Proactive selective attention across competition contexts.

Selective attention is a cognitive function that helps filter out unwanted information. Theories such as the biased competition model (Desimone & Duncan, 1995) explain how attentional templates bias processing towards targets in contexts where multiple stimuli compete for resources. However, it is unclear how the anticipation of different levels of competition influences the nature of attentional templates, in a proactive fashion. In this study, we used electroencephalography (EEG) to investigate how the anticipated demands of attentional selection (either high or low stimuli competition contexts) modulate target-specific preparatory brain activity and its relationship with task performance. To do so, participants performed a sex/gender judgment task in a cue-target paradigm where, depending on the block, target and distractor stimuli appeared simultaneously (high competition) or sequentially (low competition). Multivariate Pattern Analysis (MVPA) showed that, in both competition contexts, there was a preactivation of the target category to select, with a ramping-up profile at the end of the preparatory interval. However, cross-classification showed no generalization across competition conditions, suggesting different preparatory formats. Notably, time-frequency analyses showed differences between anticipated competition demands, with higher theta band power for high than low competition, which mediated the impact of subsequent stimuli competition on behavioral performance. Overall, our results show that, whereas preactivation of the internal templates associated with the category to select are engaged in advance in high and low competition contexts, their underlying neural patterns differ. In addition, these codes could not be associated with theta power, suggesting that they reflect different preparatory processes. The implications of these findings are crucial to increase our understanding of the nature of top-down processes across different contexts.

We know what attention is!

Attention is one of the most thoroughly investigated psychological phenomena, yet skepticism about attention is widespread: we do not know what it is, it is too many things, there is no such thing. The deficiencies highlighted are not about experimental work but the adequacy of the scientific theory of attention. Combining common scientific claims about attention into a single theory leads to internal inconsistency. This paper demonstrates that a specific functional conception of attention is incorporated into the tasks used in standard experimental paradigms. In accepting these paradigms as valid probes of attention, we commit to this common conception. The conception unifies work at multiple levels of analysis into a coherent scientific explanation of attention. Thus, we all know what attention is.

The hidden arrow in the FedEx logo: Do we really unconsciously "see" it?

The FedEx logo makes clever use of figure-ground ambiguity to create an "invisible" arrow in the background space between "E" and "x". Most designers believe the hidden arrow can convey an unconscious impression of speed and precision about the FedEx brand, which may influence subsequent behavior. To test this assumption, we designed similar images with hidden arrows to serve as endogenous (but camouflaged) directional cues in a Posner's orienting task, where a cueing effect would suggest subliminal processing of the hidden arrow. Overall, we observed no cue congruency effect, unless the arrow is explicitly highlighted (Experiment 4). However, there was a general effect of prior knowledge: when people were under pressure to suppress background information, those who knew about the arrow could do so faster in all congruence conditions (i.e., neutral, congruent, incongruent), although they fail to report seeing the arrow during the experiment. This was true in participants from North America who had heard of the FedEx arrow before (Experiment 1 & 3), and also in our Taiwanese sample who were just informed of such design (Experiment 2). These results can be well explained by the Biased Competition Model in figure-ground research, and together suggest: (1) people do not unconsciously perceive the FedEx arrow, at least not enough to exhibit a cueing effect in attention, but (2) knowing about the arrow can fundamentally change the way we visually process these negative-space logos in the future, making people react faster to images with negative space regardless of the hidden content.

Attention Modulates Human Visual Responses to Objects by Tuning Sharpening.

Visual stimuli compete with each other for cortical processing and attention biases this competition in favor of the attended stimulus. How does the relationship between the stimuli affect the strength of this attentional bias? Here, we used functional MRI to explore the effect of target-distractor similarity in neural representation on attentional modulation in the human visual cortex using univariate and multivariate pattern analyses. Using stimuli from four object categories (human bodies, cats, cars and houses), we investigated attentional effects in the primary visual area V1, the object-selective regions LO and pFs, the body-selective region EBA, and the scene-selective region PPA. We demonstrated that the strength of the attentional bias towards the target is not fixed but decreases with increasing distractor-target similarity. Simulations provided evidence that this result pattern is explained by tuning sharpening rather than an increase in gain. Our findings provide a mechanistic explanation for behavioral effects of target-distractor similarity on attentional biases and suggest tuning sharpening as the underlying mechanism in object-based attention.

Semantically Adaptive JND Modeling with Object-Wise Feature Characterization, Context Inhibition and Cross-Object Interaction.

