J Psycholinguist Res (2014) 43:167–185
DOI 10.1007/s10936-013-9244-8

Pre- and Post-head Processing for Single- andDouble-Scrambled Sentences of a Head-Final Language
as Measured by the Eye Tracking Method
Katsuo Tamaoka · Michiko Asano · Yayoi Miyaoka ·Kazuhiko Yokosawa

Published online: 21 March 2013
© Springer Science+Business Media New York 2013

Abstract Using the eye-tracking method, the present study depicted pre- and post-headprocessing for simple scrambled sentences of head-final languages. Three versions of simple
Japanese active sentences with ditransitive verbs were used: namely, (1) SO1 O2 V canonical, (2) SO2 O1 V single-scrambled, and (3) O1 O2 SV double-scrambled order. First passreading times indicated that the third noun phrase just before the verb in both single- anddouble-scrambled sentences required longer reading times compared to canonical sentences.
Re-reading times (the sum of all fixations minus the first pass reading) showed that all nounphrases including the crucial phrase before the verb in double-scrambled sentences required
longer re-reading times than those required for single-scrambled sentences; single-scrambled
sentences had no difference from canonical ones. Therefore, a single filler-gap dependency
can be resolved in pre-head anticipatory processing whereas two filler-gap dependencies
require much greater cognitive loading than a single case. These two dependencies can be
resolved in post-head processing using verb agreement information.
Keywords Head-final language · Gap-filling parsing · Scrambling ·Pre-head and post-head processing · Eye-tracking

K. Tamaoka (B)Nagoya University, Nagoya, Japane-mail: ktamaoka@lang.nagoya-u.ac.jp
M. Asano
Keio University, Fujisawa, Japane-mail: asano@sfc.keio.ac.jp
Y. Miyaoka
Hiroshima University of Economics, Hiroshima, Japane-mail: yy-miya@hue.ac.jp
K. Yokosawa
The University of Tokyo, Tokyo, Japane-mail: yokosawa@l.u-tokyo.ac.jp

123

168

J Psycholinguist Res (2014) 43:167–185

Introduction
A head-final language (head refers to a verb) is a language in which a verb is positioned at the end of the sentence as in Japanese. Pre-head anticipation processing has been
proposed by various studies (e.g., Kamide et al. 2003; Kamide and Mitchell 1999; Miyamoto
and Takahashi 2002, 2004), for processing sentences of such languages by enabling language users to incrementally construct syntactic structure without seeing the head verb.
However, these studies used either self-paced reading (e.g., Miyamoto and Takahashi 2002,
2004; Kamide and Mitchell 1999) or eye-tracking on multiple pictures with an auditorilypresented sentence (e.g., Kamide et al. 2003). The former, self-paced reading method locks aparticipant’s reading into a specific region and cannot measure backward reading times. The
latter, eye-tracking method also does not allow participants to listen to an auditorily-presented
sentence again. Consequently, neither method is able to measure post-head processing. It israther problematic that pre-head anticipation processing is strongly bound to sequential stimulus presentation, which does not allow participants to re-read or re-think once the head verb
has become known. It is expected that the head verb provides syntactically-required elementsof argument information, which permit native Japanese speakers to confirm whether or not
the verb syntactically and semantically matches previously-seen noun phrases. Therefore, by
utilizing the eye-tracking method with visually-presented sentences to measure eye fixations
and gazing times of each phrase both forward and backward (e.g., Findlay and Gilchrist
2003; McConkie and Rayner 1975; Rayner 1998; Staub and Rayner 2007), the present study
investigated both pre-head anticipation processing and post-head syntactic and semantic
matching.

Nonconfigurational and Configurational Syntactic Structure
Unlike the strict SVO (subject, verb and object) word order of English, sentences in somelanguages can be presented in multiple orders. For instance, the head-final languages ofJapanese, Korean, Mongolian and Turkish can feature OSV order as well as the canonicalorder of SOV. In an extreme case, the Sinhalese language spoken in Sri Lanka can exhibit
up to six different orders with no specific requirements; SOV is considered as the canonicalorder, while OSV, SVO, OVS, VSO and VOS are possible scrambled orders (e.g., Gair 1998;
Miyagishi 2003). Since there is no substantial difference among the syntactic positions ofphrases of scrambled sentences, Farmer (1984) and Hale (1980, 1982, 1983) claimed that
the Japanese language has what they referred to as a “flat” nonconfigurational structure. In
this structure, noun phrases can be generated freely in any position within a sentence. For
example, an SOV-ordered simple sentence, Mary-ga ringo-o tabe-ta meaning ‘Mary ate anapple’ [S NP-ga [VP NP-o V]] can be correctly expressed by re-ordering the nominal nounphrase Mary-ga and the accusative noun phrase ringo-o in OSV order as Ringo-o Mary-ga
tabe-ta, without varying the essential meaning of the SOV canonical order. Therefore, given
the nonconfigurational structure, we expected no difference in reading times for sentenceswith the different SOV and OSV word orders. In fact, a nonconfigurational structure was
supported by some psycholinguistic studies (e.g., Nakayama 1995; Yamashita 1997) thatfound no difference in processing speed between canonical and scrambled orders as measured
by the self-paced reading method.
A configurational, as opposed to a noncofigurational structure, was proposed by several
linguists (e.g., Hoji 1985, 1987; Miyagawa 1989, 2010; Saito 1985; Saito and Hoji 1983),
to support their claim that an instance of phrasal movement results in a free word order123

J Psycholinguist Res (2014) 43:167–185

169

phenomenon. Ross (1967) originally referred to this as “scrambling”. The movement ofnoun phrases from their original position in a canonically-ordered sentence produces theirderived positions. In this structure, Mary-ga ringo-o tabe-ta reflects the canonical SOV
order of an active sentence with a transitive verb. The scrambled OSV order is createdby moving the accusative noun phrase ringo-o to the initial position of the sentence. The
scrambled order requires a syntactic operation of phrasal movement from a trace (t1 ) in the
canonical position to the sentence initial position (NP-o1 ) as in [S NP-o1 [S NP-ga [VP t1 V]]].
In the configurational structure, SOV was expected to be more quickly processed than thescrambled order of OSV. Support for the configurational structure has also been substantiatedby other recent psycholinguistic studies (e.g., Koizumi and Tamaoka 2004, 2010; Mazuka et
al. 2002; Miyamoto and Takahashi 2002, 2004; Tamaoka et al. 2005), which found a delay
in reading scrambled sentences in comparison to their minimally-paired canonically-orderedsentences.
Among studies that found scrambling effects, Tamaoka et al. (2005) observed consistent inhibitory effects of scrambled order in four different types of active, passive, potential and causative sentences, strongly suggesting that native Japanese speakers use thecanonical order of sentences as the base structure in sentence processing. In this sense,
the findings of scrambling effects fit nicely into the canonical order strategy model proposed by Fodor et al. (1974), which treats the first noun phrase of a sentence as a subject.
As described in the experiments of Tamaoka et al. (2005), a delay in sentence processing (i.e., scrambling effects) is observed when the subject is not initial information. The
present study also adheres to the model of canonical order strategy, assuming that native
Japanese speakers would be able to process sentences using a base structure of SOV canonical order. Nevertheless, the base structure of canonical order per se does not sufficiently
depict the processing of scrambled sentences. In addition to the canonical order strategy, themechanism of gap-filling parsing will be necessary to explain the processing of scrambled
sentences.

