Detection theory has been applied to a host of varied problems (for example, measuring the accuracy of diagnostic systems or reliability of lie detection tests) and extends far beyond the detection of signals. This book is a primer on the subject.

When we are fatigued, we feel that our performance is worse than when we are fresh. Yet, for over 100 years, researchers have been unable to identify an objective, behavioral measure that covaries with the subjective experience of fatigue. Previous work suggests that the metrics of signal detection theory —response bias and perceptual certainty —may change as a function of fatigue, but no work has yet been done to examine whether these metrics covary with fatigue. Here, we (...) investigated cognitive fatigue using SDT. We induced fatigue through repetitive performance of the n-back working memory task, while functional magnetic resonance imaging data was acquired. We also assessed cognitive fatigue at intervals throughout. This enabled us to assess not only whether criterion and d’ covary with cognitive fatigue but also whether similar patterns of brain activation underlie cognitive fatigue and SDT measures. Our results show that both criterion and d’ were correlated with changes in cognitive fatigue: as fatigue increased, subjects became more conservative in their response bias and their perceptual certainty declined. Furthermore, activation in the striatum of the basal ganglia was also related to cognitive fatigue, criterion, and d’. These results suggest that SDT measures represent an objective measure of cognitive fatigue. Additionally, the overlap and difference in the fMRI results between cognitive fatigue and SDT measures indicate that these measures are related while also separate. In sum, we show the relevance of SDT measures in the understanding of fatigue, thus providing researchers with a new set of tools with which to better understand the nature and consequences of cognitive fatigue. (shrink)

Block [Block, N. . Two neural correlates of consciousness. Trends in Cognitive Science, 9, 46–52] and Snodgrass claim that a signal detection theory analysis of qualitative difference paradigms, in particular the exclusion failure paradigm, reveals cases of phenomenal consciousness without access consciousness. This claim is unwarranted on several grounds. First, partial cognitive access rather than a total lack of cognitive access can account for exclusion failure results. Second, Snodgrass’s Objective Threshold/Strategic model of perception relies on a problematic (...) ‘enable’ approach to perception that denies the possibility of intentional control of unconscious perception and any effect of following different task instructions on the presence/absence of phenomenal consciousness. Many of Block’s purported examples of phenomenal consciousness without cognitive access also rely on this problematic approach. Third, qualitative difference paradigms may index only a subset of access consciousness. Thus, qualitative difference paradigms like exclusion failure cannot be used to isolate phenomenal consciousness, any attempt to do so still faces serious methodological problems. (shrink)

Collerton et al.'s Perception and Attention Deficit model argues that all recurrent complex visual hallucinations result from maladaptive, deficient sensory and attentional processing. We outline a constructivist-based representation of perception using signal detection theory, in which hallucinations are modeled as false alarms when confirmational perceptual information is lacking. This representation allows for some individuals to have RCVH due to a criterion shift associated with attentional proficiency that results in an increased awareness of the environment.

The Hilbert space formalism is a powerful language to express many cognitive phenomena. Here, relevant concepts from signal detection theory are recast in that language, allowing an empirically testable extension of the quantum probability formalism to psychophysical measures, such as detectability and discriminability.

Phillips argues that blindsight is due to response criterion artefacts under degraded conscious vision. His view provides alternative explanations for some studies, but may not work well when one considers several key findings in conjunction. Empirically, not all criterion effects are decidedly non-perceptual. Awareness is not completely abolished for some stimuli, in some patients. But in other cases, it was clearly impaired relative to the corresponding visual sensitivity. This relative dissociation is what makes blindsight so important and interesting.

Several conclusions depend on a version of signal detection theory that assumes performance is based on underlying equal-variance normal distributions of trace strength. Such conclusions are questionable without empirical justification for that assumption. A thought experiment is presented to show how the assumption is probably invalid, and empirical evidence is cited for the assumption's invalidity in research on human memory.

