senior thesis 1995

8/9/2019 Senior Thesis 1995

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The Effects of Semantic Priming in EarlyVersus Late Bilinguals Versus Learners

Jennifer WeissSenior Thesis ProjectforCognitive ScienceVassar College

1994-1995


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ACKNOWLEDGEMENTS

Special thanks to Janet Andrews, my advisor, for her encouragement and guidance,to Doug Winblad for being my second reader, Carol Christensen for heremergency lessons, Debbie Ratchford, Richard Lowry for his numbers,Marta Kutas, all my gracious volunteer subjects, my housemates for theirsupport and patience, Marisa Arias for her knowledge of Spanish,and lastly to my parents for more than just the tuition payments.


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Semantic Priming in Early versus Late Bilinguals:An Inyestigation of Bilingual Language ProcessingJennifer L. Weiss

ABSTRAC T: S tu die s h ave sh ow n the e ffe ct o f seman tic p rim in g in m ono lin gu als. A recent area of studyis th e u se of ERP 's in o rd er to n ote th e n eu ro lo gica l a ctivity in vo lved in sem antic p rim in g. Th is expe rimen tin ve stig ate d diffe re nc es in b ilin gu als (e arly v s. la te vs . le arn in g) w ith re sp ec t to s emantic prim ing. Thestu dyteste d a cross la ng ua ge p rim in g a s w ell as w ith in lan gu ag e p rim in g. T he h ypomesls w as th at e arlyb ilin gu alsp ro ce ss o n a s eman tic le ve l s o th ey p rim e mo re e as ily, w hile la te b ilin gua ls a nd le arne rs d osu rface le ve l p ro ce ssin g an d the refo re sh ow le ss of an e ffect o f seman tic prim in g. T he refo re, it w ase xp ec te dth at th e e arly b ilin gu als w ou ld d is pla y a more s ig nifica ntly re du ce d N 40 0 th an th e la te b ilin gu alsa nd bo th w ou ld sh ow a g re ate r re ductio n o f N 40 0 th an the le arn ers.

INTRODUCTION:Thisstudy intends to investigate the effect of semantic priming within and across-languages for Spanish-English early bilinguals, late bilinguals, and students whohaveonly recently begun stUdying Spanish. The idea behind the study is twofold. Ifachieved, the expected results would support a theory of how a person encodes twolanguages at an early age versus how they encode a second language at a later age.Thestudy would also encourage investigations with larger implications, results thatwould tell something not only about a critical period in bilingual language acquisition,butalso critical period and language acquisition in general. The current study isbasedon the idea that there is a critical period for language acquisition and thatpeoplewho learn a second language at an early age have more interconnectedlanguages,whereas people who learn a second language at a later age are, in asense,having to work with what is already set up by the first language and by otherprocesses like memory.

Language acquisition is a broad field of study, within which there is a constantvacillation back and forth between the neurobiology and the psychology of language.A variety of theories have been formed which attempt to describe languagedevelopment in terms of stages. These theories, however, merely describe theapparentbehavior of a child. The current study is one which intends to aid in the


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investig~tionof more of the details of how the brain actually encodes language basedonphysiological phenomena not just behavioral ones. It is important to note that thesemodelsof behavior are certainly not insignificant and can prove useful when used incoordinationwith the abundance of modern data such as that provided byelectrophysiological and neurological investigations. The issue of linguisticdevelopmenthas many voices. One important issue of language development hasbeen:how rigid is the brain with regard to particular parts of the brain beingdesignatedfor particular tasks? levy and colleagues (1992) studied a child who hadalocalizedlesion in the left hemisphere as an infant and found evidence that supportsthe"plasticity model". The plasticity model is a theory that the brain has great plasticityforlanguage and if there is damage to one part of the brain, often other parts of thebrainare able to make up for the loss. The child studied by levy et at, apparently hadlinguisticabilities, including making the same kinds of grammatical errors, as normalchildrenhis age (levy et aI., 1992, p 23-24), despite the damage to parts of the brainthatare known to be important for language and do cause language disorders whendamagedin adulthood. The biggest problem with the levy study is that the child wasstudiedat an early age and so it is difficult to know, without waiting until he is older, ifhisabilities will consistently be at about the same level as those of his peers. But thecaseis initial evidence for plasticity of the brain with respect to language acquisition.

Another important issue within the field has been the question of lateralization.Manyhave tried to find out which cerebral hemisphere is involved in which parts oflanguage. Especially with regard to bilingualism there has been much bickering backandforth about whether or not bilinguals have the same proportional usage of the lefthemisphereas monolinguals (Paradis, 1990; Paradis, 1992; Berquier and Ashton,1 9 9 2 ) . For the purpose of the current study, the importance of lateralization is onlypertinentas it may provide clues to how language is encoded in the brain of an earlyversusa late bilingual. Perhaps it would be more useful to begin by looking at


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lateralization effects in monolinguals. Data such as that provided by Ojemann andMateer(1979) begin to give insight into how and where the brain stores language.Theyconclude that "phylogenetic development of language is characterized by theappearance of lateralized sequential motor and memory systems" (Ojemann andMateer,1979, p. 1403). The brain is not made of two hemispheres that mirror oneanotherand language involves many other functions such as memory and motor skills.Thus, lateralization and other issues of localization are important topics in the field oflanguageacquisition. It is essential to study the whole brain and to consider howothertasks are involved in language so that we can pinpoint what parts of the brainareused just for linguistic tasks and what parts are used in coordination with otherprocesseslike motor skills.

In understanding the biological phenomena that make up language, one keyareaof study is the critical period. Most investigators agree that timing is important inlearninglanguage. The question is determining the exact age (either mental orphysicalage), if there is a specific age, when language development is at its prime.JamesHurford suggests that the sensitive period for language acquisition ends as lateaspuberty (Hurford, 1991, p.159). A sensitive period to Hurford is a time whenexposureto language is most important because that is the time when languageprocessesare being developed in the brain. Yet biologically, development ofneuronalconnections is greatest in early childhood, and although there still isdevelopment later on, the majority takes place in the first years of life. The complexstructuresof the brain are formed early; fundamental connections are establishedbeforebirth, while after birth there is more of the same kind of neuronal development(Fox,1983, p. 1220). In other words, later development could be imagined as alayeringeffect where the base layer is determined before birth. Fox discusses this intermsof learning as well as development in general by using imprinting, a morespecifickind of learning. One can think of development as experience, which entails

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involving the present as layered on top of the recent past and both being layered ontop of the more distant past. Similarly, with imprinting the animal is born with a baseonwhich they record the experience. Thus, a duckling is born with the materialsnecessary to imprint the image of its mother (who is presumably the first thing it isgoing to see when it is born) and all it needs is that visual experience to complete avery major connection. Fox compares this process to learning and development ingeneral: a child enters the world ready to add experiences to its pre-establishedfunctions. In this way, we learn by adding experiences one on top of the other. Withlanguage acquisition, there is much debate about whether this is the actual processthatgoes on in development but it seems to me that this is at the least a good way oftalking about language acquisition, however abstract the parallel may actually be tothedevelopmental process. It is a springboard from which we can dive into theresearchwith some direction.

Critical period of language acquisition, which I will use interchangeably withsensitive period in an effort to avoid aligning myself with either theory, although theyare not exactly the same, is certainly a psychological theory but corresponds nicelywith the biological data. (A theory of an existing critical period is in a sense more strictthanthat of a sensitive period, strict in that a sensitive period implies a desirable oreven ideal time to learn whereas critical period labels an essential or imperativeperiodduring which one must learn.) Hurford reports that some research on aphasiaprovides additional evidence for a critical period because it appears that children canrecoverto a great extent whereas adults never fully recover their language abilities.Thiswould make sense given the hypothesis proposed earlier that children have moreplasticity and could possibly be reconstructing destroyed connections, whereas adultsmayhave to rely on the remaining healthy connections and use them as much asfunctionally possible for processes previously performed by the now destroyedneuronal connections.

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Hurford also argues that early language acquisition is an evolutionarilyplausible concept, although it would seem as if a critical period of languageacquisition may in fact limit people's abilities. In order to show that a critical period oflanguage acquisition is something that would develop naturally over time he creates asetof simulated individuals, attributing specific characteristics to each, and runs themthroughcycles that simulate changes such as reproduction, accidents, etc. In thisprogrammed evolutionary microcosm, Hurford finds critical period effects for all of theindividuals before 1000 generations. Thus, for each of the different conditions, he stillfindsthat within 1000 generations each individual has had offspring who display somekindof critical period. He uses this as evidence to show that a critical period oflanguageacquisition does stand the test of evolution and perseveres as an evolvedtrait.

Moreover, Mayberry (1993) found the same kind of critical period effect in herinvestigations of adult "speakers" of American Sign Language. The data fromMayberry's study, however differs from the previously described data because itstudiedsubjects who were deaf from birth as well as subjects who became deaf in latechildhood. The subjects who were born deaf learned ASL during infancy to latechildhood. Those who became deaf had learned English before they lost their hearingsoASL was considered their second language. The results were such that thosewhosesecond language was ASL performed at a much higher level than those whoacquiredASL at the same age but as their first language. In other words, the deafsubjectswho began learning sign language from an early age were native ASLsigners. The subjects who learned English before they became deaf and began tolearnASL later in their lives, did not have this same mastery of the language. This isstrongevidence for a critical period of language acquisition and also enhances theideathat we have language abilities with some predesigned structure that are generalenoughto be applied to a completely different input/output system like signing. The


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evidence from deaf subjects indicates that we have certain deep structures oflanguage that are across modalities. In any case, the study shows that there is also acritical period for signed language. This kind of evidence is another approach to thestudyof a critical period and can function as more behavioral data to supplement theevolutionary story, which is pertinent to language in humans and aids in the effort tocometo an understanding of the neurological organization of language in the brain.Marin notes that "observation of evolutionary trends in the organization of the cerebralcortex, comparative anatomical studies, evolutionary patterns of change in animalbehavior along the phylogenetic scale, and, most significantly, the intense studies ofclinicopathological correlations have given us the basis for most of our presentknowledge of the brain in relation to language" (Marin, 1982, p.52).

