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Transcript of Unmasking Losses Disguised as Wins During Slot Machine ... et al(2012... · 2010). LDWs occur on...
Unmasking Losses Disguised as Wins During Slot Machine
Play Enhances the Feedback-Related Negativity Typically
Associated With Losses
Report to the Ontario Problem Gambling Research Centre
Michelle Jaricka,b,*, Mike J. Dixona,b, Kevin A. Harriganb, and Candice Jensena,b
aDepartment of Psychology, University of Waterloo, Ontario, Canada
bGambling Research Laboratory, University of Waterloo, Ontario, Canada
March, 2012
A manuscript version of this report was submitted for publication in International
Journal of Gambling Studies on March 8, 2012.
2
Table of Contents
Table of Contents .................................................................................................... 2
List of Figures …..................................................................................................... 3
Executive Summary………...….............................................................................. 4
Introduction….......................................................................................................... 5
Method …................................................................................................................ 7
Participants ………...................................................................................... 7
Apparatus and Procedures ……................................................................... 7
EEG Acquisition and Analysis .................................................................... 9
Results …..............................................…............................................................... 10
Feedback-related negativity (FRN) ……………………........................... 11
Late positive deflection (P300) …………………………........................... 12
Discussion................................................................................................................ 12
Are LDWs interpreted as wins? .................................................................. 12
A decrease in the neural response to real wins? ......................................... 14
Limitations …………………………………….......................................... 16
Conclusions.................................................................................................. 17
Acknowledgments ................................................................................................... 18
References................................................................................................................ 19
3
List of Figures
Figure 1: Screenshot of the mutli-line slot machine simulator showing a win, loss, and
loss disguised as a win (LDW) ……………………………................................. 21
Figure 2: Grand average ERPs for wins, losses, and losses disguised as wins (LDWs)
elicited before and after the educational video for frontal electrode FCz and the
corresponding topographical maps ......................................................................... 22
4
Executive Summary
Losses disguised as wins (LDWs) occur in multi-line slot machines when it indicates the
player won, but the amount won is less than their total wager (i.e., monetary loss).
Research has shown that both LDWs and wins heighten arousal, suggesting that LDWs
might be perceived as real wins. Here we examined the neural activity associated with
LDWs to confirm whether they are interpreted in the brain as real wins, and if so,
whether this false perception could be corrected by unmasking the disguise. In two
sessions we measured event-related brain potentials (ERPs) while participants played a
multi-line slot machine simulator (unaware and aware of LDWs). Results revealed that
LDWs and real wins were similarly processed as positive outcomes (large P300). Once
aware of LDWs however, results showed an enhancement of the feedback-related
negativity following LDWs and a decrease in the P300 for real wins. This indicates that
unmasking LDWs not only affects players’ interpretations of future LDWs, but also
impacts the response to real wins. We propose that learning of LDWs might reduce the
frequency with which the player feels rewarded during slot machine play by taking the
‘buzz’ off winning.
Keywords: Slot Machines; Gambling; Event-Related Potentials; Reward; Feedback-
Related Negativity; Losses Disguised as Wins
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Introduction Slot machines are the most addictive form of gambling, with problem gamblers
contributing 60% of total revenues collected from slot machines1 - a higher percentage
than horse racing, table games, bingo, and lotteries combined (Williams & Wood, 2004).
A likely contributor to the development of slot machine addiction is the presence of
losses disguised as wins (LDWs; Dixon et al., 2010) or "Fake Wins" (Wilkes et al.,
2010). LDWs occur on modern multi-line machines, in which players can wager on more
than one line. When the player ‘wins’, the win might include only one or two lines, in
which case the monetary gain is less than the amount wagered - resulting in a monetary
loss. Unlike real losses where the machine goes into a state of quiet, the slot machine
celebrates LDWs by displaying sights and sounds that are highly similar to those that
accompany a real win. This celebration of LDWs by the slot machine may be rewarding
for the player, and therefore may provide significantly greater rate of reinforcement than
would otherwise occur if only real wins were celebrated (~25% compared to only ~12%;
Harrigan et al., 2011).
