Gilles Dutilh

University of Amsterdam, Amsterdamo, North Holland, Netherlands

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Publications (13)38.77 Total impact

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    ABSTRACT: People generally slow down after they make an error, a phenomenon that is more pronounced for older individuals than it is for young individuals. Here, we examine the origin of this age-related difference in posterror slowing (PES) by applying the diffusion model to data from young and older participants performing a random dot motion task and a lexical decision task. Results show that the PES effects on response time and accuracy were qualitatively different for young and older participants. A diffusion model analysis revealed that following an error, older participants became more cautious, processed information less effectively, and spent more time on irrelevant processes. This pattern was evident in both the random dot motion task and the lexical decision task. For young participants, in contrast, the origin of the PES effect depended on the task that was performed: In the random dot motion task, the PES effect was due to time spent on irrelevant processes; in the lexical decision task, the PES effect was due to increased caution and decreased effectiveness in information processing. Overall, PES effects were much larger in the lexical decision task than in the random dot motion task. These findings indicate that PES originates from the interplay of different psychological processes whose contribution depends on both task settings and individual differences. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
    Psychology and Aging 09/2012; · 2.73 Impact Factor
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    ABSTRACT: In many response time tasks, people slow down after they make an error. This phenomenon of post-error slowing (PES) is thought to reflect an increase in response caution, that is, a heightening of response thresholds in order to increase the probability of a correct response at the expense of response speed. In many empirical studies, PES is quantified as the difference in response time (RT) between post-error trials and post-correct trials. Here we demonstrate that this standard measurement method is prone to contamination by global fluctuations in performance over the course of an experiment. Diffusion model simulations show how global fluctuations in performance can cause either spurious detection of PES or masking of PES. Both confounds are highly undesirable and can be eliminated by a simple solution: quantify PES as the difference in RT between post-error trials and the associated pre-error trials. Experimental data are used as an empirical illustration.
    Journal of Mathematical Psychology 06/2012; 56(3):208–216. · 1.62 Impact Factor
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    ABSTRACT: People tend to slow down after they make an error. This phenomenon, generally referred to as post-error slowing, has been hypothesized to reflect perceptual distraction, time wasted on irrelevant processes, an a priori bias against the response made in error, increased variability in a priori bias, or an increase in response caution. Although the response caution interpretation has dominated the empirical literature, little research has attempted to test this interpretation in the context of a formal process model. Here, we used the drift diffusion model to isolate and identify the psychological processes responsible for post-error slowing. In a very large lexical decision data set, we found that post-error slowing was associated with an increase in response caution and-to a lesser extent-a change in response bias. In the present data set, we found no evidence that post-error slowing is caused by perceptual distraction or time wasted on irrelevant processes. These results support a response-monitoring account of post-error slowing.
    Attention Perception & Psychophysics 11/2011; 74(2):454-65. · 1.97 Impact Factor
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    ABSTRACT: Even in elementary cognitive tasks, alcohol consumption results in both cognitive and motor impairments (e.g., Schweizer and Vogel-Sprott, Exp Clin Psychopharmacol 16: 240-250, 2008). The purpose of this study is to quantify the latent psychological processes that underlie the alcohol-induced decrement in observed performance. In a double-blind experiment, we administered three different amounts of alcohol to participants on different days: a placebo dose (0 g/l), a moderate dose (0.5 g/l), and a high dose (1 g/l). Following this, participants performed a "moving dots" perceptual discrimination task. We analyzed the data using the drift diffusion model. Model parameters drift rate, boundary separation, and non-decision time allow a decomposition of the alcohol effect in terms of their respective cognitive components, that is, rate of information processing, response caution, and non-decision processes (e.g., stimulus encoding, motor processes). We found that alcohol intoxication causes higher mean RTs and lower response accuracies. The diffusion model decomposition showed that alcohol intoxication caused a decrease in drift rate and an increase in non-decision time. In a simple perceptual discrimination task, even a moderate dose of alcohol decreased the rate of information processing and negatively affected the non-decision component. However, alcohol consumption left response caution largely intact.
