The story of how cognition and fitness relate may not be simple, but simple stories and complex systems rarely go together

Cognition and reproductive success in cowbirds. David J. White, J. Arthur, H. B. Davies & M. F. Guigueno. Learning & Behavior, Dec 16 2021. https://link.springer.com/article/10.3758/s13420-021-00506-0

Abstract: Understanding the relationships between cognitive abilities and fitness is integral to an evolutionary study of brain and behavior. However, these relationships are often difficult to measure and detect. Here we draw upon an opportunistic sample of brown-headed cowbird (Molothrus ater) subjects that had two separate research experiences: First, they engaged in a large series of cognitive tests in David Sherry’s Lab in the Advanced Facility for Avian Research (AFAR) at Western University, then subsequently moved to the Field Avian Research Megalab (FARM) at Wilfrid Laurier University where they lived in large breeding flocks in aviaries with other wild-caught cowbirds. Thus, we had extensive measures of cognitive abilities, breeding behavior, and reproductive success for these birds. We report here, for the fist time, the surprisingly strong connections we found among these different measures. Female cowbirds’ spatial cognitive abilities correlated positively with how intensely they were courted by males, and with their overall egg production. Males’ spatial cognition correlated positively with their ability to engage in singing contests (“countersinging”) with other males. In addition, a separate non-spatial cognitive ability correlated positively with the attractiveness of the songs they sung. In sum, these results suggest the cognitive skills assessed in the lab were strongly connected to breeding behavior and reproductive success. Moreover, since certain cognitive abilities related to different aspects of breeding success, it suggests that cognitive modules may have specialized adaptive value, but also that these specialized skills may interact and influence fitness in surprising ways.

Discussion

Despite the small sample size, the different cognitive scores correlated with several aspects of breeding behavior and reproductive success in both males and females.

Females

Those females who reliably scored highest on spatial tests in the lab received the most courtship song from males. The number of songs sung to females is an important variable associated with pairbond strength and copulation success, and thus is integral to reproduction (White et al., 2010a, b, c). It is unclear what drives this correlation. It is possible that there is something about these females that makes them more attractive to males. Results of past work, however, would suggest that something about the females’ behavior is important in stimulating the males to sing to them more often (Maguire et al., 2013). What females do to get males to sing to them more often is unknown – though one possibility is the use of chatter in response to males’ song (Maguire et al., 2013).

The other variable significantly associated with cognition for females was egg production. Females are often highly variable in egg production between and across groups and past work has been only marginally successful in explaining this variation. Most of those explanations have revolved around the idea that females invest more in egg production in circumstances where they have the most valuable information about the quality of males present (White et al., 2010a, b, c). The cognition score used here is by far the strongest explanatory variable we have ever found for egg production. Perhaps females who have better cognitive abilities can best engage in the behaviors associated with selecting the highest quality, or most compatible mate, building the most successful pairbond, and therefore most likely to invest in egg production. An interesting aspect of this relationship is that laying more eggs leads to a higher spatial memory demand because it requires finding more nests. No matter what mechanism explains this relationship, the connection between spatial cognition and reproductive success suggests that sexual selection can be a driving force on spatial cognition in females.

Males

We had the opportunity to examine how two measures of cognitive performance related to males’ fitness. First, we found that song attractiveness, as measured in playback tests related to the males’ performance on cognitive tasks that used color stimuli in delayed match-to-sample tests. That song attractiveness related to cognitive performance supports the theory that those males best able to learn are the ones who can produce the most attractive signal – a theory of the functional value of song that has been posited for songbirds in general (Nowicki et al., 1998, 2002) and cowbirds specifically (West & King, 1988). These results connecting cognitive performance and song differ from work in song sparrows (Soha et al., 2019), where no connections between cognition and song could be detected (see also Templeton et al., 2014). Why song attractiveness should relate to cognition for color per se, is unclear. Perhaps song attractiveness and performance on the color tasks are linked by another unmeasured variable relating to male quality (health, “good genes”, or stress responsiveness). This would appear unlikely since past work has shown that song attractiveness is highly dependent on developmental (West & King, 1988) and immediate (Gersick & White, 2018) social experiences. Thus, the most likely route leading to variation in song attractiveness involves interacting and learning from the visual responses of females and other males to singing overtures. The color tasks were designed as a control for spatial memory performance and not designed specifically to examine an aspect of cognition hypothesized to be important to male breeding behavior. Thus, the color tasks may be measuring some more general aspect of visual acuity, attention, or learning. More work is needed to determine exactly what cognitive mechanism is driving color discrimination and song development. It is clear, however, that the cognitive ability measured using the color task was distinct from spatial memory skill because performance on spatial tasks did not relate to song attractiveness.

