Disfluencies along the garden path: Brain electrophysiological evidence of disrupted sentence processing

Brain & Language 111 (2009) 86–100

Contents lists available at ScienceDirect

Brain & Language

journal homepage: www.elsevier .com/locate /b&l

Disfluencies along the garden path: Brain electrophysiological evidenceof disrupted sentence processing

Nathan D. Maxfield *, Justine M. Lyon, Elaine R. SillimanUniversity of South Florida, Communication Sciences & Disorders, 4202 East Fowler Avenue, PCD1017, Tampa, FL 33620, USA

a r t i c l e i n f o a b s t r a c t

Article history:Accepted 7 August 2009Available online 17 September 2009

Keywords:DisfluencySentence processingReanalysisEvent-related potentials

0093-934X/$ - see front matter � 2009 Elsevier Inc. Adoi:10.1016/j.bandl.2009.08.003

* Corresponding author. Fax: +1 813 974 0822.E-mail address: [email protected] (N.D. Maxfie

Bailey and Ferreira (2003) hypothesized and reported behavioral evidence that disfluencies (filled andsilent pauses) undesirably affect sentence processing when they appear before disambiguating verbs inGarden Path (GP) sentences. Disfluencies here cause the parser to ‘‘linger” on, and apparently accept ascorrect, an erroneous parse. Critically, the revision process usually associated with GP-disambiguatingverbs does not appear to be triggered. In order to verify this effect, we recorded event-related potentials(ERPs) time-locked to disambiguating verbs in spoken GP sentences from 15 adults. A filled pause, silentpause, or no disfluency appeared before the GP-disambiguating verbs. Principal component analysis(PCA) revealed that fluent GP sentences elicited P600, an ERP index that revision of the initial parsewas attempted. Crucially, P600 was attenuated for sentences containing a filled or silent pause beforethe GP-disambiguating verb. However, PCA detected an N400-like activation for these items, suggestingthat listeners accepted the original (erroneous) parse and continued integrating at the verb; a conclusionthat is tentative and requires further study. A left anterior positivity was also detected at GP-disambig-uating verbs flanked by a filled pause. Discussion focuses on what these preliminary findings tell us abouthow oral comprehension proceeds when the time-course of sentence processing is disrupted.

� 2009 Elsevier Inc. All rights reserved.

1 Bailey and Ferreira (2003) showed that both disfluencies and environmental

1. Introduction

This study presents a test of the hypothesis that disfluencies caninterrupt the revision of temporarily ambiguous sentences (Bailey& Ferreira, 2003). Historically, models of language comprehensionand related research paradigms have focused on the processing ofwell-formed, error free sentences in order to draw conclusionsabout mechanisms underlying sentence processing. However, falsestarts, repetitions, filled and unfilled pauses, and other types of dis-fluencies can occur frequently in spoken language (Bortfeld, Leon,Bloom, Schober, & Brennan, 2001). One treatment of disfluenciesassumes that they do not contain relevant linguistic informationfor the parser and, as such, are filtered out (see Ferreira & Bailey,2004). Recently, however, researchers have begun to ask how suchevents are handled by the comprehension system and what, if any-thing, they can reveal about sentence processing mechanisms. Thisapproach assumes that disfluencies can directly affect how syntac-tic structure is built and interpreted during sentence processing(Ferreira, Lau, & Bailey, 2004).

Of interest here is the hypothesis that disfluencies can impactthe time-course of parsing. This hypothesis assumes that expertlanguage users parse sentences on a shallow basis, just ‘‘good en-

ll rights reserved.

ld).

ough” to rapidly derive sentence interpretations (Ferreira, Ferraro,& Bailey, 2002). The parser quickly computes, ‘‘commits” itself to,and renders sentence interpretations based upon, specific syntacticstructures (see Altmann & Steedman, 1988; Frazier & Fodor, 1978;Kamide, Altmann, & Haywood, 2003; Tyler & Marslen-Wilson,1986). If a disfluency is present, depending on its location, it mayaid in the computation of a correct parse (e.g., by marking junc-tures), or force the parser to ‘‘linger” on an incorrect parse for‘‘too long”, rendering an incorrect sentence interpretation.1

A recent test of this hypothesis (Bailey & Ferreira, 2003) exam-ined the accuracy with which listeners judged the grammaticalityof temporarily ambiguous sentences, specifically Garden Path (GP)sentences, containing disfluencies. GP sentences are useful becausethey provide a means of experimentally forcing the parser to revisesyntactic structure. Consider the sentences below (from Bailey &Ferreira, 2003):

(1a) While the man hunted the deer ran into the woods.(1b) While the man hunted the uh uh deer ran into the woods.(1c) While the man hunted the deer uh uh ran into the woods.

sounds can cue upcoming sentence structure, suggesting that the parser is sensitive tothe presence of disruption regardless of its form. Disfluencies were targeted herebecause they occur as frequently as six to 10 times per 100 words (Bortfield et al.,1999).

http://dx.doi.org/10.1016/j.bandl.2009.08.003

mailto:[email protected]

http://www.sciencedirect.com/science/journal/0093934X

http://www.elsevier.com/locate/b&l

N.D. Maxfield et al. / Brain & Language 111 (2009) 86–100 87

(1d) While the man hunted the deer that was brown and furryran into the woods.

(1a) is a GP sentence in which the listener is initially led to treatthe second noun phrase (NP), the deer, as the object/theme of thesubordinate clause verb, hunt. When the listener reaches the sec-ond verb, ran, she must revise the parse, as the deer now servesas the obligatory subject/agent of the matrix clause. Bailey andFerreira (2003) found that listeners were much more likely tojudge sentences like (1c) and (1d) ‘‘ungrammatical” than sentenceslike (1a) and (1b). Their interpretation was that allowing the parserto ‘‘linger” on the initial parse – due to the presence of disfluencyor modifiers – ‘‘commits” the listener to an erroneous interpreta-tion of NP as the object/theme of the subordinate clause. Acceptingthe erroneous parse apparently forestalls the revision process thathas come to be associated with the processing of GP sentences (seeFodor & Ferreira, 1998). However, this conclusion is tentative, duein part to the behavioral methodology used.

Behavioral linguistic data mainly allow post hoc inferences tobe made about parsing strategies that operate online. For example,grammaticality judgments, the dependent variable used by Baileyand Ferreira (2003), may reflect two influences. The psycholinguis-tic process of interest is one influence. ‘‘Offline” (i.e., extra-grammatical) variables are the other influence, which includeboth task and subject variables (Schutze, 1996) impacting gram-maticality judgments. Task variables, reviewed by Tremblay(2005), may include the concreteness (e.g., Levelt, van Gent, Haans,& Meijers, 1977) and well-formedness (e.g., Greenbaum, 1977) ofsentences, and the extent to which participants are able to relyon the frequency of sentence interpretations and prior context tomake judgments (e.g., Altmann & Steedman, 1988; Sorace, 1996).Subject variables, also reviewed by Tremblay (2005), may includethe level of linguistic training of participants (e.g., Gleitman &Gleitman, 1979; Snow & Meijer, 1977), as well as individuals’ tol-erance of unacceptable sentence forms (e.g., Greenbaum & Quirk,1970). It is difficult to know what impact such variables had onthe results reported by Bailey and Ferreira (2003).

Another behavioral approach for assessing how parse revisionproceeds when listeners are forced to linger at the disambiguationpoint of GP sentences, has been to assess listeners’ answers toquestions. The purpose is to probe their interpretations of differentaspects of GP sentences. Christianson, Hollingworth, Halliwell, andFerreira (2001) reported that participants were less likely to an-swer questions about subordinate clauses correctly than questionsabout matrix clauses. For the GP sentence, While the man huntedthe deer ran into the woods, a correct answer about the matrixclause (Did the deer run away?, for which the correct answer is ‘‘Yes”)requires that the parser revise its initial assignment of the deer asthe object/theme of the subordinate clause to the subject/agentof the matrix clause. A correct answer about the subordinate clause(Did the man hunt the deer?, for which the correct answer is, techni-cally, ‘‘No”) requires both that revision take place and the originalinterpretation (of the deer as object/theme) be dropped.2 The lowernumber of correct responses to subordinate clause questions re-ported by Christianson et al. (2001) suggests that their participantsdid not always drop their initial (erroneous) parse of GP sentences.Crucially, when the ambiguous region was lengthened by modifiers,e.g., While the man hunted the deer that was brown and graceful raninto the woods, listeners were even more likely to answer subordi-nate clause questions incorrectly. This suggests, once again, that

2 In contrast, for a non-GP sentence such as, While the man arrived the deer ran intothe woods, the first VP (arrive) is intransitive, so the second NP (the deer) is assigned asthe subject / agent of the matrix clause without initial ambiguity. In this case, acorrect answer to a subordinate clause question (Did the man arrive? for which thecorrect answer is ‘‘Yes”) does not require that an initial (erroneous) parse be dropped.

the longer one lingers on an incorrect parse, the more likely it is thata sentence will be interpreted incorrectly. However, ‘‘offline” vari-ables affected the results of this task, too, one being the plausibilityof final sentence interpretations (Christianson et al., 2001).

A more direct measure of sentence processing – one less sus-ceptible to ‘‘offline” (extragrammatical) variables – is needed toconfirm whether disfluencies affect parsing in the manner sug-gested by Bailey and Ferreira (2003). These same authors (Bailey& Ferreira, 2007) and others (Arnold, Hudson-Kam, & Tannenhaus,2007) recently turned to using eye-tracking. Another approach isto use brain electrophysiology to limit the contributions of ‘‘off-line” variables while studying the impact of disfluencies on sen-tence processing. Event-related potentials (ERPs) are voltages,generated by the brain, that can be recorded at the scalp. Crucially,specific components of the ERP signal can be associated with theactivation of specific linguistic processes (see Osterhout, McLaugh-lin, Kim, Greenwald, & Inoue, 2004).

