Sex and the single amygdala: A tale almost saved by a peek at the data

So sexy! Was bringing up ‘risky sex’ merely a strategy to publish questionable and uninformative science?

wikipedia 1206_FMRIMy continuing question: Can skeptics who are not specialists, but who are science-minded and have some basic skills, learn to quickly screen and detect questionable science in the journals and media coverage?

You don’t need a weatherman to know which way the wind blows.” – Bob Dylandylan wind blows

I hope so. One goal of my blogging is to arouse readers’ skepticism and provide them some tools so that they can decide for themselves what to believe, what to reject, and what needs a closer look or a check against trusted sources.

Skepticism is always warranted in science, but it is particularly handy when confronting the superficial application of neuroscience to every aspect of human behavior. Neuroscience is increasingly being brought into conversations to sell ideas and products when it is neither necessary nor relevant. Many claims about how the brain is involved are false or exaggerated not only in the media, but in the peer-reviewed journals themselves.

A while ago I showed how a neuroscientist and a workshop guru teamed up to try to persuade clinicians with functional magnetic resonance imaging (fMRI) data  that a couples therapy was more sciencey than the rest. Although I took a look at some complicated neuroscience, a lot of my reasoning [1, 2, 3] merely involved applying basic knowledge of statistics and experimental design. I raised sufficient skepticism to dismiss the neuroscientist and psychotherapy guru’s claims, Even putting aside the excellent specialist insights provided by Neurocritic and his friend Magneto.

In this issue of Mind the Brain, I’m pursuing another tip from Neurocritic about some faulty neuroscience in need of debunking.

The paper

Victor, E. C., Sansosti, A. A., Bowman, H. C., & Hariri, A. R. (2015). Differential Patterns of Amygdala and Ventral Striatum Activation Predict Gender-Specific Changes in Sexual Risk Behavior. The Journal of Neuroscience, 35(23), 8896-8900.

Unfortunately, the paper is behind a pay wall. If you can’t get it through a university library portal, you can send a request for a PDF to the corresponding author,

The abstract

Although the initiation of sexual behavior is common among adolescents and young adults, some individuals express this behavior in a manner that significantly increases their risk for negative outcomes including sexually transmitted infections. Based on accumulating evidence, we have hypothesized that increased sexual risk behavior reflects, in part, an imbalance between neural circuits mediating approach and avoidance in particular as manifest by relatively increased ventral striatum (VS) activity and relatively decreased amygdala activity. Here, we test our hypothesis using data from seventy 18- to 22-year-old university students participating in the Duke Neurogenetics Study. We found a significant three-way interaction between amygdala activation, VS activation, and gender predicting changes in the number of sexual partners over time. Although relatively increased VS activation predicted greater increases in sexual partners for both men and women, the effect in men was contingent on the presence of relatively decreased amygdala activation and the effect in women was contingent on the presence of relatively increased amygdala activation. These findings suggest unique gender differences in how complex interactions between neural circuit function contributing to approach and avoidance may be expressed as sexual risk behavior in young adults. As such, our findings have the potential to inform the development of novel, gender-specific strategies that may be more effective at curtailing sexual risk behavior.

My thought processes

Hmm, sexual risk behavior -meaning number of partners? How many new partners during a follow-up period constitutes “risky” and does it matter whether safe sex was practiced? Well, ignoring these issues and calling it “sexual risk behavior “allows the authors to claim relevance to hot topics like HIV prevention….

But let’s cut to the chase: I’m always skeptical about a storyline depending on a three-way statistical interaction. These effects are highly unreliable, particularly in a sample size of only N = 70. I’m suspicious why investigators ahead of time staking their claims on a three-way interaction, not something simpler. I will be looking for evidence that they started with this hypothesis in mind, rather than cooking it up after peeking at the data.

fixed-designs-for-psychological-research-35-638Three-way interactions involve dividing a sample up into at eight boxes, in this case, 2 x (2) x (2). Such interactions can be mind-boggling to interpret, and this one is no exception

Although relatively increased VS activation predicted greater increases in sexual partners for both men and women, the effect in men was contingent on the presence of relatively decreased amygdala activation and the effect in women was contingent on the presence of relatively increased amygdala activation.

