Publications by authors named "Guy E Hawkins"

In this study, we implement joint modeling of behavioral and single-trial electroencephalography (EEG) data derived from a cued-trials task-switching paradigm to test the hypothesis that trial-by-trial adjustment of response criterion can be linked to changes in the event-related potentials (ERPs) elicited during the cue-target interval (CTI). Specifically, we assess whether ERP components associated with preparation to switch task and preparation of the relevant task are linked to a response criterion parameter derived from a simple diffusion decision model (DDM). Joint modeling frameworks characterize the brain-behavior link by simultaneously modeling behavioral and neural data and implementing a linking function to bind these two submodels.

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Many psychological experiments have subjects repeat a task to gain the statistical precision required to test quantitative theories of psychological performance. In such experiments, time-on-task can have sizable effects on performance, changing the psychological processes under investigation. Most research has either ignored these changes, treating the underlying process as static, or sacrificed some psychological content of the models for statistical simplicity.

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Mind wandering is ubiquitous in everyday life and has a pervasive and profound impact on task-related performance. A range of psychological processes have been proposed to underlie these performance-related decrements, including failures of executive control, volatile information processing, and shortcomings in selective attention to critical task-relevant stimuli. Despite progress in the development of such theories, existing descriptive analyses have limited capacity to discriminate between the theories.

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A fundamental aspect of decision making is the speed-accuracy tradeoff (SAT): slower decisions tend to be more accurate, but because time is a scarce resource people prefer to conclude decisions more quickly. The current research adds to the SAT literature by documenting two previously unrecognized influences on the SAT: perception shifts and goal activation. Decision makers' perceptions of what constitutes a or a decision, and what constitutes an or decision, are based on prior experience, and these perceptions influence decision speed.

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Model comparison is the cornerstone of theoretical progress in psychological research. Common practice overwhelmingly relies on tools that evaluate competing models by balancing in-sample descriptive adequacy against model flexibility, with modern approaches advocating the use of marginal likelihood for hierarchical cognitive models. Cross-validation is another popular approach but its implementation remains out of reach for cognitive models evaluated in a Bayesian hierarchical framework, with the major hurdle being its prohibitive computational cost.

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Research has begun to investigate how goals for emotion experience-how people want to feel-influence the selection of emotion regulation strategies to achieve these goals. We make the case that it is not only how people want to that affects strategy selection, but also how they want to be seen to feel. Incorporating this expressive dimension distinguishes four unique emotion goals: (1) to experience and express emotion; (2) to experience but not express emotion; (3) to express but not experience emotion; and (4) to neither experience nor express emotion.

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Classical dynamic theories of decision making assume that responses are triggered by accumulating a threshold amount of information. Recently, there has been a growing appreciation that the passage of time also plays a role in triggering responses. We propose that decision processes are composed of 2 diffusive accumulation mechanisms-1 evidence-based and 1 time-based-that compete in an independent race architecture.

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It is commonly assumed that a specific testing occasion (task, design, procedure, etc.) provides insights that generalize beyond that occasion. This assumption is infrequently carefully tested in data.

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Background: Decision-making is the process of choosing and performing actions in response to sensory cues to achieve behavioral goals. Many mathematical models have been developed to describe the choice behavior and response time (RT) distributions of observers performing decision-making tasks. However, relatively few researchers use these models because it demands expertise in various numerical, statistical, and software techniques.

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An important feature of human cognition is the ability to flexibly and efficiently adapt behavior in response to continuously changing contextual demands. We leverage a large-scale dataset from Lumosity, an online cognitive-training platform, to investigate how cognitive processes involved in cued switching between tasks are affected by level of task practice across the adult lifespan. We develop a computational account of task switching that specifies the temporal dynamics of activating task-relevant representations and inhibiting task-irrelevant representations and how they vary with extended task practice across a number of age groups.

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Theories of perceptual decision making have been dominated by the idea that evidence accumulates in favor of different alternatives until some fixed threshold amount is reached, which triggers a decision. Recent theories have suggested that these thresholds may not be fixed during each decision but change as time passes. These collapsing thresholds can improve performance in particular decision environments, but reviews of data from typical decision-making paradigms have failed to support collapsing thresholds.

