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Insula activity during safe-sex decision-making in sexually risky men suggests negative urgency and fear of rejection drives risky sexual behavior

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Insula activity during safe-sex decision-making in sexually risky men suggests negative urgency and fear of rejection drives risky sexual behavior

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Content Insula activity during safe-sex decision-making in sexually
risky men suggests negative urgency and fear of rejection
drives risky sexual behavior
Benjamin J. Smith
Submitted in partial fulfillment of the requirements
for a Master of Arts PSYCHOLOGY
Conferral December 2015
Dana and David Dornsife School of Letters, Arts, & Sciences
University of Southern California

2 Benjamin J. Smith

Research reported in this thesis was supported by NIDA under R01DA031626, and by
NIMH under RMH082671A. The content is solely the responsibility of the authors and does not
necessarily represent the official views of NIDA or NIMH.
The author acknowledges invaluable help and advice for this project from my advisor and
Committee Chair, Prof. Steve Read, the remainder of my Master’s Committee, Prof. John
Monterosso and Prof. Antoine Bechara, and other mentors and colleagues including Prof. Lynn
Miller, Dr. Feng Xue, Dr. Emily Barkley-Levenson, Prof. Bosco Tjan, James Melrose, Felix Hao
Wang, Eustace Hsu, and many others. This project also would not be possible without hard work
by Dr. Feng Xue, Dr. Emily Barkley-Levenson, and Vita Droutman collecting data from 170 at-
times drug-addled subjects.
Portions of the methods section are extracted from the Social Affective Neuroscience of
Decision-making’s lab records, and were originally written by the present author, Dr. Feng Xue,
Dr. Emily Barkley-Levenson, and others.
I’m also grateful for the lunchtime company of Pete Meindl and David B. Newman, and
my roommates Michelle Lai, Joshua Varinsky, and Shannon Zhang, who all make me feel like I
do have family in this country after all.
Ben Smith
May 2015

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

3

Abstract
113 men (Black, Hispanic, and White gay men aged 18-31) in sexually safe and risky
groups were compared in order to examine likely neurological and psychological contributions to
risky sexual decision-making, Subjects played a computer game allowing them to make
decisions about condom use and other sexually risky decisions, while BOLD activity was
recorded using fMRI (fMRI but not behavioral data was excluded for 7 additional subjects due to
data processing errors). Subjects who made one or more sexually risky choices during gameplay
reported more unprotected anal intercourse in the previous 90 days in real life (N=25, Mdn=5)
compared to subjects who consistently made sexually safe choices (N=95, Mdn=2), confirming
that computer game behavior was related to real-life behavior, W=825.5, p=.017, r=.27. During
risky sexual decision-making, sexually riskier subjects, i.e., those who had unprotected anal
intercourse at least once in the previous 90 days (N=76), had significantly more insula activity in
a whole-brain cluster analysis, controlling for baseline activity, compared to subjects who
reported having no unprotected anal intercourse in the previous 90 days and not having ever used
methamphetamine (N=31). Additionally, there was some evidence for greater prefrontal cortex
participation in methamphetamine users (N=34) than in non-users (N=42). One cluster of activity
contrast including the insula, superior temporal sulcus, and posterior cingulate during sexually
risky decision-making was significantly (p<0.001) related to trait-level negative urgency,
suggesting that—consistent with previous literature on attachment styles and heterosexual risky
sex--susceptibility to social pressure from partners plays a role in risky sexual behavior. Activity
in regions associated with animated mentalizing strengthens the case for a concern about others’
reactions being relevant to decisions about risky sex.

4 Benjamin J. Smith
Table of contents

Abstract .................................................................................................................................... 3
Table of contents ...................................................................................................................... 4
Introduction ............................................................................................................................. 8
Sexual risk-taking .................................................................................................................. 9
Sexual risk-taking and positive and negative urgency ........................................................ 10
Methamphetamine use ......................................................................................................... 11
Virtual validity ..................................................................................................................... 11
Defining a decision-making system ..................................................................................... 11
Reflective and integrative systems. ................................................................................. 13
Insula. .............................................................................................................................. 14
Reward system. ................................................................................................................ 14
Hypotheses ........................................................................................................................... 14
Method .................................................................................................................................... 16
Subjects ................................................................................................................................ 16
Self-report data .................................................................................................................... 17
Pre-screener survey. ........................................................................................................ 17
Task ...................................................................................................................................... 17
Measures .............................................................................................................................. 19
Game task measures ........................................................................................................ 19
Self report measures ........................................................................................................ 20
Operationalizing the decision-making system ..................................................................... 20
Data Acquisition and processing ......................................................................................... 21
Results ..................................................................................................................................... 22
Behavioral ........................................................................................................................... 23
Self-reported real-life behavior. ...................................................................................... 23
Mean numbers of decisions. ............................................................................................ 23

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

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Correspondence with real-life behavior. ......................................................................... 24
Neurological ........................................................................................................................ 27
Main effects by decision type and group. ........................................................................ 28
Risk Group contrast effects by decision type. ................................................................. 32
By region: SRD activity in areas of interest .................................................................... 43
Hypotheses ...................................................................................................................... 44
Trait-level personality explanations ................................................................................ 47
Conclusion .............................................................................................................................. 53
References .............................................................................................................................. 55

6 Benjamin J. Smith
Figures Index
Figure 1. The decision-making system operationalized using the Harvard-Oxford Cortical
and Subcortical Atlases (FSL, 2014) and Deen, Pitskel, & Pelphrey’s (2011)
three-parcel insula segmentations. ..................................................................................... 13

Figure 2. Procedure used to determine whether a sexually risky decision choice is safe or
risky, taking into account the context of the choice. ......................................................... 19

Figure 3. Frequency of game decisions by type. ........................................................................... 24

Figure 4. Unprotected anal sex in previous 90 days by game behavior. ....................................... 25

Figure 5. In-game Sex-role chosen by self-reported real life behavior. ....................................... 25

Figure 6. Drinking frequency in real life in three different measures by drinking
frequency in game. ............................................................................................................ 26

Figure 7. Conversational-Baseline main effect contrast across all 3 groups.
Conversational activity was used as a contrast while analyzing other three
Decision Types. Highlighted regions are activity contrast over the z>2.3 threshold
that met the corrected cluster significance threshold of p<0.05. ....................................... 29

Figure 8. SRD-Conversational main effect contrast across all 3 groups. Highlighted
regions are activity contrast over the z>2.3 threshold that met the corrected cluster
significance threshold of p<0.05. ...................................................................................... 30

Figure 9. Alcohol-Conversational main effect contrast across all 3 groups. Highlighted
regions are activity contrast over the z>2.3 threshold that met the corrected cluster
significance threshold of p<0.05. ...................................................................................... 31

Figure 10 Sex-role-Conversational main effect contrast across all 3 groups. Highlighted
regions are activity contrast over the z>2.3 threshold that met the corrected cluster
significance threshold of p<0.05. ...................................................................................... 32

Figure 11. Safe-Sex > Risky Sex Groups (considered separately and together) during
Conversational Decision-making. Highlighted regions are activity contrast over
the z>2.3 threshold that met the corrected cluster significance threshold of p<0.05. ....... 34

Figure 12. Combined-Risky-Sex > Safe-Sex groups during Sex-role decision-making.
Highlighted regions are activity contrast over the z>2.3 threshold that met the
corrected cluster significance threshold of p<0.05. ........................................................... 35

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

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Figure 13. Combined-Risky-Sex > Safe Subjects Group contrast during SRD using the
Baseline (red) and Conversational (blue) Control. Highlighted regions are activity
contrast over the z>2.3 threshold that met the corrected cluster significance
threshold of p<0.05. ........................................................................................................... 40

Figure 14. Risky-Sex-Meth > Safe-Sex Group contrast during SRD using the
Conversational Control (blue) and Baseline Control (red). Highighted regions are
activity contrast over the z>2.3 threshold that met the corrected cluster
significance threshold of p<0.05. ...................................................................................... 41

Figure 15 Risky-Sex-Meth > Risky-Sex-No-Meth Subjects whole-brain activity contrast
during SRD; SRD > Conversational in red; no significant SRD > Baseline
contrast found.. Highlighted regions are activity contrast over the z>2.3 threshold
that met the corrected cluster significance threshold of p<0.05.” ..................................... 42

Figure 16. Insula activity by location and Risk group (Safe-Sex or Combined-Risky-Sex),
using the Baseline Control. ................................................................................................ 46

Figure 17. DLPC activity by Meth Use group for Risky Subjects (Risky-Sex-No-Meth-
Group vs. Risky-Sex-Meth Group). .................................................................................. 47

Figure 18. Relationship between Left hemisphere cluster 2 Combined-Risky-Sex > Safe-
Sex Groups, contrast during SRD, using the Conversational Control. Activity
maps show activity from both clusters that occurred within the insula. ........................... 51

Figure 19. Relationship between Left hemisphere cluster 2 Combined-Risky-Sex > Safe-
Sex Groups, contrast during SRD, using the Baseline Control. Activity maps
show activity from both clusters that occurred within the insula. ..................................... 52

