Cognitive Neuropsychology

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Neural correlates of Italian nominal compounds and potential impact of headedness effect: An ERP study

Radouane El Yagoubi a; Valentina Chiarelli ab; Sara Mondini c; Gelsomina Perrone d ; Morena Danieli a; Carlo Semenza a a University of Trieste, Trieste, Italy b CIMEC (Centro Interdipartimentale Mente/Cervello), University of Trento, Trento, Italy c University of Padova, Padova, Italy d University of Milano-Bicocca, Milano, Italy First Published on: 01 March 2008 To cite this Article: Yagoubi, Radouane El, Chiarelli, Valentina, Mondini, Sara, Perrone, Gelsomina, Danieli, Morena and Semenza, Carlo (2008) 'Neural correlates of Italian nominal compounds and potential impact of headedness effect: An ERP study', Cognitive Neuropsychology, 1 To link to this article: DOI: 10.1080/02643290801900941 URL: http://dx.doi.org/10.1080/02643290801900941

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COGNITIVE NEUROPSYCHOLOGY, iFirst, 1 – 23

Neural correlates of Italian nominal compounds and potential impact of headedness effect: An ERP study Radouane El Yagoubi University of Trieste, Trieste, Italy

Valentina Chiarelli University of Trieste, Trieste, Italy, and CIMEC (Centro Interdipartimentale Mente/Cervello), University of Trento, Trento, Italy

Sara Mondini University of Padova, Padova, Italy

Gelsomina Perrone University of Milano-Bicocca, Milano, Italy

Morena Danieli and Carlo Semenza University of Trieste, Trieste, Italy

An event-related potential (ERP) technique was used to investigate the way in which noun– noun compounds are processed during a lexical decision task with Italian speakers. Reaction times and error rates were higher for compounds than for noncompounds. ERP data showed a more negative peak in the left anterior negativity (LAN) component for compounds. These results are compatible with a dual-route model that posits not only whole-word access for compounds but also an activation of decomposed representations of compound constituents. A final result relates to head position, which in Italian compounds could be on either the left- or the right-hand side of the word. While behavioural analysis did not reveal a difference between left- and right-headed compounds, a difference was found with the P300 component. The role of the compound head as a crucial informationbearing component is discussed. Keywords: Noun-noun compounds; Headedness effect; ERPs; LAN component.

Compounding is an important and productive process in most languages. The study of how compound words are represented and processed may provide important insights into the way in which

the human mind stores, organizes, and accesses multimorphemic words. However, compared to other morphological processes, like inflection and derivation, the comprehension and production of

Correspondence should be addressed to Carlo Semenza, Department of Psychology, University of Trieste, Via S. Anastasio, 12, 34134 Trieste, Italy (E-mail: [email protected]). This research was supported by a grant from the Marie Curie Research Training Network “NUMBRA: Numeracy And Brain Development” to Radouane El Yagoubi and Carlo Semenza. We are grateful to two anonymous reviewers and in particular to the guest Editor, Michele Miozzo, for detailed comments and suggestions on earlier versions of the manuscript. # 2008 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business http://www.psypress.com/cogneuropsychology

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DOI:10.1080/02643290801900941


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compounds as well as their neurological implementation have received less attention in psycholinguistic and neuropsychological investigations. For over a quarter of a century, psycholinguistic research has focused on how inflected, derived, and compound words are stored in the mind. The main question is whether multimorphemic words are stored in the mental lexicon in their full form or whether only their morphemes are stored and then combined to form complex words. Accordingly, two competing classes of theories have been proposed supporting either the former or the latter alternative: the so-called “full-listing” theories (Butterworth, 1983; Bybee, 1995) and the so-called “decomposition” or “fullparsing” theories (Libben, Derwing, & de Almeida, 1999; McKinnon, Allen, & Osterhout, 2003; Taft, 2004; Taft & Forster, 1976). More recently, however, a class of so-called “dualroute” theories has gained ground, which is a compromise between the other two views. Dual-route theories assume that a complex word can be either stored as a whole or be decomposed into its morphological constituents (there are several variants of this view, e.g., Baayen, Dijkstra, & Schreuder, 1997; Caramazza, Laudanna, & Romani, 1988; Isel, Gunter, & Friederici, 2003; Sandra, 1990; Zwitserlood, 1994). Dual-route theories naturally raise several questions about exactly what sort of complex words are preferentially used via one route rather than the other. For example, these theories propose that very frequently used items and, in the particular case of compounds, opaque items would be stored and processed more efficiently in their full form; in contrast, less frequent items and transparent compounds would be subject to decomposition. Most works concerning morphological decomposition have been conducted on inflected and derived words. However, a number of investigations on compound decomposition in both the visual and the auditory modalities have appeared in the literature (Coolen, Van Jaarsfeld, & Schreuder, 1993; Isel et al., 2003; Jarema, Busson, Nikolova, Tsapkini, & Libben, 1999; Libben, 1993; Pratarelli, 1995; Sandra, 1990; Zwitserlood, 1994). Testifying the growing

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interest in the topic, an entire book was recently devoted to the representation and processing of compound words (Libben & Jarema, 2006). Although most of the neuropsychological studies devoted to morphology have been concerned with inflection and derivation (Badecker & Caramazza, 1987; Coltheart, 1980; De Bleser & Bayer, 1990; Patterson, 1980; Semenza, Butterworth, Panzeri, & Ferreri, 1990), a few studies have focused on compounds (see Semenza & Mondini, 2006, for a review, and Chiarelli, Menichelli, & Semenza, 2007, for updating). These investigations were carried out using tasks like picture naming, word repetition, reading, and, less frequently, writing. On the whole, evidence was found in support of fullparsing models (Semenza, Luzzatti, & Carabelli, 1997) and dual-route models (Mondini, Jarema, Luzzatti, Burani, & Semenza, 2002) rather than full-listing models. For example, in studies conducted in Italian (Mondini, Luzzatti, Saletta, Allamano, & Semenza, 2005; Semenza et al., 1997), aphasics who had more severe problems with verbs (mostly of the Broca’s type) were shown to drop the verb component in verb – noun compounds (e.g., “portamonete”: literally “carry-coins”, purse). This effect was not determined by position, since it did not hold for noun –noun compounds. However, Italian verb – noun compounds are nouns. If verb –noun compounds were not decomposed during processing, aphasics with greater difficulties for verbs would not preferentially omit the verb component. This finding constitutes one of the strongest pieces of evidence in favour of decompositionality. The specific characteristics of morphology in each language could offer promising opportunities to study compound processing and the effect of variables such as productivity (for a thorough review, see Jarema, 2006). The present study investigates the processing of compounds in the brain, focusing on headedness. The study is conducted in Italian, where rules governing headedness provide a good opportunity for investigating compound processing. The “head” of a compound is the component determining the lexical category, the syntactic features (e.g., number and gender),


