scholarly journals Modeling Distracted Performance

2019 ◽  
Author(s):  
Guy Hawkins ◽  
Matthias Mittner ◽  
Birte Forstmann ◽  
Andrew Heathcote
Keyword(s):  
Response Time ◽  
Process Model ◽  
Race Model ◽  
Mind Wandering ◽  
Choice Response ◽  
Response Process ◽  
Underlying Principle ◽  
Inter Trial Interval ◽  
Response Time Distributions ◽  
Response Task

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. We propose that the stimulus-unrelated process entrains to timing regularities in the task environment, and is unconditionally triggered as a habit or 'insurance policy' to protect against the deleterious effects of mind wandering on ongoing task performance. For two SART experiments the model provided a quantitatively precise account of a range of previously reported trends in choice, response time and self-reported mind wandering data. It also accounted for three previously unidentified features of response time distributions that place critical constraints on cognitive models of performance in situations when people might engage in task-unrelated thoughts. Furthermore, the parameters of the rhythmic race model were meaningfully associated with participants' self-reported distraction, even though the model was never informed by these data. In a validation test, we disrupted the latent rhythmic component with a manipulation of inter-trial-interval variability, and showed that the architecture of the model provided insight into its counter-intuitive effect. We conclude that performance in the presence of mind wandering can be conceived as a competitive latent decision vs. rhythmic response process. We discuss how the rhythmic race model is not restricted to the study of distraction or mind wandering; it is applicable to any domain requiring repetitive responding where evidence accumulation is assumed to be an underlying principle of behavior.

scholarly journals Evidence Accumulation Models: Current Limitations and Future Directions

2019 ◽  
Author(s):  
Nathan J. Evans ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Decision Making ◽  
Response Time ◽  
Cognitive Processes ◽  
Measurement Tool ◽  
Decision Making Process ◽  
Choice Response ◽  
Experimental Conditions ◽  
Evidence Accumulation ◽  
Choice Response Time ◽  
Response Time Distributions

Evidence accumulation models (EAMs) have been the dominant models of speeded decision-making for several decades. These models propose that evidence accumulates for decision alternatives at some rate, until the evidence for one alternative reaches some threshold that triggers a decision. As a theory, EAMs have provided an accurate account of the choice response time distributions in a range of decision-making tasks, and as a measurement tool, EAMs have provided direct insight into how cognitive processes differ between groups and experimental conditions, resulting in EAMs becoming the standard paradigm of speeded decision-making. However, we argue that there are several limitations to how EAMs are currently tested and applied, which have begun to limit their value as a standard paradigm. Specifically, we believe that a theoretical plateau has been reached for the level of explanation that EAMs can provide about the decision-making process, and that applications of EAMs have started to become restrictive and of limited value. We provide several recommendations for how researchers can help to overcome these limitations. As a theory, we believe that EAMs can provide further value through being constrained by sources of data beyond the standard choice response time distributions, being extended to the entire decision-making process from encoding to responding, and having the random sources of variability replaced by systematic sources of variability. As a measurement tool, we believe that EAMs can provide further value through being a default method of inference for cognitive psychology in place of mean response time and choice, and being applied to a broader range of empirical questions that better capture individual differences in cognitive processes.

Generalizations of the Race Model Inequality

2013 ◽  
Vol 26 (1-2) ◽  
pp. 95-122 ◽  
Author(s):  
Matthias Gondan ◽  
Steven P. Blurton
Keyword(s):  
Response Time ◽  
Statistical Power ◽  
Response Times ◽  
Race Model ◽  
Response Time Distribution ◽  
Stopping Rules ◽  
Race Model Inequality ◽  
Cumulative Response ◽  
Processing Modes ◽  
Response Time Distributions

