Effects Of Feature-based Attention Research Articles

A source for category-induced global effects of feature-based attention in human prefrontal cortex

Global effects of feature-based attention (FBA) are generally limited to stimuli sharing the same or similar features, as hypothesized in the "feature-similarity gain model." Visual perception, however, often reflects categories acquired via experience/learning; whether the global-FBA effect can be induced by the categorized features remains unclear. Here, human subjects were trained to classify motion directions into two discrete categories and perform a classical motion-based attention task. We found a category-induced global-FBA effect in both the middle temporal area (MT+) and frontoparietal areas, where attention to a motion direction globally spread to unattended motion directions within the same category, but not to those in a different category. Effective connectivity analysis showed that the category-induced global-FBA effect in MT+ was derived by feedback from the inferior frontal junction (IFJ). Altogether, our study reveals a category-induced global-FBA effect and identifies a source for this effect in human prefrontal cortex, implying that FBA is of greater ecological significance than previously thought.

Attention to visual motion suppresses neuronal and behavioral sensitivity in nearby feature space

BackgroundFeature-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.ResultsResponses 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.ConclusionsOur 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 time-course of feature-based attention effects dissociated from temporal expectation and target-related processes

Selective attention prioritises relevant information amongst competing sensory input. Time-resolved electrophysiological studies have shown stronger representation of attended compared to unattended stimuli, which has been interpreted as an effect of attention on information coding. However, because attention is often manipulated by making only the attended stimulus a target to be remembered and/or responded to, many reported attention effects have been confounded with target-related processes such as visual short-term memory or decision-making. In addition, attention effects could be influenced by temporal expectation about when something is likely to happen. The aim of this study was to investigate the dynamic effect of attention on visual processing using multivariate pattern analysis of electroencephalography (EEG) data, while (1) controlling for target-related confounds, and (2) directly investigating the influence of temporal expectation. Participants viewed rapid sequences of overlaid oriented grating pairs while detecting a “target” grating of a particular orientation. We manipulated attention, one grating was attended and the other ignored (cued by colour), and temporal expectation, with stimulus onset timing either predictable or not. We controlled for target-related processing confounds by only analysing non-target trials. Both attended and ignored gratings were initially coded equally in the pattern of responses across EEG sensors. An effect of attention, with preferential coding of the attended stimulus, emerged approximately 230 ms after stimulus onset. This attention effect occurred even when controlling for target-related processing confounds, and regardless of stimulus onset expectation. These results provide insight into the effect of feature-based attention on the dynamic processing of competing visual information.

Charged With a Crime: The Neuronal Signature of Processing Negatively Evaluated Faces Under Different Attentional Conditions

Our brains rapidly respond to human faces and can differentiate between many identities, retrieving rich semantic emotional-knowledge information. Studies provide a mixed picture of how such information affects event-related potentials (ERPs). We systematically examined the effect of feature-based attention on ERP modulations to briefly presented faces of individuals associated with a crime. The tasks required participants (N = 40 adults) to discriminate the orientation of lines overlaid onto the face, the age of the face, or emotional information associated with the face. Negative faces amplified the N170 ERP component during all tasks, whereas the early posterior negativity (EPN) and late positive potential (LPP) components were increased only when the emotional information was attended to. These findings suggest that during early configural analyses (N170), evaluative information potentiates face processing regardless of feature-based attention. During intermediate, only partially resource-dependent, processing stages (EPN) and late stages of elaborate stimulus processing (LPP), attention to the acquired emotional information is necessary for amplified processing of negatively evaluated faces.

Feature-based attention is not confined by object boundaries: Spatially global enhancement of irrelevant features.

Theories of visual attention differ in what they identify as the core unit of selection. Feature-based theories emphasize basic visual features (e.g., color, motion), demonstrated through enhancement of attended features throughout the visual field, while object-based theories propose that attention enhances all features belonging to the same object. These theories make distinct predictions about the processing of features that are not attended primarily: Object-based theories predict that such secondary, task-irrelevant features are enhanced within object boundaries, while feature-based theories predict enhancement of irrelevant features across locations, regardless of objecthood. To test these two accounts, we had participants attend a set of colored dots among distractor dots (moving coherently upward or downward) to detect brief luminance decreases, while simultaneously detecting speed changes in other sets of dots in the opposite visual field. In the first experiment, we demonstrate that participants have higher speed detection rates in the dot array that matched the motion direction of the attended color array, although motion direction was task-irrelevant. In a second experiment, we manipulated the probability that speed changes occurred in the matching motion direction and found that enhancement of the irrelevant motion direction persisted even when it was detrimental for task performance, suggesting that spatially global effects of feature-based attention cannot easily be flexibly adjusted. Overall, these results indicate that features that are not primarily attended are enhanced globally, surpassing object boundaries.