Most important for our purpose is the P600 component of theERP. As reviewed in Frisch, Schlesewsky, Saddy, and Alpermann(2002), P600 activation occurs when the parser encounters a syn-tactic violation, such as The broker persuaded to sell the stock (fromOsterhout & Holcomb, 1992); or when the parser generates anunsatisfactory disambiguation of an ambiguous string, such asThe doctor charged the patient was lying (from Osterhout, Holcomb,& Swinney, 1994). Here, the lexical bias of the verb (transitivity)initially causes the parser to assign the second NP (the patient) asthe object of the subordinate clause verb. Frisch et al. (2002)showed that P600 is also seen when the parser encounters syntac-tically ambiguous arguments. As these and other examples suggest(see Brown, Hagoort, & Kutas, 2000; Munte, Heinze, Matzke, Wie-ringa, & Johannes, 1998; Osterhout et al., 2004), P600 activationmarks the parser’s attempt to revise structural mismatch or ambi-guity. It is important to note that P600 activation to these types ofphenomena may be significantly attenuated or absent when com-prehenders are forced to attend to semantic aspects of sentences,either through explicit instruction (Hahne & Friederici, 2002) orby presenting syntactic anomalies using words whose low-clozeprobability forces semantic analysis (Gunter, Friederici, & Schrie-fers, 2000). Results of still another study suggest that individualdifferences in attention to syntactic versus semantic ramificationsof syntactic violations can also have a role in determining whetherP600 is activated (Osterhout, 1997). P600 is a positive-going, pos-terior-maximal ERP with an onset at�500 ms and a peak latency at�800 ms.3,4 P600 can be differentiated from other ERP components(namely, P300) that reflect domain-general processes, such asmemory updating, also active during sentence processing (Frieder-ici, Mecklinger, Spencer, Steinhauer, & Donchin, 2001).5

Below we present ERP data to contribute to the growing body ofliterature on the effect of disfluencies on sentence processing. Inorder to isolate our focus to studying the effects of disfluency onparse revision, we examined ERPs elicited to verbs that shouldserve to disambiguate GP sentences and were, in some instances,flanked by a preceding silent or filled pause. We predicted that flu-ently-spoken GP sentences would elicit P600 at the disambiguatingverb. Furthermore, and central to the purpose of our study, wehypothesized that GP sentences containing a silent or filled pausejust before the disambiguating verb would result in an attenuatedor absent P600, an indication that an attempt at revising the initialparse did not take place as a result of the time spent ‘‘lingering” on

3 P600 onset time and peak latency can vary with the time needed for compreh-enders to diagnose and revise an erroneous parse (Friederici, 1998).

4 Because of the associated function and waveform morphology of P600, it is alsoknown as the ‘syntactic positive shift’ (Hagoort, Brown, & Groothusen, 1993).

5 Friederici et al. (2001) isolated the P300 and P600 components of the ERP fromeach other by using Principal Component Analysis, an approach adopted here.

88 N.D. Maxfield et al. / Brain & Language 111 (2009) 86–100

an incorrect parse before each verb. An additional possibility wasthat disfluency prior to disambiguating verbs engages other pro-cessing mechanisms that are qualitatively different and, hence,would be evidenced by ERP activations other than P600. While spe-cific predictions were not made regarding what other processesmight be elicited by disfluencies or their neural correlates, a prin-cipal component analysis of the ERP data allowed us to explore thispossibility systematically.

2. Methods

2.1. Participants

Participants were 15 university students (5 female) ages 18–20 years (mean 18.4 years); 13 were right-handed. All received ex-tra class credit for participating. Each signed a consent form beforetesting, and completed a health and language questionnaire aftertesting. All were native speakers of English, in good health, withnormal hearing, and normal or corrected-to-normal vision. Nonetook medications altering cognitive function.

2.2. Materials

Three sets of GP sentences were created: (1) 30 with no disflu-encies (fluent GP); (2) 30 with a silent pause before the disambig-uating verb (GP + silent pause); and (3) 30 with a filled pause (‘‘uhuh”) before the disambiguating verb (GP + filled pause). All 90 GPsentences included a subordinate clause followed by a matrixclause. The verb in each subordinate clause was transitive. Whilethe sentences in each set were different, the same 30 disambiguat-ing verbs appeared in each set. These verbs contained one or twosyllables. The 90 GP sentences are listed in Appendix A.

In addition, 90 non-GP sentences were created by replacing thetransitively-biased verb in the subordinate clause with an intransi-tive verb.6 Thirty non-GP sentences did not contain a pause, andserved as Control items (see Appendix A). Thirty non-GP sentencescontained a silent pause, and another 30 contained a filled pause, be-tween the second NP and the matrix clause verb. These latter 60items were included to ensure that the probability of hearing sen-tences containing silent or filled pauses was equal across GP andnon-GP items. We did not want participants to associate disfluenciesexclusively with GP sentences. In addition, rare presentations of cer-tain sentence conditions can elicit P300 activations (Coulson, King, &Kutas, 1998). Holding the probability of our different sentence typesequal should have limited P3 effects from commingling with P600.Data from the 60 non-GP sentences containing disfluencies werenot ultimately analyzed.

The experimenters’ linguistic and pragmatic intuitions wereused to ensure that the relationship between the object NP andcritical verb in each sentence was plausible. Pre- and post-verbsentence structure and lexical content was similar between condi-tions. Although identical critical verbs were used in each condition,post-verb material was varied across the sentences in each condi-tion. For most items, the material following the critical verb was aprepositional phrase. In far fewer instances, a noun phrase, adjec-tive or adverb followed the critical verb. In rare instances, sen-tences ended with an infinitive/gerund phrase, or with thecritical verb itself. An advantage of varying the post-verb materialis that it limits the possibility that participants were biased tointerpret sentences in a small handful of ways that would havebeen predictable by holding the post-verb material constant (seeKim & Osterhout, 1995). As shown in Appendix A, the proportion

6 Verbs were classified as either transitive or intransitive using the DiscourseOriented Inference System (DORIS) (Bos, 2001).

of each type of post-verb material was similar across the four mainconditions, limiting the possibility that condition differences in theERPs elicited by our critical verbs were due to significantly differ-ent post-verb content.

2.2.1. Sentence recordingThe sentences were digitally recorded by a female speaker of

American English. To control for disambiguating prosodic cues inGP conditions, each GP sentence was preceded by the carrierphrase ‘‘According to Mary. . .” (see Bailey & Ferreira, 2003). Begin-ning each sentence with the carrier phrase helped the reader main-tain constant prosody while reading each GP sentence, instead ofpausing (with sharply rising and then falling intonation) beforethe object NP. We did not want listeners to be able to use this typeof end-of-phrase prosodic cue to disambiguate the GP sentences. Incontrast, the Control sentences were read aloud so that a large pro-sodic break separated the first VP and second NP. For each sentencecontaining a disfluency, the speaker added an unfilled pause (si-lently counting to two) or a filled pause (‘‘uh uh”) before the criticalverb. The sentences were then edited offline using SoundForgesoftware (Sony). Each sentence was time-compressed to 85% ofits original duration. Time compression was used to increase,slightly, rate of presentation. Finally, the stimuli were normalizedso that the peak RMS amplitude (in dB) was the same for eachsentence.

It is important to note that the silent and filled pauses were notmanipulated in order to control for duration during the originalreading of the sentences, or when the sentences were edited. Baileyand Ferreira (2003) used this same approach to keep their sen-tences sounding as naturalistic as possible. Acoustical analysis ofour sentences did reveal a statistically significant difference inthe durations of the silent versus filled pauses in the two disfluentGP conditions (mean difference = 1105 ms, t(58) = �26.2, p = .000),with filled pauses longer than silent pauses.

For the four main conditions, we assessed two additionalstimulus characteristics post hoc. The first was verb duration.Although the same verbs were used in all four conditions, theiraverage spoken duration was different between conditions: Con-trol – 227.1 ms (SD = 45.2); fluent GP – 216.9 ms (SD = 55);GP + silent pause – 255.6 ms (SD = 52); and GP + filled pause –271 ms (SD = 49.8). ANOVA revealed a statistically significantmain effect of Condition (F[3, 116] = 7.32, p = .000). Bonferroni-corrected pair-wise comparisons revealed that the difference indurations of the critical verbs for Control versus GP + filledpause was statistically significant (p = .006), as was the differ-ence in durations of the critical verbs for fluent GP versusGP + silent pause (p = .019), and the difference in durations ofthe critical verbs for fluent GP versus GP + filled pause(p = .000). In our ERP analysis, we were primarily concernedwith finding pair-wise amplitude differences between Controland each of the three experimental conditions. That the 30 crit-ical verbs had a significantly longer duration for GP + filledpause than for Control, therefore, is most relevant. Word lengthhas been shown to increase immediately following filled pauses(Levelt & Cutler, 1983) an average of 1.19 times longer thanwhen the same word appears in the same sentence contextwithout a preceding filled pause (Bell et al., 2003). The averageincrease in duration of our critical verbs following filled pausesversus no filled pause was consistent with this proportionallengthening. Our critical verbs contained just one or two sylla-bles, and listeners can predict with good accuracy what a wordis, given only the initial part of the phoneme string (Luce,1986). Much of the natural word lengthening that follows filledpauses happens via vowel lengthening (Bell et al., 2003). Themost likely impact of longer vowels is that word recognitiontime (i.e., the time at which the uniqueness point of a word


is reached) was affected, slightly affecting the latency of ERPselicited in the GP + filled pause condition. Had we modifiedthe apparently natural lengthening of words following filledpauses (via an acoustical editing procedure), our attempt at con-trol could have been perceived by participants as a violation,potentially eliciting undesirable ERP effects.

