be most easily derived for those conditions where the second link is held constant and the first link duration is varied (because under these conditions, the first-link pause was always less than the programmed first-link duration). The prediction for the terminal link is

where a is the proportionality constant, I 2 is the duration of the terminal-link fixed-interval, and t 2 is the pause in the terminal link. Because I 2 is constant in this phase, t 2 is also constant. The pause in the initial link is given by

where I 1 is the duration of the first link. Because I 2 is constant, Equation 3 is a straight line with slope a and positive y-intercept aI 2 .

Linear waiting theory can be tested with Davison's data by plotting, for every condition, t 1 and t 2 versus time-to-reinforcement (TTR); that is, plot pause in each link against TTR for that link in every condition. Linear waiting makes a straightforward prediction: All the data points for both links should lie on the same straight line through the origin (assuming that b → 0). We show this plot in Figure 1 . There is some variability, because the data points are individual subjects, not averages, but points from first and second links fit the same line, and the deviations do not seem to be systematic.

Steady-state pause duration plotted against actual time to reinforcement in the first and second links of a two-link chain schedule. Each data point is from a single pigeon in one experimental condition (three data points from an incomplete condition are omitted). (From Davison 1974 , Table 1)

A study by Innis et al. (1993) provides a dynamic test of the linear waiting hypothesis as applied to chain schedules. Innis et al. studied two-link chain schedules with one link of fixed duration and the other varying from reinforcer to reinforcer according to a triangular cycle. The dependent measure was pause in each link. Their Figure 3, for example, shows the programmed and actual values of the second link of the constant-cycle procedure (i.e., the first link was a constant 20 s; the second link varied from 5 to 35 s according to the triangular cycle) as well as the average pause, which clearly tracks the change in second-link duration with a lag of one interval. They found similar results for the reverse procedure, cycle-constant , in which the first link varied cyclically and the second link was constant. The tracking was a little better in the first procedure than in the second, but in both cases first-link pause was determined primarily by TTR.

There are some data suggesting that linear waiting is not the only factor that determines responding on simple chain schedules. In the four conditions of Davison's experiment in which the programmed durations of the first and second links added to a constant (120 s)—which implies a constant first-link pause according to linear waiting—pause in the first link covaried with first-link duration, although the data are noisy.

The alternative to the linear waiting account of responding on chain schedules is an account in terms of conditioned reinforcement (also called secondary reinforcement)—the idea that a stimulus paired with a primary reinforcer acquires some independent reinforcing power. This idea is also the organizing principle behind most theories of free-operant choice. There are some data that seem to imply a response-strengthening effect quite apart from the linear waiting effect, but they do not always hold up under closer inspection. Catania et al. (1980) reported that “higher rates of pecking were maintained by pigeons in the middle component of three-component chained fixed-interval schedules than in that component of the corresponding multiple schedule (two extinction components followed by a fixed-interval component)” (p. 213), but the effect was surprisingly small, given that no responding at all was required in the first two components. Moreover, results of a more critical control condition, chain versus tandem (rather than multiple) schedule, were the opposite: Rate was generally higher in the middle tandem component than in the second link of the chain. (A tandem schedule is one with the same response contingencies as a chain but with the same stimulus present throughout.)

Royalty et al. (1987) introduced a delay into the peck-stimulus-change contingency of a three-link variable-interval chain schedule and found large decreases in response rate [wait time (WT) was not reported] in both first and second links. They concluded that “because the effect of delaying stimulus change was comparable to the effect of delaying primary reinforcement in a simple variable-interval schedule … the results provide strong evidence for the concept of conditioned reinforcement” (p. 41). The implications of the Royalty et al. data for linear waiting are unclear, however, ( a ) because the linear waiting hypothesis does not deal with the assignment-of-credit problem, that is, the selection of the appropriate response by the schedule. Linear waiting makes predictions about response timing—when the operant response occurs—but not about which response will occur. Response-reinforcer contiguity may be essential for the selection of the operant response in each chain link (as it clearly is during “shaping”), and diminishing contiguity may reduce response rate, but contiguity may play little or no role in the timing of the response. The idea of conditioned reinforcement may well apply to the first function but not to the second. ( b ) Moreover, Royalty et al. did not report obtained time-to-reinforcement data; the effect of the imposed delay may therefore have been via an increase in component duration rather than directly on response rate.

Williams & Royalty (1990) explicitly compared conditioned reinforcement and time to reinforcement as explanations for chain schedule performance in three-link chains and concluded “that time to reinforcement itself accounts for little if any variance in initial-link responding” (p. 381) but not timing, which was not measured. However, these data are from chain schedules with both variable-interval and fixed-interval links, rather than fixed-interval only, and with respect to response rate rather than pause measures. In a later paper Williams qualified this claim: “The effects of stimuli in a chain schedule are due partly to the time to food correlated with the stimuli and partly to the time to the next conditioned reinforcer in the sequence” (1997, p. 145).