Marcotte and Morere use a different approach in their study of languageacquisition, referring to physiological evidence of a critical period (Marcotte andMorere, 1990). They recognize the many instances of data from deaf aphasics buttheyalso criticize the lack of study as to whether there is a critical period for languagelateralization effects. Their study attempts to examine the development of speech inthe left hemisphere. They found, at least in an initial investigation of the phenomenon,that the age of onset of deafness had a great effect on the specialization of the lefthemisphere for speech. They used adults who had become deaf or nearly deaf afterthirty-six months of age (who were learning to speak as normal children before theirhearingloss) and found that their left cerebral hemispheres were not significantly lessspecialized for processes involved in speech than those of normal adults, whereasthoseadults who had become profoundly deaf before thirty-six months showed amuchgreater bilateralization for speech. In other words, age of onset of deafnessmadea significant difference in the hemispheric activity involved in speech. This isgoodevidence that the physical development of the brain is an integral part oflanguagedevelopment. It also raises the question of how the two hemispheres of the


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braintake part in language. Much of the physiological data indicate that particularaspectsof language require activity of both hemispheres. "The cortical areasparticipating in speech and language reception are frequently activated bilaterallyratherthan unilaterally in the speech-dominant hemisphere. The findings agree with alargebody of ERP [Event-Related Potential] components in association with languageprocessing" (Hillyard and Picton, 1986, pp. 559-560).

Learning more about the way language is organized in the brain is crucial tounderstanding human language. Yet language is not a separate function; there are avarietyof processes involved both directly and indirectly with language. Thus,distinctionsmust be made in order to determine what parts of the brain are usedspecificallyfor language. In his 1978 study of short-term verbal memory andlanguage,Ojemann began to draw a distinction between visual short-term memory inthehippocampus and short-term memory in the language cortex (Ojemann, 1978).Thestudy showed evidence for the distinction between word-memory sites andepisodicshort-term verbal memory. Ojemann concluded that some of the areainvolvedin language is involved in the storing of short-term verbal memory, theseareasbeing the posterior part of the language cortex, while the anterior languagecortexis apparently involved in retrieval from short-term visual memory (Ojemann,1978 , p. 337). In a later study by Fried, Ojemann, and Fetz, similar investigations wereperformedand it was concluded that "a major difference between overt speech andcovertnaming appears to be the relative involvement of motor and premotor cortex"(Friedet aI., 1981, p. 355). The brain is a small space in which a great many eventsoccur. It is imperative that when investigating a particular phenomenon, theexperimentbe controlled for all variables, and all kinds of brain phenomena involvedbegiven proper attention. The idea here is that there are many different processesthatare intertwined with language and in order to find which parts of the brain do whatwithrespect to language, one must also consider the many processes involved in


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8language. If, for instance, one wishes to look for particular areas that are active in acertain language task, the other processes involved in the task should also beconsidered. It is clear that reading involves more than just the mental comprehensionofwords, and with our understanding of which parts of the brain are active for ocularprocesses, we can eliminate these areas as places where language processingoccurs. Similarly, a better understanding of memory that does not involve language(suchas non-language tasks using purely visual memory) can help us to pinpointspecific areas where language is involved during a task such as one involving wordrnernorization. In other words, it is essential that language be isolated and the way todoso is to gain knowledge of the other processes involved and how they areorganized apart from language. The more we know about the brain and its functionsthatdo not involve language, the more we will also know about the parts that doinvolve language.

As stated earlier by Marin, much of what we know about language has comefrompatients who have language-related disorders. There are a huge number ofdifferent kinds of disorders and many of them overlap greatly. Often it is difficult toclassify a patient as having one kind of disorder. Some of the most common languagedisorders, however, include Broca's aphasia and Wernicke's aphasia, which aredescribed by Schnitzer in "The Translation Hierarchy of Language" (Schnitzer, 1982).Hedescribes Broca's aphasics as people who do not have a grasp of the grammaticalrulesof their language. They also experience difficulty with word production, selectionofwords, initiation of motor activity, etc. Wernicke's aphasics, on the other hand, havedifficulties at the level of semantics, according to Schnitzer. Wernicke's aphasics alsodisplaydifficulty with phoneme sequence and with their representations of semanticcategories. Much of the actual description of the full functions of these areas is stillmissing, though. What we know about disorders such as aphasia, enables us to tell ageneralstory about what is happening where in the brain, but we still cannot describe


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theactual processes that are taking place with much detail, especially because instudyingdisorders or brain damage, it is not always clear that there are not otherproblems in other parts of the brain, for example.

Bilingualism is a topic that, like aphasia and evolutionary models, can providegreat insight into the way the brain handles language. One of the biggest questions ishowthe brain encodes two languages. Are both languages separate? Is there an"English language" box and a "Spanish language" box which have connectionsbetweenthem but are pretty much kept separate? I tend to think not. Bilingualism isnotso simple as having two languages in little storage boxes. First it is imperative todefinebilingualism. Part of the motivation for this study is to do this. Someone is oftenconsidered bilingual when he speaks two languages fluently. A more detaileddefinition may refer to fluency as being able to speak and understand both languagesasif the person were monolingual. In this case, if the person's languages are at aboutthesame level of competency, then he or she is considered bilingual (Hamers andBlanc,1983, pp. 15-17). Hamers and Blanc note that there are different kinds of testsofbilingual competence and as they point out, defining bilingualism varies dependinginwhich field it is measured. There are various aspects that make up the bilingualperson:society, ethnography, geography, self-evaluation, language comparisons andotherbehavioral data, etc. All of these are ways of determining not only a bilingual'slanguagecapabilities, but also her identity as a bilingual. The intention of this paper istoexplore the biological determinations of bilingualism. The hypothesis is that a "true"bilingual is one who has learned two languages from an early age while people wholearnlanguage after the critical period of language acquisition will only ever become"fluent"in their second language, not fully bilingual. The distinction between "fluent"andfully bilingual would, in this case, be a physiological one rather than a behavioralone. Someone who is fluent can have great control over her second language, butperhapsis slower at some language tasks than bilinguals who learned their second


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language before the critical period. That is not to discourage anyone from learning asecond language; it is clear that language can be learned after childhood and it canbe learned well. Yet I propose that what makes someone a true bilingual is aphysiological difference in how his two languages are encoded. The word "bilingual"implies two equal languages, which late bilinguals presumably do not have accordingtothis biological definition of bilingualism. If we could show that people who learn asecond language an earlier age handle their languages differently than do peoplewho learned a second language at a later age, not only would it support thehypothesis that there is a critical period for second language acquisition, but it wouldhelpin moving toward an understanding of language acquisition more generally.

With these predictions, and basing our growing understanding of the brain andofcognitive processes in general as described up until now, we can come up with aninitialhypothesis about bilingualism. If indeed particular areas of the brain havedesignated functions as the evidence seems to indicate, and there is a critical periodof language acquisition, then it seems as if a second language learned at a young age(atthe "right" age) has a particular development parallel in many senses, to thedeveloping structure of the first language in the brain. What I mean by this is that thelanguage or languages learned at an early age is what is built up from a predesignedfoundation that is the newly formed brain. Certainly there are many innate processes;infantsare not born without anything in their heads. Infants are born with the ability toperformmany functions, but with respect to language they are born with the potentialtoacquire language and they are born with many preset structures for language. Theirlanguageabilities depend on the stimulation received from their surroundings whichprovidethe experience necessary to develop advanced language skills. Breathnachexplains that "language development depends on the strengthening and weakening ofsynapticpopulations on dendritic assemblies within parallel groups of neurons in thecerebralcortex by dynamic selection", a process which declines gradually after age


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two (Breathnach, 1993, p. 45). This implies that both a first language and a secondlanguage would develop together in the brain if learned at an early age but a secondlanguage learned at an older age must be forced to fit into the neural structuredesigned in early childhood when the child learned its first language. This theory ismeant to be taken as a oversimplified version of what is happening in the brain, butcanbe used as a basis for investigations.

Evidence for this theory comes again from disorders such as aphasia. The mostsignificant support of this theory is an eighteen year old patient who had brain damageatage four (Van Lieshout et aI., 1990). This young girl had a radiation lesion in her leftthalamic and temporal region which caused problems with short-term auditorymemory,auditory word comprehension, nonword repetition, as well as fluency andnamingdifficulties (Van Lieshout et aI., 1990, p.184-185). The most interesting featureof this patient's deficits is that she had the same problems with both of her twolanguages (English and Dutch) despite the fact that she learned Dutch after theradiation lesion. This could be used as evidence for the theory of bilingualism justproposed. The girl began to learn Dutch at the age of six and a half, so she would beconsideredan early bilingual. It seems that if she had begun to learn a secondlanguageat this early age, she would have been able to compensate for the damagebecauseof the plasticity of the brain described earlier, assuming the brain is stilldevelopingat that age (which is in fact not certain). Yet she could not; the Dutch shelearnedsuffered the same problems as her English suffered from the brain damage,whichsuggests that there were fundamental language processes destroyed whichcouldnot be overcome by learning a second language after the damage was done.This is a good indication that there are designated areas for language where, forinstance,grammar and vocabulary are stored. It is also contrary to the plasticity model(unlessperhaps the development and plasticity of the brain is either slowed orstoppedaltogether earlier than age six). The patient's "assigned language areas"


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1 2werewhat suffered from the lesion, thus she lost some of her abilities in English andcould not later succeed with some aspects of Dutch because those overall languageprocesses were no longer functioning properly. The greatest information learned fromthissubject is that there are indeed shared language "areas" for the differentlanguages of an early bilingual.

