El Yagoubi et al Compounds CNP

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Neural correlates of Italian nominal compounds andpotential impact of headedness effect: An ERP studyRadouane El Yagoubi a; Valentina Chiarelli ab; Sara Mondini c; Gelsomina Perroned; Morena Danieli a; Carlo Semenza aa University of Trieste, Trieste, Italyb CIMEC (Centro Interdipartimentale Mente/Cervello), University of Trento, Trento,Italyc University of Padova, Padova, Italyd University of Milano-Bicocca, Milano, Italy

First Published on: 01 March 2008To 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, 1To link to this article: DOI: 10.1080/02643290801900941URL: http://dx.doi.org/10.1080/02643290801900941

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

Radouane El YagoubiUniversity of Trieste, Trieste, Italy

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

Sara MondiniUniversity of Padova, Padova, Italy

Gelsomina PerroneUniversity of Milano-Bicocca, Milano, Italy

Morena Danieli and Carlo SemenzaUniversity of Trieste, Trieste, Italy

An event-related potential (ERP) technique was used to investigate the way in which noun–nouncompounds are processed during a lexical decision task with Italian speakers. Reaction times anderror rates were higher for compounds than for noncompounds. ERP data showed a more negativepeak in the left anterior negativity (LAN) component for compounds. These results are compatiblewith a dual-route model that posits not only whole-word access for compounds but also an activationof 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. Whilebehavioural analysis did not reveal a difference between left- and right-headed compounds, a differ-ence was found with the P300 component. The role of the compound head as a crucial information-bearing component is discussed.

Keywords: Noun-noun compounds; Headedness effect; ERPs; LAN component.

Compounding is an important and productiveprocess in most languages. The study of how com-pound words are represented and processed mayprovide important insights into the way in which

the human mind stores, organizes, and accessesmultimorphemic words. However, compared toother morphological processes, like inflection andderivation, 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 1http://www.psypress.com/cogneuropsychology DOI:10.1080/02643290801900941

COGNITIVE NEUROPSYCHOLOGY, iFirst, 1–23

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compounds as well as their neurologicalimplementation have received less attention inpsycholinguistic and neuropsychological investi-gations. For over a quarter of a century, psycholin-guistic research has focused on how inflected,derived, and compound words are stored in themind. The main question is whether multimor-phemic words are stored in the mental lexicon intheir full form or whether only their morphemesare stored and then combined to form complexwords. Accordingly, two competing classes of the-ories have been proposed supporting either theformer or the latter alternative: the so-called“full-listing” theories (Butterworth, 1983; Bybee,1995) and the so-called “decomposition” or “full-parsing” theories (Libben, Derwing, & deAlmeida, 1999; McKinnon, Allen, & Osterhout,2003; Taft, 2004; Taft & Forster, 1976). Morerecently, however, a class of so-called “dual-route” theories has gained ground, which is a com-promise between the other two views. Dual-routetheories assume that a complex word can be eitherstored as a whole or be decomposed into its mor-phological constituents (there are several variantsof this view, e.g., Baayen, Dijkstra, & Schreuder,1997; Caramazza, Laudanna, & Romani, 1988;Isel, Gunter, & Friederici, 2003; Sandra, 1990;Zwitserlood, 1994). Dual-route theories naturallyraise several questions about exactly what sort ofcomplex words are preferentially used via oneroute rather than the other. For example, thesetheories propose that very frequently used itemsand, in the particular case of compounds, opaqueitems would be stored and processed more effi-ciently in their full form; in contrast, less frequentitems and transparent compounds would besubject to decomposition.

Most works concerning morphologicaldecomposition have been conducted on inflectedand derived words. However, a number of investi-gations on compound decomposition in both thevisual and the auditory modalities have appearedin 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

interest in the topic, an entire book was recentlydevoted to the representation and processing ofcompound words (Libben & Jarema, 2006).

Although most of the neuropsychologicalstudies devoted to morphology have been con-cerned with inflection and derivation (Badecker& Caramazza, 1987; Coltheart, 1980; De Bleser& Bayer, 1990; Patterson, 1980; Semenza,Butterworth, Panzeri, & Ferreri, 1990), a fewstudies have focused on compounds (seeSemenza & Mondini, 2006, for a review, andChiarelli, Menichelli, & Semenza, 2007, forupdating). These investigations were carried outusing tasks like picture naming, word repetition,reading, and, less frequently, writing. On thewhole, evidence was found in support of full-parsing models (Semenza, Luzzatti, & Carabelli,1997) and dual-route models (Mondini, Jarema,Luzzatti, Burani, & Semenza, 2002) rather thanfull-listing models. For example, in studies con-ducted in Italian (Mondini, Luzzatti, Saletta,Allamano, & Semenza, 2005; Semenza et al.,1997), aphasics who had more severe problemswith verbs (mostly of the Broca’s type) wereshown to drop the verb component in verb–noun compounds (e.g., “portamonete”: literally“carry-coins”, purse). This effect was not deter-mined by position, since it did not hold fornoun–noun compounds. However, Italian verb–noun compounds are nouns. If verb–noun com-pounds were not decomposed during processing,aphasics with greater difficulties for verbs wouldnot preferentially omit the verb component. Thisfinding constitutes one of the strongest pieces ofevidence in favour of decompositionality.

The specific characteristics of morphology ineach language could offer promising opportunitiesto study compound processing and the effect ofvariables such as productivity (for a thoroughreview, see Jarema, 2006). The present studyinvestigates the processing of compounds in thebrain, focusing on headedness. The study is con-ducted in Italian, where rules governing headed-ness provide a good opportunity for investigatingcompound processing. The “head” of a compoundis the component determining the lexical category,the syntactic features (e.g., number and gender),

2 COGNITIVE NEUROPSYCHOLOGY, 0000, 00 (0)

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and the semantic traits of the whole compound.The grammatical and logical head of compoundsis the rightmost element in Germanic languageslike English (but also in Finnish, Greek,Bulgarian, and Polish, just to mention a fewother languages on which psycholinguisticresearch about headedness has been conducted).The regularity of the position of the head, deter-mined with this rule, reduces the informationstored at a representational level to a minimum:“It is an XN compound”, where X may be anoun, an adjective, a verb, and so on. In otherlanguages, like Italian and French, compositionis 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 speak-ers are familiar with both kinds of compounds.Diachronically, left-headed compounds appearedat an earlier time. Moreover, they respect thecanonical order for lexical categories in Italian:noun þ modifier. In contrast, right-headed com-pounds are generally derived from other languages,mostly either from Latin or, nowadays, fromEnglish. However, right-headed compounds areincreasingly productive in contemporary Italian,as documented by the expanding number of nNneologisms and by their growing frequency ofuse (Schwarze, 2005).

