Numerical and sensory categorization of serial information by animals

Rats were trained in a straight runway on a series consisting of 4 elements, each element being defined in terms of the number of .045-gm. Noyes pellets used as reward on 4 runway trials separated by about 20 sec. The series elements were 2, 6, 12, and 0 (2-6-12-0). The animals were trained each day on 3 such series, the series themselves being separated within a day by about 12 min. for 28 days before introducing a new transfer series to assess the relevance of the order of the series elements. In previous experiments with the simpler series, 2-12-0, alterations in order of elements eliminated the animals' tendencies to run much slower to the terminal nonreward element of the series, but transfer was clearly shown here when we shifted from 2-6-12-0 to 6-12-2-0. That is, the animals continued on the transfer test to approach the terminal element slowly, a result which we interpret as supporting the view that the rats either counted the rewarded trials and used that count to predict terminal nonreward, or they behaved on the basis of cues associated with the ordinal position of the trial.     

A theory of interactive parallel processing: new capacity measures and predictions for a response time inequality series

The authors present a theory of stochastic interactive parallel processing with special emphasis on channel interactions and their relation to system capacity. The approach is based both on linear systems theory augmented with stochastic elements and decisional operators and on a metatheory of parallel channels' dependencies that incorporates standard independent and coactive parallel models as special cases. The metatheory is applied to OR and AND experimental paradigms, and the authors establish new theorems relating response time performance in these designs to earlier and novel issues. One notable outcome is the remarkable processing efficiency associated with linear parallel-channel systems that include mutually positive interactions. The results may offer insight into perceptual and cognitive configural-holistic processing systems.     

Visual search time based on stochastic serial and parallel processings

Two stochastic latency models were developed in order to account for random fluctuations of the search time that the S consumed when he was asked to search for a single target number or one of two (or three) target numbers through the sets of small two-digit numbers randomly distributed on a white square. It was shown that the search time distribution for a single target number can be adequately described in terms of McGill’s two-step serial processing model. The parallel processing model whose structure is exponential was found to fit approximately the search time distributions for the first target number that the S detects among the two (or three) target numbers predesignated. This model, however, does not satisfactorily handle the long search times.     

Simple matrix methods for analyzing diffusion models of choice probability, choice response time, and simple response time

Diffusion processes (e.g., Wiener process, Ornstein-Uhlenbeck process) are powerful approaches to model human information processes in a variety of psychological tasks. Lack of mathematical tractability, however, has prevented broad applications of these models to empirical data. This tutorial explains step by step, using a matrix approach, how to construct these models, how to implement them on a computer, and how to calculate the predictions made by these models. In particular, we present models for binaries choices for unidimensional and multiattribute choice alternatives; for simple reaction time tasks; and for three alternatives choice problems.     

A clarification of self-terminating versus exhaustive variances in serial and parallel models

A recent study published in Perception & Psychophysics (Donnelly, Found, & Miller, 1999) employs response time (RT) variances (in the form of standard deviations) in addition to mean RTs. Variances can contribute greatly to model testing. However, there is a danger of perpetuating the kinds of logical and methodological errors that have long attended research employing mean RTs alone. This commentary clarifies the theoretical and methodological issues, points out some new results concerning variability in search processes, and indicates how to resolve the global and specific challenges associated with identifying psychological mechanisms.     

A clarification of self-terminating versus exhaustive variances in serial and parallel models

A recent study published in Perception & Psychophysics (Donnelly, Found, & Müller, 1999) employs response time (RT) variances (in the form of standard deviations) in addition to mean RTs. Variances can contribute greatly to model testing. However, there is a danger of perpetuating the kinds of logical and methodological errors that have long attended research employing mean RTs alone. This commentary clarifies the theoretical and methodological issues, points out some new results concerning variability in search processes, and indicates how to resolve the global and specific challenges associated with identifying psychological mechanisms.     

Choice and response time processes in the identification and categorization of unidimensional stimuli

Lacouture and Marley (1991, 1995, 2001) have successfully modeled the probabilities of correct responses and the mean correct response times (RTs) in unidimensional absolute identification tasks for various stimulus ranges and stimulus/response set sizes, for individual and group data. These fits include those to a set of phenomena often referred to as end-anchor effects. A revised model, with the independent accumulator decision process replaced by a leaky competing accumulator decision process, fits the probabilities of correct responses and the full distributions of RTs in unidimensional absolute identification. The revised model is also applied successfully to a particular class of unidimensional categorization tasks. We discuss possible extensions for handling sequential effects in unidimensional absolute identification, and other extensions of the given class of categorization tasks that are of potential empirical and theoretical importance as a supplement to the study of multidimensional absolute identification tasks.     

