Academic literature on the topic 'Attentional capture hypothesis'
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Journal articles on the topic "Attentional capture hypothesis"
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Stilwell, Brad T., Howard Egeth, and Nicholas Gaspelin. "Electrophysiological Evidence for the Suppression of Highly Salient Distractors." Journal of Cognitive Neuroscience 34, no. 5 (March 31, 2022): 787–805. http://dx.doi.org/10.1162/jocn_a_01827.
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Abstract There has been a longstanding debate as to whether salient stimuli have the power to involuntarily capture attention. As a potential resolution to this debate, the signal suppression hypothesis proposes that salient items generate a bottom–up signal that automatically attracts attention, but that salient items can be suppressed by top–down mechanisms to prevent attentional capture. Despite much support, the signal suppression hypothesis has been challenged on the grounds that many prior studies may have used color singletons with relatively low salience that are too weak to capture attention. The current study addressed this by using previous methods to study suppression but increased the set size to improve the relative salience of the color singletons. To assess whether salient distractors captured attention, electrophysiological markers of attentional allocation (the N2pc component) and suppression (the PD component) were measured. The results provided no evidence of attentional capture, but instead indicated suppression of the highly salient singleton distractors, as indexed by the PD component. This suppression occurred even though a computational model of saliency confirmed that the color singleton was highly salient. Altogether, this supports the signal suppression hypothesis and is inconsistent with stimulus-driven models of attentional capture.
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Leblanc, Émilie, David J. Prime, and Pierre Jolicoeur. "Tracking the Location of Visuospatial Attention in a Contingent Capture Paradigm." Journal of Cognitive Neuroscience 20, no. 4 (April 2008): 657–71. http://dx.doi.org/10.1162/jocn.2008.20051.
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Currently, there is considerable controversy regarding the degree to which top-down control can affect attentional capture by salient events. According to the contingent capture hypothesis, attentional capture by a salient stimulus is contingent on a match between the properties of the stimulus and top-down attentional control settings. In contrast, bottom-up saliency accounts argue that the initial capture of attention is determined solely by the relative salience of the stimulus, and the effect of top-down attentional control is limited to effects on the duration of attentional engagement on the capturing stimulus. In the present study, we tested these competing accounts by utilizing the N2pc event-related potential component to track the locus of attention during an attentional capture task. The results were completely consistent with the contingent capture hypothesis: An N2pc wave was elicited only by distractors that possessed the target-defining attribute. In a second experiment, we expanded upon this finding by exploring the effect of target-distractor similarity on the duration that attention dwells at the distractor location. In this experiment, only distractors possessing the target-defining attribute (color) captured visuospatial attention to their location and the N2pc increased in duration and in magnitude when the capture distractor also shared a second target attribute (category membership). Finally, in three additional control experiments, we replicated the finding of an N2pc generated by distractors, only if they shared the target-defining attribute. Thus, our results demonstrate that attentional control settings influence both which stimuli attract attention and to what extent they are processed.
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ZHANG, Fan, Airui CHEN, Bo DONG, Aijun WANG, and Ming ZHANG. "Rapid disengagement hypothesis and signal suppression hypothesis of visual attentional capture." Advances in Psychological Science 29, no. 1 (2021): 45. http://dx.doi.org/10.3724/sp.j.1042.2021.00045.
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Wirth, Benedikt Emanuel, and Dirk Wentura. "Attentional bias to threat in the general population is contingent on target competition, not on attentional control settings." Quarterly Journal of Experimental Psychology 71, no. 4 (January 1, 2018): 975–88. http://dx.doi.org/10.1080/17470218.2017.1307864.
