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Loss-chasing in gambling behaviour: neurocognitive and behavioural economic perspectives
Ke Zhang and Luke Clark
Centre for Gambling Research at UBC, Department of Psychology, University of British
Columbia, Vancouver, Canada.
Address for correspondence: Dr Luke Clark, Centre for Gambling Research at UBC, Department
of Psychology, University of British Columbia, 2136 West Mall, Vancouver, British Columbia,
Canada V6T 1Z4. E-mail: luke.clark@psych.ubc.ca
This is an Author Accepted Manuscript. This paper is not the copy of record and may not exactly
replicate the final, authoritative version of the article. Please do not copy or cite without authors'
permission. The final article will be available, upon publication, as: Zhang K and Clark L (2020)
Loss-chasing in gambling behaviour: neurocognitive and behavioural economic perspectives.
Current Opinion in Behavioral Sciences, 31: 1-7. DOI
https://doi.org/10.1016/j.cobeha.2019.10.006
Funding and Disclosures
Luke Clark is the Director of the Centre for Gambling Research at UBC, which is supported by
funding from the Province of British Columbia and the British Columbia Lottery Corporation
(BCLC), a Canadian Crown Corporation. The BCLC and BC Government impose no constraints
on publishing. LC has received travel honoraria/reimbursements from the National Association
for Gambling Studies (Australia) and National Center for Responsible Gaming (US), and
honoraria for academic services from the National Center for Responsible Gaming (US) and
Gambling Research Exchange Ontario (Canada). He has not received any further direct or
indirect payments from the gambling industry or groups substantially funded by gambling. He
has received royalties from Cambridge Cognition Ltd. relating to neurocognitive testing. KZ
report no conflicts of interest.
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This work was supported by the Centre for Gambling Research at UBC core funding from the
Province of British Columbia and the British Columbia Lottery Corporation (BCLC). LC
receives funding from the Natural Sciences and Engineering Research Council (Canada) and the
BC Ministry of Finance. KZ received a Faculty of Arts Graduate Award from UBC.
Abstract
Loss-chasing describes the tendency of a gambler to amplify their betting in an effort to recoup
prior losses. It is widely regarded as a defining feature of disordered gambling, and a hallmark of
the transition from recreational to disordered gambling. We consider the empirical evidence for
this central role of loss-chasing to disordered gambling. We highlight multiple behavioural
expressions of chasing, including between-session and within-session chasing. From a
neurocognitive perspective, loss-chasing could arise from compromised executive functions
including inhibitory control, mood-related impulsivity (urgency) and compulsivity, for which
there is compelling evidence in disordered gambling. This view is contrasted with a behavioural
economic perspective that emphasizes the subjective valuation of outcomes to the gambler, and
may better account for nuances in the gamblers’ complex response to loss, such as the
significance of ‘breaking even’. Neuroimaging and psychopharmacological research on loss-
chasing may help to arbitrate between these two perspectives.
Keywords: gambling, addiction, risk-taking, impulsivity, reference points, urgency.
Highlights (3 x 85 characters):
Chasing is a sensitive symptom of disordered gambling with multiple expressions.
Neurocognitive constructs of negative urgency and compulsivity may underlie chasing.
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Behavioral economic constructs of loss-aversion and re-referencing may also contribute.
Introduction
Gambling has undergone steady expansion in recent decades, with advances in modern slot
machine design (1), online accessibility of gambling (2), and gambling marketing (3), to name
just three examples. Although the majority of gamblers bet within their means, international
estimates are that 0.1% - 5.8% of individuals display gambling problems (4). Negative
expectancy (‘house edge’) is an inherent aspect of modern commercial gambling, meaning that
continued gambling will inexorably result in financial losses. Understanding why some gamblers
continue to bet in the face of such losses is a central challenge in psychological research on
gambling. Phenomenological descriptions have traditionally highlighted loss-chasing as a
defining feature of problem gambling (5–8). The first objective of the current article is to
evaluate empirical research on this ‘centrality’ of loss-chasing. We will then consider two
approaches to understanding loss-chasing: a neurocognitive perspective that emphasizes fronto-
striatal circuitry regulating inhibition and compulsivity, and a behavioural economic perspective
that emphasizes the subjective valuation of losses to the gambler. Lastly, we consider
neuroimaging and psychopharmacological research on loss-chasing that may help to arbitrate
between these perspectives.
The Centrality of Loss-Chasing in Problem Gambling
Qualitative descriptions of disordered gambling describe how loss-chasing establishes and
maintains a downward spiral of negative consequences for the gambler’s finances, relationships,
and mental wellbeing (5). Loss-chasing is often the most commonly endorsed item in screening
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tools for disordered gambling (9). It was endorsed by 60% of gamblers who met one diagnostic
criteria, and 80% of gamblers who met 3-4 criteria (10). Chasing is also central to dominant
theoretical approaches to disordered gambling. The Pathways Model (11) is best known as a
framework for characterizing subtypes of problem gamblers, but in fact pathway 1 is posited as
a common pathway shared by all disordered gamblers, moving from gambling exposure,
through conditioning of arousal/excitement, to habitual and harmful gambling. In this common
pathway, chasing is the ‘conduit’ from learning-based processes to the negative financial
consequences.
