Distributional Analyses in Visual Lexical Decision: Orthographic Neighborhood Density and Word Frequency Effects

Distributional Analyses in Visual Lexical Decision: Orthographic Neighborhood Density and Word Frequency Effects Stephen Wee Hun Lim (gmslwhs@nus.edu.sg) Melvin J. Yap (psyyapm@nus.edu.sg) Department of Psychology, National University of Singapore Block AS4, 9 Arts Link, Singapore117570 the units for words containing these letters. Activity also feeds back from the word to the letter level, causing reverberating patterns of activity to occur between these levels. To ensure that only one word unit eventually obtains threshold, McClelland and Rumelhart (1981) also assume that inhibition occurs between word units, so that the activity level of competing word units is reduced relative to the maximally active node. Within the activation framework, word frequency is assumed to be reflected in the threshold (Morton, 1969) or resting activation level (McClelland & Rumelhart, 1981) associated with a particular word unit. The critical interpretation is that less evidence is required to enable recognition of a high-, than a low-, frequency word. The findings for orthographic neighborhood density effects (N), on the other hand, appear to be more mixed. The N metric has been defined by Coltheart, Davelaar, Jonasson, and Besner (1977) as the number of close neighbors a word has and refers to the number of words that can be created by changing a single letter of this target word. For instance, tell has many neighbors such as well, yell, sell, teal and tall, while once has no neighbors. Neighborhood effects can help specify the mechanisms underlying lexical access. The implication of the overlap in the features constituting different words is that any subset of the features constituting a particular word is unlikely to uniquely specify its corresponding lexical representation. Neighbors are items that are highly confusable with the target word, in the sense that they share a large number of their features with the target. Thus, it seems inevitable that some or all of the neighbors of a target word will be selected by the access mechanisms as eligible target candidates. Effects of N can be accommodated within activation- based models of lexical access, and appear to provide substantive support for an activation mechanism. If presenting a word leads to an activation of all lexical items that sufficiently match features of the target word, the density of the word’s neighborhood should influence access time. Unfortunately, this class of models does not make precise predictions about the nature of the effect of neighborhood density. McClelland and Rumelhart’s (1981) interactive activation model, for instance, assumes excitatory links between levels which can account for facilitatory effects of neighborhood size. Activated neighbors will feed back to their constituent letters which in turn lead to heightened activation of word units containing these letters. According to McClelland and Rumelhart Abstract The effects of orthographic neighborhood density and word frequency in visual word recognition were investigated using distributional analyses of response latencies in visual lexical decision. Main effects of density and frequency were observed in mean latencies. Distributional analyses, in addition, revealed a density x frequency interaction: for low- frequency words, density effects were mediated predominantly by distributional shifting whereas for high- frequency words, density effects were absent except at the slower RTs, implicating distributional skewing. The present findings suggest that density effects in low-frequency words reflect processes involved in early lexical access, while the effects observed in high-frequency words reflect late postlexical checking processes. Keywords: Orthographic neighborhood density; word frequency; visual lexical decision; distributional analyses Introduction Word frequency and orthographic neighborhood density effects are among the most influential findings in the visual word recognition literature. Researchers study word recognition using the lexical decision task (LDT) that requires lexicality discrimination and decision where subjects would classify stimuli as either words or nonwords, and the speeded pronunciation (word naming) task that involves lexical access but excludes the word/nonword discrimination and decision components of the LDT. During word naming, subjects would typically be tested individually and read the stimuli into a microphone (see Andrews, 1997). Word frequency effects, where latencies for common words are faster than those that are relatively less common, have been observed in many LDT studies (see Balota & Chumbley, 1990 for a review). In visual word recognition, frequency effects have been attributed to changes in activation thresholds or baselines. The logogen-style activation framework was inaugurated by Morton (1969), which assumes that information extracted from the sensory representation of the word leads to parallel activation of all word units that match that information. When sufficient activation has accumulated in a particular word unit, it reaches threshold and lexical access occurs. Morton’s (1969) initial model was later specified in greater detail by McClelland and Rumelhart (1981). Their model, which they called the interactive activation model, suggests that activation occurs at three levels. Activation of featural units feeds to units corresponding to letters, which in turn activate