Toward an Animal Model of Freely Moving Humans

Stanford University, Stanford CA

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Abstract

Our overarching goal is to establish an animal model of freely moving humans. We choose to do so in order to directly measure the context-dependency of motor cortical activity and, ultimately, other activity reliant upon free movement such as social interaction among animals. Achieving this major technological challenge requires a complete system that includes (Specific Aim 1) wireless transmission of neural data from electrode arrays chronically implanted in monkeys, (Specific Aim 2) computer-vision algorithms to automatically extract body and limb orientation during free movement, and (Specific Aim 3) new mathematical and computational models to represent and extract information from high-dimensional neural and behavioral activity. This technology will enable an animal model of freely moving humans that will advance the development of cortical neural prostheses by providing models of the context-dependant nature of motor cortical control. Unlike traditional laboratory environments used to study animal movement, human amputees and tetraplegics operate in a variety of contexts that involve their movement in the world. Understanding the motor control of complex movement in these natural settings is absolutely critical for future advances in cortically- controlled prostheses. Given our overarching goal, our hypothesis is that motor cortical activity (e.g., directional tuning curves, absolute firing rates, correlations among units, etc.) will be different in important ways when rhesus monkeys perform the same reaching arm movements in an un-constrained context (e.g., not sitting quietly, not head restrained, not in dark and quiet room, etc.) as in a traditional, highly constrained context. Our three Specific Aims will put in place the electronic, computational and mathematical technology necessary to address this hypothesis, and also to make such studies of free behavior in rhesus monkeys possible. The innovative integration of neural engineering, neuroscience, computer vision, mathematics and neural modeling will provide new tools to enable the unprecedented study of motor control during natural, unconstrained behavior.