It is important to recognize that loss-chasing can be expressed behaviourally in multiple distinct
ways (12). The wording of diagnostic items typically asks if the gambler returns another day to
recoup past losses. This between-session chasing was evident in female college athletes, in
whom it appeared to be the best discriminator between social and problem gambling (13).
Chasing can also be demonstrated within a gambling session, and in multiple ways. In laboratory
studies, individual differences in disordered gambling severity predicted persistent gambling; for
example on a simulated slot machine (14–16). Besides persistence, chasing can also be expressed
in the amount bet. For example, on a roulette task with 50/50 red/black predictions, bet size
increased on longer losing streaks, but did not change across winning streaks, which was again
interpreted as an expression of loss-chasing (17).
A Neurocognitive Perspective on Loss-Chasing
Disordered gambling is associated with altered executive functions, subserved by fronto-striatal
brain circuitry (18,19). Inhibition is a core component of the executive functions, and by a simple
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account, loss-chasing could arise from impaired inhibition, giving rise to impulsivity as the
tendency to make rapid, hasty gambling decisions in pursuit of winning. In a meta-analysis of
case-control studies assessing impulsivity in disordered gambling, moderate-to-large effect sizes
were seen on the stop signal task as the best validated assay of motor inhibition (20). The stop
signal reaction time was also sensitive to gambling severity, in a cross-sectional study assessing
non-problem, at-risk, and disordered gamblers (21). Another widely used test of impulsivity -
delay discounting, is also sensitive problem gambling severity, and could further contribute to
the temporal short-sightedness of chasing decisions (22).
In conceptualizing loss-chasing as impaired inhibition, one consideration is how losing contexts
could amplify this impairment. Psychometric research on impulsivity identifies an affect-related
component, termed urgency, as one of the most robust group differences across addictive
disorders, including gambling disorder (23,24). Negative urgency in particular may provide a
feedback mechanism in substance addictions, by which the negative affect associated with drug
withdrawal can fuel impulsive drug-seeking (25). This effect was evident in heavy alcohol
drinkers with higher negative urgency, who were more emotionally reactive to stressful events
and showed greater subsequent alcohol demand (26). Loss-chasing may be a logical counterpart
to this effect in gambling addiction, by which the negative emotions arising from gambling
losses fuel impulsive escalation of gambling. In support of this hypothesis, induced negative
mood states in recreational gamblers increased slot machine persistence (27). In a translational
model of urgency in healthy humans and rats, reward omission increased frustration and
persistent behaviour (28). Refinement of these procedures to incorporate more realistic gambling
stimuli/outcomes may be fruitful line of enquiry. These motivational expressions of chasing can
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also be captured on latency measures: Verbruggen and colleagues (29) investigated how prior
gains and losses affected the initiation latencies of gambling choices. By including a safe option
as a neutral baseline, they showed that losses prompted faster, more impulsive responding on the
next trial (29).
With persistence as its central feature, chasing may alternatively be conceptualized as a case of
compulsivity. Cognitive-behavioural research on compulsivity is relatively new compared to
models of impulsivity, but emphasizes the repetition of behaviour in a way that is insensitive to
negative consequences (30,31). Addiction experts identified seven neurocognitive constructs as
central to addictive disorders; compulsivity was the only ‘expert-initiated’ construct that was not
present within the NIH Research Domain Criteria (RDoC) (32). Yet its behavioural assessment
remains controversial. One framework separates four types of neurocognitive procedures:
contingency-based cognitive flexibility, attentional set-shifting, attentional bias, and habit
learning (30).The flexibility and set-shifting components here relate to the ‘shifting’ dimension
of executive functions (33). A systematic review and meta-analysis of these domains in gambling
disorder identified deficits in the first three domains, but no studies were identified that tested
validated probes of habit learning (34). Habit formation has a central role in the Pathways Model
of disordered gambling (11), and is perhaps especially relevant to continuous forms of gambling
such as modern slot machines. At the same time, recent work highlights the inadequacies of
current behavioural assays of habit in human subjects (35) and lack of expected group
differences in treatment-seeking drug user(36).
