Semantic processing in auditory lexical decision: Ear-of ... - Wayne State

COGNITION AND EMOTION 2007, 21 (7), 1470 1495

Semantic processing in auditory lexical decision: Ear-of-presentation and sex differences Lee H. Wurm, R. Douglas Whitman, Sean R. Seaman, Laura Hill, and Heather M. Ulstad Wayne State University, Detroit, MI, USA

In this study we examined the interplay between appetitive (approach) and defensive (avoid) responses in spoken word recognition. Ninety-two right-handed participants (half women) took part in an auditory lexical decision experiment in which speech was presented to only one ear. The danger and usefulness of the word referents interacted in predicting RTs, as in previous (binaural) studies with poorer control of psycholinguistic covariates. Specifically, higher danger ratings were associated with faster RTs for words rated low on usefulness; but higher danger ratings were associated with slower RTs for words rated high on usefulness. In addition to this primary finding, men showed more lateralised performance, as indicated by significant interactions of sex and ear of presentation with word frequency, and with the animacy of the word referents. For both sexes, word frequency had a stronger effect on accuracy for speech presented to the right ear. Finally, men’s but not women’s RTs were related to the danger dimension. This last finding provides an intriguing avenue for future research in the area of sex differences and emotion.

One of the current debates in the literature on word recognition is the extent to which information about word meanings affects the recognition process. One view is that a word’s meaning becomes fully and exclusively available only at the moment of (or immediately following) word recognition. This view is intuitively pleasing: How can a word’s meaning become available before the word is recognised? Nevertheless, a growing literature on semantic processing is leading many researchers to believe that some aspects of word meaning influence the very process by which a word is recognised, or that word meanings are computed by the perceptual system as a routine part of Correspondence should be addressed to: Lee H. Wurm, Department of Psychology and Program in Linguistics, 5057 Woodward Avenue (7th floor), Wayne State University, Detroit, MI 48202, USA. E-mail: [email protected] We would like to thank Mark Pluymaekers and an anonymous reviewer for making very helpful comments on an earlier version of this manuscript. # 2007 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business www.psypress.com/cogemotion DOI: 10.1080/02699930600980908

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the recognition process (e.g., Barsalou, 1987; Marslen-Wilson & Tyler, 1980; Pulvermu¨ller, 2001; Vakoch & Wurm, 1997; Wurm & Vakoch, 1996, 2000; Wurm, Vakoch, Aycock, & Childers, 2003; Wurm, Vakoch, & Seaman, 2004a; Wurm, Vakoch, Seaman, & Buchanan, 2004b). Given that there is a disagreement about whether semantics can influence recognition, it is not surprising that there is no consensus about what the nature of such semantic information would be. In our previous work (Wurm & Vakoch, 2000; Wurm et al., 2003, 2004b), we have argued that two semantic constructs, danger and usefulness, code information that is crucially important for survival.1 It is adaptive for an organism to be able to make very rapid judgments or classifications along these dimensions. Our selection of these particular constructs is consistent with the idea that there are different kinds of reactions to affective stimuli: appetitive reactions and defensive reactions (e.g., Bradley, Codispoti, Cuthbert, & Lang, 2001; Lang, Bradley, & Cuthbert, 1998; see also Davidson, 1992; Schneirla, 1965). Specifically we have argued that there is a relationship between appetitive reactions and the usefulness dimension, and between defensive reactions and the danger dimension. In our earlier studies, one group of participants rated a large number of words on the danger or usefulness of the word referents. A separate group of participants performed the lexical decision task or the naming task to these stimuli, and we found main effects of both danger and usefulness. Higher participant ratings on either of these dimensions led to faster lexical decision times. There was also an interesting interaction. For words low on usefulness, increasing danger led to faster RTs. This response pattern has a straightforward interpretation in terms of the importance of avoiding dangerous things. For words rated high on usefulness, though, increasing danger ratings led to slower RTs. This was interpreted as reflecting a response conflict: High usefulness leads to an approach response, while increasing danger leads to an avoid response. This interaction has been observed with both auditory and visual stimulus presentation, and with different experimental tasks required of the subject (Wurm & Vakoch, 2000; Wurm et al., 2004b). We therefore believe that the interaction between danger and usefulness, suggesting a response conflict under conditions of ‘‘dangerous but useful’’ connotation, reflects general cognitive processes related to survival. The current study had two major purposes. One was to rule out alternative explanations for our previous demonstrations of danger and usefulness effects, and the other was to determine whether the sex of the 1 Linguists may argue that danger and usefulness are pragmatic rather than semantic variables. Our treatment of them as semantic is consistent with the (perhaps technically incorrect) terminology in the psycholinguistics literature.