Gap-Filling Parsing and Anticipatory Processing
Since native Japanese speakers read a sentence from the initial noun phrase, it is difficult
to construct a syntactic structure with trace moved to the frontal position without seeing
an entire sentence. In psycholinguistic studies, gap-filling parsing has been used to explain
the delay in processing scrambled sentences. Gap-filling parsing was utilized by Frazier andothers (Crain and Forder 1985; Frazier 1987; Frazier and Clifton 1989; Frazier and Flores
D’Arcais 1989; Stowe 1986), as being especially useful in identifying a wh- filler in English.
A sentence-initial wh- phrase triggers a search for its gap to establish filler-gap dependency.
This parsing strategy has been applied to explain the processing of scrambled sentences inJapanese (e.g., Koizumi and Tamaoka 2004, 2010; Miyamoto and Takahashi 2002, 2004;
Tamaoka et al. 2005). However, it should be noted that because the studies by Tamaoka andhis colleagues (e.g., Koizumi and Tamaoka 2004, 2010; Tamaoka et al. 2005) used sentence
correctness decision tasks by presenting minimally-paired whole sentences with canonicaland scrambled orders, they cannot provide evidence of the crucial phrase where gap-fillingparsing occurs.
A phrase-by-phrase study of the processing of Japanese canonical and scrambled sentences using eye-tracking was conducted by Mazuka et al. (2002). They reported an extra
cognitive loading required for SOV-structured sentences with scrambled word order in boththe first pass and regression times at the crucial phrase of the second agreement position.

123

170

J Psycholinguist Res (2014) 43:167–185

They created paired directly-comparable sentences as in Mariko-ga otooto-o yon-da [MarikoNOM brother-ACC Verb] meaning ‘Marito called [her] younger brother’ and its scrambled
condition Otooto-o Mariko-ga yon-da [brother-ACC Mariko-NOM Verb]. In this pair, thesecond phrase of the scrambled sentence (i.e., Mariko-ga) is crucial to establish a single
filler-gap dependency. However, the same-positioned phrase of the baseline canonical sentence is otooto-o ‘brother’. Mariko is a proper noun while otooto is a general noun. As one
can easily guess from daily life, the general noun ‘brother’ is more frequently used thanthe proper noun ‘Mariko’. Thus, a difference in speed for the lexical processing of paired
nouns per se (e.g., ‘brother’ versus ‘Mariko’) can create a significant delay at the crucial
phrase.
Stimulus sentences in Mazuka et al. (2002) contain the scrambled sentence Mariko-o
Otooto-ga yonda [Mariko-ACC brother-NOM Verb], which can be compared with the canonical order of Mariko-ga otooto-o yonda [Mariko-NOM brother-ACC Verb]. However, thissentence includes a center-embedded sentence as in Mariko-o [soto-de buranko-ni notteita] otooto-ga yonda [Mariko-ACC (outside swinging on a swing) brother-NOM called],
so that this possible candidate is not appropriate for comparing scrambled sentences to thecanonical baseline. Therefore, to date, no eye-tracking study has reported either a processing delay or extra cognitive loading by first pass reading in Japanese, nor have they determined regression/re-reading times at the crucial phrase where a filler-gap dependency is
resolved.
According to ‘head-driven’ parsing (Pritchett 1991, 1992), the parser makes noun phrase
attachments based on a head verb. If this is so, strictly speaking, the parser for the Japanese
language is unable to make any attachment until seeing the head verb. In this parsing model,
native Japanese speakers, therefore, cannot process a noun phrase until seeing the head at theend of sentence. Considering an example sentence such as Utukusii nagai kami-no syoozyo-ga
50-meetoru no puuru-de oyoi-da ‘A beautiful long-haired girl swam in a 50-m pool’, native
Japanese speakers have to wait until seeing the past-tense verb ‘swam’ (oyoi-da) at the endof the sentence before the initiation of sentence parsing. This seems far too long to wait ininitiating sentence processing.
Instead of head-driven parsing, some studies (e.g., Aoshima et al. 2004; Inoue and Den
1999; Inoue and Fodor 1995; Kamide et al. 2003; Kamide and Mitchell 1999; Miyamoto
and Takahashi 2002, 2004; Ueno and Kluender 2003) suggest that native Japanese speakers
can anticipate ensuing phrases from previously-given syntactic and semantic information
before seeing the final verb. In the case of OSV-ordered Japanese active sentences [S NP-o1[S NP-ga [V P gap1 V]]], when an accusative case-marked NP-o (or O) comes first, native
Japanese speakers may assume an empty subject, constructing [S ecsub [NP-o . . .]] with theanticipation of a following verb. Using the aforementioned sentence, native Japanese speakers
will assume ‘I’ (or watashi-ga) after reading the first noun phrase ringo-o, expecting to havea verb such as tabe-ta ‘ate’ to complete the sentence ‘I ate an apple’. However, when thenominative NP-ga (Mary-ga) comes after NP-o (ringo-o), native Japanese speakers will treat
the displaced NP-o as a filler, and create its gap, resulting in a syntactic structure which
includes a filler-gap dependency [S NP-o1 [S NP-ga [VP gap1 . . .]]]. Then, they anticipate
a transitive verb to complete an active sentence. As such, in the strict version of pre-headanticipatory processing, filler-gap dependencies can be resolved in sequential order without
reference to the ending verb. This anticipatory processing seems to fit nicely into the modelof minimal attachment proposed by Frazier and Rayner (1982), who investigated parsing instructurally ambiguous sentences (i.e., garden path sentences) using eye movements.
Pre-head anticipation processing (e.g., Aoshima et al. 2004; Inoue and Den 1999;
Kamide et al. 2003; Kamide and Mitchell 1999; Miyamoto and Takahashi 2002, 2004;

123

J Psycholinguist Res (2014) 43:167–185

171

Ueno and Kluender 2003) assumes processing to be sequential with no extra cognitive
load for canonical sentences of head-final languages. However, although phrasal structure is constructed incrementally according to the sequence of given information before
seeing the head verb, it may still play an important function in finding noun phrase
agreement or in establishing filler-gap dependency when confronting a non-canonicalsentence such as one with single-/double-scrambled order or long-distance scrambling.
Native Japanese speakers may need the head verb information to resolve filler-gap dependency. Since Vitu et al. (1998) suggested refixations and regressions of eye movement
reflect difficulties of text reading, regressions in eye movements will be able to capture
the function of the head verb in relation to a filler-gap dependency. Thus, utilizing an
eye-tracking method, the present study investigated the phrase-by-phrase on-line processing of simple Japanese sentences with canonical and scrambled orders. Although thepresent study uses the case of the Japanese language, the investigation may bear application to other languages that allow scrambling such as Korean, Mongolian, Sinhalese, andTurkish.

