Reliably Measuring Learning-Dependent Distractor Suppression with Eye Tracking

In the field of psychological science, behavioral performance in computer-based cognitive tasks often exhibits poor reliability. The absence of reliable measures of cognitive processes contributes to non-reproducibility in the field and impedes investigation of individual differences. Specifically in visual search paradigms, response time-based measures have shown poor test-retest reliability and internal consistency across attention capture and distractor suppression, but one study has demonstrated the potential for oculomotor measures to exhibit superior reliability. Therefore, in this study, we investigated three datasets to compare the reliability of learning-dependent distractor suppression measured via distractor fixations (oculomotor capture) and latency to fixate the target (fixation times). Our findings reveal superior split-half reliability of oculomotor capture compared to that of fixation times regardless of the critical distractor comparison, with the reliability of oculomotor capture in most cases falling within the range that is acceptable for the investigation of individual differences. We additionally find that older adults have superior oculomotor reliability compared with young adults, potentially addressing a significant limitation in the aging literature of high variability in response time measures due to slower responses. Our findings highlight the utility of measuring eye movements in the pursuit of reliable indicators of distractor processing and the need to further test and develop additional measures in other sensory domains to maximize statistical power, reliability, and reproducibility.

Pathway-selective optogenetics reveals the functional anatomy of top-down attentional modulation in the macaque visual cortex

Spatial attention represents a powerful top-down influence on sensory responses in primate visual cortical areas. The frontal eye field (FEF) has emerged as a key candidate area for the source of this modulation. However, it is unclear whether the FEF exerts its effects via its direct axonal projections to visual areas or indirectly through other brain areas and whether the FEF affects both the enhancement of attended and the suppression of unattended sensory responses. We used pathway-selective optogenetics in rhesus macaques performing a spatial attention task to inhibit the direct input from the FEF to area MT, an area along the dorsal visual pathway specialized for the processing of visual motion information. Our results show that the optogenetic inhibition of the FEF input specifically reduces attentional modulation in MT by about a third without affecting the neurons' sensory response component. We find that the direct FEF-to-MT pathway contributes to both the enhanced processing of target stimuli and the suppression of distractors. The FEF, thus, selectively modulates firing rates in visual area MT, and it does so via its direct axonal projections.

Little engagement of attention by salient distractors defined in a different dimension or modality to the visual search target

Singleton distractors may inadvertently capture attention, interfering with the task at hand. The underlying neural mechanisms of how we prevent or handle distractor interference remain elusive. Here, we varied the type of salient distractor introduced in a visual search task: the distractor could be defined in the same (shape) dimension as the target, a different (color) dimension, or a different (tactile) modality (intra-dimensional, cross-dimensional, and, respectively, cross-modal distractor, all matched for physical salience); and besides behavioral interference, we measured lateralized electrophysiological indicators of attentional selectivity (the N2pc, Ppc, PD , CCN/CCP, CDA, and cCDA). The results revealed the intra-dimensional distractor to produce the strongest reaction-time interference, associated with the smallest target-elicited N2pc. In contrast, the cross-dimensional and cross-modal distractors did not engender any significant interference, and the target-elicited N2pc was comparable to the condition in which the search display contained only the target singleton, thus ruling out early attentional capture. Moreover, the cross-modal distractor elicited a significant early CCN/CCP, but did not influence the target-elicited N2pc, suggesting that the tactile distractor is registered by the somatosensory system (rather than being proactively suppressed), without, however, engaging attention. Together, our findings indicate that, in contrast to distractors defined in the same dimension as the target, distractors singled out in a different dimension or modality can be effectively prevented to engage attention, consistent with dimension- or modality-weighting accounts of attentional priority computation.

Neurophysiological Measures of Proactive and Reactive Control in Negative Template Use

In a visual search task, knowing features of distractors in advance leads to a more efficient visual search. Although previous studies suggested that the benefits of these negative cues rely on attentional control, it is unclear whether proactive or reactive control is involved. In this study, we analyzed the EEG data of participants performing a visual search task (n = 14). Participants searched for a shape-defined target after receiving a positive cue (target color), negative cue (distractor color), or neutral cue (non-informative). To examine proactive control, we measured EEG after the cue onset but before visual search. Our time-frequency analysis revealed a higher power of theta oscillations over frontoparietal regions after the negative cues compared with the positive and neutral cues, as well as higher theta phase synchronization within the prefrontal region, demonstrating negative cues rely more heavily on proactive control compared with other cue types. To examine reactive control, we measured EEG after the search onset. We found a lateralization of posterior alpha power toward the target side in both positive and negative cues conditions, with a later lateralization observed after negative cues. Interestingly, we observed a significant relationship between the increase of proactive theta power after negative cues and the decrease of reactive alpha power after the search. This suggests the coordination of proactive and reactive mechanisms lead to the most efficient search.