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Dot-probe studies usually find an attentional bias towards threatening stimuli only in anxious participants. Here, we investigated under what conditions such a bias occurs in unselected samples. According to contingent-capture theory, an irrelevant cue only captures attention if it matches an attentional control setting. Therefore, we first tested the hypothesis that an attentional control setting tuned to threat must be activated in (non-anxious) individuals. In Experiment 1, we used a dot-probe task with a manipulation of attentional control settings (‘threat’ – set vs. control set). Surprisingly, we found an (anxiety-independent) attentional bias to angry faces that was not moderated by attentional control settings. Since we presented two stimuli (i.e., a target and a distractor) on the target screen in Experiment 1 (a necessity to realise the test of contingent capture), but most dot-probe studies only employ a single target, we conducted Experiment 2 to test the hypothesis that attentional bias in the general population is contingent on target competition. Participants performed a dot-probe task, involving presentation of a stand-alone target or a target competing with a distractor. We found an (anxiety-independent) attentional bias towards angry faces in the latter but not the former condition. This suggests that attentional bias towards angry faces in unselected samples is not contingent on attentional control settings but on target competition.
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DiQuattro, N. E., R. Sawaki, and J. J. Geng. "Effective Connectivity During Feature-Based Attentional Capture: Evidence Against the Attentional Reorienting Hypothesis of TPJ." Cerebral Cortex 24, no. 12 (July 3, 2013): 3131–41. http://dx.doi.org/10.1093/cercor/bht172.
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Lee, Jeongmi, Carly J. Leonard, Steven J. Luck, and Joy J. Geng. "Dynamics of Feature-based Attentional Selection during Color–Shape Conjunction Search." Journal of Cognitive Neuroscience 30, no. 12 (December 2018): 1773–87. http://dx.doi.org/10.1162/jocn_a_01318.
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Feature-based attentional selection is accomplished by increasing the gain of sensory neurons encoding target-relevant features while decreasing that of other features. But how do these mechanisms work when targets and distractors share features? We investigated this in a simplified color–shape conjunction search task using ERP components (N2pc, PD, and SPCN) that index lateralized attentional processing. In Experiment 1, we manipulated the presence and frequency of color distractors while holding shape distractors constant. We tested the hypothesis that the color distractor would capture attention, requiring active suppression such that processing of the target can continue. Consistent with this hypothesis, we found that color distractors consistently captured attention, as indexed by a significant N2pc, but were reactively suppressed (indexed by PD). Interestingly, when the color distractor was present, target processing was sustained (indexed by SPCN), suggesting that the dynamics of attentional competition involved distractor suppression interlinked with sustained target processing. In Experiment 2, we examined the contribution of shape to the dynamics of attentional competition under similar conditions. In contrast to color distractors, shape distractors did not reliably capture attention, even when the color distractor was very frequent and attending to target shape would be beneficial. Together, these results suggest that target-colored objects are prioritized during color–shape conjunction search, and the ability to select the target is delayed while target-colored distractors are actively suppressed.
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Southwell, Rosy, Anna Baumann, Cécile Gal, Nicolas Barascud, Karl Friston, and Maria Chait. "Is predictability salient? A study of attentional capture by auditory patterns." Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1714 (February 19, 2017): 20160105. http://dx.doi.org/10.1098/rstb.2016.0105.
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In this series of behavioural and electroencephalography (EEG) experiments, we investigate the extent to which repeating patterns of sounds capture attention. Work in the visual domain has revealed attentional capture by statistically predictable stimuli, consistent with predictive coding accounts which suggest that attention is drawn to sensory regularities. Here, stimuli comprised rapid sequences of tone pips, arranged in regular (REG) or random (RAND) patterns. EEG data demonstrate that the brain rapidly recognizes predictable patterns manifested as a rapid increase in responses to REG relative to RAND sequences. This increase is reminiscent of the increase in gain on neural responses to attended stimuli often seen in the neuroimaging literature, and thus consistent with the hypothesis that predictable sequences draw attention. To study potential attentional capture by auditory regularities, we used REG and RAND sequences in two different behavioural tasks designed to reveal effects of attentional capture by regularity. Overall, the pattern of results suggests that regularity does not capture attention. This article is part of the themed issue ‘Auditory and visual scene analysis’.
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Rauschenberger, R., and S. Yantis. "What counts as an object in the new-object hypothesis of attentional capture?" Journal of Vision 1, no. 3 (March 14, 2010): 105. http://dx.doi.org/10.1167/1.3.105.
