Paper
19 May 2006 Neurotechnology for intelligence analysts
Amy A. Kruse, Karen C. Boyd, Joshua J. Schulman
Author Affiliations +
Abstract
Geospatial Intelligence Analysts are currently faced with an enormous volume of imagery, only a fraction of which can be processed or reviewed in a timely operational manner. Computer-based target detection efforts have failed to yield the speed, flexibility and accuracy of the human visual system. Rather than focus solely on artificial systems, we hypothesize that the human visual system is still the best target detection apparatus currently in use, and with the addition of neuroscience-based measurement capabilities it can surpass the throughput of the unaided human severalfold. Using electroencephalography (EEG), Thorpe et al1 described a fast signal in the brain associated with the early detection of targets in static imagery using a Rapid Serial Visual Presentation (RSVP) paradigm. This finding suggests that it may be possible to extract target detection signals from complex imagery in real time utilizing non-invasive neurophysiological assessment tools. To transform this phenomenon into a capability for defense applications, the Defense Advanced Research Projects Agency (DARPA) currently is sponsoring an effort titled Neurotechnology for Intelligence Analysts (NIA). The vision of the NIA program is to revolutionize the way that analysts handle intelligence imagery, increasing both the throughput of imagery to the analyst and overall accuracy of the assessments. Successful development of a neurobiologically-based image triage system will enable image analysts to train more effectively and process imagery with greater speed and precision.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Amy A. Kruse, Karen C. Boyd, and Joshua J. Schulman "Neurotechnology for intelligence analysts", Proc. SPIE 6218, Chemical and Biological Sensing VII, 621819 (19 May 2006); https://doi.org/10.1117/12.666054
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Electroencephalography

Target detection

Image analysis

Analytical research

Brain

Neuroscience

Independent component analysis

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