scholarly journals Neural mechanisms underlying distractor inhibition on the basis of feature and/or spatial expectations

2020 ◽  
Author(s):  
Dirk van Moorselaar ◽  
Nasim Daneshtalab ◽  
Heleen A. Slagter
Keyword(s):  
Statistical Learning ◽  
Neural Mechanisms ◽  
Large Individual ◽  
Distractor Location ◽  
Distractor Inhibition ◽  
Sensory Suppression ◽  
Distractor Processing ◽  
Intertrial Priming ◽  
Feature Based ◽  
Band Activity

AbstractA rapidly growing body of research indicates that inhibition of distracting information may not be under flexible, top-down control, but instead heavily relies on expectations derived from past experience about the likelihood of events. Yet, how expectations about distracting information influence distractor inhibition at the neural level remains unclear. To determine how expectations induced by distractor features and/or location regularities modulate distractor processing, we measured EEG while participants performed two variants of the additional singleton paradigm. Critically, in these different variants, target and distractor features either randomly swapped across trials, or were fixed, allowing for the development of distractor feature-based expectations. Moreover, the task was initially performed without any spatial regularities, after which a high probability distractor location was introduced. Our results show that both distractor feature- and location regularities contributed to distractor inhibition, as indicated by corresponding reductions in distractor costs during visual search and an earlier distractor-evoked Pd ERP. Yet, control analyses showed that while observers were sensitive to regularities across longer time scales, the observed effects to a large extent reflected intertrial repetition. Large individual differences further suggest a functional dissociation between early and late Pd components, with the former reflecting early sensory suppression related to intertrial priming and the latter reflecting suppression sensitive to expectations derived over a longer time scale. Also, counter to some previous findings, no increase in anticipatory alpha-band activity was observed over visual regions representing the expected distractor location, although this effect should be interpreted with caution as the effect of spatial statistical learning was also less pronounced than in other studies. Together, these findings suggest that intertrial priming and statistical learning may both contribute to distractor suppression and reveal the underlying neural mechanisms.

scholarly journals Learning what is irrelevant or relevant: Expectations facilitate distractor inhibition and target facilitation through distinct neural mechanisms

2019 ◽  
Author(s):  
Dirk van Moorselaar ◽  
Heleen A. Slagter
Keyword(s):  
Target Location ◽  
Response Times ◽  
Relevant Information ◽  
Distractor Location ◽  
Distractor Inhibition ◽  
Distractor Processing ◽  
Behavioral Studies ◽  
Outstanding Question ◽  
Target Locations ◽  
The Brain

AbstractIt is well known that attention can facilitate performance by top-down biasing processing of task-relevant information in advance. Recent findings from behavioral studies suggest that distractor inhibition is not under similar direct control, but strongly dependent on expectations derived from previous experience. Yet, how expectations about distracting information influence distractor inhibition at the neural level remains unclear. The current study addressed this outstanding question in three experiments in which search displays with repeating distractor or target locations across trials allowed observers to learn which location to selectively suppress or boost. Behavioral findings demonstrated that both distractor and target location learning resulted in more efficient search, as indexed by faster response times. Crucially, benefits of distractor learning were observed without target location foreknowledge, unaffected by the number of possible target locations, and could not be explained by priming alone. To determine how distractor location expectations facilitated performance, we applied a spatial encoding model to EEG data to reconstruct activity in neural populations tuned to the distractor or target location. Target location learning increased neural tuning to the target location in advance, indicative of preparatory biasing. This sensitivity increased after target presentation. By contrast, distractor expectations did not change preparatory spatial tuning. Instead, distractor expectations reduced distractor-specific processing, as reflected in the disappearance of the Pd ERP component, a neural marker of distractor inhibition, and decreased decoding accuracy. These findings suggest that the brain may no longer process expected distractors as distractors, once it has learned they can safely be ignored.Significance statementWe constantly try hard to ignore conspicuous events that distract us from our current goals. Surprisingly, and in contrast to dominant attention theories, ignoring distracting, but irrelevant events does not seem to be as flexible as is focusing our attention on those same aspects. Instead, distractor suppression appears to strongly rely on learned, context-dependent expectations. Here, we investigated how learning about upcoming distractors changes distractor processing and directly contrasted the underlying neural dynamics to target learning. We show that while target learning enhanced anticipatory sensory tuning, distractor learning only modulated reactive suppressive processing. These results suggest that expected distractors may no longer be considered distractors by the brain once it has learned that they can safely be ignored.