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participants or the brain hemisphere to which stimuli were presented would interact with these or other psycholinguistic variables. We sought to achieve the first major purpose by two means. First, we carefully analysed the error responses. Error data provide a rich and largely untapped source of information in most cognitive psychological studies. In the current context, it remains unknown whether danger or usefulness relate to response accuracy. Furthermore, if these variables are related to accuracy, it could either be in a way that agrees with the RT patterns, or it could be indicative of a speed vs. accuracy tradeoff. This latter possibility would be interesting in its own right, given the short time scale typical for auditory lexical decision responses (mean RTs are generally less than 500 ms). However, the effects would be considered less important to include in formal models, because they would be seen as strategic or bias-related effects that come or go depending on the specifics of the experimental situation. However, if the error analyses agree with the RT analyses, it would provide another piece of evidence that the effects need to be taken seriously by theories of perception and word recognition. Another alternative explanation we sought to rule out was that previously demonstrated effects of danger and usefulness were due to other, uncontrolled semantic processing variables. The specific semantic variables we investigated are morphological family size, number of meanings (i.e., polysemy), and concreteness (these are described in more detail in the method section). These specific variables were chosen because they are receiving increasing attention among researchers and all are believed to have their basis in semantics.2 To achieve the second major purpose of the study, we compared responses for equal numbers of men and women who heard speech stimuli presented monaurally to the left or right ear. There are some intriguing suggestions that there may be sex and/or hemisphere differences in participants’ responses to emotional or psycholinguistic stimuli, but this remains largely unexplored territory and the literature is equivocal about what is to be expected. Our interest in these two variables was primarily in whether they would interact with more thoroughly studied lexical processing variables. One suggestion of sex differences that bears on our previous work comes from the model of Taylor and colleagues, in which men and women have different biobehavioural responses to stress (Taylor et al., 2000, 2002). They proposed that the fight-or-flight reaction (the physiological response to a perceived threat, preparing an organism to either fight or flee), typically 2 Baayen, Feldman, and Schreuder (2006) demonstrate that family size is a variable rooted in semantics. In fact, while it is not central to the current proposal, Baayen et al. (2006) have argued that the word frequency effect can be thought of as semantic, too, because it reflects an underlying conceptual (rather than form-based) familiarity.


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associated with sympathetic nervous system activity, may be limited to men. While this model does not specifically address dimensions of semantic connotation, it would seem to suggest that men should be more reactive than women to the danger dimension. The model may also predict that women will be more reactive than men to the usefulness dimension. According to the model, women have a response pattern characterised as ‘‘tend-and-befriend’’, which differs from the male response pattern because of the different levels of parental investment in offspring. The authors wrote ‘‘women’s responses to stress are characterized by patterns that involve contributing to the development of social groupings, especially those involving female networks, for the exchange of resources and responsibilities’’ (Taylor et al., 2000, pp. 421 422, emphasis ours; see also Geary & Flinn, 2002). Taylor et al.’s framework is consistent with our previous interpretation of usefulness main effects (Wurm & Vakoch, 2000; Wurm et al., 2003, 2004b), though we did not apply this reasoning specifically to women. There are several studies in the literature suggesting that sex may interact with ear of presentation. These studies find that men and women exhibit differences in the asymmetry of laterality on verbal tasks (e.g., McGlone, 1980; Weekes & Zaidel, 1996), spatial tasks (e.g., Witelson, 1976) and emotion processing tasks (e.g., Coney & Fitzgerald, 2000; Kesler-West et al., 2000; Hall, Witelson, Szechtman, & Nahmias, 2004). A number of studies suggest that language processing involves more bilateral processes in females and is processed more dominantly in the left hemisphere for males (e.g., Kansaku, Yamaura, & Kitazawa, 2000; McGlone, 1980; Shaywitz et al., 1995). Recent brain imaging studies of transcallosal conduction speed confirm this conclusion (Nowicka & Ferstein, 2001).

Predictions 1. Because we believe that danger and usefulness effects reflect a fundamental aspect of ordinary perception (Wurm & Vakoch, 2000; Wurm et al., 2003, 2004b), we predicted that even when controlling for family size, number of meanings, and concreteness, response latencies would be related to danger and usefulness. For the same reason, we predicted that the error analysis would be broadly consistent with the results of the RT analysis. 2. Based on an integration of our previous work (Vakoch & Wurm, 1997; Wurm & Vakoch, 2000; Wurm et al., 2004a) and the model of Taylor and colleagues (Taylor et al., 2000, 2002), we predicted that women would show larger usefulness effects than men. We also predicted that men would show larger danger effects than women.

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3. Based on the research on sex and laterality effects summarised above (Kansaku et al., 2000; McGlone, 1980; Shaywitz et al., 1995), we predicted that men would show more ear-of-presentation interactions than women. 4. Given the assumption of language-specific structures predominating in the left hemisphere, it would seem reasonable to predict that performance on language tasks will be best when stimuli are presented to the right ear (e.g., Coney, 2005; see also Zaidel, 1978, 1990). Other researchers have asserted that such advantages do not necessarily hold in all cases (e.g., Chiarello, Liu, Shears, & Kacinik, 2002; Glosser, & Donofrio, 2001; Sereno, 1999), but we nevertheless predicted that if ear of presentation interacted with any other variables, the effects would be larger when speech was presented to the right ear.

METHOD Participants Ninety-two undergraduates (half women) from the psychology subject pool at Wayne State University participated in this study. By self-report, all were right-handed native speakers of American English with normal hearing. Participants received extra credit in a psychology course for their participation.

Stimuli We used the stimuli from Wurm and Vakoch (2000) for which a concreteness value was listed in the MRC Psycholinguistic Database (Wilson, 1988). This resulted in a list of seventy-five common nouns (see the Appendix). An equal number of pseudowords was created by changing the phoneme at the uniqueness point of a word (UP; see Marslen-Wilson & Welsh, 1978) to a different phoneme from the same broad class. For example, the word poverty [?pav3rti] was changed to the pseudoword pozerty [?paz3rti].

