Relative judgement is relatively difficult: evidence against the role of relative judgement in absolute identification

A variety of processes have been put forward to explain absolute identification performance. One difference between current models of absolute identification is the extent to which the task involves accessing stored representations in long-term memory (e.g. exemplars in memory, Kent & Lamberts, Journal of Experimental Psychology: Learning Memory and Cognition, 31, 289–305, 2005) or relative judgement (comparison of the current stimulus to the stimulus on the previous trial, Stewart, Brown & Chater, Psychological Review, 112, 881–911, 2005). In two experiments we explored this by tapping into these processes. In Experiment 1 participants completed an absolute identification task using eight line lengths whereby a single stimulus was presented on each trial for identification. They also completed a matching task aimed at mirroring exemplar comparison in which eight line lengths were presented in a circular array and the task was to report which of these matched a target presented centrally. Experiment 2 was a relative judgement task and was similar to Experiment 1 except that the task was to report the difference (jump-size) between the current stimulus and that on the previous trial. The absolute identification and matching data showed clear similarities (faster and more accurate responding for stimuli near the edges of the range and similar stimulus-response confusions). In contrast, relative judgment performance was poor suggesting relative judgement is not straightforward. Moreover, performance as a function of jump-size differed considerably between the relative judgement and absolute identification tasks. Similarly, in the relative judgement task, predicting correct stimulus identification based on successful relative judgement yielded the reverse pattern of performance observed in the absolute identification task. Overall, the data suggest that relative judgement does not underlie absolute identification and that the task is more likely reliant on an exemplar comparison process

A model of top-down gain control in the auditory system

To evaluate a model of top-down gain control in the auditory system, 6 participants were asked to identify 1-kHz pure tones differing only in intensity. There were three 20-session conditions: (1) four soft tones (25, 30, 35, and 40 dB SPL) in the set; (2) those four soft tones plus a 50-dB SPL tone; and (3) the four soft tones plus an 80-dB SPL tone. The results were well described by a top-down, nonlinear gain-control system in which the amplifier’s gain depended on the highest intensity in the stimulus set. Individual participants’ identification judgments were generally compatible with an equal-variance signal-detection model in which the mean locations of the distribution of effects along the decision axis were determined by the operation of this nonlinear amplification system

Towards a quantum probability theory of similarity judgments

We review recent progress in understanding similarity judgments in cognition by means of quantum probability theory (QP) models. We begin by outlining some features of similarity judgments that have proven difficult to model by traditional approaches. We then briefly present a model of similarity judgments based on QP, and show how it can solve many of the problems faced by traditional approaches. Finally we look at some areas where the quantum model is currently less satisfactory, and discuss some open questions and areas for further work

Learning time-varying categories

Many kinds of objects and events in our world have a strongly time-dependent quality. However, most theories about concepts and categories either are insensitive to variation over time or treat it as a nuisance factor that produces irrational order effects during learning. In this article, we present two category learning experiments in which we explored peoples’ ability to learn categories whose structure is strongly time-dependent. We suggest that order effects in categorization may in part reflect a sensitivity to changing environments, and that understanding dynamically changing concepts is an important part of developing a full account of human categorization.Daniel J. Navarro, Amy Perfors, Wai Keen Von

Motor Adaptation Scaled by the Difficulty of a Secondary Cognitive Task

Background: Motor learning requires evaluating performance in previous movements and modifying future movements. The executive system, generally involved in planning and decision-making, could monitor and modify behavior in response to changes in task difficulty or performance. Here we aim to identify the quantitative cognitive contribution to responsive and adaptive control to identify possible overlap between cognitive and motor processes. Methodology/Principal Findings: We developed a dual-task experiment that varied the trial-by-trial difficulty of a secondary cognitive task while participants performed a motor adaptation task. Subjects performed a difficulty-graded semantic categorization task while making reaching movements that were occasionally subjected to force perturbations. We find that motor adaptation was specifically impaired on the most difficult to categorize trials. Conclusions/Significance: We suggest that the degree of decision-level difficulty of a particular categorization differentially burdens the executive system and subsequently results in a proportional degradation of adaptation. Our results suggest

The wisdom of the crowd playing The Price Is Right

In The Price Is Right game show, players compete to win a prize, by placing bids on its price. We ask whether it is possible to achieve a “wisdom of the crowd” effect, by combining the bids to produce an aggregate price estimate that is superior to the estimates of individual players. Using data from the game show, we show that a wisdom of the crowd effect is possible, especially by using models of the decision-making processes involved in bidding. The key insight is that, because of the competitive nature of the game, what people bid is not necessarily the same as what they know. This means better estimates are formed by aggregating latent knowledge than by aggregating observed bids. We use our results to highlight the usefulness of models of cognition and decision-making in studying the wisdom of the crowd, which are often approached only from non-psychological statistical perspectives