PROCESSING OF ITALIAN NOUN – NOUN COMPOUNDS

and the semantic traits of the whole compound. The grammatical and logical head of compounds is the rightmost element in Germanic languages like English (but also in Finnish, Greek, Bulgarian, and Polish, just to mention a few other languages on which psycholinguistic research about headedness has been conducted). The regularity of the position of the head, determined with this rule, reduces the information stored at a representational level to a minimum: “It is an XN compound”, where X may be a noun, an adjective, a verb, and so on. In other languages, like Italian and French, composition is far less regular. For instance, Italian noun – noun compounds may be either right-headed (nN: e.g., astronave, spaceship) or left-headed (Nn: e.g., capobanda, band leader).1 Italian speakers are familiar with both kinds of compounds. Diachronically, left-headed compounds appeared at an earlier time. Moreover, they respect the canonical order for lexical categories in Italian: noun þ modifier. In contrast, right-headed compounds are generally derived from other languages, mostly either from Latin or, nowadays, from English. However, right-headed compounds are increasingly productive in contemporary Italian, as documented by the expanding number of nN neologisms and by their growing frequency of use (Schwarze, 2005). The study of headedness is complicated because it must take into account the position of the head in the compound string. In fact, assuming that compounds can be processed in a decomposed fashion, the processing of the compound constituents must be expected to be crucially influenced by their position. Position-in-the-string effects have indeed been considered in the literature. For instance, Taft and Forster (1976) suggested that, in English, initial constituents of polymorphemic words may play a more important role in lexical

access than do the second constituents. In contrast, Lima and Pollatsek (1983) found no clear constituent-specific access. The compound constituent position and the compound headedness must eventually be teased apart to fully evaluate their respective influence on compound processing. So far, this has not proven to be an easy task. It is indeed known from studies on healthy participants that the position within the compound interacts with morphological headedness in compound processing (Jarema et al., 1999; Kehayia et al., 1999; Libben, Gibson, Yoon, & Sandra, 2003). For instance, Jarema et al. (1999) contrasted the role of headedness in French, in which head position varies, and English, in which head position is fixed—a comparison that would enable the disentanglement of the effects of position versus headedness. Using a priming paradigm in the lexical decision task, they showed a stronger priming effect for the initial constituents than for the final constituents of left-headed compounds in French. By contrast, no difference was observed between compound constituents in English, a language in which compounds are right-headed. It was hard, on the basis of these findings, to fully disentangle effects due to headedness from effects due to position. Effects associated with the position of compound constituents have also been shown in aphasiological studies. For example, Ahrens (1977), in a study on German-speaking aphasics, observed that when only one part of the compound was successfully produced it was usually the first component (in German compounds, the first and the second component are the head and the modifier, respectively). This effect, however, was not replicated in other group studies of German aphasics (Blanken, 2000; Hittmair-Delazer, Andre´e, Semenza, De Bleser, & Benke, 1994). In a study conducted in Italian, Chiarelli et al. (2007)

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Other Italian compounds (i.e., verb–noun compounds, the most productive type in Italian) have an exocentric structure. In exocentric compounds, neither of the two elements is the logical and grammatical head of the compound. For instance, a portamonete, “coin purse” (literally “carry-coins”), is neither a special type of coin nor a special way of carrying something—this compound is a noun and refers to an object that is used to contain (carry) coins. This type of composition is much less common in English (e.g., pickpocket or passport, which are neither a type of pocket nor a type of port). The logical head of this type of compounds is therefore missing—that is to say, it is not phonologically specified. COGNITIVE NEUROPSYCHOLOGY, 0000, 00 (0)

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found different results with patients affected by early Alzheimer’s disease and aphasia. Patients with Alzheimer’s disease omitted and substituted the second component more often than the first one when producing a variety of compound stimuli. By contrast, aphasia patients made more errors with the first component. The tentative interpretation that the authors offered for their results is that the second component is more sensitive to factors like processing overload than is the first component. Chiarelli et al. (2007) acknowledged that in their study, as in prior aphasiological research, headedness and component positions were confounded and that various methodological constraints prevented the disentangling of the effects of each of these variables. One constraint was the limited number of depictable compounds suitable for this kind of investigation. Another constraint was that the number of critical errors obtained from each participant in reading and repetition tasks was seldom sufficient to draw clearcut conclusions, and group studies naturally tend to suffer from lack of homogeneity. For these reasons the possible effect of headedness has so far remained elusive in neuropsychological research. However, the issue of headedness cannot be ignored. Progress in understanding how word combination is represented and processed in the brain must include an understanding of the specific role of compound heads. Were the head in the same position in all languages, it would be very hard to distinguish what is simply due to processing order and what is due to the semantic and syntactic factors that distinguish the head from the nonhead components. However, the existence of both rightand left-headed compounds in Italian allows an experimental manipulation of head position that is not possible in languages that only have rightheaded compounds. This feature of Italian motivated the present investigation of the role of headedness in compounds. The study aims at investigating the neural correlates of compounds and the potential impact of headedness on the time-course of compound processing. We approached these issues by examining the temporal resolution and spatial localization of

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event-related potentials (ERPs) in response to compound stimuli. As ERPs are differentially sensitive to the various types of information and provide a continuous measure of word processing, this method seems particularly suited to an exploration of the issues at hand. Before turning to the experimental design, we first need to introduce some of the previous ERP studies on language processing focusing on the ERP components that are relevant to the present investigation. ERP studies have reported many different electrophysiological components associated with the lexical access that occurs during comprehension of written words. In their recent review, Barber and Kutas (2007) identified several components implicated in a fast and automatic word recognition process taking place within about the first 200 ms. For example, Sereno and Rayner (2003) suggest that lexical identification occurs, at least to a certain degree, between 60 and 150 ms after word fixation. Moreover, other studies have shown a lexicality effect (i.e., a difference between words and nonwords) in the ERP responses between 100 and 200 ms (192 ms, Dehaene, 1995; 150 ms, Proverbio, Vecchi, & Zani, 2004; 100 ms, Sereno, Rayner, & Posner, 1998). Findings about word frequency effects around 110– 160 ms confirmed this early lexical access (Dambacher, Kliegl, Hofmann, & Jacobs, 2006; Hauk, Davis, Ford, Pulvermuller, & Marslen-Wilson, 2006; Hauk & Pulvermuller, 2004). The P300 family component is another ERP component observed in a variety of tasks. P300 is a positive component that typically shows a centro-parietal scalp distribution with maximum amplitude around 300 ms poststimulus onset. Some authors distinguish between an early and a late P300 (peaking between 600 and 800 ms after stimulus onset; Hill, Ott, & Weisbrod, 2005). A number of factors are known to influence P300 amplitude, such as stimulus novelty and probability, relevance of the stimulus to the task at hand, the amount of attentional resources necessary to perform a task, and stimulus saliency (see Bashore & Van der Molen, 1991; Kok, 2001, for reviews). Moreover, many



