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.

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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

 

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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

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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).

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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

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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

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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.

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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

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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

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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

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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

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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

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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.

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(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

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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!

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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.

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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.

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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*).