scholarly journals Qualitative speed-accuracy tradeoff effects that cannot be explained by the diffusion model under the selective influence assumption

2020 ◽  
Author(s):  
Farshad Rafiei ◽  
Dobromir Rahnev
Keyword(s):  
Diffusion Model ◽  
Discrimination Task ◽  
Drift Rate ◽  
Response Times ◽  
Perceptual Discrimination ◽  
The Difference ◽  
Speed Accuracy ◽  
Selective Influence ◽  
Accuracy Tradeoff ◽  
Rt Distributions

It is often thought that the diffusion model explains all effects related to the speed-accuracy tradeoff (SAT) but this has previously been examined with only a few SAT conditions or only a few subjects. Here we collected data from 20 subjects who performed a perceptual discrimination task with five different difficulty levels and five different SAT conditions (5,000 trials/subject). We found that the five SAT conditions produced robustly U-shaped curves for (i) the difference between error and correct response times (RTs), (ii) the ratio of the standard deviation and mean of the RT distributions, and (iii) the skewness of the RT distributions. Critically, the diffusion model where only drift rate varies with contrast and only boundary varies with SAT could not account for any of the three U-shaped curves. Further, allowing all parameters to vary across conditions revealed that both the SAT and difficulty manipulations resulted in substantial modulations in every model parameter, while still providing imperfect fits to the data. These findings demonstrate that the diffusion model cannot fully explain the effects of SAT and establishes three robust but challenging effects that models of SAT should account for.

scholarly journals Qualitative speed-accuracy tradeoff effects that cannot be explained by the diffusion model under the selective influence assumption

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Farshad Rafiei ◽  
Dobromir Rahnev
Keyword(s):  
Diffusion Model ◽  
Discrimination Task ◽  
Drift Rate ◽  
Response Times ◽  
Perceptual Discrimination ◽  
The Difference ◽  
Speed Accuracy ◽  
Selective Influence ◽  
Accuracy Tradeoff ◽  
Rt Distributions

AbstractIt is often thought that the diffusion model explains all effects related to the speed-accuracy tradeoff (SAT) but this has previously been examined with only a few SAT conditions or only a few subjects. Here we collected data from 20 subjects who performed a perceptual discrimination task with five different difficulty levels and five different SAT conditions (5000 trials/subject). We found that the five SAT conditions produced robustly U-shaped curves for (i) the difference between error and correct response times (RTs), (ii) the ratio of the standard deviation and mean of the RT distributions, and (iii) the skewness of the RT distributions. Critically, the diffusion model where only drift rate varies with contrast and only boundary varies with SAT could not account for any of the three U-shaped curves. Further, allowing all parameters to vary across conditions revealed that both the SAT and difficulty manipulations resulted in substantial modulations in every model parameter, while still providing imperfect fits to the data. These findings demonstrate that the diffusion model cannot fully explain the effects of SAT and establishes three robust but challenging effects that models of SAT should account for.

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 Decision Making by Ensembles of Accumulators

2020 ◽  
Author(s):  
Gregory Edward Cox ◽  
Gordon D. Logan ◽  
Jeffrey Schall ◽  
Thomas Palmeri
Keyword(s):  
Decision Making ◽  
Response Times ◽  
Computational Framework ◽  
Neural Ensembles ◽  
High Level ◽  
Speed Accuracy ◽  
The Relationship ◽  
Different Levels ◽  
Accuracy Tradeoff ◽  
Rt Distributions

Evidence accumulation is a computational framework that accounts for behavior as well as the dynamics of individual neurons involved in decision making. Linking these two levels of description reveals a scaling paradox: How do choices and response times (RT) explained by models assuming single accumulators arise from a large ensemble of idiosyncratic accumulator neurons? We created a simulation model that makes decisions by aggregating across ensembles of accumulators, thereby instantiating the essential structure of neural ensembles that make decisions. Across different levels of simulated choice difficulty and speed-accuracy emphasis, choice proportions and RT distributions simulated by the ensembles are invariant to ensemble size and the accumulated evidence at RT is invariant across RT when the accumulators are at least moderately correlated in either baseline evidence or rates of accumulation and when RT is not governed by the most extreme accumulators. To explore the relationship between the low-level ensemble accumulators and high-level cognitive models, we fit simulated ensemble behavior with a standard LBA model. The standard LBA model generally recovered the core accumulator parameters (particularly drift rates and residual time) of individual ensemble accumulators with high accuracy, with variability parameters of the standard LBA modulating as a function of various ensemble parameters. Ensembles of accumulators also provide an alternative conception of speed-accuracy tradeoff without relying on varying thresholds of individual accumulators, instead by adjusting how ensembles of accumulators are aggregated or by how accumulators are correlated within ensembles. These results clarify relationships between neural and computational accounts of decision making.

