Do part-whole relations produce facilitation in the picture-word interference task?

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Do part–whole relations produce facilitation in the picture–word interference task? a

Kevin Sailor & Patricia J. Brooks

b

a

Department of Psychology, Lehman College, City University of New York, Bronx, NY USA b

Department of Psychology, College of Staten Island and the Graduate Center of City University of New York, Staten Island, NY, USA Accepted author version posted online: 05 Dec 2013.Published online: 22 Jan 2014.

To cite this article: Kevin Sailor & Patricia J. Brooks (2014) Do part–whole relations produce facilitation in the picture–word interference task?, The Quarterly Journal of Experimental Psychology, 67:9, 1768-1785, DOI: 10.1080/17470218.2013.870589 To link to this article: http://dx.doi.org/10.1080/17470218.2013.870589

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THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2014 Vol. 67, No. 9, 1768–1785, http://dx.doi.org/10.1080/17470218.2013.870589

Do part–whole relations produce facilitation in the picture–word interference task? Kevin Sailor1 and Patricia J. Brooks2 1

Department of Psychology, Lehman College, City University of New York, Bronx, NY, USA Department of Psychology, College of Staten Island and the Graduate Center of City University of New York, Staten Island, NY, USA

Downloaded by [The UC Irvine Libraries] at 02:48 20 October 2014

2

Three experiments used the picture–word interference task to evaluate competing models of lexical access in spoken word production. Both the presence of a part–whole relation and association between the target and the interfering word were manipulated. Part terms associated with targets produced facilitation at early stimulus onset asynchronies (SOAs; –300 ms in Experiment 1, –300 and – 150 ms in Experiment 3), but not at SOA 0 ms. Otherwise, part terms tended to produce interference, with unassociated part terms producing a significant semantic interference effect (SIE) at SOA of 0 ms in Experiment 1, and a similar trend in Experiment 3. Experiment 2 replicated the materials and procedure of Costa, Alario, and Caramazza (2005, Experiment 2. On the categorical nature of the semantic interference effect in the picture–word interference paradigm. Psychonomic Bulletin & Review, 12(1), 125–131), yet failed to find any semantic facilitation at SOA 0 ms. We propose that these findings are consistent with lexical competition accounts of SIE but difficult to explain in terms of the plausibility of the interfering words as responses to the target. Keywords: Picture–word interference; Lexical access; Semantic interference; Associative priming.

Theories of lexical access have been shaped in part by the fact that context exerts a strong influence on the ease of word retrieval during speech production. For example, the presence of a printed or aurally presented word increases the time required to produce the name of a pictured object in the picture–word interference (PWI) task. The amount of interference is greater when the interfering word (i.e., distractor) is semantically related to the target picture than when it is unrelated to it (Caramazza & Costa, 2000, 2001; Costa et al., 2005; Cutting & Ferreira, 1999; Damian & Martin, 1999; Lupker, 1979; Schriefers, Meyer,

& Levelt, 1990; Underwood, 1976). This semantic interference effect (SIE) is most often observed when the distractor is a coordinate of the name of the pictured object (e.g., dog and wolf) and is presented simultaneously with the picture. The SIE has typically been interpreted as arising from competition between lexical–semantic representations activated by the target picture and the distractor (Levelt, Roelofs, & Meyer, 1999). A semantically related distractor is assumed to provide stronger competition to the target’s lexical–semantic representation (e.g., lemma) than an unrelated distractor because it is activated

Correspondence should be addressed to Kevin M. Sailor, Department of Psychology, Lehman College, CUNY, 250 Bedford Park Blvd. West, Bronx, NY 10468, USA. E-mail: [email protected] We thank Dennis Bublitz, Arianna Miskin, Catherine Roca, and Paloma Wasserstein for assisting with data collection and tabulation. The work was supported by a City University of New York (CUNY) Collaborative Research Award to Sailor and Brooks; National Institutes of Health (NIH) Score Grant [grant number S06 GM 008225].

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DO PART–WHOLE RELATIONS PRODUCE FACILITATION?

directly by the distractor and indirectly by the target picture. One challenge to this view is that semantically related distractors appear to produce facilitation rather than interference in some studies. Specifically, when the distractor is a strong associate of the target picture name (e.g., hammer and nail), the distractor generally speeds retrieval relative to an unrelated and unassociated distractor (Alario, Segui, & Ferrand, 2000; Bajo, 1988; Brooks, Seiger-Gardner, & Sailor, 2013; La Heij, Dirkx, & Kramer, 1990; Sailor, Brooks, Bruening, Seiger-Gardner, & Guterman, 2009). In an influential paper, Costa et al. (2005) questioned whether the SIE extends beyond coordinates. In their study, they constructed a set of materials in which the distractor was semantically related to the pictured object but not a coordinate (e.g., milk presented with a cow) and another set in which the distractor was a coordinate (e.g., goat with a cow). Although the coordinate distractors slowed naming relative to unrelated distractors, the noncoordinate, but related, distractors produced facilitation relative to unrelated distractors. They argued that this result was problematic for lexical competition accounts because activation should spread between objects and their constituent parts. If activation spreads from the target (e.g., dog) to the distractor (e.g., tail) then distractors that name parts of the target should compete more strongly with the target than an unrelated distractor. Instead, they proposed that the PWI task requires that a choice be made between lexicalizing the semantic representation activated by the target picture and the semantic representation activated by the distractor. This decision can be made relatively quickly when the distractor is at another level of categorization or names a part of an object because the response is not relevant to naming the target picture (e.g., naming a part when the task is to name a whole object). However, processing is prolonged when the distractor is a coordinate because the distractor has to be ruled out as a possible response to the target. Another critical difference between this response exclusion account and the lexical competition account is that it claims that semantically related distractors should generally speed selection of the target’s lexical node

rather than slow its selection through lexical competition. Thus, it makes the prediction that a part distractor should facilitate target naming because it will facilitate selection of the target’s lexical node without engendering response competition, whereas a coordinate distractor will slow naming of targets due to response competition. A problem that has characterized a majority of PWI studies that have examined the SIE is a failure to distinguish between association and other semantic relations (Alario et al., 2000). Association is typically defined as the degree to which a target word elicits a second word as a response (i.e., how easily the second word comes to mind). Although many associates have a high degree of semantic similarity and are coordinates (e.g., dog and cat), other associates may be very dissimilar and possess a purely syntagmatic relationship (e.g., needle and haystack). In the case of thematically related items, it is also the case that distractors may be related as part–whole (e.g., feet–bird), as instrument–agent (e.g., brush–artist, order–waiter, vacuum–maid), or as an item occurring in a location (e.g., fish–ocean, snow–mountain) without being associated (Estes, Golonka, & Jones, 2011). The failure to recognize the distinction between associative and semantic similarity or relatedness has led researchers to draw conclusions about the role of conceptual organization in lexical access that may be unwarranted. For example, association may reflect the strength of connections at the level of word forms rather than at a conceptual level of representation. Cutting and Ferreira (1999) proposed this kind of architecture in their account of the effect of coordinate and associate distractors on homophones. They found that coordinate and associate distractors that were related to the inappropriate meaning of a target picture facilitated naming latencies relative to an unrelated distractor (e.g., dance or formal paired with a picture of a toy ball). In contrast, only coordinate distractors that were related to the appropriate meaning of a target produced reliable interference (e.g., frisbee in conjunction with the picture of a toy ball). To explain these findings, they proposed that competitors, but not associates, have inhibitory connections at the lemma level,