Spatial task performance did, however, relate to one important aspect of singing in males: countersinging. Countersinging is a skill that males must learn in order to attain and maintain dominance among males and to stimulate the reproductive output of females (White et al., 2010a, b, c). Past work has shown that countersinging is learned by juveniles over their first year of life as they approach and sing with adult males (White, King, & West, 2002a). This ability to get close to other males, sing with them in duetting bouts, and temper aggression leads to a cascade of learning other breeding skills and is highly variable among males (White et al., 2007a, b; White, King, & West, 2002a).

No other variables for males or females reached the large effect size necessary for statistical significance (other than chatter patterns in females). There is, however, a distinction that should be made between the correlation strength needed for statistical confidence and for biological relevance. Evolution can act on very small effects. Tables 1 and 2 show some of the effects that did not reach significance but will be the subject of future work, as many of them may inform us of the potential directions of effect occurring with other variables. For example, female chatter is highly stimulating and motivating to males (Burnell & Rothstein, 1994; Freed-Brown & White, 2009; Hauber et al., 2001; Lynch et al., 2017; Snyder-Mackler & White, 2011). Perhaps the production and use of chatter is a behavioral mechanism that females use to regulate males’ behavior, stimulate courtship effort, and strengthen the pairbond (Maguire et al., 2013), leading eventually to more egg output. Other interesting positive relationships with females’ spatial cognition include the song attractiveness of their pairmate, and the amount of courtship song they receive only from their pairmate (a measure of pairbond strength we have found in the past to be important for breeding success; Maguire et al., 2013).

The disclaimers here are most likely obvious: the frustratingly low sample size highlights the challenges for neuroecology and studies of animal cognition in general where the depth of understanding of individuals’ cognitive abilities trades off against testing large numbers of subjects and therefore against generalizability and statistical power. The low number of subjects precluded more detailed statistical analyses, and we could only rely on a small number of a priori comparisons requiring very strong relationships to reject a null hypothesis. Also, the birds in this study, while wild caught, experienced years of life in abnormal contexts, raising questions about generalizability to the wild (although in the aviaries they bred in patterns very similar to the resident birds). Finally, it was not the primary goal of the cognitive experiments to subsequently study fitness. Had it been, we would have ensured that we collected measures that were more directly comparable across subjects. As is, it is not clear what cognitive modules we are examining here. The color-discrimination tasks might be measuring visual acuity, attention, learning speed, etc. Spatial cognition here also includes tasks that were focused on numerical discrimination. Thus, this work should be considered an exploratory first step that, even with the limitation inherent in these data, was surprisingly successful in demonstrating relationships between different aspects of cognition and reproductive success. This discovery will drive experiments both in the lab and in aviaries for years to come.

What do these findings mean for the adaptive specialization hypothesis about cowbird spatial memory? We still have not been able to test directly whether spatial cognition abilities allow females to successfully find and select viable nests in the wild – the critical relationship posited by the adaptive specialization hypothesis that started the work with cowbirds. With modern advances in automated tracking technology and advances in neural manipulations, this relationship may be testable in the near future. The findings reported here – that different measures of cognition related to different aspects of effective breeding – support the idea that there are functionally distinct cognitive systems as proposed by Sherry and Schacter (1987). There do seem to be different cognitive domains at work here, similar to food-caching species that show different patterns of performance depending on whether a task is spatially based or color based (Olson et al., 1995). Females’ superiority in behavioral tasks and the hippocampal size evidence suggest that the potential exists for selection to act on spatial cognition through nest-finding abilities. The interconnections between these cognitive systems and diverse aspects of breeding revealed here, however, suggests some cooption, or exaptation of the cognitive system, which significantly complicates determining how selection has acted and may act (Gould & Vrba, 1982; Sherry & Schacter, 1987). Selection may be operating on spatial memory skills for both a specialized demand on the species (finding nests), and also a non-specialized demand (selecting a mate and reproducing). This suggests there are non-additive interactions among cognitive modules and fitness.

The story of how cognition and fitness relate may not be simple, but simple stories and complex systems rarely go together. The complexity of living systems presents many different routes and strategies leading to reproductive success and thus identifying how distinct memory systems relate to fitness can be challenging. Studying the wealth of links between memory systems, however – how they can work independently and together, how they react to different environments, to past experiences and to conspecifics – and ultimately lead to organizing adaptive behavior holds the promise to fully understand the evolution of the brain and intelligence.

Several adverse perinatal events were associated with an increased risk of violent and non-violent criminal convictions; low birth weight, smallness relative to gestational age and preterm birth with non-violent convictions were higher for men

Adverse perinatal events and offspring criminal convictions in men and women: A population-based study. Sofi Oskarsson et al. Journal of Criminal Justice, Volume 78, January–February 2022, 101879. https://doi.org/10.1016/j.jcrimjus.2021.101879

Highlights

• Adverse perinatal events were associated with an increased risk of violent and non-violent criminal offending

• Associations between some adverse perinatal events with criminal convictions were significantly higher for men than for women

•There was a dose-dependent association between adverse perinatal events with criminal convictions for both men and women

Abstract

Background: We examined associations of adverse perinatal events with offspring violent and non-violent criminal convictions in men and women.

