Current research funding

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High-Resolution, Parallelized Imaging of Freely Swimming Zebrafish with a Gigapixel Microscope

The major goal of this project is to use optical microscopy, working with larval zebrafish (3-6 days post fertilization), to develop large scale optical assays that offer critical insights into the human body, our brain, and the diseases that affect us.


Interrogation and manipulation of brain states through real-time analysis of neural activity

Research IncubatorAwards from the Duke Institute for Brain Sciences (DIBS)

One of the great challenges in neuroscience is to understand how local groups of cells work together in circuits to generate complex behaviors. Historically, scientists have been limited to studying only a few of these cells at a time, yet new developments in microscope and imaging technology have recently made it possible to study much larger groups of cells. In fact, for some small animals like the zebrafish, which is transparent in its larval state, it is possible to record the activity of nearly all brain cells at once. But there’s a downside: these new experiments can generate up to a terabyte of data an hour, enough to fill several hard drives per experiment! And often, the data from one day must be analyzed overnight on a computer cluster before the next experiment can start. The goal of our project is to remove much of this data analysis burden by using newly- developed data processing methods and computer hardware to analyze the incoming brain signals in real time. Our goal is to perform so-called closed-loop, all-optical experiments, in which the incoming data change the experiment as it’s being run—a feedback loop. For example, we will be able to see how some neurons respond to visual information as the data are being collected and to stimulate these same neurons based on their response patterns. Methods like these promise to dramatically expand our understanding of how networks of brain cells function together, not only in healthy brains, but in neuropsychiatric diseases.