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whereas associates, but not coordinates, have excitatory links that connect each other at the word-form level. Thus, this model predicts that coordinates produce interference because of competition among lemmas, whereas associates produce facilitation because of excitatory connections among word forms.1 An examination of PWI studies in which semantically related distractors have produced facilitation rather than interference suggests that the distractors have generally been associated with the target picture names. For example, in the Costa et al. (2005) study, many of the semantically related, noncoordinate distractors were strongly associated with their targets (e.g., pen–ink and car–bumper). An inspection of items available in the Nelson, McEvoy, and Schreiber (2004) word-association norms revealed that the average probability of a distractor in this condition eliciting the name of the target picture as a response was .20 in Experiment 1 and .13 in Experiment 2. In Experiment 1, only six of the 20 part–whole pairs that were normed were unassociated. In Experiment 2, nine part–whole pairs were not in the Nelson et al. (2004) norms; of the remaining 23 pairs, only seven were unassociated. Similarly, Muehlhaus et al. (2013) reported facilitation for target–distractor pairs that had a part– whole relation relative to controls; in this study all of the pairs were selected on the basis that they had an associative relationship as measured by free association norms. If the response exclusion account is correct then eliminating the association between the distractors and their targets should still result in pairs that produce facilitation rather than interference. On the other hand, if a strong semantic relation produces competition among lemmas then the removal of an associative relation that speeds processing via a different mechanism should result in semantic interference. To test these predictions, we created two sets of stimulus materials. One set comprised part–whole

pairs in which the distractor named a part of the object in the target picture and was associated with it (e.g., icing for cake). In the other set of part–whole pairs, the distractor named a part of the target object but was not associated with it (e.g., sugar for cake). If the response exclusion account is correct then both sets of materials should produce facilitation because the distractors should not be good candidates for lexicalization. On the other hand, if the strong semantic relationship between the object and its part leads to lexical competition at the lemma level, interference should be observed in the set of unassociated part–whole pairs. For targets paired with associated distractors, the contribution of association should either attenuate this interference or produce facilitation.

EXPERIMENT 1 Method Participants Fifty-two undergraduates (32 women and 20 men, mean age 19.5 years, range 18–46 years) were recruited from Introductory Psychology classes at a large public university and received research participation units to fulfil a course requirement. All of the participants were native speakers of English. Materials The PWI task utilized 30 black-and-white line drawings of common objects as pictures to be named (Cycowicz, Friedman, Rothstein, & Snodgrass, 1997). Each target picture was paired with five different distractors: (a) an associate that named a part of the pictured concept (e.g., TAIL superimposed over a picture of a dog); (b) an unrelated control for the associate condition—one of the 30 associate part terms that was re-paired with an unrelated picture (e.g., TAIL superimposed

1

The inclusion of excitatory connections between the word forms of associates was primarily developed to account for the effect of a distractor related to the nondepicted meaning of a target homophone, but Cutting and Ferreira (1999) did not limit these connections to the associates of homophones. For example, their Figure 4 (p. 334) depicts an excitatory connection between game and Frisbee despite the fact that neither word is a homophone. Thus, it seems reasonable to offer this account as a possible explanation of associated word forms more generally.

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over a picture of a guitar); (c) a part that was NOT an associate of the pictured concept (e.g., NOSE superimposed over a picture of a dog); (d) an unrelated control for the nonassociate condition—one of the 30 nonassociate part terms that was re-paired with an unrelated picture (e.g., NOSE superimposed over a picture of a guitar); and (e) the word GOOD to serve as a baseline (i.e., this distractor was paired with each of the targets). The distractors were selected based on established word-association norms (Nelson et al., 2004): In the associate condition, the average production frequency for the targets as responses to the distractors was .35 and .13 for distractors as responses to the name of the target. In the nonassociate condition, none of the targets was produced as a response to any of the distractors or vice versa. A list of the stimulus materials is presented in Appendix A. Four additional pictures (lobster, corn, tree, and deer) were used as practice items, in combination with eight additional distractors to yield four practice items in each of the distractor conditions. The distractors appeared in upper case Arial font, 20 points bold, in the centre of the screen, with 300 ms duration. To maximize visibility and contrast with the picture, distractors were printed in maroon. Design In the PWI task, participants were instructed to name the pictures as quickly and accurately as possible while ignoring the visually presented distractors. The onset of the distractors was manipulated in time relative to the presentation of the pictures —that is, by varying stimulus onset asynchronies (SOAs). The experimental design included two within-subject factors: distractor type (associate part, unrelated control for associate part, nonassociate part, unrelated control for nonassociate part, and baseline) and SOA (–300, –150, and 0 ms). The onset of the distractors occurred either before the presentation of the picture (SOAs of –300 and –150 ms), or simultaneously with the presentation of the picture (SOA of 0 ms). The experiment was blocked by SOA, with the order of presentation of the three SOA conditions counterbalanced across subjects. The 150 experimental

trials (30 pictures × 5 distractor types) at each SOA were further divided into five lists, such that pictures and distractors were never repeated within a list, with six trials for each of the five distractor conditions per list. The order of presentation of the trials within each list was randomized, as was the order of lists at each SOA. Procedure Adults were tested individually in a single one-hour session, conducted in a psychology laboratory. A PC computer running E-Prime 1.1 software was used to present the task (Schneider, Eschman, & Zuccolotto, 2002). Direct measurement of reaction times (RTs) was accomplished using a custommade tone generator coupled with a light detector. The light detector responded to the appearance of the picture on the screen (i.e., each picture was preceded by a black screen) and produced a tone in response to the onset of the picture. The tone generator fed directly into the digital CD recorder, but was inaudible to the participant. On a second channel, the participant’s naming response was recorded. RTs were measured directly by calibrating the time between the onset of the picture (as indicated by the tone on Channel 1) and the onset of the participant’s response (as indicated by the speech waveform on Channel 2). This procedure drastically minimized the loss of trials due to voice key insensitivity and ensured accurate naming latencies. The experimental task had three training parts and one test part. First, participants practised naming the experimental pictures with no time limit. In the event that a participant used a word other than the target picture name, the research assistant corrected the participant and made sure that the participant was familiar with the target name. The research assistant instructed the participants to avoid using articles (e.g., “a book”, or “the car”) when naming the pictures. Second, the participants were shown the experimental pictures once more, but this time they were instructed to name the pictures as fast as they could. Third, the participants were trained on the PWI task using four practice pictures paired with eight different distractors. Pictures were presented on the screen,


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one at a time, and participants were instructed to name each picture as quickly as possible while ignoring the distractor. Following this practice, the experimental trials were administered using the same PWI procedure. The participant’s response triggered the picture to disappear from the screen, with a pause of two seconds separating one trial from another. During the pause, participants were presented with a black screen with a fixation cross in the centre. Each picture was presented on the computer screen for maximum of four seconds. That is, if no answer was produced or the voice key failed to activate, a new trial was initiated after four seconds.

Results Errors occurred when the participant stuttered in producing their response or produced an incorrect name for the target picture. Error rates were tabulated, taking into consideration any trials lost due to equipment failure. Participants were highly accurate in performing the task, averaging only 1.2% errors. An analysis of variance (ANOVA) conducted on the proportions of errors as a function of SOA (–300, –150, 0 ms) and distractor type (associate part, unrelated control for associate part, nonassociate part, unrelated control for nonassociate part, and baseline) revealed a significant effect of distractor type, F1(4, 204) = 3.0, MSE = 0.00025, p = .018. However, the largest difference in error rate across the five conditions was 0.5%, with the lowest error rate observed for the baseline condition (M = 0.8%) and the highest error rates observed for associated part (M = 1.3%) and nonassociated part (M = 1.1%) conditions.

