Putative sex differences in verbal abilities and language cortex: A critical review
Introduction
Sex is interesting, and the mass media and the general public are captivated by findings of differences between men and women. The book Men Are From Mars, Women Are From Venus, by John Gray (1992), which argued for large psychological differences between the sexes, has been translated into more than 40 languages and has sold over 30 million copies (http://www.marsvenus.com).
When cognitive neuroscientists are approached by the mass media, it is often with questions related to sex differences.
Textbooks routinely cite sex differences in language competence, usually regarding verbal fluency, as established fact (e.g. Kolb and Whishaw, 2001, Mildner, 2008, Pinker, 2007). Unfortunately, it is often difficult to see where these findings come from; this is not only the case in textbooks, but can also be found in research papers on the topic. For instance, in a study on sex differences (Weiss, Kemmler, Deisenhammer, Fleischhacker, & Delazer, 2003), one can find the following statement, without any data or references to back the claim:
Women tend to be better than men in rapidly identifying matching items, a skill called perceptual speed. Common linguistic skills, in which females have been found to be superior, are verbal fluency, speech articulation, grammatical skills, and use of more complex and longer sentences.
Similar statements are found in all of the above citations.
A large number of studies reporting sex differences in brain structure and function underlying language processes have also been published (e.g. Shaywitz et al., 1995). The article by Shaywitz and colleagues, suggesting differences in language lateralization, has been cited more than 500 times, indicating the impact that these types of results have on the scientific community, not to mention the broader public opinion.
Most neuroimaging studies, however, do not distinguish between males and females. But if sex differences are real, they may possibly confound results from language studies obtained using neuroimaging techniques such as PET and fMRI. If so, measures must be taken to address the problem.
This review presents a broad overview of the multiple existing approaches to the investigation of sex differences in language performance and in the underlying brain structure and processing as well as in language-related disorders. An enormous number of such papers exist (e.g. Burman et al., 2008, Clements et al., 2006, Frost et al., 1999, Grabowski et al., 2003, Haut and Barch, 2006, Jaeger et al., 1998, Kaiser et al., 2007, Kansaku et al., 2000, Knecht et al., 2000, Plante et al., 2006, Schirmer et al., 2004, Shaywitz et al., 1995, Springer et al., 1999, van der Kallen et al., 1998, Weiss et al., 2003 to name but a few). It is not possible to cover all here and at the same time present studies from many fields. This review therefore relies primarily on results either from meta-analyses or from studies with a large number of participants (n > 100) when they exist.
Before we look at the evidence it is interesting to ask why anyone thinks that there could be differences between the language systems for males and females at all. Two theories exist that include this hypothesis.
The “hunter-gatherer”-hypothesis (e.g. see Kolb and Whishaw, 2001, Mildner, 2008) states that putative sex differences in cognitive abilities arose from a division of labour between the sexes in prehistoric humans. Men were predominantly hunters, whereas women were predominantly gatherers. According to this line of thinking, males explored larger territories during hunting than females would do during gathering, which in turn made males develop better skills for navigation, whereas the females left behind in social groups would have benefited more from developing fine-tuned tools for social interaction, one of which is language. This theory therefore predicts that women are better at language than men.
Another possible evolutionary origin of cognitive sex differences has been suggested by Miller (2000). According to this theory, language may have evolved at least partly for purposes of sexual display. This means that language ability is used in sexual selection as a fitness-indicator. Individuals displaying a large capacity for language are considered fitter by potential partners compared to less eloquent individuals. According to this theory, language is the human equivalent of peacock feathers. Due to the special dynamics of sexual selection there are great differences between the feathers of a male peacock and those of a female. Sexual selection dynamics require that males, at great costs, try to display fitness, e.g. by walking around dressed in dangerously visible colours, while females have the power to decide which male to mate with and must therefore be good detectors of fitness. Evoking such a theory about human language therefore predicts great differences between male and female language capabilities. Only fit males will have the means and the time to develop and produce inciting language. The prediction is thus that males will be better at producing language and will try at great costs to exhibit this, while females, on the other hand, are better at understanding language in order to distinguish good talkers from bad talkers (Miller, 2000). Anecdotal evidence for this theory includes the observation that acclaimed writers are still predominantly male, whereas women are known to buy and read more books than men (e.g. Halpern, 2000).
When applied to language, however, both of these theories suffer from fact that this unique part of human behaviour per definition leaves very little room for cross-species comparison. This makes the theories very difficult to falsify or even investigate scientifically (Gannon, 2002). They are, nevertheless, part of the background for most of the research conducted on sex differences in language and therefore deserve to be mentioned.
Section snippets
Verbal fluency
The task perhaps most cited as yielding sex differences is the verbal fluency task (e.g. Kolb and Whishaw, 2001, Mildner, 2008, Pinker, 2007, Sommer et al., 2004). The verbal fluency task is usually conducted in two parts, a “lexical” and a “categorical”. In both conditions, subjects are asked to come up with as many words in a minute as possible. In the lexical conditions the words have to start with a particular letter, like F, A or S, and in the categorical condition subjects have to name as
Whole brain results
Though not linked to language it is worth mentioning that a sex difference in overall brain size of around 8.0% (approx. 100 ml) favouring males is well established in the literature (Chen et al., 2007, Good et al., 2001, Kruggel, 2006). Males also have a greater global grey matter volume (Chen et al., 2007, Good et al., 2001, Kruggel, 2006, Lemaitre et al., 2005) and 16% more neurons (Pakkenberg & Gundersen, 1997). The significance of this, however, is not clear.
Regional grey matter differences
Voxel-based morphometry (VBM)
Sex and language in developmental disorders
Often-cited language-related developmental disorders that affect the sexes differently include: stuttering (Halpern, 2000), dyslexia (Halpern, 2000, Mildner, 2008), autism (Frith, 2001) and schizophrenia (Crow, 2000).
Discussion
Certain language-related deficits exhibit clear sex differences, such as stuttering, dyslexia, and autism. But it is unclear whether these deficiencies are really caused by a problem in the systems for language processing, or whether the language deficit is a by-product of something else.
A small but consistent female advantage is found in early language development. But this seems to disappear during childhood. In adults, sex differences in verbal abilities, and in brain structure and function
Acknowledgments
This work was supported by The Faculty of Humanities at the University of Aarhus, by The Danish Research Council for Culture and Communication and by The Danish National Research Foundation’s grant to Center of Functionally Integrative Neuroscience. The author wishes to thank Lone Frank from Weekend-avisen for inspiring and provoking the making of this paper. Also thanks to Torben Ellegaard Lund, Chris Frith, Dorthe Bleses, Ethan Weed, Kristian Tylén, and Andreas Roepstorff for help and
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