Assumptions of Eye Movements in the Present StudyA ‘simple’ sentence in the present study is defined as one constructed of noun phrases
with no adjectives and adverbs. For instance, a Japanese sentence with a ditransitive verb isconstructed of three noun phrases (hereafter, NP), nominative (NP-NOM), dative (NP-DAT)and accusative (NP-ACC), plus a verb. Take an example of a sentence like Tom-ga Mary-ni
hon-o kaeshi-ta meaning ‘Tom returned a book to Mary’ (Tom-NOM Mary-DAT bookACC return-PAST). The final verb ‘returned’ functions to make relations among the three
nouns, ‘Tom’, ‘Mary’ and ‘book’. It is noted that -ga is the nominative case-marker, -o theaccusative case-marker and -ni the dative case-marker. These three noun phrases without an
ending head verb can have multiple candidate verbs such as age-ta ‘gave’, kashi-ta ‘rented’,nage-ta ‘threw’, or even yomase-ta ‘caused to read’. Although all information provided byprevious noun phrases allows native Japanese speakers to predict some information including
an upcoming verb, the potential of multiple verb choices may require native Japanese speakers
to check for syntactic and semantic relations of already-seen noun phrases after seeing thehead verb. If the head verb is merely used for checking whether or not the final syntactic
and semantic structure matches with previously-seen noun phrases, the processing can beaccomplished without reading backward.
To speculatively demonstrate the on-line performance of filler-gap dependencies with simple sentences, the present study compared scrambling effects employing minimally different
syntactic structures with a baseline of processing times for canonical sentences. The following structures, comprised of three noun phrases and a single verb, will provide a foundation
for clarifying the pre- and post-head verb processing mechanism for establishing filler-gap
dependencies in an eye-tracking experiment.
E.g., Tom returned a book to Mary.
(1) Canonical order (SO1 O2 V; O1 = an indirect object and O2 = a direct object):[S NP-ga [VP NP-ni [V NP-o V]]]
Tom-ga Mary-ni Hon-o kaeshi-ta.
(2) Single-scrambled order (SO2 O1 V, a single gap within the verb phrase):[S NP-ga [VP NP-o1 [VP NP-ni [V gap1 V]]]]
Tom-ga Hon-o Mary-ni kaeshi-ta.

123

172

J Psycholinguist Res (2014) 43:167–185(3) Double-scrambled order (O1 O2 SV, two gaps outside of the verb phrase):[S NP-ni1 [S NP-o2 [ S NP-ga [VP gap1 [V gap2 V]]]]]
Tom-ni Hon-o Mary-ga kaeshi-ta
Sentence (1) is the base line canonical order. Assuming pre-head anticipation processing
based on previous studies (e.g., Aoshima et al. 2004; Inoue and Den 1999; Kamide et al.
2003; Kamide and Mitchell 1999; Miyamoto and Takahashi 2002, 2004; Ueno and Kluender2003), sentence (2) may require extra processing time at the stage of the third noun phrase(NP-ni) to resolve the single filler-gap dependency between NP-o1 and gap1 before seeing theending verb. Relatively longer eye fixations or duration will be expected in the third phrase
for sentence (2) than for sentence (1). Nevertheless, since sentence (2) has only a single
filler-gap dependency within the verb phrase, native Japanese speakers may not require extra
cognitive loading at the third noun phrase to solve this dependency, and consequently, they
may not read backward after seeing the head verb. If so, regressions in eye movements would
not be observed in sentences (1) and (2).
Sentence (3), however, is a more complex case than sentence (2), being a double scrambling condition. When a dative-marked NP of Tom-ni is read, native Japanese speakers will
construct [S ecsub [VP NP-ni. . .]] in anticipation of an accusative-marked NP-o to follow.
Then, native Japanese speakers will keep an empty category (or empty subject) and create
the phrasal structure [S ecsub [VP NP-ni1 [VP NP-o …]]], expecting a verb to complete thesentence. After these two noun phrases, they unexpectedly encounter a nominative-marked
noun phrase, Tom-ga. At this stage, they have to delete an empty category and create twofiller-gap dependencies as [S NP-ni1 [S NP-o2 [S NP-ga [VP gap1 [V gap2 . . .]]]]]. Extra
reading time, which will be observed by fixations and durations of eye movements longer
than sentence (1), and possibly (2), may be needed at the third phrase, NP-ga, which initiates the gap-filling parsing for two gaps. There are still multiple candidate verbs that may
follow these noun phrases; only the ending verb can provide information regarding semantic
relations for these noun phrases.
The strict version of pre-head anticipation processing predicts no backward reading forscrambled sentences (2) and (3). In other words, the information gathered in pre-head processing can resolve even two filler-gap dependencies, while the head verb at the end of sentencesimply fills the position of the verb phrase. However, double-scrambled sentences may exhibit
a more complex process of resolving filler-gap dependencies. Lewis (1996) proposed two(or three) as the magical number in sentence processing. She explained that two (or three)anomalies in a single sentence are far more difficult to process than a single anomaly. Quantitative change from a single gap to double may display a similar tendency. In other words,
two gaps may require extra loading of short-term memory far heavier than a single gap. Then,the information of the head verb will be used for resolving two dependencies in sentence
processing by native Japanese speakers. The eye-tracking method of the present study may
show the post-head reading observed as regressions.
It should be noted that eye-tracking data need to be carefully treated because readers
can read a wider visual span beyond the specific phrase where their eyes are fixated (e.g.,
Henderson and Ferreira 1990; Morrison 1984; Rayner and Fischer 1996). When eyes are fixated on the third-positioned noun phrase before the ending verb, the verb can be seen together
with the previous noun phrase. Thus, eye-tracking data should be cautiously interpretedusing all results of the first fixation times, the first pass reading times, re-reading times andregression-in/regression-out frequencies together. The present study aims to depict phrase-byphrase processing of simple sentences with canonical and single-/double-scrambled orders
through the careful handling of eye-tracking data.

123

J Psycholinguist Res (2014) 43:167–185

173

MethodParticipants
Eighteen native Japanese speakers (7 females and 11 males) who were either undergraduate or
graduate students at the University of Tokyo in Japan participated in the present experiment.
Ages ranged from 21 to 27 years, with the average age being 23 years and 1 month with astandard deviation of 2 years and 0 months on the day of testing.
Materials
Three versions of correct active sentences with ditransitive verbs were used for the present
experiment: namely, (1) SO1 O2 V canonical [S NP-ga [VP NP-ni [V NP-o V]]], (2) SO2 O1 V
single-scrambled [ S NP-ga [VP NP-o1 [VP NP-ni [V gap1 V]]]], and (3) O1 O2 SV doublescrambled order [S NP-ni1 [S NP-o2 [ S NP-ga [VP gap1 [V gap2 V]]]]]. Noun phrases of thebase sentences were altered to use minimum-paired single- and double-scrambled orders. For
example, the canonical-ordered sentence of Takahashi-san-ga Tanaka-san-ni hana-o okut-ta‘Takahashi presented flowers to Tanaka’, was changed to create a single-scrambled order byaltering the accusative case-marked noun phrase and the dative case-marked noun phrase
to become Takahashi-san-ga hana-o Tanaka-san-ni okut-ta. Likewise, a double-scrambled
version was created by putting both the accusative and the nominative case-marked nounphrases before the nominative case-marked noun phrase resulting in Tanaka-san-ni hana-oTakahashi-san-ga okut-ta. Family names used for sentences were taken from the 100 mostpopular names in Japan, so processing these proper names would not affect the processing
times when comparing the three sentence conditions. There were 90 target sentences created by making alterations to 30 base sentences. Based on this operation, 30 canonical, 30
single-scrambled, and 30 double-scrambled sentences (a total of 90 ‘YES’ response items,
hereafter, ‘correct sentences’) were produced for the experiment. All the correct sentenceswere in the range of 16–20 characters (M = 17.63 characters) in length including a fullstop. Noun phrases and verbs were in the range of 2–6 characters in length (M = 4.16
characters).
Thirty incorrect sentences with canonical noun phrase order were created as a base forcorrect ‘No’ response items (hereafter, ‘incorrect sentences’). These sentences were alteredin the same fashion as correct sentences. As a result, 30 canonical, 30 single-scrambled and
30 double-scrambled sentences in each type (90 in total) were prepared: Inoue-san-ga Saitosan-ni yotei-o hun-da ‘Inoue stepped schedule to Saito’ for canonical order, Inoue-san-ga
yotei-o Saito-san-ni hun-da for single-scrambled, and Saito-san-ni Yotei-o Inoue-san-ga hunda for double-scrambled. All the incorrect sentences were in the range of 16–20 characters(M = 17.52 characters) in length including a full stop. Phrases and verbs were in the range
of 2–6 characters in length (M = 4.13 characters). Family names used for these incorrectsentences were also taken from the 100 most popular names in Japan. According to theLatin-square design, these 90 correct and 90 incorrect sentences were divided into three listsof 30 correct and 30 incorrect sentences (10 each of canonical, single-scrambled and doublescrambled for both correct sentences and incorrect sentences). Therefore, each participant
saw only one version consisting of 30 correct sentences containing 10 canonical, 10 singlescrambled and 10 double-scrambled, and 30 incorrect sentences containing the same types
and numbers.
The experiment also included 15 correct and 15 incorrect filler sentences. With thesefillers, the experiment used an equal number of correct and incorrect sentences. In total, each

