Brain and Language 101 (2007) 38–49

www.elsevier.com/locate/b&l

Electrophysiological and behavioral measures of the inXuence of literal and Wgurative contextual constraints on proverb comprehension �

Todd R. Ferretti a,¤, Christopher A. Schwint a, Albert N. Katz b

a Centre for Cognitive Neuroscience, Department of Psychology, Wilfrid Laurier University, 75 University Avenue, Waterloo, Ont., Canada N2L 3C5b University of Western Ontario, London, Ont., Canada

Accepted 3 July 2006Available online 21 August 2006

Abstract

Proverbs tend to have meanings that are true both literally and Wguratively (i.e., Lightning really doesn’t strike the same place twice).Consequently, discourse contexts that invite a literal reading of a proverb should provide more conceptual overlap with the proverb,resulting in more rapid processing, than will contexts biased towards a non-literal reading. Despite this, previous research has failed toWnd the predicted processing advantage in reading times for familiar proverbs when presented in a literally biasing context. We investigatethis issue further by employing both ERP methodology and a self-paced reading task and, second, by creating an item set that controls forproblems with items employed in earlier studies. Our results indicate that although people do not take longer to read proverbs in the liter-ally and proverbially biasing contexts, people have less diYculty integrating the statements in literal than Wgurative contexts, as shown bythe ERP data. These diVerences emerge at the third word of the proverbs.© 2006 Elsevier Inc. All rights reserved.

Keywords: Proverb comprehension; Slow-cortical waves; ERP; N400; Late positivity; Self-paced reading

1. Introduction

Over the last decade researchers have begun to exam-ine how people comprehend Wgurative statements whenthey are placed in contexts that are consistent with theirWgurative or literal meanings. One of the main goals ofthis research is to understand the time-course in whichpeople construct Wgurative interpretations for statementsthat could be interpreted literally or Wguratively. DiVer-ent theoretical accounts of Wgurative language processingmake clear predictions about the time-course in whichWgurative meanings should be constructed. For example,according to the standard pragmatic model (Grice, 1975;Searle, 1979), people Wrst construct the literal meaning of

� This research was supported by a Canadian Foundation for Innova-tion (CFI) grant held by the Wrst author, and by separate NSERC Discov-ery Grants held by the Wrst and third authors.

* Corresponding author.E-mail address: tferrett@WLU.ca (T.R. Ferretti).

0093-934X/$ - see front matter © 2006 Elsevier Inc. All rights reserved.doi:10.1016/j.bandl.2006.07.002

the complete phrase and only attempt to construct a Wgu-rative interpretation when that meaning is perceived asinconsistent with the preceding context. Giora’s gradedsalience model (Giora, 2003) posits that the most salientor familiar usage of an expression, such as the nonliteralsense of a familiar proverb, will be aroused at the initialmoments of processing regardless of the nature of thepreceding context. Other models, such as the direct accessmodels (Gibbs, 1995), and the constraint-based model(Katz & Ferretti, 2001), are context-dependent and arguethat at the initial moments of processing the Wgurativemeaning of as statement is accessed at least as quickly asthe literal sense as long as the contexts are suYcientlyconstraining.

Results from studies employing on-line reading timemeasures demonstrate that people do not take longer toread a statement used Wguratively than used literally whenplaced in contexts that strongly constrain for the Wgurativeinterpretation, thereby providing support for models thatdo not posit a delay in accessing Wgurative meanings

T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49 39

(e.g., Gibbs, Bogdanovich, Sykes, & Barr, 1997; Katz & Fer-retti, 2001). Despite these Wndings, recent research involvingEvent-Related-Brain-Potential methodology (ERP) suggestthat people have more diYculty integrating the Wnal wordof statements when they are intended to be taken as nonlit-eral statements rather than as literal statements (e.g., Coul-son & Van Petten, 2002; Katz, Blasko, & Kazmerski, 2004;Pynte, Besson, Robichon, & Poli, 1996). The primary brainpotential of interest in these studies has been the N400component (Kutas & Hillyard, 1984). The N400 compo-nent is typically interpreted as indexing the ease of semanticintegration of words in context; words that are more diY-

cult to semantically integrate elicit an N400 with largeramplitudes than words that are easier to integrate. Theresults of the studies cited above show that, Wrst, negativeamplitudes that peak about 400 ms after the presentation ofthe critical word tend to be largest for sentence Wnal wordswhen they are embedded in Wgurative compared to literalcontexts and, second, the N400 is often followed by a latepositivity, in which there is a larger positive amplitude forwords presented in Wgurative than literal contexts.Researchers have interpreted these Wndings as showing thatconceptual integration is more diYcult for statementsintended to be taken Wguratively than literally (e.g., Coul-son & Van Petten, 2002) and, because these diVerencesoccur during the processing of the statements (Katz et al.,2004), they cannot be accounted for by models that holdthat literal meanings must be processed prior to generatinga Wgurative meaning (e.g., Grice, 1975).

In the following research we build on previous researchin several ways. First, we measured ERPs when people readfamiliar Wgurative statements presented in literally andWguratively biasing contexts. In our case, in addition toexamining N400 and late positivity eVects to single wordsas above, we also examine slow-cortical wave brain poten-tials that develop over multiple words in sentences andclauses. Previous research has shown that slow-wave poten-tials are sensitive to the ease in which people integrate sen-tences and clauses into a developing mental model of thetext (e.g., King & Kutas, 1995; Münte, Heinze, & Kutas,1998). Ease in integrating sentences is associated with afrontally distributed positivity which is sustained over thesentences, typically taken to indicate decreased workingmemory load relative to sentential structures that areharder to integrate. Thus, in addition to providing a mea-sure of working memory load, slow-cortical wave poten-tials are similar to N400 and late positivity componentsfound for single words in that they enable us to examinewhen a critical statement becomes more diYcult to inte-grate with preceding contexts. To our knowledge, thisresearch is the Wrst to concurrently investigate both slow-wave potentials that develop over sentences and singleword averages to provide converging indices on when andhow Wgurative statements are integrated in discourse con-texts.

