Biology subjects

Allenmark, F.

Publications and source records attributed to Allenmark, F..

11 recordsLinked to original sources

bioRxiv2026

Environmental Volatility Shifts Visual Search from Capture to Caution

Real-world distractors occur in environments whose states change at different rates. We asked whether such volatility alters early attentional gating or instead changes the criterion for committing to a response. Observers performed an additional-singleton search task with concurrent eye tracking while distractor presence followed high- or low-volatility sequences, with overall distractor prevalence held constant. Trial-pooled oculomotor capture was higher under high volatility, a pattern that appears to indicate altered filtering. That inference did not survive repetition-aware analysis: once the same-location run position was matched, capture did not detectably differ across volatility regimes. The pooled capture effect was therefore consistent with a structural consequence of the volatility manipulation, which enriched high-volatility blocks with early-run positions where capture is intrinsically high. The positive volatility signature appeared on distractor-absent trials, where high-volatility blocks were associated with longer target latency, more fixations, longer final-target dwell, and fewer errors. Same-location repetition learning showed no detectable difference in slope across regimes. A hierarchical drift-diffusion model (DDM) and a complementary volatility Kalman-filter (VKF) dynamic-state comparison indicated that manual responses were better described by architectures that allow both boundary-related and drift-related components than by a boundary-only account. Volatility, therefore, did not show detectable evidence of impairing the local gating rule; instead, the converging evidence points to a post-selective verification/caution profile, consistent with a precision-weighted read-out of environmental uncertainty.

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bioRxiv2026

Pre-stimulus Cortical State Modulates Dimension-Specific Attentional Capture

Suppressing visual distraction depends on observers goals and learning, but also on the brain state in which the next display arrives. We reanalyzed an fMRI visual-search dataset (N = 34) to ask whether pre-stimulus global signal (GS), a broad state-sensitive BOLD measure, predicts performance and attention-network engagement during learned distractor suppression. Participants searched for an orientation target while ignoring salient distractors defined in the same orientation dimension or a different color dimension; across groups, spatial regularities were assigned to same- or different-dimension distractors. Behavioral and fMRI contrasts reproduced the expected functional architecture: same-dimension distractors slowed responses and recruited a frontoparietal capture-related network, whereas different-dimension distractors produced little interference. Learned spatial suppression was clearest for same-dimension distractors, which produced larger costs and stronger visual and frontoparietal responses in the rare than frequent region. Within this architecture, GS predicted performance in opposite directions across learning contexts: higher GS preceded slower responses when same-dimension distractors carried the spatial regularity, but faster responses when different-dimension distractors did. Higher GS also preceded weaker same-dimension distractor-evoked frontoparietal activation, without a reliable group difference in that neural effect. Default-mode-network activity showed the same behavioral pattern as GS, whereas pupil size showed weaker group-level convergence and its RT slopes did not correlate with GS-RT slopes across participants. Learned distractor suppression therefore appears embedded in a broader state-performance mapping, linking pre-stimulus cortical state to how learned priority settings guide the next trial.

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bioRxiv2024

Distractor-response binding influences visual search

Intertrial priming effects in visual search and action control suggest the involvement of binding and retrieval processes. However, the role of distractor-response binding (DRB) in visual search has been largely overlooked, and the specific processing stage within the functional architecture of attentional guidance where the DRB occurs remains unclear. To address these gaps, we implemented two search tasks, where participants responded based on a separate feature from the one defining the target. We kept the target dimension consistent across trials while varying the color and shape of the distractor. Moreover, we either repeated or randomized the target position in different sessions. Our results revealed a pronounced response priming, a difference between trials where the response changed vs. repeated: they were stronger when distractor features or the target position were repeated than they varied. Furthermore, the distractor feature priming, a difference between the distractor features repetition and switch, was contingent on the target position, suggesting that DRB likely operates at late stages of target identification and response selection. These insights affirm the presence of DRB during visual search and support the framework of binding and retrieval in action control as a basis for observed intertrial priming effects related to distractor features. Public significance statementThis study investigated inter-trial effects within visual search tasks and uncovered significant evidence for the role of distractor-response binding. This phenomenon involves linking a response in a given trial to the perceptual features (e.g. color and shape) of non-target items. Crucially, the study revealed that this distractor-response binding effect depends on whether the target location is repeated nearly repeated, suggesting that the retrieval of a previous response occurs at the later stages of target identification or response selection, even though non-target features likely are identified at an earlier stage.