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The sustained attention to response task (SART) has been the primary method of studying the phenomenon of mind wandering. We develop and experimentally test the first integrated cognitive process model that quantitatively explains all stationary features of behavioral performance in the SART. The model assumes that performance is generated by a competitive race between a stimulus-related decision process and a stimulus-unrelated rhythmic response process.

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Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method that is frequently used to study cortical excitability changes and their impact on cognitive functions in humans. While most stimulators are capable of operating in double-blind mode, the amount of discomfort experienced during tDCS may break blinding. Therefore, specifically designed sham stimulation protocols are being used.

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Transcranial direct current stimulation (tDCS) has been proposed to be able to modulate different cognitive functions. However, recent meta-analyses conclude that its efficacy is still in question. Recently, an increase in subjects' propensity to mind-wander has been reported as a consequence of anodal stimulation of the left dorsolateral prefrontal cortex (Axelrod et al.

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The study of non-human primates has been foundational in understanding the neural origins of human decision processes, yet the approach rests on the assumption that one can validly extrapolate from the animal to the human. In the context of decision making, this requires constancy across species in physiological and cognitive processes. The former cannot be experimentally validated and therefore remains assumed, and recent findings have called into question the latter: non-human primates become increasingly urgent as the time spent making a decision increases, but humans do not; from a normative perspective, monkeys are making closer-to-optimal decisions than humans.

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Article Synopsis
  • Most data analyses in psychology utilize models, including cognitive models that interpret variables into psychological constructs, with response time models focusing on factors like processing ease, caution, and bias.
  • In a study with 17 research teams analyzing the same 14 data sets, teams operated blindly to determine manipulated aspects of behavior in a two-alternative forced choice task, leading to similar conclusions across various models and methods, despite the impact of modeler’s choices on inferences.
  • The findings suggest that simpler cognitive models are as effective as complex ones for analyzing response time data in standard experiments, while also highlighting circumstances where more complicated approaches might be necessary and the potential pitfalls of interpreting model results.
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We investigate a question relevant to the psychology and neuroscience of perceptual decision-making: whether decisions are based on steadily accumulating evidence, or only on the most recent evidence. We report an empirical comparison between two of the most prominent examples of these theoretical positions, the diffusion model and the urgency-gating model, via model-based qualitative and quantitative comparisons. Our findings support the predictions of the diffusion model over the urgency-gating model, and therefore, the notion that evidence accumulates without much decay.

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Three studies reexamined the claim that clarifying the causal origin of key statistics can increase normative performance on Bayesian problems involving judgment under uncertainty. Experiments 1 and 2 found that causal explanation did not increase the rate of normative solutions. However, certain types of causal explanation did lead to a reduction in the magnitude of errors in probability estimation.

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MicroRNAs (miRNAs) within the ventral and dorsal striatum have been shown to regulate addiction-relevant behaviours. However, it is unclear how cocaine experience alone can alter the expression of addiction-relevant miRNAs within striatal subregions. Further, it is not known whether differential expression of miRNAs in the striatum contributes to individual differences in addiction vulnerability.

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Functional neuroimaging data indicate the dorsal striatum is engaged when people are required to vary the cautiousness of their decisions, by emphasizing the speed or accuracy of responding in laboratory-based decision tasks. However, the functional contribution of the striatum to decision making is unknown. In the current study we tested patients with focal ischemic lesions of the dorsal striatum and matched non-lesion control participants on a speed-accuracy tradeoff (SAT) task.

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In recent years there has been a significant commercial interest in 'brain training' - massed or spaced practice on a small set of tasks to boost cognitive performance. Recently, researchers have combined cognitive training regimes with brain stimulation to try and maximize training benefits, leading to task-specific cognitive enhancement. It remains unclear, however, whether the performance gains afforded by such regimes can transfer to untrained tasks, or how training and stimulation affect the brain's latent information processing dynamics.

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Deciding between multiple courses of action often entails an increasing need to do something as time passes - a sense of urgency. This notion of urgency is not incorporated in standard theories of speeded decision making that assume information is accumulated until a critical fixed threshold is reached. Yet, it is hypothesized in novel theoretical models of decision making.

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The role of the default-mode network (DMN) in the emergence of mind wandering and task-unrelated thought has been studied extensively. In parallel work, mind wandering has been associated with neuromodulation via the locus coeruleus (LC) norepinephrine (LC-NE) system. Here we propose a neural model that links the two systems in an integrative framework.

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