In this study we employ proverbs to examine the eVectsof contextual constraints on Wgurative language processing.

Proverbs are unique relative to metaphors or irony, themost commonly studied forms of non-literal language,because they can be regarded as generally true statementsboth literally and Wguratively (e.g., lightning really doesn’tstrike the same twice). In contrast, a metaphor such as Chil-dren are precious gems, is true Wguratively but not literally.One consequence of this property of proverbs is that whena familiar proverb is placed within a context that invites aliteral reading, there is inevitably a greater degree of con-ceptual overlap between the target proverb and words inthe context than when the same target is placed in a contextthat invites a non-literal proverbial reading. One mightexpect that this diVerence alone would lead to faster read-ing times for familiar proverbs placed in literal biasing con-texts relative to Wgurative biasing contexts in previousresearch. However, Katz and Ferretti (2001, 2003) usingword-by-word self-paced reading methodology found thatpeople read familiar proverbs at the same rate whether ornot they are presented in literal or Wgurative contexts, andwhether or not explicit markers are employed to signal thereader that an upcoming statement should be interpretedliterally or Wguratively.

2. Experiment 1

In Experiment 1 we use ERP methodology to examinehow people interpret familiar proverbial statements in lit-eral and Wgurative biasing contexts. There are severaladvantages to using ERP methodology. First, ERP meth-odology is well known for having a Wne temporal resolu-tion. Second, individuals can simply read forcomprehension without having to push buttons to advancethrough text. Third, ERP methodology provides insightinto the electrophysiological response of the brain to pro-cessing familiar proverbs. As discussed above, slow-wavepotentials, the N400, and late positivity components (LPC)have all been shown to be a sensitive measure of when diY-culties arise in integrating words and sentences in discoursecontexts. Moreover, topographic diVerences in brain poten-tials provide additional insight into how diVerent popula-tions of neurons contribute to diVerences found betweenconditions.

Our main predictions for slow-wave potentials and sin-gle word averages are similar. SpeciWcally, if people haveless diYculty integrating the proverbs in literal than Wgura-tive contexts due to greater conceptual overlap in the literalcontexts, then we would expect to Wnd more positive slow-wave amplitudes at frontal locations for the literal thanWgurative condition. The diVerence in slow wave ampli-tudes should begin at the point in which the literal condi-tion becomes easier to integrate than the Wgurativecondition, and this diVerence should be sustained over theproverbial statements. Based on previous research on Wgu-rative language processing (e.g., Coulson & Van Petten,2002; Katz et al., 2004), we also expect to Wnd a smallerN400 and a smaller LPC at the word(s) in the proverbialstatement in which people begin to have less diYculty in the

40 T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49

literal conditions. Alternatively, if the proverbial statementsare interpreted as easily in the two contexts, then we wouldnot expect to Wnd any diVerences in the ERP results.

2.1. Participants

Twenty-four participants participated in the ERP exper-iment and 99 students participated in the rating studies. Allparticipants were native English speaking undergraduatestudents from Wilfrid Laurier University who receivedcourse credit for their participation.

2.2. Materials and procedure

2.2.1. Rating studiesWe Wrst conducted a rating study to ensure that our

proverbs were familiar to our population. Twenty-sevenparticipants were presented with 116 proverbs and wereasked to rate on a 7 point scale how familiar each proverbwas to them (1Dnot at all familiar, 7D very familiar). Wethen selected 58 familiar proverbs (all seven words long)that served as the basis for constructing our target para-graphs. For each of the 58 proverbs, we constructed a con-text that invited a literal reading and a context that inviteda Wgurative reading.

Each of the contexts had 4 sentences preceding eachproverb, and the sentence before the proverb was alwaysidentical across the two contextual conditions. The contextswere in narrative form and described interactions betweenpeople (see examples 1a and 1b). For the literal biasing con-texts we ensured that the content words of the familiarproverbs did not appear in the contexts. This ensured thatany advantage found for the literal contexts could not be aresult of repetition priming between the words in the con-texts and words in the proverbs.

(1a) Figuratively biasing context“What you need is an investment to shelter your proWt”,

said Ann. “But it’s been a volatile market since the crash,”replied George. “Look, I lost a lot of money last year.”“Don’t worry, you’ll be alright,” she assured him. Lightningnever strikes the same place twice.” “How can you be cer-tain?”, he asked. “Its true, the market goes in cycles; itwon’t crash again for years,” she replied.

(1b) Literally biasing context“Let’s take shelter from the rain under this broken tree,”

said Ann. “But it’s dangerous to hide under a tree during astorm,” replied George. “Look, the tree has been hit oncealready.” “Don’t worry, you’ll be alright,” she assured him.“Lightning never strikes the same place twice.” “How canyou be certain?,” he asked. “Its true, once the energy dissi-pates, it takes a while to rebuild,” she replied.

We then validated our stimuli with two additional ratingstudies. In order to ensure that the proverbs were equallycomprehensible in the literal and Wgurative contexts, weasked 48 participants to rate each paragraph for how easythey thought the proverbs were to comprehend in the con-texts (1Dnot all easy to comprehend, 7D very easy to com-

prehend). In the second study, 24 participants providedratings for how literal or Wgurative they thought the prov-erbs were in the diVerent contexts (1Dvery literal, 7DveryWgurative). This rating study ensured that our contexts wereliteral or Wguratively biased as claimed.