Dixon et al. (2010) showed that LDWs produce enhanced nervous system arousal,
similar to the arousal elicited by real wins. Skin conductance responses (SCRs) were
recorded while participants played a multi-line slot machine and the results indicated that
although wins amounted to a net gain and LDWs to a net loss, the nervous system arousal
generated by each outcome appeared to be indistinguishable. It is well known that
nervous system arousal is a very powerful source of reinforcement for most individuals
(Brown, 1986). Thus, the findings of Dixon et al. suggest that one way in which positive
reinforcement may hide loss is through arousal.
Arousal has also been implicated in the maintenance of pathological gambling
(Brown, 1986), and thus slot machines with numerous LDWs could turn out to be more
pleasurable. It is unclear, however, whether the heightened arousal associated with LDWs
and wins is due to the player interpreting them both as winning outcomes. Although
Dixon et al. (2010) suggested that the equivalent SCRs generated by wins and LDWs was
evidence for players miscategorizing LDWs as wins, a theoretical limitation is that
LDWs could elicit arousal through frustration while wins might elicit arousal through 1 Reported for our home jurisdiction of Ontario, Canada (Williams and Wood, 2004).
6
excitement. Therefore, there is no way of knowing the valence of the arousal with SCRs
alone. The current study bypasses this limitation by measuring the neural activity
associated with LDWs and real wins while participants played a multi-line slot machine
simulator. By measuring the brain waves directly, we sought to determine whether the
brain response to LDWs resembled that of a real win or a unique outcome.
Electrophysiological studies have frequently reported two event-related potential
(ERP) components elicited in response gambling-like behaviours: the feedback-related
negativity (FRN) observed between 250-500 ms, and a positive waveform peaking
between 300-600 ms (P300). The FRN has been widely shown to reflect negative
feedback (e.g., monetary losses; Hajcak, et al., 2007; Holroyd and Coles, 2002; Wu &
Zhou, 2009), while a greater P300 has been found following positive outcomes (e.g.,
wins), with high motivational impact, that violate our expectancies (Nieuwenhuis, et al.,
2005; Wu and Zhou, 2009). However, it is important to acknowledge that (a) the P300 is
one of the most studied components in ERP research due to its’ ubiquitous nature, and (b)
there is still debate over whether the FRN codes negative outcomes and P300 positive
outcomes, as this has not always been found (e.g., Bellebaum and Daum, 2008; Sato et
al., 2005; Yeung and Sanfey, 2004).
The aim of this research however, is not to narrow in on any specific component,
but rather to determine any differences in the general waveform following wins and
LDWs. Consistent with Dixon et al. (2010)'s miscategorization hypothesis that LDWs are
being misrepresented as real wins, we hypothesized that when unaware of LDWs the
ERP waveforms elicited by them would not significantly differ from the ERP waveforms
elicited by real wins. In ERP component terms, both wins and LDWs might encompass a
large P300 (possibly larger for real wins since the P300 has also been linked to
magnitude of the reward), and LDWs might elicit a small (if any) FRN. These findings
would support Dixon et al. (2010)’s hypothesis that LDWs are not being correctly
categorized as losing outcomes, so therefore they are likely being misinterpreted as
winning outcomes.
Yet this result might only be the case only when LDWs are successfully disguised
by the slot machine. That is, misperceiving LDWs as wins might only work for naïve
players, and not for players who are made aware of the disguise. Thus, we also examined
7
if the awareness of LDWs in slot machines could change the brain response elicited by
LDWs. Thus, we recorded ERPs after participants watched a 5-minute video specifically
designed to “unmask” LDWs. We hypothesized that increasing players’ awareness of
LDWs might be reflected in their ERP signatures, possibly showing an enhanced FRN
representative of negative feedback.
Methods Participants
Twenty-one students from the University of Waterloo participated. One student
was removed due to excessive artifacts. All students (17 females; mean age of 22.5
years) scored 0-1 on the Problem Gambling Severity Index (PGSI), indicating that they
were free from gambling related problems. Participants reported no neurological or
psychiatric conditions. Participants were financially compensated ($20) for their time,
and informed that they would have the opportunity to gain an extra $10 depending on
their end balance on the slot machine. The Office of Research Ethics at the University of
Waterloo approved all statements and procedures and participants gave written informed
consent before the any procedures were initiated.
