Signal detection theory: Considerations for general application.

Notes that while there exist a number of papers describing the theory of signal detection, it appears that many psychologists are not aware of the ease with which signal detection theory can be applied, the range of applications possible, or the limitations of signal detection theory. This paper briefly summarizes the assumptions of signal detection theory and describes the procedures, the limitations, and practical considerations relevant to its application. A worked example of an application of signal detection theory to the study of cognitive processes is included. (46 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Overview: Signal production and detection.

Studies of signal production and detection are complicated by the diverse modalities used by animals, constraints of human signal perception, and limitations of a controlled laboratory environment. These complications can be addressed by creative approaches to studying anatomical adaptations for signal production and detection, innovative technology, and careful studies of signal production and detection in the field. These solutions should overcome the perceptual limitations of researchers as they explore Umwelten in other species. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Signal detection theory with finite mixture distributions: Theoretical developments with applications to recognition memory.

An extension of signal detection theory (SDT) that incorporates mixtures of the underlying distributions is presented. The mixtures can be motivated by the idea that a presentation of a signal shifts the location of an underlying distribution only if the observer is attending to the signal; otherwise, the distribution is not shifted or is only partially shifted. Thus, trials with a signal presentation consist of a mixture of 2 (or more) latent classes of trials. Mixture SDT provides a general theoretical framework that offers a new perspective on a number of findings. For example, mixture SDT offers an alternative to the unequal variance signal detection model; it can also account for nonlinear normal receiver operating characteristic curves, as found in recent research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Separating mnemonic process from participant and item effects in the assessment of ROC asymmetries.

One of the most influential findings in the study of recognition memory is that receiver operating characteristic (ROC) curves are asymmetric about the negative diagonal. This result has led to the rejection of the equal-variance signal detection model of recognition memory and has provided motivation for more complex models, such as the unequal-variance signal detection and dual-process models. Here, the authors test the possibility that previous demonstrations of ROC asymmetry do not reflect mnemonic process but rather reflect distortions due to averaging data over items. Application of a hierarchical unequal-variance signal detection model reveals that asymmetries are in fact a real phenomenon and do not reflect distortions from averaging data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Sensitive absorbance detection method for capillary electrophoresis based on laser wave-mixing

Forward-scattering four-wave mixing is demonstrated as a sensitive absorbance detection method for capillary electrophoresis, using an argon ion laser operating at 457.9 nm. Since this four-wave mixing laser technique utilizes only two input laser beams, it offers important advantages, including ease of optical alignment, high wave-mixing efficiency and low excitation power requirements. In addition, since the analytical signal is a laser-like coherent beam, highly efficient optical signal detection can be performed with minimum optical background noise. Excellent detection sensitivity and short absorption path lengths, and hence, small detector probe volumes, are some of the useful features this absorbance detection method offers for on-column detection of both fluorescing and non-fluorescing analytes in capillary electrophoresis and liquid chromatography. Preliminary "detected" concentration detection limit of 8.5.10(-8) M, mass detection limit of 13 amol and an absorbance-unit detection limit of 1.35.10(-5) AU are determined for dabsyl-glycine using this absorbance detection method.     

An application of signal detection theory with finite mixture distributions to source discrimination.

A mixture extension of signal detection theory is applied to source discrimination. The basic idea of the approach is that only a portion of the sources (say A or B) of items to be discriminated is encoded or attended to during the study period. As a result, in addition to 2 underlying probability distributions associated with the 2 sources, there is a 3rd distribution that represents items for which sources were not attended to. Thus, over trials, the observed response results from a mixture of an attended (A or B) distribution and a nonattended distribution. The situation differs in an interesting way from detection in that, for detection, there is mixing only on signal trials and not on noise trials, whereas for discrimination, there is mixing on both A and B trials. Predictions of the mixture model are examined for data from several recent studies and in a new experiment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Do logistic regression and signal detection identify different subgroups at risk? Implications for the design of tailored interventions.

