Eugenia Chiappe grew up in Buenos Aires (Argentina), where she spent her formative years drawing, acting, and dancing in a Trapeze show. She did her undergraduate studies at the School of Natural and Exact Sciences at the University of Buenos Aires, where she was fascinated by physical chemistry, biophysics, developmental biology, and evolution. After a stroke of luck, she landed in New York City as a Howard Hughes Medical Institute (HHMI) Predoctoral Fellow to study the cellular bases of the cochlear amplifier in Jim Hudspeth’s lab at the Rockefeller University (2003–2006). After graduation, she joined the lab of Vivek Jayaraman in HHMI’s Janelia Research Campus, where she participated in the development of technology to record activity in neurons in a behaving fly. With her long-standing interest in motor control, she started her own lab in the fall of 2012 at the Neuroscience division of the Champalimaud Foundation’s research program in Lisbon (Portugal), where she studies the role of self-motion estimation in the control of locomotion. She was recently awarded a European Research Council (ERC) starting grant to study how visuomotor networks represent accurate ongoing movements to minimize unintended rotations during goal-oriented locomotion. What do you think inspired your interest in biology/science? Essentially, it was the process of being able to explain the invisible. This interest only emerged and developed during my last years of high school though. I had never before considered science. As a girl, I was determined to become either an architect or a performing artist. I spent much of my time acting as well as playing sports and then converging these hobbies into circus art performances. Therefore, I grew up drawing, tuning my sensitivities to a sense of functional esthetics, moving my body, and really honing these crafts. It was not until my first lectures in Chemistry and Physics that my world and determination collapsed, as I became fascinated by the fact that properties of matter invisible to the naked eye form the essentials for how things work and how life has evolved. At that time, I did not know any scientists, and no one close to my family’s social network was doing scientific research. Nevertheless, I set up an improvised visit to the School of Science (which happens to be next to the School of Architecture) at the University of Buenos Aires, thinking that I was going to be able to ask a burning question: what does the process that leads to discovery and explanation look like? Of course, I did not manage to talk to any scientists, but I loved the school atmosphere and the messages to the students posted on the walls. This is how I decided to enroll at college, registering simultaneously in Chemistry and Biology — two independent undergraduate programs — because I could not make up my mind. What do you most like about a scientific career? Two things. First, I really enjoy the intellectual challenge that comes with understanding an important neurobiological problem, something that we do not know or understand well yet. Identifying good questions to address the problem — to make it accessible to experimental examination — is what really motivates me. I like the adventure of being out of my comfort zone to design the best experiments, those that lead to clear explanations either by using new technology or by finding new perspectives or ways of thinking about a problem. That is, I love the creative part of our work. None of these aspects are easy, and it takes time as well as tons of discipline and training — in a way, it is very similar to excelling as a circus performer. Second, at a community level, I really like working and collaborating with bright people from all over the world. In addition, I find mentoring — i.e., fostering the curiosity and critical thinking of younger colleagues — a very satisfying responsibility as a scientist. In recent years, I also became involved in mentoring women in science, technology, engineering, and mathematics (STEM) through different mechanisms, such as structured programs (for example, the Cornelia Harte Mentoring program), or through direct connections with women in STEM across the globe. Looking at data (for example, NSF surveys), one can see that, in 2007, when I was starting my postdoc, about 34% of non-faculty, postgraduate researchers were women in STEM fields. During the following 10 years, this percentage grew to only about 40%. At faculty and leadership positions, the numbers are even lower. Paradoxically, in these 10 years we find that there has been an increase in women starting academic STEM careers. Therefore, we must work hard to create an environment that retains this talent. What’s your favorite experiment? My favorite experiments are those that are conceptually very simple and that provide a powerful explanation of a biological phenomenon. For behavioral neurosciences, an example of such ‘clever’ experiments is represented by the work in the 1950s of Von Holst and Mittelstaedt in flies (Naturwissenschaften (1950) 37, 464–476) and Sperry in fish (J. Comp. Physiol. Psychol. (1950) 43, 482–489). By twisting the head of the flies and the eyes of the fish, as well as letting the animals move around under these conditions, these studies clearly showed that behavior could not be explained by the ongoing ‘classical reflex theory’. I also think that