The patient described above is one subject who begins to help us paint apictureof language acquisition and of how it is that the brain handles language. Westartto wonder about these possible differences between early and late bilinguals.There is certainly evidence that there is some kind of difference, presumablyphysiological, between people who learn a language at an early age and those wholearna second language at a later age. Again, it is assumed that this has to do withbiological development and some kind of critical period of language acquisition.Thereis evidence from all different realms that support this and provide evidence fordifferent kinds of bilingualism that depend on learning the second language during thecriticalperiod. Vaid uses evidence from previous researchers as well as aninvestigation of visual field asymmetries to argue that late bilinguals process words intheirsecond language at a more surface level (Vaid, 1987). Vaid cites a study byGenesee et al. where the investigators found that late bilinguals could identify in whichlanguage a word was presented faster than earlier bilinguals could. The latebilinguals displayed earlier neural responses in their right hemisphere during thislanguage identification task while early bilinguals showed faster responses in the lefthemisphere. Vaid's study finds a right visual field superiority for late bilinguals whilenosuch effect was found for either early bilinguals nor for the rnonolinqual group(Vaid,1987, p. 273). This evidence was interpreted as supporting the hypothesis thatlatebilinguals processing at a more surface level while early bilinguals are perhapsprocessing at a more semantic level. Semantic level processing means processing atthelevel of the representation or symbol as opposed to processing at the surface level

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1 3which refers to a focus on the syntactic features of an object or word. Vaid points outthat "this orientation to meaning may have developed in early bilinguals as a way ofovercoming the potential interference created by having to attribute two symbols to anygiven referent" (Vaid, 1987, p. 275).

Johnson and Newport (1991) approach the issue of a critical period from adifferent angle. These authors attempted to investigate critical period and maturationaleffectson the ability to learn universal properties of language. In their conclusion theyarguedfor a critical period, claiming, "linguistic universals such as subjacency becomelessaccessible to the language learner with increasing maturation" (Johnson andNewport, 1991, p. 254). Meanwhile, Magiste (1992) offers additional evidence for acritical period by examining elementary school-age children to high school students.Shefound that it takes younger children less time to become bilingual than olderchildren, as measured by a picture naming task. This study was of German childrenwhocame to live in Sweden. Other studies of different languages include JohnsonandNewport's (1989) reference to Korean and Chinese speakers who entered theUnitedStates at an early age as having a significant advantage over those whoenteredafter puberty (Johnson and Newport, 1989). In their study they noted severalthings,one of which is that children are better at learning a second language thanadults (Johnson and Newport, 1989, p. 89). The second point was that their dataindicatedthat "subjects who arrived in the United States before the age of sevenreachednative performance on the test" where as "for arrivals after that age, there wasa linear decline in performance up through puberty" (Johnson and Newport, 1989, p.90) . Yet the subjects who arrived after puberty did not seem to show this decreasingabilitywith age; they simply all performed at a much lower level than those who hadarrivedbefore puberty.

Another article of interest is one by Berthier and colleagues, in which a subjectdisplayed aphasia with respect to both of his two languages after having diluted

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amobarbital injected into his left middle cerebral artery (Berthier et aI., 1990, p. 452).Theauthors explain that by the way the patient reacted, first speaking in English andthenonly being able to speak his native language Spanish after 52 seconds after theinjection, implies that in the subject "English was represented in the central Sylviancore of the left hemisphere, while Spanish was better represented in the more distalperisylvian regions" (Berthier et aI., 1990, p. 452). The interesting part of this studywas that the subject was a late bilingual who had learned English as his secondlanguage while in high school. Thus, the separation of the two languages in the braininthis case was an actual physical one for this late bilingual. It is not clear that this isthecase for all late bilinguals and it would also be important to do research to see ifearlybilinguals display a different reaction to this kind of injection. Unfortunately, thecasesin which this kind of injection is necessary are not abundant. Yet it isencouraging that actual biological data such as this one subject indicate a separationof the two languages, and it can be used as a stepping stone towards a theory of lateversus early bilingualism.

Thus, the evidence seems to indicate that there is a critical period for languageacquisition, including second acquisition. This both enhances the probability of acritical period for language in general and leads to more interesting questionsregarding bilingualism. One topic of interest in language studies is an effect calledsemantic priming. The idea behind the current study is that perhaps the semanticprimingeffect can be used to investigate differences between early and late bilinguals.Semantic priming was first measured by reaction time where subjects were given a listofword pairs and were asked later to recognize words that were in this list in anotherlist. The research showed that people's reaction times were faster for words whichweresemantically related to the words they followed than for words which followedunrelatedwords. This effect has been labelled the semantic priming effect. The ideaisthat people are better at learning words if they are "primed" by a related word.


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1 5Holcombexplains, "Semantic priming can be characterized as resulting, at leastpartially,from the spread of activation from a recently accessed lexical item (cat) to thedetectorof the target item of interest (dog), so that when the target word is actuallypresenteda short time later, its detector is "primed" or closer to its recognitionthreshold. An implicit assumption of this type of contextual priming effect is that thelexiconis organized semantically" (Holcomb, 1993, p. 48). In most simplistic terms,semanticpriming is simply making it easier to access one word by first stating anotherthatis related. It is as if by saying the word "cat", the ANIMAL "box" is opened so thatwhenthe next word is "dog", it is easier to get at because the "box" is already open.

More recently, semantic priming has been analyzed thanks to technologicaladvancements. Because of technology, our ability to recognize and study mentalphenomena has changed drastically. Physiological measures such as event-relatedpotentials(ERPs), have given new insight into the field of psychology. We now havetheability to better investigate patients with disorders to discover what the brain is allabout,and we can also study healthy subjects as well. We can study normalfunctioningof the brain in ways we could not just a few years ago. We can studynormalpatients in comparison to brain damaged subjects and we can investigate thedifferences in normal subjects. These differences in subjects are called individualvariation,which is most definitely an issue of concern. Ojemann (1991) notes that insomestudies there are differences between men and women, while other studies addthatvariation in language abilities is directly correlated with differences in eachlanguagecortex. In Ojemann's earlier study (Ojemann, 1978), a concern would bethatperhaps different people react differently to electrical stimulation. In his study,Ojemannuses patients who suffer from epilepsy. This is a variable that may have hadaneffect on the results and it is difficult to say that the results can indeed generalize totherest of the population. For these kinds of reasons, it is difficult to study languagefunctionsin the brain overall because of the variance among individuals. Yet many


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16distinctions can and have been drawn. Studies such as those usingelectrophysiological data, for example, provide better and more controlled evidencebecausethey are more flexible as to who may be tested. That is, a very particulargroupcan be used or a wide variety of individuals can be tested. And the data is moregeneralizable. Thus, measures such as event-related potentials have provided uswiththe ability to take a giant leap forward in our endeavors within the field ofpsychology and cognitive science.

Event-related potentials (ERPs) measure brain activity at particular sites inreferenceto a controlled presentation of a stimulus. "ERPs are recordings of theelectricfield which the brain produces in fixed time-relation to an event" (Brandeis andLehmann, 1986, p. 151). They are useful because they can be used to determinewherethe brain is active for different kinds of processes. They can also be recorded todetermine whether a person responds more to one kind of stimuli than another. ERPsaremeasured from electrodes placed at different sites on the scalp, attached with a gelthatis both cohesive and conductive. Subjects are presented tasks while theelectrodes are on their heads, and as they participate in the activities the electrodescanmeasure how much activity there is in the brain at particular times relative to, forexample, the presentation of a stimulus. In the case of the current study, the subjectslistenedto a list of words while the ERP measured their brain activity at seven differentelectrodesites: Fz, Cz, Pz, P3, P4, T5, and T6 (see Appendix A).

To interpret ERP data, many different kinds of tests can be applied. Forinstance,some studies require measures such as peak latency or area under thecurve. Some compare peak amplitude at a particular point in time while othersaverageover a period of time. This study used mean amplitude as the measure; meanamplitudeis the average amplitude over a particular time period, called an epoch.Thiskind of measure can be used to compare across subjects or for different kinds ofstimuli. ERP data can be interpreted in many different ways depending on how one


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1 7choosesto. analyze it and what kinds of variables are involved. The study of languagehasmost definitely benefitted from this kind of technology. ERPs have often beenusedto find physiological similarities and differences in peoples' responses tolanguagetasks. Brandeis and Lehmann note that because of the invention ofelectrophysiological data collection, theories such as one proposed by Osgood in1952, can now be tested with more concrete investigations (Brandeis and Lehmann,1986 , p. 156). Brandeis and Lehmann explain that in a study using ERPs, Chapmanandcolleagues found evidence which "suggested that similar neurophysiologicalrepresentations of connotative meaning exist across subjects, paralleling theuniversalityof the Osgood scales at the behavioral level" (Brandeis and Lehmann,1986 , p. 156). Similarly, behavioral studies of memory and language led into laterE R P studies of the same phenomena. From ERP studies it was determined that apositivecomponent at 300 milliseconds after presentation of a stimulus (P300) variesaccordingto the probability of the stimulus as expected by the subject. In other words,changesin P300 are often the result of some kind of unexpected perceptual stimulus.Inone study cited by Brandeis and Lehmann (1986) incongruous words werepresentedat the end of a sentence and instead of finding an expected effect of P300,theauthors found a a negative effect at about 400 ms after the stimulus was presented( N 4 0 0 ) (Brandeis and Lehmann, 1986, p. 156). This finding has lead to a great deal offurtherstudy of N400.