123

174

J Psycholinguist Res (2014) 43:167–185

Fixation is displayedfor 1,000ms.
A stimulus sentence ispresented until a participant
presses ‘Yes’ or ‘No’ key.

Behavioral and eye-movement data are recorded.

Feedback is given by a beep
only for an incorrect response.

The next stimuli is presented after 3,000 ms.

Fig. 1 Procedure of a single trailof the three sets of stimuli consisted of 90 sentences, 45 correct sentences and 45 incorrectsentences.
Apparatus
An eye-tracking method was used with native Japanese speaking participants. Stimuli weredisplayed at the center of a monitor (Sony Trinitron MultiScan G520) controlled by acomputer with a visual stimulus generator graphics card (Cambridge Research Systems VSG
2/5). All characters were displayed in MS Gothic (Japanese fixed-width font). Each character
subtended a visual angle of 0.96◦ horizontally and vertically. The stimulus sentences were
written horizontally in black on a white display. Reading times were measured from the onsetof the target stimuli by means of a digital millisecond timer. Although participants viewed thescreen with both eyes (binocular), left eye movements were monitored using a dual Purkinje
eye tracker (Cambridge Research Systems Video Eyetracker Toolbox 2.10). The resolutionof the eye tracker was 0.1◦ and the sampling rate was 50 Hz (measured every 20 ms).
Procedure
Each participant was seated in front of the monitor in a quiet room. A head and chin rest
was used to maintain a viewing distance of 57 cm. Participants were asked to read sentences and perform correctness decisions using response keys connected to a computer.
Prior to beginning the experimental session, participants engaged in a 20-point calibration
sequence for the eye tracker. Ten practice trials were given. As shown in Fig. 1, in the
beginning of each experimental trial, an asterisk ‘*’ appeared for 1,000 ms as a fixation
point at the position of the first character of the following stimulus sentence. Immediately
after the offset of the fixation point, a stimulus sentence was presented. Participants wererequired to read each sentence silently and to press a key as soon as they finished reading.
Reading times and eye movements were measured from the onset of the sentence to thekey press response. Reading times were measured for each phrasal region of eye fixation
times.
When a response was registered, the stimulus sentence disappeared and was replaced by aquestion mark ‘?’. Participants were required to answer whether or not the stimulus sentence
was acceptable, by pressing the ‘Yes’ or ‘No’ key. If the correctness decision was incorrect,
an auditory beep error message presented feedback to keep the participant’s motivation high.
The question mark ‘?’ disappeared after this response was made. The next trial began 3,000 ms

123

J Psycholinguist Res (2014) 43:167–185

175

later. The eye tracker was recalibrated when participants returned for the experiment after
an intermission. The entire process took under 30 min for each participant to complete, withthe actual experiment requiring about 15 min. Eye fixation durations under 80 ms were notincluded in the calculation of reading times. Only the data from trials with less than 10 %missing data points (89.4 % of all trials) and in which sentence plausibility decisions werecorrect were used for data analysis.

Results
Behavioral Data of Reaction Times and Error Rates
Only correctly identified sentences for the sentence correctness decision were used for reaction time analysis. The statistical tests which follow analyze both participant (F1 ) and item
(F2 ) variability. The means of reaction times and error rates for correct sentences are presented in Table 1.
A one-way analysis of variance (ANOVA) with repeated measures was conducted forreaction time data of canonical, single-scrambled and double-scrambled word orders. Means
and standard errors of reaction times for these three sentence types of correct sentences
are shown in Table 1. There was a main effect on reaction times for correct sentences[F1 (2, 34) = 21.03, p < .001, F2 (2, 58) = 17.07, p < .001]. Multiple comparisonsusing Tukey’s HSD showed that canonical order (M = 1, 490) had the same processing
speed for sentence correctness decision as single-scrambled (M = 1, 544). However, bothof them were significantly faster than double-scrambled (M = 1, 889). Reaction time datafor incorrect sentences did not show a significant main effect [F1 (2, 34) = 2.14, p = .134,
F2 (2, 58) = 0.97, p = .384].
As for error rates, a one-way ANOVA was conducted for canonical, single-scrambled
and double-scrambled word orders. There was a main effect on error rates for correct sentences [F1 (2, 34) = 10.30, p < .001, F2 (2, 58) = 11.20, p < .001]. Multiple comparisonsusing Tukey’s HSD showed that canonical order (M = 1.67 %) had the same error rates forsentence correctness decision as single-scrambled (M = 2.22 %), but both of them showedsignificantly lower error rates than double-scrambled (M = 12.92 %). Error rate data for

Table 1 Behavioral data for correct and incorrect sentences
Sentence type

Correct sentences

Incorrect sentences

Reading times (ms)Error rate

Reading times (ms)Error rate

M

SE

M

SE

M

SE

M

SE

1 Canonical

1,490

121

2 Single-scrambled

1,544

118

1.67 %

0.88 %

1,510

97

2.22 %

0.98 %

2.22 %

0.98 %

1,546

109

2.78 %

3 Double-scrambled

1,889

150

1.53 %

12.92 %

3.02 %

1,583

104

2.22 %

0.98 %

Main effects

***

***

Multiple comparison

123

123

ns

ns

M refers to means while SE refers to standard errors
Underlined numerals indicate sentence types differed significantly in multiple comparison
ns refers to ‘not significant’ * p < .05; ** p < .01; *** p < .001

123

176

J Psycholinguist Res (2014) 43:167–185

Table 2 First fixation times in regions of noun phrases and verb for correct sentences
Sentence type