Table 1 presents the mean RTs as a function of distractor type and SOA. RTs exceeding a participant’s mean by three standard deviations (outliers) were removed. Two sets of analyses were conducted, one with subjects as the random factor (F1) and the other with items as the random factor (F2). Each set of analyses was conducted as repeatedmeasures designs in which SOA and distractor type were within-subjects (within-items) factors. These analyses revealed significant main effects of SOA [F1(2, 102) = 186.5, MSE = 4435.1, p , .001; F2(2, 58) = 1247.0, MSE = 766.1, p , .001] and distractor type [F1(4, 204) = 54.6, MSE = 504.7, p , .001; F2(4, 116) = 22.0, MSE = 808.4, p , .001] as well as a significant interaction of SOA and distractor type [F1(8, 408) = 16.9, MSE = 410.9, p , .001; F2(8, 232) = 9.7, MSE = 460.0, p , .001]. Planned comparisons were conducted to test for associative priming and semantic interference effects at each SOA. First, for associative priming, we examined the difference between the associate part and the unrelated control for associate part distractor types. The obtained difference scores are shown in Figure 1 (solid bars), with asterisks indicating which of the planned comparisons were significant. Pictures paired with an associate part were named faster than their controls at SOA –300 ms [F1(1, 408) = 14.9, MSE = 410.9, p , .001; F2(1, 232) = 6.8, MSE = 460.0, p = .01], but not at SOA –150 ms (F1 and F2 , 1) or SOA 0 ms (F1 and F2 ≤ 1.1, p ≥ .30). Second, we examined the difference between the nonassociate part and the unrelated controls for nonassociate part distractor types to test for semantic interference. Pictures paired with a part that was not an associate were named

Table 1. Mean RTs for Experiment 1 as a function of SOA and distractor type Distractor type SOA (ms) –300 –150 0

Associate part

Associate control

Nonassociate part

Nonassociate control

Baseline (good)

584 (82) 617 (83) 713 (97)

599 (78) 620 (80) 709 (108)

596 (80) 621 (80) 715 (94)

589 (69) 615 (88) 697 (96)

582 (70) 599 (79) 653 (97)

Note: N = 52. RT = reaction time, in ms; SOA = stimulus onset asynchrony. Standard deviations in parentheses.

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Figure 1. Associative priming and nonassociate interference in Experiment 1 with stimulus onset asynchronies (SOAs) of –300, –150, and 0 ms (N = 52).

reliably slower than their controls at an SOA 0 ms [F1(1, 408) = 19.6, MSE = 410.9, p , .001; F2(1, 232) = 13.8, MSE = 460.0, p , .001], but not at SOA –300 ms [F1(1, 408) = 3.4, MSE = 410.9, p = .07; F2(1, 232) = 1.9, MSE = 460.0, p = .17] or SOA –150 ms [F1(1, 408) = 2.6, MSE = 410.9, p = .11; F2(1, 232) = 1.4, MSE = 460.0, p = .24].

First, in our experiment, the distractor had a duration of 300 ms, whereas in the Costa et al. experiments the distractor remained on the screen until the participant responded. Second, we repeated the full design at each of three SOAs, whereas Costa et al. presented the full design just once at SOA 0 ms. To determine whether these factors could have produced the observed differences in the results, we presented participants with two blocks of trials using the same targets and distractors as those employed by Costa et al., Experiment 2. In the first block, the distractor appeared concurrently with the target picture (i.e., SOA = 0 ms) and remained on the screen until the trial was terminated. In the second block, the onset of the distractor was again simultaneous with the onset of the target but it was terminated after 300 ms. Thus, the first block constituted a literal replication of Experiment 2 of Costa et al., whereas the second block limited the duration of the distractor in accordance with the procedure of our Experiment 1 and additionally doubled the number of times each target picture was presented.

Method EXPERIMENT 2 The preceding analysis suggests that the facilitation observed in Costa et al. (2005) was probably the product of the association between many of the part term distractors and their targets. Although our results are largely consistent with the observed time course of facilitation and interference in studies that have employed coordinates and associates (Alario et al., 2000; Brooks et al., 2013; La Heij et al., 1990; Sailor et al., 2009), the fact that Costa et al. observed facilitation for their materials at an SOA of 0 ms suggests that we should have observed facilitation with the associated part term distractors at this SOA, given the similarities in our materials and procedures. For this reason, we conducted a replication of Costa et al. (2005), Experiment 2. In addition to the difference in materials, our procedure in Experiment 1 differed from the Costa et al. (2005) procedure in two respects.

Participants Twenty-six undergraduates (11 women and 15 men, mean age 19.9 years, range 18–26 years) were recruited from the same source as that in Experiment 1. All were native speakers of English. Materials and design The PWI task utilized the 32 part–whole pairs that were used in Experiment 2 of Costa et al. (2005) and followed the same design. Twenty-four black-and-white line drawings of common objects served as pictures to be named; most of the pictures were taken from Cycowicz et al. (1997). Each target picture was paired with four different distractors: (a) a word that named a salient part of the pictured concept (e.g., WINGS superimposed over a picture of a bird); (b) an unrelated control for the part distractor condition—that is, a part word that was re-paired with an unrelated picture (e.g., WINGS superimposed over a picture of a boat); and (c–d) two other unrelated filler words (e.g.,


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POETRY or FOSSIL superimposed over a picture of a bird). The average log word frequency (M = 8.09) and length (M = 5.76 letters) of the unrelated filler distractors, as estimated by the English Language Lexicon Project (Balota et al., 2007), were closely matched to the log word frequency and length of the related distractors (M = 8.11 and M = 5.75, respectively). These filler distractors were not identical to those used in Costa et al. (2005), as the identity of these items was not provided in their report. A list of the stimulus materials is presented in Appendix B. Four additional pictures (lobster, corn, tree, and deer) were used as practice items, in combination with eight additional distractors to yield four practice items in each of the distractor conditions. The 128 experimental trials (32 pictures × 4 distractors) were further divided into four lists, such that pictures and distractors were never repeated within a list. The order of presentation of the trials within each list was randomized, as was the order of lists in each block. Procedure The procedure was identical to the SOA 0 ms condition of Experiment 1 except that in the first block the presentation of the distractor remained superimposed on the target picture until the participant responded, whereas in the second block the distractor was removed after 300 ms.

