A crucial problem in motor neuroscience is to understand how muscles are activated to produce normal or pathological motor behavior. However, our understanding of how individual motor units (the muscle fibers activated by a single motor neuron) pattern their spiking to precisely control behavior is poor due to the limitations of current electromyographic (EMG) methods, which include fine wires inserted into muscles and, more recently, cutaneous EMG arrays used to record individual motor units, particularly in human subjects. However, both wire-based and cutaneous arrays face crucial limitations. Notably, they cannot record the very small and/or deep muscles that mediate fine motor control, due to tissue damage induced by wire insertion and by surface array's inability to monitor signals from deeper muscles. Furthermore, surface arrays have limited use outside of tightly-controlled (e.g. isometric force) tasks in humans, are not appropriate for long-term use in natural behaviors or in rehabilitative contexts, and perform poorly in animal models. Finally, wire electrodes typically provide only bulk multiunit recording (rather than single-unit spike trains). In this cross-disciplinary proposal between an electrophysiologist (Dr. Sober) and an electrical engineer (Dr. Bakir), we propose to fill this gap by creating a new generation of micro-scale, high channel-count EMG arrays to record massively parallel single-unit data across many muscles during natural behaviors.