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Event-related brain indices of gap-filling processing in Kaqchikel

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In many languages with flexible word order, transitive sentences in which the subject precedes the object have been reported to have a processing advantage during sentence comprehension compared with those in which the subject follows the object. This observation brings up the question of why this subject-before-object (SO) order should be preferred in sentence comprehension, together with the related empirical question of whether this preference is universal across all human languages. In the present ERP study, we address these two issues by examining the word order preference in Kaqchikel, a Mayan language spoken in Guatemala, in which the verb-object-subject (VOS) order is the syntactically basic word order. In the experiment, native speakers of Kaqchikel were auditorily presented four types of sentences (VOS, VSO, SVO, and OVS), followed by a picture that either matched or mismatched an event described in a preceding sentence, while their EEGs were recorded. The result of the ERP experiment showed that VSO elicited a larger positive component, called a P600 effect, in the comparison to the canonical word order, VOS in the third region (i.e., O of VSO versus S of VOS), in which the filler-gap dependency was supposed to be established in VSO sentences. Furthermore, SVO also exhibited a P600 effect compared to VOS in the third region, reflecting an increased syntactic processing cost. These results indicate that the syntactically basic word order, VOS, requires a lower amount of cognitive resources to process than other possible word orders in Kaqchikel. Based on these results, we argue that the SO preference in sentence comprehension reported in previous studies may not reflect a universal aspect of human languages; rather, processing preference may be language-specific to some extent, reflecting syntactic differences in individual languages.
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In: Event-Related Potential (ERP) ISBN: 978-1-53610-805-7
Editor: Samuel R. Harris © 2017 Nova Science Publishers, Inc.
Chapter 3
EVENT-RELATED BRAIN INDICES
OF GAP-FILLING PROCESSING
IN KAQCHIKEL
Masataka Yano 1, 2, Daichi Yasunaga 3, *
and Masatoshi Koizumi 1
1 Graduate School of Arts and Letters, Tohoku University, Sendai, JAPAN,
2 Japan Society for the Promotion of Science, Tokyo, JAPAN
3 Faculty of Letters, Kanazawa University, Kanazawa, JAPAN
ABSTRACT
In many languages with flexible word order, transitive sentences in which the subject
precedes the object have been reported to have a processing advantage during sentence
comprehension compared with those in which the subject follows the object. This
observation brings up the question of why this subject-before-object (SO) order should be
preferred in sentence comprehension, together with the related empirical question of
whether this preference is universal across all human languages. In the present ERP study,
we address these two issues by examining the word order preference in Kaqchikel, a
Mayan language spoken in Guatemala, in which the verb-object-subject (VOS) order is
the syntactically basic word order. In the experiment, native speakers of Kaqchikel were
auditorily presented four types of sentences (VOS, VSO, SVO, and OVS), followed by a
picture that either matched or mismatched an event described in a preceding sentence,
while their EEGs were recorded. The result of the ERP experiment showed that VSO
elicited a larger positive component, called a P600 effect, in the comparison to the
canonical word order, VOS in the third region (i.e., O of VSO versus S of VOS), in
which the filler-gap dependency was supposed to be established in VSO sentences.
Furthermore, SVO also exhibited a P600 effect compared to VOS in the third region,
reflecting an increased syntactic processing cost. These results indicate that the
syntactically basic word order, VOS, requires a lower amount of cognitive resources to
process than other possible word orders in Kaqchikel. Based on these results, we argue
that the SO preference in sentence comprehension reported in previous studies may not
reflect a universal aspect of human languages; rather, processing preference may be
language-specific to some extent, reflecting syntactic differences in individual languages.
Keywords: basic word order, field-based neurolinguistics, P600, Guatemala,
Kaqchikel, syntactic complexity, processing load
* Corresponding Author address
Email: daichi.y@staff.kanazawa-u.ac.jp, koizumi@sal.tohoku.ac.jp
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
1. INTRODUCTION
Human languages differ in many respects, such as basic word order and grammatically
possible orders of individual languages. The word order of languages, such as English, is
relatively fixed, while other languages, such as Japanese, allow some word-order alternations.
In many languages with flexible word orders, transitive sentences in which the subject (S)
precedes the object (O) (SO Word Order = SOV, SVO, VSO) have been reported to have a
processing advantage compared with those in which S follows O (OS Word Order = OSV,
OVS, VOS) (e.g. Bader & Meng, 1999 for German; Kaiser & Trueswell, 2004 for Finnish;
Kim, 2012 for Korean, Mazuka, Itoh, & Kondo, 2002; and Tamaoka et al., 2005 for Japanese;
Sekerina, 1997 for Russian; Tamaoka et al., 2011 for Sinhalese). The SO word order is
processed faster than OS word orders, according many psycholinguistic studies using self-
paced reading (Koizumi & Imamura, 2016) and eye-tracking (Mazuka et al., 2002).
Neurolinguistics studies also have showed a similar SO processing preference. Functional
magnetic resonance imaging (fMRI) studies have found a greater activation at the left inferior
frontal gyrus in the processing of the OS word order compared to the SO word order (Grewe
et al., 2007 for German, Kim et al., 2009; and Kinno et al., 2008 for Japanese). The
processing advantage in the SO word order has also been revealed in ERP studies; the SO
word order elicits a late positivity effect, called a P600 effect, and/or (sustained) anterior
negativity (Erdocia et al., 2009 for Basque; Rösler et al., 1998 for German; Ueno & Kluender,
2003; and Hagiwara et al., 2007 for Japanese). Taken together, abundant evidence supports
the claim that the SO word order is preferred to the OS word order in many of the world’s
languages.
This observation brings up the question of why the SO word order should be preferred in
sentence comprehension, together with the related empirical question of whether this
preference is universal across all human languages. In the literature, a number of factors have
been proposed as to what affects the word-order preference in sentence comprehension and
production. These may be divided into two broad theoretical positions (Koizumi et al., 2014).
