Dimension intertrial and cueing effects in localization: support for pre-attentively weighted one-route models of saliency

Biasing Allocations of Attention via Selective Weighting of Saliency Signals: Behavioral and Neuroimaging Evidence for the Dimension-Weighting Account

Objects that stand out from the environment tend to be of behavioral relevance, and the visual system is tuned to preferably process these salient objects by allocating focused attention. However, attention is not just passively (bottom-up) driven by stimulus features, but previous experiences and task goals exert strong biases toward attending or actively ignoring salient objects. The core and eponymous assumption of the dimension-weighting account (DWA) is that these top-down biases are not as flexible as one would like them to be; rather, they are subject to dimensional constraints. In particular, DWA assumes that people can often not search for objects that have a particular feature but only for objects that stand out from the environment (i.e., that are salient) in a particular feature dimension. We review behavioral and neuroimaging evidence for such dimensional constraints in three areas: search history, voluntary target enhancement, and distractor handling. The first two have been the focus of research on DWA since its inception and the latter the subject of our more recent research. Additionally, we discuss various challenges to the DWA and its relation to other prominent theories on top-down influences in visual search.

You prime what you code: The fAIM model of priming of pop-out

Our visual brain makes use of recent experience to interact with the visual world, and efficiently select relevant information. This is exemplified by speeded search when target- and distractor features repeat across trials versus when they switch, a phenomenon referred to as intertrial priming. Here, we present fAIM, a computational model that demonstrates how priming can be explained by a simple feature-weighting mechanism integrated into an established model of bottom-up vision. In fAIM, such modulations in feature gains are widespread and not just restricted to one or a few features. Consequentially, priming effects result from the overall tuning of visual features to the task at hand. Such tuning allows the model to reproduce priming for different types of stimuli, including for typical stimulus dimensions such as 'color' and for less obvious dimensions such as 'spikiness' of shapes. Moreover, the model explains some puzzling findings from the literature: it shows how priming can be found for target-distractor stimulus relations rather than for their absolute stimulus values per se, without an explicit representation of relations. Similarly, it simulates effects that have been taken to reflect a modulation of priming by an observers' goals-without any representation of goals in the model. We conclude that priming is best considered as a consequence of a general adaptation of the brain to visual input, and not as a peculiarity of visual search.

The role of context in volitional control of feature-based attention

Visual selection can be biased toward nonspatial feature values such as color, but there is continued debate about whether this bias is subject to volitional control or whether it is an automatic bias toward recently seen target features (selection history). Although some studies have tried to separate these 2 sources of selection bias, mixed findings have not offered a clear resolution. The present work offers a possible explanation of conflicting findings by showing that the context in which a trial is presented can determine whether volitional control is observed. We used a cueing task that enabled independent assessments of the effects of color repetitions and current selection goals. When the target was presented among distractors with multiple colors (heterogeneous blocks), Experiment 1 revealed clear goal-driven selection effects, but these effects were eliminated when the target was a color singleton (pop-out blocks). When heterogeneous and pop-out displays were mixed within a block (Experiment 2), however, goal-driven selection was observed with both types of displays. In Experiment 3, this pattern was replicated using an encoding-limited task that included brief displays and an A' measure of performance. Thus, goal-driven selection of nonspatial features is potentiated in contexts where there is strong competition with distractors. Selection history has powerful effects, but we find clear evidence that observers can exert volitional control over feature-based attention. (PsycINFO Database Record

Singleton search is guided by knowledge of the target, but maybe it shouldn't be

Among studies of visual search for a singleton, some studies show evidence of top-down attentional guidance driven by goals, while others do not, leading to uncertainty as to how goal-driven guidance should be included in attentional theories. Six experiments tested this guidance when a target shape is found by locating a singleton feature (color or shape) and an orientation within the target is then reported. Experiments 1 and 2 use the dimensional priming paradigm underlying the most effective arguments against goal-driven guidance, and show evidence for guidance in many circumstances. Experiment 3 extends the results to feature priming, and demonstrates a complex interaction between attentional goals and memory for previous targets. In Experiment 4, symbolic (word) cues were just as effective as image cues, further strengthening the case for goal-driven guidance. In Experiments 5 and 6, as in the previous experiments, valid cues again produced faster responses than invalid cues, showing the advantage of goal-driven guidance. Surprisingly, however, responses were even faster when the cues were uninformative. Furthermore, participants who began the experiment with neutral cues seemed to ignore informative cues later in the experiment. The results show that attention can be guided by goals even in easy searches, but that searchers have much flexibility in the use of this guidance, and may choose not to use it. Furthermore, their decisions about using this guidance are not always well informed, because they are not aware of the relative costs and benefits.