Second, we determined that the post-verb material was similarin duration between conditions. The average duration from onsetof critical verb to end of sentence was as follows for each of the fourcritical conditions: Control – 762.7 ms (SD = 139); fluent GP –745.8 ms (SD = 123.4); GP + silent pause – 777.4 ms (SD = 138.4);and GP + filled pause – 786.9 ms (SD = 152.3). ANOVA did not reveala main effect of Condition in the duration of post-verb material(F[3, 116] = .502, p = .682). If ERPs related to sentence closure (seeOsterhout & Holcomb, 1992) were present in our dataset, theyshould have been elicited at approximately the same latency forall four conditions.

2.2.2. Probe questionsOne Yes/No question was designed for each sentence. Each

question tested participants’ interpretation of the second NP; spe-cifically, whether the second NP was interpreted as object/themeof the subordinate clause, or as subject/agent of the matrix clause(following Christianson et al., 2001). Within each condition, half ofthe questions probed subordinate clause and half probed matrixclause (see Section 1 for examples).

2.3. Procedure

Each participant was tested in a single session. Before testing,the participants read instructions indicating they were to listencarefully to each sentence, answer a Yes/No question by pressingone of two buttons on a response box, and then rate the confidencethey had with a selected answer along a 4-point scale by pressingone of four buttons on the response box.7 Testing then began, last-ing for �25–30 min.

Each testing session was comprised of 5 blocks of 36 sen-tences. Each block contained 6 sentences from each of the 6 dif-ferent conditions, presented in randomized order. As eachsentence was presented, a crosshair (+) was displayed on thecomputer monitor. Each sentence was followed by a writtenprobe question, appearing 2000 ms after the offset of the sen-tence-final word. The question remained on-screen until the par-ticipant responded, and then a 4-point Likert scale appeared.After confidence was rated, an intertrial interval of 1500 mspassed, followed by the next sentence.

2.4. Apparatus and recording

Each participant was seated in a dimly-lit, sound-attenuatingbooth, facing a 19-in. LCD monitor. Sentences were presentedvia insert earphones (Etymotic Research, Model E-2). Yes/No re-sponses and confidence ratings were recorded using a push-but-ton response box (Psychological Software Tools). ContinuousEEG was recorded from each participant during testing at a sam-

7 Confidence ratings were included here only to ensure participants answeredprobe questions as thoughtfully as possible. Ratings of confidence are useful foridentifying individual differences in how decisions are made under conditions ouncertainty (see Stankov & Crawford, 1996). As noted in the Introduction, individuadifferences in the perception of syntactic anomaly can affect whether P600 activationis observed. Therefore, it may be beneficial to revisit our data in a future report fromthe perspective of individual differences, by relating our confidence data with our ERPresults.

fl

pling rate of 500 Hz. SCAN software, Version 4.3 (Neuroscan),controlled EEG recording. Each participant wore a QuikCap (Neu-roscan) fitted with 66 active recording electrodes made of Ag/AgCl, as well as one reference and one ground electrode. Fouradditional electrodes recorded electro-ocular activity. QuikGel(Neuroscan) was used as the medium between each electrodeand the scalp. Electrode impedance was kept below 30 kX (Fer-ree, Luu, Russell, & Tucker, 2001). Continuous EEG was low-passfiltered online, at a corner frequency of 100 Hz. E-Prime experi-mental control software (Psychological Software Tools, version1.1), run on a PC computer, was used to present the sentencesand log behavioral responses.

2.5. EEG-to-average-ERP data reduction

The continuous EEG record of each participant was segmentedinto individual epochs. Each epoch was comprised of EEG data re-corded from each of the 66 active recording electrodes, during pre-sentation of the critical verb in each sentence, beginning 200 msbefore the onset of the verb, terminating 2200 ms following theonset of the verb. Epoch length was truncated to a critical interval(0–2000 ms relative to stimulus onset) following averaging. How-ever, we began with an extended epoch to ensure that the proce-dures, described next, would adequately correct or reject artifactson the leading and trailing edges of this critical (0–2000 ms) timeinterval.

2.5.1. EEG ocular artifact correctionInspection of the EEG data revealed that most participants’

recordings were contaminated by eye blink artifact. To salvage asmany trials as possible (Picton et al., 2000), we used an Indepen-dent Component Analysis (ICA)-based (Bell & Sejnowski, 1995)ocular artifact correction procedure modified from Dien (2005a,2005b). At least one blink component was identified for each par-ticipant. The average number of trials corrected for blink activitywas as follows for each of the four conditions: Control- 22.2 trialscorrected (SD = 3.7); fluent GP – 21.4 trials corrected (SD = 3.7);GP + silent pause – 21.9 trials corrected (SD = 3.2); and GP + filledpause – 19.5 trials corrected (SD = 5.5). ANOVA did not reveal amain effect of Condition in the number of trials corrected(F[3, 56] = 1.24, p = .303). The ICA approach used here has beenshown in published reports to accurately identify and remove ocu-lar artifact without significantly warping/skewing ERP variance(see, for example, Glass et al., 2004).

2.5.2. EEG trial rejectionAfter ICA blink correction, channels whose fast-average ampli-

tude exceeded 200 microvolts (large drift) were marked bad; aswere channels whose differential amplitude exceeded 100 micro-volts (high-frequency noise). Any trial with more than three badchannels (5% of the total number of channels) was rejected. No par-ticipant lost more than 20% of their trials for any condition, andmost participants lost well under 10% of their trials per conditiondue to bad channel artifact.

2.5.3. Final EEG processingFor any accepted trial with channels marked bad (63), the EEG

activity at those channels was replaced using spherical splineinterpolation (Ferree, 2000). The EEG trials were averaged together,separately for each condition, with the exception of the Con-trol + silent pause and Control + filled pause conditions, whichwere not analyzed. As a result, each participant had four sets ofERP averages, one for each condition. For each participant, no fewerthan 24 artifact-free trials went into the set of ERP averages foreach condition. The averaged ERP data were truncated to include


only the critical time window (0–2000 ms after verb onset), re-ref-erenced to linked mastoids, and baseline-corrected (0 to+100 ms).8

2.6. Data analysis

2.6.1. Behavioral dataTrial-by-trial accuracy of the push-button responses was scored

for each participant automatically during testing in E-prime. Accu-racy rates were submitted to a repeated-measures analysis of var-iance (ANOVA). Sentence Type (Control, GP, GP + silent pause,GP + filled pause) and Clause Type (matrix versus subordinate)were treated as within-subjects factors. The reported p-values forthis analysis were corrected when the assumption of sphericitywas violated (Greenhouse & Geisser, 1959). As noted above, partic-ipants’ confidence ratings were not analyzed.

2.6.2. Electrophysiological dataThe ERP data were submitted to a covariance-based, two-step,

temporal-spatial PCA (Dien & Frishkoff, 2005).9 In step one, thesubject ERP averages were entered into a matrix with 1001 col-umns (one column per sampling point) and 3960 rows (averagedERPs for 15 participants, at each of 64 electrodes, in each of fourconditions). This matrix was submitted to a temporal PCA in orderto identify distinct windows of time in the ERP averages (temporalfactors) during which similar voltage variance was active acrossconsecutive sampling points. Twenty-three temporal factors wereretained. A subset of those temporal factors (n = 13) had a time-course roughly consistent with known linguistically-evoked poten-tials (peak latency between 150 and 1200 ms). In step two, a spa-tial PCA was performed on the factor scores associated with each ofthose temporal factors. The scores for each temporal factor (repre-senting the ERP variance within a specific time window) were en-tered into a matrix with 64 columns (one column per electrode)and 60 rows (temporal factor scores for 15 participants, in eachof four conditions). This matrix was submitted to a spatial PCA inorder to identify topographically coherent regions of ERP variance(spatial factors) within the time window associated with each tem-poral factor. Thirteen spatial PCAs were carried out, one for each of13 potentially relevant temporal factors.

8 For Control and GP sentences, the critical verb was preceded immediately bylexical material. For GP-disfluency sentences, the critical verb was precededimmediately by a filled or silent pause. Our concern was that the different materialpreceding our critical verbs in the different conditions elicited different types of ERPactivity, unevenly affecting ERP amplitude immediately preceding and at the onsetof presentation of our critical verbs in the different conditions. Other publishedstudies have used a post-stimulus baseline correction procedure in order to offsetthis effect (e.g., Neville, Nichol, Barss, Forster, & Garrett, 1991; Friederici, Hahne, &Mecklinger, 1996; Hahne, 2001; Hahne & Friederici, 1999; Hahne & Friederici, 2001;Osterhout et al., 1994). We adopted their approach. In order to validate thisprocedure, Friederici et al. (1996) (among other examples) first baseline-correctedtheir averaged ERPs using a post-stimulus interval. They then determined, viastatistical analysis, that amplitude differences were not present in the ERPs betweenconditions during the post-stimulus baseline interval. Along this same line, ourPrincipal Component Analysis (reported below) failed to uncover any ERP amplitudedifferences between conditions in the duration covering our post-stimulus baselineinterval (0 to + 100 ms), i.e., there were no temporal factors with a peak latencybetween 0 and +100 ms post-verb that captured ERP amplitude differences betweenconditions.

9 PCA is a relatively easy-to-use procedure that allows users to comprehensivelyexamine a large data set while at the same time improving measurement accuracy (ifused correctly, see Dien & Frishkoff, 2005). The parsimonious results afforded bytemporal-spatial PCA allowed us to constrain the high Type-1 error rate that wouldotherwise have come with conducting multiple statistical tests, i.e., for conditioneffects at each of 64 electrodes within one or more time windows (as has been donetraditionally). PCA is also desirable in the present case, as we were looking for bothknown effects (P600), and for other ERP effects via a controlled exploratory analysis ofthe data for which PCA is especially suited.

