scholarly journals The Decisive Role of Non-Decision Time for Interpreting the Parameters of Decision Making Models

2021 ◽  
Author(s):  
Gabriel Weindel ◽  
thibault gajdos ◽  
Boris BURLE ◽  
F.-Xavier Alario
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Computational Models ◽  
Decisive Role ◽  
Decision Time ◽  
Current Evidence ◽  
Choice Data ◽  
Physiological Measurement ◽  
Motor Processes ◽  
Speed Accuracy

Computational models of decision making are becoming increasingly popular to interpret reaction time and choice data in terms of decision and non-decision related processes. But current evidence remains scarce as to whether parameters of a mathematical model such as the Drift Diffusion Model (DDM) can recover genuine latent psychological processes. In this study, we combine an experimental approach using a decision making task with a physiological decomposition of each reaction time into a motor and pre-motor time using electro-myography. The aim is to test whether the non-decision time parameter of a DDM, assumed to contain encoding and motor processes, varies according to both psychophysical predictions of stimulus encoding and the physiological measurement of motor processes. Our results show that 1) the encoding time is accounted by a DDM only in the case of instructions emphasizing speed over accuracy and 2) that the onset of muscular activity does not sign the end of the accumulation of evidence. This questions the ability of DDM to account for how participants achieve speed-accuracy tradeoff as well as the interpretability of its parameters in terms of decision and non-decision processes.

EEG Classification with a Sequential Decision-Making Method in Motor Imagery BCI

2017 ◽  
Vol 27 (08) ◽  
pp. 1750046 ◽  
Author(s):  
Rong Liu ◽  
Yongxuan Wang ◽  
Geoffrey I. Newman ◽  
Nitish V. Thakor ◽  
Sarah Ying
Keyword(s):  
Decision Making ◽  
Stopping Time ◽  
Decision Time ◽  
Sequential Decision Making ◽  
Ratio Test ◽  
Sequential Decision ◽  
Eeg Classification ◽  
Average Maximum ◽  
Subject Specific ◽  
Speed Accuracy

To develop subject-specific classifier to recognize mental states fast and reliably is an important issue in brain–computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this paper, a sequential decision-making strategy is explored in conjunction with an optimal wavelet analysis for EEG classification. The subject-specific wavelet parameters based on a grid-search method were first developed to determine evidence accumulative curve for the sequential classifier. Then we proposed a new method to set the two constrained thresholds in the sequential probability ratio test (SPRT) based on the cumulative curve and a desired expected stopping time. As a result, it balanced the decision time of each class, and we term it balanced threshold SPRT (BTSPRT). The properties of the method were illustrated on 14 subjects’ recordings from offline and online tests. Results showed the average maximum accuracy of the proposed method to be 83.4% and the average decision time of 2.77[Formula: see text]s, when compared with 79.2% accuracy and a decision time of 3.01[Formula: see text]s for the sequential Bayesian (SB) method. The BTSPRT method not only improves the classification accuracy and decision speed comparing with the other nonsequential or SB methods, but also provides an explicit relationship between stopping time, thresholds and error, which is important for balancing the speed-accuracy tradeoff. These results suggest that BTSPRT would be useful in explicitly adjusting the tradeoff between rapid decision-making and error-free device control.

The Effect of Part Proliferation on Assembly Line Operators' Decision Making Capabilities

1979 ◽  
Vol 23 (1) ◽  
pp. 169-173
Author(s):  
Susanne M. Gatchell
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Choice Reaction Time ◽  
Assembly Line ◽  
Research Study ◽  
Reaction Times ◽  
Decision Time ◽  
Error Rates

In order to quantify the effects of part proliferation on assembly line operators' decision making capabilities, a research study was conducted. Using a Choice Reaction Time technique, 16 operators were tested to determine their reaction times and error rates when selecting parts. These operators were from four training levels (trained, relief, untrained/job and untrained/plant) and had to decide between 4, 7 or 10 major parts. Results show that operators with 10 parts made 46% more errors and needed 13% more decision time than operators with 4 parts. Furthermore, the relief and untrained/job operators made three times more errors than the trained operators. The untrained/plant operators had over five times more errors than the trained operators. These results indicate that all operators could make a selection when working with 10 major parts. However, their reaction times and error rates increased as the number or parts increased from 4 to 10.