The study of headedness is complicated becauseit must take into account the position of the headin the compound string. In fact, assuming thatcompounds can be processed in a decomposedfashion, the processing of the compound constitu-ents must be expected to be crucially influenced bytheir position. Position-in-the-string effects haveindeed been considered in the literature. Forinstance, Taft and Forster (1976) suggested that,in English, initial constituents of polymorphemicwords may play a more important role in lexical

access than do the second constituents. In contrast,Lima and Pollatsek (1983) found no clear con-stituent-specific access. The compound constitu-ent position and the compound headedness musteventually be teased apart to fully evaluate theirrespective influence on compound processing. Sofar, this has not proven to be an easy task. It isindeed known from studies on healthy participantsthat the position within the compound interactswith morphological headedness in compound pro-cessing (Jarema et al., 1999; Kehayia et al., 1999;Libben, Gibson, Yoon, & Sandra, 2003). Forinstance, Jarema et al. (1999) contrasted the roleof headedness in French, in which head positionvaries, and English, in which head position isfixed—a comparison that would enable the disen-tanglement of the effects of position versus head-edness. Using a priming paradigm in the lexicaldecision task, they showed a stronger primingeffect for the initial constituents than for thefinal constituents of left-headed compounds inFrench. By contrast, no difference was observedbetween compound constituents in English, alanguage in which compounds are right-headed.It was hard, on the basis of these findings, tofully disentangle effects due to headedness fromeffects due to position.

Effects associated with the position of com-pound constituents have also been shown in apha-siological studies. For example, Ahrens (1977), ina study on German-speaking aphasics, observedthat when only one part of the compound was suc-cessfully produced it was usually the first com-ponent (in German compounds, the first and thesecond component are the head and the modifier,respectively). This effect, however, was not repli-cated in other group studies of German aphasics(Blanken, 2000; Hittmair-Delazer, Andree,Semenza, De Bleser, & Benke, 1994). In a studyconducted in Italian, Chiarelli et al. (2007)

1 Other Italian compounds (i.e., verb–noun compounds, the most productive type in Italian) have an exocentric structure. In exo-

centric 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) 3

PROCESSING OF ITALIAN NOUN–NOUN COMPOUNDS

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found different results with patients affected byearly Alzheimer’s disease and aphasia. Patientswith Alzheimer’s disease omitted and substitutedthe second component more often than the firstone when producing a variety of compoundstimuli. By contrast, aphasia patients made moreerrors with the first component. The tentativeinterpretation that the authors offered for theirresults is that the second component is more sen-sitive to factors like processing overload than is thefirst component. Chiarelli et al. (2007) acknowl-edged that in their study, as in prior aphasiologicalresearch, headedness and component positionswere confounded and that various methodologicalconstraints prevented the disentangling of theeffects of each of these variables. One constraintwas the limited number of depictable compoundssuitable for this kind of investigation. Anotherconstraint was that the number of critical errorsobtained from each participant in reading and rep-etition tasks was seldom sufficient to draw clear-cut conclusions, and group studies naturally tendto suffer from lack of homogeneity. For thesereasons the possible effect of headedness has sofar remained elusive in neuropsychologicalresearch. However, the issue of headednesscannot be ignored. Progress in understandinghow word combination is represented and pro-cessed in the brain must include an understandingof the specific role of compound heads.

Were the head in the same position in alllanguages, it would be very hard to distinguishwhat is simply due to processing order and whatis due to the semantic and syntactic factors thatdistinguish the head from the nonhead com-ponents. However, the existence of both right-and left-headed compounds in Italian allows anexperimental manipulation of head position thatis not possible in languages that only have right-headed compounds. This feature of Italian motiv-ated the present investigation of the role of head-edness in compounds.

The study aims at investigating the neural cor-relates of compounds and the potential impact ofheadedness on the time-course of compound pro-cessing. We approached these issues by examiningthe temporal resolution and spatial localization of

event-related potentials (ERPs) in response tocompound stimuli. As ERPs are differentially sen-sitive to the various types of information andprovide a continuous measure of word processing,this method seems particularly suited to anexploration of the issues at hand. Before turningto the experimental design, we first need to intro-duce some of the previous ERP studies onlanguage processing focusing on the ERP com-ponents that are relevant to the presentinvestigation.

ERP studies have reported many different elec-trophysiological components associated with thelexical access that occurs during comprehensionof written words. In their recent review, Barberand Kutas (2007) identified several componentsimplicated in a fast and automatic word recog-nition process taking place within about the first200 ms. For example, Sereno and Rayner (2003)suggest that lexical identification occurs, at leastto a certain degree, between 60 and 150 ms afterword fixation. Moreover, other studies haveshown a lexicality effect (i.e., a differencebetween words and nonwords) in the ERPresponses 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 effectsaround 110–160 ms confirmed this early lexicalaccess (Dambacher, Kliegl, Hofmann, & Jacobs,2006; Hauk, Davis, Ford, Pulvermuller, &Marslen-Wilson, 2006; Hauk & Pulvermuller,2004). The P300 family component is anotherERP component observed in a variety of tasks.P300 is a positive component that typicallyshows a centro-parietal scalp distribution withmaximum amplitude around 300 ms poststimulusonset. Some authors distinguish between an earlyand a late P300 (peaking between 600 and800 ms after stimulus onset; Hill, Ott, &Weisbrod, 2005). A number of factors areknown to influence P300 amplitude, such asstimulus novelty and probability, relevance of thestimulus to the task at hand, the amount of atten-tional resources necessary to perform a task, andstimulus saliency (see Bashore & Van der Molen,1991; Kok, 2001, for reviews). Moreover, many


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studies have revealed that P300 amplitude could bean index of adaptation of working-memory traceswhen unexpected information has to be integratedinto an individual’s model of the environment(context updating theory; Donchin & Coles,1988). Alternatively, P300 amplitude can be seenas an indicator of closure of a perceptual epochor internal template when expectations pertainingto specific stimuli are met (context closure theory;Verleger, 1988).