In the past it was recognized that in certain word recognition tasks it takespeopleless time to recognize a target word that has previously been presentedfollowinga related word than for a target word that has been presented following anunrelatedword. In other words, "RTs [Reaction Times] are slower to name or classify atargetword (e.g., dog) when it is preceded by an unrelated context (e.g., the word car)thanwhen it is preceded by a related context (e.g., the word cat)" (Holcomb, 1993, p.4 7 ) . This difference was named the "semantic priming effect" and is still used to


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1 8describeour greater success at learning words when they are followed bysemantically related words than when they are followed by unrelated ones. Holcombdescribes,"Semantic priming can be characterized as resulting, at least partially, fromthespread of activation from a recently accessed lexical item (cat) to the detector of thetargetitem of interest (dog), so that when the target word is actually presented a shorttimelater, its detector is "primed" or close to its recognition threshold" (Holcomb, 1993,p.48). As Hillyard and Picton tell us, a study was done where the authors werelookingat ERP measures of a person's reaction to a word unrelated categorically tothelist of words in which the incongruous word was presented (Hillyard and Picton,1986 , p.568). What Hillyard and Picton report is that the investigators found a greaterN400for these unrelated words and thus proposed that N400 was a measure ofreactionto semantic relatedness. Using this finding along with the study cited earlier,researchbegan into how N400 was related to semantics. Hillyard and Picton continuetotell us of a study, similar to the task described earlier where sentences werepresentedwith unexpected words at the end of them, only in this new study there wasacomparison of N400 amplitudes for unexpected words that were unrelated to thesentencecompared with amplitudes for unexpected words that were actually related totheword that was expected. What they found was that "the N400 wave was smallerwhenthe unexpected words were semantically related to the most likely completion ofthesentence" (Hillyard and Picton, 1986, p. 568). Thus there is a greater reduction inN400for semantically related targets than for unrelated words. This phenomenon wasagainsupported by the data from a study by Holcomb (1993) in which he presentedsubjectswith related and unrelated word pairs and measured reaction time as well asreductionin N400. He found both results: reaction times were shorter for relatedtargetsthan unrelated targets and reduction of N400 was greater for related targetsthanfor unrelated targets.

r;


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1 9These results all indicate that there is a reliable method of recognizing semantic

priming based on electrophysiological data. Sentin, Kutas, and Hillyard (1993)expandon this by investigating the same phenomenon of semantic priming as seen inareduction of N400, but they present the stimuli auditorily. The study shows that agreater reduction of N400 amplitude occurs for auditorily presented related pairs thanoccursfor auditorily presented unrelated pairs. The investigators presented theirsubjectswith two different tasks. The first task, called the Memorize task, required thatsubjectssimply listen to a list of words and memorize as many as they could. Thesecondtask, called the Count Nonwords task, required that subjects count tothemselves silently the number of nonwords in a list of words. Sentin et al.hypothesized that "the N400s in the recognition memory task would be more sensitivetothe activation of the semantic.information both within and between words relative tothelexical decision task in which nonwords were counted" (Sentin et aI., 1993, p. 162).

There were 16 subjects with normal hearing, all right-handed. The authorstestedthese subjects, measuring their ERPs while the subjects were performing oneachof the tasks. In addition to left and right mastoids for a reference, and vertical andhorizontaleye electrodes for eye movements, they used electrode sites Fz, Cz, Pz, P3,P 4 , T5, T6, as well as six other specially selected sites. The data was collected in theformof an EEG and later averaged over epochs. The subjects were also given a wordrecognitiontask measured by a questionnaire that consisted of old words, new wordsthatwere related to old targets, and new words that were unrelated to words in thepreviouslist. Subjects had to determine whether the words were old or new and hadtoratetheir confidence. The results of the study indicated a Significant effect ofsemanticrelatedness, electrode site, and an interaction of semantic relatedness withbothelectrode site and task.

Sentin and colleagues summarize their data by stating, "In general, theseresultsconfirm the existence of a robust semantic priming effect on the N400


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component in the auditory modality" and "the amount of attention directed to semanticanalysis appears to be important in determining the size of the N400 priming effect"(Bentinet aI., 1993, p. 167). Their data also indicates that auditory presentation ofstimulishows the same semantic priming effect as visual presentation. As far as therelatedversus unrelated pairs, they saw a difference in mean amplitude between therelated and the unrelated pairs. Their related pairs were divided into categoricallyrelatedpairs and antonym pairs and although the semantic priming effect was a bitlargerfor the antonyms, it was not significantly greater than that of the categoricallyrelatedpairs. As far as the effect of electrodes, the authors found that the electrodesthatwere more frontal and more central had greater negativity. In order to performmoreanalyses, the EEG data was divided into three epochs: 300-400 ms, 400-700 ms,and700-900 ms. The semantic priming effect proved greatest in the middle epoch of400-700 ms. In the recognition task there was a significantly greater percentage offalsealarms for new words that were related than there was for new words that wereunrelatedto words in the previous list. The Bentin et al. study is useful because itexpandsthe field of semantic priming to include ERP analysis of the auditory modality.

Based on the information provided by the Bentin et al. study, the currentinvestigation was an effort to discover if our knowledge of semantic priming and N400couldperhaps provide insight into the critical period of bilingual language acquisition.Themain focus was how early bilinguals prime under these conditions versus howlatebilinguals and learners do. The hypothesis was that early bilinguals would showagreater effect of semantic priming, thus a greater reduction at N400, than would thelatebilinguals or the learners. The benefit of using ERP measures for examining thesemantic priming effect is that the three groups' N400 amplitudes could easily becontrasted.

Semantic priming across languages is not such a new idea; it has recently beenstudiedby several investigators. One study by Tzelgov and Eben-Ezra describes an


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21effectof semantic priming found between languages where the subjects were requiredto pronounce the target words. The authors do not specify all of the ages of acquisitionforthe subjects, but most of them appear to have learned both of their languages at anearlyage. The study investigates the theory of "automatic spread of activation", whichisa way of describing the way words are connected in the brain. They found that bothprimelanguage and target language have effects on the priming effect, that is whethertheprime was in the same language or not was important in the priming effect. Theyclaimthat these results are "most consistent with the notion that the between-languagesemanticpriming effect reflects a structural feature of the semantic network-it is notorganised in terms of language specific areas" (Tzelgov and Eben-Ezra, 1992, p.266).Also,Chen and Ng (1989) found better lexical decision performance when the primewasa translation than when the prime was a semantically related word. They alsofoundthat between-language and within-language primes give way to equivalenteffectsof semantic facilitation. They interpret their results as being support for aconcept-mediation model where "words in the two languages, and pictures, are allmentallyconnected by means of an amodal conceptual system, and that on the basisofthese links to concepts, subjects can actually respond to various kinds of tasksinvolvingthe processing of pictures and words, such as lexical decision and naming"(Chenand Ng, 1989, p. 460). The biggest problem with the Chen and Ng study wasthatthey did not specify whether the bilinguals were early or late bilinguals, althoughfromtheir description of the subjects as having studied English in school for twelveyears,it is assumed that they must be late bilinguals considering the mean age wastwenty. Finally, a third bilingual study used N400 to note differences in bilinguals andmonolinguals (Ardal et aI., 1990). They did not, however, find differences due to ageofacquisition. These studies are all beginnings of new kinds of investigations intobilingual language processing from which much can be said about the way languageisencoded.


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In conclusion, this study was designed to investigate the difference betweenearly bilinguals, late bilinguals, and early bilinguals with respect to semantic priming.The null hypothesis is that if indeed there is no difference in the organization of twolanguages for those who learned both languages at an early age versus those wholearned a second language after early childhood, then one would not expect that thereismany difference in the semantic priming effect for these two groups. In addition, onewould not expect that the subjects would perform any differently on the recognitiontask.PROCEDURE:Thisstudy was modelled after the study by Sentin, Kutas, and Hillyard whoinvestigated semantic priming with auditory stimuli. Their study found a reducedN400,thus an effect of semantic priming, when stimuli were presented auditorily. Thecurrent study uses Sentin, Kutas, and Hillyard (1993) as a basis to investigatesemantic priming in bilinguals. Thus, the main added variable was the use of twodifferent languages. The study used targets in English primed by English words (E-E),targets in English primed by Spanish words (S-E), Spanish targets primed by Englishwords (E-S), and Spanish targets with Spanish primes (S-S). The purpose of usingthesefour types was to find if early bilinguals, late bilinguals, and people just learninga second language show semantic priming within languages (S-S and E-E) andacross languages (E-S and S-E). The hypothesis was that early bilinguals wouldshowgreater semantic priming than the late bilinguals and similarly, the learnerswouldshow even less of an effect of semantic priming than the late bilinguals.

The second part of the study was designed to test how we" the subjects didindeedlearn the words, a sort of recognition task. It also was designed to see ifperhaps early bilinguals code their words at a semantic level while late bilinguals domoresurface processing. The list presented included target words that were on theprevious list, target words that were not, and some words that were translations of


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targetwords on the previous list. The hypothesis here being that the early bilingualswouldmake more mistakes if they were "paying more attention to" the meaning of thewordsrather than which language they were in, thus suggesting that they process on asemantic level rather than a surface level. Again, processing at the semantic levelindicates that there is some feature about an object or idea that is represented in thebrainin a particular way which is shared by both languages. Surface processing, ontheother hand, has to do with grammatical and other such organizational features ofan idea.SUBJECTSThesubjects were college students who volunteered for the study or were givenlaboratorycredit for their Introductory to Psychology course. All subjects were right-handedwith normal hearing. There were five pilot subjects whose data were not usedinthe study but rather were simply test subjects used to insure that the study wouldproceedsmoothly. There were seven subjects in the early bilingual group, seven inthelate bilingual group, and four in the learner group. Subjects in the early bilingualgroupwere mainly those who had been brought up speaking both English andSpanishor had studied it from an early age (at least before age 9). Late bilingualswerethose who became fluent after age 10. They had either studied or moved to orfroma Spanish-speaking country. Learners were those who had possibly beenexposedto Spanish earlier but had not studied it or had not become familiar with thelanguageuntil much later, for example in high school or college.STIMULIThewords used were recordings of a female voice digitized by the NeuroScan STIMSoundprogram. Each word was a separate Sound file and each file was baselinecorrectedand filtered in order to control for irrelevant sounds recorded. Each wordwasrecorded through a microphone, corrected, and then moved to the beginning ofthefile so that all of the stimuli onset were equivalent. Words were no longer than 700


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24ms. The stimuli were presented biaurally through foam insert earphones at a preset90.0dB. The stimulus onset interval was set at 2000 ms, 250 ms longer than the SOAusedby Sentin et al. The reason for the difference was due to difficulties with the STIMsystemthat could only be avoided by increasing the SOA.

