scholarly journals Stability and Change in Diffusion Model Parameters over Two Years

2021 ◽  
Vol 9 (2) ◽  
pp. 26
Author(s):  
Mischa von Krause ◽  
Stefan T. Radev ◽  
Andreas Voss ◽  
Martin Quintus ◽  
Boris Egloff ◽  
...  
Keyword(s):  
Individual Differences ◽  
Diffusion Model ◽  
Processing Speed ◽  
Rank Order ◽  
Temporal Stability ◽  
Model Parameters ◽  
Stability And Change ◽  
Trade Offs ◽  
Time Period ◽  
Speed Accuracy

In recent years, mathematical models of decision making, such as the diffusion model, have been endorsed in individual differences research. These models can disentangle different components of the decision process, like processing speed, speed–accuracy trade-offs, and duration of non-decisional processes. The diffusion model estimates individual parameters of cognitive process components, thus allowing the study of individual differences. These parameters are often assumed to show trait-like properties, that is, within-person stability across tasks and time. However, the assumption of temporal stability has so far been insufficiently investigated. With this work, we explore stability and change in diffusion model parameters by following over 270 participants across a time period of two years. We analysed four different aspects of stability and change: rank-order stability, mean-level change, individual differences in change, and profile stability. Diffusion model parameters showed strong rank-order stability and mean-level changes in processing speed and speed–accuracy trade-offs that could be attributed to practice effects. At the same time, people differed little in these patterns across time. In addition, profiles of individual diffusion model parameters proved to be stable over time. We discuss implications of these findings for the use of the diffusion model in individual differences research.

scholarly journals Qualitative speed-accuracy tradeoff effects can be explained by a diffusion/fast-guess mixture model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Roger Ratcliff ◽  
Inhan Kang
Keyword(s):  
Mixture Model ◽  
Diffusion Model ◽  
Response Times ◽  
Model Fit ◽  
Orientation Discrimination ◽  
Model Parameters ◽  
Stimulus Contrast ◽  
Accuracy Stress ◽  
Speed Accuracy ◽  
Selective Influence

AbstractRafiei and Rahnev (2021) presented an analysis of an experiment in which they manipulated speed-accuracy stress and stimulus contrast in an orientation discrimination task. They argued that the standard diffusion model could not account for the patterns of data their experiment produced. However, their experiment encouraged and produced fast guesses in the higher speed-stress conditions. These fast guesses are responses with chance accuracy and response times (RTs) less than 300 ms. We developed a simple mixture model in which fast guesses were represented by a simple normal distribution with fixed mean and standard deviation and other responses by the standard diffusion process. The model fit the whole pattern of accuracy and RTs as a function of speed/accuracy stress and stimulus contrast, including the sometimes bimodal shapes of RT distributions. In the model, speed-accuracy stress affected some model parameters while stimulus contrast affected a different one showing selective influence. Rafiei and Rahnev’s failure to fit the diffusion model was the result of driving subjects to fast guess in their experiment.

scholarly journals Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

2019 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Anna-Lena Schubert ◽  
Dirk Hagemann ◽  
Christoph Löffler ◽  
Gidon T. Frischkorn
Keyword(s):  
Individual Differences ◽  
Age Differences ◽  
Processing Speed ◽  
Cognitive Aging ◽  
Fluid Intelligence ◽  
Higher Order ◽  
Mediation Effect ◽  
Model Parameters ◽  
Response Planning ◽  
Age Related

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined.

scholarly journals Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

2019 ◽  
Author(s):  
Anna-Lena Schubert ◽  
Dirk Hagemann ◽  
Christoph Löffler ◽  
Gidon T. Frischkorn
Keyword(s):  
Individual Differences ◽  
Age Differences ◽  
Processing Speed ◽  
Cognitive Aging ◽  
Fluid Intelligence ◽  
Higher Order ◽  
Mediation Effect ◽  
Model Parameters ◽  
Response Planning ◽  
Age Related

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined. Data and analysis code are available at https://osf.io/hy5fw/.

scholarly journals Linking behavioural syndromes and cognition: a behavioural ecology perspective

2012 ◽  
Vol 367 (1603) ◽  
pp. 2762-2772 ◽  
Author(s):  
Andrew Sih ◽  
Marco Del Giudice
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Behavioural Ecology ◽  
Risk Sensitivity ◽  
Model Species ◽  
Behavioural Syndromes ◽  
Trade Offs ◽  
Behavioural Types ◽  
Cognitive Speed ◽  
Speed Accuracy

With the exception of a few model species, individual differences in cognition remain relatively unstudied in non-human animals. One intriguing possibility is that variation in cognition is functionally related to variation in personality. Here, we review some examples and present hypotheses on relationships between personality (or behavioural syndromes) and individual differences in cognitive style. Our hypotheses are based largely on a connection between fast–slow behavioural types (BTs; e.g. boldness, aggressiveness, exploration tendency) and cognitive speed–accuracy trade-offs. We also discuss connections between BTs, cognition and ecologically important aspects of decision-making, including sampling, impulsivity, risk sensitivity and choosiness. Finally, we introduce the notion of cognition syndromes, and apply ideas from theories on adaptive behavioural syndromes to generate predictions on cognition syndromes.

scholarly journals Steadfast Standards or Fluctuating Fancies? Stability and Change in People’s Mate Criteria Over 27 Months

