Information-accumulation theory of speeded categorization.

Abstract

A process model of perceptual categorization is presented, in which it is assumed that the earliest stages of categorization involve gradual accumulation of information about object features. The model provides a joint account of categorization choice proportions and response times by assuming that the probability that the information-accumulation process stops at a given time after stimulus presentation is a function of the stimulus information that has been acquired. The model provides an accurate account of categorization response times for integral-dimension stimuli and for separable-dimension stimuli, and it also explains effects of response deadlines and exemplar frequency.The time course of perceptual categorization has recently become the topic of much research (e.g

The relative importance of perceptual and memory sampling processes in determining the time course of absolute identification.

“…The only way the EGCM-RT could account for this is by assuming either that perceptual processing outlasted the stimulus duration or that perceptual processing was completed within 500 ms. If the latter was true, then this would indicate that in these experiments the majority of the RT was due to non-perceptual processing and response production, which runs counter to previous applications of the EGCM-RT in which the time course of perceptual processing appeared to explain a large amount of variability in performance across several different tasks (Lamberts, 1998(Lamberts, , 2000 Guest & Lamberts, 2010, 2011 Kent & Lamberts, 2005, 2006b, 2016, for a review see Kent et al, 2014).In Experiment 2, we collected extensive individual participant data on the time course of absolute identification by manipulating stimulus duration. Unlike other absolute identification studies in which stimulus duration has been manipulated Perceptual and memory sampling in absolute identification 34 34 (Garner & Creelman, 1964, Pollack [cited in Miller, 1956; Ward, 1991) the current study measured both response choice and RT and reported these measures for all stimuli.…”

“…These models suggest that, over the time course of a trial, a representation of a stimulus is gradually built up through repeated sampling of the stimulus such that the information that is fed into the decision process changes over time. In such models (e.g., Lamberts, 2000) task performance at a given point in time is limited by the state of the perceptual representation of the stimulus at that time.Thus the time course of perceptual processing plays a major role in determining response latencies and the choices made.In contrast, many other models of the time course of cognition assume that there is a relatively fast perceptual processing stage, followed by a decision stage in which either a single sample, or multiple samples, of the stimulus representation feeds through into the decision process. In these, sequential sampling, models the emphasis is on the dynamics of the response selection stage determining the time course of performance.…”

“…For example, in the Selective Attention, Mapping, and Ballistic Accumulator model (SAMBA;Brown et al, 2008) it is assumed that perceptual processing takes a relatively small amount of time and that a relatively robust psychophysical representation enters response selection processes fairly quickly. In contrast, the time course of perceptual processing is central in the Extended Generalized Context Model (EGCM; Kent & Lamberts, 2005, 2016.The EGCM was initially developed to account for the time course of categorization performance (Lamberts, 1998(Lamberts, , 2000 extending the Generalized Context Model (Nosofsky, 1986). It assumes that, over time, perceptual information is gradually accumulated such that a representation of a stimulus evolves from an undifferentiated representation to a well-defined representation.…”

Comparison and Contrast in Perceptual Categorization.

“…According to exemplar models, a category is represented by storing exemplars as they are experienced, and categorization is a function of the similarity of the target instance to some set of those stored exemplars that are retrieved for comparison (Estes, 1994;Lamberts, 1995Lamberts, , 2000Medin & Schaffer, 1978;Nosofsky, 1986;Nosofsky & Palmeri, 1997). So, to continue our example, the target hue is compared with a set of blue exemplars and a set of purple exemplars, and the target is included in the category to which its summed similarity is greatest.…”

Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration

“…However, this decision process, in addition to being computationally expensive, may take longer than is practical. If the case is urgent, a doctor might forego considering all available tests and base a quick but "good-enough" decision on a subset of information (Lamberts, 2000;Payne et al, 1988;Rieskamp and Hoffrage, 2008;Wright, 1974), a form of heuristic decision-making known as satisficing (Simon, 1956(Simon, , 1955. While satisficing under uncertainty and high time pressure is ubiquitous in daily life, very little is known about its underlying computational principles and neural mechanisms.…”