Rapid image analysis using neural signals

The problem of extracting information from large collections of imagery is a challenge with few good solutions. Computers typically cannot interpret imagery as effectively as humans can, and manual analysis tools are slow. The research reported here explores the feasibility of speeding up manual image analysis by tapping into split second perceptual judgments using electroencephalograph sensors. Experimental results show that a combination of neurophysiological signals and overt physical responses-detected while a user views imagery in high speed bursts of approximately 10 images per second-provide a basis for detecting targets within large image sets. Results show an approximately six-fold, statistically significant, reduction in the time required to detect targets at high accuracy levels compared to conventional broad-area image analysis.