studies have revealed that P300 amplitude could be an index of adaptation of working-memory traces when unexpected information has to be integrated into an individual’s model of the environment (context updating theory; Donchin & Coles, 1988). Alternatively, P300 amplitude can be seen as an indicator of closure of a perceptual epoch or internal template when expectations pertaining to specific stimuli are met (context closure theory; Verleger, 1988). The N400 component is one of the most important ERP waveforms related to language processing (though not specific to the linguistic domain). The N400 (Kutas & Hillyard, 1980) is a negative peak with a maximum amplitude around 400 ms after stimulus onset. It typically shows a centro-parietal scalp distribution in the visual modality and a more frontal distribution in the auditory modality. It is thought to reflect semantic integration processes, as its amplitude is especially large for words that are difficult to anticipate and integrate within a sentence context because they are semantically unexpected or incongruous. However, the N400 has been correlated not only with aspects of semantic processing in sentence context, but also with the lexico-semantic processing of single words (Kutas & Federmeier, 2000). This conclusion is supported by the finding that the N400 component has a more negative amplitude for nonwords (or pseudowords) than words. This effect is assumed to reflect greater demands on a lexico-semantic memory search for nonwords, since they do not have a lexical representation (Attias & Pratt, 1992; Bentin, 1987; Friedrich, Eulitz, & Lahiri, 2006; Picton & Hillyard, 1988; Supp et al., 2004). Unlike N400, which reflects a lexico-semantic integration process, LAN (left anterior negativity) and P600 components are associated with a morpho-syntactic analysis of linguistic stimuli. LAN occurs approximately in the same time window as the semantic N400 effect, but generally has a more anterior scalp distribution and is sometimes left-lateralized. LAN has specifically been associated with the initial morphosyntactic processing (Friederici, 1995, 2001) and has been found in all the studies that used morphosyntactic

violations. Alternatively, it has been proposed that LAN reflects an increased working-memory load (Coulson, King, & Kutas, 1998; Kluender & Kutas, 1993). P600, in turn, is a positive component showing a parietal scalp distribution with maximum amplitude peaking between 500 and 900 ms after stimulus onset. It has been associated with syntactic processing and the repair or reanalysis of syntactic violations (Coulson et al., 1998; Friederici, 2002; Friederici, Hahne, & Mecklinger, 1996; Neville, Nicol, Barss, Forster, & Garrett, 1991; Osterhout, McKinnon, Bersick, & Corey, 1996) and seems to be more susceptible to controlled processes than earlier components (Hahne & Friederici, 1999). So far, only a few of the ERP studies that have appeared in the literature were devoted to compounds. In one such study, Koester, Gunter, Wagner, and Friederici (2004) conducted a series of experiments in which German compounds were presented in the auditory modality. They manipulated the gender agreement (a) between a determiner and the initial (nonhead) compound constituent and (b) between a determiner and the last compound constituent (i.e., the head). Although only the head is morphosyntactically relevant in German, both constituents elicited LAN if the gender was incongruent. This finding, replicated by Koester, Gunter, and Wagner (2007), was taken as a strong indication of morphosyntactic decomposition. There would in fact be no congruency effects on the first constituents if they were not independently processed, and compounds were not analysed in a decomposed form. Unfortunately, because it is not possible to manipulate head position in German, Koester and collaborators could not disentangle the contributions of head processing and component position. Therefore previous ERP studies could not provide information about the specific role of the head and the neurological underpinning of head processing. It is, however, important to determine whether the compound head, a concept stemming from theoretical linguistics, has a psychological and neurological basis. It is also important to ascertain whether compound heads are processed COGNITIVE NEUROPSYCHOLOGY, 0000, 00 (0)

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in the brain differently from the nonhead, modifier components. In the present study conducted in Italian, ERP and behavioural data were recorded using visually rather than orally presented transparent compounds in a lexical decision task. As mentioned above, head positions were manipulated. Thus left-headed compounds were contrasted with right-headed compounds. An example of a leftheaded compound is capobanda, band leader. Capobanda refers to a type of leader, not to a type of band; therefore capo (leader) is the head of this compound. The head also determines the lexical gender; capo is masculine, banda is feminine; thus capobanda is masculine. An example of a right-headed compound is astronave, spaceship, literally “starship”. Astronave is a sort of ship rather than a star; therefore nave (ship) is the head: Since nave is feminine, astronave is also feminine. In order to minimize confounds due to transparency and grammatical class, only transparent, nominal compounds were used. Compound words were contrasted with noncompound words that had a real word embedded on their left side (e.g., coccodrillo, crocodile, where cocco means coconut, while drillo is a nonword) or on their right side (e.g., tartaruga, tortoise; where ruga means wrinkle and tarta is a nonword). Nonwords were generated by exchanging the two real morphemes of a compound word (e.g., capobanda ! bandacapo) or by exchanging the two segments of a noncompound word (e.g, coccodrillo ! drillococco). The lack of previous studies on this particular topic makes it difficult to generate specific predictions concerning our results. Therefore, the predictions we discuss below are as specific as possible. As in previous studies, we predict that nonwords would be associated with longer reaction times (RTs) and with a larger N400 negativity than are words (Bentin, 1987; Kutas & Federmeier, 2000). Moreover, as suggested by full-parsing models (e.g., Libben et al., 1999; McKinnon et al., 2003; Taft, 2004; Taft & Forster, 1976), if compound nouns are processed through morphosyntactic decomposition, then they would be associated with longer RTs than noncompound nouns. Moreover, if as a result of

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decomposition the morphosyntactic features of the individual components are analysed, then we should also observe the LAN and P600 components that have been shown to be associated with morpho-syntactic analysis (see Friederici & Kotz, 2003, for a review). These components are expected to be differentially affected by compounds and noncompounds. Finally, larger P300 amplitude for rightthan for left-headed compounds may indicate an increased use of attentional resources or the need to update working memory when the crucial information is contained in the second component.

