How – and why – do individuals arrive at different interpretations of the same information?
Individuals often interpret the same information in different ways. Do certain personality traits bias individuals toward one interpretation or another? How are divergences in interpretation reflected in brain activity before, during and after exposure to ambiguous information? Can we use ambiguity as a feature rather than a bug, to tease out meaningful individual variation in both brain and behavior? In this line of work, we combine novel experimental paradigms (e.g., bespoke naturalistic tasks) with innovative approaches to analyzing both neural and behavioral data to investigate and model the processes by which individuals appraise complex information in light of their intrinsic tendencies and prior experiences.
How do individual brains differ in their functional organization, and how does this relate to behavior?
Our previous work has shown that patterns of functional brain connectivity are unique enough across subjects and stable enough within subjects to serve as a “fingerprint” that can identify an individual from a large group. Moreover, features of these connectivity fingerprints predict high-level behaviors such as fluid intelligence and sustained attention. In ongoing work, we are characterizing how functional brain organization is modulated by both trait- and state-level factors, with the ultimate goal of developing neuroimaging-based biomarkers for real-world applications.
We have a keen interest in developing new methods to help us answer these exciting questions. As one recent example, we developed and continue to help refine the Connectome-based Predictive Modeling (CPM) method for predicting behavior from functional connectivity. As another example, together with collaborators, we are also helping to advance acquisition and analysis methods for layer-specific fMRI, especially for cognitive applications in higher-order association regions of the brain.