Methods: All singleton births between 1973 and 1995 (n = 1,146,570 men, n = 1,085,217 women) were identified through Swedish population-based registers. Information about adverse perinatal events was retrieved from the Medical Birth Register. Outcomes were criminal convictions collected from the National Crime Register. We estimated absolute and relative risks of being convicted of criminal convictions using the Kaplan-Meier method and survival analyses for men and women separately. We also tested for differences in magnitudes of associations for men versus women.

Results: Several adverse perinatal events were associated with an increased risk of violent and non-violent criminal convictions in both men and women. Associations between low birth weight, smallness relative to gestational age and preterm birth with non-violent criminal convictions were statistically significantly higher for men than for women. There was a dose-dependent association between adverse perinatal events with violent and non-violent criminal convictions for both men and women, indicated by the strengthened magnitude of HR estimates with exposure to an increasing number of adverse perinatal events.

Conclusions: Adverse perinatal events are associated with violent and non-violent criminal convictions in men and women, with some differences in risk estimates between sexes. Findings are compatible with theoretical accounts implicating disruption of the neurodevelopment during the perinatal period.

4. Discussion

In this large-scale population-based study, we found that several adverse perinatal events were associated with an increased risk of violent and non-violent criminal convictions. These results are not only in line with findings from previous research (Liu et al., 2009), but also extend these. Specifically, we add to the existing literature by showing that the exposure to adverse perinatal events increases the risk of violent and non-violent criminal convictions, in both men and women. Further, we found evidence for a dose-dependent relationship between adverse perinatal events and criminal behavior, whereby the exposure to an increasing number of adverse perinatal events elevated the risk for violent and non-violent convictions in both men and women. Additionally, our findings suggest that there may be different adverse perinatal events that heightened the risk of violent and non-violent criminal convictions for men compared to women, even though they are few. For example, observed associations for low birth weight and preterm birth with non-violent criminal convictions were significantly higher for men than for women. These findings build on the existing knowledge regarding the potential importance of early risk factors for criminal offending and point to a dose-dependent relationship.

We also found that small head circumference at birth was associated not only with violent criminal convictions as reported in earlier studies (Ikäheimo et al., 2007) but also with non-violent criminal convictions. These findings were evident for both men and women. Small head circumference has in the previous literature been referred to as a minor physical anomaly (Denno, 1990). From a biopsychosocial criminological perspective, minor physical anomalies have been viewed as reflecting physical and neural maldevelopment of the fetus during pregnancy, potentially due to both genetic and environmental influences (Raine, 2002b; Raine, 2019). Minor physical anomalies have long been a known correlate of male aggression (Waldrop et al., 1978) and criminality (Raine, 2013), but the current results indicate that this association extends to criminal offending among women.

One previous study using a sample that overlapped partly with the present study's, reported a reduced risk of any criminal conviction among offspring who were born preterm (D'Onofrio et al., 2013). This association remained even among discordant siblings, pointing to an independent association between being born preterm and later criminal offending. Being born preterm would thus serve as a protective factor for later criminality. We found that in models adjusted for birth year, preterm birth increased the risk for violent and non-violent criminal convictions among men, but not women. However, in mutually adjusted models, preterm birth was associated with violent criminal convictions but not non-violent convictions, among men, but not women. The discrepancy in findings may be due to the fact that the present study examined men and women separately, whereas the previous study (D'Onofrio et al., 2013) used a total population sample with an adjustment for offspring sex. Another explanation may relate to the different outcomes studied: whereas the present study utilized violent and non-violent criminal convictions as separate outcomes and D'Onofrio et al. (2013) employed any criminal conviction as the outcome.

Taken together, these findings highlight the importance of examining men and women separately when studying associations between adverse perinatal events and criminal convictions, as well as studying violent and non-violent criminal convictions as separate outcomes. The male brain has been suggested to be more susceptible to influences early in life that can disrupt normative neurological development (Golding & Fitzgerald, 2019), and it is well-known that preterm birth is associated with behavioral and psychological problems in later life (Bhutta et al., 2002). Our findings suggest that the association between preterm birth and criminal offending should be further investigated to better understand whether this is a factor contributing to the higher overall rate of criminal convictions for men as compared to women.

One previous study has demonstrated associations between adverse perinatal events and later self-reported violent behavior in a dose-dependent manner, among both men and women (Murray et al., 2015). Our results are in line with these findings and suggest that when adverse perinatal events accumulate in the same individual (up to four for men and up to three for women in the present study), the risk for criminal convictions in the offspring increases for both men and women. The dose-dependent association between adverse perinatal events and offspring criminality is in line with biopsychosocial criminological theory, which suggest that adverse perinatal events contribute to a disruption of neuropsychological development, which in turn can heighten the risk for criminal behavior (Raine, 2002c). It is possible that the accumulation of adverse perinatal events in the same individual index disruption of fetal development during pregnancy more effectively than exposure to a single event. This may further be why we see relatively weak associations between individual adverse perinatal events with offspring criminal convictions, as well as low cumulative incidences, even though there are some indications that certain adverse perinatal events are more important than others (e.g., smallness for gestational age). Further research is needed to clarify the nature and etiological basis of the dose-dependent association between perinatal events and later criminal behavior in offspring, which in turn can inform clinical practice and possibly prevention efforts.