One view suggests that the SO preference is attributed to the grammatical factors of
individual languages, such as syntactic complexities. Word orders other than a syntactically
basic one are derived from a syntactically basic word order through syntactic operations such
as scrambling and inducing syntactic complexities. This theory hypothesises that a
syntactically determined basic SO word order in a language is favoured, compared to other
available word orders because derived OS word orders require the processing of more
complex syntactic structures (see Gibson, 2000; Hawkins, 2004; Marantz, 2005; O’Grady,
1997; Pritchett & Whitman, 1995, among others). We refer to this view as the individual
grammar theory. In contrast, universal human cognitive features (e.g., conceptual
accessibility) may play a primary role in determining the word-order preference. This
alternative view, which we refer to as the universal cognition theory, suggests the SO word
order is preferred, regardless of the basic word order of individual languages (Bornkessel-
Schlesewsky & Schlesewsky, 2009a, 2009b; Kemmerer, 2012; Tanaka et al., 2011 among
others). Such a view may be supported by the fact that a vast majority of the world’s
languages have one of the SO word orders as a basic word order (SOV: 48%, SVO: 41%,
VSO: 8%, VOS: 2%, OVS: 1%, OSV: 0.5%, Dryer, 2005; see also Gell-Mann & Ruhlen,
2011). In particular, several studies have reported that prominent entities such as an agent,
Event-related brain indices of gap-filling processing in Kaqchikel
3
animate ones, concrete ones, prototypical ones tend to appear as sentence-initial subjects (cf.,
Branigan, Pickering & Tanaka, 2008; Bock & Warren, 1985; Bornkessel-Schlesewsky &
Schlesewsky, 2009a; Hirsh-Pasek & Golinkoff, 1996; Primus, 1999; Slobin & Bever, 1982).
This theory predicts the SO preference as independent from syntactic differences in
individual languages.
Because these two theories correctly predict the SO processing advantage that has been
reported in SO languages, it remains unclear as to whether it is specific to some human
languages or general and therefore can be observed across all human languages. Nevertheless,
these two possibilities can be disentangled by targeting OS languages—languages in which O
precedes S in a syntactically basic word orderbecause they offer an opposite prediction
regarding a preferred order. The individual grammar theory predicts an OS preference in the
OS languages because the SO word order has a more complex syntactic structure than does
the OS word order. Thus, unlike SO languages, the OS word order should require a lower
processing cost than the SO word order in OS languages. In contrast, according to the
universal cognition theory, SO preference should be observed in such languages because this
theory predicts that an SO preference would not pertain to the syntactic characteristics of
individual languages. Therefore, the SO word order would be processed more easily than the
OS word order, even in OS languages.
This study reports on an ERP study of Kaqchikel, a Mayan OS word-order language
spoken in Guatemala. Before reporting the results in detail, we first review some basic
characteristics of Kaqchikel in Section 2 to explain why this language provides a valuable
means for testing two above-mentioned hypotheses.
2. KAQCHIKEL
Kaqchikel is one of the Mayan languages spoken in Guatemala. It is spoken mainly in the
highlands west of Guatemala City. The number of native speakers of Kaqchikel is estimated
to be 450,000 people (Brown, Maxwell & Little, 2006: 2; Lewis, 2009; Tay Coyoy, 1996: 55).
Like other Mayan languages, Kaqchikel is an ergative language, so that the transitive
object received the same Case as the subject of the intransitive verb (i.e., absolutive Case),
while the transitive subject received an ergative Case. As shown in (1), Kaqchikel is a head-
marking language with Case morphologies attached to verbs. This language allows a subject
and an object to be dropped; both subjects and objects can be identified based on Case
information carried by the verbs. 1
(1) Y-e’-in-to’
IC-ABS3pl-ERG1sg-help
‘I help them.’
According to García Matzar & Rodríguez Guaján (1997) and others, the syntactic basic
order of Kaqchikel is VOS, as exemplified in (2). VOS is typically used in a neutral context,
in which neither the subject nor the object is topicalised or focused (Ajsivinac Sian et al.,
2004: 162; Gracía Matzar & Rodríguez Guaján, 1997: 333; Rodríguez Guaján, 1994: 200;
1 The following abbreviations were used: ABS [absolutive], CP [completive], DET [determiner], ERG [ergative],
IC [incompletive], pl [plural], sg [singular], 1 [first person], 3 [third person], PM [plural marker]
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
Tichoc Cumes et al., 2000: 195). However, different word orders are also allowed,
specifically VSO, SVO and OVS. In the case that the subject and the object are thematically
irreversible, as in (2b), VSO is also possible, although VOS is favoured. In cases where the
subject and the object are not semantically biased towards either an agent or a patient (i.e., the
subject and the object are thematically reversible), the VOS interpretation is overwhelmingly
preferred to VSO, as shown in (3).
(2) a. X-Ø-u-chöy ri chäj ri ajanel. [VOS]
CP-ABS3sg-ERG3sg-cut DET pine.tree DET carpenter
b. X-Ø-u-chöy ri ajanel ri chäj. [VSO]
CP-ABS3sg-ERG3sg-cut DET carpenter DET pine.tree
‘The carpenter cut the pine tree.’
(3) a. X-Ø-r-oqotaj ri me’s ri tz’i’.
CP-ABS3sg-ERG3sg-run.after DET cat DET dog
‘The dog ran after the cat.’
b. X-Ø-r-oqotaj ri tz’i’ ri me’s.
CP-ABS3sg-ERG3sg-run.after DET dog DET cat
‘The cat ran after the dog.’
As given in (4a), SVO is derived from VOS by preposing S to the topicalised position,
which can also host certain types of adjuncts such as locative and instrumental adjuncts
(Gracía Matzar & Rodríguez Guaján, 1997: 334). OVS is also a derived word order with O
topicalised in the context, as exemplified in (4b).
(4) a. Ri ajanel x-Ø-u-chöy ri chäj. [SVO]
DET carpenter CP-ABS3sg-ERG3sg-cut DET pine.tree
‘The carpenter cut the pine tree.’
b. Ri chäj x-Ø-u-chöy ri ajanel. [OVS]
DET pine.tree CP-ABS3sg-ERG3sg-cut DET carpenter
These word-order alternations are schematised in (5). Although the precise syntactic
structure of Mayan languages is still under debate, it is sufficient for the present purpose to
assume that VOS is structurally simpler than other grammatically possible word orders in
Kaqchikel transitive sentences (cf., England, 1991; Tada, 1993, Preminger. 2011; see also
Aissen, 1992; Coon, 2010 among many others for other Mayan languages).
(5) Word Order Schematic syntactic structure
VOS [V O S]
VSO [[ V gapi S ] Oi ]
SVO [ Si [ V O gapi ]]
OSV [ Oi [ V gapi S ]]
It is noteworthy that although the VOS is syntactically basic word order, the subject is
topicalised (i.e., SVO) very frequently in Kaqchikel to maintain discourse cohesion (England,
1991: 472; Kubo et al., 2012; Maxwell & Little, 2006: 102; Rodríguez Guaján, 1994: 201).
