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Learning theory proposes that drug seeking is a synthesis of multiple controllers. Whereas goal-directed drug seeking is determined by the anticipated incentive value of the drug, habitual drug seeking is elicited by stimuli that have formed a direct association with the response. Moreover, drug-paired stimuli can transfer control over separately trained drug seeking responses by retrieving an expectation of the drug's identity (specific transfer) or incentive value (general transfer). This review covers outcome devaluation and transfer of stimulus-control procedures in humans and animals, which isolate the differential governance of drug seeking by these four controllers following various degrees of contingent and noncontingent drug exposure. The neural mechanisms underpinning these four controllers are also reviewed. These studies suggest that although initial drug seeking is goal-directed, chronic drug exposure confers a progressive loss of control over action selection by specific outcome representations (impaired outcome devaluation and specific transfer), and a concomitant increase in control over action selection by antecedent stimuli (enhanced habit and general transfer). The prefrontal cortex and mediodorsal thalamus may play a role in this drug-induced transition to behavioral autonomy.
Ann. N.Y. Acad. Sci. ISSN 0077-8923
Issue: Addiction Reviews
Associative learning mechanisms underpinning the
transition from recreational drug use to addiction
Lee Hogarth,1Bernard W. Balleine,2Laura H. Corbit,3and Simon Killcross1
1School of Psychology, University of New South Wales, Sydney, Australia. 2Brain and Mind Research Institute, University of
Sydney, Sydney, Australia. 3School of Psychology, University of Sydney, Sydney, Australia
Address for correspondence: Lee Hogarth, School of Psychology, University of New South Wales, Sydney, NSW 2052,
Learning theory proposes that drug seeking is a synthesis of multiple controllers. Whereas goal-directed drug seeking
is determined by the anticipated incentive value of the drug, habitual drug seeking is elicited by stimuli that have
formed a direct association with the response. Moreover, drug-paired stimuli can transfer control over separately
trained drug seeking responses by retrieving an expectation of the drug’s identity (specific transfer) or incentive
value (general transfer). This review covers outcome devaluation and transfer of stimulus-control procedures in
humans and animals, which isolate the differential governance of drug seeking by these four controllers following
various degrees of contingent and noncontingent drug exposure. The neural mechanisms underpinning these four
controllers are also reviewed. These studies suggest that although initial drug seeking is goal-directed, chronic drug
exposure confers a progressive loss of control over action selection by specific outcome representations (impaired
outcome devaluation and specific transfer), and a concomitant increase in control over action selection by antecedent
stimuli (enhanced habit and general transfer). The prefrontal cortex and mediodorsal thalamus may play a role in
this drug-induced transition to behavioral autonomy.
Keywords: addiction; learning theory; goal; cue-reactivity; habit
A recurrent theme in addiction theory is that drug
seeking has multiple determinants. Wikler1argued
that the euphoric effects of the drug maintained
initial drug use, whereas addiction itself stemmed
from the emergence of a withdrawal syndrome.
Tolerance2and opponent-process theories3elabo-
rated this notion of a shift from positive to neg-
ative reinforcement. Subsequently, the importance
of negative reinforcement was questioned by the
observation that drug self-administration engages
dopamine, the brain substrate of reward,4and by the
lawful relationship between the frequency of drug
seeking and the magnitude of drug reward.5But
denying the importance of negative reinforcement
(but see Ref. 6) put positive reinforcement theorists
at pains to explain the transition from recreational
drug use to addiction. Tiffany7answered this ques-
tion from a cognitive viewpoint, arguing that drug
seeking may be mediated by desire, or elicited au-
tomatically by drug cues, and the latter controller
predominates in addiction. Robinson and Berridge8
made a similar argument from a behavioral neuro-
science perspective, stating that drug seeking may be
driven by hedonic anticipation of the drug (liking),
or autonomous cue-locked conditioned behavior
(wanting), thus accounting for addicts’ paradoxi-
cal continuation of drug use despite intentions to
Contemporary addiction theories have elabo-
rated these themes. The behavioral economists have
garnered evidence that human drug dependence
is a choice recruited by the reinforcement value
of the drug,9but is also accompanied by an in-
ability to use knowledge of abstract future con-
sequences in decision making.10 Similarly, animal
learning theorists have substantiated evidence that
drug self-administration is a function of the rein-
forcement value of the drug11,12 but also undergoes a
doi: 10.1111/j.1749-6632.2012.06768.x
12 Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences.
Hogarth et al. Abnormal learning underpinning dependence
transition to automatic control by drug-paired stim-
uli.13 Finally, cognitive neuroscientists have shown
that drug liking is associated with drug-induced
dopamine activation14 and that clinically diagnosed
addiction is accompanied by hypofrontality and ex-
ecutive dysfunction.15 The common theme in all
of these frameworks, therefore, is that initial drug
use is mediated by the drug acting as a positive rein-
forcer, whereas the transition to clinical dependence
is linked to a loss of intentional regulation and con-
comitant emergence of automatic control over drug
Learning theory and addiction
The current review aims to detail this transitional
theory of addiction by inspecting human and ani-
mal learning research that has tested the differential
governance of behavior at various stages of drug
exposure. The ideas developed here were first in-
troduced by Norman White who drew a link be-
tween the role of the striatum in memory and ad-
dictive behavior.16,17 The formal associative learning
account was then outlined by Anthony Dickin-
son during symposium proceedings from empiri-
cal work with natural rewards.18 These ideas were
then translated to behavioral neuroscience research
with addictive drugs in collaboration with Trevor
Robbins and Barry Everitt.19–21 Simultaneously, be-
havioral neuroscience research continued with nat-
ural rewards that clarified the associative mecha-
nisms outlined here,22–24 and which are depicted
schematically in Figure 1. According to this per-
spective, experience of the drug outcome is encoded
separately in terms of its specific sensory correlates
or perceptual identity (Oi) and its consummatory,
postingestive or incentive value (Ov), and these two
representations of the drug can differentially enter
into associations.25,26 As a consequence, the agent
(person or animal) acquires four forms of associa-
tive knowledge.
(1) Goal-directed learning. The agent acquires
knowledge of the instrumental contingency
between the drug seeking response and the
drug’s identity and value (R–Oiv). Moreover,
the representation of the drug’s value is up-
dated by internal states, such as deprivation
or satiety, which predict the current value of
the drug. Consequently, retrieval of the rep-
resentation of the drug and its current value
Figure 1. Experience of the drug outcome is separately en-
coded in terms of its perceptual identity (Oi) and incentive
value (Ov) and establishes learning about (1) the goal-directed
instrumental contingency between drug seeking response and
the drug (R–Oiv); (2) the habitual contingency between drug
stimuli and the drug seeking response (S–R); and (3) the Pavlo-
vian contingency between drug stimuli and the drug (S–Oiv ).
It is argued that chronic drug exposure generates a progressive
impairment in capacity to retrieve or utilize the specific iden-
tity of outcomes (Oi), which causes a transition in behavioral
control from the R–Oiv and S–Oiassociations to the S–R and
S–Ovassociations. That is, addiction reflects a loss of control
over behavior by knowledge of the consequences indexed by
outcome devaluation and specific transfer, in favor of control
by antecedent stimuli indexed by devaluation insensitivity and
general transfer.