Performance bottlenecks in the optimization of JND modeling based on low-level manual visual feature metrics have emerged. High-level semantics bear a considerable impact on perceptual attention and subjective video quality, yet most existing JND models do not adequately account for this impact. This indicates that there is still much room and potential for performance optimization in semantic feature-based JND models. To address this status quo, this paper investigates the response of visual attention induced by heterogeneous semantic features with an eye on three aspects, i.e., object, context, and cross-object, to further improve the efficiency of JND models. On the object side, this paper first focuses on the main semantic features that affect visual attention, including semantic sensitivity, objective area and shape, and central bias. Following that, the coupling role of heterogeneous visual features with HVS perceptual properties are analyzed and quantified. Second, based on the reciprocity of objects and contexts, the contextual complexity is measured to gauge the inhibitory effect of contexts on visual attention. Third, cross-object interactions are dissected using the principle of bias competition, and a semantic attention model is constructed in conjunction with a model of attentional competition. Finally, to build an improved transform domain JND model, a weighting factor is used by fusing the semantic attention model with the basic spatial attention model. Extensive simulation results validate that the proposed JND profile is highly consistent with HVS and highly competitive among state-of-the-art models.

Attention along the cortical hierarchy: Development matters.

We build on the existing biased competition view to argue that attention is an emergent property of neural computations within and across hierarchically embedded and structurally connected cortical pathways. Critically then, one must ask, what is attention emergent from? Within this framework, developmental changes in the quality of sensory input and feedforward-feedback information flow shape the emergence and efficiency of attention. Several gradients of developing structural and functional cortical architecture across the caudal-to-rostral axis provide the substrate for attention to emerge. Neural activity within visual areas depends on neuronal density, receptive field size, tuning properties of neurons, and the location of and competition between features and objects in the visual field. These visual cortical properties highlight the information processing bottleneck attention needs to resolve. Recurrent feedforward and feedback connections convey sensory information through a series of steps at each level of the cortical hierarchy, integrating sensory information across the entire extent of the cortical hierarchy and linking sensory processing to higher-order brain regions. Higher-order regions concurrently provide input conveying behavioral context and goals. Thus, attention reflects the output of a series of complex biased competition neural computations that occur within and across hierarchically embedded cortical regions. Cortical development proceeds along the caudal-to-rostral axis, mirroring the flow in sensory information from caudal to rostral regions, and visual processing continues to develop into childhood. Examining both typical and atypical development will offer critical mechanistic insight not otherwise available in the adult stable state. This article is categorized under: Psychology > Attention.

Attention as a multi-level system of weights and balances.

This opinion piece is part of a collection on the topic: "What is attention?" Despite the word's place in the common vernacular, a satisfying definition for "attention" remains elusive. Part of the challenge is there exist many different types of attention, which may or may not share common mechanisms. Here we review this literature and offer an intuitive definition that draws from aspects of prior theories and models of attention but is broad enough to recognize the various types of attention and modalities it acts upon: attention as a multi-level system of weights and balances. While the specific mechanism(s) governing the weighting/balancing may vary across levels, the fundamental role of attention is to dynamically weigh and balance all signals-both externally-generated and internally-generated-such that the highest weighted signals are selected and enhanced. Top-down, bottom-up, and experience-driven factors dynamically impact this balancing, and competition occurs both within and across multiple levels of processing. This idea of a multi-level system of weights and balances is intended to incorporate both external and internal attention and capture their myriad of constantly interacting processes. We review key findings and open questions related to external attention guidance, internal attention and working memory, and broader attentional control (e.g., ongoing competition between external stimuli and internal thoughts) within the framework of this analogy. We also speculate about the implications of failures of attention in terms of weights and balances, ranging from momentary one-off errors to clinical disorders, as well as attentional development and degradation across the lifespan. This article is categorized under: Psychology > Attention Neuroscience > Cognition.

The Rejection Template of Working Memory Operates after Attention Capture.