Procedure Participants were tested either individually or in pairs in a sound-attenuating chamber. We used monaural stimulus presentation and randomly assigned participants to hear the stimuli either in the left ear or the right ear. Monaural presentation makes detection of hemispheric effects more difficult (Voyer, 2003), but given some of the problems with dichotic tasks (having to do with biases, participant strategies, and attentional effects), we thought this a preferable conservative approach. Stimuli were presented over Koss R/80 headphones at a comfortable listening level. The headphones’


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circumaural closed-ear design prevented sound from entering the undesired ear, either from a participant’s own headphones or from those of another participant (if there was one) in the sound-attenuating chamber. A different random stimulus order was used for each participant (or pair of participants). Participants heard stimuli presented over the headphones, one at a time, and were told to make a speeded lexical decision to each one. For genuine words they pressed the right button on a two-button mouse with their right index fingers. For pseudowords they pressed the left button on the mouse with their left index fingers. Responses and response latencies were recorded by the experimental software. Before the main experiment, a set of 20 practice items was presented to the participants.

Analysis of response times We performed a repeated-measures multiple regression analysis on the correct lexical decision times to the 75 critical words (Baayen, 2004; Baayen, Tweedie, & Schreuder, 2002; Pinheiro & Bates, 2000; Quene´ & van den Bergh, 2004; see also Lorch & Myers, 1990), with participant as the grouping factor. We included in the model several predictors: 1. Trial number. This allowed us to partition variance attributable to practice or fatigue effects. 2. Duration of the spoken word, in milliseconds. 3. Location of the uniqueness point within the spoken word, in milliseconds. We measured from the middle of the prototypical phoneme in question (following Radeau, Mousty, & Bertelson, 1989). 4. Number of competitors, which we used as a measure of the auditory neighbourhood density. For number of competitors, we calculated the cohort size of one phoneme prior to the uniqueness point (that is, the number of words that cannot be ruled out by the acoustic input until the uniqueness point). This variable has been found to influence auditory lexical decision and naming times (Wurm & Aycock, 2003; Wurm & Ross, 2001). Lexical processing of spoken materials is usually found to be more difficult in dense neighbourhoods. 5. Whether the first syllable of the word is stressed. 6. Sex of the participant. As noted above, we were particularly interested in interactions with sex. 7. Ear to which stimuli were presented. As with sex, we were particularly interested in ear interactions. 8. Word frequency, taken from the CELEX lexical database of 17.9 million tokens (Baayen, Piepenbrock, & Gullikers, 1995). 9. Whether the word referent is animate. This is a variable of central concern in the formation of concepts (e.g., Gelman, 1990). However, it

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has not received much attention from researchers studying word recognition processes in non-disordered adults. 10.Morphological family size, defined as the number of compound words and derived words in which a given target word appears as a constituent. For example, the morphological family of work would include words such as workbook, worker, and so on. A great deal of research has demonstrated that large families facilitate visual lexical processing (Bertram, Baayen, & Schreuder, 2000; de Jong, Feldman, Schreuder, Pastizzo, & Baayen, 2002; de Jong, Schreuder, & Baayen, 2003; Schreuder & Baayen, 1997), but there has been less research looking at the effects of this variable on auditory processing (Wurm, Ernestus, Schreuder, & Baayen, 2006). 11.Number of meanings. Previous research suggests that the more meanings a word has, the faster that word will be recognised (but see Rodd, Gaskell, & Marslen-Wilson, 2002). Again, though, the majority of this work has used visually presented stimuli, whereas the current study used auditorily presented stimuli. We defined number of meanings as the number of synonym sets a word has in WordNet (Beckwith, Fellbaum, Gross, & Miller, 1991; Fellbaum, 1998; Miller, 1990). A synonym set is a set of semantically related words. 12.Concreteness of the word referent, taken from the MRC Psycholinguistic database (Wilson, 1988). Words with concrete referents are often processed faster than those with abstract ones, for both normal and lesioned participants (e.g., Kounios, & Holcomb, 1994; Strain & Herdman, 1999; Strain, Patterson, & Seidenberg, 1995; Tyler, Voice, & Moss, 2000). 13.Danger of the word referent. Ratings were taken from Wurm and Vakoch (2000). 14.Usefulness of the word referent. Ratings were taken from Wurm and Vakoch (2000). In our statistical analysis we assessed the interaction of all variables with sex and with ear of presentation. We also assessed the danger /usefulness interaction, and its interactions with sex and ear, because this interaction is a central part of the theoretical framework developed in our earlier work (Wurm & Vakoch, 2000; Wurm et al., 2003, 2004b). Several variables had positively skewed distributions, and were therefore log transformed to minimise the effects of atypical outliers. These were: frequency, duration, danger rating, uniqueness point location, morphological family size, number of meanings, and number of competitors. In addition, the distribution of concreteness values had severe negative skew. These values were inverse, reflect, and square root transformed (see Tabachnick & Fidell, 2001; we then multiplied the transformed values by


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/1 so that the regression coefficients could be interpreted directly). Table 1 shows the intercorrelations for the regressors after performing all necessary transformations.