Apparatus and Procedure
Participants sat comfortably at a distance of ~ 60 cm in front of a 17” cathode ray
tube (CRT) computer monitor that displayed a 9-line slot machine simulator
(programmed in Flash by Game Planit Interactive Corp.) The simulator looked and
performed like a real multi-line slot machine (see Figure 1), except that the rewarding
sounds that typically accompanied both LDWs and winning outcomes were silenced
(since they could interfere with the acquisition of clean ERP data). The simulator
consisted of five reels with informative counters along the bottom (e.g, amount wagered,
credit balance, and amount won). Similar to multiline slot machines found in casinos,
LDWs and real wins were highlighted by a coloured, flashing line joining the winning
symbols. A spin was initiated by pressing the “spin” button, whereupon the reels started
spinning and came to a stop sequentially from left to right (entire spin duration was about
8
3 seconds). Once the outcome was delivered (i.e., stop of the last reel), the events were
marked as a win, loss, or LDW.
INSERT FIGURE 1 ABOUT HERE
To reduce eye-movements, we asked participants to fixate their eyes on a triangle
shown positioned between the reels and informative counters (see Figure 1). This
controlled participants’ eye movements, while allowing them to spread their attention
amongst other aspects of the display. In order to make it easier for participants to do this,
the simulator used was smaller than a real slot machine display (4° high and 8° wide of
visual angle). This smaller display size made it easy for participants to covertly attend to
the bet and payout boxes for the calculation required to detect an LDW. To minimize
eye-movement artifacts, participants were asked to refrain from blinking and making
saccades once the reels stopped and the outcome was delivered. Participants played 20
practice spins (4 wins, 4 LDWs, and 12 losses) to get comfortable with this procedure.
Each spin took approximately 3 seconds before the outcome was delivered. For the
duration of the experiment, participants spun at a casual rate (approx. 1 second between
spins) and were allotted frequent breaks to rest their eyes. The experimenter was present
throughout to make sure participants were performing well and that the equipment was
functioning properly.
Before playing in the ‘unaware’ session, all aspects of the slot machine simulator
were thoroughly described, including the paytable and counters. Participants were
informed that they would be starting with 2000 credits and that they would be given a
bonus of $10 if their end balance remained the same (or increased) at the end of the
session. The bonus was put in place to reward participants for winning and to give them
something to lose out on if they did not win2. Participants were instructed to, “play all 9
lines, bet 1 credit per line, for a total of 9 credits per spin”. This controlled wager resulted
in comparable amounts of LDWs and real wins (50 and 40, respectively). These
2 Do to ethical constraints we were prohibited from allowing participants to play with their own money, as is the case in casinos. While this seems to take the risk out of gambling, it is a limitation that the majority of gambling research must to adhere to.
9
proportions are similar to the actual proportion of outcomes on a real slot machine
(12.2% wins, 13.7% LDWs, and 74.1% losses reported in Dixon et al., 2010). Following
the 20 practice spins, participants played 250 spins for which ERPs were recorded. In the
‘aware’ session, participants first watched a five-minute video that outlined all aspects of
multi-line machines, including examples of all the different outcomes (i.e., wins, losses,
and importantly, LDWs). Following this short video, ERPs were recorded while
participants played another 250 spins on the slot machine simulator. The main purpose of
the video was to highlight the presence of LDWs and to demonstrate the appropriate
calculation (total spin wager minus win amount) required to unambiguously tell whether
they won or lost money on that spin. After each playing session (unaware and aware
conditions), participants were asked to give an estimate of how many times they lost
during that session out of 250. Testing lasted approximately 1 hour (30 minutes of EEG
set-up and 30 minutes of slot machine play).
EEG Acquisition and Analysis
EEG was recorded using the ActiveTwo Biosemi EEG system with 72 Ag-AgCl
electrodes embedding within a mesh cap. Sixty-six electrodes were arranged according
to the International 10/20 system and two electrodes placed on the left and right mastoids.
For the electro-oculograms (EOGs), two facial electrodes were placed on the outer canthi
of both eyes and one above and below the left eye. Data were recorded continuously and
sampled at a rate of 512Hz for offline analysis. Impedances for all electrodes were
maintained below 5 kΩ.