Repetition priming in selective attention: A TVA analysis

Current behavior is influenced by events in the recent past. In visual attention, this is expressed in many variations of priming effects. Here, we investigate color priming in a brief exposure digit-recognition task. Observers performed a masked odd-one-out singleton recognition task where the target-color either repeated or changed between subsequent trials. Performance was measured by recognition accuracy over exposure durations. The purpose of the study was to replicate earlier findings of perceptual priming in brief displays and to model those results based on a Theory of Visual Attention (TVA; Bundesen, 1990). We tested 4 different definitions of a generic TVA-model and assessed their explanatory power. Our hypothesis was that priming effects could be explained by selective mechanisms, and that target-color repetitions would only affect the selectivity parameter (α) of our models. Repeating target colors enhanced performance for all 12 observers. As predicted, this was only true under conditions that required selection of a target among distractors, but not when a target was presented alone. Model fits by TVA were obtained with a trial-by-trial maximum likelihood estimation procedure that estimated 4-15 free parameters, depending on the particular model. We draw two main conclusions. Color priming can be modeled simply as a change in selectivity between conditions of repetition or swap of target color. Depending on the desired resolution of analysis; priming can accurately be modeled by a simple four parameter model, where VSTM capacity and spatial biases of attention are ignored, or more fine-grained by a 10 parameter model that takes these aspects into account.

Distractors less salient than targets capture attention rather than producing non-spatial filtering costs

Distractors that are less salient than the target evoke reaction time interference in the distractor search paradigm. Here, we investigated whether this interference indeed results from spatial attentional capture or merely from non-spatial filtering costs. Target and distractor salience was manipulated parametrically and the modulation of reaction time interference by the distance between both stimuli was taken as an indicator of attentional capture. For distractors that were less salient than the target, we found distance to be predictive of reaction time interference. Moreover, this relationship was modulated by the difference in relative salience of target and distractor: the less salient the distractor was compared to the target, the weaker was the influence of distance. These results are in accordance with the sequential sampling model of salience-based selection by Zehetleitner et al. (Zehetleitner, M., Koch, A.I., Goschy, H., Müller, H.J., 2013. Salience-based selection: Interference by distractors less salient than the target. PLoS ONE 8: e52595.). This model assumes the salience map to be computed by noisy accumulation of sensory evidence. As a result, the salience map output fluctuates around its true value and less salient locations can be denoted as most salient. A distractor less salient than the target can therefore capture attention with a certain probability. We conclude that reaction time interference by less salient distractors in the distractor search paradigm is a result of attentional capture in a proportion of trials, rather than a result of non-spatial filtering costs.

Salience-based selection: attentional capture by distractors less salient than the target

Current accounts of attentional capture predict the most salient stimulus to be invariably selected first. However, existing salience and visual search models assume noise in the map computation or selection process. Consequently, they predict the first selection to be stochastically dependent on salience, implying that attention could even be captured first by the second most salient (instead of the most salient) stimulus in the field. Yet, capture by less salient distractors has not been reported and salience-based selection accounts claim that the distractor has to be more salient in order to capture attention. We tested this prediction using an empirical and modeling approach of the visual search distractor paradigm. For the empirical part, we manipulated salience of target and distractor parametrically and measured reaction time interference when a distractor was present compared to absent. Reaction time interference was strongly correlated with distractor salience relative to the target. Moreover, even distractors less salient than the target captured attention, as measured by reaction time interference and oculomotor capture. In the modeling part, we simulated first selection in the distractor paradigm using behavioral measures of salience and considering the time course of selection including noise. We were able to replicate the result pattern we obtained in the empirical part. We conclude that each salience value follows a specific selection time distribution and attentional capture occurs when the selection time distributions of target and distractor overlap. Hence, selection is stochastic in nature and attentional capture occurs with a certain probability depending on relative salience.

Dynamic weighting of feature dimensions in visual search: behavioral and psychophysiological evidence

Dimension-based accounts of visual search and selection have significantly contributed to the understanding of the cognitive mechanisms of attention. Extensions of the original approach assuming the existence of dimension-based feature contrast saliency signals that govern the allocation of focal attention have recently been employed to explain the spatial and temporal dynamics of the relative strengths of saliency representations. Here we review behavioral and neurophysiological findings providing evidence for the dynamic trial-by-trial weighting of feature dimensions in a variety of visual search tasks. The examination of the effects of feature and dimension-based inter-trial transitions in feature detection tasks shows that search performance is affected by the change of target-defining dimensions, but not features. The use of the redundant-signals paradigm shows that feature contrast saliency signals are integrated at a pre-selective processing stage. The comparison of feature detection and compound search tasks suggests that the relative significance of dimension-dependent and dimension-independent saliency representations is task-contingent. Empirical findings that explain reduced dimension-based effects in compound search tasks are discussed. Psychophysiological evidence is presented that confirms the assumption that the locus of the effects of feature dimension changes is perceptual pre-selective rather than post-selective response-based. Behavioral and psychophysiological results are considered within in the framework of the dimension weighting account of selective visual attention.

Stimulus saliency modulates pre-attentive processing speed in human visual cortex

The notion of a saliency-based processing architecture [1] underlying human vision is central to a number of current theories of visual selective attention [e.g., 2]. On this view, focal-attention is guided by an overall-saliency map of the scene, which integrates (sums) signals from pre-attentive sensory feature-contrast computations (e.g., for color, motion, etc.). By linking the Posterior Contralateral Negativity (PCN) component to reaction time (RT) performance, we tested one specific prediction of such salience summation models: expedited shifts of focal-attention to targets with low, as compared to high, target-distracter similarity. For two feature-dimensions (color and orientation), we observed decreasing RTs with increasing target saliency. Importantly, this pattern was systematically mirrored by the timing, as well as amplitude, of the PCN. This pattern demonstrates that visual saliency is a key determinant of the time it takes for focal-attention to be engaged onto the target item, even when it is just a feature singleton.