8 Benjamin J. Smith
Tables Index
Table 1. Hierarchical organization of terminology used in this article to denote systems,
regions, and sub-regions of the decision-making system. ................................................. 21

Table 2. Risky sex behavior by group: mean and standard deviation of instances of
unprotected anal intercourse in the previous 90 days. ....................................................... 23

Table 3. Number of subjects with a given self-reported frequency of meth use in the last 3
months. Group inclusion criteria was an affirmative answer to the question, “Have
you ever used methamphetamine?” ................................................................................... 23

Table 4. Behavioral statistics for each decision type. ................................................................... 24

Table 5. Risky-Sex-Combined and Safe-Sex contrasts, along with any activity in
decision-making regions, with SRD, Alcohol and Sexrole Decision Types with
conversational or baseline controls. L=Left; R: Right. ..................................................... 36

Table 6. Regions, voxels, peak position and magnitude for each contiguous sub-cluster
within the insula in the SRD > Conversational, Risky-Sex-Combined > Safe-Sex
Group comparison. ............................................................................................................ 37

Table 7. Risky Non-meth and Risky meth contrasts, along with any activity in decision-
making regions, with SRD, Alcohol and Sexrole Decision Types with
conversational or baseline controls. L=Left; R: Right; DLPC=dorsolateral
prefrontal cortex; FOC=frontal orbital cortex; SFG, MFG, IFG: Superior, middle,
inferior frontal gyrus. ......................................................................................................... 39

Table 8 Risky sex (UAI90) correlations with personality variables. Using Benjamini-
Hochberg False discovery rate correcting for 50 multiple comparisons,
correlations denoted with † p<0.1, * p<0.05, **p<0.01, *** p<0.001 indicating
corrected p-values. ............................................................................................................. 48

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

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Introduction
Choices about sexual behavior have a strong influence on health (Bearinger, Sieving,
Ferguson, & Sharma, 2007). Often decisions are made 'in the heat of the moment' (Sheeran,
Abraham, & Orbell, 1999) during negotiations with sexual partners (Noar, Carlyle, & Cole,
2006). Understanding the decision-making processes in sexual situations themselves is crucial
for understanding the decision-making processes influencing health outcomes.
Computer game simulations allow subjects to participate in experiences simulating real-
life situations difficult to capture from within the confines of an fMRI scanner, enhancing
ecological validity. We asked sexually risky and non-risky subjects to play a game designed to
simulate and reduce risky sexual behavior (Miller & Read, 2005), while in a scanner, and
recorded their fMRI responses as they made everyday and sexual choices in the game. To our
knowledge, this included the first test of the correspondence of behavior between real life and a
computer game simulation played within the confines of an fMRI scanner.
We compared the responses of three groups of men who have sex with men (aged 18-31):
sexually non-risky men, sexually risky men, and sexually risky men who use methamphetamine
(henceforth “meth”). By comparing the differences in processing from the three groups, we can
identify differences in decision-making circuitry between the groups that are related to more or
less risky behavior.
Decision-making theory described by Bechara (2005) and others helped to define
predictions for behavior and guidelines for interpreting results. This paper describes literature
about sexual risk-taking and decision-making processes in general. It then describes our sexual
risk-taking task and the hypothesized results based on decision-making theory. It then describes
how insula activity was identified and negative urgency could play a causal role for that activity.
Sexual risk-taking
Sexual risk-taking remains a critical problem for health. Currently around one million
adults in the United States have an HIV diagnosis. The CDC and others (2015) estimate new
diagnoses derived from male-to-male sexual contact number around 30,000 (CDC & others,
2015).

10 Benjamin J. Smith
In addition to actually using a condom, carrying a condom and having a condom
available for a sexual encounter are considered valuable for preparing individuals for safe sex
(Sheeran, Abraham, & Orbell, 1999). Safe sex and condom use communication are crucial (Noar,
Carlyle, & Cole, 2006) and communication about condom use increases the likelihood of
condom use in non-primary partner sexual encounters (Lo, Reisen, Poppen, Bianchi, & Zea,
2011). Thus, condom use is a priority for preventing the spread of HIV and other STIs, and the
psychosocial aspects—particularly decisions that people make when negotiating safe sex with
their partners–are important for condom use. For these reasons, the game focuses on practicing
safe sex, defined as anal sex with a condom or alternative sexual activities rather than
unprotected anal sex.
Sexual risk-taking and positive and negative urgency
It is important to understand the distinctive traits and characteristics of individuals who
have more risky sex. Understanding these characteristics provides insight into the reasons why
individuals in general take risks, when they do. By examining the neural characteristics of risk-
takers and not only the personality traits, we can draw links to neurological theories of decision-
making. Examining neural activity at the time of decision-making helps to identify exactly what
processes are responsible for risky decisions. In this context, neural activity can help us
determine whether risky decisions are more driven by a lack of cognitive control or a greater
desire for reward.
There is a known connection between sexually risky decision-making and trait-level
positive and negative urgency, defined respectively as “the tendency to engage in rash action in
response to extreme positive affect”, and “the tendency to engage in rash action in response to
extreme negative affect” (Cyders & Smith, 2008, p. 807). Cyders & Smith (2008) argued that
positive and negative urgency play distinct roles in promoting rash action, including risky sexual
behavior. Importantly, positive and negative urgency can be linked to the insular cortex (Xue, Lu,
Levin, & Bechara, 2010). Positive urgency has been experimentally linked with risk-taking and
alcohol consumption (Cyders, Zapolski, Combs, Settles, Fillmore, & Smith, 2010) as well as
illegal drug use and risky sexual behavior (Zapolski, Cyders, & Smith, 2009). Negative urgency
has also been associated with risky sexual behavior (Simons, Maisto, & Wray, 2010). The
mediating variable could be anxiety arising from fear of one’s partner’s reaction to a discussion

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

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about safe sex. Anxious attachment has been associated with lower condom use (Strachman &
Impett, 2009) in heterosexual women and men (Feeney, Peterson, Gallois, & Terry, 2000), and
with sexually transmitted infections and adolescent pregnancy (Cooper, Shaver, & Collins, 1998).
Häcker, Schmälzle, Renner, & Schupp (2014) found that during assessment of sexual risk,
appeared to include activity in subjects’ anterior insula and medial prefrontal regions, suggesting
that we should expect to find activity in these regions during sexual risk tasks.
Methamphetamine use
Due to the role meth use plays in causing risky sex in men who have sex with men
(Buchacz, et al., 2005; Appleby, Storholm, Ayala, & Miller, 2007; Molitor, Truax, Ruiz, & Sun,
1998), we were interested in examining the relationship between meth use status and risky sexual
situations. The similarity and differences between drug abuse problems and simple susceptibility
to rewarding stimuli – like sexual encounters – also make it interesting to compare the difference
between meth and non-meth users with the difference between people with risky and non-risky
sexual practices. The similarities and differences between drug abuse disorders and compulsive
behavioral problems like gambling are an area of active research (Leeman & Potenza, 2012), and
some evidence suggests both striatal abnormalities and abnormal inferior frontal connectivity
could be responsible (Ersche, Jones, Williams, Turton, Robbins, & Bullmore, 2012).
Virtual validity
The video game design enhances ecological validity compared to more prevalent highly
controlled experimental designs, but only to the extent that subjects interact with stimuli within
the game similarly to real-world stimuli. Godoy (2007) found that 26% of variance of past
unprotected anal intercourse (UAI) among subjects could be predicted by computer game
activity, and that 12% of future UAI can be predicted by computer game activity, and found that
virtual risk-taking had a stronger relationship with behavior in the next 90 days (collected in a
follow-up sample) than intentions; past behavior was more predictive than both.
Defining a decision-making system

Bechara (2005) proposed a neurobiological framework described here as the decision-
making system. This framework makes predictions about the kind of differences expected

12 Benjamin J. Smith
between safe and risky subjects. The decision-making system is an interaction between several
components, broadly speaking, a reward system, a reflective system (Bechara, 2005) and an
integrative system (Figure 1). The reward system is centered around the striatum and amygdala,
which often drives impulsive behavior; a cognitive control and response inhibition system is
centered around the dorsolateral prefrontal cortex (DLPC) which exerts deliberate and conscious
control on behavior (Ridderinkhof, van den Wildenberg, Segalowitz, & Carter, 2004) through
modulating the valuation system, and the integrative valuation system which weighs the
comparative values of alternative actions is primarily identified with the ventromedial prefrontal
cortex (VMPC) (Basten, Biele, Heekeren, & Fiebach, 2010).

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

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Figure 1. The decision-making system operationalized using the Harvard-Oxford Cortical and Subcortical Atlases (FSL,
2014) and Deen, Pitskel, & Pelphrey’s (2011) three-parcel insula segmentations.

Reflective and integrative systems. Prior work has often described a “reflective system”
(Bechara, 2005) within the decision-making system that includes both the DLPC and VMPC.