Classification response times in probabilistic rule-based category structures: Contrasting exemplar-retrieval and decision-boundary models

Experiments were conducted to contrast the predictions from exemplar models and rule-based decisionboundary models of perceptual classification. Observers classified multidimensional stimuli into categories that could be described in terms of easily verbalized logical rules. The critical manipulation was that some pairs of stimuli received probabilistic feedback, whereas other control pairs received deterministic feedback. Despite the probabilistic feedback, the probabilistic pairs and the deterministic pairs were the same distance from idealobserver, rule-based decision boundaries. Across two experiments with varying category structures, observers classified the probabilistic pairs with slower response times (RTs) and lower accuracies than the comparison deterministic pairs. The effects were relatively long term, extending into test blocks in which all feedback was withheld. The results were as predicted by exemplar models, but challenged models that posit that RT is a function solely of the distance of a stimulus from rule-based boundaries. The studies add considerable generality to previous ones and suggest that, even in domains involving rule-based category structures, exemplar-retrieval processes play a significant role. Supplemental materials related to this article may be downloaded from http:// mc.psychonomic-journals.org/content/supplemental.     

Estimating an unobserved component of a serial response time model

A method is developed for estimating the response time distribution of an unobserved component in a two-component serial model, assuming the components are stochastically independent. The estimate of the component's density function is constrained only to be unimodal and non-negative. Numerical examples suggest that the method can yield reasonably accurate estimates with sample sizes of 300 and, in some cases, with sample sizes as small as 100.The author wishes to thank David Kohfeld, Jim Ramsay, Jim Townsend and two anonymous referees for a number of useful and stimulating comments on an earlier version of this paper.     

Desire for control and optimistic time predictions

Halkjelsvik, T., Rognaldsen, M. & Teigen, K. H. (2012). Desire for control and optimistic time predictions. Scandinavian Journal of Psychology 53, 499–505. Few studies have investigated individual differences in time predictions. We report two experiments that show an interaction between the personality trait Desirability of Control and reward conditions on predictions of performance time. When motivated to perform a task quickly, participants with a strong desire for control produced more optimistic predictions than those with a weaker desire for control. This effect could also be observed for a completely uncontrollable task. The results are discussed in relation to the finding that power produces more optimistic predictions, and extend this work by ruling out some previously suggested explanations.     

Processing time for naming and categorization of letters and numbers

A reaction-time experiment was carried out to examine the relationship between naming and categorization. Ss were shown one item at a time and asked either to name the item or to categorize the item as a letter or number. The size of the stimulus set was varied systematically across Ss. Naming time increased as the stimulus set size increased; categorization time could be predicted by the time required for naming, plus a constant. These results were interpreted as indicating that naming must precede categorization.     

Equivalent effects of grouping by time, voice, and location on response timing in verbal serial memory

The grouping of list items is known to improve serial memory accuracy and constrain the nature of temporal errors. A recent study (M. T. Maybery, F. B. R. Parmentier, & D. M. Jones, 2002) showed that grouping results in a temporal organization of the participants' responses that mimics the list structure but not the timing of its presentation. Here the authors tested the prediction that the temporal grouping of responses should yield the same pattern of response time (RT) irrespective of the method of grouping at presentation. Comparing temporal, location, and voice grouping, the results show that although these methods impact on recall accuracy to varying degrees, all 3 conditions produce significant and equivalent peaks in RT at the first position of each group. The RT data were accurately simulated through a model based on ACT-R's (J. R. Anderson & M. Matessa, 1997) basic principles. Altogether, the data suggest that the temporal organization of responses in verbal serial recall results from (a) declarative knowledge about the list's structure that is independent of the perceptual means by which grouping is induced at presentation and (b) the level of activation of the items per se.     

Order and serial position effects in response time with multiple-item probe recognition

We examined the order effect in item-recognition response time, that is, differences in response time for multiple-item probes containing items in the same or in the reverse order as those in the memory set. Experiment 1 used the response condition in which only one item must be positive for a positive response, Experiment 2 used homogeneous probes in which all the items are either positive or negative, and Experiment 3 used the condition in which all the items must be positive. Of particular interest were the serial position variations in order effects for probes containing items that were adjacent in the memory set. We previously found that such effects are an indication of subjective grouping of the memory set and the matching of the probe with these subgroups. The order effect in the one-positive condition was only weak in most cases, but it was strong with homogeneous probes when the memory set was objectively grouped or was ungrouped but with a constant set size. There were also strong order effects in the all-positive condition for probes with items that were nonadjacent in the memory set. Our results are interpreted in terms of a parallel match process based on a distribution over position of items in subjective or objective groups. We account for the origin of the distribution-over-position process in terms of multiple representations of the grouped memory sets. The model assumes that each subgroup is represented in memory several, and perhaps very many, times and that considerable error in item positioning can occur over the multiple representations of any group.     

