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This article investigates the decisional and attentional drivers of the attentional repulsion effect (ARE) using the diffusion decision model (DDM). The ARE is a phenomenon in which a subjective expansion of space is experienced outside the focus of attention. It is thought to occur due to changes in the functioning of visual cell receptive fields. The DDM is a model of the decision-making process that assumes responses are selected by sequentially sampling an encoded representation of a stimulus until sufficient evidence has been accumulated favoring one response alternative over the other. The model decomposes observed choice and response times into different latent variables corresponding to the rate of evidence accumulation, response caution, response bias, and the time course of stimulus encoding and response execution. In this article, we interpret changes in the rate of evidence accumulation as primarily reflecting perceptual-driven changes in stimulus representation. We interpret changes in response bias as primarily reflecting decision-level changes. We utilize the DDM's ability to estimate these variables independently to explore how they are each affected by cueing manipulations to clarify whether the ARE emerges due to attentional or decisional drivers, or some combination of the two. The results of this study could shed light on the mechanisms underlying the ARE, and has implications in our understanding of spatial attention., (© 2023. The Psychonomic Society, Inc.)

The recently developed diffusion model for conflict tasks (DMC) Ulrich et al. (Cognitive Psychology, 78, 148-174, 2015) provides a good account of data from all standard conflict tasks (e.g., Stroop, Simon, and flanker tasks) within a common evidence accumulation framework. A central feature of DMC's processing dynamics is that there is an initial phase of rapid accumulation of distractor evidence that is then selectively withdrawn from the decision mechanism as processing continues. We argue that this assumption is potentially troubling because it could be viewed as implying qualitative changes in the representation of distractor information over the time course of processing. These changes suggest more than simple inhibition or suppression of distractor information, as they involve evidence produced by distractor processing "changing sign" over time. In this article, we (a) develop a revised DMC (RDMC) whose dynamics operate strictly within the limits of inhibition/suppression (i.e., evidence strength can change monotonically, but cannot change sign); (b) demonstrate that RDMC can predict the full range of delta plots observed in the literature (i.e., both positive-going and negative-going); and (c) show that the model provides excellent fits to Simon and flanker data used to benchmark the original DMC at both the individual and group level. Our model provides a novel account of processing differences across Simon and flanker tasks. Specifically, that they differ in how distractor information is processed on congruent trials, rather than incongruent trials: congruent trials in the Simon task show relatively slow attention shifting away from distractor information (i.e., location) while complete and rapid attention shifting occurs in the flanker task. Our new model highlights the importance of considering dynamic interactions between top-down goals and bottom-up stimulus effects in conflict processing., (© 2023. The Author(s).)

Current models of attention propose that we can tune attention in a top-down controlled manner to a specific feature value (e.g., shape, color) to find specific items (e.g., a red car; feature-specific search ). However, subsequent research has shown that attention is often tuned in a context-dependent manner to the relative features that distinguish a sought-after target from other surrounding nontarget items (e.g., larger, bluer, and faster; relational search ). Currently, it is unknown whether search will be feature-specific or relational in search for multiple targets with different attributes. In the present study, observers had to search for 2 targets that differed either across 2 stimulus dimensions (color, motion; Experiment 1) or within the same stimulus dimension (color; Experiment 2: orange/redder or aqua/bluer). We distinguished between feature-specific and relational search by measuring eye movements to different types of irrelevant distractors (e.g., relatively matching vs. feature-matching). The results showed that attention was biased to the 2 relative features of the targets, both across different feature dimensions (i.e., motion and color) and within a single dimension (i.e., 2 colors; bluer and redder). The results were not due to automatic intertrial effects (dimension weighting or feature priming), and we found only small effects for valid precueing of the target feature, indicating that relational search for two targets was conducted with relative ease. This is the first demonstration that attention is top-down biased to the relative target features in dual target search, which shows that the relational account generalizes to multiple target search. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Contextual cuing refers to a response time (RT) benefit that occurs when observers search through displays that have been repeated over the course of an experiment. Although it is generally agreed that contextual cuing arises via an associative learning mechanism, there is uncertainty about the type(s) of process(es) that allow learning to influence RT. We contrast two leading accounts of the contextual cuing effect that differ in terms of the general process that is credited with producing the effect. The first, the expedited search account, attributes the cuing effect to an increase in the speed with which the target is acquired. The second, the decision threshold account, attributes the cuing effect to a reduction in the response threshold used by observers when making a subsequent decision about the target (e.g., judging its orientation). We use the diffusion model to contrast the quantitative predictions of these two accounts at the level of individual observers. Our use of the diffusion model allows us to also explore a novel decision-level locus of the cuing effect based on perceptual learning. This novel account attributes the RT benefit to a perceptual learning process that increases the quality of information used to drive the decision process. Our results reveal both individual differences in the process(es) involved in contextual cuing but also identify several striking regularities across observers. We find strong support for both the decision threshold account as well as the novel perceptual learning account. We find relatively weak support for the expedited search account.