Results Errors occurred when the participant stuttered in producing their response or produced an incorrect name for the target picture. Error rates were tabulated, taking into consideration any trials lost due to

equipment failure. Participants were highly accurate in performing the task, averaging only 2.5% errors. An ANOVA conducted on the proportions of errors as a function of distractor type (part, unrelated control) and distractor duration (same as picture, 300 ms) revealed an effect of distractor duration that just failed to meet conventional levels of significance, F1(1, 25) = 3.7, MSE = 0.001, p = .06, with marginally higher error rates when the distractor remained on the screen (M = 3.2%) than when it was visible for only 300 ms (M = 1.7%). There was no significant effect of distractor type, F1 , 1, or interaction between distractor type and distractor duration, F1 , 1. Table 2 presents the mean RTs as a function of distractor type and distractor duration. RTs exceeding a participant’s mean by three standard deviations (outliers) were removed. Two sets of analyses were conducted, one with subjects as the random factor (F1) and the other with items as the random factor (F2). Following Costa et al. (2005, Experiment 2), each set of analyses was conducted as repeatedmeasures designs in which distractor type and distractor duration were within-subjects factors (i.e., the filler distractors were excluded). These analyses revealed a significant main effect of distractor duration [F1(1, 25) = 24.2, MSE = 6189.2, p , .001; F2(1, 31) = 241.4, MSE = 791.9, p , .001], but not distractor type (F1 and F2 , 1). The interaction of distractor type and distractor duration was not reliable (F1 and F2 , 1). It is important to note that the short distractor duration always occurred on the second block of trials; hence, the distractor duration effect could reflect an impact of practice or it might reflect a benefit of removing the distractor. The fact that

Table 2. Mean RTs for Experiment 2 as a function of the duration of the distractor and distractor ype Distractor type Duration of distractor (ms) Same as picture 300

Part

Unrelated control

Unrelated filler 1

Unrelated filler 2

778 (117) 701 (77)

777 (116) 703 (91)

759 (96) 702 (83)

763 (104) 699 (88)

Note: N = 26. RT = reaction time, in ms. Standard deviations in parentheses.

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distractor duration did not interact with the distractor type means that the failure to observe facilitation in this experiment, or in Experiment 1, cannot be attributed to a difference in how long the distractor was presented.


EXPERIMENT 3 In Experiment 1, associated and related distractors produced facilitation at SOA –300 ms, and unassociated but related distractors produced interference at SOA 0 ms. In Experiment 2, we failed to detect an effect of part terms that varied in terms of their degree of association with their targets. One of the difficulties in evaluating the contributions of association and semantic relatedness is that they are generally correlated (Hutchison, 2003). As we noted in the introduction, it is quite likely that most previous studies of picture–word interference have inadvertently manipulated the degree of association when manipulating the presence/absence of a taxonomic or part–whole relation. By the same token, it is possible that our manipulation of association had an impact on the strength of the part–whole relation for related items in the associated versus the unassociated conditions of Experiment 1. If association produces facilitation whereas semantic relatedness produces slowing, the impact of each factor will be hard to establish if they are correlated across items. Experiment 3 was designed to control for the strength of the semantic relatedness between items while manipulating the degree of association of the related items. We elected to measure the relatedness of part terms using values generated by latent semantic analysis (LSA; Landauer, Foltz, & Laham, 1998). LSA is based on information gleaned from large corpora of text about the degree to which two words tend to co-occur in similar texts. Although LSA uses the co-occurrence of words in text to extract the relatedness of words, it does not directly measure the co-occurrence of words in the language. Initially, a very large matrix is formed in which the occurrence of words in a given text is recorded. Singular value decomposition is used to reduce the dimensionality of this original

matrix of co-occurrence data. The relatedness of two words is measured in terms of the cosine of the angle between the two vectors that represent the terms. Values close to one indicate words with very similar meanings, and values close to zero indicate that two terms are not related. In Experiment 3, we chose LSA to equate the degree of relatedness across associated and unassociated distractor–target pairs for several reasons. First, it is available for a large number of words, and it captures aspects of relations among words that are not captured by association (Maki & Buchanan, 2008). Second, it is not based on similarity of features, which might fail to capture the relation between a part and a whole. Third, an inspection of the materials used in the first two experiments indicated that part–whole pairs differed from unrelated controls on this measure. In Experiment 1, the average LSA of related pairs (M = .28) was greater than that for unrelated pairs (M = .07) even after controlling for the degree of forward and backward association across items, F(1, 86) = 13.8, p , .001. In Experiment 2, the average value of related pairs (M = .42) was greater than that of unrelated pairs (M = .05), t(31) = 9.17, p , .001. Similar to Experiment 1, association was manipulated by selecting an associated and an unassociated part term for each target picture. These two sets of terms were matched for their average LSA cosine value to the target. This matching makes it possible to estimate the effects of association independently of changes in the degree to which the distractors are related to the target.

Method Participants Twenty-eight (20 women and 8 men, mean age 21 years, range 18–34 years) were recruited from the same source as that in Experiments 1 and 2. All of the participants were native speakers of English. Materials and design The PWI task utilized 24 black-and-white line drawings of common objects as pictures to be named, most of which were taken from Cycowicz


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et al. (1997). Each target picture was paired with five different distractors: (a) an associate that named a part of the pictured concept (e.g., SIREN superimposed over a picture of an ambulance); (b) an unrelated control for the associate condition—one of the 24 associate part terms that was re-paired with an unrelated picture (e.g., THORN superimposed over a picture of an ambulance); (c) a part that was not an associate of the pictured concept (e.g., DASHBOARD superimposed over a picture of an ambulance); (d) an unrelated control for the nonassociate condition—one of the 24 nonassociate part terms that was repaired with an unrelated picture (e.g., SCENT superimposed over a picture of an ambulance); and (e) the word GOOD to serve as a baseline (i.e., this distractor was paired with each of the targets). The distractors were selected based on established word-association norms (Nelson et al., 2004): In the associate condition, the average production frequency for the targets as responses to the distractors was .32 and .09 for distractors as responses to the target name. Only two of the targets were produced as a response to any of the distractors in the nonassociate condition, and the average production frequency was less than .001. LSA values were retrieved from the LSA web interface (http://lsa.colorado.edu/). The topic space was set to “general reading up to first year college (300 factors)” using the pairwise comparison interface and term-to-term comparisons. The average LSA value in the associated parts condition was .37 for related items and .08 for its unrelated controls. The average LSA value in the unassociated parts condition was .36 and .08 for its unrelated controls. A list of the stimulus materials is

presented in Appendix C. Four additional pictures (lobster, corn, train, and deer) were used as practice items. The design was identical to that of Experiment 1 except that each target picture was paired once with a distractor from each of the experimental conditions and twice with the word GOOD at each SOA. This change reduced the relatedness proportion to .33. The 144 experimental trials (24 pictures × 6 repetitions) were further divided into six lists such that pictures and distractors were never repeated within a list and were presented at each of the three SOAs (–300, –150, and 0 ms). Procedure The procedure was identical to that in Experiment 1.

Results Errors occurred when the participant stuttered in producing their response or produced an incorrect name for the target picture. Error rates were tabulated, taking into consideration any trials lost due to equipment failure. Participants were highly accurate in performing the task, averaging only 0.9% errors. An ANOVA conducted on the proportions of errors as a function SOA (–300, –150, 0 ms) and distractor type (associate part, unrelated control for associate part, nonassociate part, unrelated control for nonassociate part, and baseline) revealed a significant effect of distractor type, F1(4, 108) = 4.1, MSE = 0.001, p = .004, but the largest difference in error rate across the five conditions was 1.1%. The proportion of errors was identical for the associated parts and

Table 3. Mean RTs for Experiment 3 as a function of SOA and distractor type Distractor type SOA (ms) –300 –150 0

Associate part

Associate control

Nonassociate part

Nonassociate control

Baseline (good)

523 (68) 552 (62) 622 (77)

557 (64) 570 (59) 621 (77)

536 (65) 556 (66) 621 (77)

541 (60) 555 (61) 615 (85)

512 (51) 528 (61) 571 (74)

Note: N = 28. RT = reaction time, in ms; SOA = stimulus onset asynchrony. Standard deviations in parentheses.