The N400 component is one of the mostimportant ERP waveforms related to languageprocessing (though not specific to the linguisticdomain). The N400 (Kutas & Hillyard, 1980) isa negative peak with a maximum amplitudearound 400 ms after stimulus onset. It typicallyshows a centro-parietal scalp distribution in thevisual modality and a more frontal distribution inthe auditory modality. It is thought to reflectsemantic integration processes, as its amplitude isespecially large for words that are difficult toanticipate and integrate within a sentencecontext because they are semantically unexpectedor incongruous. However, the N400 has been cor-related not only with aspects of semantic proces-sing in sentence context, but also with thelexico-semantic processing of single words (Kutas& Federmeier, 2000). This conclusion is sup-ported by the finding that the N400 componenthas a more negative amplitude for nonwords (orpseudowords) than words. This effect is assumedto reflect greater demands on a lexico-semanticmemory search for nonwords, since they do nothave 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-semanticintegration process, LAN (left anterior negativity)and P600 components are associated with amorpho-syntactic analysis of linguistic stimuli.LAN occurs approximately in the same timewindow as the semantic N400 effect, but generallyhas a more anterior scalp distribution and is some-times left-lateralized. LAN has specifically beenassociated with the initial morphosyntactic proces-sing (Friederici, 1995, 2001) and has been found inall the studies that used morphosyntactic

violations. Alternatively, it has been proposedthat LAN reflects an increased working-memoryload (Coulson, King, & Kutas, 1998; Kluender& Kutas, 1993). P600, in turn, is a positive com-ponent showing a parietal scalp distribution withmaximum amplitude peaking between 500 and900 ms after stimulus onset. It has been associatedwith syntactic processing and the repair or reanaly-sis 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 susceptibleto controlled processes than earlier components(Hahne & Friederici, 1999).

So far, only a few of the ERP studies that haveappeared in the literature were devoted to com-pounds. In one such study, Koester, Gunter,Wagner, and Friederici (2004) conducted a seriesof experiments in which German compoundswere presented in the auditory modality. Theymanipulated the gender agreement (a) between adeterminer and the initial (nonhead) compoundconstituent and (b) between a determiner andthe last compound constituent (i.e., the head).Although only the head is morphosyntacticallyrelevant in German, both constituents elicitedLAN if the gender was incongruent. Thisfinding, replicated by Koester, Gunter, andWagner (2007), was taken as a strong indicationof morphosyntactic decomposition. There wouldin fact be no congruency effects on the first con-stituents if they were not independently processed,and compounds were not analysed in a decom-posed form.

Unfortunately, because it is not possible tomanipulate head position in German, Koesterand collaborators could not disentangle the contri-butions of head processing and component pos-ition. Therefore previous ERP studies could notprovide information about the specific role of thehead and the neurological underpinning of headprocessing. It is, however, important to determinewhether the compound head, a concept stemmingfrom theoretical linguistics, has a psychologicaland neurological basis. It is also important toascertain whether compound heads are processed



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in the brain differently from the nonhead, modifiercomponents.

In the present study conducted in Italian, ERPand behavioural data were recorded using visuallyrather than orally presented transparent com-pounds in a lexical decision task. As mentionedabove, head positions were manipulated. Thusleft-headed compounds were contrasted withright-headed compounds. An example of a left-headed compound is capobanda, band leader.Capobanda refers to a type of leader, not to atype of band; therefore capo (leader) is the headof this compound. The head also determines thelexical gender; capo is masculine, banda is feminine;thus capobanda is masculine. An example of aright-headed compound is astronave, spaceship,literally “starship”. Astronave is a sort of shiprather than a star; therefore nave (ship) is thehead: Since nave is feminine, astronave is also fem-inine. In order to minimize confounds due totransparency and grammatical class, only transpar-ent, nominal compounds were used. Compoundwords were contrasted with noncompound wordsthat had a real word embedded on their left side(e.g., coccodrillo, crocodile, where cocco meanscoconut, while drillo is a nonword) or on theirright side (e.g., tartaruga, tortoise; where rugameans wrinkle and tarta is a nonword). Nonwordswere generated by exchanging the two real mor-phemes of a compound word (e.g., capobanda !

bandacapo) or by exchanging the two segments of anoncompound word (e.g, coccodrillo ! drillococco).The lack of previous studies on this particulartopic makes it difficult to generate specific predic-tions concerning our results. Therefore, the predic-tions we discuss below are as specific as possible.

As in previous studies, we predict that non-words would be associated with longer reactiontimes (RTs) and with a larger N400 negativitythan are words (Bentin, 1987; Kutas &Federmeier, 2000). Moreover, as suggested byfull-parsing models (e.g., Libben et al., 1999;McKinnon et al., 2003; Taft, 2004; Taft &Forster, 1976), if compound nouns are processedthrough morphosyntactic decomposition, thenthey would be associated with longer RTs thannoncompound nouns. Moreover, if as a result of

decomposition the morphosyntactic features ofthe individual components are analysed, then weshould also observe the LAN and P600 com-ponents that have been shown to be associatedwith morpho-syntactic analysis (see Friederici &Kotz, 2003, for a review). These components areexpected to be differentially affected by com-pounds and noncompounds. Finally, larger P300amplitude for right- than for left-headed com-pounds may indicate an increased use of atten-tional resources or the need to update workingmemory when the crucial information is containedin the second component.

Method

ParticipantsThe task was administered to 20 participants whohad given their informed consent. Because of alarge number of artefacts, the data from 2 partici-pants 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 25years (range ¼ 20–31 years). They were testedindividually, in a single session that lasted abouthalf an hour. All participants were right-handednative Italian speakers. They were neurologicallynormal, not taking specific medication, and hadnormal or corrected-to-normal vision. Visualacuity was checked at the beginning of theexperiment.