Identifying subgroups of high-risk individuals can lead to the development of tailored interventions for those subgroups. This study compared two multivariate statistical methods (logistic regression and signal detection) and evaluated their ability to identify subgroups at risk. The methods identified similar risk predictors and had similar predictive accuracy in exploratory and validation samples. However, the 2 methods did not classify individuals into the same subgroups. Within subgroups, logistic regression identified individuals that were homogeneous in outcome but heterogeneous in risk predictors. In contrast, signal detection identified individuals that were homogeneous in both outcome and risk predictors. Because of the ability to identify homogeneous subgroups, signal detection may be more useful than logistic regression for designing distinct tailored interventions for subgroups of high-risk individuals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A dynamic stimulus-driven model of signal detection.

Signal detection theory forms the core of many current models of cognition, including memory, choice, and categorization. However, the classic signal detection model presumes the a priori existence of fixed stimulus representations—usually Gaussian distributions—even when the observer has no experience with the task. Furthermore, the classic signal detection model requires the observer to place a response criterion along the axis of stimulus strength, and without theoretical elaboration, this criterion is fixed and independent of the observer's experience. We present a dynamic, adaptive model that addresses these 2 long-standing issues. Our model describes how the stimulus representation can develop from a rough subjective prior and thereby explains changes in signal detection performance over time. The model structure also provides a basis for the signal detection decision that does not require the placement of a criterion along the axis of stimulus strength. We present simulations of the model to examine its behavior and several experiments that provide data to test the model. We also fit the model to recognition memory data and discuss the role that feedback plays in establishing stimulus representations. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Continuous recollection versus unitized familiarity in associative recognition.

Recollection has long been thought to play a key role in associative recognition tasks. Evidence that associative recollection might be a threshold process has come from analyses of the associative recognition receiver operating characteristic (ROC). Specifically, the ROC is not as curvilinear as a signal detection theory requires. In addition, the ?-ROC is usually curvilinear, as a threshold recollection model requires, not linear, as a signal detection model requires. In Experiment 1, word pairs were strengthened at study, which yielded a curvilinear ROC and a linear ?-ROC (in accordance with signal detection theory). This result suggests that associative recognition performance was based on a continuous variable, one that likely consists of either unitized familiarity or continuous recollection. The remember–know procedure and an unexpected cued recall test suggested that the more curvilinear ROC in the strong condition was mainly due to increased recollection. In Experiment 2, word pairs were presented for an old–new recognition decision before being presented for an associative recognition decision. When pairs consisting of items not recognized as having been seen on the list were removed from the analysis, the ROC again became curvilinear, the ?-ROC again became linear, and most associative recognition decisions were associated with remember judgments. These findings suggest that the curvilinear ?-ROC often observed on associative recognition tests results from noise, as a mixture signal detection model assumes, and that recollection is a continuous process that yields a curvilinear ROC that is well characterized by signal detection theory. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Improved sensitivity of detection with the commercial automated gel electrophoresis (HPGE-1000) apparatus through modification of its optical system

In a representative application to a fluorescently detectable protein of commercial automated gel electrophoresis apparatus (HPGE-1000, LabIntelligence, Belmont, CA) the sensitivity of detection by fluorescence was significantly increased by elimination of the mirror below the gel tray. That increase in detection sensitivity is due to a decrease of fluorescent background noise by nearly one order of magnitude, overcompensating a decrease in signal by a factor of two. The resulting increase in signal/noise ratio, i.e., detection sensitivity, should allow for lowered sample loads by which the band width is reduced with benefits to resolution.     

