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Abstract

Select literature regarding cue competition, the contents of learning, and retrieval processes is summarized to demonstrate parallels and differences between human and nonhuman associative learning. Competition phenomena such as blocking, overshadowing, and relative predictive validity are largely analogous in animal and human learning. In general, strong parallels are found in the associative structures established during learning, as well as in the basic phenomena associated with information retrieval. Some differences arise too, such as retrospective evaluation, which seems easier to observe in human than in nonhuman animals. However, the parallels are sufficient to indicate that the study of learning in animals continues to be relevant to human learning and memory.
International Journal of Psychology and Psychological Therapy, 2017, 17, 2, 223-244
Printed in Spain. All rights reserved. Copyright © 2017 AAC
Of Rats and People: A Select Comparative Analysis of Cue
Competition, the Contents of Learning, and Retrieval
Juan M Rosas
Universidad de Jaén, España
A Matías Gámez
Universidad de Cádiz, España
Samuel P León
Universidad Internacional de la Rioja, España
Gabriel González Tirado
Universidad de Jaén, España
J Byron Nelson
Universidad del País Vasco, España
* Correspondence concerning this article: Juan M. Rosas, Departamento de Psicología, Universidad de Jaén, 23071, Jaén,
España. Email: jmrosas@ujaen.es. Acknowledgments: This work was funded by grants PSI2014-52263-C2-1-P and
PSI2014-52263-C2-2-P from the Ministerio de Economía y Competitividad.
AbstrAct
Select literature regarding cue competition, the contents of learning, and retrieval processes is
summarized to demonstrate parallels and differences between human and nonhuman associative
learning. Competition phenomena such as blocking, overshadowing, and relative predictive validity
are largely analogous in animal and human learning. In general, strong parallels are found in the
associative structures established during learning, as well as in the basic phenomena associated with
information retrieval. Some differences arise too, such as retrospective evaluation, which seems easier
to observe in human than in nonhuman animals. However, the parallels are sufcient to indicate that
the study of learning in animals continues to be relevant to human learning and memory.
Key words: associative learning, cue competition, contents of learning, retrieval processes, comparative
psychology, humans, animals.
How to cite this paper: Rosas JM, Gámez AM, León SP, González-Tirado G, & Nelson JB (2017)
Of Rats and People: A Select Comparative Analysis of Cue Competition, the Contents of Learning,
and Retrieval. International Journal of Psychology & Psychological Therapy, 17, 223-244.
The origins of experimental research in associative learning are linked to early
studies with a variety of animal species such as dogs (e.g., Pavlov, 1927), cats (e.g.,
Thorndike, 1898), pigeons (e.g., Skinner, 1938) and rats (e.g., Tolman, 1948). Interest
Novelty and Signicance
What is already known about the topic?
Despite some common roots, human and nonhuman learning and memory research has largely evolved
separately during the last decades.
The separate evolution of animal and human learning and memory research may give the impression that they
are independent, and ndings and ideas from one eld are of little interest to the other.
What this paper adds?
The paper reviews select literature regarding cue competition, the contents of learning, and retrieval processes
in human and nonhuman associative learning.
The paper highlights strong parallels between human and nonhuman animals in cue competition phenomena, in
the associative structures established during learning, and in the basic mechanisms of retrieval.
Although differences arise, such as retrospective evaluation which is easier to nd in human than in nonhuman
animals, parallels show that the study of animal learning continues to be relevant to human learning and
memory.
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in such work with animals itself traces back to Darwin, who brought the idea that
there is continuity among species to the forefront of scientic thought (Boakes, 1984).
The idea, that “…the difference in mind between man and the higher animals, great
as it is, certainly is one of degree and not of kind” (Darwin, 1871, pp 105) led to the
emergence of comparative psychology, concerning itself with the comparison of the
“intellectual” capabilities of various species. Though called “comparative” psychology,
the eld began by seeking to support that there is continuity among species. That is,
the eld was arguably looking for generality, as opposed to differences. That emerging
eld developed the initial methods, logic, and frame of thought needed to investigate
abstract constructs, such as learning and intelligence, in nonverbal organisms. Though
comparative psychology is still alive today, its approach and methods towards understanding
intellectual capability gave birth to the Behaviorist schools of thought and the eld of
Learning Theory. Both are branches from the same tree with comparative psychology
at its base (Boakes, 1984).
During the rst half of the twentieth century much of the general psychological
theory was based on animal research (e.g., Hull, 1943; Skinner, 1938; Tolman, 1967).
With the “cognitive revolution” against the strict tenets of what was becoming “radical”
behaviorism, studies of human learning and memory began to develop more independently
of animal learning during the second half of the century. Animal learning lost most of
its early dominance of psychology in this time. However, parallels between the results
found in animal learning and those found in human instrumental, predictive, and causal
learning during the last quarter of the past century show that animal research is still
relevant. Both animal and human research still contribute to an understanding of general
principles (see for instance, Shanks & Dickinson, 1987). The goal of this review is to
provide a brief overview of some of these more recent parallels, focusing on the cases
of competition between stimuli, the contents of learning, and the conditions affecting
memory retrieval.
competition between stimuli
Blocking (e.g., Kamin, 1969), Overshadowing (e.g., Mackintosh, 1976), and
Relative Validity (e.g., Wagner, Logan, Haberlandt, & Price, 1968) are three hallmark
effects of associative learning. These effects have come to be collectively referred to as
“cue-competition” effects. They are all examples where stimuli appear to compete with
each other to become predictors of upcoming events. These effects were fundamental in
the development of the Rescorla-Wagner (1972) model, which brought them together into
a single theoretical framework, and predicting these phenomena has become a required
basis for any following theory.
The blocking experiment, as reported by Kamin (1969), consisted of two critical
groups of rats that received training in which different conditioned stimuli (CSs) were
paired with a shock unconditioned stimulus (US) while barpressing for food. The result
of that training was that the rats suppressed their barpressing in the presence of the
CSs that predicted the shock. One group received LN+ trials, where a light (L) was
compounded with a Noise (N) and paired with the US (+). These rats showed a very
strong suppression response when tested with just L during the test. Though there
was likely some effect of conditioning L in compound with N, simply conditioning L
in compound with another stimulus did not prevent the animals learning about L and
the shock. The data of most interest are from the other group. There, the animals rst
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received parings of N with the shock, and then parings of L and N with the shock in
the same manner as the previous group. Even though they had more experience with
shock, very little conditioned response to L was observed. At the time LN was paired
with shock, N was already a good predictor of shock, and it is said to have “blocked”
learning about L.