(Oiv) determines the propensity to select the
associated drug seeking responses from among
competing outcome choices based on a com-
parison of their relative values.27 Thus,ahigher
value drug produces a greater proportion of in-
tentional choice of that outcome from among
alternative rewards.28
(2) Habit learning. The agent forms an associ-
ation between external stimuli (S) and the
drug seeking response (R) in proportion to
the contingent co-occurrence of these two
events before drug reinforcement and the re-
inforcement value of that outcome (Ov).29
This S–R/reinforcement process enables the
drug stimulus, when reencountered, to elicit
the drug seeking response directly without re-
trieving any representation of the drug out-
come. Such habitual drug seeking accords with
the clinical characterization of addiction as
reflecting a loss of intentional regulation of
Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences. 13
Abnormal learning underpinning dependence Hogarth et al.
(3) Specific transfer. External stimuli also acquire
an association with the drug outcome in accor-
dance with the predictive contingency between
these events, enabling stimuli to retrieve a rep-
resentation of the drug’s identity and/or value.
Retrieval of the outcome’s identity (S–Oi)can,
in turn, elicit separately trained instrumental
responses that are associated with that same
outcome via a bidirectional O–R, or ideomo-
tor, connection (S–Oi–R).30
(4) General transfer. By contrast, retrieval of the
outcome’s affective value (S–Ov) elicits a mo-
tivational state akin to the drug itself, which
exerts a general excitatory effect on prevailing
responses controlled by the other associations
The claim made in this paper is that these var-
ious forms of behavioral control interact to deter-
mine the propensity to engage in drug seeking at any
given moment. Our claim is that continuing drug
exposure impairs retrieval or utilization of the rep-
resentation of specific outcome identities (Oi), thus
impairing control of action by knowledge of specific
outcomes (R–Oiv and S–Oi–R) toward more general
control over actions by antecedent stimuli (S–R and
[S–Ov]–R). We now turn to empirical evidence for
this psychological account of addiction.
Goal-directed drug seeking
The outcome devaluation procedure provides the
principal method for identifying goal-directed con-
trol.32 A version of this procedure is presented in
Table 1. In this procedure, rats learn that two dif-
ferent lever press responses (R) produce different
rewarding outcomes (O). For example, one lever
may produce drug reward such as alcohol or cocaine
(O1), whereas the other lever produces an alterna-
tive natural reward such as sucrose (O2). The drug
is then devalued by pairing it with lithium chloride-
induced gastrointestinal sickness, specific satiety, or
related manipulation, such that the value of the drug
is diminished. The critical test then comes when
the animal is again given the opportunity to press
the two levers in an extinction test where the re-
sponses no longer produce their respective rewards.
The question at stake is whether the animal will re-
duce responding for the drug outcome (R1 <R2).
Because the outcomes are not presented in the ex-
tinction test, any such devaluation effect cannot be
attributed to S–R/reinforcement (habit) learning,
Tab l e 1. The outcome devaluation procedure used to
demonstrate goal-directed versus habitual control of ac-
tion selection. The agent learns that two responses (R1
and R2) earn different rewarding outcomes (O1 and O2).
One outcome is then devalued (O1 or O2) before an ex-
tinction test in which the agent can again perform the
two responses (R1/R2) without feedback from the out-
comes. A reduction in choice of the response that earned
the devalued outcome (R1=R2) must be goal-directed in
that it is controlled by knowledge of the R–O contingency
and the current incentive value of the O. By contrast, a
null effect of the devaluation treatment on responding in
the extinction test (R1 =R2) suggests responding is ha-
bitual in that it is elicited directly by the stimulus context
without engaging knowledge of the consequences (S–R)
Instrumental Devaluation Extinction
training treatment test
R1–O1 O1 or O2 R1/R2
that is, by experience of the drug outcome modu-
lating the capacity of contextual cues to elicit drug
seeking response. Furthermore, because the proce-
dure contains no stimuli that differentially signal
the two outcomes, a devaluation effect cannot be
attributed to a change in capacity of such cues to
elicit responding for their associated outcomes (S–
Oiv–R). Instead, a reduction in drug choice in the
extinction test must be mediated by animals’ in-
tegration of knowledge of the R–Oiv contingencies
acquired during instrumental training, with knowl-
edge of current low value of the drug outcome (Ov)
acquired during the devaluation treatment, which
together determine the propensity to select that re-
sponse. In other words, a devaluation effect in the
extinction test demonstrates that drug seeking is
goal-directed in that it is determined by the antici-
pated reward value of the drug.
Two studies illustrate the outcome devaluation
procedure in demonstrating goal-directed control
of drug seeking. In a study by Olmstead et al.,33 rats
were trained on a seeking–taking chain in which
they had to press a seeking lever to gain access to
a taking lever, which in turn delivered intravenous
cocaine. To test whether the seeking response was
goal-directed, the taking lever was extinguished by
terminating cocaine delivery. The seeking lever was
14 Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences.
Hogarth et al. Abnormal learning underpinning dependence
not present during this extinction training. The fact
that this extinction training led to an immediate re-
duction in rats’ performance of the seeking response
in extinction indicated that this response was medi-
ated by knowledge of its consequences, that is, the
low current value of the taking lever.
Hutcheson et al.34 employed a similar design.
Training on a seeking–taking chain for heroin was
followed by a revaluation treatment in which self-
administration via the taking response was expe-
rienced in a withdrawal state to establish the high
value of heroin in this state. Rats were then again
given access to the seeking lever in extinction, and
the finding that withdrawal produced an increase
in performance of the seeking response indicated
that it was goal-directed in that is was mediated by
knowledge of the current high value of the heroin
The outcome devaluation procedure has also
been modified for humans.35,36 In the concurrent
training stage of these experiments, smokers learned
two key press responses, where R1 produced tobacco
points and R2 produced chocolate points. Tobacco
was then devalued by smoking to satiety, evaluation
of smoking health warnings, for example, “smok-
ing causes cancer,”36 or by administration of nico-
tine nasal spray.35 The finding that tobacco choice
in the extinction test was sensitive to these deval-
uation treatments (R1 <R2) indicated that it was
goal-directed in being mediated by knowledge of the
current value of the drug outcome.
A key observation replicated in these human ex-
periments was that individual variation in level of
tobacco dependence was associated with a prefer-
ential selection of the tobacco versus the chocolate
response. Similar preferences have been established
in animals11 and human cocaine users37 and con-
firms the economic theorists’ main contention that
drug dependence reflects individual differences in
the reinforcement value of the drug.9The outcome-
devaluation procedure qualifies this notion by dis-
tinguishing the contribution of goal-directed (R–
Oiv) and habitual (S–R) drug seeking to this drug
preference. We know that choice of the drug seek-
ing response was goal-directed as it was sensitive
to devaluation in the extinction test. Any resid-
ual contribution of S–R learning to this drug pref-
erence would be marked by variation in sensitiv-
ity to devaluation treatment in the extinction test.
As there was no systematic variation across levels
of nicotine dependence in sensitivity to devalua-
tion, it may be concluded that preferential tobacco
choice across dependence level was mediated en-
tirely by valuation of the drug as a goal, and not by
differential S–R formation. The conclusion, there-
fore, is that drug seeking within these parameters
is goal-directed, and that level of dependence, at
least at this early stage of drug exposure, reflects the
valuation of the drug as a specific goal (see Refs.
Habitual drug seeking
As noted, the outcome devaluation procedure can
evaluate the habitual status of instrumental perfor-
mance32 (see Table 1). Whereas sensitivity of drug
seeking to devaluation in the extinction test (R1 <
R2) signifies goal-directed control, insensitivity to
devaluation in the extinction test (R1 =R2) demon-
strates that retrieval of the current value of the drug
plays no role in drug seeking. Instead, drug seeking
is deemed to have become habitual, being elicited by
contextual stimuli that have acquired a direct S–R
association with drug seeking during instrumental
training, without retrieving a representation of cur-
rent value of the drug.
