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As a group leader at Janelia Farm, Anthony Leonardo will study salamanders and dragonflies, efficient killers that are far more likely to be found roaming Janelia's bucolic landscape than inside the laboratory itself. But the salamander and dragonfly are Leonardo's chosen subjects in research that is building a bridge between the macroscopic world of behavior and the microscopic world of neural circuits.
Leonardo is one of the top young investigators in neuroethology, the study of the neural basis of animal behavior. He earned his Ph.D. in computation and neural systems from the California Institute of Technology in 2002, and has long been fascinated by the brain and how animals behave as they do. His undergraduate training in artificial intelligence and computer science at Carnegie Mellon University included experience modeling human cognition. But it was as a graduate student at Caltech, under the guidance of Masakazu Konishi, that Leonardo began to look inside living brains to understand the complexities of neural circuit dynamics.
That creative early research, probing the mechanisms underlying song generation in the zebra finch, produced some surprising findings. Leonardo tested the prevailing theory that once zebra finches have learned their songs through mimicking a bird serving as a tutor, those songs then become hardwired in the bird's brain. He developed a computer-controlled system to perturb the feedback heard by singing adult finches. By replaying their recorded songs slightly out-of-sync, Leonardo found that the finches' songs deteriorated markedly. After Leonardo withdrew the distorted feedback, the zebra finches gradually recovered their original songs. "We revealed that the songs were stable not because they had become hardwired but because they are maintained dynamically," he says.
The second portion of his doctoral work was done at Bell Labs where he collaborated with Michale Fee to help develop a miniature, motorized microdrive—a tiny device implanted onto the bird's head—that could monitor the activity of several individual neurons while the bird sang. The results of experiments done with the microdrive were surprising. "We had assumed that when the bird produced two similar sounds at different times in his song, the same patterns of neurons would fire in the same sequence. Instead we found that the bird uses entirely different sets of neurons to encode the same sound," Leonardo says. In essence, the bird has played a clever trick—because it only sings a single song, it represents each moment in the song with a different set of neurons. "We hypothesize that this makes learning much faster and more robust because correcting errors in one portion of the song does not affect sounds produced at later times," Leonardo explains. Elegant theoretical work in the laboratory of HHMI investigator Sebastian Seung at MIT has tested this idea and shown that the structure of neuronal firing patterns can indeed arise from song-learning rules that minimize learning time.
What relevance can lessons from a bird brain have for understanding the human mind? Leonardo's hope is that, just as single neurons in different species operate according to the same physical principles, the same logic applies to networks of neurons. "We often have the sense that beneath the complexity of the countless connections linking neurons into a circuit, there lies some relatively simple computation," Leonardo says. "My goal is to develop an understanding of those computations. Model systems like the songbird are useful because they have a complex yet stereotyped behavior that is generated by a small number of brain areas. These types of systems present well-defined and tractable problems. We should be able to solve them in their entirety, from the earliest stages of sensory processing to the final moments of motor control."
Enter the salamander, an amphibian that excels at snagging flying insects with its "ballistically launched" tongue. While a postdoctoral fellow in the lab of Markus Meister at Harvard, Leonardo studied how salamanders capture their rapidly moving prey. He investigated a circuit in the retina that allows the salamander to correct for the motion of its prey during the brief interval in which the neural signal is transmitted. Without such a circuit, the salamander's tongue would hit where its prey was moments ago, rather than its real position. Leonardo showed that the circuit that produces this computation does so only for a small range of target sizes and speeds that are matched to the prey captured by the salamander. So signatures of the salamanders' specialized prey preferences may actually begin in the retina.
At Janelia Farm, Leonardo will tempt his salamanders with computer simulations of a tasty moving insect. He's now working on a touch-screen version that will actually record tongue positions as the salamanders strike at the computer monitor. While the salamanders track their virtual prey, Leonardo will measure the response of visual neurons involved in tracking the prey's position. In addition to salamanders, he has begun a second line of research to study the neural circuitry underlying prey capture in the dragonfly. One project will attempt to implant miniature electrodes into dragonfly visual neurons and record from them wirelessly while the dragonflies fly and catch prey. "Of tremendous importance to our work, " he says, "is looking at neural circuits in different brain areas and different animals. How do different circuits solve the same underlying behavioral problem?"
Leonardo will move to Janelia Farm from Cambridge, Mass., with his wife, neurobiologist Roian Egnor (a new JFRC Fellow), and their 3-year-old daughter. He cites the opportunity for collaboration as among the most appealing aspects of the Janelia Farm campus. "Each lab plays a different role in the big picture of understanding the basis of neural processing," he says. "Together we will be able to do things none of us could do alone."