Although scientists know that information stored in working memory guides visual attention, how this is accomplished is still under debate. Specifically, there is a dispute between the Biased Competition Model and Visual Attention Theory. The current study used two experiments to resolve this controversy based on previous research. Experiment 1 found that although inverse efficiency scores for High and Low numbers of memory distractors were both longer than the Baseline (no memory distractors), they did not significantly differ from each other. This indicated that memory might guide attention via a capture-then-global-inhibition process. Experiment 2 addressed the possibility that the findings resulted from the time needed to reject the interfering objects by requiring both memory-matching and memory-mismatching conditions to be rejected under a highlighted target. This result showed that the memory-matching condition resulted in longer search times than the memory-mismatching condition, indicating an attention-capture effect based on working memory. Together, the two experiments support the idea that when multiple memory-matching distractors in a search array first capture an individual's attention, it then acts as a template that allows the individual to suppress all interfering items that containing memory information holds. This study supports the Biased Competition Model early on in visual search. However, the late stage of visual search supports the Visual Attention Theory. These advance our knowledge regarding the relationship between working memory content and attention.

Task demands determine whether shape or arousal of a stimulus modulates competition for visual working memory resources.

It has been posited (Öhman, 1986) that the processing of threatening stimuli became prioritized during the course of mammalian evolution and that such objects may still enjoy an advantage in visual processing to this day. It has been well-documented that both mid-level visual features (i.e., conjunctions of low-level features) and the arousal level of threatening stimuli affect attentional allocation (Cisler & Koster, 2010; Wolfe & Horowitz, 2004). Despite this, few studies have investigated the effect these factors have on visual working memory resources. Here, we investigated these factors using a rapid serial visual presentation (RSVP) paradigm, and by manipulating mid-level features (specifically, shape: similar vs. dissimilar) and the arousal level (non-threatening vs threatening) of the stimuli. Participants watched an RSVP stream in preparation for an upcoming memory test. Then, they completed a two-alternative forced-choice recognition memory test (with semantically matched foils) wherein they had to identify which item they had seen in the RSVP stream. Our results showed that when shape was a sufficient feature to discriminate the target from the other items in the stream, there was no effect of arousal (i.e., threat level) on reaction time or accuracy during the memory test. However, when the shapes of all the stimuli in the visual stream were highly similar, an effect of arousal appeared: When the target had a different arousal level than the background items (i.e., non-targets), performance was improved. Together, the results suggest that both mid-level visual features and arousal level can modulate competition for visual working memory resources.

Preparatory attention incorporates contextual expectations.

Humans are remarkably proficient at finding objects within complex visual scenes. According to current theories of attention,1-3 visual processing of an object of interest is favored through the preparatory activation of object-specific representations in visual cortex.4-15 One key problem that is inherent to real-world visual search but is not accounted for by current theories is that a given object will produce a dramatically different retinal image depending on its location, which is unknown in advance. For instance, the color of the retinal image depends on the illumination on the object, its shape depends on the viewpoint, and (most critically) its size can vary by several orders of magnitude, depending on the distance to the observer. In order to benefit search, preparatory activity thus needs to incorporate contextual expectations. In the current study, we measured fMRI blood-oxygen-level-dependent (BOLD) activity in human observers while they prepared to search for objects at different distances in indoor-scene photographs. First, we established that observers instantiated preparatory object representations: activity patterns in object-selective cortex evoked during search preparation (while no objects were presented) resembled activity patterns evoked by viewing those objects in isolation. Second, we demonstrated that these preparatory object representations were systematically modulated by expectations derived from scene context: activity patterns reflected the predicted retinal image of the object at each distance (i.e., distant search evoking smaller object representations and nearby search evoking larger object representations). These findings reconcile current theories of attentional selection with the challenges of real-world vision.

Neural Basis of Biased Competition in Development: Sensory Competition in Visual Cortex of School-Aged Children.

The fundamental receptive field (RF) architecture in human visual cortex becomes adult-like by age 5. However, visuo-spatial functions continue to develop until teenage years. This suggests that, despite the early maturation of the RF structure, functional interactions within and across RFs may mature slowly. Here, we used fMRI to investigate functional interactions among multiple stimuli in the visual cortex of school children (ages 8 to 12) in the context of biased competition theory. In the adult visual system, multiple objects presented in the same visual field compete for neural representation. These competitive interactions occur at the level of the RF and are therefore closely linked to the RF architecture. Like in adults, we found suppression of evoked responses in children's visual cortex when multiple stimuli were presented simultaneously. Such suppression effects were modulated by the spatial distance between the stimuli as a function of RF size across the visual system. Our findings suggest that basic competitive interactions in the visual cortex of children above age 8 operate in an adult-like manner, with subtle differences in early visual areas and area MT. Our study establishes a paradigm and provides baseline data to investigate the neural basis of visuo-spatial processing in typical and atypical development.