StimuliThe experimental items consisted of 112 words(see Appendix), divided into four sets each con-taining 28 items: (a) transparent left-headednoun–noun compounds (e.g., capobanda, bandleader); (b) transparent right-headed noun–nouncompounds (e.g., astronave, spaceship); (c) non-compound nouns with a real word embedded inthe left side of the whole word (e.g., coccodrillo,crocodile, where cocco means “coconut”); (d) non-compound nouns with a real word embedded inthe right side of the word (e.g., tartaruga, tortoise;where ruga means “wrinkle”). The word embeddedon the left or right side of noncompounds was notrelated in meaning to the whole word. Frequency,


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length (number of letters), familiarity, imageabil-ity, and age of acquisition were calculated or col-lected through questionnaires for the compoundand noncompound words.

Obtaining the frequencies of Italian com-pounds is not a trivial task, because existing fre-quency dictionaries rarely include newcompounds—in fact, they include few, if any,compounds. Available frequency dictionaries arebased on written corpora from various textsources (fiction and nonfiction literature, tran-scription of controlled speech, such as academicreports, news, etc.). On the contrary, recent com-pounds tend to be used in the nonformal speech ofeveryday life (e.g., in the language of advertising).Some researchers have solved the problem of cal-culating the frequencies of unseen compounds bysumming the frequencies of the constituents(Jansen, Bi, & Caramazza, 2007). Researchers incomputational linguistics have recently proposedan alternative method that takes advantage of thelarge variety of texts available on the Web. Of par-ticular relevance here, Keller and Lapata (2003)demonstrated that similar frequency counts wereobtained from Web sources and the large textcorpora that were used in the past (e.g., theBrown corpus for English). We adopted asimilar method for determining the frequenciesof our experimental words. Frequencies were cal-culated from a large corpus of over 23 millionwords from newspapers and other text sourcesavailable from Italian Web sites and were log-transformed before being entered in the analysis.

Familiarity, imageability and age of acquisitionwere collected via three different questionnaires

administered to three different groups, each madeup of 30 raters who were native Italian speakersand did not participate in the ERP experiment(see Table 1). The three groups were balancedwith respect to gender, age, and schooling. Thefour item sets included in the experiment werematched 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 comparisonsusing Bonferroni corrections showed a significantdifference only between right-headed compoundsand noncompounds with a word embedded onthe 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 comparisonsdone using Bonferroni correction reached signifi-cance only between right-headed compounds andnoncompounds with a word embedded on theleft, tbonferroni(108) ¼ 2.87; padj ¼ .03.

We tried to match compound and noncom-pound words for length (number of letters).Compounds were slightly longer, on average byabout one letter, F(3, 108) ¼ 10.50; p , . 001.However, there was no difference in lengthbetween left- and right-headed compounds.

A list of nonwords was generated from theexperimental items by exchanging the positionsof the two constituents of the compounds (e.g.,for capobanda the corresponding nonword wasbandacapo) or by exchanging the positions ofthe two segments of the noncompounds (e.g., fortartaruga the nonword was rugatarta).

Experimental nouns were further intermixedwith 88 word fillers and 88 nonwords. The wordfillers 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 10.21 (1.10) 10.82 (1.83) 9.32 (1.47) 9.04 (0.69)

Familiarity 4.89 (0.89) 4.60 (1.09) 5.26 (0.97) 5.38 (1.05)

Frequency (log) 2.19 (0.30) 2.29 (0.42) 2.06 (0.62) 1.92 (0.64)

Imageability 5.16 (1.08) 4.31 (1.42) 4.82 (1.19) 4.57 (1.44)

Age of acquisition 4.60 (1.05) 5.34 (1.16) 4.36 (81.21) 4.53 (1.58)

Note: Standard deviations in parentheses.



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suffixed or prefixed nouns or long nouns withoutreal nouns embedded (e.g., macedonia, “fruitsalad”). They were matched with the experimentalnouns for length and position of primary wordstress. Each of the word fillers was also used tocreate a corresponding nonword by substitutingthree of its letters (in two different syllables).Word fillers and nonwords were included tomake participants unaware of the tested variables.

The set of stimuli showed in the lexicaldecision task included a total of 200 words and200 nonwords. The experiment was controlled byE-Prime software (Version 1.1). The stimuli weredisplayed 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 backgroundwith size 32 font, Courier New typeface.

ProcedureParticipants were seated comfortably in a sound-attenuated booth, with response keys under theirleft and right hands. They were instructed topress the “YES” key if the stimulus was a wordand the “NO” key if the stimulus was a nonword,as quickly and accurately as possible. Responsehands were counterbalanced across participants.

The set of stimuli was divided into four blockseach containing an equal number of trials from the

different experimental conditions. Block order wascounterbalanced across participants, and thestimuli were randomized for each participant.Each block lasted approximately 7 minutes, andshort rest periods were provided between blocks.To familiarize participants with the task, eachexperimental session started with a practiceblock. The sequence of events within a trial wasas follows (see Figure 1): A warning-fixationstimulus was displayed in the centre of the screenfor 500 ms, followed by the stimulus, whichremained until the participant responded. Thetime was recorded from the moment the stimuliappeared till when the participant answered bypressing one of the two response keys.Participants were given a maximum of 3,000 msto answer. The intertrial interval (ITI) followedthe participant’s response and lasted 2,000 ms.During the ITI a mask sequence of # appearedon the screen, and participants could blink ormove their eyes. Participants were asked torefrain from blinking and moving (except for thekey press response) during the critical phase ofelectroencephalography (EEG) recording.

Data acquisition and analysisRTs for correct responses and error rates were ana-lysed 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. non-words), type of words (compounds vs. noncom-pounds), and headedness (left- vs. right-headedcompounds or left- vs. right-embedded noncom-pounds) as factors. Strictly speaking the term“headedness”, a label used for the sake of simpli-city, is inappropriate for this last factor, since thisincludes both compounds and noncompounds.Such an ambiguity would be absent in post hoccomparisons.

Continuous EEG was recorded from 28 scalpelectrodes mounted on an elastic cap (Electro-Cap International) and located at standard left-and 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 plusan electrode placed over the right mastoid werereferenced to the left mastoid electrode. The datawere recorded continuously by a SynAmps ampli-fier and NeuroScan 4.3 software. Each electrodewas rereferenced offline to the algebraic averageof the left and right mastoids. Impedances ofthese electrodes never exceeded 5 kV. The hori-zontal electro-oculogram (HEOG) was recordedfrom a bipolar montage with electrodes placed1 cm to the left and right of the external canthi.The vertical electro-oculogram (VEOG) wasrecorded from a bipolar montage with electrodesplaced above and below the right eye. The EEGwas amplified by a Synamp’s amplifier digitizedat a rate of 500 Hz and filtered during the offlineanalysis with a band pass of 0.01–30 Hz. EEGepochs containing EOG activity were detectedby wavelet analysis and were corrected using aregression method in the time domain(Semlitsch, Anderer, Shuster, & Presslich, 1986).ERPs were extracted by averaging trials separatelyfor participants, electrodes, and experimentalconditions.