Behavioural Economics and Loss-Chasing
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According to Prospect Theory, choice is guided by a value function that relates objective gains
and losses to their subjective value to the person (37). The value function (Figure 1) has three
key characteristics, which may contribute to loss-chasing in a number of ways. First, the S-shape
displays diminishing sensitivity to accumulating outcomes. Second, the loss function is steeper
than the gain function, accounting for loss aversion: losses typically ‘loom larger’ than
equivalently-sized gains (e.g. 38). Third, gain and loss prospects are evaluated relative to a
reference point, which is relevant in the context of a series of gambles: to what extent does the
individual update their reference point between each gamble?
Empirical studies of the value function in disordered gambling have focused primarily on loss
aversion (39–43). Two studies (39,40) support an intuitive prediction that disordered gamblers
have reduced loss aversion relative to healthy controls. However, another study found that loss
aversion was bimodally distributed in disordered gamblers (43), and other studies related these
individual differences to treatment duration (41) or preferences for strategic vs non-strategic
games (42).
Chasing may be related to a gambler’s capacity to re-reference between successive gambles.
Imas (44) compared risky betting in healthy participants under two conditions, termed ‘paper
losses’ and ‘realized losses’. The paper loss condition displayed the participant’s earnings as an
account balance, and in this condition, bet size increased in response to losing feedback. If the
losses were realized by the transfer of money (either physically or imagined) between gambles,
this loss-chasing effect was abolished, which Imas (44) attributed to re-referencing. Future work
can usefully investigate whether regular and problem gamblers also benefit from financial re-
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referencing, and how in-game mechanics can promote such effects (see also 45).
Figure 1: Consider two successive gambles, both offering a 50% probability of winning $10 and 50%
probability losing $10. The first gamble is accepted and the outcome is the $10 loss. In making the
decision for the second gamble could re-reference back to the origin (𝑅); this may bias risk avoidance
because the steepest part of the loss function is at 𝑅. Alternatively, the gambler may not update their
reference point, evaluating the second gamble from 𝑅. This may bias the gambler towards risk-taking,
due to diminishing sensitivity of losses at 𝑅. Hypothetically, gamblers could also partially update their
reference point to an intermediate point between 𝑅 and 𝑅.
A further development in gambling research is ‘behavioural tracking’ of account-based data,
either from online gambling platforms or casino loyalty card data (2). This ‘big data’ has the
advantage of being field data, from gamblers using their own funds. In one study, gamblers who
later closed their accounts displayed increased losses and increasing bet size in the days prior to
closure, a possible sign of chasing (46). But their increased bets appeared to be seen on less risky
gambles; such ‘strategic’ adjustment in betting style is arguably hard to reconcile with lower-
level executive dysfunction emphasized by the neurocognitive perspective. Another longitudinal
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analysis of data from the same gambling operator (bwin.com) looked at trends in weekly betting
as a function of profits and losses (47). On average, online gamblers increased their betting as a
function of the long-term loss (i.e. since the start of the data window), but simultaneously,
betting decreased in proportion to recent losses over the prior week. A similar effect was
observed in a field study in casino gamblers: on sessions following large losses (>1000 Swiss
Francs), the overall pattern was for patrons to reduce wagering on the following visit (48). It is
unclear to what extent these patterns reflect recreational versus disordered gambling, but these
studies highlight once again the complex response to losses among gamblers.
Neurobiological Correlates of Loss-Chasing
Neuroimaging and psychopharmacological studies may help to arbitrate between these two
perspectives. If the neural substrates of chasing behaviour indicate underactivity of prefrontal
control systems associated with generalized disinhibition and persistence, this would support the
neurocognitive perspective. If chasing were related to brain systems implicated in outcome
processing, and displayed sensitivity to subjective value and reference points, this would support
the behavioural economic stance. Certainly, a number of studies have tested reward signalling in
disordered gamblers using variants of the Monetary Incentive Delay Task (MIDT; see 49). A
meta-analysis of MIDT studies in gambling disorder found reduced striatal signalling to reward
anticipation cues (50). Perhaps surprisingly - given the recognition of loss-chasing in the
diagnosis - fewer studies have examined neural responses to anticipated and delivered loss in
gamblers. There is some psychophysiological evidence that dysregulation in gambling disorder is
predominantly gain-related, with no alterations in aversive threat processing (51). Nevertheless,
using fMRI, Balodis et al., (52) found that individuals with gambling disorder showed reduced
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activity in medial prefrontal cortex and striatum during both anticipation and receipt of loss
outcomes. In another study, the response to loss avoidance was decreased in disordered gamblers
in the same brain regions, but the response to loss anticipation was actually increased (53).
Striatal hyper-activity to loss anticipation was also seen in a further experiment, in which loss-
related activity in the anterior insula also correlated positively with gambling severity (54).
