How to inhibit a distractor location? Statistical learning versus active, top-down suppression

Recently, Wang and Theeuwes (Journal of Experimental Psychology: Human Perception and Performance, 44(1), 13–17, 2018a) demonstrated the role of lingering selection biases in an additional singleton search task in which the distractor singleton appeared much more often in one location than in all other locations. For this location, there was less capture and selection efficiency was reduced. It was argued that statistical learning induces plasticity within the spatial priority map such that particular locations that are high likely to contain a distractor are suppressed relative to all other locations. The current study replicated these findings regarding statistical learning (Experiment 1) and investigated whether similar effects can be obtained by cueing the distractor location in a top-down way on a trial-by-trial basis. The results show that top-down cueing of the distractor location with long (1,500 ms; Experiment 2) and short stimulus-onset symmetries (SOAs) (600 ms; Experiment 3) does not result in suppression: The amount of capture nor the efficiency of selection was affected by the cue. If anything, we found an attentional benefit (instead of the suppression) for the short SOA. We argue that through statistical learning, weights within the attentional priority map are changed such that one location containing a salient distractor is suppressed relative to all other locations. Our cueing experiments show that this effect cannot be accomplished by active, top-down suppression. Consequences for recent theories of distractor suppression are discussed

Implicit attentional biases in a changing environment

The current study investigates whether statistical regularities that change over time affect attentional selection. While searching for a target singleton, the distractor singleton was presented much more often in one location than in all other locations. Crucially, the location that had a distractor much more often, changed to new locations during the course of the experiment. Here we established exactly how the bias of attention followed these changes in the display. Unlike previous studies, we show that selection was remarkably flexible as the attentional bias followed the changes in the environment incorporating contributions of previous contingencies to the current attentional bias. Importantly, the initial learning experience had a lingering and enduring effect on subsequent attentional biases. We argue that the weights within the spatial priority map of selection are adjusted to changing environments, even though observers are unaware of these changes in the environment

Spatial enhancement due to statistical learning tracks the estimated spatial probability

It is well known that attentional selection is sensitive to the regularities presented in the display. In the current study we employed the additional singleton paradigm and systematically manipulated the probability that the target would be presented in one particular location within the display (probabilities of 30%, 40%, 50%, 60%, 70%, 80%, and 90%). The results showed the higher the target probability, the larger the performance benefit for high- relative to low-probability locations both when a distractor was present and when it was absent. We also showed that when the difference between high- and low-probability conditions was relatively small (30%) participants were not able to learn the contingencies. The distractor presented at a highprobability target location caused more interference than when presented at a low-probability target location. Overall, the results suggest that attentional biases are optimized to the regularities presented in the display tracking the experienced probabilities of the locations that were most likely to contain a target. We argue that this effect is not strategic in nature nor the result of repetition priming. Instead, we assume that through statistical learning the weights within the spatial priority map are adjusted optimally, generating the efficient selection priorities.info:eu-repo/semantics/publishedVersio

Visual memory benefits from prolonged encoding time regardless of stimulus type

It is generally assumed that the storage capacity of visual working memory (VWM) is limited, holding about 3-4 items. Recent work with real-world objects, however, has challenged this view by providing evidence that the VWM capacity for real-world objects is not fixed but instead increases with prolonged encoding time (Brady, Stormer, & Alvarez, 2016). Critically, in this study, no increase with prolonged encoding time was observed for storing simple colors. Brady et al. (2016) argued that the larger capacity for real-world objects relative to colors is due to the additional conceptual information of real-world objects. With basically the same methods of Brady et al., in Experiments 1-3, we were unable to replicate their basic findings. Instead, we found that visual memory for simple colors also benefited from prolonged encoding time. Experiment 4 showed that the scale of the encoding time benefit was the same for familiar and unfamiliar objects, suggesting that the added conceptual information does not contribute to this benefit. We conclude that visual memory benefits from prolonged encoding time regardless of stimulus type

Retrieving non-linear features from noisy quantum states

Accurately estimating high-order moments of quantum states is an elementary precondition for many crucial tasks in quantum computing, such as entanglement spectroscopy, entropy estimation, spectrum estimation and predicting non-linear features from quantum states. But in reality, inevitable quantum noise prevents us from accessing the desired value. In this paper, we address this issue by systematically analyzing the feasibility and efficiency of extracting high-order moments from noisy states. We first show that there exists a quantum protocol capable of accomplishing this task if and only if the underlying noise channel is invertible. We then establish a method for deriving protocols that attain optimal sample complexity using quantum operations and classical post-processing only. Our protocols, in contrast to conventional ones, incur lower overheads and avoid sampling different quantum operations due to a novel technique called observable shift, making the protocols strong candidates for practical usage on current quantum devices. The proposed method also indicates the power of entangled protocols in retrieving high-order information, whereas in the existing methods, entanglement does not help. Our work contributes to a deeper understanding of how quantum noise could affect high-order information extraction and provides guidance on how to tackle it.Comment: 23 pages, 6 figure

