The paradox of sex differences in intelligence: Part II – Neurobiological evidence

The focus of the second part is on structural and functional sex differences in the central nervous system that might relate to the observed differences in cognitive performance – general intelligence, verbal ability and mental rotation.

Differences in brain structure

On average males have larger total brain volumes than females. This difference is rather robust as demonstrated in several studies and meta-analyses (Leonard, et al., 2008; Yan, et al., 2011; Ruigrok, et al., 2014). The difference remains unchanged also after correcting for body size. The average difference is 100 grams when corrected for body size and 140 grams when uncorrected (Rushton and Ankney, 2009). In a recent meta-analysis of 126 studies including newborns to individuals over 80 years old (best represented for individuals 18–59 years old), Ruigrok and colleagues (2014) found that on average, males have larger absolute intracranial volumes (12%), total brain volume (11%), cerebrum (10%), grey matter (9%), white matter (13%), cerebrospinal fluid (11,5%), and cerebellum (9%) than females.

A second rather stable observation reported in several studies and meta-analyses is that brain size positively correlates with intelligence (Vernon et al., 2000; Rushton and Ankney, 2009; Pietschnig et al., 2015; Ritchie et al., 2015). As can be seen in the table below, the correlations between brain volume and intelligence reported in three meta-analyses show robust positive correlations, explaining 9% to 16% of variance. 

meta-analysis	year	number of  samples	N	unweighted mean r	n-weighted mean r
Vernon et al., 2000	1987 – 1999	11	432	.40	.38
Rushton and Ankney, 2009	1998 – 2007	28	1,389	.40	.38
Pietschnig et al., 2015	1991 – 2012	38	3,254	.30	–

Combining these two propositions: (1) males have larger brains than females and (2) brain size correlates positively with intelligence; lead Lynn (1999) and Nyborg (2005) to conclude that males are more intelligent than females. Lynn (1999) predicted that males should outperform females for about 3.8 IQ points. This prediction comes rather close to the one obtained by Nyborg (2005), who analyzed two studies and showed a male advantage of 3.6 points. In a recent study based on the dataset from the NLSY97 survey, which represents 15+ million 12–17 year old adolescents living in the US in 1997, Nyborg (2015) estimated an IQ male advantage of 6.83 points for blacks, 7.03 for hispanics and 3.6 points for whites (mean SD = 1.7).

At first glance the data and the explanation seem straightforward. However, intellect cannot be accurately determined by just looking at the cubic content of a skull. This implication is in line with contemporary brain theories describing the brain’s connectome architecture as a comprehensive network map of the nervous system of a given organism. A review of empirical and computational studies strongly suggests that brain hubs play important roles in information integration underpinning complex cognitive function (van den Heuvel and Sporns, 2013). The idea can be traced back to Harry Jerison (1991) characterizing the brain as a “mapping machine”, and maps as different representations (sensory and motor) of the external world. The author suggested that the number of these maps is related to the complexity of viewing and representing the external world. Therefore, the increase in relative brain size can be explained as the need for improving ways of knowing reality. For example, the squirrel has 3 visual areas, the owl monkey has 14 representations of the visual world and it is estimated that humans have 30, therefore we can “see” 27 kind of things which the squirrel cannot (Kolb and Whishaw, 2009).

Size matters but so does organization, moreover, some studies suggest that it is the interaction between size and organization that is important (Gong et al., 2009; 2011; Yan et al, 2011). A MRI tractography study found that female brains are much more efficient than male brains (Gong et al., 2009). For females the difference was especially pronounced in six brain regions (five of which were in the left hemisphere) and for males just in two, both in the right hemisphere. This finding is in line with the reported male advantage in spatial processing and female superiority in verbal ability. In another study that replicated the finding that females have higher local efficiency in cortical anatomical networks than males, it was further shown that individuals with smaller brains had higher local efficiency than those with larger brains (Yan et al., 2011). The correlation was found only in females suggesting an interaction between sex and brain size. Moreover, a large scale diffusion tensor imaging (DTI) study by Ingalhalikar and colleagues (2014), which included 949 individuals (8–22 y, 428 males and 521 females), found that on the cerebral level male brains displayed more connectivity within the hemispheres (intrahemispheric), whereas female brains displayed more connectivity between hemispheres (interhemispheric), while in the cerebellum, a reverse pattern was observed,  with males showing stronger connections between the left cerebellar hemisphere and the contralateral cortex. The differences were most pronounced in young adults (17.1 – 22 years). The findings lead the authors to conclude: “Overall, the results suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes” (Ingalhalikar et al., 2014; p. 823). In  another study this view was challenged,  suggesting that this pattern of connectivity is mainly driven by brain size and not by sex per se due to the confounding of sex and brain size –  males have bigger brains than females (Hänggi et al., 2014).

