Jan 14 2011
A new study, published in PLOS One, predicts performance on a complex video game by looking at MRI scans of subjects prior to attempting the task. University of Illinois Beckman Institute director Art Kramer and his colleagues used standard MRI scanning (T2 images) of the basal ganglia (the putamen, caudate, and nucleus acumbens) and then correlated the findings with later performance on a video game in which players have to attack a fortress with a spaceship. They found that certain patterns of white matter connections in the putamen and caudate (but not gray matter, and not the nucleus acumbens) predicted 55-68% of the variance among the players. They then confirmed their results with a new group of subjects.
This type of research raises many interesting questions and possibilities. First, if it pans out it can be a useful method for determining aptitude. If the results of this study can be replicated and turn out to be typical, it seems that this type of analysis may be superior to actual performance testing in predicting later performance on a complex task. The author of the study is quoted as saying:
“There are many, many studies, hundreds perhaps, in which psychometricians, people who do the quantitative analysis of learning, try to predict from SATs, GREs, MCATS or other tests how well you’re going to succeed at something, but never to this degree in a task that is so complex.”
I suppose this would highly depend on how close the predictive test is to the later task. But using standardized cognitive or academic tests is a reasonable comparison.
What is intriguing is thinking about where this research paradigm can go (with existing technology and probable future technology). Will this lead to hundreds of studies in which the robustness of specific aspects of brain anatomy are used to make accurate predictions about the potential of individuals to succeed in areas of performance? How will this knowledge be applied? What are the limits of this approach, and how modifiable are the outcomes by training and effort? Is anatomy destiny, or rather are these researchers just looking at the results of prior life experience? In other words, did subjects who were good at video games due to prior experience have more robust white matter connections in their basal ganglia, or were they born with that potential? (Actually – both are likely contributors, so the real question is, what is the relative contribution of each factor.)
While this type of research holds out the promise of specific applications, I would not jump to any conclusions too quickly. It’s possible that the results of such an analysis will reflect a complex combination of underlying factors that are hard to tease out. This research will help us in the quest to reverse-engineer the brain – at least in respect to figuring out how specific brain regions contribute to specific kinds of tasks and learning.
Before we take this information and use it for some practical purpose, we would really need to specifically validate such applications. For example, already there is talk of using these results to tailor specific training or education programs to individuals, by taking into account their neurological strengths and weaknesses. Such attempts at exploiting specific learning styles have not fared well in the past, however. Before we try this with MRI data, we would need studies that show that using different training approaches based upon different neurological profiles actually makes a difference in the final outcome. I would caution against prematurely extrapolating from this preliminary evidence to specific applications.
But despite my caution, I predict that this is likely to happen, or at least some pseudoscientific version of it. You can already buy products that promise to adjust your brain waves. It seems almost inevitable that companies will crop up that promote themselves by referring to this kind of research, and promise to use some brain reading device in order to give you what is essentially a cold reading of your personality and potential. It will be the new phrenology.
A worse possibility is that schools, companies, or other institutions will use some watered-down version of this research in order to screen applicants, give career advice, or tailor learning programs. Companies already use pseudoscientific handwriting analysis, and school systems have been bamboozled into using things like Brain Gym, so this seems highly likely. I will probably have to write blogs debunking such applications of this kind of thing in the future.
The abuse question aside – what is the real potential of this kind of analysis? It’s not clear, we will have to wait and see what the research shows. But let us take the hypothetical situation that this research does pan out, and we can peek into your brain and do an actual analysis of your neurological potential, and make fairly accurate predictions about your future performance. What are the ethics and implications of this?
On the positive side this information can be used to help people – to guide them in their choice of career and hobbies, to individualize training and education programs (at least in part), to help people take advantage of perhaps hidden strengths, and to shore up their weaknesses. It is probable that there are many people who struggle to succeed in certain areas and are not aware that they are laboring under a specific neurological deficiency. This technology would help them identify and then either deal with or work around such deficiencies.
But I can also easily imagine the dark side of such technology, and I suspect I am not alone. The press release on this research finishes with this note:
The findings should not be interpreted to mean that some people are destined to succeed or fail at a given task or learning challenge, however, Kramer said.
“We know that many of these components of brain structure and function are changeable,” he said.
Neurology is not destiny – got it. But what if the research shows it is 60% of destiny? Would it be fair to use such scans as part of an entry exam into a university or competitive job? Would the wide use of such technology make people feel helpless in the face of their hardwiring – why bother trying if you were not born to succeed?
As a scientist and skeptic I always want to know the truth, regardless of the consequences. But at the same time we have to be careful about the unintended consequences of how that truth is conveyed. It often comes down to what is emphasized. In general, it is better to emphasize what people can control rather than what is beyond their control. By definition, you can’t do anything about that which is beyond your control, so don’t worry about it. You can always make the best with the potential that you do have.
So while using brain scanning to tell potential (and who knows, maybe eventually personality, criminal potential, empathy, and a host of meaningful attributes) may be useful when applied appropriately, we have to be careful about creating a society in which so much emphasis is placed on something that individuals cannot control. It’s hard to talk about this without sounding like I am advocating political correctness or even social engineering, which I am not. Rather, it is simply more practical to keep focused on the malleable. It’s like the difference between talent and skill. We are born with talent, but we develop skill. It’s OK to recognize and even celebrate talent (which I think we do as a culture too much), but we should emphasize our celebration of hard work – because that is something everybody can do to improve themselves.
While I hope and expect that this research paradigm will go forward and produce interesting and useful results, we also need to keep our eyes open about the full consequences of how we use such knowledge. Another way to look at this is that social systems have to consider how they affect human motivation. Systems that look great on paper may fail if they are not compatible with human emotions and psychology.
9 Responses to “Predicting Performance from Brain Imaging”
Leave a Reply
You must be logged in to post a comment.