Method Participants The task was administered to 20 participants who had given their informed consent. Because of a large number of artefacts, the data from 2 participants were excluded from the grand ERP averages. Thus, the final data were collected from 18 adults (8 men and 10 women), whose mean age was 25 years (range ¼ 20– 31 years). They were tested individually, in a single session that lasted about half an hour. All participants were right-handed native Italian speakers. They were neurologically normal, not taking specific medication, and had normal or corrected-to-normal vision. Visual acuity was checked at the beginning of the experiment. Stimuli The experimental items consisted of 112 words (see Appendix), divided into four sets each containing 28 items: (a) transparent left-headed noun –noun compounds (e.g., capobanda, band leader); (b) transparent right-headed noun – noun compounds (e.g., astronave, spaceship); (c) noncompound nouns with a real word embedded in the left side of the whole word (e.g., coccodrillo, crocodile, where cocco means “coconut”); (d) noncompound nouns with a real word embedded in the right side of the word (e.g., tartaruga, tortoise; where ruga means “wrinkle”). The word embedded on the left or right side of noncompounds was not related in meaning to the whole word. Frequency,



length (number of letters), familiarity, imageability, and age of acquisition were calculated or collected through questionnaires for the compound and noncompound words. Obtaining the frequencies of Italian compounds is not a trivial task, because existing frequency dictionaries rarely include new compounds—in fact, they include few, if any, compounds. Available frequency dictionaries are based on written corpora from various text sources (fiction and nonfiction literature, transcription of controlled speech, such as academic reports, news, etc.). On the contrary, recent compounds tend to be used in the nonformal speech of everyday life (e.g., in the language of advertising). Some researchers have solved the problem of calculating the frequencies of unseen compounds by summing the frequencies of the constituents (Jansen, Bi, & Caramazza, 2007). Researchers in computational linguistics have recently proposed an alternative method that takes advantage of the large variety of texts available on the Web. Of particular relevance here, Keller and Lapata (2003) demonstrated that similar frequency counts were obtained from Web sources and the large text corpora that were used in the past (e.g., the Brown corpus for English). We adopted a similar method for determining the frequencies of our experimental words. Frequencies were calculated from a large corpus of over 23 million words from newspapers and other text sources available from Italian Web sites and were logtransformed before being entered in the analysis. Familiarity, imageability and age of acquisition were collected via three different questionnaires

administered to three different groups, each made up of 30 raters who were native Italian speakers and did not participate in the ERP experiment (see Table 1). The three groups were balanced with respect to gender, age, and schooling. The four item sets included in the experiment were matched for imageability, F(3, 108) ¼ 3.73; ns. However, they differed with respect to familiarity, F(3, 108) ¼ 3.48; p , .05; multiple comparisons using Bonferroni corrections showed a significant difference only between right-headed compounds and noncompounds with a word embedded on the right, tbonferroni(108) ¼ –2.88; padj ¼ .03. Item sets also differed in terms of age of acquisition, F(3, 108) ¼ 3.22; p , .05; multiple comparisons done using Bonferroni correction reached significance only between right-headed compounds and noncompounds with a word embedded on the left, tbonferroni(108) ¼ 2.87; padj ¼ .03. We tried to match compound and noncompound words for length (number of letters). Compounds were slightly longer, on average by about one letter, F(3, 108) ¼ 10.50; p , . 001. However, there was no difference in length between left- and right-headed compounds. A list of nonwords was generated from the experimental items by exchanging the positions of the two constituents of the compounds (e.g., for capobanda the corresponding nonword was bandacapo) or by exchanging the positions of the two segments of the noncompounds (e.g., for tartaruga the nonword was rugatarta). Experimental nouns were further intermixed with 88 word fillers and 88 nonwords. The word fillers were four syllables long and consisted of

Table 1. Means of the psycholinguistic variables Compounds

Noncompounds

Variable

Right-headed

Left-headed

Left-embedded word

Right-embedded word

Length Familiarity Frequency (log) Imageability Age of acquisition

10.21 (1.10) 4.89 (0.89) 2.19 (0.30) 5.16 (1.08) 4.60 (1.05)

10.82 (1.83) 4.60 (1.09) 2.29 (0.42) 4.31 (1.42) 5.34 (1.16)

9.32 (1.47) 5.26 (0.97) 2.06 (0.62) 4.82 (1.19) 4.36 (81.21)

9.04 (0.69) 5.38 (1.05) 1.92 (0.64) 4.57 (1.44) 4.53 (1.58)

Note: Standard deviations in parentheses. COGNITIVE NEUROPSYCHOLOGY, 0000, 00 (0)

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suffixed or prefixed nouns or long nouns without real nouns embedded (e.g., macedonia, “fruit salad”). They were matched with the experimental nouns for length and position of primary word stress. Each of the word fillers was also used to create a corresponding nonword by substituting three of its letters (in two different syllables). Word fillers and nonwords were included to make participants unaware of the tested variables. The set of stimuli showed in the lexical decision task included a total of 200 words and 200 nonwords. The experiment was controlled by E-Prime software (Version 1.1). The stimuli were displayed in the centre of a 1900 computer screen, which was placed 70 cm in front of the participants. All stimuli appeared in black on a silver background with size 32 font, Courier New typeface. Procedure Participants were seated comfortably in a soundattenuated booth, with response keys under their left and right hands. They were instructed to press the “YES” key if the stimulus was a word and the “NO” key if the stimulus was a nonword, as quickly and accurately as possible. Response hands were counterbalanced across participants. The set of stimuli was divided into four blocks each containing an equal number of trials from the

different experimental conditions. Block order was counterbalanced across participants, and the stimuli were randomized for each participant. Each block lasted approximately 7 minutes, and short rest periods were provided between blocks. To familiarize participants with the task, each experimental session started with a practice block. The sequence of events within a trial was as follows (see Figure 1): A warning-fixation stimulus was displayed in the centre of the screen for 500 ms, followed by the stimulus, which remained until the participant responded. The time was recorded from the moment the stimuli appeared till when the participant answered by pressing one of the two response keys. Participants were given a maximum of 3,000 ms to answer. The intertrial interval (ITI) followed the participant’s response and lasted 2,000 ms. During the ITI a mask sequence of # appeared on the screen, and participants could blink or move their eyes. Participants were asked to refrain from blinking and moving (except for the key press response) during the critical phase of electroencephalography (EEG) recording. Data acquisition and analysis RTs for correct responses and error rates were analysed with 2 2 2 repeated measure analyses of

Figure 1. Sequence and length of the various events making up a trial. Nn: left-headed noun–noun compounds. nN: right-headed noun– noun compounds. NC1: noncompound nouns with a real word embedded on the left side of the whole word. NC2: noncompound nouns with a real word embedded on the right side of the whole word. Fillers: long nouns without an embedded real word. During the intertrial interval (ITI) a mask sequence appeared at the centre of the screen to inform participants that they could blink and move their eyes.