ERP data were analysed for correct responsesonly by computing the mean amplitude in selectedlatency windows. The analysis period was1,400 ms, starting from the onset of the word ornonword stimuli. The preceding 100-ms period

was used as a prestimulus baseline. ANOVAswere used for all statistical tests and were carriedout with the Greenhouse–Geisser correction forsphericity departures (Geisser & Grenhouse,1959). To explore the potential topographic differ-ences, the electrodes were split on the basis of theirspatial dimension (caudality: anterior vs. pos-terior). ANOVAs for ERPs used a repeatedmeasures design taking the following variables asfactors: lexicality (words vs. nonwords); type ofword (compounds vs. noncompounds); headed-ness; and caudality (anterior vs. posteriorregions). For the two levels of the variable caudal-ity, we chose seven anterior electrode positions(Fp1, F3, Fc3, Fz, Fp2, F4, Fc4) and seven pos-terior positions (C3, Cp3, P3, Pz, C4, CP4, P4).Significant interactions between experimentalvariables were clarified either by breaking theminto simple effects or by means of post hoccomparisons.

Results

Behavioural dataAnalyses were conducted by participants (F1) andby items (F2). Moreover the minF (F 0) was alsocalculated (Raaijmakers, Schrijnemakers, &Gremmen, 1999).

There was a significant main effect of lexicalityon RTs, F1(1, 17) ¼ 55.26; p , .001; F2(1, 27) ¼86.60; p , .001; F 0(1, 36) ¼ 33.73; p , .001:Participants responded more quickly to realwords (915 ms) than to nonwords (1,226 ms).The main effect of type of word was also signifi-cant, F1(1, 17) ¼ 137.32; F2(1, 27) ¼ 52.68; p ,

.01; F 0(1, 42) ¼ 38.07; p , .001: RTs werelonger for compounds (1,154 ms) than for non-compounds (986 ms). No main effect of headed-ness was found, F1(1, 17) ¼ 9.70; p , .05; F2(1,27) , 1; ns; F 0(1, 31) , 1; ns. Table 2 summarizesthe mean reaction times for the four experimentalconditions 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 lowerfor nonwords (7.45%) than for words (13.55%).The only other significant difference was a lower



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error rate for noncompounds (5.85%) than com-pounds: 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 forwords was unexpected. Therefore, an analysiswas done to examine whether this discrepancyreflected the participants’ lack of familiarity witha few of the compounds, the category of itemsthat seemed more susceptible to errors. However,an item analysis revealed that it was not the casethat errors concentrated on a small group of com-pounds. It is possible that our participants wereunsure about whether the compounds existed inItalian, despite being relatively familiar with themeaning of these words.

To assess the contribution of familiarity and ageof acquisition (two variables that were unbalancedin our words), we carried out an analysis of covari-ance (ANCOVA), entering item means as thedependent variable. The ANCOVA yielded thesame results.

ERP dataThe traces presented in Figure 2 show the grandaverage potentials recorded at the midline electro-des (Fz, Cz, and Pz). The ERPs elicited by com-pound words and nonwords are superimposed onthe left side, and the ERPs elicited by noncom-pound words and nonwords are superimposed onthe right side. As shown in the figure, within theinitial 270 ms, words and nonwords elicitedsimilar N1-P2 complexes whether they were com-pounds or noncompounds. A negative componentwas then elicited, between 300 and 500 ms,

followed by a late positive shift with onsetlatency around 600 ms. These two effects arevery similar to the N400 and P600 componentsreported in previous language studies. Moreover,the direct comparison between compound andnoncompound words seems to reveal a negativedifference, starting around 270 ms, which islarger for compound than for noncompoundwords and is distributed around the anterior sites(see Figure 3). This effect can be related to theLAN component. Most interestingly, Figure 4shows a larger positive component for right-than for left-headed compounds, peaking ataround 300 ms and distributed around the pos-terior sites. This first positive peak was followedby a second positivity, with the same polarity(more positive for right-headed compoundwords) and distribution (around the posteriorsites) as the first, but being more extended(between 500 and 800 ms). These two positivitiescan be related to components of the P300 family.In contrast, the ERPs elicited by left- and right-word-embedded noncompounds did not differ(see Figure 5).

In order to examine these effects in furtherdetail, five latency ranges of main interest weredistinguished, both from visual inspection of theERP traces and from comparison with previousresults available in the literature: the 0–270-msinterval, to test the N1-P2 complexes; the270–370-ms and 370–500-ms intervals, to testthe LAN and the N400 components, respectively;and the 310–360-ms and 500–800-ms intervals,to test the components of the P300 familyand P600. Table 3 summarizes the results of theanalyses performed in these successive latencybands.

0–270 ms. The ANOVA revealed no significantmain effects or interactions (all Fs , 1).

270–370 ms. The analysis shows a main effect oflexicality, F(1, 17) ¼ 13.92, p , .001: Nonwordselicited a larger negativity than did words.There was also a main effect of type ofwords, F(1, 17) ¼ 5.74, p , .05, with compoundseliciting a larger negativity than noncompounds.

Table 2. Mean reaction times for the four experimental conditions

Condition Word Nonword

Left-headed

compounds (Nn)

999 (360) 1,268 (424)

Right-headed

compounds (nN)

985 (343) 1,364 (497)

Left-embedded word

noncompounds (NC1)

826 (287) 1,153 (439)

Right-embedded word

noncompounds (NC2)

847 (312) 1,119 (411)

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


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Moreover, the ANOVA showed a significantType of Word � Caudality interaction, F(1, 17)¼ 10.30, p , .005, reflecting differencesbetween types of word only at the anterior sites,F(1, 17) ¼ 11.07, p , .005, and not at theposterior sites (F , 1). Neither a main effect norinteractions were found for headedness in thislatency range.