Event-related brain indices of gap-filling processing in Kaqchikel
5
Using a picture-description task, Kubo et al. (2012) revealed that SVO (74.4%) was used
more frequently than VOS (24.2%) and VSO (1.4%) (see also Kubo et al., 2015). It has been
suggested that when examining the ‘basic word order’ of Mayan languages, syntactically
determined word order’ from the standpoint of syntactic complexity needs to be distinguished
from ‘pragmatically determined word order, commonly used for pragmatic purposes (Brody,
1984; England, 1991). For this study, we assume that the syntactically basic word order is
VOS, because SVO has a more complex syntactic structure.
By utilising this OS property of the Kaqchikel language, Yasunaga et al. (2015)
conducted an ERP study to explore the relationship between the syntactically basic word
order and the processing difficulty (see also Kiyama et al., 2013; Koizumi et al. 2014 for
behavioural studies in Kaqchikel). In their ERP experiment, a picture-sentence matching task
was employed in which participants were presented a line-drawn coloured picture depicting a
transitive event, followed by an auditory linguistic stimulus shown in (6), while
electroencephalogram (EEG) was recorded. The transitive sentences were truth-conditionally
the same, but varied in word order: VOS, VSO, SVO, and OVS. The participants were
required to judge whether the sentence matched the preceding picture after the response cue
appeared. Yasunaga et al. (2015) found that SVO elicited a late positive shift, called a P600
effect, compared to VOS in the third region (i.e., O of SVO versus S of VOS). The P600 for
SVO was interpreted to reflect the increased syntactic processing cost to associate the
preposed S with its original position. VSO showed N400 and P600 effects in the comparison
to VOS in the second region (see Section 4 for discussion regarding the timing of P600).
These results indicate that VOS is easier to process than other possible word orders, such as
SVO and VSO. This fact suggests that the SO preference in sentence comprehension may not
be universal.
(6) a. VOS
Xkoyoj ri xar ri taq käq
CP-ABS3sg-ERG3pl-call DET blue DET PM red
“The reds called the blue.”
b. VSO
Xkoyoj ri taq käq ri xar
c. SVO
Ri taq käq xkoyoj ri xar
d. OVS
Ri xar xkoyoj ri taq käq
As discussed in Yasunaga et al., however, the remaining issue to be addressed concerns
the effect of non-linguistic visual context on sentence comprehension. Because their
participants were presented a picture that describes a following sentence, participants could
generate an explicit prediction for the upcoming sentence, which may be violated by certain
types of sentences once participants listened to the sentence. As discussed below in detail,
P600 is enhanced by not only gap-filling processes but also syntactic reanalysis. If the
syntactically basic word order, VOS, is expected before the sentence presentation, other word
orders such as SVO and VSO do not match the expected syntactic structure. Therefore, it is
reasonable that SVO and VSO elicited a greater P600 amplitude than that elicited by VOS
due to the effortful accommodation of the syntactic structure. Thus, it is necessary to examine
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
the extent to which the visual context affected the time-course of sentence processing to
evaluate more precisely whether the OS preference is robust in Kaqchikel sentence processing.
3. EXPERIMENT
We conducted an ERP experiment, aiming to investigate the word-order preference in
Kaqchikel sentence processing. Using the sentence-picture matching task and comparing the
current results with those of Yasunaga et al. (2015), the effects of visual context were
examined. Observing an OS preference even in the present experiment, in which concrete
prediction is not possible, would provide more solid evidence for the individual grammar
theory.
3.1. Procedure and Stimuli for the ERP Experiment
A sentence-picture matching task was employed in this experiment. In this task, a
Kaqchikel sentence was first presented auditorily through a headset. During the sound
presentation, participants were asked to gaze at the fixation presented in the centre of the
monitor and not to blink or move while EEG was recorded. After the sentence was heard, a
picture was presented in the centre of the screen, either matching or mismatching the event
described by the preceding sentence. Upon seeing the picture, the participants were asked to
judge whether the picture was congruent with the sentence and then to press a YESor NO
button to record their judgement (Figure 1). Instructions were given in Kaqchikel by a native
speaker.
The target sentences were arranged into four word orders, as shown in (6) above: VOS,
VSO, SVO, and OVS. They are all transitive sentences with thematically reversible agents
and patients. The following six verbs, which were commonly used in Kaqchikel were
employed: ch’äy “hit”, jik’ “pull”, nïm “push”, oyoj “call”, pixab “bless”, and xib’ik
“surprise”. Agents and patients were familiar colour terms describable in Kaqchikel: käq
“red”, xar “blue”, säq “white”, and q’ëq “black”. Either the subject or object of each sentence
was pluralised so that they were morphosyntactically disambiguated by the agreement
marking of the verb. Half of the sentences contained a singular subject and a plural object,
whereas the other half contained a plural subject and a singular object.
→→→→→
500$ms
700$ms
700$ms
700$ms
1200$$ms
2
1
Fixation
ITI
$$$$$Sentence$presentation$$$Picture$presentation
Figure 1. Design of the task used in the experiment. Participants were instructed to judge
whether the picture they saw is congruent with the preceding sentence and to respond by
pressing one of two buttons. EEGs were recorded while participants listened to the sentences.
The sentences were recorded by a male native speaker of Kaqchikel. The duration of each
sentence was edited in Praat ver. 5.1.31 to create an equal duration across the four word-order
conditions by slightly shortening the duration of some pauses between regions. There was no
particular word-order condition whose sentences were edited more heavily (in terms of the
Event-related brain indices of gap-filling processing in Kaqchikel
7
total shortened time duration) than the sentences of any other conditions. After the editing, all
the test items were judged to be natural in terms of prosody by our native Kaqchikel
consultants. The averages and standard deviations of time duration for each word order are
given in Table 1. A one-way analysis of variance (ANOVA) showed no significant
differences among the word orders in terms of time duration between the onset and offset of
the sentence (F (3, 141) = 0.986, p = 0.40). The stimulus onset asynchrony (SOA) between
the first and second regions (i.e., the duration of Region 1) and the SOA between the second
and third regions (i.e., the duration of Region 2) are more than 900 ms in all the four
conditions. Thus, it can be safely assumed that EEG signals up to approximately 900 ms after
the onset of each region were not affected by the beginning of the subsequent region. Regions
directly compared with each other were comparable and not significantly different in duration.
In particular, there was no main effect of word order among the four conditions on the
duration of the third region (F (3, 141) = 1.08, p = 0.36). The trigger pulses were inserted
with the onset of each region for all stimulus sentences by visually inspecting the speech
waveform of each sentence using Praat by the experimenters.
Table 1. Mean duration (ms) of each region (n = 48)
(M = mean, SD = standard deviation).