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bioRxiv2023

Learning regular cross-trial shifts of the target location in serial search involves awareness: an eye-tracking study

People can learn, and utilize, not only static but also dynamic (cross-trial) regularities in the positioning of target items in parallel, pop-out visual search. However, while static target-location learning also works in serial search, acquiring dynamic regularities seems prevented by the demands imposed by item-by-item scanning. Also, questions have been raised regarding a role of explicit awareness for utilizing (at least) dynamic regularities to optimize performance. The present study re-investigated whether dynamic regularities may be learned in serial search when regular shifts of the target location occur frequently, and whether such learning would correlate with awareness of the dynamic rule. To this end, we adopted the same regularity used by Yu et al. (2023) to demonstrate dynamic learning in parallel search: a cross-trial shift of the target location in, e.g., clockwise direction within a circular array in 80% of the trials, which was compared to irregular shifts in the opposite (e.g., counterclockwise; 10%) or some other, random direction (10%). The results showed that [2/3] of participants learned the dynamic regularity, with their performance gains correlating with awareness: the more accurately they estimated how likely the target shifted in the frequent direction, the greater their gains. Importantly, part of the gains accrued already early during search: a large proportion of the very first and short-latency eye movements was directed to the predicted location, whether or not the target appeared there. We discuss whether this rule-driven behavior is causally mediated by conscious control. (248 words).

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bioRxiv2022

Asymmetric learning of dynamic spatial regularities in visual search: facilitation of anticipated target locations, no suppression of predictable distractor locations

Static statistical regularities in the placement of targets and salient distractors within the search display can be learned and used to optimize attentional guidance. Whether statistical learning also extends to dynamic regularities governing the placement of targets and distractors on successive trials has been less investigated. Here, we applied the same dynamic cross-trial regularity (one-step shift of the critical item in clock-/counterclockwise direction) either to the target or a distractor, and additionally varied whether the distractor was defined in a different (color) or the same dimension (shape) as the target. We found robust learning of the predicted target location: processing of the target at this (vs. a random) location was facilitated. But we found no evidence of proactive suppression of the predictable distractor location. Facilitation of the anticipated target location was associated with explicit awareness of the dynamic regularity, whereas participants showed no awareness of the distractor regularity. We propose that this asymmetry arises because, owing to the targets central role in the task set, its location is explicitly encoded in working memory, enabling the learning of dynamic regularities. In contrast, the distractor is not explicitly encoded; so, statistical learning of distractor locations is limited to static regularities. Public significance statementCan we learn the cross-trial dynamic regularity of a target or a task-irrelevant salient distractor (e.g., one-step shift of the critical item in clock-/counterclockwise direction) to boost search performance? The present study found robust learning of the predicted target location, but no evidence of proactive suppression of the predictable distractor location. Facilitation of the anticipated target location was associated with explicit awareness of the dynamic regularity. This asymmetry highlights the important role of the target-centered task set in the learning of dynamic regularities.

