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Defense Intelligence Reference Document Technological Approaches To Controlling

Defense Intelligence Agency · 36 pages · text from the file's own layer

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.

  • p. 5 UNCLASSIFIED/)' Pett :SPPll!ltllt '11815 .,.LY Technological Approaches to Controlling External Devices in the Absence of…
  • p. 8 …Neurons require some time to reset between firings, nominally the duration of the pulse for that…
  • p. 10 UNCLASSIFIED/ ,erg A gffllil.t.L '1181!! 8HLY The brain activity mentioned above is a complex…
  • p. 13 …The response time to execute a command using these systems is measured in seconds. The results…
  • p. 14 …application, the fact that 100 IT is about 100 million times smaller than the Earth's…
  • p. 15 …In current MRis, these gradient fields are produced with electromagnets, and the series of time-dependent…
  • p. 18 …prior to implantation, and then the tasks are repeated multiple times while muscle action and cortical…
  • p. 19 …the movement control algorithm is similar to a population vector in that movement at each time…
  • p. 20 UNCLASSIFIED/,'P81il 8PPll!ltllt ~81!! 8HLV Japan in real time. Using visual feedback to the monkey…
  • p. 21 …employed to allow for real-time bidirectional interface with the nervous system. After several modifications, Fetz…
  • p. 22 …understand the brain, its regions of activity and how those area correlate to real time stimulation…
  • p. 25 …FOV=60x60mrn 7 • Experiment time=512 s. (B) (Top) Microelectrode array used in the study. (Bottom…
  • p. 28 …Movement times to target were on the order of 1-2 seconds with up to 75…
  • p. 29 …This trial lasted 3 months before the physical connection between the nerve and the microarray deteriorated…
  • p. 31 …Also beneficial to reaction time is the combined EMG EEG devices mentioned above since the pathways…
  • p. 32 …Proof of principle studies in this technology could emerge at any time, and given the demonstrated…
  • p. 34 …time. J Cogn Neurosci 2002 Nov 15; 14(8): 1200-14. " Hatsopoulos NG, Donoghue JP. The…
  • p. 36 …Targeted muscle reinnervation for real- time myoelectric control of multifunction artificial arms. JAMA 2009 Feb 11…
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16 Cummings ML, Guerla1n S. Developing operator capacity estimates for supervisory control of autonomous
vehicles. Hum Factors 2007 Feb;49(1):1-15.
11 Enzinger C, Ropele S, Fazekas F, Loitfelder M, Gorani F, Seifert T, et al. Brain motor system function in a patient
with complete spinal cord injury following extensive brain-computer interface training. Exp Brain Res 2008
Sep; 190(2) :215-23.
18 Berger H. Uber das elektrenkephalogramm des menschen. Archiv fur Psychiatrie und Nervenkrankheiten
1929;87( 1): 527-80.
19 Davis P. Effects of acoustic stimuli on the waking human brain. Journal of Neurophysiology 1939;2:494-Q.
20 Blankertz B, Dornhege G, Krauledat M, Muller KR, Curio G. The non-invasive Berlin Brain-Computer Interface:
fast acquisition of effective performance in untrained subjects. Neuroimage 2007 Aug 15 ;37(2): 539-50.
21 Kubler A, Kotchoubey B, Kaiser J, Wolpaw JR, Birbaumer N. Brain-computer communication: unlocking the
locked in. Psychol Bull 2001 May;127(3):358-75.
22 Bai 0, Lin P, Vorbach S, Floeter MK, Hattori N, Hallett M. A high performance sensorimotor beta rhythm-based
brain-computer interface associated with human natural motor behavior. J Neural Eng 2008 Mar;5(1):24-35.
23 Iversen I, Ghanayim N, Kubler A, Neumann N, Birbaumer N, Kaiser J. Conditional associative learning examined
in a paralyzed patient with amyotrophic lateral sclerosis using brain-computer interface technology. Behav Brain
Funct 2008;4:53.
24 Iversen IH, Ghanayim N, Kubler A, Neumann N, Birbaumer N, Kaiser J. A brain-computer interface tool to assess
cognitive functions in completely paralyzed patients with amyotrophic lateral sclerosis. Clin Neurophysiol 2008
Oct; 119(10):2214-23.
25 Sellers EW, Kubler A, Donchin E. Brain-computer interface research at the University of South Florida Cognitive