Interestingly, the adverse perinatal events that evidenced an association with criminal offending in the mutually adjusted models differed for men and women. For men, the summative index encompassed extremely low and low birthweight, small for gestational age, small head circumference, and post-term birth for non-violent criminal convictions, with the addition of preterm birth for violent criminal convictions. For women, the summative index encompassed of low birth weight, small head circumference, and post-term birth. The implication is that certain adverse perinatal events, when accounting for all others, are more important for men than for women and vice versa. We opted for an empirically driven approach that allowed for different adverse perinatal events to be included in the summative indices for men and women respectively. Our results highlight the need to differentiate between men and women in the study of adverse perinatal events in relation to criminal convictions, since men and women likely are at different risk of experiencing adverse perinatal events (Zeitlin et al., 2002), as well as engage in criminality. This approach was further supported by the HR estimates for the summative index in the total population (Table S3 in Supporting Information), which in general were not significant or in most cases exhibited overlapping CIs. The dose-dependent relationship between adverse perinatal events and offspring criminal behavior should be explored more extensively in future research to better understand the differences between men and women.

Some unexpected findings in our study should also be noted. Certain adverse perinatal events were associated with a decreased risk of violent and non-violent criminal convictions (e.g., breech presentation, assisted vaginal delivery). Breech presentation, as well as other adverse perinatal events, have previously been related to a lack of oxygen to the fetus (i.e., anoxia), which in turn has been described as a risk factor for criminal offending (Tibbetts, 2011). No study thus far has specifically examined breech presentation in relation to criminal offending, let alone different types of breech positions (e.g., frank breech, complete breech). Further research using other samples is needed to explicate the role of different breech presentations and other aspects of delivery on risk for later criminality.

In our sensitivity analyses, we stratified the full sample including men and women based on levels of SES. Previous work has reported associations between exposure to adverse perinatal events in combination with psychosocial adversities, such as maternal rejection (Raine et al., 1994; Raine et al., 1997) and a disadvantaged family environment (Piquero & Tibbetts, 1999) and later criminal behavior in the offspring. However, a few exceptions should be noted though (Murray et al., 2010; Murray et al., 2015). In the current study, HR estimates were largely unaffected by stratifying the sample into levels of SES, if anything they were somewhat attenuated for all groups.

Findings from the present study should be considered in the light of certain limitations. Some of our reported associations, particularly those for the female portion of the sample, need to be interpreted with caution because of the small number of individuals being exposed to particular adverse perinatal events, as well as the small portion of criminal offenders among females. Owing to these factors, HR estimates for females were less precise than those for males, with wider confidence intervals.

Another limitation is that, although the great majority of births in Sweden are recorded in the MBR, there are still 1–3% of all births during each of the past 20 years that are missing from the register (the National Board of Health and Welfare, 2021). While the MBR contains information of varying quality, the adverse perinatal events included in the present study have previously shown high validity (Källén & Källén, 2003). It is also important to acknowledge that our criminal convictions data relied on official records, which may not be representative of all men and women who have engaged in criminal activity. While registry data reduces the risk of misclassification in one way by limiting recall bias that is often associated with interview data, the results in the present study assume the same level of misclassification of criminal convictions for men and women. While more research is needed on this specific topic, especially in relation to registry data, there is some evidence for a more lenient treatment of female offenders as compared to male offenders (Doerner & Demuth, 2014). Lastly, we performed sensitivity analyses in the total sample of men and women, stratified on levels of SES. Ideally, this would have been done in men and women separately but was not possible due to statistical power restrictions.

The greater male variability in personality (boldness, aggression, activity, sociality and exploration) cannot be found in 220 species examined

A meta-analysis of sex differences in animal personality: no evidence for the greater male variability hypothesis. Lauren M. Harrison,Daniel W. A. Noble,Michael D. Jennions. Biological Reviews, December 14 2021. https://doi.org/10.1111/brv.12818

Abstract: The notion that men are more variable than women has become embedded into scientific thinking. For mental traits like personality, greater male variability has been partly attributed to biology, underpinned by claims that there is generally greater variation among males than females in non-human animals due to stronger sexual selection on males. However, evidence for greater male variability is limited to morphological traits, and there is little information regarding sex differences in personality-like behaviours for non-human animals. Here, we meta-analysed sex differences in means and variances for over 2100 effects (204 studies) from 220 species (covering five broad taxonomic groups) across five personality traits: boldness, aggression, activity, sociality and exploration. We also tested if sexual size dimorphism, a proxy for sex-specific sexual selection, explains variation in the magnitude of sex differences in personality. We found no significant differences in personality between the sexes. In addition, sexual size dimorphism did not explain variation in the magnitude of the observed sex differences in the mean or variance in personality for any taxonomic group. In sum, we find no evidence for widespread sex differences in variability in non-human animal personality.

