University of California, Berkeley
Dr. Dan is also a professor of neurobiology at the University of California, Berkeley.
Yang Dan's laboratory studies how visual information is processed by cortical circuits and how circuit dynamics vary across brain states. Using both bottom-up and top-down approaches and a combination of electrophysiology, imaging, and computational techniques, her group aims to understand neural processing at multiple levels, from single synapses to cortical microcircuitry, and from network dynamics to animal behavior.
As a child, Yang Dan had a head start in math. Before she ever entered a classroom in her hometown of Beijing, her father, a nuclear physicist, taught her elementary math. She entered math competitions in elementary school, and in high school she won first prize two years in a row in the Beijing High School Mathematics Competition. "You know, once you have a little advantage, you just have fun with it," she says with a bit of a shrug and a laugh.
Following undergraduate studies in physics at Beijing University, Dan applied to Columbia University for graduate work in biology, where she received an HHMI predoctoral fellowship. She'd never taken a biology course, but she thought it might satisfy her desire to study profound questions. Her classmates in New York often asked how she was coping with the transition from China to the United States. "New York is such a big city, like Beijing, I didn't feel a culture shock," she says. "It was all of the biology courses that were more overwhelming!"
Now studying the neurobiology of vision at the University of California, Berkeley, Dan finds that her previous training in physics and mathematics enables her to take on more complex biology questions than she might otherwise. Instead of looking at what happens at the level of a single neuron, or with a simple pattern of stimulation, Dan tackles the big-picture, systems-level questions: What happens in a circuit of connected neurons or when a neuron receives complex stimuli, as in real life? "I think in systems neuroscience, data analysis is always a huge deal," Dan says. "Everybody in my lab writes their own programs. It is an essential part of looking at the data."
Dan's group recently used a mixture of experimental and computational approaches to explain how the brain gives rise to a visual illusion. The researchers measured electrical activity in the visual cortex of animals in response to stimuli, developed mathematical models, and, working with human volunteers, explored the relationship between physical stimuli and the sensations or perceptions they evoke. Their experiments relied on a visual trick that uses motion to distort the relationship between objects. Normally, humans can easily see whether three objects are aligned with each other. However, if one of the objects has a texture that moves across its surface, like the stripes on a barbershop pole, the object itself appears to be shifted in the direction the texture is moving. "It's a very powerful illusion," Dan says. "If you use a ruler, you will see that the objects are aligned. But when you look at it you say, 'No way, they are definitely not aligned.'"
Their data led Dan's team to hypothesize that the illusion results from two features of the neural circuit that processes the visual stimuli: the connections are stronger on one side of the circuit than the other, and some of the neurons in the circuit preferentially respond to motion in one direction. Furthermore, their model simulation suggests that this asymmetric circuit could be part of a pattern that is widely observed in the brain.
Most previous explanations of visual illusions have relied only on information about the receptive field properties of neurons, such as the area in space from which they detect stimuli. Dan's group went further, working out how the neurons in the circuit interact with one another and how the circuit is shaped by changes to the synapse.
One of her next aims is to discover the rules that govern two major visual processing regions in the brain, whose functions are not understood. Biologists know that visual signals pass from the eye to an area in the occipital lobe at the back of the brain called V1, which is the primary visual cortex. From there they travel to area V2 and on to area V4 and to another segment called the inferior temporal cortex. V1 detects relatively simple edges, and the inferior temporal cortex is involved in facial recognition, but what V2 and V4 do is unknown.
Testing the responses of these neurons to simple stimuli is unlikely to solve the puzzle, says Dan. Instead, she and her team are testing neuronal responses in V2 and V4 to complex stimuli, such as natural scenes, and then using their computational skills to sort out what exactly the neurons in each region respond to. They don't have answers yet, but Dan has set up several approaches to work on the problem, including a collaboration with researchers in Shanghai.
Dan takes her responsibility as teacher and role model—especially to women scientists—seriously. These duties give her the opportunity to support the next generation. She's even mentoring some of the students in the lab of her Shanghai colleagues. "China is a huge country, with a lot of very talented students, who are working very hard," she says. "The students are hungry for guidance. I talk to them, look at their data, and give them some suggestions. It is really rewarding." Perhaps Dan's help will prove to be their extra advantage—just like the one Dan's father gave her as a child.