310–360 ms. This epoch is included in the largerepoch analysed previously (270–370 ms). As inour previous analysis, the ANOVA showedsimilar 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 pre-vious analysis, an interaction between lexicality

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.



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and headedness was found, F(1, 17) ¼ 5.12, p ,

.05. To further track this interaction, separateANOVAs were conducted for words and non-words. The ANOVAs on word ERPs revealed amain 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 thatthe interactions observed with words were due tothe right-headed compound words producing a

more positive P300 response than the left-headed compound words over the posterior sites,F(1, 17) ¼ 4.63, p , .05 (see Figure 4). Such adifference was not observed with noncompoundwords (Fs , 1; see Figure 5).

370–500 ms. The ANOVA showed that the maineffect of lexicality was significant, F(1, 17) ¼ 41.28,p , .001: Nonwords elicited a larger N400 com-ponent than did words. The main effect of type ofwords was not significant but the Lexicality �

Type of Word interaction was significant,

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.


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F(1, 17) ¼ 7.30, p , .05. As can be seen in Figure 2,the N400 lexicality effect was larger for noncom-pounds, F(1, 17) ¼ 34.70, p , .001, than for com-pounds, F(1, 17) ¼ 7.64, p , .05.

500–800 ms. Analyses of this epoch showed thatthere were differences between words and

nonwords, F(1, 17) ¼ 77.06, p , .001, with non-words being associated with more positive voltagesthan words. Moreover, the ANOVA revealed twointeractions: 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 preceding310–360-s epoch, words and nonwords were

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.



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analysed separately. The ANOVA on word ERPsrevealed a main effect of type of word, F(1, 17) ¼2.40, p , .05: Noncompound words elicited alarger positivity than did compound words.There was also a main effect of Headedness, F(1,17) ¼ 14.30, p , .001, and an interesting inter-action between type of word and headedness,

F(1, 17) ¼ 4.46, p , .05. As in the preceding310–360-s epoch, follow-up analyses revealedthat this interaction was due to the right-headedcompound words producing a larger positivitythan the left-headed compound words, F(1, 17)¼ 6.07, p , .05. However, there was no diffe-rence between left- and right-word-embedded

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.


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noncompounds. Finally, an ANOVA on non-words revealed no significant main effects or inter-actions during this epoch (Fs , 1).

Discussion

The goal of the present study was to investigatethe neurophysiological correlates of Italiannoun–noun compounds. In particular, the aimwas to understand whether compound wordsdiffer significantly from noncompound words atthe neural level and to determine which ERP com-ponents could reveal this difference. One innova-tive aspect of this study is the exploration of theheadedness effect, undertaken by contrastingItalian left-headed and right-headed compounds.We first discuss the behavioural results (RTs anderror rates) and electrophysiological resultsrelated to word/nonword differences. We thenconsider the difference between compound andnoncompound nouns, before finally analysing therole of the morphological and semantic headsembedded in compound nouns.

The word/nonword effect on RTs is consistentwith the effect observed on ERPs. As in previousstudies, nonwords are associated with longer RTsand 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 beassociated with visual mechanisms devoted toletter processing, but rather with a higher levelmechanism devoted to word processing. The

difference in N400 for nonwords might reflect asearch within the lexico-semantic memory,which is particularly demanding for nonwordsthat lack lexico-semantic representations (Attias& Pratt, 1992; Friedrich et al., 2006; Picton &Hillyard, 1988; Supp et al., 2004). In the presentexperiment, an interesting interaction wasobserved between Lexicality and Type of Wordwithin the N400 component (specifically, in the370–500-ms window). This interaction reflecteda larger N400 lexicality effect for noncompoundwords than for compound words. Our result maybe related to the presentation of nonwordscreated by inverting the component words (seeMethod section). Crucially, the nonwordsderived from compound words contained tworeal words, as in the nonword spadapesce, whichwas obtained from the compound pescespada(swordfish) by switching the constituents pesce(fish) and spada (sword). Participants may accessthe meaning of both constituents as a result of adecomposition process; this in turn would mitigatethe impact of the linguistic difference betweenwords and nonwords in the compound-noun cat-egory. In contrast, for nonwords derived fromnoncompounds (e.g., forosema, obtained fromsemaforo, traffic lights) one of the two components(sema) has no meaning. This difference in stimuluscomposition may account for the larger N400 lexi-cality effect observed with nonwords derived fromnoncompound words: As they deviated morenoticeably from familiar words, they generated agreater N400 response.

The difference between compounds and non-compounds is also observed in behavioural data:

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 2 2 2 2 2 2 2 2 2 2 2 2 2

270–370 þ þ 2 2 2 2 2 2 2 þ 2 2 2

370–500 þ 2 þ 2 2 2 2 2 2 2 2 2 2

310–360 þ þ 2 2 þ 2 2 2 2 þ 2 2 2

500–800 þ 2 þ 2 þ 2 2 2 2 2 2 2 2

Note: þ¼ significant effect (p , .05). 2¼ 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).



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Longer RTs and higher error rates were found forcompounds than for noncompounds. This effect isprobably due to the fact that compounds require agreater involvement of cognitive resources, whichare recruited to access not only the whole word,but also its constituents. This interpretation isfurther confirmed by the ERP results. Withinthe 270–370-ms time window, increased nega-tivity was observed in the anterior areas for com-pounds compared to noncompounds. Theincreased negativity for compounds is likely to belinked to LAN. As explained in theIntroduction, the LAN component has beenassociated with the initial morphosyntactic proces-sing (Friederici, 1995, 2001) needed to detectpotential errors; however, some authors havesuggested that LAN reflects an increasedworking-memory load (Coulson et al., 1998;Kluender & Kutas, 1993). The finding that theLAN amplitude was more negative for compounds(than for noncompounds) might be explained bythe formation of a morphosyntactic representationof the constituents. LAN modulation has alsobeen noted in the two ERP papers on Germancompound processing, and it has been taken as evi-dence of compound decomposition during com-prehension (Koester et al., 2007; Koester et al.,2004). The LAN effect observed in our study pro-vides a critical piece of evidence against full-listingmodels and in favour of decomposition or dual-route models of compound processing.

