Evolution results in a marvelous diversity of phenotypes whose sole function is to support the propagation of the genetic code. What drives the ever-increasing complexity of adaptive traits has been a core focus of evolutionary biology. One of the greatest evolutionary mysteries has been the evolution of cognition. What kind of selective pressure was necessary to produce a brain capable of understanding the intricacies of the universe and the brain itself? In which environments are such extreme phenotypes adaptive? Evolution of cognition has been based on comparative and correlative approaches and correlating cognitive functions across animal phylogeny with known history of studied populations. Our lab aims to advance the field by moving forward from indirect inference in natural populations to direct experimental evolution of brain and cognition in the lab. The major goal of our group is to push the limits of evolutionary neuroscience, especially cognition and brain research through use of the method of experimental evolution. We leverage the genetic, phenotypic and experimental utility of the model fruit fly, Drosophila melanogaster, and the power of experimental evolution to map the genetic and environmental underpinnings of adaptive cognition in diverse populations. By developing high-throughput phenotyping methods that combine real-time imaging and machine learning techniques, robotics and automatization, we can select for high and low cognitive ability in whole experimental populations of Drosophila over each generation and "force" the evolution of cognition. At the same time, we can manipulate natural selective pressures that have been hypothesized to influence the evolution of the brain, such as social interaction or environmental complexity. Moving the study of evolution of brain from past selection to real-time, present, and controlled selection will bring us closer to directly answering a long-lasting mystery: how does a brain evolve cognition?


Genetic variation is the essential substrate for evolution. To understand how and why some variant are selected while others are not, we first need to understand the breadth of variation that is available to selection. Our lab aims to identify natural phenotypic variation underlying neuronal traits such as neuronal and brain morphology, biological processes involved with cognition such as learning and memory, decision making and perception, an variation in neuronal circuitry underlying cognition. Using the extensive genetic resources available for Drosophila melanogaster we can map the natural genetic variation underpinning phenotypic variation of neuronal traits. Understanding natural genetic variation of neuronal traits will help us better understand regulation of these traits on a molecular level as well as their evolutionary potential.