Temporal aspects of stimulus-driven attending in dynamic arrays

Auditory sequences of tones were used to examine a form of stimulus-driven attending that involves temporal expectancies and is influenced by stimulus rhythm. Three experiments examined the influence of sequence timing on comparative pitch judgments of two tones (standard, comparison) separated by interpolated pitches. In two of the experiments, interpolated tones were regularly timed, with onset times of comparison tones varied relative to this rhythm. Listeners were most accurate judging the pitch of rhythmically expected tones and least accurate with very unexpected ones. This effect persisted over time, but disappeared when the rhythm of interpolated tones was either missing or irregular.     

A model for detection and recognition with signal uncertainty

A model for signal detectability suggested by Luce is extended to situations in which the observer is uncertain of some important characteristic of the signal, such as frequency. By making a single assumption concerning the observer's covert response behavior, two solutions are obtained corresponding to qualitatively different behavior. Decrements in detectability and in recognition with uncertainty are shown to be particular functions of discriminability and detectability of the stimuli in other situations. Relevant experimental data are considered.This work was supported by grant NSF-G5544 from the National Science Foundation. The author is indebted to R. Duncan Luce for critical discussion of the content and helpful suggestions concerning the form of this paper. Useful comments have been made by David M. Green, Francis W. Irwin, Roger M. Shepard, and W. P. Tanner, Jr.     

Operator behavior in a dynamic visual signal detection task

The effects of changes in signal-to-noise ratio (SIN) and feedback state on the operator’s detection behavior, particularly derived operator thresholds, were investigated using a discrete visual signal. It was found that: (1) the operator behaves as if he has established different thresholds as a function of S/N; (2) his decision thresholds are relatively independent of the presence or absence of feedback; and (3) the operator will change his threshold accordingly for a change from one S/N to another. A model of the operator’s behavior, which introduced the concept of “operator” noise. yielded predictions of detection and false alarm probabilities which were extremely close to the observed values.     

A direct test of the unequal-variance signal detection model of recognition memory

Analyses of the receiver operating characteristic (ROC) almost invariably suggest that, on a recognition memory test, the standard deviation of memory strengths associated with the lures (σ_lure) is smaller than that of the targets (σ_target). Often, σ_lure/σ_target ≈ 0.80. However, that conclusion is based on a model that assumes that the memory strength distributions are Gaussian in form. In two experiments, we investigated this issue in a more direct way by asking subjects to simply rate the memory strengths of targets and lures using a 20-point or a 99-point strength scale. The results showed that the standard deviation of the ratings made to the targets (s _target) was, indeed, larger than the standard deviation of the ratings made to the lures (s _lure). Moreover, across subjects, the ratios _lure/s _target correlated highly with the estimate of σ_lure/σtarget obtained from ROC analysis, and both estimates were, on average, approximately equal to 0.80.     

Metacontrast as measured under a signal detection model

Metacontrast is assessed both by percent accuracy and by the dichotomous sensitivity and criterion measures of a signal-detection model in a forced-choice detection task. The results showed a monotonic increase in sensitivity with increasing mask delay, and an abrupt shift of subjects' response criterion at an 80 ms interstimulus interval. The results are discussed in terms of the interpretational advantages of a signal-detection approach to metacontrast investigation.     

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).     

A generalized signal detection model to predict rational variation in base rate use

The predominant models of rational behavior currently used to analyze a large class of experiments imply that subjects neglect or place insufficient weight on base rates when making probabilistic judgments. We argue that the evidence is inadequate for this conclusion because the models make needlessly restrictive assumptions about how base rates should be used. The restrictive assumptions stem from a misuse of Bayes' rule that ignores specific aspects of how the proportions arose. We develop a model of rational behavior that generalizes signal detection theory to reflect the environment subjects routinely face and we reexamine the relevant experimental literature. Variation observed in subjects' responses to base rate information is explained by the present rational model more fully than by extant models.     

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.     