Pupil Size Predicts Partner Choices in Online Dating

Pupil Size Predicts Partner Choices in Online Dating. Tila M. Pronk, Rebecca I. Bogaers, Mara S. Verheijen and Willem W. A. Sleegers. Social Cognition, Vol. 39, No. 6, December 2021. https://doi.org/10.1521/soco.2021.39.6.773

Abstract: People's choices for specific romantic partners can have far reaching consequences, but very little is known about the process of partner selection. In the current study, we tested whether a measure of physiological arousal, pupillometry (i.e., changes in pupil size), can predict partner choices in an online dating setting. A total of 239 heterosexual participants took part in an online dating task in which they accepted or rejected hypothetical potential partners, while pupil size response was registered using an eye tracker. In line with our main hypothesis, the results indicated a positive association between pupil size and partner acceptance. This association was not found to depend on relationship status, relationship quality, gender, or sociosexual orientation. These findings show that the body (i.e., the pupils) provides an automatic cue of whether a potential partner will be selected as a mate, or rejected.

AI processing of fMRI data knows with a 94+ pct accuracy when are the subjects seeing sexual images

The Brain Activation-Based Sexual Image Classifier (BASIC): A Sensitive and Specific fMRI Activity Pattern for Sexual Image Processing. Sophie R van ’t Hof, Lukas Van Oudenhove, Erick Janssen, Sanja Klein, Marianne C Reddan, Philip A Kragel, Rudolf Stark, Tor D Wager. Cerebral Cortex, bhab397, December 16 2021. https://doi.org/10.1093/cercor/bhab397

Abstract: Previous studies suggest there is a complex relationship between sexual and general affective stimulus processing, which varies across individuals and situations. We examined whether sexual and general affective processing can be distinguished at the brain level. In addition, we explored to what degree possible distinctions are generalizable across individuals and different types of sexual stimuli, and whether they are limited to the engagement of lower-level processes, such as the detection of visual features. Data on sexual images, nonsexual positive and negative images, and neutral images from Wehrum et al. (2013) (N = 100) were reanalyzed using multivariate support vector machine models to create the brain activation-based sexual image classifier (BASIC) model. This model was tested for sensitivity, specificity, and generalizability in cross-validation (N = 100) and an independent test cohort (N = 18; Kragel et al. 2019). The BASIC model showed highly accurate performance (94–100%) in classifying sexual versus neutral or nonsexual affective images in both datasets with forced choice tests. Virtual lesions and tests of individual large-scale networks (e.g., visual or attention networks) show that individual networks are neither necessary nor sufficient to classify sexual versus nonsexual stimulus processing. Thus, responses to sexual images are distributed across brain systems.

Keywords: erotic images, machine learning prediction model, multivariate analysis, neuroimaging, sexual stimuli processing, support vector machine classification

Discussion

Sexual stimulus processing is a core component of human affective and motivational systems, and part of a fundamental repertoire of motivations conserved across nearly all animal species. Previous work using sexual stimuli has made important advances (e.g., Georgiadis et al. 2006; Walter et al. 2008b; Abler et al. 2013; Borg et al. 2014; Stark et al. 2019), but these studies have generally included small sample sizes and have focused on characterizing responses in individual brain regions using standard brain-mapping approaches. Findings have been variable across studies (for meta-analyses, see Stoléru et al. 2012; Poeppl et al. 2016), and it remained unclear whether brain responses to sexual stimuli are robustly and reproducibly different from responses to nonsexual positive or negative affective stimuli.

Here, we employed a multivariate predictive model grounded in population-coding concepts in neuroscience (Pouget et al. 2000; Shadlen and Kiani 2007; Kragel et al. 2018) and systems-level characterization, based on growing evidence that various psychological processes are grounded in distributed networks rather than local regions or isolated circuits (Kamitani and Tong 2005; Kuhl et al. 2012; Arbabshirani et al. 2017). We identified a generalizable pattern of brain responses to sexual stimuli whose organization is conserved across individual participants, but which is distinct from responses to other conceptually related (nonsexual) affective images. We used cross-validated machine learning analyses to identify a brain model, which we termed the BASIC model (for purposes of sharing and reuse), that can classify sexual from neutral, positive, and negative affective images with nearly perfect accuracy in forced-choice tests, including an independent validation cohort tested on a different population (US vs. Europe), scanner, and stimulus set from those used to develop the model. Together with previous smaller-sample analyses that differentiate multivariate brain responses to romantic or sexual stimuli from responses to other types of affective and emotional events (Kassam et al. 2013; Kragel et al. 2019), our results suggest that sexual stimuli are represented by a relatively unique brain “signature” that is not shared by other types of affective stimuli.