Two studies illustrate the use of the outcome-
devaluation procedure to demonstrate the habitual
status of drug seeking. In the first study, Dickinson
et al.13 trained rats to acquire two instrumental re-
sponses, one for alcohol and one for food pellets,
before one of these outcomes was devalued by pair-
ing it with lithium chloride-induced sickness. When
the rats were again given the opportunity to respond
for these outcomes in extinction, it was found that
performance of the food-seeking response was re-
duced by the devaluation treatment, indicating that
food seeking was goal-directed. By contrast, perfor-
mance of the alcohol-seeking response was insensi-
tive to devaluation, suggesting that alcohol seeking
had become an S–R habit. A second study used a
similar design to confirm that cocaine seeking was
similarly prone to habitual control compared to nat-
ural reward seeking.43
A question arises as to why habitual drug seek-
ing was established by these two procedures,13,43
whereas goal-directed drug seeking was found in the
earlier designs.33–36 In explaining these divergent re-
sults, one might appeal to a number of variables that
have been demonstrated to modulate the balanceb e-
tween goal-directed and habitual control, including
Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences. 15
Abnormal learning underpinning dependence Hogarth et al.
position of the response within an instrumental se-
quence or chain,44–46 amount of training,47,48 num-
ber of available responses,49 and/or reinforcement
value of the outcome.50 The important point made
by this literature is that goal-directed and habitual
actions exist in a dynamic balance that can be bi-
ased in one direction or the other by conditions of
training or testing that favor acquisition/expression
of the R–O versus S–R association. Our basic argu-
ment is that within this complex system, drugs exert
a constant pressure in favor of the S–R association
by impairing retrieval or utilization of the specific
identity of outcomes.
Corbit et al.51 has recently mapped the progres-
sive transition to habitual control of drug seeking
with extended training. In this study, rats acquired
a self-administration response for alcohol, before
alcohol was devalued by ad libitum consumption
(satiety). Alcohol seeking was then tested in extinc-
tion to evaluate goal-directed control of this be-
havior. Following two weeks of self-administration
training, the response remained sensitive to deval-
uation, but by eight weeks of training, the response
was insensitive to devaluation, suggesting a transi-
tion from goal-directed to habitual control had oc-
curred with training (cocaine seeking shows a sim-
ilar transition to habit with extended training52).
An important additional finding of this study was
that noncontingent administration of alcohol was
sufficient to accelerate habitual control over natural
reward-seeking responses. Thus, not only do drug
self-administration responses become habitual, but
also noncontingent drug exposure renders contem-
poraneously acquired naturally rewarded instru-
mental actions habitual.
In humans, a comparable effect of noncontin-
gent alcohol exposure on habitual control has re-
cently been demonstrated.53 Participants were ad-
ministered with 0.4 g/kg of alcohol or placebo before
instrumental training with R1 and R2 for chocolate
and water,respectively. Chocolate was then devalued
by ad libitum consumption before choice between
R1 and R2 was tested in extinction. The finding
that alcohol attenuated goal-directed control over
chocolate choice in the extinction test supports the
translational relevance of animal models, and sug-
gests that accelerated habit learning can be demon-
strated with acute drug dosing.
A key study by Nelson and Killcross54 re-
vealed that noncontingent drug exposure enhanced
habit formation during instrumental training rather
than at the extinction test. They preexposed rats
to amphetamine for seven days before a seven-
day injection-free period. Instrumental training
for sucrose was then undertaken before this out-
come was devalued by specific satiety or lithium
chloride–induced sickness. The results from the
extinction test indicated that both devaluation
treatments failed to modify sucrose seeking in
the amphetamine-exposed rats, suggesting this re-
sponse had become habitual, whereas placebo rats
showed goal-directed control (see also Refs. 50 and
55). Importantly, chronic amphetamine only accel-
erated habit formation if administered before in-
strumental training, but not if administered after
training. Consistent with this, all the aforemen-
tioned studies that have shown effects of contin-
gent13,43,51 and noncontingent51 drug exposure on
habit learning have undertaken drug administration
contemporaneously with instrumental training.
The implication, therefore, is that during instru-
mental training, the ability of the outcome represen-
tation to enter into new learning may be impaired by
drug exposure, favoring acquisition of the S–R over
the R–Oiv contingencies, but once R–Oiv learning is
acquired drug free, deployment of this knowledge
at test is not impaired by drug exposure.
In reconciling the aforementioned studies, one
can propose a transitional model of addiction
wherein initial drug seeking is goal-directed,33–36
but following extended training comes under ha-
bitual S–R control,13,43 and contemporaneously ac-
quired natural reward seeking also comes under
habitual control.51,53,54 Ultimately, the agent’s be-
havioral repertoire comes to be dominated by S–R
Specific transfer of stimulus control over drug
The Pavlovian to instrumental transfer procedure
is the principal method for demonstrating control
over responding by stimuli retrieving a representa-
tion of the specific identity of their paired outcome
(Oi) (e.g., Ref. 56; see Table 2). In this design, rats
are given Pavlovian training in which one stimulus
(S1) signals drug availability (O1), whereas a sec-
ond stimulus (S2) signals the availability of an alter-
native reward, for example sucrose (O2). Separate
instrumental training is then undertaken wherein
rats learn that one lever produces the drug (O1)
16 Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences.
Hogarth et al. Abnormal learning underpinning dependence
Tab l e 2. The Pavlovian to instrumental transfer proce-
dure used to demonstrate transfer of stimulus control
over action selection. The agent learns that two stimuli
(S1 and S2) predict different rewarding outcomes (O1
and O2). They separately learn that two responses (R1
and R2) differently earn those same rewarding outcomes
(O1 and O2). In the transfer test, the stimuli (S1 and S2)
are presented whilst the responses (R1 and R2) are avail-
able. A specific transfer effect is demonstrated when each
stimulus selectively enhances responding for the same
outcome (S1:R1 >R2, S2:R1 <R2). This specific transfer
effect suggests that each stimulus elicited a representa-
tion of the identity of its associated outcome (Oi), which
in turn elicited its associated response (S–Oi–R). By con-
trast, a general transfer effect is demonstrated when each
stimulus enhances both responses equally above a pre-
or no-stimulus baseline (S1/S2: >R1/R2). This general
transfer effect suggests that each stimulus elicited a rep-
resentation of the value (Ov) but not identity (Oi)ofits
associated outcome which produced a general enhance-
ment of responding ([S–Ov]–R)
Pavlovian Instrumental Extinction
training training test
S1–O1 R1–O1 S1:R1/R2
S2–O2 R2–O2 S2:R1/R2
whereas the other lever produces sucrose (O2). Fi-
nally, in the Pavlovian to instrumental transfer test,
each stimulus is presented for the first time while
the two instrumental responses are available in ex-
tinction. The question at stake is whether each stim-
ulus will enhance performance of the response with
which it shares the same outcome (i.e., S1:R1 >
R2, S2:R1 <R2). Such an outcome-specific trans-
fer effect demonstrates that each stimulus retrieved
a representation of its associated outcome, which
in turn retrieved the response that was associated
with that outcome (S–Oi–R). The effect cannot be
attributed to the formation of an S–R association
because the stimuli and the responses were never
contingently reinforced during training, and fur-
thermore, because the transfer test was conducted
in extinction, so no S–R association can form across
that period either.
There is currently only one demonstration of
outcome-specific transfer of stimulus control over
drug seeking per se57 (although there are many
demonstrations in natural reward learning58). In
this study, smokers first learned that two arbitrary
stimuli (S1 and S2) predicted tobacco points or
money, respectively, before learning that two re-
sponses (R1 and R2) earned tobacco points and
money, respectively. In the transfer test, the two
stimuli were found to selectively enhance perfor-
mance of the response that had earned the same
outcome. Thus, each stimulus must have retrieved
a representation of its associated outcome (points),
which in turn elicited the response that had pro-
duced that outcome (S–Oi–R).