Electrophysiological evidence for parallel and serial processing during visual search

Event-related potentials were recorded from young adults during a visual search task in order to evaluate parallel and serial models of visual processing in the context of Treisman's feature integration theory. Parallel and serial search strategies were produced by the use of feature-present and feature-absent targets, respectively. In the feature-absent condition, the slopes of the functions relating reaction time and latency of the P3 component to set size were essentially identical, indicating that the longer reaction times observed for larger set sizes can be accounted for solely by changes in stimulus identification and classification time, rather than changes in post-perceptual processing stages. In addition, the amplitude of the P3 wave on target-present trials in this condition increased with set size and was greater when the preceding trial contained a target, whereas P3 activity was minimal on target-absent trials. These effects are consistent with the serial self-terminating search model and appear to contradict parallel processing accounts of attention-demanding visual search performance, at least for a subset of search paradigms. Differences in ERP scalp distributions further suggested that different physiological processes are utilized for the detection of feature presence and absence.     

Responding under time pressure: Testing two animal learning models and a model of visual categorization

Two experiments are reported, which employed a Pavlovian eyelid conditioning procedure with human participants. The experiments tested the predictions of three models of the time-course of processing under time pressure. These were the extended generalized context model (Lamberts, 1998), and two variants of the Rescorla-Wagner model (Rescorla & Wagner, 1972), which were activated in cascade mode. Reinforcement schedules in the experiments were equivalent either to an AND rule or to an XOR rule. The time available for processing the conditioned stimulus and initiating a conditioned response was manipulated by varying the interval from the onset of the conditioned stimulus to the onset of the unconditioned stimulus. The results were in accord with the predictions of one of the two variants of the Rescorla-Wagner model.     

Synonym comprehension and the generality of categorization models

Memory & Cognition - When subjects classify a two-word display as representing the “same” category or two “different” categories, semantic similarity between the words...     

Processing time predictions of current models of perception in the classic additive factors paradigm

This article explores the consequences for factorial additivity in a Sternberg [(1969). The discovery of processing stages: Extensions of donders method In: W.G. Koster (Ed.), Attention and performance II, Acta Psychologica, 30, 276-315] additive-factors paradigm of the assumptions adopted by models of perception that relate the representation of a stimulus to decision time. Three example models, signal detection theory with the latency-distance hypothesis, stochastic general recognition theory, and a random walk model of exemplar classification, are interrogated to determine what type of interaction they predict factors will yield in a hypothetical factorial (choice) reaction time experiment in which the ‘empirical’ factors’ effects are manifest as parameter changes. All frameworks make the critical assumption that decision time depends on the perceptual representation of the stimulus as well as the architecture. As a consequence, nonadditivity of factors thought to affect different “stages” in the classical approach emerges within the current modeling approach. The nature of this influence is revealed through analytic investigations and simulation. Earlier empirical findings of failures of selective influence that have defied adequate explanation are reinterpreted in light of the present findings.     

Comparing decision bound and exemplar models of categorization

The performance of a decision bound model of categorization (Ashby, J992a; Ashby & Maddox, in press) is compared with the performance of two exemplar models. The first is the generalized context model (e.g., Nosofsky, 1986, 1992) and the second is a recently proposed deterministic exemplar model (Ashby & Maddox, in press), which contains the generalized context model as a special case. When the exemplars from each category were normally distributed and the optimal decision bound was linear, the deterministic exemplar model and the decision bound model provided roughly equivalent accounts of the data. When the optimal decision bound was nonlinear, the decision bound model provided a more accurate account of the data than did either exemplar model. When applied to categorization data collected by Nosofsky (1986, 1989), in which the category exemplars are not normally distributed, the decision bound model provided excellent accounts of the data, in many cases significantly outperforming the exemplar models. The decision bound model was found to be especially successful when(1) single subject analyses were performed, (2) each subject was given relatively extensive training, and (3) the subject's performance was characterized by complex suboptimalities. These results support the hypothesis that the decision bound is of fundamental importance in predicting asymptotic categorization performance and that the decision bound models provide a viable alternative to the currently popular exemplar models of categorization.