RESULTS RTs for trials on which the participant made the lexical decision incorrectly were not included (4.4% of the trials). The mean RT for correct trials was 482 ms (SD /231). Table 2 shows the final statistical model for predicting RTs, which were log-transformed because of positive skew. We retained in the model all main effects, but only those interaction terms that were themselves significant, or that are needed in the model so that a higher-order interaction can be interpreted (e.g., Cohen & Cohen, 1983). A statistical model with this many variables in it is at some risk of overfitting the data. Therefore we carried out a bootstrap validation on the by-item mean RTs with 200 bootstrap runs. This provided an estimate of the explained variance that is conservative, and a more realistic measure of how well the model would predict new data (Harrell, 2001). The difference between the raw R2 (.707) and the bootstrap-adjusted R2 (.657) was .050, which is considered small. This ensures that our statistical model does not overfit the data. As a second safeguard against multicollinearity and overfitting, we re-ran the analyses reported in Tables 2 and 3 without the morphological family size variable. Inspection of Table 1 shows that family size is involved in half of the significant correlations in the predictor set, including the four strongest ones. The reanalyses produced one change from the reported analyses: The significant inhibitory effect of number of competitors in Table 2 was no longer significant when family size was removed from the analysis. We feel safe in concluding that the obtained results are not due to overfitting the data, or to high multicollinearity among the regressor variables. We begin with a description of the significant main effects. Words with unstressed first syllables, or animate referents were recognised more quickly. Trial number was significant; its positive coefficient means that participants slowed during the course of the experiment, probably due to fatigue. Words with later UPs were recognised faster,3 as were words with longer durations 3 For consistency with our previous work, we measured RTs from the UP of each word. It might be argued that a more theory-neutral approach would be to measure RTs from item onset, but in fact it makes little difference. In an onset analysis, the UP effect changes sign, so that words with later UPs are recognised later. All effects that are not significant in our presented analysis are also not significant in the onset analysis; and all of the effects that are significant in our presented analysis are also significant in the onset analysis, except for the main effects of stress and morphological family size.

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TABLE 1 Regressor intercorrelations

Meanings Frequency Danger Usefulness Concreteness Family size Duration Uniqueness point

Frequency

Danger

Usefulness

Concreteness

Family size

Duration

.225

.004 .100

.074 .356** /.109

/.020 /.197 .024 .261*

.430** .464*** .055 .238* .064

/.260* /.108 .151 /.077 /.147 /.511***

Note : *p B/.05; **p B/.01; ***p B/.001.

Uniqueness point .362** .162 /.019 .323** .094 .450*** /.188

Competitors .010 .005 /.032 .172 .066 .307** /.322** .127


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TABLE 2 Summary of regression analysis for variables predicting log auditory lexical decision time Factors and interactions involving factors Ear Sex Stressed first syllable Animate referent Ear/sex Ear/log word frequency Sex/log word frequency Sex/log danger Ear/animate referent Sex/animate referent Ear/sex/log word frequency Ear/sex/animate referent

Continuous variables Trial number Log UP location Log item duration Log number of competitors Log word frequency Concretenessa Log morph. family size Log number of meanings Log danger Usefulness Log danger/usefulness

df 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,

F

89 89 5956 5956 88 5949 5949 5949 5949 5949 5946 5946

1.01 B/1.0 212.88*** 57.64*** B/1.0 B/1.0 B/1.0 5.78* 3.12$ B/1.0 6.18* 4.37*

Regression coefficient (B)

Standard error of B

df

t

0.0003 /0.7620 0.3287 0.0122 /0.0150 /0.0079 /0.0280 /0.0042 /0.0078 /0.0120 0.0236

0.0001 0.0217 0.0359 0.0047 0.0044 0.0015 0.0057 0.0086 0.0068 0.0029 0.0043

5956 5956 5956 5956 5956 5956 5956 5956 5956 5956 5949

4.177*** /35.196*** 9.149*** 2.590** /3.410*** /5.386*** /4.950*** /0.486 /1.145 /4.141*** 5.515***

Notes : $p B/.10; *p B/.05; **p B/.01; ***p B/.001. aConcreteness values were transformed as described in the analysis section.

or denser neighbourhoods (as indexed by number of competitors). More frequent words and more concrete words were recognised faster, as were words with larger morphological families. Words with higher usefulness ratings were also recognised faster. All of these effects are in the expected direction, although in some of our experiments the trial number effect has a negative coefficient, suggesting increased speed with practice. The expected danger /usefulness interaction was significant (pB/.001) and is shown in Figure 1. This figure was created by plotting the regression equation, using the median values for all continuous variables in the model except for danger and usefulness. In making the plot, ‘‘danger’’ was a vector that ran from the natural log of 1 to the natural log of 8 (1 to 8 representing the number scale used to make the ratings). A value of 1.49 was used for low usefulness, and 5.07 was used for high usefulness (these are one SD below

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Figure 1. Predicted log reaction time (RT) as a function of log danger and usefulness, in milliseconds. ‘‘L’’ means low usefulness and ‘‘H’’ means high usefulness (defined as one standard deviation below and above the median, respectively). Neither danger nor usefulness was dichotomised for the statistical analysis.

and above the median, respectively). Readers are reminded that both danger and usefulness were continuous variables that were not dichotomised for the statistical analysis. As the figure shows, the slope of the relationship between danger and RTs depends significantly on usefulness. As usefulness increases from low to high, this slope changes from facilitative to inhibitory, which is the same pattern we have observed previously (Wurm & Vakoch, 2000; Wurm et al., 2004b). There was a significant sex/danger interaction, shown in Figure 2. Separate regression analyses for the sexes showed that increasing danger led to significant facilitation for men only, B / /.0198, SE B /0.0101, t(2931) / /1.964, p B/.05; for women: B /.0032, SE B /0.0092, t(3016) / 0.346, p /.73. There was a marginal ear /animate referent interaction (p/.077), with the animacy effect being (marginally) stronger for speech presented to the right ear. More interesting, though, is the significant three-way interaction of ear, sex, and animate referent (pB/.05). Figure 3 shows the RT advantage for words with animate referents, as a function of sex and ear of presentation. Separate analyses for women and for men illuminate the nature of this three-way interaction. For women, there was no hint of an ear /animacy

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Figure 2. Predicted log reaction time (RT) as a function of sex and log danger, in milliseconds. ‘‘M’’ means men and ‘‘W’’ means women.

60 Left Ear Right Ear

Mean Animacy Effect (msec)

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Figure 3. Mean animacy effect as a function of sex and ear of presentation, in milliseconds. The animacy effect was calculated as the mean RT for words with inanimate referents minus the mean RT for words with animate referents.

