Signal detection and localization by real observers

A model for detection and localization (DAL) was applied to the processing of a noise-masked tonal signal by human Ss. The model was supported in that consistent values of d’ were obtained from rating. forced-choice (FC). and DAL procedures. Also. the rating d’ accurately predicted per cent correct on the FC and DAL trials. A shortcoming of the theory was its failure to account satisfactorily for the details of FC and DAL stimulus-response matrices.     

Signal detection comparisons of phonemic and phonetic priming: The flexible-bias problem

The phonemic priming effect may reflect the hidden dynamics of spoken word perception and has thus been a key topic of recent research. This investigation compared phonemic and phonetic priming (cf. Goldinger, Luce, Pisoni, & Marcario, 1992), using signal detection methods. Although these methods were intended to provide separate indices of sensitivity and bias changes, the results were more complex. Instead, phonemic priming engendered a flexible, trial-specific strategy that affected hits and false alarms (and thereby altered sensitivity) but also created behavioral changes indicative of a bias. Together with previous research, the results suggest that phonemic priming data must be interpreted with caution, and they underscore the limitations of signal detection analyses in priming research (Norris, 1995). However, if a researcher can anticipate the likely form a bias will assume, signal detection methods can reveal priming effects.     

Signal detection and matching: analyzing choice on concurrent variable-interval schedules.

Pigeons' pecks on a red key and a green key were followed by access to grain according to pairs of concurrent independent variable-interval schedules in a combined signal detection/matching law paradigm. Pecks on the red key were reinforced by the richer variable-interval schedule if a short-duration tone had been presented; pecks on the green key were reinforced by the richer variable-interval schedule if a long-duration tone had been presented. Pecks on the green key given a short-duration tone, or on the red key given a long-duration tone, were reinforced by the leaner variable-interval schedule. The data were analyzed according to both signal detection's and the matching law's separate measures of, first, the discrimination of the choices and, second, the bias to make one response or another. Increasing the difficulty of the tone-duration discrimination decreased both methods' measures of the discrimination of the choices and did not change both methods' measures of the bias to make one response or another. Changing the leaner variable-interval schedule so that it approached the richer variable-interval schedule decreased signal detection's measure of discrimination but left its measure of response bias and the matching law measures unchanged. Data collected only until a subject's first changeover response following presentation of a long or a short tone showed higher values for both methods' measures of discrimination, no change in signal detection's measure of response bias, and lower values for the matching law's measure of response bias. Relationships between the matching law's and signal detection's methods of analyzing choice are discussed. It is concluded that a signal detection analysis is more efficient for examining changes in the difficulty of a discrimination, whereas a matching law analysis is more effective for examining the effects of changes in relative reinforcer frequency.     

Signal detection and threshold models of source memory

Recently, several authors claimed that the curvilinear shape of rating-based source memory receiver operating characteristics (ROCs) refutes threshold models. However, rating-based ROCs are not diagnostic to disprove threshold models. Furthermore, source memory ROC-analyses ignore influences of other processes like old-new-detection and old-new-response-tendencies, so direct estimation of parameters is preferable. Five source monitoring experiments with different response bias manipulations and materials were conducted. We fitted the Two High Threshold Multinomial Model of Source Monitoring by Bayen, Murnane, and Erdfelder (1996) and the Multivariate Signal Detection Model for Selection DeCarlo (2003). We also included rating-based ROCs. The results suggest that both models are at least equally valid as measurement tools which capture bias processes in the corresponding parameters, and they can perhaps be integrated theoretically.     

Signal detection theory with item effects

Applications of signal detection theory (SDT) often involve presentations of different items on each trial, such as slides in a medical imaging study or words in a memory study. If factors particular to the items themselves, apart from being a signal or noise, affect observers’ responses, then ‘item effects’ are present. One way to model these effects is to use a latent continuous variable as an item ‘factor’, such as item ‘difficulty’. Details of SDT models with item effects are clarified via derivations of their implied conditional means, variances, and covariances. Intra-item correlations are defined and suggested as measures of the magnitude of item effects. The SDT-item models are simple random coefficient models and can be fit with standard software. More general models, such as item models with mixing and/or with random observer effects, are also considered.     

Signal probability, reinforcement and signal detection.

Five pigeons were trained to detect differences in light intensity. Two stimuli, S1 and S2, differing in intensity, were arranged on the center key of a three-key chamber according to set probabilities. A peck on the center key turned on the two side keys. When S1 was presented on the center key, a peck on the left key was "correct" and when S2 was presented, a peck on the right key was "correct." Correct responses produced reinforcement and incorrect responses produced 3-second blackout. Detection performance was measured under three procedures. The first was a standard signal-detection design in which the probability of S1 was varied and the number of reinforcements obtained for correct responses to S1 was allowed to covary. In the second procedure, the probability of S1 was again varied but the distribution of reinforcements between the two choices was kept equal. In the third procedure, probability of S1 was held constant while the distribution of reinforcements was varied between the two choices. Changes in response bias were a function of variations in the relative reinforcement ratio for the choice responses and not a function of variations in the probability of stimulus presentation. Discriminability remained constant across the three procedures.     