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variance (ANOVAs) with lexicality (word vs. nonwords), type of words (compounds vs. noncompounds), and headedness (left- vs. right-headed compounds or left- vs. right-embedded noncompounds) as factors. Strictly speaking the term “headedness”, a label used for the sake of simplicity, is inappropriate for this last factor, since this includes both compounds and noncompounds. Such an ambiguity would be absent in post hoc comparisons. Continuous EEG was recorded from 28 scalp electrodes mounted on an elastic cap (ElectroCap International) and located at standard leftand right-hemisphere positions over frontal, central, parietal, occipital, and temporal areas (International 10/20 System, at Fz, FCz, Cz, CPz, Pz, Oz, Fp1, Fp2, F3, F4, C3, C4, P3, P4, O1, O2, F7, F8, T3, T4, Ft7, Ft8, Fc3, Fc4, Cp3, Cp4, Tp7, Tp8). These recording sites plus an electrode placed over the right mastoid were referenced to the left mastoid electrode. The data were recorded continuously by a SynAmps amplifier and NeuroScan 4.3 software. Each electrode was rereferenced offline to the algebraic average of the left and right mastoids. Impedances of these electrodes never exceeded 5 kV. The horizontal electro-oculogram (HEOG) was recorded from a bipolar montage with electrodes placed 1 cm to the left and right of the external canthi. The vertical electro-oculogram (VEOG) was recorded from a bipolar montage with electrodes placed above and below the right eye. The EEG was amplified by a Synamp’s amplifier digitized at a rate of 500 Hz and filtered during the offline analysis with a band pass of 0.01– 30 Hz. EEG epochs containing EOG activity were detected by wavelet analysis and were corrected using a regression method in the time domain (Semlitsch, Anderer, Shuster, & Presslich, 1986). ERPs were extracted by averaging trials separately for participants, electrodes, and experimental conditions. ERP data were analysed for correct responses only by computing the mean amplitude in selected latency windows. The analysis period was 1,400 ms, starting from the onset of the word or nonword stimuli. The preceding 100-ms period

was used as a prestimulus baseline. ANOVAs were used for all statistical tests and were carried out with the Greenhouse –Geisser correction for sphericity departures (Geisser & Grenhouse, 1959). To explore the potential topographic differences, the electrodes were split on the basis of their spatial dimension (caudality: anterior vs. posterior). ANOVAs for ERPs used a repeated measures design taking the following variables as factors: lexicality (words vs. nonwords); type of word (compounds vs. noncompounds); headedness; and caudality (anterior vs. posterior regions). For the two levels of the variable caudality, we chose seven anterior electrode positions (Fp1, F3, Fc3, Fz, Fp2, F4, Fc4) and seven posterior positions (C3, Cp3, P3, Pz, C4, CP4, P4). Significant interactions between experimental variables were clarified either by breaking them into simple effects or by means of post hoc comparisons.

Results Behavioural data Analyses were conducted by participants (F1) and by items (F2). Moreover the minF (F 0 ) was also calculated (Raaijmakers, Schrijnemakers, & Gremmen, 1999). There was a significant main effect of lexicality on RTs, F1(1, 17) ¼ 55.26; p , .001; F2(1, 27) ¼ 86.60; p , .001; F 0 (1, 36) ¼ 33.73; p , .001: Participants responded more quickly to real words (915 ms) than to nonwords (1,226 ms). The main effect of type of word was also significant, F1(1, 17) ¼ 137.32; F2(1, 27) ¼ 52.68; p , .01; F 0 (1, 42) ¼ 38.07; p , .001: RTs were longer for compounds (1,154 ms) than for noncompounds (986 ms). No main effect of headedness was found, F1(1, 17) ¼ 9.70; p , .05; F2(1, 27) , 1; ns; F 0 (1, 31) , 1; ns. Table 2 summarizes the mean reaction times for the four experimental conditions for both words and nonwords. Error rates showed a main effect of lexicality, F1(1, 17) ¼ 12.00; p , .001; F2(1, 27) ¼ 7.40; p , .01; F 0 (1, 44) ¼ 4.57; p , .05: They were lower for nonwords (7.45%) than for words (13.55%). The only other significant difference was a lower COGNITIVE NEUROPSYCHOLOGY, 0000, 00 (0)

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Table 2. Mean reaction times for the four experimental conditions Condition Left-headed compounds (Nn) Right-headed compounds (nN) Left-embedded word noncompounds (NC1) Right-embedded word noncompounds (NC2)

Word

Nonword

999 (360)

1,268 (424)

985 (343)

1,364 (497)

826 (287)

1,153 (439)

847 (312)

1,119 (411)

Note: Standard deviations in parentheses. Reaction times in ms.

error rate for noncompounds (5.85%) than compounds: 15.13%; F1(1, 17) ¼ 69.93; p , .001; F2(1, 27) ¼ 38.93; p , .001; F 0 (1, 44) ¼ 25.01; p , .001. Higher accuracy for nonwords than for words was unexpected. Therefore, an analysis was done to examine whether this discrepancy reflected the participants’ lack of familiarity with a few of the compounds, the category of items that seemed more susceptible to errors. However, an item analysis revealed that it was not the case that errors concentrated on a small group of compounds. It is possible that our participants were unsure about whether the compounds existed in Italian, despite being relatively familiar with the meaning of these words. To assess the contribution of familiarity and age of acquisition (two variables that were unbalanced in our words), we carried out an analysis of covariance (ANCOVA), entering item means as the dependent variable. The ANCOVA yielded the same results. ERP data The traces presented in Figure 2 show the grand average potentials recorded at the midline electrodes (Fz, Cz, and Pz). The ERPs elicited by compound words and nonwords are superimposed on the left side, and the ERPs elicited by noncompound words and nonwords are superimposed on the right side. As shown in the figure, within the initial 270 ms, words and nonwords elicited similar N1-P2 complexes whether they were compounds or noncompounds. A negative component was then elicited, between 300 and 500 ms,

10


followed by a late positive shift with onset latency around 600 ms. These two effects are very similar to the N400 and P600 components reported in previous language studies. Moreover, the direct comparison between compound and noncompound words seems to reveal a negative difference, starting around 270 ms, which is larger for compound than for noncompound words and is distributed around the anterior sites (see Figure 3). This effect can be related to the LAN component. Most interestingly, Figure 4 shows a larger positive component for rightthan for left-headed compounds, peaking at around 300 ms and distributed around the posterior sites. This first positive peak was followed by a second positivity, with the same polarity (more positive for right-headed compound words) and distribution (around the posterior sites) as the first, but being more extended (between 500 and 800 ms). These two positivities can be related to components of the P300 family. In contrast, the ERPs elicited by left- and rightword-embedded noncompounds did not differ (see Figure 5). In order to examine these effects in further detail, five latency ranges of main interest were distinguished, both from visual inspection of the ERP traces and from comparison with previous results available in the literature: the 0 – 270-ms interval, to test the N1-P2 complexes; the 270 –370-ms and 370– 500-ms intervals, to test the LAN and the N400 components, respectively; and the 310 –360-ms and 500 –800-ms intervals, to test the components of the P300 family and P600. Table 3 summarizes the results of the analyses performed in these successive latency bands. 0 –270 ms. The ANOVA revealed no significant main effects or interactions (all Fs , 1). 270 –370 ms. The analysis shows a main effect of lexicality, F(1, 17) ¼ 13.92, p , .001: Nonwords elicited a larger negativity than did words. There was also a main effect of type of words, F(1, 17) ¼ 5.74, p , .05, with compounds eliciting a larger negativity than noncompounds.



Figure 2. Grand average event-related potentials (ERPs) recorded in the lexical decision task at midline electrodes (Fz ¼ frontal; Cz ¼ central, Pz ¼ parietal). ERPs are compared between words and nonwords for compounds (left panel) and noncompounds (right panel). Amplitude (mV) is represented on the ordinate, with negative voltage up, and time (ms) on the abscissa.