14 Benjamin J. Smith
The VMPC is more specialized in integrating and valuing signals from the DLPC and striatum
(Mason, O'Sullivan, Montaldi, Bentall, & El-Deredy, 2014), whereas a major role of the DLPC
in decision-making is to exercise self-control through modulation of the VMPC (Hazy, Frank, &
O'Reilly, 2007). To acknowledge these differences, here the two are described distinctly as the
reflective and integrative systems, respectively, within an overall decision-making system that
also includes the reward system and the insula. In the task, we should expect to find activity
related to response inhibition and reflective thought processes in the lateral prefrontal cortex,
while valuation of alternative actions may be found in the orbitofrontal cortex (OFC) or VMPC.
This should affect the amount of activity observed in more sexually risky compared to safer
subject groups during sexually risky activities, if sexual risk is related to response inhibition or
caution during decision-making.
Insula. Naqvi & Bechara (2009) describe a role for the insula representing a desire signal
which may be qualitatively different from reward signal (Naqvi & Bechara, 2009; Xue, Lu,
Levin, & Bechara, 2010). For this reason, the role of the insula was here considered separately to
the role of other parts of the reward system.
Reward system. Since the striatum, including the nucleus accumbens, putamen, and
caudate, is primarily implicated in reward activity, we should expect to see more activity in these
regions in the task during rewarding periods such as sexually salient decisions. Hence, if sexual
risk is driven by reward, then we should see additional activity in the striatum for more risky
subjects. Likewise, since the insula is associated with desire, if stronger desire susceptibility is
related to risky sexual behavior, we should observe more insula activity in more sexually risky
subjects.
Hypotheses

We considered several possible explanations for sexually risky behavior. Each possible
cause makes different predictions about the BOLD activity observable during the task.
Controlled processing differences, including lack of response inhibition, could cause differences
between safe and risky groups in the dlPFC. Differences in sensitivity to reward could also lead
to observable group-level BOLD differences during risky decision-making, expected in the
striatal region. Finally, differences in responses to proprioceptive desire cues could be detectable
by BOLD insula contrast.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

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Patients with VMPC lesions seem unable to effectively integrate controlled processing
(Yechiam, Busemeyer, Stout, & Bechara, 2005) and engage in riskier behavior as a result. For
this reason, we hypothesize that controlled processing can reduce risky behavior. In normal
subjects, population-level variance in response inhibition produces can moderate risky sexual
variance in risky behavior (Nydegger, Ames, Stacy, & Grenard, 2014). If the reflective system,
typically responsible for signaling pain or pleasure of future prospects (Bechara, 2005), is
relatively weaker, response inhibition and imagining future adverse consequences (e.g., an HIV+
diagnosis) during risky sexual behavior could also be weaker, thus increasing the likelihood of
risky behavior. If this is the mechanism producing additional risk in sexually risky subjects, then
we might expect less controlled processing in those subjects during sexually risky decision-
making.
Alternatively, in the current task, subjects are cued with emotional-laden images of a
“future self” having suffered adverse health consequences from having had unprotected sex. This
may cause subjects, particularly subjects who typically don't normally exercise caution, to act
more cautiously in this instance than they normally would. If this is the case, we would expect to
find additional controlled processing in risky subjects as they must exert more effort to engage in
the same amount of controlled processing. This could be observable either with greater
dorsolateral PFC activity contrast for risky subjects (H1.1), particularly if subjects continue to
make safe choices—reflecting extra deliberative effort that risky subjects need to retain response
inhibition—or lesser activity contrast for risky subjects (H1.2)—reflecting lower use of
deliberative control.
Second, risky subjects are expected to have a greater sensitivity to reward, identifiable by
a stronger striatal response to rewarding stimuli. Thus, in simulated sexual situations, we expect
activity in the dorsal striatum, representing an activated desire form of reward sensitivity (H2).
Third, risky subjects may experience greater desire or urge on exposure to desired stimuli.
Bechara (2005) proposed that the insula transmits signals from the body representing desire or
urge. Naqvi & Bechara (2009) reviewed evidence for this, suggesting that the insula transmits
interoceptive information from the body to the rest of the decision-making system to produce
decisions. Xue, Lu, Levin, & Bechara (2010) found a relationship between right insula activity
and trait level urgency. A stronger desire signal during safe sex negotiation could cause subjects

16 Benjamin J. Smith
to be more willing to forgo safe sex practices if they feel that asserting a need for safe sex could
cause their partner to withdraw. Since the insula plays a role in interoception, extra insula
activity could indicate a more viscerally-felt somatic response which may lead to very strongly
somatic-driven decisions. For these reasons, it is proposed that risky subjects may experience an
additional urge and desire signal identifiable by a greater insula response to rewarding stimuli
(H3).
Additionally, we were interested in the neural factors behind use of meth with risky
behavior. Our design enables us to examine the difference between users of meth and non-users,
as well as contrasting users with other equally risky subjects and less risky subjects in the sexual
domain. Relative to non-users with similar levels of risk, meth users ought to have abnormal
striatal activity (H4.1) and may also have abnormal inferior frontal activity (H4.2).
Method
Portions of this method section were taken verbatim from the Social and Affective
Neuroscience of Decision-making's lab records, written by the present author, Feng Xue, Emily
Barkeley-Levenson, and others.
Subjects
The study was approved in advance by the USC University Park Internal Review Board.
Subjects were recruited using flyers and craigslist advertisements in the Los Angeles area. This
study was part of a larger study, and of all subjects recruited, 120 subjects (Black, Hispanic, and
White gay men aged 18-30) completed an interactive videogame task allowing them to make
decisions about practicing safer sex, choosing a sexual position, and consuming alcohol.
Subjects were comprised of three groups: subjects who neither had unprotected anal
intercourse in the previous 90 days, nor ever used meth (Safe group; N=31), subjects who had
unprotected anal intercourse in the previous 90 days but had never used meth (risky, no-meth
group; N=42) and subjects who had used meth at least once in lifetime and had had unprotected
anal intercourse in the previous 90 days (risky meth-using group; N=34). Seven subjects were
excluded due to data processing errors; an additional 6 subjects were excluded because they
reported using meth but only having safe sex so did not fit the inclusion criteria for any group,

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

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leaving 107 subjects included across the three experimental groups. Of the 34 subjects in the
risky meth-using group, 51% (Table 3) had used in the previous 90 days.
Self-report data
In order to sign up for the study, subjects first completed a pre-screen questionnaire
online. The pre-screener collected data to determine subjects’ eligibility for the study and other
relevant information. In the lab, before subjects began the first session, they also reported other
relevant information.
Pre-screener survey.
Subjects reported their sex, drug, and alcohol use, focusing particularly on the prior 90 days, as
well as various personality and other subjects’ sexual history. Sexual practice data included:
• whether the subject had had a primary partner within that time
• the number of non-primary partner men with whom they had had anal sex
• the numbers of times the subject had unprotected and protected receptive and insertive
anal sex, the number of times the subjects were on meth for each of those four kinds of
anal sex, and the numbers of partners with whom the subject had each of those four kinds
of anal sex.
For alcohol and each other drug, subjects were asked to indicate whether they have used,
whether they ever injected, the last date used, the number of years they have been using the drug,
whether they used in the last three months and how many times in that period.
Subjects also reported demographic information and other data related to sexual health and
their suitability for participation in an fMRI study.
Task
The fMRI task was a video game in which subjects had the opportunity to meet computer
characters and hook up with them, negotiating safer sex practice along the way. The video game
was variously presented in first-person and third-person perspective. The player first chose an
avatar and moved their avatar around a 3D animated environment in which they interacted with
computer controlled characters in house party, bar, and bedroom settings. Previous results
validating the game’s relationship to real-life behavior are described in forthcoming papers by
Lynn Miller, Paul Robert Appleby, Johnnie L. Christensen, and colleagues. Research suggests

18 Benjamin J. Smith
bars (Grov, Parsons, & Bimbi, 2007) remain prominent places for men who have sex with men
to meet with one another.
There were two runs of the game. In the first run, the first scene was set at the player’s
home and the player had an opportunity to take a condom or not before. In the second scene,
subjects interacted, flirted, and danced with computer controlled characters in a house party, and
made decisions about drinking alcohol. In the third scene, the player’s avatar was alone with a
character they selected in the previous scene, began foreplay, and had initial opportunities to
negotiate condom use. In the fourth scene, the player’s avatar was in the bedroom with the other
character, and negotiated manual, oral, and anal sex, anal sex positions, and condom use. In the
second run, the basic script was repeated, except that the scene took place at a bar rather than a
house party.
At frequent points throughout game play, a “future self” avatar interrupted the narrative
and urged the player to make safe sex choices. The message is a sex-positive message
emphasizing use of condom during anal sex, or non-penetrative sex, rather than unprotected anal
sex, to reduce the risk of spreading HIV. Safer sex choices included carrying a condom when
leaving the house, opting for oral or manual rather than anal sex, and opting to use a condom if
anticipating anal sex. Unsafe sex choices included opting for anal sex rather than oral or manual
sex if not using a condom has previously been agreed to. Figure 2 contains further information
about the choices considered “safe” or “unsafe”. Choices like choosing a sex role (top vs. bottom)
and alcohol use (beer vs. water) were not coded as relevant to safer sex choices.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

19

Figure 2. Procedure used to determine whether a sexually risky decision choice is safe or risky, taking into account the
context of the choice.

taking a
condom or
not?
→
Chose to
take a
condom?
Yes → SAFE

Chose
initiating
sex over
insisting
on safe
sex?