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bioRxiv2022

Learning to suppress likely distractor locations in visual search is driven by the local distractor frequency

Salient but task-irrelevant distractors interfere less with visual search when they appear in a display region where distractors have appeared more frequently in the past ( distractor-location probability cueing). This effect could reflect the (re-)distribution of a global, limited attentional inhibition resource. Accordingly, changing the frequency of distractor appearance in one display region should also affect the magnitude of interference generated by distractors in a different region. Alternatively, distractor-location learning may reflect a local response (e.g., habituation) to distractors occurring at a particular location. In this case, the local distractor frequency in one display region should not affect distractor interference in a different region. To decide between these alternatives, we conducted three experiments in which participants searched for an orientation-defined target while ignoring a more salient orientation distractor that occurred more often in one vs. another display region. Experiment 1 varied the ratio of distractors appearing in the frequent vs. rare regions (60/40-90/10), with a fixed global distractor frequency. The results revealed the cueing effect to increase with increasing probability ratio. In Experiments 2 and 3, one ( test) region was assigned the same local distractor frequency as in one of the conditions of Experiment 1, but a different frequency in the other region - dissociating local from global distractor frequency. Together, the three experiments showed that distractor interference in the test region was not significantly influenced by the frequency in the other region, consistent with purely local learning. We discuss the implications for theories of statistical distractor-location learning. Public Significance StatementWe are frequently distracted by salient visual stimuli which are irrelevant to the task at hand. Previous studies have shown that knowledge of the location(s) where a distractor is most likely to occur helps the observer to mitigate distraction. In this study we compared different theories of how the frequency and spatial distribution of distractor occurrence in different locations could influence the ability to avoid distraction. The results favored a local learning account: the ability to avoid distraction by distractors occuring in a particular spatial region is primarily influenced by how often distractors have occurred in that region.

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bioRxiv2022

Duration reproduction under memory pressure: Modeling the roles of visual memory load in duration encoding and reproduction

Duration estimates are often biased by the sampled statistical context, yielding the classical central-tendency effect, i.e., short durations are over- and long duration underestimated. Most studies of the central-tendency bias have primarily focused on the integration of the sensory measure and the prior information, without considering any cognitive limits. Here, we investigated the impact of cognitive (visual working-memory) load on duration estimation in the duration encoding and reproduction stages. In four experiments, observers had to perform a dual, attention-sharing task: reproducing a given duration (primary) and memorizing a variable set of color patches (secondary). We found an increase in memory load (i.e., set size) during the duration-encoding stage to increase the central-tendency bias, while shortening the reproduced duration in general; in contrast, increasing the load during the reproduction stage prolonged the reproduced duration, without influencing the central tendency. By integrating an attentional-sharing account into a hierarchical Bayesian model, we were able to predict both the general over- and underestimation and the central-tendency effects observed in all four experiments. The model suggests that memory pressure during the encoding stage increases the sensory noise, which elevates the central-tendency effect. In contrast, memory pressure during the reproduction stage only influences the monitoring of elapsed time, leading to a general duration over-reproduction without impacting the central tendency.

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bioRxiv2022

Predictive coding in ASD: inflexible weighting of prediction errors when switching from stable to volatile environments

The nature of predictive-processing differences between individuals with autism spectrum disorder (ASD) and typically developing (TD) individuals is widely debated. Some studies suggest impairments in predictive processing in ASD, while others report intact processes, albeit with atypical learning dynamics. Here, we assessed duration reproduction tasks in high- and low-volatility settings to examine the updating dynamics of prior beliefs and sensory estimates. Employing a two-state Bayesian model, we differentiated how individuals with ASD and TD controls update their priors and perceptual estimates, and how these updates affect long-term prediction and behavior. Our findings indicate that individuals with ASD use prior knowledge and sensory input similarly to TD controls in perceptual estimates. However, they place a greater weight on sensory inputs specifically for iteratively updating their priors. This distinct approach to prior updating led to slower adaptation across trials; individuals with ASD relied less on their priors in perceptual estimates during the first half of sessions but achieved comparable integration weights as TD controls by the end of the session. By differentiating these aspects, our study highlights the importance of considering inter-trial updating dynamics to reconcile diverse findings of predictive processing in ASD. In consequence to the current findings, we suggest the distinct iterative updating account of predictive processing in ASD. Significance StatementResearch on predictive processing in Autism Spectrum Disorder (ASD) remains controversial. The current study employed a two-state Bayesian model in varied volatility settings to explore inter-trial updating dynamics in ASD compared to typically developing (TD) peers. We found that individuals with ASD, while utilizing prior knowledge similarly to TD controls, place a disproportionate emphasis on sensory inputs when updating their priors. This unique pattern of slower adaptation during iterative updating leads to significant behavioral differences in the first half of trials between the two groups, but comparable levels by the end of the session. These findings not only highlight the importance of considering different timescales and dynamic updating processes in ASD, but also suggest that the predictive processing framework in ASD involves unique prior updating mechanisms that is likely associated with increased sensory reliance.