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Figure 4.

Predicted log reaction time (RT) as a function of sex, ear of presentation, and log word frequency, in milliseconds. Data for women are shown in the left panel; data for men are shown in the right panel. ‘‘L’’ means left ear; ‘‘R’’ means right ear.

interaction, F(1, 3013) B/1.0, p /.95. There was a significant and statistically equivalent RT advantage for words with animate referents, regardless of ear of presentation (38 ms for words presented to the left ear; 29 ms for words presented to the right ear; both ps B/.001). For men, the ear /animacy interaction was significant, F(1, 2928) /6.96, p B/.01. Men showed only a marginal animacy effect for stimuli presented to the left ear, 21 ms; F(1, 1456) /3.394, pB/.10. However, they showed a robust 49 ms animacy effect for words presented to the right ear, F(1, 1469) /23.244, pB/.001. Another three-way interaction was also significant: Sex/ear /word frequency (see Figure 4). For women (left panel), the ear /frequency interaction did not reach significance, F(1, 3013) /2.25, p /.13. The frequency effects are both significant (both ps B/.01) and are statistically


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TABLE 3 Summary of logistic regression analysis for variables predicting error likelihood x2

Variable Factors and interactions involving factors Ear Sex Stressed first syllable Animate referent Ear/sex Ear/log word frequency Sex/log word frequency Sex/log danger Ear/sex/log word frequency

1.62 7.41** 0.68 8.46** 0.71 6.49* 2.52 0.02 2.22

Regression coefficient

Standard error

Wald Z

0.0006 0.9017 2.2175 0.1689 /0.5585 /0.1170 0.0055 /0.1010 /0.3784 /0.1032 0.0261

0.0010 0.2723 0.4720 0.0685 0.0753 0.0211 0.0834 0.1358 0.1018 0.0479 0.0700

0.60 3.31*** 4.70*** 2.47* /7.42*** /5.55*** 0.07 /0.74 /3.74*** /2.16* 0.37

Continuous variables Trial number Log UP location Log item duration Log number of competitors Log word frequency Concretenessa Log morph. family size Log number of meanings Log danger Usefulness Log danger/usefulness

Notes : *p B/.05; **p B/.01; ***p B/.001. aConcreteness values were transformed as described in the analysis section. df /1 for each x2 test.

equivalent no matter which ear the speech was presented to. For men (right panel), the ear /frequency interaction was significant, F(1, 2929) /5.36, p B/.05. For words presented to the left ear, there was a robust frequency effect (B / /.0245, SE B /0.0080, t/ /3.0632, pB/.01) but there was no effect for speech presented to the right ear (p/.9).

Analysis of response errors We used the variables from our statistical model predicting log RTs above, but in a new logistic regression model with the dependent variable being the responses to the 75 critical words, categorised as either ‘‘correct’’ or ‘‘incorrect’’. This analysis allowed us to investigate whether danger and usefulness are related to accuracy; and if so, in a way that agrees with the RT analysis or in a way suggesting that there has been a speed vs. accuracy tradeoff. It also allowed elucidation of additional aspects of the RT analysis.

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Figure 5.

Predicted log odds ratio for incorrect lexical decision as a function of several variables. Significant main effects from a logistic regression analysis predicting error likelihood are shown (see Table 3).

Readers should note that even though the ratio of correct to incorrect responses is roughly 22 to 1, this does not invalidate a logistic regression model. It does call into question the interpretation of indices of model fit (e.g., Tabachnick & Fidell, 2001), because the model could simply predict the same value for every case and be correct over 95% of the time. We will not present or interpret these fit indices. An imbalanced response distribution can also be expected to have a negative effect on statistical power, so we must guard against over-interpreting null results. As will be seen, there was very good agreement between this analysis and the RT analysis, which underscores the validity of the statistical model. Table 3 shows the results of this analysis, and Figure 5 shows the significant main effects in the model. Better accuracy (i.e., lower odds of making an error) was associated with animate word referents, shorter item durations, earlier UPs, sparser neighbourhoods, higher word frequency, higher concreteness, and higher usefulness. All of these effects were also significant predictors of log RT, and in the same directions (e.g., higher word


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frequency predicts better accuracy and shorter latency). An apparent exception to this is the UP effect: A later UP predicted shorter RTs above, but here it is associated with worse accuracy. As noted previously, though, if RTs are measured from item onset instead of from the UP, then the later the UP is in a word, the longer the RTs are (see Footnote 3). Two main effects were significant here that were not in the RT analysis: Women made significantly fewer errors than men, and higher log danger ratings were associated with better accuracy. Ear interacted with word frequency (p B/.05). Separate post hoc analyses showed that the beneficial effect of frequency on accuracy, although substantial and significant no matter which ear the speech was presented to (both ps B/.001), was significantly stronger for speech presented to the right ear (B / /.644, compared to /.483 for the left ear).

GENERAL DISCUSSION The current study had two major purposes. One was to rule out alternative explanations for previous demonstrations of danger and usefulness effects in auditory lexical decision. This was accomplished through the inclusion of additional, previously uncontrolled, semantic variables, and a thorough analysis of participants’ accuracy data. Prior to the current study, it was not known whether danger or usefulness had any relation to listeners’ accuracy in lexical decision. The high level of agreement between the error analysis and the RT analysis lends additional support to the notion that danger and usefulness are genuine perceptual effects that need to be considered in theoretical models. It is worth emphasising that even though danger and usefulness did not interact in predicting error likelihood, they both had significant main effects and are thus both related to participants’ accuracy. Our results clearly show that danger and usefulness effects are present in lexical decision times and error rates even when morphological family size, polysemy, and concreteness are accounted for. Higher danger ratings are associated with better identification accuracy. Higher usefulness ratings are associated with better accuracy and faster response times. Importantly, the interaction we have previously observed was once again present in the response times (Figure 1): The inhibitory effect of increasing danger at high levels of usefulness is the effect we have interpreted as evidence of a response conflict (i.e., this object is both dangerous and useful, and so activates both approach and avoid response tendencies). The significance of the information coded by the danger and usefulness dimensions is important enough that the effects can be seen in word recognition.