No → RISKY

Yes → RISKY

initiating sex
or insisting
on safe sex

Previously
agreed to
safe sex
Yes → NA

→

Previously
agreed to
unsafe sex
Yes → No → SAFE

No → No → NA

using a
condom or
not
→
Chose to
use a
condom?
Yes → SAFE

No → RISKY

Choice
is
between
…

condom, no
condom, or
alternative
sex activity?
→ Condom → SAFE

→ No Condom → RISKY

→ Alternative → SAFE

Chose
anal over
alternative
?
Yes → RISKY

anal or
alternative
sex activity
→
Previously
agreed to
safe sex
Yes → NA

Previously
agreed to
unsafe sex
Yes → No → SAFE

No → No → NA

safe or
unsafe anal,
alternative,
or leaving?
→ Safe → SAFE

→ Unsafe → RISKY

→ Alternative → SAFE

→ Leaving → SAFE

switching
positions, no
condom,
alternative,
or leaving
→ No condom → RISKY

→ Switching → RISKY

→ Alternative → SAFE

→ Leaving → SAFE

Measures
Game task measures
Four categories of tasks were identified. First, several times in the game, a computer
character offered the player choice between a beer or a water, and these decision were coded as
alcohol decisions. Second, prior to each anal sex scenario, players chose between taking the top
or bottom sex role. Third, subjects engaged in a number of choices that affected their likelihood
of having unsafe sex (Figure 2), and these were coded as sexually risky decisions (SRDs). Fourth,
subjects had a number of choices to make across all sections of the game, including decisions

20 Benjamin J. Smith
about what to say in conversation and decisions about what kind of sex to have. Any of these
decisions not affecting sexual safety as previously defined here were defined as “conversational”
decisions.
Self report measures
Subjects were asked to report experienced cravings for drugs and alcohol as well as a
Family, Friends, & Society scale, a Sexual Functioning and Meth Use scale, a Relationship
Interdependency Scale (RIS), a Mindfulness scale, an Attachment scale, the UPPS-P scale
(Lynam, Smith, Cyders, Fischer, & Whiteside, 2007) measuring Positive and Negative Urgency,
Lack of Premeditation, Lack of Perserverance, and Sensation-Seeking, a Big-5 Personality scale,
and a BIS/BAS scale (Carver & White, 1994).
Subjects also reported demographic information and other data related to sexual health
and their suitability for participation in an fMRI study.
Operationalizing the decision-making system
Anatomical regions of interest were defined hierarchically from the bottom up using the
Harvard-Oxford Cortical and Subcortical Atlases (FSL, 2014) and Deen, Pitskel, & Pelphrey's
(2011) three-parcel insula segmentations (Table 1). These Sub-regions are grouped into several
regions, and those regions are in turn grouped into reflective, integrative, reward, and insula
subsystems. Together, those subsystems make up the “decision-making system” (Figure 1).

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

21

Table 1. Hierarchical organization of terminology used in this article to denote systems, regions, and sub-regions of the
decision-making system.
System Region Subregion
Reflective dlPFC Superior frontal gyrus

Middle frontal gyrus

vlPFC Inferior frontal gyrus (pars opercularis)

Inferior frontal gyrus (pars triangularis)

Supplementary motor area Juxtapositional lobule cortex

Frontal pole Frontal pole

Hippocampus hippocampus

dmPFC Paracingulate Gyrus

Cingulate gyrus, anterior division
Integrative vmPFC Paracingulate Gyrus

Cingulate gyrus, anterior division

Frontal medial cortex

Subcollosal Cortex
oPFC Frontal Orbital Cortex
Impulsive Amygdala Amygdala

Striatum caudate

putamen
Nacc Accumbens
Insula Insular Anterior dorsal insular cortex

Anterior ventral insular cortex
Posterior insular cortex

Data Acquisition and processing
For each subject, MRI imaging data was collected over one or two sessions in a 3T Siemens
MAGNETOM Tim/Trio scanner at the University of Southern California Dana and David
Dornsife Neuroimaging Institute. In each session, a T1-weighted anatomical image, a DTI image,
and several task-related functional image sequences were collected.
Subjects lay supine on the scanner bed, and viewed visual stimuli back-projected onto a
screen through a mirror attached to the head coil. Foam pads were used to minimize head motion.
Stimulus presentation and timing of all stimuli and response events were achieved using Matlab
(Mathworks) and Psychtoolbox (www.psychtoolbox.org). Participants’ responses were collected
online using a MRI-compatible button box.

22 Benjamin J. Smith
Functional images were acquired using T2*-weighted (TR=2000 ms, TE=25 ms, 64x64
matrix size with a resolution of 3 mm2, using 41 3.0-mm axial slices) imaging. Functional tasks
collected over the two sessions were the CUPs task, a GoNoGo task, a Stroop task, the game task,
and two reward and punishment reversal learning tasks. Due to time constraints, not all tasks
were acquired from all participants.
fMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version
6.00, part of FSL (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl). Time-series statistical
analysis was carried out using FILM with local autocorrelation correction (Woolrich, Ripley,
Brady, & Smith, 2001). Subjects completed one or two runs of the game, depending on the
amount of time taken to complete the first run as well as other tasks during the scan session. As
described above, decision-making events were separated into 4 different categories. Regressors
were created for each decision category, as well as a fifth regressor describing all decisions. Each
regressor was compared against an implicit baseline in a general linear model. In addition,
alcohol, sex role, and sexually risky decisions were contrasted against conversational decision-
making in linear models, so in total, eight contrasts were examined. A temporal derivative was
added to each model and the result was convolved with a double-gamma HRF. Then, a fixed-
effects analysis calculated all 8 activity contrasts across both runs for each subject. Finally, a
simple OLS mixed-effects analysis combined results across all 107 subjects for 6 activity
contrasts (those based on alcohol, conversational, and sexually risky decisions) and across 86
subjects who had at least one sex role decision for 2 sex role activity contrasts. Z (Gaussianized
T/F) statistic images were thresholded using clusters determined by Z>2.3 and a (corrected)
cluster significance threshold of P=0.05 (Worsley, 2001).
Gameplay ran for approximately 15 minutes. A boxcar time series of decisions in each
run were obtained. Contrasts were then averaged across 2 runs, then across all 107 subjects in a
random-effects analysis, contrasting the 3 groups, and run for both whole-brain and ROI
analyses for each of the subsystems described (reward, deliberative control, integrative) above.
Results

In this section, behavioral results are reported first, followed by detailed descriptions of
activity in each contrast examined. Both the main effect for each task, and group contrasts for

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

23

each task are discussed. Then, the results are reported organized by region and in relation to the
original hypotheses. Finally, some post-hoc ROI analyses are described.
Behavioral
Self-reported real-life behavior.
Risky sex and meth use behavior for groups are described in Table 2 and Table 3.
Table 2. Risky sex behavior by group: mean and standard deviation of instances of unprotected anal intercourse in the
previous 90 days.

UAI90

M
SD
Safe-Sex-No-Meth 0 0
Risky-Sex-No-Meth 6.28 8.1
Risky-Sex-Meth 12.9 17.1

Table 3. Number of subjects with a given self-reported frequency of meth use in the last 3 months. Group inclusion
criteria was an affirmative answer to the question, “Have you ever used methamphetamine?”

Risky-Sex-Meth Group: Meth use in last 3 months
# Subjects 14 1 1 1 1 1 2 2 1 1
Frequency 0 3 4 5 6 8 12 16 26 30

Mean numbers of decisions.
The mean number of sexually risky decisions (SRDs) per subject was 7.30, and of those, the
mean number of unsafe choices made by each subject was only 0.32, indicating that in the game,
most of participants choices are safe ones. Because most decisions are safe—even decisions by
subjects in the two Risky Groups—it is unlikely the two risky groups will show less reflective-
system activity for risky decisions. Means and medians of the number and duration of each
decision type are described in Table 4. When modeled in the GLM, the entire decision duration
from presentation to choice selection was considered.SRDs took on average 8.1 s (SD=4.64);
conversational decisions 7.1 s (SD=4.5); sex-role decisions 4.0 s (SD=2.2) and alcohol decisions
3.5 s (SD=1.7) (Figure 3).

24 Benjamin J. Smith
Table 4. Behavioral statistics for each decision type.
alcohol conversational sexrole srd
Mean decisions per subject (N) 6.7
1.1
45.1
10.8
1.1
0.8
7.3
2.4
Median decisions per subject (N) 7.0

45.0

1.0

7.0

Mean decision duration (s) 3.5
1.7
7.1
4.5
4.0
2.2
8.1
4.6
Median decision duration (s) 3.2 6.4 3.5 7.0
Notes. Small type denotes standard deviation of adjacent figure.

