I am looking to recruit new graduate students to join the CatLab in Fall 2015. Check the web pages for Psychological Sciences for details on our graduate program and how to apply for admission.

My laboratory currently focuses on two interrelated lines of research. One examines the temporal dynamics of visual object recognition, categorization, and the development of perceptual expertise using behavioral experiments (laboratory and online), computational modeling, and cognitive neuroscience techniques; some of this work is in collaboration with Isabel Gauthier and other members of the Perceptual Expertise Network and is funded by grants from the National Science Foundation and Vanderbilt University.

The other like of research develops and tests cognitive and neural models of perceptual decision making that explain the dynamics of behavior and the dynamics of neural activity in awake behaving monkeys; some of this work is in collaboration with Jeffrey Schall and Gordon Logan and is funded by a grant from the National Eye Institute.

This opening to my personal statement describes some of the general topics we try to understand in the CatLab:

In order to survive, animals and humans need to discriminate predator from prey, edible from inedible, friend from foe. We need to be able to recognize objects in the world as kinds of things because we rarely see the exact same object twice. What we learn about one object should generalize to other objects of the same kind. Kinds of things are called categories. Recognizing an object as a kind of thing is called categorization. Once an object is categorized, whatever knowledge we have about that category can be used to make inferences and inform future actions. If I see a large brown creature in the woods, I need to know whether I should start slowly backing away or pull out my camera to snap a picture. If I see a tasty-looking mushroom at the base of a tree, I need to know if eating it might send me to the hospital. If I see a person walking toward me along the trail, I need to know if it is a stranger or my son.

Humans categorize to dizzying degrees. Some are commonplace, like when we categorize chairs from tables, trees from shrubs, or cats from dogs. Some are remarkable, like when an expert birder rapidly categorizes a subspecies at a glance that a novice might easily confuse with a dozen or more similar species, or when an expert guitar enthusiast recognizes the make and model just by looking at its headstock or pickups. Most of us engage in similarly remarkable categorizations every day. We easily identify the faces of people we know at a glance. Arguably, different people are as structurally similar to one another as different chimpanzees, yet for most people, chimpanzees look the same but people look quite different. Whether faces and objects, the same thing can be categorized at different levels of abstraction. That person across the room is a living thing, a human, a male, a boy, and my son. The object I am sitting on is a piece of furniture, a chair, and a leather wing chair, of a particular make I have long forgotten and probably never knew.

I am interested in how visual categorizations are made and how visual categories are learned. What are the mechanisms? How are objects and object categories represented? How are object representations compared with category representations in memory? How does object categorization affect object representations? How are perceptual decisions about category made? How does object categorization inform action? How do representations and processes change with learning and expertise? I often test hypotheses about mechanisms by instantiating those hypotheses as mathematical and computational models. Model predictions about behavior and brain activity can be derived mathematically or simulated computationally. These predictions can be compared statistically with observed data and with predictions made by models instantiating competing hypotheses. Some of my work is purely mathematical and computational, some combines modeling with empirical data measuring behavior or brain activity, and some is purely empirical but is often motivated by testing predictions of mechanistic models.

-Thomas Palmeri