Threshold nonlinearities and signal detection theory

The review summarizes Kulikowski's contributions to the mechanisms involved in visual detection and discrimination. His findings provide strong evidence for the existence of 'barriers' which block weak activity in the visual system. It is proposed that the properties of these barriers may underlie near-optimal detection in conditions of signal uncertainty.     

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.     

Calculation of signal detection theory measures

Signal detection theory (SDT) may be applied to any area of psychology in which two different types of stimuli must be discriminated. We describe several of these areas and the advantages that can be realized through the application of SDT. Three of the most popular tasks used to study discriminability are then discussed, together with the measures that SDT prescribes for quantifying performance in these tasks. Mathematical formulae for the measures are presented, as are methods for calculating the measures with lookup tables, computer software specifically developed for SDT applications, and general purpose computer software (including spreadsheets and statistical analysis software).     

The mirror effect and mixture signal detection theory

The mirror effect for word frequency refers to the finding that low-frequency words have higher hit rates and lower false alarm rates than high-frequency words. This result is typically interpreted in terms of conventional signal detection theory (SDT), in which case it indicates that the order of the underlying old item distributions mirrors the order of the new item distributions. However, when viewed in terms of a mixture version of SDT, the order of hits and false alarms does not necessarily imply the same order in the underlying distributions because of possible effects of mixing. A reversal in underlying distributions did not appear for fits of mixture SDT models to data from 4 experiments.     

BayesSDT: Software for Bayesian inference with signal detection theory

This article describes and demonstrates the BayesSDT MATLAB-based software package for performing Bayesian analysis with equal-variance Gaussian signal detection theory (SDT). The software uses WinBUGS to draw samples from the posterior distribution of six SDT parameters: discriminability, hit rate, false alarm rate, criterion, and two alternative measures of bias. The software either provides a simple MATLAB graphical user interface or allows a more general MATLAB function call to produce graphs of the posterior distribution for each parameter of interest for each data set, as well as to return the full set of posteriorsamples.     

Alternatives to a table of criterion values in signal detection theory

Gardner, Dalsing, Reyes, and Brake (1984) supplied a table of criterion values (β) related to hit and false-alarm rates in signal detection theory. Other methods of calculatingβ are suggested as more accurate alternatives to using that table. A short computer program is provided to calculate β and the sensitivity indexd’.     

Auditory threshold,signal-to-noise ratio and signal detection theory

The use of Signal Detection Theory has demonstrated that there is not an auditory threshold at the level supposed by classical psychophysics, but has not disproved the existence of an auditory threshold at a lower level. Following the recommended signal detection theory procedure fairly closely, an experiment obtained evidence either of the existence of a signal-to-noise ratio audi tory threshold, or a nonlinear relationship between stimulus and response which could not be statistically distiguished from such a threshold , Using the same apparatus and subjects, audi tory thresholds were also obtained using the classical method of limits. The acoustic pressure for the classical thresholds was about five times as great as for the signal detection theory method.     

Using magnitude estimation to investigate the perceptual components of signal detection theory

Several experiments suggest that the relation between detection, signal energy, and perceived tone intensity is very different from the relation between detection, signal energy, and perceived tone duration. We propose a new task, the magnitude estimation and detection (MED) task, that allows one to assess the relation between the psychological dimensions of a stimulus and detection. In Experiment 1, we used the MED task to assess the relation between perceived tone intensity and detection in a yes/no task. The data show a strong relation between the two. In Experiment 2, we used the MED task to assess the relation between perceived tone duration and detection in a yes/no task. The data show a relatively weak relation between the two. Our data suggest that tone intensity is a less perceptually noisy dimension than tone duration. We present the advantages and disadvantages of the MED task with the hope that this task can aid researchers in better understanding the perceptual and decisional mechanisms underlying various cognitive processes.     

A signal detection theory analysis of gap detection in the rat

An innocuous sensory event (a prestimulus) briefly preceding a startle-eliciting stimulus (SES) reduces the amplitude of the elicited reflex. This study used signal detection theory (SDT) techniques to quantify the effects of gaps (pauses in otherwise continuous noise) on the rat’s acoustic startle reflex. Sixteen rats were given four identical test sessions consisting of the randomized presentation of 150 trials of the SES alone and 150 trials of a gap-and-SES combination. Gap duration (1, 2, 4, and 8 msec) varied between sessions. Data analyses based on amplitude, difference scores, percentage scores, and SDT techniques identified similar patterns. The three longest gaps, but not the shortest, were reliably detected, and differences among these three were identified with percentage and SDT analyses. Analyses of amplitude changes over test sessions yielded different patterns for each measure. The results demonstrate that an SDT analysis is a sensitive index of prestimulus effects.     