Fixation times (ms) of correct sentences in each region
NP1

NP2

NP3

Verb

M

SE

M

SE

M

SE

M

SE

1. Canonical

219

11

186

10

214

14

172

18

2. Single-scrambled

223

11

209

16

223

9

139

14

3. Double-scrambled

208

11

206

15

215

11

157

18

Main effectsnsns* (only F2 )* (only F1 )Multiple comparison
M refers to means while SE refers to standard errors
ns refers to ‘not significant’ * p < .05; ** p < .01; *** p < .001

correct ‘No’ responses did not show a significant main effect [F1 (2, 34) = 0.10, p = .910,
F2 (2, 58) = 0.10, p = .908].
Behavioral data revealed significant main effects on both reaction times and error rates
among canonical, single-scrambled and double-scrambled sentences only for correct sentences, but not for incorrect sentences. Therefore, further analysis was carried out only fordata of correct sentences obtained by eye tracking.
First Fixation Times for Each Phrase
The first fixation times for each phrase were calculated by the initial fixation duration while theeye was fixated within the visual region around each noun phrase or the verb. A fixation was
defined as a period of time when the eye did not move more than the width of a character (0.96◦
of arc) for 80 ms or longer. The means of the first fixation times for each phrase are reported
in Table 2. For correct ‘Yes’ responses, the first fixation times of three types of sentences wereanalyzed by one-way ANOVA with repeated measures. The main effect on the first fixation
times for the region of the third phrase (NP3 ) was not significant in participant analysis[F1 (2, 34) = 0.30, p = .074], but significant in item analysis [F2 (2, 58) = 3.22, p < .05].
Multiple comparisons using Tukey’s HSD showed that first fixation durations on the thirdphrase of single-scrambled sentences were longer than those of canonical sentences.
The main effect for the region of the verb was significant in participant analysis[F1 (2, 34) = 5.37, p < .01], but not significant in item analysis [F2 (2, 58) = 2.10, p =.131]. Multiple comparisons using Tukey’s HSD showed that first fixation durations on theverb of canonical sentences were longer than those of single-scrambled sentences.
First Pass Reading Times
The first pass reading times were the total of the durations of fixations made on each phrasefrom the first fixation until the eye moved to another phrase or verb region. For correctsentences, the pre-head reading times for each of the three noun phrases and the verb
were examined by one-way ANOVAs. The means of reading times for each phrase arereported in Table 3. The pre-head reading times in the third phrase showed a significant main
effect [F1 (2, 34) = 16.38, p < .001, F2 (2, 58) = 20.77, p < .001]. Multiple comparisons using Tukey’s HSD showed that reading times of the third phrase of both single- anddouble-scrambled sentences were longer than in canonical sentences. Since both scrambled123

J Psycholinguist Res (2014) 43:167–185

177

Table 3 First pass reading times in noun phrases and verb for correct sentences
Sentence type

Reading times (ms) of correct sentences in each region
NP1

NP2

NP3

Verb

M

SE

M

SE

M

SE

M

SE

1. Canonical

342

31

278

21

266

22

192

24

2. Single-scrambled

345

34

254

25

377

30

162

21

3. Double-scrambled

347

40

256

28

411

40

167

20

Main effects

ns

ns

***

Multiple comparison

ns

123

M refers to means while SE refers to standard errors
Underlined numerals indicate sentence types differed significantly in multiple comparison
ns refers to ‘not significant’ * p < .05; ** p < .01; *** p < .001
Table 4 Re-reading times in noun phrases (NP) and verb for correct ’Yes’ responses
Sentence type

Reading times (ms) of correct ‘Yes’ responses
NP1

NP2

NP3

Verb

M

SE

M

SE

M

SE

M

SE

1. Canonical

48

17

95

28

15

7

7

4

2. Single-scrambled

38

8

66

17

63

17

3

2

3. Double-scrambled

96

19

150

30

175

37

22

9

Main effects

**

*

***

Multiple comparison

213

213

123

* (only F1 )M refers to means while SE refers to standard errors
Underlined numerals indicate sentence types differed significantly in multiple comparison* p < .05; ** p < .01; *** p < .001

conditions produced one gap for single-scrambled and two gaps for double-scrambled orderin the third phrase (NP3 ), this result indicates that pre-head parsing involved resolving afiller-gap dependency before the head verb was seen. However, nouns of scrambled orderat this phrase are not matched with nouns of canonical order, a finding which is examinedfurther in the Discussion section. No main effects were found in reading times of the regionsof the first phrase (NP1 ), second phrase (NP2 ) or verb.
Re-reading Times
Re-reading times were calculated by the total reading duration (sum of all fixations) minus thefirst pass reading duration. Re-reading times for each of the three noun phrases and the verb
were examined by the same ANOVAs. The means of reading times for each phrase are reported
in Table 4. Re-reading times showed significant main effects in all three noun phrase positions.
Re-reading times in the first phrase (NP1 ) showed a significant main effect [F1 (2, 34) =7.31, p < .01, F2 (2, 58) = 6.52, p < .01]. Tukey’s HSD multiple comparisons showedthat double-scrambled sentences had longer reading times than either canonical or singlescrambled sentences. In the second noun phrase (NP2 ), the re-reading times also showed asignificant main effect [F1 (2, 34) = 5.11, p < .05, F2 (2, 58) = 5.28, p < .01]. Tukey’s

123

178

J Psycholinguist Res (2014) 43:167–185
0.1 time
1.0 time

Canonical(SO1O2V)

SingleScrambled(SO2O1V)
DoubleScrambled(O1O2SV)

Satoosan-ga Suzukisan-ni
Skaban-oazuketa.

O2

V

O1

Satoosan-ga kaban-o Suzukisan-ni
S

O2

O1

Satoosan-ni kaban-o Suzukisan-ga
O1

O2

S

azuketa.
V

azuketa.
V

Fig. 2 Phrasal eye movements for three types of sentences. Note: Figure 2 depicts an average movement of
more than 0.1 times. Black arrows above each sentence show eye movements of first pass phrasal readingfrom one region (a noun phrase or a verb) to another. Gray arrows below each sentence show eye movementsof second or later pass phrasal reading from one region to another. The size of an arrow indicates averagefrequency of movements. S refers to a subject and V refers to a verb. O1 refers to indirect object marked by adative case-maker–ni while O2 refers to direct object marked by an accusative case-marker -o

HSD multiple comparisons showed that double-scrambled sentences showed longer reading
times than single-scrambled sentences. Likewise, re-reading times in the third phrase (NP3 )showed a significant main effect [F1 (2, 34) = 15.25, p < .001, F2 (2, 58) = 21.63, p <.001]. Again, Tukey’s HSD multiple comparisons showed that double-scrambled sentences
showed longer reading times than either canonical or single-scrambled sentences. Re-reading
times in the region of the verb was significant in participant analysis [F1 (2, 34) = 4.10, p <.05], but not significant in item analysis [F2 (2, 58) = 2.92, p = .060], which was considered
not significant. Tukey’s HSD multiple comparisons showed that re-reading times on theverb were longer in double-scrambled sentences than in single-scrambled sentences. In sum,double-scrambled sentences required longer re-reading times in all noun phrases than singlescrambled sentences; the latter had no difference from canonical sentences.
Regression-Out and Regression-In Gaze Phrasal Eye Movements
The trend of gaze phrasal movements more frequent than an average of 0.1 times for thethree types of sentences is depicted in Fig. 2. Black arrows above each sentence show eye
movements of the first pass phrasal reading while gray arrows below each sentence show eye
movements of the second or later pass phrasal reading. The size of an arrow indicates theaverage frequency of movements. The trend of black arrows indicates that native Japanese
speakers read all three types of sentences sequentially from left to right. In contrast, the streamof gray arrows in double-scrambled sentences indicates backward reading or regression
from verbs toward the second noun phrase (NP2 ), and further from NP2 to the third nounphrase (NP3 ) while canonical and single-scrambled sentences only showed a minor degreeof phrasal movement from verb to NP2 . Single-scrambled sentences showed a minor degreeof movement from NP2 to NP3 . Detailed analyses were conducted for regression-out andregression-in frequencies.