The difference between compounds and non-compounds also appears in a later temporalwindow (starting at 500 ms) and is due to agreater amplitude and a more positive-goingpeak for noncompounds. Such positivity can beinterpreted as a P600 component. P600 has beenassociated with syntactic processing and therepair or reanalysis of syntactic violations(Coulson et al., 1998; Friederici, 2002; Friedericiet al., 1996; Neville et al., 1991; Osterhout et al.,1996) although it can also be elicited by nonpre-ferred syntactic structures (Coulson et al., 1998;Friederici, 2002; Neville et al., 1991) and seemsto be more susceptible to controlled processesthan are earlier components (Hahne &Friederici, 1999). The cause of the positive shift

we observed for noncompound nouns as opposedto compound nouns can be attributed to the par-ticular nature of the stimuli used in our exper-iment. A decomposition strategy would lead tothe detection of, for example, the word cocco(coconut) embedded in the word stimulus cocco-drillo (crocodile), which also contains thenonword drillo. This may generate ambiguity andperhaps induce a double checking of the lexicalstatus of nonwords like drillo. Some reanalysis,entailing more demanding processes, may there-fore be necessary. Noncompound nouns like cocco-drillo may, as a consequence, elicit a greater P600amplitude than do compound nouns.

Concerning the comparison between left- andright-headed compounds, behavioural results indi-cated that there was no difference (either in RTs orerror rates) between these two conditions.However, ERP data showed a difference betweenthese compounds within a particular timewindow—that is, starting at 310 ms up to800 ms. In particular, right-headed compoundsshowed a more positive peak than left-headedcompounds, and the effect was clearly localizedin the posterior area. Interestingly, this differenceis not present between left- and right-word-embedded noncompounds. The increase in posi-tivity elicited by right-headed compounds can berelated to the P300 component. Our finding of asignificant difference between left- and right-headed compounds at P300 indicates that thecompound head is a relevant element, at least con-cerning the electrophysiological activity of thebrain. Regarding the functional significance ofpolarity (with a more positive-going peak forright- than for left-headed), different interpret-ations could be considered. First, left- and right-headed compounds can differ in terms of theamount of attentional resources that they require.Indeed, the amplitude of P300 varies accordingto the amount of attentional resources investedin processing relevant stimuli (see Bashore &Van der Molen, 1991; Kok, 2001, for reviews).Another interpretation may be related to the factthat Italian left-headed compounds have a rela-tively more canonical order than right-headedcompounds. Left-headed compounds reflect the


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order of grammatical classes normally found inItalian sentences, where the noun precedes themodifier. In contrast, right-headed compoundsare the marked case, and, though productive,they do not reproduce the canonical orderbecause they originated from an ancient language(Latin) or were built on imitation of words fromother contemporary languages (most frequentlyfrom English, which only has right-headed com-pounds). It is thus possible that right-headed com-pounds require more attentional resources to beprocessed. A third interpretation is related to thecontext-updating theory (Donchin & Coles,1988). According to this theory, the amplitudeof the P300 is thought to reflect the processes bywhich information is updated in workingmemory as a function of incoming, contextuallyrelevant information. One can speculate that in alanguage like Italian that has two positionaloptions, updating takes place with the right-headed compounds. That is, the left componentis “automatically” recognized as the head, but itsinformation needs to be updated when the rightcomponent is processed and recognized as theproper head. This would result in an increase ofthe P300 amplitude. Such an increase would notoccur with left-headed compounds because noupdate is needed with these words.

Conclusions

In sum, a number of potentially interesting resultsemerged from this investigation. Indeed, wereported several specific time-linked electro-physiological correlates of compound processing.

Further neurophysiological evidence wasobtained that compounds behave differently fromnoncompounds. There were two types of evidencedemonstrating a difference between compoundsand noncompounds: (a) a larger N400 lexicalityeffect for noncompounds and (b) a modulation ofthe morpho-syntactic components (LAN andP600) observed only with compounds. Our elec-trophysiological findings converge with thosereported by Koester and coworkers (Koesteret al., 2007; Koester et al., 2004), even thoughthe two studies investigated lexical decision in

different modalities (visual vs. auditory). Our find-ings are also in line with data from lesion studies.

It is noteworthy that in our study the headed-ness effect was successfully distinguished fromthe position effect for the first time. This resultwas not obtained in lesion studies and, whileperhaps strongly suggested by their results, wasnot demonstrated by Koester and coworkers,since German does not allow the same control ofhead position that is possible in Italian. Whetherthe P300 component modulation found in thepresent experiment could be better interpreted interms of allocation of attentional resources or interms of working-memory processing remains amatter of speculation and is in need of furtherinvestigation, through ERPs or neuroimaging.As reported in the Introduction, the regularity ofhead position determined with the rightmostelement rule reduces the information stored at arepresentational level to a minimum. In languageswhere the head can be on the left, components likeP300 may be markers of processes involving thehead. In conclusion, it is important to emphasizethat the finding of specific electrophysiologicalcorrelates associated with the processing of thecompound head is not necessarily expected. Theconcept of compound head stems from theoreticallinguistics, and the information contained in itmay not impose different processing demandsfrom the information contained in the modifier.Our neurophysiologically grounded findingsinstead show that the information contained incompound heads may constrain the way in whichour 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 Stimulus Translation

Translation of

stimulus constituents

Nn Acquavite Brandy acqua (water); vite (grapes)

Nn Arcobaleno Rainbow arco (bow); baleno (lightning)

Nn Bancoposta [lit.] Counter post (the post office counter) banco (counter); posta (post)

Nn Boccaporto Hatchway bocca (mouth); porto (harbor)

Nn Bordovasca [lit.] The edge of a swimming pool bordo (edge); vasca (basin)

Nn Burrocacao Lipsalve burro (butter); cacao (cocoa)

Nn Calzamaglia Tights calza (sock); maglia (knitting)

Nn Camposcuola School camp campo (camp); scuola (school)

Nn Capobanda Band leader capo (leader); banda (band)

Nn Ceralacca Sealing wax cera (wax); lacca (lake)

Nn Finecorsa Terminal station fine (end); corsa (run)

Nn Focamonaca Monk seal foca (seal); monaca (monk)

Nn Fondovalle Valley bottom fond (bottom); valle (valley)

Nn Girocollo Round neck giro (round); collo (neck)