Psychophysiology Laboratory: the P300 Speller. IEEE Trans Neural Syst Rehabil Eng 2006 Jun;14(2):221-4.
26 Greene K. Brain sensor for market research: A startup claims to read people's minds while they view ads. 2007
[May 12, 2009]; Available from: http://www.technologyreview.com/B1ztech/19833!7a-f.
27 Greene K. Connecting Your Brain to the Game Using an EEG cap, a startup hopes to change the way people
interact with video games. 2007 [May 12, 2009]; Available from:
http : //www. tech no Iogy rev Iew. com/ BI ztech/ 182 7 6/?a - f.
28 Popescu F, Fazli S, Badower Y, Blankertz B, Muller KR. Single trial classification of motor imagination using 6 dry
EEG electrodes. PLoS ONE 2007;2(7):e637.
29 van Gerven M, Jensen O. Attention modulations of posterior alpha as a control signal for two-dimensional brain-
computer interfaces. J Neurosci Methods 2009 Apr 30;179(1):78-84.
30 Mellinger J, Schalk G, Braun C, Preissl H, Rosenstiel W, Birbaumer N, et al. An MEG-based brain-computer
interface (BCI). Neuroimage 2007 Jul 1;36(3):581-93.
31 Ohta H, Matsui T, Uchikawa Y. Whole-head SQUID system in a superconducting magnetic shield. Neural Clin
Neurophysiol 2004;2004:58.
32 Kraus RH, Jr., Volegov P, Matlachov A, Espy M. Toward direct neural current imaging by resonant mechanisms at
ultra-low field. Neuroimage 2008 Jan 1;39(1):310-7.
33 McDermott R, Lee S, ten Haken B, Trabesinger AH, Pines A, Clarke J. Microtesla MRI with a superconducting
quantum interference device. Proc Natl Acad Sci US A 2004 May 25;101(21):7857-61.
34 Chen Y, Intes X, Tailor DR, Regatte RR, Ma H, Ntziachristos V, et al. Probing rat brain oxygenation with near-
infrared spectroscopy (NIRS) and magnetic resonance imaging (MRI). Adv Exp Med Biol 2003;510:199-204.
3' Luu S, Chau T. Decoding subjective preference from single-trial near-infrared spectroscopy signals. J Neural Eng
2009 Feb;6(1):016003.
36 Loeb GE. Cochlear prosthetics. Annu Rev Neurosci 1990;13:357-71.
37 Bailey L. New cochlear implant could improve hearing. University of Michigan News Service [serial on the
Internet]. 2006: Available from: http://www. umich .edu/news/index. html?Releases/2006/Feb06/r020606a.
38 Cheng YC, Brown RW, Chung YC, Duerk JL, FuJita H, Lewin JS, et al. Calculated RF electric field and temperature
distributions in RF thermal ablation: comparison with gel experiments and liver imaging. J Magn Reson Imaging
1998 Jan-Feb;8(1):70-6.
39 Kamitani Y, Tong F. Decoding the visual and subjective contents of the human brain. Nat Neurosci 2005
May;8(5) :679-85.
4° Kamitani Y, Tong F. Decoding seen and attended motion directions from activity in the human visual cortex. Curr
Biol 2006 Jun 6;16(11):1096-102.
41 Fagg AH, Hatsopoulos NG, de Lafuente V, Maxon KA, Nemati S, Rebesco JM, et al. Biomimetic brain machine
interfaces for the control of movement. J Neurosci 2007 Oct 31;27(44):11842-6.
42 Kim HK, Carmena JM, Biggs SJ, Hanson TL, Nicolelis MA, Srinivasan MA. The muscle activation method: an
approach to impedance control of brain-machine interfaces through a musculoskeletal model of the arm. IEEE
Trans Biomed Eng 2007 Aug;54(8):1520-9.
13 Kawata M. Brain controlled robots. HFSP J 2008 Jun;2(3):136-42.
44 Jackson A, Moritz CT, Mavoori J, Lucas TH, Fetz EE. The Neurochip BCI: towards a neural prosthesis for upper
limb function. IEEE Trans Neural Syst Rehabil Eng 2006 Jun;14(2): 187-90.
4 s Leuthardt EC, Miller KJ, Schalk G, Rao RP, Ojemann JG. Electrocorticography-based brain computer interface--
the Seattle experience. IEEE Trans Neural Syst Rehabil Eng 2006 Jun;14(2):194-8.
46 Diorio C, Mavoori J. Computer electronics meet animal brains. IEEE Computer 2003;36(1):69-75.
47 Parikh H, Marzullo TC, Kipke DR. Lower layers in the motor cortex are more effective targets for penetrating
microelectrodes in cortical prostheses. J Neural Eng 2009 Apr;6(2):026004.
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Report, from the dia collection. The PDF is mirrored here; the original link is under it. 36 pages are in the text index: search them above, or from the library's search.