The first task was to listen to a list of word pairs based on a list provided by theauthorsof the Sentin, Kutas, and Hillyard study. Their list consisted of 128 word pairsbutthe list used here was expanded to include 144 word pairs. The added pairs werebasedon word pairs considered, but not actually used by Sentin et al. Sentin andcolleagues had chosen only words that ranged in frequency from 10 to 2,110 permillionoccurrences as noted in Francis & Kucera (1982), and they cited a meanfrequencyof 83.7. They also used word pairs that had been previously ranked,accordingto relatedness, by eighty students. They only chose word pairs that weregivena mean rating above 2.95 for semantic relatedness. These were the word pairsalsoused in the current study to form a general list of 144 semantically related pairs.Thelist of semantically related words was then broken into four categories (S-S, S-E,E - S , or E-E). This was accomplished by assigning numbers 1-4 to the list of wordpairswhich were ranked in order of semantic relatedness, the rating assigned from theSentinet al. study. The word pairs of each of the four categories were then assignedeitheran R or a U. In order to form two lists from the 144 related pairs, the list of wordswasdivided up such that for one list the pairs with a U were kept related while thosewithan R were made unrelated, while in the other list the U pairs were made unrelatedwhilethe R pairs were kept with their related primes. Thus there were two final lists,ListA and List S, where List A was a randomly assigned list of word pairs in which theR targets were kept with their related prime while the U targets were randomlyassignedan unrelated prime that was of the same category type (S-S, S-E, E-S, or E-E ) . List B consisted the same list of word pairs but the U pairs were kept with theirrelatedprimes while the R pairs were made unrelated. The random reassignment of


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primesfor each list, in order to make the unrelated pairs, was within type, so that forexamplea S-E target was sure to have an unrelated prime that was in Spanish. As intheBentin, Kutas, and Hillyard study, there were pairs of categorically related words aswellas antonyms. In order to increase the number of pairs, both categorically relatedpairsand antonyms were added, although more antonyms were added so that theproportionof antonyms to categorically related pairs was greater than in the 8entin etal.study. This was deemed acceptable because 8entin et al. did not find a significantdifferencebetween the types and collapsed their data. They found that priming wasslightlybetter for antonyms but it was not statistically significant. Therefore, there wasnothreat of affecting the data by adding more antonyms than categorically relatedpairs;the only effect would be an increased overall semantic priming, but this wouldbeforall three groups (early, late, and learners) so would not affect the results of thisparticularstudy.

F IG U R E 119 pairs of S-S U17 pairs of S-E U19 pairs of E-S U17 pairs of E-E U

17 pairs of S-S R19 pairs of S-E R17 pairs of E-S R19 pairs of E-E R

In both List A and List 8 there were thirty-six across-language unrelated pairsandthirty-six across-language related pairs while there were thirty-six same-languageunrelatedpairs and thirty-six same-language related pairs (see Figure 1). See Figure2fora division of the categories into the two lists. Both lists had the same order fortheirtargets, thus only the order of the primes was different for the two lists.


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-----"-----------------------------------------------------FIGURE219 pairs of S-S Unrelated17 pairs of S-E Unrelated19 pairs of E-S Unrelated17 pairs of E-E Unrelated

17 pairs of S-S Related19 pairs of S-E Related17 pairs of E-S Related19 pairs of E-E Related

List A:

19 pairs of S-S Related17 pairs of S-E Related19 pairs of E-S Related17 pairs of E-E Related

17 pairs of S-S Unrelated19 pairs of S-E Unrelated17 pairs of E-S Unrelated19 pairs of E-E Unrelated

List B:

The second task consisted of a recognition task using a list of 144 words. Thelistwas simply the list of targets from the previous task divided up into three categoriesandput in a new randomly assigned order. One third of the words in this list were thesametargets presented again, one third were a translation of targets (that is, if thewordwas previously DOG, the new word presented was that same word but inSpanish, PERRO), and one third were completely new unrelated words. Theseunrelatedwords were assigned so as to have the same amount of Spanish andEnglishwords as there was in the one third of the list of targets. Then this new list wasrandomized in order to intersperse the three categories (Old, New- Translation, andNew-Unrelated). The New- Translation group was a substitution for the New- Relatedgroupused in the Sentin, Kutas, and Hillyard study. From here on the "New" categorywillbe used to refer specifically to the New- Unrelated group, which "Translation" willbeused to refer to the New- Translation words. See Figure 3 for a division of the threecategories.


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FIGURE3New: 8-8: 6 R, 6 U8-E: 6 R, 6 UE-8: 6 R, 6 U

E-E: 6 R, 6 U

Old: 8-8: 5 R , 7 U8-E: 6 R, 6 UE-8: 5 R, 7 UE-E: 6 R, 6 U

Translations: 8-8: 6 R, 6 U8-E: 7 R, 5 UE-8: 6 R, 6 UE-E: 7 R, 5 U

METHODInthe first task, the subject was asked to listen to a list of words, some of which were inEnglishand some in Spanish. The subject was told that he would see a gray screenwitha light blue cross in the center and was asked to fixate on the blue cross, movinghishead as little as possible and blinking at a comfortable rate but trying not to blinktoooften. Then he was asked to memorize as many of the words as he could. Finally,the list was presented and the ERP was measured while the subject was listening tothe list and trying to memorize these words.

After the list was finished the subject was instructed that she would now hearanother list of words, some of which were on the previous list and some of which werenot. She asked to place her right hand on the mouse, with her index finger on the keyonthe left, and her middle finger on the key on the right. Then she was asked torespondto each word she heard, that if the word she heard was on the previous list, topressone of the keys and if it was not on the previous list, to press the other key.Subjectswere counterbalanced for which finger they used for new and old words.Thus,the subjects who heard List A were divided in half, half of them were required topressthe left key for old words and half were required to press the right key for oldwords. Subjects who heard List B were also divided in this way. In the second task,ERPwas not measured. The point of the second task was two-fold. The first objectwasto make sure the subjects did in fact memorize the words in the first list. The other

..


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goalof the second task was to measure the reaction time. It was predicted that theEarlybilinguals would react faster, if indeed early bilinguals process at a moresemantic level than late bilinguals, who may process at the surface level. Similarly, itwaspredicted that the Early bilinguals would actually make more mistakes on theNew-Translation words than the Late bilinguals. This is because if Early subjectswereprocessing the words at a semantic level, perhaps their coding for language waslesssignificant and would be more readily ignored when they heard the translation oftheword in the previous list. In other words, they were processing the wordssemanticallyso when recognizing words, the translation of the target would would callupthe same semantic representation and these subjects would mistakenly claim thewordwas indeed on the previous list when it was not.

Finally, each subject was asked to fill out a questionnaire to rate his languageabilities,performance on the tasks, and other personal questions such as if he knewanyother languages.ELECTROPHYSIOLOG ICAl DATA COLLECTIONTheevent-related potentials were recorded from electrodes in the Electrocap. Therecordingsites used were Fz, Pz, Cz, P3, P4, TS, and T6. In addition, vertical eyemovementsand blinks were recorded from one individual electrode placed above theeyeand another just below. Additional individual electrodes were used, one behindeachear over the right and left mastoids, for the purpose of off-line averaging. Again,theuse of the mastoids (as opposed to using earlobes) was due to the attempt toreplicateas closely as possible the Sentin et al, study. While each of the lists werepresented,the subjects were asked to fixate on a small light blue cross which waspresentedon a dark gray screen. This was in an effort to limit movement of the headandeyes of the subject while the data was being recorded. Each word wasconsidereda separate sweep, lasting 1300 ms. The program for the lists of words waswrittenon Gentask, a program within the STIM system of Neuroscan. The Gentask file


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communicates with the SCAN system, which records the EEG. Each sweep beganexactly100 ms before the stimulus was presented and ended at 1200 ms after theonsetof the stimulus. This period was used to allow for later analysis of the datawherethe total EEG would be divided into epochs as in the Sentin, Kutas, and Hillyardstudy.RESULTS

Each ERP was baseline corrected for all the of the electrodes, using theprestimulus interval (-100 to 0 ms) as the baseline measure. Then each ERP wasartifactreduced to correct for eye blinks, usually using around a 450 millisecondsweepduration and a trigger threshold of ten percent. Finally, the data was runthroughan artifact rejection process. Once the data was collected and corrected,averageswere taken for each of the types one through twelve for each subject. Typeassignmentscan be seen in Figure 4. Averages were also taken for each of thecategories (unrelated targets, related antonym targets, and categorically relatedtargets)regardless of which kind of pair (S-S, S-E, etc.). This was to done so that itcouldbe analyzed whether or not there was indeed a reduced N400, an effect ofsemanticpriming, for related versus unrelated targets.

FIGURE4E R P types: 1: S-S Unrelated

2: S-E Unrelated3: E-S Unrelated4: E-E Unrelated5: S-S Related Antonym6: S-E Related Antonym

7: E-S Related Antonym8: E-E Related Antonym9: S-S Related Category10: S-E Related Category11: E-S Related Category12: E-E Related Category

The ERP averaged files were then used to measure the mean amplitudebetween400 and 700 ms. This epoch was used because in the Sentin et al. study,

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30thiswas th.e epoch in which they found the greatest effect of semantic priming. Thisdatawas analyzed in a multifactorial analysis of variance with repeated measures.TheANOVA consisted of a dependent variable of mean amplitude with one betweensubjects measure (Group) and two within groups measures (Electrode site andRelatedness). The repeated measure of Group had three levels: Early, Late, andLearner. Electrode site was divided into the seven electrodes: Fz, Cz, Pz, P3, P4, T5,T6. Relatedness of targets also had three categories: Antonym, Categorically related,andUnrelated. The ANOVA showed the following significant effects: Group: F (2,15) =6.254,P = .0106; Electrode site: F (6,90) = 33.626, P = .0001; Relatedness: F (2,30) =6.473,P = .0046. There was also an interaction effect of Relatedness and Group: F(4,30)= 6.427, P = .0007. No other effects were significant. Further comparisons wereperformed in order to view the effects within the variables. Early and Late groups werecontrasted (F [1,15] = 3.325, P = .922) as were Late and Learner groups (F [1,15] =3.951,P = .0654) and Early versus Learners (F [1,15] = 12.401, P = .0031). There wasasignificant interaction effect of Relatedness with Early versus Late subjects (F [2,30] =5.440,P = .0096), a significant effect of Relatedness with Late versus Learners (F[2,30]= 5.223, P = .0113), and a significant effect of Relatedness with Early versusLearner(F [2,30] = 8.888, P = .0009). See Appendix B for means tables. Thesignificanteffect of Relatedness also called for more detailed analysis such as RelatedversusUnrelated (F [1,30] = 1.394, P = NS) which combined the Category andAntonymcategories to form the Related group. Then Category and Antonym werecontrastedto find a significant difference between the two (F [1,30] = 11.551, P =.0019). Similarly, Category versus Unrelated was significant (F [1,30] = 7.409, P =.0107)although Antonym versus Unrelated was not (F [1,30] = .458, P = NS). No othersignificanteffects were found for the ERP data.