Based on the results of these rating studies we selected 32proverbs and their corresponding literal and Wgurativebiasing contexts to serve as the experimental stimuli. Themean ratings for these items are presented in Table 1. Over-all, the items were rated similar for ease of comprehension(t(31)D1.15, pD .26), and the Wgurative contexts receivedhigher Wgurative ratings than the corresponding literal con-texts (t(31)D11.38, p < .001). Finally, the 32 proverbs wererated relatively high for familiarity, MD4.9.

The 32 proverbs were placed across two experimentallists with the restriction that each participant read eachproverb only once and each proverb appeared in a Wgura-tive and literal context. Ninety-six Wller trials similar in nar-rative form and length were included in each list to createan experimental environment in which all of the itemswould be read in their usual manner, i.e., without inducing astrategy to read for Wgurative meaning. Accordingly, noneof these trials included Wgurative statements. The low pro-portion of Wller trials relative to Wgurative trials is a controlthat is missing from previous research investigating theeVect of context on interpreting literal and Wgurative lan-guage. In total, only 25% of the paragraphs involved afamiliar proverb, in half of those trials the proverb wasused literally and in half of the trials the proverb was usedWguratively.

Participants sat in a chair in front of a computer moni-tor located in an electrically shielded chamber. They wereinstructed to read the words one at a time and to answerperiodic comprehension questions by pressing buttonslabeled “Yes” and “No”. The 32 Experimental paragraphsand 96 Filler paragraphs were presented one word at a timein the center of a computer screen. All words were pre-sented for a duration of 300 ms with an SOA of 500 ms. TheWnal word was always followed by 2000 ms of blank screen.

2.2.2. EEG recording and analysisThe electroencephalogram (EEG) was recorded from 64

electrodes distributed evenly over the scalp. See Fig. 1 for aschematic diagram of the layout of the 64 channel cap andthe corresponding electrode labels. Eye movements andblinks were monitored via additional electrodes placed on

Table 1Mean norming ratings (on a 1–7 likert scale) for Wgurative and literalparagraphs used in Experiment 1 and 2

¤¤ p < .01.

Ease of comprehension Context Wgurativeness

M SE M SE

Figurative paragraphs 5.5 .1 5.5 .2Literal paragraphs 5.3 .1 2.3 .2DiVerence +.2 +3.2¤¤

T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49 41

the outer canthus and infraorbital ridge of each eye. Elec-trode impedances were kept below 5 k�. EEG and was pro-cessed through a Neuroscan Synamps2 ampliWer set at abandpass of 0.05–100 Hz, and was digitized at 250 Hz.

3. Results and discussion

The data were re-referenced oV-line to the average of theright and left mastoids. High frequency noise was removedby applying a low-pass Wlter set at 30 Hz. ERPs were thencomputed in epochs that extended from 200 ms before theWrst word of the sentence to 1000 ms after the Wnal word’sonset (i.e., ¡200 to 4000 ms). Single word epochs were cal-culated that extended from 100 ms before each word to1000 ms following the onset of the words. Trials contami-nated by blinks, eye-movements, and excessive muscleactivity, were rejected oV-line before averaging; 25% of thetrials were lost due to artifacts in the slow wave averages,and 20% of the trials were lost in the single word averages.We discuss the slow-wave analyses Wrst, followed by thesingle word analyses.

3.1. Slow-wave averages (¡200 ms to 4000 ms)

Fig. 2 shows the slow-wave potentials for both contex-tual conditions at one frontal and one central/parietal elec-trode site (FZ, CPZ) located down the midline, and Fig. 3

shows the topographical distribution of the results for allchannels. As can be seen, the slow-cortical waves for bothcontexts become progressively more positive across theproverbs. However, at about the third word of the proverbsthe literal condition starts to become signiWcantly morepositive than the Wgurative condition, and this positivity issustained over the remaining words in the proverbs. Theobserved diVerences between the context types were largestover frontal sites, smallest over posterior sites, and had asimilar distribution across the right and left hemispheres.

3.1.1. Overall analysisWe conducted 3-way ANOVAs on the mean amplitude

for each condition at 7 separate regions of interest: one foreach 500 ms word region in the proverbs. The main factorsof interest were Context (literal vs. Wgurative) and Elec-trode Site, both of which were within participants variables.List was used as a between participant factor to stabilizeany variance caused by rotating participants across thediVerent lists (Pollatsek & Well, 1995). Table 2 shows theresults for each region of interest. All p-values in this andsubsequent analyses are reported after Epsilon correction(Huynh-Felt) for repeated measures with greater than onedegree of freedom.

As illustrated in Table 2, there was no signiWcant maineVect of Context and no interaction between Context andElectrode Site at the Wrst two words of the proverbs.

Fig. 1. Schematic diagram showing the electrode labels and sites for the 64 channel electrode caps used in Experiment 1.

42 T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49

However, at the third word of the proverbs, the main eVectof Context was signiWcant—greater positivity was foundfor proverbs located in literal compared to Wgurative con-texts. From the fourth word through to the sixth word, theinteraction between Context and Electrode Site was signiW-cant. At the seventh word, the interaction was marginallysigniWcant (p < .08).

3.1.2. Slow-wave distribution analysisIn order to examine the observed interactions between

Context and Electrode Site, we conducted a 5-wayANOVA on the proverb regions in which the interactionwas signiWcant. In addition to the Context and List Factorsused in the overall analysis, we added Hemisphere (left vs.right), Laterality (lateral vs. medial), and Anteriority

Fig. 2. Experiment 1 mean amplitudes at one frontal site (FZ) and one central/parietal site (CPZ) located on the midline Wltered with a low pass Wlter set at30 Hz (left columns) and at .7 Hz (right columns) to reveal slow-wave development over proverbs. The Wgurative condition is shown in blue and the literalcondition is shown in red.

