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Cognitive loads and time courses related to word order preference in Kaqchikel sentence production: an NIRS and eye-tracking study

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The word order that is easiest to understand in a language generally coincides with the word order most frequently used in that language. In Kaqchikel, however, there is a discrepancy between the two: the syntactically basic VOS incurs the least cognitive load, whereas SVO is most frequently employed. This suggests that processing load is primarily determined by grammatical processes, whereas word order selection is affected by additional conceptual factors. Thus, the agent could be conceptually more salient than other elements even for Kaqchikel speakers. This hypothesis leads us to the following expectations: (1) utterance latency should be shorter for SVO sentences than for VOS sentences; (2) Kaqchikel speakers should pay more attention to agents than to other elements during sentence production; and (3) despite these, the cognitive load during sentence production should be higher for SVO than for VOS. A Kaqchikel sentence production experiment confirmed all three expectations.
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Cognitive loads and time courses related to
word order preference in Kaqchikel sentence
production: an NIRS and eye-tracking study
Masatoshi Koizumi, Yasuhiro Takeshima, Ryo Tachibana, Riku Asaoka, Godai
Saito, Keiyu Niikuni & Jiro Gyoba
To cite this article: Masatoshi Koizumi, Yasuhiro Takeshima, Ryo Tachibana, Riku Asaoka,
Godai Saito, Keiyu Niikuni & Jiro Gyoba (2019): Cognitive loads and time courses related to word
order preference in Kaqchikel sentence production: an NIRS and eye-tracking study, Language,
Cognition and Neuroscience, DOI: 10.1080/23273798.2019.1650945
To link to this article: https://doi.org/10.1080/23273798.2019.1650945
© 2019 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group
Published online: 05 Aug 2019.
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REGULAR ARTICLE
Cognitive loads and time courses related to word order preference in Kaqchikel
sentence production: an NIRS and eye-tracking study
Masatoshi Koizumi
a,b,c
, Yasuhiro Takeshima
d
, Ryo Tachibana
e
, Riku Asaoka
f
, Godai Saito
g
, Keiyu Niikuni
h
and
Jiro Gyoba
g
a
Department of Linguistics, Graduate School of Arts & Letters, Tohoku University, Sendai, Japan;
b
Harvard-Yenching Institute, Cambridge, USA;
c
National Institute for Japanese Language and Linguistics, Tachikawa, Japan;
d
Department of Psychology, Doshisha University, Kyoto, Japan;
e
Department of Psychology, Queens University, Kingston, Canada;
f
College of Human and Social Sciences, Kanazawa University, Ishikawa,
Japan;
g
Department of Psychology, Graduate School of Arts & Letters, Tohoku University, Sendai, Japan;
h
Department of Clinical Psychology,
Niigata Seiryo University, Niigata, Japan
ABSTRACT
The word order that is easiest to understand in a language generally coincides with the word order
most frequently used in that language. In Kaqchikel, however, there is a discrepancy between the
two: the syntactically basic VOS incurs the least cognitive load, whereas SVO is most frequently
employed. This suggests that processing load is primarily determined by grammatical processes,
whereas word order selection is aected by additional conceptual factors. Thus, the agent could
be conceptually more salient than other elements even for Kaqchikel speakers. This hypothesis
leads us to the following expectations: (1) utterance latency should be shorter for SVO sentences
than for VOS sentences; (2) Kaqchikel speakers should pay more attention to agents than to
other elements during sentence production; and (3) despite these, the cognitive load during
sentence production should be higher for SVO than for VOS. A Kaqchikel sentence production
experiment conrmed all three expectations.
ARTICLE HISTORY
Received 29 August 2018
Accepted 24 July 2019
KEYWORDS
Word order preference;
processing load; sentence
production; utterance
latency; VOS language
1. Introduction
Languages dier in terms of the order in which the
subject (S), the object (O), and the verb (V) are aligned
in sentences. In English, for example, most transitive
declarative sentences follow the SVO order, and the
other orders are either quite rare or impossible. In
other languages, word order is more exible with mul-
tiple possibilities being allowed. Japanese employs SOV
and OSV; all the six logically possible orders are actually
used in Finnish; and so on. It has been observed, in many
exible as well as rigid word order languages, that the
syntactically basic word order is easier to process than
the other grammatically possible word orders (derived
word orders) (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, Kan-
duboda, & Sakai, 2011 for Sinhalese).