Causal investigation of mid-frontal theta activity in memory guided visual search

Midfrontal theta activity is crucial for attentional and cognitive control. However, its causal role in facilitating visual search, particularly from the perspective of distractor inhibition, is yet to be discovered. We applied theta band transcranial alternate current stimulation (tACS) over frontocentral regions when participants searched for targets among heterogeneous distractors with foreknowledge of distractor features. The results demonstrated improved visual search performance in the theta stimulation group compared to the active sham group. Moreover, we observed the facilitation effect of the distractor cue only in participants who exhibited larger inhibition benefits, which further confirms the role of theta stimulation in precise attentional control. Taken together, our results provide compelling causal evidence for the involvement of midfrontal theta activity in memory-guided visual search.

Statistical Learning of Distractor Suppression Downregulates Prestimulus Neural Excitability in Early Visual Cortex

Visual attention is highly influenced by past experiences. Recent behavioral research has shown that expectations about the spatial location of distractors within a search array are implicitly learned, with expected distractors becoming less interfering. Little is known about the neural mechanism supporting this form of statistical learning. Here, we used magnetoencephalography (MEG) to measure human brain activity to test whether proactive mechanisms are involved in the statistical learning of distractor locations. Specifically, we used a new technique called rapid invisible frequency tagging (RIFT) to assess neural excitability in early visual cortex during statistical learning of distractor suppression while concurrently investigating the modulation of posterior alpha band activity (8-12 Hz). Male and female human participants performed a visual search task in which a target was occasionally presented alongside a color-singleton distractor. Unbeknown to the participants, the distracting stimuli were presented with different probabilities across the two hemifields. RIFT analysis showed that early visual cortex exhibited reduced neural excitability in the prestimulus interval at retinotopic locations associated with higher distractor probabilities. In contrast, we did not find any evidence of expectation-driven distractor suppression in alpha band activity. These findings indicate that proactive mechanisms of attention are involved in predictive distractor suppression and that these mechanisms are associated with altered neural excitability in early visual cortex. Moreover, our findings indicate that RIFT and alpha band activity might subtend different and possibly independent attentional mechanisms.SIGNIFICANCE STATEMENT What we experienced in the past affects how we perceive the external world in the future. For example, an annoying flashing light might be better ignored if we know in advance where it usually appears. This ability of extracting regularities from the environment is called statistical learning. In this study, we explore the neuronal mechanisms allowing the attentional system to overlook items that are unequivocally distracting based on their spatial distribution. By recording brain activity using MEG while probing neural excitability with a novel technique called RIFT, we show that the neuronal excitability in early visual cortex is reduced in advance of stimulus presentation for locations where distracting items are more likely to occur.

What to expect where and when: how statistical learning drives visual selection

While the visual environment contains massive amounts of information, we should not and cannot pay attention to all events. Instead, we need to direct attention to those events that have proven to be important in the past and suppress those that were distracting and irrelevant. Experiences molded through a learning process enable us to extract and adapt to the statistical regularities in the world. While previous studies have shown that visual statistical learning (VSL) is critical for representing higher order units of perception, here we review the role of VSL in attentional selection. Evidence suggests that through VSL, attentional priority settings are optimally adjusted to regularities in the environment, without intention and without conscious awareness.

Electrophysiological Evidence for Target Facilitation Without Distractor Suppression in Two-Stimulus Search Displays

This study used electrophysiological measures to investigate how attention is deployed to target and distractor stimuli during visual search using search displays with a small set-size. Participants viewed randomized sequences of two-item displays that consisted of either a target and a distractor (differing in color) or a pair of task-irrelevant filler stimuli having a third color, all presented in an ongoing stream of flickering gray circles. The allocation of attention was assessed by concurrent recordings of steady-state visual evoked potentials (SSVEPs) elicited by the flickering displays and perturbations of the endogenous alpha rhythm following each type of display. The aim was to test a central prediction of the signal suppression hypothesis, namely that the processing of distractors will be proactively suppressed below the level of filler stimuli. Amplitude modulations of both the SSVEP and the lateralized alpha rhythm provided converging evidence against early proactive suppression of highly salient distractors. Instead, these electrophysiological measures were consistent with the view that in this type of two-stimulus search task there is an initial capture of attention by all color-change stimuli (targets, distractors, and fillers) followed by a further focusing of attention upon the target, with no evidence for suppression of the distractor.

