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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.
“The Advance”8 pages
UNCLASSIFIED/ ,«F&lil: 8ffllltllt t!l91!! e11e I directly in the cortex or cerebellum can take the fullest advantage of neural training and processing capability. Two research paths currently showing the most promise are optical interfaces and ex-vivo preparation of electrode arrays encased in engineered neural tissue. New electrode designs that could establish two-way communication with single neurons are also promising. The cerebellar connection point is extremely interesting to perhaps provide a connection that would effectively make the external device a part of the body as far as the brain is concerned. The current state of the art using metal electrode arrays for proximal stimulation and sensing does not appear to be advancing toward long duration viability as a commercial BMI without some unforeseen advance in two-way communication. Peripheral connections have some theoretical promise, but an example of such an implant in a human trial did not shown terrific success over several weeks it functioned. Implantation of cortical arrays in human trials has not been conducted on a wide scale for durations longer than a few weeks, and two-way electrical communication has yet to be realistically demonstrated, limiting the possible commercial application portfolio for this technology. Many possible research directions for disruptive advances have been presented. These areas and the physiological-physical interconnection field of study as a whole should be monitored regularly for advances, as well as the ancillary technology areas of brain plasticity, neural signal decoding, and general basic neuroscience. Advances in any and all of these areas could alter the future landscape of commercial applications and dramatically alter our understanding of what is possible through thought-directed control. 1 Alberts B. Molecular biology of the cell. 4th ed. New York: Garland Science; 2002. 2 Polich J. Updating P300: an integrative theory of P3a and P3b. Clin Neurophysiol 2007 Oct;118(10):2128-48. 3 Ravden D, Polich J. On P300 measurement stability: hab1tuat1on, intra-trial block variation, and ultradian rhythms. Biol Psychol 1999 Oct;51(1):59-76. 4 Sutton S, Braren M, Zubin J, John ER. Evoked-potential correlates of stimulus uncertainty. Science 1965 Nov 26; 150(700): 1187-8. 5 Sawaki R, Katayama J. Top-down directed attention to stimulus features and attentional allocation to bottom-up deviations. J Vis 2008;8(15):4 1-8. "Huettel SA, Song AW, McCarthy G. Functional magnetic resonance imaging. Sunderland, Mass.: Sinauer Associates, Publishers; 2004. 7 Kandel ER, Schwartz JH, Jessell TM. Principles of neural science. 4th ed. New York: McGraw-Hill, Health Professions Division; 2000. 8 Ogawa S, Tank OW, Menon R, Ellermann JM, Kim SG, Merkle H, et al. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci US A 1992 Jul 1 ;89( 13): 5951-5. 9 Emerging Cognitive Neuroscience and Related Technologies. Washington DC: National Research Council of the National Academies; 2008. 10 Miller MB, Van Horn JD, Wolford GL, Handy TC, Valsangkar-Smyth M, Inati S, et al. Extensive individual differences in brain activations associated with episodic retrieval are reliable over time. J Cogn Neurosci 2002 Nov 15; 14(8): 1200-14. " Hatsopoulos NG, Donoghue JP. The Science of Neural Interface Systems. Annu Rev Neurosci 2009 Mar 24. 12 Fitts PM. The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol 1954 Jun;47(6):381-91. 13 Drury CG, Hoffmann ER. A model for movement time on data-entry keyboards. Ergonomics 1992;35(2):129 - 47. H Choi C, Micera S, Carpaneto J, Kim J. Development and quantitative performance evaluation of a noninvasive EMG computer interface. IEEE Trans Bio med Eng 2009 Jan; 56( 1): 188 ·91. 15 Soukoreff RW, MacKenzie IS. Theoretical upper and lower bounds on typing speed using a stylus and soft keyboard. Behaviour & Information Technology 1995;14(6):370-9. 28 UNCLASSIFIED/ ,'F811. 8FFll!lit.l! 1!191!! 8HL I
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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.