Alcohol and Speed-Accuracy Tradeoff

1979 ◽  
Vol 21 (4) ◽  
pp. 433-443 ◽  
Author(s):  
O. H. RUNDELL ◽  
HAROLD L. WILLIAMS
Keyword(s):  
Body Weight ◽  
Reaction Time ◽  
Discrimination Task ◽  
The Other ◽  
Pitch Discrimination ◽  
Alcohol Dose ◽  
Independent Effects ◽  
Speed Accuracy ◽  
Accuracy Tradeoff ◽  
And Task

Performance on two auditory choice reaction time (RT) tasks was studied in a group of 12 subjects under the influence of graded doses of ethyl alcohol ranging from placebo to 1 g/kg body weight. Deadline procedures were employed in a side discrimination and a pitch discrimination task to permit the calculation of speed-accuracy tradeoff functions (accuracy versus RT). Accuracy declined as a function of dose, but alcohol did not significantly influence RT. Conversely, accuracy was not affected by task; but the pitch discrimination task required an average of 88 ms more time than the side task. Alcohol dose and task produced independent effects on the speed-accuracy tradeoff function. As dose increased, the slope of the tradeoff function declined; but slopes were equivalent for the two tasks. On the other hand, the x-intercept (where accuracy equals chance levels) was 90 ms greater for the pitch task than for the side task.

scholarly journals Bayesian confidence for drift diffusion observers in dynamic stimuli tasks

2020 ◽  
Author(s):  
Joshua Calder-Travis ◽  
Rafal Bogacz ◽  
Nick Yeung
Keyword(s):  
Diffusion Model ◽  
Drift Rate ◽  
Response Times ◽  
Time Dependent ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Dynamic Stimuli ◽  
Computationally Expensive ◽  
Insight Into ◽  
Confidence Data

AbstractMuch work has explored the possibility that the drift diffusion model, a model of response times and choices, could be extended to account for confidence reports. Many methods for making predictions from such models exist, although these methods either assume that stimuli are static over the course of a trial, or are computationally expensive, making it difficult to capitalise on trial-by-trial variability in dynamic stimuli. Using the framework of the drift diffusion model with time-dependent thresholds, and the idea of a Bayesian confidence readout, we derive expressions for the probability distribution over confidence reports. In line with current models of confidence, the derivations allow for the accumulation of “pipeline” evidence which has been received but not processed by the time of response, the effect of drift rate variability, and metacognitive noise. The expressions are valid for stimuli which change over the course of a trial with normally distributed fluctuations in the evidence they provide. A number of approximations are made to arrive at the final expressions, and we test all approximations via simulation. The derived expressions only contain a small number of standard functions, and only require evaluating once per trial, making trial-by-trial modelling of confidence data in dynamic stimuli tasks more feasible. We conclude by using the expressions to gain insight into the confidence of optimal observers, and empirically observed patterns.

scholarly journals Speed-Accuracy Tradeoffs in Spatial Orientation Information Processing

1983 ◽  
Vol 27 (5) ◽  
pp. 359-363
Author(s):  
Robert E. Schlegel ◽  
William F. Storm
Keyword(s):  
Information Processing ◽  
Response Time ◽  
Ethyl Alcohol ◽  
Spatial Orientation ◽  
Response Times ◽  
Period Analysis ◽  
Alcohol Response ◽  
Orientation Information ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

A study was conducted to further evaluate the Manikin Task, a test of spatial orientation information processing. The objectives of the study were to determine the speed vs. accuracy tradeoff characteristics of the task and to assess performance on the task under the influence of ethyl alcohol. Response times and accuracy were measured on five subjects over a five-week period. Analysis of the data indicated a definite decline in accuracy corresponding to a forced decrease in response time. The effect of alcohol was evidenced by a change in the slope of the speed-accuracy tradeoff function.