123J Psycholinguist Res (2014) 43:167–185

179

Table 5 Regression-out gaze movement for correct sentences
Sentence type

Regressions-out in regions
NP2

NP3

Verb

M

SE

M

SE

M

SE

1. Canonical

0.10

0.03

0.07

0.02

0.36

0.08

2. Single-scrambled

0.08

0.02

0.16

0.05

0.34

0.06

3. Double-scrambled

0.18

0.05

0.32

0.08

0.51

0.09

Main effects
Multiple comparison* (only F2 )*** (only F1 )

213

123

213

M refers to means while SE refers to standard errors
Underlined numerals indicate sentence types differed significantly in multiple comparison* p < .05; ** p < .01; *** p < .001

Regression-out gaze movement is defined as the probability of regressions out of a
specific phrase. The mean regression-out frequency for each region in each sententialcondition is shown in Table 5. The regression-out in the second noun phrase (NP2 )showed a significant main effect only in item analysis [F1 (2, 34) = 2.44, p = .102,
F2 (2, 58) = 3.31, p < .05]. Tukey’s HSD multiple comparisons showed that doublescrambled sentences showed more frequent regression-out gaze movements than singlescrambled sentences. In the third noun phrase (NP3 ), the regression-out movement showeda significant main effect [F1 (2, 34) = 7.65, p < .01, F2 (2, 58) = 11.66, p < .001].
Tukey’s HSD multiple comparisons showed that double-scrambled sentences showed more
frequent regression-out gaze movements than canonical and single-scrambled sentences.
Likewise, the verb region showed a significant main effect only in the participant analysis[F1 (2, 34) = 3.93, p < .05, F2 (2, 58) = 1.78, p = .178]. Again, Tukey’s HSD multiple comparisons showed that double-scrambled sentences had more frequent regression-out
movements than single-scrambled sentences. Regression-out gaze movements include frequencies before seeing the verb. For example, regression-out from the third noun phrase canindicate re-reading from NP3 to NP2 before seeing the verb. Thus, strictly speaking, only
regression-out from the verb can indicate post-head movement. The third noun phrase, beingat the position to resolve two filler-gap dependencies seems to be crucial for processing
double-scrambled sentences.
Regression-in gaze movement is defined as how often eye gaze enters into a specificregion after the first pass reading. The mean gaze movements for each region of three typesof sentential condition are shown in Table 6. The first noun phrase (NP1 ) showed a significant main effect [F1 (2, 34) = 3.66, p < .05, F2 (2, 58) = 3.33, p < .05]. However,Tukey’s HSD multiple comparisons showed no significant differences among three typesof sentences. Likewise, the second noun phrase (NP2 ) showed a significant main effect[F1 (2, 34) = 6.17, p < .01, F2 (2, 58) = 4.19, p < .05]. Tukey’s HSD multiple comparisons indicated that double-scrambled sentences showed more frequent regression-in movements than canonical and single-scrambled sentences. Furthermore, the third noun phrase(NP3 ) showed a significant main effect only in item analysis [F1 (2, 34) = 2.76, p = .077,
F2 (2, 58) = 4.02, p < .05]. Tukey’s HSD multiple comparisons indicated that doublescrambled sentences showed more frequent regression-in movements than canonical sentences, but single-scrambled sentences did not. Regression-in gaze movements indicated

123

180

J Psycholinguist Res (2014) 43:167–185

Table 6 Regression-in gaze movement for correct sentences
Sentence type

Regressions-in in regions
NP1

NP2

NP3

M

SE

M

SE

M

SE

1 Canonical

0.21

0.06

0.27

0.07

0.05

0.02

2 Single-scrambled

0.22

0.05

0.26

0.06

0.10

0.03

3 Double-scrambled

0.38

0.07

0.48

0.09

0.14

0.04

Main effects**** (only F2 )Multiple comparison

ns

213

123

M refers to means while SE refers to standard errors
Underlined numerals indicate sentence types differed significantly in multiple comparison
ns refers to ‘not significant’ * p < .05; ** p < .01; *** p < .001

that eyes moved frequently to the second noun phrase when processing double-scrambled
sentences.

Discussion
To depict pre- and post-head gap-filling parsing, the present study investigated the processingof canonical and single-/double-scrambled sentences.
Behavioral data of reaction times for sentence correctness decision only showed significant
delay and higher errors only for double-scrambled sentences in comparison to canonicaland single-scrambled sentences. The differences between canonical and single-scrambled
sentences were 54 ms in speed and 0.56 % in accuracy, neither of which were significant. The
overall reaction times and error rates did not distinguish single-scrambled sentences from thebaseline of canonical order. On the other hand, double-scrambled sentences showed greaterdifficulties, with an extra 399 ms in speed and 11.25 % in accuracy as compared with thoseof canonical order. In terms of behavioral data, single-scrambled sentences seem to display asimilar degree of processing difficulty as canonical sentences. As Lewis (1996) suggested, two(or three) anomalies require far stronger cognitive loading than a single anomaly. However,as behavioral data can provide the basis for only an overall estimation, further detailed
investigation was carried out by the eye-tracking method (e.g., Findlay and Gilchrist 2003;
McConkie and Rayner 1975; Rayner 1998; Staub and Rayner 2007) measuring eye fixation
durations and regression frequencies in each phrase.
The first pass reading time showed longer fixation time at the third noun phrase for singleand double-scrambled sentences in comparison to canonical order. This result may suggestthat native Japanese speakers resolve filler-gap dependencies just before seeing the final
head verb. As the pre-head anticipatory processing (e.g., Aoshima et al. 2004; Inoue and Den
1999; Inoue and Fodor 1995; Kamide et al. 2003; Kamide and Mitchell 1999; Miyamoto
and Takahashi 2002, 2004; Ueno and Kluender 2003) expects, both sentences with singlescrambled (SO1 O2 V) and double-scrambled (O1 O2 SV) orders require gap-filling parsing at
the third phrase before seeing the head verb. A single-scrambled order has a single filler-gap
dependency between NP-o1 and gap1 as in [S NP-ga [VP NP-o1 [VP NP-ni [V gap1 V]]]]
while a double-scrambled order has two filler-gap dependencies, NP-ni1 and gap1, and NPo2 and gap2 , as in [S NP-ni1 [S NP-o2 [S NP-ga [VP gap1 [V gap2 V]]]]]. Then, native123

