Dr. Michael Frank Explores Learning, Research and Neuroscience with Study.com

May 09, 2011

Dr. Michael Frank is a professor and researcher at Brown University. Working alongside some of his students, Dr. Frank recently published a study on how advice effects human learning and decision making. Study.com caught up with him to learn more about his research and the fascinating field of cognitive neuroscience.

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By Megan Driscoll

Dr. Michael Frank Brown University

Study.com: What is your educational background and how did you come to teach in the neuroscience department at Brown?

Dr. Michael Frank: I got my undergraduate degree in electrical engineering at Queen's University in Kingston, Canada. I then went on to do a master's in biomedical applications in engineering at the University of Colorado, where I learned that the brain can be studied from an engineering perspective. I stayed there to earn a Ph.D. in Neuroscience and Psychology. I was taken by the ways in which the brain can be studied using mathematical and computational tools, and appreciated this even more when I learned that this approach can help explain various aspects of cognition and the mind.

I now teach in the department of Cognitive, Linguistic and Psychological Sciences at Brown, where I am also affiliated with the Brown Institute for Brain Science and the department of Neuroscience.

Study.com: You recently conducted a study examining a genetic disposition to weighing advice over experience when making choices or considering information. Can you summarize your results for our readers?

MF: We've previously found that there are certain genes that are predictive of the ability to learn from experience as a function of positive or negative outcomes. These genes control function of the neurochemical dopamine. Bradley Doll, a graduate student in my lab, was interested in how advice or instructions influence the degree to which people learn from subsequent experience. Importantly, the advice given was not always accurate, allowing us to study to what extent people learn from their true experiences versus just following advice they had been given beforehand.

We found that the same genes that are predictive of better learning from experience without any advice are now predictive of poor performance when given misleading advice. This may be surprising, as one might think that those who are better at learning from experience might be better at figuring out that the advice was wrong. Instead, the findings supported the idea that people are always learning in the context of a hypothesis they have, in a way that looks like a confirmation bias - they count evidence that supports what they thought already more than evidence that refutes it - and that this distorted learning process has the same genetic correlates as that of simple experiential learning.

Study.com: Genetic propensities are often understood to be the result of evolutionary advantage. Can you explain how your findings might have evolved in some humans?

MF: With the development of language, humans are able to massively increase the efficiency of the learning process. We don't have to randomly try out different strategies to figure out the best way to nourish ourselves in different contexts; we can simply apply what others have discovered. In general, it may be useful to then bias what we learn from our own experience in these contexts to accord with what is supposedly the best strategy, so that we don't stop doing it just because it produces a few negative results in the short term. So these genetic effects may be adaptive in some contexts.

Of course, there is a trade-off, because one would want to be able to eventually disregard bad advice, and it may be useful to have both kinds of genetic variants in the population.

Study.com: What broader implications could your findings have for learning? Would someone with this genetic variation be better or worse suited to a classroom environment?

MF: It is far too early to apply these findings to a classroom environment, not to mention the ethical issues that would likely come up. Even if genetics could, in the future, be used to help determine for which learning environment or style a student may be best suited, one certainly would not want to deprive other students of a particular environment because of their genes.

Study.com: Do you have any follow up studies planned to further pursue this subject? Can you share any of the details?

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MF: We are testing various other aspects of the theory that we think best explains these findings. For example, after going through multiple rounds of experience (some of which are supportive of the advice but more of which are not), the theory predicts that people will learn to adopt the advised strategy. At this point, they would no longer need to retrieve the 'rule' in memory. Bradley is testing this notion by giving participants a distracting task to see if they still act in accordance with the advice even if they can't retrieve it in memory.

Study.com: What are your other major areas of research, and how does this study tie in to them?

MF: My lab studies the neural and cognitive mechanisms of learning, decision making and cognitive control (the ability to adaptively regulate behavior in accordance with current goals). We build theoretical models and test their implications in diseases and medications that affect the brain systems involved, using brain imaging.

The genetic studies allow us to examine whether individual differences in cognitive performance can in part be explained by variations that affect these same brain systems. Correlation is not causation, so it is difficult to know whether any gene is directly or only indirectly related to cognitive function. But together with studies that pharmacologically manipulate the same chemicals, we can be more confident.

Study.com: What courses do you teach at Brown? Does your research influence your teaching (and vice versa)? In what ways?

MF: I teach Computational Cognitive Neuroscience (a computer-based course in which students learn how to simulate various aspects of brain function, not unlike the one that got me into this field in the first place). I am also currently teaching a class called Mechanisms of Motivated Decision-Making.

Certainly my research methods, and to some degree the content, influence my teaching. Like any researcher, I emphasize the methods and approaches that I find to be most informative or compelling. And it is not uncommon for students to ask questions that can lead to new research projects.

Study.com: What advice would you give to a college student who's considering going into neuroscience?

MF: Read broadly and don't invest too much in conclusions adduced from any one research method, as each alone has flaws. In cognitive neuroscience, the whole is greater than the sum of its parts.

Study.com: Finally, I'd like to offer you the opportunity to share anything you'd like about your research and the field of learning and decision making in neuroscience.

MF: This field of research is really captivating. One of the difficult issues is that to make statements about the basic mechanisms of learning and decision making, one has to derive somewhat contrived laboratory measures of specific aspects of these phenomena. It then becomes more challenging to make conclusions about real-world situations, because these typically involve many intertwining factors. This is especially salient in genetics research.

So we have to always keep this in mind, that while basic science questions are important to address as fundamental issues, we should not overstate our case, given that whatever mechanisms one is studying are likely to be only a small part of the bigger picture.

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