The conclusion seems to be that linear waiting plays a relatively major, and conditioned reinforcement (however defined) a relatively minor, role in the determination of response timing on chain fixed-interval schedules. Linear waiting also provides the best available account of a striking, unsolved problem with chain schedules: the fact that in chains with several links, pigeon subjects may respond at a low level or even quit completely in early links ( Catania 1979 , Gollub 1977 ). On fixed-interval chain schedules with five or more links, responding in the early links begins to extinguish and the overall reinforcement rate falls well below the maximum possible—even if the programmed interreinforcement interval is relatively short (e.g., 6×15=90 s). If the same stimulus is present in all links (tandem schedule), or if the six different stimuli are presented in random order (scrambled-stimuli chains), performance is maintained in all links and the overall reinforcement rate is close to the maximum possible (6 I , where I is the interval length). Other studies have reported very weak responding in early components of a simple chain fixed-interval schedule (e.g., Catania et al. 1980 , Davison 1974 , Williams 1994 ; review in Kelleher & Gollub 1962 ). These studies found that chains with as few as three fixed-interval 60-s links ( Kelleher & Fry 1962 ) occasionally produce extreme pausing in the first link. No formal theory of the kind that has proliferated to explain behavior on concurrent chain schedules (discussed below) has been offered to account for these strange results, even though they have been well known for many years.

The informal suggestion is that the low or zero response rates maintained by early components of a multi-link chain are a consequence of the same discrimination process that leads to extinction in the absence of primary reinforcement. Conversely, the stimulus at the end of the chain that is actually paired with primary reinforcement is assumed to be a conditioned reinforcer; stimuli in the middle sustain responding because they lead to production of a conditioned reinforcer ( Catania et al. 1980 , Kelleher & Gollub 1962 ). Pairing also explains why behavior is maintained on tandem and scrambled-stimuli chains ( Kelleher & Fry 1962 ). In both cases the stimuli early in the chain are either invariably (tandem) or occasionally (scrambled-stimulus) paired with primary reinforcement.

There are problems with the conditioned-reinforcement approach, however. It can explain responding in link two of a three-link chain but not in link one, which should be an extinction stimulus. The explanatory problem gets worse when more links are added. There is no well-defined principle to tell us when a stimulus changes from being a conditioned reinforcer, to a stimulus in whose presence responding is maintained by a conditioned reinforcer, to an extinction stimulus. What determines the stimulus property? Is it stimulus number, stimulus duration or the durations of stimuli later in the chain? Perhaps there is some balance between contrast/extinction, which depresses responding in early links, and conditioned reinforcement, which is supposed to (but sometimes does not) elevate responding in later links? No well-defined compound theory has been offered, even though there are several quantitative theories for multiple-schedule contrast (e.g., Herrnstein 1970 , Nevin 1974 , Staddon 1982 ; see review in Williams 1988 ). There are also data that cast doubt even on the idea that late-link stimuli have a rate-enhancing effect. In the Catania et al. (1980) study, for example, four of five pigeons responded faster in the middle link of a three-link tandem schedule than the comparable chain.

The lack of formal theories for performance on simple chains is matched by a dearth of data. Some pause data are presented in the study by Davison (1974) on pigeons in a two-link fixed-interval chain. The paper attempted to fit Herrnstein's (1970) matching law between response rates and link duration. The match was poor: The pigeon's rates fell more than predicted when the terminal links (contiguous with primary reinforcement) of the chain were long, but Davison did find that “the terminal link schedule clearly changes the pause in the initial link, longer terminal-link intervals giving longer initial-link pauses” (1974, p. 326). Davison's abstract concludes, “Data on pauses during the interval schedules showed that, in most conditions, the pause duration was a linear function of the interval length, and greater in the initial link than in the terminal link” (p. 323). In short, the pause (time-to-first-response) data were more lawful than response-rate data.

Linear waiting provides a simple explanation for excessive pausing on multi-link chain fixed-interval schedules. Suppose the chief function of the link stimuli on chain schedules is simply to signal changing times to primary reinforcement 4 . Thus, in a three-link fixed-interval chain, with link duration I , the TTR signaled by the end of reinforcement (or by the onset of the first link) is 3 I . The onset of the next link signals a TTR of 2 I and the terminal, third, link signals a TTR of I . The assumptions of linear waiting as applied to this situation are that pausing (time to first response) in each link is determined entirely by TTR and that the wait time in interval N +1 is a linear function of the TTR in the preceding interval.

To see the implications of this process, consider again a three-link chain schedule with I =1 (arbitrary time units). The performance to be expected depends entirely on the value of the proportionality constant, a , that sets the fraction of time-to-primary-reinforcement that the animal waits (for simplicity we can neglect b ; the logic of the argument is unaffected). All is well so long as a is less than one-third. If a is exactly 0.333, then for unit link duration the pause in the third link is 0.33, in the second link 0.67, and in the first link 1.0 However, if a is larger, for instance 0.5, the three pauses become 0.5, 1.0, and 1.5; that is, the pause in the first link is now longer than the programmed interval, which means the TTR in the first link will be longer than 3 the next time around, so the pause will increase further, and so on until the process stabilizes (which it always does: First-link pause never goes to ∞).

The steady-state wait times in each link predicted for a five-link chain, with unit-duration links, for two values of a are shown in Figure 2 . In both cases wait times in the early links are very much longer than the programmed link duration. Clearly, this process has the potential to produce very large pauses in the early links of multilink-chain fixed-interval schedules and so may account for the data Catania (1979) and others have reported.