1
In Japanese, for
example, sentences with the syntactically basic SOV
order are processed faster than comparable OSV sen-
tences according to various psycholinguistic studies
using sentence plausibility judgment tasks (Chujo,
1983; Tamaoka et al., 2005), self-paced reading
(Koizumi & Imamura, 2017; Shibata et al., 2006), and
eye tracking (Mazuka et al., 2002; Tamaoka et al., 2005).
Neurolinguistic studies have also shown a similar proces-
sing advantage of the syntactically basic word order.
Functional magnetic resonance imaging (fMRI) studies
have found a higher activation of the left inferior
frontal gyrus (IFG) while processing derived word
orders when compared to basic word orders (Grewe
et al., 2007 for German, Kim et al., 2009 and Kinno, Kawa-
mura, Shioda, & Sakai, 2008 for Japanese). Furthermore,
studies with event-related potentials (ERPs) have
revealed that relative to syntactically basic word orders,
derived word orders elicit a late positivity eect called
P600 and/or (sustained) anterior negativity (Erdocia,
Laka, Mestres-Missé, & Rodriguez-Fornells, 2009 for
Basque, Rösler, Pechmann, Streb, Roeder, & Hennighau-
sen, 1998 for German, Ueno & Kluender, 2003 and Hagi-
wara, Soshi, Ishihara, & Imanaka, 2007 for Japanese).
This basic word order advantage has also been
observed in sentence production, as syntactically basic
word orders are more frequently used than are derived
© 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution-N onCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/
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any way.
CONTACT Masatoshi Koizumi koizumi@tohoku.ac.jp
LANGUAGE, COGNITION AND NEUROSCIENCE
https://doi.org/10.1080/23273798.2019.1650945
word orders. For instance, Imamura and Koizumi (2011)
reported that among Japanese transitive sentences
with a nominal subject and a nominal object in the
corpus of novels they studied, more than 97% followed
the SOV word order. This shows that although Japanese
is said to be a free word order languageor aexible
word order language, the SOV order is strongly pre-
ferred to the OSV order in sentence production. Higher
rates of basic word order utterances have been reported
in many other exible languages as well (Slobin & Bever,
1982 for Turkish and Serbo-Croatian, Hakulinen & Karls-
son, 1980 for Finnish, Bates, 1976 for Italian).
As articulated by Tamaoka and Koizumi (2006), one
possible interpretation of this correlation between the
syntactically basic word order, the word order easiest
to understand, and the word order most frequently
employed has to do with syntactic complexity. The syn-
tactically basic word order in a language, by denition,
is associated with simpler syntactic structures than the
other grammatically possible orders in that language. It
is, therefore, less demanding in terms of working-
memory load, and is hence easier to process (cf.
Gibson, 2000; Hawkins, 2004; Marantz, 2005;OGrady,
1997; Pritchett & Whitman, 1995; Tamaoka et al., 2005).
That is, syntactic complexity aects the processing load
in the sense that the former partially determines the
latter. Processing load, in turn, aects production fre-
quency because, all other things being equal, a structure
that is easier to process is more likely to be used than one
which is more dicult to process. As speakers of the
language are more procient in sentence structures
and words that are used frequently, they are more
likely to process these with greater speed and accuracy,
and hence, production frequency also aects processing
load. This model is schematically shown in Figure 1.
In some languages, however, there is a discrepancy
between these three kinds of word orders (Brody, 1984;
Koizumi et al., 2014). Kaqchikel, a Mayan language
spoken in Guatemala, is a case in point. It is a head-
marking and morphologically ergative language in
which subjects and objects are not overtly case-marked
for grammatical relations. Rather, grammatical relations
are obligatorily marked on predicates, for example, a
verb with two sets of agreement morphemes, one set
for a transitive subject and another for a transitive
object and an intransitive subject. The word order of Kaq-
chikel is relatively exible, and all the logically possible
six word orders are grammatically allowed. Among
these, VOS is considered the basic word order of Kaqchi-
kel by many Mayan language researchers (Ajsivinac Sian,
García Matzar, Cutzal, & Alonzo Guaján, 2004; Tichoc et
al., 2000; García Matzar & Rodríguez Guaján, 1997; Rodrí-
guez Guaján, 1994). SVO is another commonly used word
order. For the purpose of the present study, we assume
the schematic syntactic structures shown in (1) below,
in which VOS is structurally simpler than the other orders.