    Psychopharmacology 08/2011; 219(4):1017-25. · 4.06 Impact Factor
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    ABSTRACT: When people repeatedly practice the same cognitive task, their response times (RT) invariably decrease. Dutilh, Vandekerckhove, Tuerlinckx, and Wagenmakers (2009) argued that the traditional focus on how mean RT decreases with practice offers limited insight; their diffusion model analysis showed that the effect of practice is multifaceted, involving an increase in rate of information processing, a decrease in response caution, adjusted response bias, and, unexpectedly, a strong decrease in nondecision time. In this study, we aim to further disentangle these effects into stimulus-specific and task-related components. The data of a transfer experiment, in which repeatedly presented sets and new sets of stimuli were alternated, show that the practice effects on both speed of information processing and time needed for peripheral processing are partly task-related and partly stimulus-specific. The effects on response caution and response bias appear to be task-related. This diffusion model decomposition provides a perspective on practice that is more detailed and more informative than the traditional analysis of mean RT.
    Experimental Psychology 05/2011; 58(6):434-42. · 2.22 Impact Factor
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    ABSTRACT: Most models of response time (RT) in elementary cognitive tasks implicitly assume that the speed-accuracy trade-off is continuous: When payoffs or instructions gradually increase the level of speed stress, people are assumed to gradually sacrifice response accuracy in exchange for gradual increases in response speed. This trade-off presumably operates over the entire range from accurate but slow responding to fast but chance-level responding (i.e., guessing). In this article, we challenge the assumption of continuity and propose a phase transition model for RTs and accuracy. Analogous to the fast guess model (Ollman, 1966), our model postulates two modes of processing: a guess mode and a stimulus-controlled mode. From catastrophe theory, we derive two important predictions that allow us to test our model against the fast guess model and against the popular class of sequential sampling models. The first prediction--hysteresis in the transitions between guessing and stimulus-controlled behavior--was confirmed in an experiment that gradually changed the reward for speed versus accuracy. The second prediction--bimodal RT distributions--was confirmed in an experiment that required participants to respond in a way that is intermediate between guessing and accurate responding.
    Cognitive Science A Multidisciplinary Journal 03/2011; 35(2):211-50. · 2.59 Impact Factor
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    ABSTRACT: The Balloon Analogue Risk Task, or BART, aims to measure risk taking behavior in a controlled setting. In order to quantify the processes that underlie performance on the BART, Wallsten, Pleskac, and Lejuez (2005) proposed a series of mathematical models whose parameters have a clear psychological interpretation. Here we examine a 2-parameter simplification of Wallsten et al.’s preferred 4-parameter model. A parameter recovery study shows that — with plausible restrictions on the number of participants and trials — both parameters (i.e., risk taking γ+ and response consistency β) can be estimated accurately. To demonstrate how the 2-parameter model can be used in practice, we implemented a Bayesian hierarchical version and applied it to an empirical data set in which participants performed the BART following various amounts of alcohol intake.
    Journal of Mathematical Psychology 01/2011; · 1.62 Impact Factor
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    ABSTRACT: PRIOR INFORMATION BIASES THE DECISION PROCESS: actions consistent with prior information are executed swiftly, whereas actions inconsistent with prior information are executed slowly. How is this bias implemented in the brain? To address this question we conducted an experiment in which people had to decide quickly whether a cloud of dots moved coherently to the left or to the right. Cues provided probabilistic information about the upcoming stimulus. Behavioral data were analyzed with the linear ballistic accumulator (LBA) model, confirming that people used the cue to bias their decisions. The functional magnetic resonance imaging (fMRI) data showed that presentation of the cue differentially activated orbitofrontal cortex, hippocampus, and the putamen. Directional cues selectively activated the contralateral putamen. The fMRI analysis yielded results only when the LBA bias parameter was included as a covariate, highlighting the practical benefits of formal modeling. Our results suggest that the human brain uses prior information by increasing cortico-striatal activation to selectively disinhibit preferred responses.
