- Molecular Biology/Princeton Neuroscience Institute
Title: Associate Professor of Molecular Biology and the Princeton Neuroscience Institute.
- Computational Neuroscience
- The McDonnell Center for Systems Neuroscience
- The Scully Center for the Neuroscience of Mind and Behavior
Field: Quantitative approaches to systems neuroscience
Office: 316 Schultz Laboratory
9 Guyot Hall
What are we interested in? Here’s an example: you’re browsing DVDs in a video store. You pick one up—you like it, perhaps you might buy it, but you’re not sure yet. You put it back down, and stroll down the aisle, pick a second DVD up. You compare them; perhaps today you decide to buy the first DVD. What happened in your brain as you went through all this? What are the neural mechanisms that allow you to remember, for a few seconds, how much you liked the first DVD; to compare the two DVDs; to make a decision; to apply the rules of behavior appropriate for the context you’re in (here, a video store)? In other words, what are the neural mechanisms underlying our cognitive abilities?
What methods do we use in our research? We use a combination of computational, behavioral, and electrophysiological techniques. We train rats to perform tasks that require cognitive components that we’re interested in studying. For example, we train them to remember a stimulus for a few seconds, and to then make a behavior based on their memory of the stimulus. We can then study neural responses during this behavior, and observe the neural correlates of short-term memory. To help us understand the mechanisms behind our findings, we build computational models of networks of spiking neurons, with which we explore the circuit architectures and mechanistic hypotheses that could explain the experimental results. The models both give us greater insight into potential mechanisms, and help us decide what are the best next experiments to test and distinguish between hypotheses.
Who are we? Personnel in the lab range from purely computational to purely experimental. We try to minimize the barriers in going from one end of this spectrum to the other: all researchers in the lab are encouraged to flow easily and freely within the computational/experimental spectrum, according to their own interests and needs at any given point in time, and to talk frequently with people at other points of the spectrum.