In redundant signals tasks, participants respond in the same way to two different stimuli which are presented either alone or in combination (redundant stimuli). Responses to redundant stimuli are typically faster than responses to single stimuli. Different explanations account for such redundancy gains, including race models and coactivation models. Race models predict that the cumulative response time distribution for the redundant stimuli never exceeds the summed distributions of the single stimuli (race model inequality, RMI, Miller, 1982). Based on work by Townsend and Nozawa (1995) we demonstrate that the RMI is a special case of a more general interaction contrast of response time distributions for stimuli of different intensity, or stimuli presented with onset asynchrony. The generalization of the RMI is, thus, suited for a much wider class of experiments than the standard setup in which response times for single stimuli are compared to those for double stimuli. Moreover, predictions can be derived not only for the race model, but for serial, parallel, and coactive processing modes with different stopping rules. Compared to the standard RMI, statistical power of these interaction contrasts is satisfactory, even for small onset asynchronies.

scholarly journals The effect of alcohol hangover on choice response time

2016 ◽  
Vol 30 (7) ◽  
pp. 654-661 ◽  
Author(s):  
James A Grange ◽  
Richard Stephens ◽  
Kate Jones ◽  
Lauren Owen
Keyword(s):  
Response Time ◽  
Cognitive Processing ◽  
Process Model ◽  
Response Selection ◽  
Information Value ◽  
Choice Response ◽  
Limited Information ◽  
Processing Efficiency ◽  
Choice Response Time ◽  
Alcohol Hangover

The effect of alcohol hangover on cognitive processing has received little attention. We explored the effect of alcohol hangover on choice response time (RT), a dominant dependent variable (DV) in cognitive research. Prior research of the effect of hangover on RT has produced mixed findings; all studies reviewed relied exclusively on estimates of central tendency (e.g. mean RT), which has limited information value. Here we present novel analytical methods by going beyond mean RT analysis. Specifically, we examined performance in hangover conditions ( n=31) across the whole RT distribution by fitting ex-Gaussian models to participant data, providing a formal description of the RT distribution. This analysis showed detriments to performance under hangover conditions at the slower end of the RT distribution and increased RT variance under hangover conditions. We also fitted an explicit mathematical process model of choice RT – the diffusion model – which estimates parameters reflecting psychologically-meaningful processes underlying choice RT. This analysis showed that hangover reduced information processing efficiency during response selection, and increased response caution; changes in these parameters reflect hangover affecting core decisional-components of RT performance. The implications of the data as well as the methods used for hangover research are discussed.

scholarly journals Associations Between Control Beliefs and Response Time Inconsistency in Older Adults Vary as a Function of Attentional Task Demands

2018 ◽  
Vol 75 (9) ◽  
pp. 1819-1830
Author(s):  
Eric S Cerino ◽  
Robert S Stawski ◽  
G John Geldhof ◽  
Stuart W S MacDonald
Keyword(s):  
Older Adults ◽  
Locus Of Control ◽  
Response Time ◽  
Cognitive Aging ◽  
Perceived Competence ◽  
Task Demands ◽  
Community Dwelling ◽  
Time Inconsistency ◽  
Control Beliefs ◽  
Choice Response

Abstract Objective Control beliefs are established correlates of cognitive aging. Despite recent demonstrations that response time inconsistency (RTI) represents a proxy for cognitive processing efficiency, few investigations have explored links between RTI and psychosocial correlates. We examined associations among RTI and control beliefs (perceived competence and locus of control) for two choice-response time (RT) tasks varying in their attentional demands. Method Control beliefs and RTI were measured weekly for 5 weeks in a sample of 304 community-dwelling older adults (Mage = 74.11 years, SD = 6.05, range = 64–92, 68.58% female). Results Multilevel models revealed that for the attentionally demanding task, reporting higher perceived competence than usual was associated with lower RTI for relatively younger participants and greater RTI for relatively older participants. For the less attentionally demanding task, reporting higher perceived competence than usual was associated with lower RTI for relatively older participants. Links between locus of control and RTI were comparatively scant. Discussion Our findings suggest that control beliefs may have adaptive and maladaptive influences on RTI, depending on dimension of control beliefs, individual differences in level of control beliefs and age, as well as attentional task demands. Both for whom and when control beliefs can be leveraged to optimize cognitive aging are discussed.

Accuracy versus choice response time in sound localization

1996 ◽  
Vol 49 (4) ◽  
pp. 405-417 ◽  
Author(s):  
Sharon M. Abel ◽  
P.Joy Banerjee
Keyword(s):  
Response Time ◽  
Sound Localization ◽  
Choice Response ◽  
Choice Response Time
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