learning; from association to cognition
TRANSCRIPT
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Learning: From Associationto Cognition
David R. Shanks
Division of Psychology and Language Sciences, University College London,London WC1H 0AP United Kingdom; email: [email protected]
Annu. Rev. Psychol. 2010. 61:273–301
First published online as a Review in Advance onSeptember 15, 2009
The Annual Review of Psychology is online at
psych.annualreviews.org
This article’s doi:10.1146/annurev.psych.093008.100519
Copyright c 2010 by Annual Reviews. All rights reserved
0066-4308/10/0110-0273$20.00
Key Words
association, awareness, blocking, cognition, conditioning, inference,
reasoning
Abstract Since the very earliest experimental investigations of learning, tension
has existed between association-based and cognitive theories. Associationism accounts for the phenomena of both conditioning and “higher
forms of learning via concepts such as excitation, inhibition, and reinforcement, whereas cognitive theories assume that learning depend
on hypothesis testing, cognitive models, and propositional reasoning
Cognitive theories have received considerable impetus in regard to bothuman andanimal learning from recent research suggesting that the ke
illustration of cue selection in learning, blocking, often arises from inferential reasoning. At the same time, a dichotomous view that separate
noncognitive, unconscious(implicit) learning from cognitive, consciou(explicit) learning has gained favor. This review selectively describes ke
findings from this research, evaluates evidence for and against associative and cognitive explanatory constructs, and critically examines both
the dichotomous view of learning as well as the claim that learning canoccur unconsciously.
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S-R: stimulus-response
Associationism: theassumption that learning can beunderstood in terms of the formation andexpression of excitatory or inhibitory associations, formed via reinforcement
Implicit learning:synonymous withunconscious learning. Also termed“procedural” incontrast to“declarative”(conscious) learning
Contents
INTRODUCTION .. . . . . . . . . . . . . . . . . 274
ROLE OF COGNITIONIN LEARNING . . . . . . . . . . . . . . . . . . . 275
Blocking: Associative Accounts . . . . . 276Blocking: Cognitive Accounts . . . . . . 277
Retrospective Revaluation . . . . . . . . . . 281Blocking: Memory for the
Blocked Cue . . . . . . . . . . . . . . . . . . . . 283
AWARENESS AND LEARNING . . . . 285Eyeblink Conditioning............. 285
Fear Conditioning . . . . . . . . . . . . . . . . . 286Evaluative Conditioning. . . . . . . . . . . . 287
The Perruchet Effect . . . . . . . . . . . . . . 289Sequence Learning. . . . . . . . . . . . . . . . . 290
Visual Search and ContextualCuing . . . . . . . . . . . . . . . . . . . . . . . . . . 292
CONCLUSIONS AND FUTUREDIRECTIONS . . . . . . . . . . . . . . . . . . . . 293
INTRODUCTION
It seems unlikely that any investigator would
carry out an Instructed Conditioning study
with a motor response since, in plain English,
this would consist of telling S to move his fin-
ger. However, common sense is not a good
guide when predicting the behavior of investi-
gators operating in an S-R framework. Exper-
iment 6 in Hunter (1938) consists of produc-
ing finger withdrawal conditioning by saying,
“Lift your finger,” or “Don’t lift your finger.”
If Ss didn’t make a finger withdrawal response
to “Liftyour finger,” theywere shocked. To in-
sure objectivity the commands were presented
by telephone. The Ss conditioned. (Brewer
1974, p. 14)
Brewer’s lampooning of studies conducted within the framework of stimulus-response
(S-R) behaviorism, on the grounds that they ignored the ubiquitous involvement of con-
scious thinking in learning and memory, willdoubtless make many modern researchers
reflect with amusement and relief on how farexperimental psychology has come since those
dark days. The present review takes Breweseminal re-evaluation of the relations
between learning and cognition as its start
point. One conclusion of Brewer’s assault wthe notion that processes of association form
tion and reinforcement are largely irrelevfor the understanding of human learni
Another conclusion was that learning invaably arises from the operation of consci
cognitive processes. This review reassesthese fundamental hypotheses about learn
in the light of contemporary research. Associationism has dominated the hist
of learning theory. This prominence originafrom the work in the early part of the past c
tury by Edward Thorndike, for whom an u
derstandingof the reinforcement processes tcause strengthening of S-R connections (e
the Laws of Effect and Exercise) was a cetral concern. Related to his associationist p
losophy, Thorndike also believed that learncould occur unconsciously or implicitly: he w
the pioneer of what we now know as the fiof implicit learning (Thorndike 1931). Beca
he viewed reinforcing events as being effethat automatically stamped in S-Rbonds, rat
than as providing information, Thorndike weager to show that rewards and punishme
can affect learning even when the individ
is unaware that such learning is taking plaand he conducted numerous studies (review
by Postman 1962) attempting to establish th Thus Thorndike combined two positions,
signing a key role to reinforcement procesin learning together with the claim that th
learning processes can proceed independenof awareness.
A very different view of learning can traced back to the Gestaltists (especially K ¨ oh
and Koffka) and field theorists (particula Tolman) who took an opposing position
the effect versus information issue. For theevents did not provide the opportunity
gradual trial-and-error learning, but rather
the context for the development of insight aproblem solving. Tolman in particular argu
that reinforcement is not a necessary conditfor learning; instead, cognitive relationsh
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(hypotheses or cognitive maps) are formed be-tween stimuli or events as a result of contiguity
and organizational principles (see the review
of learning by Melton 1950, in the very first Annual Review of Psychology). Debate between
S-R and field theories, and the importance of phenomena such as latent learning, dominated
much of experimental psychology up until thecognitive revolution (see Holland 2008).
By the time Brewer (1974) came to review the literature, it was abundantly plain that the
traditional S-R theory of conditioning, includ-ing core notions such as the automatic and
unconscious stamping in (i.e.,reinforcement) of associative links, was not appropriate for either
classical or operant (instrumental) condition-
ing, nor did it provide an adequate framework for such important applied problems as
understanding the development of phobias(Rachman 1977). Evidence that conditioning
of autonomic, motor, as well as more complexresponses only occurs in parallel with expectan-
cies and awareness convinced Brewer that allconditioning is the result of cognitive process-
ing, in particular of the formation and testingof conscious hypotheses. Although tension has
existed between associative and cognitive viewsof learning for a century, the topic has received
renewed attention in the past few years. The
considerable evidence that awareness necessar-ily accompanies learning has been challenged
recently as the study of implicit learning hasgained momentum. The present article reviews
some of the current evidence from this areaand asks whether Brewer’s position remains
the most viable interpretation: Is learningintrinsically a conscious process? On the other
hand, much recent research has retained thestrongly antiassociationist perspective, which
Brewer championed, regarding concepts likereinforcement as superfluous. Recent evidence
bearing on this issue is also reviewed.
In exploring the relationship betweenassociative and cognitive processing, this
article examines a fundamental theme that hasremained unresolved since the early days of
experimental psychology. Recent research is re- viewed, mostly published since 2000, covering
Conditioning: inclassical or Pavlovianconditioning, aconditioned stimulu(CS; e.g., a tone)predicts an
unconditionedstimulus (US; e.g.,food or shock). As aresult of learning, thresponse normally evoked by the US(e.g., salivation orfreezing) or a similarresponse comes to bevoked by the CS
CS: conditionedstimulus
US: unconditionedstimulus
contributions from the areas of associative andcontingency learning, and implicit learning
and memory. A guiding question is whether our
explanatory scope for explaining the richnessof learning would be seriously curtailed if con-
cepts such as excitation and reinforcement wereabandoned. Plainly, it is not sufficient to reject
traditional S-R theory. Instead, cognitive the-ories that dispense with associative constructs
must be contrasted with those modern theoriesthat incorporate cognitive constructs such as
attention and awareness while also assigninga fundamental role to association formation.
Extraordinarily rich explanations of learningphenomena have been achieved by models built
out of automatic link machinery (i.e., connec-
tionist, neural network, or parallel distributedprocessing accounts) in which representations
are coded subsymbolically (McClelland &Rumelhart 1986, Rumelhart & McClelland
1986, Thomas & McClelland 2008). Suchmodels demonstrate massive “emergentism,”
in that processes that seem cognitive and highlevel emerge from the operations and inter-
actions of very elementary processing units. These processes yield knowledge structures
and states of activation which, when sufficiently strong and stable, constitute the contents of
consciousness (see Maia & Cleeremans 2005).
It is against this contemporary associationist framework that the present review compares
the alternative propositional-cognitive theory.
ROLE OF COGNITION IN LEARNING
Should we think of learning as the automatic
formation of a mental link or bond between acue (or CS) and an outcome (or US), or instead
as the acquisition of a propositional belief
representing the relationship between them?One counterintuitive but well-documented
empirical observation forcefully captures theparadox of learning and cognition. This is
the finding that verbal instructions seem tobe largely interchangeable with experienced
events. The mere instruction that a tone willbe followed by shock is sufficient to cause an
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Blocking: thefundamentaldemonstration of cueselection in learning. When a pair of cues A and B predicts an
outcome, the degree of learning about the A-outcomerelationship is reduced(blocked) if B haspreviously on its ownpredicted that outcome
increase in skin conductance that is indistin-guishable from that obtained when the tone
is actually paired with shock (e.g., Cook &
Harris 1937, McNally 1981). In more recent research, Lovibond (2003) has shown that
this interchangeability extends to more subtledesigns including blocking (described below).
The paradox is that if true conditioning, withevents that are actually experienced, engages
(Brewer notwithstanding) an automatic andunconscious learning mechanism, then how
can verbal, cognitive, conscious instructionsmake contact with that mechanism? Contrary
to commonly held belief, we seem to be faced with the conclusion that conditioning in fact
gives rise to conscious, cognitive, propositional
representations rather than to automatic, un-conscious ones. This is precisely the position
adopted by many contemporary researchers(De Houwer 2009, Mitchell et al. 2009), in
which associative processes are jettisoned.In the past few years, the cognitive approach
(now commonly referred to as propositionalor inferential) has kindled renewed attention
and emphasis. To what extent, then, do cogni-tive processes penetrate learning? Should con-
structs such as reinforcement and excitationplay any role in our explanatory frameworks?