And then the “simple” interpretation?

These findings suggest unique gender differences in how complex interactions between neural circuit function contributing to approach and avoidance may be expressed as sexual risk behavior in young adults.

And the public health implications?

As such, our findings have the potential to inform the development of novel, gender-specific strategies that may be more effective at curtailing sexual risk behavior.

hs-amygdalaJust how should these data inform public health strategies beyond what we knew before we stumbled upon this article? Really, should we stick people’s heads in a machine and gather fMRI data  before offering them condoms? Should we encourage computer dating services to post along with a recent headshot, recent fMRI images showing that prospective dates do not have their risky behavior center in the amygdala activated? Or encourage young people to get their heads examined with an fMRI before deciding whether it’s wise to sleep with somebody new?

So it’s difficult to see the practical relevance of these findings, but let’s stick around and consider the paragraph that Neurocritic singled out.

The paragraph

outlierThe majority of the sample reported engaging in vaginal sex at least once in their lifetime (n = 42, 60%). The mean number of vaginal sexual partners at baseline was 1.28 (SD =0.68). The mean increase in vaginal sexual partners at the last follow-up was 0.71 (SD = 1.51). There were no significant differences between men and women in self-reported baseline or change in self-reported number of sexual partners (t=0.05, p=0.96; t=1.02, p= 0.31, respectively). Although there was not a significant association between age and self-reported number of partners at baseline (r = 0.17, p= 0.16), younger participants were more likely to report a greater increase in partners over time (r =0.24, p =0.04). Notably, distribution analyses revealed two individuals with outlying values (3 SD from M; both subjects reported an increase in 8 partners between baseline and follow up). Given the low rate of sexual risk behavior reported in the sample, these outliers were not excluded, as they likely best represent young adults engaging in sexual risk behavior.

What triggers skepticism?

This paragraph is quite revealing if we just ponder it a bit.

First, notice there is only a single significant correlation (p=.04) in a subgroup analysis. Differences between men and women were examined finding no significant findings in either baseline or changes in number of sexual partners over the length of the observation. However, disregarding that finding, the authors went on to explore changes in number of partners over time among the younger participants and, bingo, there was their p =0.04.

Whoa! Age was never mentioned in the abstract. We are now beyond the 2 x 2 x 2 interaction mentioned in the abstract and rooting through another dimension, younger versus older.

But, worse, getting that significance required retaining two participants with eight new sexual partners each during the follow-up period. The decision to retain these participants was made after the pattern of results was examined with and without inclusion of these outliers. The authors say so and essentially say they decided because it made a better story.

The only group means and standard deviation included these two participants. Even including the participants, the average number of new sexual partners was less than one during some follow-up. We have no idea whether that one was risky or not. It’s a safer assumption that having eight new partners is risky, but even that we don’t know for sure.

Keep in mind for future reference: Investigators are supposed to make decisions about outliers without reference to the fate of the hypothesis being studied. And knowing nothing about this particular study, most authorities would say if two people out of 70 are way out there on a particular variable that otherwise has little variance, you should exclude them.

It is considered a Questionable Research Practice to make decisions about inclusion/exclusion based on what story the outcome of this decision allows the authors to tell. It is p-hacking, and significance chasing.

And note the distribution of numbers of vaginal sex partners. Twenty eight participants had none at the end of the study. Most accumulated less than one during the follow up, and even that mean number was distorted by two having eight partners. Hmm, it is going to be hard to get multivariate statistics to work appropriately when we get to the fancy neuroscience data. We could go off on discussions of multivariate normal or Poisson distributions or just think a bit..

We can do a little detective work and determine that one outlier was a male, another a female. (*1) Let’s go back to our eight little boxes of participants that are involved in the interpretation of the three-way interaction. It’s going to make a great difference exactly where the deviant male and female are dropped into one of the boxes or whether they are left out.

And think about sampling issues. What if, for reasons having nothing to with the study, neither of these outliers had shown up? Or if only one of them had showed up, it would skew the results in a particular direction, depending on whether the participant was the male or female.