scholarly journals A Dissociation of Attention, Executive Function and Reaction to Difficulty: Development of the MindPulse Test, a Novel Digital Neuropsychological Test for Precise Quantification of Perceptual-Motor Decision-Making Processes

2021 ◽  
Vol 15 ◽  
Author(s):  
Sandra Suarez ◽  
Bertrand Eynard ◽  
Sylvie Granon
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Processing Speed ◽  
Neuropsychological Test ◽  
Reaction Time Task ◽  
Decision Time ◽  
Reference Points ◽  
Motor Speed ◽  
Simple Reaction Time Task ◽  
Base Time

Traditionally, neuropsychological testing has assessed processing speed and precision, closely related to the ability to perform high-order cognitive tasks. An individual making a decision under time pressure must constantly rebalance its speed to action in order to account for possible errors. A deficit in processing speed appears to be afrequent disorder caused by cerebral damage — but it can be hard to pinpoint the exact cause of the slowdown. It is therefore important to separate the perceptual-motor component of processing speed from the decision-time component. We present a technique to isolate Reaction Times (RTs): a short digital test to assess the decision-making abilities of individuals by gauging their ability to balance between speed and precision. Our hypothesis is that some subjects willaccelerate, and others slow down in the face of the difficulty. This pilot study, conducted on 83 neurotypical adult volunteers, used images stimuli. The test was designed to measure RTs and correctness. After learning release gesture, the subjects were presented with three tasks: a simple Reaction Time task, a Go/No-Go, and a complex Go/No-Go with 2 simultaneous Choices. All three tasks have in common a perceptual component and a motor response. By measuring the 3 reference points requiring attentional and executive processing, while progressively increasing the conceptual complexity of the task, we were able to compare the processing times for different tasks — thus calculating the deceleration specific to the reaction time linked to difficulty. We defined the difficulty coefficient of a task as being the ratio of the group average time of this task minus the base time/average time of the unit task minus the base time. We found that RTs can be broken down into three elementary, uncorrelated components: Reaction Time, Executive Speed, and Reaction to Difficulty (RD). We hypothesized that RD reflects how the subject reacts to difficulty by accelerating (RD < 0) or decelerating (RD > 0). Thus we provide here a first proof of concept: the ability to measure four axes of the speed-precision trade-off inherent in a subject’s fundamental decision making: perceptual-motor speed, executive speed, subject accuracy, and reaction to difficulty.

scholarly journals Speed-Accuracy Tradeoff Operator Characteristics of Endogenous and Exogenous Covert Orienting of Attention

2005 ◽  
Vol 5 ◽  
pp. 128-146 ◽  
Author(s):  
Peter A. McCormick ◽  
Lori Francis
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Perceptual Sensitivity ◽  
Operating Characteristics ◽  
Attention Task ◽  
Endogenous Orienting ◽  
Decision Making Processes ◽  
Speed Accuracy ◽  
Accuracy Tradeoff ◽  
Preferential Access

There is debate over the mechanisms that govern the orienting of attention. Some argue that the enhanced performance observed at a cued location is the result of increased perceptual sensitivity or preferential access to decision-making processes. It has also been suggested that these effects may be the result of trades in speed for accuracy on the part of the observers. In the present study, observers performed either an exogenous or an endogenous orienting of attention task under both normal instructions (respond as quickly and as accurately as possible) and speeded instructions that used a deadline procedure to limit the amount of time observers had to complete a choice reaction time (CRT) task. An examination of the speed-accuracy operating characteristics (SAOCs) yielded evidence against the notion that CRT precuing effects are due primarily to a tradeoff of accuracy for speed.

scholarly journals Computational modelling of the speed–accuracy tradeoff: No evidence for an association with depression symptomatology

2021 ◽  
Author(s):  
James A. Grange
Keyword(s):  
Decision Making ◽  
Environmental Changes ◽  
Computational Modelling ◽  
Decision Time ◽  
Two Phase ◽  
Total N ◽  
Human Cortex ◽  
The Right ◽  
Depression Symptomatology ◽  
Speed Accuracy