Frontal (FZ)

ms-200.0 300.0 800.0 1300.0 1800.0 2300.0 2800.0 3300.0 3800.0

µV

0.0

-2.5

-5.0

2.5

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15.0

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20.0

ms-200.0 300.0 800.0 1300.0 1800.0 2300.0 2800.0 3300.0 3800.0

µV

0.0

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-5.0

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5.0

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12.5

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17.5

20.0

Central/Parietal (CPZ)

ms-200.0 300.0 800.0 1300.0 1800.0 2300.0 2800.0 3300.0 3800.0

µV

0.0

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-5.0

2.5

5.0

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20.0

ms-200.0 300.0 800.0 1300.0 1800.0 2300.0 2800.0 3300.0 3800.0

µV

0.0

-2.5

-5.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0

Fig. 3. Topographical distribution of mean amplitudes in micro-volts at all electrode sites for each 500 ms word region starting at the third word of prov-erbs through the seventh word for Wgurative contexts and literal contexts.

Figurative Context

Literal Context

3rd word th4 word

th 5 word 6 word 7 wordth th

Proverb Region

+10.0

+9.1

+8.1

+7.2

+6.3

+5.3

+4.4

+3.4

+2.5

+1.6

+0.6

-0.3

-1.3

-2.2

-3.1

-4.1

-5.0

T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49 43

(prefrontal vs. frontal vs. parietal vs. occipital). All of theseadditional factors were within participants variables. Theresults of this analysis are presented in Table 3. We onlyreport the results for the interactions involving contextbecause those are the only interactions that are of theoreti-cal interest here.

As shown in Table 3, the Context by Anteriority interac-tion was signiWcant at all regions examined with, in eachcase, the mean amplitudes being more positive in the literalcompared to the Wguratively biased contexts at prefrontalsites, all p’s < .002, and at frontal sites, all p’s < .001. In con-trast, there were no diVerences between the two contexts atparietal and occipital sites.

3.2. Single-word averages

3.2.1. N400 analysis (300–500 ms)The results of the N400 analysis are presented in Table 4.

Fig. 4 shows the N400 at one frontal electrode (FZ) andone central/parietal electrode (CPZ) located along the mid-line for the third word of the proverbs. Fig. 4 also shows thetopographical distribution of the amplitudes for the twoconditions in the N400 region for all electrodes. At the thirdword of the proverbs, the literal condition was less negativethan the Wgurative condition, F(1,18)D 20.80, p < .001, andthis eVect of context interacted with electrode site,F(61,1098)D3.76, p < .01. No other main eVects or interac-tions for the N400 were found at any of the other words in

Table 2Experiment 1 grand average (nD 20) slow-wave results for each of the 7word regions (500 ms epochs) in the proverbs

a D p > .05 < 10.¤ p 6 .05.

¤¤ p < .01.

Context Electrode£ Context

Word1st F < 1 F < 12nd F < 1.1 F < 13rd F(1,18) D 4.33¤ F < 1.14th F(1,18) D 2.55 F(61,1098) D 2.83¤¤

5th F(1,18) D 2.95 F(61,1098) D 2.49¤

6th F(1,18) D 2.45 F(61,1098) D 2.63¤

7th F(1,18) D 2.53 F(61,1098) D 1.96a

the proverbs. We examine the interaction between contextand electrode site in the topographical distribution analysisreported below.

3.2.2. N400 distribution analysisThe same 5-way distribution ANOVA reported above

was also performed on the mean N400 amplitudes. Theresults of this analysis are reported in Table 5. As shown inthe table, there was a marginal Context by Anteriorityinteraction, F(3,54)D 3.56, p < .06. This marginal eVectoccurred because the N400 region was less negative for lit-eral contexts than Wgurative contexts at frontal (meandiVerenceD 2.65 �V; F(1,54)D 42.90, p < .001) and prefron-tal sites (mean diVerenceD 2.11�V; F(1,54)D 27.14,p < .001) than at parietal (mean diVerenceD 1.44�V;F(1,54)D 11.02, p < .05) and occipital sites (meandiVerenceD .95 �V; F(1,54)D5.50, p < .05).

The interaction between Context and Laterality reachedsigniWcance, F(1,18)D4.51, p < .05. This interactionoccurred because the diVerence between Wgurative and lit-eral contexts was larger at medial electrode sites (meandiVerenceD 2.02 �V; F(1,18)D 136.74, p < .001) than at lat-eral sites (mean diVerenceD1.50 �V; F(1,18)D 75.51,p < .001).

Finally, the three-way interaction between Context,Anteriority, and Laterality also was signiWcant,F(3,54)D 6.06, p < .01. This interaction occurred because thediVerence between the Wgurative and literal contexts atanterior and posterior electrode sites was larger at medialrather than lateral sites. The observed diVerences in N400

Table 4Experiment 1 grand average N400 (300–500 ms) results for each of the 7words in the proverbs

¤¤ p < .01.

Context Electrode£ Context

Word1st F < 1 F < 1.312nd F < 1.25 F < 13rd F(1,18) D 20.80¤¤ F(61,1098) D 3.76¤¤

4th F < 1 F < 15th F < 1 F < 16th F(1,18) D 2.47 F < 1.847th F < 1 F < 1

Table 3Experiment 1 topographic distribution results for the slow-wave averages at each of the 4 regions in which Context and Electrode Site interacted

¤ p < .05.¤¤ p 6 .01.