Okay, if we were wasting our time continuing to read the article after finding what we did in the abstract, we are certainly wasting more of our time by continuing after reading this paragraph. But let’s keep poking around as an educational exercise.

The rest of the methods and results sections

We learn from the methods section that there was an ethnically diverse sample with a highly variable follow-up, from zero days to 3.9 years (M = 188.72 d, SD = 257.15; range = 0 d–3.19 years). And there were only 24 men in the original sample for the paper of 70 participants.

We don’t know whether these two outliers had eight sexual partners within a week of the first assessment or they were the ones captured in extending the study to almost 4 years. That matters somewhat, but we also have to worry whether this was an appropriate sample – with so few participants in it in the first place and even fewer who had sex by the end of the study – and length of follow-up to do such a study. The mean follow-up of about six months and huge standard deviation suggest there is not a lot of evidence of risky behavior, at least in terms of casual vaginal sex.

This is all getting very funky.

So I wondered about the larger context of the study, with increasing doubts that the authors had gone to all this trouble just to test an a priori hypothesis about risky sex.

We are told that the larger context is the ongoing “Duke Neurogenetics Study (DNS), which assesses a wide range of behavioral and biological traits.” The extensive list of inclusions and exclusions suggests a much more ambitious study. If we had more time, we could go look up the Duke Neurogenetics Study and see if that’s the case. But I have a strong suspicion that the study was not organized around the specific research questions of this paper (*2). I really can’t tell without any preregistration of this particular paper but I certainly have questions about how much Hypothesizing after the Results Are Known (HARKing) is going on here in the refining of hypotheses and measures, and decisions about which data to report.

Further explorations of the results section

I remind readers that I know little about fMRI data. Put it aside and we can discover some interesting things reading through the brief results section.

Main effects of task

As expected, our fMRI paradigms elicited robust affect-related amygdala and reward-related VS activity across the entire parent sample of 917 participants (Fig. 1). In our substudy sample of 70 participants, there were no significant effects of gender (t(70) values < 0.88, p values >0.17) or age (r values < 0.22; p values > 0.07) on VS or amygdala activity in either hemisphere.

figure1Hmm, let’s focus on the second sentence first. The authors tell us absolutely nothing is going on in terms of differences in amygdala and reward-related VS activity in relation to age and gender in the sample of 70 participants in the current study. In fact, we don’t even need to know what “amygdala and reward-related VS activity” is to wonder why the first sentence of this paragraph directs us to a graph not of the 70 participants, but a larger sample of 917 participants. And when we go to figure 1, we see some wild wowie zowie, hit-the-reader-between-the-eyes differences (in technical terms, intraocular trauma) for women. And claims of p < 0.000001 twice. But wait! One might think significance of that magnitude would have to come from the 917 participants, except the labeling of the X-axis must come from the substudy of the 70 participants for whom data concerning number of sex partners was collected. Maybe the significance comes from the anchoring of one of the graph lines by the one wayout outlier.

Note that the outlier woman with eight partners anchors the blue line for High Left Amygdala. Without inclusion of that single woman, the nonsignificant trends between women with High Left Amygdala versus women with Low Left Amygdala would be reversed.

figure2The authors make much of the differences between Figure 1 showing Results for Women and Figure 2 showing Results for Men. The comparison seems dramatic except that, once again, the one outlier sends the red line for Low Left Amygdala off from the blue line for High Left Amygdala. Otherwise, there is no story to tell. Mind-boggling, but I think we can safely conclude that something is amiss in these Frankenstein graphs.

Okay, we should stop beating a corpse of an article. There are no vital signs left.

Alternatively, we could probe the section on Poisson regressions and minimally note some details. There is the flash of some strings of zeros in the P values, but it seems complicated and then we are warned off with “no factors survive Bonferroni correction.” And then in the next paragraph, we get to exploring dubious interactions. And there is the final insult of the authors bringing in a two-way interaction trending toward significance among men, p =.051.

But we were never told how all this would lead as we were promised in the end of the abstract, “to the development of novel, gender-specific strategies that may be more effective at curtailing sexual risk behavior.”