Information recoverability of noisy quantum states

Extracting classical information from quantum systems is an essential step of many quantum algorithms. However, this information could be corrupted as the systems are prone to quantum noises, and its distortion under quantum dynamics has not been adequately investigated. In this work, we introduce a systematic framework to study how well we can retrieve information from noisy quantum states. Given a noisy quantum channel, we fully characterize the range of recoverable classical information. This condition allows a natural measure quantifying the information recoverability of a channel. Moreover, we resolve the minimum information retrieving cost, which, along with the corresponding optimal protocol, is efficiently computable by semidefinite programming. As applications, we establish the limits on the information retrieving cost for practical quantum noises and employ the corresponding protocols to mitigate errors in ground state energy estimation. Our work gives the first full characterization of information recoverability of noisy quantum states from the recoverable range to the recovering cost, revealing the ultimate limit of probabilistic error cancellation

MiR-550a-3p restores damaged vascular smooth muscle cells by inhibiting thrombomodulin in an <em>in vitro</em> atherosclerosis model

Thrombomodulin (TM) is involved in the pathological process of atherosclerosis; however, the underlying mechanism remains unclear. Oxidised low-density lipoprotein (Ox-LDL; 100 μg/mL) was used to induce human vascular smooth muscle cells (HVSMCs) into a stable atherosclerotic cell model. The expression levels of miR-550a-3p and TM were detected by real-time reverse transcription-polymerase chain reaction. Cell proliferation was estimated using CCK8 and EDU assays. Wound scratch and transwell assays were used to measure the ability of cells to invade and migrate. Propidium iodide fluorescence-activated cell sorting was used to detect apoptosis and cell cycle changes. A dual-luciferase reporter assay was performed to determine the binding of miR-550a-3p to TM. Our results suggested the successful development of a cellular atherosclerosis model. Our data revealed that TM overexpression significantly promoted the proliferation, invasion, migration, and apoptosis of HVSMCs as well as cell cycle changes. Upregulation of miR-550a-3p inhibited the growth and metastasis of HVSMCs. Furthermore, miR-550a-3p was confirmed to be a direct target of TM. Restoration of miR-550a-3p expression rescued the effects of TM overexpression. Thus, miR-550a-3p might play a role in atherosclerosis and, for the first time, normalised the function of injured vascular endothelial cells by simultaneous transfection of TM and miR-550a-3p. These results suggest that the miR-550a-3p/TM axis is a potential therapeutic target for atherosclerosis

Statistical regularities modulate attentional capture independent of search strategy

An earlier study using the additional singleton task showed that statistical regularities regarding the distractor location can cause an attentional bias that affects the amount of attentional capture by distractors and the efficiency of selection of targets. The distractor singleton was systematically present more often in one location than in all other locations. The present study investigated whether this bias also occurs when observers adopt a feature search mode, i.e., when they search for a specific feature (circle) between elements with different shapes, while ignoring a colored distractor singleton. It is assumed that in feature search, observers can ignore distractors in a top-down way and as such one expects that statistical regularities about the distractor location should not play a role. Contrary to this prediction, we found that even in feature search, both attentional capture by the distractors and the efficiency of selecting the target were impacted by these statistical regularities. Moreover, statistical regularities regarding the feature value of the distractor (its color) had no effect on the amount of capture or the efficiency of selection. We claim that statistical regularities cause passive lingering biases of attention such that on the priority map, the location containing a high probability distractor competes less for attention than locations that are less likely to contain distractors

Statistical regularities modulate attentional capture

The present study investigated whether statistical regularities can influence visual selection. We used the classic additional singleton task in which participants search for a salient shape singleton while ignoring a color distractor singleton. The color distractor singleton was systematically presented more often in 1 location than in all other locations. For this high-probability location, we found that both the amount of attentional capture by distractors and the efficiency of selecting the target were reduced. There was a spatial gradient of suppression, as the attentional capture effect and the efficiency of selecting the target scaled with the distance from the high-probability location. Some participants were aware of the statistical regularities, but this did not affect the results whatsoever. We interpret these findings as evidence that spatially statistical regularities that are unknown to the observer can influence attention such that locations that have a high probability of containing a distractor are suppressed relative to all other locations. (PsycINFO Database Recor

The viewer-center reference frame in visual distractor probability learning

Jiang (2013) found that the probabillity leaning in target selection was viewer-center reference, and our cognitive mechanism underlyign the target selection and distractor suppression maybe different. Therefore, we want to ues the design in Wang (2018) to investigate the spatial reference frame in distractor's probability learnin