scholarly journals Supplemental Material for Hierarchical Diffusion Models for Two-Choice Response Times

2011 ◽  
Keyword(s):  
Response Times ◽  
Diffusion Models ◽  
Choice Response ◽  
Hierarchical Diffusion

scholarly journals Hierarchical diffusion models for two-choice response times.

2011 ◽  
Vol 16 (1) ◽  
pp. 44-62 ◽  
Author(s):  
Joachim Vandekerckhove ◽  
Francis Tuerlinckx ◽  
Michael D. Lee
Keyword(s):  
Response Times ◽  
Diffusion Models ◽  
Choice Response ◽  
Hierarchical Diffusion

scholarly journals Combining Visual Contrast Information with Sound Can Produce Faster Decisions

2019 ◽  
Author(s):  
Birgitta Dresp-Langley ◽  
Marie Monfouga
Keyword(s):  
Response Times ◽  
Luminance Contrast ◽  
Forced Choice ◽  
Sound Frequency ◽  
Choice Response ◽  
Relative Depth ◽  
Probability Summation ◽  
Visual Contrast ◽  
Contrast Information ◽  
The Right

Pieron's and Chocholle’s seminal psychophysical work predicts that human response time to information relative to visual contrast and/or sound frequency decreases when contrast intensity or sound frequency increases. The goal of this study is to bring to the fore the ability of individuals to use visual contrast intensity and sound frequency in combination for faster perceptual decisions of relative depth (“nearer”) in planar (2D) object configurations on the basis of physical variations in luminance contrast. Computer controlled images with two abstract patterns of varying contrast intensity, one on the left and one on the right, preceded or not by a pure tone of varying frequency, were shown to healthy young humans in controlled experimental sequences. Their task (two-alternative forced-choice) was to decide as quickly as possible which of two patterns, the left or the right one, in a given image appeared to “stand out as if it were nearer” in terms of apparent (subjective) visual depth. The results show that the combinations of varying relative visual contrast with sounds of varying frequency exploited here produced an additive effect on choice response times in terms of facilitation, where a stronger visual contrast combined with a higher sound frequency produced shorter forced-choice response times. This new effect is predicted by cross-modal audio-visual probability summation.

Reinforcement-Based Decision Making in Corticostriatal Circuits: Mutual Constraints by Neurocomputational and Diffusion Models

2012 ◽  
Vol 24 (5) ◽  
pp. 1186-1229 ◽  
Author(s):  
Roger Ratcliff ◽  
Michael J. Frank
Keyword(s):  
Decision Making ◽  
Diffusion Model ◽  
Response Times ◽  
Simulated Data ◽  
Diffusion Models ◽  
Choice Data ◽  
Interactive Decision Making ◽  
Corticostriatal Circuits ◽  
Nondecision Time

In this letter, we examine the computational mechanisms of reinforce-ment-based decision making. We bridge the gap across multiple levels of analysis, from neural models of corticostriatal circuits—the basal ganglia (BG) model (Frank, 2005 , 2006 ) to simpler but mathematically tractable diffusion models of two-choice decision making. Specifically, we generated simulated data from the BG model and fit the diffusion model (Ratcliff, 1978 ) to it. The standard diffusion model fits underestimated response times under conditions of high response and reinforcement conflict. Follow-up fits showed good fits to the data both by increasing nondecision time and by raising decision thresholds as a function of conflict and by allowing this threshold to collapse with time. This profile captures the role and dynamics of the subthalamic nucleus in BG circuitry, and as such, parametric modulations of projection strengths from this nucleus were associated with parametric increases in decision boundary and its modulation by conflict. We then present data from a human reinforcement learning experiment involving decisions with low- and high-reinforcement conflict. Again, the standard model failed to fit the data, but we found that two variants similar to those that fit the BG model data fit the experimental data, thereby providing a convergence of theoretical accounts of complex interactive decision-making mechanisms consistent with available data. This work also demonstrates how to make modest modifications to diffusion models to summarize core computations of the BG model. The result is a better fit and understanding of reinforcement-based choice data than that which would have occurred with either model alone.

scholarly journals Effects of Short-Term Physical Activity Interventions on Simple and Choice Response Times

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Kevin Norton ◽  
Lynda Norton ◽  
Nicole Lewis
Keyword(s):  
Physical Activity ◽  
Response Time ◽  
Human Performance ◽  
Response Times ◽  
Exercise Program ◽  
Rate Of Change ◽  
Choice Response ◽  
Before And After ◽  
Age Range ◽  
Active Adults