The offline analysis was performed using EEGLAB (Swartz Center for
Computational Neuroscience, UC San Diego) with the ERP Lab Toolbox (Luck and
Lopez-Calderon, UC Davis). The EEG of all electrodes was re-referenced to the average
of the two mastoids and digitally bandpass filtered between 0.01-30 Hz using a digital
filter. Events were time-locked to the slot machine outcome labeled as a win, loss, or
LDW. The signals were digitized into epochs of 800 ms (200 ms pre- and 600 ms post-
outcome onset), baseline corrected to the 200 ms before the outcome onset, and averaged.
It is necessary to acknowledge that the baseline was 200 ms before the last reel came to a
stop. As such, players could see symbols on the first four reels and the spinning motion of
10
the last reel. While this baseline is unconventional (e.g., not being a blank screen), we
feel that the perceptual characteristics of the baseline is irrelevant seeing as though we are
interested in the interpretation of the outcome (top-down evaluation), not the perception
of the symbols (bottom-up effects). An important confound would be if participants could
determine the outcome of the spin prior to the reels stopping (i.e., during the baseline).
However, due to the overwhelming and confusing nature of multiline machines, it is
virtually impossible for a naïve player following the symbols on 9 different lines to know
the outcome before the reels came to a stop. Typically the complexity of the multiple
lines forces players to rely on the slot machine indicators to determine whether they won
or lost. Thus, the overwhelming nature of multiline slot machines allows us to be certain
that participants were unaware of the outcome prior to outcome delivery and thus, the
baseline used is appropriate for our purposes. The cleanliness of the baseline can also be
observed in the Figure 2.
Artifacts due to eye movements and muscle activity were removed using the
moving window peak-to-peak threshold methodology that removed trials with brain
potentials that exceeded 100 μV in 50 ms steps. We then manually inspected the data for
additional artifacts (eye movements, muscle activity) or noise overlooked during the
initial artifact rejection procedure.
Results Artifacts due to eye- and muscle-movements were removed from the data and
grand average ERPs were calculated for each of the outcomes (wins and LDWs) for both
the unaware and aware conditions. Note that due to the perceptual differences (flashing
lights) associated with the machines’ celebration of wins (real wins and LDWs)
compared to losses (no flashing lights) compounded with the drastic differences in trial
proportion (160 losses compared with 40 wins and 50 LDWs), we could only analyze
LDWs and wins.
Grounded in previous research, we identified the FRN as a peak between 250-300
ms in the frontal-central recording sites, and the P300 as a positive deflection between
200-600 ms in central electrodes along the midline. Consistent with previous research
and by visual inspection we analyzed the fronto-central electrode FCz due to the
11
magnitude of the response relative to other electrode locations (Qi, et al., 2011). To
evaluate the FRN we calculated the (positive) peak minus the (negative) dip for each
participant. For this calculation we measured the maximum positive amplitude between
200-250 ms and subtracted the maximum negative amplitude between 250-350 ms (i.e.,
highest peak minus lowest dip). For the P300 we calculated the average amplitude of the
positive deflection between 350-450 ms post-outcome for each participant. As a control,
we compared the measures calculated at FCz with those calculated at the parietal
electrode POz, expecting no evidence of the FRN and P300 in posterior regions. The
mean peak-dip values for the FRN and average amplitude for the P300 were then
submitted to separate 3-way analysis of variances (ANOVAs) with the variables
Condition (unaware or aware), Outcome (win or LDW), and Electrode (FCz or POz) as
within subject factors.
Our key predictions concerned whether the neural response to LDWs would be
significantly different from real wins, thus we restricted our statistical comparisons to
include only wins and LDWs (not losses). Our hypotheses were two-fold: (1) LDWs will
be miscategorized as winning outcomes and thus, the ERP waveform produced by LDWs
will not be significantly different than that of real wins, and (2) that LDWs would elicit
an enhanced FRN (typically associated with negative feedback) once players became
aware of them as a potential slot machine outcome. The grand average ERPs for LDWs
and real wins in the aware or unaware conditions can be seen in Figure 2. Thus, any
change in neural response following LDWs might reflect a cognitive change in the
categorization of LDWs from a win (when unaware) to a loss (once aware). Any
cognitive change is also likely to be reflected in the players’ loss estimates, such that they
should estimate greater amount of losses once aware of LDWs.