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An additional benefit of the current study is the extension of the existing literature looking at other semantic variables. Most studies of concreteness have used visual stimulus presentation (but see Prior, Cumming, & Hendy, 1984; Spreen, Borkowski, & Gordon, 1966; Tyler et al., 2000), and most of the studies on family size have focused on words composed of multiple morphemes (but see Baayen et al., 2002; Schreuder & Baayen, 1997). Our study clearly showed concreteness effects on both RTs and accuracy with auditory presentation of stimuli. It also showed that there is a robust family size effect on RTs for auditory presentation of words which are nearly all composed of just a single morpheme. The second major purpose of the current study was to determine whether the sex of the participants or the brain hemisphere to which stimuli were presented would interact with psycholinguistic variables. Two of our sexspecific predictions were supported by the data, while one was not. The finding that men but not women were affected by words’ danger ratings is new in the literature, and lends some tentative support to the model of Taylor et al. (2000, 2002). However, in our view that model also predicted that women would be more sensitive than men to the usefulness dimension, and the data did not bear that out. To pursue these questions more directly, it would be desirable to examine whether the ratings themselves, and not just response times in relation to those ratings, differ by sex. The potential role of these sex-specific ratings (if any differences exist) on RTs could then be examined as well. In light of the fact that Wurm and Vakoch (2000) did not record rating-participant sex, these questions must be left for future research. The other prediction that was borne out by the data was that men would show more lateralised performance than women. Women showed strong frequency and animacy effects regardless of ear of presentation, but for men the effects were restricted to one ear. However, we predicted that in any ear interactions the effects would be stronger for speech presented to the right ear. This was the case for the animacy effect but the opposite was true for the frequency effect. The analysis of the accuracy data shed some light on this unexpected result, in that there was a clear ear by word frequency interaction, in the predicted direction (i.e., frequency had a stronger effect on accuracy for speech presented to the right ear), for both men and women. Therefore, the current study finds that men do show a word frequency effect regardless of ear of presentation, if one considers the error data along with the RTs. We believe that the lack of conclusive data on the issue of hemispheric frequency effects (see Coney, 2005) might be due to a failure of many researchers to fully explore their error data. The animacy effect itself warrants some discussion because of its relation to the theoretical framework of the current study and our related work. While the animacy effect does not receive a great deal of attention in word


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recognition studies, it is an important construct probably established relatively early in the lexicons of children. Gelman (1990) argues, for example, that the animate inanimate distinction is one that is learned by children easily and rapidly through the joint operation of fundamental causal principles and perceptual processes having to do with patterns of movement. In addition, there is some recent evidence from word association studies that animacy effects are more widespread than has been assumed. For example, Saffran, Coslett, and Keener (2003) found that animate and inanimate words and pictures elicit different kinds of responses in word association tasks. Their data suggest that information about the uses of objects gets retrieved along with the names of the objects themselves, or at least is very highly associated with the names of those objects. Similarly, Schwartz, Baldo, Graves, and Brugger (2003) showed that the animate inanimate distinction appears very clearly in the data patterns of participants performing what is believed to be a purely phonemic version of the verbal fluency task (e.g., ‘‘List all the words you can think of beginning with the letter T’’). These findings, along with the arguments of Gelman (1990), fit nicely with the interpretational framework we have developed for danger and usefulness effects: They are pervasive, fundamental perceptual effects grounded in behaviourally appropriate responses to stimuli. Current models of auditory word recognition are ill-equipped to explain the results of this study. Few models have made any attempt to incorporate semantic information as a fundamental part of the recognition process (see Marslen-Wilson, 1987; Moss, McCormick, & Tyler, 1997; Tyler, Moss, Galpin, & Voice, 2002; Zwitserlood, 1989), and none has included information such as the danger and usefulness of word referents. In addition, no formal model has included the sex of the listener or the hemispheres of the brain as important variables, beyond general statements about the left hemisphere being the locus of language-related processes for nearly all right-handed listeners. One possible framework for interpreting the observed semantic effects is a two-part semantic analysis (cf. Pulvermu¨ller, 2001). Both parts of this analysis proceed rapidly and automatically, but one uses danger and usefulness or dimensions that code similarly valuable information (Evaluation, Potency, and Activation are possibilities; see Vakoch & Wurm, 1997; Wurm & Vakoch 1996; Wurm et al., 2004a). Dimensional values from this part of the analysis would be integrated with the results of the other, more detailed part of the analysis, because in comprehension it is necessary to know more detailed information about the object in question. A butterfly, for example, is not defined simply by the conjunction of ‘‘not very dangerous’’ and ‘‘not very useful’’, but by these characteristics in combination with many others. However, under some circumstances a response can be initiated on the basis of a small number of these characteristics, before the

