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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/ /POI': OPFIClltt U.!I! Oflt I • Developing complex neural networks on top of chips prior to implant. • Development of chronic electrode materials such as biopolymers that may be suitable for implant without an ex-vivo grown sheath. • Creating a biological to biological interface upon implant. This technol ogy does still rely on proximal sensing and stimulation of action potentials, but the neural tissue at the biological to physical interface is engineered rather than native, thus providing the opportunity to develop an effective bridging network to seamlessly integrate between the two systems. Development of such chronic implant capability could make feasible the nondestructive addition of cerebellar pathways for control activity that incorporates the huge potential of brain plasticity without adding significant cognitive burden on the prefrontal cortex. This would effectively turn the controlled device into part of the body as far as the brain is concerned. IMPLANTABLE CHIPS, LADDERS AND ARRAYS Research utilizing ECoG or neocortica l ladder array technology is the state of the art in neural communication. However, stimulating nerves or peripheral pathways in this matter without damage to the receiving cells has proven difficult. Even in cochlear arrays, normal functioning of the surrounding tissue is lost and only a fraction of the quality of natural stimulation is available. Locating single neurons has also been challenging, though new electrode designs are being developed. These devices will continue to be useful for research applications such as better understanding of network structure and network function in conjunction with fMRI. BMI application will continue in the foreseeable future to be lim ited to instances where closed-loop with visual or other traditional sensory feedback is sufficient. Until new electrode designs develop a robust method of two-way communication with single neurons, they will not be the dominant BMI technology for use in normal, healthy individua ls. Conclusions The gamut of modern technologies that connect neural systems to physical systems has been surveyed, with attention to the underlying physiological signals. Many examples have been presented of studies illustrating the different research paths under way. Two of these technologies show the most promise of near term and long term successful high -ba ndwidth integration of brain and external systems. In the near term, noninvasive electrical sensors that primarily rely on EMG signals, but also include those weaker signals directly from neuronal firing, are expected to dominate real-world applications. The decoding of these signals from just a handful of dry sensors can produce a large combination of on-off and variable strength control commands that should surpass the information capability of traditional electro mechanical interfaces in the next 5 years. This technology is limited, however, by the number of available EMG sites and the required coherent firing of very large numbers of neurons. To surpass these limitations, technologies capable of connections to individual neurons on a large scale will be necessary. In the far term, an invasive approach to establish high-bandwidth duplex communication networks, 5-20 bits/second, using interfaces with single neurons UNCLASSIFIED/ /P91l err1e1Jct U.!I! or•t I 27
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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.