Nested oscillations and brain connectivity during sequential stages of feature-based attention

Brain mechanisms of visual selective attention involve both local and network-level activity changes at specific oscillatory rhythms, but their interplay remains poorly explored. Here, we investigate anticipatory and reactive effects of feature-based attention using separate fMRI and EEG recordings, while participants attended to one of two spatially overlapping visual features (motion and orientation). We focused on EEG source analysis of local neuronal rhythms and nested oscillations and on graph analysis of connectivity changes in a network of fMRI-defined regions of interest, and characterized a cascade of attentional effects at multiple spatial scales. We discuss how the results may reconcile several theories of selective attention, by showing how β rhythms support anticipatory information routing through increased network efficiency, while reactive α-band desynchronization patterns and increased α-γ coupling in task-specific sensory areas mediate stimulus-evoked processing of task-relevant signals.

Behavioral and electrophysiological evidence for a dissociation between working memory capacity and feature-based attention

When attending to visual objects with particular features, neural processing is typically biased toward those features. Previous work has suggested that maintaining such feature-based attentional sets may involve the same neural resources as visual working memory. If so, the extent to which feature-based attention influences stimulus processing should be related to individuals' working memory capacity. Here we used electroencephalography (EEG) to record brain activity in 60 human observers while they monitored stimulus streams for targets of a specific color. Distractors presented at irrelevant locations evoked strong electrophysiological markers of attentional signal enhancement (the N2pc and PD components) despite producing little or no behavioral interference. Critically, there was no relationship between individual differences in the magnitude of these feature-based biases on distractor processing and individual differences in working memory capacity as measured using three separate working memory tasks. Bayes factor analyses indicated substantial evidence in support of the null hypothesis of no relationship between working memory capacity and the effects of feature-based attention on distractor processing. We consider three potential explanations for these findings. One is that working memory and feature-based attention draw upon distinct neural resources, contrary to previous claims. A second is that working memory is only related to feature-based attention when the attentional template has recently changed. A third is that feature-based attention tasks of the kind employed in the current study recruit just one of several subcomponents of working memory, and so are not invariably correlated with an individual's overall working memory capacity.

Global effects of feature-based attention depend on surprise

Recent studies have shown that prediction and attention can interact under various circumstances, suggesting that the two processes are based on interdependent neural mechanisms. In the visual modality, attention can be deployed to the location of a task-relevant stimulus (‘spatial attention’) or to a specific feature of the stimulus, such as colour or shape, irrespective of its location (‘feature-based attention’). Here we asked whether predictive processes are influenced by feature-based attention outside the current spatial focus of attention. Across two experiments, we recorded neural activity with electroencephalography (EEG) as human observers performed a feature-based attention task at fixation and ignored a stream of peripheral stimuli with predictable or surprising features. Central targets were defined by a single feature (colour or orientation) and differed in salience across the two experiments. Task-irrelevant peripheral patterns usually comprised one particular conjunction of features (standards), but occasionally deviated in one or both features (deviants). Consistent with previous studies, we found reliable effects of feature-based attention and prediction on neural responses to task-irrelevant patterns in both experiments. Crucially, we observed an interaction between prediction and feature-based attention in both experiments: the neural effect of feature-based attention was larger for surprising patterns than it was for predicted patterns. These findings suggest that global effects of feature-based attention depend on surprise, and are consistent with a recent theory that suggests attention optimises the precision of predictions by modulating the gain of prediction errors.