Proverb region

4th word 5th word 6th word 7th word

C£A F(3,54) D 7.12¤¤ F(3,54)D 5.68¤¤ F(3,54) D 5.62¤¤ F(3,54) D 4.33¤

C£L F < 1 F < 1 F < 1 F < 1C£H F < 1 F < 1 F < 1 F < 1.13C£A£L F < 1 F < 1.60 F < 1 F < 1.67C£A£H F < 1 F < 1 F < 1 F < 1C£L£H F < 1 F < 1 F < 1 F < 1C£A£L£H F < 1.16 F < 1.12 F < 1 F < 1

44 T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49

between medial and lateral locations is frequently found(e.g., Federmeier & Kutas, 1999), and are consistent withresearch involving intracranial electrode recordings thatshow that the neurogenerators for the N400 are likelylocated in the anterior medial temporal lobes (e.g., McCar-thy, Nobre, Bentin, & Spencer, 1995).

3.2.3. Late positivity analysis (700–1000 ms)The results of the LPC analysis for all electrode sites are

reported in Table 6. As shown in the table, there was a sig-niWcant main eVect of context at the third word,F(1,18)D 4.90, p < .05. This eVect occurred because the lit-eral condition was more positive than the Wgurative condi-tion. There also was a signiWcant interaction betweencontext and electrode site at the third word,F(61,1098)D 8.53, p < .001, and at the fourth word,F(61,1098)D 2.56, p < .01. The sustained frontal positivity inthe slow-wave potentials for the literal condition is the pri-mary cause of the main eVect of context and the interactionwith electrode site. At posterior locations the LPC patternis reversed (especially at the fourth word)—the literal con-dition is less positive than the Wgurative condition. The dis-tribution analysis reported below provides statisticalevidence for these claims. No other main eVects or interac-tions were found at any of the other words in the proverbs.

3.2.4. Late positivity distribution analysisThe results of the topographic distribution analysis for

the third and fourth words are presented in Table 5. At thethird word, context and anteriority interacted,F(3,54)D13.54, p < .001. This interaction occurred becausethe literal condition was much more positive than the Wgu-rative condition at prefrontal (mean diVerenceD2.71 �V;F(1,18)D33.05, p < .001) and frontal sites (meandiVerenceD2.65 �V; F(1,18)D 31.57, p < .001), whereasthese diVerences were much smaller and in the opposite

Table 5Experiment 1 N400 and LPC topographic distribution results at each ofthe 4 regions in which context and electrode site interacted

a D p > .05 < 10.¤ p < .05.

¤¤ p 6 .01.

3rd word (N400) 3rd word (LPC) 4th word (LPC)

C£A F(3,54) D 3.56a F(3,54) D 13.54¤¤ F(3,54) D 2.69C£L F(1,18) D 4.51¤ F(1,18) D 2.69 F < 1C£H F(1,18) D 2.14 F(1,18) D 2.43 F < 1C£A£L F(3,54) D 6.06¤¤ F(3,54) D 5.18¤¤ F < 1.39C£A£H F < 1 F < 1.51 F < 1CxLxH F < 1 F < 1 F < 1CxAxLxH F < 1.88 F < 1 F(3,54) D 2.41a

Fig. 4. (A) Experiment 1 single word grand averages at one frontal site (FZ) and one central/parietal site (CPZ) located on the midline for the third wordof the proverbs. The Wgurative condition is shown in blue and the literal condition is shown in red. (B) The topographical distribution of the mean ampli-tudes for all electrode locations in the N400 region (300–500 ms) at the third word for both contexts.

A B

Frontal (FZ) Figurative Context (300–500 ms)

ms-100.0 150.0 400.0 650.0 900.0

µV0.0

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Central/Parietal (CPZ)Literal Context (300–500 ms)

ms-100.0 150.0 400.0 650.0 900.0

µV0.0

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0

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T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49 45

direction at parietal (mean diVerenceD .35�V; F < 1) andoccipital sites (mean diVerenceD .30 �V; F < 1). No otherinteractions reached signiWcance.

Both the single-word and the slow-wave analysesreported above demonstrate that people had less diYcultyintegrating the proverbs when they are embedded in literalthan in Wgurative contexts. Both types of averages convergeto show that these diVerences began to occur by the thirdword of the proverbs and, in the slow-wave averages, thesediVerences were sustained over the remaining words of theproverbs.

The slow-wave results also demonstrated that the largestdiVerences were found at prefrontal and frontal electrodesites, a Wnding that is consistent with previous researchexamining the relationship between slow-cortical waves insentence processing and working memory load (e.g., King& Kutas, 1995; Münte et al., 1998). We take the slow-waveresults as compelling evidence that people had less diYcultyintegrating the familiar proverbial statements when theywere placed in literal rather than Wgurative-biasing con-texts.

The N400 and LPC Wndings in the single-word averagesfor the third and fourth word are more diYcult to interpretas a result of the large diVerences in slow-wave amplitudesat anterior electrode locations. For example, the distribu-tion analysis for the N400 analysis demonstrated a two-wayinteraction between anteriority and context whereby the lit-eral context was much less negative than the Wgurative con-texts at anterior positions than at posterior locations. ThesediVerences are due to amplitudes at anterior locations cap-turing both the greater slow-wave positivity for the literalcontexts and the less negative N400 in the literal contexts.Thus, it could be the case that our N400 results (and LPCresults) are primarily driven by the slow-wave diVerencesrather than diVerences in the N400 and LPC components.In order to establish whether our N400 and LPC eVects atthe third word are signiWcant at posterior locations (wherethey typically are maximal) without the inXuence of theslow-wave diVerences at anterior locations, we conductedseparate N400 and LPC analysis with all electrode loca-tions anterior to the central electrodes removed from theanalysis. We also conducted the same analysis for the LPCregion at the fourth word.