In his commentary, Bundesen (2018) argued that limited encoding capacity can account for the near-equivalent set size effects on performance under conditions of simultaneous and sequential presentation reported by Sewell, Lilburn, and Smith (2014). While we agree that limited encoding capacity could, in principle, account for this equivalency, we argue that such an account rests on a number of fortuitous temporal coincidences. In particular, we note that pure encoding capacity limitations appear ill equipped to explain near-equivalent simultaneous-sequential performance across a range of stimulus exposure durations, set sizes, and with stimuli with quite different attentional demands. (PsycINFO Database Record, ((c) 2018 APA, all rights reserved).)

A central question in working memory research concerns the degree to which information in working memory is accessible to other cognitive processes (e.g., decision-making). Theories assuming that the focus of attention can only store a single object at a time require the focus to orient to a target representation before further processing can occur. The need to orient the focus of attention implies that single-object accounts typically predict response time costs associated with object selection even when working memory is not full (i.e., memory load is less than 4 items). For other theories that assume storage of multiple items in the focus of attention, predictions depend on specific assumptions about the way resources are allocated among items held in the focus, and how this affects the time course of retrieval of items from the focus. These broad theoretical accounts have been difficult to distinguish because conventional analyses fail to separate components of empirical response times related to decision-making from components related to selection and retrieval processes associated with accessing information in working memory. To better distinguish these response time components from one another, we analyze data from a probed visual working memory task using extensions of the diffusion decision model. Analysis of model parameters revealed that increases in memory load resulted in (a) reductions in the quality of the underlying stimulus representations in a manner consistent with a sample size model of visual working memory capacity and (b) systematic increases in the time needed to selectively access a probed representation in memory. The results are consistent with single-object theories of the focus of attention. The results are also consistent with a subset of theories that assume a multiobject focus of attention in which resource allocation diminishes both the quality and accessibility of the underlying representations. (PsycINFO Database Record, ((c) 2016 APA, all rights reserved).)