Correspondence with real-life behavior.
Subjects who made at least one unsafe SRD during gameplay had more unprotected sex
in the previous 90 days (N=25, Mdn=5) than subjects who made no SRDs during gameplay
(N=96, Mdn=25), W=831.5, p=.016, r=.27, CI[-5.0,-0.0]. (Figure 4) Chosen in-game sex
positions (i.e., top or bottom) were correlated with sex positions taken in real life (r
s
[43]=0.764,
p<0.001; Figure 5). In-game alcohol consumption (Figure 6) was correlated with estimated
drinks per week (r
s
[121]=0.223, p<0.014) and negatively correlated with estimated time since
last drink (r
s
[121]=-0.208, p<0.023).

Figure 3. Frequency of game decisions by type.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

25

Figure 4. Unprotected anal sex in previous 90 days by game behavior.

Figure 5. In-game Sex-role chosen by self-reported real life behavior.

26 Benjamin J. Smith

Figure 6. Drinking frequency in real life in three different measures by drinking frequency in game.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

27

Neurological

This section reports activity for four categories of decision-making: sexually risky
decisions (SRDs), sex-role decisions, alcohol decisions, and conversational decisions. The SRD
decision type is the most directly applicable to hypotheses about risky sexual decision-making.
The sex-role decisions are also considered, because they represent decision-making with similar
or greater erotic salience than SRDs but without the strong risky decision-making component.
Game design explicitly instructed subjects that risky sex decisions were risky, but did not imply
any danger from alcohol decision-making, so alcohol decision-making was not made a salient
risk by the game design; however, alcohol decision contrasts are still described here.
The key contrasts here are the interaction contrasts between groups, particularly between
the Safe Sex Group and the Risky Sex Combined Groups, and particularly the SRD contrast.
Main effect contrasts for each decision type are first described to aid interpretation, and
additional contrasts are undertaken where they can shed light on ambiguities from the primary
interaction contrasts.
The conversational decision-making task provides a useful control for examining the
other tasks, as it represents decision-making under a condition of lesser erotic salience and at
least objective risk. In this section, the alcohol, sex-role, and SRD contrasts are often reported
simultaneously with and without the Conversational Control, which is simply comprised of the
Conversational main effect contrast. The objective for reporting contrasts with and without the
Conversational control is not to see how the two contrasts differ, but to gain a measure of
robustness of the results. It’s unclear whether activity occurring only with the Baseline Control is
occurring due to generalized decision-making activity or to the specific aspects of a particular
kind of decision, and observing conversational contrast in the same region helps to indicate the
result is really a result of the particular type of decision being made. Similarly, it’s difficult to
evaluate activity contrast occurring during only the Conversational Control, because it’s unclear
whether the contrast is due to differences in the Conversational Control across two conditions or
in the Decision Type of interest. Looking to see whether regions with activity controlled by the
Conversational activity control also contrast in the baseline control can help resolve whether the
difference is due to conversational activity or not.

28 Benjamin J. Smith
To quantify effects found in each region, whole-brain cluster analysis contrasts were
masked by each of the four decision-making subsystems (reflective, integrative, reward, and
insula). Because many of the clusters were dispersed across regions, this yielded a number of
sub-clusters not contiguous with one another for each main cluster. The peak z-stat magnitude
and location of each contiguous sub-cluster is reported, in mm in MNI space. These can be
treated thought of as local maxima for the four specific decision-making subsystems.
Main effects by decision type and group.
There were strong main effects of activity for SRDs, sex-role decisions, and alcohol
decisions contrasted with the Conversational Control. Some DLPC contrast was observed across
all three of these decision types, but presence of reward system and integrative system activity
contrast was more specific to particular decision types. All results in this section describe
contrasts with the Conversational Control, since the main effect without that control is not
informative.
Overall, SRD, alcohol, and sex-role main effect contrasts with Conversational Control
indicated decision-making processing during those three Decision Types differed from the
conversational decisions with which they were contrasted. Sex-role decisions, but not SRDs, had
stronger striatal activity than Conversational Controls. All three decision types showed at least
some additional lateral prefrontal cortex activity contrast with Conversational Control, indicating
additional controlled activity contrast.
Conversational activity. Figure 7 shows there was extensive decision-making network
activity throughout the Conversational task. Using the conversational task as a control to the
other three Decision Type tasks offers a valuable check on whether activity is simply arising as a
result of selecting items from a menu or whether there is additional activity arising from the
particular kind of decision being made.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

29

Figure 7. Conversational-Baseline main effect contrast across all 3 groups. Conversational activity was used as a contrast
while analyzing other three Decision Types. Highlighted regions are activity contrast over the z>2.3 threshold that met the
corrected cluster significance threshold of p<0.05.
Main Effects: SRDs (Figure 8).There was SRD dorsal bilateral prefrontal cortex activity
contrast with the Conversational Control across the three Risk groups (13973 voxels; z-max =
7.52 at [30, 58, 20]) extending down to the inferior frontal gyrus (142 voxels; z-max = 4.82 at
[52, 20, -2]). There was also some evidence of VMPC (215 voxels, z-max=5.4 at [8, 50, 4]) and
anterior insula (left: 131 voxels; z-max=6.66 at [-30, 20, -8]; right: 63; z-max = 5.51 at [32, 30, -
8]) activity. Overall, the result indicates a more active decision-making system for SRDs
compared to the Conversational Control.
Activity was present across the striatum, from the intersection of the right putamen and
caudate (120 voxels; z-max = 3.83 at [18, 12, -4]) and the intersection of the right putamen and
thalamus (30 voxels; z-max = 4.00 at [10, 0, 12]) to the left putamen and nucleus accumbens
(110 voxels; z-max=3.56 at [-16, 16, -8]) and caudate (57 voxels; z-max=3.63 at [-8, 0, 10]).

30 Benjamin J. Smith

Figure 8. SRD-Conversational main effect contrast across all 3 groups. Highlighted regions are activity contrast over the
z>2.3 threshold that met the corrected cluster significance threshold of p<0.05.
Main effects: Alcohol decisions. The Alcohol decision contrast (choosing between water
and beer) did not show additional reward system contrast with the Conversational Control. The
lack of striatal activity could suggest decision-making less driven by experience of intrinsic
reward (Figure 9).. There was strong dorsal frontal pole activity (e.g., 1815 voxels; z-max=5.23
at [46, 46, 10]) and some VMPC activity (e.g., 246 voxels; z-max=7.09 at [-24, 34, -14]) present,
suggesting both controlled-system thought and valuation processes.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

31

Figure 9. Alcohol-Conversational main effect contrast across all 3 groups. Highlighted regions are activity contrast over
the z>2.3 threshold that met the corrected cluster significance threshold of p<0.05.

Main effects: Sex-role decisions (Figure 10). Like the alcohol decisions and SRD, the
sex-role decision contrasts showed evidence of prefrontal cortex activity for all risk groups. They
also showed VMPC and right insula activity. In addition to strong amygdala activity, there was
also strong evidence of bilateral caudate activity in this Decision Type, unlike for other Decision
Type contrasts.

32 Benjamin J. Smith

Figure 10 Sex-role-Conversational main effect contrast across all 3 groups. Highlighted regions are activity contrast over
the z>2.3 threshold that met the corrected cluster significance threshold of p<0.05.
Risk Group contrast effects by decision type.
To evaluate Risk group comparisons of activity for each decision type, it was possible to
examine both baseline and Conversational control contrasts. Baseline control contrasts are useful
for measuring overall group differences encapsulating all relevant features of a decision-making
process, while the Conversational Control allows us to examine contrast unique to a specific type
of decision. Table 5 describes activity found in contrasts between the Safe-Sex and Combined-
Risky-Sex Groups.
Risk Group contrasts for the conversational decision type.
It is important to examine conversational decision-making activity contrasts because
other decisions are considered using conversational decision-making as a control.
There were no decision-making system differences between the Safe-Sex and the Risky-
Sex-No-Meth Groups during conversational decision-making. However, there were Safe-Sex >
Risky-Sex-Meth differences. The Safe-Sex > Risky-Sex-Meth contrast (Figure 11) showed
activity in the integrative system VMPC (e.g., 95 voxels; z-max = 3.92 at [-10, 50, -2]) and OFC
(left: 46 voxels; z-max = 3.13 at [40, 20, -8]; right: 27 voxels; z-max=3.2 at [-42, 34, -8] and 19

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

33

voxels; z-max=3.01 at [-32, 28, 2]), some reflective system activity (e.g., 478 voxels; z-
max=3.81 at [38, 50, 32] and 210 voxels; z-max=3.05 at 42, 52, -6]), and reward system activity
(e.g., 225 voxels; z-max=3.67 at [-18, 8 -10]. This effect was also present in the left anterior
insula (63 voxels; z-max=3.22 at [-38, 18, -2]) in the Safe-Sex > Combined-Risky-Sex contrast
(Figure 11, blue highlighted areas). There is additional right insula-temporal activity in the
Risky-Sex-No-Meth > Risky-Sex-Meth contrast (151 voxels; z-max=3.89 at [-34, 2, -12]) and
additional Safe-Sex > Risky-Sex-Meth activity in the frontal pole and right insula (e.g., 91
voxels; z-max=3.89 at [-40, 16, -2]).
Because the conversational decisions are used here as controls for other decision contrasts,
Risk Group conversational differences need to be kept in mind. Any Combined-Risky-Sex >
Safe-Sex left insula activity and Risky-Sex-No-Meth > Risky-Meth right insula activity contrast
when using conversational decisions as a control need to be compared to contrasts with a
Baseline Control to ensure the effect goes beyond the conversational group difference.