A meta-analysis of the relative efficacy and toxicity of Pneumocystis carinii prophylactic regimens

Accurate onset detection of the voluntary response is a prerequisite in reaction time studies when used in investigations on human motor control. The detection algorithm required performs a transformation of the continuous physical signal (e.g., force, movement) containing the response into a discrete event from which the reaction time (RT) is derived. Therefore, RT always comprises both the cognitive and/or motor delay component imaging the duration of the initiation process conducted by the sensorimotor system and, in addition, some spurious delay caused by the detection algorithm. As a standard method, onset detection is realized by the measurement device itself (e.g., the release of a micro switch) by defining the response onset as the point where the observed signal passes a certain threshold. Thus, weak and abnormal response profiles which are typical for a variety of central motor disorders (e.g., Parkinson's disease) may introduce high RT variability as well as systematic errors. The aim of this study was to improve accuracy of onset detection by application of an appropriate filter to the measured signal before entering the final decision stage. Three algorithms (lowpass differentiator, inverse filter, linear autoregressive (AR) predictor) were implemented and tested on simulated and real data under both on-line and off-line conditions with special interest to the influence of quasi-periodic background activity like tremor. It is shown that a significant improvement in onset detection accuracy, compared with the simple switch, can be achieved by using appropriate low order adaptive filters with the AR-predictor being the most efficient solution.     

Feature sampling in detection: Implications for the measurement of perceptual independence.

The article presents the feature sampling signal detection (FS-SDT) model, an extension of the multivariate signal detection (SDT) model. The FS-SDT model assumes that, because of attentional shifts, different subsets of features are sampled for different presentations of the same multidimensional stimulus. Contrary to the SDT model, the FS-SDT model enables the estimation of pure perceptual effects that are uncontaminated by strategic attention shifts. The consideration of feature sampling in detection and identification opens a new perspective on the problem of measuring, respectively, the separability and integrality of stimulus dimensions. Disregarding feature sampling as a component process in detection and identification usually results in biased estimations of perceptual independence concepts relevant for judgments of whether stimulus dimensions are processed independently. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

No Special K! A signal detection framework for the strategic regulation of memory accuracy.

Two experiments investigated criterion setting and metacognitive processes underlying the strategic regulation of accuracy on the Scholastic Aptitude Test (SAT) using Type-2 signal detection theory (SDT). In Experiment 1, report bias was manipulated by penalizing participants either 0.25 (low incentive) or 4 (high incentive) points for each error. Best guesses to unanswered items were obtained so that Type-2 signal detection indices of discrimination and bias could be calculated. The same incentive manipulation was used in Experiment 2, only the test was computerized, confidence ratings were taken so that receiver operating characteristic (ROC) curves could be generated, and feedback was manipulated. The results of both experiments demonstrated that SDT provides a viable alternative to A. Koriat and M. Goldsmith's (1996c) framework of monitoring and control and reveals information about the regulation of accuracy that their framework does not. For example, ROC analysis indicated that the threshold model implied by formula scoring is inadequate. Instead, performance on the SAT should be modeled with an equal-variance Gaussian, Type-2 signal detection model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Signal detection theory and generalized linear models.

Generalized linear models are a general class of regressionlike models for continuous and categorical response variables. Signal detection models can be formulated as a subclass of generalized linear models, and the result is a rich class of signal detection models based on different underlying distributions. An example is a signal detection model based on the extreme value distribution. The extreme value model is shown to yield unit slope receiver operating characteristic (ROC) curves for several classic data sets that are commonly given as examples of normal or logistic ROC curves with slopes that differ from unity. The result is an additive model with a simple interpretation in terms of a shift in the location of an underlying distribution. The models can also be extended in several ways, such as to recognize response dependencies, to include random coefficients, or to allow for more general underlying probability distributions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Free-field binaural unmasking in budgerigars ( Melopsittacus undulatus ).