Wait time (pause, time to first response) in each equal-duration link of a five-link chain schedule (as a multiple of the programmed link duration) as predicted by the linear-waiting hypothesis. The two curves are for two values of parameter a in Equation 1 ( b =0). Note the very long pauses predicted in early links—almost two orders of magnitude greater than the programmed interval in the first link for a =0.67. (From Mazur 2001 )

Gollub in his dissertation research (1958) noticed the additivity of this sequential pausing. Kelleher & Gollub (1962) in their subsequent review wrote, “No two pauses in [simple fixed interval] can both postpone food-delivery; however, pauses in different components of [a] five-component chain will postpone food-delivery additively” (p. 566). However, this additivity was only one of a number of processes suggested to account for the long pauses in early chain fixed-interval links, and its quantitative implications were never explored.

Note that the linear waiting hypothesis also accounts for the relative stability of tandem schedules and chain schedules with scrambled components. In the tandem schedule, reinforcement constitutes the only available time marker. Given that responding after the pause continues at a relatively high rate until the next time marker, Equation 1 (with b assumed negligible) and a little algebra shows that the steady-state postreinforcement pause for a tandem schedule with unit links will be

where N is the number of links and a is the pause fraction. In the absence of any time markers, pauses in links after the first are necessarily short, so the experienced link duration equals the programmed duration. Thus, the total interfood-reinforcement interval will be t + N − 1 ( t ≥ 1): the pause in the first link (which will be longer than the programmed link duration for N > 1/ a ) plus the programmed durations of the succeeding links. For the case of a = 0.67 and unit link duration, which yielded a steady-state interfood interval (IFI) of 84 for the five-link chain schedule, the tandem yields 12. For a = 0.5, the two values are approximately 16 and 8.

The long waits in early links shown in Figure 2 depend critically on the value of a . If, as experience suggests (there has been no formal study), a tends to increase slowly with training, we might expect the long pausing in initial links to take some time to develop, which apparently it does ( Gollub 1958 ).

On the scrambled-stimuli chain each stimulus occasionally ends in reinforcement, so each signals a time-to-reinforcement (TTR) 5 of I , and pause in each link should be less than the link duration—yielding a total IFI of approximately N , i.e., 5 for the example in the figure. These predictions yield the order IFI in the chain > tandem > scrambled, but parametric data are not available for precise comparison. We do not know whether an N -link scrambled schedule typically stabilizes at a shorter IFI than the comparable tandem schedule, for example. Nor do we know whether steady-state pause in successive links of a multilink chain falls off in the exponential fashion shown in Figure 2 .

In the final section we explore the implications of linear waiting for studies of free-operant choice behavior.

Although we can devote only limited space to it, choice is one of the major research topics in operant conditioning (see Mazur 2001 , p. 96 for recent statistics). Choice is not something that can be directly observed. The subject does this or that and, in consequence, is said to choose. The term has unfortunate overtones of conscious deliberation and weighing of alternatives for which the behavior itself—response A or response B—provides no direct evidence. One result has been the assumption that the proper framework for all so-called choice studies is in terms of response strength and the value of the choice alternatives. Another is the assumption that procedures that are very different are nevertheless studying the same thing.

For example, in a classic series of experiments, Kahneman & Tversky (e.g., 1979) asked a number of human subjects to make a single choice of the following sort: between $400 for sure and a 50% chance of $1000. Most went for the sure thing, even though the expected value of the gamble is higher. This is termed risk aversion , and the same term has been applied to free-operant “choice” experiments. In one such experiment an animal subject must choose repeatedly between a response leading to a fixed amount of food and one leading equiprobably to either a large or a small amount with the same average value. Here the animals tend to be either indifferent or risk averse, preferring the fixed alternative ( Staddon & Innis 1966b , Bateson & Kacelnik 1995 , Kacelnik & Bateson 1996 ).

In a second example pigeons responded repeatedly to two keys associated with equal variable-interval schedules. A successful response on the left key, for example, is reinforced by a change in the color of the pecked key (the other key light goes off). In the presence of this second stimulus, food is delivered according to a fixed-interval schedule (fixed-interval X ). The first stimulus, which is usually the same on both keys, is termed the initial link ; the second stimulus is the terminal link . Pecks on the right key lead in the same way to food reinforcement on variable-interval X . (This is termed a concurrent-chain schedule.) In this case subjects overwhelmingly prefer the initial-link choice leading to the variable-interval terminal link; that is, they are apparently risk seeking rather than risk averse ( Killeen 1968 ).

The fact that these three experiments (Kahneman & Tversky and the two free-operant studies) all produce different results is sometimes thought to pose a serious research problem, but, we contend, the problem is only in the use of the term choice for all three. The procedures (not to mention the subjects) are in fact very different, and in operant conditioning the devil is very much in the details. Apparently trivial procedural differences can sometimes lead to wildly different behavioral outcomes. Use of the term choice as if it denoted a unitary subject matter is therefore highly misleading. We also question the idea that the results of choice experiments are always best explained in terms of response strength and stimulus value.

