Main Goals

For the past few years, we and others have proposed that a new generation of tools can be developed in the next few decades in which direct brain-machine interfaces (BMIs) will be used to allow subjects to interact seamlessly with a variety of actuators and sensory devices through the expression of their voluntary brain activity. In fact, recent animal research on BMIs has supported the contention that we are at the brink of a technological revolution, where artificial devices may be "integrated" in the multiple sensory, motor, and cognitive representations that exist in the primate brain. Such a demonstration would lead to the introduction of a new generation of actuators/sensors that can be manipulated and controlled through direct brain processes in virtually the same way that we see, walk, or grab an object.

At the core of this new technology is our growing ability to use electrophysiological methods to extract information about intentional brain processes (e.g., moving an arm) from the raw electrical activity of large populations of single neurons, and then translate these neural signals into models that control external devices. Moreover, by providing ways to deliver sensory (e.g., visual, tactile, auditory, etc.) feedback from these devices to the brain, it would be possible to establish a reciprocal (and more biologically plausible) interaction between large neural circuits and machines and hence fulfill the requirements for artificial actuators of significantly augmenting human motor performance to be recognized as simple extensions of our bodies. Using this premise and taking advantage of recent developments in the field of nanotechnology, one can envision the construction of a set of closed-loop control BMIs capable of restoring or augmenting motor performance in macro, micron, and even nano environments (Fig. C.14).

Figure C.14. General architecture of a closed-loop control brain-machine interface: Neuroprosthesis for restoring motor function of damaged brain areas.
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