Moreover, the ANOVA showed a significant Type of Word Caudality interaction, F(1, 17) ¼ 10.30, p , .005, reflecting differences between types of word only at the anterior sites, F(1, 17) ¼ 11.07, p , .005, and not at the posterior sites (F , 1). Neither a main effect nor interactions were found for headedness in this latency range.

310 –360 ms. This epoch is included in the larger epoch analysed previously (270 –370 ms). As in our previous analysis, the ANOVA showed similar effects of lexicality, F(1, 17) ¼ 13.53, p , .001, type of words, F(1, 17) ¼ 5.20, p , .05, and Type of Word Caudality interaction, F(1, 17) ¼ 10.53, p , .005. However, unlike in the previous analysis, an interaction between lexicality COGNITIVE NEUROPSYCHOLOGY, 0000, 00 (0)

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EL YAGOUBI ET AL.

Figure 3. The grand average event-related potentials (ERPs) obtained for the compound and noncompound stimuli, which were recorded from 16 selected scalp sites, are overlapped. Recording from central electrodes (Cz) is enlarged at the bottom of the figure. Amplitude (mV) is represented on the ordinate, with negative voltage up, and time (ms) on the abscissa.

and headedness was found, F(1, 17) ¼ 5.12, p , .05. To further track this interaction, separate ANOVAs were conducted for words and nonwords. The ANOVAs on word ERPs revealed a main effect of headedness, F(1, 17) ¼ 5.13, p , .05, Type of Word Headedness, F(1, 17) ¼ 8.23, p , .01, and Type of Word Headedness Caudality interactions, F(1, 17) ¼ 2.24, p , .05; results did not reach significance with nonwords (Fs , 1). Follow-up analyses demonstrated that the interactions observed with words were due to the right-headed compound words producing a

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more positive P300 response than the leftheaded compound words over the posterior sites, F(1, 17) ¼ 4.63, p , .05 (see Figure 4). Such a difference was not observed with noncompound words (Fs , 1; see Figure 5). 370 –500 ms. The ANOVA showed that the main effect of lexicality was significant, F(1, 17) ¼ 41.28, p , .001: Nonwords elicited a larger N400 component than did words. The main effect of type of words was not significant but the Lexicality Type of Word interaction was significant,



Figure 4. The grand average event-related potentials (ERPs) obtained for left- and right-headed compound stimuli, which were recorded from 16 selected scalp sites, are overlapped. Recording from parietal electrodes (Pz) is enlarged at the bottom of the figure. Amplitude (mV) is represented on the ordinate, with negative voltage up, and time (ms) on the abscissa.

F(1, 17) ¼ 7.30, p , .05. As can be seen in Figure 2, the N400 lexicality effect was larger for noncompounds, F(1, 17) ¼ 34.70, p , .001, than for compounds, F(1, 17) ¼ 7.64, p , .05. 500 –800 ms. Analyses of this epoch showed that there were differences between words and

nonwords, F(1, 17) ¼ 77.06, p , .001, with nonwords being associated with more positive voltages than words. Moreover, the ANOVA revealed two interactions: Lexicality Type of Word, F(1, 17) ¼ 3.34, p , .05, and Lexicality Headedness, F(1, 17) ¼ 9.48, p , .01. As in the preceding 310 –360-s epoch, words and nonwords were COGNITIVE NEUROPSYCHOLOGY, 0000, 00 (0)

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Figure 5. The grand average event-related potentials (ERPs) obtained for left- and right-embedded noncompound stimuli, which were recorded from 16 selected scalp sites, are overlapped. Recording from parietal electrodes (Pz) is enlarged at the bottom of the figure. Amplitude (mV) is represented on the ordinate, with negative voltage up, and time (ms) on the abscissa.

analysed separately. The ANOVA on word ERPs revealed a main effect of type of word, F(1, 17) ¼ 2.40, p , .05: Noncompound words elicited a larger positivity than did compound words. There was also a main effect of Headedness, F(1, 17) ¼ 14.30, p , .001, and an interesting interaction between type of word and headedness,

14


F(1, 17) ¼ 4.46, p , .05. As in the preceding 310 –360-s epoch, follow-up analyses revealed that this interaction was due to the right-headed compound words producing a larger positivity than the left-headed compound words, F(1, 17) ¼ 6.07, p , .05. However, there was no difference between left- and right-word-embedded



Table 3. Summary of results regarding the effects of the different factors in the different latency ranges Latency range (ms)

A

B

AB

C

AC

BC

ABC

D

AD

BD

CD

BCD

ABCD

0–270 270– 370 370– 500 310– 360 500– 800

2 þ þ þ þ

2 þ 2 þ 2

2 2 þ 2 þ

2 2 2 2 2

2 2 2 þ þ

2 2 2 2 2

2 2 2 2 2

2 2 2 2 2

2 2 2 2 2

2 þ 2 þ 2

2 2 2 2 2

2 2 2 2 2

2 2 2 2 2

Note: þ ¼ significant effect ( p , .05). 2 ¼ nonsignificant effect. A ¼ lexicality (words/nonwords). B ¼ type of word (compounds/noncompounds). C ¼ headedness (left-headed/right-headed compounds). D ¼ caudality (anterior/posterior).

noncompounds. Finally, an ANOVA on nonwords revealed no significant main effects or interactions during this epoch (Fs , 1).

Discussion The goal of the present study was to investigate the neurophysiological correlates of Italian noun –noun compounds. In particular, the aim was to understand whether compound words differ significantly from noncompound words at the neural level and to determine which ERP components could reveal this difference. One innovative aspect of this study is the exploration of the headedness effect, undertaken by contrasting Italian left-headed and right-headed compounds. We first discuss the behavioural results (RTs and error rates) and electrophysiological results related to word/nonword differences. We then consider the difference between compound and noncompound nouns, before finally analysing the role of the morphological and semantic heads embedded in compound nouns. The word/nonword effect on RTs is consistent with the effect observed on ERPs. As in previous studies, nonwords are associated with longer RTs and with larger N400 negativity than are words (Bentin, Kutas, & Hillyard, 1995; Bentin, McCarthy, & Wood, 1985; Holcomb, 1988, 1993; Holcomb & Neville, 1990; Kounios & Holcomb, 1994). N400 is not believed to be associated with visual mechanisms devoted to letter processing, but rather with a higher level mechanism devoted to word processing. The

difference in N400 for nonwords might reflect a search within the lexico-semantic memory, which is particularly demanding for nonwords that lack lexico-semantic representations (Attias & Pratt, 1992; Friedrich et al., 2006; Picton & Hillyard, 1988; Supp et al., 2004). In the present experiment, an interesting interaction was observed between Lexicality and Type of Word within the N400 component (specifically, in the 370 –500-ms window). This interaction reflected a larger N400 lexicality effect for noncompound words than for compound words. Our result may be related to the presentation of nonwords created by inverting the component words (see Method section). Crucially, the nonwords derived from compound words contained two real words, as in the nonword spadapesce, which was obtained from the compound pescespada (swordfish) by switching the constituents pesce (fish) and spada (sword). Participants may access the meaning of both constituents as a result of a decomposition process; this in turn would mitigate the impact of the linguistic difference between words and nonwords in the compound-noun category. In contrast, for nonwords derived from noncompounds (e.g., forosema, obtained from semaforo, traffic lights) one of the two components (sema) has no meaning. This difference in stimulus composition may account for the larger N400 lexicality effect observed with nonwords derived from noncompound words: As they deviated more noticeably from familiar words, they generated a greater N400 response. The difference between compounds and noncompounds is also observed in behavioural data: COGNITIVE NEUROPSYCHOLOGY, 0000, 00 (0)

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EL YAGOUBI ET AL.