Concurrent Schedules

Bearing these caveats in mind, let's look briefly at the extensive history of free-operant choice research. In Herrnstein's seminal experiment (1961 ; see Davison & McCarthy 1988 , Williams 1988 for reviews; for collected papers see Rachlin & Laibson 1997 ) hungry pigeons pecked at two side-by-side response keys, one associated with variable-interval v 1 s and the other with variable-interval v 2 s ( concurrent variable-interval–variable-interval schedule). After several experimental sessions and a range of v 1 and v 2 values chosen so that the overall programmed reinforcement rate was constant (1/ v 1 + 1/ v 2 = constant), the result was matching between steady-state relative response rates and relative obtained reinforcement rates:

where x and y are the response rates on the two alternatives and R ( x ) and R ( y ) are the rates of obtained reinforcement for them. This relation has become known as Herrnstein's matching law. Although the obtained reinforcement rates are dependent on the response rates that produce them, the matching relation is not forced, because x and y can vary over quite a wide range without much effect on R ( x ) and R ( y ).

Because of the negative feedback relation intrinsic to variable-interval schedules (the less you respond, the higher the probability of payoff), the matching law on concurrent variable-interval–variable-interval is consistent with reinforcement maximization ( Staddon & Motheral 1978 ), although the maximum of the function relating overall payoff, R ( x ) + R ( y ), to relative responding, x /( x + y ), is pretty flat. However, little else on these schedules fits the maximization idea. As noted above, even responding on simple fixed- T response-initiated delay (RID) schedules violates maximization. Matching is also highly overdetermined, in the sense that almost any learning rule consistent with the law of effect—an increase in reinforcement probability causes an increase in response probability—will yield either simple matching ( Equation 5 ) or its power-law generalization ( Baum 1974 , Hinson & Staddon 1983 , Lander & Irwin 1968 , Staddon 1968 ). Matching by itself therefore reveals relatively little about the dynamic processes operating in the responding subject (but see Davison & Baum 2000 ). Despite this limitation, the strikingly regular functional relations characteristic of free-operant choice studies have attracted a great deal of experimental and theoretical attention.

Herrnstein (1970) proposed that Equation 5 can be derived from the function relating steady-state response rate, x , and reinforcement rate, R ( x ), to each response key considered separately. This function is negatively accelerated and well approximated by a hyperbola:

where k is a constant and R 0 represents the effects of all other reinforcers in the situation. The denominator and parameter k cancel in the ratio x / y , yielding Equation 5 for the choice situation.

There are numerous empirical details that are not accounted for by this formulation: systematic deviations from matching [undermatching and overmatching ( Baum 1974 )] as a function of different types of variable-interval schedules, dependence of simple matching on use of a changeover delay , extensions to concurrent-chain schedules, and so on. For example, if animals are pretrained with two alternatives presented separately, so that they do not learn to switch between them, when given the opportunity to respond to both, they fixate on the richer one rather than matching [extreme overmatching ( Donahoe & Palmer 1994 , pp. 112–113; Gallistel & Gibbon 2000 , pp. 321–322)]. (Fixation—extreme overmatching—is, trivially, matching, of course but if only fixation were observed, the idea of matching would never have arisen. Matching implies partial, not exclusive, preference.) Conversely, in the absence of a changeover delay, pigeons will often just alternate between two unequal variable-interval choices [extreme undermatching ( Shull & Pliskoff 1967 )]. In short, matching requires exactly the right amount of switching. Nevertheless, Herrnstein's idea of deriving behavior in choice experiments from the laws that govern responding to the choice alternatives in isolation is clearly worth pursuing.

In any event, Herrnstein's approach—molar data, predominantly variable-interval schedules, rate measures—set the basic pattern for subsequent operant choice research. It fits the basic presuppositions of the field: that choice is about response strength , that response strength is equivalent to response probability, and that response rate is a valid proxy for probability (e.g., Skinner 1938 , 1966 , 1986 ; Killeen & Hall 2001 ). (For typical studies in this tradition see, e.g., Fantino 1981 ; Grace 1994 ; Herrnstein 1961 , 1964 , 1970 ; Rachlin et al. 1976 ; see also Shimp 1969 , 2001 .)

We can also look at concurrent schedules in terms of linear waiting. Although published evidence is skimpy, recent unpublished data ( Cerutti & Staddon 2002 ) show that even on variable-interval schedules (which necessarily always contain a few very short interfood intervals), postfood wait time and changeover time covary with mean interfood time. It has also long been known that Equation 6 can be derived from two time-based assumptions: that the number of responses emitted is proportional to the number of reinforcers received multiplied by the available time and that available time is limited by the time taken up by each response ( Staddon 1977 , Equations 23–25). Moreover, if we define mean interresponse time as the reciprocal of mean response rate, 6 x , and mean interfood interval is the reciprocal of obtained reinforcement rate, R ( x ), then linear waiting yields

where a and b are linear waiting constants. Rearranging yields

where 1/ b = k and a / b = R 0 in Equation 6 . Both these derivations of the hyperbola in Equation 6 from a linear relation in the time domain imply a correlation between parameters k and R 0 in Equation 6 under parametric experimental variation of parameter b by (for example) varying response effort or, possibly, hunger motivation. Such covariation has been occasionally but not universally reported ( Dallery et al. 2000 , Heyman & Monaghan 1987 , McDowell & Dallery 1999 ).