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more detailed semantic analysis is completed. This idea is consistent with the findings of researchers that word meanings can be computed at several different levels of granularity, depending on the requirements of the task and the linguistic context (Hobbs, 1985; Sturt, Sanford, Stewart, & Dawydiak, 2004; see also Ferreira, Bailey, & Ferraro, 2002, for a similar view of sentence processing). Forster and Hector (2002) proposed a cascaded model that continuously monitors activation in semantic features such as ‘‘animalness’’. Participants in their study had to quickly decide whether a printed stimulus was an animal name or not, and the authors found that that performance on pseudowords was hindered by the presence of a close orthographic neighbour only if that neighbour was an animal name. For example, participants had a difficult time rejecting the pseudoword turple as an animal name, presumably because it has the real word turtle as a neighbour. This is an attractive possibility in that semantic variables can clearly have effects prior to the unique identification of a word, and in principle any kind of semantic feature would be allowable into a model with this architecture. An interesting question for future research concerns the discreteness of the to-be-monitored information: Can it be continuous as appears to be the case given the current study, or must it be dichotomised into ‘‘dangerous’’ vs. ‘‘not dangerous’’, as in the usual conception of featural analyses? Another intriguing model architecture was proposed by Gaskell and Marslen-Wilson (1997). In this model the speech signal is mapped directly onto a distributed representation for a word. This representation carries all information associated with that word, including semantics. Because the connections in such a model would have to encode semantic information, the effects of a word’s semantics should be evident at every step in the recognition process. In its current form the model is underspecified as to the nature of the semantic information associated with a word, but the basic architecture makes the model an attractive possibility. Given the results of the current study, models in which semantics are activated or monitored as a routine part of the recognition process are in an especially good position to provide insight into the temporal dynamics of coactivated word candidates. Prior to a word becoming uniquely specified by the acoustic input, the semantics of all co-activated words should be activated to some degree. As Wurm et al. (2004a) noted, this leads to predictions that could be tested by the appropriate contrasting of semantic neighbourhoods. On the one hand, if homogeneous neighbourhoods of words that are high on usefulness (for example) can be found, then an enhanced usefulness effect might be observed (and it might emerge very early in processing, as well). On the other hand, it is probably possible to find single words whose danger or usefulness values are dramatically different from the averages of


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the acoustic neighbourhoods in which they reside. Such an investigation would allow a determination of whether the co-activated semantics is an average of the neighbourhood’s usefulness, which in most cases would be uninformative, or whether each word’s value is activated and maintained separately. This latter situation strikes us as more likely given the data we have in hand. This would be akin to the perceptual system maintaining multiple active hypotheses about word meanings for homonyms (e.g., bug, with insect- and spy-related meanings) and for words not yet fully specified by the input (as when the phoneme string [kæp] activates both captain and capital, e.g., Zwitserlood, 1989; see also Marslen-Wilson, 1987). As summarised in the introduction, women and men seem to show different patterns of laterality on a variety of different experimental tasks having to do with emotion, spatial ability, and verbal/linguistic ability. However, those studies have not addressed the relationship between lexical or semantic effects and sex differences in the asymmetry of language processing. The current study demonstrated that sex differences in lexical/ semantic processing interacted with ear of presentation, and suggests that these research domains should not be treated as distinct from one another. Future research should further explore the manner in which sensitivity to meaning influences the emergence of sex-related asymmetries in language processing. Manuscript received 23 February Revised manuscript received 24 August Manuscript accepted 24 August First published online 2 July

2006 2006 2006 2007

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APPENDIX Critical stimuli with regressor values Word

Duration

Danger

Usefulness

Concreteness

Number of meanings

Family size

Number of competitors

1.946 2.303 2.996 2.398 1.609 2.890 3.401 4.344 1.099 3.178 1.609 1.099 3.296 0.693 3.611 3.045 4.984 2.303 4.762 3.584 0.693 4.190 4.220 1.792 1.386

6.293 6.133 5.958 5.613 6.209 6.144 6.114 6.153 6.144 6.269 6.244 6.755 6.385 6.172 5.823 5.932 6.295 6.096 5.924 6.163 6.389 6.094 6.140 5.903 5.852

6.293 6.380 6.351 6.480 6.450 6.583 6.555 6.436 6.725 6.540 6.497 6.755 6.385 6.377 6.301 6.550 6.295 6.344 6.370 6.399 6.389 6.303 6.323 6.304 6.246

0.678 0.198 1.807 0.612 0.145 0.172 0.272 0.989 0.118 2.056 1.891 0.486 0.145 0.318 0.678 0.341 1.511 0.198 0.542 1.919 0.678 0.447 0.629 0.783 0.223

2.000 5.969 4.719 1.813 5.969 3.656 6.031 4.656 2.188 1.281 2.781 5.219 1.813 5.344 5.875 6.875 3.281 2.688 2.344 1.813 2.469 2.968 1.406 3.469 1.438

/6.708 /5.385 /7.348 /5.099 /4.000 /6.557 /5.196 /7.616 /7.483 /5.831 /6.708 /7.874 /9.165 /5.196 /5.916 /8.888 /11.832 /6.403 /10.770 /16.186 /7.681 /8.124 /9.950 /5.745 /15.297

0.693 1.099 1.099 1.609 1.099 1.609 1.946 1.609 1.792 1.792 2.197 1.792 2.639 1.609 1.792 0.693 2.398 2.079 2.708 1.099 2.303 0.693 2.079 1.792 1.946

5.398 1.609 1.099 1.099 0.000 1.946 0.000 2.079 0.000 1.099 1.386 0.000 2.398 0.693 1.386 0.693 1.946 1.386 1.099 2.303 1.792 0.693 2.773 1.609 1.099

