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This Defense Intelligence Reference Document was produced by the Defense Intelligence Agency's Defense Warning Office under the Advanced Aerospace Weapon System Applications program and dated 23 March 2010. It surveys noninvasive and invasive brain-machine interface technologies, including EEG, MEG, fMRI, NIRS and implanted electrode arrays, that could control external devices without limb-operated interfaces. It concludes that noninvasive electrical monitoring is the most promising near-term approach. For the long term it favors invasive single-neuron cortical connections.
From the source: Release of 2026-09-18 Incident: 3/23/10, Las Vegas, Nevada. Released with redactions. This document is a Defense Intelligence Reference Document (DIRD), a technical reference format used by the Defense Intelligence Agency (DIA) to capture baseline knowledge on a specific topic for later analytic use. DIRDs are best understood as reference and synthesis products rather than as original research. It is one of 38 DIRDs produced under the Advanced Aerospace Weapon System Applications Program (AAWSAP) between 2009 and 2011. Because AAWSAP’s scope permitted a broad range of supporting topics, not every DIRD in the series directly concerns aerospace systems or future threat assessment. The following summary reflects the DIRD’s scope and framing at the time of writing and should not be read as implying current validation of the concepts discussed. This DIRD surveys brain-machine interface technologies intended to allow users to control external devices without conventional manual controls, and it evaluates both noninvasive and invasive approaches for turning neural or related physiological signals into usable commands. The report reviews the underlying neural signals, distinguishes between open- and closed-loop control systems, and examines technologies including scalp-based electrical recording, magnetic and imaging-based methods, and implanted cortical interfaces, with particular attention to bandwidth, response time, signal quality, and practical usability. It concludes that, in the near term, the most practical systems are likely to be noninvasive electrical approaches that draw heavily on muscle and neural signals, while longer-term high-bandwidth control would likely require more advanced invasive interfaces capable of robust two-way communication with individual neurons. The document presents thought-based control of external devices as a research field with plausible assistive and specialized applications, while emphasizing that naturalistic, high-performance control remained constrained by major technical and physiological limits.
UNCLASSIFIED/ /P91t 9Ffl@IAL YSIE 8HLY on the cortex to implant cortical arrays is determined from previous experiments in fMRI (References 39, 40). In this way, a map is constructed correlating electrical neural activity with muscle movement. The goal of this exercise is to develop an algorithm that will predict which muscles move based on reading the neural activity alone. The reading of the neural activity for eye movement can then be used to move a device such as a camera lens. There are two main models of fine motor control, one where the cortical motor areas perform all of the control functions and receive all sensory feedback, and a second where the cortical areas direct the function and receive interpreted feedback through sub-cortical or even peripheral networks. For open-loop invasive BMI applications, this is an academic question since peripheral interfaces would receive and send the same signals in both models, and cortical interfaces would blindly adapt external decoding algorithms based on the signals present regardless of model. There have been numerous demonstrations of nonhuman primates controlling robots or graphical cursors in real-time through signals collected from cortical areas that employ open loop experimentation (References 41, 42). Kim, et al. conducted experiments where monkeys are trained on tasks prior to implantation, and then the tasks are repeated multiple times while muscle action and cortical activity are monitored (Reference 42). In these trials, shoulder and elbow torque were measured while the arm itself was constrained in an exoskeleton such that the hand would only move in a plane axial to the monkey's torso. A visual cursor was introduced and projected on a screen above the monkeys hand to follow the 2-D motion from the center starting point to the various task targets, which are also projected on the screen. The shoulder and elbow position recorded the state of flexation of 6 sets of muscle groups, collectively called the musculoskeletal arm model (MAM). Relating the spiking activity from implanted arrays to even this simplified 2-D MAM motion proved quite complex, and no fit correlating the observed movements and neural activity could be obtained with a linear model when kinematic impedance was considered. 15 Even considering the six inputs, the 2-D problem is essentially a computer cursor control and therefore a relatively simple device, fully specified by a Cartesian coordinate system. The ultimate goal of these control systems is to manipulate something much more complex, like an arm, which may have many more degrees of freedom organized in a completely different coordinate system. For these tests a more elaborate "tracking system" may be utilized in teaching a primate to feed itself16 using a directly observed cortically controlled robotic arm. Open-loop control systems have an inherent drawback in cases where cortical activity controls movement directly via an adaptive algorithm. Training the algorithm is the critical part of interface development. The adaptive algorithms use an iterative process to create a brain-to-cursor motion decoding scheme based on how the neurons fire when different targets are presented and therefore rely on previous normal feedback training - the brain knows how to move an arm because it has been moving an arm for most of its life. 15 Impedance to motion is essential for realistic operation of artificial limbs. 16 Food in this experiment is used as a reward. UNCLASSIFIED/ /F8R 8FFI&I.t.k Y&liii 8,.kY 12
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Official release, from the pursue 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.