Concurrent-Chain Schedules

Organisms can be trained to choose between sources of primary reinforcement (concurrent schedules) or between stimuli that signal the occurrence of primary reinforcement ( conditioned reinforcement : concurrent chain schedules). Many experimental and theoretical papers on conditioned reinforcement in pigeons and rats have been published since the early 1960s using some version of the concurrent chains procedure of Autor (1960 , 1969) . These studies have demonstrated a number of functional relations between rate measures and have led to several closely related theoretical proposals such as a version of the matching law, incentive theory, delay-reduction theory, and hyperbolic value-addition (e.g., Fantino 1969a , b ; Grace 1994 ; Herrnstein 1964 ; Killeen 1982 ; Killeen & Fantino 1990 ; Mazur 1997 , 2001 ; Williams 1988 , 1994 , 1997 ). Nevertheless, there is as yet no theoretical consensus on how best to describe choice between sources of conditioned reinforcement, and no one has proposed an integrated theoretical account of simple chain and concurrent chain schedules.

Molar response rate does not capture the essential feature of behavior on fixed-interval schedules: the systematic pattern of rate-change in each interfood interval, the “scallop.” Hence, the emphasis on molar response rate as a dependent variable has meant that work on concurrent schedules has emphasized variable or random intervals over fixed intervals. We lack any theoretical account of concurrent fixed-interval–fixed-interval and fixed-interval–variable-interval schedules. However, a recent study by Shull et al. (2001 ; see also Shull 1979) suggests that response rate may not capture what is going on even on simple variable-interval schedules, where the time to initiate bouts of relatively fixed-rate responding seems to be a more sensitive dependent measure than overall response rate. More attention to the role of temporal variables in choice is called for.

We conclude with a brief account of how linear waiting may be involved in several well-established phenomena of concurrent-chain schedules: preference for variable-interval versus fixed-interval terminal links, effect of initial-link duration, and finally, so-called self-control experiments.

preference for variable-interval versus fixed-interval terminal links On concurrent-chain schedules with equal variable-interval initial links, animals show a strong preference for the initial link leading to a variable-interval terminal link over the terminal-link alternative with an equal arithmetic-mean fixed interval. This result is usually interpreted as a manifestation of nonarithmetic (e.g., harmonic) reinforcement-rate averaging ( Killeen 1968 ), but it can also be interpreted as linear waiting. Minimum TTR is necessarily much less on the variable-interval than on the fixed-interval side, because some variable intervals are short. If wait time is determined by minimum TTR—hence shorter wait times on the variable-interval side—and ratios of wait times and overall response rates are (inversely) correlated ( Cerutti & Staddon 2002 ), the result will be an apparent bias in favor of the variable-interval choice.

effect of initial-link duration Preference for a given pair of terminal-link schedules depends on initial link duration. For example, pigeons may approximately match initial-link relative response rates to terminal-link relative reinforcement rates when the initial links are 60 s and the terminal links range from 15 to 45 s ( Herrnstein 1964 ), but they will undermatch when the initial-link schedule is increased to, for example, 180 s. This effect is what led to Fantino's delay-reduction modification of Herrnstein's matching law (see Fantino et al. 1993 for a review). However, the same qualitative prediction follows from linear waiting: Increasing initial-link duration reduces the proportional TTR difference between the two choices. Hence the ratio of WTs or of initial-link response rates for the two choices should also approach unity, which is undermatching. Several other well-studied theories of concurrent choice, such as delay reduction and hyperbolic value addition, also explain these results.

Self-Control

The prototypical self-control experiment has a subject choosing between two outcomes: not-so-good cookie now or a good cookie after some delay ( Rachlin & Green 1972 ; see Logue 1988 for a review; Mischel et al. 1989 reviewed human studies). Typically, the subject chooses the immediate, small reward, but if both delays are increased by the same amount, D , he will learn to choose the larger reward, providing D is long enough. Why? The standard answer is derived from Herrnstein's matching analysis ( Herrnstein 1981 ) and is called hyperbolic discounting (see Mazur 2001 for a review and Ainslie 1992 and Rachlin 2000 for longer accounts). The idea is that the expected value of each reward is inversely related to the time at which it is expected according to a hyperbolic function:

where A i is the undiscounted value of the reward, D i is the delay until reward is received, i denotes the large or small reward, and k is a fitted constant.

Now suppose we set D L and D S to values such that the animal shows a preference for the shorter, sooner reward. This would be the case ( k =1) if A L =6, A S =2, D L = 6 s, and D S = 1 s: V L =0.86 and V S =1—preference for the small, less-delayed reward. If 10 s is added to both delays, so that D L = 16 s and D S =11 s, the values are V L =0.35 and V S =0.17—preference for the larger reward. Thus, Equation 8 predicts that added delay—sometimes awkwardly termed pre-commitment— should enhance self-control, which it does.

