At the Princeton Social Neuroscience Lab, we study the thoughts, cognitive processes, and behaviors that occur at the place where our internal world meets the external social world. We employ methods like functional neuroimaging, machine learning, and behavioral experiments to gain empirical insights into questions about the self and the social world.
One person can never truly know the contents of another person’s mind. Despite the inherent opacity of others’ thoughts, feelings, and intentions, humans are actually quite proficient at inferring others’ invisible, internal mental states—a capacity known as mentalizing. The lab uses behavioral and neuroimaging methods to explore the processes that allow us to accomplish these mind reading feats.
One way to understand others’ minds is through the process of simulation, where people use their own self-knowledge to infer other people’s mental states and traits. Our research has explored the cognitive processes underlying such social inferences, such as egocentric anchoring and adjustment (Tamir & Mitchell, 2010; Tamir & Mitchel, 2013), and the flexible self-application hypothesis (Todd, Simpson, & Tamir, 2016).
A second route to understanding others’ minds is through model-based social cognition. Our lab has developed the 3D Mind Model, a framework for explaining how people model the social world around them (Tamir & Thornton, 2018). Our multi-layered framework distills the complexity of the social world into low-dimensional maps. For example, we have shown that people represent mental states using three dimensions: rationality, social impact, and valence (Tamir, Thornton, Contreras, & Mitchell, 2016). This model of the social mind is tailored to the problem of predicting other people. We have used behavioral, linguistic, and neuroimaging analyses to show that people use these dimensions to accurately predict how a person will transition from one state to the next, or from one action to the next (Thornton & Tamir, 2017; Thornton, Weaverdyck, & Tamir, 2019). This model thus offers a computationally tractable method for modeling how people represent and predict others’ states and behaviors.
Current lab projects:
What are the consequences of using the self to understand others? How does simulating others change a person’s sense of self (e.g., Meyer, Zhao, & Tamir, 2020)?
How stable is the 3D Mind Model across different targets (e.g., Thornton, Weaverdyck, Mildner & Tamir, 2019)? Modalities? Cultures?
How do people learn how to accurately predict others? What are the social benefits of doing so?
How do two brains predict each other during naturalistic social interaction?
Humans are social animals. We live, work, and play side-by-side with other people, constantly communicating, interacting, and connecting. Why are people so driven to interact? Our lab is interested in understanding how proximal social rewards drive complex social behaviors.
One pervasive social behavior is our tendency to broadcast information to other people – to self-disclose. Researchers estimate that 30-40% of conversation content and 80% of posts to social media sites are devoted to relaying information about the self to other people. What motivates self-disclosure? We find using both functional neuroimaging and behavioral economics methods that people value any opportunity to share information with others - both self-referential and arbitrary information alike (Tamir & Mitchell, 2012; Tamir, Zaki, & Mitchell, 2015).
In these studies, we broke down complex social behaviors into their simpler ingredients to determine which basic social building blocks remain valuable when isolated from the rest of their social milieu. We find that the drive for social experiences is so strong that people continue to pursue even the most minimalistic of social experiences (Jolly, Tamir, Burum, & Mitchell, 2019). We outline this approach of decontextualizing social experiences, alongside the complementary approach of recontextualzing social experiences, in a review paper (Tamir & Hughes, 2019).
Social media are designed to capitalize on the doggedness with which people seek opportunities to self-disclose, inform, and co-experience. How do social media exploit our selfish and social motives (Tamir & Ward, 2015)? How can researchers harness social media to learn about the building blocks of the social mind (Meshi, Tamir, & Heekeren, 2015)?
Current lab projects:
How can we harness new technology to study social cognition in a naturalistic, generalizable, and longitudinal way? See our new research platform, The Person Project.
How does the value of disclosure change across development? in individuals with autism?
What are the social, hedonic, and cognitive consequences of using the internet and social media (e.g., Tamir, Templeton, Ward, & Zaki, 2019)?
How do the stories we hear shape the stories we tell? How do basic memory processes shape the stories we remember?
Our bodies can only ever exist in the here-and-now. However, through the power of our imagination, humans can conjure up experiences wholly divorced from their current environment—a capacity known as simulation. The lab studies the cognitive and neural mechanisms that support successful simulation.
We have examined the neural network responsible for simulation, the brain’s default network, and found that it is engaged more for simulating proximal than distal scenarios in four dimensions—spatial, temporal, hypothetical, and social distance alike (Tamir & Mitchell, 2011). We have explored this process by studying individuals with demonstrated expertise in imagination and creativity (Meyer, Hershfield, Waytz, Mildner, & Tamir, 2019). We have explored other consequences of thinking outside the here and now, for example on an individual's perceived meaning in life (Waytz, Hershfield, & Tamir, 2015). Finally, we have explored fiction reading as a means of facilitating simulations of both people and places (Tamir, Bricker, Dodell-Feder, & Mitchell, 2016; Dodell-Feder & Tamir, 2018).
Current lab projects:
Can reading fiction improve one's ability to simulate other’s minds?
What is the relation between creativity and social cognition? Can training in one improve the other?
What features define the landscape of thought that our mind wanders through during everyday simulations? Can we use computational models of memory to model the flow of spontaneous thought through this space?