scholarly journals The effect of episodic retrieval on inhibition in task switching: a diffusion model analysis

2019 ◽  
Vol 84 (7) ◽  
pp. 1965-1999
Author(s):  
Agnieszka W. Kowalczyk ◽  
James A. Grange
Keyword(s):  
Diffusion Model ◽  
Task Switching ◽  
Drift Rate ◽  
Response Times ◽  
Response Selection ◽  
Task Repetition ◽  
Episodic Retrieval ◽  
Processing Efficiency ◽  
Selection Processes ◽  
The Cost

Abstract Inhibition in task switching is inferred from $$n-2$$ n - 2 task repetition costs: slower response times and poorer accuracy for ABA task switching sequences compared to CBA sequences, thought to reflect the persisting inhibition of task A across an ABA sequence. Much work has examined the locus of this inhibition effect, with evidence that inhibition targets response selection processes. Consistent with this, fits of the diffusion model to $$n-2$$ n - 2 task repetition cost data have shown that the cost is reflected by lower estimates of drift rate, suggesting that inhibition impairs information processing efficiency during response selection. However, we have shown that the $$n-2$$ n - 2 task repetition cost is confounded with episodic retrieval effects which masquerade as inhibitory costs. The purpose of the current study was to conduct a comprehensive analysis of diffusion model fits to new data within a paradigm that controls for episodic interference. Across four experiments (total $$N = 191$$ N = 191 ), we find evidence that the reduction of drift rate for $$n-2$$ n - 2 task repetition costs is only evident under conditions of episodic interference, and the cost is absent when this interference is controlled for. In addition, we also find evidence that episodic retrieval influences task preparation processes and response caution. These findings provide important constraints for theories of task switching that suggest inhibition selectively targets response selection processes.

scholarly journals Neurally constrained modeling of speed-accuracy tradeoff during visual search: gated accumulation of modulated evidence

2019 ◽  
Vol 121 (4) ◽  
pp. 1300-1314 ◽  
Author(s):  
Mathieu Servant ◽  
Gabriel Tillman ◽  
Jeffrey D. Schall ◽  
Gordon D. Logan ◽  
Thomas J. Palmeri
Keyword(s):  
Decision Making ◽  
Visual Search ◽  
Response Times ◽  
Frontal Eye Field ◽  
Search Performance ◽  
Model Framework ◽  
Accumulator Model ◽  
Eye Field ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

Stochastic accumulator models account for response times and errors in perceptual decision making by assuming a noisy accumulation of perceptual evidence to a threshold. Previously, we explained saccade visual search decision making by macaque monkeys with a stochastic multiaccumulator model in which accumulation was driven by a gated feed-forward integration to threshold of spike trains from visually responsive neurons in frontal eye field that signal stimulus salience. This neurally constrained model quantitatively accounted for response times and errors in visual search for a target among varying numbers of distractors and replicated the dynamics of presaccadic movement neurons hypothesized to instantiate evidence accumulation. This modeling framework suggested strategic control over gate or over threshold as two potential mechanisms to accomplish speed-accuracy tradeoff (SAT). Here, we show that our gated accumulator model framework can account for visual search performance under SAT instructions observed in a milestone neurophysiological study of frontal eye field. This framework captured key elements of saccade search performance, through observed modulations of neural input, as well as flexible combinations of gate and threshold parameters necessary to explain differences in SAT strategy across monkeys. However, the trajectories of the model accumulators deviated from the dynamics of most presaccadic movement neurons. These findings demonstrate that traditional theoretical accounts of SAT are incomplete descriptions of the underlying neural adjustments that accomplish SAT, offer a novel mechanistic account of decision-making mechanisms during speed-accuracy tradeoff, and highlight questions regarding the identity of model and neural accumulators. NEW & NOTEWORTHY A gated accumulator model is used to elucidate neurocomputational mechanisms of speed-accuracy tradeoff. Whereas canonical stochastic accumulators adjust strategy only through variation of an accumulation threshold, we demonstrate that strategic adjustments are accomplished by flexible combinations of both modulation of the evidence representation and adaptation of accumulator gate and threshold. The results indicate how model-based cognitive neuroscience can translate between abstract cognitive models of performance and neural mechanisms of speed-accuracy tradeoff.

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.

Sign in / Sign up

Export Citation Format

Share Document