Successful decision making often requires finding the right balance between the speed and accuracy of responding: Emphasising speed can lead to error-prone performance, yet emphasising accuracy leads to a slowing of performance. Such speed–accuracy tradeoffs (SATs) therefore require establishing appropriate response settings to optimise performance in response to changing environmental demands. Such strategic adaptaion of response settings relies on the striatal regions of human cortex, an area implicated in depression. The current study explored the association between depression symptomatology and SAT performance. Two experiments presented participants with an SAT paradigm embedded within a simple decision-making task, together with measures of depression symptomatology. Experiment 1 (N = 349) was correlational, whereas Experiment 2 was a two-phase experiment where participants (N = 501) were first pre-screened on depression symptomatology and extreme-low and extreme-high responders (total N = 91) were invited to Phase 2. Behavioural data were modelled with a drift diffusion model. Behavioural data and associated diffusion modelling showed large and robust SAT effects. Emphasising accuracy led to an increase in boundary separation, an increase in drift rate, and an increase in non-decision time. However, the magnitude of the changes of these parameters with SAT instructions were not associated with measures of depression symptomatology. The results suggest that the strategic adaptation of response settings in response to environmental changes in speed--accuracy instructions do not appear to be associated with depression symptomatology.

Neuroticism and Speed-Accuracy Tradeoff in Self-Paced Speeded Mental Addition and Comparison

2010 ◽  
Vol 31 (3) ◽  
pp. 130-137 ◽  
Author(s):  
Hagen C. Flehmig ◽  
Michael B. Steinborn ◽  
Karl Westhoff ◽  
Robert Langner
Keyword(s):  
Reaction Time ◽  
Response Speed ◽  
Time Variability ◽  
Reaction Time Variability ◽  
Comparison Task ◽  
Processing Efficiency ◽  
Mental Addition ◽  
Speed Accuracy ◽  
The Relationship ◽  
Accuracy Tradeoff

Previous research suggests a relationship between neuroticism (N) and the speed-accuracy tradeoff in speeded performance: High-N individuals were observed performing less efficiently than low-N individuals and compensatorily overemphasizing response speed at the expense of accuracy. This study examined N-related performance differences in the serial mental addition and comparison task (SMACT) in 99 individuals, comparing several performance measures (i.e., response speed, accuracy, and variability), retest reliability, and practice effects. N was negatively correlated with mean reaction time but positively correlated with error percentage, indicating that high-N individuals tended to be faster but less accurate in their performance than low-N individuals. The strengthening of the relationship after practice demonstrated the reliability of the findings. There was, however, no relationship between N and distractibility (assessed via measures of reaction time variability). Our main findings are in line with the processing efficiency theory, extending the relationship between N and working style to sustained self-paced speeded mental addition.

scholarly journals Shifting uncertainty intolerance: methylphenidate and attention-deficit hyperactivity disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alekhya Mandali ◽  
Arjun Sethi ◽  
Mara Cercignani ◽  
Neil A. Harrison ◽  
Valerie Voon
Keyword(s):  
Decision Making ◽  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Computational Models ◽  
Risky Choice ◽  
Risk Tolerance ◽  
Healthy Population ◽  
Hyperactivity Disorder ◽  
Risky Choices ◽  
Cardinal Symptom

AbstractRisk evaluation is a critical component of decision making. Risk tolerance is relevant in both daily decisions and pathological disorders such as attention-deficit hyperactivity disorder (ADHD), where impulsivity is a cardinal symptom. Methylphenidate, a commonly prescribed drug in ADHD, improves attention but has mixed reports on risk-based decision making. Using a double-blinded placebo protocol, we studied the risk attitudes of ADHD patients and age-matched healthy volunteers while performing the 2-step sequential learning task and examined the effect of methylphenidate on their choices. We then applied a novel computational analysis using the hierarchical drift–diffusion model to extract parameters such as threshold (‘a’—amount of evidence accumulated before making a decision), drift rate (‘v’—information processing speed) and response bias (‘z’ apriori bias towards a specific choice) focusing specifically on risky choice preference. Critically, we show that ADHD patients on placebo have an apriori bias towards risky choices compared to controls. Furthermore, methylphenidate enhanced preference towards risky choices (higher apriori bias) in both groups but had a significantly greater effect in the patient population independent of clinical scores. Thus, methylphenidate appears to shift tolerance towards risky uncertain choices possibly mediated by prefrontal dopaminergic and noradrenergic modulation. We emphasise the utility of computational models in detecting underlying processes. Our findings have implications for subtle yet differential effects of methylphenidate on ADHD compared to healthy population.

