We report on a novel technology for microfabricating 3D origami-styled micro electromechanical systems (MEMS) structures with glassy carbon (GC) features and a supporting polymer substrate. GC MEMS devices that open to form 3D microstructures are microfabricated from GC patterns that are made through pyrolysis of polymer precursors on high-temperature resisting substrates like silicon or quartz and then transferring the patterned devices to a flexible substrate like polyimide followed by deposition of an insulation layer. The devices on flexible substrate are then folded into 3D form in an origami-fashion. These 3D MEMS devices have tunable mechanical properties that are achieved by selectively varying the thickness of the polymeric substrate and insulation layers at any desired location. This technology opens new possibilities by enabling microfabrication of a variety of 3D GC MEMS structures suited to applications ranging from biochemical sensing to implantable microelectrode arrays. As a demonstration of the technology, a neural signal recording microelectrode array platform that integrates both surface (cortical) and depth (intracortical) GC microelectrodes onto a single flexible thin-film device is introduced. When the device is unfurled, a pre-shaped shank of polyimide automatically comes

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Somatosensory brain-machine-interfaces (BMIs) can create naturalistic sensations by modulating activity of neural populations in the brain. By utilizing different spatial or temporal patterns of intra-cortical micro-stimulation (ICMS) in primary sensory cortex (S1), human patients suffering somatosensory loss can experience both cutaneous and proprioceptive sensory feedback. As evidenced by motor deficits in deafferented patients, rapid somatosensory feedback is critical for dexterous motor ability, in part because visual feedback is much slower than naturally occurring somatosensory input. However, somatosensory BMI studies typically report significantly longer cognitive processing latencies for cortical electrical stimulation than for naturally occurring somatosensations or visual sensations. In this study, we show that multi-channel electrical stimulation patterns elicit naturalistic somatosensory percepts in a human tetraplegic participant. Crucially, somatosensations evoked by multi-channel ICMS are cognitively processed at comparable latencies to naturally evoked sensations and significantly faster than visual sensations, as measured via a simple reaction time test. Further investigation demonstrated multi-channel stimulation could significantly reduce minimum amplitude detection thresholds and such reductions in charge density resulted in more frequent natural sensation descriptors reported by the human participant. Multi-channel ICMS patterns also evoked percepts with highly stable somatotopic locations. While some single-channel ICMS patterns evoked sensations 20-80% of the time, most multi-channel patterns could evoke sensations with 100% repeatability, an important step in demonstrating BCI device reliability. These improvements are all significant advances towards state-of-the-art sensory BMIs. The addition of such low-latency artificial sensory feedback to motor BMIs is expected to improve movement accuracy and increase embodiment for human users.