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Orquin, Jacob L., Martin P. Bagger, and Simone Mueller Loose. "Learning affects top down and bottom up modulation of eye movements in decision making." Judgment and Decision Making 8, no. 6 (November 2013): 700–716. http://dx.doi.org/10.1017/s1930297500004733.
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AbstractRepeated decision making is subject to changes over time such as decreases in decision time and information use and increases in decision accuracy. We show that a traditional strategy selection view of decision making cannot account for these temporal dynamics without relaxing main assumptions about what defines a decision strategy. As an alternative view we suggest that temporal dynamics in decision making are driven by attentional and perceptual processes and that this view has been expressed in the information reduction hypothesis. We test the information reduction hypothesis by integrating it in a broader framework of top down and bottom up processes and derive the predictions that repeated decisions increase top down control of attention capture which in turn leads to a reduction in bottom up attention capture. To test our hypotheses we conducted a repeated discrete choice experiment with three different information presentation formats. We thereby operationalized top down and bottom up control as the effect of individual utility levels and presentation formats on attention capture on a trial-by-trial basis. The experiment revealed an increase in top down control of eye movements over time and that decision makers learn to attend to high utility stimuli and ignore low utility stimuli. We furthermore find that the influence of presentation format on attention capture reduces over time indicating diminishing bottom up control.
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Itthipuripat, Sirawaj, Kexin Cha, Napat Rangsipat, and John T. Serences. "Value-based attentional capture influences context-dependent decision-making." Journal of Neurophysiology 114, no. 1 (July 2015): 560–69. http://dx.doi.org/10.1152/jn.00343.2015.
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Normative theories posit that value-based decision-making is context independent. However, decisions between two high-value options can be suboptimally biased by the introduction of a third low-value option. This context-dependent modulation is consistent with the divisive normalization of the value of each stimulus by the total value of all stimuli. In addition, an independent line of research demonstrates that pairing a stimulus with a high-value outcome can lead to attentional capture that can mediate the efficiency of visual information processing. Here we tested the hypothesis that value-based attentional capture interacts with value-based normalization to influence the optimality of decision-making. We used a binary-choice paradigm in which observers selected between two targets and the color of each target indicated the magnitude of their reward potential. Observers also had to simultaneously ignore a task-irrelevant distractor rendered in a color that was previously associated with a specific reward magnitude. When the color of the task-irrelevant distractor was previously associated with a high reward, observers responded more slowly and less optimally. Moreover, as the learned value of the distractor increased, electrophysiological data revealed an attenuation of the lateralized N1 and N2Pc responses evoked by the relevant choice stimuli and an attenuation of the late positive deflection (LPD). Collectively, these behavioral and electrophysiological data suggest that value-based attentional capture and value-based normalization jointly mediate the influence of context on free-choice decision-making.
Books on the topic "Attentional capture hypothesis"
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Gormley, Bill. James Q. Wilson,. Edited by Martin Lodge, Edward C. Page, and Steven J. Balla. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199646135.013.2.
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This chapter examines James Q. Wilson’sBureaucracy: What Government Agencies Do and Why they Do it, and compares Wilson’s approach to that of neoclassical economics, paying particular attention to his denunciation of William Niskanen’s “bureaucratic imperialism” hypothesis and his rejection of “principal-agent” models which predict widespread “shirking” by bureaucrats. It discusses his argument that every bureaucracy has a distinctive culture that helps shape the behavior of individual bureaucrats. The chapter explores Wilson’s other views with regards to “capture theory,” accountability, and the ability of markets to promote efficiency and of governments to promote equity. Finally, it evaluates Wilson’s impact on other scholars, emphasizing: his bottom–up approach to studying bureaucracy, organizational culture, his typologies of policy proposals that differ in terms of benefits and costs, and of administrative agencies that differ in terms of outputs and outcomes.
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Gutzmann, Daniel. The Grammar of Expressivity. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198812128.001.0001.
