In the traditional view, the nervous system performs the computational "heavy lifting" in an organism. This view neglects, however, the critical role of biomaterials, passive mechanical physics, and other pre-neuronal or non-neuronal systems. Given that neurons consume forty times more energy per unit mass than structural materials such as bone, it is better, when possible, that biological systems employ relatively inexpensive structural materials rather than relying on more costly neuronal control. In this "bone-brain continuum" view, animal intelligence and behavioral control systems can only be understood using integrative modeling approaches that expose the computational roles of both neural and non-neural substrates and their close coupling in behavioral output. To this end, a group of researchers from Northwestern University, The Johns Hopkins University, and Harvard University propose to create a unique high fidelity neuromechanical model of a vertebrate. The effort is divided between the development of a general purpose computational tool set for neuromechanics research and application of these tools to an ideally suited model system, weakly electric knifefish.
The research will lead to breakthroughs in fundamental problems of how nervous systems work together with biomechanics to generate adaptive behavior. The final goal of the research is to construct an integrated neuromechanical model of a unique biological system - weakly electric knifefish - that places biomechanics and neural control on equal footing. Prior such neuromechanical models have used highly simplified models of mechanics and highly abstracted neuronal control approaches. This research advances the state of the art by incorporating high-fidelity mechanics with neuronal mechanisms motivated by direct neurophysiological evidence. Ultimately, this computational approach will help elucidate how animals distribute computations between brain and bone.