scholarly journals Statistical learning of frequent distractor locations in visual search involves regional signal suppression in early visual cortex

2021 ◽  
Author(s):  
Bei Zhang ◽  
Ralph Weidner ◽  
Fredrik Allenmark ◽  
Sabine Bertleff ◽  
Gereon R. Fink ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Visual Search ◽  
Statistical Learning ◽  
Neural Mechanisms ◽  
Learning Paradigm ◽  
Distractor Location ◽  
Attention Networks ◽  
Signal Suppression ◽  
Behavioural Patterns ◽  
Early Visual Cortex

Observers can learn the 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 frontoparietal attention networks remains unclear. We used fMRI and a regional distractor-location learning paradigm (Sauter et al. 2018, 2020) with two types of distractors defined in either the same (orientation) or a different (colour) 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 behavioural patterns. This reduction was more robust with same-dimension distractors. Crucially, behavioural 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 colour-processing area within the fusiform gyrus was activated more when a colour distractor was present versus absent and with a distractor occurring at a rare versus frequent location. These results support statistical learning of frequent distractor locations involving regional suppression in the early visual cortex and point to differential neural mechanisms of distractor handling with different- versus same-dimension distractors.

scholarly journals Statistical regularities cause attentional suppression with target-matching distractors

2020 ◽  
Author(s):  
Dirk Kerzel ◽  
Stanislas Huynh Cong
Keyword(s):  
High Frequency ◽  
Target Location ◽  
Low Frequency ◽  
Target Display ◽  
Distractor Location ◽  
Target Feature ◽  
Statistical Regularities ◽  
Feature Based ◽  
The Impact ◽  
Target Matching

AbstractVisual search may be disrupted by the presentation of salient, but irrelevant stimuli. To reduce the impact of salient distractors, attention may suppress their processing below baseline level. While there are many studies on the attentional suppression of distractors with features distinct from the target (e.g., a color distractor with a shape target), there is little and inconsistent evidence for attentional suppression with distractors sharing the target feature. In this study, distractor and target were temporally separated in a cue–target paradigm, where the cue was shown briefly before the target display. With target-matching cues, RTs were shorter when the cue appeared at the target location (valid cues) compared with when it appeared at a nontarget location (invalid cues). To induce attentional suppression, we presented the cue more frequently at one out of four possible target positions. We found that invalid cues appearing at the high-frequency cue position produced less interference than invalid cues appearing at a low-frequency cue position. Crucially, target processing was also impaired at the high-frequency cue position, providing strong evidence for attentional suppression of the cued location. Overall, attentional suppression of the frequent distractor location could be established through feature-based attention, suggesting that feature-based attention may guide attentional suppression just as it guides attentional enhancement.

scholarly journals Capacities and neural mechanisms for auditory statistical learning across species

2019 ◽  
Vol 376 ◽  
pp. 97-110 ◽  
Author(s):  
Jennifer K. Schiavo ◽  
Robert C. Froemke
Keyword(s):  
Statistical Learning ◽  
Neural Mechanisms

scholarly journals Functional Localization of an Attenuating Filter within Cortex for a Selective Detection Task in Mice

2020 ◽  
Author(s):  
Krithiga Aruljothi ◽  
Krista Marrero ◽  
Zhaoran Zhang ◽  
Behzad Zareian ◽  
Edward Zagha
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Selection Process ◽  
Detection Task ◽  
Neural Mechanisms ◽  
Selective Detection ◽  
Strong Signal ◽  
Distractor Processing ◽  
Goal Directed Behavior ◽  
Signal Activation

