Adaptive visual selection in feature space.

Visual perception relies on efficient selection of task-relevant information for prioritized processing. A prevalent mode of selection is feature-based selection, and a key question in the literature is the shape of the selection profile-that is, when a feature is selected, what is the landscape of priority for all features in that dimension? Past studies have reported conflicting findings with both monotonic and nonmonotonic profiles. We hypothesized that feature selection can be adaptively adjusted based on stimulus factors (feature competition) and task demands (selection precision). In three experiments, we manipulated these contextual factors in a central task while measuring selection profile in a peripheral task. We found a nonmonotonic, surround suppression, profile when feature competition and selection precision was high, but observed a monotonic profile when these factors were low. Furthermore, manipulation of selection precision alone can shape selection profile independent of feature competition. These findings reconcile previous conflicting results and importantly, demonstrate that feature selection is highly adaptive, allowing flexible allocation of processing resources to ensure efficient extraction of visual information.

The profile of attentional modulation to visual features.

Although it is well established that feature-based attention (FBA) can enhance an attended feature, how it modulates unattended features remains less clear. Previous studies have generally supported either a graded profile as predicted by the feature-similarity gain model or a nonmonotonic profile predicted by the surround suppression model. To reconcile these different views, we systematically measured the attentional profile in three basic feature dimensions-orientation, motion direction, and spatial frequency. In three experiments, we instructed participants to detect a coherent feature signal against noise under attentional or neutral condition. Our results support a nonmonotonic hybrid model of attentional modulation consisting of feature-similarity gain and surround suppression for orientation and motion direction. For spatial frequency, we also found a similar nonmonotonic profile for higher frequencies than the attended frequency, but a lack of attentional modulation for lower frequencies than the attended frequency. The current findings can reconcile the discrepancies in the literature and suggest the hybrid model as a new framework for attentional modulation in feature space. In addition, a computational model incorporating known properties of spatial frequency channels and attentional modulations at the neural level reproduced the asymmetric attentional modulation, thus revealing a connection between surround suppression and the basic neural architecture of an early visual system.

Attention induces surround suppression in visual working memory.

Controversy currently exists regarding whether visual working memory (VWM) maintains sensory or non-sensory representations. Here, we tested the nature of VWM representations by leveraging a perceptual surround suppression effect when an item is attended. Participants performed a delayed-estimation task in which they memorized an array of six colors. A cue indicated which location was most likely probed. In separate experiments, we manipulated external attention (via a precue) or internal attention (via a retrocue). Both types of attention elicited a surround suppression effect, such that memory performance showed a Mexican-hat profile as a function of cue-probe offsets. Given the sensory origin of the surround suppression effect, our results thus provide compelling evidence that VWM maintenance relies on sensory mechanisms.

Attention to colors induces surround suppression at category boundaries.

We investigated how attention to a visual feature modulates representations of other features. The feature-similarity gain model predicts a graded modulation, whereas an alternative model asserts an inhibitory surround in feature space. Although evidence for both types of modulations can be found, a consensus has not emerged in the literature. Here, we aimed to reconcile these different views by systematically measuring how attention modulates color perception. Based on previous literature, we also predicted that color categories would impact attentional modulation. Our results showed that both surround suppression and feature-similarity gain modulate perception of colors but they operate on different similarity scales. Furthermore, the region of the suppressive surround coincided with the color category boundary, suggesting a categorical sharpening effect. We implemented a neural population coding model to explain the observed behavioral effects, which revealed a hitherto unknown connection between neural tuning shift and surround suppression.