I am a cognitive scientist who uses computational modeling and behavioral experimentation to investigate those complex forms of cognition that are uniquely human, and indeed make us human. My primary line of research is in mathematical and computational thinking, where my students and I investigate the cognitive mechanisms underlying our ability to understand abstract mathematical concepts (e.g., in geometry and topology) and to reason about computationally hard problems (e.g., the travelling salesperson problem).
My recent work involves the study of mindfulness as a trait and a state. See my book on the effects of mindfulness on brain, mind, and life. In our research, we're interested in a new, broader definition of mindfulness, which includes self-awareness, self-regulation, as well as self-transcendence. We're particularly interested in how these aspects foster not just personal wellbeing, but can also be of benefit to others, by fostering wisdom, virtue, compassion, and social justice.
The fundamental premise of my work is that computational models from cognitive psychology and cognitive science can be adapted to provide testable process models of decision-making phenomena and optimized to support the decision-making of professionals. I direct the Decision Processes Laboratory (DPL). The DPL utilizes a range of experimental methodologies (behavioral, eye-tracking, EEG) and computational techniques (statistical, mathematical, neural networks) to investigate decision-making phenomena.
My early research examined neural mechanisms of sensory-based recollections. I have also become interested in understanding how memory operates under varying demands on attention, and how we arrive at decisions that are based on our memories and perceptions. The lab has been studying perceptual decision making in order to identify neural signals related to different stages of the decision process. We have recently been building from our early research in this area to study how memory, attention, and decision-making abilities change in healthy aging.
Cognitive control refers to the set of processes by which we direct our actions toward a specific goal. At the most basic level, control processes allow us to translate a presented stimulus into an appropriate motor action. However, these processes and representations quickly become more complex when trying to understand more involved behaviors such as learning peoples names or watching and understanding films.
I work on the high-level aspects of perceptual decision making. My research attempts to elucidate the brain mechanisms that influence what we perceive, as well as build computational models that explain current findings and lead to novel testable predictions. Specific areas of emphasis include visual metacognition, neural network models of vision, high-level processes like expectation and attention, and the role of large-scale brain networks in cognition.
My area of expertise is in the cognitive neuroscience of aging. My specialties include the application of functional and structural neuroimaging methods to understand cognitive and brain aging as well as behavioral endocrinology. I have devoted much of my career to the study of the effects of steroid hormones on behavior and brain function. Among my contributions to this field are studies assessing the effect of gonadal steroids on spatial cognition, hemispheric asymmetry and interhemispheric communication.