Stochastic accumulation of feature information in perception and memory

It is now well established that the time course of perceptual processing influences the first second or so of performance in a wide variety of cognitive tasks. Over the last20 years, there has been a shift from modeling the speed at which a display is processed, to modeling the speed at which different features of the display are perceived and formalizing how this perceptual information is used in decision making. The first of these models(Lamberts, 1995) was implemented to fit the time course of performance in a speeded perceptual categorization task and assumed a simple stochastic accumulation of feature information. Subsequently, similar approaches have been used to model performance in a range of cognitive tasks including identification, absolute identification, perceptual matching, recognition, visual search, and word processing, again assuming a simple stochastic accumulation of feature information from both the stimulus and representations held in memory. These models are typically fit to data from signal-to-respond experiments whereby the effects of stimulus exposure duration on performance are examined, but response times (RTs) and RT distributions have also been modeled. In this article, we review this approach and explore the insights it has provided about the interplay between perceptual processing, memory retrieval, and decision making in a variety of tasks. In so doing, we highlight how such approaches can continue to usefully contribute to our understanding of cognition

Absolute identification by relative judgment

In unidimensional absolute identification tasks, participants identify stimuli that vary along a single dimension. Performance is surprisingly poor compared with discrimination of the same stimuli. Existing models assume that identification is achieved using long-term representations of absolute magnitudes. The authors propose an alternative relative judgment model (RJM) in which the elemental perceptual units are representations of the differences between current and previous stimuli. These differences are used, together with the previous feedback, to respond. Without using long-term representations of absolute magnitudes, the RJM accounts for (a) information transmission limits, (b) bowed serial position effects, and (c) sequential effects, where responses are biased toward immediately preceding stimuli but away from more distant stimuli (assimilation and contrast)

The dynamics of syntax acquisition: facilitation between syntactic structures

This paper sets out to show how facilitation between different clause structures operates over time in syntax acquisition. The phenomenon of facilitation within given structures has been widely documented, yet inter-structure facilitation has rarely been reported so far. Our findings are based on the naturalistic production corpora of six toddlers learning Hebrew as their first language. We use regression analysis, a method that has not been used to study this phenomenon. We find that the proportion of errors among the earliest produced clauses in a structure is related to the degree of acceleration of that structure's learning curve; that with the accretion of structures the proportion of errors among the first clauses of new structures declines, as does the acceleration of their learning curves. We interpret our findings as showing that learning new syntactic structures is made easier, or facilitated, by previously acquired ones

On the interaction between exemplar-based concepts and a response scaling process

Copyright © 2007 Elsevier Inc. All rights reserved.An analysis of the "response scaling" parameter in the Generalized Context Model is presented. In light of the existing debate over the behavior of the model when this parameter is included, three different interpretations are discussed, in order to illustrate the effect of the parameter at the decision level, the category similarity level, and the representational structure level. © 2007 Elsevier Inc. All rights reserved.Daniel J. Navarrohttp://www.elsevier.com/wps/find/journaldescription.cws_home/622887/description#descriptio

Sequence effects in the categorization of tones varying in frequency

In contrast to exemplar and decision-bound categorization models, the memory and contrast models described here do not assume that long-term representations of stimulus magnitudes are available. Instead, stimuli are assumed to be categorized using only their differences from a few recent stimuli. To test this alternative, the authors examined sequential effects in a binary categorization of 10 tones varying in frequency. Stimuli up to 2 trials back in the sequence had a significant effect on the response to the current stimulus. The effects of previous stimuli interacted with one another. A memory and contrast model, according to which only ordinal information about the differences between the current stimulus and recent preceding stimuli is used, best accounted for these dat