INSERT FIGURE 2 ABOUT HERE
Feedback-related Negativity (FRN)
The ANOVA to evaluate the FRN showed a significant 3-way interaction
between Awareness condition, Outcome, and Electrode location, F(1, 20) = 7.353, p <
.05. Planned comparisons revealed the source of this interaction, indicating that there was
12
a significantly greater peak-to-dip increase at electrode FCz following LDWs once
players were aware of their presence in the slot machine game, t(20) = 2.087, p < .05.
This was not the case for real wins, nor did this change occur at electrode POz. Thus,
only once LDWs were unmasked as losses was there a significant enhancement of the
FRN following LDWs.
Late positive deflection (i.e., P300)
The ANOVA for the P300 amplitude revealed a significant main effect of
Awareness, F(1, 20) = 4.82, p < .05), indicating that the amplitude for both wins and
LDWs decreased once LDWs were unmasked (i.e., participants were aware of them).
There was also a main effect of Electrode location, F(1, 20) = 4.93, p < .05, such that the
overall amplitude was greater at electrode FCz. Importantly, there was a significant two-
way interaction between Awareness and Outcome, F(1, 20) = 6.53, p < .05, revealing that
the P300 amplitude was diminished only in response to wins, not LDWs. This interaction
was marginally significant across electrodes, F(1, 20) = 3.77, p = .06, suggesting that the
change in P300 was more dramatic at the frontal electrode FCz.
Discussion Here we aimed to uncover the underlying neural activity associated with LDWs
by measuring event-related brain potentials (ERPs). Specifically, we sought to determine
whether the brain activity elicited by LDWs was similar to that of a real win (large P300),
or closer to that of a typical loss (increased FRN). Given that LDWs elicit similar levels
of arousal (Dixon et al., 2010; Wilkes et al., 2010), we predicted that the ERP signature
for LDWs would initially mimic the ERP signature for wins.
Are LDWs interpreted as wins?
Prior to being aware of the disguise, LDWs showed a similar neural response
pattern as real wins in the sense that wins and LDWs showed similar ERP waveforms,
both eliciting a large P300. Indeed, it can be seen in Figure 1 that the waveforms
produced by wins and LDWs are nearly overlapping. This finding suggests that LDWs
are successfully disguised as winning outcomes by multi-line slot machines. The
13
similarity between the waveforms produced by LDWs and wins also provides converging
evidence with Dixon et al. (2010) who showed similarly large SCRs for both wins and
LDWs. Together these studies provide converging evidence that LDWs appear to be
miscategorized by players as winning outcomes. This miscategorization hypothesis
makes intuitive sense if players are unaware that LDWs exist in slot machine gambling.
If it looks like a win, and sounds like a win, it’s probably a win – not a loss.
Thus, our key prediction was that once players became cognizant of LDWs as a
potential outcome, they might start to correctly categorize them as losses. As such, LDWs
would start to elicit a neural response associated with negative feedback (i.e., enhanced
FRN). In other words, we expected that once players realized that some ‘wins’ resulted in
a loss of credits (and therefore should be interpreted as a loss) the brain response
following LDWs would also change to reflect their newfound awareness. Consistent with
our predictions, participants’ subjective reports of how often they lost after each 200-spin
session suggested that they were indeed beginning to classify LDWs as losses. The loss
judgments following each session indicated that participants were feeling like they were
losing more in the ‘aware’ session, than the ‘unaware’ session. Interestingly, the players’
estimates when unaware of LDWs accurately reflected the amount of regular losses
(estimated: 153, actual: 160), while the loss estimates once aware of LDWs most
accurately reflected regular losses plus LDWs (estimated: 197, actual: 210). Crucially,
the ERP results showed a significant FRN response to LDWs that was enhanced once
participants were aware of LDWs (see Figure 2). The presence of an FRN-like response
associated with LDWs implies that once learning about the deceitful properties of LDWs
they began to elicit a response typically associated with negative outcomes (e.g.,
monetary losses).
