scholarly journals Affective bias through the lens of Signal Detection Theory

2020 ◽  
Author(s):  
Shannon M Locke ◽  
Oliver Joe Robinson
Keyword(s):  
Anxiety Disorders ◽  
Signal Detection ◽  
Signal Detection Theory ◽  
Mental Health Problems ◽  
Decision Criterion ◽  
Detection Theory ◽  
Prior Probabilities ◽  
Modelling Framework ◽  
Wide Range ◽  
Affective Bias

Affective bias - a propensity to focus on negative information at the expense of positive information - is a core feature of many mental health problems. However, it can be caused by wide range of possible underlying cognitive mechanisms. Here we illustrate this by focusing on one particular behavioural signature of affective bias - increased tendency of anxious/depressed individuals to predict lower rewards - in the context of the Signal Detection Theory (SDT) modelling framework. Specifically, we apply this framework to a tone-discrimination task (Aylward et al., 2019a), and argue that the same behavioural signature (differential placement of the 'decision criterion' between healthy controls and individuals with mood/anxiety disorders) might be driven by multiple SDT processes. Building on this theoretical foundation, we propose five experiments to test five hypothetical sources of this affective bias: beliefs about prior probabilities, beliefs about performance, subjective value of reward, learning differences, and need for accuracy differences. We argue that greater precision about the mechanisms driving affective bias may eventually enable us to better understand and treat mood and anxiety disorders.

Deterioration of the Useful Visual Field with Age and Sleep Deprivation: Insight from Signal Detection Theory

2009 ◽  
Vol 109 (1) ◽  
pp. 270-284 ◽  
Author(s):  
Joceline Rogé ◽  
Catherine Gabaude
Keyword(s):  
Visual Field ◽  
Sleep Deprivation ◽  
Signal Detection ◽  
Signal Detection Theory ◽  
Age Groups ◽  
Decision Criterion ◽  
Detection Theory ◽  
Perceptual Sensitivity ◽  
Middle Aged ◽  
Two Indices

The goal of this study was to establish whether the deterioration of the useful visual field due to sleep deprivation and age in a screen monitoring activity could be explained by a decrease in perceptual sensitivity and/or a modification of the participant's decision criterion (two indices derived from signal detection theory). In the first experiment, a comparison of three age groups (young, middle-aged, elderly) showed that perceptual sensitivity decreased with age and that the decision criterion became more conservative. In the second experiment, measurement of the useful visual field was carried out on participants who had been deprived of sleep the previous night or had a complete night of sleep. Perceptual sensitivity significantly decreased with sleep debt, and sleep deprivation provoked an increase in the participants' decision criterion. Moreover, the comparison of two age groups (young, middle-aged) indicated that sensitivity decreased with age. The value of using these two indices to explain the deterioration of useful visual field is discussed.

scholarly journals Affective Bias Through the Lens of Signal Detection Theory

2021 ◽  
Vol 5 (1) ◽  
pp. 4-20
Author(s):  
Shannon M. Locke ◽  
Oliver J. Robinson
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
Affective Bias

scholarly journals Testing the Foundations of Signal Detection Theory in Recognition Memory

2018 ◽  
Author(s):  
David Kellen ◽  
Samuel Winiger ◽  
John Cameron Dunn ◽  
Henrik Singmann
Keyword(s):  
Recognition Memory ◽  
Signal Detection ◽  
Latent Variable ◽  
Signal Detection Theory ◽  
Detection Theory ◽  
Fundamental Properties ◽  
Wide Range ◽  
Behavioral Constraints ◽  
Memory Experiment ◽  
Empirical Foundation

Signal Detection Theory (SDT) plays a central role in the characterization ofhuman judgments in a wide range of domains, most prominently in recognition memory. But despite its success, many of its fundamental properties are often misunderstood, especially when its comes to its testability. The present work examines five main properties that are characteristic of existing SDT models of recognition memory: i) random-scale representation, ii) latent-variable independence, iii) likelihood-ratio monotonicity, iv) ROC function asymmetry, and v) non-threshold representation. In each case, we establish testable consequences and test them against data collected in the appropriately-designed recognition memory experiment. We also discuss the connection between yes-no, forced-choice, and ranking judgments. This connection introduces additional behavioral constraints and yields an alternative method of reconstructing yes-no ROC functions. Overall, the reported results provide a strong empirical foundation for SDT modeling in recognition memory.

Induced Forgetting Is the Result of True Forgetting, Not Shifts in Decision-making Thresholds

2021 ◽  
pp. 1-13
Author(s):  
Emma Megla ◽  
Geoffrey F. Woodman ◽  
Ashleigh M. Maxcey
Keyword(s):  
Decision Making ◽  
Signal Detection ◽  
Signal Detection Theory ◽  
Brain Activity ◽  
Decision Criterion ◽  
Detection Theory ◽  
Criterion Shift ◽  
Memory Representations ◽  
Induced Forgetting

Abstract Induced forgetting occurs when accessing an item in memory appears to harm memory representations of categorically related items. However, it is possible that the actual memory representations are unharmed. Instead, people may just change how they make decisions. Specifically, signal detection theory suggests this apparent forgetting may be due to participants shifting their decision criterion. Here, we used behavioral and electrophysiological measures to determine whether induced forgetting is truly due to changes in how items are represented or simply due to a shifting criterion. Participants' behavior and brain activity showed that induced forgetting was due to changes in the strength of the underlying representations, weighing against a criterion shift explanation of induced forgetting.

So, Whatever Happened to Signal Detection Theory?

1995 ◽  
Vol 40 (10) ◽  
pp. 972-972
Author(s):  
Jerome R. Busemeyer
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Detection Theory
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