General transfer of stimulus control over drug
By contrast, in a related animal procedure, Cor-
bit and Janak59 paired S1 and S2 with ethanol or
sucrose, respectively, and then trained R1 and R2
with these same outcomes, respectively. The results
showed that the ethanol stimulus enhanced the rate
of both R1 and R2 equally above a no-stimulus base-
line, indicating that this stimulus exerted a general
excitatory effect on instrumental reward seeking by
retrieving the value (S–Ov) rather than identity (S–
Oi) of the outcome. By contrast, the sucrose stimu-
lus produced a specific transfer effect, selectively en-
hancing instrumental responding for sucrose over
ethanol, indicating that it had retrieved the out-
come’s identity (S–Oi). These data are consistent
with the view that drug-associated cues favor gen-
eral facilitatory effects on appetitive instrumental
responses compared to natural reward-paired cues
(see also Refs. 60 and 61).
The divergent results of these human and an-
imal transfer studies may be resolved by ap-
pealing to Konorski’s view25 that outcomes are
encoded separately in terms of their perceptual iden-
tity (sensory correlates) and consummatory or in-
centive value.26 On this view, the tobacco points
outcome used by Hogarth et al.57 was largely per-
ceptual and minimally consummatory, and so the
stimulus paired with this outcome favored a specific
transfer effect that relied on the retrieval of this out-
come’s perceptual identity (S–Oi–R). By contrast
the ethanol consummatory outcome employed by
Corbit and Janak59 possessed a substantial pharma-
cological/consummatory effect, and so the stimulus
paired with this event favored a general motivational
enhancement based upon retrieval of the outcome
value ([S–Ov]–R).
Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences. 17
Abnormal learning underpinning dependence Hogarth et al.
Other studies substantiate this characterization of
the specific and general forms of stimulus control.62
First, the magnitude of the specific transfer effect is
determined by the reliability of the S–O contingency
in training,63–65 but is insensitive to outcome deval-
uation.31,66–68 Importantly, specific transfer effects
by drug cues on drug seeking in humans are similarly
insensitive to devaluation achieved by drug sati-
ety, health warnings,36,69 and pharmacotherapy.35
Moreover, the finding that drug cue effects on sub-
jective craving70,71 and drug taking69 are similarly
autonomous of devaluation by satiety and pharma-
cotherapy, supports the validity of specific (S–Oi
R) transfer effects in addiction. By contrast, general
transfer effects are modulated by devaluation of the
outcome,31,72 and cross over to other reinforcers of
the same hedonic category.73 Thus, general transfer
effects are deemed to be mediated by the stimu-
lus retrieving a representation of the current value
(Ov) but not identity (Oi) of the outcome, and as
a consequence, the effect is sensitive to changes in
motivational state but is not response selective ([S–
Not only does contingent drug exposure cause
drug cues to favor general over specific transfer,59
but noncontingent drug exposure may also cause
natural reward cues to undergo this same transi-
tion. In a recent study, Shiflett et al.74 found that
noncontingent exposure to chronic amphetamine
administered following Pavlovian and instrumen-
tal training (i.e., before the transfer test) abolished
the specific transfer effect and enhanced the general
transfer effect. Specifically, rats received Pavlovian
training in which S1 predicted chocolate and S2
predicted grain. Instrumental training was then un-
dertaken in which two responses, R1 and R2, earned
these same outcomes, respectively. Then, half of rats
were given seven days of amphetamine administra-
tions and the remainder placebo (similar to Ref.
54). Finally, in the transfer test, the two stimuli
were tested for a specific transfer effect in which
each stimulus selectively enhanced responding for
the same outcome, or a general transfer effect in
which each stimulus enhanced responding for both
outcomes equally above a prestimulus baseline. The
remarkable finding was that amphetamine expo-
sure before test abolished the specific transfer effect
and enhanced the general transfer effect. A simi-
lar enhancement of the general transfer effect pro-
duced by natural reward cues on reward seeking has
been found following acute75 and chronic76 am-
phetamine administered before the testing phase,
although in these latter studies no attempt was made
to assess specific transfer.
Overall, these studies favor a transitional model
wherein early in training, drug cues retrieve the
drug’s identity and thus produce specific trans-
fer effects.35,36,57 Extended drug exposure, how-
ever, causes stimuli to lose contact with the drug’s
identity and instead make contact with the drug’s
value, thus causing a transition from specific to
general transfer.59–61 Moreover, contemporaneously
acquired natural reward cues also shift contact
from their outcome’s identity to its value, caus-
ing a comparable transition from specific to general
Synthesis of psychological studies
The transition to behavioral autonomy depicted
across the studies reported here is consistent with
a singular impairment in the capacity to retrieve or
utilize the specific identity of outcomes as a conse-
quence of drug exposure. This impairment can ex-
plain why drug seeking is initially goal-directed (R–
Oiv) and under specific stimulus control (S–Oi–R),
but then becomes habitual (S–R) and under general
stimulus control ([S–Ov]–R). Whereas the former
two controllers require a representation of the spe-
cific identity of the drug, the latter two controllers
do not. Moreover, the finding of the same transition
in natural reward-seeking responses acquired con-
temporaneously with drug exposure suggests that
the impairment in capacity to represent the specific
outcomes applies to the entire class of appetitive
rewards (it remains to be seen whether aversive out-
comes are similarly affected). Finally, this account
suggests that stress,77 trait impulsivity,78,79 con-
flict,80,81 hypofrontality,82–84 and schizophrenia85,86
may be linked with drug dependence and relapse be-
cause they exacerbate this impairment in capacity to
represent/utilize specific outcome identities.
The claim that a single impairment underpins
both the loss of goal-directed control and the loss of
specific transfer is challenged by a dissociation be-
tween these two effects. Specifically, goal-directed
control was abolished by chronic amphetamine ad-
ministered before training but not administered
before test, suggesting that chronic amphetamine
impairs acquisition of response-outcome knowl-
edge during instrumental training but does not
18 Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences.
Hogarth et al. Abnormal learning underpinning dependence
directly impair the retrieval/utilization of outcome
identity required for goal-direction control at test.54
By contrast, chronic amphetamine abolished spe-
cific transfer when administered before test,74 sug-
gesting that chronic amphetamine can directly abol-
ish the retrieval/utilization of outcome identity re-
quired for the specific transfer effect. Identifying a
common learning mechanism that operates during
both instrumental training and the transfer test to
produce the observed transition to behavioral au-
tonomy is arguably crucial for isolating the core
associative pathology in addiction.
Neural basis of action control
The following section reviews animal studies that
have examined the neural basis of the four con-
trollers underpinning natural reward and drug seek-
ing. The purpose of this section is to identify sub-
strates upon which chronic drug exposure might
act to produce the transition to autonomy depicted
earlier, that is, reduce goal-directed learning and
specific transfer, and/or enhance habit learning and
general transfer.
Neural basis of goal-directed action
Lesions of the prelimbic (PL) region of the pre-
frontal cortex have been shown to produce precisely
the same deficit in goal-directed control as chronic
amphetamine.54 That is, lesions of the PL abolish
goal-directed control of natural reward seeking if
they occur before instrumental training48,87,88 but
not if they occur before test.89 Comparable effects
have been found following lesions of the mediodor-
sal thalamus, which also abolish acquisition90 but
not expression91 of goal-directed action. As the
mediodorsal thalamus provides the major thalamic
input to the PL, it is believed that these two regions
form a functional circuit. The correspondence of
PL, mediodorsal thalamic lesions, and chronic am-
phetamine exposure on acquisition of goal-directed
control supports these two brain regions in medi-
ating the effect of drug exposure on transition to
behavioral autonomy.