This finding provides some hope that education and awareness could modulate
the brains’ interpretation of LDWs to classify them correctly as losses, rather than
incorrectly as wins. It is important to keep in mind that players were exposed to a five-
minute video delineating all of the outcomes (not just LDWs), and they only passively
watched the video once. It would be interesting for future research to investigate whether
increasing the exposure to educational material aimed at unmasking LDWs could
14
permanently change the way players view LDWs, or whether this cognitive awareness
only lasts for the duration of the playing session.
A decrease in the neural response to real wins?
Unsuspecting, our key manipulation of making participants aware of LDWs not
only modified the FRN to LDWs, but also decreased the P300 response to real wins. In
fact, the P300 elicited by wins was not only reduced once participants were aware of
LDWs, it was completely diminished. This finding at first glance seems to be in contrast
with our predictions - that only the neural response to LDWs would be affected by LDW
awareness. However, there are a number of reasons why the P300 might have dissipated
following real wins in the context of our study and there are plenty of cognitive states that
affect the P3003. To narrow it down to gambling-type contexts, Wu and Zhou (2009)
recently showed that the P300 is sensitive to at least three aspects of an outcome
evaluation: valence, magnitude, and expectancy. That is, the P300 can be enhanced in
response to positive outcomes that are relatively unexpected and modulated by
magnitude. However, none of these seem to apply to the current findings. Making
participants aware of LDWs did not change the fact that real wins are still positive
outcomes that are relatively unexpected (compared to losses), and are typically associated
with a high magnitude.
Thus, from our experience with the participants in this study we propose two
potential explanations for the reduced positive waveform following real wins. First, the
attenuation of the P300 following real wins in our study could reflect the players’
skepticism regarding all subsequent ‘wins’ (LDWs plus wins) as potential negative
outcomes. This creation of doubt might have inhibited players from immediately
interpreting the real wins as positive, exciting, unexpected events, given that the win
could turn out to be a monetary loss (i.e., LDW). Indeed, research has highlighted the
affective role played by the P300 during outcome evaluation, such that the brain codes
for positive versus negative outcomes with the goal to optimize future choices 3 We have considered that fatigue might also play a role in the absence in the P300, however we did not find the same reduction in ERP amplitude following LDWs or losses to support that concern. In fact, the experimenter noted that participants seemed to be more interested in playing once they were aware of LDWs in the second session.
15
(Nieuwenhuis et al., 2005). If players’ were concentrating on not being fooled by LDWs,
they might have been hesitant to celebrate real wins until they were sure it was a
monetary gain. This delayed gratification might have reduced the initial excited for the
win, as well as delayed the production of the P300.
Alternatively, the diminished P300 for real wins could reflect a diminished
interest in real wins, since players might have been more interested in detecting LDWs.
In other words, the reduction in the P300 could reflect a decrease in attention to winning
outcomes in general due to the increase in attention to finding LDWs. It seems reasonable
to assume that once participants became aware of the disguise inherent in slot machines,
they became focused on seeing it for themselves. Research has shown that the P300 over
frontal electrode sites (termed P3a component) is associated with an orienting response to
an attention-grabbing stimulus (e.g., Comerchero and Polich, 1999). This increase in
attention towards identifying LDWs might have attenuated the significance of real wins.
Of course, this possibility and the possibility mentioned previously are not necessarily
mutual exclusive, and it could be the case that learning of LDWs attenuates the
significance of real wins by reducing players’ attention to wins and causing delayed
gratification.
An important implication for both of the proposed accounts (i.e., reduced
excitement and reduced attention to wins) is that learning of LDWs might (in the short-
term) reduce the motivational value associated with winning outcomes. It has been
reported by previous frequent gamblers in our lab that learning of LDWs seems to take
the “buzz” off of winning in general. Seeing as though this “buzz” might be a prominent
source of reinforcement for pathological gambling (Brown, 1986), any decrease in this
“buzz” might transfer into a reduced amount of reinforcement (or enjoyment) for
pathological gamblers. This is especially important when research has shown that
participants experienced proportionally more LDWs (17.1%) than real wins (15.6%)
when players play the maximum number of lines (Dixon et al., 2010). If it is the case that
a simple five-minute video detailing how to detect LDWs could direct players’ attention
to LDWs during slot machines play, while also diminishing the significance of real wins,
then such an intervention might prove beneficial. LDW awareness might not only change
players interpretations of LDWs (as negative outcomes), but might also in turn decrease
16
the degree of reinforcement experienced by the player on more than 50% of the ‘wins’.