4.127 0.693 1.386 1.609 0.693 1.099 1.386 0.693 0.693 0.693 1.609 2.398 2.398 2.398 1.386 2.079 1.386 1.386 0.693 2.079 2.639 3.219 2.197 2.197 4.691

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Uniqueness point


ant apple arrow balloon banana basket blanket bottle butterfly cancer cannon canteen card carrot chicken clothing club cork corner crime crow desk dust eagle echo

Frequency

Word

Uniqueness point

Duration

Danger

Usefulness

Concreteness

Number of meanings

Family size


2.565 3.296 2.079 5.176 3.584 2.773 4.997 2.773 1.946 1.386 2.197 2.996 1.946 4.344 2.944 2.565 2.708 1.609 2.890 0.693 1.946 2.773 4.466 2.708 4.489 2.303 1.946 2.773

6.229 6.205 5.749 6.460 6.368 6.361 6.248 6.436 6.184 6.240 5.568 6.014 6.260 6.089 6.211 5.935 5.930 6.075 6.280 6.052 6.174 6.098 5.756 6.332 5.849 6.163 5.775 5.775

6.229 6.852 6.494 6.460 6.368 6.545 6.522 6.436 6.564 6.240 6.681 6.344 6.649 6.438 6.351 6.319 6.637 6.288 6.504 6.443 6.422 6.450 6.902 6.332 6.681 6.554 6.613 6.642

0.524 1.609 1.253 1.950 0.916 0.645 0.662 0.941 1.379 1.417 1.955 0.405 1.597 1.852 0.466 0.447 1.802 0.296 1.749 1.322 1.371 1.226 0.486 1.000 0.118 2.027 1.781 0.272

5.500 6.031 3.188 7.156 5.469 2.250 7.969 3.906 4.563 4.344 1.563 3.969 4.781 5.750 4.406 4.750 2.719 1.219 3.031 3.156 4.781 5.000 2.625 2.656 2.000 1.406 1.375 6.031

/6.000 /14.933 /4.583 /7.348 /7.211 /6.557 /7.211 /7.550 /6.633 /11.136 /8.544 /16.155 /7.211 /6.083 /5.831 /7.483 /11.136 /10.583 /4.690 /5.745 /7.141 /6.403 /19.799 /7.000 /14.967 /11.045 /13.638 /4.472

1.792 1.386 1.099 2.890 1.946 2.565 1.386 2.303 2.398 3.045 0.693 1.946 0.693 1.609 1.099 1.946 1.099 1.099 1.609 0.693 2.398 1.946 1.386 2.773 1.099 2.079 1.386 1.099

2.079 0.000 0.693 3.892 3.296 1.792 1.386 2.079 0.693 2.303 0.000 1.792 0.000 2.398 2.398 2.708 0.000 0.000 1.609 0.000 2.398 1.792 1.792 3.178 0.000 1.386 0.000 0.000

2.996 1.609 2.565 3.434 2.303 1.792 2.303 1.792 1.099 1.386 1.099 1.386 2.708 3.829 1.792 1.099 0.693 2.398 1.099 3.258 3.466 1.609 1.099 3.045 1.099 1.099 1.099 2.833

WURM ET AL.

egg electricity elephant fire fish flag food fork hammer hook hurricane joke kerosene knife lamp leaf lightning lint lion moose nail needle philosophy pin poetry poison pollution potato

Frequency

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Appendix (Continued )

Appendix (Continued ) Word

Uniqueness point

Duration

Danger

Usefulness

Concreteness

Number of meanings

Family size


2.485 0.693 2.708 0.693 3.807 1.792 1.946 2.773 0.693 2.708 1.386 1.386 2.079 1.609 2.996 0.693 4.094 0.693 0.693 6.098 4.025 2.398

6.332 6.004 6.460 5.991 6.260 6.463 6.370 6.504 5.724 5.914 5.914 6.263 5.694 6.397 6.061 5.375 6.390 6.023 6.157 6.425 6.372 6.230

6.501 6.746 6.460 6.400 6.553 6.463 6.582 6.645 6.842 6.611 6.721 6.557 6.435 6.397 6.661 6.608 6.390 6.335 6.561 6.425 6.372 6.230

0.542 1.862 0.504 0.577 1.765 1.838 0.447 1.198 0.296 0.145 0.296 0.953 1.812 0.678 1.862 1.946 1.000 0.318 0.090 1.159 0.645 0.198

3.844 1.938 5.125 2.313 2.281 5.719 3.469 5.688 5.156 3.500 2.344 1.688 2.969 2.156 1.531 1.406 6.875 2.750 1.781 7.969 6.906 5.406

/3.742 /7.681 /7.000 /1.000 /5.292 /8.062 /5.916 /7.616 /6.245 /11.136 /7.550 /7.937 /6.164 /9.000 /6.325 /2.236 /6.708 /9.487 /13.153 /5.745 /6.557 /6.403

1.609 1.386 1.792 1.792 2.197 1.609 1.792 1.099 1.386 1.792 1.386 1.386 1.099 0.693 1.099 1.099 1.609 1.386 1.609 2.398 2.197 1.386

1.609 0.000 2.639 0.000 1.792 1.386 2.197 1.099 0.000 0.000 0.000 1.609 1.386 0.693 1.099 0.000 2.197 0.693 0.000 4.111 3.611 2.079

0.693 2.565 2.303 2.944 0.693 1.099 1.099 2.890 0.693 1.099 2.833 0.693 4.043 0.693 1.099 0.693 2.485 2.639 2.079 3.401 2.996 2.079

Note : Values for frequency, danger, uniqueness point, duration, meanings, family size and competitors have been log transformed. Concreteness values were transformed as described in the analysis section.


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Frequency

1495