Nn Gommapiuma Foam rubber gomma (rubber); piuma (feather)

Nn Granoturco Maize grano (grain); turco (Turkish)

Nn Grillotalpa Mole cricket grillo (cricket); talpa (mole)

Nn Melograno Pomegranate melo (apple tree); grano (grain)

Nn Metroquadro Square metre metro (metre); quadro (square)

Nn Padrefamiglia [lit.] The head of the household padre (father); famiglia (family)

Nn Parcomacchine [lit.] The company fleet of cars parco (park); macchine (cars)

Nn Pastafrolla Short pastry pasta (dough); frolla (butter dough)

Nn Pescespada Swordfish pesce (fish); spada (sword)

Nn Pianoterra Ground floor piano (floor); terra (ground)

Nn Prezzobase Starting price prezzo (price); base (base)

Nn Retrobottega Backshop retro (back); bottega (shop)

Nn Roccaforte Fortress rocca (rock); forte (fort)

Nn Toporagno Shrew topo (mouse); ragno (spider)

nN Aliscafo Hydrofoil ali (wings); scafo (hull)

nN Architrave Lintel archi (bows); trave (beam)

nN Astronave Spaceship astro (star); nave (ship)

nN Audiofrequenza Audio-frequency audio (audio); frequenza (frequency)

nN Barbabietola Beet barba (beard); bietola (chard)

nN Broncospasmo Bronchospasm bronco (broncho); spasmo (spasm)

nN Calciomercato [lit.] Soccer market calcio (soccer); mercato (market)

nN Cartamoneta Paper money carta (paper); moneta (money)

nN Crocevia Crossroads croce (cross); via (road)

(Continued overleaf )



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Table 3. (Continued)

Type Stimulus Translation

Translation of

stimulus constituents

nN Docciaschiuma Shower gel doccia (shower); schiuma (foam)

nN Fangoterapia Mud therapy fango (mud); terapia (therapy)

nN Ferrolega Ferroalloy ferro (iron); lega (league)

nN Filobus Trolley bus filo (yarn); bus (bus)

nN Fluidodinamica Fluid dynamics fluido (fluid); dinamica (dynamics)

nN Fotoromanzo Picture story foto (photograph); romanzo (romance)

nN Luogotenente Lieutenant luogo (place); tenente (tenant)

nN Madrepatria Motherland madre (mother); patria (land)

nN Mondovisione World vision mondo (world); visione (vision)

nN Montepremio Jack-pot monte (mountain); premio (prize)

nN Motosega Chain saw moto (motor); sega (saw)

nN Nanosecondo Nanosecond nano (nano); secondo (second)

nN Pollicoltura Poultry farming polli (chickens); coltura (farming)

nN Radiocronaca Running commentary radio (radio); cronaca (commentary)

nN Servosterzo Power steering servo (servant); sterzo (steering)

nN Terremoto Earthquake terre (lands); moto (motion)

nN Vetroresina Fibre-glass plastic vetro (glass); resina (resin)

nN Videogioco Videogame video (video); gioco (game)

nN Zootecnica Zoo technology zoo (zoo); tecnica (technology)

Noncompounds

Type Stimulus Translation Translation of the embedded word

NC1 Barracuda Barracuda barra (bar)

NC1 Cavaliere Horse-rider cava (mine)

NC1 Clorofilla Chlorophyll cloro (chloro)

NC1 Coccodrillo Crocodile cocco (coconut)

NC1 Collaudo Test/inspection colla (glue)

NC1 Cremagliera Rack crema (cream)

NC1 Filastrocca Rigmarole fila (row)

NC1 Filosofo Philosopher filo (yarn)

NC1 Formalina Formalin forma (shape)

NC1 Funerale Funeral fune (cable)

NC1 Gelosia Jealousy gelo (chill)

NC1 Maleficio Spell male (ill)

NC1 Maresciallo Marshal mare (sea)

NC1 Melanoma Melanoma mela (apple)

NC1 Melodia Melody melo (apple-tree)

NC1 Mercenario Mercenary merce (goods)

NC1 Meteorite Meteorite meteo (weather-report)

NC1 Oratore Orator ora (hour)

NC1 Paladino Paladin pala (shovel)

NC1 Pappagorgia Double chin pappa (baby-food)

NC1 Pastorizia Sheep farming pasto (meal)

NC1 Pellegrino Pilgrim pelle (skin)

NC1 Peperone Pepper pepe (pepper)

(Continued overleaf )


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Type Stimulus Translation Translation of the embedded word

NC1 Polpastrello Pulp polpa (pulp)

NC1 Pontefice Pontiff ponte (bridge)

NC1 Salamandra Salamander sala (hall)

NC1 Serratura Lock serra (greenhouse)

NC1 Temperatura Temperature tempera (distemper)

NC2 Accidente Accident dente (tooth)

NC2 Accredito Crediting/credit dito (finger)

NC2 Catafalco Catafalque falco (hawk)

NC2 Catastrofe Catastrophe strofe (strophes)

NC2 Dirigente Manager/director gente (people)

NC2 Discepolo Disciple polo (pole)

NC2 Fazzoletto Handkerchief letto (bed)

NC2 Imbarazzo Embarrassment razzo (rocket)

NC2 Logaritmo Logarithm ritmo (rythm)

NC2 Mandragola Mandrake gola (throat)

NC2 Marzapane Marzipan pane (bread)

NC2 Megalite Megalith lite (quarrel)

NC2 Patriarca Patriarch arca (arch)

NC2 Pavimento Floor mento (chin)

NC2 Pentecoste Pentecost coste (coasts)

NC2 Pirofila Oven-proof dish fila (row)

NC2 Prezzemolo Parsley molo (pier)

NC2 Pugilato Boxing lato (side)

NC2 Recidiva Relapse diva (goddes)

NC2 Requisito Requirement sito (site)

NC2 Rotocalco Illustrated

magazine

calco (impression)

NC2 Scarafaggio Cockroach faggio (beech tree)

NC2 Schiamazzo Din mazzo (bunch)

NC2 Semaforo Traffic light foro (hole)

NC2 Tartaruga Tortoise ruga (wrinkle)

NC2 Varicella Chickenpox cella (cell)

NC2 Vegetale Vegetable tale (someone)

NC2 Virulenza Virulence lenza (fishing-line)



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