In Overshadowing, two stimuli, often differing in salience, are combined and
paired with a US (as in the groups above). The result is that stimuli tend to show less
conditioning when tested individually than if they had been conditioned alone. Moreover,
when they differ in salience, the less salient stimulus shows weaker conditioning than
the more salient stimulus. In theory, the more salient stimulus conditions faster (e.g.,
Kamin & Schaub, 1963) and becomes a good predictor of the upcoming US. Thus, it
also blocks further learning about the less salient stimulus. For example, Mackintosh
(1976) combined a salient 85db noise and a light and paired that compound with shock.
The data were converted to standard “suppression ratios” where responding in the CS
is expressed as a percentage of overall responding in the trial. Small numbers indicate
strong suppression, and numbers near .5 indicate no suppression whatsoever. When
tested with those stimuli, the resulting suppression ratios for the noise and light were
.18 and .39, respectively. Clearly, the intense noise elicited much greater suppression
than the light. The rats also showed less conditioning to the light than a group that was
conditioned to the light alone (suppression ratio= .14).
Relative validity is a similar phenomenon coming from a more complicated
design. Here, animals receive multiple trials with a cue (X) embedded in compounds
with different cues (AX, BX). The trials are arranged so that the correlation of cues A
and B with the outcome is either perfect (e.g., AX+/BX-) or imperfect (AX+/AX-/BX+/
BX-), while the relationship of X with the outcome is the same in each condition. The
animals are subsequently tested with X. Cue X elicits greater conditioned responding in
the imperfect condition (e.g., Wagner et alii, 1968). The idea here (as embodied in the
Rescorla-Wagner [1972] model) is that in the perfect condition, A and B are strongly
associated with the outcome, which can only support a limited amount of learning,
and they thus block learning about X. Such blocking does not occur in the imperfect
condition where A and B are not so strongly associated with the outcome.
Each of these hallmark associative learning effects has been demonstrated in
humans. Blocking can be clearly seen in the work of Arcediano, Miller, and Matute
(1997). Participants played a video game (“Martians”) where a baseline of key pressing
on a keyboard was established by ring lasers at invading Martians. On this baseline,
CSs in the form of colored ickers of the screen or tones played through headphones,
signaled that the Martians were protected by a reective screen and could not be destroyed.
During that time participants had to suppress their rate of ring; otherwise, their ring
would reect back to them and thousands of Martians would invade the planet. Within
the design, two groups received conditioning with a compound AX, and a test with X.
In the Blocking group, A had been established as a predictor that the Martians could
not be destroyed in an earlier phase, while in the Control group A had simply been
pre-exposed. On test, there was greater suppression to X in the Control group (.27) than
in the Blocking group (.39). Though clear in this experiment and several others (e.g.,
Siegel & Allan, 1985; Shanks, 1985), the effects of blocking are not always so clear
in humans. Sometimes the effect has not been obtained when it would ordinarily be
expected based on the design (e.g., Davey & Singh, 1988; Lovibond, Siddel, & Bond,
1988), though it is also true that blocking is not always reliably observed in animals
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(Maes et alii, 2016). Moreover, some results suggest that humans are sensitive to the
phasic nature of experiments. That is, they sometimes may treat the separate phases as
if they were unrelated, preventing the conditioning in the prior phase from blocking
learning in the later phase (see Hinchy, Lovibond, & Ter Hoost, 1995). It is safe to say,
however, that in the absence of the elicitation of other processes which might prevent
or obscure it, blocking is fundamental in human associative learning.
Overshadowing has likewise been clearly demonstrated with humans (e.g.,
Baetu & Baker, 2010; Le Pelley & McLaren, 2001; Okifuji & Friedman, 1992; Spetch,
1995). For example, Baetu and Baker (2010), trained participants on a computer in a
predictive-learning task where foods were paired with changes in hormone levels in
ctitious people. Later, participants were presented with the food cues and asked to rate
whether hormone levels would increase, decrease, or remain the same. Larger numbers
are associated with a predicted increase in hormone levels. Within the design, two cues,
I and J occurred together and predicted an increase in hormone levels. Another cue, N,
also predicted a hormone increase. When tested with these stimuli, ratings for N (82.64)
were higher than to either I (26.21) or J (30.57). When conditioned in compound, the
stimuli overshadowed each other resulting in less associative strength accruing to the
individual stimuli than to one conditioned alone.
A clear demonstration of the relative validity effect comes from the work of
Baker, Mercier, Vallee-Tourangeau, Frank, and Pan (1993). In that study participants
observed a tank crossing a eld and the tank was either destroyed, or not. There were
two cues that participants could use to try to determine whether the tank would be
destroyed. In two conditions, the tank could be camouaged, and a plane could appear
on the screen. The camouage was not necessarily a good predictor of the outcome;
50% of the time the tank was destroyed when the camouage was present, and the tank
was destroyed 50% of the time when the camouage was not present. In one condition
the plane was a perfect predictor of the outcome. In another condition the plane was
an imperfect predictor. It predicted the outcome no better than the camouage. When
participants were asked to judge the contingency between the camouage and the tank
exploding, participants from the condition where the plane was no better at predicting
the explosion ranked the contingency as higher than in the condition where the plane
was the better predictor (see also Matute, Arcediano, & Miller, 1996).
