The interaction between organisms and their environments is complex, adaptive, and deeply shaped by memory. The Sometimes Opponent Processes Model offers one way to understand how repeated experiences alter learning, attention, and emotional response. Providing a framework to untangle the complexity of these processes is the Sometimes Opponent Processes (SOP) Model. By examining how stimulus representations move through primary activation (A1), secondary activation (A2), and inactivity, the SOP model reveals how learning and habituation unfold over time.

As we delve deeper into the SOP model, we uncover layers of understanding about motivation and emotion intertwined with associative learning principles—an essential key to understanding how behavior changes in an adaptive world.

Learning, Environmental Cues, and Conditioning

SOP provides a useful framework for understanding how organisms learn from environmental cues. In classical conditioning, a neutral conditioned stimulus (CS), such as a tone or light, may become associated with an unconditioned stimulus (US), such as food or shock. According to SOP, learning depends partly on the activation states of these representations when they overlap. This concept is a basic premise in behaviorism. We see it in Ivan Palov’s experiments with dogs and John B. Watson’s fear conditioning.

Excitatory learning is most likely when the CS is in its A1 state while the US is also in A1. In this situation, the organism experiences the cue and the outcome as strongly co-active. The cue comes to predict the outcome (Wagner, 1981; Wagner & Brandon, 2001).

Conditioned inhibition can occur under different conditions. If the CS is in A1 while the US representation is in A2, the cue may signal the absence or reduction of the expected US. In this way, SOP explains not only how cues become predictors of events, but also how they become predictors that an expected event will not occur (Wagner, 1981).

This distinction is important. Organisms do not merely learn that one thing follows another. They learn patterns of presence, absence, timing, and expectation. SOP gives these patterns a formal structure by showing how the moment-to-moment state of a memory representation influences what is learned.

SOP, Homeostasis, and Opponent-Process Theory

SOP’s name reflects its connection to earlier opponent-process theories of motivation. Solomon and Corbit (1974) proposed that strong emotional or hedonic experiences often trigger a primary reaction followed by a slower, opposing process. Fear may be followed by relief. Pleasure may be followed by discomfort or craving. Repeated exposure can strengthen the opponent process, changing the emotional tone of the experience over time (Solomon, 1980).

SOP incorporates this general idea but applies it more broadly to memory processing. In Wagner’s model, the secondary state is not limited to emotional reactions. It is a general feature of how stimulus representations are activated, decay, and influence later processing. The word ‘sometimes’ is important: the model does not claim that every stimulus automatically produces an opposing process. Rather, opponent-like effects depend on the activation state of the relevant stimulus and outcome representations.

This is especially relevant to habituation, the gradual reduction in response to a repeated stimulus. A new refrigerator hum may be irritating at first. After repeated exposure, the sound fades from awareness. SOP explains this as a form of priming. Because the representation of the sound has recently been active, it is more likely to remain in A2. When the sound occurs again, fewer elements can enter A1, and the response is reduced.

The same process can occur over longer periods. If a particular context repeatedly accompanies a stimulus, the context itself may later prime the stimulus representation into A2. This helps explain why familiar environments often feel less demanding than unfamiliar ones. The nervous system has already learned what to expect, adapting to the novel environment. Consequently, the new environment elicits fewer A1 reactions. The organism essentially settles into a homeostatic state.

Priming Theory and SOP

Priming theory plays a central role in SOP. In everyday language, priming means that prior exposure to something changes how we respond to it later. SOP gives this idea a more precise mechanism.

When a stimulus representation is already active in short-term memory, especially in A2, it is less capable of being strongly reactivated into A1. The stimulus is no longer wholly new. It has already been partially processed. As a result, the organism may respond less intensely and learn less from the repeated encounter (Wagner, 1981, p. 6).

This idea helps explain why familiar stimuli often lose their emotional force. A person moving into an apartment near a busy street may initially notice every passing truck. Over time, the traffic noise becomes part of the background. The sound has not disappeared. Rather, its representation is routinely primed, making it less likely to command full attention.

Wagner’s SOP model expanded priming theory by specifying when priming should reduce responding and when it may contribute to more complex effects. This precision was one of the model’s major contributions. Earlier priming accounts could explain reduced responding in many cases, but they had difficulty predicting when a primed stimulus might instead contribute to greater anticipation or facilitation.

Short-Term and Long-Term Habituation

SOP distinguishes between short-term and long-term habituation.

Short-term habituation occurs within a session. A repeated sound, light, or touch produces a progressively smaller response because recent presentations leave the stimulus representation in A2. Since elements in A2 are less able to return immediately to A1, the stimulus loses some of its impact.