Blocking: Associative Accounts
The signature phenomenon of blocking
(Kamin 1969) has played a key role in the
history of learning theory and has been centin the debate between proponents of associat
and cognitive theories. Blocking is the fun
mental demonstration that learning about relationshipbetweentwoeventsdependson
just their frequency of pairing, but also on extent to which one provides information ab
the other. Consider the pairing of a cue andoutcome,orofaconditionedstimulus(CS)w
an unconditioned stimulus (US). When cueand B are paired together and predict an o
come, the extent to which learning accrues A is diminished if B has previously, in the
sence of A, been paired with the outcome ( Table 1). Thus blocking refers to a two-sta
designinwhichBisestablishedasareliablep
dictor of the outcome in stage 1 (denoted B with A and B occurring together and jointly p
dicting the outcome in stage 2 (denoted AB As a concrete example, laboratory studies w
human participants might describe a hypothical individual suffering from allergic reactio
to somefoods but not others. Onday 1 the in vidual eats tomatoes and suffers an allergic
action, and on day 2 she eats tomatoes togeth with pasta and again suffers a reaction. The p
ticipant’s task is to judge the extent to whpasta is associated with the reaction, and blo
ing refers to the fact that the initial tomato
allergy pairing will weaken the perceived pasallergy connection.
Standard associationist accounts of bloing rely on concepts such as excitati
Table 1 Experimental designs relating to blocking
Condition Pretraining Stage 1 Stage 2 Test Comment
Blocking B+ AB+ A B+ trials reduce responding to A at test
Blocking control AB+ A Responding to A at test is strong
Backward blocking AB+ B+ A B+ trials reduce responding to A at test
Subadditivity C+ /D+ /CD+ B+ AB+ A Pretraining reduces blocking (i.e., enhances
responding to A) Additivity C+ /D+ /CD++ B+ AB+ A Pretraining enhances blocking (i.e., reduces
responding to A)
Maximality + B+ AB+ A Pretraining reduces blocking (i.e., enhances
responding to A)
Submaximality ++ B+ AB+ A Pretraining enhances blocking (i.e., reduces
responding to A)
Note: A–D: cues or conditioned stimuli. + indicates occurrence of the outcome or unconditioned stimulus. ++ indicates an outcome of larger magnitu
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reinforcement, associability, and surprise(Dickinson 1980, Mackintosh 1983, Rescorla
& Wagner 1972). In the classic Rescorla-
Wagner theory, for instance, an excitatory association is assumed to form in stage 1
between B and the outcome, with the latterplaying the role of reinforcer. In stage 2,
the reinforcing power of the outcome isdiminished because its occurrence is no longer
surprising—it is predicted by the presence of cue B. Thus the outcome does not serve as a
reinforcer of the A-outcome association, andlittle learning accumulates to A. This theory,
whose history and influence is reviewed by Miller et al. (1995), has played such a central
role in recent learning theory that it has in
effect acted as the departure point for almost all subsequent theories. Its influence arose in
considerable part from its ability to explain theblocking effect Kamin discovered.
Although subject to numerous theoreticalsubtleties (Mackintosh 1975, Pearce & Hall
1980), this explanatory framework is supportedby a wealth of evidence (Mackintosh 1983), in-
cluding such diverse findings as that learning isretarded for a blocked cue that is subsequently
paired with an entirely new outcome (LePelley et al. 2007), that blocking occurs in or-
ganisms not generally assumed to be endowed
with cognitive capacities (including the marinemollusc Hermissenda; Rogers & Matzel 1996),
and that the dopamine system in the brain ap-pears to provide a reinforcing mechanism with
just the required formal properties (Fletcheret al. 2001, Waelti et al. 2001). Although the
modern associationist perspective differs in nu-merous ways from the classic S-R theories of
Tolman, Guthrie, Hull, and others, in its fun-damental form it incorporates many of the con-
cepts Brewer was so determined to reject (for areview of the intellectual transition from early
to contemporary learning theories, see Mowrer
& Klein 2001).It is also important to note that associa-
tive models of learning have often inaccurately been described as assuming automatic trans-
fer of activation from the CS representation tothe US representation. In reality, modern asso-
ciative theories have placed great emphasis onattentional, controlled processing and related
concepts such as limited-capacity workingmemory (Mackintosh 1975, Pearce & Hall
1980,Wagner1981),andtheroleofattentionin
human as well as animal conditioning has beenrecognized for many years (Dawson & Schell
1982). The important question, of course, is whether cognitive concepts such as these, and
the evidence for their role, ultimately requireabandoning the associationist perspective.
Blocking: Cognitive Accounts
Waldmann & Holyoak (1990, 1992) were the
instigators of the cognitive challenge to the as-
sociationist account of blocking. Their key ob-servation was that associations have no seman-
tic properties, whereas human learning seemsto be highly sensitive to such properties. For
instance, on the associationist theory, it shouldnot matter whether cues and outcomes are de-
scribed as causes and effects, respectively, oras effects and causes. Imagine an experimen-
tal task in which the participant is shown in-formation about substances in the blood of a
hypothetical patient together with informationabout whether the patient is suffering from a
target disease. From an associative perspective,
the task involves learning connections betweenthe substance (cue or CS) and the disease (out-
come or US). However, the substance could bedescribed as a cause of or as an effect of the dis-
ease, and Waldmann & Holyoak (1990, 1992)showed that from a rational perspective these
interpretations can have radically different im-plications. Indeed, they argued that blocking
would only be expected in a cause-effect sce-nario and not in an effect-cause scenario, and
they presented experimental evidence consis-tent with this prediction.
Later research has confirmed that the inter-
pretation of events, over and above their simplepairing, can substantially modulate blocking,
but this research has also shown that learningis sometimes quite immune to the way events
are described (e.g., Cobos et al. 2002, L ´ opezet al. 2005, Waldmann 2000). For example,
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L ´ opez et al. (2005) presented participants witha simulated device in which switches and lights
on one side of a box were connected to lights
on the other side of the box. Participants ei-ther saw trials in which the cue played the role
of a cause and the outcome the role of an ef-fect, or vice versa. The main finding was that
this causal interpretation had no effect except in conditions where L ´ opez et al. (2005) went to
extreme lengths to emphasize the causal natureof the task to participants. Thus there do seem
to be conditions in which the associationist the-ory provides an appropriate account of partici-
pants’ behavior, although we aresome wayfroma full understanding of the boundary conditions
for such an account.
In related work, Matute and her colleagues(Matute et al. 2002, Vadillo et al. 2005) have ex-
tensively studiedaspects of theprecise formatof questions probing associative knowledge. Sup-
pose participants observe trials in which vari-ous medicines are related to allergic reactions.
Probe questions might ask to what extent amedicine causes the allergic reaction, the extent
to which it predicts or indicates the reaction,or the extent to which medicine and allergy
co-occur. Contrary to the simple idea that asingle associative connection underlies all such
judgments, these studies reveal qualitative dif-
ferences between different judgment questions.For example, Vadillo et al. (2005) found that
causal and prediction judgments could be dis-sociated. Yet as Vadillo et al. themselvesnoted, a
slightly more subtle associative account wouldhave no difficulty accounting for this finding.
Such an account would assume that causal judg-ments are assessed by simply probing the asso-
ciative strength of the target cue on its own, while prediction judgments are based on the
combined associative strength of the target cueplus the context.
Recall that the essence of associative ap-
proaches is that they assume that presentationof a cue calls to mind (given sufficient atten-
tional resources and so on) the outcome with which it was associated. Now consider a situ-
ation in which a cue competition effect suchas blocking occurs (B+ in stage 1 followed by
AB+ in stage 2). It has been known for ma years (Dickinson et al. 1984) that associative
causal judgments for A will be low in compison to a control condition in which the ini
B+ trials are omitted (see Table 1). But stud
have also shown that judgments of the probility of the outcome given cue A will manif
a blocking-like effect (De Houwer et al. 20Lagnado & Shanks 2002, L ´ opez et al. 19
Price & Yates 1993). This is a striking resbecause the probability of the outcome giv
cue A, P (O/A), is unaffected by whether or nB+ trials are presented in stage 1. Associat
theories explain this effect by proposing t A’s associative weight, which is reduced in
blocking condition, is part of the evidence usto make a probability judgment. Even thou
the probabilities are objectively the same in two conditions, the cue much more stron
makes us think of the outcome in the cont
than in the blocking condition, and this mtal activation unavoidably biases our probabi
judgment. Explaining the bias in terms of infentialprocesses appears difficult. Similar effe
emerge in terms of memory for the relatioship between a blocked cue and its associa
outcome (discussed below).De Houwer et al. (2002) took a differe
approach to explore cognitive influencesblocking. They proposed that blocking ari
from a chain of reasoning from the prem“the outcome is as probable and intense afte
as after AB” to the conclusion “therefore A
not a cause of the outcome.” They also nothowever, that such an inference is valid only
the effect is not occurring at its maximal psible level. The inference only follows if th
is room for the outcome to occur with greaprobability or intensity. To test this analy
they described the outcome in a blockdesign as occurring with an intensity of
on a scale from 0–10 (maximal condition). Houwer et al. (2002) speculated that if block
arises as a result of reasoning, rather than frassociative processes, then their participa
should be unsure about the status of the block
cue A under these conditions. In stage 1 thlearned that cue B predicted the outcome, a
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then in stage 2 they observed A and B occur-ring together with the same outcome. Such
information is insufficient to distinguish
between A having no relationship with theoutcome versus it having a strong relationship
that is masked by a ceiling effect. If B is already causing the outcome with maximal intensity,
then A cannot increase or alter that outcome,evenifitdoeshaveacausalrelationshipwiththe
outcome. De Houwer et al. (2002) contrastedthe maximal condition with a submaximal one
in which the same events were presented, but the outcome was always described as occurring
with intensity 10/20. Hence, in this case thefailure of A to change the magnitude of the
outcome in stage 2 is significant, as it could
have done so: The outcome still has roomto increase in magnitude, but did not do so.
Consistent with this analysis, De Houwer et al.(2002) observed much stronger blocking in
the submaximal condition and argued that this finding is fundamentally inconsistent with
associative theories of blocking.In a related modification to the standard
blocking design (see Table 1), a number of au-thors (Beckers et al. 2005, Lovibond et al. 2003,
Mitchell & Lovibond 2002) have given theirparticipants pre-exposure designed to confirm
or contradict the idea that cues have additive
causal value. If participants believe cues are ad-ditive, then the failure of cue B to cause an
increase in the outcome’s magnitude indicatesthat it is ineffective, andblocking shouldbe sub-
stantial. However, if they believe that cues aresubadditive (i.e., that two cues, each of which
causes an outcome with magnitude M, do not produce an outcome of magnitude 2M when
paired together), then the failure of B to in-crease the outcome’s magnitude is not evidence
that B lacks any causal power. In that event,blocking should be much weaker in the subad-
ditive condition, and this is the pattern com-
monly observed (Beckers et al. 2005, Lovibondet al. 2003, Mitchell & Lovibond 2002).