Blocking and overshadowing have received extensive study in humans, in large
part, due to the ease at which they lend themselves to “retrospective revaluation”
(for a recent review see Miller & Witnauer, 2016). After learning about the stimuli,
further experience with one of the stimuli affects how participants respond to the
other. In general, after conditioning a compound, additional treatment with one of the
stimuli tends to have the opposite effect on the other. To illustrate, consider a study by
Wasserman and Berglan (1998). Here participants were presented with food cues that
were paired with allergic symptoms in ctitious patients. Within-subject, participants
received compound cues AW, CY, and BX. Each was paired separately with an allergic
reaction over trials. Then, they received additional trials where A was presented and
continued to be paired with the allergic reaction, while C was presented alone without
the reaction. Presenting A with the outcome following AW trials is what is referred to
as a “Backward Blocking” design as it is functionally the reverse of the blocking design
presented earlier. When tested with cues W and X participants should rate these cues
as equally predictive of the allergic reaction because they were all trained in the same
way in compound with another cue.
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On test, responding to W was less than responding to X. Presenting A with the
outcome after the AW trials led subjects to retrospectively re-evaluate the association
between W and the outcome. When tested with Y, responding to Y was greater than
responding to X. The presentations of C, previously conditioned in compound with Y,
were without the outcome, and they had the opposite effect on Y. It appeared that as
C underwent extinction, participants re-evaluated the association between Y and the
outcome, treating Y more like the cause than they would have without the additional
C- trials. When the CY compound was conditioned, C and Y should have mutually
overshadowed each other. Additional presentations of C without the outcome increased
responding to Y. That is, Y retrospectively recovered from overshadowing. Further
representative demonstrations of these types of effects can be found in Arcediano,
Escobar, and Matute (2001), Dickinson and Burke (1996), Shanks (1985) and Van
Hamme & Wasserman (1994).
Although backward blocking appears reliably in humans, it either does not occur
in animals (e.g., Miller, Hallam, & Graham, 1990; Schweitzer & Green, 1982) or only in
special circumstances (Denniston, Miller, & Matute, 1996; Miller & Matute, 1996). The
situations where it appears with animals seem to be those where the stimuli involved
are not “biologically signicant” (Denniston, Miller, & Matute, 1996; Miller & Matute,
1996), a term used by Miller and Matute to refer to the ability of a stimulus to elicit
a response. Because the predicted outcomes in a typical animal study are signicant
in some way (e.g., food, electric shock), as opposed to the innocuous stimuli used in
predictive learning tasks, the associations established during compound conditioning
are assumed to be somehow protected from further change as might be induced by
retrospective revaluation techniques. Interestingly, backward blocking has been obtained
in humans using electric shock as an outcome (Mitchell & Lovibond, 2002), which
would contradict the idea presented by Miller and his colleagues. The effect, however,
was dependent on the instructions used.
Unlike backward blocking, recovery from overshadowing-type effects have been
reported more extensively in the animal literature, beginning with Kaufman and Bolles
(1981), and subsequently (e.g., Blaisdell, Gunther, & Miller, 1999; Matzel, Schachtman,
& Miller 1998; Miller, Barnet, & Grahame 1992). However, these types of effects are
not universally found when they are sought (Holland, 1984; 1999; Rahut, McPhee,
DiPietro, & Ayres, 2000).
In summary, basic associative effects involving blocking and overshadowing that
occur in rats also occur in humans, although in the latter case other processes may
be involved that make people more sensitive to manipulations such as retrospective
revaluation. Tasks with humans have been shown to be sensitive to the wording of
instructions and test questions (Matute et alii, 1996; Matute, Vegas, De Marez, 1992;
Mitchell & Lovibond, 2002). Nevertheless, the fundamentals of the phenomena appear
to be largely the same between man and animal.
the contents of leArning
In the previous section we showed that the study of competition between stimuli has
played a core role both in determining the conditions governing associative learning and
in the evaluation of the mechanisms that underlie the formation of associations between
events. Although there are cases where humans exhibit phenomena, such as retrospective
evaluation, where animals do not, the opposite is far less true. Conditions which affect
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associative learning in animals also affect that learning in humans in similar ways. In
this section we will focus on the comparative analysis of the contents of learning during
acquisition and extinction in both classical conditioning and instrumental conditioning.
Contents of acquisition in classical conditioning
When a CS is repeatedly paired with a US the CS comes to elicit a conditioned
response that is used as an indication that an association has been formed. In the
conditioning literature there are two general theories about the type of associations
that are established in classical conditioning. S-R theories consider that an association
is established between a stimulus and response (S-R), so that the CS directly elicits a
version of the unconditioned response (UR) with which it was paired. The US simply
acts as a catalyst for the formation of the S-R association, but is not part of it (e.g.,
Hull, 1943). Alternatively, S-S theories assume that classical conditioning results in an
association between two stimuli, the CS and the US, so that the presentation of the
CS evokes the representation of the US. The conditioned response (CR) appears as an
effect of eliciting the US representation (e.g., Pavlov, 1927; Tolman, 1932; Wagner,
1981; Wagner & Brandon, 1989).
Animal studies have distinguished between these two types of learning by modifying
the value of the outcome after conditioning in “outcome revaluation” procedures. A
manipulation is used to change how the animal would respond to the US itself. A food-
US might be paired with lithium chloride so that an aversion is conditioned to it and
animals subsequently avoid the food. A loud frightening noise US might be presented
over and over so that the animal’s fear of it habituates. Because the US is not involved
in response generation according to S-R learning, the CR should not be affected by
post-conditioning modications of the US. On the other hand, if the CR is a function
of an evoked representation of the US, and that representation has been changed, then
the response evoked by S should also change as it serves to evoke the modied US
representation. In general, the results are consistent with the idea that S-S learning
takes place in classical conditioning. Post-conditioning changes of the outcome produce
changes in the CR (e.g., Rescorla, 1973; Rescorla & Freberg, 1978). Similar results
have been found using the outcome revaluation procedure in human predictive learning
(Gámez, Martos, Abad, & Rosas, 2013). After learning to respond to a cue predicting
attacking vessels (e.g., planes, ships) participants were simply told that the vessel was
now indestructible. Attaching that new information to the predicted outcome led to a
suppression of responding to the cue. Participants had not learned to simply respond
to the cue, rather, they had detailed knowledge as to what event the cue predicted and
the impact of their actions on that event.