J Psycholinguist Res (2014) 43:167–185

181

Japanese speakers anticipate a ditransitive verb to complete an active sentence. In pre-headanticipatory processing, native Japanese speakers construct phrasal syntactic structures prior
to encountering the head verb. However, the strict version of pre-head anticipatory processing
cannot be applicable, at least, for the processing of double-scrambled sentences which showed
longer re-reading times (the total reading duration minus the first pass reading duration) thansingle-scrambled sentences.
Before discussing post-head parsing, the explanation of pre-head gap-filling parsing
should be carefully interpreted. First, the third phrases of canonical and single-/doublescrambled conditions consist of different noun phrases: inanimate accusative-marked (-o)
nouns for canonical, dative-marked (-ni) proper nouns for single-scrambled sentences, andnominative-marked (-ga) proper nouns for double-scrambled sentences. Stated precisely,
direct comparison is only possible between single- and double-scrambled conditions: thetwo scrambled sentences were matched with the same nouns in the same phrasal position and the only differences were case-markers. Second, due to the wide visual span (e.g.,
Henderson and Ferreira 1990; Morrison 1984; Rayner and Fischer 1996) that human beings
have, when eyes are fixated on the third-positioned noun phrase, the ending head verb can beseen together with the previous noun phrase. Given these two reasons, the first pass reading
time does not provide sufficient evidence to support the pre-head gap-filling parsing, but can,however, suggest the possibility.
The post-head gap-filling parsing was investigated by re-reading times. Single-scrambled
sentences did not show any difference from canonical sentences in any noun phrase. The
single-scrambled sentences of the present study were produced by swapping the dative nounphrase and accusative noun phrase. This type of scrambling is called internal verb phrase
movement, which may not require much cognitive loading to establish a single filler-gap
dependency at the third phrase just before the head verb. In contrast, double-scrambled
sentences needed longer re-reading times in the first, second and third noun phrases thansingle-scrambled sentences. A possible interpretation of these refixation times as an index
of parsing difficulties (Vitu et al. 1998) might run as follows. Native Japanese speakers
have to resolve two filler-gap dependencies for double-scrambled sentences. To accomplish
this, they have to read backward to find appropriate agreement among three noun phrases
with information of the ditransitive head verb. This post-head gap-filling parsing, reflectedin the re-reading times of the three noun phrases in the double-scrambled sentences, took
significantly longer than that of single-scrambled sentences. Since nouns and verbs wereidentical between the single- and double-scrambled sentences, this post-head gap-fillingparsing has a great potential for the processing model for double-scrambled sentences.
Regression-in and regression-out frequencies also provided convincing support for the
post-head gap-filling parsing. As indicated by regression-in gaze movements, doublescrambled sentences showed higher regression-in frequency at the second phrase than either
single-scrambled or canonical. This result suggests that the eyes of native Japanese speakers
move from the verb or the third phrase to the second phrase. In addition, regression-out gazemovements indicated that double-scrambled sentences showed higher regression-out frequency at the third phrase. For double-scrambled sentences, native Japanese speakers readbackward from the third phrase to the second or the first. Both regression-in and regressionout gaze movements support the post-head parsing are required to resolve two filler-gap
dependencies of double-scrambled sentences.
Synthesizing the findings of significant re-reading times for all noun phrases withthe findings of regression-in and regression-out gaze movements, it appears that native
Japanese speakers re-read double-scrambled sentences after seeing the head verb (including seeing the verb during fixations at the third phrase) back mostly to the nominative-

123

182

J Psycholinguist Res (2014) 43:167–185

marked third phrase (NP-ga) and accusative-marked second phrase (NP-o), and occasionally to the dative-marked first phrase (NP-ni) to check verb agreements. Using information of the ditransitive head verb, native Japanese speakers read back to NP-ni and NP-oto resolve filler-gap dependencies at the third noun phrase (NP-ga) for double-scrambled
sentences. In sum, the pre-head anticipatory parsing might be enough to establish a fillergap dependency for single-scrambled sentences. However, the head verb plays an important function for resolving the two filler-gap dependencies of double-scrambled sentences.
The present study clearly depicted the post-head gap-filling parsing of double-scrambled
sentences.

Appendix: Sentences Used in the Present Experiment
For stimuli of correct ‘Yes’ decisions (correct sentences), 30 canonical sentences were alteredto create 30 single-scrambled and 30 double-scrambled sentences (a total of 90 correct sentences). These stimuli were used for analysis in the present study. In the same manner, forcorrect ‘No’ decisions (incorrect sentences), 30 incorrect canonical sentences were altered tomake 30 single-scrambled and 30 double-scrambled sentences. The experiment also included
15 unacceptable and 15 acceptable filler sentences. Three examples of correct ‘Yes’ responses
with three word orders are presented here in the “Appendix”.

Takahashi presented flowers to Tanaka.
(1) Canonical sentence[S NP-ga [VP NP-ni [V NP-o V]]]
Takahashi-san-ga Tanaka-san-ni hana-o okut-ta.
Takahashi-san-NOM Tanaka-san-DAT flowers-ACC present-PAST(2) Single-scrambled sentence[S NP-ga [VP NP-o1 [V P NP-ni [V gap1 V]]]]
Takahashi-san-ga hana-o Tanaka-san-ni okut-ta.
Takahashi-san-NOM flowers-ACC Tanaka-san-DAT present-PAST(3) Double-scrambled sentence[S NP-ni1 [S NP-o2 [S NP-ga [VP gap1 [V gap2 V]]]]]
Tanaka-san-ni hana-o Takahashi-san-ga okut-ta.
Tanaka-san-DAT flowers-ACC Takahashi-san-NOM present-PASTYamasaki returned a dictionary to Abe.
(1) Canonical sentence[S NP-ga [VP NP-ni [V NP-o V]]]
Yanasaki-san-ga Abe-san-ni jisho-o kaeshi-ta.
Yamasaki-san-NOM Abe-san-DAT (a) dictionary-ACC return-PAST(2) Single-scrambled sentence[S NP-ga [VP NP-o1 [VP NP-ni [V gap1 V]]]]
Yamasaki-san-ga jisho-o Abe-san-ni kaeshi-ta.
Yamasaki-san-NOM (a) dictionary-ACC Abe-san-DAT return-PAST123

J Psycholinguist Res (2014) 43:167–185

183(3) Double-scrambled sentence[S NP-ni1 [S NP-o2 [S NP-ga [VP gap1 [V gap2 V]]]]]
Abe-san-ni jisho-o Yamasaki-san-ga kaeshi-ta.
Abe-san-DAT (a) dictionary-ACC Yamasaki-san-NOM return-PAST

Kondo offered beer to Murakami.
(1) Canonical sentence[S NP-ga [VP NP-ni [V NP-o V]]]
Kondo-san-ga Murakami-san-ni biiru-o susume-ta.
Kondo-san-NOM Murakami-san-DAT beer-ACC offer-PAST(2) Single-scrambled sentence[S NP-ga [VP NP-o1 [VP NP-ni [V gap1 V]]]]
Kondo-san-ga biiru-o Murakami-san-ni susume-ta.
Kondo-san-NOM beer-ACC Murakami-san-DAT offer-PAST(3) Double-scrambled sentences[S NP-ni1 [S NP-o2 [S NP-ga [VP gap1 [V gap2 V]]]]]
Murakami-san-ni biiru-o Kondo-san-ga susume-ta.
Murakami-san-DAT beer-ACC Kondo-san-NOM offer-PAST