Putting the Nonsocial Into Social Neuroscience: A Role for Domain-General Priority Maps During Social Interactions.

Whether on a first date or during a team briefing at work, people's daily lives are inundated with social information, and in recent years, researchers have begun studying the neural mechanisms that support social-information processing. We argue that the focus of social neuroscience research to date has been skewed toward specialized processes at the expense of general processing mechanisms with a consequence that unrealistic expectations have been set for what specialized processes alone can achieve. We propose that for social neuroscience to develop into a more mature research program, it needs to embrace hybrid models that integrate specialized person representations with domain-general solutions, such as prioritization and selection, which operate across all classes of information (both social and nonsocial). To illustrate our central arguments, we first describe and then evaluate a hybrid model of information processing during social interactions that (a) generates novel and falsifiable predictions compared with existing models; (b) is predicated on a wealth of neurobiological evidence spanning many decades, methods, and species; (c) requires a superior standard of evidence to substantiate domain-specific mechanisms of social behavior; and (d) transforms expectations of what types of neural mechanisms may contribute to social-information processing in both typical and atypical populations.

Biased competition in semantic representation during natural visual search.

Humans divide their attention among multiple visual targets in daily life, and visual search can get more difficult as the number of targets increases. The biased competition hypothesis (BC) has been put forth as an explanation for this phenomenon. BC suggests that brain responses during divided attention are a weighted linear combination of the responses during search for each target individually. This combination is assumed to be biased by the intrinsic selectivity of cortical regions. Yet, it is unknown whether attentional modulation of semantic representations are consistent with this hypothesis when viewing cluttered, dynamic natural scenes. Here, we investigated whether BC accounts for semantic representation during natural category-based visual search. Subjects viewed natural movies, and their whole-brain BOLD responses were recorded while they attended to "humans", "vehicles" (i.e. single-target attention tasks), or "both humans and vehicles" (i.e. divided attention) in separate runs. We computed a voxelwise linearity index to assess whether semantic representation during divided attention can be modeled as a weighted combination of representations during the two single-target attention tasks. We then examined the bias in weights of this linear combination across cortical ROIs. We find that semantic representations of both target and nontarget categories during divided attention are linear to a substantial degree, and that they are biased toward the preferred target in category-selective areas across ventral temporal cortex. Taken together, these results suggest that the biased competition hypothesis is a compelling account for attentional modulation of semantic representations.

Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex.

A new approach to understanding the interaction between cortical areas is provided by a mathematical analysis of biased competition, which describes many interactions between cortical areas, including those involved in top-down attention. The analysis helps to elucidate the principles of operation of such cortical systems, and in particular the parameter values within which biased competition operates. The analytic results are supported by simulations that illustrate the operation of the system with parameters selected from the analysis. The findings provide a detailed mathematical analysis of the operation of these neural systems with nodes connected by feedforward (bottom-up) and feedback (top-down) connections. The analysis provides the critical value of the top-down attentional bias that enables biased competition to operate for a range of input values to the network, and derives this as a function of all the parameters in the model. The critical value of the top-down bias depends linearly on the value of the other inputs, but the coefficients in the function reveal non-linear relations between the remaining parameters. The results provide reasons why the backprojections should not be very much weaker than the forward connections between two cortical areas. The major advantage of the analytical approach is that it discloses relations between all the parameters of the model.

Effects of arousal on biased competition in attention and short-term memory.

A recent theory proposes that arousal amplifies the competition between stimulus representations, strengthening already strong representations and weakening already weak representations in perception and memory. Here, we report a stringent test of this arousal-biased competition theory in the context of visual attention and short-term memory. We examined whether pre-trial arousal enhances the bottom-up attentional bias toward physically salient versus less salient stimuli in a multi-letter identification task. Arousal was manipulated by presenting an arousing versus a neutral picture (Experiment 1) or sound (Experiment 2) at the start of each trial. Bayesian statistics revealed strong evidence for the null hypothesis in both experiments: Arousal did not modulate the effects of physical salience on letter identification. The experiments were repeated with EEG measurements and subjective stimulus ratings, which confirmed that the stimuli successfully manipulated physiological and subjective arousal. These results pose a challenge for the arousal-biased competition theory.

Toward an integrative science of social vision in intergroup bias.