34 Benjamin J. Smith

Figure 11. Safe-Sex > Risky Sex Groups (considered separately and together) during Conversational Decision-making.
Highlighted regions are activity contrast over the z>2.3 threshold that met the corrected cluster significance threshold of
p<0.05.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

35

Group interaction effects for sex-role decisions. There was no evidence for decision-
making activity specific to sex-role judgments here. Although sex-role decision-making is an
interesting contrast, they are not directly relevant to our hypotheses. For these reasons, sex-role
decision contrasts will not be considered further.

Figure 12. Combined-Risky-Sex > Safe-Sex groups during Sex-role decision-making. Highlighted regions are activity
contrast over the z>2.3 threshold that met the corrected cluster significance threshold of p<0.05.

36 Benjamin J. Smith
Group interaction effects for SRDs. These effects must be examined closely because
they are most relevant to the hypothesis for this current study. All significant effects observed
between Safe-Sex and both Risky Sex groups during SRD, for both Conversational and baseline
Control, were additional activity in the risky groups compared to the safe group. There was no
additional decision-making activity in the reverse direction, i.e., additional activity for Safe-Sex >
Risky-Sex groups (Table 5). Some activity only occurred during the Conversational Baseline,
and this activity needs to be considered in light of the Conversational Safe-Sex > Risky-Sex
contrast (Figure 11).

Table 5. Risky-Sex-Combined and Safe-Sex contrasts, along with any activity in decision-making regions, with SRD,
Alcohol and Sexrole Decision Types with conversational or baseline controls. L=Left; R: Right.
Decision
Type
Voxel
size
-log10
(p-value)
Z-max
Z-max (mm)
COPE-
MEAN
Decision-making
regions covered
Group Contrast X Y Z
[Risky Sex
Combined] >
[Safe Sex]
SRD Conversational 1628 6.0 4.4 -46 -18 16 12.4 L insula

1480 5.5 4.19 70 -16 2 20.8 R insula

Baseline 1727 6.4 3.93 -30 -10 22 13.7 L posterior insula

1460 5.5 3.95 66 -18 0 23.5

846 3.2 4.22 62 -66 6 25.3

512 1.8 4.19 30 -16 -8 17.7 R insula, putamen
432 1.4 3.74 -36 -50 -6 17
Alcohol Conversational
(No contrast)

Baseline
Sexrole Conversational 1326 7.2 3.92 58 -66 -14 82.6

599 3.4 4.06 -14 -76 -36 68.9

425 2.3 3.31 0 -74 48 67.5

Baseline 593 3.2 3.85 28 -76 -18 87.8

512 2.7 3.48 -18 -92 38 63.1

444 2.3 3.71 -16 -76 -30 67.4
[Safe Sex] >
[Risky Sex
Combined]
SRD Conversational
(No contrast)

Baseline
Alcohol Conversational
(No contrast)

Baseline 658 2.3 3.73 -44 12 10 29 L insula
Sexrole Conversational
(No contrast)

Baseline

Combined-Risky-Sex Group > Safe-Sex. Activity in the bilateral insula (Table 6; Figure
13), right superior temporal gyrus (Conversational control 263 voxels; z-max=4.18 at [70, -16, 2])
and temporal pole (Conversational control, across 2 sub-clusters, 65 voxels; z-max=3.15 at [50, 8,
-10]) was observed in the Combined-Risky-Sex Group > Safe-Sex Group for both controls
(Figure 13). Posterior cingulate gyrus (34 voxels; z-max=3.47 at [-14, -46, 34]) and anterior

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

37

rather than posterior insula activity was observed when the Conversational Control rather than
Baseline control was used. The group contrast using the Baseline Control showed precuneus
cortex (Baseline Control 248 voxels across 5 sub-clusters; z-max=3.19 at [-18, -60, 24]) activity.
Effects were considered further to determine whether they were driven equally by both Risky
Sex groups.
Table 6. Regions, voxels, peak position and magnitude for each contiguous sub-cluster within the insula in the SRD >
Conversational, Risky-Sex-Combined > Safe-Sex Group comparison.
X Y Z
Left anterior dorsal insula 10 3.03 -34 6 6
anterior dorsal insula 1 2.32 -40 10 -2
posterior insula 1 2.31 -40 -18 10
Right anterior dorsal insula 181 3.78 34 14 -8
posterior insula 23 3.19 42 -16 4
Left anterior ventral insula 6 2.72 -40 -10 10
Right anterior ventral insula 101 3.74 42 -16 4
posterior insula 1 2.42 38 -22 16
Location Voxels
Peak
z-stat
mm

Risky-Sex-Meth > Safe-Sex. Comparing Risky-Sex-Meth > Safe-Sex subjects with
Baseline Control (Table 7), activity was observed in the right posterior insula and right temporal
gyrus, and the right central opercular cortex and precuneus cortex. This is similar to the
Combined-Risky-Sex > Safe-Sex Groups comparison, though different cluster in the precuneus
cortex reached significance. Some of this insula activity contrast could be driven by differences
observed in conversational insula activity (Figure 8) but SRD insula contrast remains even when
using Baseline Control.
Meth use differences. Results suggest that Meth-using subjects used the DLPC more
during the risky sex task compared to the non-risky sex task. Comparing Risky-Sex-No-Meth >
Safe-Sex Subjects, there was no significant contrast found. Comparing Risky-Sex-Meth > Risky-
Sex-No-Meth subjects (Table 7), there was only activity contrast when using the Conversational
Control (Figure 14). In that case, temporal gyrus, striatal (750 voxels across 9 sub-clusters; z-
max=3.94 at [-14, 8, 10]), and DLPC contrast (e.g., 3610 voxels; z-max=4.2 at [44, 18, 48]), but
no significant additional insula activity, was observed. Considering that the Safe-Sex > Risky-
Sex-Meth contrast showed additional conversational activity in the OFC, temporal cortex, and
striatum (Figure 11), the SRD differences observed with the conversational control (Figure 14) in

38 Benjamin J. Smith
those regions might not reflect real differences in conversational decision-making. Conversely,
in the DLPC, there was much more Risky-Sex- Meth > Risky-Sex- No-Meth contrast than
conversational decision-making activity contrast (Figure 11), so the extra Risky-Sex-Meth
activity in the DLPC may reflect real differences between the Risky-Sex-Meth and Risky-Sex-
No-Meth groups, i.e., a difference correlated with math use while controlling for Risky Sex.
SRD Interaction Summary. In summary, the Combined-Risky-Sex > Safe-Sex insula
contrast was observed for either baseline. Although the Risky-Sex-No-Meth > Safe subjects
contrast did not show significant activity, insula contrast was not observed in the Risky-Sex-
Meth > Risky-Sex-No-Meth group contrast either. Additionally, at least some of the activity that
was observed in the Risky-Sex-Meth > Risky-Sex-No-Meth contrast could be explained in terms
of greater conversational activity for Risky-Sex-No-Meth subjects. For these reasons, it seems
clear the insula contrast observed does reflect a difference between Risky Sex and safe sex
subjects rather than between meth-using and non-meth-using subjects.
Some of the precuneal-posterior temporal cingulate activity could be a result of the
contrast between meth using and non-meth-using subjects.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

39

Table 7. Risky Non-meth and Risky meth contrasts, along with any activity in decision-making regions, with SRD,
Alcohol and Sexrole Decision Types with conversational or baseline controls. L=Left; R: Right; DLPC=dorsolateral
prefrontal cortex; FOC=frontal orbital cortex; SFG, MFG, IFG: Superior, middle, inferior frontal gyrus.