Word Order M SD MSD MSD MSD
VOS 2895 155 1189 126 955 124 751 118
VSO 2904 149 1199 147 978 124 727 115
SVO 2896 152 948 122 1122 123 826 134
OVS 2899 156 902 182 1132 130 865 108
A total of 192 sentences with four word orders (48 items per condition) and
corresponding pictures were presented using Stim2 (Neuroscan Inc.). In the half of the trials,
the sentences were congruent with the following pictures (e.g., The reds called the blue, see
Figure 1), and in the other half of the trials, the sentences were incongruent. Incongruent
pictures depicted an event in which a different agent involves (e.g., The blacks called the
blue), a different patient involves (e.g., The reds called the black), an agent and patient are
reversed (e.g., The blue called the reds), and the action is not correct (e.g., The reds pushed
the blue).
The stimuli were presented randomly among the participants, such that the participants
could not expect correct responses during the auditory presentation. The participants
completed practice trials to become familiarised with the experimental task. Participants took
a rest every six minutes, and the total recording time was approximately 40 minutes.
3.2. Prediction
The P600 effect, a late positive ERP component, was used to examine processing loads.
It has been observed that P600 is elicited by the filler-gap integration cost, distributing over
the scalp with a posterior focus. This effect is robust and is often observed across types of
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
difficulty with processing loads against dependency formation (Kaan et al., 2000), types of
languages (Chinese; Yang, Charles & Liu, 2010, Dutch; Hagoort & Brown, 2000, Japanese;
Hagiwara et al., 2007), and various methodological factors, such as modality of the stimulus
(i.e., visual or auditory). A P600 effect is also observed for syntactically anomalous sentences
(e.g., The hungry guests helped himself to the food; Osterhout & Mobley, 1995),
grammatically non-preferred continuation (e.g., The man is painting the house and the garage
is already finished; Kaan & Swaab, 2003a; 2003b), sentences with thematically violations
(e.g., For breakfast the eggs would only eat toast and jam; Kuperberg et al., 2003), and
picture-sentence mismatches (e.g., The triangle stands in front of the square, after presenting
a picture depicting a triangle behind a square; Vissers et al., 2008) (see Bornkessel-
Schlesewsky & Schlesewsky, 2009b for a more general review). The present study used only
grammatical sentences, which did not require a revision of the initial phrasing. In addition,
the participants could not determine whether the upcoming picture matched the sentence
during the auditory presentation. Therefore, the P600 effect observed in the present
experiment is considered to reflect an increased syntactic-processing cost due to a gap-filling
process.
The sets of words used for S and O were identical to each other across the four conditions.
Thus, the ERPs elicited by S and O could be directly compared. On the other hand, V was
different from S and O in a number of respects, including meaning, grammatical category,
production frequency, and the number of phonemes and morphemes. As these factors affect
the distribution and amplitudes of ERPs (e.g., Bornkessel-Schlesewsky & Schlesewsky,
2009b), ERPs elicited by S/O and those elicited by V were not compared. Put simply, the
following four comparisons are those of interest: VOS versus SVO in the third region, VSO
versus VOS in the second and third region, SVO and OVS in the second and third region.
According to the individual grammar theory, syntactic complexities matter in sentence
processing. If SVO involves a filler-gap dependency, as schematically shown in (5), we
predict P600 to be elicited in the third region, where the parser is supposed to associate the
dislocated S with the original gap position in the comparison to VOS. For the same reason,
VSO should also elicit a P600 effect compared to VOS in the third region, reflecting an
enhanced cost for integrating O with the gap site. As for the comparison between SVO and
OVS, the first region should not differ because the participants could not determine whether
the first NP is S or O until receiving agreement information in the second region. In the
second region of the OVS sentence, the parser is expected to associate O with the gap
following V, whereas it is not expected in the SVO sentence. Thus, OVS would show a
greater P600 amplitude than SVO. In the third region, however, SVO would elicit a P600
effect compared to OVS because the parser encounters the gap site at this region. On the other
hand, the universal cognition hypothesis would predict a different pattern. This theory
predicts that VOS and OVS induce an increased processing load than do SVO and VSO.
3.3. Participants
Sixteen native speakers of Kaqchikel participated in the experiment (10 females and 6
males, M = 30.4 years, SD = 8.4). These participants also use Spanish in daily life. All
participants were classified as right-handed based on the Edinburgh handedness inventory
(Oldfield, 1971), and all of them had normal or corrected-to-normal vision. None of the
participants had a history of neurological disorder. Written informed consent was obtained
Event-related brain indices of gap-filling processing in Kaqchikel
9
from all participants prior to the experiment, and the participants were paid for their
participation. Approval for the study was obtained from the Ethics Committee of the
Graduate School of Arts and Letters, Tohoku University.
3.4. Electrophysiological Recording
EEGs were recorded from 17 Ag-AgCl electrodes located at F3, F4, C3, C4, P3, P4, O1,
O2, F7, F8, T7, T8, P7, P8, Fz, Cz, and Pz according to the international 10-20 system (Jasper,
1958), using NuAmps (NeuroScan). Additional electrodes were placed below and to the left
of the left eye to monitor horizontal and vertical eye movements. EEGs were re-referenced to
the average value of the earlobes offline. The impedances of all electrodes were maintained at
less than 5 kΩ throughout the experiment. The EEGs were amplified with a bandpass of 0.01
to 50 Hz and digitised at 250 Hz.
3.5. Electrophysiological Data Analysis
The match and mismatch trials were collapsed in each condition because the participants
could not determine whether the upcoming picture matched the sentence during the auditory
presentation. Trials with large artefacts (exceeding ±80 µV) were automatically removed
from the analysis. The baseline was set to 100 ms prior to the onset of each region. The ERPs
were quantified by calculating the mean amplitude of every 200 ms, starting from 100 ms
after the onset of each region (i.e., 100300 ms, 300–500 ms, and 500–700 ms, 700900 ms).
All EEGs were filtered offline using a 30 Hz low-pass filter for presentation purposes.
The analyses were conducted separately at the midline (Fz, Cz, and Pz), lateral (F3, F4,
C3, C4, P3, P4, O1 and O2), and temporal (F7, F8, T7, T8, P7, and P8) arrays. The midline
analysis consisted of repeated measures analyses of variance (ANOVA) with two within-
group factors: WORD ORDER × ANTERIORITY. The lateral and temporal analyses involved
three within-group factors: WORD ORDER × ANTERIORITY × LATERALITY. The Greenhouse-
Geisser correction was applied for all effects involving more than one degree of freedom
(Greenhouse & Geisser, 1959). In these cases, the original degrees of freedom and the
corrected p-value were reported.
3.6. Results
3.6.1. Behavioural Data
At the end of each trial, our participants performed the sentence-picture matching task.
Figures 2 and 3 show the mean accuracy and response times across participants for each
condition.