We investigated the capacity of visual short-term memory (VSTM) in a phase discrimination task that required judgments about the configural relations between pairs of black and white features. Sewell et al. (2014) previously showed that VSTM capacity in an orientation discrimination task was well described by a sample-size model, which views VSTM as a resource comprised of a finite number of noisy stimulus samples. The model predicts the invariance of [Formula: see text] , the sum of squared sensitivities across items, for displays of different sizes. For phase discrimination, the set-size effect significantly exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items in the display captures attention and receives a disproportionate share of resources. The choice probabilities and response time distributions from the task were well described by a diffusion decision model in which the drift rates embodied the assumptions of the attention-weighted sample-size model., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Normalization models of visual sensitivity assume that the response of a visual mechanism is scaled divisively by the sum of the activity in the excitatory and inhibitory mechanisms in its neighborhood. Normalization models of attention assume that the weighting of excitatory and inhibitory mechanisms is modulated by attention. Such models have provided explanations of the effects of attention in both behavioral and single-cell recording studies. We show how normalization models can be obtained as the asymptotic solutions of shunting differential equations, in which stimulus inputs and the activity in the mechanism control growth rates multiplicatively rather than additively. The value of the shunting equation approach is that it characterizes the entire time course of the response, not just its asymptotic strength. We describe two models of attention based on shunting dynamics, the integrated system model of Smith and Ratcliff (2009) and the competitive interaction theory of Smith and Sewell (2013). These models assume that attention, stimulus salience, and the observer's strategy for the task jointly determine the selection of stimuli into visual short-term memory (VSTM) and the way in which stimulus representations are weighted. The quality of the VSTM representation determines the speed and accuracy of the decision. The models provide a unified account of a variety of attentional phenomena found in psychophysical tasks using single-element and multi-element displays. Our results show the generality and utility of the normalization approach to modeling attention., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Research suggests that visual short-term memory (VSTM) has both an item capacity, of around 4 items, and an information capacity. We characterize the information capacity limits of VSTM using a task in which observers discriminated the orientation of a single probed item in displays consisting of 1, 2, 3, or 4 orthogonally oriented Gabor patch stimuli that were presented in noise for 50 ms, 100 ms, 150 ms, or 200 ms. The observed capacity limitations are well described by a sample-size model, which predicts invariance of ∑(i)(d'(i))² for displays of different sizes and linearity of (d'(i))² for displays of different durations. Performance was the same for simultaneous and sequentially presented displays, which implicates VSTM as the locus of the observed invariance and rules out explanations that ascribe it to divided attention or stimulus encoding. The invariance of ∑(i)(d'(i))² is predicted by the competitive interaction theory of Smith and Sewell (2013), which attributes it to the normalization of VSTM traces strengths arising from competition among stimuli entering VSTM., (PsycINFO Database Record (c) 2014 APA, all rights reserved.)

We generalize the integrated system model of Smith and Ratcliff (2009) to obtain a new theory of attentional selection in brief, multielement visual displays. The theory proposes that attentional selection occurs via competitive interactions among detectors that signal the presence of task-relevant features at particular display locations. The outcome of the competition, together with attention, determines which stimuli are selected into visual short-term memory (VSTM). Decisions about the contents of VSTM are made by a diffusion-process decision stage. The selection process is modeled by coupled systems of shunting equations, which perform gated where-on-what pathway VSTM selection. The theory provides a computational account of key findings from attention tasks with near-threshold stimuli. These are (a) the success of the MAX model of visual search and spatial cuing, (b) the distractor homogeneity effect, (c) the double-target detection deficit, (d) redundancy costs in the post-stimulus probe task, (e) the joint item and information capacity limits of VSTM, and (f) the object-based nature of attentional selection. We argue that these phenomena are all manifestations of an underlying competitive VSTM selection process, which arise as a natural consequence of our theory., (PsycINFO Database Record (c) 2013 APA, all rights reserved.)

The concept of attention is central to theorizing in learning as well as in working memory. However, research to date has yet to establish how attention as construed in one domain maps onto the other. We investigate two manifestations of attention in category- and cue-learning to examine whether they might provide common ground between learning and working memory. Experiment 1 examined blocking and highlighting effects in an associative learning paradigm, which are widely thought to be attentionally mediated. No relationship between attentional performance indicators and working memory capacity (WMC) was observed, despite the fact that WMC was strongly associated with overall learning performance. Experiment 2 used a knowledge restructuring paradigm, which is known to require recoordination of partial category knowledge using representational attention. We found that the extent to which people successfully recoordinated their knowledge was related to WMC. The results illustrate a link between WMC and representational-but not dimensional-attention in category learning., ((PsycINFO Database Record (c) 2012 APA, all rights reserved).)

