The gist of the abnormal: Above-chance medical decision making in the blink of an eye

Very fast extraction of global structural and statistical regularities allows us to access the “gist”—the basic meaning—of real-world images in as little as 20 ms. Gist processing is central to efficient assessment and orienting in complex environments. This ability is probably based on our extensive experience with the regularities of the natural world. If that is so, would experts develop an ability to extract the gist from the artificial stimuli (e.g., medical images) with which they have extensive visual experience? Anecdotally, experts report some ability to categorize images as normal or abnormal before actually finding an abnormality. We tested the reality of this perception in two expert populations: radiologists and cytologists. Observers viewed brief (250- to 2,000-ms) presentations of medical images. The presence of abnormality was randomized across trials. The task was to rate the abnormality of an image on a 0–100 analog scale and then to attempt to localize that abnormality on a subsequent screen showing only the outline of the image. Both groups of experts had above-chance performance for detecting subtle abnormalities at all stimulus durations (cytologists d' ≈ 1.2 and radiologists d' ≈ 1), whereas the nonexpert control groups did not differ from chance (d' ≈ 0.23, d' ≈ 0.25). Furthermore, the experts’ ability to localize these abnormalities was at chance levels, suggesting that categorization was based on a global signal, and not on fortuitous attention to a localized target. It is possible that this global signal could be exploited to improve clinical performance.