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
90.1% 93.2% 94.8%
74.5%
0%
20%
40%
60%
80%
100%
VOS%
VSO%
SVO%
OVS%
Match&responses
72.1%
69% 73.7% 68%
VOS% VSO% SVO% OVS%
Mismatch&responses&
Figure 2. Mean accuracy in the sentence-picture matching task. Error bars indicate standard
errors.
2044.6&
1875.3&
1644.1&
2237.4&
1400&
1600&
1800&
2000&
2200&
2400&
2600&
VOS&
VSO&
SVO&
OVS&
Match&responses
2056.1&
1893&
1971.1&
2014.2&
VOS&
VSO&
SVO&
OVS&
Mismatch&responses
Figure 3. Mean response times (ms) in the sentence-picture matching task. Error bars indicate
standard errors.
The repeated measures ANOVA was conducted with two within-subject factors:
RESPONSE TYPE (match/mismatch) × WORD ORDER (VOS/VSO/SVO/OVS). For response
accuracy, the main effect of RESPONSE TYPE and that of WORD ORDER were significant (F (1,
15) = 53.16, p < 0.01; F (3, 45) = 11.48, p < 0.01). Because the two-way interaction was also
significant (F (3, 45) = 9.36, p < 0.01), we conducted post-hoc analyses. The simple main
effect of WORD ORDER was not significant in the mismatch responses, whereas it reached a
significant level in the match responses due to the lower response accuracy in OVS compared
to the other three conditions (VOS, VSO, and SVO).
For response times, we analysed only the trials in which the participants gave correct
responses (i.e., correct match and correct mismatch responses). Response times exceeding 2.5
standard deviations from each participant’s mean in each condition were also discarded. The
result showed a significant main effect of WORD ORDER (F (3, 45) = 10.57, p < 0.01) and a
two-way interaction (F (3, 45) = 5.37, p < 0.05). Again, the mismatch responses did not differ
across the four conditions (all ps > 0.05). In the match responses, however, response times for
SVO were significantly faster than those for VOS and OVS (t (15) = 4.20, p < 0.01; t (15) =
3.92, p < 0.01). Participants responded significantly faster to VSO than OVS (t (15) = 3.49, p
Event-related brain indices of gap-filling processing in Kaqchikel
11
< 0.01). Although the response times for VSO ware also numerically shorter than those for
VOS, the difference did not reach a significant level (t (15) = 1.74, p = 0.15).
3.6.2. Electrophysiological Data
3.6.2.1. SVO versus VOS
Figure 4 shows the grand average ERPs in the third region of SVO and VOS. A visual
inspection suggested that the ERPs of SVO showed a greater positivity compared with those
of VOS.
The ANOVA showed significant main effects of WORD ORDER in all arrays without any
interaction in the time window of 100300 ms. A significant two-way interaction was
observed in the midline and temporal arrays in 300500 ms. Post-hoc analyses revealed
significant effects at Pz and P7/8 (Pz: F (1, 15) = 5.73, p < 0.05; P7/8: F (1, 15) = 5.39, p <
0.05). In the later time windows, there was no significant main effect or interaction of interest
in any array. These results indicate that the most frequent word order, SVO elicited a greater
positivity compared to the syntactically basic word order, VOS.
Table 2. Statistical results for the third region of SVO versus VOS.
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
Word Order
F-value 12.95 11.41 5.33 1.18 1.02 0.29 0.72 0.47 0.17 0.03 < 0.01 0.04
Significance ** ** * n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
WO × Anteriority
F-value 2.33 0.25 1.13 3.08 2.36 5.25 0.37 0.53 1.10 1.00 1.17 1.51
Significance n.s. n.s. n.s. + n.s. * n.s n.s. n.s. n.s. n.s. n.s.
WO × Laterality
F-value 1.79 1.60 0.53 0.55 1.25 2.75 1.26 2.65
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
WO × A × L
F-value 0.84 2.14 0.45 0.56 0.22 0.57 0.11 0.67
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
100–300 ms
300–500 ms
500–700 ms
700–900 ms
Note: n.s.: p > .10, +: p < .10, *: p < .05, **: p < .01, ***: p < .005, ****: p < .001
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
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Figure 4. The grand average ERPs for the third region of SVO and VOS. The blue line
indicates SVO and the black line indicates VOS. The X-axis represents time duration, and
each hash mark represents 100 ms. The Y-axis represents the voltage, which ranges from -5
to 5 µV. Negativity is plotted upward. The topographical voltage maps represent the mean
difference calculated as SVO minus VOS for every 100 ms from 300 to 800 ms after the
onset of the third region.
One may think that these positivities appeared so early at the third region that they did
not reflect filler-gap integration processes, which have been assumed to be performed in the
P600 time window (5001000 ms). Accordingly, we also analysed ERPs time-locked to the
onset of the first region to assess the ERP difference of the second region of VOS and SVO,
though the words of the second region were categorically different (i.e., O of VOS and V of
SVO). The repeated measures ANOVA revealed a significant main effect of WORD ORDER
without any interaction in the temporal array in the time window of 15001700 ms
(corresponding approximately 500700 ms after the onset of the second region) (Table 3).
Event-related brain indices of gap-filling processing in Kaqchikel
13
Table 3. Statistical results for the second and third regions of SVO versus VOS.
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
midline lateral temporal
Word Order
F-value 0.02 < 0.01 4.77 0.10 0.14 1.21 2.04 0.77 4.57 4.86 3.50 7.01 8.50 6.21 9.36
Significance n.s. n.s. * n.s. n.s. n.s. n.s. n.s. * * + * * * *
WO × Anteriority
F-value 0.43 0.87 0.51 0.87 0.37 < 0.01 1.58 1.22 0.51 3.28 0.02 0.01 4.32 0.06 0.01
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. + n.s. n.s. * n.s. n.s.
WO × Laterality
F-value 0.92 2.70 0.15 3.76 < 0.01 5.10 0.34 3.53 3.08 0.93
Significance n.s. n.s. n.s. + n.s. * n.s. + + n.s.
WO × A × L
F-value 0.39 0.02 0.31 0.05 0.22 0.10 0.13 0.32 0.09 0.65
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
Word Order
F-value 8.05 7.28 11.52 8.55 9.91 9.34 7.21 8.49 10.00 6.10 6.59 10.79
Significance * * ** * ** ** * * ** * * **
WO × Anteriority
F-value 3.56 0.14 0.06 4.43 0.16 0.76 4.20 0.46 0.85 4.01 0.43 0.41
Significance * n.s. n.s. * n.s. n.s. * n.s. n.s. * n.s. n.s.