Long-term habituation depends more heavily on context. Over repeated sessions, the environment in which the stimulus occurs may become associated with that stimulus. Later, the context can retrieve or prime the stimulus representation into A2 before the stimulus is even presented. This is known as retrieval-generated priming (Wagner, 1981; Uribe-Bahamonde et al., 2019).

For example, a person who has lived for years beside a train line may barely notice the sound at home. Yet the same train noise might feel startling in an unfamiliar location. The difference is not only the sound itself but the context that prepares the nervous system to process it.

This distinction between recent exposure and contextual priming allows SOP to explain how organisms conserve attention. We cannot respond with full intensity to every repeated stimulus. Habituation allows the organism to reserve stronger responses for novelty, change, and possible significance.

Validation of SOP’s Habituation Processes

The capacity of the SOP model to account for habituation processes has received quantitative support. In a study, Uribe-Bahamonde et al. (2019) used computer simulations to demonstrate that Wagner’s SOP model accurately captures the 9 to 10 universally recognized behavioral parameters of habituation.

They quantitatively confirmed that short-term habituation (within-session effects) results from self-generated priming, where recent exposure to a stimulus leaves its memory elements lingering in the refractory A2 state. In contrast, long-term habituation (between-session effects) is driven by associatively generated (or retrieval-generated) priming.

In this process, the surrounding context acts as a conditioned stimulus that retrieves the stimulus representation directly into the A2 state, preemptively dampening the primary A1 response before the stimulus even appears

The Library Analogy

One way to understand SOP is to imagine memory as a large library.

An inactive stimulus representation is like a book resting on the shelf. It is available, but not currently in use.

A representation in A1 is like a book open in front of you, actively being read. It occupies attention and strongly influences thought and behavior.

A representation in A2 is like a book recently read and still lying open on the desk. It is accessible, but it is no longer the focus of active reading. Because it is already on the desk, pulling out another copy of the same book does not feel like a fresh event.

Habituation follows naturally from this image. The first encounter with a stimulus brings the book sharply into attention. Repeated encounters leave it lingering nearby, reducing the need to process it as new. Contextual priming works similarly. The library shelf, room, or topic may remind the system that this book has been encountered before, preparing the organism to respond with less intensity.

The analogy is simple, but it captures the elegance of SOP: behavior depends not only on what is presented, but also on the current state of the representation when it appears.

SOP Compared with Earlier Conditioning Models

SOP advanced associative learning theory by adding real-time memory dynamics to conditioning models.

The Rescorla-Wagner model (1972), for example, provided a major account of prediction error in learning. It explained how organisms learn when outcomes are surprising and how learning changes as outcomes become expected. However, it was largely a trial-level model. It focused on the relationship between cues and outcomes across trials, rather than the moment-to-moment activation state of memory representations during a trial.

SOP added temporal detail. It asked whether a stimulus representation was in A1, A2, or inactive at the relevant moment. This allowed the model to explain why timing, spacing, context, and prior exposure matter so much in learning.

SOP also differs from models such as Pearce-Hall (1980) and Mackintosh (1975), which emphasize changes in the associability or attentional value of conditioned stimuli. Those models ask how much attention a cue receives as learning progresses. SOP asks a different, though related, question: what is the cue’s current memory state, and how does that state affect learning and response?

This focus on dynamic activation states gives SOP its distinctive theoretical contribution.

Empirical Evidence for SOP

SOP has been applied to a wide range of phenomena in associative learning and conditioning.

In spontaneous recovery, a conditioned response reappears after a delay following extinction. SOP explains this partly through changes in activation state. After time passes, the relevant representation may return from A2 to inactivity, making it available for renewed activation when the conditioned stimulus is presented again (Wagner, 1981; Wagner & Brandon, 2001).

In latent inhibition, pre-exposure to a conditioned stimulus without reinforcement slows later conditioning. SOP explains this by suggesting that repeated pre-exposure makes the CS more likely to enter A2, reducing its ability to form a strong new association when paired with a US (Lubow & Gewirtz, 1995).

In conditioned inhibition, a cue comes to signal that an expected outcome will not occur. SOP explains this through the relationship between the A1 state of the CS and the A2 state of the US representation. When the cue is active while the expected outcome is represented in a decayed or absent state, inhibitory learning can develop (Wagner, 1981).

SOP has also influenced simulation-based approaches to learning theory. Its computational structure made it useful for researchers interested in formal modeling, connectionist frameworks, and the temporal dynamics of conditioning (Wagner & Brandon, 2001).

Extensions and Modifications

As with many influential theories, SOP generated later modifications. Researchers recognized that the original model needed greater flexibility to account for more complex learning phenomena, especially those involving absent cues, retrospective revaluation, and causal judgment.