Voxel
size
-log10
(p-
value)
Z-max
Z-max (mm)
COPE-
MEAN
Decision-making regions
covered
Contrast X Y Z
[Risky Sex
Meth] >
[Risky Sex
No Meth]
SRD
Conversational 16999 4.49 58 24 -2 18.3 R DLPC, frontal pole, R
caudate, putamen, R posterior
insula, R FOC

1894 6.75 4.14 -18 -2 26 16.4 Frontal pole, L caudate,
putamen

720 2.68 3.83 6 38 28 16.4 SFG, paracingulate gyrus

459 1.5 3.87 -52 -36 -10 19.3

Baseline (No contrast)
Alcohol
Conversational (No contrast)

Baseline

Sexrole
Conversational (No contrast)

Baseline
[Risky Sex
No Meth] >
[Risky Sex
Meth]
SRD
Conversational (No contrast)

Baseline
Alcohol
Conversational 1724 6.45 3.95 -24 -80 36 25.8 Cuneal cortex

652 2.47 3.6 14 -46 -2 29.3 Precuneus cortex

564 2.06 4.48 -38 -6 -8 26.1 L posterior insula cortex

520 1.86 3.82 10 -44 44 27.3

Baseline 10205 24.2 5.12 -24 -80 36 31.2 bilateral caudate & putamen

2303 7.78 4.71 -38 -6 -8 29.2 L insula, putamen

998 3.65 4.03 36 24 58 31.7 R SFG, MFG, IFG

685 2.42 3.87 40 48 -6 27.5 R frontal pole, FOC

614 2.12 4.04 -12 -76 -6 38.8

573 1.94 3.49 -30 56 -10 27.9 L frontal pole, FOC

453 1.39 3.91 -30 14 64 31.5 L MFG

Sexrole Conversational
(No contrast)

Baseline

40 Benjamin J. Smith

Figure 13. Combined-Risky-Sex > Safe Subjects Group contrast during SRD using the Baseline (red) and Conversational
(blue) Control. Highlighted regions are activity contrast over the z>2.3 threshold that met the corrected cluster
significance threshold of p<0.05.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

41

Figure 14. Risky-Sex-Meth > Safe-Sex Group contrast during SRD using the Conversational Control (blue) and Baseline
Control (red). Highighted regions are activity contrast over the z>2.3 threshold that met the corrected cluster significance
threshold of p<0.05.

42 Benjamin J. Smith

Figure 15 Risky-Sex-Meth > Risky-Sex-No-Meth Subjects whole-brain activity contrast during SRD; SRD >
Conversational in red; no significant SRD > Baseline contrast found.. Highlighted regions are activity contrast over the
z>2.3 threshold that met the corrected cluster significance threshold of p<0.05.”

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

43

By region: SRD activity in areas of interest
Of the four different Decision Types measured, only SRDs showed theoretically
interesting activity contrasts between groups, and these are described below.
Right insula. The risky meth group has significantly more insula activity compared to the
safe group, regardless of the baseline used. Although combining the Combined-Risky-Sex>
Safe-Sex Groups contrast does show anterior insula activity, there are no significant contrasts
between the Risky-Sex-No-Meth group and either of the other groups. The mean of activity
within the right insula was compared between the two groups. Using the Baseline Control, across
the right insula as a whole, there were significant differences between the Safe-Sex and the
Risky-Sex-No-Meth group (t[53]=-2.02, p<0.05), and between the Safe-Sex and Risky-Sex-Meth
group (t[62]=-2.14, p<0.05) but not between the two Risky Sex groups (t=-0.45, p>0.05). This
difference did not appear when using the Conversational Control; only the difference between
the Safe-Sex > Risky-Sex-Meth contrast was significant (t[56]=-2.612, p<0.05). Although the
Risky-Sex-Meth > Risky-Sex-No-Meth contrast did show heightened right insula activity using
the Conversational Control, further analysis is needed to show the the effect is not driven by
conversational activity between those two groups.
Dorsolateral prefrontal cortex. There was significant right DLPC activity in the Risky-
Sex-Meth > Safe-Sex contrast regardless of the Control used (Figure 14). There is a difference in
dorsal prefrontal cortex use with the Risky-Sex-Meth group appearing to have more dorsal
prefrontal cortex activity than the Risky-Sex-No-Meth group (Figure 15
)
. Taken together, these
two results result seem to clearly indicate greater right DLPC activity for the Risky-Sex-Meth
group compared to the other groups. Because the Risky Meth subjects did not significantly differ
from the other subjects in proportion of SRDs made (t[78.9]=-0.31, p>0.05), it could be that
these subjects need to employ additional effort to exert the same response inhibition.
Striatal activity. There appeared to be little or no striatal activity contrast between the
Risky-Sex groups and the Safe-Sex subjects using the Baseline Control. Although the Risky-
Sex-Meth group did show additional SRD striatal activity compared to the other two groups
using a Conversational Control, this can be explained by additional striatal activity for the
conversational data for both No-Meth groups (Figure 11). It appeared that No-Meth subjects
experienced more striatal activity during ordinary conversational activity than did Meth subjects

44 Benjamin J. Smith
(875 voxels over 9 sub-clusters; z-max = 4.18 at [28, 2, 6]. Meth users scored significantly
higher on a sensation-seeking scale than non-meth users (t[55]=-2.51, p=0.012), consistent with
the notion these subjects are high sensation-seekers that require a high level of stimulation to be
excited.
VMPC. There did not appear to be any differences in VMPC processing using the
baseline contrast, and SRD contrasts with the Conversational Control could be explained in
terms of conversational processing differences.
Hypotheses
The results described above were considered in relation to the hypotheses described in the
methods section of this document.
H1: Differential Reflective-system activity for risky subjects compared to safe subjects.
Whole-brain contrasts during SRD decisions using the Conversational Control showed
significantly more DLPC activity (Figure 8), suggesting that subjects did engage in deliberative
control processing more for SRDs than conversational decisions. However, there was no
significant difference in DLPC activity during SRDs for risky compared to safe subjects (Figure
13, Figure 15), leaving H1 unsupported.
H2: Differential reward-system activity for risky subjects compared to safe subjects.
Main effects contrasts during SRD decisions using the Conversational Control showed
significantly more striatal (caudate, left putamen) activity (Figure 8), which suggests that SRDs
(made during sex scenes), or the context in which they are made, stimulate the reward system
more than conversational decisions (during other scenes). Significantly more striatal (right
posterior putamen) activity during the SRD Combined-Risky-Sex > Safe-Sex group contrast was
observed (Figure 13), but only when not using the Conversational Control. Because no
significant differences in conversational activity were observed for this region, there’s not
evidence that the Conversational Control might be causing the effect, so the additional striatal
activity in the Risky Sex group seems like some support for H2.
H3: Differential insula activity for risky subjects compared to safe subjects. Main
effect SRDs contrasts with the Conversational Control showed significantly more bilateral insula
activity (Figure 13), suggesting an insula reaction to SRDs compared to other decision-making.
Significantly more posterior right insula activity was observed during the SRD Combined-Risky-
Sex > Safe-Sex subjects regardless of control (Baseline or Conversational), and while using the

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

45

Conversational Control, anterior right insula activity was also observed. However, because the
Safe-Sex group showed significantly more conversational activity in this area (Figure 11) than
the Risky-Sex-Meth subjects, it could be suggested the significant SRD contrast with a
Conversational Control may be due to conversational activity difference. To test whether right
anterior insula activity could be observed even without the Conversational Control, the contrast
means of the anterior ventral insula cortex from the Safe-Sex and Combined-Risky-Sex groups
were compared using the baseline contrast; significant anterior ventral (t[50]=2.18, p=0.036) and
marginally significant anterior dorsal (t[50]=1.97, p=0.054) activity contrast was observed
(Figure 16). Thus, H3 is supported.

46 Benjamin J. Smith

Figure 16. Insula activity by location and Risk group (Safe-Sex or Combined-Risky-Sex), using the Baseline Control.
H4: Abnormally striatal and inferior-frontal activity for meth users. SRD Main effect
contrasts with the Conversational Control showed significantly more bilateral DLPC activity,
suggesting that subjects did engage in more controlled processing about SRDs compared to
conversational decisions. Significantly more right DLPC activity was observed during SRDs for
meth users compared to each of the other groups, regardless of task contrast (baseline or
conversational), except that no activity contrast was found for the SRD Risky-Sex-Meth >
Risky-Sex-No-Meth contrast using the Baseline Control. No significant differences in

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

47

conversational activity were observed for the region, so the Conversational Controlled difference
can't easily be attributed to differences in the conversational task. To test whether DLPC contrast
between the Risky-Sex-Meth and Risky Sex No Math could also be observed during the baseline
task contrast, the dorsolateral portion of the activity cluster found for the Risky-Sex-Meth –
Risky-Sex-No-Meth using the Conversational Control was tested for a significant difference in
the contrast using the Baseline Control. There remained a significant DLPC activity contrast
(t[56]=2.51, p=0.014; Figure 17). Thus, H4 appears to be supported.

Figure 17. DLPC activity by Meth Use group for Risky Subjects (Risky-Sex-No-Meth-Group vs. Risky-Sex-Meth Group).