Using a different approach, Paredes Olay, Abad, Gámez, and Rosas, (2002) adapted
the Pavlovian-to-Instrumental Transfer (PIT) task to the study of the contents of learning
in humans. The PIT procedure has proved useful for analyzing the contents of learning in
animals (e.g., Colwill, 1993; Delamater, 1996). In this procedure the association between
a stimulus and an outcome is measured through the inuence this association has on an
instrumental response that has been associated with the same outcome. For example,
in rats a CS that predicts a food pellet will energize lever pressing when that pressing
leads to the delivery of food (e.g., Corbit & Balleine, 2011; Overmier & Lawry, 1979;
Trapold & Overmier, 1972). In dogs, a CS that predicts a shock will increase runway
shuttling to avoid that shock (e.g., Rescorla & Solomon, 1967).
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Paredes Olay et alii (2002) rst trained participants in a video game in which
they had to defend Andalusia from attacks by destroying planes and ships (O1 and
O2, counterbalanced) by performing two responses, R1 and R2, on the keyboard of
a computer (e.g., an orange key destroyed the ships and a green key destroyed the
planes). While looking at an image of a city and beach with a sky overhead, a ship or
a plane would appear on the screen and remain until the relevant key had been pressed
enough times on a variable interval 5-s schedule at which time the ship or plane was
shown exploding. In a second phase, a Pavlovian association was established between
two cues, C1 and C2 (colored drawings representing the logos of ctitious Defense
Companies), and each of the outcomes previously associated with R1 and R2. During
this phase, participants were told that they were observing the results from another
participant. Logos (e.g., C1) appeared on the screen along with targets (e.g. O1) and
the participant was told to guess which weapon the hidden participant was using. After
they guessed, and independently of what they guessed, the ship or plane was destroyed.
During the test, participants were given the opportunity to perform R1 and R2 in the
presence and absence of C1 and C2. Participants preferably performed the instrumental
response that matched the outcome signaled by the logo (R1 in the presence of C1 and
R2 in the presence of C2) showing that an S-S association was established during the
Pavlovian conditioning of C1 and C2.
In a task involving food rewards, Lovibond and Colagiuri (2013) instrumentally
trained people to press a button on a variable-ratio 10 schedule for M&M chocolates.
Then, the option to respond was removed and they received Pavlovian conditioning
of a red or blue light, one of which (counterbalanced) was always followed with the
delivery of an M&M (e.g., R+/B-). Following the Pavlovian conditioning of one of the
colors, the participants were allowed to respond on the button again for the chocolate.
Presentations of the colored lights selectively increased responding. That is, if the light
had been paired with chocolate, it increased instrumental responding for chocolate (see
also Colagiuri & Lovibond, 2015; Lovibond, Satkunaraja, & Colagiuri, 2015). Results
of studies that revalue the outcome or assess the impact of a predicted outcome on
instrumental responding in humans both concur with the ndings from animal research.
Classical conditioning results in the formation of strong S-S associations.
Contents of extinction learning in classical conditioning
Extinction consists of repeated presentation of the CS without the US, which
leads to a decrease in the CR (Pavlov, 1927). In the simplest approach, extinction may
eliminate the associations established during the acquisition training (e.g., Rescorla &
Wagner, 1972). However, as we will see in a later section, manipulations such as the
simple passage of time or a change of context after extinction produce a recovery of
the extinguished response. Such a recovery would be impossible if extinction erased the
original learning. Thus, extinction is widely regarded as being a new form of inhibitory
learning that competes with the expression of the original association learned during
acquisition (e.g., Bouton, 1993; Konorski, 1948; Wagner & Brandon, 1989). Animal
research reveals that extinction involves new learning that, minimally, affects how the
CS is represented (Pavlov, 1927; Robbins, 1990), leads to the formation of inhibitory
stimulus-response (S-noCR) associations (e.g., Rescorla, 1993), and recent evidence
indicates that extinction involves inhibition of the US representation as advocated by
the theories cited above (Laurent, Chieng, & Balleine, 2016; see also Schachtman,
Threlkeld, & Meyer, 2000).
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Though evidence for each of these mechanisms exists, less is known about the
exact way these mechanisms operate and interact. For example, using the PIT procedure
with rats, Delamater (1996) found that the PIT transfer effect described earlier remained
unchanged across a variety of different extinction manipulations. That nding is not
wholly compatible with the idea that the US representation is suppressed. Rather, it
suggests that a CR is inhibited leaving the US representation intact and able to affect
other US-related responses. Research with humans has not investigated the mechanisms
of extinction as extensively as they have been investigated in animals. Yet, where those
mechanisms have been investigated, parallel results have been found. Rosas, Paredes
Olay, García Gutiérrez, Espinosa, and Abad (2010) obtained an identical result to that
obtained by Delamater (1996) in humans using the Paredes Olay et alii (2002) procedure
described above. Hogarth et alii (2014) also found that PIT survives simple extinction
treatments.
Contents of learning in instrumental conditioning
In a typical instrumental conditioning situation, a target response (R) is followed
by a rewarding outcome (O) when performed in the presence of a discriminative stimulus
(SD). Studies regarding the contents of instrumental conditioning have found evidence of
the formation of R-O, SD-O, SD-R, and SD-(R-O) associations in both animals and humans.
R-O. A procedure often used to demonstrate the R-O association is the outcome
revaluation procedure described above. After training a response using a food reward,
the food is made unappealing by paring it with lithium chloride. Using this procedure,
Colwill and Rescorla (1985) found that rats showed a clear preference for a response
whose reinforcer had not been devalued after conditioning. This selective decrease in a
response whose reinforcer has been devalued, compared to one that has not, has been
also reported in human instrumental conditioning (e.g., Gámez & Rosas, 2007; Vega,
Vila, & Rosas, 2004). A recent report of this effect in humans also comes from Morris,
Quail, Grifths, Green, and Balleine (2015). In their task, participants shook a virtual
vending machine to obtain a preferred snack. Then, participants viewed a video showing
their favorite snack infested with cockroaches. Viewing the video decreased their rate of
subsequent machine tilting, clearly showing that their behavior was not simply elicited
by the stimulus, but was “goal directed” and controlled by knowledge of the outcome
produced by the response.
