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Does sensory information reach conscious awareness in a discrete, all-or-nothing manner or a gradual, continuous manner? To answer this question, we examined behavioral performance across four different paradigms that manipulate visual awareness: the attentional blink, backward masking, the Sperling iconic memory paradigm, and retro-cuing. We then asked how well we could account for participants’ ( N = 112 adults) behavior using a signal detection framework that factors in psychophysical scaling to model participants’ responses along a single continuum. We found that this model easily accounted for the data from each of these diverse paradigms. Moreover, we reanalyzed the data from prior studies that had posited a discrete view of perceptual awareness and found that our continuous signal detection model outperformed the models that had been used to support an all-or-nothing view of consciousness. This set of data is consistent with the idea that conscious awareness occurs along a graded continuum. 

Feature-based attention is known to enhance visual processing globally across the visual field, even at task-irrelevant locations. Here, we asked whether attention to object categories, in particular faces, shows similar location-independent tuning. Using EEG, we measured the face-selective N170 component of the EEG signal to examine neural responses to faces at task-irrelevant locations while participants attended to faces at another task-relevant location. Across two experiments, we found that visual processing of faces was amplified at task-irrelevant locations when participants attended to faces relative to when participants attended to either buildings or scrambled face parts. The fact that we see this enhancement with the N170 suggests that these attentional effects occur at the earliest stage of face processing. Two additional behavioral experiments showed that it is easier to attend to the same object category across the visual field relative to two distinct categories, consistent with object-based attention spreading globally. Together, these results suggest that attention to high-level object categories shows similar spatially global effects on visual processing as attention to simple, individual, low-level features. 

The algorithms in this paper (when combined with our FOCS’16 paper) allow one to, in almost linear time, compute a whole bunch of things about random walks in directed graphs. For example, one can compute the stationary distribution, hitting the time between a pair of vertices, commute times between all vertices, escape probabilities, approximations of the mixing time, and more.