The most often reported sex differences in brain substructures are gray matter proportion (women have a higher proportion of gray matter), the relative size of the corpus callosum (larger in women), and the sizes of Brocca and Wernicke speech areas (proportionally larger in women) (e.g., Allen et al., 2003; Knaus et al., 2006).  When these differences were adjusted for brain volume the following picture emerged: both women and men with lower cerebral volumes had higher proportions of gray matter (this relationship is slightly stronger for women), the same holds true for callosal volume - individuals with smaller brains had relatively larger callosa (Leonard et al., 2008). The analysis of speech areas yielded similar results, with the exception of planum temporale in the left hemisphere. In women, planar size did not depend on cerebral volume, whereas in men it did (Leonard et al., 2008). The planum temporale lies posterior to the primary auditory cortex within the lateral fissure which forms the heart of Wernicke’s area. A very simplified model of the neural basis of language assumes that the meaning of words is represented in Wernicke’s area (Kolb and Whishaw, 2009). These findings provide further evidence for female superiority in verbal ability.

Taken together, brain structure and in particular brain size can to some extent explain the assumed sex differences in g as well as female superiority in verbal processing.

Differences in brain function

Based on a review of research pertinent to the relationship between psychometrically determined intelligence and functional characteristics of brain activation observed during cognitive task performance, it can be concluded that most of the reviewed studies have demonstrated a negative correlation between brain activity under cognitive load and intelligence (Neubauer and Fink 2009). The explanation of these findings was an efficiency theory – the non-use of many brain areas irrelevant for task performance, as well as the more focused use of specific task-relevant areas in individuals with high IQs  (Haier, 1993).  During performance on numerical and figural tasks, males are more likely to produce cortical activation patterns that are in line with the neural efficiency hypothesis, whereas no significant differences are reported for females (Neubauer et al., 2002; Neubauer & Fink, 2003; Neubauer et al. 2005; Lipp et al., 2012). Perhaps the most important finding of these studies is that the inverse intelligence–activation relationship (i.e., neural efficiency) appears to be moderated by task content and gender. Males and females display the expected inverse IQ–activation relationship in the domain in which they usually perform better: females in verbal domains, and males in the visuospatial domain. Because not only ability factors, but also situational factors such as implicitly activated stereotypes can impair performance (Steele, 1997) hence, the observed differences could also have emerged, because of male/female negative stereotypes. However, a recent study demonstrated that sex differences in neural efficiency during performance on visuo-spatial tasks do not result from the stereotype threat effect (Dunst et al., 2013).

A possible explanation for the observed sex-related efficiency patterns in spatial performance could be hippocampal shape as reported by Colom and colleagues (2013).  The hippocampus is a structure in the limbic lobe of the cortex that is thought to mediate spatial memory and spatial navigation (Kolb and Whishaw, 2009). Colom reported a positive association between hippocampal shape and performance on spatial tasks in males (larger radial distance – higher score), whereas for females this relation was negative (shorter radial distance – higher score).

Sex differences in neural efficiency have also been reported for emotional intelligence (Jaušovec & Jaušovec 2008), which refers to the ability to recognize emotion, reason with emotion and emotion-related information, and process emotional information as part of general problem solving (Mayer et al.,  1999). Namely, females tend to surpass males on tests of emotional intelligence (Mayer et al., 2008). In our study (Jaušovec and Jaušovec, 2008), the most robust sex-related difference in brain activity was observed in lower-2 alpha band (8-10 Hz). Males and females displayed an inverse IQ activation relationship in the domain in which they usually perform better: females in the emotional intelligence domain, and males in the visuospatial ability domain. Because activity in the lower-2 alpha band is related to attentional processes it was suggested that high ability representatives of both sexes compensate for their inferior problem solving skills (males in emotional tasks and females in spatial rotation tasks) by increasing their level of attention.