Table 6Experiment 1 grand average late positivity results (700–1000 ms) for eachof the 7 words in the proverbs

¤ p < .05.¤¤ p < .01.

Context Electrode£ Context

Word1st F < 1 F < 12nd F(1,18) D 2.22 F < 13rd F(1,18) D 4.90¤ F(61,1098) D 8.53¤¤

4th F < 1 F(61,1098) D 2.56¤

5th F < 1.45 F < 16th F < 1 F < 1.287th F < 1.80 F < 1.14

The results of the N400 analysis without anterior elec-trodes at the third word revealed a robust main eVect ofcontext, F(1,18)D13.52, p < .01. As expected, the N400 forthe literal condition (MD .16 �V) was less negative than forthe Wgurative condition (MD1.67 �V). However, the maineVect of context for the LPC region at the third word(F < 1) and fourth word (F(1,18)D 2.70, pD .12) did notreach signiWcance. Therefore, our results suggest that ourN400 eVects at the third word are genuine, whereas ourLPC eVects at the third and fourth word are primarilydriven by the diVerences in the slow-wave amplitudes atanterior electrode locations.

Our N400 results are consistent with previous Wgurativelanguage research showing that people have less diYcultyintegrating the Wnal word of statements when they areintended to be taken as literal statements rather than asmetaphoric or sarcastic statements (e.g., Coulson & VanPetten, 2002; Katz et al., 2004; Pynte et al., 1996). Interest-ingly, the N400 diVerences found between the two contextswere localized to the third word. This pattern is diVerentthan the slow-wave analysis that indicated people had lessdiYculty integrating the familiar statements in the literalcontexts from the third word through to the seventh word.These diVerences between single word and slow-wave aver-ages should be interpreted with caution, however, as the100 ms pre-stimulus baselines for the single word averagesfollowing the third word may be inXuenced by N400 eVectsresulting from each preceding word. For example, becausethe SOA for each word was 500 ms, the pre-stimulus base-line for the fourth word will fall within the typical N400range (i.e., 400–500). As a result, the amplitudes of the waveforms for the subsequent word will be increased ordecreased to the degree that they are away from the base-line value in the 400–500 ms following the onset of the pre-ceding word. The multiword averages reported above canbe useful in this regard because they were conducted with abaseline that started 200 ms before the onset of the Wrstword of the proverb. As shown in Fig. 2, there is some evi-dence, albeit indirect, that N400 amplitudes are less nega-tive in literal than Wgurative contexts at most of the otherwords in the proverbs, including the second, fourth, Wfth,and seventh word. These diVerences in N400 amplitude,however, are much smaller than that found at the thirdword.

Although there was some evidence of a less positive LPCfor the literal than Wgurative contexts at the fourth word,the diVerence between the two conditions was not signiW-cant when only the central and posterior electrode loca-tions where examined. Thus, the LPC data are similar toprevious research (e.g., Coulson & Van Petten, 2002) asthere was less positivity associated with the literal conditionthan the Wgurative condition at scalp locations in which theLPC is typically maximal, although in our case these diVer-ences did not reach signiWcance.

The question remains, however, about why the diVer-ences between contextual conditions in the slow-corticalwaves begin to be signiWcant at the third word and,

46 T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49

similarly, why the largest diVerences in the N400 amplitudeare found at third word. We believe that it is at this pointthat people have received enough of the familiar proverbialstatements to recognize them as common Wgurative expres-sions. As a result, it is at this point that people can begin tointegrate the well-known meanings of these phrases withthe discourse contexts and, therefore, we begin to see diVer-ences in the ease in which people can integrate the meaningsof the proverbs in the literal and Wgurative contexts. Thisclaim is consistent with previous self-paced reading resultsby Katz and Ferretti (2001) that show by the second wordof the proverbs people began to diVerentiate between famil-iar and unfamiliar proverbs, and this was true for both theliteral and Wgurative contexts. However, it is important tonote that an additional baseline condition would berequired to ensure that the recognition of familiar proverbsemployed here occurs at the same point in the proverbs.

In summary, the slow-wave averages and the single wordaverages clearly show that integrating familiar proverbsinto literal discourse contexts is less diYcult than when theyare placed in Wgurative discourse contexts. However, theseWndings are not consistent with previous self-paced readingexperiments that have shown that people read familiarproverbs at the same rate whether presented in Wgurative orliteral biasing contexts (Katz & Ferretti, 2001, 2003). Theself-paced reading data with proverbs are consistent with alarge body of evidence for other instances of highly familiarforms of non-literal language and, as such, the Wndings ofExperiment 1, based on an arguably more sensitive measureof temporal processing, have important theoretical implica-tions. Because a diVerent set of passages were employed inthe present study than in the earlier self-pace reading stud-ies, it is diYcult to directly compare the present results withthe earlier null eVect. For example, it could simply be thecase that a self-paced reading study involving the currentitem set would produce reading times that are more consis-tent with the present ERP results. Consequently, Experi-ment 2 addresses whether the pattern observed here withERP data would be replicated in a self-paced reading taskwhen the same set of items are employed.

4. Experiment 2

Experiment 2 was designed to examine people’smoment-by-moment comprehension of familiar proverbswhen they are presented in contexts that are either biasedtoward their literal or Wgurative meanings. The readingexperiment is a replication and extension of Katz and Fer-retti (2001, 2003). The main diVerence here is that we onlyinvestigate familiar proverbs and we examine proverbs thatall have the same length. Using proverbs that are all thesame length permits a Wner-grained analysis of word-by-word processing than was employed in the previous experi-ments, in which the variable number of words in the middleregion of the proverbs were averaged together as a singleregion. A second important diVerence is that we employalmost three times the number of items (i.e., 32 vs. 12), thus

providing an increased representative dataset and thus agreater likelihood of detecting reading time diVerences ifthey exist.