The following specific procedures were used to conduct the ini-tial temporal PCA, and each of the subsequent spatial PCAs. In or-der to determine how many dominant-variance componentscould be extracted, we used Rule M (Preisendorder & Mobley,1988). All components meeting this criterion were rotated to sim-ple structure using Promax (Hendrickson & White, 1964) with Kai-ser normalization and k = 2 (Richman, 1986; Tataryn, Wood, &Gorsuch, 1999). All PC analyses were completed using PCA Toolbox(Dien, 2005a, 2005b). Our primary goal was to identify a temporal–spatial factor combination whose time-course, scalp topography,and associated variance were consistent with P600 activation. Totest for experimental effects, factor scores summarizing the voltagevariance associated with specific pairs of temporal and spatial fac-tors were submitted to a repeated-measures ANOVA with SentenceType (Control, GP, GP + silent pause, GP + filled pause) as a within-subjects factor. When sphericity was not met, degrees of freedomwere corrected (Greenhouse & Geisser, 1959).

3. Results

3.1. Behavioral data

As shown in Fig. 1, Control sentences elicited the greatest num-ber of items correct. Repeated-measures ANOVA revealed a maineffect of Clause Type (F(1, 14) = 12.56, MSe = 261.08, p = .003); amain effect of Sentence Type (F(3, 42) = 33.44, MSe = 615.723,p = .000); and an interaction of Clause Type and Sentence Type(F = (3, 42) = 11.61, MSe = 57.54, p = .000). Since sphericity wasnot met for the interaction (e = .605, p = .027), pair-wise compari-sons of Sentence Type within each Clause condition were madeusing Bonferroni correction (Stevens, 1999). Participants mademore errors on GP sentences of all three types than on Control sen-tences (Fig. 1, right panel). Each pair-wise difference (Control ver-sus GP of each type) was statistically significant (p < .05). Forsubordinate clause questions, GP + filled pause elicited even moreerrors than fluent GP sentences (Fig. 1, right panel; p < .05 for thisdifference). For matrix clause questions, participants made moreerrors on each type of GP sentence than on Controls (Fig. 1, left pa-nel; each Control versus GP difference was significant, p < .05). Nofurther differences were observed for matrix clause questions.

3.2. Electrophysiological data

3.2.1. Temporal-spatial PCAGrand average waveforms at nine scalp electrodes are shown in

Fig. 2. These waveforms summarize ERP activations seen across thescalp in each condition which, as described above, were decom-posed using a two-step PCA. For the initial temporal PCA, 23 tem-poral factors were retained and Promax-rotated, accounting for82.52% of the variance. Just three of those 23 temporal factors wereultimately shown to be associated with interpretable, statisticallysignificant ERP effects. Fig. 3 illustrates their factor loadings. High-est loadings indicate the time at which temporally discrete voltagevariance was most active. Each temporal factor will, hereafter, bereferred to by its peak latency (T222, T344, and T1060, respec-tively). As described above, a separate spatial PCA was run on thefactor scores associated with each of these temporal factors. Onlyspatial factors associated with interpretable, statistically signifi-cant experimental effects are reported below.

3.2.2. T222, left anterior activationThree spatial factors were retained and Promax-rotated for

T222, partitioning the voltage variance within the T222 time win-dow into three scalp regions. One spatial factor was defined by aleft anterior scalp topography (Fig. 4, top right panel). Repeated-

GP with Filled Pause: Subordinate

Clause Question

GP with Silent Filler: Subordinate

Clause Question

GP: Subordinate

Clause Question

Control: Subordinate

Clause Question

GP with Filled Pause:

Matrix Clause

Question

GP with Silent Filler:

Matrix Clause

Question

Garden Path (GP): Matrix

Clause Question

Control: Matrix Clause

Question

Mea

n Co

rrec

t and

95%

Con

fiden

ce In

terv

als

15

10

5

0

Fig. 1. Mean number of items correct and 95% confidence intervals for each condition.

15

10

5

0

2000150010005000

FC3 15

10

5

0

2000150010005000

FCz 15

10

5

0

2000150010005000

FC4

15

10

5

0

2000150010005000

CP3 15

10

5

0

ampl

itude

(mic

rovo

lts)

2000150010005000time (milliseconds)

control Garden Path (GP) GP + silent pause GP + filled pause

CPz 15

10

5

0

2000150010005000

CP4

15

10

5

0

2000150010005000

PO5 15

10

5

0

2000150010005000

POz 15

10

5

0

2000150010005000

PO6

Fig. 2. Grand average ERP waveforms for each of the four main conditions at nine electrodes.


measures ANOVA of the temporal-spatial factor scores – summa-rizing the voltage variance active within the T222 time windowat this left anterior scalp region – revealed a main effect of SentenceType (F(3, 42) = 5.19, MSe = 4.46, p = .004). Since sphericity wasmet (e = .745, p = .21), multiple comparisons were made using Tu-key’s HSD test (Stevens, 1999), revealing a statistically significantdifference between Control and GP + filled pause (p = .006). A sta-

tistically significant difference between GP + silent pause andGP + filled pause was also detected (p = .04). As shown in Fig. 4(bottom panel), the voltage activity was more positive in ampli-tude for GP + filled pause than for each of these other two condi-tions. This activity is consistent with a known word-evokedpotential discussed below. Fig. 4 (middle panel) shows this activityin the grand averaged waveform.

0.8

0.6

0.4

0.2

0.0

-0.2fact

or lo

adin

gs (s

tand

ard

scal

e)


0.8

0.6

0.4

0.2

0.0

-0.2fact

or lo

adin

gs (s

tand

ard

scal

e)


0.8

0.6

0.4

0.2

0.0

-0.2fact

or lo

adin

gs (s

tand

ard

scal

e)


Fig. 3. Factor loadings for three temporal factors associated with experimentaleffects.


3.2.3. T344, posterior parietal activationMoving later in time to T344, three spatial factors were retained

and Promax-rotated, partitioning the voltage variance within thistime window into three scalp regions. As shown in Fig. 5 (top rightpanel), one spatial factor was defined by a posterior parietal scalptopography. Repeated-measures ANOVA of the temporal-spatialfactor scores – summarizing the voltage variance active withinthe T344 time window at this posterior parietal scalp region – re-vealed a main effect of Sentence Type (F(3, 42) = 7.24, MSe = 5.79,p = .001). Sphericity was met (e = .724, p = .17), and so multiplecomparisons were made using Tukey’s HSD test (Stevens, 1999),revealing a statistically significant difference between Controland GP + silent pause (p = .001), and a statistically significant dif-ference between Control and GP + filled pause (p = .04). A statisti-cally significant difference between GP (no disfluency) andGP + silent pause was also detected (p = .007). As shown in Fig. 5(bottom panel), the voltage activity was more negative in ampli-tude for GP + silent pause and GP + filled pause than for Controland GP. This activity is consistent with an N400-type ERP compo-nent. Fig. 5 (middle panel) shows this activity in the grand aver-aged waveform.

3.2.4. T1060, left posterior parietal activationFinally, three spatial factors were retained and Promax-rotated

for the latest (T1060) temporal factor, partitioning the voltage var-iance within this time window into three scalp regions. As shownin Fig. 6 (top right panel), one spatial factor was defined by a left

posterior parietal scalp topography. Repeated-measures ANOVAof the temporal-spatial factor scores – summarizing the voltagevariance recorded within the T1060 time window at this left pos-terior parietal scalp region – revealed a main effect of Sentence Type(F(3, 42) = 3.16, MSe = 1.76, p = .034). With sphericity met (e = .813,p = .45), multiple comparisons were made using Tukey’s HSD test(Stevens, 1999), revealing a statistically significant difference be-tween Control and fluent GP (p = .02). As shown in Fig. 6 (bottompanel), the voltage activity was more positive in amplitude for flu-ent GP than for Control. This effect is consistent with P600 activa-tion. Fig. 6 (middle panel) illustrates this activity in the grandaverage waveform.

4. Discussion

4.1. Summary of experiment and findings

GP and non-GP control sentences were presented to 15 adults.GP sentences contained no disfluency, a silent pause, or a filledpause before the disambiguating verb. A probe question was givenafter each sentence to assess participants’ interpretations of eitherthe subordinate or matrix clause. Comprehension was less accuratefor GP versus non-GP sentences. Subordinate clause questions forGP + filled pause items elicited the greatest number of errors.

Scalp-recorded ERPs elicited by the critical verb in each GP sen-tence (and to verbs appearing at the same location in non-GP sen-tences) were analyzed. Principal component analysis revealed thatP600 was elicited by the fluent GP condition, but not by the twoGP + disfluency conditions. However, N400 was elicited by disam-biguating verbs in the GP + disfluency conditions, i.e., followingfilled and silent pauses. An early left anterior positivity was alsoelicited following filled pauses.

4.2. Comprehension accuracy

Our participants had less accurate comprehension for GP sen-tences, with and without disfluencies, than for non-GP sentences.Christianson et al. (2001) hypothesized that when comprehendersencounter ambiguity, such as in GP sentences, they revise theirinterpretations on an incomplete basis. To investigate this hypoth-esis, they asked participants to answer questions about differentaspects of GP sentences, a procedure we borrowed. As outlinedin Section 1, for sentences like ‘‘While Bill hunted the deer ran intothe woods” (Christianson et al., 2001), participants were less likelyto answer questions about the subordinate clause correctly (e.g.,Did the man hunt the deer?, for which an incorrect answer wouldbe, technically, ‘‘Yes”) than questions about matrix clause (e.g.,Did the deer run away?, for which an incorrect answer would be‘‘No”). This suggests that they did not always drop their initialinterpretation. This was especially true when the ambiguous re-gion was lengthened by modifiers, and when the final sentenceinterpretation was plausible (even if incorrect). These results wereinterpreted as indicating that revision is not an ‘‘all or none” pro-cess, but that the parser derives a just ‘‘good enough” representa-tion of the input based upon both the timeliness and plausibilityof information available in sentence presentations.