Men typically demonstrate distinct advantages on a broad range of visual tasks. The most pronounced sex differences of nearly one standard deviation have been reported for mental rotation, the ability to imagine visual shapes rotated to an orientation other than the one in which they are presented (Mackintosh & Bennett, 2005).  Neuroimaging studies investigating this phenomenon have produced rather diverse results. Several functional magnetic resonance imaging (fMRI) studies have reported significant differences in brain activity between males and females during performance on mental rotation tasks, even though no differences on the behavioral level were observed (Jordan et al., 2002; Hugdahl et al., 2006; Butler et al., 2006). On the other hand, some studies reported no significant sex differences in brain activity, yet reported that men outperformed women on the spatial rotational tasks used during brain imaging (Halari et al., 2005; Bell et al., 2006). Furthermore, there are still other studies that employed neuroelectric or hemodynamic brain imaging techniques and reported sex differences both in performance and in brain activation patterns (Gur et al., 2000; Gootjes et al., 2008; Hahn et al., 2009; Lipp et al., 2012; Jaušovec 2012). Moreover, research suggests that males show predominantly parietal activation during performance on mental rotation tasks, whereas females also show frontal brain activity (Hugdahl et al., 2006; Butler et al, 2006). A meta-analysis of early studies on sex differences in brain lateralization in relation to mental rotation indicated a strong preference for the right hemisphere in males, while females showed no hemispheric advantage (Vogel et al.,  2003). On the other hand, certain studies revealed that during spatial processing, men show greater and more bilateral activation than women (Gur et al., 2000), and that such differences can even be observed in preschool children (Hahn et al., 2009).

Despite these inconsistent findings, it has often been suggested that men and women apply different strategies while solving mental rotation tasks (Jordan et al., 2002; Butler et al., 2006; Hugdahl et al, 2006,  Gootjes et al., 2008). It was hypothesized that women performed mental rotation tasks in an effortful, “top-down” way, whereas men used an automatic, “bottom-up” strategy. Top-down processing has been linked to activity in the prefrontal cortex, which plays a role in decision making and spatial working memory. In contrast, bottom–up processing tends to be associated with less prefrontal involvement, less frontal control of task performance, and a greater involvement of primary sensory brain regions (Butler et al., 2006). A similar distinction was proposed by Hugdahl et al. (2006), who associated the frontal lobe activity of females with a serial reasoning strategy and activity in the parietal lobe with a “gestalt” perceptual strategy, as displayed by men. On the other hand, Gootjes et al. (2008) related male right hemispheric activity with a holistic strategy, and a more intense left hemispheric activity observed in females with an analytic strategy. 

In a  study conducted in our lab (Jaušovec and Jaušovec, 2012) we were able to show that the variable sex, when controlled for differences in ability levels and hormonal changes, had no influence on performance on a mental rotation task.  In contrast, significant differences in brain activity patterns between males and females were observed for participants who displayed high mental rotation ability. In comparison to males, females displayed more theta synchronization. This difference was especially pronounced in frontal brain areas (see figure below). Moreover, females displayed more intense interhemispheric coupling between left fronto-central and right parieto-occipital areas. Theta activity is relatively specific for control in working memory (Sauseng, et al., 2010) thus the obtained differences in brain activity patterns suggest that females solved the rotation tasks via intense working memory processing (theta synchronization). The frontal pattern of brain activity in females further points to more controlled processing that involves the central executive.

In a second experiment we tried to influence the spatial ability of females with origami training. Origami is the art of folding paper without the aid of scissors or glue into pieces of sculpture. A pretest-posttest study design with an active control group (communications and social skills training) was used. The groups were equalized with respect to general intelligence and mental rotation ability. Brain activity was measured with electroencephalography (EEG) and near infrared spectroscopy (NIRS) – a technique that measures absolute oxy-hemoglobin concentration (HbO₂) in left and right orbitofrontal brain areas. Only the origami group showed a significant effect of training (d = .70). Even more notable were the findings on brain activation patterns displayed by the origami group after training. After 18 hours of origami training, females changed their brain activation patterns so that they become almost identical to those of  males with high spatial ability (see figure above). The same patterns of brain activity were also observed for induced event-related coherence values: after origami training females showed inter- and intra-hemispheric decoupling in frontal brain areas, accompanied by intra- and inter-hemispheric coupling of parieto-occipital areas with frontal and central brain areas, as well as intrahemispheric coupling in the left parieto-occipital brain area (see figure below).  

The neuroelectric activation patterns were accompanied by similar cardiovascular brain activation patterns as measured by NIRS. Namely, after origami training a decrease in females’ frontal brain HbO₂ concentrations was observed, a pattern which corresponded with the decrease in frontal theta synchronization.

Conclusion

Research has uncovered a considerable amount of data pointing towards sex differences in brain structure, organization, and function in relation to general intelligence. Thus, it is unlikely that they are not reflected in  performance on intelligence tests[1]. Hence we are faced with a paradox: differences in the origin of intelligent behavior – the brain, are not visible in the psychometric model that represents it – g.

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[1] A minor possibility exists that females compensate for these neurobiological differences in employing different solution strategies, as it was shown in our study investigating sex differences in mental rotation (Jaušovec and Jaušovec 2012).

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