Objective. Response time (RT) is important for health and human performance and provides insight into cognitive processes. It deteriorates with age, is associated with chronic physical activity (PA), and improves with PA interventions. We investigated associations between the amount and type of PA undertaken and the rate of change in RT for low-active adults across the age range 18–63 yr.Methods. Insufficiently active adults were assigned to either a walking (n=263) or higher-intensity (n=380) exercise program conducted over 40 days. Active controls were also recruited (n=135). Simple response time (SRT) and choice response time (CRT) were measured before and after the intervention and at 3-, 6-, and 12-month follow-up.Results. SRT and CRT slowed across the age range; however, habitually active participants at baseline had significantly faster CRT (p<0.05). The interventions increased weekly PA with corresponding increases in physical fitness. These changes were mirrored in faster CRT across the study for both intervention groups (p<0.05). No changes were found for SRT.Conclusions. Both PA interventions resulted in improvements in CRT among adults starting from a low activity base. These improvements were relatively rapid and occurred in both interventions despite large differences in exercise volume, type, and intensity. There were no effects on SRT in either intervention.

scholarly journals Combining Visual Contrast Information with Sound Can Produce Faster Decisions

Information ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 346 ◽  
Author(s):  
Birgitta Dresp-Langley ◽  
Marie Monfouga
Keyword(s):  
Response Times ◽  
Luminance Contrast ◽  
Forced Choice ◽  
Sound Frequency ◽  
Choice Response ◽  
Relative Depth ◽  
Probability Summation ◽  
Visual Contrast ◽  
Contrast Information ◽  
The Right

Pieron’s and Chocholle’s seminal psychophysical work predicts that human response time to information relative to visual contrast and/or sound frequency decreases when contrast intensity or sound frequency increases. The goal of this study is to bring to the forefront the ability of individuals to use visual contrast intensity and sound frequency in combination for faster perceptual decisions of relative depth (“nearer”) in planar (2D) object configurations based on physical variations in luminance contrast. Computer controlled images with two abstract patterns of varying contrast intensity, one on the left and one on the right, preceded or not by a pure tone of varying frequency, were shown to healthy young humans in controlled experimental sequences. Their task (two-alternative, forced-choice) was to decide as quickly as possible which of two patterns, the left or the right one, in a given image appeared to “stand out as if it were nearer” in terms of apparent (subjective) visual depth. The results showed that the combinations of varying relative visual contrast with sounds of varying frequency exploited here produced an additive effect on choice response times in terms of facilitation, where a stronger visual contrast combined with a higher sound frequency produced shorter forced-choice response times. This new effect is predicted by audio-visual probability summation.

scholarly journals On the Relation Between the (Censored) Shifted Wald and the Wiener Distribution as Measurement Models for Choice Response Times

2017 ◽  
Vol 42 (2) ◽  
pp. 116-135 ◽  
Author(s):  
Robert Miller ◽  
Stefan Scherbaum ◽  
Daniel W. Heck ◽  
Thomas Goschke ◽  
Sören Enge
Keyword(s):  
Response Times ◽  
Measurement Tool ◽  
Parameter Estimates ◽  
Choice Response ◽  
Diffusion Modeling ◽  
Measurement Models ◽  
Diffusion Parameters ◽  
Parametric Survival ◽  
Omission Errors ◽  
Parametric Survival Analysis

Inferring processes or constructs from performance data is a major hallmark of cognitive psychometrics. Particularly, diffusion modeling of response times (RTs) from correct and erroneous responses using the Wiener distribution has become a popular measurement tool because it provides a set of psychologically interpretable parameters. However, an important precondition to identify all of these parameters is a sufficient number of RTs from erroneous responses. In the present article, we show by simulation that the parameters of the Wiener distribution can be recovered from tasks yielding very high or even perfect response accuracies using the shifted Wald distribution. Specifically, we argue that error RTs can be modeled as correct RTs that have undergone censoring by using techniques from parametric survival analysis. We illustrate our reasoning by fitting the Wiener and (censored) shifted Wald distribution to RTs from six participants who completed a Go/No-go task. In accordance with our simulations, diffusion modeling using the Wiener and the shifted Wald distribution yielded identical parameter estimates when the number of erroneous responses was predicted to be low. Moreover, the modeling of error RTs as censored correct RTs substantially improved the recovery of these diffusion parameters when premature trial timeout was introduced to increase the number of omission errors. Thus, the censored shifted Wald distribution provides a suitable means for diffusion modeling in situations when the Wiener distribution cannot be fitted without parametric constraints.

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