These maximality and additivity effects havebeen the subject of extensive further research
since their original discovery. For instance,Beckers et al. (2006) have reported additivity
Maximality:information (e.g.,20/20) implying thatan outcome isoccurring at its ceilinlevel. Contrast with
submaximality (e.g.,10/20)
Additivity: trials (eC+, D+, CD++, where ++ denotes ahigh-magnitudeoutcome) that implythat the predictive value of cues adds when they arecombined. Contrast with subadditivity (e.g., C+, D+, CD+
Inferential theory:assumes that cueselection effects arethe result of inferencfrom beliefs. Inblocking, for exampllittle weight is assignto the blocked cuebecause participantsassume cue additivitand reason that the cdoes not increase thmagnitude of the
outcome
effects in conventionalconditioning procedures with rats and concluded that similar inferential
reasoning processes and “remarkable cognitive
abilities” (p. 100) are employed. In their stud-ies, both subadditivity (C+, D+, CD+)andad-
ditivity (C+, D+, CD++, where ++ denotesa US with higher magnitude) pretraining in-
fluenced blocking, the former reducing it andthe latter enhancing it. Moreover, maximality
pretraining also had an influence: specifically,a pretreatment in which the animals received
unsignaled large magnitude (++) as well assmaller (+) shocks led to an enhancement of
blocking, consistent with the inference that theblocked cue could have, but did not, increase
the magnitude of the US and therefore must
have been an ineffective cue. Are these findings inconsistent with associ-
ationist accounts, as has often been claimed?Perhaps thepresence of the effects in laboratory
rats should lead us to look particularly carefully for simpler explanations. And indeed there is a
strong counterargument that additivity effectsmight have a rather different basis, at least in
some circumstances. Wheeler et al. (2008) re-ported an additivity pretraining effect, namely
that subadditivity pretraining attenuated block-ing. Specifically, they presented rats in a fear-
conditioning preparation with trials in which
C, D, and the compound CD all signaled theUS (C+, D+, CD+), thus providing informa-
tion that the causal consequences of combin-ing cues were not additive. Then in the main
training stage the rats received B+ followed by AB+ trials in a typical blocking arrangement
prior to an assessment of conditioned respond-ing to the target CS A. Wheeler et al. (2008)
found that the subadditivity pretreatment sub-stantially weakened the blocking effect—that
is, enhanced learning about A—consistent withthe inferential theory. The subadditive trials in-
dicate that the outcome of the combination of
two reliable cues is not additive, and hence inthe main stage of the experiment the animals
might have reasoned that A was a perfectly validpredictor of the US, despite not increasing the
US’s magnitude. Yet Wheeler et al. (2008) went on to show that their subadditivity pretreatment
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was sensitive to a number of manipulationstypically found to impair generalization. For
example, a change of context from the pretreat-
ment to the blocking phase reduced the impact ofthesubadditivitytrials.Thissuggeststhepos-
sibility that the effect emerges not because of controlled inference, but rather because the
pretreatment allows the formation of some as-sociative structures that generalize (or fail to
generalize under a context switch) to the block-ing phase.
The nature of this putative generalizationmechanism has been explored by Haselgrove
(2009). One common way of building gen-eralization into associative theories is to as-
sume that stimuli are composed of multiple el-
ements and that some of these elements may be shared between nominally distinct stimuli.
Consider the additivity design employed by Beckers et al. (2006) and Wheeler et al. (2008)
in which blocking of A after B+ and AB+ trialsis attenuated if subadditivity is demonstrated in
a previous learning phase with C+, D+, andCD+ trials. Haselgrove (2009) noted that most
of the stimuli used in these experiments camefrom the same modality (auditory) and sug-
gested that this might enhance generalizationbetween them. To model this, Haselgrove con-
ducted a simple simulation of this experimen-
tal design using the Rescorla-Wagner theory,but assuming that one additional element or
cue was present on every trial. Surprisingly, thissimple model reproduced the key finding that
the pretreatment stage reduced blocking, andthe reason for this was that the common ele-
ment accrued asymptotic associative strength inthe pretreatment stage, such that when A was
presented in the blocking test (with the com-monelementassumedalsotobepresent),ahigh
level of responding was predicted. Haselgrove(2009) also showed that the model predicted
the contrasting effect of an enhancement of
blocking after additivity pretraining (i.e., C+,D+, CD++), as observed by Beckers et al.
(2006), as well as after submaximality pretrain-ing, and concluded that the inferential basis for
the additivity effect, at least in rats, is far fromproven.
Schmajuk & Larrauri (2008) also testeconnectionist model with the events of a typ
additivity design. In their model, associatconnections are updated by a reinforcem
process, and the connections have no sy
bolic reference. Although different frHaselgrove’s (2009) model in some import
respects, it also reproduced the additiveffect. Schmajuk & Larrauri (2008) conclu
that it is not necessary to interpret additiveffects in terms of propositional reasoning.
Another line of research has considered possibility that maximality and additivity effe
have their influence not via changing hypothses and reasoning about cue combinations b
ratherby inducing shifts between elemental aconfigural processing. There is now a consid
able body of evidence suggesting that organis(both human and nonhuman) can repres
stimuli in rather flexible ways (Melchers et
2008). In particular, the same nominal stimucan be coded either as an irreducible config
ration or as the sum of a set of elements. Finstance, in a human Pavlovian conditioni
study by Melchers et al. (2004a), participainitially saw either a feature-neutral discri
ination or a matched control discriminati The control discrimination (A +, AB+, C
CB−) afforded an elemental solution: Corrresponses are made on all trials if theparticip
learns a strong positive association between A and the US, with all other cues having assoc
tive weights of zero, and assuming additivity
cue weights. Despite being almost identical,feature-neutral discrimination (A −, AB+, C
CB−) cannot be solved this way; there is no of weights for the individual elements that yi
correct responses across all trial types. Henthis problem requires a more complex soluti
such as the formation of configural representions in which AB and CD are represented
distinct from the sum of their constituent pa To test the hypothesis that participants
deed solved these discriminations in qualitively different ways, Melchers et al. (200
next gave both groups a new discriminati
(EX+, FX−, followed by test trials withand F) and found very different behavior a
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function of the initial problem. Specifically,greater responding to E than to F was evident
in the group pretrained on the control discrim-
ination but not in the one pretrained on thefeature-neutral one. Such a pattern is consis-
tent with the hypothesis that the group trainedon the control discrimination transferred an el-
emental strategy to the new problem, broke theEX and FX compounds into elements, and as-
signed a positive weight to E and weights of zero to F and X, whereas the group trained on
the feature-neutral discrimination transferreda configural strategy in which compounds and
elements are treated as independent.Building on this idea, Livesey & Boakes
(2004; see also Williams et al. 1994) reported
that a range of manipulations thought to en-hance elemental processing increased blocking
(in much the same way as additivity instruc-tions), whereas manipulations assumed to en-
hanceconfigural processing decreased blocking(as with subadditivity instructions). Strikingly,
by presenting the cues in a configural manner,Livesey & Boakes (2004) were able to elimi-
nate blocking even when an additivity pretreat-mentstagewasprovided.Sucharesultraisesthe
strong possibility that maximality and additiv-ity effects have some of their influence via shift-
ing the balance between elemental and config-
ural processing. However, whether this account can explain all of the relevant results is unclear.
Beckers et al. (2005) found, for example, that additivity information affected blocking even
when it was presented after the target trials, anoutcome difficult to reconcile with the idea that
the locus of additivity effects resides solely intheir influence on the way the blocking stimuli
are coded. Lastly, a subtractivity pretreatment employed by Mitchell et al. (2005b) affected
blocking in the way predicted by a reasoningaccount.
Retrospective Revaluation
Cognitive interpretations have also been of-fered for the phenomenon of backward block-
ing (Dickinson & Burke 1996, Shanks 1985, Van Hamme & Wasserman 1994) and other
Retrospectiverevaluation: indirechange in a cue’sassociative strengthresulting from laterinformation. An
example is backwardblocking (when B+trials follow AB+ onthey cause a reductioin responding to A)
examples of retrospective revaluation. In abackward blocking design ( Table 1), trials in
which A and B are paired with the outcome pre-
cede B-outcome trials. According to traditionaltheories (Rescorla & Wagner 1972), blocking
(reduced judgmentsof therelationship between A and the outcome) should not occur under
such circumstances; yet numerous studies haveconfirmed that it does. The inferential expla-
nation is that individuals reason just as they doin forward blocking. B and AB predict the same
outcome, thus they conclude that A is not anindependent cause.
But once again the main findings are not incompatible with associationism. In an elegant
analysis, for instance, Ghirlanda (2005) showed
that a range of retrospective effects includingbackward blocking are in fact entirely compati-
ble with the Rescorla-Wagner theory, provideda suitable scheme for stimulus representation
is employed. Traditional applications of thetheory simply assume that each stimulus is rep-
resented by a single unit or node in a network.Under such circumstances, it is true that back-
ward blocking cannot be predicted. However,Ghirlanda (2005) showed that this conclusion
does not hold when each cue is instead rep-resented via a pattern of activity distributed
over a large number of units. Ghirlanda
(2005) reported simulations in which arrays of 50 units coded each elemental stimulus, yield-
ing backward blocking (reduction of judgmentsfor A after AB+, B+ training) as well as its con-
verse, unovershadowing (increase in judgmentsfor A after AB+, B− training) and backward
conditioned inhibition (negative judgmentsfor A after AB−, B+ training). A key element
of distributed coding schemes is that they allow distinct cues to activate overlapping sets
of elements, thus capturing the fundamentalprinciple of stimulus generalization. Kruschke
(2008) has reported similar theoretical de-
velopments for dealing with retrospectiverevaluation, but in the context of models
driven by Bayesian considerations. Kruschkeassumes that knowledge is not captured by a
single strength of association, but instead by adistribution of degrees of belief over a range of
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hypotheses, with these beliefs being optimally adjusted in response to learning feedback.