Trait-level personality explanations
In order to search for possible explanations for the observed differences in Safe-Sex and
Combined-Risky-Sex groups during SRDs, 25 personality subscale values were tested for a
correlation with the real life incidences of risky sex measure (Table 8). Using familywise error
rate correction (Benjamini & Yekutieli, 2001) for 25 multiple comparisons, there were 5
significant correlations with real life incidences of risky sex at the p<0.05 level. Negative

48 Benjamin J. Smith
urgency, lack of premeditation, positive urgency, neuroticism, and withdraw were all directly
related to risky sex rate. Negative urgency (r
s
=0.41, p<0.0001 uncorrected) was notable for the
strongest relationship with risky sex.
Because the SRD contrast was a dichotomized contrast between risky and safe subjects,
the trait level correlation tests were re-run as t-tests to examine whether there was any difference
in the personality correlations when real life incidences of risky sex was treated as a
dichotomized value, as with the SRD contrast. Negative urgency was similarly the strongest
contrast (t=3.51, p
cor
<0.001) and the four factors with p<0.05 in Table 8 showed a significant
(p
cor
<0.01) difference between the risk groups, although attachment anxiety was only significant
(p<0.05) at the uncorrected level.
Table 8 Risky sex (UAI90) correlations with personality variables. Using Benjamini-Hochberg False discovery rate
correcting for 50 multiple comparisons, correlations denoted with † p<0.1, * p<0.05, **p<0.01, *** p<0.001 indicating
corrected p-values.
Personality Factor
r
s

Attachment Anxiety 0.235 †
UPPS Negative Urgency 0.407 ***
UPPS Lack of premeditation 0.295 *
UPPS Positive Urgency 0.303 *
Big5: Neuroticism 0.269 *
Big5: Neuroticism/Withdrawal 0.302 *

As the insula is thought to be associated with desire and urgency in particular (Xue, Lu,
Levin, & Bechara, 2010), and because the insula is the primary decision-making system item
which has activity in this task, the insula makes an ideal place to start examining the relationship
between risky sex and urge. Indeed, the insula is active during the SRD contrasts both with
Conversational and Baseline control, so would be a very plausible mediator for the relationship. I
examined the relationship between these negative urgency and the clusters of significant
Combined-Risky-Sex > Safe-Sex activity contrast. FSL's meants function was used to extract
the mean activity contrast of the two clusters.
Overall, FSL detected two clusters in the SRD-CON, Combined-Risky-Sex > Safe-Sex
Group contrast. The left hemisphere cluster stretches over the insula, operculum cortex, posterior
cingulate gyrus, and precuneus cortex (1334 voxels; z-max = 4.36 at [-46, -18, 16]), while the
right hemisphere cluster (1407 voxels; z-max = 4.18 at [70, -16, 2]), stretches from the frontal

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

49

orbital cortex to the insula, operculum cortex, precentral gyrus, and superior temporal gyrus.
Each cluster was tested for a relationship with urge; for the left hemisphere cluster, the
relationship was strongly significant (SRD-Baseline: r=0.35, p<0.001; SRD-CON: r=0.35;
p<0.001). The relationship between left insula and trait-level urge was tested. There was a
relationship between regions of the left insula active during the SRD with Baseline Control
contrast and trait-level urge (r=0.23, p<0.05; Figure 19; Table 6), and between regions of the left
insula active during the SRD with Conversational Control contrast (r=0.23, p<0.05; Figure 18;
Table 6). Examining 3 components of the left insula in their entirety, only the left posterior
insula cortex showed a significant relationship with negative urge, r
s
=0.23, p<0.05.
In the test, right insula activity (Table 6) was positively related to negative urgency, but
not significantly (r=0.18, p<0.1). The relationship between each of the 3 right insula anatomical
components and urge was tested; only the right posterior insula cortex showed a significant
relationship with negative urge, r
s
=0.23, p<0.02. Taken together with the strong correlation
between negative urgency and the left hemisphere cluster described above, this evidence of
significant relationships between the left and right posterior insula and negative urgency suggests
that the relationship may be mediated primarily by the posterior, not anterior insula, combined
with brain regions which could include the right temporal cortex, opercular cortex, and
precuneus cortex. These relationships could work in tandem with the insula to produce feelings
of negative urgency during SRD.
Negative urgency could explain the Combined-Risky-Sex > Safe-Sex contrast. Negative
urgency tests the extent to which subjects can control their feelings and actions under pressure; a
high score indicates a strong sense of urgency and corresponding lack of control. The more
highly a subject scored on the negative urgency scale, the higher their activity contrast in regions
that set apart risky subjects from safe subjects during the SRD task (compared to conversational).
Taken together with the context—negotiating safer sex practice—this suggests that engaging in
risky sex could be driven by a lack of control in a negative situation. Given the relationship with
negative urgency, the activity contrast observed is likely related to subjects' lack of ability to
control feelings under pressure. Rather than being simply driven by sexual excitement to unsafe
behavior, our data suggests that a sense of negative could be related to unsafe sexual practice.

50 Benjamin J. Smith
The network observed in the SRD-CON Combined-Risky-Sex > Safe-Sex Group
Contrast does overlap with regions described as parts of the mentalizing system. Specifically,
there evidence of temporal pole contrast, strong superior temporal sulcus activity, described as
part of a network uniquely making up animation-induced mentalizing (Lieberman, 2010), along
with the fusiform gyrus, which was not observed here. When not controlling for conversational
decision-making, activity in the precuneus, also implicated in decision-making (Lieberman, 2010)
was also observed. All this suggests that risky subjects were involved in extra animation-
induced—rather than reflective—mentalizing.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

51

Figure 18. Relationship between Left hemisphere cluster 2 Combined-Risky-Sex > Safe-Sex Groups, contrast during SRD,
using the Conversational Control. Activity maps show activity from both clusters that occurred within the insula.

52 Benjamin J. Smith

Figure 19. Relationship between Left hemisphere cluster 2 Combined-Risky-Sex > Safe-Sex Groups, contrast during SRD,
using the Baseline Control. Activity maps show activity from both clusters that occurred within the insula.

Insula activity during safe-sex decision-making in sexually risky men suggests negative
urgency and fear of rejection drives risky sexual behavior

53

Conclusion
This study is the first showing that computer game simulations may be used in fMRI
scanners to perform experiments with a high level of ecological validity. The study also shows
that existing theory on the decision-making system applies to decision-making about risky sex in
a real-life context. It suggest that trait negative urgency, mediated by insula, posterior cingulate
cortex, and right superior temporal sulcus during SRD, may be responsible for more risky sexual
behavior.
Main effect task contrasts with the conversational decision-making showed activity in the
major areas of the decision-making system, including reflective system activity, integrative
system activity, reward system activity, and the insula. This suggests that the three decision-
making tasks—alcohol, sex-role, and SRDs—really are, on aggregate more demanding on
subjects to make decisions.
Very few subjects made risky choices in the game. It's not known how many more risky
choices would have occurred, had there not been active reminders about the dangers of risky sex
in the game. It can be safely assumed that the safe sex lesson reminders embedded in the game
do prime subjects to be considering safe sex during game sex situations. Although some
literature (Miller & Read, 2005) suggests such a game is effective in lowering future sexual
decision-making rates, so that it appears that the decision-making during the game is somewhat
similar to real-life decision-making, the game does force risk considerations in a way that don't
appear in real life. In some instances, where subjects make a risky decision, they immediately see
a “future self” character who will admonish them for not making a safe choice, or show ominous
signs of future illness, and sometimes both. This allows us to be confident about the trade-offs
that subjects are experiencing as they consider SRDs in gameplay.
Subjects who make more risky decisions in real life may be more influenced by these
interventions than others. Although subjects who made more risky game decisions were the same
subjects making more risky real-life choices, all subjects, including sexually risky subjects, made
mostly safe choices. This may be a result of the intervention protocol, but whether or not this is
the case, it's clear that across groups, despite little or no variance in actual subject decision-
making outcomes during gameplay, fMRI results show that the way in which subjects arrived at

54 Benjamin J. Smith
those outcomes does appear to differ between groups. These differing pathways may influence
real-life behavior and sexual risks that subjects take.
There appeared to be a few key differences in sexually risky decision-making (SRD)
between groups. First, there was additional insula activity in the risky groups compared to the
safe group. This may indicate that subjects in the risky groups face off a stronger desire signal
when making their decision. However, an ROI analysis of the insula appears to suggest a
different reason for this insula activity. Negative urgency, also related to incidences of real-life
risky sex, also appeared to have a relationship with insula activity in the region that differed
between game subjects. For this reason, it seems likely the additional insula activity was due in
part to additional negative urgency felt in an SRD situation by riskier MSM. More broadly, this
may provide the first neural evidence for a relationship between risky sex and a negative urgency,
a relationship already found behaviorally (Simons, Maisto, & Wray, 2010). A network
suggestive of animated mentalizing, including the superior temporal sulcus and posterior
cingulate (Lieberman, 2010) was concurrently active specifically for SRDs. This supports the
interpretation that a negative urgency feeling, prompted by fear about partner’s reaction to safe
sex negotiation, might lead to some of the risky sexual behavior seen in our subjects.
Meth-using subjects appear to have more activity in their DLPC, striatal, and insula
regions more than the other subjects during sexually risky decisions. Further analysis is needed
to examine why. During this task, where meth users are not making more unsafe decisions than
other subjects, meth users may be differentially recruit the DLPC just to reach the same level of
control.

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urgency and fear of rejection drives risky sexual behavior

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Core Title Insula activity during safe-sex decision-making in sexually risky men suggests negative urgency and fear of rejection drives risky sexual behavior

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Publication Date 09/03/2015

Defense Date 06/23/2015

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