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This Defense Intelligence Reference Document from the Defense Intelligence Agency, dated 23 March 2010, was produced under the Advanced Aerospace Weapon System Applications (AAWSA) Program. It surveys invasive and noninvasive brain-machine interface technologies for controlling external devices without limb-operated interfaces. The technologies covered include EEG, MEG, fMRI, NIRS, and implanted electrode arrays. It concludes that noninvasive electrical monitoring is the most promising near-term approach. In the long term, it favors invasive single-neuron cortical connections that use optical stimulation or chip-based arrays.
UNCLASSIFIED/;'P81il 8PPll!ltllt ~81!! 8HLV of a spiking train to trigger a switch, or as complex as decoding signal from noise utilizing a 300-channel EEG cap. ~-------------------------, : Additional sensory : I ____I ____________________ I Input interface Brain l Output Output signal interface processing Components of a Closed-loop BMI Control System Input signal processing External Device Figure 2. The General Layout of a Closed-Loop Control Interlace. The input and output interfaces can attach to read or affect activity of cerebral or peripheral neurons. Additional sensory feedback channels such as visual displays, audio tones, or haptic feedback are possible. In some system designs, especially noninvasive types, these sensory feedback channels replace stimulation inputs. In an open-loop interface, either the input or output signal paths are absent. One consideration in developing a BMI control system is the utility of the application: does it make sense to directly tie these controls to neural activity? The bulk of research in direct neural interfaces is toward the goal of restoring mechanical capabilities to those individuals who have either lost limbs or lost control of limbs through central nervous system injury or disease. In these cases it is of obvious utility to produce a system that moves a cursor across screen to select an item over the course of several seconds; however, for a healthy individual, it is far more practical to execute a hand movement to control a mechanical device4 to achieve the same goal. An exception to consider is the case of applications where the subject's hands or feet are already occupied with other essential tasks in the overall application. A research question for any such application is whether training a subject to utilize a BMI is advantageous over a more complex mechanical interface. Furthermore, whether training on a new BMI affects learning/retaining proficiency with similar BMis is an additional concern. Moreover, for any BMI, one can quantitatively describe the information transfer in controlling the magnitude of human motor action (Reference 12). Since the advent of digital control of external devices, this information is expressed in equivalent bits per 4 Mechanical device as used here represents any limb-operated interface, such as a mouse or touchscreen. 5 UNCLASSIFIED/ ;CFQA: QFFIGIPk IP&'i Qllk¥
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Report, from the dia collection. The PDF is mirrored here; the original link is above. 36 pages are in the text index: search them above, or from the library's search.