WO × Laterality
F-value 4.37 0.22 2.21 1.54 2.32 1.18 1.08 1.26
Significance + n.s. n.s. n.s. n.s. n.s. n.s. n.s.
WO × A × L
F-value 0.38 0.48 0.05 0.83 0.14 0.51 0.32 0.37
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
1900–2100 ms
1100–1300 ms
1300–1500 ms
1500–1700 ms
1700–1900 ms
2100–2300 ms
2300–2500 ms
2500–2700 ms
2700–2900 ms
Note: n.s.: p > .10, +: p < .10, *: p < .05, **: p < .01, ***: p < .005, ****: p < .001
In 17001900 ms, a significant main effect of WORD ORDER was observed in the midline
and temporal array, and the marginally significant main effect was observed in the lateral
array. The main effect in the midline interacted with ANTERIORITY (F (2, 30) = 3.28, p = 0.05),
suggesting that the larger positivity for SVO distributed at the central (Cz) and posterior (Pz)
region rather than the frontal region (Fz) (Fz: F (1, 15) = 0.52, p > 0.10; Cz: F (1, 15) = 7.60, p
< 0.05; Pz: F (1, 15) = 5.10, p < 0.05). The two-way interaction of WORD ORDER ×
LATERALITY approached a level of significance (F (1, 15) = 3.53, p = 0.07) in the temporal
array, reflecting the fact that the positivity was pronounced at the right hemisphere (F (1, 15)
= 12.22, p < 0.05) rather than the left hemisphere (F (1, 15) = 1.97, p = 0.11). The WORD
ORDER effect did not interact with other topographical factors in the lateral arrays. In the later
time windows corresponding to the third region (19002100 ms, 21002300 ms, 23002500
ms, 25002700 ms, 27002900 ms), main effects of WORD ORDER were consistently
significant, due to greater positivity for SVO compared with VOS. A significant interaction of
WORD ORDER and ANTERIORITY was also observed in the midline in these time windows,
reflecting a pronounced positivity at the centro-parietal sites (19002100 ms: Cz: F (1, 15) =
11.72, p < 0.01; Pz: F (1, 15) = 11.09, p < 0.01, 21002300 ms: Cz: F (1, 15) = 8.76, p < 0.01;
Pz: F (1, 15) = 9.60, p < 0.01; 23002500 ms: Cz: F (1, 15) = 9.01, p < 0.01; Pz: F (1, 15) =
12.47, p < 0.01; 25002700 ms: Cz: F (1, 15) = 9.52, p < 0.01; Pz: F (1, 15) = 7.49, p < 0.05;
27002900 ms: Cz: F (1, 15) = 8.90, p < 0.01; Pz: F (1, 15) = 5.57, p < 0.05). These results
suggest that the late posterior positivity for SVO appeared at the second region, which
increased in amplitude at the third region.
3.6.2.2. VSO versus VOS
Figure 5 shows the grand average ERPs in the third region of VSO and VOS.
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
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Figure 5. The grand average ERPs for the third region of VSO and VOS. The red line
indicates VSO and the black line indicates VOS. The X-axis represents time duration, and
each hash mark represents 100 ms. The Y-axis represents the voltage, which ranges from -5
to 5 µV. Negativity is plotted upward. The topographical voltage maps represent the mean
difference calculated as VSO minus VOS for every 100 ms from 300 to 800 ms after the
onset of the third region.
Table 4. Statistical results for the third region of VSO versus VOS.
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
Word Order
F-value 2.27 2.02 0.73 0.28 0.50 0.08 1.14 2.78 1.85 0.03 0.07 0.43
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
WO × Anteriority
F-value 2.77 1.97 4.55 8.12 10.94 9.73 5.19 6.06 7.81 2.33 2.73 4.53
Significance + n.s. * ** *** ** * ** ** n.s. + *
WO × Laterality
F-value 1.21 0.05 8.96 0.74 2.55 0.15 4.75 1.91
Significance n.s. n.s. ** n.s. n.s. n.s. * n.s.
WO × A × L
F-value 3.66 2.33 1.21 0.01 1.06 0.15 0.58 0.49
Significance * n.s. n.s. n.s. n.s. n.s. n.s. n.s.
100–300 ms
300–500 ms
500–700 ms
700–900 ms
Note: n.s.: p > .10, +: p < .10, *: p < .05, **: p < .01, ***: p < .005, ****: p < .001
Event-related brain indices of gap-filling processing in Kaqchikel
15
In the comparison of VSO and VOS, the effects of interest were not observed in the
second region in any array. In the third region, on the other hand, VSO elicited a posterior
positivity compared to VOS. In the time window of 100300 ms, two-way interactions of
WORD ORDER and ANTERIORITY were significant in the midline and temporal arrays,
reflecting a positive deflection at Pz and P7/8 (Pz: F (1, 15) = 4.51, p = 0.05; P7/8: F (1, 15) =
6.48, p < 0.05). In 300500 ms, the two-way interaction revealed a frontal negativity at F7/8
(F (1, 15) = 4.54, p < 0.05) and a significant posterior positivity at P7/8, and O1/2 (P7/8: F (1,
15) = 6.26, p < 0.05; O1/2: F (1, 15) = 5.26, p < 0.05). In 500700 ms, VSO elicited a
significant positivity at Pz, P3/4, P7/8, and O1/2 (Pz: F (1, 15) = 4.95, p < 0.05; P3/4: F (1,
15) = 5.41, p < 0.05; O1/2: F (1, 15) = 12.71, p < 0.01). The P7/8 electrodes also showed a
significant effect in the time window of 700900 ms (F (1, 15) = 7.10, p < 0.05). The main
effect of WORD ORDER did not reach a significant level in any time window. These results
indicate that VSO was harder to process than VOS.
3.6.2.3. SVO versus OVS
Figures 6 and 7 show the grand average ERPs in the second and third region of SVO and
OVS, respectively. Visual inspection suggests that, in the second region, OVS elicited a
positivity compared to SVO, which in turn elicited a greater (frontal) positivity than OVS in
the third region.
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
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Figure 6. The grand average ERPs for the second region of OVS and SVO. The green line
indicates OVS and the blue line indicates SVO. The X-axis represents time duration, and each
hash mark represents 100 ms. The Y-axis represents the voltage, which ranges from -5 to 5
µV. Negativity is plotted upward. The topographical voltage maps represent the mean
difference calculated as OVS minus SVO for every 100 ms from 300 to 800 ms after the
onset of the second region.
Table 5. Statistical results for the second region of SVO versus OVS.