Introspection is a fundamental part of our mental lives. Nevertheless, its reliability and its underlying cognitive architecture have been widely disputed. Here, I propose a principled way to model introspection. By using time-tested principles from signal detection theory (SDT) and extrapolating them from perception to introspection, I offer a new framework for an introspective signal detection theory (iSDT). In SDT, the reliability of perceptual judgments is a function of the strength of an internal perceptual (...) response (signal- to-noise ratio) which is, to a large extent, driven by the intensity of the stimulus. In parallel to perception, iSDT models the reliability of introspective judgments as a function of the strength of an internal introspective response (signal-to-noise ratio) which is, to a large extent, driven by the intensity of conscious experiences. Thus, by modelling introspection after perception, iSDT can calibrate introspection’s reliability across a whole range of contexts. iSDT offers a novel, illuminating way of thinking about introspection and the cognitive processes that support it. (shrink)

How should we measure metacognitive sensitivity, i.e. the efficacy with which observers’ confidence ratings discriminate between their own correct and incorrect stimulus classifications? We argue that currently available methods are inadequate because they are influenced by factors such as response bias and type 1 sensitivity . Extending the signal detection theory approach of Galvin, Podd, Drga, and Whitmore , we propose a method of measuring type 2 sensitivity that is free from these confounds. We call our measure (...) meta-d′, which reflects how much information, in signal-to-noise units, is available for metacognition. Applying this novel method in a 2-interval forced choice visual task, we found that subjects’ metacognitive sensitivity was close to, but significantly below, optimality. We discuss the theoretical implications of these findings, as well as related computational issues of the method. We also provide free Matlab code for implementing the analysis. (shrink)

Signal detection theory (SDT) is best known as a method for separating sensitivity from bias. If sensitivity reflects early sensory processing and bias later cognition, then SDT can be use to study penetrability by asking whether cognitive manipulations affect sensitivity. This assumption is too simple, but SDT can nonetheless be helpful in developing specific methods of how sensory and cognitive information combine. Two such approaches are described.

Do dissociations imply independent systems? In the memory field, the view that there are independent implicit and explicit memory systems has been predominantly supported by dissociation evidence. Here, we argue that many of these dissociations do not necessarily imply distinct memory systems. We review recent work with a single-system computational model that extends signal-detection theory (SDT) to implicit memory. SDT has had a major influence on research in a variety of domains. The current work shows that it (...) can be broadened even further in its range of application. Indeed, the single-system model that we present does surprisingly well in accounting for some key dissociations that have been taken as evidence for independent implicit and explicit memory systems. (shrink)

Legislation and ethical guidelines around the globe call for effective human oversight of AI-based systems in high-risk contexts – that is oversight that reliably reduces the risks otherwise associated with the use of AI-based systems. Such risks may relate to the imperfect accuracy of systems (e.g., inaccurate classifications) or to ethical concerns (e.g., unfairness of outputs). Given the significant role that human oversight is expected to play in the operation of AI-based systems, it is crucial to better understand the conditions (...) for effective human oversight. We argue that the reliable detection of errors (as an umbrella term for inaccuracies and unfairness) is crucial for effective human oversight. We then propose that Signal Detection Theory (SDT) offers a promising framework for better understanding what affects people’s sensitivity (i.e., how well they are able to detect errors) and response bias (i.e., the tendency to report errors given a perceived evidence of an error) in detecting errors. Whereas an SDT perspective on the detection of inaccuracies is straightforward, we demonstrate its broader applicability by detailing the specifics for an SDT perspective on unfairness detection, including the need to choose a standard for (un)fairness. Additionally, we illustrate that an SDT perspective helps to better understand the conditions for effective error detection by showing examples of task-, system-, and person-related factors that may affect the sensitivity and response bias of humans tasked with detecting unfairness associated with the use of AI-based systems. Finally, we discuss future research directions for an SDT perspective on error detection. (shrink)

Recognizing dishonesty is difficult. It involves both cognitive and moral judgments in situations where it is often costly to gather information. Some individuals are better at it than others; some situations make information gathering less costly. This article uses signal detection theory to model the individual and situational effects on assessments that someone has lied. Signal detection theory is explained, and examples of how it can be used to model other moral judgments are provided.

Studying the neural correlates of conscious awareness depends on a reliable comparison between activations associated with awareness and unawareness. One particularly difficult confound to remove is task performance capacity, i.e. the difference in performance between the conditions of interest. While ideally task performance capacity should be matched across different conditions, this is difficult to achieve experimentally. However, differences in performance could theoretically be corrected for mathematically. One such proposal is found in a recent paper by Lamy, Salti and Bar-Haim [Lamy (...) D, Salti M, Bar-Haim Y. Neural correlates of subjective awareness and unconscious processing: an ERP study. J Cognitive Neurosci 2009,21:1435-46], who put forward a corrective method for an electroencephalography experiment. We argue that their analysis is essentially grounded in a version of High Threshold Theory, which has been shown to be inferior in general to Signal Detection Theory. We show through a series of computer simulations that their correction method only partially removes the influence of perfor- mance capacity, which can yield misleading results. We present a mathematical correction method based on Signal Detection Theory that is theoretically capable of removing performance capacity confounds. We discuss the limitations of mathemati- cally correcting for performance capacity confounds in imaging studies and its impact for theories about consciousness. (shrink)