SD-R. Showing that R-O associations are established in instrumental conditioning
does not imply that no other associations are involved in this type of learning. Colwill
(1994) presents evidence she interprets as SD-R associations in rats. She used a complex
transfer procedure in which a group of rats was rewarded with food (O1) in the presence
of two discriminative stimuli (A and B) if they performed two instrumental responses
(i.e., A:R1-O1 and B:R2-O1). Next, two new responses were trained with two new
reinforcers in the absence of the SD’s (R3-O2 and R4-O3). In a third phase, the original
responses R1 and R2 were followed by outcomes O2 and O3, also in the absence of
the SD (R1-O2 and R2-O3). Finally, during the extinction test, responding to R3 and
R4 was recorded in the presence of discriminative stimuli A and B. The idea behind
the experiment is that the SD’s would selectively affect other responses trained with
the same outcome by way of the expression of an associative chain that begins with
an S-R association (e.g., A-R1-O1). Colwill found that the SDs selectively affected
performance to R3 and R4. When the SD had been paired with the response that shared
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an outcome, it depressed responding. The SD produced transfer (in this case a negative
transfer) through an S-R-O chain, which depends upon establishing an S-R association.
The A-R1 association evoked representations of both O1 and O2, creating interference
with other responses that shared one of those outcomes. SD A, however, had no effect
on R4, for which the response associated with the SD did not share an outcome.
Gámez and Rosas (2007) have reported results in human instrumental conditioning
that reach the same conclusions as Colwill (1994), but with a more direct evaluation that
would be difcult to implement in animals. Using the Andalusia-defense video game
described earlier participants learned to destroy an enemy (e.g., a ship) in the presence
of particular SDs (a red or blue oval near the top of screen) by pressing keys. The
relevant response key depended on the SD. Then, on test, participants viewed the beach
scene, but a new outcome (e.g., a plane) was present. Despite having no knowledge of
the correct response for that stimulus, the chosen response was determined by the SD
with which the response had been previously associated. This result is evidence of the
direct involvement of the SD-R association in human instrumental conditioning (see also
Gámez, León, & Rosas, 2016).
SD-O. Instrumental conditioning also produces associations between the discriminative
stimulus and the outcome (SD-O association) comparable to that established between the
CS and the US in classical conditioning in both human (Gámez & Rosas, 2005, 2007)
and non-human animals (Colwill & Rescorla, 1986, 1988). Using a transfer procedure
analogous to that used by Colwill and Rescorla (1988), Gámez and Rosas (2007)
trained participants to perform a response that was followed by a specic outcome
in the presence of a given SD [i.e., SD-(R1-O1)]. Then, participants learned two new
responses that were trained in the absence of any SD, one of which produced the outcome
from the earlier phase (i.e., R3-O1 and R4-O2). When presented with the phase-1 SD,
participants preferentially chose to respond on the alternative that had been reinforced
with the outcome that was paired with SD in the earlier phase (R3 in the example).
SD-(R-O). In addition to the R-O, SD-R and SD-O binary associations, hierarchical
[SD -(R-O)] associations have been found where the SD signals an entire response-outcome
unit (Colwill & Rescorla, 1990; Gámez & Rosas, 2007; Skinner, 1938). Colwill and
Rescorla (1990) trained rats in a discrimination in which the outcomes of two responses,
R1 and R2, were reversed depending on the SD present [e.g., A-R1-O1), A-(R2-O2),
B-(R1-O2), B-(R2-O1)]. After devaluating one of the outcomes, they tested the rats’
performance in the two response alternatives in the presence of each discriminative
stimulus. Rats preferentially chose the response alternative that was followed by the
non-devalued outcome, so that the specic response chosen changed depending on the
SD presented. In this design, the binary associations discussed earlier would lead to an
indistinct choice between the two response alternatives. Thus, the result demonstrates
that they had formed hierarchical SD-(R-O) associations. Using an analogous design,
Gámez and Rosas (2007) found similar results in human instrumental conditioning. Using
the Andalusia-defense task participants were trained in a task where A signaled that R1
led to O1 and R2 led to O2. The assignment of outcomes to responses was reversed
in the presence of B. Then, O1 was devalued by instructing the participants that the
enemy was now indestructible. In the presence of A, participants performed R2 more
than R1, in the presence of B that pattern was reversed (the opposite occurred when
O2 was devalued). Like the results of Colwill and Rescorla (1990), these ndings show
that the SD’s A and B were associated with entire R-O units.
Recent reports by Gámez et alii (2016) and Thrailkill and Bouton (2015) invited
further comparisons that have not yet been made. Gámez et alii (2016) showed that
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instrumental learning also involves associations between the context where training
takes place and each of the aforementioned elements. These authors used the Andalusia-
defense game and found that context-O, context-SD, and context-R associations were
established after just three conditioning trials within the same training paradigm. In
animals, evidence for these types of associations with context in instrumental learning
has not yet been sought. In rats, a context switch tends to cause a loss of the portion
of responding maintained by habit (Thrailkill & Bouton, 2015). The role of habit in
responding in instrumental learning tasks has yet to be investigated.
Contents of extinction learning in instrumental conditioning
Extinction of instrumental responding occurs when a response is no longer followed
by its outcome leading to a decrease in response strength. To determine the fate of the R-O
association during extinction, Rescorla (1993) devaluated the reinforcer after extinction.
He found that responses that had been associated with that outcome were depressed,
even when that response-outcome association had undergone extinction. Such a nding
suggests that the association between the response and the outcome survives extinction.
The mechanism responsible for the response decrease during extinction seems to be
relatively independent of the state of the R-O association. Something similar happens
with the SD-O association. Using a transfer technique where SD‘s selectively increase
responding on a response alternative with which they had shared outcomes, Rescorla
(1992) observed transfer regardless of whether the response had been extinguished or
not. The SD-O association appeared to also survive instrumental extinction. The results
of those, and related, experiments further ruled out the possibility that SD-noO or R-noO
inhibitory associations are established during extinction. Those ndings are similar to
what had been found during classical conditioning and suggest an inhibitory association
between the SD and the response (SD-noR) as the most likely candidate to explain the
learning during the instrumental extinction (e.g., Rescorla, 1991).
