Individuals with different motivations often report seeing the same image differently, but it is unclear whether this reflects a bias in what they *see* or what they *report* seeing. Can people with diverse goals and motives truly perceive the same visual stimuli differently? In recent work, I combined computational modeling and fMRI to provide a neurocomputational account of how motivation biases visual perception.
When presented with the identical political content, conservatives and liberals tend to interpret information in a manner that supports their existing beliefs. These biases contribute to increasing ideological polarization in America. What psychological and neural processes drive the divergent processing of political information? To address this question, we employed a novel multimethod approach that combines fMRI with semantic analyses of naturalistic political content.
People are motivated to seek out socially valued individuals in their community (i.e. people who are trustworthy, supportive and well-connected). How do people identify these individuals? What happens when expectations of social value are misinformed, for example, when someone is less trustworthy than their reputation suggests? In this line of work, I use fMRI, social network analyses and computational modeling to examine how social value guides social interactions.
In a separate line of work, my collaborators and I have studied the neural bases of human communication. We found that (1) experiencing, (2) talking about and (3) listening to a verbal description of an event elicits shared patterns of neural activity across individuals. The fidelity of this neural pattern correlated with communication success. These results suggest that communication is associated with the construction of shared neural representations.