We describe our work using linear discrimination of multi-channel electroencephalography for single-trial detection of neural signatures of visual recognition events. We demonstrate the approach as a methodology for relating neural variability to response variability, describing studies for response accuracy and response latency during visual target detection. We then show how the approach can be utilized to construct a novel type of brain-computer interface, which we term cortically-coupled computer vision. In this application, a large database of images is triaged using the detected neural signatures. We show how ‘cortical triaging’ improves image search over a strictly behavioral response.