By contrast, the dorsomedial striatum (DMS)
has been shown to be essential for both the ac-
quisition92,93 and the expression94 of goal-directed
learning. Importantly, posttraining DMS inactiva-
tion has been shown to abolish goal-directed con-
trol of alcohol seeking, suggesting common neural
mechanisms underpinning both natural and drug
reward goal-directed learning.51 In addition, lesions
of the basolateral amygdala (BLA) abolish sensitivity
to outcome devaluation whether given before95,96
or after instrumental training.91,97 Thus the DMS
and BLA, in failing to mimic the selective effect
of amphetamine on loss of goal-directed learning
at acquisition, may not play a direct role in drug
sensitization-induced transition to behavioral au-
Neural basis of habitual action
Habitual action, by contrast, is mediated by the dor-
solateral striatum (DLS) and infralimbic cortex. As
noted earlier, overtraining instrumental contingen-
cies favors a transition from R–Oiv to S–R con-
trol, that is, progressive loss of sensitivity to de-
valuation in the extinction test.47 However, rats
with lesions to the DLS either pre- or posttrain-
ing fail to develop habitual control and remain
sensitive to devaluation irrespective of training,
indicating that the DLS is required for the acqui-
sition and expression habit learning.51,98,99 Impor-
tantly, posttraining inactivation of the DLS has also
been shown to abolish expression of habitual co-
caine seeking52 and alcohol seeking51 following ex-
tended training, rendering these behaviors once
again goal-directed, and confirming the common
neural mechanisms underpinning both natural and
drug reward habit learning. In addition, pretraining
functional disconnection of DLS and the amygdala
central nucleus (CN) has also recently been shown to
abolish habitual control of action and restore goal-
directed control.29 Finally, lesions of the infralim-
bic cortex made before instrumental training abol-
ish the transition to habit following overtraining.48
Thus, chronic drug exposure might act on any of
these regions to promote the dominance of S–R
Neural basis of specific transfer
of stimulus control
The ability of stimuli to transfer selective control
over separately trained instrumental responding
for the same outcome is abolished by pretrain-
ing62 and posttraining lesions of the orbitofrontal
cortex (OFC),100 by pretraining lesions and post-
training inactivation of the nucleus accumbens
(NAC) shell,101,102 by pretraining96,103,104 and post-
training91 lesions of the BLA, and pretrain-
ing functional disconnection between these two
Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences. 19
Abnormal learning underpinning dependence Hogarth et al.
structures.105 In addition, posttraining inactiva-
tion of the DMS106 and posttraining lesions of the
mediodorsal thalamus91 also eliminate the selec-
tive transfer effect. Thus, to impair specific trans-
fer, chronic drug exposure may act on any of these
Neural basis of general transfer
of stimulus control
The ability of conditioned stimuli to produce a gen-
eral excitatory effect on separately trained instru-
mental responses is abolished by posttraining inac-
tivation of the DLS,106 posttraining inactivation of
the ventral tegmental area (VTA),31,107pre- or post-
training inactivation of the NAC core,102,108 andpre-
training lesions of the amygdala CN.96 Thus, chronic
drug exposure may influence any of these regions to
enhance general transfer effects.
Synthesis of behavioral neuroscience
PL and medial dorsal thalamic lesions show a strik-
ing correspondence with chronic drug exposure
in producing behavioral autonomy. Specifically,
these lesions abolish acquisition but not expression
of goal-directed control,48,87–91 which matches ex-
actly the effect of chronic amphetamine54 (see also
Ref. 51 for related effect with alcohol). However, le-
sions to the PL do not modify the specific transfer
effect,88 but posttraining lesions of the mediodorsal
thalamus do,91 matching the impact of chronic am-
phetamine.74 Thus, lesions of the mediodorsal tha-
lamus produce precisely the same effect as chronic
drug exposure. It is also noteworthy that lesions
of the OFC abolish specific transfer,62,100 but not
outcome devaluation,100 indicating that damage at
this region alone could not produce the exact pat-
tern of chronic drug exposure. Thus, although the
effect of chronic drug exposure on transition to be-
havioral autonomy could be produced by a combi-
nation of PL and OFC damage—a view strength-
ened by the observation of hypofunction in these
regions in addicts109,110—damage to the mediodor-
sal thalamus alone could impair both forms of
behavior control, and so has the advantage of
To conclude, we propose that initial drug seeking
is goal-directed, tracks the anticipated value of the
drug (R–Oiv), and is responsive to specific transfer
(S–Oi–R) effects by drug cues. Chronic drug expo-
sure, however, impairs the capacity to retrieve or
utilization of the specific identity of outcomes, and
so produces a transition of behavioral control from
goal-directed learning (R–Oiv) and specific transfer
(S–Oi–R) to habit (S–R) and general transfer ([S–
Ov]–R). This transition occurs in relation to both
drug outcomes and natural reward outcome, result-
ing in a narrowing of the addict’s behavioral reper-
toire to general cue excitation of dominant S–R drug
habits, with restricted capacity for intentional selec-
tion of alternative actions. This associative frame-
work captures the cardinal diagnostic characteristics
of heightened drug reinforcement, loss of willed reg-
ulation of drug seeking, and restricted engagement
with alternative activities. Future research needs to
clarify precisely how this transition to autonomy is
accelerated by drugs of abuse compared to natural
rewards, whether by differences in reward value,50
kinetics,111 neuroadaptations,112,113 or neurotoxic-
ity114 and precisely how this alters the balance be-
tween corticostriatal circuits underpinning the four
There are several implications concerning treat-
ment strategy. Consistent with Tiffany’s7insight, we
have argued that goal-directed action and habit ex-
ist in a dynamic balance which may be additive,32
competitive,46 or hierarchical,45 but switching be-
tween the two modes apparently can occur within
the span of a single response sequence and/or lon-
gitudinally with training. If addiction does reflect
a progressive weakening of the role of outcome
retrieval/utilization in the execution of action se-
quences, allowing drug habits to dominate, then
treatments such as expectancy challenge116 and ex-
tinction training,117 which arguably work by chang-
ing the specific representation of the drug may not
provide the optimal strategy. Instead, treatments
that enhance the capacity to engage representations
of the future such as working memory training118
combined with provisions of alternative reward con-
tingencies119 may be more efficacious in redirect-
ing addicts from their established habits. Moreover,
given that capacity for goal-directed control can be
reinstated by manipulations of brain function48,51,52
and by uncertainty, which has definable neural sub-
strates,46 suggests that neuropharmacology could
complement such learning approaches to install new
intentional action choices.
20 Ann. N.Y. Acad. Sci. 1282 (2013) 12–24 c
2012 New York Academy of Sciences.
Hogarth et al. Abnormal learning underpinning dependence
This work was supported by MRC Grant #G0701456
to L.H., NHMRC Grant #633268 to B.B. and S.K.,
and NHMRC Grant #568872 to S.K. and B.B.
Conflicts of interest
The authors declare no conflicts of interest.
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... For example, an auditory stimulus (CS) that was paired with cocaine consumption could promote independently trained instrumental drug-seeking/drug-taking behaviors in rats (LeBlanc, Ostlund, & Maidment, 2012). This enhanced specific PIT effect could reflect a greater susceptibility to addiction-related cues, due to excessive incentive salience that has been endowed after repetitively paired with drugrelated rewards (Hogarth, Balleine, Corbit, & Killcross, 2013;Mahlberg et al., 2021). Moreover, PIT was also proposed to reflect the change in behavioral control (i.e., a shift from goal-directed to habitual behavior control) in addictions, however in human studies it is not clear yet how exactly specific and general PIT is related to goal-directed versus habitual behavior (Garbusow et al., 2022). ...
