Transforming Sensory Signals into Muscle Activations in a Behavior with Dynamic Constraints

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Animals are thought to have diverged from plants more than 1.5 billion years ago. Basic to this split are different strategies for obtaining the energy needed for life: for a plant, it is "stay in place and absorb," and for an animal, it is "move around and grab." As soon as motion enters the scene, so do two quite different regimes under which motion can occur: the first is the "viscous" regime, in which an animal will stop in its tracks as soon as it ceases generating locomotory forces, and the second is the "dynamic" regime, in which an animal will keep moving even after it ceases generating such forces. For our fluid-bound ancestors, this transition occurred with the dawn of the multicellular animals around 0.6 billion years ago. Control of motion is much more difficult in the dynamic regime, a fact well known in the engineering of robotic systems. This sets the fundamental problem for nervous systems to solve: the transformation of sensory signals into motor signals in a manner that accounts for the animal's dynamic constraints. Dr. MacIver will lead a multidisciplinary group of researchers with expertise in neuroscience, robotics, and fluid dynamics to understand how sensory signals are transformed into motor signals by the brain of weakly electric fish, Apteronotus albifrons, with particular attention paid to how the dynamic constraints of the fish affect this transformation. The researchers hypothesize that neural structures supporting this transformation are simplified by sensory and motor capabilities that are well tuned to the dynamics of the task. The team's research objectives are to 1) reconstruct muscle activations occurring during prey-capture behavior; 2) reconstruct the sensory information about the prey reaching the brain during this behavior; and 3) develop a computational framework for transforming the reconstructed brain input into the estimated muscle activation signals. Experiments on real fish and on a virtual fish with realistic sensing and mechanics will be combined to test several key hypotheses, including the claim that a trajectory to the prey that minimizes the animal's effort will be identical to one that minimizes uncertainty about behaviorally relevant properties of the prey, such as its location. These studies require an ambitious interdisciplinary effort in neurobiology, computational neuroscience, fluid dynamics, and robotics. The research will have broad applicability to understanding the principles of sensorimotor transformations in animals. The group further expects that their work on the fluid dynamics of locomotion will have applications to animal flight and swimming, and the engineering of micro-air and aquatic vehicles. The project will also involve undergraduate students in aspects of the research and will develop a robotic fish installation to inform the public about this type of multidisciplinary research.