Behavioral data from our experiment were consistent withthose previous findings. Our participants, too, were less accuratewhen answering subordinate clause questions in GP sentencescompared to matrix clause questions. In addition to replicating thiseffect, we also found that listeners were even less accurate whenanswering subordinate clause questions for GP + filled pause sen-tences than for fluently-spoken GP sentences. Similar to whenmodifiers lengthen the ambiguous region in GP sentences (seeChristianson et al., 2001), comprehenders also have a particularly

0.8

0.6

0.4

0.2

0.0

-0.2fact

or lo

adin

gs (

stan

dard

sca

le)


15

10

5

0

2000150010005000

FC3

tem

pora

l-spa

tial f

acto

r sc

ore

ampl

itude

1.5

1.0

.5

0.0

-.5

-1.0

-1.5

control

Garden Path (GP)

GP + silent pause

GP + filled pause

Fig. 4. Factor loadings for T222 (top left). Topographic map of the left anterior spatial factor associated with T222 (top right). Factor scores summarizing the ERP variancewithin the T222 time window at this scalp region (bottom). Illustration of this component activity in the grand averaged waveform at electrode FC3 (middle).


difficult time revising their interpretations of GP sentences whenthe ambiguous region is lengthened by a filled pause. One possiblereason, revealed by our ERP data, is that parse revision did not ap-pear to be attempted for these items.

4.3. P600 effects

Fluently-spoken GP sentences were shown in our study to elicitP600, as expected. P600 activation is typically treated as a measureof parse revision, observed when an inappropriate, less-preferred,or ambiguous syntactic structure is encountered during sentenceprocessing (Frisch et al., 2002). Our results reveal however thatP600 activation, and the revision process it is thought to index,do not necessarily translate into better comprehension accuracy.Participants were less accurate when answering comprehensionquestions about fluent GP sentences, where P600 was observed,than about control sentences. Based on these results, P600 activa-

tion seems to index an attempt, although not always successful, atparse revision. Lewis (1998) notes that when sentence ambiguity isdiagnosed, resolution is open to ‘‘. . .potentially any knowledgesource (semantic and contextual). . .” (p. 278). For many of ouritems, the first VP and second NP had a plausible relationship(e.g., As the man hunted the deer ran away), potentially reinforcingan incorrect interpretation (the act of hunting, directed at a deer, ishighly plausible even though the relationship is incorrect in thissentence). The second VP also may have served to reinforce anincorrect interpretation (it is quite plausible that a deer, apparentlybeing hunted, would be running). Participants’ use of world knowl-edge to interpret sentences could have masked any attempts theymay have made to revise each parse at a grammatical level; reiter-ating the importance of using a dependent variable, such as ERPs,less sensitive to ‘‘offline” variables.

More importantly, P600 was not detected for GP sentences con-taining disfluencies – including both filled and silent pauses – be-

0.8

0.6

0.4

0.2

0.0

-0.2fact

or lo

adin

gs (s

tand

ard

scal

e)


15

10

5

0

2000150010005000

POz

tem

pora

l-spa

tial f

acto

r sco

re a

mpl

itude

1.0

.5

0.0

-.5

-1.0

-1.5

-2.0

control

Garden Path (GP)

GP + silent pause

GP + filled pause

Fig. 5. Factor loadings for T344 (top left). Topographic map of the posterior parietal spatial factor associated with T344 (top right). Factor scores summarizing the ERPvariance within the T344 time window at this scalp region (bottom). Illustration of this component activity in the grand averaged waveform at electrode POz (middle).


fore the disambiguating verb. Christianson et al. (2001), as well asBailey and Ferreira (2003), entertained the possibility that patternsseen in their behavioral data indicated that incomplete or no revi-sion was attempted when the ambiguous region in GP sentenceswas lengthened by modifiers or by disfluencies, respectively. Asnoted above, P600 activation marks the parser’s attempt to revisestructural mismatch or ambiguity. As such, it is typically elicitedby disambiguating verbs in GP sentences. A statistically undetect-able P600 in our GP-disfluency conditions tentatively supports thehypothesis that lengthening the ambiguous region in GP sentenceswith a disfluency interrupts attempts at parse revision. P600 wasundetectable not only when the ambiguous region was lengthenedby a long filled pause, but also when brief intervening silence (i.e.,an unfilled pause) was inserted.

Our focus now turns to explaining why attempts at parse revi-sion may be interrupted in this way. As reviewed in Section 1, both

(Christianson et al., 2001) and (Bailey & Ferreira, 2003) hypothe-sized that time spent lingering on a parse can force the parser toaccept it. Another ERP effect observed in our study yields evidencethat the erroneous parse preceding disfluencies in GP sentencesfails to elicit revision because it is treated as, or takes on the statusof, a correct parse.

4.4. N400 effects

In contrast to fluently-spoken GP sentences, GP sentencescontaining both filled and silent pauses failed to elicit P600, butdid elicit an N400-type ERP component at the disambiguating verb.N400 is an ERP measure of lexical-semantic processing, activatedas people attempt to integrate a word with its (preceding)semantic context. N400 typically peaks in amplitude at �400–550 ms after word onset, has a larger amplitude when a word is

0.8

0.6

0.4

0.2

0.0

-0.2fact

or lo

adin

gs (s

tand

ard

scal

e)


15

10

5

0

2000150010005000

PO5

tem

pora

l-spa

tial f

acto

r sco

re a

mpl

itude

2.5

2.0

1.5

1.0

.5

0.0

-.5

control

Garden Path (GP)

GP + silent pause

GP + filled pause

Fig. 6. Factor loadings for T1060 (top left). Topographic map of the left posterior parietal spatial factor associated with T1060 (top right). Factor scores summarizing the ERPvariance within the T1060 time window at this scalp region (bottom). Illustration of this component activity in the grand averaged waveform at electrode PO5 (middle).


semantically incongruous with its context, and has a parietal–max-imal scalp topography (Dien, Frishkoff, & Tucker, 2000; Fischler,1990; Kutas & Hillyard, 1980, 1983; Kutas, Lindamood, & Hillyard,1984; McCallum, Farmer, & Pocock, 1984).

Important for the interpretation of our results is the distinctionbetween N400 and P600 ERP components, which appear to markfunctionally inverse sentence processes. For example in Kolk, Chw-illa, Van Herten, and Oor (2003), participants read sentences con-taining in one set syntactic anomalies (sentences containingsubject–verb disagreement), and in another set semantic anoma-lies (sentences depicting semantically implausible events). Bothtypes of sentences elicited P600, suggesting that attempts at revi-sion are not domain-specific to syntax but can also be elicited bysemantically implausible stimuli. Noteworthy, too, the semanticanomalies failed to elicit N400. Kolk et al. (2003) interpreted this

result as follows: ‘‘. . .if a reader does not trust she has correctlyprocessed the sentence, why would she integrate what she has justread (p. 32)?” The implication is that if a listener (or her parser)‘‘trusts” the current interpretation of a sentence, she will attemptto integrate forthcoming words into that sentence, a processmarked by N400. If the listener does not ‘‘trust” the current inter-pretation of a sentence, she will attempt to revise it, a processmarked by P600. This latter effect was seen for our fluently-spokenGP items, while the former effect was seen for our GP + disfluencyitems. We tentatively interpret these results as indicating that theparser fails to revise GP sentences at the presentation of disambig-uating verbs following disfluencies because it accepts the originalparse as correct.

The same interpretation may be reached via the results of adifferent study regarding the functional significance of P600 ver-


sus N400. Osterhout (1997) reported that syntactically anomalousopen-class words presented during sentence processing eliciteddifferent ERP components from different participants; specifically,P600 from some participants but more often N400. While thisdoes not necessarily challenge the view that N400 is generatedas individuals attempt to integrate a word’s meaning with itssemantic context (see Fischler, 1990), it does reveal that strate-gies used to process sentences may be optional, driven to someextent by individual differences in how sentence anomalies areperceived. As Osterhout (1997) suggests, some participants maybe more sensitive to syntactic ramifications of syntacticallyanomalous open-class words, while most are sensitive to theirsemantic ramifications. Assuming individual differences had aplace in our results, it seems that most of our listeners inter-preted GP-disambiguating verbs following disfluencies as impact-ing their comprehension at a semantic level. As discussed above,this may have been because they were committed to an interpre-tation as a result of lingering on their initial parse before verbpresentation.

An alternative explanation for our N400 effects is possible. ERPevidence was recently reported that filled pauses have the effect oforienting listeners’ attention toward approaching linguistic stimuli(Collard, Corley, MacGregor, & Donaldson, 2008). It may be that thepresence of disfluency before GP-disambiguating verbs – ratherthan causing the parser to semantically integrate a verb into aparse on which it has lingered for too long – actually forces (redi-rects) listeners’ attention away from the syntactic analysis of sen-tences and more toward semantic analysis of the verb, elicitingN400.

Results from a different study suggest, however, that it is unli-kely disfluencies actually force attention specifically towardsemantic analysis of approaching stimuli. In that study (Corley,MacGregor, & Donaldson, 2007), participants listened to sentencescontaining a final word either predictable or unpredictable fromcontext. Half of the sentences contained a filled pause (‘‘er”) beforethe final word. For sentences not containing the filled pause, N400activation was larger for unpredictable than predictable words.This effect was attenuated when a filled pause preceded the sen-tence-final word (e.g., That drink’s too hot; I have just burn’t my ernails, where nails is unpredictable from the sentence and, in the ab-sence of the filled pause, would have elicited a particularly robustN400 activation). Corley et al. (2006) gave two accounts of what ef-fect the filled pause may have had on processing of the sentence-final words. One was that a filled pause can affect post-lexical pro-cessing, i.e., filled pauses often co-occur with and signal sentencerepairs, making it more difficult for the listener to continue inte-grating information and, hence, attenuating N400 activation uponthe presentation of a word following the filled pause. A secondexplanation was that a filled pause can affect pre-lexical process-ing, for example, by interfering with the listener’s ability to con-tinue making predictions about forthcoming information; so thatwhat might have been treated as an unpredictable word loses thisstatus, again attenuating N400 activation. Both accounts suggestthat disfluencies force attention away from, rather than toward,semantic analysis of sentences.