... The PIT effects thus indicate an impact of S on the R-O associations, only S could act differently in specific and general PIT effects. It was proposed that the specific PIT effects reflect that the Pavlovian stimulus has activated both the cue identity and its incentive value in the PIT transfer test and hence triggered a change in goal-directed control of behaviors (Hogarth et al., 2013;Mahlberg et al., 2021;Seabrooke, Hogarth, Edmunds, & Mitchell, 2019;Sebold et al., 2016). With prolonged use of drugs, the Pavlovian stimuli (S) lose the ability to trigger the specific identity of the drugs and instead retrieve only the affective value, leading to a shift from specific PIT to general PIT (Everitt & Robbins, 2016). ...
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Background and aims: The Pavlovian-to-instrumental transfer (PIT) effect is a phenomenon that Pavlovian conditioned cues that could influence one's instrumental behavior. In several substance and behavioral addictions, such as tobacco use disorder and gambling disorder, addiction-related cues could promote independently trained instrumental drug-seeking/drug-taking behaviors, indicating a specific PIT effect. However, it is unclear whether Internet gaming disorder (IGD) would show a similar change in PIT effects as other addictions. The study aimed to explore the specific PIT effects in IGD. Methods: We administrated a PIT task to individuals with IGD (n = 40) and matched health controls (HCs, n = 50), and compared the magnitude of specific PIT effects between the two groups. The severity of the IGD symptoms was assessed by the Chinese version 9-item Internet Gaming Disorder Scale (IGDS) and the Internet Addiction Test (IAT). Results: We found that: (1) related to the HCs group, the IGD group showed enhanced specific PITgame effects, where gaming-related cues lead to an increased choice rate of gaming-related responses; (2) in the IGD group, the magnitude of specific PITgame effects were positively correlated with IAT scores (rho = 0.39, p = 0.014). Discussion and conclusions: Individuals with IGD showed enhanced specific PIT effects related to HCs, which were associated with the severity of addictive symptoms. Our results highlighted the incentive salience of gaming-related cues in IGD.
... One explanation could be that gambling cues boost participants' impulsivity specifically when playing for bigger rewards (Miedl, Büchel, & Peters, 2014). Alternatively, this may be interpreted as an increased motivational effect of gambling cues on performance (Genauck et al., 2019), an effect also known as Pavlovian-instrumental transfer (Dickinson & Balleine, 1994), which is often considered as an important factor for the development of and relapse to addictive behavior in associative-learning models of addiction (Everitt & Robbins, 2015;Hogarth, Balleine, Corbit, & Killcross, 2013). However, no interaction between cue-reactivity and reward anticipation or any relation with craving was seen on a neural level. ...
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Background and aims Dysfunction of the striatum, a brain region part of the mesolimbic reward system, is a key characteristic of addictive disorders, but neuroimaging studies have reported conflicting findings. An integrative model of addiction points to the presence or absence of addiction-related cues as an explanation for hyper- or hypoactivation, respectively, of the striatum. Methods To test this model directly, we investigated striatal activation during monetary reward anticipation in the presence versus absence of addiction-related cues using functional MRI. Across two studies, we compared 46 alcohol use disorder (AUD) patients with 30 matched healthy controls; and 24 gambling disorder (GD) patients with 22 matched healthy controls. Results During monetary reward anticipation, hypoactivation of the reward system was seen in AUD individuals compared to HCs. Additionally, a behavioral interaction was seen where gambling cues made participants, across groups, respond faster for bigger, but slower for smaller rewards. However, no striatal differences were seen in response to addiction-related cues between AUD or GD patients and their matched controls. Finally, despite substantial individual differences in neural activity to cue-reactivity and reward anticipation, these measures did not correlate, suggesting that they contribute independently to addiction aetiology. Discussion and Conclusions Our findings replicate previous findings of blunted striatal activity during monetary reward anticipation in alcohol use disorder but do not support the idea that addiction-related cues explain striatal dysfunction as suggested by the model.
... Diversos estudios, como los de Aguilar et al. (2012), Hogarth et al. (2013), Levin (2011), Velásquez-Martínez y Ortiz (2014), resaltan la existencia de mecanismos biológicos de recompensa asociados al excesivo consumo de spa, que afectan directamente la inhibición de respuestas y el aprendizaje entre estímulo-respuesta; según los Centros de Integración Juvenil (2016), Oliveira et al. (2017), Volkow y Morales (2015), estos mecanismos involucran, entre las áreas cerebrales, el área tegmental ventral, el núcleo accumbens, las cortezas cingulada anterior, orbitofrontal y prefrontal medial, el sistema límbico, la amígdala, el tálamo, el hipocampo y el hipotálamo; además, de neurotransmisores, como la dopamina, la acetilcolina, el glutamato, el gaba y la noradrenalina. Diversas investigaciones (Blum et al., 2012;León-Regal et al., 2014;Oliveira et al., 2017;Pinel, 2007;Uhl et al., 2019) reiteran que el sistema dopaminérgico mesotelencefálico es responsable de los mecanismos neuroadaptativos; con relación a los reforzadores condicionados, estos reforzadores se presentan en la vía mesolímbica, asociados al placer y la satisfacción que se experimenta a partir de las circunstancias y los estímulos, considerándolos como necesarios biológicamente, debido a su gratificación (Chamizo y Rivera, 2012;oms, 2005); lo cual lleva a la repetición de ciertas actuaciones, como el consumo de spa, propiciando conductas adictivas; y a desequilibrios asociados a la actividad cognitivo-comportamental. ...
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Este estudio tuvo como propósito caracterizar el comportamiento y los estados de ánimo de consumidores de sustancias psicoactivas en comparación con no consumidores, identificando la relación existente entre los estados de ánimo, la conducta suicida, la violencia y los comportamientos agresivos. Se formuló como una investigación transversal, de enfoque cuantitativo y con un diseño de análisis comparativo-correlacional. La selección de la muestra se realizó por modelo no probabilístico. Participaron 4237 personas, entre consumidores y no consumidores de sustancias psicoactivas (spa) (ilegales). Se emplearon los inventarios de ansiedad y de depresión de Beck, una escala de valoración subjetiva del estado de ánimo, y el registro de una historia socioclínica. Se halló relación entre el consumo de sustancias psicoactivas y la presencia de comportamientos negativos característicos de agresividad, e ideación y conductas suicidas. Sin embargo, los consumidores han sufrido menos bullying escolar y laboral. Asimismo, los consumidores de sustancias psicoactivas atribuyen, por autopercepción, mayores niveles de ansiedad y depresión, a sus estados de ánimo, en relación con los no consumidores. Se encontró coherencia con la presencia objetiva de sintomatología característica de ansiedad y depresión; reconociendo acertadamente sus estados de ánimo. Usuarios de spa suelen consumir en mayor medida medicamentos para el control del sueño y los estados de ánimo, y asisten con más frecuencia a consulta psicológica.
... For example, as noted previously, general transfer is thought to underlie maladaptive behavioural responding in various psychiatric conditions, such as stress and anxiety (Pool et al., 2015;Quail et al., 2017), drug addiction (Belin et al., 2009;Hogarth et al., 2013;Ostlund et al., 2014), alcohol use disorder Garbusow et al., 2016), and bipolar disorder (Hallquist et al., 2018). Given our conclusion that BNST mediates general transfer and possibly regulates instrumental motivation, there should be evidence indicating that the BNST plays a role in these same conditions. ...