exploratory experiments — that is, experiments that are not hypothesis driven — are important too. They provide the opportunity to observe and gather evidence in an unbiased manner and to generate ideas that can then be tested more specifically. The explosion of technological development in the past 10 years has been critical in facilitating both kinds of experiments — it is an amazing time for neuroscience and for the biological sciences in general. What is your greatest research ambition? With respect to our specific research plan, we would like to venture as far as possible in the direction of answering the following questions. First, what does the pattern of activity in a neural network mean in terms of computations? Second, how do these computations relate to animal behavior? Third, how conserved are computations across different brain functions and animal systems? We take an experimental approach to these questions by studying how the central nervous system (CNS) is organized to support conserved functional principles governing locomotive systems in all animals. One level of satisfactory answer for us will be to find a way to build an agent that moves through space in a very similar manner to an animal, which in our case is the fruit fly, Drosophila melanogaster. This organism provides unique advantages in our quest to understand neural circuit activity in the context of locomotion that include a small body size, an accessible CNS for the kind of measurements we analyze, and the presence of two different modes of locomotion, flying and walking. These characteristics give us the opportunity to perform integrative and comparative analysis to extract computational principles that are beyond the specifics of the actuation of movement. In doing so, we aim to develop a computational framework that can establish connections to neural activity observed in similar circumstances in other animals, including mammals. What do you consider the most exciting aspect of your research? In one project in the lab, we study populations of visual neurons that are sensitive to visual motion cues. These cells are four synapses away from photoreceptors, yet visual signals can only partially explain neural activity when flies are engaged in locomotion. The extra-retinal activity comprises different components that are related to the behavioral state and goals of the animal, as well as to the details of ongoing movements, either on a moment-by-moment basis or over longer timescale regimes. It is just so incredible to see this plethora of signals interacting in rather complex ways during behavior at the early stages of visual processing. We do not know what they represent computationally yet. However, very similar signals are present across analogous systems in vertebrates, suggesting that motor-guided extra-retinal processing is a conserved phenomenon in visual networks across the animal kingdom. We are very interested in examining what the role of these multimodal signals is for visually guided internal representations, especially for those signals that we observed being broadcast throughout different regions of the fly brain. What is the biggest mistake you have made? One important mistake that I made as an independent scientist was to give luck very little credit. As everything else in life, luck is an important component in our scientific career. And what I specifically mean by luck are the unexpected opportunities around the corner that we may not have anticipated. To take advantage of these strokes of luck, one must be prepared to recognize them. It requires vision, open-mindedness, and being able to take risks. I think that it is very important to be attentive to the details of data, to welcome the so-called negative results and mistakes! A really bad mistake would be not to pay attention to them; history tells us that mistakes have been critical for important discoveries to happen. What is the best advice you’ve been given? The best advice that I have received was from my PhD advisor, Jim Hudspeth. He once told me that, above all, a successful project requires perseverance to keep motivation and curiosity high through all the trials and errors of experimental research. Trial and error means that we must think of a particular problem in new ways that require a lot of creativity. And without motivation, I do not think that creativity can be ignited. What do you see as the biggest challenges confronting science? Anything that curtails the ability to pursue curiosity-driven and risky research hampers scientific progress. Curiosity-driven research is at the heart of important advancements in health and technology. That is, basic research is for the benefit of the entire society. Our reservoir of knowledge will shrink rapidly if funding is focused on more applied science. Likewise, our knowledge of biology will be impoverished if funding is restricted to a few animal models. As a society, we need to provide continuous funding support where it is needed most — for basic science projects that are pushing the boundaries of the unknown — because innovative connections can be facilitated only if knowledge is there. With the rising challenges related to climate change and new infectious diseases, more than ever we must expand funding for basic research to find the solutions to a complex global ecological crisis and pandemic public health issues.