The most dramatic prediction from this analysis was made and confirmed by Mazur (1987 , 2001) in an experiment that used an adjusting-delay procedure (also termed titration ). “A response on the center key started each trial, and then a pigeon chose either a standard alternative (by pecking the red key) or an adjusting alternative (by pecking the green key) … the standard alternative delivered 2 s of access to grain after a 10-s delay, and the adjusting alternative delivered 6 s of access to grain after an adjusting delay” (2001, p. 97). The adjusting delay increased (on the next trial) when it was chosen and decreased when the standard alternative was chosen. (See Mazur 2001 for other procedural details.) The relevant independent variable is TTR. The discounted value of each choice is given by Equation 8 . When the subject is indifferent does not discriminate between the two choices, V L = V S . Equating Equation 8 for the large and small choices yields

that is, an indifference curve that is a linear function relating D L and D S , with slope A L / A S > 1 and a positive intercept. The data ( Mazur 1987 ; 2001 , Figure 2 ) are consistent with this prediction, but the intercept is small.

It is also possible to look at this situation in terms of linear waiting. One assumption is necessary: that the waiting fraction, a , in Equation 1 is smaller when the upcoming reinforcer is large than when it is small ( Powell 1969 and Perone & Courtney 1992 showed this for fixed-ratio schedules; Howerton & Meltzer 1983 , for fixed-interval). Given this assumption, the linear waiting analysis is even simpler than hyperbolic discounting. The idea is that the subject will appear to be indifferent when the wait times to the two alternatives are equal. According to linear waiting, the wait time for the small alternative is given by

where b S is a small positive intercept and a S > a L . Equating the wait times for small and large alternatives yields

which is also a linear function with slope > 1 and a small positive intercept.

Equations 9 and 11 are identical in form. Thus, the linear waiting and hyperbolic discounting models are almost indistinguishable in terms of these data. However, the linear waiting approach has three potential advantages: Parameters a and b can be independently measured by making appropriate measurements in a control study that retains the reinforcement-delay properties of the self-control experiments without the choice contingency; the linear waiting approach lacks the fitted parameter k in Equation 9 ; and linear waiting also applies to a wide range of time-production experiments not covered by the hyperbolic discounting approach.

Temporal control may be involved in unsuspected ways in a wide variety of operant conditioning procedures. A renewed emphasis on the causal factors operating in reinforcement schedules may help to unify research that has hitherto been defined in terms of more abstract topics like timing and choice.

ACKNOWLEDGMENTS

We thank Catalin Buhusi and Jim Mazur for comments on an earlier version and the NIMH for research support over many years.

1 The first and only previous Annual Review contribution on this topic was as part of a 1965 article, “Learning, Operant Conditioning and Verbal Learning” by Blough & Millward. Since then there have been (by our estimate) seven articles on learning or learning theory in animals, six on the neurobiology of learning, and three on human learning and memory, but this is the first full Annual Review article on operant conditioning. We therefore include rather more old citations than is customary (for more on the history and philosophy of Skinnerian behaviorism, both pro and con, see Baum 1994 , Rachlin 1991 , Sidman 1960 , Staddon 2001b , and Zuriff 1985 ).

2 By “internal” we mean not “physiological” but “hidden.” The idea is simply that the organism's future behavior depends on variables not all of which are revealed in its current behavior (cf. Staddon 2001b , Ch. 7).

3 When there is no response-produced stimulus change, this procedure is also called a conjunctive fixed-ratio fixed-time schedule ( Shull 1970 ).

4 This idea surfaced very early in the history of research on equal-link chain fixed-interval schedules, but because of the presumed importance of conditioned reinforcement, it was the time to reinforcement from link stimulus offset, rather than onset that was thought to be important. Thus, Gollub (1977) , echoing his 1958 Ph.D. dissertation in the subsequent Kelleher & Gollub (1962) review, wrote, “In chained schedules with more than two components … the extent to which responding is sustained in the initial components … depends on the time that elapses from the end of the components to food reinforcement” (p. 291).

5 Interpreted as time to the first reinforcement opportunity.

6 It is not of course: The reciprocal of the mean IRT is the harmonic mean rate. In practice, “mean response rate” usually means arithmetic mean, but note that harmonic mean rate usually works better for choice data than the arithmetic mean (cf. Killeen 1968 ).

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Home — Essay Samples — Psychology — Operant Conditioning — The Connection Between Classical And Operant Conditioning

The Connection Between Classical and Operant Conditioning

• Categories: Operant Conditioning

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• Last Updated November 30th, 2018 07:12 pm. (n.d.). Operant Conditioning (B.F. Skinner). Retrieved from https://www.instructionaldesign.org/theories/operant-conditioning/.
• Mcleod, S. (2018, August 21). Classical Conditioning. Retrieved from https://www.simplypsychology.org/classical-conditioning.html.
• Bouton, M. E. (2019). Conditioning and learning. In R. Biswas-Diener & E. Diener (Eds), Noba textbook series: Psychology. Champaign, IL: DEF publishers. Retrieved from http://noba.to/ajxhcqdr
• King, L.A. (2016). The Science of Psychology: An Appreciative View. McGraw-Hill Education.