Results in humans are not so clear. The only study analyzing the contents of
instrumental extinction in humans, as far as we know, reports results that differ from
those found in animals (Gámez & Rosas, 2005). These authors designed an experiment
based on a transfer procedure similar to that used by Rescorla (1992) in order to test
whether the SD-O association was affected by extinction. After an acquisition phase in
which participants were trained to perform two instrumental responses for two different
outcomes (R1-O1 and R2-O2), new training was conducted in which two new responses
were followed by the same outcomes in the presence of two discriminative stimuli (SD1-
(R3-O1) and SD2–(R4-O2) ). Finally, after one of those responses was extinguished, a
test was performed in which the SD’s that had been previously associated with R3 and
R4 were presented, but only R1 and R2 were available. Extinction abolished the normal
transfer effect. That is, if R3 had been extinguished, SD1 would no longer affect R1.
That result suggests that, unlike in rats, extinction of instrumental responses led to the
formation of SD-noO associations in the human task. The generality of this divergence
is still to be determined as it is the result of a single experiment and it questions
the uniformity of what has been otherwise parallel conclusions between human and
nonhuman animals in terms of the contents of associative learning (see also Hogarth
et alii, 2014). As with the cue-competition phenomena discussed earlier, knowledge
gained from animal research as to the mechanisms involved in learning continues to
be conrmed in humans.
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bAsic conditions of retrievAl
As with studies of cue competition and the contents of learning, studies examining
basic conditions of memory retrieval have also revealed striking similarities in how it
is accomplished in human and nonhuman animals. In the following paragraphs, we will
focus on a brief analysis of spontaneous forgetting and retrieval failures that occur with
manipulations of the contexts in which learning and testing takes place.
Spontaneous forgetting
One important issue within the experimental studies of memory has been to
establish the conditions in which forgetting occurs. From a layperson point of view,
forgetting of information is understood as an erasure of the learned information and
seems unavoidable. Much of what is learned seems to be condemned to be forgotten and
the only issue is how long it will take. However, the literature in this eld suggests that
while some information seems to be easily forgotten, other information is very resilient
and difcult to forget. Rosas and Bouton (1996) found that, in rats, a single experience
with a taste paired with gastric distress is similarly remembered 5 or 21 days after the
experience took place. Hoffman, Selekman, and Jensen (1966) found that pigeons were
able to retain information acquired in a fear-conditioning situation for over 30 months.
Gleitman and Holmes (1967), using a conditioned suppression procedure in rats, found
that rats showed the same level of fear either one day or three months after training (see
also Hendersen, 1978, 1985; Thomas, 1979), even if that training was pre-asymptotic.
In another line of work, Revusky (1968) found that when one-month old rats consumed
two solutions (coffee and vinegar), one when they were thirsty and the other when
they were sated, they developed a preference for the solution ingested while they were
thirsty. This preference remained even when they were tested 60 days after the original
experience. Similar results were found in appetitive conditioning in crickets (Gryllus
bimaculatus) in which a peppermint odor was paired with access to water. The crickets
retained appetitive and differential conditioning for up to 4 days, although aversive
conditioning seemed to disappear after 24 hours (Matsumoto & Mizunami, 2002).
Our own anecdotal experience suggests that humans are no exception, and
that is conrmed in the laboratory. Enright, Rovee-Collier, Fagen, and Caniglia (1983)
instrumentally trained three-month old infants to kick in order to activate a mobile in a
single session, and that learning was retained for up to two weeks. Conditioned eye-blink
response in 20- and 30-day old infants has been also shown to be retained when tested
10 days after conditioning (Little, Lipsitt, & Rovee-Collier, 1984; see also Sullivan,
Rovee-Collier, & Tynes, 1979). In similar lines, Schugens and Daum (1999) found that
eyelid conditioning remains practically intact two months after training in patients with
amnesia produced by different factors (brain injury, alcohol abuse or early Alzheimer’s
disease), and in their respective controls. Analogous results have been found within
human causal and predictive learning studies. Vila and Rosas (2001) found that the
relationship between a ctitious drug and an imaginary disease remained intact 48 hours
after the end of training (see also Romero, Vila, & Rosas, 2003). Schiller et alii (2010)
have produced evidence of the persistence of memory that a colored square predicts a
shock after one year in college-aged participants. Taken together, these results suggest
that in species ranging from insects to humans, information about simple relationships
between two events can be retained for long periods of time, showing little evidence
of forgetting by the simple passage of time.
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Other instances of learning are clearly more affected by the simple passage of
time. For example, Sahley, Martin, and Gelperin (1990) trained slugs (Limax maximus)
in a differential conditioning task in which an aversive odor was paired with an attractive
taste (CS1+), while another odor was presented alone, without the taste (CS2-). The
preference for CS1 developed rapidly. However, this preference was attenuated when
slugs received the test 48 hours after conditioning. These results are consistent with
the idea that forgetting of specic details may occur with the passage of time, and that
the organisms subsequently confuse CS+ and CS-. In a classic experiment, Thomas
and Riccio (1979) trained rats in a conditioned suppression task using a blocking
design. A noise was rst paired with an electric shock, and then a compound formed
by a different noise and a light was paired with the same shock either 1 or 21 days
after the initial training with the noise. These authors found that blocking of the light
was greater after the 21-day interval than after the 1-day retention interval, suggesting
that rats had increasing difculty discriminating between the original sound and the
new sound as time passed (see Riccio, Richardson, & Ebner, 1984). This forgetting of
the precise attributes of the stimulus and situation has also been observed in humans
(Bahrick, Clarck, & Bahrick, 1967; for a review see Bouton, Nelson, & Rosas, 1999).
The combination of the results reported in the two previous paragraphs suggests
that not all information is equally likely to be affected by the retention interval. For
example, Thomas (1979) found, in pigeons, that conditioned inhibition, in which one
learns that a stimulus signals the absence of an outcome, can be forgotten after a 21-day
retention interval. Such forgetting did not occur with excitatory conditioning (Gleitman,
1967; but see Sissons & Miller, 2009).
Perhaps the most obvious cases of differential retrieval of different types of
information are the multiple examples of extinction and interference that appear in the
literature. When an animal, whether human or not, learns a relationship between two
stimuli or between a response and an outcome, and this relationship is later changed,
the initially acquired information is very resistant to the effects of a retention interval.