(1) Order Schematic syntactic structure
VOS [VOS]
SVO [S
i
[VO gap
i
]]
VSO [[V gap
i
S] O
i
]
OVS [O
i
[V gap
i
S]]
Sentence comprehension studies with behavioural
indices (Kiyama, Tamaoka, Kim, & Koizumi, 2013;
Koizumi et al., 2014), fMRI (Koizumi & Kim, 2016), and
ERPs (Yano, Yasunaga, & Koizumi, 2017; Yasunaga,
Yano, Yasugi, & Koizumi, 2015) have all observed that
the syntactically basic VOS is easier to process than
SVO and other derived word orders in Kaqchikel.
Despite the fact that VOS is the syntactically basic word
order and the easiest to understand among grammati-
cally possible word orders in Kaqchikel, it is the SVO
order that is most frequently used in this language
(England, 1991; Kubo, Ono, Tanaka, Koizumi, & Sakai,
2015; Maxwell & Little, 2006; Rodríguez Guaján, 1994).
According to Kubo et al. (2015), for instance, of all the
sentences with a transitive verb and nominal subject
and object produced in their sentence-production exper-
iment with a picture-description task, sentences with the
SVO, VOS, and VSO orders constituted 74.4%, 24.2%, and
1.4%, respectively. In fact, not just in Kaqchikel but in
many other Mayan languages as well, word orders in
which subjects are preposed appear more frequently
than the syntactically determined basic word order.
The question is why this should be the case at all.
Koizumi et al. (2014) suggested that three conceivable
factors combined together contribute toward the higher
production ratio of SVO sentences.
2
The rst has to do
with the head-marking nature of Kaqchikel. As men-
tioned earlier, Kaqchikel is a head-marking language
that exhibits subject and object agreement markers on
the verb. The verbal complex of a transitive sentence
Figure 1. Relationship among syntax, processing, and frequency.
(Adopted from Tamaoka & Koizumi, 2006).
2M. KOIZUMI ET AL.
contains information on the person and the number of
the subject and object. Therefore, in Kaqchikel, having
a verbal complex in the sentence-initial position may
be advantageous in that it helps develop predictions of
the upcoming subject and object, rendering the proces-
sing of the subsequent portion of the sentence easier. In
case of sentence production, in contrast, verb-initial
word orders in Kaqchikel may be more disadvantageous
than nominal-initial word orders such as SVO. This is
because in order to initiate a sentence with a verbal
complex, conceptual and grammatical information on
the subject and object must have been activated and
processed to a certain degree, prior to the beginning
of the utterance (Figure 2). For this reason, therefore,
subject-initial sentences may be easier to initiate than
verb-initial sentences for Kaqchikel speakers, and
hence, SVO is produced more frequently than VOS
and VSO.
A second possible factor for the preference of SVO in
sentence production is concerned with the saliency of
subjects.There are two interrelated but dierent ways
in which relative conceptual saliencies aect word
order selection in sentence production. First, conceptual
factors may directly aect word order selection (De
Smedt, 1990; Kempen & Hoenkamp, 1987; Myachykov
& Tomlin, 2008; Tanaka, Branigan, McLean, & Pickering,
2011). The order of word retrieval from the mental
lexicon at the stage of grammatical processing may be
determined by the availability of individual concepts at
the stage of conceptual processing, and the structure
of the sentence being generated is accordingly con-
strained by whichever word is retrieved rst. In other
words, conceptually more accessible entities may claim
early word order positions irrespective of grammatical
function. In this respect, SVO is preferred over VOS in
Kaqchikel partly because of the relatively higher concep-
tual saliency of the agent directly inuencing the word
order of utterances in Kaqchikel. Second, conceptual
factors may also inuence the way in which grammatical
functions are assigned, which, in turn, indirectly aects
word order choice through the mediation of the
grammar of a particular language (Bock & Warren,
1985; Lee, Brown-Schmidt, & Watson, 2013; McDonald,
Bock, & Kelly, 1993). It has been observed in many
languages that subjects tend to become topics of con-
versation more easily than other immediate sentence
constituents, and topics tend to appear at the beginning
of sentences. Indeed, in Mayan languages, constituents
that appear before verbs are often interpreted as the
topic of the utterance, and the observation that there
is a syntactically designated position for topic before
verbs is widely supported (Aissen, 1992; England, 1991;
García Matzar & Rodríguez Guaján, 1997). This means
that although VOS is syntactically the basic word order
and induces a lower processing load, SVO is used more
frequently in conversation because the agent, being con-
ceptually salient, is likely to be assigned to the gramma-
tical roles of subject and topic, and a topicalized subject,
in turn, is placed in the preverbal position according to
the grammar of Kaqchikel (Tichoc et al., 2000; Ajsivinac
Sian et al., 2004).