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Intro Psych Blog (F23)_Group 1

Making connections between theory and everyday life…

Classical Conditioning

A type of learning where an organism learns to associate stimuli is defined as classical conditioning. There are four parts to classical conditioning: unconditioned stimulus, conditioned stimulus, unconditioned response, and conditioned response. Unconditioned stimulus is the stimulus that leads to an automatic response. In Pavlov’s dog experiment, he conditioned a dog. The unconditioned stimulus would be the dog’s food in his experiment. The unconditioned response is the automatic response to a stimulus. So in this case of Pavlov’s experiment, the unconditioned response would be the salvation from the dog when the dog sees food. Pavlov then conditioned the dog with the sound of a bell. The bell would be rang and the dog would be given food. After repeating the conditioning, eventually the dog associates the sound of the bell to food and will start salvation. In this experiment the conditioned stimulus is the bell which is a stimulus that results in the conditioned response. The conditioned response is the salvation from the dog. The conditioned response results from the conditioned stimulus, so in this experiment the sound of the bell makes the dog drool because the sound of the bell is associated with the dog’s food. 

“Unconditioned Stimulus in Classical Conditioning: Definition & Examples.” Www.simplypsychology.org , www.simplypsychology.org/unconditioned-stimulus.html.

I have conditioned my dog even though my parents doubted me. I have a small dog named Bentley. I wanted to teach him to put up his paw when I say the word “paw”. His favorite treats to eat are carrots so I had a bunch of carrots ready to give him. In the beginning I would say the word “paw” and use my hands to lift up his paw. Then I would reward him with a carrot. I did that multiple times for 4 days. As I kept doing it, my dog started to learn that in order to get a treat he needs to put up his paw. Eventually, he was conditioned. If I say “paw” to Bentley then he will place his paw in my hand. Most of the time I will still give him a treat after but he will do it without a treat as well. My parents did not think my dog would learn it because he has never been good at learning tricks but I simply told them that it’s classical conditioning and that he would learn after repeated trials. Due to classical conditioning, Bentley is able to do multiple tricks. 

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Theory of Operant Conditioning Essay

Introduction, main discussion.

Operant conditioning presents the idea that “behavior is a function of its consequences.” (Robbins & Judge, 2008, p. 55). In other words, people act and behave a certain way to get something they want or to avoid it. This kind of behavior is learned and voluntary unlike the classical conditioning theory that presents the idea that behavior is reflexive and unlearned. To carry out this behavior it has to be learned and that can be done through the introduction of reinforcements. If a good or behavior is reinforced it is highly likely that it will be repeated. (Robbins & Judge, 2008, pp. 55–56).

B.F. Skinner, the mastermind behind the operant conditioning theory “argued that creating pleasing consequences to follow specific forms of behavior would increase the frequency of that behavior. He demonstrated that people will most likely engage in desired behaviors if they are positively reinforced for doing so; that rewards are most effective if they immediately follow the desired response; and that behavior that is not rewarded, or is punished, is less likely to be repeated” (Robbins & Judge, 2008, p. 56). For example, if your are praised every time you come up with a creative idea at work you will be more likely to be motivated to come up with more ideas and present them without hesitation. Appraisal might give you intrinsic motivation to repeat that behavior whereas if your ideas are ignored and tossed out the window without even being considered, next time you might think twice before presenting an idea even though it might be genius.

There are two types of reinforcers: primary and secondary. Primary reinforcers include food, water, sex, etc. They are physiologically or biologically determined. Secondary reinforcers are praise, recognition, money and etc. They derive their effect from a consistent pairing with other reinforcements in the past.

There are five reinforcement strategies: positive reinforcement, negative reinforcement, punishment and extinction. Positive reinforcement occurs “when a behavior is strengthened as a result of receiving a positive condition.” (Types of Operant Conditioning) In other words, if you perform action x, and the result is action y, and if action y is a good result that makes you feel good or is a positive one, you will do action x more often. For example, when I play tennis, I feel good and energized, so I play more tennis.

“Negative reinforcement happens when a behavior is strengthened as a result of stopping or avoiding a negative condition.” In other words, if partaking in action ‘x’ feels bad and partaking in action ‘y’ feels better, I will probably partake in action ‘y’ more. For example, if I have more fun playing tennis with person ‘a’ and I don’t enjoy playing tennis with person ‘b’ I will probably play with person ‘a’ more than person ‘b’.

“Punishment works when a behavior is weakened as a result of experiencing a negative condition.” (Types of Operant Conditioning) Basically if you do something and consequence is a bad one, you will perform that action less. For example, you get points subtracted from your class participation grade if you’re late for class so you try to come to class on time so you don’t get class participation points deducted.

“Extinction occurs when a behavior is weakened as a result of not experiencing an expected positive condition or a negative condition is stopped.” (Types of Operant Conditioning) This basically means that when an action is performed and there is no response to it, neither negative nor positive which will eventually cause the action to decline. For example, if a professor wants his or her class to stop asking questions during the lecture he can start to ignore students who raise their hands. Eventually when the students get no response from the professor they will stop raising their hand.