Prefrontal Control of Proactive and Reactive Mechanisms of Visual Suppression

In everyday life, we are continuously struggling at focusing on our current goals while at the same time avoiding distractions. Attention is the neuro-cognitive process devoted to the selection of behaviorally relevant sensory information while at the same time preventing distraction by irrelevant information. Distraction can be prevented proactively, by strategically prioritizing task-relevant information at the expense of irrelevant information, or reactively, by suppressing the ongoing processing of distractors. The distinctive neuronal signature of these suppressive mechanisms is still largely unknown. Thanks to machine-learning decoding methods applied to prefrontal cortical activity, we monitor the dynamic spatial attention with an unprecedented spatial and temporal resolution. We first identify independent behavioral and neuronal signatures for long-term (learning-based spatial prioritization) and short-term (dynamic spatial attention) mechanisms. We then identify distinct behavioral and neuronal signatures for proactive and reactive suppression mechanisms. We find that while distracting task-relevant information is suppressed proactively, task-irrelevant information is suppressed reactively. Critically, we show that distractor suppression, whether proactive or reactive, strongly depends on the implementation of both long-term and short-term mechanisms of selection. Overall, we provide a unified neuro-cognitive framework describing how the prefrontal cortex deals with distractors in order to flexibly optimize behavior in dynamic environments.

Statistical Learning of Frequent Distractor Locations in Visual Search Involves Regional Signal Suppression in Early Visual Cortex

Observers can learn locations where salient distractors appear frequently to reduce potential interference-an effect attributed to better suppression of distractors at frequent locations. But how distractor suppression is implemented in the visual cortex and within the frontoparietal attention networks remains unclear. We used fMRI and a regional distractor-location learning paradigm with two types of distractors defined in either the same (orientation) or a different (color) dimension to the target to investigate this issue. fMRI results showed that BOLD signals in early visual cortex were significantly reduced for distractors (as well as targets) occurring at the frequent versus rare locations, mirroring behavioral patterns. This reduction was more robust with same-dimension distractors. Crucially, behavioral interference was correlated with distractor-evoked visual activity only for same- (but not different-) dimension distractors. Moreover, with different- (but not same-) dimension distractors, a color-processing area within the fusiform gyrus was activated more when a distractor was present in the rare region versus being absent and more with a distractor in the rare versus frequent locations. These results support statistical learning of frequent distractor locations involving regional suppression in early visual cortex and point to differential neural mechanisms of distractor handling with different- versus same-dimension distractors.

Strategic Distractor Suppression Improves Selective Control in Human Vision

Our visual environment is complicated, and our cognitive capacity is limited. As a result, we must strategically ignore some stimuli to prioritize others. Common sense suggests that foreknowledge of distractor characteristics, like location or color, might help us ignore these objects. But empirical studies have provided mixed evidence, often showing that knowing about a distractor before it appears counterintuitively leads to its attentional selection. What has looked like strategic distractor suppression in the past is now commonly explained as a product of prior experience and implicit statistical learning, and the long-standing notion the distractor suppression is reflected in α band oscillatory brain activity has been challenged by results appearing to link α to target resolution. Can we strategically, proactively suppress distractors? And, if so, does this involve α? Here, we use the concurrent recording of human EEG and eye movements in optimized experimental designs to identify behavior and brain activity associated with proactive distractor suppression. Results from three experiments show that knowing about distractors before they appear causes a reduction in electrophysiological indices of covert attentional selection of these objects and a reduction in the overt deployment of the eyes to the location of the objects. This control is established before the distractor appears and is predicted by the power of cue-elicited α activity over the visual cortex. Foreknowledge of distractor characteristics therefore leads to improved selective control, and α oscillations in visual cortex reflect the implementation of this strategic, proactive mechanism.SIGNIFICANCE STATEMENT To behave adaptively and achieve goals we often need to ignore visual distraction. Is it easier to ignore distracting objects when we know more about them? We recorded eye movements and electrical brain activity to determine whether foreknowledge of distractor characteristics can be used to limit processing of these objects. Results show that knowing the location or color of a distractor stops us from attentionally selecting it. A neural signature of this inhibition emerges in oscillatory alpha band brain activity, and when this signal is strong, selective processing of the distractor decreases. Knowing about the characteristics of task-irrelevant distractors therefore increases our ability to focus on task-relevant information, in this way gating information processing in the brain.