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
Word Order
F-value 1.77 3.37 1.62 0.14 0.53 0.10 2.00 2.45 0.77 0.39 0.96 0.18
Significance n.s. + n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
WO × Anteriority
F-value 1.76 1.43 2.59 1.65 2.88 2.51 1.76 3.22 6.64 4.06 5.99 10.01
Significance n.s. n.s. n.s. n.s. + n.s. n.s. + * * * **
WO × Laterality
F-value 0.16 0.67 0.17 2.69 0.09 1.27 0.40 5.31
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. *
WO × A × L
F-value 0.38 0.14 1.24 1.69 1.07 1.35 0.83 0.31
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
100–300 ms
300–500 ms
500–700 ms
700–900 ms
Note: n.s.: p > .10, +: p < .10, *: p < .05, **: p < .01, ***: p < .005, ****: p < .001
Event-related brain indices of gap-filling processing in Kaqchikel
17
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Figure 7. The grand average ERPs for the third region of SVO and OVS. The blue line
indicates SVO and the green line indicates OVS. The X-axis represents time duration, and
each hash mark represents 100 ms. The Y-axis represents the voltage, which ranges from -5
to 5 µV. Negativity is plotted upward. The topographical voltage maps represent the mean
difference calculated as SVO minus OVS for every 100 ms from 300 to 800 ms after the
onset of the third region.
Table 6. Statistical results for the third region of SVO versus OVS.
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
midline lateral
temporal
Word Order
F-value 4.58 1.94 1.29 0.08 < 0.01 0.02 1.43 0.49 1.00 0.93 0.37 2.16
Significance * n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
WO × Anteriority
F-value 1.84 2.88 1.44 1.66 1.13 0.33 4.71 4.89 2.88 2.63 3.97 2.64
Significance n.s. n.s. n.s. n.s. n.s. n.s. * * + + * n.s.
WO × Laterality
F-value 0.11 0.84 0.08 0.95 0.42 3.27 < 0.01 0.63
Significance n.s. n.s. n.s. n.s. n.s. + n.s. n.s.
WO × A × L
F-value 0.45 0.42 0.02 0.13 0.10 0.11 0.41 0.20
Significance n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
100–300 ms
300–500 ms
500–700 ms
700–900 ms
Note: n.s.: p > .10, +: p < .10, *: p < .05, **: p < .01, ***: p < .005, ****: p < .001
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
In line with the visual inspection, the two-way interaction of WORD ORDER and
ANTERIORITY was marginally significant in the lateral array in 300500 ms of the second
region, reflecting a positivity for OVS at O1/2 (F (1, 15) = 3.33, p = 0.08). The two-way
interaction of WORD ORDER × ANTERIORITY was significant in the temporal array and
marginally significant in the lateral array in 500700 ms. Post-hoc analyses showed
significant effects at P7/8 and O1/2, and marginal effects at C3/4 and P3/4 (P7/8: F (1, 15) =
6.40, p < 0.05; O1/2: F (1, 15) = 6.83, p < 0.05; C3/4: F (1, 15) = 3.42, p = 0.08; P3/4: F (1,
15) = 4.09, p = 0.06). In the time window of 700900 ms, the WORD ORDER × ANTERIORITY
interaction was significant in all arrays, due to significant effects at Pz, P3/4, P7/8, and O1/2
(Pz: F (1, 15) = 5.22, p < 0.05; P3/4: F (1, 15) = 5.85, p < 0.05; P7/8: F (1, 15) = 9.36, p <
0.01; O1/2: F (1, 15) = 8.28, p < 0.05).
In the third region, SVO showed a significant positivity at Fz, and a marginally
significant positivity at F3/4 and F7/8 in 500700 ms time window (Fz: F (1, 15) = 5.76, p <
0.05; F3/4: F (1, 15) = 4.19, p = 0.05; F7/8: F (1, 15) = 3.28, p = 0.09). The analysis of 700
900 ms time window showed a significant effect at Fz and a marginally significant effect at
F3/4 (Fz: F (1, 15) = 5.30, p < 0.05; F3/4: F (1, 15) = 4.08, p = 0.06). These results indicate
that OVS elicited a posterior positivity compared with SVO in the second region, whereas the
effect was reversed in the third region. In the comparison of the first region of SVO and OVS,
there was no significant difference in any array.
4. DISCUSSION
Through the investigation of whether the syntactically canonical VOS word order is
preferred to other grammatically available word orders during sentence comprehension, the
present experiment explored the relation between syntactic complexities and processing
complexities. Our prediction was borne out by the results of the ERP experiment, which
demonstrated that SVO elicited a greater positivity in the comparison to VOS in the second
and third regions. Furthermore, VSO elicited a similar posterior positivity compared to VOS
in the third region. OVS showed a greater positive shift than SVO in the second region,
whereas the opposite pattern was observed as had been expected. These results clearly
indicate that VOS is the easiest word order among the grammatically possible word orders in
Kaqchikel, which was in line with our previous findings (Yasunaga et al., 2015). In other
words, (V)OS preference was observed in Kaqchikel during sentence comprehension,
providing empirical support for what we have called the individual grammar theory. If the SO
preference that has been observed in the sentence comprehension of many languages is
attributed to the universal aspect of human cognition, a P600 effect would appear in the VOS
sentences, which is, however, incompatible with our results regarding P600 patterns.
Therefore, the SO preference in sentence comprehension may not reflect a universal aspect of
human languages; rather, processing preference may be language-specific to some extent,
reflecting syntactic differences in individual languages.
Notably, however, slightly different results from Yasunaga et al. (2015) were obtained in
the current experiment with respect to the timing of P600 in the comparison of VOS and VSO.
Yasunaga et al. (2015), which used a picture-sentence matching task, reported a P600 effect
for VSO in the second region (i.e., S of VSO), whereas we observed a P600 effect for VSO in
the third region, in which the parser encountered a filler that had to be associated with the gap
Event-related brain indices of gap-filling processing in Kaqchikel
19
position (i.e., [V gapi S] Oi]). Because the picture and auditory stimuli used in the present
experiment were the same as those in Yasunaga et al., the difference of these results pertains
to the relative order of the picture and auditory stimuli, namely, the availability of context
prior to the sentence. In the present experiment, where there is no useful explicit context, the
participants cannot know the lexical item of the filler upon encountering S of VSO; the
participants must wait for the filler, O, to associate the filler with the gap location and
confirm semantic compatibility between the filler and the verb. Therefore, P600 was observed
in the third region, reflecting the increased gap-filling cost. On the other hand, the preceding
visual context in Yasunaga et al.’s experiment may have encouraged their participants to
predict O of VSO because the picture depicts the transitive event with an agent (S) and a
patient (O). If so, the participants can predictively build the syntactic structure of [V gapi S]
Oi] and check semantic compatibility between the filler and the verb to facilitate efficient
sentence processing. Accordingly, P600 was elicited in the second region, reflecting the
predictive gap-filler association process. If this is the case, it implies that the parser can
predictively associate a filler that is unseen but highly predictable with a gap site in the gap-
filler dependency as long as there is a non-linguistic context that is useful for identifying the
lexical item of the filler (see also Yano et al., 2014 for similar discussion). In an alternative
view, it is plausible that the picture presentation could trigger an expectation for VOS
sentences, although there is no specific prediction for a sentence form without contextual
information. If VOS is predicted prior to hearing a sentence, the second regionS of VSO
leads to an expectation mismatch, inducing a tentative conflict between the picture and the
sentence. To reconcile this conflict, syntactic reanalysis was required and P600 was elicited in
the second region in Yasunaga et al.’s experiment. This view may be supported by their
observation that P600 effect for VSO was preceded by a small N400 effect enhanced by
lexico-semantic surprisal (Yasunaga et al., 2015).