Social neuroscience is unveiling how the brain coordinates the construal of social categories and the generation of intergroup biases from facial perception. Recent evidence indicates that social categorization is more sensitive and malleable to elemental facial features than previously assumed. At the same time, perception of social categories can be crafted by top-down factors, including prior knowledge, motivations, and social expectations. In this review, we summarize extant wisdom and propose a model that goes beyond traditional accounts that have conceived stereotypes and prejudices as the end result of "reading out" social categories in the face, and have assumed a hierarchical brain organization. Our model proposes recursive and dynamic interactions amid distant brain regions. Accordingly, the reciprocal exchange of sensory evidence and predictions biases and "explains away" visual input in face perception regions until a compromise is achieved and social perception stabilizes. Ideally, this effort would contribute to shape a research field at the interface between neural and social sciences, which is often referred to as social vision.

Flexibility in Attentional Control: Multiple Sources and Suppression.

In daily life, it is critical that we are able to direct our visual attention to information that is important for our tasks while avoiding distracting information. To control our attention, we engage "attentional templates" that reconfigure how incoming visual signals are processed in our brains. But what are these attentional templates and how do they work? Much of our understanding of the nature of attentional templates has been driven by the proposed mechanism linking attentional templates and working memory from the biased competition model [1] (Desimone and Duncan, 1995). Over the past 20 years, research inspired by this proposal has vastly increased our understanding of attentional control. This work has highlighted flexibility in attentional control, with multiple sources of control and flexible enhancement or suppression based on task demands.

Emotion Induced Blindness Is More Sensitive to Changes in Arousal As Compared to Valence of the Emotional Distractor.

Emotion Induced Blindness (EIB) refers to the impairment in the identification of a neutral target image that follows a threatening or fearful distractor image. It has been suggested that valence plays a significant role in driving the perceptual impairment in EIB. Recent findings from the literature suggest that arousal has a very important role in biasing early cognitive functions. Hence, in the present study, we systematically investigate the role of valence (Experiment 1) and arousal (Experiment 2) in determining the impairment in EIB. The results suggest that when valence is controlled for, the stimuli with higher arousal level lead to greater impairment in target detection. Moreover, under high arousal condition, both positive and negative stimuli lead to significantly greater impairment in target detection. Present study suggests that impairment in EIB is sensitive to the arousal component of the emotional image as compared to valence. The arousal biased competition account that explains the effect of arousal on cognitive processing can sufficiently explains the current results.

Preparatory attention in visual cortex.

Top-down attention is the mechanism that allows us to selectively process goal-relevant aspects of a scene while ignoring irrelevant aspects. A large body of research has characterized the effects of attention on neural activity evoked by a visual stimulus. However, attention also includes a preparatory phase before stimulus onset in which the attended dimension is internally represented. Here, we review neurophysiological, functional magnetic resonance imaging, magnetoencephalography, electroencephalography, and transcranial magnetic stimulation (TMS) studies investigating the neural basis of preparatory attention, both when attention is directed to a location in space and when it is directed to nonspatial stimulus attributes (content-based attention) ranging from low-level features to object categories. Results show that both spatial and content-based attention lead to increased baseline activity in neural populations that selectively code for the attended attribute. TMS studies provide evidence that this preparatory activity is causally related to subsequent attentional selection and behavioral performance. Attention thus acts by preactivating selective neurons in the visual cortex before stimulus onset. This appears to be a general mechanism that can operate on multiple levels of representation. We discuss the functional relevance of this mechanism, its limitations, and its relation to working memory, imagery, and expectation. We conclude by outlining open questions and future directions.

Emotional influences on perception and working memory.

Although there has been steady progress elucidating the influence of emotion on cognition, it remains unclear precisely when and why emotion impairs or facilitates cognition. The present study investigated the mechanisms involved in the influence of emotion on perception and working memory (WM), using modified 0-back and 2-back tasks, respectively. First, results showed that attentional focus modulated the impact of emotion on perception. Specifically, emotion facilitated perceptual task performance when it was relevant to the task, but it impaired performance when it was irrelevant to the task. The differential behavioural effect of emotion on perception as a function of attentional focus diminished under high WM load. Second, attentional focus did not directly modulate the impact of emotion on WM, but rather its influence depended on the dynamic relationship between internal representations. Specifically, WM performance was worse when the material already being held online and the new input were of matching emotions (e.g. both were negative), compared to when they were not. We propose that the competition between "bottom-up" and "top-down" processing for limited cognitive resources explains the nature of the influence of emotion on both perception and WM.