Multidimensional selection by temporal attention and feature-based attention: Evidence from event-related potentials

Numerous studies have shown that temporal attention plays an important role in selective attention. The present study used the event-related potential (ERP) to investigate how temporal attention modulates effects of feature-based attention in visual selection when both dimensions are task-relevant. We combined a modified temporal cueing paradigm with a feature-based attention task. In each trial, either a valid or an invalid temporal cue announced a short or long foreperiod (FP). After each FP, a visual stimulus in one of two colors was presented. Participants were instructed to respond only if the stimulus had a specific color and followed the cued FP. We observed ERP amplitude modulations due to feature-based attention at different processing levels. Importantly, feature-based attention effects were modulated by temporal attention. These results suggest that temporal attention not only facilitates stimulus processing on its own but also serves as a selection mechanism that can modulate stimulus processing in other dimensions.

The role of inferior frontal junction in controlling the spatially global effect of feature-based attention in human visual areas.

Feature-based attention has a spatially global effect, i.e., responses to stimuli that share features with an attended stimulus are enhanced not only at the attended location but throughout the visual field. However, how feature-based attention modulates cortical neural responses at unattended locations remains unclear. Here we used functional magnetic resonance imaging (fMRI) to examine this issue as human participants performed motion- (Experiment 1) and color- (Experiment 2) based attention tasks. Results indicated that, in both experiments, the respective visual processing areas (middle temporal area [MT+] for motion and V4 for color) as well as early visual, parietal, and prefrontal areas all showed the classic feature-based attention effect, with neural responses to the unattended stimulus significantly elevated when it shared the same feature with the attended stimulus. Effective connectivity analysis using dynamic causal modeling (DCM) showed that this spatially global effect in the respective visual processing areas (MT+ for motion and V4 for color), intraparietal sulcus (IPS), frontal eye field (FEF), medial frontal gyrus (mFG), and primary visual cortex (V1) was derived by feedback from the inferior frontal junction (IFJ). Complementary effective connectivity analysis using Granger causality modeling (GCM) confirmed that, in both experiments, the node with the highest outflow and netflow degree was IFJ, which was thus considered to be the source of the network. These results indicate a source for the spatially global effect of feature-based attention in the human prefrontal cortex.

The effect of feature-based attention on flanker interference processing: An fMRI-constrained source analysis

The present study examined whether feature-based cueing affects early or late stages of flanker conflict processing using EEG and fMRI. Feature cues either directed participants’ attention to the upcoming colour of the target or were neutral. Validity-specific modulations during interference processing were investigated using the N200 event-related potential (ERP) component and BOLD signal differences. Additionally, both data sets were integrated using an fMRI-constrained source analysis. Finally, the results were compared with a previous study in which spatial instead of feature-based cueing was applied to an otherwise identical flanker task. Feature-based and spatial attention recruited a common fronto-parietal network during conflict processing. Irrespective of attention type (feature-based; spatial), this network responded to focussed attention (valid cueing) as well as context updating (invalid cueing), hinting at domain-general mechanisms. However, spatially and non-spatially directed attention also demonstrated domain-specific activation patterns for conflict processing that were observable in distinct EEG and fMRI data patterns as well as in the respective source analyses. Conflict-specific activity in visual brain regions was comparable between both attention types. We assume that the distinction between spatially and non-spatially directed attention types primarily applies to temporal differences (domain-specific dynamics) between signals originating in the same brain regions (domain-general localization).

An Extended Normalization Model of Attention Accounts for Feature-Based Attentional Enhancement of Both Response and Coherence Gain.

Paying attention to a sensory feature improves its perception and impairs that of others. Recent work has shown that a Normalization Model of Attention (NMoA) can account for a wide range of physiological findings and the influence of different attentional manipulations on visual performance. A key prediction of the NMoA is that attention to a visual feature like an orientation or a motion direction will increase the response of neurons preferring the attended feature (response gain) rather than increase the sensory input strength of the attended stimulus (input gain). This effect of feature-based attention on neuronal responses should translate to similar patterns of improvement in behavioral performance, with psychometric functions showing response gain rather than input gain when attention is directed to the task-relevant feature. In contrast, we report here that when human subjects are cued to attend to one of two motion directions in a transparent motion display, attentional effects manifest as a combination of input and response gain. Further, the impact on input gain is greater when attention is directed towards a narrow range of motion directions than when it is directed towards a broad range. These results are captured by an extended NMoA, which either includes a stimulus-independent attentional contribution to normalization or utilizes direction-tuned normalization. The proposed extensions are consistent with the feature-similarity gain model of attention and the attentional modulation in extrastriate area MT, where neuronal responses are enhanced and suppressed by attention to preferred and non-preferred motion directions respectively.