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bioRxiv2021

Statistical learning of frequent distractor locations in visual search involves regional signal suppression in 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.

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bioRxiv2018

Probability cueing of singleton-distractor locations in visual search: priority-map- or dimension-based inhibition?

Observers can learn the likely locations of salient distractors in visual search, reducing their potential to capture attention (Ferrante et al., 2018; Sauter et al., 2018a; Wang & Theeuwes, 2018a). While there is agreement that this involves positional suppression of the likely distractor location(s), it is contentious at which stage of search guidance the suppression operates: the supra-dimensional priority map or feature-contrast signals within the distractor dimension. On the latter account, advocated by Sauter et al., target processing should be unaffected by distractor suppression when the target is defined in a different (non-suppressed) dimension to the target. At odds with this, Wang and Theeuwes found strong suppression not only of the (color) distractor, but also of the (shape) target when it appeared at the likely distractor location. Adopting their paradigm, the present study ruled out that increased cross-trial inhibition of the single frequent (frequently inhibited) as compared to any of the rare (rarely inhibited) distractor locations is responsible for this target-location effect. However, a reduced likelihood of the target appearing at the frequent vs. a rare distractor location contributes to this effect: removing this negative bias abolished the cost to target processing with increasing practice, indicative of a transition from priority-map- to dimension-based - and thus a flexible locus of - distractor suppression.\n\nPublic Significance StatementDistraction by a salient visual stimulus outside the focus of the task at hand occurs frequently. The present study examined whether and how knowledge of the likely location(s) where the distractors occur helps the observer to mitigate distraction. The results confirmed that observers can learn to suppress distracting stimuli at likely locations. Further, they showed that, the suppression may occur at different levels in the hierarchically organized visual system where the priorities of which objects to be attended in the environment are determined.

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bioRxiv2018

Inter-trial effects in visual pop-out search: Factorial comparison of Bayesian updating models

Many previous studies on visual search have reported inter-trial effects, that is, observers respond faster when some target property, such as a defining feature or dimension, or the response associated with the target repeats versus changes across consecutive trial episodes. However, what processes drive these inter-trial effects is still controversial. Here, we investigated this question using a combination of Bayesian modeling of belief updating and evidence accumulation modeling in perceptual decision-making. In three visual singleton ( pop-out) search experiments, we explored how the probability of the response-critical states of the search display (e.g., target presence/absence) and the repetition/switch of the target-defining dimension (color/ orientation) affect reaction time distributions. The results replicated the mean reaction time (RT) inter-trial and dimension repetition/switch effects that have been reported in previous studies. Going beyond this, to uncover the underlying mechanisms, we used the Drift-Diffusion Model (DDM) and the Linear Approach to Threshold with Ergodic Rate (LATER) model to explain the RT distributions in terms of decision bias (starting point) and information processing speed (evidence accumulation rate). We further investigated how these different aspects of the decision-making process are affected by different properties of stimulus history, giving rise to dissociable inter-trial effects. We approached this question by (i) combining each perceptual decision making model (DDM or LATER) with different updating models, each specifying a plausible rule for updating of either the starting point or the rate, based on stimulus history, and (ii) comparing every possible combination of trial-wise updating mechanism and perceptual decision model in a factorial model comparison. Consistently across experiments, we found that the (recent) history of the response-critical property influences the initial decision bias, while repetition/switch of the target-defining dimension affects the accumulation rate, likely reflecting an implicit top-down modulation process. This provides strong evidence of a disassociation between response- and dimension-based inter-trial effects.

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