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.

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.

scholarly journals Computational modelling of attentional selectivity in depression reveals perceptual deficits

2020 ◽  
pp. 1-10
Author(s):  
James A. Grange ◽  
Michelle Rydon-Grange
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
Flanker Task ◽  
Computational Modelling ◽  
Visual Selective Attention ◽  
Two Phase ◽  
Attention Tasks ◽  
Perceptual Representations ◽  
Attentional Selectivity ◽  
Depression Symptomatology

Abstract Background Depression is associated with broad deficits in cognitive control, including in visual selective attention tasks such as the flanker task. Previous computational modelling of depression and flanker task performance showed reduced pre-potent response bias and reduced executive control efficiency in depression. In the current study, we applied two computational models that account for the full dynamics of attentional selectivity. Method Across three large-scale online experiments (one exploratory experiment followed by two confirmatory – and pre-registered – experiments; total N = 923), we measured attentional selectivity via the flanker task and obtained measures of depression symptomology as well as anhedonia. We then fit two computational models that account for the dynamics of attentional selectivity: The dual-stage two-phase model, and the shrinking spotlight (SSP) model. Results No behavioural measures were related to depression symptomology or anhedonia. However, a parameter of the SSP model that indexes the strength of perceptual input was consistently negatively associated with the magnitude of depression symptomatology. Conclusions The findings provide evidence for deficits in perceptual representations in depression. We discuss the implications of this in relation to the hypothesis that perceptual deficits potentially exacerbate control deficits in depression.

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.

scholarly journals Computational modelling of attentional selectivity in depression reveals perceptual deficits

2020 ◽  
Author(s):  
Jim Grange ◽  
Michelle Rydon-Grange
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
Flanker Task ◽  
Computational Modelling ◽  
Visual Selective Attention ◽  
Two Phase ◽  
Total N ◽  
Attention Tasks ◽  
Perceptual Representations ◽  
Attentional Selectivity

Depression is associated with broad deficits in cognitive control, including in visual selective attention tasks such as the flanker task. Previous computational modelling of depression and flanker task performance showed reduced preprotent response bias and reduced executive control efficiency in depression. In the current study we applied two computational models that account for the full dynamics of attentional selectivity. Across 3 large-scale online experiments (one exploratory experiment followed by two confirmatory—and pre-registered experiments; Total N = 923) we measured attentional selectivity via the flanker task and obtained measures of depression symptomology as well as anhedonia. We then fit two computational models that account for the dynamics of attentional selectivity: The Dual-Stage Two Phase model, and the Shrinking Spotlight model. No behavioural measures were related to depression symptomology or anhedonia. However, a parameter of the Shrinking Spotlight model that indexes the strength of perceptual input was consistently negatively associated with the magnitude of depression symtomology. The findings provide evidence for deficits in perceptual representations in depression. We discuss the implications of this in relation to the hypothesis that perceptual deficits potentially exacerbate control deficits in depression.

Awareness and Decision Making in Professional Ethics

2000 ◽  
Vol 5 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Ronny Swain
Keyword(s):  
Decision Making ◽  
Professional Ethics ◽  
Ethical Decision Making ◽  
Code Of Ethics ◽  
Professional Autonomy ◽  
Ethical Awareness ◽  
Ethical Decisions ◽  
The Right ◽  
Aid Decision

The paper describes the development of the 1998 revision of the Psychological Society of Ireland's Code of Professional Ethics. The Code incorporates the European Meta-Code of Ethics and an ethical decision-making procedure borrowed from the Canadian Psychological Association. An example using the procedure is presented. To aid decision making, a classification of different kinds of stakeholder (i.e., interested party) affected by ethical decisions is offered. The author contends (1) that psychologists should assert the right, which is an important aspect of professional autonomy, to make discretionary judgments, (2) that to be justified in doing so they need to educate themselves in sound and deliberative judgment, and (3) that the process is facilitated by a code such as the Irish one, which emphasizes ethical awareness and decision making. The need for awareness and judgment is underlined by the variability in the ethical codes of different organizations and different European states: in such a context, codes should be used as broad yardsticks, rather than precise templates.

Would you Make the Right Decision? – Decision Making Biases in Economy - Related Dilemmas

2018 ◽  
Vol 9 (1) ◽  
pp. 59-66
Author(s):  
Zsuzsanna Gödör ◽  
Georgina Szabó
Keyword(s):  
Decision Making ◽  
Online Survey ◽  
Framing Effect ◽  
Economic Knowledge ◽  
Bank Account ◽  
Financial Decisions ◽  
Hungarian Population ◽  
The Moment ◽  
The Right ◽  
Decision Making Biases

Abstract As they say, money can’t buy happiness. However, the lack of it can make people’s lives much harder. From the moment we open our first bank account, we have to make lots of financial decisions in our life. Should I save some money or should I spend it? Is it a good idea to ask for a loan? How to invest my money? When we make such decisions, unfortunately we sometimes make mistakes, too. In this study, we selected seven common decision making biases - anchoring and adjustment, overconfidence, high optimism, the law of small numbers, framing effect, disposition effect and gambler’s fallacy – and tested them on the Hungarian population via an online survey. In the focus of our study was the question whether the presence of economic knowledge helps people make better decisions? The decision making biases found in literature mostly appeared in the sample as well. It proves that people do apply them when making decisions and in certain cases this could result in serious and costly errors. That’s why it would be absolutely important for people to learn about them, thus increasing their awareness and attention when making decisions. Furthermore, in our research we did find some connection between decisions and the knowledge of economics, people with some knowledge of economics opted for the better solution in bigger proportion

Peristaltic Carreau-Yasuda nanofluid flow and mixed heat transfer analysis in an asymmetric vertical and tapered wavy wall channel

2020 ◽  
Vol 1 (1) ◽  
pp. 128-140 ◽  
Author(s):  
Mohammad Hatami ◽  
◽  
D Jing ◽  
Keyword(s):  
Heat Transfer ◽  
Least Square Method ◽  
Weissenberg Number ◽  
Least Square ◽  
Heat Transfer Analysis ◽  
Phase Method ◽  
Nanofluid Flow ◽  
Two Phase ◽  
Nanoparticles Concentration ◽  
The Right

In this study, two-phase asymmetric peristaltic Carreau-Yasuda nanofluid flow in a vertical and tapered wavy channel is demonstrated and the mixed heat transfer analysis is considered for it. For the modeling, two-phase method is considered to be able to study the nanoparticles concentration as a separate phase. Also it is assumed that peristaltic waves travel along X-axis at a constant speed, c. Furthermore, constant temperatures and constant nanoparticle concentrations are considered for both, left and right walls. This study aims at an analytical solution of the problem by means of least square method (LSM) using the Maple 15.0 mathematical software. Numerical outcomes will be compared. Finally, the effects of most important parameters (Weissenberg number, Prandtl number, Brownian motion parameter, thermophoresis parameter, local temperature and nanoparticle Grashof numbers) on the velocities, temperature and nanoparticles concentration functions are presented. As an important outcome, on the left side of the channel, increasing the Grashof numbers leads to a reduction in velocity profiles, while on the right side, it is the other way around.

The Effects of Decision Time on Perceptions of Decisions and Decision Makers in (Moral) Trade-Off Scenarios

2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Process ◽  
Decision Time ◽  
Decision Makers ◽  
Process Information ◽  
Total N ◽  
Trade Off ◽  
Financial Gain ◽  
Trade Offs ◽  
Sacred Values ◽  
Moral Context

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.

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