Penny M. Pexman

The impact of feedback semantics in visual word recognition: number-of-features effects in lexical decision and naming tasks.

The notion of feedback activation from semantics to both orthography and phonology has recently been used to explain a number of semantic effects in visual word recognition, including polysemy effects (Hino & Lupker, 1996; Pexman & Lupker, 1999) and synonym effects (Pecher, 2001). In the present research, we tested an account based on feedback activation by investigating a new semantic variable: number of features (NOF). Words with high NOF (e.g., LION) should activate richer semantic representations than do words with low NOF (e.g., LIME). As a result, the feedback activation from semantics to orthographic and phonological representations should be greater for high-NOF words, which should produce superior lexical decision task (LDT) and naming task performance. The predicted facilitory NOF effects were observed in both LDT and naming.

There are many ways to be rich: Effects of three measures of semantic richness on visual word recognition

Previous studies have reported that semantic richness facilitates visual word recognition (see, e.g., Buchanan, Westbury, & Burgess, 2001; Pexman, Holyk, & Monfils, 2003). We compared three semantic richness measures—number of semantic neighbors (NSN), the number of words appearing in similar lexical contexts; number of features (NF), the number of features listed for a word’s referent; and contextual dispersion (CD), the distribution of a word’s occurrences across content areas—to determine their abilities to account for response time and error variance in lexical decision and semantic categorization tasks. NF and CD accounted for unique variance in both tasks, whereas NSN accounted for unique variance only in the lexical decision task. Moreover, each measure showed a different pattern of relative contribution across the tasks. Our results provide new clues about how words are represented and suggest that word recognition models need to accommodate each of these influences.

Ambiguity and Synonymy Effects in Lexical Decision, Naming, and Semantic Categorization Tasks: Interactions Between Orthography, Phonology, and Semantics

In this article, ambiguity and synonymy effects were examined in lexical decision, naming, and semantic categorization tasks. Whereas the typical ambiguity advantage was observed in lexical decision and naming, an ambiguity disadvantage was observed in semantic categorization. In addition, a synonymy effect (slower latencies for words with many synonyms than for words with few synonyms) was observed in lexical decision and naming but not in semantic categorization. These results suggest that (a) an ambiguity disadvantage arises only when a task requires semantic processing, (b) the ambiguity advantage and the synonymy disadvantage in lexical decision and naming are due to semantic feedback, and (c) these effects are determined by the nature of the feedback relationships from semantics to

Context Incongruity and Irony Processing

In this research we investigated the role of context in interpretation (Experiments 1 and 2) and relative processing (Experiment 3) of literal and ironic statements. As such, we manipulated degree of situational negativity (using strongly negative, weakly negative, and neutral contexts) and found that, in strongly negative situations, reading times for ironic statements were slower than for literal statements, whereas in weakly negative situations reading times for ironic statements were faster than or equivalent to reading times for literal statements. When these reading time data were related to interpretation data, we found that differences in processing time could be predicted by certain aspects of interpretation. We argue that these results support a direct access model of figurative language processing (e.g., Gibbs, 1994), and also support Colstons (2002) theory of contrast and assimilation in verbal irony.

Number-of-features effects and semantic processing

Participants list many semantic features for some concrete nouns (e.g.,lion) and fewer for others (e.g.,lime; McRae, de Sa, & Seidenberg, 1997). Pexman, Lupker, and Hino (2002) reported faster lexical decision and naming responses for high number of features (NOF) words than for low-NOF words. In the present research, we investigated the impact of NOF on semantic processing. We observed NOF effects in a self-paced reading task when prior context was not congruent with the target word (Experiment 1) and in a semantic categorization task (concrete vs. abstract; Experiment 2A). When we narrowed our stimuli to include high- and low-NOF words from a single category (birds), we found substantial NOF effects that were modulated by the specificity of the categorization task (Experiments 3A, 3B, and 3C). We argue that these results provide support for distributed representation of word meaning.

Evidence for the activation of sensorimotor information during visual word recognition: The body–object interaction effect

We examined the effects of sensorimotor experience in two visual word recognition tasks. Body-object interaction (BOI) ratings were collected for a large set of words. These ratings assess perceptions of the ease with which a human body can physically interact with a words referent. A set of high BOI words (e.g., mask) and a set of low BOI words (e.g., ship) were created, matched on imageability and concreteness. Facilitatory BOI effects were observed in lexical decision and phonological lexical decision tasks: responses were faster for high BOI words than for low BOI words. We discuss how our findings may be accounted for by (a) semantic feedback within the visual word recognition system, and (b) an embodied view of cognition (e.g., Barsalous perceptual symbol systems theory), which proposes that semantic knowledge is grounded in sensorimotor interactions with the environment.