Classic Visual Search Effects in an Additional Singleton Task: An Open Dataset

Visual search refers to our ability to find what we are looking for among many competing visual inputs. Here, we report the availability of a rich dataset that replicates key visual search effects and shows that these effects are robust to several changes to the experimental design. Experiment 1 replicates classic findings from an additional singleton visual search task. First, participants are captured by a salient but irrelevant color singleton, as indexed by slower response times when a color singleton distractor is present versus absent. Second, attentional capture by a color singleton is reduced when the visual search array contains heterogeneous shapes rather than homogenous shapes. Finally, attentional capture by a color singleton is reduced when the display colors are repeated rather than switched unpredictably from trial to trial. Experiment 2 demonstrates that these classic visual search effects are robust to small procedural changes such as task timing (i.e., a 2-8 second rather than ~1 second inter-trial interval). Experiment 3 demonstrates that these classic effects are likewise robust to changes to the distractor frequency (75% rather than 50%) and to fully blocking versus interleaving blocks of two task conditions. All told, this dataset includes 8 sub-experiments, 190 participants and >210,000 trials, and it will serve as a useful resource for power analyses and exploratory analyses of visual search behaviors.

Memory precision for salient distractors decreases with learned suppression

Attention operates as a cognitive gate that selects sensory information for entry into memory and awareness (Driver, 2001, British Journal of Psychology, 92, 53–78). Under many circumstances, the selected information is task-relevant and important to remember, but sometimes perceptually salient nontarget objects will capture attention and enter into awareness despite their irrelevance (Adams & Gaspelin, 2020, Attention, Perception, & Psychophysics, 82[4], 1586–1598). Recent studies have shown that repeated exposures with salient distractor will diminish their ability to capture attention, but the relationship between suppression and later cognitive processes such as memory and awareness remains unclear. If learned attentional suppression (indicated by reduced capture costs) occurs at the sensory level and prevents readout to other cognitive processes, one would expect memory and awareness to dimmish commensurate with improved suppression. Here, we test this hypothesis by measuring memory precision and awareness of salient nontargets over repeated exposures as capture costs decreased. Our results show that stronger learned suppression is accompanied by reductions in memory precision and confidence in having seen a color singleton at all, suggesting that such suppression operates at the sensory level to prevent further processing of the distractor object.

Target enhancement or distractor suppression? Functionally distinct alpha oscillations form the basis of attention

Recent advances in attention research have been propelled by the debate on target enhancement versus distractor suppression. A predominant neural correlate of attention is the modulation of alpha oscillatory power (~10 Hz), which signifies shifts of attention in time, space and between sensory modalities. However, the underspecified functional role of alpha oscillations limits the progress of tracking down the neurocognitive basis of attention. In this short opinion article, we review and critically examine a synthesis of three conceptual and methodological aspects that are indispensable for a mechanistic understanding of the role of alpha oscillations for attention. (a) Precise mapping of the anatomical source and the temporal response profile of neural signals reveals distinct alpha oscillatory processes that implement facilitatory versus suppressive components of attention. (b) A testable framework enables unanimous association of alpha modulation with either target enhancement or different forms of distractor suppression (active vs. automatic). (c) Linking anatomically specified alpha oscillations to behavior reveals the causal nature of alpha oscillations for attention. The three reviewed aspects substantially enrich study design, data analysis and interpretation of results to achieve the goal of understanding how anatomically specified and functionally relevant neural oscillations contribute to the implementation of facilitatory versus suppressive components of attention.