A comparison of signal detection theory to the objective threshold/strategic model of unconscious perception

A key problem in unconscious perception research is ruling out the possibility that weak conscious awareness of stimuli might explain the results. In the present study, signal detection theory was compared with the objective threshold/strategic model as explanations of results for detection and identification sensitivity in a commonly used unconscious perception task. In the task, 64 undergraduate participants detected and identified one of four briefly displayed, visually masked letters. Identification was significantly above baseline (i.e., proportion correct > .25) at the highest detection confidence rating. This result is most consistent with signal detection theory's continuum of sensory states and serves as a possible index of conscious perception. However, there was limited support for the other model in the form of a predicted "looker's inhibition" effect, which produced identification performance that was significantly below baseline. One additional result, an interaction between the target stimulus and type of mask, raised concerns for the generality of unconscious perception effects.     

A signal detection analysis of the recognition heuristic

The recognition heuristic uses a recognition decision to make an inference about an unknown variable in the world. Theories of recognition memory typically use a signal detection framework to predict this binary recognition decision. In this article, I integrate the recognition heuristic with signal detection theory to formally investigate how judges use their recognition memory to make inferences. The analysis reveals that false alarms and misses systematically influence the performance of the recognition heuristic. Furthermore, judges should adjust their recognition response criterion according to their experience with the environment to exploit the structure of information in it. Finally, the less-is-more effect is found to depend on the distribution of cue knowledge and judges’ sensitivity to the difference between experienced and novel items. Theoretical implications of this bridge between the recognition heuristic and models of recognition memory are discussed.     

Vibrotactile signal detection

The theory of signal detectability was applied to vibrotactile sensitivity in two experiments. The first experiment showed The psychometric function to be satisfactorily linear when a sensitivity index of the d family was plotted against the signal intensity expressed in decibels. The second experiment yielded receiver-operating-characteristic (ROC) curves of a familiar form for the yes-no and rating response methods. Reasonably consistent estimates of sensitivity were obtained in the second experiment from the yes-no. rating, and forced-choice methods. The sensitivity indices examined were d’ and d_e’, based on Gaussian density functions; A, based on Rayleigh density functions; and the distribution-free indices, P(A) and F(C). For each type of index a tendency was observed for the forced-choice value to be lower than the yes-no and rating values.     

Spreadsheet signal detection

A number of studies in perception, attention, and memory employ signal detection theory (SDT) to assess the accuracy of an observer’s detection or discrimination performance. Some of the problems that students have with understanding and using SDT are associated with the calculations needed to obtain SDT parameters and predictions. All of these calculations, plus the simulation of SDT processes, can be performed using a spreadsheet application program, such as Excel or Quattro Pro. This paper offers a short tutorial on how to use a spreadsheet program to increase your students’ knowledge and understanding of SDT.     

A dynamic model of loudness adaptation

Previous research on loudness adaptation has provided heterogeneous and partly contradictory results. One major reason seems to be the inconsistent use of the term 'adaptation', which is due to differing operational definitions. Here, a measurement-theoretic definition of loudness adaptation is introduced, which also comprises a new method for the identification of certain linear dynamic systems. This is of particular interest, since there is a lack of dynamic models describing loudness adaptation. An experiment with sinusoidal sound stimuli (3000 Hz) was performed to test whether loudness adaptation can be modeled by such a linear system. The results of the system identification indicate that this is possible. Therefore, it can be concluded that the given definition of loudness adaptation might be appropriate and that the method of system identification is an applicable research tool.     

Sample size and the detection of means: A signal detection account

Using statistical theory as a basis, Kareev (e.g., 1995) claimed that people's ability to correctly infer the existence of a population correlation should be greater for small than for large samples. Simulations by R. B. Anderson, Doherty, Berg, and Friedrich (2005) identified conditions favoring small samples but could not determine whether such an advantage was due to sampling skew, variance, or central tendency displacement. In the present study, we investigated theoretical effects of sample size (n) on the detection of population means under circumstances in which sampling variance is unconfounded with skew or central tendency displacement. The results demonstrate an extremely limited, criterion-specific, small-sample advantage that was attributable to n-related sampling variance and that occurred only with highly conservative, suboptimal criterion placement.     