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their controls (M = 1.1%) but was slightly higher for the unassociated parts (M = 1.5%) than for their controls (M = 0.4%), F1(1, 27) = 4.8, MSE = 0.002, p = .038. Table 3 presents the mean RTs as a function of SOA and distractor type. RTs exceeding a participant’s mean by three standard deviations (outliers) were removed. Two sets of analyses were conducted, one with subjects as the random factor (F1) and the other with items as the random factor (F2). Each set of analyses was conducted as repeated measures designs in which SOA and distractor type were within-subjects (within-items) factors. These analyses revealed significant main effects of SOA [F1(2, 54) = 58.8, MSE = 3761.9, p , .001; F2(2, 46) = 397.4, MSE = 487.4, p , .001], and distractor type [F1(4, 108) = 54.8, MSE = 449.7, p , .001; F2(4, 92) = 30.8, MSE = 785.4, p , .001] as well as a significant interaction of SOA and distractor type [F1(8, 216) = 7.0, MSE = 278.4, p , .001; F2(8, 184) = 5.1, MSE = 373.3, p , .001]. Planned comparisons were conducted to test for associative priming and semantic interference effects at each SOA. First, for associative priming, we examined the difference between the associate part and the unrelated control for associate part distractor types. The obtained difference scores are shown in Figure 2 (solid bars), with

Figure 2. Associative priming and nonassociate interference in Experiment 3 with stimulus onset asynchronies (SOAs) of –300, –150, and 0 ms (N = 28).

asterisks indicating which of the planned comparisons were significant. Pictures paired with an associate part were named faster than their controls at SOA –300 ms [F1(1, 216) = 57.8, MSE = 278.4, p , .001; F2(1, 184) = 34.5, MSE = 373.3, p , .001] and SOA –150 ms [F1(1, 216) = 17.1, MSE = 278.4, p , .001; F2(1, 184) = 10.9, MSE = 373.3, p = .001], but not at SOA 0 ms [F1 and F2 , 1]. Second, we examined the difference between the nonassociate part and the unrelated controls for nonassociate part distractor types to test for semantic interference. Pictures paired with a part that was not an associate were named slower than their controls at an SOA of 0 ms; this difference, however, was reliable only in the analysis with items as the random factor [F1(1, 216) = 1.7, MSE = 278.4, p = .197; F2(1, 184) = 4.0, MSE = 373.3, p = .048]. As in Experiment 1, there was no difference between the nonassociate part and the unrelated controls for nonassociate part distractor types at SOA –300 ms [F1(1, 216) = 1.6, MSE = 278.4, p = .21; F2(1, 184) = 2.9, MSE = 373.3, p = .088] or SOA –150 ms (F1 and F2 , 1).

GENERAL DISCUSSION Previous studies have found that semantically related distractors slow picture naming relative to unrelated distractors in some cases (Caramazza & Costa, 2000, 2001; Cutting & Ferreira, 1999; Damian & Martin, 1999; Lupker, 1979; Schriefers et al., 1990; Underwood, 1976), but speed picture naming in other cases (Alario et al., 2000; Bajo, 1988; Costa et al., 2005; La Heij et al., 1990). These conflicting results have led to the suggestion that interference effects may be limited to coordinate distractors because they are more difficult to reject as plausible responses to the targets than unrelated words (Costa et al., 2005; Mahon, Costa, Peterson, Vargas, & Caramazza, 2007) and that facilitation should be observed with semantically related items that are not coordinates. In the current study, part term distractors produced facilitation only when the target was associated with the distractor and at earlier


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SOAs (–300 ms in Experiment 1 and –300 and –150 ms in Experiment 3). If the distractor was unassociated with the target, then part terms did not differ from control items at SOAs of –300 and –150 ms and produced interference at SOA 0 ms (reliable in the F1 and F2 analyses in Experiment 1, but only reliable in the F2 analysis in Experiment 3). The fact that part terms that were not associates slowed picture naming is difficult to reconcile with the response exclusion account that was originally offered by Costa et al. (2005) and more recently elaborated by Mahon et al. (2007). According to the elaborated hypothesis, the SIE is a postlexical effect that occurs because both the target and the distractor can activate production-ready representations. With the exception of foot and hand in Experiment 1, all of the targets in both experiments were whole objects. All of the distractors were constituents or attributes of these objects, and none of the distractors was the name of a target picture. Thus, the task demands were quite consistent across individual stimuli and should have maximized the opportunity for participants to use consistent features of the distractors to aid in excluding them as responses. For these reasons, the interference observed for the nonassociate part–whole pairs is difficult to explain in the terms of the response exclusion hypothesis. One possible caveat to this conclusion that must be considered is whether our experimental materials made it more difficult to exclude the distractor as a response to the target than was the case with the materials used by Costa et al. (2005) because more of the distractors in our experiments were visible constituents of the target picture. If the distractors were harder to exclude in our experiments then a failure to obtain facilitation would be consistent with the response exclusion account. The prediction would be that visible parts should be harder to exclude, and therefore they would produce more interference. Thus, the reason that Costa et al. obtained facilitation was that their distractors did not name visible parts of the target objects, and the reason that we failed to obtain interference was that many of our parts were visible.

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To address this issue, we conducted a post hoc analysis of the materials from Experiments 1 and 2 by including the visibility of the distractor as a factor. For each experiment, the item means were analysed separately for associated part–whole pairs and unassociated part–whole pairs, as the distractors differed within each of these sets. A repeated measures analysis was conducted in which relatedness was nested within target (i.e., part versus unrelated distractor for a given picture), and the visibility of the part was entered as a covariate. In all cases, the F values for the interaction between visibility of the part and relatedness and the three-way interaction between visibility, relatedness, and SOA were less than 1. These results suggest that the visibility of the part did not qualify the basic effect of relatedness in each set of associated items and unassociated items, nor did it qualify the interaction between relatedness and SOA. Furthermore, it is worth noting that the number of visible parts was greater in the associated conditions of Experiment 1 (n = 20) and Experiment 3 (n = 14) than it was in the unassociated conditions of Experiment 1 (n = 12) and Experiment 3 (n = 12). To the extent that a visible part should be harder to exclude as a response, as predicted by the response exclusion hypothesis, one would expect to find more interference in the associated conditions than in the unassociated conditions, which is opposite to what we found. Although the current results are not consistent with the response exclusion hypothesis, they are generally consistent with the results of several other studies in which association and semantic relatedness have been manipulated (Abdel Rahman & Melinger, 2007; Alario et al., 2000; Brooks et al., 2013; La Heij et al., 1990; Sailor et al., 2009). In four of these studies (Abdel Rahman & Melinger, 2007; Alario et al., 2000; Brooks et al., 2013; Sailor et al., 2009), coordinate pairs that were not associates produced interference at some SOAs or did not reliably differ from their controls (i.e., they never produced facilitation). In contrast, associates that were not coordinates produced facilitation at some SOAs or did not differ from their controls (i.e., they never produced




