Dyhr Research

I am particularly interested in bridging different levels of biological understanding, from the molecular machinery driving cellular processes to the emergent behaviors at the organismal level. More specifically, I study the neural computations underlying sensorimotor processing during active movement. My research uses a combination of techniques including electrophysiology, psychophysical experiments, high-speed videography, and computational modeling.

Biography

Academic Background:

I have always had a broad interest in the sciences. As a consequence, I never settled on working within a single discipline. Coming out of my undergraduate education at Johns Hopkins University, I was torn between my interest in understanding the world through first principles (physics) and my interest in studying how the brain perceives and interacts with the world (neuroscience).  I was able to marry these two seemingly divergent interests during my PhD work at the University of Arizona, where my research focused on reversing engineering the neural computations underlying motion vision in flying insects (bees in particular). I also developed a parallel interest in engineering, attempting to apply my models of visual computation to robotic systems.

After receiving my PhD, I worked as a postdoctoral researcher at the University of Washington where I combined my expertise in sensory processing with the motor output side of the nervous system. I was trained in biomechanics and control theory, a subdiscipline of engineering. I used this training to develop models and experiments to better understand how feedback between sensory and motor systems influences the structure of computation in the nervous system. While my research is complicated in the sense that I use advanced mathematical models to develop quantitative predictions, my biological experiments are relatively simple (and fun).  For example, training bumblebees to fly through a tunnel to collect a sugar water reward, or testing the ability of hovering moths to track (and feed from) robotically controlled flowers.