Suppression effects in feature-based attention

Attending to a feature enhances visual processing of that feature, but it is less clear what occurs to unattended features. Single-unit recording studies in middle temporal (MT) have shown that neuronal modulation is a monotonic function of the difference between the attended and neuron's preferred direction. Such a relationship should predict a monotonic suppressive effect in psychophysical performance. However, past research on suppressive effects of feature-based attention has remained inconclusive. We investigated the suppressive effect for motion direction, orientation, and color in three experiments. We asked participants to detect a weak signal among noise and provided a partially valid feature cue to manipulate attention. We measured performance as a function of the offset between the cued and signal feature. We also included neutral trials where no feature cues were presented to provide a baseline measure of performance. Across three experiments, we consistently observed enhancement effects when the target feature and cued feature coincided and suppression effects when the target feature deviated from the cued feature. The exact profile of suppression was different across feature dimensions: Whereas the profile for direction exhibited a "rebound" effect, the profiles for orientation and color were monotonic. These results demonstrate that unattended features are suppressed during feature-based attention, but the exact suppression profile depends on the specific feature. Overall, the results are largely consistent with neurophysiological data and support the feature-similarity gain model of attention.

Feature-based attention modulates surround suppression.

Stimuli appearing in the surround of the classical receptive field (CRF) can reduce neuronal firing and perceived contrast of a preferred stimulus in the CRF, a phenomenon referred to as surround suppression. Suppression is greatest when the surrounding stimulus has the same orientation and spatial frequency (SF) as the central target. Although spatial attention has been shown to influence surround suppression, the effects of feature-based attention have yet to be characterized. Using behavioral contrast adaptation in humans, we examined center-surround interactions between SF and orientation, and asked whether attending to one feature dimension versus the other influenced suppression. A center-surround triplet comprised of a central target Gabor and two flanking Gabors were used for adaptation. The flankers could have the same SF and orientation as the target, or differ in one or both of the feature dimensions. Contrast thresholds were measured for the target before and after adapting to center-surround triplets, and postadaptation thresholds were taken as an indirect measure of surround suppression. Both feature dimensions contributed to surround suppression and did not summate. Moreover, when center and surround had the same feature value in one dimension (e.g., same orientation) but had different values in the other dimension (e.g., different SF), there was more suppression when attention was directed to the feature dimension that matched between center and surround than when attention was directed to the feature dimension that differed. These results demonstrate that feature-based attention can influence center-surround interactions by enhancing the effects of the attended dimension.

Short-term retention of visual information: Evidence in support of feature-based attention as an underlying mechanism

Retention of features in visual short-term memory (VSTM) involves maintenance of sensory traces in early visual cortex. However, the mechanism through which this is accomplished is not known. Here, we formulate specific hypotheses derived from studies on feature-based attention to test the prediction that visual cortex is recruited by attentional mechanisms during VSTM of low-level features. Functional magnetic resonance imaging (fMRI) of human visual areas revealed that neural populations coding for task-irrelevant feature information are suppressed during maintenance of detailed spatial frequency memory representations. The narrow spectral extent of this suppression agrees well with known effects of feature-based attention. Additionally, analyses of effective connectivity during maintenance between retinotopic areas in visual cortex show that the observed highlighting of task-relevant parts of the feature spectrum originates in V4, a visual area strongly connected with higher-level control regions and known to convey top–down influence to earlier visual areas during attentional tasks. In line with this property of V4 during attentional operations, we demonstrate that modulations of earlier visual areas during memory maintenance have behavioral consequences, and that these modulations are a result of influences from V4.

Suppressive effects of feature-based attention to motion and orientation

Suppressive effects of feature-based attention to motion and orientation

Feature-based attentional modulation of orientation perception in somatosensation.