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We review recent studies assessing the role of the bed nucleus of the stria terminalis (BNST) in the motivational control of instrumental conditioning. This evidence suggests that the BNST and central nucleus of the amygdala (CeA) form a circuit that modulates the ventral tegmental area (VTA) input to the nucleus accumbens core (NAc core) to control the influence of Pavlovian cues on instrumental performance. In support of these claims, we found that activity in the oval region of BNST was increased by instrumental conditioning, as indexed by phosphorylated ERK activity (Experiment 1), but that this increase was not due to exposure to the instrumental contingency or to the instrumental outcome per se (Experiment 2). Instead, BNST activity was most significantly incremented in a test conducted when the instrumental outcome was anticipated but not delivered, suggesting a role for BNST in the motivational effects of anticipated outcomes on instrumental performance. To test this claim, we examined the effect of NMDA-induced cell body lesions of the BNST on general Pavlovian-to-instrumental transfer (Experiment 3). These lesions had no effect on instrumental performance or on conditioned responding during Pavlovian conditioning to either an excitory conditioned stimulus (CS) or a neutral CS (CS0) but significantly attenuated the excitatory effect of the Pavlovian CS on instrumental performance. These data are consistent with the claim that the BNST mediates the general excitatory influence of Pavlovian cues on instrumental performance and suggest BNST activity may be central to CeA-BNST modulation of a VTA-NAc core circuit in incentive motivation.
... Understanding the behaviors being measured is of clear importance. The most prominent models of addiction take a behavioral neuroscience perspective (Berridge & Robinson, 2016;Hogarth, Balleine, Corbit, & Killcross, 2013) grounded in learning, reinforcement and conditioning, and so an analysis of the behaviors reinforcing smartphone addiction is long overdue. The mechanisms underpinning many behavioral addictions are poorly understood , but are crucial to prominent models of these candidate disorders (Brand et al., 2019). ...
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It has been claimed that smartphone usage constitutes a behavioral addiction, characterised by compulsive, excessive use of one’s phone and psychological withdrawal or distress when the phone is absent. However, there is uncertainty about key phenomenological and conceptual details of smartphone addiction. One of the central problems has been understanding the processes that link smartphone usage, and addiction. The question this paper aims to answer is straightforward: based on measures utilised in the literature, what does ‘behavior’ mean in the context of smartphone addiction? As part of a larger project, a scoping review of the smartphone addiction literature was undertaken. This identified 1305 studies collecting smartphone addiction data. Just under half (49.89%) of all published smartphone addiction papers did not report the collection of any smartphone specific behaviors. Those that did tended to focus on a small cluster of self-reported behaviors capturing volume of overall use: hours spent using a smartphone per day, number of pickups, duration of smartphone ownership, and types of app used. Approximately 10% of papers used logged behavioral data on phones. Although the theoretical literature places increasing focus on context and patterns of use, measurements of behavior tend to focus on broad, volumetric measures. The number of studies reporting behavior has decreased over time, suggesting smartphone addiction is becoming increasingly trait-like. Both major phone operating systems have proprietary apps that collected behavioral data by default, and research in the field should take advantage of these capabilities when measuring smartphone usage.
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Short video indulgence refers to an individual’s compulsive and uncontrollable consumption of short videos, leading to significant behavioral or attention impairments, and subsequently causing difficulties in interpersonal relationships, learning, and/or work adaptation. With the continuous expansion of the short video user base and the trend towards younger groups, threats of short video indulgence to users’ physical and mental health have aroused extensive attention. From a human-computer interaction perspective, we synthesized and delineated the relevant factors contributing to the occurrence of short video indulgence. The objective is to formulate a comprehensive framework delineating the intricate mechanism that underpins the phenomenon of short video indulgence, thereby shedding light on the intricacies involved in its developmental process. At first, in order to explore the delineation between short video usage and indulgence, we categorized short video usage into “instrumental” and “ritualistic” forms. Instrumental usage refers to user behavior driven by specific goals or needs, where short videos serve as tools or means to achieve particular objectives. Ritualistic usage refers to user behavior without a specific objective, where short videos become habitual behaviors associated with particular contexts, times, or situations. The transition from conventional utilization of short videos to the state of short video indulgence appears to encompass a notable shift in usage behavior, evolving from a utilitarian “instrumental” function to a more “ritualistic” engagement. After that, the present work formulates a conceptual framework delineating the mechanisms underlying the onset of short video indulgence, delving into the domains of human-computer interaction and susceptibility traits. The first section encompasses four facets: information technology, content provision, human-computer interaction, and user experience. Their salient characteristics encompass technological advancement, content richness, interactive efficiency, and user immersion. Furthermore, propelled by recommendation algorithms, users’ engagement with short videos becomes increasingly fortified. The second section systematically expounds the susceptibility factors contributing to short video indulgence. The four categories of unique susceptibility traits align with the four stages of interactive mechanisms, while the categories represented by common susceptibility traits have an inducing effect on general addictive behaviors. Considering the analogous nature of short video indulgence to general online indulgence, the unique and common susceptibility traits exhibit mutual intersection and overlap. Overall, the role of interactive mechanisms lies in arousing susceptibility traits, rendering individuals more susceptible to allure and ensnarement in a cycle of addictive behaviors. Simultaneously, susceptibility traits amplify users’ responsiveness and vulnerability to inducing factors. The multifaceted components within the realm of human-computer interaction, propelled by recommendation algorithms, intricately intertwine with users’ susceptibility traits, driving the transformation of users’ engagement with short videos from an “instrumental” to a “ritualistic” approach, ultimately leading to the emergence of short video indulgence. This framework seeks to illuminate the genesis and progression of short video indulgence, offering researchers in this domain a comprehensive conceptual structure to foster the scientific governance of short video indulgence. Subsequently, in order to achieve a deeper understanding of the mechanism behind short video indulgence, we offered theoretical interpretations of short video indulgence from cognitive, emotional, motivational, and social perspectives. The dual process theory, opponent process theory, uses and gratifications theory and social shaping of technology theory were employed to elucidate the process of short video indulgence formation. Finally, this study concludes by summarizing the existing shortcomings in the current field of research. The points are concluded as follows: 1)The research methods are limited, there should be a diversification of research perspectives; 2)Insufficient attention to technology emphasizes the need to emphasize improvements in technology that contribute to addiction; 3)The mechanism of formation is unclear, there should be a deepening of the research into the mechanisms of occurrence; 4)Inadequate research on user characteristics highlights the need to focus on susceptibility factor studies. Keywords: Short Video Indulgence, Human-Computer Interaction, Instrumental Use, Ritual Use, Algorithmic Closed Loop
Aims: By performing three transcranial magnetic stimulation (TMS) experiments, we measured the motor-specific modulatory mechanisms in the primary motor cortex (M1) at both the intercortical and intracortical levels when smokers actively approach or avoid smoking-related cues. Design, Setting and Participants: For all experiments, the design was group (smokers versus non-smokers) × action (approach versus avoidance) × image type (neutral versus smoking-related). The study was conducted at the Shanghai University of Sport, CHN, TMS Laboratory. For experiment 1, 30 non-smokers and 30 smokers; for experiment 2, 16 non-smokers and 16 smokers; for experiment 3, 16 non-smokers and 16 smokers. Measurements: For all experiments, the reaction times were measured using the smok- ing stimulus–response compatibility task. While performing the task, single-pulse TMS was applied to the M1 in experiment 1 to measure the excitability of the corticospinal pathways, and paired-pulse TMS was applied to the M1 in experiments 2 and 3 to mea- sure the activity of intracortical facilitation (ICF) and short-interval intracortical inhibition (SICI) circuits, respectively. Findings: Smokers had faster responses when approaching smoking-related cues (F1,58 = 36.660, P < 0.001, ηp2 = 0.387), accompanied by higher excitability of the corti- cospinal pathways (F1,58 = 10.980, P = 0.002, ηp2 = 0.159) and ICF circuits (F1,30 = 22.187, P<0.001, ηp2=0.425), while stronger SICI effects were observed when they avoided these cues (F1,30 = 10.672, P = 0.003, ηp2 = 0.262). Conclusions: Smokers appear to have shorter reaction times, higher motor-evoked potentials and stronger intracortical facilitation effects when performing approach responses to smoking-related cues and longer reaction times, a lower primary motor cortex descending pathway excitability and a stronger short-interval intracortical inhibition effect when avoiding them.