Furthermore, our virtual lesion analysis suggests that the classifications of sexual versus neutral/affective conditions are not solely due to differences in visual or attention processing, as predictions are intact even leaving out large-scale cortical networks devoted to attention and vision. In addition, the spatial scale evaluation demonstrates that whole-brain level classification (both voxel- and parcel-wise) shows the highest model performance compared with individual large-scale network parcels. The BASIC model shows effects not only in subcortical but also in cortical areas, in line with previous human (for meta-analyses, see Stoléru et al. 2012; Poeppl et al. 2016) and animal research (for meta-analysis, see Pfaus 2009). From a basic biological perspective, this might be surprising. Evolutionarily relevant key features of sexual signals in nonhuman primates may include sex calls, pheromones, and the presentation of genitals. The sexual signals presented here are, in comparison, highly complex visual scenes containing a variety of sexual content, triggering valuation processes accompanied by neural activity on the cortical level. Even though our and previous research shows strong evidence for large cortical involvement, there still seems to be a bias in picking brain areas for region of interest (ROI) analyses toward subcortical regions. This is reflected in the neurosynth “sexual” brain map, based on an automated meta-analysis that includes coordinates from a priori ROI analyses. For example, the study with the highest loading on the term “sexual” in neurosynth (Strahler et al. 2018) used ROI analyses that included almost exclusively subcortical areas.

Many types of validation are beyond the scope of this study, but we were able to provide validation of several key elements. First is the application to a new cohort with different population characteristics, equipment, and paradigm details, with large effect sizes for sexual versus nonsexual affective images. Second, we investigated the effects of globally distributed signal in white matter and ventricle spaces, which can capture complex effects of head movement and task-correlated physiological noise and have been found to drive some multivariate predictive models in the past. Lack of relationships with these non–gray matter areas, along with significant contributions to the model in known affective/motivational systems, increases confidence that the model is driven by neuroscientific relevant systems. Third, we investigated whether the model showed differential effects for male versus female subgroups or varied with age. It did not, supporting the notion that despite individual differences there is a generalizable brain response across individuals (note, this study did not include nonheterosexual, noncis individuals, and individuals of different age groups). This is in line with the findings of previous neuroimaging meta-analyses that revealed common “unisex” brain responses to sexual stimuli (Poeppl et al. 2016; Mitricheva et al. 2019).

Interpretation of a machine learning–based model is complex because the classification is not explained by one region or network, but by a combination across regions. One set of regions may encode one aspect, for example the positive valance aspect, another set may encode the arousal aspect, and yet another set the concept of personal closeness. All these sets then jointly contribute to the overall discrimination of sexual from general affective images. The studies we analyzed do not have sufficient information to link specific brain areas to specific component processes underlying response to sexual images, but we do evaluate our model in light of previous neuroscientific literature here to examine the neurobiological plausibility of the model (Kohoutová et al. 2020).

Brain areas included in the BASIC model are also present in the most recent meta-analytical model of brain responses to sexual stimuli (Stoléru et al. 2012), although the BASIC model presents a more comprehensive and precisely specified set of hypotheses about which voxels, with which relative activity pattern across them, to test and validate in future studies. In terms of resting-state networks (see Fig. 5), we see positive and negative weight effects emerge: negative weights (relative decreases in activity associated with sexual image processing) in somatomotor networks and positive weights (relative increases) in dorsal and ventral attention networks. In addition, weights in the default mode network (DMN) are near-zero when averaging across the entire DMN. However, when looking at default mode subnetworks, DMN A (ventral medial PFC and posterior cingulate areas) shows strong positive weights, whereas DMN C (hippocampal and more posterior occipital areas) shows strong negative weights. This relates to previous research linking DMN to drug, gambling, and food craving and their regulation, which generally involve DMN A regions, and the vmPFC and NAc in particular (Hare et al. 2009; Kober et al. 2010; Hutcherson et al. 2012; Kearney-Ramos et al. 2018; Aronson Fischell et al. 2020; Schmidt et al. 2020). Both these areas are involved in the BASIC model, in line with previous research linking these areas to sexual stimuli. For instance, previous studies have reported significant vmPFC activation during sexual compared with monetary rewards (Schmidt et al. 2020), and neural reactivity to sexual stimuli in the NAc was positively correlated with sexual arousal ratings (Klein et al. 2020). In addition, activation of both regions to food and sex cues has been found to predict subsequent risky sexual behavior (Demos et al. 2012).