The overall performance of all subjects on the recognition task 49.0% correct.Subjectsdid better on the New words (57.2%) than they did on the Translations


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31(50.8%)while scoring the lowest on the Old words (45.2%). The mean latency overallwas1.1768 ms and was divided as such: 1.1878 for the New words, 1.1677 for theOldwords, and 1.1829 for the Translation words. It should be noted that therecognition task data for one of the eighteen subjects was not used because it wasincomplete due to a computer error in presentation. This subject was one of the fourLearnersubjects. The recognition task data was also subjected to an ANOVA withrepeated measures. The latency and percent correct measures were individuallycompared to two between-subject measures, Group (Early, Late, and Learner) and List(ListA and List B), as well as one within-subject variable which was the Type. Typewasbroken up into eighteen cells as described in Figure 5.

FIGURE5131: Translation from S-S Related 151: Old from S-S Related pair132: Translation from S-E Related 152: Old from S-E Related pair133: Translation from E-S Related 153: Old from E-S Related pair134: Translation from E-E Related 154: Old from E-E Related pair135: Translation from S-S Unrelated 161: Old from S-S Unrelated pair136: Translation from S-E Unrelated 162: Old from S-E Unrelated pair137: Translation from E-S Unrelated 163: Old from E-S Unrelated pair138: Translation from E-E Unrelated 164: Old from E-E Unrelated pair

141: Spanish New Unrelated142: English New Unrelated

The results of the ANOVAs showed no significant effects for latency. The onlysignificanteffect for percent correct was List: F (1,13) = 7.147, P = .0191 as seen inAppendixC. More detailed analysis of the types, which required collapsing acrosscertaintypes such as Old, New, Translation, Related, and Unrelated resulting in asignificanteffect of type for Old versus New words (F [1,221] = 5.000, P = .0264).Translation versus New, Related Translation versus Related Old, and UnrelatedTranslation versus Unrelated Old, all proved insignificant. Other contrasts were


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performed, such as looking at response to targets from between-language pairs ascompared to within-language pairs, but none appeared to be statistically significant.DISCUSSION:

Just from glancing at the grand averages for the related targets versus theunrelated targets, one can see a decreased negativity for the related words around400 ms for most of the electrode sites (See Appendix D , parts I-XII). Similarly, theeffectof relatedness was a significant one. This indicates a replication of the semanticprimingeffect found in the Sentin et at. study. Looking again at the grand averages,thepeak is clearly delayed, usually greatest at around 430 ms, an effect also found intheBentin study. Sentin et al, also found a negative wave at about 100 ms afterpresentation of the stimuli which can also be seen in the grand averages for thecurrentstudy. The other important result to note in the grand averages is thedifference between the electrodes. Fz, Cz, and Pz were clearly more negative andseemto show greater semantic priming (see Graph 1). Similarly, P3, P4, T5 and T6whichare more posterior and parietal sites, did not show as great of negativity as thethreecentral and more anterior locations. This is consistent with the results noted byBentinand colleagues who found that "during the 300-900-ms epoch the ERPs weresignificantly more negative frontocentrally than at the parietal and temporal sites"(Bentinet aI., 1993, p. 163).

'-


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GRAPH 1Interaction Plot Effect: ELECTRODE SITEDependent: MEAN AMPLITUDEwith standard error bars

wP: : Jr -: : s -0~~~

.: 1

~ ~24-;0


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' R A P H 2

\ 34\

Effect: GROUPDependent: MEAN AMPLITUDEwith standard error bars

Interaction Plot

-.6

~ -.8( : 4: : > - 1E - < I: : 1 -1.2P o .~ -1.4~~

-1.6

~ -1.8. .. . -20II)

~ -2.2C 1 i~ -2.4. . . . . . -2.6C 1 io -2.8

P H 3

EARLY LATEGROUP

LEARNER

Effect: RELATEDNESSDependent: MEAN AMPLITUDEwith standard error bars

Interaction Plot

-.4

~ -.6( : 4: : >E - < -.8: : 1P o . - 1~~ -1.2~ -1.4. .. .0II) -1.6~C 1 i -1.8~.. . . -2. .. C 1 iU

-2.2CATEGORY ANTONYMi-

RELATEDNESSUNRELATED


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R A P H 2

\ 34

Effect: GROUPDependent: MEAN AMPLITUDEwith standard error bars

Interaction Plot

-.6~ -.80; :J - 1 - < 1 . . . . -1.2..l~ -1.44;~

-1.6~ -1.8. . .0 -2(/)

~ -2.2a J~ -2.4. . . .. . . . -2.6a JU -2.8

P H 3

EARLY LATEGROUP

LEARNER

Effect: RELATEDNESSDependent: MEAN AMPLITUDEwith standard error bars

Interaction Plot

--.4~ -.60; : JE - < -.8: : 1~~ - 1

~-1.2

~ -1.4. . .0(/) -1.6a J -1.8: ? :. . . . -2. . .a JU -2.2CATEGORY . UNRELATEDNTONYMRELATEDNESS


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In Graph 3 we see the effect of relatedness. Although there was not an overalldifference between the related words and the unrelated ones, the categorically relatedtargets words displayed significantly less negativity than antonyms and unrelatedtargets. There was a significant contrast between category and antonyms as well asbetween category and unrelated. Antonym and unrelated targets did not show anysignificant difference. In the Bentin et al. study, the antonyms actually showed agreatereffect of semantic priming for antonym targets than for categorically relatedtargets,although this effect was not a statistically significant one. There are severalpossibleexplanations for why the antonyms did not show the same effect in this study.Theexpectation had been that the antonyms would be approximately equivalent to thecategorically related words. This was not the case overall. By looking at theinteraction effect of relatedness and group (see Graph 4), we can see that for the earlygroupthe category type was much higher than the antonym while results for the lategroupshowed that they were equivalent. The most bothersome evidence comes fromthelearners, who show the opposite effect than was expected. The fact that theantonymsfor the learners was so significantly different is reason for concern. One factthatshould be investigated is the difference in List A versus List B. There was asignificant difference in the recognition task and if this is representative of this data,someunderstanding may evolve from a comparison of the two lists for the ERP data.Forinstance, in the recognition task, the percent correct was much lower for List A thanforList B. This may be interpreted as those subjects who were presented List A forsomereason showed less semantic priming, as possibly shown in the recognitiondata. If this is the case, there may be something wrong with the structure of List A andifonly List B were analyzed for relatedness * group effects, perhaps there would beresultsmore consistent with the Bentin et al. study. Another possibility is thatantonymsacross languages are just not the same as antonyms within languages.Thiscould be for a number of reasons. One reason is that oftentimes antonyms are

35


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.. "' . . .

36

culturally defined, or at least emphasized more in some societies than in others, suchas BLACKIWHITE. Perhaps trying to prime across languages for these kinds of pairsdoes not prove to be consistent with a semantic priming effect. Also, usingBLACKIWHITE again as an example, perhaps these are not in fact coded as antonymsacross languages but rather as categorically related words under the category"COLORS". Another possible explanation is the fact that words do not always havesemantic equivalents across languages. The Spanish words used were asconceptually accurate translations from the English words provided by Sentin andcolleagues as is possible; however that still does not rule out the possibility of a wordin one language meaning something slightly different in the other language. Similarly,homophones were avoided as much as possible, but it is clear that some words caninitiate several different semantic codes. The word "sink" can be interpreted as theobject in a kitchen or it can be the verb of an object not staying afloat. Perhaps primesthat could have more than one meaning were misleading, especially in the case ofantonyms. For List A and List S word pairs, see Appendix E I-II.

GRAPH 4Interaction Plot Effect: RELATEDNESS * GROUP

Dependent: MEAN AMPLITUDEwith standard error bars

~ .50;: J 05~ - .5~

- 1 ~ f0 CATEGORY

~ - 1 .5 i ANTONYM~ Ii UNRELATED'+ - < - 20III - 2 .5C l) -3~~ -3.5l)U

-4EARLY LATE LEARNER

GFOJP


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". -37

The recognition data provided results that were quite curious. First of all, therewas no significant effect of latency. Second of all the percent correct overall was only49.1 percent, significantly lower than that of the Sentin et al. study, and only at chancelevel. See Graph 5 for percent correct by group. One interpretation of this result is thatthe subjects did worse because of the added language. In other words, perhaps therewas an overall effect of language being a confusing factor in the task, causing all of thesubjects to perform worse. One way to investigate this would be to contrast the meanpercent correct for the bilingual groups, the Early and the Late groups, with theLearner group. If indeed the mean was significantly higher for the bilingual groupsthan for the learning group, then it may be that the early bilinguals did not display anysignificant number of false alarms on the translations because the overall performanceon this recognition task was so poor. This could be further investigated by examiningthe data to see whether the bilinguals did better overall. One would expect that thebilinguals would have done better than the learners if just the added language was thefactor that caused the subjects to perform so poorly on the recognition task. If thebilinguals did better than the learners, then it is possible that overall performance wasskewed by the data from the learners. It would also be important to investigatewhether the two bilingual groups had the same success rate on the translations.

. ..


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- - - - - .