Another prominent development is
Dickinson & Burke’s (1996) proposal that theformation of a within-compound association
between cues A and B in a backward blockingdesign plays a key role in the retrospection
effect. In the first stage, these cues are com-bined and jointly predict the outcome (AB+).
It is assumed that participants not only learnassociations between each of the cues and the
outcome, but also between the cues themselves.In the second stage, B is presented in isolation
and predicts the outcome (B+). Dickinson& Burke’s (1996) revised associative theory
proposes that B activates the representation of
A in the second stage via the within-compoundassociation formed in the first stage. While
the physically presented cue, B, undergoes anormal increment in associative strength when
the outcome is presented, the associatively ac-tivated representation of A undergoes a change
of the opposite polarity. Hence the B+ trialslead to a reduction in A’s associative strength.
Learning is governed by associative processesand by reinforcement as conceptualized in the
traditional theory. Melchers et al. (2004b) proposed an alterna-
tive account based more on memory retrieval
processes than on associative activation. Onthis account, participants access trial types from
memoryandreplaythemmentally[asimilarno-tion is central to McClelland et al.’s (1995) con-
nectionist theory of the relationship betweenthe hippocampal and neocortical memory sys-
tems]. Hence AB+ trials are recalled and re-hearsed during stage two when B+ trials are
observed. If such replayed trials function muchlike experienced trials, then backward block-
ing would emerge as a simple result of the on-going adjustment of associative strengths and
would not be the product of true reasoning.
The concepts of within-compound associations(Dickinson & Burke 1996) and memory-based
rehearsal (Melchers et al. 2004b) are obviously closely related.
These associative accounts are supportedby a range of evidence. Aitken et al. (2001)
reported that retrospective changes are relato the strength of the critical within-compou
association. In another set of tests, Melchet al. (2004b, 2006; see also Vandorpe et
2007) found that the magnitude of the r
rospective change was related to participanmemory for the trial pairings and proposed t
it is only if the AB pairing can be recalled thdownward adjustments in A’s strength can
induced. Importantly, Melchers et al. (2002006) and Vandorpe et al. (2007) also fou
that there was no corresponding correlationtween forward blocking and participants’ me
ory for the compound trials. This is as expecby standard associative theories, because f
ward blocking (B+ followed by AB+) is drivsimply by competition between A and B on t
AB trials. Any association between A and Birrelevant for such competition.
As noted by Mitchell et al. (2005a) a
Vandorpe et al. (2007), however, these retspective revaluation effects are also consist
with cognitive accounts. Having observed Atrials, participants can infer that A has so
predictive value, but when they subsequenobserve B+ trials, they should now alter th
conclusion because they have informatindicating that A adds nothing beyond wha
signals. Such a chain of inference assigns an iportant role to memory in that the adjustm
of belief about A requires recollection of thepairing. On the other hand, forward blocki
is not expected to be similarly dependent
memory. In this case (B+ followed by ABindividuals can infer during the AB trials t
A is nonpredictive so long as they rememthe B+ trials, and there is no necessity
memory of the conjunction of A and B. Henthe asymmetry observed by Melchers et
(2004b, 2006) and Vandorpe et al. (200 where backward but not forward block
correlates with memory for the cue compouis compatible with a cognitive account.
Indeed, Mitchell et al. (2005a) andVandoet al. (2007) have argued that the patterns
behavior in the retrospective case are better
plained by inference than by associative mecanisms. In an ingenious experiment, Mitch
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et al. (2005a) succeeded in reversing thenormal backward blocking effect such that B+trials presented subsequent to AB+ ones actu-
ally caused an increase rather than a decreasein ratings for cue A. They achieved this re-
sult by employing a method akin to the ad-ditivity manipulation described previously, in
which they pretrained participants to believethat compoundspredictive of theoutcome must
be composed of elements with equivalent pre-dictive values. Mitchell et al. (2005a) thus con-
cluded that their participants solved the task viadeliberate inference, akin to that observed in
other rule-learning designs (Shanks & Darby 1998). Associative approaches might seek to ex-
plain this result in terms of a shift between ele-
mental and configural processing. The reversalof blocking observed by Mitchell et al. (2005a)
is consistent with configural-based associativetheory, assuming there was some generalization
between the A and B cues. An even more striking empirical example of
backward blocking is the second-order effect reported by De Houwer & Beckers (2002a,b;
Melchers et al. 2004b). In their three-stage pro-cedure, participants first saw cues AB paired
with the outcome (AB+) and then were showntrials in which cues AC were paired with the
outcome (AC+). Finally, trials were presented
in which B occurred either with or without the outcome (B+ or B−). To give a concrete
illustration, imagine that the foods avocadoand banana cause an allergic reaction and that,
subsequently, avocado and cheese also causethe allergy. Finally, banana in isolation either
causes or does not cause the allergy. Consider aparticipant for whom B was paired with the out-
come in the final stage. On a cognitive reason-ing account, such a participant might be ex-
pected to infer that since B is a good predic-tor, then A must be a poor predictor: This is
a standard backward blocking effect. However,
the participant might go on to infer that if A isa poor predictor, then C is a good one. Thus,
even though B is never paired with C, the finalstage trials (B+ or B−) might alter the attri-
bution of predictive significance to C, and thisis exactly the result observed by De Houwer
& Beckers (2002a,b). The occurrence of theallergy in the presence of banana (B+) led to
a concomitant increase in the judged relation-ship between cheese (C) and the allergy, while
conversely its nonoccurrence led to a decrease.
Although it is true that such a result might sig-nal the importance of reasoning in blocking-
like designs, Melchers et al. (2004b) found that the magnitude of the retrospective change in
second-order blocking was again related to par-ticipants’ memory for the trial pairings and ar-
gued that the data were therefore compatible with an alternative account based on associa-
tive reinforcement combined with rehearsal of previous trial types.
Blocking: Memory for theBlocked Cue
The role of memory in cue learning has been
central to the evaluation of another predictionthat distinguishes associative and cognitive
models. As noted above, the classic associativeanalysis of blocking (B+ trials followed by AB+trials) proposes that the accumulation of asso-ciative strength by B in the first stage endows it
with the capacity to compete more effectively with cue A in the compound stage. This com-
petition can arise because the outcome, being
unsurprising, is not processed (Rescorla & Wagner 1972) or because cue A is only
weakly attended to and hence not processed(Mackintosh 1975, Pearce & Hall 1980). Ei-
ther way, the consequence of these processingfailures is that only a very weak association (if
any) is formed between cue A and the outcome,resulting in low judgments of the A-outcome
association. A clear prediction from such ananalysis is that there should be a further man-
ifestation of blocking, namely poor memory for the outcome paired with A. Thus not only
should participants judge the association to be
weak, but they also should find it hard to recallthat the outcome co-occurred with A because
that cue will fail to activate the outcomerepresentation associatively. The opposite
prediction, however, follows from inferentialaccounts. Indeed, these must assume that the
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A-outcome relationship is strongly recalled.Participants are assumed to reason roughly as
follows: “If A predicts the outcome, then the ef-
fect of AB would have been greater than that of B alone. B and AB predicted the same outcome,
thus A is not predictive.” Intrinsic to this chainof inference is that participants must remember
that AB predicted the outcome, which is to say they must code the fact that A (in conjunction
with B) was paired with the outcome. This hypothesis has been tested in recent
experiments. Mitchell et al. (2006) devised ablocking task with many different foods as the
cues and with allergies as the outcomes, suchthat recall could be tested. In addition to re-
vealing blocking on judgments, the results were
clear in showing that recall of the outcome as-sociated with cue A was poor in comparison
with appropriate control cues. This pattern isexactly as predicted by the associative account.
A further important aspect of Mitchell et al.’s(2006) experiments was that these results were
obtained in a task in which subadditivity pre-training was employed. Recall that such pre-
training ought to eliminate or at least reduceblocking. In providing evidence that the out-
come is no larger following a compound of predictive cues than with the cues in isolation,
subadditivity pretraining leaves the predictive
status of B ambiguous. The fact that forwardblocking (on both predictive judgments and re-
call measures) was observed thus seems to offerstrong support for the associative analysis and is
difficult to reconcile with inferential accounts,although other data involving more complex
designs have favored the latter (Mitchell et al.2005c, 2007).
Scully & Mitchell (2008) conducted a sim-pler test of cue memory in the context of ex-
tinction rather than blocking. After pairing acue with an outcome (A +), the cue was then
extinguished (A −). In a subsequent test, ratings
of the A-outcome relationship were reduced asa result of the extinction phase. More impor-
tantly, cued recall of the outcome paired with A in the first stage was significantly impaired in
comparison to a nonextinguished control cue.Such a result is again problematic for inferential
accounts. The basic extinction result (on cotingency judgments) can be explained very e
ily by assuming that participants compute someasure of the statistical contingency betwe
the cue and the outcome. For example, an
ferential account might incorporate rules baon the metric P [defined as the difference
tween the probability of the outcome given cue, P (O/C), and the probability of the o
come in the absence of the cue, P (O/ ∼C which would yield a lower measure for an
tinguished cue compared to a control cue bcause the extinction (A −) trials reduce P (O/
(For discussion of the possible psychologicalality of these and similar rules, see Cheng 19
Cheng & Holyoak 1995; Perales & Shan2007, 2008). However, such an account p
vides no reason to anticipate poor memory the initial A + pairings. Indeed, to the ext
that the calculation of P (O/C) requires a reco
of the history of trial outcomes, good recolltion of the pairings would seem to be necessa
Of course, inferential accounts could be suppmented with additional processes to accomm
date memory failure, but these processes wouhave to include precisely the sorts of interf
ence mechanisms that associative theory has voted much effort to developing (Bouton 199
Whereas the Mitchell et al. (2006) study scribed above assessed memory for the exten
which a blocked cue can prompt recall of its sociated outcome, other research has asked
related question of whether a weakened me
ory representation is formed for the blockcue itself. It was noted above that some (but n
all) associative analyses assume that blockarises from a failure adequately to process
blocked cue (Mackintosh 1975, Pearce & H1980). Griffiths & Mitchell (2008) devised
ingenious modification of a blocking task agusing foods as the cues and allergies as the o
come, but added the feature that categoriesfoods (e.g., fruits) played the role of cues A a
B in a blocking design. These categories wcomposed of instances (e.g., apples, banan
such that each actual instance only appea
once in the training stage. At test, new aold instances from the critical categories w
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presented, and participants rated the likelihoodof each instance causing the food allergy, as well
as making a conventional old/new recognition
memory judgment. Blocking of predictiveratings was, as usual, observed. Griffiths &
Mitchell’s (2008) most striking finding, how-ever, was that recognition of the instances of the
blocked category was significantly poorer thanthat of appropriate control cues, consistent
with associative theories that attribute blockingto a reduction in attention to and processing
of the blocked cue. In sum, then, these studiesexamining memory in the context of blocking
designs provide quite strong support for the in- volvement of associative processes. As Griffiths
& Mitchell (2008) also note, their procedure
provides a novel bridge between studies of as-sociative learning and research on recognition
and other forms of memory, and hence opensup several promising avenues for further work.