Rushing through the discussion section, we note the disclosure that

The nature of these unexpected gender differences on clear and warrants further consideration.

So, the authors confess that they did not start with expectations of finding a gender difference. They had nothing to report from a subset of data from an ambitious project put together for other purposes with an ill-suited follow-up for the research question (and even an ill-suited experimental task. They made a decision to include two outliers, salvaged some otherwise weak and inconsistent differences, and then constructed a story that depended on their inclusion. Bingo, they can survive confirmation bias and get published.

Readers might have been left with just their skepticism about the three-way interaction described in the abstract. However, the authors implicated themselves by disclosing in the article their examination of a distribution and reasons for including outlier. Then they further disclosed they did not start with a hypothesis about gender differences.

Why didn’t the editor and reviewers at Journal of Neuroscience (impact factor 6.344) do their job and cry foul? Questionable research practices (QRPs) are brought to us courtesy of questionable publication practices (QPPs).

And then we end with the confident

These limitations notwithstanding, our current results suggest the importance of considering gender-specific patterns of interactions between functional neural circuits supporting approach and avoidance in the expression of sexual risk behavior in young adults.

Yet despite this vague claim, the authors still haven’t explained how this research could be translated to practice.

Takeaway points for the future.

Without a tip from NeuroCritic, I might not have otherwise zeroed in on the dubious complex statistical interaction on which the storyline in the abstract depended. I also benefited from the authors for whatever reason telling us that they had peeked at the data and telling us further in the discussion that they had not anticipated the gender difference. With current standards for transparency and no preregistration of such studies, it would’ve been easy for us to miss what was done because the authors did not need to alert us. Until there are more and better standards enforced, we just need to be extra skeptical of claims of the application of neuroscience to everyday life.

Trust your skepticism.

Apply whatever you know about statistics and experimental methods. You probably know more than you think you do

Beware of modest sized neuroscience studies for which authors develop storylines from the patterning authors can discover in their data, not from a priori hypotheses suggested by a theory. If you keep looking around in the scientific literature and media coverage of it, I think you will find a lot of this QRP and QPP.

Don’t go into a default believe-it mode just because an article is peer-reviewed.


  1. If both the outliers were of the same gender, it would have been enough for that gender to have had significantly more sex partners than the other.
  1. Later we had told in the Discussion section that particular stimuli for which fMRI data were available were not chosen for relevance to the research question claimed for this this paper.

We did not measure VS and amygdala activity in response to sexually provocative stimuli but rather to more general representations of reward and affective arousal. It is possible that variability in VS and amygdala activity to such explicit stimuli may have different or nonexistent gender-specific patterns that may or may not map onto sexual risk behaviors.

Special thanks to Neurocritic for suggesting this blog post and for feedback, as well as to Neuroskeptic, Jessie Sun, and Hayley Jach for helpful feedback. However, @CoyneoftheRealm bears sole responsibility for any excesses or errors in this post.











12 thoughts on “Sex and the single amygdala: A tale almost saved by a peek at the data”

  1. Dear James,

    A lovely breakdown of this paper. If I may, I would like to add a couple of further points.

    First, my main issue is of the vagueness of the prediction of the valence of the amygdala for the effect. Their intro reads:

    “we further hypothesized that this VS-associated risk would only be expressed in the context of relatively decreased amygdala activity.”

    But their summary of the data in the discussion reads, “our results suggest that the expression of VS-associated risk is moderated by the magnitude of amygdala activity in a gender-specific manner. Specifically, in men but not women relatively increased VS activity was associated with greater number of partners over time, only in the context of relatively decreased amygdala activity. “

    They then engage in some very heavy reverse inferences (e.g.,; to explain away the gender discrepancy in the data, and I found this to a paragraph of gobbledy-gook. For all I know, if this interaction with gender is real (a big if, given your breakdown), it might be as easily described as saying that the amygdala is important for assigning valence to a face, and that this is different in men and women. If I was cruel, I would say that men who get more sexual partners over time don’t mind choosing ugly women… etc etc. This would provide as valid an explanation of their data as the one they gave, and there are many more explanations that are equally as valid.