2018 ◽  
Vol 45 (5) ◽  
pp. 671-687 ◽  
Author(s):  
Carrie A. Bredow ◽  
Nicole Hames
Keyword(s):  
Survey Data ◽  
Significant Relationship ◽  
Rank Order ◽  
Temporal Stability ◽  
Mate Preferences ◽  
Age Changes ◽  
Stability And Change ◽  
Individual Level ◽  
Time Points ◽  
The Stability

Although research on mate preferences has been built on the assumption that the criteria people report at one point in time should predict their future partnering behavior, little is known about the temporal stability of people’s standards. Using survey data collected at four time points from 285 originally unmarried individuals, this study examined the rank-order, mean-level, individual-level and ipsative stability of people’s mate criteria over 27 months. Overall, reported standards exhibited moderate to high baseline stability, with rank-order and ipsative estimates comparable to those reported for personality traits. At the same time, mean- and individual-level analyses revealed small, but significant, increases in participants’ reported criteria over the study, as well as significant variability in individual trajectories. Consistent with theory, the stability of individuals’ standards was moderated by several contextual factors, including age, changes in perceived mate value, and significant relationship events.

scholarly journals Developing individual differences in primate behavior: The role of genes, environment and their interplay

2019 ◽  
Author(s):  
Christoph Julian von Borell ◽  
Alexander Weiss ◽  
Lars Penke
Keyword(s):  
Individual Differences ◽  
Social Behavior ◽  
Behavioral Ecology ◽  
Nonhuman Primates ◽  
Behavior Genetics ◽  
Rank Order ◽  
Future Research ◽  
Stability And Change ◽  
Behavioral Stability

As is the case for humans, it has long been thought that nonhuman primates can be described in terms of their personality. Scientific observations that support this view include the presence of individual differences in social behavior and that they are relatively stable throughout life. Consequently, individuals are constrained in their behavioral flexibility when dealing with various environmental challenges. Still, the variation among individuals during development suggests that the environment influences how primates behave. Research in fields including psychology, behavior genetics, and behavioral ecology have tried to identify the mechanisms responsible for this interplay of behavioral stability and change. In this review we integrate theories and findings from research on humans and nonhuman primates that highlight how and to what extent genetic and environmental contributions shape the development of social behavior. To do so we first provide an overview and define what is meant by mean level and rank-order change of behavior. We then review explanations of behavioral stability and change, focusing on the role of genetic effects, how environmental circumstances influence behavioral variation throughout development, and how genetic and environmental influences may interact to produce this variation. Finally, we point to future research directions that could help us to further understand the development of social behavior in primates from within a behavior genetics framework.

scholarly journals Cognitive styles: speed–accuracy trade-offs underlie individual differences in archerfish

2020 ◽  
Vol 160 ◽  
pp. 1-14 ◽  
Author(s):  
Nick A.R. Jones ◽  
Mike Webster ◽  
Cait Newport ◽  
Christopher N. Templeton ◽  
Stefan Schuster ◽  
...  
Keyword(s):  
Individual Differences ◽  
Cognitive Styles ◽  
Trade Offs ◽  
Speed Accuracy

Trajectories of Victimization From Early To Mid-Adolescence

2010 ◽  
Vol 38 (1) ◽  
pp. 85-104 ◽  
Author(s):  
Christopher J. Sullivan ◽  
Pamela Wilcox ◽  
Graham C. Ousey
Keyword(s):  
Individual Differences ◽  
Antisocial Behavior ◽  
Empirical Research ◽  
Current Analysis ◽  
Longitudinal Patterns ◽  
Stability And Change ◽  
Intraindividual Change ◽  
Criminological Research ◽  
Time Period ◽  
Growing Body

A rapidly growing body of criminological research focuses on longitudinal trajectories of offending, with the aim of exploring stability and change in antisocial behavior. A particularly intriguing debate within this area involves the issue of whether there are multiple classes of offenders defined by distinct longitudinal patterns of offending. Parallel research on criminal victimization, however, is lacking, with few studies exploring potential variation in individual trajectories of victimization. The current analysis uses data from a panel of nearly 4,000 adolescents observed across a 4-year period to address this question. The authors examined whether there are distinct classes of victimization trajectories across this time period. The analysis revealed four groups. Descriptive analyses for key correlates of victimization were then conducted to explore their potential correspondence with those of the observed victimization classes. The findings have implications for theory and empirical research regarding between-individual differences and intraindividual change in victimization.

scholarly journals Analysis of speed-accuracy trade-offs using the Wiener diffusion model for choice reaction times

2021 ◽  
Author(s):  
Annalise Aleta LaPlume
Keyword(s):  
Response Time ◽  
Diffusion Model ◽  
Response Times ◽  
Reaction Times ◽  
Response Time Data ◽  
Choice Response ◽  
Time Data ◽  
Trade Offs ◽  
R Programming ◽  
Speed Accuracy

A methodology review paper on the utility and challenges of modelling speed-accuracy trade-offs in response time data. The paper reviews the importance of accounting for speed-accuracy trade-offs when measuring response times, and provides background on diffusion models for response time data. It then describes a practical software implementation of the EZ-diffusion model to model speed-accuracy trade-offs in choice response time data using the R programming language.

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