My personality and life choices can be explained very well with the Operant Conditioning theory. Intrinsic motivation means more to me than anything else in the world. I am also very motivated by money but intrinsic factors weigh out more than extrinsic motivational factors for me. I’m not a very goal oriented person and I go with the flow of things, trying to accomplish the tasks at hand and then dealing with other situations as they come along my path. The only time I set goals is when I am highly motivated to accomplish a task. Each time I am positively appraised by a professor I get motivated to repeat the same behavior. For example earning a teachers respect is far more important to me than scoring an A grade. When a teacher values me as their student based on what I have to offer to the class and my keen desire to learn instead of evaluating me on the grade I might get on a midterm I am more motivated to excel in the class. Studying and completing assignments seem like tedious activities to me and I usually procrastinate a lot but whenever I know that if I accomplish a certain task my ideas will be appreciated in or outside the classroom I will be more motivated to complete the task. To me appraisal is more important than other factors.

Like any individual I make a lot of mistakes and as I go over them I can classify many of my life incidents either according to negative reinforcement or punishment. The distinction between negative reinforcement and punishment is that in the former “the aversive consequence is used to increase the future occurrence of a wanted behavior” whereas in the latter the “aversive consequence is used to decrease the future occurrence of an undesired behavior.” Negative reinforcement increases the probability of the desired behavior by escape and avoidance. When it comes to making decisions I sometimes use the escape method. I let the guilt ring on and only do something about it once I can’t handle it anymore. For example I recently ordered a product through a friend and later decided that I want to cancel the order. The friend hadn’t taken any advance money from me and hadn’t proceeded with making the order. I badly wanted to cancel the order but I felt bad because I had put her through quite a lot of trouble when I was going through the decision making process before placing the order. Henceforth, the embarrassment of wanting to cancel the order kept on driving me crazy until I finally called her one day and explained my situation to her and apologized for the inconvenience. I finally felt better and relieved because I had escaped the situation.

Punishment is one aspect where the operant theory fails to explain my personality and the life choices I have made. According to the Operant Theory of Conditioning punishment decreases behavior whereas in my case it has always led to increased behavior. This phenomenon that B. F. Skinner forgot to incorporate is called rebelliousness. To be told that I will be punished a certain way has never worked on me. In elementary school punishment for a bad behavior would be asked to stand in a corner, in middle school it might mean detention, and in high school it might mean something more consequential. If we look back at our high school days when was it ever that detention helped a student improve his grades or behavior. The kids who got detention were already doing poorly to begin with. Punishing someone is usually not the answer to get a specific behavioral response. Punishment can have many side effects such as rebelliousness especially if a person is being punished on unreasonable grounds. Growing up we have all felt that we were unfairly punished by our parents. For some of us this tactic worked and lead us to become highly successful individuals whereas for some of us this led to massive acts of rebellion such as dyeing our hair pink and red, get face and body piercing, getting permanent tattoo’s, staying out after curfew and breaking so many other rules. Obviously other social theories like the ones of deviance and control also play a part into rebellious activities that Operant Conditioning Theory fails to explain this dilemma even partially.

Sometimes punishments can also be given on false premises and without complete knowledge of the situation for example punishing an entire group of friends because on kids act of deviance. I have also experienced that when I get punishment by loosing access to money I am not too bothered but when I get punished by being looked down upon by someone I respect it makes a huge difference to me. Cheating in a class and getting caught by my favorite professor would be a punishment in itself and will motivate me to never do the same thing again. This happened with me quite a few years ago and caused me to quit cheating all at once for a very long period of time. If I am punished for sloppy work or get a late work penalty by getting a lower pay I am not too bothered because in the end all I’m loosing is money. Money, good grades, or any such rewards are of very less importance to me and never motivate me to increase to decrease a particular type of behavior.

The theory of extinction is somewhat more valid than the theory of punishment. When I look back I can observe that whenever my suggestions or opinions in a classroom have been ignored I have slowly opted away from making any suggestions at all. Ignoring someone usually does cause the other party to stop whatever action he or she is repeating. As I dig deeply into the matter I feel that there can be two explanations of why people fit in with the theory of extinction and why some people don’t. The first factor has to do with confidence, someone who is very confident and believes in him or her self very highly then he might be persistent in repeating his actions if he or she is ignored. Another theory could be that he or she is simply ignorant and fails to asses the situation around him well. A person who succumbs to extinction might either be low on confidence, which is something I feel I am at time or is very intelligent and knows that holding ones tongue at appropriate times can be more beneficial than harmful. Although the extinction aspect of the Operant Conditioning Theory is applicable in my case it might not be in someone else’s case.

In conclusion, although the Operant Conditioning Theory successfully explains many ideas concerning behavior it fails to give importance to social concepts like deviance and control, rebelliousness, self esteem and confidence issues. The Operant Conditioning Theory is simple a ‘very simple’ way of categorizing behavioral patterns that in reality might be far more complex and deep rooted in other concepts.

• Robbins, S. P., & Judge, T. A. (2008). Essentials of organizational behavior . Upper Saddle River, N.J.: Pearson Education International.
• Types of Operant Conditioning . Web.
• Chicago (A-D)
• Chicago (N-B)

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Bibliography

IvyPanda . "Theory of Operant Conditioning." October 20, 2021. https://ivypanda.com/essays/theory-of-operant-conditioning/.

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