Signal detection and identification at successive stages of observation

The relationship of signal identification to signal detection was examined in a series of experiments. The signals were idealized lines and patterns of lines in a spectrographic display. On each trial, progressively more of the complete spectrogram was exposed in successive observation intervals, and after each interval the observer made both detection and identification responses that were based on the accumulating evidence. One model we employed conceives of detection and identification as proceeding together over time as parts of a unified process. A second model used shows how thejoint detection-and-identification ROC—a relative operating characteristic that relates the joint probability of correct detectionand correct identification to the probability of a false detection—may be predicted from the simple detection ROC. Both models were supported by the data.     

Signal detection theory, the approach of choice: model-based and distribution-free measures and evaluation

New and old methods of analyzing two-choice experiments with confidence ratings are evaluated. These include the theory of signal detectability (TSD), Luce's choice theory,nonparametric techniques based on areas under receiver-operating characteristic (ROC) functions, andmethods based on S' and omega, proposed by Balakrishnan and his colleagues. New methods for assessing the bias of a complete ROC function are proposed, together with an additional area-based measure of response bias. Area measures of both sensitivity and bias proved the most consistent. Response bias for a full ROC function was larger than bias at the cut point and also provided additional information. Participants showed voluntary control of bias for all measures except omega. Unequal variance versions of TSD and choice models gave similar fits to data, with the choice model closer to an equal variance version. Discrimination data from Balakrishnan (1999) formed the empirical test bed.     

Signal detection methods for measurement of utility in animals

Analytic methods of signal detection theory were employed to assess the utility of reinforcers. Four pigeons were trained to detect the presence or absence of a stimulus by pecking one of two side keys in a trial-by-trial choice paradigm. The relative rate of positive reinforcement for correct choices was varied to offset the biasing effects of electric shock for incorrect right side-key choices. The effects of relative rate of reinforcement on bias were similar at all shock intensities even though the subjects' sensitivity changed during the course of the experiment. The relative rate of reinforcement required to produce equal bias was calculated and plotted against shock intensity to generate utility functions. The relative rate of reinforcement necessary to offset the bias induced by shock was an increasing function of shock intensity.     

Signal detection evidence for limited capacity in visual search

The nature of capacity limits (if any) in visual search has been a topic of controversy for decades. In 30 years of work, researchers have attempted to distinguish between two broad classes of visual search models. Attention-limited models have proposed two stages of perceptual processing: an unlimited-capacity preattentive stage, and a limited-capacity selective attention stage. Conversely, noise-limited models have proposed a single, unlimited-capacity perceptual processing stage, with decision processes influenced only by stochastic noise. Here, we use signal detection methods to test a strong prediction of attention-limited models. In standard attention-limited models, performance of some searches (feature searches) should only be limited by a preattentive stage. Other search tasks (e.g., spatial configuration search for a "2" among "5"s) should be additionally limited by an attentional bottleneck. We equated average accuracies for a feature and a spatial configuration search over set sizes of 1-8 for briefly presented stimuli. The strong prediction of attention-limited models is that, given overall equivalence in performance, accuracy should be better on the spatial configuration search than on the feature search for set size 1, and worse for set size 8. We confirm this crossover interaction and show that it is problematic for at least one class of one-stage decision models.     

Interplay of the production and picture superiority effects: A signal detection analysis

Three experiments explored the interaction between the production effect (greater memory for produced compared to non-produced study items) and the picture superiority effect (greater memory for pictures compared to words). Pictures and words were presented in a blocked (E1) or mixed (E2, E3) design, each accompanied by an instruction to silently name (non-produced condition) or quietly mouth (produced condition) the corresponding referent. Memory was then tested for all study items as well as an equal number of foil items using a speeded (E1, E2) or self-paced (E3) yes-no recognition task. Experiments 1, 2, and 3 all revealed a small but reliable production×stimulus interaction. Production was also found to result in a liberal shift in response bias that could result in the overestimation of the production effect when measured using hits instead of sensitivity. Together our findings suggest that the application of multiple distinctive processes at study produces an especially discriminative memory trace at test, more so than the summation of each process individually.     

Signal detection theory analyses of semantic priming in word recognition

Word recognition, semantic priming, and cognitive impenetrability research have used signal detection theory (SDT) measures to separate perceptual and postperceptual processes. In the D. Norris (1986) checking model and model simulation (D. Norris, 1995), priming alters only postperceptual word decision criteria: Stimulus-related priming reduces uncertainty, increasing sensitivity; stimulus-unrelated priming increases false alarms more than hits, reducing sensitivity. This work is cited as strong evidence that criterion changes can alter perceptual sensitivity and that SDT is inappropriate for investigating complex cognitive processes. The authors' current SDT ideal observer analysis of the model demonstrates that related priming does not directly alter sensitivity and that unrelated priming increases only false-alarm rate, reducing sensitivity. This analysis provides new perspectives on SDT concepts of complex decision processing.     

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.     

Counselling and Computers: Introduction and Overview

The symposium on counselling and computers is introduced through a general consideration of the role of computers in both the counselling process and its administrative accoutrements.