Transcranial magnetic stimulation over the right dorsolateral prefrontal cortex modulates visuospatial distractor suppression

Visual selective attention allows us to filter relevant inputs from irrelevant inputs during visual processing. In contrast to rich research exploring how the brain facilitates task‐relevant inputs, less is known about how the brain suppresses irrelevant inputs. In this study, we used transcranial magnetic stimulation (TMS) to investigate the causal role of the right dorsolateral prefrontal cortex (DLPFC), a crucial brain area for attentional control, in distractor suppression. Specifically, 10‐Hz repetitive TMS (rTMS) was applied to the right DLPFC and Vertex at the stimuli onset (stimuli‐onset TMS) or 500 ms prior to the stimuli onset (prestimuli TMS). In a variant of the Posner cueing task, participants were instructed to identify the shape of a white target while ignoring a white or colored distractor whose location was either cued in advance or uncued. As anticipated, either the location cue or the colored distractor led to faster responses. Notably, the location cueing effect was eliminated by stimuli‐onset TMS to the right DLPFC, but not by prestimuli TMS. Further analyses showed that stimuli‐onset TMS quickened responses to uncued trials, and this TMS effect was derived from the inhibition at the distractor in both visual fields. In addition, TMS over the right DLPFC had no specific effect on the colored distractor compared to the white one. Considered collectively, these findings indicate that the DLPFC plays a crucial role in visuospatial distractor suppression and acts upon stimuli presentation. Besides, it seems the DLPFC contributes more to location‐based distractor suppression than to color‐based one.

Passive exposure attenuates distraction during visual search

Distractions are ubiquitous in our sensory environments. How do we keep them from capturing attention? Existing research has focused primarily on mechanisms of strategic control or statistical learning, both of which require knowledge (explicit or implicit) of what features belong to distractors before suppression occurs. Here, we test the hypothesis that task-free exposure to stimuli is sufficient to attenuate their effect as distractors later on. In 3 experiments, subjects were exposed to either colored or achromatic circles on "circle displays" interleaved with "target search displays." Later, new distractors were introduced into the search displays using colors from the circle displays. We consistently found that passively viewed colors produced less interference when introduced as new visual search distractors. We conclude that learning during passive exposure was due to habituation mechanisms that attenuate sensory responsivity to recurring stimuli, allowing attention to operate more efficiently to select task-relevant targets or novel stimuli. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The same, but different: Preserved distractor suppression in old age is implemented through an age-specific reactive ventral fronto-parietal network

Previous studies have shown age-related impairments in the ability to suppress salient distractors. One possibility is that this is mediated by age-related impairments in the recruitment of the left intraparietal sulcus (Left IPS), which has been shown to mediate the suppression of salient distractors in healthy, young participants. Alternatively, this effect may be due to a shift in engagement from proactive control to reactive control, possibly to compensate for age-related impairments in proactive control. Another possibility is that this is due to changes in the functional specificity of brain regions that mediate salience suppression, expressed in changes in spontaneous connectivity of these regions. We assessed these possibilities by having participants engage in a proactive distractor suppression task while in an fMRI scanner. Although we did not find any age-related differences in behavior, the young (N = 15) and older (N = 15) cohorts engaged qualitatively distinctive brain networks to complete the task. Younger participants engaged the predicted proactive control network, including the Left IPS. On the other hand, older participants simultaneously engaged both a proactive and a reactive network, but this was not a consequence of reduced network specificity as resting state functional connectivity was largely comparable in both age groups. Furthermore, improved behavioral performance for older adults was associated with increased resting state functional connectivity between these two networks. Overall, the results of this study suggest that age-related differences in the recruitment of a left lateralized ventral fronto-parietal network likely reflect the specific recruitment of reactive control mechanisms for distractor inhibition.

Specificity and persistence of statistical learning in distractor suppression

Statistical regularities in distractor location trigger suppression of high-probability distractor locations during visual search. The degree to which such suppression reflects generalizable, persistent changes in a spatial priority map has not been examined. We demonstrate that suppression of high-probability distractor locations persists after location probabilities are equalized and likely reflects a genuine reshaping of the priority map rather than more transient effects of selection history. Statistically learned suppression generalizes across contexts within a task during learning but does not generalize between task paradigms using unrelated stimuli in identical spatial locations. These findings suggest that stimulus features do play a role in learned spatial suppression, potentially gating the weights applied to a spatial priority map. However, the binding of location to context during learning is not automatic, in contrast to the previously reported interaction of location-based statistical learning and stimulus features. (PsycINFO Database Record (c) 2020 APA, all rights reserved).