Research Interests: I am interested in the acquisition and representation
of conceptual knowledge. An important observation is that conceptual
knowledge is not an undifferentiated, homogoenous system but is instead
organized into components specific to a domain (living; non-living) or
attribute type (color; shape; etc). One aspect of my research asks about
the factors that lead to such divisions and determine their cortical
placement. My most current line of work asks how different kinds of
conceptual knowledge are acquired, and to what end they are put to use
computationally. Specifically, I hope to account for the acquisition of
properties of objects that are not physical qualities (e.g., color or
shape) but which denote regularities in their interactions with the world
(e.g., the functions of artifacts and psychological properties of animate
kinds). This latter kind of property tends to be more abstract than the
former; an account of such property learning could thus yield insights into
how humans acquire abstract conceptual knowledge more generally.
Research Interests: I examine how semantic memory structure enables and constrains high level cognitive processes, such as memory retrieval and creative thinking, in typical and clinical populations (such as persons with autism). To achieve this, I use computational methods to represent semantic memory structure and empirical neurocognitive methods to directly examine these computational findings.
Research Interests: I’m interested in the how episodic memories are altered with consolidation, and how this process is related to the acquisition of semantic and conceptual knowledge. As a graduate student, I used behavioral and neuroimaging methods to examine how episodic memories with overlapping information come to be represented over time.
Research Interests: I am interested in the role of executive function in accessing, maintaining and manipulating semantic memories in the processing of both verbal and non-verbal input streams. For example, predictive processing may play a role in our ability to understand rapid linguistic input. Prediction may also contribute to our ability to rapidly identify objects and recall relevant information about them as we move through the visual world. However, open questions remain regarding the extent to which predictive processing in the verbal and non-verbal domains relies on shared neural and cognitive mechanisms, and the extent to which differences across domains can be explained by general principles of neural organization. Similar questions arise in comparing working memory function and the broader class of contextual facilitation effects across the verbal and non-verbal domains.