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While the expressive function of natural language has received much attention in recent years, the role grammar plays in the interpretation of expressive items has mainly been neglected in the semantic and pragmatic literature. On the other hand, while there have been syntactic studies of some expressive phenomena they do not explicitly connect to recent developments in semantics. This book bridges this gap, showing that semantics and pragmatics alone cannot capture all grammatical particularities of expressive items and that expressivity has strong syntactic reflexes that interact with the semantic interpretation and account for the mismatches between the syntax and semantics of these phenomena. The main thesis he argues for—the hypothesis of expressive syntax—is that expressivity is a syntactic feature, on a par with other established syntactic features like tense or gender. Evidence for this claim is drawn from three detailed case studies of expressive phenomena: expressive adjectives, expressive intensifiers, and expressive vocatives. These expressions exhibit some puzzling properties and by developing an account of them employing minimalist approaches to syntactic features and agreement, the author shows that expressivity, as a syntactic feature, can partake in agreement operations, trigger movement, and syntactically be selected for. This not only provides indirect evidence for the hypothesis of expressive syntax and extends the usefulness of operations on syntactic features operation beyond their traditional domains, but also highlights the hidden role grammar may play for phenomena that are often considered to be solely semantic in nature.
Book chapters on the topic "Attentional capture hypothesis"
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Lantschner, Emma. "Theoretical Foundations: Reflexive Governance, EU Enlargement Process, and Non-Discrimination." In Reflexive Governance in EU Equality Law, 42–107. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192843371.003.0003.
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Chapter 2 reviews explanatory models of rule adoption of Europeanization, policy transfer, and diffusion literature, and the conditions they identify for a successful transfer of norms and ideas. It argues that the external incentives model might best explain the likelihood of rule adoption but if the ultimate goal is that rules are applied and enforced, learning-based approaches have to be strengthened in the enlargement process. Different approaches to reflexive governance, from collaborative-relational to experimentalist, pragmatist, and genetic approaches, all focusing in different ways on the conditions required for a learning process to be successful, are presented claiming that they offer ideas that merit closer study to establish their potential in improving the performance in the EU enlargement process and beyond. The hypothesis is that reflexive governance is well suited to improve compliance and reduce likelihood of backsliding as it captures all the actors involved in framework regulation as is the case of the transposition of binding directives. To test the plausibility of the hypothesis, a case study on Croatia with a focus on the equality acquis is carried out by means of process tracing. This showed that while the argument could be partly confirmed, there is also a need for more consistent and transparent monitoring, which could be achieved by the use of indicators. Furthermore, pooling of results and the drawing of conclusions from such results, which is decisive for the success of a reflexive governance system, is given too little attention. The subsequent chapters thus set out to make a contribution to these identified lacunae.
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Vega, Julio, Eduardo Perdices, and José María Cañas. "Attentive Visual Memory for Robot Localization." In Robotic Vision, 406–36. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2672-0.ch021.
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Cameras are one of the most relevant sensors in autonomous robots. Two challenges with them are to extract useful information from captured images and to manage the small field of view of regular cameras. This chapter proposes a visual perceptive system for a robot with a mobile camera on board that cope with these two issues. The system is composed of a dynamic visual memory that stores the information gathered from images, an attention system that continuously chooses where to look at, and a visual evolutionary localization algorithm that uses the visual memory as input. The visual memory is a collection of relevant task-oriented objects and 3D segments. Its scope and persistence is wider than the camera field of view and so provides more information about robot surroundings and more robustness to occlusions than current image. The control software takes its contents into account when making behavior or navigation decisions. The attention system considers the need of reobserving objects already stored, of exploring new areas and of testing hypothesis about objects in the robot surroundings. A robust evolutionary localization algorithm has been developed that can use both the current instantaneous images or the visual memory. The system has been programmed and several experiments have been carried out both with simulated and real robots (wheeled Pioneer and Nao humanoid) to validate it.
Conference papers on the topic "Attentional capture hypothesis"
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Huang, Xuancheng, Jiacheng Zhang, Zhixing Tan, Derek F. Wong, Huanbo Luan, Jingfang Xu, Maosong Sun, and Yang Liu. "Modeling Voting for System Combination in Machine Translation." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/511.
