2019 Janet Taylor Spence Award
Jon Freeman
New York University
psych.nyu.edu/freemanlab
Please briefly describe your research interests.
I’m interested in the cognitive and neural mechanisms that allow us to make sense of other people. When we encounter others, we instantly make any number of social judgments. For example, we categorize others into social groups, perceive their emotions, and infer their personality. We often arrive at rich, elaborate impressions and form an internal model of another person from even the most minimal cues. All the while, we’re rarely aware that we’re making these judgments, and we also have little conscious access to the specific cues that drive them. My lab’s research aims to understand the mechanisms that drive such split-second social perceptions and, in turn, how they drive behavior. We use functional neuroimaging, behavioral paradigms (e.g., real-time behavioral techniques such as mouse tracking), and computational modeling to investigate how a variety of social cognitive and visual processes shape perceptual and interpersonal decisions. We try to take an interdisciplinary and multilevel approach to examine these questions, incorporating insights across social psychology and the cognitive, vision, and neural sciences. My lab’s research is also currently taking additional directions at the juncture of social cognition, vision, emotion, and decision making.
What was the seminal event, or series of events, that led you to an interest in your award-winning research?
Taking cognitive neuroscience in college opened my eyes and spurred my interest in getting involved in three different labs. Being in New York City for college, where you can walk by hundreds of different people in only a few seconds, made me deeply curious about how social perception works. The elaborate information we infer about others with the most minimal cues while walking down the street began to fascinate me. First impressions drive some of our most important decisions in life, and yet we’re generally unaware of the cues or information that drives our perceptions and evaluative reactions. My undergraduate research with Kerri Johnson, Liz Phelps, and Daniela Schiller showed me early on that these fundamental questions can be addressed with a rigorous scientific approach, and this set me on a path to working in graduate school with Nalini Ambady. In my first year of graduate school, I read Michael Spivey’s book Continuity of Mind, which strongly shaped my research trajectory. It provided a cognitive science framework that, although having nothing directly to do with social perception, made me think entirely differently about social perception and its underlying cognitive dynamics.
Tell us about one of the accomplishments you are most proud of within this area of research. What factors led to your success?
My work has always dealt with fundamental issues of representations in social cognition, and mouse tracking and computational modeling have been quite valuable in understanding underlying social cognitive representations. But in recent years, we’ve been using multivariate fMRI to probe the structure of representational neural patterns, and in my view this has provided the perfect triangulation with mouse tracking and modeling to better understand underlying representations in social perception and how they may be computed and transformed. For example, we’ve leveraged these three techniques in tandem with one another to provide a comprehensive means to test the impact of stereotypes or emotion-concept knowledge on face perception and identify at what level of neural representation these impacts manifest. In this example, we are finding that these impacts on representational structure manifest in even visual face-processing regions, providing support for a prediction from our modeling work and documenting how “deeply” social cognition may constrain visual processes. Besides these specific empirical demonstrations, I think that the triangulation of underlying social cognitive representations using mouse tracking, modeling, and multivariate fMRI is exciting and may have a number of broad uses in the future. Much of the success with beginning this work in my lab is owed to my stellar and talented graduate students, namely Ryan Stolier and Jeffrey Brooks.
What contributions, or contributors, to psychological science do you feel have had a major impact on your career path?
I was fortunate to have had incredibly supportive mentors, and the intellectual guidance and freedom they gave me has had a major impact on my career path. As an undergraduate, working with Kerri Johnson heavily shaped my theoretical perspective. Working with Liz Phelps and her post-doc at the time, Daniela Schiller, taught me much about neuroimaging and cognitive neuroscience, which I was able to bring with me to graduate school. My graduate mentor, Nalini Ambady, gave me immense flexibility to explore my intellectual interests and provided a model of mentorship that I try every day to embody as a PI myself now. My research is deeply interdisciplinary and so in starting out I needed informal training from multiple perspectives. Nalini and Kerri provided social psychological perspectives, and I additionally sought collaborations with Phil Holcomb to learn about electrophysiology, with Ken Nakayama to receive training in vision science, and with Rick Dale for formative discussions on cognitive modeling, dynamical systems, and mouse tracking. I am indebted to all my mentors and grateful for these opportunities. My faculty colleagues at Dartmouth and NYU have also been a source of great support. Finally, I consider myself very fortunate to have been able to begin my faculty career with stellar students and trainees, and they’ve contributed substantially to my path and taught me a great deal as well. One of my favorite aspects of being able to do science for a career is the community of colleagues, collaborators, mentors, and students that we all are a part of, and it makes science all the more rewarding. Being a part of such an inspiring and talented community of researchers has certainly had an impact on me and my career.
What questions do you hope to tackle in the future?
I’m eager to apply our theoretical and methodological approach to better understand how we built internal models of other people and to test different possible neural representational spaces that underlie these models. I’m also looking forward to testing potential downstream consequences resulting from stereotypically or conceptually shaped face perception, such as whether affected perceptions serve as a form of a visual confirmation bias that sustains or exacerbates already-existing social associations. I’m also quite interested in exploring learning, malleability, and change and developing techniques to change people’s perceptions, potentially in a long-term fashion. This work would have implications both for developing better interventions (e.g., bias interventions) and informing our understanding of how the interplay between basic systems underlying social cognition, visual perception, and decision making.
What does winning this award mean to you both personally and professionally?
I am very honored to receive this award. This year’s recipients and those of previous years are truly inspiring, and it’s humbling for my work to be recognized alongside them.