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Adolescence is a developmental period that encompasses, but is not limited to, puberty and continues into early adulthood. During this period, maturation and refinement are observed across brain regions such as the prefrontal cortex (PFC), which is critical for cognitive function. Adolescence is also a time when excessive alcohol consumption in the form of binge drinking peaks, increasing the risk of long-term cognitive deficits and the risk of developing an alcohol use disorder later in life. Animal models have revealed that adolescent ethanol (EtOH) exposure results in protracted disruption of neuronal function and performance on PFC-dependent tasks that require higher-order decision-making. However, the role of astrocytes in EtOH-induced disruption of prefrontal cortex-dependent function has yet to be elucidated. Astrocytes have complex morphologies with an extensive network of peripheral astrocyte processes (PAPs) that ensheathe pre- and postsynaptic terminals to form the ‘tripartite synapse.’ At the tripartite synapse, astrocytes play several critical roles, including synaptic maintenance, dendritic spine maturation, and neurotransmitter clearance through proximity-dependent interactions. Here, we investigate the effects of adolescent binge EtOH exposure on astrocyte morphology, PAP-synaptic proximity, synaptic stabilization proteins, and dendritic spine morphology in subregions of the PFC that are important in the emergence of higher cognitive function. We found that adolescent binge EtOH exposure resulted in subregion specific changes in astrocyte morphology and astrocyte-neuronal interactions. While this did not correspond to a loss of astrocytes, synapses, or dendritic spines, there was a corresponding region-specific and EtOH-dependent shift in dendritic spine phenotype. Lastly, we found that changes in astrocyte-neuronal interactions were not a consequence of changes in the expression of key synaptic structural proteins neurexin, neuroligin 1, or neuroligin 3. These data demonstrate that adolescent EtOH exposure results in enduring effects on neuron-glia interactions that persist into adulthood in a subregion-specific PFC manner, suggesting selective vulnerability. Further work is necessary to understand the functional and behavioral implications.
An overview of today's diverse theoretical and methodological approaches to action and the relationship of action and cognition. The emerging field of action science is characterized by a diversity of theoretical and methodological approaches that share the basic functional belief that evolution has optimized cognitive systems to serve the demands of action. This book brings together the constitutive approaches of action science in a single source, covering the relation of action to such cognitive functions as perception, attention, memory, and volition. Each chapter offers a tutorial-like description of a major line of inquiry, written by a leading scientist in the field. Taken together, the chapters reflect a dynamic and rapidly growing field and provide a forum for comparison and possible integration of approaches. After discussing core questions about how actions are controlled and learned, the book considers ecological approaches to action science; neurocogntive approaches to action understanding and attention; developmental approaches to action science; social actions, including imitation and joint action; and the relationships between action and the conceptual system (grounded cognition) and between volition and action. An emerging discipline depends on a rich and multifaceted supply of theoretical and methodological approaches. The diversity of perspectives offered in this book will serve as a guide for future explorations in action science. ContributorsLawrence W. Barsalou, Miriam Beisert, Valerian Chambon, Thomas Goschke, Patrick Haggard, Arvid Herwig, Herbert Heuer, Cecilia Heyes, Bernhard Hommel, Glyn W. Humphreys, Richard B. Ivry, Markus Kiefer, Günther Knoblich, Sally A. Linkenauger, Janeen D. Loehr, Peter J. Marshall, Andrew N. Meltzoff, Wolfgang Prinz, Dennis R. Proffitt, Giacomo Rizzolatti, David A. Rosenbaum, Natalie Sebanz, Corrado Sinigaglia, Sandra Sülzenbrück, Jordan A. Taylor, Michael T. Turvey, Claes von Hofsten, Rebecca A. Williamson
This review applies some new experimental findings and theoretical ideas about how reinforcers act on the neural mechanisms of learning and memory to the problem of how addictive drugs affect behaviour. A basic assumption of this analysis is that all changes in behaviour, including those involved in drug addiction and the initiation of drug self-administration, require the storage of new information in the nervous system. Animal studies suggest that such information is processed in several (this review deals with three) more or less independent learning and memory systems in the mammalian brain. Reinforcers can interact with these systems in three ways: they activate neural substrates of observable approach or escape responses, they produce unobservable internal states that can be perceived as rewarding or aversive, and they modulate or enhance the information stored in each of the memory systems. It is suggested that each addictive drug maintains its own self-administration by mimicking some subset of these actions. Evidence supporting the notion of multiple memory systems and data on the actions of several drugs (amphetamine, cocaine, nicotine, alcohol and morphine) on these systems are briefly reviewed. The utility of the concept of ''reward'' for understanding the effects of drugs on behaviour is discussed. Evidence demonstrating actions of drugs on multiple neural substrates of reinforcement suggests that no single factor is likely to explain either addictive behaviour in general or self-administration in particular. Some of the findings on the development and maintenance of self-administration by animals of the five exemplar drugs are discussed in the context of these ideas.
Outcome Expectancies and Efficacy ExpectationsConclusions References
This paper presents a biopsychological theory of drug addiction, the 'Incentive-Sensitization Theory'. The theory addresses three fundamental questions. The first is: why do addicts crave drugs? That is, what is the psychological and neurobiological basis of drug craving? The second is: why does drug craving persist even after long periods of abstinence? The third is whether 'wanting' drugs (drug craving) is attributable to 'liking' drugs (to the subjective pleasurable effects of drugs)? The theory posits the following. (1) Addictive drugs share the ability to enhance mesotelencephalic dopamine neurotransmission. (2) One psychological function of this neural system is to attribute 'incentive salience' to the perception and mental representation of events associated with activation of the system. Incentive salience is a psychological process that transforms the perception of stimuli, imbuing them with salience, making them attractive, 'wanted', incentive stimuli. (3) In some individuals the repeated use of addictive drugs produces incremental neuroadaptations in this neural system, rendering it increasingly and perhaps permanently, hypersensitive ('sensitized') to drugs and drug-associated stimuli. The sensitization of dopamine systems is gated by associative learning, which causes excessive incentive salience to be attributed to the act of drug taking and to stimuli associated with drug taking. It is specifically the sensitization of incentive salience, therefore, that transforms ordinary 'wanting' into excessive drug craving. (4) It is further proposed that sensitization of the neural systems responsible for incentive salience ('for wanting') can occur independently of changes in neural systems that mediate the subjective pleasurable effects of drugs (drug 'liking') and of neural systems that mediate withdrawal. Thus, sensitization of incentive salience can produce addictive behavior (compulsive drug seeking and drug taking) even if the expectation of drug pleasure or the aversive properties of withdrawal are diminished and even in the face of strong disincentives, including the loss of reputation, job, home and family. We review evidence for this view of addiction and discuss its implications for understanding the psychology and neurobiology of addiction.