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System combination is an important technique for combining the hypotheses of different machine translation systems to improve translation performance. Although early statistical approaches to system combination have been proven effective in analyzing the consensus between hypotheses, they suffer from the error propagation problem due to the use of pipelines. While this problem has been alleviated by end-to-end training of multi-source sequence-to-sequence models recently, these neural models do not explicitly analyze the relations between hypotheses and fail to capture their agreement because the attention to a word in a hypothesis is calculated independently, ignoring the fact that the word might occur in multiple hypotheses. In this work, we propose an approach to modeling voting for system combination in machine translation. The basic idea is to enable words in hypotheses from different systems to vote on words that are representative and should get involved in the generation process. This can be done by quantifying the influence of each voter and its preference for each candidate. Our approach combines the advantages of statistical and neural methods since it can not only analyze the relations between hypotheses but also allow for end-to-end training. Experiments show that our approach is capable of better taking advantage of the consensus between hypotheses and achieves significant improvements over state-of-the-art baselines on Chinese-English and English-German machine translation tasks.
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Wang, Yongqing, Huawei Shen, Shenghua Liu, Jinhua Gao, and Xueqi Cheng. "Cascade Dynamics Modeling with Attention-based Recurrent Neural Network." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/416.
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An ability of modeling and predicting the cascades of resharing is crucial to understanding information propagation and to launching campaign of viral marketing. Conventional methods for cascade prediction heavily depend on the hypothesis of diffusion models, e.g., independent cascade model and linear threshold model. Recently, researchers attempt to circumvent the problem of cascade prediction using sequential models (e.g., recurrent neural network, namely RNN) that do not require knowing the underlying diffusion model. Existing sequential models employ a chain structure to capture the memory effect. However, for cascade prediction, each cascade generally corresponds to a diffusion tree, causing cross-dependence in cascade---one sharing behavior could be triggered by its non-immediate predecessor in the memory chain. In this paper, we propose to an attention-based RNN to capture the cross-dependence in cascade. Furthermore, we introduce a \emph{coverage} strategy to combat the misallocation of attention caused by the memoryless of traditional attention mechanism. Extensive experiments on both synthetic and real world datasets demonstrate the proposed models outperform state-of-the-art models at both cascade prediction and inferring diffusion tree.
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Ramírez Sepúlveda, Cristian Andrés. "La nueva geografía económica del comercio al por menor en el gran Santiago de Chile." In International Conference Virtual City and Territory. Concepción: Centre de Política de Sòl i Valoracions, 2005. http://dx.doi.org/10.5821/ctv.7379.
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The objective of the present investigation is framed within a line of investigation developed
by the author, relative to reveal the new space configuration economic that displays
the great cities in the context of the Economic Globalization. The hypothesis in the Industry
of Retail is one of whom has experienced the greater economic dynamism in Chile
and that has characteristics that would frame it within the process of flexible production
in Advanced Capitalism. The retail, sector that the attention of the great economic
groups has captured that make investments and space competition in related activities,
generates new spaces of leisure and consumption, determining a singular space distribution
of the use, that is more and more dynamic and precarious in its nature. The investigation
concludes that a clear tendency to the integration of activities exists from the centers
of the posfordista economic power towards the consumer, space model of businesses
whose diffusion is made in the extensive Latin American Region.
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Zhou, Jinxin, Takero Yoshida, Junbo Zhang, Sanggyu Park, and Daisuke Kitazawa. "Three-Dimensional Physical Environment Modelling for Integrated Multi-Trophic Aquaculture (IMTA) Implementation in Onagawa Bay, Japan." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95672.
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Abstract Continually increasing demands on aquaculture products drive the current monoculture to upgrade and upscale because of not only economic but environmental sustainability reasons. Over the past decade, open water integrated multi-trophic aquaculture (IMTA) practiced as a potential alternative has been demonstratively illustrated from both scientific and public attention. Basing on previous studies of this synergistic aquaculture system, we, here, studied the physical environment in Onagawa Bay as the cornerstone for further IMTA implementation. Onagawa Bay locates in Miyagi Prefecture, Japan, and because of its mature practice on polyculture, it is recognized as a suitable site for IMTA. Unfortunately, the earthquake and tsunami in 2011 caused a huge uncertainty on physical environment changes. Still insufficient researches have been conducted on physical environment study, especially through modelling method. Here, adopting the three-dimensional Marine Environmental Committee (MEC) ocean model, we described the setup and validation for Onagawa Bay in this research. At the present stage, simulation results can best fit observation data on the tidal elevation with the correlation coefficient between observed and simulated tidal elevation reaching 0.96, captured the main characteristic of flow velocity, and exhibited homogenous tendency towards water temperature. Furthermore, through the plot of the residual velocity field and statistical seasonal velocity distribution, potential aquaculture configuration has been discussed spatio-temporally on the hypothesis that high current speeds contribute to the further implementation.