Longer RTs and higher error rates were found for compounds than for noncompounds. This effect is probably due to the fact that compounds require a greater involvement of cognitive resources, which are recruited to access not only the whole word, but also its constituents. This interpretation is further confirmed by the ERP results. Within the 270 –370-ms time window, increased negativity was observed in the anterior areas for compounds compared to noncompounds. The increased negativity for compounds is likely to be linked to LAN. As explained in the Introduction, the LAN component has been associated with the initial morphosyntactic processing (Friederici, 1995, 2001) needed to detect potential errors; however, some authors have suggested that LAN reflects an increased working-memory load (Coulson et al., 1998; Kluender & Kutas, 1993). The finding that the LAN amplitude was more negative for compounds (than for noncompounds) might be explained by the formation of a morphosyntactic representation of the constituents. LAN modulation has also been noted in the two ERP papers on German compound processing, and it has been taken as evidence of compound decomposition during comprehension (Koester et al., 2007; Koester et al., 2004). The LAN effect observed in our study provides a critical piece of evidence against full-listing models and in favour of decomposition or dualroute models of compound processing. The difference between compounds and noncompounds also appears in a later temporal window (starting at 500 ms) and is due to a greater amplitude and a more positive-going peak for noncompounds. Such positivity can be interpreted as a P600 component. P600 has been associated with syntactic processing and the repair or reanalysis of syntactic violations (Coulson et al., 1998; Friederici, 2002; Friederici et al., 1996; Neville et al., 1991; Osterhout et al., 1996) although it can also be elicited by nonpreferred syntactic structures (Coulson et al., 1998; Friederici, 2002; Neville et al., 1991) and seems to be more susceptible to controlled processes than are earlier components (Hahne & Friederici, 1999). The cause of the positive shift

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we observed for noncompound nouns as opposed to compound nouns can be attributed to the particular nature of the stimuli used in our experiment. A decomposition strategy would lead to the detection of, for example, the word cocco (coconut) embedded in the word stimulus coccodrillo (crocodile), which also contains the nonword drillo. This may generate ambiguity and perhaps induce a double checking of the lexical status of nonwords like drillo. Some reanalysis, entailing more demanding processes, may therefore be necessary. Noncompound nouns like coccodrillo may, as a consequence, elicit a greater P600 amplitude than do compound nouns. Concerning the comparison between left- and right-headed compounds, behavioural results indicated that there was no difference (either in RTs or error rates) between these two conditions. However, ERP data showed a difference between these compounds within a particular time window—that is, starting at 310 ms up to 800 ms. In particular, right-headed compounds showed a more positive peak than left-headed compounds, and the effect was clearly localized in the posterior area. Interestingly, this difference is not present between left- and right-wordembedded noncompounds. The increase in positivity elicited by right-headed compounds can be related to the P300 component. Our finding of a significant difference between left- and rightheaded compounds at P300 indicates that the compound head is a relevant element, at least concerning the electrophysiological activity of the brain. Regarding the functional significance of polarity (with a more positive-going peak for rightthan for left-headed), different interpretations could be considered. First, left- and rightheaded compounds can differ in terms of the amount of attentional resources that they require. Indeed, the amplitude of P300 varies according to the amount of attentional resources invested in processing relevant stimuli (see Bashore & Van der Molen, 1991; Kok, 2001, for reviews). Another interpretation may be related to the fact that Italian left-headed compounds have a relatively more canonical order than right-headed compounds. Left-headed compounds reflect the



order of grammatical classes normally found in Italian sentences, where the noun precedes the modifier. In contrast, right-headed compounds are the marked case, and, though productive, they do not reproduce the canonical order because they originated from an ancient language (Latin) or were built on imitation of words from other contemporary languages (most frequently from English, which only has right-headed compounds). It is thus possible that right-headed compounds require more attentional resources to be processed. A third interpretation is related to the context-updating theory (Donchin & Coles, 1988). According to this theory, the amplitude of the P300 is thought to reflect the processes by which information is updated in working memory as a function of incoming, contextually relevant information. One can speculate that in a language like Italian that has two positional options, updating takes place with the rightheaded compounds. That is, the left component is “automatically” recognized as the head, but its information needs to be updated when the right component is processed and recognized as the proper head. This would result in an increase of the P300 amplitude. Such an increase would not occur with left-headed compounds because no update is needed with these words.

Conclusions In sum, a number of potentially interesting results emerged from this investigation. Indeed, we reported several specific time-linked electrophysiological correlates of compound processing. Further neurophysiological evidence was obtained that compounds behave differently from noncompounds. There were two types of evidence demonstrating a difference between compounds and noncompounds: (a) a larger N400 lexicality effect for noncompounds and (b) a modulation of the morpho-syntactic components (LAN and P600) observed only with compounds. Our electrophysiological findings converge with those reported by Koester and coworkers (Koester et al., 2007; Koester et al., 2004), even though the two studies investigated lexical decision in

different modalities (visual vs. auditory). Our findings are also in line with data from lesion studies. It is noteworthy that in our study the headedness effect was successfully distinguished from the position effect for the first time. This result was not obtained in lesion studies and, while perhaps strongly suggested by their results, was not demonstrated by Koester and coworkers, since German does not allow the same control of head position that is possible in Italian. Whether the P300 component modulation found in the present experiment could be better interpreted in terms of allocation of attentional resources or in terms of working-memory processing remains a matter of speculation and is in need of further investigation, through ERPs or neuroimaging. As reported in the Introduction, the regularity of head position determined with the rightmost element rule reduces the information stored at a representational level to a minimum. In languages where the head can be on the left, components like P300 may be markers of processes involving the head. In conclusion, it is important to emphasize that the finding of specific electrophysiological correlates associated with the processing of the compound head is not necessarily expected. The concept of compound head stems from theoretical linguistics, and the information contained in it may not impose different processing demands from the information contained in the modifier. Our neurophysiologically grounded findings instead show that the information contained in compound heads may constrain the way in which our brain processes compounds. Manuscript received 12 December 2006 Revised manuscript received 2 October 2007 Revised manuscript accepted 8 January 2008 First published online day month year

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APPENDIX List of the experimental stimuli Nn, left-headed compounds; nN, right-headed compounds; NC1, noncompounds with a real word embedded on the left side of the whole word; NC2, noncompounds with a real word embedded on the right side of the whole word (letter strings corresponding to real Italian words are underlined and translated).