In a reaction time study of human tactile orientation detection the effects of spatial attention and feature-based attention were investigated. Subjects had to give speeded responses to target orientations (parallel and orthogonal to the finger axis) in a random stream of oblique tactile distractor orientations presented to their index and ring fingers. Before each block of trials, subjects received a tactile cue at one finger. By manipulating the validity of this cue with respect to its location and orientation (feature), we provided an incentive to subjects to attend spatially to the cued location and only there to the cued orientation. Subjects showed quicker responses to parallel compared to orthogonal targets, pointing to an orientation anisotropy in sensory processing. Also, faster reaction times (RTs) were observed in location-matched trials, i.e., when targets appeared on the cued finger, representing a perceptual benefit of spatial attention. Most importantly, RTs were shorter to orientations matching the cue, both at the cued and at the uncued location, documenting a global enhancement of tactile sensation by feature-based attention. This is the first report of a perceptual benefit of feature-based attention outside the spatial focus of attention in somatosensory perception. The similarity to effects of feature-based attention in visual perception supports the notion of matching attentional mechanisms across sensory domains.

Effects of feature-based attention on voxel tuning curves for individual faces

Effects of feature-based attention on voxel tuning curves for individual faces

Similar Effects of Feature-Based Attention on Motion Perception and Pursuit Eye Movements at Different Levels of Awareness

Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth-pursuit eye movements in response to moving dichoptic plaids--stimuli composed of two orthogonally drifting gratings, presented separately to each eye--in human observers. Monocular adaptation to one grating before the presentation of both gratings renders the adapted grating perceptually weaker than the unadapted grating and decreases the level of awareness. Feature-based attention was directed to either the adapted or the unadapted grating's motion direction or to both (neutral condition). We show that observers were better at detecting a speed change in the attended than the unattended motion direction, indicating that they had successfully attended to one grating. Speed change detection was also better when the change occurred in the unadapted than the adapted grating, indicating that the adapted grating was perceptually weaker. In neutral conditions, perception and pursuit in response to plaid motion were dissociated: While perception followed one grating's motion direction almost exclusively (component motion), the eyes tracked the average of both gratings (pattern motion). In attention conditions, perception and pursuit were shifted toward the attended component. These results suggest that attention affects perception and pursuit similarly even though only the former reflects awareness. The eyes can track an attended feature even if observers do not perceive it.

A dynamical neural simulation mapping feature-based attention to location with non-linear cortical circuits

Visual attention mechanisms allow the visual cortex todirect cortical processing to salient locations within avisual scene, at the expense of diminished processing ofstimuli at other locations. The deployment of attentionto a given location is known as spatial attention.Attention may also be applied to a known feature in avisual scene, such as a colour or shape, enhancing itsoccurrences across the visual field. In [1], a model ofbinding distributed feature representations throughfeature-based attention predicted that attentional feed-back would act in all positions of the visual scene in lowlevel visual areas. There is now experimental evidencethat this mechanism exists [2].We present here a neural dynamical model of feature-based attention that directs attention to salient locationsinamulti-objectscenethrough interaction of stimulusdriven and cue driven neural activation. This interactionis managed by a disinhibition circuit gating output to aretinotopic neural region of the dorsal stream, thelateral intraparietal area (LIP). When visual stimuli arepresented to primary visual cortex (V1), neural activa-tion spreads into higher ventral stream areas throughincreasing neural receptive fields between layers.Stimulus driven neurons activate excitatory output andinhibitory interneuron populations in the disinhbitioncircuit. When a salient feature is cued by activation ofits associated anterior inferotemporal (AIT) neuronalpopulation, neural activity propagates to lower visualareas across all locations of the visual field. Activity inthis top-down flow inhibits the inhibitory interneuronpopulation allowing excitatory output from the disinhi-bition circuit to LIP in a retinotopic manner whereactivity is correlated in the stimulus and cue drivenpathways. In areas where the two pathways do notmatch, local inhibition in the disinhibition layer preventsneighbouring circuits’ excitatory populations from out-putting to LIP.The model exhibits effects of feature-based attention,such as the feature similarity gain principle and biasedcompetition through interactions of stimulus and cueinitiated neural activity. The dynamical nature of themodel as neural populations of Wilson-Cowan differen-tial equations allows the time-course of neural activityto be investigated.ConclusionsAlthough originally designed as a model for binding, themodel replicates the experimental correlates of feature-based attention, which strongly suggests its functionalrole is actually binding An important prediction of themodel is that local non-matches between cue andstimulus are the most important information projectedfrom the ventral to the dorsal stream and that this inter-action is highly non-linear. We present candidates forneural circuits implementing this interaction.