However, information about the change is clearly deteriorated by different manipulations
which we will briey describe below, including the passage of time (for a review see
Bouton, 1993).
Spontaneous recovery from extinction
Spontaneous recovery is dened as the recovery of an extinguished response that
is observed with the passage of time between the end of the extinction and the test. This
phenomenon, initially described by Pavlov (1927), is found in many different animal
species and with a variety of different procedures, showing that recovery of information
learned in extinction is more affected by the passage of time than information about
acquisition. For example, Rosas and Bouton (1996) found that when a sweet taste was
paired with gastrointestinal discomfort in rats, rats avoid subsequent consumption of the
avored solution. However, if the rat is forced to drink the sweet taste again (because
it has no other liquid alternatives) and the taste is not followed by the discomfort,
the aversion eventually extinguishes and the rat no longer rejects the sweet taste. In a
well-controlled situation, these authors found that when rats were tested 18 days after
extinction ended, they showed spontaneous recovery of the original aversion to the sweet
taste. Analogous results have been found among a diverse set of species and tasks, such
as autoshaping in pigeons (e.g., Robbins, 1990), instrumental conditioning in rats (e.g.,
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Rescorla, 1997), salivary conditioning in dogs (e.g., Pavlov, 1927), gustatory aversive
conditioning in goats (Kimball & Billings, 2007) and in the conditioning of the proboscis
extension response after odor-sugar access pairings in bees (Sandoz & Pham-Delègue,
2004). Spontaneous recovery is not limited to simple extinction, but also occurs after
counterconditioning. When a CS is rst associated with shock or food, and then later
associated with the US not used in the rst phase, a retention interval causes a loss of
performance associated with phase 2 and a recovery of that associated with the earlier
phase (e.g., Bouton & Peck, 1992).
In humans, this phenomenon is also easily observed. Schiller et alii (2008) used
a fear conditioning paradigm in which a stimulus (a colored image of a snake) was
paired with a moderate shock in the wrist in 33% of the trials (CS1+) while another
stimulus was presented without shock (CS2-); twenty-four hours after extinguishing
CS1, spontaneous recovery was observed measuring the galvanic skin response as a CR.
Likewise, spontaneous recovery from such retroactive inhibition has been found when
participants learn two successive paired associated lists so that the same words were
presented in both lists but paired with different associates in each case (A-B, A-C).
Recall of associates from the rst list increased over time while recall of associates in
the second list decreased over time (between 1 min and 48 hours: Underwood, 1948; for
a review see Brown, 1976). Similar results have been shown in eye blink conditioning
(Franks, 1963; Hartman & Grant, 1962) and verbal expectations (e.g., Humphreys, Miller,
& Ellson, 1940). Spontaneous recovery of both extinction (e.g., Vila and Rosas, 2001)
and other treatments where later learning interferes with initial learning (e.g., Alvarado,
Jara, Vila, & Rosas, 2006; Rosas, Vila, Lugo, & López, 2001) has been found in human
causal and predictive learning, as well as instrumental preparations (e.g., Vila, Romero,
& Rosas, 2002).
Renewal from extinction
Bouton and Bolles (1979) found that when rats received fear conditioning in a
context (i.e., context “A”) and then received extinction in a different context, context
“B”, subsequent testing of the CS in context A produced a renewal of the extinguished
CR, compared to a control group in which acquisition, extinction and testing took
place in the same context. Such an effect has been termed “ABA renewal”, where the
letters indicate the contexts where acquisition, extinction, and testing phases take place.
Renewal is also found when acquisition and extinction take place in one context and
the test takes place in a different context (AAB renewal, e.g., Bouton & Ricker, 1994;
Tamai & Nakajima, 2000; Rosas, García Gutiérrez, & Callejas Aguilera, 2007), as well
as in the ABC case when acquisition, extinction and testing take place in three different
contexts (e.g., Bouton & Swartzentruber, 1986; Thomas, Larsen, & Ayres, 2003). These
latter ndings, AAB and ABC Renewal, suggest that retrieval of information about
extinction depends on the similarity between the context in which extinction takes
place and the context of testing. Testing in the context of acquisition is not necessary
to observe renewal. AAB and ABC renewal experiments clearly show that retrieval of
the learning that occurs during extinction is more likely to be affected by a context
change than learning that occurs during acquisition.
Renewal also occurs after counterconditioning. For example, rather than undergo
extinction, a tone that predicts food might be now paired with shock. However, the
performance elicited by the tone, either food- or fear-related performance, depends on
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the context of testing (e.g., Peck & Bouton, 1990). Renewal might be best viewed as an
example of a more general phenomenon by which new conicting information learned
about a stimulus comes to be controlled by the context in which it occurs (Nelson,
2002; Nelson & Callejas Aguilera, 2007).
Renewal in humans has received considerable attention in the last two decades,
particularly because it is viewed as a factor contributing to relapse after the treatment of
phobias (e.g., Mineka, Mystkowski, Hladek, & Rodríguez, 1999), aversive conditioning
(e.g., Effting & Kindt, 2007, Neumann, Lipp, & Cory, 2007), and addictions such as
alcoholism (e.g., Stasiewicz, Brandom, & Bradizza, 2007), or smoking (e.g., Thewissen,
Snijders, Havermans, Van den Hout, & Jansen, 2006). Renewal is also found after
extinction or interference treatments in predictive learning tasks (e.g., Paredes Olay
& Rosas, 1999; Rosas & Callejas Aguilera, 2006; Rosas, García Gutierrez, & Callejas
Aguilera, 2006), and in conditioning using videogames (e.g., Havermans, Keuker, Lataster,
& Jansen, 2005; Nelson, Sanjuan, Vadillo Ruiz, Pérez, & León, 2011; Neumann, 2006).