The attention literature distinguishes two general mechanisms by which attention can benefit performance: gain (or resource) models and orienting (or switching) models. In gain models, processing efficiency is a function of a spatial distribution of capacity or resources; in orienting models, an attentional spotlight must be aligned with the stimulus location, and processing efficiency is a function of when this occurs. Although they involve different processing mechanisms, these models are difficult to distinguish empirically. We compared performance with abrupt-onset and no-onset Gabor patch stimuli in a cued detection task in which we obtained distributions of reaction time (RT) and accuracy as a function of stimulus contrast. In comparison to abrupt-onset stimuli, RTs to miscued no-onset stimuli were increased and accuracy was reduced. Modeling the data with the integrated system model of Philip L. Smith and Roger Ratcliff (2009) provided evidence for reallocation of processing resources during the course of a trial, consistent with an orienting account. Our results support a view of attention in which processing efficiency depends on a dynamic spatiotemporal distribution of resources that has both gain and orienting properties., ((c) 2012 APA, all rights reserved.)

The relationship between attention and visual masking was investigated in a cued detection task using a factorial masking manipulation. Stimuli were either unmasked, or were masked with simultaneous (integration) masks, or delayed (interruption) masks, or integration-interruption mask pairs. The cuing effects in detection sensitivity were smallest with unmasked stimuli, intermediate with single masks, and largest with integration-interruption pairs. Large cuing effects in RT were found in all stimulus conditions. The results are inconsistent with general mechanisms of contrast gain and response gain, which do not predict interactions with interruption masks. The data were modeled using the integrated system model of visual attention of P. L. Smith and R. Ratcliff (2009), which provides an account of both RT and accuracy. The model fits suggest the action of two independent attentional mechanisms: an early selection mechanism that enhances the perceptual representation of attended, noisy stimuli, and a late selection mechanism that increases the rate of information transfer to visual short-term memory. The results are consistent with a distributed, multi-locus system of attentional control.

The gaze cueing effect is the tendency for people to respond faster to targets appearing at locations gazed at by others, compared with locations gazed away from by others. The effect is robust, widely studied, and is an influential finding within social cognition. Formal evidence accumulation models provide the dominant theoretical account of the cognitive processes underlying speeded decision-making, but they have rarely been applied to social cognition research. In this study, using a combination of individual-level and hierarchical computational modelling techniques, we applied evidence accumulation models to gaze cueing data (three data sets total, N = 171, 139,001 trials) for the first time to assess the relative capacity that an attentional orienting mechanism and information processing mechanisms have for explaining the gaze cueing effect. We found that most participants were best described by the attentional orienting mechanism, such that response times were slower at gazed away from locations because they had to reorient to the target before they could process the cue. However, we found evidence for individual differences, whereby the models suggested that some gaze cueing effects were driven by a short allocation of information processing resources to the gazed at location, allowing for a brief period where orienting and processing could occur in parallel. There was exceptionally little evidence to suggest any sustained reallocation of information processing resources neither at the group nor individual level. We discuss how this individual variability might represent credible individual differences in the cognitive mechanisms that subserve behaviourally observed gaze cueing effects. [ABSTRACT FROM AUTHOR]

Elderly bilingual speakers exhibit a response time (RT) advantage on tests of executive function such as the Flanker task. There is, however, a lack of consensus regarding the cognitive mechanisms underlying this bilingual advantage . We analysed Flanker task performance from elderly bilingual (N = 29, age range = 55–75) and monolingual (N = 27, age range = 53–75) speakers using Ratcliff's (1978) diffusion model, which conceptualizes decision-making as a stochastic evidence accumulation process governed by parameters with empirically validated psychological interpretations. These parameters were analysed to investigate differences in cognitive processing between bilingual and monolingual groups in flanker RT performance. A bilingual advantage on decision making onset (the non-decision time parameter) was observed. Non-decision time was shorter on incongruent flanker trials for bilingual speakers but other parameters relating to quality of evidence (drift rate) and decision criterion (boundary separation) did not differ between groups. We interpret this non-decision time cost as reflecting a process of attentional ‘filtering out’ of distracting information. We therefore contend that lifelong bilingual language experience generates enhanced attentional control for seniors. [ABSTRACT FROM AUTHOR]