Finally, the similarity-based competitionmay con-
tribute to the frequency of SVO. Gennari, Mirković, and
MacDonald (2012)argued that when there is a temporal
overlap in the planning of two conceptually similar
nouns, the similarity leads to interference between the
semantic information of the nouns. As a result, when
the concept of one noun is activated, the concept of
the other noun is inhibited, and the latter is mentioned
away from the initially activated noun, or simply
omitted in the sentence. Moreover, the eect of concep-
tual similarity interacts with language-specic grammati-
cal constraints, and the actual instantiation may vary
across languages. Kubo et al. (2015) examined how simi-
larity-based competition inuences speakerschoices of
sentence patterns in Kaqchikel. The production of VOS
sentences is interesting because the most accessible
element, an animate agent noun usually realised as the
subject, must be retained in memory until the end of
the sentence, and hence, it potentially competes with
other elements. If similarity-based competition arises
between the subject and object in Kaqchikel, one of
them must be realised away from the other. Since the
object usually follows the verb in Kaqchikel, the increase
in competition would lead to the decrease of VOS word
order. Kubo et al. (2015) conducted two picture
Figure 2. A schematic model of language processing.
LANGUAGE, COGNITION AND NEUROSCIENCE 3
description experiments to verify this prediction. In these
experiments, the animacy of the patient noun was
manipulated (human, animal, inanimate object) such
that similarity between the agent (human) and patient
varied among conditions. The results showed that VOS
sentences were produced more often with an inanimate
patient than with an animal or human patient, as pre-
dicted by similarity-based competition. Speakers of Kaq-
chikel, therefore, seem to be sensitive to the competition
caused by the similarity of noun concepts involved in an
event described in the sentence. They select the sen-
tence pattern in order to resolve competition between
nouns with similar concepts.
The above considerations taken together lead us to
the following expectations. First, if subject-initial sen-
tences are easier to initiate than verb-initial sentences
in Kaqchikel because of its head-marking nature and
the conceptual saliency of the agent, then utterance
latency should be shorter for SVO than for VOS in Kaqchi-
kel. Second, if the agent is conceptually more salient than
other entities even for speakers of VOS languages, Kaq-
chikel speakers should pay more attention to agents
than to other elements during sentence production.
Third, despite these, the cognitive load during sentence
production should be higher for SVO sentences than for
VOS sentences because the production of a sentence
surely includes, as its central part, the construction of lin-
guistic representations, and the grammatical processes
involved in this are presumably similar to those involved
in the comprehension of a parallel sentence, although
there may be some dierences (Momma & Phillips,
2018). Additionally, it is interesting to observe how the
animacy of the patient may or may not inuence time
course and cognitive load in Kaqchikel sentence pro-
duction. In particular, the similarity-based competition in
the sense of Gennari et al. (2012) would incur some cog-
nitive load in VOS sentences compared to SVO sentences.
This factor should impede the production processes of
VOS compared to SVO especially when the subject and
object are similar to each other (e.g. both are human). If
this is so, we would expect the interaction of the eect
of syntactic complexity and that of similarity-based com-
petition: the dierence between SVO and VOS, in cogni-
tive load, should be smaller when the event is reversible
(i.e. the human agent is acting on the human patient)
than when the event is non-reversible (i.e. the human
agent acting on the inanimate patient).
In this study, we report a sentence production exper-
iment with a picture description task conducted to test
these predictions by measuring the utterance latencies,
eye movements, and cortical activations of Kaqchikel
speakers. The results conrmed all but the last expec-
tation, as reported in detail below.
Before presenting the details of the current Kaqchikel
production study, we will briey discuss, as a basis for
comparison, a parallel study we had conducted previously
with Japanese speakers (Takeshima et al., 2014), and
another relevant study on a Mayan language, Tzeltal, by
Norclie, Konopka, Brown, and Levinson (2015).