Is more always better? Effects of semantic richness on lexical decision, speeded pronunciation, and semantic classification

Evidence from large-scale studies (Pexman, Hargreaves, Siakaluk, Bodner, & Pope, 2008) suggests that semantic richness, a multidimensional construct reflecting the extent of variability in the information associated with a word’s meaning, facilitates visual word recognition. Specifically, recognition is better for words that (1) have more semantic neighbors, (2) possess referents with more features, and (3) are associated with more contexts. The present study extends Pexman et al. (2008) by examining how two additional measures of semantic richness, number of senses and number of associates (Pexman, Hargreaves, Edwards, Henry, & Goodyear, 2007), influence lexical decision, speeded pronunciation, and semantic classification performance, after controlling for an array of lexical and semantic variables. We found that number of features and contexts consistently facilitated word recognition but that the effects of semantic neighborhood density and number of associates were less robust. Words with more senses also elicited faster lexical decisions but less accurate semantic classifications. These findings point to how the effects of different semantic dimensions are selectively and adaptively modulated by task-specific demands.

Children's Perceptions of the Social Functions of Verbal Irony

Verbal irony can serve many social functions: Speakers can mute the aggression conveyed by criticism or temper the praise conveyed by a compliment (the Tinge Hypothesis; Dews, Kaplan, & Winner, 1995), and speakers can also bring humor to a situation. A full understanding of ironic language requires one to make complex inferences about speaker intent, a task that can be challenging for children. This study was devised as a developmental test of the Tinge Hypothesis. Two experiments assessed 5- to 6- and 7- to 8-year-old childrens abilities to detect and interpret the aggressive and humorous intent of speakers who made ironic criticisms, literal criticisms, ironic compliments, and literal compliments depicted in puppet shows. When children detected the use of irony, their aggression ratings provided support for the Tinge Hypothesis but their humor ratings indicated that the humor function was not recognized.

Neural Correlates of Concreteness in Semantic Categorization

In some contexts, concrete words (CARROT) are recognized and remembered more readily than abstract words (TRUTH). This concreteness effect has historically been explained by two theories of semantic representation: dual-coding [Paivio, A. Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45, 255287, 1991] and context-availability [Schwanenflugel, P. J. Why are abstract concepts hard to understand? In P. J. Schwanenflugel (Ed.), The psychology of word meanings (pp. 223250). Hillsdale, NJ: Erlbaum, 1991]. Past efforts to adjudicate between these theories using functional magnetic resonance imaging have produced mixed results. Using event-related functional magnetic resonance imaging, we reexamined this issue with a semantic categorization task that allowed for uniform semantic judgments of concrete and abstract words. The participants were 20 healthy adults. Functional analyses contrasted activation associated with concrete and abstract meanings of ambiguous and unambiguous words. Results showed that for both ambiguous and unambiguous words, abstract meanings were associated with more widespread cortical activation than concrete meanings in numerous regions associated with semantic processing, including temporal, parietal, and frontal cortices. These results are inconsistent with both dual-coding and context-availability theories, as these theories propose that the representations of abstract concepts are relatively impoverished. Our results suggest, instead, that semantic retrieval of abstract concepts involves a network of association areas. We argue that this finding is compatible with a theory of semantic representation such as Barsalous [Barsalou, L. W. Perceptual symbol systems. Behavioral & Brain Sciences, 22, 577660, 1999] perceptual symbol systems, whereby concrete and abstract concepts are represented by similar mechanisms but with differences in focal content.

An Abundance of Riches: Cross-Task Comparisons of Semantic Richness Effects in Visual Word Recognition

There is considerable evidence (e.g., Pexman et al., 2008) that semantically rich words, which are associated with relatively more semantic information, are recognized faster across different lexical processing tasks. The present study extends this earlier work by providing the most comprehensive evaluation to date of semantic richness effects on visual word recognition performance. Specifically, using mixed effects analyses to control for the influence of correlated lexical variables, we considered the impact of number of features, number of senses, semantic neighborhood density, imageability, and body–object interaction across five visual word recognition tasks: standard lexical decision, go/no-go lexical decision, speeded pronunciation, progressive demasking, and semantic classification. Semantic richness effects could be reliably detected in all tasks of lexical processing, indicating that semantic representations, particularly their imaginal and featural aspects, play a fundamental role in visual word recognition. However, there was also evidence that the strength of certain richness effects could be flexibly and adaptively modulated by task demands, consistent with an intriguing interplay between task-specific mechanisms and differentiated semantic processing.