The most problematic result of the recognition task, as well as the study overall,is the difference found in List A and List 8 (see Appendix C for means table andgraph). Again, this could be due to an uneven distribution of problematic words likehomophones or a poor translation. Tzelgov and Eben-Ezra (1992) note that abstractand concrete words yield different results in semantic priming. Perhaps there was atrend for more abstract words to be found in List A. The difference between the twolists may also be a problem relating to the distribution of subjects who were presentedeach of the lists. There were several subjects in List 8 who did exceptionally well onthe recognition tasks, so perhaps this caused differences in the data. Similarly,because one of the subject's data was not used, there was only one subject in theLearner group that was presented with List 8; if this subject happened to do very wellon the task, the entire learner group as well as the overall data may have beenaffected by this. A way to investigate this further would be to test more subjects so as

GRAPH 5

5352

I- 51o 50a:a: 490o~ 48'0 47(/)c< ll 46)~Qi 45o 44

4342

38

Interaction Plot Effect: GROUPDependent: PERCENT CORRECTwith standard error bars

EARLY LATE LEARNERGroup...,


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.Js, -10.80(JI:

-1.61

3.20 Unrelated(green)

A P P E t i D I X Dpart IUelated vs(red)

2 . 40

1.60

0.80

-2 .4 0

- 3.20

-4.00' , I I I I I I I I I

- 1 00 30 940 1070 1 2006 0 2'~0 4 20 55 0 680 810

11 I I iseconds


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GRAND AVERAGE.

Unrelated(green)

A P P E N D I X Dpart VRelated vs(red)

4.10

3.2 0

2 . 30

1.40

0.513l~+'o:>obI:

-1. 30

-2 . 20

-3.10

-4.13 0 1 I I I I I I I I I I-1013 30 8 10 940 107061 3 290 420 550 680

11ll i seconds

1 200


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~~oJob -13.40~

G R A H D A V E R A G E4.10 Related us Unrelated

(red) (green)A P P E N D I X Dpart VI

3.20

2.31 3

1.40

0.50

-1.30

-2.20

-3.10

-4.013 I I I I I I I I ! I I

-1 13 0 un 0 12 0013 4213 810 '~4 060 290 5 s e 6313

11iI I iseconds


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GRAND AVERAGE

R el at ed v s U nr el at ed( r ed ) (g re en )

4.10 A P P E N D I X Dp ar t V I I

3 . 2 1 3

2 . 3~ 3

1.413

lq+'-o::>.JbI:

-1.30

- 2 . 2 1 3

-3.113

-4.1313' , I I I I I I I I I

-1 00 30 8 1 0 94 0 un1360 2913 4213 550 6 8 0

11 1 1 j sec ond s

12013


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APPEND IXE - part I L IST A

1 C LLWIA KIDNEY 3.05 2 u 22 C BOCA JURY 3.44 2 u 23 C YEAR MONTH 3.36 4 r 124 C BEE RO BLE I 3.10 3 u 3

I 5 C CORBATA CHAQUETA 3.35 1 r 96 A BARCO SECO 3.54 1 u 17 C CANDY BOOK 3.32 4u 48 C DOOR WINDOW 3.26 4 r 12

I 9 A OFTEN LLENO 3.00 3 u 31 0 C MOTOR ENG INE 3.51 4 r 121 1 C TRACTO 'R LENS 3.26 2 u 21 2 C DOCTOR ENFERMERA 3.56 3 r 111 3 C NEST SMOKE 3.00 4 u 41 4 A SUMMER INVIERNO 3.46 3 r 7

1 1 5 C VIA GATO 3.97 1 u 111 6 C EARTH LUNA 3.21 3 r 111 7 C INFANTE BABY 3.61 2 r 101 8 A MIEDO VALENTI' A 3.08 1 r 51 9 A TH IN OESTE 3.28 3 u 32 0 A WIN PERDER 3.06 3 r 72 1 A JAMON MEJOR 3.45 1 u 12 2 C ENFERMO TIO 3.29 1 u 12 3 A LONG FOUND 3.23 4 u 42 4 A WHEEL DENSO 3.21 3 u 32 5 C FUTURE ELEG IR 3.41 3 u 32 6 A AGWA LAST 3.26 2 u 22 7 A FRIJOLES SANO 3.67 1 u 1

!

2 8 C CABEZA PELO 3.23 1 r 92 9 C KNIT SEW 3.45 4 r 1230 C RELAX DISFRUTAR 3.25 3 r 1131 C CORDERO OVEJA 3.48 1 r 932 C MANZANA ORANGE 3.24 2 r 1033 A FLOAT SINK 3.39 4 r 834 C VERDURA FRUTA 3.70 1 r 935 A ACTIVE PASIVO 3.26 3 r 736 A CIGAR NONE 3.32 4 u 437 A SUAVE DURO 3.26 1 r 53 8 C PISTOLA RIFLE 3.28 2 r 103 9 A MAS LES S 3.29 2 r 640 C CERRADURA KEY 3.16 2 r 1041 C MOJADO OJO 3.18 1 u 142 A COMPRAR IR 3.32 1 u 11 43 C LOST BUTTER 3.63 4u 444 C RARAMENTE NEVER 3.80 2 r 1045 A TRUE FALSE 3.19 4 r 846 A FAME LEVANTARSE 3.72 3 u I 3

:=un related, r= related)


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APP ENDIXE - part I L IST A

4 7 A TOBACO NIGHT 3.07 2 u 24 8 C HOUSE CIUDAD 3.47 3 r 114 9 C CAR CAMION 3.32 3 r 115 0 A SU N PASAOO 3.51 3 u 3S 1 A OPEN CLOSED 2.97 4 r 85 2 A MESA TARDE 3.02 1 u 15 3 C CERCA PIPE 3.22 2 u 25 4 A HI 'GADO O LD 3.69 2 u 25 5 C BATH TU B 3.57 4 r 125 6 C OREJA GUISANTES 3.10 1 u 15 7 A HIGH BAJO 3.59 3 r 75 8 A GOOD BAD 3.62 4 r 85 9 C LARGE ENORME 3.39 3 r 116 0 C SIT M IEL 3.27 3 u 36 1 A GAME DE'BIL 3.41 3 u 36 2 A EMPEZ AR PARAR 3.61 1 r 56 3 C AR MY MARINA 3.43 3 r 116 4 A ODIAR LOVE 3.82 2 r 66 5 A EAST TOSCO 3.11 3 u 36 6 C MOV IE GREEN 3.37 4 u 46 7 C PINE SIEMPRE 3.79 3 u 36 8 A PUSH PULL 3.28 4 r 86 9 A ARRIBA BELOW 3.52 2 r 6

I 7 0 C JO 'VEN MATAR 2.97 1 u 17 1 C MADURO ADULTO 3.39 1 r 97 2 C LIFE LLANTA 3.52 3 u 37 3 A PRIM ERO UG LY 3.15 2 u 27 4 A DREAM W IDE 3.15 4 u 47 5 C NEGRO CALLE 3.61 1 u 1

I 7 6 A L I'DER FOLLOWER 3.13 2 r 6I 7 7 C MERCADO BOTE 3.24 1 u 17 8 C PECHO SHOULDER 3.36 2 r 107 9 A IZQU IERDA DERECHA 3.18 1 r 58 0 A TEMPRANO VENDER 3.21 1 u 18 1 C CABALLO COW 3.52 2 r 10

I 8 2 C CORAZON TIENDA 3.47 1 u 18 3 C ALL SLEEP 3.55 4u 48 4 C GRIEF PENA 3.67 3 r 118 5 C BLOSSOM GLOR IA 3.24 3 u 38 6 C TENNIS RACKET 3.23 4 r 128 7 A ROMPER ARREGLAR 3.72 1 r 58 8 A FRIEND ENEMY 3.72 4 r 8

1 8 9 A VENIR RECHAZAR 3.14 1 u 19 0 C BRAZO PIERNA 3.56 1 r 99 1 C PINTURA BROCHA 3.26 1 r 99 2 A PEOR BLANCO 4.00 11u 1

(u=unr elated , r=re lated)


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APPEND IXE - part I L IST A

93 C CO MENZ AR SHOES 3.33 2 u 294 C STORM WIND 3.08 4 r 1295 C RIO STREAM 2.97 2 r 1096 A FELIZ SAD 3.00 2 r 697 C PERRO PULMONES 3.43 1 u 198 A IMPAR EVEN 3.21 2 r 699 A COPPER PEACE 3.68 4 u 4100 C NARROW F ILM 3.21 4 u 4101 C BONITO THREAD 3.68 2 u 2102 A A'NGEL FAR 3.61 2 u 2103 C VINO CERVEZA 3.13 1 r 9104 C RAT MOUSE 3.40 4 r 12

: 105 A LIVE D IE 3.47 4 r 81106 A DEEP SHORT 3.46 4 u 4107 A ANTES AFTER 3.66 2 r 6108 C WARM BRASS 3.11 4 u 4109 A BOTAS DEV IL 3.46 2 u 2110 C FLOWER GALLETA 2.95 3 u 3

1111 C ENO JAD O ENFADADO 3.07 1 r 91112 C GENTLE JUGAR 3.15 3 u 3113 A FRONT TRAS 3.69 3 r 7114 A BREAD SMOOTH 3.05 4 u 4115 C ROUGH TREE 3.43 4 u 4

1116 C JUEZ NOSE 3.12 2 u 2117 A POBRE RICO 3.47 1 r 5118 C BLUE HOT 3.47 4 u 4119 C WAR BIRD 3.25 4 u 4120 C ACEPTAR SILLA 3.53 1 u 1121 C BARN FARM 3.70 4 r 12122 C MAR ISLAND 3.43 2 r 10123 C SON DAUGHTER 2.95 4 r 12124 C CH IQU rrO SNOW 3.56 2 u 2125 A GAFAS END 3.35 2 u 2126 C H ILL MONTAN"A 3.12 3 r 11127 C TIA CERDO 3.37 1 u 1128 A G IVE RECIBIR 3.33 3 r 7129 C ARCO ARROW 3.45 2 r 10130 C ASESINAR PLOW 3.39 2 u 2131 A D IFF IC ULT EASY 3.08 4 r 8I132 C HAND PIE 3.00 3 r 11133 C WOOD ESTRELLA 3.36 3 u 3134 A AUTHOR SHALLOW 3.55 4 u 4135 C SORPRESA SOBRESALTO 3.45 1 r 9136 C MONK PRIEST 3.15 4 r 12137 C EMPTY FLORECER 3.58 3 u 3138 A VOTE MUERTE 3.63 3 u 3