At the same time, other research has shown that P600 activa-tion is attenuated when attention is directed specifically towardsemantic analysis (Gunter et al., 2000; Hahne & Friederici, 2002;Osterhout, 1997). Attenuated P600 in conjunction with unattenu-ated N400 activation at GP-disambiguating verbs following disflu-encies, as seen in our study, suggests that semantic analysis was, infact, the active process for these items. More research is needed todetermine the extent to which time spent lingering on an incorrectparse due to disfluency versus attentional shift forced by disfluen-

cy contributes to an emphasis on semantic interpretations of GP-disambiguating verbs following disfluencies.

We emphasize that each of the different interpretations pre-sented in this section is tentative. Since our study was focusedat the outset on P600 evidence for the effects of disfluency onparse revision, we did not control factors other than semanticincongruity that are known to modulate the amplitude ofN400-like ERP components. For example, we did not explicitlycontrol the strength and direction of semantic associationbetween object NP and critical verb (see Franklin, Dien, Neely,Huber, & Waterson, 2007), or the frequency of our object NPsand critical verbs (see Frishkoff, Perfetti, & Westbury, 2009).Although we do not believe such factors varied dramatically be-tween conditions in our experiment, i.e., causing N400 effects toappear in our GP-disfluency conditions but not our other condi-tions, future extensions of this research would still benefit fromgreater control over these types of factors. For example, controlsof this type might shed light on whether certain semantic factorsstrongly bias listeners to continue integrating speech semanti-cally following unhelpful disfluencies, versus time-spent-linger-ing on a parse triggering this process in an all-or-nothingfashion regardless of semantic context, or whether these two fac-tors interact in some way.

4.5. Early left anterior positivity

Finally, GP + filled pause items elicited an early left anteriorpositivity peaking in amplitude at �220 ms after verb onset. Thiseffect resembles a brain activation reported by Posner and col-leagues (Abdullaev & Posner, 1997; Posner & Pavese, 1998; Sny-der, Abdullaev, Posner, & Raichle, 1995). Tasks requiredparticipants to process word meaning in isolation versus in rela-tion to a semantic context. Words processed in isolation wereshown to elicit a left anterior, positive-going ERP peaking inamplitude at �200 ms after word onset. This effect was not asrobust when the same words were processed in relation to asemantic context. Posner and Pavese (1998) interpret this patternagainst evidence suggesting that frontal brain areas have a rolein processing word meaning, while posterior brain areas have arole in processing combinations of words. As discussed above,N400 activation, with its later time-course and parietal scalptopography, is indicative of the type of ERP elicited when wordsare processed in relation to other words in a semantic context.Processing word meaning in isolation, on the other hand, seemsto elicit the earlier left anterior positivity.

We tentatively interpret the early left anterior positivity seenin our study to GP-disambiguating verbs following filled pausesas reflecting that those verbs were processed to some extent asisolated events. Filled pauses are more likely to precede open-class words than other word types (Maclay & Osgood, 1959)and, therefore, may give such words special status that affectshow they are processed, such as signaling listeners to pay partic-ularly close attention. As noted above, filled pauses have beenshown to orient attention to upcoming stimuli (Collard et al.,2008), although this was shown to result in an attenuation ofthe P300 at the word subsequent to the filled pause; an effectseemingly unrelated to the early positivity seen in our study. An-other possibility is that the relatively long durations of the filledpauses used here (in comparison to the silent pauses, see Section2) caused listeners to treat the disambiguating verbs to some ex-tent as isolated events. It is difficult to know to what extent thefilled (audible) quality of our filled pauses versus their durationcontributed to the effect they had on the processing of GP-disam-biguating verbs that followed them. Both warrant further study.


Whatever the precise functional interpretation, it appears thatthe underlying processing strategy marked by this ERP had a par-ticularly undesirable effect on comprehension. Listeners madethe greatest number of errors when answering subordinateclause questions for GP + filled pause sentences. Assuming finitecognitive resources (Just, Carpenter, & Miyake, 2003), a tendencyto process verbs following filled pauses as isolated events maydraw resources away from attempts at lexical-semantic integra-tion involving those same verbs. As noted above, integratingGP-disambiguating verbs into the preceding context followingdisfluency (marked by N400) benefited comprehension accuracyat least as well as attempts to revise fluently-spoken GPsentences following disambiguating verbs (marked by P600). Per-haps each processing strategy allows comprehenders to recoversome of the same information, albeit through different routes.When a filled pause is present, the additional process markedby the early positivity might affect one’s ability to recover thisinformation.

10 Although on paper, some of the Control sentences have the potential to induce agarden path effect, each was read aloud with a clear prosodic phrase break betweenthe first VP and second NP.

5. Summary and conclusions

ERPs seen in this study have revealed that at least three differ-ent routes may be used to process disambiguating verbs in GPsentences, depending on whether they are preceded by a silentpause, a filled pause, or no disfluency. One route, seen for flu-ently-spoken GP sentences, involves an attempt at sentence revi-sion at the disambiguating verb, marked by P600 activation. Asecond route, found for both GP + filled pause and GP + silentpause items, involves an initial parse of the GP sentence being ac-cepted as correct (even though it is really incorrect) and some at-tempt made at integrating the meaning of the disambiguatingverb into the incorrect parse, marked by N400 activation. A thirdroute, seen only for GP + filled pause items, seems to involve pro-cessing the disambiguating verb – to some extent – as an isolatedevent. Of these three processing routes, it seems that simulta-neous activation of both the second and third routes, seen forGP + filled pause items, negatively impacts comprehension accu-racy the most.

Our results are bound to some extent by the nature of theparticular types of sentences used in this study (Clark, 1973).For example, in a follow-up study currently underway, we areasking whether disambiguating verbs with a stronger transitivebias (reflexive absolute transitive verbs) might counteract someof the undesirable effects that disfluencies had on sentence pro-cessing in the current study. Since multiple sources of informa-tion can become available during sentence interpretation(Kuperberg, Kreher, Sitnikova, Caplan, & Holcomb, 2007; Lewis,1998), it is possible that disfluencies encountered in sentenceshave a greater negative impact in some contexts versus others,depending upon the type and richness of information available.Another interesting direction for future research involves varyingthe probability of disfluent sentences. In the present study, theprobability of hearing a fluent versus disfluent sentence wasmade equal in order to prevent P600 activations from commin-gling with late P300 effects that might have been elicited ifour disfluent GP sentences were presented as rare events (seeCoulson et al., 1998). At the same time, this may have limitedthe ecological validity of our findings, and it remains to be seenhow well our results generalize to contexts more indicative ofthe natural distribution of disfluencies. Disfluencies can have po-sitive effects, too, on sentence processing, e.g., when they appearat helpful locations (Bailey & Ferreira, 2003). The range of effectshas yet to be explored but, as we have seen here, may force usto update our current understanding of how sentence processing

unfolds in those situations where a disfluent signal connectsconversational partners.

Appendix A. Stimulus list

(underline denotes verb to which ERPs were time-locked)

Control items10:

1. As the man arrived the poodle barked loudly.2. As the student digressed the book became more difficult.3. As Tom meddled the hot dogs began to burn.4. As the man drilled the smoke flew up the chimney.5. As the waitress dawdled the customers complained about

the wait.6. As Jack languished the glasses broke with a crash.7. As the woman scampered the corner came into view.8. As Jack snored the fish cooked on the grill.9. As Susan slumbered the letter fell to the floor.

10. As the man napped the smoke filled up the chimney.11. As the lion snored the gazelle jumped over the bush.12. As the lawyer corresponded the contract lay on the desk.13. As the worker drilled the truck left the depot.14. As the dog dug the cat licked its paws.15. As the player fell the ball missed the net.16. As the puppy played the kitten napped on the sofa.17. As the man left a table opened by the window.18. As the orchestra tuned the symphony played on the radio.19. As Bill slept the turkey remained on the table.20. As the clown entertained the balls rolled on the ground.21. As the lion rested the baboon screamed in terror.22. As the woman looked on the award shone in the lights.23. As the secretary telephoned the paper slid from the pile.24. As the woman slipped the water spilled on the floor.25. As the caricaturist sang the child stood on the sidewalk.26. As the farmer rested the corn swayed in the breeze.27. As the cowboy snored the horse sweated profusely.28. As the man mowed the box tipped over.29. As the committee procrastinated the candidates waited.30. As the doctor sneezed the patient watched the t.v.

Summary of post-verb content: critical verb was followed by a

� Prepositional phrase (21 items).� Noun phrase (4 items).� Adverb (2 items).� Adjective (1 item).� Infinitive phrase (1 item).� Sentence ended with the critical verb (1 item).

Garden Path (no disfluency) items

1. As Angela cleaned the dog barked in the yard.2. As the student read the book became more difficult.3. As Tom grilled the hotdogs began to burn.4. As the woman turned the corner came into view.5. As the waitress served the customers complained about the

noise.6. As Jack ordered the fish cooked on the grill.7. As the maid dusted the vase broke in two.8. As Susan wrote the letter fell to the floor.


9. As the man blew the smoke flew up the chimney.10. As the woman washed the bath filled up with water.11. As the lion approached the gazelle jumped over the bush.12. As the lawyer studied the contract lay on the desk.13. As the worker loaded the truck left the depot.14. As the dog smelled the cat licked its paws.15. As the player dunked the ball missed the net.16. As the puppy sniffed the kitten napped on the sofa.17. As the man reserved a table opened by the window.18. As the orchestra performed the symphony played on the

radio.19. As Bill ate the turkey remained on the table.20. As the clown juggled the balls rolled on the floor.21. As the lion attacked the baboon screamed in terror.22. As the woman accepted the award shone in the lights.23. As the secretary stapled the papers slid from the pile.24. As the woman drank the water spilled on the floor.25. As the caricaturist drew the child stood on the sidewalk.26. As the farmer gathered the corn swayed in the breeze.27. As the cowboy rode the horse sweated profusely.28. As the man moved the box tipped over.29. As the committee interviewed the candidates waited.30. As the doctor cured the patient watched the t.v.