interference). In Experiment 2 of La Heij et al. (1990), coordinates that were strong associates were compared with coordinates that were weak associates. When the distractor preceded the target by 400 ms, strong associates produced facilitation (69 ms) whereas weak associates failed to produce interference (3 ms). In contrast, when the distractor appeared simultaneously with the target, strong associates were only 3 ms faster than their controls, whereas weak associates produced interference (17 ms). This pattern of stronger facilitation for associated materials at earlier SOAs (–400 to –200 ms) and stronger interference for coordinates at shorter SOAs (–150 to 0 ms) characterizes the results of the four studies in which SOA has been manipulated (Alario et al., 2000; Brooks et al., 2013; La Heij et al., 1990; Sailor et al. 2009). Taken together, these results are similar to the current results. The presence of a semantic relation in the absence of association produced interference for part–whole pairs at SOA 0 ms in Experiment 1 (reliable only by items in Experiment 3). The presence of a semantic relation coupled with association produced facilitation at the earlier SOAs (–300 ms in Experiment 1 and –300 and –150 ms in Experiment 3), which disappeared at SOA 0 ms. The different time course for facilitation and interference is important because it provides additional constraints on accounts of lexical access. The response exclusion account claims that two competing influences determine facilitation and interference: Whereas conceptual priming produces facilitation, the need to exclude responses as candidate names for targets produces interference. Coordinate distractors are semantically related and therefore produce priming of the target; this facilitation, however, is balanced by response competition because coordinate distractors compete with the target for articulation. To accommodate a failure to obtain interference at early SOAs (e.g., –300 ms) coupled with interference at later SOAs (e.g., 0 ms) one must assume that conceptual priming is much stronger at the early SOAs than at later SOAs. This stronger conceptual priming at the early SOAs is required to balance the effects of later response competition;

otherwise the net effect on RT would be slowing at SOA –300 ms as well as at SOA 0 ms. To explain the observed pattern of results in this study, one would have to assume that the associated part terms facilitated conceptual processing of targets at SOA –300 ms, but the unassociated part terms did not. However, this account is difficult to reconcile with the failure to observe interference for unassociated coordinates at early SOAs. The average LSA cosine value for coordinates in Sailor et al. (2009) was .29. These items produced interference at later SOAs (–150 and 0 ms), but not at early SOAs (–300 and –450 ms). As we have outlined, these results suggest that conceptual facilitation occurred at the early SOAs. In Experiment 3 of the current study, the average LSA cosine between unassociated part terms and their targets (M = .36) was slightly higher than that for the coordinates in Sailor et al. To the extent that LSA indexes conceptual relatedness, if coordinates produced enough facilitation to offset response competition at the early SOAs in Sailor et al., then the LSA values of the unassociated parts indicate that these items should have produced a net facilitory effect, given that they should not produce response competition. “Pure” semantic priming in the absence of association is fairly well established in the lexical decision and word-naming literatures for functionally related words (e.g., broom–floor), and these literatures do not suggest that coordinate relations produce stronger priming than other semantic relations (Hutchison, 2003). Thus, early facilitation and later interference appear to be hard to explain in terms of the degree to which related distractors prime conceptual representations at the early SOAs, but not at later SOAs. Our results also bear on a recent proposal by Abdel Rahman and Melinger (2009) designed to explain patterns of facilitation and interference for related materials. They proposed that semantic interference reflects strong competition at the lexical level, and facilitation reflects priming at the conceptual level coupled with weaker competition at the lexical level. Specifically, their swinging lexical network proposal claims that coordinate distractors activate a relatively large cohort at the lexical level due to the overlap they share with


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related lexical items. The competition among these lexical items slows processing more than the facilitation produced at the conceptual level by the semantic relatedness of the items. In contrast, they argue that “activation from target and competitor diverges onto mutually unrelated representations” (Abdel Rahman & Melinger, 2009, p. 719) because strongly associated distractors do not share a common category node and share few features. This divergence of activation means that a relatively small cohort is activated with fewer competitors to the target. The net effect of this reduced competition is that the slowing that it produces is insufficient to offset the facilitation produced at the conceptual level. This smaller cohort does not produce as much competition at the lexical level, and the slowing is insufficient to offset facilitation at the conceptual level. Thus, coordinates produce a net slowing and associates a net speeding of processing relative to unrelated controls. To account for the results of Costa et al. (2005), Abdel Rahman and Melinger (2009) argued that part terms activate a relatively small cohort. Clearly, our results are at odds with the swinging lexical network account in several respects. First, part terms did not generally produce facilitation. It is possible that the general account is correct but that part terms activate a relatively large cohort, and therefore facilitation is not observed for part terms. However, this conclusion does not explain why semantic interference does not seem to be as robust in the case of the part–whole relations as it is for category coordinates. Second, related distractors produced facilitation in Experiment 3 only if they were associated, even though targets and their distractor were matched for LSA cosine values across the two conditions. This matching was accomplished by selecting an associated part and an unassociated part for the same target picture with the restriction that the average LSA value of these terms was equivalent in the two conditions. The swinging lexical cohort model claims that associates produce facilitation because they share a smaller semantic cohort with the target than coordinates. If the LSA cosine is thought of as a measure of semantic

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distance, with values closer to 1 indicating smaller distances, then the cosine between a target and part term can be thought of as the semantic distance between these concepts, and the density of words within the region defined by this distance can be estimated by counting the number of words whose cosine is greater than the cosine between target and part term (cf. Kittredge, Dell, & Schwartz, 2007). This definition of semantic neighbourhood suggests that employing distractors whose average distance from a common set of targets was identical should have produced very similar sized semantic cohorts for associated and unassociated parts in Experiment 3. To ascertain whether the semantic overlap between distractor and target was comparable in the two conditions, we estimated the density of items around both the target and the distractor. We estimated the semantic neighbourhood of the target, by counting the number of words with a higher LSA value to the target than its part term. A search of the LSA space revealed that the average number of words with a higher LSA value to the target did not reliably differ between related associates (M = 692) and related nonassociates (M = 581), t , 1. Conversely, we estimated the semantic neighbourhood of the part terms by counting the number of words with a higher LSA value to the part term than the target. Again, the average value for the related associates (M = 559) and related nonassociates (M = 583) did not differ, t , 1. The problem for the swinging lexical network hypothesis is that we observed a reliable pattern of facilitation for related associates despite the fact that the LSA measure provides no support for the claim that the semantic cohort is smaller for these pairs than for the nonassociated pairs, where facilitation was never observed. Our results are similar to those of a recent study by Bormann (2011) in which the category size of targets was manipulated. The rationale for manipulating category size was that members of smaller categories should share a smaller cohort with a coordinate distractor than members of larger categories. Although distractors that were category coordinates produced slower naming of targets in a standard PWI task, the size of this SIE did not differ for targets from small and large




categories. Thus, two different measures of cohort size appear to provide little support for the claim that cohort size is a determinant of whether facilitation or interference is observed in the PWI task. There are also aspects of our results that constrain the lexical competition account offered by Cutting and Ferreira (1999). Cutting and Ferreira argued that associates facilitated target naming because they did not have inhibitory connections at the lemma level and had excitatory links at the word-form level. Although they did not explicitly claim that noncoordinate semantic relations did not compete at the lemma level, the fact that part terms interfered with target naming at SOA 0 ms would seem to suggest that within this framework other semantic relations would have to have inhibitory links at the lemma level between related terms. If part terms do compete at the lemma level with their targets, then one would have to assume that when the distractor precedes the target by 300 ms, the activation of its lemma would have to have decayed sufficiently to preclude competition with the target and resultant interference. On the other hand, the activation at the word-form level would have to decay relatively slowly to produce an effect on the activation of the target’s word form for part terms that are strongly associated with the target. One potential difficulty with this account is that associative facilitation does not seem to occur at late SOAs. For example, visually presented distractors did not produce reliable facilitation at SOAs of +150 and +300 ms in the Sailor et al. (2009) study, nor was there semantic interference for coordinate distractors at these late SOAs. To the extent that the lack of semantic interference at these SOAs indicates a lack of interference at the lemma level, one would expect to see facilitation if the word-form representation of the associated distractor activated the word-form representation of the target. In addition, studies indicate that orthographically and potentially phonologically related visual distractors produce facilitation at later SOAs than those at which associative facilitation is reported. For example, Starreveld and La Heij (1996) observed that orthographically related visual distractors produced facilitation at