The detection of signals in noise is important for understanding both the mechanisms of hearing and how the auditory system functions under more natural conditions. In humans, the auditory system gains some improvement if the signal and noise are separated in space (binaural masking release). Birds with small heads are at a disadvantage in separating noise and signal sources relative to large mammals, because interaural time differences are much smaller. Two binaural phenomena in budgerigars related to the detection of tones in noise were examined. Budgerigars show 8 dB of free-field binaural masking release when signal and noise are presented to their right side and correlated noise is presented to their left side. Budgerigars also show a spatial masking release of 9 dB when a signal and noise are separated in azimuth by 90°. These results are similar to those found in humans and other mammals with much larger heads. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Attentional mechanisms in simple visual detection: A speed–accuracy trade-off analysis.

Recent spatial cuing studies have shown that detection sensitivity can be increased by the allocation of attention. This increase has been attributed to one of two mechanisms: signal enhancement or uncertainty reduction. Signal enhancement is an increase in the signal-to-noise ratio at the cued location; uncertainty reduction is a reduction in the uncertainty associated with the location of the target. In displays with low uncertainty, cuing effects are typically found only if targets are backwardly masked. This phenomenon is known as the mask-dependent cuing effect. This effect was investigated in four experiments using the response signal paradigm, which controlled for speed–accuracy tradeoffs. For unmasked targets, cues failed to improve detection accuracy when uncertainty was absent (Experiment 1), but large cuing effects were obtained when uncertainty was present (Experiment 2). For masked targets, stronger cuing effects were obtained with a backward pattern mask (Experiment 3) than with a simultaneous noise mask (Experiment 4). We conclude that the cuing effects in simple detection with well-localized targets are due to a dynamic signal enhancement mechanism. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Process dissociation and mixture signal detection theory.

The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely analyzed study. The results suggest that a process other than recollection may be involved in the process dissociation procedure. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Postreceptoral chromatic detection mechanisms revealed by noise masking in three-dimensional cone contrast space

We used a noise masking technique to test the hypothesis that detection is subserved by only two chromatic postreceptoral mechanisms (red-green and blue-yellow) and one achromatic (luminance) mechanism. The task was to detect a 1-c/deg Gaussian enveloped grating presented in a mask of static, spatially low-passed binary or Gaussian distributed noise. In the main experiment, the direction of the test stimulus (termed the signal) was constant in cone contrast space, and the direction of the noise was sampled in equally spaced directions within a plane (the noise plane) in the space. The signal was chosen to coincide with one of the three cardinal directions of three postulated mechanisms. The noise plane was selected to span two of the cardinal directions, including that chosen as the signal direction. As the noise direction was sampled around the noise plane, the signal detection threshold was found to vary in accordance with a linear cosine model, which predicted noise directions yielding maximum and minimum masking of the signal. In the direction of minimum masking (termed a null direction), the noise was found to have no masking effect on the signal. Moreover, the null was not orthogonal to the signal direction but lay instead in one of the cardinal directions. Our findings suggest that detection is mediated by only three mechanisms. In a further experiment we found little or no cross masking between each pair of cardinal directions up to the limit of our noise mask contrasts. This further supports the presence of no more than three independent postreceptoral mechanisms.     

Measures and interpretations of vigilance performance: evidence against the detection criterion

Operators' performance in a vigilance task is often assumed to depend on their choice of a detection criterion. When the signal rate is low this criterion is set high, causing the hit and false alarm rates to be low. With increasing time on task the criterion presumably tends to increase even further, thereby further decreasing the hit and false alarm rates. Virtually all of the empirical evidence for this simple interpretation is based on estimates of the bias measure beta from signal detection theory. In this article, I describe a new approach to studying decision making that does not require the technical assumptions of signal detection theory. The results of this new analysis suggest that the detection criterion is never biased toward either response, even when the signal rate is low and the time on task is long. Two modifications of the signal detection theory framework are considered to account for this seemingly paradoxical result. The first assumes that the signal rate affects the relative sizes of the variances of the information distributions; the second assumes that the signal rate affects the logic of the operator's stopping rule. Actual or potential applications of this research include the improved training and performance assessment of operators in areas such as product quality control, air traffic control, and medical and clinical diagnosis.