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Bacci, Alessandro, and Bruno Facchini. "Turbulence Modeling for the Numerical Simulation of Film and Effusion Cooling Flows." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-27182.
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RANS simulations are known to suffer from serious deficiencies in the prediction of jet in a crossflow (JCF) because of the high complexity of this kind of flow. Particularly, the coherent structures resulting from the interaction of the two flow streams are characterized by a highly unsteady and anisotropic behavior which hardly stresses the hypotheses underling common eddy viscosity models (EVMs). Direct numerical simulation (DNS) and large eddy simulation (LES) methodologies are still excessively computationally intensive to be used as ordinary design tools. Therefore, the development of reliable RANS turbulence models for film cooling flows deserved a great deal of attention from the gas turbine community. Computations presented in this work were carried out using a modified k-ε turbulence model specifically designed for film cooling flows. The model, due to Lakehal et al., is based on the usage of an anisotropic eddy viscosity. The model has been implemented in the framework of a CFD commercial package through the user subroutine features. Computational model is developed following the suggestions of Walters and Leylek concerning the correct representation of the problem geometry and the location of the boundary conditions. The predictive capabilities of the model concerning the ability to capture the main flow structures as well as heat transfer features are investigated. Comparison of computed adiabatic effectiveness profiles with experimental measurements is provided in order to quantitatively validate the model. Results obtained with standard EVMs, particularly a two layer standard k-ε model, are also shown in order to reveal the improvements in the predictive capabilities resulting from the modified models.
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Lazar, Mihael, and Aleš Hladnik. "Improved reconstruction of the reflectance spectra from RGB readings using two instead of one digital camera." In 11th International Symposium on Graphic Engineering and Design. University of Novi Sad, Faculty of technical sciences, Department of graphic engineering and design, 2022. http://dx.doi.org/10.24867/grid-2022-p96.
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The colour of an observed object can be described in many different manners, and the description by its reflectance provides the unambiguous colour representation. The reflectance description can be acquired by expensive multispectral cameras or, e.g., with time-sequential multispectral illumination. In our experiment, we propose that under the condition of constant and uniform illumination, the reflectance can be deduced from the object's RGB camera readouts, captured alongside the set of colour patches with known spectral characteristics. Translation from a colour description in RGB space into reflectance spectra, independent of illuminant and camera sensor characteristics, was performed with the help of an artificial neural network (ANN). In our study, the hypothesis was proposed that the ANN's performance of reflectance reconstruction can be enhanced by employing richer learning datasets using RGB input sets of two cameras instead of just one. Additional second camera information would be adequate only if the equivalent channels of cameras used are linearly independent. A quantitative measure of nonlinearity (QMoN), which is the metric primarily developed for use in chemistry, was employed to estimate the degree of nonlinearity. Additional attention was paid to ANN training, structure and learning set sizes. Two ANN training algorithms have been utilised, a faster GPU executed standard backpropagation and an order of magnitude slower CPU based, but with significantly better convergence Levenberg-Marquardt training algorithm. The number of neurons in the hidden ANN layer varied from the size of the input layer to a number greater than the number in the output layer. The complete set of colour samples was divided into five learning sets of different sizes, with the smaller sets being subsets of the larger ones. To assess performances of the resulting ANNs, mean squared error, the goodness of fit and colour differences calculated from original and reconstructed reflectances assuming several standard illuminations have been compared. A noticeable reflectance performance improvement has been found by using two cameras, even though the cameras' equivalent channels exerted only small degrees of nonlinearity.