This draws to a close the review of recent studies guided by cognitive or inferential views
of learning. There is no doubt that this researchhas considerably enriched our understanding
of basic learning processes in both humans andanimals. An extensive body of evidence can be
marshaled in support of the radical claim that associative processes play no role in learning.
However, although manipulations designed to
alter individuals’ beliefs have certainly beenshown to influence behavior, it remains possible
that the locus of some or all such manipulationsis in their effects on associative rather than
inferential processes. Associative theory has,over the decades, often succeeded in explaining
phenomena initially thought to be beyondits bounds, and there are solid reasons to
believe that the same may apply to some of thefindings described here (e.g., additivity effects).
Results such as the effects of cue competitionon memory and judgment for a blocked cue
seem, in contrast, to provide positive evidence
for basic associative processes, and it remainsa challenge, therefore, to inferential accounts
to explain such findings. A view of learning in which knowledge is formed out of associative
connections between distributed representa-tions of events remains viable, perhaps offering
a middle way between the extreme cognitivismof inferential accounts and the equally extreme
reductionism of S-R theory.
AWARENESS AND LEARNING
Brewer’s (1974) view of conditioning was that
in humans it is invariably accompanied by con-tingency awareness. There has been a wealth
of research on this topic since the 1970s, so it is natural to ask whether a contemporary per-
spective would lead us to revise this conclusion. The outcome of one recent review (Lovibond
& Shanks 2002) tended to confirm Brewer’sposition. After analyzing experimental results
on Pavlovian autonomic conditioning, condi-
tioning with subliminal stimuli, eyeblink con-ditioning, conditioning in amnesia, evaluative
conditioning, and conditioning under anesthe-sia, Lovibond & Shanks (2002) concluded that
there were no strong grounds for revising the view that awareness is a necessary condition for
learning in these preparations. In the present section, some recent studies of eyeblink, fear,
and evaluative conditioning are described priorto a selective review of implicit learning stud-
ies using other experimental procedures, suchas motor sequence learning.
Eyeblink Conditioning The voluminous literature on human skele-tal conditioning has been supplemented by a
small number of studies published since the re- view period covered by Lovibond & Shanks
(2002). An important distinction in such stud-ies is between trace conditioning procedures,
in which there is a temporal gap between thetermination of the CS and the onset of the
US, and delay conditioning, in which the on-
set of the US occurs before the termination of the CS. It is generally agreed that awareness,
typically measured by a postconditioning as-sessment of contingency knowledge, is neces-
sary for the acquisition of responding in typicallaboratory trace eyeblink conditioning prepa-
rations (Clark & Squire 1998, Lovibond &Shanks 2002). However, the possibility of delay
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CR: conditionedresponse
conditioning in the absence of awareness ismuch more controversial.
Two recent studies (Bellebaum & Daum
2004, Knuttinen et al. 2001) failed to obtain ev-idence of conditioning in the absence of contin-
gency awareness. A study by Smith et al. (2005),however, did obtain such evidence. Specifi-
cally, participants were presented with two au-ditory stimuli (a tone and white noise), one of
which predicted an airpuff to the eye. Smithet al. (2005) observed reliable delay condi-
tioning in participants classified subsequently as being unaware of the correct CS-US rela-
tionship. The status of this work is difficult to gauge, however, because a subsequent at-
tempt to replicate the key findings yielded no
evidence whatsoever of unaware conditioning.Lovibond and colleagues (P.F. Lovibond, J.J.C.
Loo, G. Weidemann, and C.J. Mitchell,manuscript submitted) reported two experi-
ments that used the same methods and pro-cedure and in addition introduced some fur-
ther variables (e.g., contrasting short versuslong awareness questionnaires). Even for par-
ticipants treated identically to those of Smithet al. (2005), awareness was a necessary con-
dition for the observation of differential con-ditioning. Plainly, whatever the basis of these
discrepant findings, it would be premature to
abandon the conclusion from earlier studiesthat awareness and conditioning tend to be as-
sociated rather than dissociated.
Fear Conditioning
In studies of fear conditioning, the US is typ-ically a shock or loud noise, and the CR is
a change in skin conductance. The literatureon awareness and fear conditioning has been
supplemented by a handful of recent studies.
Knight et al. (2003) devised a novel delay con-ditioning procedure for studying unconscious
fear conditioning. One tone CS (CS+) pre-dicted the US (loud noise), whereas another
tone (CS−) did not, but during acquisitionthe intensity of the CSs was varied to render
some of them imperceptible. Participants in-dicated whenever they heard a tone and also
continuously registered their expectancy of US on a rating scale. Knight et al. (2003)
portedthatunperceivedCSs evokeddifferen
CRs but not differential US expectancy ratin That is to say, when the tone CS+ could not
detected, it failed to evoke a conscious repof expectancy of the loud noise but did evok
conditioned change in skin conductance. This impressive demonstration of unaw
learning was subsequently replicated in tfurther studies by Knight et al. (2006, 200
Knight et al. (2006) reported at the same tithat the effect was not observed in trace co
ditioning, where differential conditioned sponding only occurred to perceived CSs.
the delay condition that replicated the earlKnight et al. (2003) study, statistical analy
found that differential CRs to unperceived C
yielded a t value of 1.86, significant at 0.05 (otailed, df = 12). A comparable analysis fou
that differential expectancy ratings yielded value of 1.68 which is nonsignificant at 0.05
a neuroimaging study employing the same pcedure, Knight et al. (2009) obtained similar
sults, with CR differentiation yielding a relia
t value of 2.46 compared to expectancy ratin
reported to be nonsignificant at t = 2.05 (df
14 in both cases, though this latter effect is s
nificant one-tailed). Hence, the conclusionunaware conditioning in these two replicatio
rests on one effect falling on just one side of t
critical t value and the other effect falling just the other side. Firmer replication eviden
is needed to allow the Knight et al. (2003) resto be properly evaluated.
Moreover, in a careful study employing snal detection methods, unperceived CSs in f
conditioning did not elicit differential skin coductance responses (Cornwell et al. 2007), a
other research has found that fear conditionin delay as well as trace procedures is depend
on awareness. For instance, Weike et al. (20used a conventional procedure in which fa
served as CS+ and CS− and shock as the U
in trace and delay conditioning preparatioDifferential skin conductance conditioned
sponses only occurred in participants clasfied by a postconditioning test as contingen
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aware. As Weike et al. (2007, p. 178) noted,“electrodermal conditioning seems to primarily
index cognitive learning of the rules or circum-
stances in which a specific stimulus is signal-ing an aversive event, which is a declarative and
explicit memory.” Weike et al. (2007) did re-port that a differentmeasure of fear, potentiated
startle responses, developed in participants un-aware of the CS-US contingency in delay con-
ditioning, but this result is hard to interpret asit occurred only on trials administered prior to
the awareness questionnaire and not on onespresented after it. Dawson et al. (2007), in con-
trast, found a good association between startlemodulation and awareness.
Evaluative Conditioning
Evaluative conditioning refers to the transfer of
affect or liking from one stimulus to another asa result of the pairing of those stimuli.This may
be an important mechanism involved in the de- velopment of people’s likes and dislikes for such
everyday things as faces, consumer goods, andmusic. In a typical experiment, pictures judged
pre-experimentally as being affectively neutralare paired with ones rated as highly liked or dis-
liked. The neutral pictures therefore serve asCSs and the affectively valenced ones as USs.
The common finding is that affective reactions
to the CS pictures are pulled in the directionof the US pictures with which they are asso-
ciated, such that a neutral picture paired witha highly liked picture itself comes to be liked;
the converse is true for a neutral picture paired with a disliked picture. The important question
is whether participants have to be aware of thenature of the stimulus pairings in order to show
these learning effects. Is it necessary to be awarethat a certain CS picture was paired with a liked
or disliked US picture in order for its valenceto change? Lovibond & Shanks (2002) (see also
Field&Davey1999,Shanks&Dickinson1990)
highlighted a number of methodological con-cerns in some of the studiesincluded in their re-
view but concluded that the more careful onesdemonstrated (with the possible exception of
evaluative conditioning of tastes—see below)that contingency awareness is indeed necessary.
More recent studies serve to confirm thisconclusion. For example, Pleyers et al. (2007)
and Stahl et al. (2009) paired images (e.g., con-sumerproducts;theCSs)withpositivelyorneg-
atively valenced US pictures. Evaluative condi-
tioning only occurred for those CSs for whichparticipants were contingency aware. Dawson
et al. (2007) used faces as their CSs and USsand embedded CS-US pairings in a short-term
visual memory test. Instead of measuring evalu-ative conditioning viaexplicit ratings, they mea-
sured skin conductance. Again, evaluative con-ditioning only occurred when participants were
aware of the CS-US pairings. A study by Walther & Nagengast (2006)
againshowed evaluative conditioning accompa-nied by above-chance awareness—as measured
by a recognition test—at the group level. These
authors claimed, however, that the condition-ing effect they observed was significant only in
participants classified as performing at or below chance in the recognition test and not in those
performing above chance. Apart from the fact that the interaction between awareness group
and conditioning was not in fact statistically significant in their data, the method of exam-
ining learning effects post hoc in a subgroupof participants classified as unaware can lead
to highly questionable conclusions. This widely used technique is almostguaranteedto generate
apparent but potentially misleading evidence of
unaware learning. To illustrate this point, consider the fol-
lowing extremely simple simulation. Supposedata for a number of hypothetical participants
are generated, each producing a conditioningscore. Assume also that this score is based on a
normally distributed variable x with a mean of 30 and standard deviation of 20. Hence x rep-
resents the knowledge underlying the partici-pant’s conditioned responding. The mean con-
ditioning score for the group is of course about 30, but a proportion of participants will score
at or below zero, taken here to reflect chance
performance. Next, assume that the awarenessscore is also based on x, but with added noise.
