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Objects represent a fundamental selection unit of visual attention. However, at odds with the integrated competition account, our recent study demonstrated that attentional facilitation of constituent features does not spread automatically within an object, but instead depends on the specific task relevance of each feature. Here, we employed a novel experimental design, allowing simultaneous electrophysiological measurements of the allocation of attention to two distinct features (rotation and color) within one object (a square) during both trial-wise and block-wise cued shifts of attention. This was possible through the presentation of a square that evokes two distinct steady-state visual evoked potentials (SSVEPs) for its rotation and its color changes, respectively. Given the continuous oscillatory nature of SSVEPs, we were able to investigate the time course of neural activity in the early visual cortex of the human brain when subjects attended to one of the two features, compared to when the whole object was attended. This approach enabled us to uncover feature-based mechanisms of attention within one object, as well as their interaction with object-based mechanisms. Both behavioral and electrophysiological results indicate a biphasic process composed of an early transient integration of the constituent object features, followed by sustained mechanisms of feature selection with amplification of the to-be-attended feature, followed temporally by suppression of the to-be-ignored feature.

Listeners use multiple acoustic features, to different extents in different circumstances, in perceiving variable speech signals as streams of phonemes. One class of models conceptualizes this phonetic cue weighting as allocating different amounts of attention to different acoustic features (i.e., attentional theories ). These theories posit or assume that similar neural mechanisms underlie phonetic cue weighting and a more general form of auditory feature-based selective attention. We describe multiple attentional theories, consider their relationship to other models of phoneme perception, and review related empirical evidence. In general, attentional theories are able to explain both training-induced and context-dependent cue reweighting. The neuroscientific literature on auditory feature-based selective attention suggests potential neural mechanisms of phonetic cue weighting, including at the single-neuron level. At least three challenges need to be met in order to ascribe all of cue weighting to auditory feature-based selective attention: (1) the complexity of continuous speech, (2) individual differences in cue weighting and selective attention abilities, and (3) any need for specialized neural systems in allocating attention to phonetic cues. To date, using attentional theories to understand speech perception has been fruitful, but more detailed and mechanistic models of feature-based selective attention are needed in order to define the extent to which the attention literature applies in full to cue weighting in speech perception.

Feature-based attention (FBA) enhances the representation of image characteristics throughout the visual field, a mechanism that is particularly useful when searching for a specific stimulus feature. Even though most theories of visual search implicitly or explicitly assume that FBA is under top-down control, we argue that the role of top-down processing in FBA may be limited. Our review of the literature indicates that all behavioural and neuro-imaging studies investigating FBA suffer from the shortcoming that they cannot rule out an effect of priming. The mere attending to a feature enhances the mandatory processing of that feature across the visual field, an effect that is likely to occur in an automatic, bottom-up way. Studies that have investigated the feasibility of FBA by means of cueing paradigms suggest that the role of top-down processing in FBA is limited (e.g. prepare for red). Instead, the actual processing of the stimulus is needed to cause the mandatory tuning of responses throughout the visual field. We conclude that it is likely that all FBA effects reported previously are the result of bottom-up priming.

Humans can rapidly and accurately extract statistical information about features of the visual environment, an ability referred to as ensemble perception. However, little is known about how ensemble estimates are affected when task-irrelevant and distracting feature information is present. Here, we tested how effectively feature-based attention—when tuned to a specific color—can select a single item set out of two intermixed ensembles of colored lines. Participants were instructed to report the average orientation of a target-colored item set, while ignoring a second differently colored set. To assess how representational overlap between the two sets impacts color-based selection, we systematically varied the orientation similarity between the relevant and irrelevant items. Our results showed that participants’ orientation reports were reliably biased towards the irrelevant items, but interestingly, these biases were only observed when the item sets overlapped in orientation space. In a second experiment, using a visual mask to disrupt access to color information at different time points, we found that these biases were stronger when less time was available to process the stimuli. Together, these results suggest that ensemble representations are rapidly formed based on all available information in the relevant feature dimension, regardless of task relevance, and that selective attention weights and separates these ensemble representations at a relatively later processing stage. This selection appears highly effective when the underlying population activity generated by the two sets is separable along the to-be-estimated feature dimension, but is dampened when relevant and irrelevant ensemble representations overlap in feature space.

Background Feature-based attention prioritizes the processing of the attended feature while strongly suppressing the processing of nearby ones. This creates a non-linearity or “attentional suppressive surround” predicted by the Selective Tuning model of visual attention. However, previously reported effects of feature-based attention on neuronal responses are linear, e.g., feature-similarity gain. Here, we investigated this apparent contradiction by neurophysiological and psychophysical approaches. Results Responses of motion direction-selective neurons in area MT/MST of monkeys were recorded during a motion task. When attention was allocated to a stimulus moving in the neurons’ preferred direction, response tuning curves showed its minimum for directions 60–90° away from the preferred direction, an attentional suppressive surround. This effect was modeled via the interaction of two Gaussian fields representing excitatory narrowly tuned and inhibitory widely tuned inputs into a neuron, with feature-based attention predominantly increasing the gain of inhibitory inputs. We further showed using a motion repulsion paradigm in humans that feature-based attention produces a similar non-linearity on motion discrimination performance. Conclusions Our results link the gain modulation of neuronal inputs and tuning curves examined through the feature-similarity gain lens to the attentional impact on neural population responses predicted by the Selective Tuning model, providing a unified framework for the documented effects of feature-based attention on neuronal responses and behavior.