In the experiment reported in Takeshima et al. (2014),
participants (native speakers of Japanese) described pic-
tures of simple transitive events involving familiar char-
acters and actions while their gaze, speech, and brain
activation were recorded. The results revealed that the
utterance latency was shorter in the SOV condition (i.e.
SOV sentences) than in the OSV condition (OSV sen-
tences). The brain activities for the SOV order were
lower compared with that for the OSV order at the left
inferior frontal gyrus (IFG). In both conditions, the relative
xation times were higher for the agent than for the
patient during the rst 700 ms after the onset of the
picture presentation (see Figure 3). The period of the
rst several hundred milliseconds (until around 400
600 ms) after picture onset arguably corresponded to
event apprehension at the stage of conceptual proces-
sing (Grin & Bock, 2000; Norclie et al., 2015,
Figure 2; but see also Gleitman, January, Nappa, & Trues-
well, 2007). Therefore, this pattern of eye movement
conrmed the saliency and early processing of agent at
the stage of conceptual processing in Japanese sentence
production. To summarise, all the three indices con-
verged to indicate the processing advantage of the syn-
tactically basic word order in Japanese.
Norclieetal.(2015) conducted a similar eye-tracked
picture description experiment with native speakers of
Tzeltal. They found an animacy eect on word order pre-
ference parallel to the ndings in Kubo et al. (2015): verb-
initial word order was more frequent when the event was
non-reversible compared to when the event was revers-
ible. While producing SVO sentences Tzeltal speakers
xated preferentially on the rst-mentioned character
(i.e. the agent) before speech onset and xated preferen-
tially on the second-mentioned character (i.e. the patient)
after speech onset. However, in the formulation of VOS
orders, speakersattention and gaze were more evenly
distributed across the two characters, with a smaller
advantage of agent than while producing SVO orders.
We now turn to the Kaqchikel sentence production
experiment.
2. Materials and methods
2.1. Participants
Eighteen native speakers of Kaqchikel (9 females and 9
males) participated in this experiment. Five participants,
4M. KOIZUMI ET AL.
whose accuracy of word order was below 60%, were
excluded from the nal analysis. We, thus, eventually
analyzed 13 participants (8 females, 5 males; mean age
± SD = 31.5 years ± 11.2). All of the 13 participants were
Kaqchikel-Spanish bilinguals (age of acquisition of
Spanish: 5.6 years ± 3.5), and spoke Kaqchikel as the
primary language at home. All of them were classied
as right-handed based on the Edinburgh Handedness
Inventory (Oldeld, 1971), and had normal or
corrected-to-normal vision. The present study was
approved by the Ethics Committee of the Graduate
School of Arts and Letters, Tohoku University. All partici-
pants provided written informed consent prior to their
participation.
2.2. Apparatus
The experimental methods used were the same as those
in the Japanese experiment reviewed above (Takeshima
et al., 2014). During the experiment, the participants sat
in front of an LCD display (Tobii; Tobii TX300 screen
unit; resolution: 1024 × 768 pixels; refresh rate: 60 Hz).
The viewing distance was approximately 60 cm. The
experiment was controlled by E-Prime 2.0 with E-Prime
Extensions for Tobii (Psychology Software Tools, Inc.)
and a PC (Dell: Precision T7500). We used a voice recor-
der (Olympus: Voice Trek DS-850), an eye tracker (Tobii;
Tobii TX300; sampling rate: 300 Hz), and a multi-
channel NIRS system (Shimadzu: FOIRE-3000) to record
the participantsutterances, eye movements, and the
relative concentration changes in oxygenated, deoxyge-
nated, and total hemoglobin (oxy-Hb, deoxy-Hb, and
total-Hb, respectively) in the blood. The NIRS instrument
exploits the optimal properties of oxy-Hb and deoxy-Hb
forms with dierent absorption spectra in the near infra-
red (NIR) wavelength region. By using two NIR wave-
lengths (780 and 830 nm) and applying data analyses
based on the modied LambertBeer law, this instru-
ment measures the above indices (Homae, Watanabe,
Nakano, & Taga, 2007). A whole-head probe cap was
used. The probes were placed over the prefrontal
cortex of each hemisphere, each consisting of a 4 × 3
array with 6 emitters and 6 detectors, constituting 17
channels per hemisphere (see Figure 4 below). We
arranged these probes in reference to the international
1020 system: the locations of the 5th receiver and
Figure 3. Relative xation time during the picture presentation for (a) canonical SOV utterances and (b) scrambled OSV utterances in
Japanese. The black vertical lines represent speech onset. (Adopted from Takeshima et al., 2014).