Specifically, the awareness score is derived foreach value of x by simply adding a uniformly
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distributed random number, for example be-tween −40 and 40. The critical point is that
the conditioning and awareness scores are both
based on the same underlying knowledge, x.
The only difference is that noise is added to
generate the awareness score. If one nowselectsall the participants who score at or below zero
on the awareness measure, what is their aver-age conditioning score? The answer is that it is
about 10 (SD ≈ 15), reliably greater than zero. This in statistical terms is just a regression-to-
the-mean effect (the expected value of a normal variable x conditional upon x + e < 0, where e
is a random variable with mean 0, is not con-strained to be less than or equal to zero), but
it illustrates that the practice of looking at con-
ditioning (or any other measure) in a sampleof participants selected post hoc as scoring at
or below chance on an awareness measure isa very dangerous practice. Above-chance con-
ditioning may be evident in such a subsampleeven though conditioning and awareness derive
solely (except for random noise) from the sameunderlying source.
As mentioned above, there were a smallnumber of studies (e.g., Baeyens et al. 1990)
on evaluative conditioning with tastes that Lovibond & Shanks (2002) highlighted as pro-
viding tantalizing evidence of unaware learn-
ing and thus meriting further research. Twostudies have indeed followed up this earlier
work. Dickinson & Brown (2007) replicated theBaeyens et al. (1990) procedure, which involves
presenting participants with compound drinksthat are both flavored (e.g., vanilla) and col-
ored (e.g., blue) as well as being pleasant or un-pleasant. Pleasant tastes were created by adding
sugar; unpleasant ones had the bitter substancepolysorbate 20 added to them. From a condi-
tioning perspective, pleasantness can be consid-ered the US and the flavors and colors as CSs,
and evidence of evaluative conditioning would
comprise pairing-dependent changes in likabil-ity ratings for the flavors or colors when pre-
sented in isolation. Thus a participant might come to increase her liking of vanilla as a re-
sult of blue-vanilla-sugar pairings, or decrease
her liking ratings for red drinks as a resultred-banana-polysorbate pairings. At the end
the experiment, awareness for the various CUS contingencies can be assessed by prese
ing colorless flavors or flavorless colors with
any US. Although Dickinson & Brown (20introduced a number of procedural impro
ments on the original Baeyens et al. (19procedure, they nonetheless replicated the k
observation, namely evidence of flavor evuative conditioning in the absence of awa
ness. More specifically, liking ratings of the vors changed as a consequence of their pairin
with sugar/polysorbate. Strikingly, participa were able to recall the color-US pairings
not the flavor-US ones. Thus participants show some degree of contingency awarene
butitwasnotrelatedtoevaluativeconditioni
They knew the color contingencies and not flavor ones, but showed conditioning of flavo
Wardle et al. (2007) introduced some furtprocedural improvements such as counterb
ancing the order of presentation of the evaative conditioning and contingency awaren
tests and using a better format for the awaness questions. Whereas Dickinson & Bro
(2007) asked participants to identify which vor went with a particular US, in Wardle et a
procedure they tasted a flavor and rated thconfidence that it went with sugar or polys
bate. Under such circumstances, Wardle et(2007)found high levels of flavor-USand col
US awareness, as well as evaluative con
tioning of the flavors (but not of the colo Thus the key evidence of unaware conditio
ing was no longer observed. When Waret al. (2007) broke down their data according
contingency awareness, they found that flaevaluative conditioning was confined to tho
participants who demonstrated awareneNotwithstanding the earlier cautions expres
about such analyses, the results revealed no idence of evaluative conditioning in unaw
participants. Moreover, when Wardle et (2007) reanalyzed Dickinson & Brown’s (20
data by separating aware from unaware part
ipants, they obtained the same pattern. Th
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whatever the final picture to emerge from thisintriguing line of research, it seems safe to
conclude that it has not as yet yielded strong
evidence of unconscious learning.
The Perruchet Effect
In the Lovibond & Shanks (2002) review, oneother empirical result was highlighted as pro-
viding potentially convincing evidence of un-aware learning. This is the Perruchet effect,
which arises in conditions of partial reinforce-ment. Perruchet (1985) used an eyeblink con-
ditioning preparation in which the CS wasreinforced on 50% of trials. In the trial se-
quence, runs of CS-alone or CS-US trials oc-
curred. When a run comprised CS-alone trials,Perruchet found that the likelihood of the con-
ditioned response declined across trials. Forexample, if there happened to be a sequence
of four CS-alone trials, the likelihood of aCR would tend to decline across these four
trials. Conversely, in a run of CS-US trials,the likelihood of the CR would tend to in-
crease across trials. Such changes are consis-tent with the increments and decrements in
associative strength that would be predictedby any reinforcement-based learning theory.
Perruchet (1985) reported, however, that par-
ticipants’ expectation of the US showed exactly the opposite pattern. In a run of CS-alone tri-
als, expectation of the US increased the longerthe run, consistent with the well-known gam-
bler’s fallacy. In a run of CS-US trials, expec-tation of the US decreased the longer the run.
Thus, the Perruchet effect comprises a strikingdissociation between conditioned responding
and awareness, and hence evidence for unawarelearning.Participantsseemtohavethoughtthat
the next trial must contain an outcome different from the preceding ones in order to maintain
the 50% reinforcement probability. Perruchet
et al. (2006) obtained a similar pattern in a re-action time (RT) experiment. Here, the CS was
a warning tone and the US an imperative stim-ulus to which participants had to respond with
a rapid button-press. While expectancy ratings
Perruchet effect: while CRs increaseacross a run of CS-Utrials, US expectancyratings decrease, and vice versa for a serie
of CS-alone trialsRT: reaction time
showed the gambler’s fallacy pattern, RTs be-came slower with runs of CS-alone trials and
faster with runs of CS-US ones.
Recent follow-up studies on this intriguingphenomenon have raised as many questions as
they have answered, however. Both the gam-bler’s fallacy aspect of the results (the changes
in conscious expectancy with run length) andthe behavioral part of the results are matters
of dispute. The circumstances for assessing ex-pectancy are hardly ideal. In Perruchet et al.’s
(2006) studies, participants moved a pointer ona dial to indicate their moment-by-moment ex-
pectancythatthetargetwouldoccuronthenext trial. These expectancies, measured at a point
just before presentation of the target, were the
primary data. But suppose the participant only changed his/her expectancy rating every few
seconds. With a very short cue (<1 sec) anda stimulus-onset asynchrony of only 500 msec,
the participant has virtually no time to registerany CS-dependent change in expectancy. Sup-
pose that, for whatever reason, expectancy of the target is not the same in the intertrial in-
terval as it is when the CS is actually present. The method would provide almost no chance of
detecting such changes. Perruchet et al. (2006)acknowledged this issue and took some steps
to ameliorate it, but without a much longer
stimulus-onset asynchrony it is hard to be con-fident in their results. In short, although the
gambler’s fallacy is unquestionably observed inmany situations, it is difficult to accept uncrit-
ically the claim that it occurs here and that ex-pectancy ratings are largest after runs of cue-
alone trials. Turning to the other part of the dissociation,
recall that CRs and speeded button-pressesshow a pattern whereby responses are less likely
or rapid after a run of CS-alone trials than arun of CS-US trials. A key question is whether
these changes in responding are genuinely as-
sociative in nature. If they are not, then theresult may have less to do with learning and
more to do with performance aspects of thetask, such as US-recency effects. To investigate
whether the effect is truly associative, Mitchell
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et al. repeated the Perruchet et al. (2006) RTstudy but arranged backward pairings or ran-
dom occurrences of the warning stimulus (CS)
and imperative stimulus (US). Under such cir-cumstances, participants have no opportunity
to use the warning stimulus to prepare for theUS. Despite this, Mitchell et al. (2009) saw
the same behavioral effect as in the standardforward-pairing condition. They also observed
the typical pattern when the CSs were omittedentirely. The obvious conclusion is that changes
in RT to the imperative stimulus have nothingto do with learning predictive relationships, but
rather are a consequence of runs of motor re-sponses. When there is a run of CS-US trials,
for example, then the frequency of the US (and
hence of responses to the imperative stimulus)is high, whereas when there is a run of CS-alone
trials, the frequency of the US declines. It seemsthat in the RT experiment it is variation in the
frequency of responses that determines reac-tion times, unconnected to learning anything
about the relationship between the CS andUS.
Weidemann et al. (2009) reported a similaranalysis in the context of eyeblink condition-
ing rather than speeded button pressing. In thiscase, the associative basis of the effect seems
more secure. They found that the behavioral
effect (fewer CRs after a run of CS-alone trialsthan a run of CS-US trials) was not the conse-
quence of US (airpuff) recency. Thus, there issome reason to believe that the Perruchet effect
in eyeblink conditioning represents genuine ev-idence of unaware learning, in that conditioned
eyeblink responses follow a pattern that is com-pletely opposite to the pattern displayed in ex-
pectancy ratings. However, the effect in otherbehavioral preparations such as speeded button
pressing seems much less secure. Plainly thisis an area where more research is needed and
where firm conclusions must await the outcome
of that research. What of other experimental procedures
within the broad domain of implicit learning?Numerous tasks have been developed and ex-
plored over the past few years, such as artificialgrammar learning, the learning of sequential
dependencies in speeded RT settings, and learning of contextual cues in visual sear
We now turn to a brief review of some of tevidence.
Sequence Learning
Nissen & Bullemer (1987)deviseda simple pcedure in which a visual target appeared
each trial at one of four locations in a displand the participant’s task was to press the a
propriate key for that location as fast as psible. Targets moved from location to locati
according to a fixed, but nonsalient, sequen(later studies have employed noisy or prob
bilistic sequences). Although participants w
not instructed about the presence of the quence, they nonetheless showed evidence
sequence learning in that their RTs were fasthan in a control condition with random tar
locations, an effect that has been replicatednumerous subsequent studies. This task, w
its heavy emphasis on perceptual-motor speprovides an ideal method for studying impl
learning: If participants readily learn the tarsequence as evidenced by speeded RTs, are th
also aware of the sequence? Or can procedulearning occur even in the absence of sequen
awareness?