The visual images in the eyes contain much more information than the brain can process. An important selection mechanism is feature-based attention (FBA). FBA is best described by attention filters that specify precisely the extent to which items containing attended features are selectively processed and the extent to which items that do not contain the attended features are attenuated. The centroid-judgment paradigm enables quick, precise measurements of such human perceptual attention filters, analogous to transmission measurements of photographic color filters. Subjects use a mouse to locate the centroid—the center of gravity—of a briefly displayed cloud of dots and receive precise feedback. A subset of dots is distinguished by some characteristic, such as a different color, and subjects judge the centroid of only the distinguished subset (e.g., dots of a particular color). The analysis efficiently determines the precise weight in the judged centroid of dots of every color in the display (i.e., the attention filter for the particular attended color in that context). We report 32 attention filters for single colors. Attention filters that discriminate one saturated hue from among seven other equiluminant distractor hues are extraordinarily selective, achieving attended/unattended weight ratios >20:1. Attention filters for selecting a color that differs in saturation or lightness from distractors are much less selective than attention filters for hue (given equal discriminability of the colors), and their filter selectivities are proportional to the discriminability distance of neighboring colors, whereas in the same range hue attention-filter selectivity is virtually independent of discriminabilty.

We investigated whether spatial filtering can restrict attentional selectivity during visual search to a currently task-relevant attentional window. While effective filtering has been demonstrated during singleton search, feature-based attention is believed to operate spatially globally across the entire visual field. To test whether spatial filtering depends on search mode, we assessed its efficiency both during feature-guided search with colour-defined targets and during singleton search tasks. Search displays were preceded by spatial cues. Participants responded to target objects at cued/relevant locations, and ignored them when they appeared on the uncued/irrelevant side. In four experiments, electrophysiological markers of attentional selection and distractor suppression (N2pc and P D components) were measured for relevant and irrelevant target-matching objects. During singleton search, N2pc components were triggered by relevant target singletons, but were entirely absent for singletons on the irrelevant side, demonstrating effective spatial filtering. Critically, similar results were found for feature-based search. N2pcs to irrelevant target-colour objects were either absent or strongly attenuated (when these objects were salient), indicating that the feature-based guidance of visual search can be restricted to relevant locations. The presence of P D components to salient objects on the irrelevant side during feature-based and singleton search suggests that spatial filtering involves active distractor suppression. These results challenge the assumption that feature-based attentional guidance is always spatially global. They suggest instead that when advance information about target locations becomes available, effective spatial filtering processes are activated transiently not only in singleton search, but also during search for feature-defined targets.

A central question in the field of attention is whether visual processing is a strictly limited resource, which must be allocated by selective attention. If this were the case, attentional enhancement of one stimulus should invariably lead to suppression of unattended distracter stimuli. Here we examine voluntary cued shifts of feature-selective attention to either one of two superimposed red or blue random dot kinematograms (RDKs) to test whether such a reciprocal relationship between enhancement of an attended and suppression of an unattended stimulus can be observed. The steady-state visual evoked potential (SSVEP), an oscillatory brain response elicited by the flickering RDKs, was measured in human EEG. Supporting limited resources, we observed both an enhancement of the attended and a suppression of the unattended RDK, but this observed reciprocity did not occur concurrently: enhancement of the attended RDK started at 220 ms after cue onset and preceded suppression of the unattended RDK by about 130 ms. Furthermore, we found that behavior was significantly correlated with the SSVEP time course of a measure of selectivity (attended minus unattended) but not with a measure of total activity (attended plus unattended). The significant deviations from a temporally synchronized reciprocity between enhancement and suppression suggest that the enhancement of the attended stimulus may cause the suppression of the unattended stimulus in the present experiment.

Prior information about distractor facilitates selective attention to task-relevant items and helps the optimization of oculomotor planning. In the present study, we capitalized on gaze-position decoding to examine the dynamics of attentional deployment in a feature-based attentional task that involved two groups of dots (target/distractor dots) moving toward different directions. In Experiment 1, participants were provided with target cues indicating the moving direction of target dots. The results showed that participants were biased toward the cued direction and tracked the target dots throughout the task period. In Experiment 2 and Experiment 3, participants were provided with cues that informed the moving direction of distractor dots. When the distractor cue varied on a trial-by-trial basis (Experiment 2), participants continuously monitored the distractor’s direction. However, when the to-be-ignored distractor direction remained constant (Experiment 3), participants would strategically bias their attention to the distractor’s direction before the cue onset to reduce the cost of redeployment of attention between trials and reactively suppress further attraction evoked by distractors during the stimulus-on stage. This functional dissociation reflected the distinct influence that expectation produced on ocular control. Taken together, these results suggest that monitoring the distractor’s feature is a prerequisite for feature-based attentional inhibition, and this process is facilitated by the predictability of the distractor’s feature.

This paper elaborates a recent conceptualization of feature-based attention in terms of attention filters (Drew et al., Journal of Vision, 10 (10:20), 1–16, 2010 ) into a general purpose centroid-estimation paradigm for studying feature-based attention. An attention filter is a brain process, initiated by a participant in the context of a task requiring feature-based attention, which operates broadly across space to modulate the relative effectiveness with which different features in the retinal input influence performance. This paper describes an empirical method for quantitatively measuring attention filters. The method uses a “statistical summary representation” (SSR) task in which the participant strives to mouse-click the centroid of a briefly flashed cloud composed of items of different types (e.g., dots of different luminances or sizes), weighting some types of items more strongly than others. In different attention conditions, the target weights for different item types in the centroid task are varied. The actual weights exerted on the participant’s responses by different item types in any given attention condition are derived by simple linear regression. Because, on each trial, the centroid paradigm obtains information about the relative effectiveness of all the features in the display, both target and distractor features, and because the participant’s response is a continuous variable in each of two dimensions (versus a simple binary choice as in most previous paradigms), it is remarkably powerful. The number of trials required to estimate an attention filter is an order of magnitude fewer than the number required to investigate much simpler concepts in typical psychophysical attention paradigms.