The BASIC model included positive weights (a higher likelihood that the image was sexual with increasing activity) in several additional regions thought to be important for sexual responses: the hypothalamus, amygdala, somatomotor cortices, and insula. The hypothalamus is a small area near the ventricles and sinus spaces, and this likely introduces substantial variability. A preliminary study by Walter et al. (2008b) using ultra high-resolution imaging at 7 T, which is likely to have superior ability to detect hypothalamic activity, found signal dropouts in ventral subcortical structures such as the hypothalamus. Similar dropout may have limited sensitivity in the hypothalamus in this study. However, findings of hypothalamic activation in sexual stimulus processing have varied across studies. The meta-analysis by Stoléru et al. (2012) found that 37.8% of studies reported hypothalamic responses to visual sexual stimuli. A motivational role for hypothalamus is included in the model of Stoléru et al. (2012) as well, although this has only been found in animal studies. Responses of the hypothalamus have been related to the regulation of autonomic responses, and in particular the physiological aspect of sexual arousal (Ferretti et al. 2005). Here, we did not measure genital responses and can therefore not know if the stimuli triggered a physiological response. Further research, including genital response measures, could therefore shed more light on the role of the hypothalamus in sexual behavior.

The amygdala and somatomotor cortices are part of the emotional component of the model of sexual stimuli processing by Stoléru et al. (2012). All these show positive weights in the BASIC model. Within the amygdala, positive weights were found in the corticomedial division, in contrast from emotions more generally, which most often show central nucleus and sometimes basolateral activation (Wager et al. 2008; Yarkoni et al. 2010). The insula has previously been reported to sex, food, and drug craving (Pelchat et al. 2004; Yokum et al. 2011; Murdaugh et al. 2012; Tang et al. 2012), as well as interoception (Paulus and Stewart 2014). The insula is, however, large and heterogeneous region. Within the insula, the BASIC model included positive weights in two areas: the right ventral anterior insula and posterior insula PoI2 (from Glasser et al. 2016). The posterior insula is held to be important for somatosensory representations, multisensory information, and pleasant touch (Olausson et al. 2002; Cera et al. 2020). The anterior insula seems to play a role in visceral information processing and subjective feelings (Craig 2002; Uddin 2015). However, the ventral anterior insula is distinct from the dorsal anterior insula identified in most studies and has stronger associations with ventromedial prefrontal and subcortical structures including the amygdala, and functional associations with emotion and gustation (Chang et al. 2013; Wager and Barrett 2017).

In addition, another subcortical region little discussed in the Stoléru et al. (2012) meta-analysis but involved in the BASIC model is the midbrain periaqueductal gray (PAG). The PAG is best-known for its role in pain and defensive behaviors, but animal literature also shows effects of lesions on sexual behavior (Lonstein and Stern 1998), particularly lordosis. Many PAG neurons express estrogen receptors, and areas where these neurons are concentrated are targeted by inputs from the hypothalamus (Bandler and Shipley 1994). This and related pathways through the PAG are thought to be involved in sexual readiness (Holstege and Georgiadis 2004). In humans, nearby areas of the midbrain are activated during male ejaculation (Holstege et al. 2003; Georgiadis et al. 2009), though precise localization is difficult, and other studies have related human PAG activity more to bonding than sex (Ortigue et al. 2010).

The overlap of areas in BASIC model with some drug- and food-cue reactivity studies, but not others, suggests that different types of appetitive stimuli and responses may activate dissociable systems in some cases. Exploring these differences in depth is beyond the scope of this study but very interesting for future studies. An interesting next step, for instance, would for example be to test BASIC model on a different set of rewarding stimuli.

Thus, future validation for BASIC model can involve testing it on many other types of stimuli but our work already shows that based on brain data, we can distinguish sexual from general affective processing. Previous research has associated sexual stimuli with positive affect, as the wide use of IAPS, where sexual images are placed under positive affect, indicates. This strong link between positive affect and sexual stimuli might be the result of the assessment method of affect. Most studies have used a bipolar scale (i.e., negative to positive affect/valence) but when using to separate unipolar scales, both positive and negative affect have been reported during sexual stimuli (Peterson and Janssen 2007). Here, we show that the BASIC model has the highest cosine similarity with the sexual condition as expected (see Supplementary Figure 1) but shows more cosine similarity to the negative condition in Study 1 than the positive condition. Hence, in line with previous research, this work therefore demonstrates that the intuitive link between positive affect and sexual stimuli is much more complicated.

In addition to the link between sexual stimuli and general affect, we were able to gain some insight into whether the BASIC model captures general arousal or valence. To examine the role of general arousal and valence in the prediction of BASIC model, we adopted two strategies. First, we measured valence and arousal in Study 1 and performed a sensitivity analysis, testing whether the BASIC model was sensitive to valence and arousal of nonsexual images. Second, we applied the BASIC model to an independent test dataset (Study 2), in which sexual and nonsexual images were matched on valence and arousal. Regarding the first strategy, the self-reported data showed that sexual images had a significantly lower arousal than the negative images, but significantly higher BASIC responses. In addition, positive images had a higher valence than neutral or negative images but did not produce higher BASIC responses. Regarding the second strategy, the BASIC model responded more strongly to sexual than nonsexual images matched on valence and arousal and did not respond to either positively or negatively valenced nonsexual images. In addition, the strong classification performance was replicated in both Study 1 and Study 2 despite differences in the content of sexual images (Study 1 showed explicit sex scenes with couples, whereas Study 2 showed both clothed and naked couples and individuals) and likely general arousal levels. Together, these findings indicate that it is not sensitive to general arousal and valence per se but is instead sensitive to sexual content. This is in line with a previous study by Walter et al. (2008a), demonstrating that during a sexual stimulus, activation patterns modulated by general emotional arousal differed from activation patterns modulated by sexual stimulus intensity.