Based on the results of previous studies examining theinXuence of literal and Wgurative contexts on Wgurative lan-guage comprehension (Gibbs et al., 1997; HoVman & Kem-per, 1987; InhoV, Lima, & Carroll, 1984; Katz & Ferretti,2001, 2003), it is expected that overall reading latencies forproverbs placed in literal and Wgurative biasing contextsshould be similar across each of the critical regions exam-ined. However, if the lack of a diVerence between the twocontextual conditions found in previous research is due tosmall item sets and problems associated with averagingreading times in the mid-region of the proverbs, then wemay Wnd, as we did with the ERP data in Experiment 1,some advantage in reading times for proverbs in the literalbiasing contexts due to the greater conceptual overlapbetween the context and the proverbs than would be foundbetween the proverbs and the words in the correspondingWgurative biasing contexts.

5. Method

5.1. Participants

Twenty-four participants participated in the readingexperiment. All participants were native English speakingundergraduate students from Wilfrid Laurier Universitywho received course credit for their participation.

5.2. Materials and procedure

The materials were identical to Experiment 1.

5.2.1. Self-paced reading taskThe paragraphs were displayed on a 17 in. Apple moni-

tor controlled by a Macintosh G4. They were presentedusing PsyScope (Cohen, MacWhinney, Flatt, & Provost,1993) in a one-word-at-a-time moving window format.Paragraphs were initially presented on the screen with eachnon-space character replaced by a dash. Participantspressed a button to reveal the Wrst word of the paragraph.Each subsequent button press revealed the next word andreplaced the previous word with dashes. Participants readeach paragraph in this manner and then answered a yes–nocomprehension question.

Testing sessions began with 4 practice items. Participantsthen read the remaining 128 experimental trials. Each ses-sion lasted approximately 1 h. Reading latencies for eachword were recorded by the computer and were measured asthe time interval between successive button presses.

5.3. Design

The analysis was conducted on 10 diVerent regions inand around the proverbs; the word immediately precedingthe proverbs, each of the seven words comprising the

T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49 47

proverbs, and the two words immediately following theproverbs. The analysis for the two Wnal regions was a gaugeof sentence “wrap-up” eVects.

We conducted 2-way analysis of variance on eachregion. The main factor of interest was Context (literal vs.Wgurative), which was within participants (F1) and withinitems (F2). List (F1) and Item Rotation Group (F2) wereused as a between factor to stabilize any variance caused byrotating participants and items across the diVerent lists(Pollatsek & Well, 1995). Any reading latency that wasgreater than three standard deviations from the mean wasremoved from the analysis. Items in which the participantsincorrectly answered the comprehension question wereremoved from the analysis.

6. Results and discussion

The mean reading times for each of the 10 criticalregions are shown in Fig. 5. As can be seen, participantsread each word in the proverbial statements at a similarrate, regardless of contextual bias. Moreover, there was noevidence of any diVerences in sentence wrap-up eVects atthe two regions following the proverbs. In all regions, thediVerence in reading times was not signiWcant, all F’s < 1.3.

The results are consistent with previous research by Katzand Ferretti (2001, 2003) showing that people read familiarproverbs at the same rate when they are embedded in literaland Wgurative biasing contexts. These results are also con-sistent with an extensive body of evidence that show thatpeople do not need additional time to read other forms ofWgurative language, such as metaphors, idioms, and indirectspeech acts, compared to their non-literal counterparts (e.g.,Gibbs, 1989; Gibbs et al., 1997; HoVman & Kemper, 1987;InhoV et al., 1984). The results of Experiment 2 are incon-sistent with all models that obligate the reader to Wrst pro-cess the literal sense of a proverb, such as the standardpragmatic approach of Searle (1979) or a literal-Wrst modelspeciWc to proverb processing (Honeck, 1997).

We recognize that it is diYcult to draw conclusions fromexperiments that produce a null eVect, but we suggest thatthere are a number of reasons why the self-paced moving

Fig. 5. Experiment 2 mean reading times (ms). Error bars with larger capscapture the literal condition and bars with smaller caps capture the Wgura-tive condition.

250

275

300

325

350

375

400

Before First Second Third Fourth Fifth Sixth Seventh After 1 After 2

Proverb Region

Literal Context

Figurative Context

window procedure used here would have detected diVer-ences between reading times had they been present. First, inour previous research examining the inXuence of literal andWgurative contexts on proverb interpretation (e.g., Katz &Ferretti, 2001) we investigate both familiar and unfamiliarproverbs. As mentioned above, in that study we also didnot Wnd diVerences in reading times for familiar proverbsbut we did Wnd robust contextual inXuences on readingtimes for unfamiliar proverbs. Thus, in that study we repli-cate the same null eVect seen here but also show that mov-ing window methodology is sensitive to diVerences in howeasily people can construct Wgurative interpretations in theliteral and Wgurative contexts for unfamiliar proverbs.Moreover, in the present study we used almost three timesthe number of items per condition and controlled for theoverall length of the proverbs and still did not Wnd anyreading time diVerences. Second, as mentioned above, thenull eVects observed here are consistent with a large bodyof evidence that suggests that people often do not needmore time to read Wgurative statements in Wgurative thanliteral contexts. Third, other researchers have shown thatmoving window methodology is sensitive to the earliestmoments of processing in other domains of language com-prehension, such as when examining the interactionbetween syntax and semantics during syntactic ambiguityresolution (e.g., McRae, Spivey-Knowlton, & Tanenhaus,1998). Fourth, examination of Fig. 5 and our statisticalanalysis show that there were no diVerences in readingtimes that were even close to being signiWcant. In short, webelieve that our present experiment would have been sensi-tive to reading times had they been present.

