Gregory R. Samanez-Larkin

Vanderbilt University, USA

What does your research focus on?

In general I am interested in how cognition and motivation develop and change over adulthood and into old age. Most of my recent work has specifically examined age-related change in learning and decision making — particularly related to finances. The larger goal of all of this work is to contribute to a more comprehensive model of human aging that integrates evidence and theory from psychology, neuroscience, and economics.

What drew you to this line of research? Why is it exciting to you?

The specific focus on aging is largely the result of hearing several talks by Laura Carstensen in 2002. Fresh out of undergrad, I started attending conferences where Laura was speaking. Hearing for the first time about the drastic demographic changes on the horizon and the unique divergent trajectories of emotion and cognition was incredibly inspiring. I felt a sense of urgency and almost immediately my initial interest in emotion and individual differences had a direction! This felt, to me, like an area where science had the potential to address important changes that are happening right now. In fact, some of the research I am doing now with Brian Knutson and Camelia Kuhnen on susceptibility to consumer fraud in older age will be immediately used to inform the design of prevention efforts by the FINRA Investor Education Foundation. This is an area where there is potential for instant translation, which is very exciting for me.

Who were/are your mentors or psychological influences?

Some of the people who have directly influenced my thinking and style most are Barb Fredrickson, Laura Carstensen, David Laibson, James Birren, and Robert Butler. I’m also a big fan of John von Neumann and David Marr.

To what do you attribute your success in science?

I am tremendously thankful for the collaborators I have had along the way — from undergraduate research assistants to my faculty advisors. Being surrounded with great people makes all of this that much more rewarding and fun. I have always been more inspired by hard work than being “smart,” so I try to surround myself with people who have similar values. This is probably partially related to growing up in a small Midwestern town, an area of the country where labor is highly valued, and then further instilled by my parents along the way (I recently gave my mom, a middle school teacher, a copy of Carol Dweck’s ‘Mindset’ because it reminds me so much of her parenting and teaching style). When something interests me, I get intensely fixated on learning everything I can about it. Before I found my direction in science, it was directed at hobbies like rock climbing, and before that wakeboarding. I scoured magazines and websites for every bit of information I could find. I was even interested in how the equipment was engineered and manufactured and how any emerging technology might change things. It’s both a blessing and a curse, but I approach science with that same spirit. Luckily, I have always been surrounded with people (including my wife!) that help channel this tendency into something less obsessive and more productive. At all of the places I have been trained — Michigan, Stanford, Vanderbilt — I have had very motivating advisors who have helped me learn to find the answers.
What’s your future research agenda?

Probably like a lot of psychologists, my general goal (beyond just the curiosity of figuring out how things work) is to improve well being. I hope that my work can in some way help people make better decisions throughout life that contribute to remaining “mentally sharp, physically fit, and financially secure” in old age (a phrase I picked up from the Stanford Center on Longevity).

Any advice for even younger psychological scientists? What would you tell someone just now entering graduate school or getting their PhD?

One of the most important things I have learned so far is to value criticism. It’s natural to be sensitive and let negative feedback dampen your motivation. While working on my undergraduate honors thesis, one of my readers told me I should probably reconsider a career in science if this (my first draft) was the best I could do. At the time it was devastating. Although I might not deliver feedback the same way, they were right. It wasn’t the best I could do. I had to dust myself off and keep going. The actual science can be frustrating when things don’t work out like you planned and people will constantly challenge your ideas, but you have to learn to love that. It’s all part of making progress. I think about it this way: most of the time when someone offers a critique, they cared enough to pay attention and actually say something about it. A lot of the studies I have most enjoyed working on have come from a critic’s challenge for me to address a limitation of prior work.

The other important thing I learned in graduate school is to give as many talks as possible. It gets easier every time!

What publication are you most proud of or feel has been most important to your career?

So far the publication I am most proud of is a paper that was published in 2010 in the Journal of Neuroscience. It was a bit more challenging to publish than my first few papers, which may have added to the satisfaction of actually getting it accepted. It went through review at a few journals and with each round got better and better. I also particularly like this paper because it is my most integrative to date (both in terms of disciplines and methods). Inspired by early theorizing by James Birren in the 1970’s, more recent computational work by Shu-Chen Li, and a handy statistic developed by von Neumann in 1940’s, we developed a novel measure of neural variability to assess both age differences and relationships with investment behavior. The relationship we observed between age and investment mistakes was mediated by an increase in mesolimbic neural variability. The age-related increase in variability in the midbrain and striatum subsequently replicated in a study by Douglas Garrett in Cheryl Grady’s lab using completely different methods. This paper has also led to a lot of fruitful discussion and several follow-up projects with Shu-Chen Li, Doug Garrett, and Cami Kuhnen.