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Simon Farrell

Publications and source records attributed to Simon Farrell.

6 recordsLinked to original sources
PubMed2005

Human cognition and a pile of sand: a discussion on serial correlations and self-organized criticality.

Recently, G. C. Van Orden, J. G. Holden, and M. T. Turvey (2003) proposed to abandon the conventional framework of cognitive psychology in favor of the framework of nonlinear dynamical systems theory. Van Orden et al. presented evidence that "purposive behavior originates in self-organized criticality" (p. 333). Here, the authors show that Van Orden et al.'s analyses do not test their hypotheses. Further, the authors argue that a confirmation of Van Orden et al.'s hypotheses would not have constituted firm evidence in support of their framework. Finally, the absence of a specific model for how self-organized criticality produces the observed behavior makes it very difficult to derive testable predictions. The authors conclude that the proposed paradigm shift is presently unwarranted.

Cognition↗
PubMed2004

Estimation and interpretation of 1/falpha noise in human cognition.

Recent analyses of serial correlations in cognitive tasks have provided preliminary evidence of the presence of a particular form of long-range serial dependence known as 1/f noise. It has been argued that long-range dependence has been largely ignored in mainstream cognitive psychology even though it accounts for a substantial proportion of variability in behavior (see, e.g., Gilden, 1997, 2001). In this article, we discuss the defining characteristics of long-range dependence and argue that claims about its presence need to be evaluated by testing against the alternative hypothesis of short-range dependence. For the data from three experiments, we accomplish such tests with autoregressive fractionally integrated moving-average time series modeling. We find that long-range serial dependence in these experiments can be explained by any of several mechanisms, including mixtures of a small number of short-range processes.

Auditory Perception↗
PubMed2004

AIC model selection using Akaike weights.

The Akaike information criterion (AIC; Akaike, 1973) is a popular method for comparing the adequacy of multiple, possibly nonnested models. Current practice in cognitive psychology is to accept a single model on the basis of only the "raw" AIC values, making it difficult to unambiguously interpret the observed AIC differences in terms of a continuous measure such as probability. Here we demonstrate that AIC values can be easily transformed to so-called Akaike weights (e.g., Akaike, 1978, 1979; Bozdogan, 1987; Burnham & Anderson, 2002), which can be directly interpreted as conditional probabilities for each model. We show by example how these Akaike weights can greatly facilitate the interpretation of the results of AIC model comparison procedures.

Bayes Theorem↗
PubMed2003

Dissimilar items benefit from phonological similarity in serial recall.

In short-term serial recall, similar sounding items are remembered less well than items that do not sound alike. This phonological similarity effect has been observed with lists composed only of similar items, and also with lists that mix together similar and dissimilar items. An additional consistent finding has been what the authors call dissimilar immunity, the finding that ordered recall of dissimilar items is the same whether these items occur in pure dissimilar or mixed lists. The authors present 3 experiments that disconfirm these previous findings by showing that dissimilar items on mixed lists are recalled better than their counterparts on pure lists if order errors are considered separately from intrusion errors (Experiment 1), or if intrusion errors are experimentally controlled (Experiments 2 and 3). The memory benefit for dissimilar items on mixed lists poses a challenge for current models of short-term serial recall.

Association Learning↗
PubMed2002

An endogenous distributed model of ordering in serial recall.

We introduce a distributed model of memory for serial order, called SOB, that produces ordered serial recall by relying on encoding and retrieval processes that are endogenous to the model. SOB explains the basic shape of the serial position curve, the pattern of errors during recall (including the balance between transpositions, omissions, intrusions, and erroneous repetitions), the effects of list length on the distribution of errors, the overall level of recall and response latency, and the effects of natural language frequency on recall performance. In addition, contrary to several recent suggestions, SOB demonstrates that distributed representations can support unambiguous recall, selective response suppression, and novelty-sensitive encoding.

Humans↗