A series of imaging and psychopharmacological studies by Rogers and colleagues used a double-
or-quits (‘Martingale’) task to operationalize chasing decisions more directly. Participants
receive an initial loss, and then make a series of choices to either accept that loss or take a
gamble to recover the loss, with a risk of doubling its value (55,56). In a proof of principle study
in healthy participants, quitting decisions resulted in large cortical activation including anterior
insula, dorsal anterior cingulate cortex, and parietal cortex (55), while chase decisions yielded a
more focal response in ventromedial prefrontal cortex and subgenual anterior cingulate cortex,
which typically represent subjective reward value. A later study compared these responses in
gambling disorder and healthy control groups, and included a third group with cocaine
dependence (56). There were no group differences in the medial frontal network on quit
decisions, but in the response to the loss preceding decision, medial prefrontal activity was
heightened in the gambling disorder group on sequences that were ultimately quit, highlighting
the high cognitive-emotional demands that these decisions entail (56).
Other studies in gambling disorder have examined the neural circuitry that underpins cognitive
flexibility, centring on the lateral prefrontal cortex (57,58). Using a probabilistic reversal
learning task, Verdejo-Garcia et al., (58) compared groups with gambling disorder, healthy
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controls, and cocaine dependence. The three groups performed similarly on a task that was
optimized for neuroimaging, but the gamblers and cocaine users displayed reduced activation in
ventrolateral prefrontal cortex during the critical contingency reversals. Notably, brain
stimulation techniques including transcranial direct current stimulation (tDCS) may be able to
enhance lateral prefrontal cortical function, with recent evidence for improvements in cognitive
flexibility in a group with gambling disorder on the Wisconsin Card Sort Task (59).
At a neurochemical level, dopamine and serotonin transmission has been reliably implicated in
loss-chasing. Using the double-or-quits task in healthy participants, a dietary serotonin depletion
reduced the overall number of chase decisions (60). This finding merges with the extensive pre-
clinical literature on the role of serotonin in punishment-induced inhibition (61–63), such that a
serotonin imbalance could conceivably result in punishment-induced disinhibition as a mechanism
for loss-chasing. In convergent evidence from a genotyping study using a serotonin polygenic
score, genetic influences on serotonin transmission were associated with alcohol problems via trait
negative urgency (64). Meanwhile, psychopharmacological challenge studies with dopamine
agents (methylphenidate, pramipexole) indicate a complementary role, as a function of the value
of the loss being chased. According to ‘escalation of commitment’ (65), participants may chase an
inconsequential loss but typically become more cautious at larger stakes; enhancing dopamine
transmission attenuated this effect (60,66). A rodent model of the loss-chasing task provided
further details on receptor subtypes and anatomical localization. Decisions to quit were modulated
by 5-HT1A drug (8-OH-DPAT) (67) but not a 5-HT2A receptor antagonist (68), and the 5-HT1A
agent affected chasing in opposite directions when injected into anterior insular versus
orbitofrontal cortex (68). For dopamine, the D2 receptor drug eticlopride reduced chase decisions
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while a D1 agent (SCH23390) did not influence loss-chasing (67).
Discussion
The present article compared loss-chasing from the perspectives of a neurocognitive approach,
emphasizing inhibition, compulsivity, and negative urgency, and a behavioural economic
approach that emphasizes individual differences in aspects of the value function. In terms of
established neurocognitive case-control differences in disordered gambling, there is a strong
support for the former approach, although this ‘low level’ perspective remains under-specified in
describing how chasing behaviours emerge under losing contexts. In reviewing both behavioural
and neuroimaging evidence for the effects of losses in people with gambling problems, there is
evidence for both hypo and hyper reactivity, which mirror the phenomenological question as to
whether people with disordered gambling are fundamentally less affected by losing (providing a
simple explanation for why they persist in such risky behaviour), or whether chasing is better
conceptualized as a sensitization of loss-related processing. We argue that the behavioural
economic perspective provides some insights into the nuances of this loss response; for example,
in describing the asymmetry of loss-aversion. Reference point updating may also be very
relevant to chasing, both in terms of individual differences in the tendency to update, and
features of the game environment that encourage re-referencing; these effects could explain the
significance of breaking even for gamblers who chase (48). Currently, there is limited research
looking to characterize these effects in people with gambling disorder, and there is an added
methodological challenge of designing gambling tasks that can isolate multiple components of
Prospect Theory simultaneously. We note that the neurocognitive and behavioural economic
accounts are not mutually exclusive, and in fact have much to be gained from integration. The
translational studies of the double-or-quits task offer a case in point, and future research could
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manipulate subjective value in paradigms used to probe negative urgency or habit learning. The
unresolved question here is whether chasing is best considered as a series of independently-
triggered impulsive decisions, perhaps of escalating intensity and desperation, or rather as a
‘batch’ of compulsive responses that is issued without reflection upon individual choices or
outcomes (i.e. re-referencing). The nature of free choice is a fundamental question in addictive
disorders (69) and understanding these mechanisms will also shape our understanding of
substance addictions and other candidate behavioural addictions.
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