� Prepositional phrase (22 items).� Noun phrase (4 items).� Adverb (1 item).� Adjective (1 item).� Infinitive phrase (1 item).� Sentence ended with the critical verb (1 item).

Garden Path (+silent pause) items

1. As the audience watched the dogs [ ] barked at the judges.2. As the maid attended the mistress [ ] became angry.3. As the student typed the message [ ] began playing.4. As the chef stirred the pot [ ] broke into pieces.5. As the dog sniffed the owner [ ] came home.6. As the waitress served the customer [ ] complained about

the bill.7. As the chef selected the vegetables [ ] cooked on the stove.8. As the mom remembered the child [ ] fell onto the ground.9. As the lecturer read the Powerpoint[ ] filled the screen.

10. As the pilot raced the plane [ ] flew over head.11. As the receptionist paged the guest [ ] jumped up.12. As the manager counted the stock [ ] lay unorganized.13. As the sergeant ordered the soldier [ ] left the compound.14. As the vet nursed the dog [ ] licked its owner.15. As the cook measured the flour [ ] missed the bowl.16. While the therapist massaged the client [ ] napped on the

bed.17. While the driver loaded the trunk [ ] opened by itself.18. While the professor lectured the students [ ] played games.19. While the chef grilled the steak [ ] remained uncooked.20. While the carpenter whittled the stick [ ] rolled onto the

floor.21. While the man hunted the hawk [ ] screamed overhead.22. While the maid dusted the diamonds [ ] shone brilliantly.23. While the workman drilled the screw [ ] slid from the hole.24. While the diners drank the wine [ ] spilled onto the floor.25. While the teacher counted the children [ ] stood in line.26. While the farmer chewed the corn [ ] swayed in the wind.27. While the police charged the thief [ ] sweated profusely.28. While the wind blew the candles [ ] tipped over.

29. While the soldiers attacked the enemy [ ] waited in theshadows.

30. While the police arrested the criminals [ ] watched from thediner.


� Prepositional phrase (17 items).� Noun phrase (6 items).� Adverb (3 items).� Adjective (3 items).� Gerund phrase (1 item).

Garden Path (+filled pause) items

1. While the cat attacked the dog uh uh barked loudly.2. While the woman baked the cake uh uh became cool.3. While the preacher blessed the congregation uh uh began to

sing.4. While the bull charged the fence uh uh broke in half.5. While the accountant counted the money uh uh came in the

mail.6. While the chauffer drove the old lady uh uh complained

about the heat.7. While the mom iced the cake uh uh cooked.8. While the man gathered the leaves uh uh fell onto the grass.9. While the instructor graded the students uh uh filled the

seats.10. While the vet helped the bird uh uh flew out of the cage.11. While the man hunted the deer uh uh jumped over the

fence.12. While the woman knitted the socks uh uh lay on the sofa.13. While the scientist lectured the students uh uh left the

room.14. While the fireman rescued the cat uh uh licked its paws.15. While the stewards loaded the passengers uh uh missed the

plane.16. While the therapist massaged the man uh uh napped in the

chair.17. While the carpenter measured the door uh uh opened.18. While the customer ordered the CD uh uh played on the

stereo.19. While the officers investigated the crime uh uh remained

unsolved.20. While the diner ate the tomato uh uh rolled onto the floor.21. While the officer searched the woman uh uh screamed out

loud.22. While the couple selected the ring uh uh shone in the lights.23. While the waiter served the meal uh uh slid onto the floor.24. While the chef smelled the sauce uh uh spilled onto the

cooker.25. While the old man smoked the pipe uh uh stood on the shelf.26. While the child sniffed the flowers uh uh swayed in the

breeze.27. While the rider steered the ponies uh uh sweated profusely.28. While the baby swallowed the juice uh uh tipped over.29. While the spectators watched the players uh uh waited in

the tunnel.30. While the nurse woke the patient uh uh watched t.v.

Summary of post-verb content: Critical verb was followed by a

� Prepositional phrase (18 items).� Noun phrase (5 items).� Adverb (2 items).� Adjective (2 items).


� Infinitive phrase (1 item).� Sentence ended with the critical verb (2 items).

References

Abdullaev, Y. G., & Posner, M. I. (1997). Time course of activating brain areas ingenerating verbal associations. Psychological Science, 8, 56–59.

Altmann, G. T. M., & Steedman, M. (1988). Interaction with context during humansentence processing. Cognition, 30, 191–238.

Arnold, J. E., Hudson-Kam, C. L., & Tannenhaus, M. K. (2007). If you say thee uh youare describing something hard: The online attribution of disfluency duringreference comprehension. Journal of Experimental Psychology: Learning, Memoryand Cognition, 33(5), 914–930.

Bailey, K. G. B., & Ferreira, F. (2007). The processing of filled pause disfluencies in thevisual world. In R. P. G. Van Gompel, M. H. Fischer, W. S. Murray, & R. L. Hill(Eds.), Eye movements: A window on mind and brain (pp. 485–500). Oxford, UK:Elsevier Inc..

Bailey, K. G. D., & Ferreira, F. (2003). Disfluencies affect the parsing of garden-pathsentences. Journal of Memory and Language, 49, 183–200.

Bell, A., Jurafsky, D., Fossler-Lussier, E., Girand, C., Gregory, M., & Gildea, D. (2003).Effects of disfluencies, predictability, and utterance position on word formvariation in English conversation. Journal of the Acoustical Society of America,113, 1001–1024.

Bell, A. J., & Sejnowski, T. J. (1995). An information maximisation approach to blindseparation and blind deconvolution. Neural Computation, 7(6), 1129–1159.

Bortfeld, H., Leon, S., Bloom, J., Schober, M., & Brennan, S. (2001). Disfluency rates inconversation: Effects of age, relationship, topic, role, and gender. Language andSpeech, 44, 123–147.

Bos, J. (2001). DORIS 2001: Underspecification, resolution, and inference fordiscourse representation structures. In Blackburn & Kohlhase (Eds.), ICoS-3:Inference in computational semantics. Workshop Proceedings.

Brown, C., Hagoort, P., & Kutas, M. (2000). Postlexical integration processes inlanguage comprehension: Evidence from brain-imaging research. In M. S.Gazzaniga (Ed.), The new cognitive neurosciences (pp. 881–895). Cambridge, MA:MIT Press.

Christianson, K., Hollingworth, A., Halliwell, J., & Ferreira, F. (2001). Thematic rolesassigned along the garden path linger. Cognitive Psychology, 42, 368–407.

Clark, H. H. (1973). The language-as-fixed-effect fallacy: A critique of languagestatistics in psychological research. Journal of Verbal Learning and VerbalBehavior, 12, 335–359.

Collard, P., Corley, M., MacGregor, L. J., & Donaldson, D. I. (2008). Attention orientingeffects of hesitations in speech: Evidence from ERPs. Journal of ExperimentalPsychology: Learning, Memory, and Cognition, 34, 696–702.

Corley, M., MacGregor, L. J., & Donaldson, D. I. (2007). It’s the way that you, er, say it:Hesitations in speech affect language comprehension. Cognition, 105, 658–668.

Coulson, S., King, J. W., & Kutas, M. (1998). Expect the unexpected: Event-related brainresponse to morphosyntactic violations. Language and Cognitive Processes, 13,21–58.

Dien, J. (2005a). ICA blink toolbox [Computer software]. Lawrence, KS: University ofKansas.

Dien, J. (2005b). PCA toolbox [Computer software]. Lawrence, KS: University ofKansas.

Dien, J., & Frishkoff, G. A. (2005). Principal components analysis of event-relatedpotential datasets. In T. Handy (Ed.), Event-related potentials: A methodshandbook. Cambridge: MIT Press.

Dien, J., Frishkoff, G. A., & Tucker, D. M. (2000). Differentiating the N3 and N4:Electrophysiological semantic incongruity effects. Brain and Cognition, 43, 148–152.

Ferree, T. C. (2000). Spline interpolation of the scalp EEG. Eugene, OR: ElectricalGeodesics, Inc..

Ferree, T. C., Luu, P. L., Russell, J., & Tucker, D. M. (2001). Scalp-electrode impedance,infection risk, and EEG data quality. Clinical Neurophysiology, 112(3), 536–544.

Ferreira, F., & Bailey, K. G. D. (2004). Disfluencies and human languagecomprehension. Trends in Cognitive Science, 8, 231–237.

Ferreira, F., Ferraro, V., & Bailey, K. G. D. (2002). Good-enough representations inlanguage comprehension. Current Directions in Psychological Science, 11, 11–15.

Ferreira, F., Lau, E. F., & Bailey, K. G. D. (2004). Disfluencies, languagecomprehension, and tree adjoining grammars. Cognitive Science, 28, 721–749.

Fischler, I. S. (1990). Comprehending language with event-related potentials. In J.W. Rorbaugh, R. Parasuraman, & R. Johnson, Jr. (Eds.), Event-related brainpotentials: Basic issues and applications (pp. 165–177). New York: OxfordUniversity Press.

Fodor, J. D., & Ferreira, F. (1998). Reanalysis in sentence processing. Boston: Kluwer.Franklin, M., Dien, J., Neely, J., Huber, L., & Waterson, L. D. (2007). Semantic priming

modulates the N400, N300, and N400RP. Clinical Neurophysiology, 118(5),1053–1068.

Frazier, L., & Fodor, J. D. (1978). The sausage machine: A new two-stage parsingmodel. Cognition, 6, 1–34.