AbstractAn essential feature of goal-directed behavior is the ability to selectively respond to the diverse stimuli in one’s environment. However, the neural mechanisms that enable us to respond to target stimuli while ignoring distractor stimuli are poorly understood. To study this sensory selection process, we trained male and female mice in a selective detection task in which mice learn to respond to rapid stimuli in the target whisker field and ignore identical stimuli in the opposite, distractor whisker field. In expert mice, we used widefield Ca2+ imaging to analyze target-related and distractor-related neural responses throughout dorsal cortex. For target stimuli, we observed strong signal activation in primary somatosensory cortex (S1) and frontal cortices, including both the whisker representation of primary motor cortex (wMC) and anterior lateral motor cortex (ALM). For distractor stimuli, we observe strong signal activation in S1, with minimal propagation to frontal cortex. Our data support only modest subcortical filtering, with robust, step-like attenuation in distractor processing between mono-synaptically coupled regions of S1 and wMC. This study establishes a highly robust model system for studying the neural mechanisms of sensory selection and places important constraints on its implementation.SummaryResponding to task-relevant stimuli while ignoring task-irrelevant stimuli is critical for goal-directed behavior. Yet, the neural mechanisms involved in this selection process are poorly understood. We trained mice in a detection task with both target and distractor stimuli. During expert performance, we measured neural activity throughout cortex using widefield imaging. We observed responses to target stimuli in multiple sensory and motor cortical regions. In contrast, responses to distractor stimuli were abruptly suppressed beyond sensory cortex. Our findings localize the sites of attenuation when successfully ignoring a distractor stimulus, and provide essential foundations for further revealing the neural mechanism of sensory selection and distractor suppression.

scholarly journals Global Effects of Feature-based Attention Depend on Surprise

2019 ◽  
Author(s):  
Cooper A. Smout ◽  
Marta I. Garrido ◽  
Jason B. Mattingley
Keyword(s):  
Sensory Information ◽  
Focus Of Attention ◽  
Neural Mechanisms ◽  
Visual Modality ◽  
Recent Theory ◽  
Prediction Errors ◽  
Neural Responses ◽  
Attention Task ◽  
Feature Based ◽  
Task Irrelevant

AbstractRecent 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 the idea that attention optimises the precision of predictions by modulating the gain of prediction errors.Significance StatementTwo principal mechanisms facilitate the efficient processing of sensory information: prediction uses prior information to guide the interpretation of sensory events, whereas attention biases the processing of these events according to their behavioural relevance. A recent theory proposes to reconcile attention and prediction under a unifying framework, casting attention as a ‘precision optimisation’ mechanism that enhances the gain of prediction errors. Crucially, this theory suggests that attention and prediction interact to modulate neural responses, but this hypothesis remains to be tested with respect to feature-based attention mechanisms outside the spatial focus of attention. Here we show that global effects of feature-based attention are enhanced when stimuli possess surprising features, suggesting that feature-based attention and prediction are interdependent neural mechanisms.

scholarly journals Right inferior frontal gyrus implements motor inhibitory control via beta-band oscillations in humans

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Michael Schaum ◽  
Edoardo Pinzuti ◽  
Alexandra Sebastian ◽  
Klaus Lieb ◽  
Pascal Fries ◽  
...  
Keyword(s):  
Inhibitory Control ◽  
Response Inhibition ◽  
Supplementary Motor Area ◽  
Inferior Frontal Gyrus ◽  
Neural Mechanisms ◽  
Beta Band ◽  
Changing Environments ◽  
Band Power ◽  
The Right ◽  
Band Activity

Motor inhibitory control implemented as response inhibition is an essential cognitive function required to dynamically adapt to rapidly changing environments. Despite over a decade of research on the neural mechanisms of response inhibition, it remains unclear, how exactly response inhibition is initiated and implemented. Using a multimodal MEG/fMRI approach in 59 subjects, our results reliably reveal that response inhibition is initiated by the right inferior frontal gyrus (rIFG) as a form of attention-independent top-down control that involves the modulation of beta-band activity. Furthermore, stopping performance was predicted by beta-band power, and beta-band connectivity was directed from rIFG to pre-supplementary motor area (pre-SMA), indicating rIFG’s dominance over pre-SMA. Thus, these results strongly support the hypothesis that rIFG initiates stopping, implemented by beta-band oscillations with potential to open up new ways of spatially localized oscillation-based interventions.

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