A contextual effect in feature detection with application of signal detection methodology

These experiments address the question of whether the perception of a form is exclusively determined by a prior analysis of its elements. Employing a signal detection task, Experiment 1 replicated the finding of Weisstein and Harris (1974) that embedding a line segment feature in a unitary figural context facilitates its detection. The results of Experiment 2 suggest that the most probable agent of this context effect on feature detection is the three-dimensionality of the unitary context. With bi-hemiretinal stimulus presentation. Experiment 3 showed a significant context effect in the right, but not in the left visual field. Some current paradigms are applied to these results.     

Visual laterality effects: A signal detection analysis

Subjects were asked to indicate, by a simple motor response, the presence or absence of a pre-designated target letter in unilaterally presented consonant trigrams. For horizontally oriented stimuli (Experiment 1), perceptual sensitivity was greater in the right visual hemifield. For vertically oriented stimuli (Experiment 2), perceptual sensitivity did not differ between visual hemifields. Decision making was less conservative and reaction time was shorter with right hemifield presentation, regardless of stimulus orientation. Practice effects and serial position curves were examined. Implications of these results attribute laterality effects to iconic scanning patterns and to postperceptual decision processes.     

Searching for stimulus-driven shifts of attention

Several types of dynamic cues (e.g., abrupt onsets, motion) draw attention in visual search tasks even when they are irrelevant. Although these stimuli appear to capture attention in a stimulus-driven fashion, typical visual search tasks might induce an intentional strategy to focus on dynamic events. Because observers can only begin their search when the search display suddenly appears, they might orient to any dynamic display change (Folk, Remington, & Johnston, 1992; Gibson & Kelsey, 1998). If so, the appearance of capture might result from task-induced biases rather than from the properties of the stimulus. In fact, such biases can even create the appearance of stimulus-driven capture by stimuli that typically do not capture attention (Gibson & Kelsey, 1998). The possibility of task-induced, topdown biases plagues the interpretation of all previous studies claiming stimulus-driven attention capture by dynamic stimuli. In two experiments, we attempt to eliminate potential task-induced biases by removing any need to monitor for display changes. In the first experiment, search displays did not change on most trials. In the second experiment, although new search displays appeared on each trial, we ensured that observers never saw the changes, by making them during large saccades. In both cases, dynamic events still received search priority, suggesting that some dynamic stimuli capture attention in a stimulus-driven fashion.     

Simple reaction time as a race between signal detection and time estimation: A paradigm and model

A new paradigm for simple reaction time is described in which signal detection and time production trials are interleaved. A model is proposed which views the signal detection and time production processes as independent and engaged in a race whose outcome determines the observed response latencies. The model also allows the distribution of detection latencies to be extracted from the data.     

A dynamic context model of interactive behavior

A dynamic context model of interactive behavior was developed to explain results from two experiments that tested the effects of interaction costs on encoding strategies, cognitive representations, and response selection processes in a decision-making and a judgment task. The model assumes that the dynamic context defined by the mixes of internal and external representations and processes are sensitive to the interaction cost imposed by the task environment. The model predicts that changes in the dynamic context may lead to systematic biases in cognitive representations and processes that eventually influence decision-making and judgment outcomes. Consistent with the predictions by the model, results from the experiments showed that as interaction costs increased, encoding strategies and cognitive representations shifted from perception-based to memory-based. Memory-based comparisons of the stimuli enhanced the similarity and dominance effects, and led to stronger systematic biases in response outcomes in a choice task. However, in a judgment task, memory-based representations enhanced only the dominance effects. Results suggested that systematic response biases in the dominance context were caused by biases in the cognitive representations of the stimuli, but response biases in the similarity context were caused by biases in the comparison process induced by the choice task. Results suggest that changes in interaction costs not only change whether information was assessed from the external world or from memory but also introduce systematic biases in the cognitive representation of the information, which act as biased inputs to the subsequent decision-making and judgment processes. Results are consistent with the idea of interactive cognition, which proposes that representations and processes are contingent on the dynamic context defined by the information flow between the external task environment and internal cognition.