A diVerent, but related issue, is how the diVerent presen-tation rates for each word across the two experiments mayhave led to the diVerences observed between the experi-ments. Although words were presented one at a time inboth experiments, in Experiment 1 the words were pre-sented for a 300 ms duration with an SOA of 500 ms (notethat this is a standard SOA used in ERP investigations oflanguage comprehension), whereas in Experiment 2 peoplewere able to read each word at their own rate. It is interest-ing to note that people in Experiment 2 read each word forapproximately 325 ms on average, only slightly slower thanthe 300 ms word presentation duration in Experiment 1.However, given the SOA of 500 ms in Experiment 1, thissuggests that people were forced to read at a rate of 175 msper word slower on average in Experiment 1 than Experi-ment 2 (keep in mind that we comparing two diVerentgroups of people). In our opinion, it is diYcult to see howslowing people down while they read by such a smallamount of time would make it harder rather than easier tointegrate the exact same phrases in Wgurative contexts thanfor literal contexts. For example, given that the phraseswere familiar statements we would expect, as suggestedabove, that people would probably retrieve the meaning ofthe phrases long before they Wnished reading those phrases.Presumably giving people more time to retrieve the mean-ing of those familiar phrases by slowing down presentation

48 T.R. Ferretti et al. / Brain and Language 101 (2007) 38–49

rates would give them more time to integrate the meaningof those familiar statements with the preceding discoursecontexts. Thus, it is diYcult to see how the slight diVerencesin word presentation rate across the two experiments wouldlead to more diYculty in the Wgurative than literal condi-tion in Experiment 1, but not lead to any diVerences inExperiment 2.

7. General discussion

The present research extends previous research on Wgu-rative language processing in a number of ways. Perhapsthe most intriguing Wnding is that our ERP results showthat people have less diYculty when processing familiarproverbial phrases placed in contexts that invite a literalinterpretation than when placed in Wguratively biasing con-texts, whereas no such diVerences were found for the sameitems in a self-paced reading task. In our case, we directlycompared self-paced reading times and ERP potentials toidentical stimulus sets and found clear diVerences in thepattern of results across the two measures. The diVerencesbetween the two methodologies speak to the importance ofusing converging measures to investigate Wgurative lan-guage processing. In particular, our results add to a smallbut growing body of literature that shows how ERP meth-odology provides a measure that is more sensitive thanreading time measures in indexing the diYculty readershave when comprehending Wgurative statements embeddedin diVerent contexts (e.g., Coulson & Van Petten, 2002;Katz et al., 2004).

In the present case, we examined slow-wave potentialsthat are known to be sensitive to working memory loadduring sentence processing and also N400 and LPC ampli-tudes. As such, the diVerences in ERP amplitudes weobserve here between the literal and Wgurative-inviting con-texts is consistent with the interpretation that the diVer-ences reXect a greater ease in integrating the proverb withthe discourse context when it is being used in its literal sensethan in its familiar non-literal sense, an interpretation alsoconsistent with that given by Coulson and Van Petten(2002) in their ERP study of metaphor processing. More-over, here we Wnd that this diVerence emerges by the thirdword of the proverb. Thus problems in integrating the pro-verbial sense of the sentence into the emerging discoursestructure is found well before the reading of the proverbhas been completed. Recall that the proverbs we employedwere familiar and, therefore, the non-literal, proverbialsense should have been highly salient (see Giora, 2003).Consequently, problems in integration found with the Wgu-rative context are not likely to be due to a problem inaccessing a viable non-literal meaning of the proverb per se,but to diYculty in creating coherent discourse. We arguehere that this diVerence is due to the characteristic of prov-erbs that, when used literally, they tend to be true both liter-ally and Wguratively. Thus a proverb used literally sharesgreater conceptual overlap with the context than when thesame statement is preceded by non-literal context.

7.1. Implications for models of Wgurative language processing

Our results are most consistent with models that positthat people construct a Wgurative interpretation very earlyin the processing of a Wgurative statement when the con-texts are suYciently constraining (Gibbs, 1994; Gibbs et al.,1997; Katz & Ferretti, 2001). The fact that we Wnd diVer-ences in slow-wave potentials for the two contexts at thethird word of the proverb is strong evidence against modelsof Wgurative language processing which posit that the literalmeaning of an entire statement must be processed prior toconstructing a Wgurative meaning (e.g., Grice, 1975).

The Wndings also appear problematic for another theorythat assumes obligatory access of sentence meaning,namely, the graded salience hypothesis (Giora, 2003). Pro-ponents of this approach would need to explain why thefamiliar (and hence salient) proverbs used in the ERPexperiment were more diYcult to integrate into the Wgura-tive context than into the literal context, because that the-ory proposes that it should be at least as easy, and maybeeven easier, to integrate into the Wgurative context than intothe literal context. Taken together, our data is consistentwith models that assume we actively construct interpreta-tions during discourse processing, rather than retrieveentrenched meanings from semantic memory.

In conclusion, our results indicate the utility of usingERP methodology to investigate slow-wave potentials thatdevelop over sentences and clauses for the on-line investi-gation of Wgurative language processing. The presentresearch is the Wrst to show that people have less diYcultyintegrating familiar proverbs presented in literal contextsthan Wgurative contexts, data consistent with theories thatemphasize the active construction of meaning (literal andnon-literal alike) during discourse processing.

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