    Frontiers in Human Neuroscience 01/2010; 4:40. · 2.91 Impact Factor
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    ABSTRACT: When people repeatedly perform the same cognitive task, their mean response times (RTs) invariably decrease. The mathematical function that best describes this decrease has been the subject of intense debate. Here, we seek a deeper understanding of the practice effect by simultaneously taking into account the changes in accuracy and in RT distributions with practice, both for correct and error responses. To this end, we used the Ratcliff diffusion model, a successful model of two-choice RTs that decomposes the effect of practice into its constituent psychological processes. Analyses of data from a 10,000-trial lexical decision task demonstrate that practice not only affects the speed of information processing, but also response caution, response bias, and peripheral processing time. We conclude that the practice effect consists of multiple subcomponents, and that it may be hazardous to abstract the interactive combination of these subcomponents in terms of a single output measure such as mean RT for correct responses. Supplemental materials may be downloaded from http://pbr.psychonomic-journals.org/content/supplemental.
    Psychonomic Bulletin & Review 12/2009; 16(6):1026-36. · 2.99 Impact Factor
  • NeuroImage 01/2009; 47. · 6.25 Impact Factor
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    ABSTRACT: Human decision-making almost always takes place under time pressure. When people are engaged in activities such as shopping, driving, or playing chess, they have to continually balance the demands for fast decisions against the demands for accurate decisions. In the cognitive sciences, this balance is thought to be modulated by a response threshold, the neural substrate of which is currently subject to speculation. In a speed decision-making experiment, we presented participants with cues that indicated different requirements for response speed. Application of a mathematical model for the behavioral data confirmed that cueing for speed lowered the response threshold. Functional neuroimaging showed that cueing for speed activates the striatum and the pre-supplementary motor area (pre-SMA), brain structures that are part of a closed-loop motor circuit involved in the preparation of voluntary action plans. Moreover, activation in the striatum is known to release the motor system from global inhibition, thereby facilitating faster but possibly premature actions. Finally, the data show that individual variation in the activation of striatum and pre-SMA is selectively associated with individual variation in the amplitude of the adjustments in the response threshold estimated by the mathematical model. These results demonstrate that when people have to make decisions under time pressure their striatum and pre-SMA show increased levels of activation.
    Proceedings of the National Academy of Sciences 12/2008; 105(45):17538-42. · 9.81 Impact Factor
  • Gilles Dutilh
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    ABSTRACT: When people repeatedly perform the same cognitive task, their mean response times (RTs) invariably de- crease. The mathematical function that best describes this decrease has been the subject of intense debate. Here, we seek a deeper understanding of the practice effect by simultaneously taking into account the changes in accuracy and in RT distributions with practice, both for correct and error responses. To this end, we used the Ratcliff diffusion model, a successful model of two-choice RTs that decomposes the effect of practice into its constituent psychological processes. Analyses of data from a 10,000-trial lexical decision task demonstrate that practice not only affects the speed of information processing, but also response caution, response bias, and peripheral processing time. We conclude that the practice effect consists of multiple subcomponents, and that it may be hazardous to abstract the interactive combination of these subcomponents in terms of a single output measure such as mean RT for correct responses. Supplemental materials may be downloaded from http://pbr .psychonomic-journals.org/content/supplemental.
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    ABSTRACT: Ph: (+31) 20–525–6629 E–mail may be sent to gilles.dutilh@gmail.com. People generally slow down after they make an error, a phenomenon that is more pronounced for elderly participants than it is for young participants. Here we examine the origin of this age–related difference in post–error slowing (PES) by applying the diffusion model to data from young and elderly participants performing a random dot motion task. Results show that the PES effects on response time and accuracy were qualitatively different for young and el-derly participants. A diffusion model analysis revealed that following an error, elderly par-ticipants became more cautious, processed information less effectively, and spent more time on irrelevant processes (e.g., overcoming disappointment). For young participants, however, PES was captured predominantly by a modest increase in time wasted on irrelevant processes. These findings indicate that for elderly participants, PES originates from the interplay of three different psychological processes.