    Second, as to the gender effects, I can’t see anything about correcting readings for the fact that women, on average, have smaller brains than men. Also, for some reason, women tend to squirm more in a scanner than men do ( Also, this is yet another example where they do not even offer an a priori prediction of what gender differences will reveal or any hypotheses in the introduction, and yet explore them statistically, then report interactions. How odd.



  2. I really enjoyed re-reading this critique. A few more points that someone doesn’t even need basic statistical knowledge to pick up on:

    They should be using the right outcome measure. You have implied this, but to emphasise the point: if the authors are interested in sexually transmitted diseases then clearly that should have been their primary outcome measure, not number of partners. Obviously, this would be more invasive or embarrassing to measure, but it is doable. It would certainly this would be preferable to using a proxy outcome that barely changes across the course of study, apart from two outliers.

    Also, the task that Victor et al., used to get the fMRI data had nothing to do with what they were trying to measure. They used a strange matching face paradigm of neutral, angry, fearful and surprised faces and the fMRI data “focused on general activity associated with all four expressions.” There is no theoretical basis for this task given apart from “we used it previously”. I don’t know much about fMRI but I imagine that they mashed together all the activity in the amygdala and VS during this task for the regression analysis. There would be so much activity over the course of this task that there wouldn’t be much of use, so to me (although of course I’m not an expert, and could be wrong) it seems a particularly silly way to study fMRI.

    And then there’s the dizzying neuroscience results concerning brain regions that affect the amygdala *this* way and the VS *that* way, except for when they do the opposite. And none of this is properly theoretically based.



    1. Thanks, and Hayley Jach is still an honors student, not yet a grad student. Maybe there is hope for restoring the trustworthiness of psychology if we can get people like her into routine crowdsourced postpublication peer review.


  3. Thanks again James for this useful exercise. We have seen, in the space of a single article, several basic conceptual and statistical flaws, including dubious and unpowered three-way interactions with no theoretical basis, inappropriate inclusion of outliers, HARKing, and overselling of potential practical implications, just to name a few.

    A further interpretive issue that is that the authors claimed, in the opening of their discussion, that “Our current results are broadly consistent with those of Demos et al. (2012) demonstrating that the magnitude of VS activity is associated with sexual risk behaviors in the form of increased partners over time.” However, they didn’t even report the main effect of VS activity on number of sexual partners (most likely because there wasn’t one), so it seems tenuous to claim that the three-way interaction results are even “broadly consistent” with these previous findings.

    As another methodological issue, these patterns of activation may not even be robust. A very well-done recent fMRI study by Charlene Wu and colleagues ( suggests that test-retest reliability is more important than signal-to-noise ratio within a session.

    In their words: “standard measures of neural activity (e.g., contrasts or fitted functions) may suffer from reduced reliability by mixing neural responses to different task components (e.g., unreliable components with reliable components)… validity depends more on test–retest reliability across sessions than signal- to-noise ratio within a session. Although methodologists have argued for recruiting ever-increasing numbers of subjects to ensure the robustness of research findings (e.g., Ioannidis, 2005), a more parsimonious and efficient solution for expensive neuroimaging studies might involve improving measurement.” (p. 287)

    This limitation is by no means unique to this study (in fact, my impression is that it’s rare in fMRI studies to obtain test-retest scans), but I think threatens the validity of many fMRI studies. And I think it’s also worth sharing examples of studies that demonstrate best practices (e.g., establishing test-retest reliability in fMRI studies), even if they’re not perfect, just to show what a study needs to do to be taken seriously.



  4. A trivial point, but you should change

    First, notice they is only a single significant correlation…
    First, notice there is only a single significant correlation…

    I know Jessie personally and could not agree more with your assessment.



  5. Dear Dr Coyne,
    Very good and thorough statistical analysis of this paper, with excellent teaching points!
    We have just published a Journal Club comment in J Neuro about this paper, highlighting some of the same issues (our comment was under review at the time you published this blog, journals’ reactivity is much slower than online reactions…):


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