Dismantling the idea of male and female brains: neuroscientist Gina Rippon
Image credit: Dreamstime
Professor Gina Rippon is an expert in neuroimaging based at Aston University, Birmingham. In her first book, 'The Gendered Brain: the new neuroscience that shatters the myth of the female brain', she dismantles the theory of essential sex differences in the brain and argues that our experiences in a gendered world are largely responsible for the men and women we become.
What is the “whack-a-mole” myth of sex differences you take on in this book?
The ‘whack-a-mole’ myth is that there is such a thing as a male brain and a female brain, where the male and female refer to a brain from a man and a brain from a woman. The idea is that the biology or biological programming which determines the anatomical characteristics of a man and a woman also determine brain characteristics has been around for 200 years or more, where scientists work backwards from a kind of political status quo where women were socially, educationally, financially and politically inferior and they took it upon themselves to believe that could be explained in terms of brain characteristics. Down the years, there’s been a kind of ‘hunt the differences’. People would say they’d found the explanation and then somebody else would say “No, that methodology doesn’t work” and it keeps coming up. It’s a perpetual idea.
The gendered brain is the idea that we now know how much impact the world has on shaping what the brain can do [the idea that the brain is ‘plastic’]. It’s not as though the brain has got an automatic programme which unfolds irrespective of what’s going on around it. It’s clearly influenced a lot by what is going on round it, so a gendered world – which I’m claiming the world is – produces a gendered brain.
Could you describe the noteworthy sex/gender differences?
The continued focus on sex as a biological variable which doesn’t in any way intersect with the world is interesting. That focus is often justified in terms of gender gaps in mental health statistics: there are much higher incidences of depression, social anxiety, eating disorders and self-harm in women, but running through the list of those problems I would not accept that they’re culture-free or life experience-free. If there is a different incidence in women, it is inappropriate to focus on a biological explanation if you’re not also looking at the environment in which a woman is functioning.
I would like to emphasise that me and the people I work with are not sex difference deniers; we don’t think biology is irrelevant. Many of us are neuroscientists, so we would have wasted a huge amount of our lives researching the brain if we’re going to claim it’s irrelevant! But biology is inexplicably entangled with the cultural factors that you experience. Just focusing on the biological sex factor, we think, is harmful and inaccurate - that’s why we criticise the research. We don’t say don’t do it, but think about what else might be going on that you should include in your research design and the interpretation of your data.
I can imagine that could end up misrepresented as somebody who rejects biology.
Yes, it’s set up as a straw man […] Of course there are biological sex differences. Anybody who says there aren’t is a lunatic. In fact, I got a bit anxious with the title of the book because I don’t think I shatter the myth of the female brain. I think I shatter the old myth of the female brain, but there are new explanations that if women are treated differently, they’ll end up with brains that are different, or different behavioural profiles because of how the world has treated them.
How did the emergence of brain-imaging techniques such as fMRI affect myths of essential sex differences?
The emergence of fMRI (functional magnetic resonance imaging) in the 1990s really revolutionised our understanding of the brain. Up until then, almost all of the evidence had come from diseased brains or dead brains, so once you could look at a real, intact, functioning human brain, that was an amazing breakthrough. Suddenly you’ve got these amazing pictures of different structures in the brain - you could see how the blood flow changed as somebody was, say, learning a list of words or doing a spatial task - so it’s very, very compelling. But with respect to research on sex differences […] you’ve got very detailed pictures designed to look at differences. The data are about differences and it led straight into the debate about what we wanted to know about men’s and women’s brains, the continuation of the idea that you just needed to find differences in brain structures in order to explain behavioural differences.
That whole question sort of got into disrepute because it got hijacked by neuro-trash of the Men are from Mars, Women are from Venus type; effectively people who didn’t really understand what neuroimaging was about but could take these compelling images and put them into a chapter on why men don’t cry and women can’t read maps or something. The neuroimaging community saw what was going on and started to be much more careful to explain what they were doing: the fact that it wasn’t a real-time movie of a brain, it was the end product of a huge number of statistical decisions aimed at finding differences, so you only reported when you found differences, you didn’t report when you didn’t.
Were you disappointed by the use of fMRI to support the essential sex differences theory?
In the very early stages I started using brain imaging for exactly the same purposes. I started using it looking for those sex differences and thinking there must be something wrong with my research because I just couldn’t find any and when I started looking at the literature, I started thinking when they do find differences they’re very tiny and another study on the same area reports no differences. I came to be aware that there was something funny going on and essentially stopped doing research into sex differences. About 10 years ago I was asked to do a review into how neuroimaging at that stage was being used to look at sex differences and I was horrified and disappointed. Within my own field there was a lot of irresponsible research methodology and interpretation.
What new techniques or technologies in neuroimaging could move the debate forward constructively?
I put somebody in a scanner for an hour and could be analysing the data for another 18 months, so you get these enormous datasets just from individuals. People have moved to sharing datasets and establishing standards so we have access to much, much better datasets and we’ve got much more nuanced ways of looking at them. I think the more subtle techniques may be able to start looking at brain-imaging data more like fingerprints: a better way of identifying individuals. The whole history of brain imaging is looking for the language centre or the memory network or the visual centre, but what’s emerging is just how different brains are person to person. There’s also new machine learning techniques that allow you to take these vast datasets and ask much more open-ended questions: “Can you find a pattern in this?” All our statistics so far have been predicated on us asking “find a difference”.
I think getting away from the idea of male and female brains would actually be quite helpful because we lose so much data by focusing on just those two labels. If you’re looking for a key difference as your starting point, I think you’re already biased and that’s where open-ended machine learning techniques come in. We could be coming up with different types of brains. You can never be doing science in a political vacuum and I think people should acknowledge that and find ways of being objective.
Some argue that women are not naturally suited to STEM careers and this is why they are underrepresented in these sectors. Is this a flawed way of thinking?
There’s this old-fashioned 19th-century thinking of “not many women are in science and it’s because they can’t do it, not because they don’t do it”. I think the distinction between can’t and don’t is really important in STEM.
There’s this emerging narrative about the gender paradox where the countries with the smallest gender equity gap have the biggest STEM gender gap and I think the trouble there is it’s a reflection of the same argument. You talk about women being free to choose and not choosing science, but maybe it’s something to do with the science [rather than the women]. We know the main driver of our brains is that we should be social; we should be fitting into an appropriate social network. Women look at this discipline where there aren’t many people like them. [Some people] assume biology is in the driving seat, but let’s look at the culture itself. Would you really want to be the only woman in a physics undergraduate degree class?
I’m not saying there can’t be some kind of biological difference between boys and girls that could reflect their preferences, but biology functions in a social context and we have much more agency in changing social structures and the culture of an institution [than in changing biology].