Abstract
Reverse Hierarchy Theory proposes several dramatic propositions regarding conscious visual perception. These include the suggestion that, while the visual system receives scene details and builds from them representations of the objects, layout, and structure of the scene, nevertheless, the first conscious percept is that of the gist of the scene – the result of implicit bottom-up processing. Only later does conscious perception attain scene details by return to lower cortical area representations. Recent studies at our lab analyzed phenomena whereby participants receive and perceive the gist of the scene before and without need for consciously knowing the details from which the gist is constructed. One striking conclusion is that “pop-out” is an early high-level effect, and is therefore not restricted to basic element features. Thus, faces pop-out from heterogeneous objects, and participants are unaware of rejected objects. Our recent studies of ensemble statistics perception find that computing set mean does not require knowledge of its individuals. This mathematically-improbable computation is both useful and natural for neural networks. I shall discuss just how and why set means are computed without need for explicit representation of individuals. Interestingly, our studies of neglect patients find that their deficit is in terms of tasks requiring focused attention to local details, and not for those requiring only global perception. Neglect patients are quite good at pop-out detection and include left-side elements in ensemble perception.