'u=unrelated. r=related)~


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APPENDIXE - part I LIST A

1 3 9 A AMARGO DULCE 3.35 1 r 51 4 0 C STRONG META'LlCO 3.45 3 u 31 4 1 A INCORRECTO RIGHT 3.42 2 r 61 4 2 C DIA LITTLE 3.48 2 u 21 4 3 A NOISE SILECIO 3.15 3 r 71 4 4 C MAESTRO STUDENT 3.10 2 r 10

u=unrelated, r=related)


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AP PEND IX E - p art II List B

1 C H I'G ADO KIDNEY 3.05 2 u 102 C JUEZ JURY 3.44 2 u 103 C BARN MONTH 3.36 4 r 44 C PINE ROBLE 3.10 3 u 115 C BRAZO CHAQUETA 3.35 1 r 16 A MOJADO SECO 3.54 1 u 5

I 7 C AUTHOR BOOK 3.32 4 u 128 C GOOD W INDOW 3.26 4 r 49 A EMPTY LLENO 3.00 3 u 710 C TRUE ENG INE 3.51 4 r 411 C GAFAS LENS 3.26 2 u 1012 C GRIEF ENFERMERA 3.56 3 r 3

! 13 C CIGAR SMOKE 3.00 4u ' 12: 14 A RELAX INV IERNO 3.46 3 r 3115 C PERRO GATO 3.97 1 u 9I 16 C FRONT LUNA 3.21 3 r 317 C FELIZ BABY 3.61 2 r 218 A SUAVE V ALEN TI' A 3.08 1 r 119 A EAST OESTE 3.28 3 u 720 A ACTIVE PERDER 3.06 3 r 3

I 21 A PEOR MEJOR 3.45 1 u 5I 22 C TIA TIO 3.29 1 u 9123 A LOST FOUND 3.23 4u 8124 A TH IN DENSO 3.21 3 u 7I 25 C VOTE ELEG IR 3.41 3 u 1126 A PRIMERO LAST 3.26 2 u 627 A ENFERMO SANO 3.67 1 u 528 C PINTURA PELO 3.23 1 r 1129 C YEAR SEW 3.45 4 r 4! 30 C LARGE DISFRU TAR 3.25 3 r 3I 31 C ROMPER OVEJA 3.48 1 r 132 C PECHO ORANGE 3.24 2 r 233 A DOOR SINK 3.39 4 r 434 C SORPRESA FRUTA 3.70 1 r 1

I 35 A NO ISE PASIVO 3.26 3 r 3I 36 A ALL NONE 3.32 4u 83 7 A IZQU IERDA DURO 3.26 1 r 138 C IMPAR RIFLE 3.28 2 r 239 A PISTOLA LES S 3.29 2 r 240 C INCORRECTO KEY 3.16 2 r 241 C OREJA OJO 3.18 1 u 942 A VENIR IR 3.32 1 u 5143 C BREAD BUTTER 3.63 4 u 12144 C CERRAD URA NEVER 3.80 2 r 2

145 A SON FALSE 3.19 4 r 41146A SIT LEVANTARSE 3.72 3 u 7

(u=related, r= u n re la ted )


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APPENDIXE - part II List B

47 A D IA INIGHT 3.07 2 u 648 C FRIEND CIUDAD 3.47 3 r 349 C SUMMER ICAM ION 3.32 3 r 350 A FUTURE PASAOO 3.51 3 u 751 A MOTOR CLOSED 2 .9 7 4 r 452 A TEMPRANO TARDE 3.02 1 u 553 C TOBACO PIPE 3.2 2 2 u 1 054 A JO'VEN O LD 3.6 9 2 u 655 C D IFF ICULT TUB 3.57 4 r 456 C FRIJO LES GUISANTES 3.1 0 1 u 957 A CAR BAJO 3.59 3 r 358 A RAT BAD 3.6 2 4 r 459 C G IVE ENORME 3.39 3 r , 36 0 C BEE M IEL 3.2 7 3 u 116 1 A STRONG DE'BIL 3.4 1 3 u 76 2 A ODIAR PARAR 3.6 1 1 r 16 3 C H IGH MARINA 3.43 3 r 36 4 A ENOJADO LOVE 3.8 2 2 r 26 5 A GENTLE TOSCO 3.1 1 3 u 76 6 C BLUE GREEN 3.37 4 u 1 26 7 C O FTEN SIEMPRE 3.7 9 3 u 116 8 A FLOAT PULL 3.2 8 4 r 46 9 A RIO BELOW 3.52 2 r 27 0 C ASESINAR MATAR 2 .9 7 1 u 97 1 C CORBATA ADULTO 3.39 1 r 17 2 C WHEEL LLANTA 3.52 3 u 1 17 3 A BONITO UGLY 3.15 2 u 67 4 A NARROW WIDE 3.1 5 4u B7 S C VIA CALLE 3.6 1 1 u 97 6 A INFANTE FOLLOWER 3.1 3 2 r 27 7 C BARCO BOTE 3.2 4 1 u 97 8 C M AESTRO SHOULDER 3.36 2 r 27 9 A VERDURA DERECHA 3.1 8 1 r 18 0 A COMPRAR VENDER 3.2 1 1 u 58 1 C ARCO COW 3.52 2 r 2

1 8 2 C MERCADO TIENDA 3.47 1 u 98 3 C DREAM SLEEP 3.55 4u 1 28 4 C DOCTOR PENA 3.6 7 3 r 38 5 C FAME GLORIA 3.2 4 3 u 1 18 6 C L IVE RACKET 3.2 3 4 r 48 7 A AMARGO ARREGLAR 3.7 2 1 r 18 8 A EARTH ENEMY 3.7 2 4 r 48 9 A ACEPTAR RECHAZAR 3.1 4 1 u 59 0 C MIEDO PIERNA 3.56 1 r 19 1 C CABElA BROCHA 3.2 6 1 r 19 2 A NEGRO BLANCO 4.00 1 u 5

~=related,r=unrelated)


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APPEND IX E - part II List B

93 C BOTAS SHOES 3.33 2 u 1094 C KNIT W IND 3.08 4 r 495 C CABALLO STREAM 2.97 2 r 296 A Lt'D ER SAD 3.001 2 r 297 C CORAZON PU LMONES 3.43 1 u 998 A MANZANA EVEN 3.21 2 r 299 A WAR PEACE 3.68 4 u 8100 C MOVIE FILM 3.21 4u 12101 C AGWA THREAD 3.68 2 u 10102 A CERCA FAR 3.61 2 u 6103 C MADURO CERVEZA 3.13 1 r 1104 C MONK MOUSE 3.40 4 r 4105 A STORM D IE 3.47 4 r 4106 A LONG SHORT 3.46 4 u 8107 A ARRIBA AFTER 3.66 2 r 2108 C COPPER BRASS 3.11 4u 12109 A A 'NGEL DEVIL 3.46 2 u 6110 C CANDY GALLETA 2.95 3 u 11111 C POBRE ENFADADO 3.07 1 r 1112 C GAME JUGAR 3.15 3 u 11113 A H ILL TRAS 3.69 3 r 3114 A ROUGH SMOOTH 3.05 4 u 8115 C FLOWER TREE 3.43 4u 12116 C BOCA NOSE 3.12 2 u 10117 A V INO RICO 3.47 1 r 1118 C WARM HOT 3.47 4u 12119 C NEST BIRD 3.25 4 u 12120 C MESA SILLA 3.53 1 u 9121 C BATH FARM 3.70 4 r 4122 C ANTES ISLAND 3.43 2 r 2123 C TENNIS DAUGHTER 2.95 4 r 4124 C LLLNIA SNOW 3.56 2 u 10125 A COMENZAR END 3.35 2 u 6126 C HOUSE MONTAN " A 3.12 3 r 3127 C JAMON CERDO 3.37 1 u 9128 A HAND RECIBIR 3.33 3 r 3129 C RARAMENTE ARROW 3.45 2 r 2130 C TRACTO 'R PL OW 3.39 2 u 10131 A PUSH EASY 3.08 4 r 4132 C W IN PIE 3.00 3 r 3133 C SUN ESTRELLA 3.36 3 u 11134 A DEEP SHALLOW 3.55 4 u 8135 C CORDERO SOBRESALTO 3.45 1 r 1136 C OPEN PRIEST 3.15 4 r 4; 137 C BLOSSO M FLORECER 3.58 3 u 111138 A LIFE MUERTE 3.63 3 u 7

(u=related, r=unrelated)


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APPENDIX E - part II List B

139 A EMPEZAR DULCE 3.35 1 r 1140 C WOOD META'LlCO 3.45 3 u 11141 A MAS RIGHT 3.42 2 r 2142 C CHIQUITa LITTLE 3.48 2 u 10143 A ARMY SILECIO 3.15 3 r 3144 C MAR STUDENT 3.10 2 r 2

i

(u=related, r=unrelated)


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. . - - - .BIBLIOGRAPHY

Ardal,S., Donald, M.W., Meuter, R., Muldrew, S. and Luce, M. (1990). "BrainResponses to Semantic Incongruity in Bilinguals." Brain and Language, 39,pp. 187-205Bentin,S., Kutas, M., and Hillyard, S.A. (1993). "Electrophysiological evidence for taskeffects on semantic priming in auditory word processing." Psychophysiology,30, pp. 161-169.Berquier,A. and Ashton, R. (1992). "Language Lateralization in Bilinguals: More NotLess Is Needed: A Reply to Paradis (1990)." Brain and Language, 43, pp. 528-533.Brandeis, D. and Lehmann, D. (1986). "Event-Related Potentials of the Brain andCognitive Processes: Approaches and Applications." Neuropsychologia, vol.24(1), pp. 151-168.Berthier,M.L., Starkstein, S.E., Lylyk, P. and Leiguarda, R. (1990). "DifferentialRecovery of Languages in a Bilingual Patient:

senior thesis 1995

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