Sophie Aimon is a postdoctoral fellow at University of California San Diego and Kavli Institute for Brain and Mind in the laboratory of Dr. Ralph Greenspan. She received a master’s degree in theoretical physics of complex systems from Université Paris Diderot, and did her PhD in biophysics in the Institut Curie in Paris. Dr. Aimon is interested in global states of activity in the brain and how the brain spontaneously shifts between these states. Her research focuses on characterizing activity in the brain of behaving or resting fruit flies. She uses a new ultra-fast microscopy technique to record the activity in the whole fly brain and works closely with theoretical neuroscientists to analyze the data and model network activity.
“Network activity underlying various behavioral states in adult Drosophila”
The fruit fly may seem like a simple creature with a simple set of behaviors—locate food, escape predators and find a mate. Yet even just flying through space to follow a ripened fruit’s wafting aroma is a surprisingly complex feat. The fly must home in on the fruit by tracking the odor, it must navigate the complex visual flow of a three-dimensional world and, all the while, it must maintain flight speed and direction in the face of shifting air currents. This is no small task and requires most, if not all, of the fly’s brain. Yet how the fly’s relatively small brain of 100,000 neurons—by comparison, a human brain contains a million times more neurons—guides the insect’s flight is unclear. In part, this is because of the technical hurdles in observing the activity of those 100,000 neurons all at once and at the speed of neural processing. In our work, we have overcome this limitation with novel microscope technology that can observe the activity of the fly’s entire brain forty times faster than previous techniques. Using sophisticated genetic and imaging techniques, we can take measurements of neural activity at up to 200 times per second. Our experimental design also allows us to observe brain activity during behaviors such as walking and grooming. Because the fly’s brain anatomy is well-known, we can correlate activity to specific brain areas. This allows us to ask fundamental questions about brain function. Are specific brain regions involved for specific behaviors? Or are the same regions involved but with different patterns of activity? How do different brain regions interact with each other? And what happens in the brain when an animal switches from one activity to the next? A key part of our approach will be to collaborate with theoretical neuroscientists to build computer models that will make sense of this new and exciting source of data. Armed with these models, we will be in a better position to interpret whole-brain activity in more complex animals, such as humans, when technology has sufficiently advanced to collect that data.