Figure 4. Locations of the probes used in NIRS measurements.
LANGUAGE, COGNITION AND NEUROSCIENCE 5
15th emitter were arranged at T8 and T7, respectively.
The sampling rate of each channel was 10 Hz.
2.3. Stimuli
We prepared 20 pictures (1024 × 724 pixels) depicting a
two-character transitive event. Half the pictures
showed human agents acting on human patients, and
the other half showed human agents acting on inani-
mate patients. The agent was depicted on the left side
and the patient on the right side. In order to counterba-
lance the locations, we also prepared 20 pictures that
were mirror images of the originals. These 40 pictures
were the same as those used in the previous Japanese
study (Takeshima et al., 2014).
2.4. Procedure
The participants were given instructions in Kaqchikel by
an experimenter who is a native speaker of Kaqchikel.
Before the experiment, the participants observed the pic-
tures provided as stimuli in a random order and
described the events depicted in the pictures using tran-
sitive sentences in Kaqchikel. If the participants could not
utter the content or if they interpreted the content incor-
rectly, the experimenter explained the picture. After this
session, the participants were tted with NIRS probes
and the nine-point eye tracking calibration was
performed.
Each trial began with the presentation of a xation
cross for 8000 ms, followed by an instructional display
of word order for 5000 ms (Figure 5). A short beeping
sound was presented for 500 ms simultaneously with
the onset of this instructional display to use in utterance
latency analysis. The Kaqchikel word Banöl subjector
Banoj verbwas shown in the instructional display.
After the instructional display, a picture was presented
for 8000 ms. The participants were instructed to describe
the event in the picture as concisely as possible in Kaq-
chikel, starting with the subject after the Banöl display
or the verb after the Banoj display. Thus, it was expected
that the participants would produce Kaqchikel sentences
in the SVO and VOS orders after the Banöl and Banoj dis-
plays, respectively. The xation cross appeared again
after the picture display. The participants performed a
total of 40 trials, with 20 pictures per word order. The
agent was depicted on the left side in 10 pictures, and
on the right side in the other 10 pictures.
2.5. Analysis
We excluded data from trials in which participants could
not produce utterances of the instructed type. This led to
the removal of 30.19% of all data.
3
We calculated the utterance latency for each con-
dition using Sound Engine (http://soundengine.jp/). The
latency was dened as the interval between the onset
of the picture presentation and the starting point of
the participants utterance. Interjections, such as Lets
see,were not included in the utterance.
The gaze data were aggregated into 50 ms time bins.
For each bin, we then calculated the probability of looks
at the agent and patient during the time allotted to each
picture (8 s) using area of interest (AOI) analysis. There
was no signicant dierence in size between the AOI
for agent and the AOI for patient (agent AOI =
168289.8 ± 39.55 pixels, patient AOI = 168281.2 ± 40.94
pixels, p= .54) (Figure 6).
For the statistical analysis, we used a target advantage
score (Kronmüller & Barr, 2015), which is typically dened
as the probability of looks at the target object minus the
probability of looks at the non-target object (see, for
instance, Symeonidou, Dumontheil, Chow, & Breheny,
2016). Here, we designated the agent entity on a
picture as the targetand the patient entity as the
non-target,so that a higher score indicated that the
participant looked more at the agent entity than the
patient.
We focused on oxy-Hb as an index of neural activation
because it is more sensitive to changes in the regional
cerebral blood ow than deoxy-Hb and total-Hb concen-
trations (Hoshi, 2003). The raw oxy-Hb data were high-
pass ltered at 0.02 Hz to remove signal drift (Taga,
Asakawa, Maki, Konishi, & Koizumi, 2003). Data were
averaged for each participant and each condition and
converted into z-scores (Otsuka et al., 2007; Schroeter,
Zysset, Kruggel, & von Cramon, 2003), so that the mean
values and standard deviations for the base line period
(5 s before picture presentation) were 0 and 1, respect-
ively. We averaged the oxy-Hb values during the
Figure 5. Schematic representation of the procedure in the
present experiment.