This decrease in reinforcement could have important implications for the treatment of
pathological gambling, and at the very least, be most encouraging for initiatives aimed at
preventing problem gambling.
Limitations
Although we are confident in our results, we wish to note some important
limitations of the design of the current study. In terms of the ecological validity, we admit
that there are many differences between the lab context we used here and the casino
context in which slot machines are played, an issue that plagues most laboratory studies.
One obvious deviation from real gambling is that we could not allow (ethically) for
participants to gamble with their own money in the event that they lost, nor could we
afford to pay participants if they won the jackpot - both of which would otherwise be
possible gambling in a casino. Due to this limitation, one might argue that there is no real
associated risk or reward with gambling in our laboratory setting. While this is a valid
argument, the current study solely focused on whether LDWs elicited positive or negative
feedback which has little to do with the degree of risk taken or with the magnitude of the
end reward. Of course we wanted participants to feel rewarded with wins, and we did try
to motivate this by offering participants $10 extra if they gained more than 2000 credits
at the end of the session. Lastly, we feel as though maintaining experimental control over
bet size, reward amount, and degree of risk is common across gambling-type studies and
is crucial in order to collect clean data.
In addition, we prioritized clean data over ecological validity through the removal
of the celebratory music typically associated with “winning” outcomes (both real wins
and LDWs) during slot machine play. That is, the slot machine simulator was silenced
and did not offer players the possibility to discern LDWs from real wins on the bases of
sound alone - that being that LDWs produce a shorter celebration song compared to real
wins. First, there is currently no research to suggest that players’ can recognize wins and
LDWs solely based on the sound alone. In fact, we believe that introducing the
celebratory music would have only further disguised LDWs. Second, introducing the
17
sound component would have also introduced noise into the ERP data. Thus, the removal
of the sounds was necessary for us to collect clean data.
Finally, given that our study exclusively tested individuals who gambled
infrequently, our findings are limited to that group and cannot be generalized to include
problem gamblers. While an important goal for the future is to find out how gambling
outcomes are interpreted by problem gamblers, it was first necessary to investigate how
LDWs were interpreted by a naïve group of gamblers. Thus, despite this limitation to
generalize to problem gamblers, the current study with infrequent gamblers lay the
necessary groundwork to show that (a) LDWs are processed as positive outcomes in the
brain (similar to real wins), and (b) unmasking LDWs not only modified the neural
response that is typical of a negative outcome, but might have attenuated the
reinforcement elicited by real wins. Our next step will be to examine if these results hold
true for problem gamblers as well.
Conclusions
Our results here suggest that naïve players’ are largely unaware of LDWs as a
potential slot machine outcome, which unsurprisingly causes them to interpret LDWs
incorrectly as wins. However, hope is restored in that players show a change in neural
response to LDWs once LDWs are unmasked and players become aware of the disguise.
Therefore, we highly recommend players be informed about the true nature of LDWs in
slot machines. This awareness could in turn help gamblers regulate their playing
behaviour. Here, our data promotes optimism that with further knowledge about slot
machines and all possible outcomes (especially the presence of LDWs), players
(infrequent and frequent alike) might learn to classify LDWs for what they really are –
losses!
18
Acknowledgements:
This research was funded by the Ontario Problem Gambling Research Centre, with a
Level I Research Grant to M.J., M.J.D., and K.A.H. We would like to thank Frank
Preston for his help with data collection.
19
References
Bellebaum, C. & Daum, I. (2008). Learning-related changes in reward expectancy are
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Figure 1: Screenshot of the mutliline slot machine simulator. Examples of a win, loss,
and LDW are illustrated. Participants fixated on the yellow triangle during play.
22
Figure 2: Grand average ERPs and topographical maps produced by LDWs and
real wins. The figure highlights the significant differences between the two
conditions: unaware of LDWs and aware of LDWs. The shaded areas represent the
components of interest (i.e., FRN and P300). It is apparent in the figure that LDWs
elicited a larger FRN compared to wins once participants were aware of LDWs (p <
.05*) and the P300 was significantly reduced for wins (p < .05*).