Friederici, A. D. (1998). Diagnosis and reanalysis: Two processing aspects the brainmay differentiate. In J. D. Fodor & F. Ferreira (Eds.), Reanalysis in sentenceprocessing (pp. 177–200). Boston: Kluwer.

Friederici, A. D., Hahne, A., & Mecklinger, A. (1996). Temporal structure of syntacticparsing: Early and late event-related brain potential effects elicited by syntactic

anomalies. Journal of Experimental Psychology: Learning, Memory, and Cognition,22, 1219–1248.

Friederici, A. D., Mecklinger, A., Spencer, K. M., Steinhauer, K., & Donchin, E. (2001).Syntactic parsing preferences and their on-line revisions: A spatio-temporalanalysis of event-related brain potentials. Cognitive Brain Research, 11, 305–323.

Frisch, S., Schlesewsky, M., Saddy, D., & Alpermann, A. (2002). The P600 as anindicator of syntactic ambiguity. Cognition, 85, B83–B92.

Frishkoff, G. A., Perfetti, C. A., & Westbury, C. (2009). ERP measures of partialsemantic knowledge: Left temporal indices of skill differences and lexicalquality. Biological Psychology, 80, 130–147.

Glass, K., Frishkoff, G. A., Frank, R. M., Davey, C., Dien, J., & Maloney, A. D. (2004). Aframework for evaluating ICA methods of artifact removal from multichannelEEG. In ICA 2004, LNCS 3195 (pp. 1033–1040). Berlin, Heidelberg: SpringerVerlag.

Gleitman, H., & Gleitman, L. R. (1979). Language use and language judgment. In C. J.Fillmore, W. Kempler, & W. S.-Y. Wang (Eds.), Individual differences in languageability and language behavior (pp. 103–126). New York: Academic.

Greenbaum, S. (Ed.). (1977). Acceptability in language. The Hague: Mouton.Greenbaum, S., & Quirk, R. (1970). Elicitation experiments in English: Linguistic studies

in use and attitude. Coral Gables, FL: University of Miami.Greenhouse, S., & Geisser, S. (1959). On methods in the analysis of profile data.

Psychometrika, 24, 95–112.Gunter, T. C., Friederici, A. D., & Schriefers, H. (2000). Syntactic gender and semantic

expectancy: ERPs reveal early autonomy and late interaction. Journal ofCognitive Neuroscience, 12, 556–568.

Hagoort, P., Brown, C. M., & Groothusen, J. (1993). The syntactic positive shift as anERP measure of syntactic processing. Language and Cognitive Processes, 8,439–483.

Hahne, A. (2001). What’s different in second-language processing? Evidence fromevent-related brain potentials. Journal of Psycholinguistic Research, 30(3),251–266.

Hahne, A., & Friederici, A. D. (1999). Electrophysiological evidence for two steps insyntactic analysis: Early automatic and late controlled processes. Journal ofCognitive Neuroscience, 11, 194–205.

Hahne, A., & Friederici, A. D. (2001). Processing a second language: Late learners’comprehension mechanisms as revealed by event-related brain potentials.Bilingualism: Language and Cognition, 4(2), 123–141.

Hahne, A., & Friederici, A. D. (2002). Differntial task effects on semantic andsyntactic processes as revealed by ERPs. Cognitive Brain Research, 13,339–356.

Hendrickson, A. E., & White, P. O. (1964). A quick method for rotation to obliquesimple structure. British Journal of Statistical Psychology, 17, 65–70.

Just, M. A., Carpenter, P. A., & Miyake, A. (2003). Neuroindices of cognitive workload:Neuroimaging, pupillometric, and event-related potential studies of brain work.Theoretical Issues in Ergonomic Science, 4(1–2), 56–88.

Kamide, Y., Altmann, G. T. M., & Haywood, S. L. (2003). Prediction and thematicinformation in incremental sentence processing: Evidence from anticipatoryeye movements. Journal of Memory and Language, 49, 133–156.

Kim, A., & Osterhout, L. (1995). The independence of combinatory semanticprocessing: Evidence from event-related potentials. Journal of Memory &Language, 52, 205–225.

Kolk, H. H. J., Chwilla, D. J., Van Herten, M., & Oor, P. J. W. (2003). Structure andlimited capacity in verbal working memory: A study with event-relatedpotentials. Brain & Language, 85(1), 1–36.

Kuperberg, G. R., Kreher, D. A., Sitnikova, T., Caplan, D. N., & Holcomb, P. J. (2007).The role of animacy and thematic relationships in processing active Englishsentences: Evidence from event-related potentials. Brain & Language, 100,223–237.

Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentialsreflect semantic incongruity. Science, 207, 203–205.

Kutas, M., & Hillyard, S. A. (1983). Event-related brain potentials to grammaticalerrors and semantic anomalies. Memory and Cognition, 11, 539–550.

Kutas, M., Lindamood, T., & Hillyard, S. A. (1984). Word expectancy and event-related brain potentials during sentence processing. In S. Kornblum & J. Requin(Eds.), Preparatory states and processes (pp. 217–238). Hillsdale, NJ: Erlbaum.

Levelt, W. J. M., & Cutler, A. (1983). Prosodic marking in speech repair. Journal ofSemantics, 2, 205–217.

Levelt, W. J. M., van Gent, J. A. W. M., Haans, A. F. J., & Meijers, A. J. A. (1977).Grammaticality, paraphrase, and imagery. In S. Greenbaum (Ed.), Acceptabilityin language (pp. 87–101). The Hague: Mouton.

Lewis, R. L. (1998). Reanalysis and limited repair parsing: Leaping off the gardenpath. In J. D. Fodor & F. Ferreira (Eds.), Reanalysis in sentence processing(pp. 247–286). Boston: Kluwer.

Luce, P. A. (1986). A computational analysis of uniqueness points in auditory wordrecognition. Perception and Psychophysics, 39, 155–158.

Maclay, H., & Osgood, C. E. (1959). Hesitation phenomena in spontaneous Englishspeech. Word, 15, 19–44.

McCallum, W. C., Farmer, S. F., & Pocock, P. K. (1984). The effects of physical andsemantic incongruities on auditory event-related potentials.Electroencephalography and Clinical Neurophysiology, 59, 477–488.

Munte, T., Heinze, H., Matzke, M., Wieringa, B., & Johannes, S. (1998). Brainpotentials and syntactic violations revisited: No evidence for specificity of thesyntactic positive shift. Neuropsychologia, 36, 217–226.

Neville, H. J., Nicol, J., Barss, A., Forster, K. I., & Garrett, M. F. (1991). Syntacticallybased sentence processing classes: Evidence from event-related brainpotentials. Journal of Cognitive Neuroscience, 3, 151–165.


Osterhout, L. (1997). On the brain response to syntactic anomalies: Manipulationsof word position and word class reveal individual differences. Brain & Language,59, 494–522.

Osterhout, L., & Holcomb, P. (1992). Event-related brain potentials elicited bysyntactic anomaly. Journal of Memory and Language, 31, 785–804.

Osterhout, L., Holcomb, P. J., & Swinney, D. A. (1994). Brain potentials elicited bygarden-path sentences: Evidence of the application of verb information duringparsing. Journal of Experimental Psychology: Learning, Memory and Cognition, 20,786–803.

Osterhout, L., McLaughlin, J., Kim, A., Greenwald, R., & Inoue, K. (2004). Sentences inthe brain: Event-related potentials as real-time reflects of sentencecomprehension and language learning. In M. Carreiras & C. Clifton, Jr. (Eds.),The on-line study of sentence comprehension: Eyetracking ERP and beyond.Psychology Press.

Picton, T. W., Bentin, S., Berg, P., Donchin, E., Hillyard, S. A., Johnson, R. Jr., et al.(2000). Guidelines for using human event-related potentials: Recordingstandards and publication criteria. Psychophysiology, 37, 127–152.

Posner, M. I., & Pavese, A. (1998). Anatomy of word and sentence meaning.Proceedings of the National Academy of Sciences, USA, 95, 899–905.

Preisendorder, R. W., & Mobley, C. D. (1988). Principal component analysis inmeteorology and oceanography. New York: Elsevier.

Richman, M. (1986). Rotation of principal components. Journal of Climatology, 6,293–335.

Schutze, C. T. (1996). The empirical base of linguistics: Grammaticality judgments andlinguistic methodology. University of Chicago Press.

Snow, C. E., & Meijer, G. (1977). On the secondary nature of syntactic intuitions. In S.Greenbaum (Ed.), Acceptability in language (pp. 163–177). The Hague: Mouton.

Snyder, A. Z., Abdullaev, Y., Posner, M. I., & Raichle, M. E. (1995). Scalp electricalpotentials reflect regional cerebral blood flow responses during processing ofwritten words. Proceedings of the National Academy of Science, USA, 92,1689–1693.

Sorace, A. (1996). The use of acceptability judgments in second language acquisitionresearch. In W. C. Ritchie & T. K. Bhatia (Eds.), Handbook of second languageacquisition (pp. 375–409). San Diego, CA: Academic.

Stankov, L., & Crawford, J. D. (1996). Confidence judgments in studies of individualdifferences. Personality & Individual Differences, 21(6), 971–986.

Stevens, J. P. (1999). Intermediate statistics. Mahwah, NJ: Lawrence Erlbaum.Tataryn, D. J., Wood, J. M., & Gorsuch, R. L. (1999). Setting the value of k in

Promax: A Monte-Carlo study. Educational and Psychological Measurement, 59,384–391.

Tremblay, A. (2005). Theoretical and methodological perspectives on the use ofgrammaticality judgments in linguistic theory. Second Language Studies, 24,29–167.

Tyler, L. K., & Marslen-Wilson, W. D. (1986). The effects of context on therecognition of polymorphemic words. Journal of Memory and Language, 25,741–752.

Documents

Disfluencies along the garden path: Brain electrophysiological evidence of disrupted sentence processing