Dickinson and Burke (1996) proposed an important revision of Wagner’s model. Their modified associative theory allowed both present and absent cues to undergo changes in associative strength. In this framework, an absent cue can be affected when it has a within-compound association with a cue that is present. Importantly, the direction of change for the absent cue may differ from that of the present cue.

This modification helped explain forms of retrospective revaluation, where learning about one cue changes the perceived significance of another cue after the original learning episode has already occurred. Such phenomena are difficult to explain using only direct cue-outcome pairings.

Other related work, including Holland’s review of occasion setting, extended associative-learning discussions into more complex cue-control phenomena (Holland, 1992). These developments show both the strength and the challenge of SOP. Its core mechanisms are powerful, but complex learning often requires additional assumptions.

Critiques and Limitations

SOP’s strength lies in its precision, but that precision also creates challenges. As models become more detailed, they may require more parameters. This can make predictions more flexible but sometimes less decisive.

One critique of extended SOP models is that their flexibility may make them difficult to test conclusively. If several parameter adjustments can account for different outcomes, it becomes harder to determine whether the model is truly explaining the phenomenon or merely accommodating it after the fact.

Another limitation concerns complex cue interactions. Some findings involving conditioned stimulus preexposure, overshadowing, extinction, and retrospective revaluation have required further theoretical refinement. The extended comparator hypothesis, for example, has been proposed as an alternative framework for explaining some of these complex effects (Denniston et al., 2001).

These critiques do not erase SOP’s contribution. Rather, they place it within the normal evolution of psychological theory. A strong model opens new questions. It clarifies many phenomena while exposing areas where the mechanisms need additional development.

Implications for Understanding Behavior

SOP is a technical model, but its implications reach beyond laboratory conditioning.

Human beings constantly respond to cues, contexts, and expectations. We habituate to background noise. We become sensitized to signals of threat. We learn that some environments are safe and others demand vigilance. We respond differently to the same stimulus depending on whether it is new, expected, recently encountered, or emotionally charged.

SOP helps explain why experience changes perception. The world does not strike the nervous system with equal force every time. A cue is filtered through memory, expectation, and activation state. What we notice, ignore, fear, or learn depends partly on what is already active within us (Schneider, 2012; LeDoux, 2015).

This has implications for understanding anxiety, tolerance, emotional adaptation, attention, and behavioral conditioning. While SOP is not a clinical theory in itself, it provides a foundation for thinking about how repeated experiences shape emotional and behavioral responses over time.

A trauma cue, for instance, may not function merely as an external stimulus. It may reactivate a network of associations, bodily responses, and anticipatory states (van der Kolk, 2015). A comforting routine may similarly prime safety, reducing the need for defensive response. In both cases, the organism is not simply reacting to the present. It is reacting through the memory states that the present evokes.

Associated Concepts

• Automatization Theory: This theory explains how tasks become automatic through practice and repetition, impacting cognitive, motor, and social skills. The theory involves three stages: cognitive, associative, and autonomous.
• Associative Learning: This is a type of learning where an individual or animal learns to associate two or more stimuli or events. This can involve learning that certain environmental cues predict specific outcomes or that certain actions lead to particular consequences.
• Tolman’s Rat Experiments: These experiments conducted by psychologist Edward C. Tolman revealed the rats’ latent learning and formation of cognitive maps, challenging behaviorism and expanding cognitive psychology’s understanding of internal mental processes and spatial navigation.
• Applied Behavior Analysis (ABA): This therapy style is a scientific method focused on understanding and improving human behavior using evidence-based strategies.
• Law of Contiguity: This refers to the concept that the mind associates two events or stimuli experienced close together in time and/or space.
• Behavior Modification: This concept rooted in behaviorism aims to shape behavior through reinforcement and punishment. Techniques like positive reinforcement, negative reinforcement, and punishment are key.

A Few Words by Psychology Fanatic

The Sometimes Opponent Processes Model reminds us that behavior is rarely a simple response to the world as it appears in a single moment. We meet each stimulus through the living history of prior encounters. Some experiences arrive with force because they are new, intense, or unexpected. Others fade into the background because the nervous system has already processed them enough to conserve attention.

Wagner’s SOP model gives this familiar reality a formal structure. By distinguishing between A1, A2, and inactive memory states, it explains how learning depends on timing, context, repetition, and expectation. It also reveals why the same event may produce different responses across time. What once startled us may later pass unnoticed. What once brought pleasure may lose intensity. What once seemed neutral may become a signal of safety, threat, or absence.

The model is not without limitations. Like all strong theories, it continues to invite revision, debate, and empirical testing. Yet SOP remains an important contribution to learning theory because it captures something deeply psychological: we do not simply respond to stimuli. We respond to stimuli as they are represented, remembered, primed, and transformed within us.

Last Updated: May 10, 2026