SOA +100 ms. Damian and Martin (1999) found that visually presented distractors that overlapped phonologically and orthographically with the target name facilitated naming relative to an unrelated distractor at SOAs of +100 and +200 ms, provided that the duration of the distractor was limited to 200 ms. Unless these late orthographic effects involve a mechanism in which activation does not spread from the word form of the distractor to the word form of the target, it is unclear why associates would not produce similar facilitation at late SOAs. Thus, it remains to be seen whether these discrepancies at positive SOAs can be reconciled with the basic account offered by Cutting and Ferreira (1999). In summary, the part–whole relation provides an interesting test of hypotheses about the nature of the SIE. Unlike coordinate distractors, parts do not share multiple features with targets and represent a different level of semantic organization from the targets. At the same time, parts are commonly assumed to facilitate activation of target concepts (Costa et al., 2005; Levelt et al., 1999). The fact that naming targets was slowed by the presence of the name of a constituent part suggests that the response exclusion hypothesis does not provide a comprehensive account of the SIE. It also suggests that the lexical competition hypothesis is still a viable account of how semantic factors influence lexical access. Original manuscript received 30 December 2012 Accepted revision received 19 November 2013 First published online 22 January 2014

REFERENCES Abdel Rahman, R., & Melinger, A. (2007). When bees hamper the production of honey: Lexical interference from associates in speech production. Journal of Experimental Psychology: Learning, Memory and Cognition, 33, 604–614. doi:10.1037/0278-7393.33. 3.604 Abdel Rahman, R., & Melinger, A. (2009). Semantic context effects in language production: A swinging lexical network proposal and a review. Language and


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Cognitive Processes, 24, 713–734. doi:10.1080/ 01690960802597250 Alario, F.-X., Segui, J., & Ferrand, L. (2000). Semantic and associative priming in picture naming. The Quarterly Journal of Experimental Psychology A: Human Experimental Psychology, 53A(3), 741–764. doi:10.1080/027249800410535 Bajo, M.-T. (1988). Semantic facilitation with pictures and words. Journal of Experimental Psychology: Learning, Memory and Cognition, 14(4), 579–589. doi:10.1037/0278-7393.14.4.579 Balota, D. A., Yap, M. J., Cortese, M. J., Hutchison, K. A., Kessler, B., Loftis, B., … Treiman, R. (2007). The english lexicon project. Behavior Research Methods, 39, 445–459. Retrieved June 6, 2007, from http://elexicon.wustl.edu/ Bormann, T. (2011). The role of lexical-semantic neighborhood in object naming: Implications for models of lexical access. Frontiers in Psychology, 2, 127. doi:10. 3389/fpsyg.2011.00127 Brooks, P. J., Seiger-Gardner, L., & Sailor, K. (2013). Contrasting effects of associates and coordinates in children with and without language impairment: A picture-word interference study. Applied Psycholinguistics. Advance online publication. doi:10. 1017/S0142716412000495 Caramazza, A., & Costa, A. (2000). The semantic interference effect in the picture-word interference paradigm: Does the response set matter? Cognition, 75 (2), B51–B64. doi:10.1016/S0010-0277(99)00082-7 Caramazza, A., & Costa, A. (2001). Set size and repetition in the picture-word interference paradigm: Implications for models of naming. Cognition, 80 (3), 291–298. doi:10.1016/S0010-0277(00)00137-2 Costa, A., Alario, F.-X., & Caramazza, A. (2005). On the categorical nature of the semantic interference effect in the picture-word interference paradigm. Psychonomic Bulletin & Review, 12(1), 125–131. doi:10.3758/BF03196357.2005-04938-012 Cutting, J. C., & Ferreira, V. S. (1999). Semantic and phonological information flow in the production lexicon. Journal of Experimental Psychology: Learning, Memory and Cognition, 25(2), 318–344. doi:10. 1037/0278-7393.25.2.318 Cycowicz, Y. M., Friedman, D., Rothstein, M., & Snodgrass, J. G. (1997). Picture naming by young children: Norms for name agreement, familiarity, and visual complexity. Journal of Experimental Child Psychology, 65, 171–237. doi:10.1037/0278-7393.25.2.318 Damian, M. F., & Martin, R. C. (1999). Semantic and phonological codes interact in single word

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production. Journal of Experimental Psychology: Learning, Memory and Cognition, 25(2), 345–361. doi:10.3758/BF03196474 Estes, Z., Golonka, S., & Jones, L. L. (2011). Thematic thinking: The apprehension and consequences of thematic relations. In B. Ross (Ed.), Psychology of learning and motivation, Vol. 54 (pp. 249–294). Burlington: Academic Press. Hutchison, K. A. (2003). Is semantic priming due to association strength or feature overlap? A microanalytic review. Psychonomic Bulletin & Review, 10 (4), 785–813. doi:10.3758/BF03196544 Kittredge, A. K., Dell, G. S., & Schwartz, M. F. (2007). Omissions in aphasic picture naming: Late age-ofacquisition is the culprit, not low semantic density. Brain and Language, 103(1–2), 132–133. doi:10. 1080/02643290701674851 La Heij, W., Dirkx, J., & Kramer, P. (1990). Categorical interference and associative priming in picture naming. British Journal of Psychology, 81 (4), 511–525. doi:10.1111/j.2044-8295.1990. tb02376.x Landauer, T. K., Foltz, P. W., & Laham, D. (1998). An introduction to latent semantic analysis. Discourse Processes, 25(2–3), 259–284. doi:10.1080/ 01638539809545028 Levelt, W. J. M., Roelofs, A., & Meyer, A. S. (1999). A theory of lexical access in speech production. Behavioral and Brain Sciences, 22(1), 1–75. doi:10. 1017/S0140525X99001776 Lupker, S. J. (1979). The semantic nature of response competition in the picture-word interference task. Memory & Cognition, 7(6), 485–495. doi:10.3758/ BF03198265 Mahon, B. Z., Costa, A., Peterson, R., Vargas, K. A., & Caramazza, A. (2007). Lexical selection is not by competition: A reinterpretation of semantic interference and facilitation effects in the picture-word interference paradigm. Journal of Experimental Psychology: Learning, Memory and Cognition, 33(3), 503–535. doi:10.1037/0278-7393.33.3.503 Maki, W. S., & Buchanan, E. (2008). Latent structure in measures of associative, semantic, and thematic knowledge. Psychonomic Bulletin & Review, 15(3), 598–603. doi:10.3758/PBR.15.3.598 Muehlhaus, J., Heim, S., Sachs, O., Schneider, F., Habel, U., & Sass, K. (2013). Is the motor or the garage more important to the car? The difference between semantic associations in single word and sentence production. Journal of Psycholinguistic Research, 42(1), 37–49.




Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (2004). The University of South Florida free association, rhyme, and word fragment norms. Behavior Research Methods, Instruments & Computers, 36(3), 402–407. doi:10.3758/BF03195588 Sailor, K., Brooks, P. J., Bruening, P. R., SeigerGardner, L., & Guterman, M. (2009). Exploring the time course of semantic interference and associative priming in the picture-word interference task. Quarterly Journal of Experimental Psychology, 62, 789–801. doi:10.1080/17470210802254383 Schneider, W., Eschman, A., & Zuccolotto, A. (2002). E-prime user’s guide. Pittsburgh: Psychology Software Tools.

Schriefers, H., Meyer, A. S., & Levelt, W. J. M. (1990). Exploring the time course of lexical access in language production: Picture-word interference studies. Journal of Memory and Language, 29(1), 86–102. Starreveld, P. A., & La Heij, W. (1996). Time-course analysis of semantic and orthographic context effects in picture naming. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(4), 896–918. doi:10.1037/0278-7393.22.4.896 Underwood, G. (1976). Semantic interference from unattended printed words. British Journal of Psychology, 67(3), 327–338. doi:10.1111/j.20448295.1976.tb01519.x

APPENDIX A. STIMULI FOR EXPERIMENT 1

Target picture

Associate

Unrelated control for associate

Non-associate

Unrelated control for non-associate

Angel Apple Balloon Bird Book Cake Car Chair Church Clock Dog Doughnut Elephant Fish Foot Guitar Hamburger Hand House Kangaroo Knife Knight Lamp Peach Ring Rose Shark Skeleton Train Zebra

HALO CORE HELIUM FEATHER PAGE ICING GAS SEAT STEEPLE ALARM TAIL HOLE TRUNK SCALES TOE STRING BUN FINGER ROOF POUCH BLADE ARMOR SHADE FUZZ DIAMOND THORN JAWS BONE ENGINE STRIPE

GAS PAGE ARMOR DIAMOND CORE TOE HALO BUN TRUNK POUCH STRING STRIPE STEEPLE ENGINE ICING TAIL SEAT SHADE JAWS ALARM THORN HELIUM FINGER BONE FEATHER BLADE ROOF FUZZ SCALES HOLE

GOWN SKIN RUBBER LEG PRINT SUGAR LOCK BACK DOOR NUMBERS NOSE FLOUR MOUTH EYE JOINT WOOD TOMATO MUSCLE WINDOW STOMACH STEEL HELMET CORD JUICE METAL LEAF GILLS RIB MOTOR HEAD

LOCK PRINT HELMET METAL SKIN JOINT GOWN TOMATO MOUTH STOMACH WOOD HEAD DOOR MOTOR SUGAR NOSE BACK CORD GILLS NUMBERS LEAF RUBBER MUSCLE RIB LEG STEEL WINDOW JUICE EYE FLOUR


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APPENDIX B. STIMULI FOR EXPERIMENT 2 Target picture

Part term

Unrelated control for part term

Filler 1

Filler 2

Airplane Ambulance Bird Boat Bottle Cactus Canoe Car Cherry Chimney Church Cigarette Dog Eagle Fish Flashlight House Keg Lighter mattress Motorcycle Newspaper Pear Rifle Rose Sink Snake Stove Submarine Tree Truck Volcano

PROPELLER STRETCHER WINGS RUDDER CORK SPINES PADDLE ENGINE PIT SOOT PEW TOBACCO TAIL TALONS GILLS BATTERY STAIRS BEER FLAME SPRINGS BRAKES PAGES CORE TRIGGER THORNS DRAIN VENOM BURNERS PERISCOPE BRANCHES WHEELS LAVA

TOBACCO PERISCOPE CORE LAVA GILLS TRIGGER VENOM BRANCHES DRAIN PEW SOOT PROPELLER BEER BURNERS CORK SPRINGS FLAME TAIL STAIRS BATTERY THORNS WHEELS WINGS SPINES BRAKES PIT PADDLE TALONS STRETCHER ENGINE PAGES RUDDER

LIMELIGHT DISPENSER WITCH RATTLE GOWN FRILLS LADDER SCRIPT ZIP RUNT OAT VACCINE RACK VENEER CRIMP TRAFFIC THIGHS LAKE RIVER SILICON GARLIC APPLE SNOW PLANETS STARCH TONE FLOUR PUDDLES TARANTULA READINGS POCKET TORSO

VACCINE TARANTULA SNOW TORSO CRIMP PLANETS FLOUR READINGS TONE OAT RUNT LIMELIGHT LAKE PUDDLES GOWN SILICON RIVER RACK THIGHS TRAFFIC STARCH POCKET WITCH FRILLS GARLIC ZIP LADDER VENEER DISPENSER SCRIPT APPLE RATTLE

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APPENDIX C. STIMULI FOR EXPERIMENT 3

Target picture

Associate

Unrelated control for associate

Non-associate

Unrelated control for non-associate

Ambulance Balloon Bear Bike Box Car Chicken Computer Elephant Fence Fish Hand House Knife Lamp Pants Pie Rose Sheep Shirt Skeleton Skirt Tent Tree

SIREN HELIUM CLAW PEDAL CARDBOARD ENGINE BREAST KEYBOARD TRUNK PICKET SCALES PALM BRICK BLADE SHADE ZIPPER CRUST THORN WOOL COLLAR BONE HEM STAKE LEAF

THORN CLAW HELIUM COLLAR WOOL BONE SHADE STAKE PICKET TRUNK CRUST BRICK PALM ZIPPER BREAST BLADE SCALES SIREN CARDBOARD PEDAL ENGINE KEYBOARD LEAF HEM

DASHBOARD RUBBER NOSE WHEEL LID WINDOW HEAD MEMORY HIDE LATCH TAIL NAIL CEILING HANDLE SWITCH STITCH DOUGH SCENT EARS FABRIC RIB WAIST POLE KNOT

SCENT NOSE RUBBER FABRIC EARS RIB SWITCH WAIST LATCH HIDE DOUGH POLE KNOT STITCH HEAD HANDLE TAIL DASHBOARD LID WHEEL WINDOW MEMORY NAIL CEILING


1785

Facilitation and interference in the color-naming task.

Prelexical facilitation and lexical interference in auditory word recognition.

Do mitochondria produce oxygen radicals in vivo?

Semantic facilitation without association in a lexical decision task.

Predator facilitation or interference: a game of vipers and owls.

Phonetic interference under varying conditions of phonetic facilitation.

Empirical relations as interference correctives in multichannel analyzers.

Output and retrieval interference in the missing-number task.

Do Reactions to Tests Produce Changes in the Construct Measured?

Attentional switches and dual-task interference.

Do Schwann cells produce collagen type III?

Simultaneous fMRI and EEG during the multi-source interference task.

Dual-task interference in evaluative conditioning: Similarity matters!

Flanker interference effects in a line bisection task.

Task choice and semantic interference in picture naming.

Exploring adolescent cognitive control in a combined interference switching task.

Distractor interference during a choice limb reaching task.

Do different therapies of AML produce different outcomes?

How do "mute" cicadas produce their calling songs?

Task-Specific Facilitation of Cognition by Anodal Transcranial Direct Current Stimulation of the Prefrontal Cortex.

Why do plants produce so many terpenoid compounds?

Do the pancreatic primordial buds in embryogenesis have the potential to produce all pancreatic endocrine cells?

Do task and sex differences influence the visual evoked potential?

A potential role of reward and punishment in the facilitation of the emotion-cognition dichotomy in the Iowa Gambling Task.