Compounds

Type Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn Nn nN nN nN nN nN nN nN nN nN

Stimulus Acquavite Arcobaleno Bancoposta Boccaporto Bordovasca Burrocacao Calzamaglia Camposcuola Capobanda Ceralacca Finecorsa Focamonaca Fondovalle Girocollo Gommapiuma Granoturco Grillotalpa Melograno Metroquadro Padrefamiglia Parcomacchine Pastafrolla Pescespada Pianoterra Prezzobase Retrobottega Roccaforte Toporagno Aliscafo Architrave Astronave Audiofrequenza Barbabietola Broncospasmo Calciomercato Cartamoneta Crocevia

Translation

Translation of stimulus constituents

Brandy Rainbow [lit.] Counter post (the post office counter) Hatchway [lit.] The edge of a swimming pool Lipsalve Tights School camp Band leader Sealing wax Terminal station Monk seal Valley bottom Round neck Foam rubber Maize Mole cricket Pomegranate Square metre [lit.] The head of the household [lit.] The company fleet of cars Short pastry Swordfish Ground floor Starting price Backshop Fortress Shrew Hydrofoil Lintel Spaceship Audio-frequency Beet Bronchospasm [lit.] Soccer market Paper money Crossroads

acqua (water); vite (grapes) arco (bow); baleno (lightning) banco (counter); posta (post) bocca (mouth); porto (harbor) bordo (edge); vasca (basin) burro (butter); cacao (cocoa) calza (sock); maglia (knitting) campo (camp); scuola (school) capo (leader); banda (band) cera (wax); lacca (lake) fine (end); corsa (run) foca (seal); monaca (monk) fond (bottom); valle (valley) giro (round); collo (neck) gomma (rubber); piuma (feather) grano (grain); turco (Turkish) grillo (cricket); talpa (mole) melo (apple tree); grano (grain) metro (metre); quadro (square) padre (father); famiglia (family) parco (park); macchine (cars) pasta (dough); frolla (butter dough) pesce (fish); spada (sword) piano (floor); terra (ground) prezzo (price); base (base) retro (back); bottega (shop) rocca (rock); forte (fort) topo (mouse); ragno (spider) ali (wings); scafo (hull) archi (bows); trave (beam) astro (star); nave (ship) audio (audio); frequenza (frequency) barba (beard); bietola (chard) bronco (broncho); spasmo (spasm) calcio (soccer); mercato (market) carta (paper); moneta (money) croce (cross); via (road)

(Continued overleaf )


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Table 3. (Continued)

Type nN nN nN nN nN nN nN nN nN nN nN nN nN nN nN nN nN nN nN

Stimulus

Translation Shower gel Mud therapy Ferroalloy Trolley bus Fluid dynamics Picture story Lieutenant Motherland World vision Jack-pot Chain saw Nanosecond Poultry farming Running commentary Power steering Earthquake Fibre-glass plastic Videogame Zoo technology

Docciaschiuma Fangoterapia Ferrolega Filobus Fluidodinamica Fotoromanzo Luogotenente Madrepatria Mondovisione Montepremio Motosega Nanosecondo Pollicoltura Radiocronaca Servosterzo Terremoto Vetroresina Videogioco Zootecnica

Translation of stimulus constituents doccia (shower); schiuma (foam) fango (mud); terapia (therapy) ferro (iron); lega (league) filo (yarn); bus (bus) fluido (fluid); dinamica (dynamics) foto (photograph); romanzo (romance) luogo (place); tenente (tenant) madre (mother); patria (land) mondo (world); visione (vision) monte (mountain); premio (prize) moto (motor); sega (saw) nano (nano); secondo (second) polli (chickens); coltura (farming) radio (radio); cronaca (commentary) servo (servant); sterzo (steering) terre (lands); moto (motion) vetro (glass); resina (resin) video (video); gioco (game) zoo (zoo); tecnica (technology)

Noncompounds Type

Stimulus

NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1 NC1

Barracuda Cavaliere Clorofilla Coccodrillo Collaudo Cremagliera Filastrocca Filosofo Formalina Funerale Gelosia Maleficio Maresciallo Melanoma Melodia Mercenario Meteorite Oratore Paladino Pappagorgia Pastorizia Pellegrino Peperone

Translation Barracuda Horse-rider Chlorophyll Crocodile Test/inspection Rack Rigmarole Philosopher Formalin Funeral Jealousy Spell Marshal Melanoma Melody Mercenary Meteorite Orator Paladin Double chin Sheep farming Pilgrim Pepper

Translation of the embedded word barra (bar) cava (mine) cloro (chloro) cocco (coconut) colla (glue) crema (cream) fila (row) filo (yarn) forma (shape) fune (cable) gelo (chill) male (ill) mare (sea) mela (apple) melo (apple-tree) merce (goods) meteo (weather-report) ora (hour) pala (shovel) pappa (baby-food) pasto (meal) pelle (skin) pepe (pepper)

(Continued overleaf )

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Table 4. (Continued) Type

Stimulus

NC1 NC1 NC1 NC1 NC1 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2 NC2

Polpastrello Pontefice Salamandra Serratura Temperatura Accidente Accredito Catafalco Catastrofe Dirigente Discepolo Fazzoletto Imbarazzo Logaritmo Mandragola Marzapane Megalite Patriarca Pavimento Pentecoste Pirofila Prezzemolo Pugilato Recidiva Requisito Rotocalco

NC2 NC2 NC2 NC2 NC2 NC2 NC2

Scarafaggio Schiamazzo Semaforo Tartaruga Varicella Vegetale Virulenza

Translation

Translation of the embedded word

Pulp Pontiff Salamander Lock Temperature Accident Crediting/credit Catafalque Catastrophe Manager/director Disciple Handkerchief Embarrassment Logarithm Mandrake Marzipan Megalith Patriarch Floor Pentecost Oven-proof dish Parsley Boxing Relapse Requirement Illustrated magazine Cockroach Din Traffic light Tortoise Chickenpox Vegetable Virulence

polpa (pulp) ponte (bridge) sala (hall) serra (greenhouse) tempera (distemper) dente (tooth) dito (finger) falco (hawk) strofe (strophes) gente (people) polo (pole) letto (bed) razzo (rocket) ritmo (rythm) gola (throat) pane (bread) lite (quarrel) arca (arch) mento (chin) coste (coasts) fila (row) molo (pier) lato (side) diva (goddes) sito (site) calco (impression) faggio (beech tree) mazzo (bunch) foro (hole) ruga (wrinkle) cella (cell) tale (someone) lenza (fishing-line)


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