scholarly journals Cognitive Control of Working Memory: A Model-Based Approach

2021 ◽  
Vol 11 (6) ◽  
pp. 721
Author(s):  
Russell J. Boag ◽  
Niek Stevenson ◽  
Roel van Dooren ◽  
Anne C. Trutti ◽  
Zsuzsika Sjoerds ◽  
...  
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Cognitive Control ◽  
Relevant Information ◽  
Decision Time ◽  
Control Processes ◽  
Prepotent Response ◽  
New Information ◽  
Empirical Performance ◽  
Flow Of Information

Working memory (WM)-based decision making depends on a number of cognitive control processes that control the flow of information into and out of WM and ensure that only relevant information is held active in WM’s limited-capacity store. Although necessary for successful decision making, recent work has shown that these control processes impose performance costs on both the speed and accuracy of WM-based decisions. Using the reference-back task as a benchmark measure of WM control, we conducted evidence accumulation modeling to test several competing explanations for six benchmark empirical performance costs. Costs were driven by a combination of processes, running outside of the decision stage (longer non-decision time) and showing the inhibition of the prepotent response (lower drift rates) in trials requiring WM control. Individuals also set more cautious response thresholds when expecting to update WM with new information versus maintain existing information. We discuss the promise of this approach for understanding cognitive control in WM-based decision making.

293 Predictive utility of a brief scale to identify U.S. Army Soldiers who are genetically vulnerable and resilient to sleep loss

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A117-A117
Author(s):  
Janna Mantua ◽  
Carolyn Mickelson ◽  
Jacob Naylor ◽  
Bradley Ritland ◽  
Alexxa Bessey ◽  
...  
Keyword(s):  
Decision Making ◽  
Reaction Time ◽  
Sleep Deprivation ◽  
Cognitive Performance ◽  
Response Inhibition ◽  
Sleep Loss ◽  
Cutoff Score ◽  
Cognitive Subscale ◽  
Army Soldiers ◽  
Psychomotor Vigilance

Abstract Introduction Sleep loss that is inherent to military operations can lead to cognitive errors and potential mission failure. Single Nucleotide Polymorphisms (SNPs) allele variations of several genes (COMT, ADORA2A, TNFa, CLOCK, DAT1) have been linked with inter-individual cognitive resilience to sleep loss through various mechanisms. U.S. Army Soldiers with resilience-related alleles may be better-suited to perform cognitively-arduous duties under conditions of sleep loss than those without these alleles. However, military-wide genetic screening is costly, arduous, and infeasible. This study tested whether a brief survey of subjective resilience to sleep loss (1) can demarcate soldiers with and without resilience-related alleles, and, if so, (2) can predict cognitive performance under conditions of sleep loss. Methods Six SNPs from the aforementioned genes were sequenced from 75 male U.S. Army special operations Soldiers (age 25.7±4.1). Psychomotor vigilance, response inhibition, and decision-making were tested after a night of mission-driven total sleep deprivation. The Iowa Resilience to Sleeplessness Test (iREST) Cognitive Subscale, which measures subjective cognitive resilience to sleep loss, was administered after a week of recovery sleep. A receiver operating characteristic (ROC) curve was used to determine whether the iREST Cognitive Subscale can discriminate between gene carriers, and a cutoff score was determined. Cognitive performance after sleep deprivation was compared between those below/above the cutoff score using t-tests or Mann-Whitney U tests. Results The iREST discriminated between allele variations for COMT (ROC=.65,SE=.07,p=.03), with an optimal cutoff score of 3.03 out of 5, with 90% sensitivity and 51.4% specificity. Soldiers below the cutoff score had significantly poorer for psychomotor vigilance reaction time (t=-2.39,p=.02), response inhibition errors of commission (U=155.00,W=246.00,p=.04), and decision-making reaction time (t=2.13,p=.04) than Soldiers above the cutoff score. Conclusion The iREST Cognitive Subscale can discriminate between those with and without specific vulnerability/resilience-related genotypes. If these findings are replicated, the iREST Cognitive Subscale could be used to help military leaders make decisions about proper personnel placement when sleep loss is unavoidable. This would likely result in increased safety and improved performance during military missions. Support (if any) Support for this study came from the Military Operational Medicine Research Program of the United States Army Medical Research and Development Command.

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