To avoid the likelihood that verbal responto postexperimental questions underestim
awareness, researchers have developed altnative tests to assess awareness. In one su
test, participants are asked to report thconscious sequence knowledge by reproduc
or generating the training sequence or paof it. In another test, they observe sequen
chunks and signal whether they are old (tis, from the learned sequence) or new. W
such tests, Gaillard et al. (2009), Jim ´ enez et(2006), Norman et al. (2006, 2007), Perruc
& Amorim (1992), Perruchet et al. (199
Shanks & Johnstone (1999), Shanks et (2003, 2005, 2006), Stefaniak et al. (200
and Wilkinson & Shanks (2004) have all ported clear associations between learning a
awareness, and indeed Perruchet et al. (19and Shanks & Johnstone (1999) have sho
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that above-chance performance on a test of awareness can precede any reliable degree of
chronometrically measured sequence learning.
Bremner et al. (2007) discovered, remarkably,that 2-year-olds were able to report their
sequence knowledge in a generation test.Some studies have reported sequence learn-
ing in the absence of awareness as measuredby generation or recognition tests (e.g., Dennis
et al. 2006; Fu et al. 2009, Vandenberghe et al.2006), but these results are hard to interpret.
For example, Dennis et al. (2006) reported that sequence learning in young participants was
accompanied by awareness, but not in olderparticipants. Yet, in one experiment, the older
group did show awareness. Fu et al. (2008) re-
ported that after short amounts of sequencetraining, participants lacked awareness in that
they generated the learned sequence even wheninstructed to avoid doing so. Taking control
as an index of awareness ( Jacoby 1991), Fuet al. (2008) concluded that under these cir-
cumstances, sequence knowledge was not con-sciously accessible. However, in a subsequent
report, Fu et al. (2009) failed to observe this ef-fect when they used a slightly different genera-
tion test for assessing awareness, although they did obtain other apparent evidence of implicit
learning.
Vandenberghe et al. (2006) trained both am-nesic and control participants with a determin-
istic sequence comprising a fixed 12-locationsequence or with a probabilistic sequence in
which the majority of targets appeared at pre-ordained locations while the minority appeared
at unexpected locations. Vandenberghe et al.(2006) concluded that although control par-
ticipants were able to learn both types of sequences, amnesics could learn only the de-
terministic ones (although learning of prob-abilistic sequences in amnesia is possible: see
Shanks et al. 2006). On subsequent tests (gen-
eration andrecognition)of sequence awareness,there was evidence that participants in the con-
trol group trained on a deterministic sequence were conscious of that sequence (replicating the
findings of Wilkinson & Shanks 2004), whereascontrols trained on a probabilisticsequence and
amnesics trained with a deterministic sequence were not. Vandenberghe et al. (2006) there-
fore concluded that in the latter cases, learn-ing was implicit. However, they did not re-
port statistical tests to confirm the reliability
of deterministic sequence learning in the am-nesic group, and with only six participants in
this group, it is by no means clear that learningoccurred. The results for the controls trained
on probabilistic sequences must also be treated with caution. Participants in comparable con-
ditions of experiments by Shanks et al. (2003,2005) and Fu et al. (2008) showed substan-
tial levels of sequence awareness, despite be-ing trained for only about half as many trials.
Until more is known about the basis of thesediscrepant results, null results such as those of
Vandenberghe et al. (2006) should be treated with caution.
Also relevant are data from brain imaging
studies of implicit and explicit learning. Plainly,data showing that different neural networks are
activated under implicit and explicit learningconditions would provide powerful support
for the idea that learning can be dissociatedfrom awareness. In fact, this does not seem to
be the case. In a careful functional magneticresonance neuroimaging study, Willingham
et al. (2002) defined an implicit condition asone in which recognition was at chance and
an explicit condition as one above chance inrecognition. These investigators found that
the same neural systems (e.g., left prefrontal
cortex, left inferior parietal cortex, and right putamen) were activated in both conditions but
that additional regions were activated in theexplicit condition (e.g., premotor cortex). This
seems to challenge the idea of distinct implicit and explicit learning processes. Even under
implicit conditions, Willingham et al. (2002)did find a difference (albeit nonsignificant)
between recognition ratings for old and new test sequences of a comparable magnitude to
those typically found. Thus, it seems reason-able to conjecture that Willingham et al.’s
implicit and explicit groups merely represented
participants with weaker and stronger sequenceknowledge.
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Visual Search and Contextual Cuing
Another task that has gained some popularity
for the study of implicit learning involves thecontextual cuing of target locations in a visual
search setting. Suppose that a target such as ahorizontal letter T appears among a set of hor-
izontal L distracters, and the participant’s task
is to indicate the orientation of the T. Supposealso that on some trials the configuration of dis-
tracters is repeated from earlier trials, and that intheserepeateddisplaysthelocationofthetar-
get is constant. If the participant is able to learnabout the repeated displays, and that the loca-
tion of the target is reliably cued by a familiardistracter context, then faster localization re-
sponses might be made to repeated comparedto unique displays. Chun & Jiang (1998), who
devisedthis task, showed that participants could
indeed learn about repeated configurations andmake especially fast responses to them whileapparently being unaware of the repetition of
displays (see also Chun & Jiang 2003).
Later studies have replicated these resultsbut have also suggested that participants are
generally aware of the display repetitions, pro- vided that their awareness is assessed appropri-
ately. Smyth & Shanks (2008) measured aware-ness with two methods. In one, participants
were shown repeated displays, but with the
T replaced by another distracter L, and wereasked to indicate where they thought the miss-ing T would be located. When this test incor-
porated only 12 trials, no evidence of aware-ness was obtained (that is, performance was at
chance despite the fact that in the preceding
target-search part of the experiment, RTs werefaster to repeated displays). However, when the
number of trials was increased to 48, thus in-creasing the reliability and power of the test,
above-chance performance was observed. For
instance, reliability increased from r = 0.09to r = 0.46. Thus, evidence that learning inthe contextual cuing task is unconscious comes
from studies in which the assessment of aware-ness is unreliable. Smyth & Shanks (2008) also
evaluated awareness in a test in which partici-pants were simply shown repeated and unique
displays and asked to report which ones thhad seen previously. This test once again
vealed above-chance levels of awareness. Suabove-chance recognition was also observed
Preston & Gabrieli (2008) and Vaidya et
(2007, Exp. 2). In the influential study by Ch& Phelps (1999), contextual cuing was observ
in control but not amnesic individuals. Tauthors argued that the task assesses impli
learning because recognition was statisticallychance. Yet, the mean recognition hit and fal
alarm rates (0.37 versus 0.32 for the contro0.64 versus 0.42 for the amnesics) for old a
new displays suggest the alternative possibithat a real awareness effect was masked by u
reliability in their measure and low statistipower.
Nevertheless, a common finding in this
search is that awareness (as measured by reconition, for example) and implicit performan
tend to be uncorrelated. For instance, in Preston & Gabrieli (2008)and Smyth & Shan
(2008) studies, the correlations were closezero, and implicit performance was no grea
for recognized than for unrecognized configrations. In the Smyth & Shanks (2008) study
was also the case that analyses of contextual ing in “unaware” participants showed relia
learning effects (see also Howard et al. 200But for the reason described above, these fin
ings still do not constitute clear evidenceimplicit learning. In addition to the possibi
that the awareness test was unreliable (How
et al. 2004 tested awareness with only test displays), such dissociations are predic
by single-system models that do not incorprate the implicit–explicit distinction (Shanks
Perruchet 2002, Shanks et al. 2003) when iteor participants are selected post hoc. Su
pose that there is a single knowledge bthat controls performance both in an impli
test, such as contextual cuing, and in an plicit test, such as recognition. Suppose al
however, that independent sources of noor error contribute to each performance m
sure. As noted above, under such circu
stances, it will inevitably be the case that siulated participants selected after the fact
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scoring at or below chance on the explicit measure will score above chance on the im-
plicit one, and likewise for configurations se-
lected post hoc on the same basis. Indeed, thesemodels can even predict correlations of zero
between implicit and explicit measures, despitethem arising from the same underlying repre-
sentation (Berry et al. 2006, Kinder & Shanks2003).
Thus the evidence is rather compelling that awareness is a necessary condition for learning
across a wide range of experimental prepara-tions. On this substantial issue, Brewer (1974)
seems to have been correct in his conclusion.
CONCLUSIONS AND FUTUREDIRECTIONS
This review of recent research on the roles of associative and cognitive processes in human
learning points to two main conclusions: first,that learning across a range of preparations and
conditions is almost invariably accompanied by awareness of the experimentalcontingency; and
second, that although manipulations of indi- viduals’ beliefs can profoundly affect the way
they acquire information, associationist con-cepts continue to play a key role in explaining
learning.
These conclusions run counter to the cur-rent zeitgeist in the psychology of learning.
The study of implicit (i.e., unconscious) learn-ing has become a very substantial and distinct
research topic, influencing other areas such asdevelopmental psychology and cognitive neu-
roscience, and perpetuating a belief going back at least as far as Thorndike (1931) that learning
can proceed independently of awareness. Thepresent review suggests that the core concept
at the heart of this research area commands re-markably little empirical support. The present
review also suggests that the current fashion
for viewing learning as an entirely cognitive,inferential process faces a number of chal-
lenges. Certainly, cognitive processes penetrate very deeply into many of the subprocesses that
contribute to learning, yet associationist con-cepts such as reinforcement and activation are
nevertheless implied by some of the key find-ings considered here.
An important question is the extent to which so-called dual-process theories have util-
ity in helping us to understand learning. These
theories (Broadbent et al. 1986, Evans 2008,Kahneman 2003, Sloman 1996) propose that
the mind is composed of two systems, one au-tomatic, implicit, nonrational, and unconscious
and the other slow, effortful, rational, explicit,and conscious. Thus the first system is consis-
tent with unconscious learning and the second with inferential reasoning. The present review
should make it clear that the need for two sys-tems has yet to be established, at least in rela-
tion to learning. It is quite debatable whetherany significant forms of learning can proceed
automatically or unconsciously, nor is it the
case that apparently rational forms of learningcan be explained only by reasoning-like pro-
cesses: We have seen several examples of phe-nomena, such as retrospective revaluation, that
can be explained associativelyas well as they caninferentially.
Of course, advocates of dual-process theo-ries drawsupport froma range of domains inad-
dition to learning, including decision-making,reasoning, andmany aspects of social cognition.
There are numerous examples of what appearto be powerful unconscious influences on be-
havior (Nisbett & Wilson 1977, Wilson 2002).