Another intriguing result comes from the response times in the behavioural sentence-
picture matching task. Although the (V)OS advantage in Kaqchikel sentence processing has
been observed as discussed above, response times for the picture were faster for SVO than
VOS. This is somewhat surprising given that SVO incurred an enhanced processing cost at
the sentence-final position due to the gap-filling process. VSO also showed a similar
tendency for SO advantage relative to VSO, although the numeric difference between VSO
and VOS did not reach a significant level. While some explanations are possible for this
different preference, a possible explanation concerns the relative order of the agent and the
patient. In our experimental materials, the subject and object corresponded to the agent and
patient of the action, respectively. Assuming that the agent-patient order is favoured in event
apprehension of the picture (see Sauppe al., 2013), the SO word order may have an advantage
in checking potential mismatches between the picture and the sentence. Because there is no
direct evidence for this conjecture at the present time, future experiments recording gaze
locations and EEGs are necessary to examine the relationship between sentence
comprehension and event apprehension.
5. CONCLUSION
Word-order preference during Kaqchikel sentence comprehension was investigated using
event-related potentials. The major finding of the present study is that the syntactically
Masataka Yano, Daichi Yasunaga and Masatoshi Koizumi
canonical word order, VOS, is easier to process than the most frequent word order, SVO, and
other grammatically available word orders, suggesting that the SO word-order preference
may not be universal across human languages. Rather, the present study shows that
processing complexities are closely tied to the syntactic complexities, reflecting filler-gap
integration processes indexed by P600 effects. From a broader perspective, the present study
sheds light on the importance of cross-linguistic psycholinguistic research to uncover
universal and language-particular aspects of the human language faculty. The issue of
whether the OS preference can be observed in other languages awaits further cross-linguistic
investigation.
ACKNOWLEDGEMENT
We are grateful to Lolmay Pedro Oscar García Mátzar, Juan Esteban Ajsivinac Sian,
Yoshiho Yasugi, and the participants in our experiment for their invaluable support for our
research in Guatemala. This study was supported by JSPS KAKENHI Grant Number
15H02603 (PI: Masatoshi Koizumi).
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In both written and spoken forms, the Sinhalese language allows all six possible word orders for active sentences with transitive verbs (i.e., SOV, OSV, SVO, OVS, VSO, and VOS), even though its unmarked order is subject-object-verb (SOV) (e.g., Gair, 1998; Miyagishi, 2003; Yamamoto, 2003). Reaction times for sentence correctness decisions showed SOV < SVO = OVS = OSV = VSO = VOS for the written form, and SOV < SVO = OVS < OSV = VSO = VOS for the spoken form. The different degrees of reaction times may correspond to the three different types of word order alternation. First, the fastest reaction time for SOV word order corresponds to the canonical order SOV without any structural change, represented as [TP S [VP O V] ] for both the written and spoken forms. Second, word order alternation at the same structural level is involved in both SVO and OVS, [TP S [VP t1 V O1] ] for SVO and [TP t1 [VP O V ] S1 ] for OVS, resulting in a slower reaction speed than SOV. Third, and again for only the spoken form, word order alternation takes place at a different structural level, [TP’ O1 [TP S [VP t1 V ] ] ] for OSV, [TP’ V1 [TP S [VP O t1] ] ] for VSO, and double word order alternations take place within the same level as [TP t1 [VP t2 V O2] S1] for VOS. These word order alternations for OSV, VSO and VOS require an extra cognitive load for sentence processing, even heavier than for a single word order alternation of SVO and OVS taking place at the same structural level. The present study thus provided evidence that the speed of sentence processing can be predicted from the cognitive load involved in word order alternation in a configurational phrase structure.
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This study investigated the processing load of transitive sentences in two different basic word orders (i.e., VOS and SVO) in Kaqchikel Maya, with a particular focus on the animacy of the object. The results of a sentence plausibility judgment task showed that VOS sentences were processed faster than SVO sen- tences regardless of the animacy of the object. This supports the traditional analysis in Mayan linguistics that, although SVO is the most frequently used word order, the syntactically determined basic word order is VOS in Kaqchikel, as in many other Mayan languages. More importantly, the results suggest that the processing load in Kaqchikel sentence comprehension is more strongly affected by syntactic canonicity than production frequency or object animacy.
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Kaqchikel is one of approximately thirty Mayan languages spoken in Belize, Guatemala, Mexico, and, increasingly, the United States. Of the twenty-two Mayan languages spoken in Guatemala, Kaqchikel is one of the four "mayoritarios," those with the largest number of speakers. About half a million people living in the central highlands between Guatemala City and Lake Atitlán speak Kaqchikel. And because native Kaqchikel speakers are prominent in the field of Mayan linguistics, as well as in Mayan cultural activism generally, Kaqchikel has been adopted as a Mayan lingua franca in some circles. This innovative language-learning guide is designed to help students, scholars, and professionals in many fields who work with Kaqchikel speakers, in both Guatemala and the United States, quickly develop basic communication skills. The book will familiarize learners with the words, phrases, and structures used in daily communications, presented in as natural a way as possible, and in a logical sequence. Six chapters introduce the language in context (greetings, the classroom, people, the family, food, and life) followed by exercises and short essays on aspects of Kaqchikel life. A grammar summary provides in-depth linguistic analysis of Kaqchikel, and a glossary supports vocabulary learning from both Kaqchikel to English and English to Kaqchikel. These resources, along with sound files and other media on the Internet at ekaq.stonecenter.tulane.edu, will allow learners to develop proficiency in all five major language skills-listening comprehension, speaking, reading, writing, and sociocultural understanding.
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