Application of signal detection theory to perception of differences in line length

This paper is an attempt to specify the equinormal model for application to different tasks which are currently used in psychophysics (i.e. phenomenal report, detection, and 2AFC). The same set of stimuli (pairs of horizontal colinear lines) is presented in procedures which differ by the task, the probability of the signal, and the succession of the stimuli of the set. This approach leads to the specification of the sensorial and the decisional aspects of the model.The data indicate that (1) the sensitivity index d' to differences in line length is the same function of the physical stimulus independently of paradigm, as far as the same task is concerned. However, and according to the predictions, its value becomes larger by a factor of 2 in a two alternative forced choice task; (2) d' increases with stimulus exposure time; (3) latency of responses generally decreases with increasing d', and are dissimilar for correct and incorrect responses; (4) when the temporal succession of the stimuli is random the subject's criterion, x_c, is not chosen to optimize the percentage correct, which would require a dependance of criterion upon stimulus amplitude and prior probabilities.     

Source monitoring and multivariate signal detection theory, with a model for selection

Participants in source monitoring studies, in addition to determining whether an item is old or new, also discriminate the source of the item, such as whether the item was presented in a male or female voice. This article shows how to apply multivariate signal detection theory (SDT) to source monitoring. An interesting aspect of one version of the source monitoring procedure, from the perspective of multivariate SDT, is that it involves a type of selection, in that a discrimination response is observed only if the detection decision is that an item is old. If the selection is ignored, then the estimate of the discrimination parameter can be biased; the nature and magnitude of the bias are illustrated. A bivariate signal detection model that recognizes selection is presented and its application is illustrated. The approach to source monitoring via multivariate SDT provides new results that are informative about underlying psychological processes.     

Decision noise: An explanation for observed violations of signal detection theory

In signal detection theory (SDT), responses are governed by perceptual noise and a flexible decision criterion. Recent criticisms of SDT (see, e.g., Balakrishnan, 1999) have identified violations of its assumptions, and researchers have suggested that SDT fundamentally misrepresents perceptual and decision processes. We hypothesize that, instead, these violations of SDT stem from decision noise: the inability to use deterministic response criteria. In order to investigate this hypothesis, we present a simple extension of SDT—the decision noise model—with which we demonstrate that shifts in a decision criterion can be masked by decision noise. In addition, we propose a new statistic that can help identify whether the violations of SDT stem from perceptual or from decision processes. The results of a stimulus classification experiment—together with model fits to past experiments—show that decision noise substantially affects performance. These findings suggest that decision noise is important across a wide range of tasks and needs to be better understood in order to accurately measure perceptual processes.     

Source memory for unrecognized items: Predictions from multivariate signal detection theory

We report three experiments investigating source memory for words that were called "new" on a recognition test. In each experiment, participants could accurately specify the source of words that they failed to recognize. Results also demonstrated that source memory for unrecognized items varied with the bias to respond "old" in recognition decisions: Participants displayed unrecognized source memory when they were told that 25% of the recognition test words were old (promoting conservative responding) but not when they were told that 75% of the test words were old (promoting liberal responding). Our results were successfully predicted by a multivariate signal detection approach to recognition/source memory.     

Analysis of a two-alternative force-choice signal detection theory model

A basic problem in psychophysics is recovering the mean internal response and noise amplitude from sensory discrimination data. Since these components cannot be estimated independently, several indirect methods were suggested to resolve this issue. Here we analyze the two-alternative force-choice method (2AFC), using a signal detection theory approach, and show analytically that the 2AFC data are not always suitable for a reliable estimation of the mean internal responses and noise amplitudes. Specifically, we show that there is a subspace of internal parameters that are highly sensitive to sampling errors (singularities), which results in a large range of estimated parameters with a finite number of experimental trials. Four types of singular models were identified, including the models where the noise amplitude is independent of the stimulus intensity, a situation often encountered in visual contrast discrimination. Finally, we consider two ways to avoid singularities: (1) inserting external noise to the stimuli, and (2) using one-interval forced-choice scaling methods (such as the Thurstonian scaling method for successive intervals).     

Towards a behavioral theory of bias in signal detection

A behavioral model for performance on signal-detection tasks is presented. It is based on a relation between response and reinforcement ratios which has been derived from both animal and human research on the distribution of behavior between concurrently available schedules of reinforcement. This model establishes the ratio of obtained reinforcements for the choice responses, and not the probability of stimulus presentation, as the effective biaser in signal-detection research. Furthermore, experimental procedures which do not control the obtained reinforcement ratio are shown to give rise to unstable bias contours. Isobias contours, on the other hand, arise only from controlled reinforcement-ratio procedures.     

Complexity of visual icons studied via signal detection theory

Two investigations on how humans perceive information from visually rendered complex objects, such as military icons (glyphs) were conducted. A signal detection theory framework was employed to evaluate the sensitivity and specificity of human subject performance. The 6 adults tested showed that as complexity increased, their accuracy in performance decreased. Study 1 showed that complex dimensions (features) could not be assigned arbitrarily. Study 2 developed a rank ordering for features of an iconic object.