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Brain-machine interfaces (BMIs) have the potential to help people with a wide range of clinical disorders. For example, researchers have demonstrated human neuroprosthetic control of computer cursors [1, 2, 3], robotic limbs [4, 5], and speech synthesizers [6] using no more than 256 electrodes. While these successes suggest that high fidelity information transfer between brains and machines is possible, development of BMI has been critically limited by the inability to record from large numbers of neurons. Noninvasive approaches can record the average of millions of neurons through the skull, but this signal is distorted and nonspecific [7, 8]. Invasive electrodes placed on the surface of the cortex can record useful signals, but they are limited in that they average the activity of thousands of neurons and cannot record signals deep in the brain [9]. Most BMI’s have used invasive techniques because the most precise readout of neural repre- sentations requires recording single action potentials from neurons in distributed, functionally-linked ensembles [10].

Microelectrodes are the gold-standard technology for recording action potentials, but there has not been a clinically- translatable microelectrode technology for large-scale recordings [11]. This would require a system with material prop- erties that provide high biocompatibility, safety, and longevity. Moreover, this device would also need a practical surgi- cal approach and high-density, low-power electronics to ultimately facilitate fully-implanted wireless operation.

Most devices for long-term neural recording are arrays of electrodes made from rigid metals or semiconductors [12, 13, 14, 15, 16, 17, 18]. While rigid metal arrays facilitate penetrating the brain, the size, Young’s modulus and bending stiff- ness mismatches between stiff probes and brain tissue can drive immune responses that limit the function and longevity of these devices [19, 11]. Furthermore, the fixed geometry of these arrays constrains the populations of neurons that can be accessed, especially due to the presence of vasculature.

An alternative approach is to use thin, flexible multi-electrode polymer probes [20, 21]. The smaller size and increased flexibility of these probes should offer greater biocompatibility. However, a drawback of this approach is that thin poly- mer probes are not stiff enough to directly insert into the brain; their insertion must be facilitated by stiffeners [22, 21], injection [23, 24] or other approaches [25], all of which are quite slow [26, 27]. To satisfy the functional requirements for a high-bandwidth BMI, while taking advantage of the properties of thin-film devices, we developed a robotic approach,

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