Reinstatement
The reinstatement effect is the recovery of an extinguished response that occurs
when the organism is exposed to the outcome after extinction and before the test. The
CS and US do not need to be paired again. The organism simply needs to re-experience
the US in the context where the CS will be tested. This phenomenon has been shown
in aversive (e.g., Rescorla & Heth, 1975) and appetitive conditioning (e.g., Delamater,
1997) with rats. It is also shown in counterconditioning (e.g., Brooks, Hale, Nelson, &
Bouton, 1995). The effect is found in humans both after extinction in causal learning
(Vila & Rosas, 2001) and after interference (counterconditioning) in human predictive
learning (e.g., García Gutiérrez & Rosas, 2003a, 2003b; García Gutiérrez, Rosas, &
Nelson, 2005).
In studies of reinstatement after counterconditioning we nd a potential divergence
between nonhuman and human animal studies. While evaluating explanations for
the reinstatement effect, García Gutiérrez and Rosas (2003a), sequentially paired the
same cue with two different outcomes (A-O1 and then A-O2) and then evaluated the
relationship between the cue and the two outcomes. Before conducting the test, during
the reinstatement phase, either the original outcome (O1), the phase 2 outcome (O2),
or a third outcome that had not appeared before was presented. Reinstatement occurred
regardless of which outcome was presented during the reinstatement phase. That result
is consistent with an explanation offered by Bouton (1993) suggesting that reinstatement
occurs because of what could be characterized as a change in the subjective perception
of the context by the participant as a consequence of the context-outcome pairings.
Unlike in humans, Delamater (1997) reports outcome-specic reinstatement both in
classical and instrumental conditioning in rats. These divergent results in animals and
humans should make us cautious when considering that the effect of reinstatement,
behaviorally identical in the rat and the human being, is due to the same mechanism
in both species. Nevertheless, the divergence must also be accepted with equal caution
because while García Gutiérrez and Rosas (2003a) used a counter-conditioning procedure
to reduce the initial response, Delamater (1997) used simple extinction. The use of
multiple different outcomes, as opposed to the outcomes presence vs. absence, could
have served to promote generalization between them, rendering them both effective in
producing reinstatement.
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Effects of context change on simple acquisition
Earlier we pointed out that simple acquisition seemed to be a phenomenon resistant
to forgetting with the simple passage of time. The same appears to be the case with
context change. Generally speaking, information about a consistent relationship between
a cue and an outcome, a CS and a US, transfers well across different contexts in both
animals and humans. However, this general characteristic also has exceptions (for a
review see Rosas, Todd, & Bouton, 2013). For example, Hall and Honey (1990), using
a single paring of a CS with an intense footshock in rats, found that the conditioned
response did not transfer well between different contexts. However, transfer was basically
perfect after 5 conditioning trials. In contrast, Bonardi, Hall, and Honey (1990) found
good transfer of taste aversion between contexts with a single conditioning trial, and
poor transfer between contexts after 5 conditioning trials. León, Callejas Aguilera, and
Rosas (2012) noted that procedural aspects such as the experience animals have with
the contexts may modulate context-switch effects after acquisition in some situations.
They reported that a taste aversion acquired after a single trial transferred well across
contexts only if the contexts were familiar at the time of conditioning. This aspect
cannot necessarily account for the contradictory results summarized above, as in both
studies animals had experience with the contexts before conditioning started. In humans,
research suggests that context changes deteriorate performance after simple acquisition
in the initial stages of training, but not when training is more extended (León, Abad,
& Rosas, 2010), analogous to what was reported by Hall and Honey (1990). Similar
losses of performance with context-switch effects have been also reported in animal
(e.g., Bouton & Todd, 2014) and human instrumental conditioning (León, Abad, &
Rosas, 2010).
Additionally, some studies show that simple acquisition may be found to be
context dependent, even after training reaches an asymptote (see Rosas et alii, 2013).
For instance, in a predictive learning task Rosas and Callejas Aguilera (2006) found that
retrieval of a consistent relationship between a cue and an outcome was deteriorated by
a change of context when it was learned in a situation in which another cue received
extinction. That effect led the authors to propose that extinction results in attention to the
contexts, and that contextual attention leads to information being learned coming under
the control of that context. Nevertheless, in a behavioral video-game task, Nelson and
Lamoureux (2015) found that extinction of a cue had no effect on contextual control of
simple acquisition, even though attention to contexts was maintained. In animals, similar
contradictory results have been found. Rosas and Callejas Aguilera (2007) showed that a
simple conditioned aversion to one avor is forgotten with a change in context when it
is learned after the extinction of an aversion conditioned to a different avor. However,
Nelson, Lombas, and León (2011), using an appetitive conditioning procedure in rats,
found that extinction of a CS that predicts food, if anything, increased the transfer of
another CS to a different context. The mechanisms that underlie these divergent effects
are presently not fully understood, but the parallel investigations with both animals and
humans will undoubtedly facilitate the understanding of those mechanisms.
conclusions
Though clearly not exhaustive, we have presented a general review of many parallels
and a few divergences between animal and human associative learning with regard to
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cue competition, the contents of learning, and conditions affecting retrieval processes.
Overall, we have shown considerable parallels in the associative learning processes
between animals and man. Competition phenomena such as blocking, overshadowing,
and relative validity are largely analogous. When examining the associative structures
formed in classical and instrumental conditioning, additional parallels are observed.
Finally, forgetting and retrieval seem to be affected by many of the same factors in
human and nonhuman animals. Human and nonhuman animals share a signicant number
of simple predictive and retrieval mechanisms that are essential to their successful
interaction with the world. For guiding their actions, associative processes in humans
could be elaborated by seemingly more complex cognitive processes (e.g., reasoning).
But much can still be learned about human behavior and its mechanisms from the study
of animals where such complexity need not be inferred.
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The role of within-compound associations. Quarterly Journal of Experimental Psychology, 52B, 121-138.
Doi: 10.1080/713932675
Received, January 5, 2017
Final Acceptance, March 15, 2017
... After this manipulation, the second stimulus acquires less associative strength than the first one (i.e., it is ''blocked''; e.g., Kamin, 1969;Westbrook and Brookes, 1988). Both effects are well established in the literature and have been replicated in a variety of species including humans (Vandorpe and De Houwer, 2005;Ellis, 2006;Prados, 2011;Rosas et al., 2017). Both have also been particularly relevant for research in Pavlovian conditioning, and for the development of theoretical explanations and mathematical models of learning (see e.g., Mallea et al., 2019). ...
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