While the recognition of ambiguous emotions is crucial for successful social interactions, previous work has shown that they are perceived differently depending on whether they are viewed on male or female faces. The present paper aims to shed light on this phenomenon by exploring two hypotheses: the confounded signal hypothesis, which posits the existence of perceptual overlaps between emotions and gendered morphotypes, and the social role hypothesis, according to which the observer's responses are biased by stereotypes. Participants were asked (...) to categorise blended faces (i.e. artificial faces made ambiguous by mixing two emotions) in a forced-choice task. Six emotions were used to create each blend (neutral, surprise, sadness, fear, happiness, anger), for a total of 15 expressions. We then applied signal detection theory – considering both the morphotype of the stimuli and the participants’ gender – to distinguish participants’ perceptual processes from their response biases. The results showed a perceptual advantage for anger on male faces and for sadness on female faces. However, different strategies were deployed when labelling emotions on gendered morphotypes. In particular, a response bias towards angry male faces establishes their special status, as they resulted in both excellent detection and a tendency to be over-reported, especially by women. (shrink)

There is a widespread attitude in epistemology that, if you know on the basis of perception, then you couldn't have been wrong as a matter of chance. Despite the apparent intuitive plausibility of this attitude, which I'll refer to here as “stochastic infallibilism”, it fundamentally misunderstands the way that human perceptual systems actually work. Perhaps the most important lesson of signal detection theory (SDT) is that our percepts are inherently subject to random error, and here I'll highlight (...) some key empirical research that underscores this point. In doing so, it becomes clear that we are in fact quite willing to attribute knowledge to S that p even when S's perceptual belief that p could have been randomly false. In short, perceptual processes can randomly fail, and perceptual knowledge is stochastically fallible. The narrow implication here is that any epistemological account that entails stochastic infallibilism, like safety, is simply untenable. More broadly, this myth of stochastic infallibilism provides a valuable illustration of the importance of integrating empirical findings into epistemological thinking. (shrink)

In this paper we compare different models of vagueness viewed as a specific form of subjective uncertainty in situations of imperfect discrimination. Our focus is on the logic of the operator “clearly” and on the problem of higher-order vagueness. We first examine the consequences of the notion of intransitivity of indiscriminability for higher-order vagueness, and compare several accounts of vagueness as inexact or imprecise knowledge, namely Williamson’s margin for error semantics, Halpern’s two-dimensional semantics, and the system we call Centered semantics. (...) We then propose a semantics of degrees of clarity, inspired from the signal detection theory model, and outline a view of higher-order vagueness in which the notions of subjective clarity and unclarity are handled asymmetrically at higher orders, namely such that the clarity of clarity is compatible with the unclarity of unclarity. (shrink)

Starting from macroscopic and microscopic facts of cerebellar histology, we propose a new functional interpretation that may elucidate the role of the cerebellum in movement control. The idea is that the cerebellum is a large collection of individual lines (Eccles's : Eccles et al. 1967a) that respond specifically to certain sequences of events in the input and in turn produce sequences of signals in the output. We believe that the sequence-in/sequence-out mode of operation is as typical for the cerebellar cortex (...) as the transformation of sets into sets of active neurons is typical for the cerebral cortex, and that both the histological differences between the two and their reciprocal functional interactions become understandable in the light of this dichotomy. The response of Purkinje cells to sequences of stimuli in the mossy fiber system was shown experimentally by Heck on surviving slices of rat and guinea pig cerebellum. Sequential activation of a row of eleven stimulating electrodes in the granular layer, imitating a of the stimuli along the folium, produces a powerful volley in the parallel fibers that strongly excites Purkinje cells, as evidenced by intracellular recording. The volley, or has maximal amplitude when the stimulus moves toward the recording site at the speed of conduction in parallel fibers, and much smaller amplitudes for lower or higher The succession of stimuli has no effect when they in the opposite direction. Synchronous activation of the stimulus electrodes also had hardly any effect. We believe that the sequences of mossy fiber activation that normally produce this effect in the intact cerebellum are a combination of motor planning relayed to the cerebellum by the cerebral cortex, and information about ongoing movement, reaching the cerebellum from the spinal cord. The output elicited by the specific sequence to which a is tuned may well be a succession of well timed inhibitory volleys the motor sequences so as to adapt them to the complicated requirements of the physics of a multijointed system. (shrink)