Yet it is equally important to note that sophis-ticated theoretical and methodological analysis
of consciousness has been applied to few do-mains more thoroughly than it has to the field
of learning. When examples of apparent uncon-scious influences in other domains have been
subjected to the same levelof scrutiny, it has not been uncommon to find that the evidence for
such influences is considerably weakened; goodillustrations are Maia & McClelland’s (2004)
demonstration of the role of awareness in theIowa Gambling Task, and the extensive evi-
dence that attitudes measured implicitly (e.g.,
by the Implicit Association Test) are often not truly unconscious (Gawronski et al. 2006). It is
plain that future research with more demand-ing tests of awareness will allow much firmer
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conclusions to be drawn about the limits of un-conscious processing.
The phenomenon of blocking has been cen-
tral to the research reviewed here. It is of coursepossible that what appear to be instances of
the same phenomenon in fact arise for differ-ent reasons. For instance, blocking might be
a single name for a set of related outcomesthat arise from overlapping or even indepen-
dent processes. It was mentioned above that blocking can be observed in marine molluscs
as well as in humans and numerous species inbetween; plainly that does not imply that it oc-
curs for the same reason. Perhaps associativeprinciples are more important in some species
or circumstances, and cognitive ones in others.
Although such a possibility must be borne inmind, it must also be recognized that the sim-
ilarities between blocking in different speciesrun very deep. In both humans and rats, for
example, blocking is sensitive to manipulationsof additivity information. Indeed, it has proven
quite difficult to find any associative learningphenomena that appear to be qualitatively dif-
ferent across species or across contexts withina species (such as across implicit and explicit
learning conditions in humans). Thus, support-ers of dual-process theories face the important
challenge in future work of demonstrating such
qualitative differences more convincingly thanhas been achieved so far.
It is also entirely reasonable to take the view that whereas unconscious learning has proven
hard to demonstrate in the sorts of preparationsreviewed here (e.g., eyeblink conditioning), it
does nonetheless occur in other circumstances. Typical experimental procedures for studying
implicit learning tend to employ single labo-ratory sessions with meaningless stimuli (tones
and lights), so perhaps forms of more graduallearning with meaningful stimuli are being ig-
nored. It is undoubtedly important that future
work attempts to extend beyond simple labo-ratory tasks. Yet a good deal of research has
been undertaken in which learning is studiedover quite prolonged periods during which ex-
pertise is established (e.g., 10,000 repetitionsin table tennis: Koedijker et al. 2008) and with
meaningful (e.g., linguistic: Leow & Bow2005) materials and numerous perceptual a
motor as well as cognitive tasks, without yieing stronger evidence.
The major alternative to the inferential a
dual-process perspectives derives both frtraditional associative learning theory but a
from the success of the connectionist projin human cognition (McClelland & Rumelh
1986, Rumelhart & McClelland 1986, Thom& McClelland 2008). It is not possible to
view this project in detail here, but its essencomponents are the critical role played by as
ciative processes together with the appreciatthat when such processes operate across d
tributed representations, high-level reasoninlike behavior may emerge. The simulation
Ghirlanda (2005) described above is a strikillustration of this, in that it showed how r
rospective revaluation (the apparently infer
tial readjustment of the weight assigned tcue) may result from activationand incremen
learning withina simple network of neuron-lprocessing units. Although connectionist mo
els are in principle consistent with unconsciolearning, it is often assumed that stable state
activation within the brain, subject to selectattention, are precisely those states of which
are conscious (Maia & Cleeremans 2005). Although the present review has focused
studies explicitly designed to test and compassociative and inferential accounts, other fin
ings not reviewed here continue to defy exp
nation in anything other than associative termPrinciple among these is the nonrational asp
of many conditioned behaviors, a point maforcefully by Dickinson (1980, 2009; see a
Shanks 1990). In a procedure such as fear coditioning,forexample,presentationofaCSt
predicts an aversive US such as shock evokerange of responses including sweating and
evated heart rate, yet there is no rational bafor these responses. Or consider the even m
striking example of pigeon autoshaping, a m jor source of evidence in the study of con
tioned behavior. If a keylight signals the p
sentation of food, the pigeon will approach apeck it. Although the approach behavior mig
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be the product of rational inference—if the pi-geon “believes”that approach will cause food to
be obtained—it is hard to see any chain of infer-
ences that would cause the pigeon to peck thekeylight. Such pecking does not affect the de-
livery of food, and indeed pigeons will continueto peck even when pecking causes omission of
the food. The form of the response (the pigeonappears to try to eat a keylight that predicts food
and drink one that predicts water) strongly sug-gests Pavlov’s original mechanism of stimulus
substitution, whereby the CS becomes associ-ated with and takes the place of the US. It is
very hard to see any involvement of cognitiveor inferential operations in this type of learning
and behavior.
Many gaps remain in our knowledge of thecontributions of cognitive and associative pro-
cesses to learning. Perhaps the most important
item for the research agenda is to gain a fullerunderstanding of the limits of associative prin-
ciples in explaining additivity and related ef-
fects on blocking. As described in this review, it hasbeen clearly demonstrated that the outcome
of a blocking experiment, in both humans andanimals, can be radically altered by pretreat-
ments designed to demonstrate the additivity or nonadditivity of cues. Yet the precise locus of
these effects is still unknown. It is possible that they operate by altering the beliefs that form
the basis for inferences about predictive value,but it is also possible that configural process-
ing or generalization are the key mechanismsthat are affected by such manipulations. These
and related questions will surely feature promi-nently in future research seeking to under-
stand the inferential and associative aspects of
learning.
SUMMARY POINTS
1. A review of the literature illustrates that although they are based on radically different
principles, cognitive and associative accounts of learning can both encompass a broadrange of empirical phenomena. Decisive tests are difficult to devise.
2. Forty years after its discovery, the phenomenon of blocking continues to lie at the heart of theoretical debate. Explanations in terms of the automatic formation of associations
are certainly inadequate.
3. Learning is strongly influenced by pretreatments that provide information about the
additivity or nonadditivity of cue weights and by other manipulations of beliefs relevant to inferential reasoning.
4. There is a substantial body of results, including the effects of cue competition on memory and judgment, that provides evidence for associative processes such as activation and
reinforcement.
5. Robust and replicable instances of unconscious learning have failed to emerge in the
experimental literature, consistent with the view that awareness is a necessary conditionfor all forms of learning, including conditioning.
6. Although its basis is not yet fully understood, the Perruchet effect represents perhaps themost clear-cut current evidence for independent implicit and explicit learning systems.
DISCLOSURE STATEMENT
The author is not aware of any biases that might be perceived as affecting the objectivity of thisreview.
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Annual Review of
Psychology
Volume 61, 2010 Contents
Prefatory
Love in the Fourth Dimension
Ellen Berscheid
Brain Mechanisms and Behavior
The Role of the Hippocampus in Prediction and Imagination
Randy L. Buckner
Learning and Memory Plasticity; Neuroscience of Learning
Hippocampal-Neocortical Interactions in Memory Formation,
Consolidation, and Reconsolidation
Szu-Han Wang and Richard G.M. Morris
Stress and Neuroendocrinology
Stress Hormone Regulation: Biological Role
and Translation Into Therapy Florian Holsboer and Marcus Ising
Developmental Psychobiology
Structural Plasticity and Hippocampal Function
Benedetta Leuner and Elizabeth Gould
Cognitive Neuroscience
A Bridge Over Troubled Water: Reconsolidation as a Link Between
Cognitive and Neuroscientific Memory Research Traditions
Oliver Hardt, Einar ¨ Orn Einarsson, and Karim Nader
Cognitive Neural Prosthetics
Richard A. Andersen, Eun Jung Hwang, and Grant H. Mulliken
Speech Perception
Speech Perception and Language Acquisition in the First Year of Life
Judit Gervain and Jacques Mehler
vi
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Chemical Senses (Taste and Smell)
An Odor Is Not Worth a Thousand Words: From Multidimensional
Odors to Unidimensional Odor Objects
Yaara Yeshurun and Noam Sobel 219
Somesthetic and Vestibular Senses
Somesthetic Senses
Mark Hollins 243
Basic Learning and Conditioning
Learning: From Association to Cognition
David R. Shanks 273
Comparative Psychology
Evolving the Capacity to Understand Actions, Intentions, and Goals
Marc Hauser and Justin Wood 303
Human Development: Processes
Child Maltreatment and Memory
Gail S. Goodman, Jodi A. Quas, and Christin M. Ogle 325
Emotional, Social, and Personality Development
Patterns of Gender Development
Carol Lynn Martin and Diane N. Ruble 353
Adulthood and Aging
Social and Emotional AgingSusan T. Charles and Laura L. Carstensen 383
Development in Societal Context
Human Development in Societal Context
Aletha C. Huston and Alison C. Bentley 411
Genetics and Psychopathology
Epigenetics and the Environmental Regulation
of the Genome and Its Function
Tie-Yuan Zhang and Michael J. Meaney
439
Social Psychology of Attention, Control, and Automaticity
Goals, Attention, and (Un)Consciousness
Ap Dijksterhuis and Henk Aarts 467
Co nt en ts v ii
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Bargaining, Negotiation, Conflict, Social Justice
Negotiation
Leigh L. Thompson, Jiunwen Wang, and Brian C. Gunia
Personality Development: Stability and Change
Personality Development: Continuity and Change Over theLife Course
Dan P. McAdams and Bradley D. Olson
Work Motivation
Self-Regulation at Work
Robert G. Lord, James M. Diefendorff, Aaron C. Schmidt, and Rosalie J. Hall
Cognition in Organizations
Creativity
Beth A. Hennessey and Teresa M. Amabile
Work Attitudes ( Job Satisfaction, Commitment, Identification)
The Intersection of Work and Family Life: The Role of Affect
Lillian T. Eby, Charleen P. Maher, and Marcus M. Butts
Human Factors (Machine Information, Person Machine Information,
Workplace Conditions)
Cumulative Knowledge and Progress in Human Factors
Robert W. Proctor and Kim-Phuong L. Vu
Learning and Performance in Educational Settings The Psychology of Academic Achievement
Philip H. Winne and John C. Nesbit
Personality and Coping Styles
Personality and Coping
Charles S. Carver and Jennifer Connor-Smith
Indexes
Cumulative Index of Contributing Authors, Volumes 51–61
Cumulative Index of Chapter Titles, Volumes 51–61
Errata
An online log of corrections to Annual Review of Psychology articles may be found
http://psych annualreviews org/errata shtml