Sexual stimuli have often been used by researchers to study sexual arousal, although it is unclear if a state of sexual arousal is elicited by short visual sexual stimuli and therefore whether it was present during conditions used in BASIC model. In Study 1, the sexual images consisted of heterosexual couples engaged in sexual interactions, and self-reported sexual arousal was significantly higher in the sexual conditions versus the other conditions. Based on these results, we might suspect that the images, although presented for a short duration, might have induced a certain level of sexual arousal, at least at the subjective self-report level. However, in Study 2, participants were presented not only with couples, but also sexual or romantic images of an individual man or woman. Assuming that not all participants were bisexual, participants were presented with sexual images depicting both individuals consistent and inconsistent with their preferred sex. Thus, even though the images might not have induced high levels of sexual arousal in all participants, we can distinguish sexual from general affective processing in the brain, which was the aim of our study. For future research, it would be interesting to examine whether the BASIC model can also differentiate between longer visual sexual stimuli, whether sexual arousal is more likely to be induced by long than short-duration, and whether the BASIC model responds to sexual stimuli of other modalities, for example, sensory (genital stimulation), cognitive (fantasy), or auditory.

Ponseti et al. (2012) conducted one of the few studies on sexual stimulus processing that used multivariate analysis. They classified preferred and nonpreferred (e.g., child nudity vs. adult nudity) sexual stimuli based on brain data in participants with and without pedophilia using nude frontal images of adults and children. This classification might be more linked to sexual arousal, although it is still hard to evaluate whether sexual arousal was induced. In order to gain additional insight into sexual arousal specifically, future research could examine if sexual arousal is elicited during sexual image presentation, and to identify the brain processes generating it, multivariate analysis could be used to predict sexual arousal ratings based on brain data collected during sexual image presentation. In our study, this was not possible due to a lack of within-subject variability in the sexual arousal ratings during the sexual image blocks. Parada et al. (2016) presents large variability of sexual arousal ratings and, using a parametric modulation analysis, found various subregions of the parietal cortex that showed significant changes in activation corresponding to the degree of self-reported sexual arousal with no gender differences. Future studies could further examine role of the parietal cortex in the subjective experience of sexual arousal.

Besides self-reported sexual arousal, genital responses are often assessed in psychophysiological studies to examine sexual arousal (Rosen and Beck 1988; Janssen and Prause 2016). The assessment of genital response in neuroimaging studies is sparse (Arnow et al. 2009; Parada et al. 2018). Parada et al. (2018) presents several brain regions (supramarginal gyri, frontal pole, lateral occipital cortex, and middle frontal gyri in men; same regions plus the ACC/PCC, right cerebellum, insula, frontal operculum, and paracingulate gyrus) to be correlated with changes in genital response, with a stronger brain–genital relation in women compared with men in several regions. Assessment of genital response during fMRI research could improve our understanding of the interaction between brain and genital and the gender differences between this interaction. In addition, multivariate analysis could be used to predict genital arousal levels and self-reported sexual arousal based on brain data, and these patterns could be compared. This type of study design would allow for a mediation analysis, which could give more insight into the brain organization by examining the distributed, network-level patterns that mediate the stimulus intensity effects on sexual arousal (Geuter et al. 2020).

A limitation of this study is that although the BASIC model can accurately classify sexual and nonsexual images with forced choice tests, we did not identify one absolute threshold that could be used as a quantitative measure across studies. Future studies thus have to establish a threshold in a study-specific manner and make relative comparisons across conditions within-study, which is a limitation. However, we do show that the BASIC model can be generalized to individuals studied in other research centers with forced choice tests, though the absolute scale of the response is likely to vary across studies as a function of scanner field strength, signal-to-noise ratio, and other signal properties.

To summarize, in this study, we applied multivariate neuroimaging analyses to investigate sexual stimulus processing in the brain. This approach allowed for the development of the BASIC model, which can accurately classify sexual versus neutral and positive and negative affective images in two separate datasets, consisting of different types of sexual stimuli and individuals. The BASIC model includes a precisely specified pattern of cortical and subcortical areas, some of which have received relatively little attention in the literature on human sexual responses (e.g., cortical networks). Some may be shared across other appetitive responses (e.g., vmPFC and NAc for drug cues), but the BASIC model may also diverge from studies of other appetitive responses as well (e.g., in the insula). The work gives insight into the complex processing of sexual stimuli and supports the notion that processing sexual stimuli is a neurologically complex, potentially unique mental event that involves multiple networks distributed in the brain. There are many avenues open for future validation and further development, such as testing the BASIC model to nonsexual rewarding stimuli or sexual stimuli of other modalities, and linking the work to sexual arousal.