References
Aoshima, S., Phillips, C., & Weinberg, A. (2004). Processing filler-gap dependencies in a head-final language.
Journal of Memory and Language, 51, 23–54.
Crain, S., & Forder, J. D. (1985). How can grammars help parsers? In D. R. Dowty, L. Karttunen, &A. M. Zwicky (Eds.), Natural language parsing (pp. 94–128). Cambridge: Cambridge University Press.
Farmer, A. (1984). Modularity in syntax: A study of Japanese and English. Cambridge, MA: MIT Press.
Findlay, J. M., & Gilchrist, I. D. (2003). Active vision: The psychology of looking and seeing. Oxford: Oxford
University Press.
Fodor, J. A., Bever, T. G., & Garrett, M. F. (1974). The psychology of language. New York: McGraw-Hill.
Frazier, L. (1987). Syntactic processing: Evidence from Dutch. Natural Language and Linguistic Theory, 5,
519–559.
Frazier, L., & Clifton, C, Jr. (1989). Identifying gaps in English sentences. Language and Cognitive Processes,
4, 93–126.
Frazier, L., & Flores D’Arcais, G. B. (1989). Filler driven parsing: A study of gap filling in Dutch. Journal of
Memory and Language, 28, 331–344.
Frazier, L., & Rayner, K. (1982). Making and correcting errors during sentence comprehension: Eye movements in the analysis of structurally ambiguous sentences. Cognitive Psychology, 14, 178–210.
Gair, W. J. (1998). Syntax: Configuration, order, and grammatical function. In: B.C. Lust (Ed.), Studies in South
Asian linguistics; Sinhala and other South Asian languages (pp. 47–110). New York: Oxford University
Press.
Hale, K. (1980). Remarks on Japanese phrase structure: Comments on the papers on Japanese syntax. MIT
Working Papers in Linguistics, 2, 185–203.
Hale, K. (1982). Preliminary remarks on configurationality. North East Linguistic Society, 12, 86–96.
Hale, K. (1983). Warlpiri and the grammar of non-configurational language. Natural Language and Linguistic
Theory, 1, 5–47.
Henderson, J. M., & Ferreira, F. (1990). Effects of foveal processing difficulty on the perceptual span in reading:
Implications for attention and eye movement control. Journal of Experimental Psychology: Learning,
Memory and Cognition, 16, 417–429.
Hoji, H. (1985). Logical form constraints and configurational structure in Japanese. Ph.D. dissertation, Seattle,
USA: University of Washington.

123

184

J Psycholinguist Res (2014) 43:167–185

Hoji, H. (1987). Week crossover and Japanese phrase structure. In T. Imai & M. Saito (Eds.), Issues in Japanese
linguistics (pp. 163–201). Dordrecht: Foris.
Inoue, M., & Den, Y. (1999). Influence of verb-predictability on ambiguity resolution in Japanese. In Proceedings of the 2nd international conference on cognitive science and the 16th annual meeting of the Japanesecognitive science society joint conference, pp. 499–502.
Inoue, A., & Fodor, J. D. (1995). Information-paced parsing of Japanese. In R. Mazuka & N. Nagai (Eds.),
Japanese sentence processing (pp. 9–63). Hilsdale, NJ: Lawrence Erlbaum.
Kamide, Y., Altmann, G. T. M., & Haywood, S. L. (2003). Prediction and thematic information in incremental
sentence processing: Evidence from anticipatory eye movements. Journal of Memory and Language, 49,
133–156.
Kamide, Y., & Mitchell, D. C. (1999). Incremental pre-head attachment in Japanese parsing. Language andCognitive Processes, 14(5/6), 631–662.
Koizumi, M., & Tamaoka, K. (2004). Cognitive processing of Japanese sentences with ditransitive verbs.
Gengo Kenkyu (Journal of the Linguistic Society of Japan), 125, 173–190.
Koizumi, M., & Tamaoka, K. (2010). Psycholinguistic evidence for the VP-internal subject position in
Japanese. Linguistic Inquiry, 41, 663–680.
Lewis, R. (1996). Interference in short-term memory: The magical number two (or three) in sentence processing. Journal of Psycholinguistic Research, 25, 93–115.
Mazuka, R., Itoh, K., & Kondo, T. (2002). Cost of scrambling in Japanese sentence processing. In M. Nakayama(Ed.), Sentence processing in East-Asian languages (pp. 131–166). Stanford, CA: CSLI (Center for the
Study of Language and Information).
McConkie, G. W., & Rayner, K. (1975). The span of the effective stimulus during a fixation in reading.
Perception and Psychophysics, 17, 578–586.
Miyagawa, S. (1989). Structure and case marking in Japanese: Syntax and semantics. Vol. 22. San Diego,
CA: Academic Press.
Miyagawa, S. (2010). Why Agree? Why Move? Unifying agreement-based and discourse configurational
languages (Linguistic Inquiry Monograph 54). Cambridge, MA: MIT Press.
Miyagishi, T. (2003). Shinharago no dakkaku/gukaku meishi to dooshi no musubitsuki relationship between
ablative/instrumental case nouns. Yasuda Joshi Daigaku Kiyoo Yasuda Women’s University Bulletin, 31,
1–26.
Miyamoto, E., & Takahashi, S. (2002). The processing of wh-phrases and interrogative complementizers inJapanese. In N. Akatuka & S. Strauss (Eds.), Japanese/Korean linguistics (Vol. 10, pp. 62–75). Stanford,
CA: CSLI (Center for the Study of Language and Information),
Miyamoto, E., & Takahashi, S. (2004). Filler-gap dependencies in the processing of scrambling in Japanese.
Language and Linguistics, 5, 153–166.
Morrison, R. E. (1984). Manipulation of stimulus onset delay in reading: Evidence for parallel programmingof saccades. Journal of Experimental Psychology: Human Perception and Performance, 5, 667–682.
Nakayama, M. (1995). Scrambling and probe recognition. In R. Mazuka & N. Nagai (Eds.), Japanese sentence
processing (pp. 257–273). Hillsdale, HJ: Erlbaum.
Pritchett, B. L. (1991). Head position and parsing ambiguity. Journal of Psycholinguistic Research, 20(3),251–270.
Pritchett, B. L. (1992). Grammatical competence and parsing performance. Chicago: University of Chicago
Press.
Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological
Bulletin, 124, 372–422.
Rayner, K., & Fischer, M. H. (1996). Mindless reading revisited: Eye movements during reading and scanningare different. Perception and Psychophysics, 58, 734–747.
Ross, J.-R. (1967). Constraints on variables in syntax. Ph.D. dissertation. Cambridge, USA: Massachusetts
Institute of Technology.
Saito, M. (1985). Some asymmetries in Japanese and their theoretical implications. Ph.D. dissertation. Cambridge, USA: Massachusetts Institute of Technology.
Saito, M., & Hoji, H. (1983). Weak cross-over and move α in Japanese. Natural Language & Linguistic Theory,
1, 245–259.
Staub, A., & Rayner, K. (2007). Eye movements and on-line comprehension processes. In M. G. Gaskell (Ed.),
The Oxford handbook of psycholinguistics (pp. 327–342). Oxford: Oxford University Press.
Stowe, L. (1986). Parsing wh-constructions: Evidence for on-line gap location. Language and Cognitive
Processes, 1, 227–245.
Tamaoka, K., Sakai, H., Kawahara, J., Miyaoka, Y., Lim, H., & Koizumi, M. (2005). Priority information used
for the processing of Japanese sentences: Thematic roles, case particles or grammatical functions. Journalof Psycholinguistic Research, 34, 273–324.

123

J Psycholinguist Res (2014) 43:167–185

185

Ueno, M., & Kluender, R. (2003). Event-related brain indices of Japanese scrambling. Brain and Language,86, 243–271.
Vitu, F., McConkie, G. W., & Zola, D. (1998). About regressive saccades in reading and their relation toword identification. In G. Underwood (Ed.), Eye guidance in reading and scene perception (pp. 101–124).
Amsterdam: North-Holland.
Yamashita, H. (1997). The effects of word-order and case marking information on the processing of Japanese.
Journal of Psycholinguistic Research, 26, 163–188.

123