6M. KOIZUMI ET AL.
picture presentation period (8000 ms). We analyzed the
same channels as in the Japanese study, that is, channels
29, 30, 32, and 33, which were estimated as including the
left dorsolateral prefrontal cortex and the left IFG. Some
previous NIRS studies have reported that the oxy-Hb
values in these regions were increased by the cognitive
load in language-related tasks such as picture naming,
word uency, and sentence correctness judgment
(Kovelman et al., 2009; Noguchi, Takeuchi, & Sakai,
2002; Watanabe et al., 1998).
3. Results
3.1. Utterance latency and duration
The utterance latency results are shown in Table 1.We
conducted a two-way analysis of variance (ANOVA)
with word order (2: SVO vs. VOS) and patient animacy
(2: animate vs. inanimate) as the within-participant
factors. The analyses revealed a signicant main eect
of word order (F(1, 12) = 18.37, p< .01,
h
2
p= .60), indicat-
ing that utterance latency was shorter in the SVO con-
dition than in the VOS condition. On the other hand,
the main eect of patient animacy (F(1, 12) = 0.03, p
= .87,
h
2
p= .00) and the interaction (F(1, 12) = 0.01, p
= .93,
h
2
p= .00) were not signicant. In other words, utter-
ance latency was not modulated by patient animacy.
We also calculated the utterance durations and oset
times (Tables 2 and 3). The utterance durations did not
dier signicantly among the dierent conditions: the
main eect of word order (F(1, 12) = 0.58, p= .46,
h
2
p
= .05), the main eect of patient animacy (F(1, 12) =
1.48, p= .25,
h
2
p= .11), and the interaction (F(1, 12) =
0.13, p= .73,
h
2
p= .01). As for the utterance osets, a sig-
nicant main eect of word order was found (F(1, 12) =
8.52, p< .05,
h
2
p= .42), indicating that the utterances
ended earlier in the SVO condition than in the VOS con-
dition. On the other hand, neither the main eect of
Figure 6. An example of AOI setting. The left AOI covers the agent area, and the right AOI covers the patient area, with the sizes of the
two AOIs being comparable.
Table 1. The means and standard deviations of utterance latency
(ms) for word order and patient animacy conditions.
Patient animacy
Animate Inanimate
SVO 1921 (265) 1919 (219)
VOS 2246 (411) 2230 (404)
Note: n= 13. The values in parentheses indicate the standard deviation.
Table 2. The means and standard deviations of utterance
duration (ms) for word order and patient animacy conditions.
Patient animacy
Animate Inanimate
SVO 2950 (1006) 2781 (741)
VOS 3000 (1122) 2907 (789)
Note: n= 13. The values in parentheses indicate the standard deviation.
Table 3. The means and standard deviations of utterance oset
(ms) for word order and patient animacy conditions.
Patient animacy
Animate Inanimate
SVO 4871 (1102) 4700 (768)
VOS 5247 (1410) 5137 (940)
Note: n= 13. The values in parentheses indicate the standard deviation.
LANGUAGE, COGNITION AND NEUROSCIENCE 7
patient animacy (F(1, 12) = 1.09, p= .32,
h
2
p= .08) nor the
interaction (F(1, 12) = 0.05, p= .83,
h
2
p= .00) was signi-
cant. This pattern of the utterance oset time parallels
that of the utterance latency.
3.2. Eye movement
We analyzed the data for 6000 ms from picture onset
because the mean utterance osets were less than
6000 ms (see Table 3 and Figure 9). The time courses
of the target advantage score for each experimental con-
dition are shown in Figure 7.
We divided the data into six 1000-ms time windows
(see Figure 7) and conducted three-way by-participant
(F
1
) and by-item (F
2
) ANOVAs, using word order (2),
patient animacy (2), and time window (6: 01000 ms,
10002000 ms, 20003000 ms, 30004000 ms, 4000
5000 ms, 50006000 ms) as independent variables. The
mean target advantage score for the corresponding
1000-ms time window was taken as the dependent vari-
able. Greenhouse-Geisser corrections were used where
applicable.
The ANOVAs demonstrated a signicant main eect
of word order (F
1
(1, 12) = 20.05, p< .01,
h
2
p= .63; F
2
(1,
18) = 6.80, p< .05,
h
2
p= .27), a signicant main eect of
time window (F
1
(5, 60) = 9.20, p< .01,
h
2
p= .43; F
2
(5,
90) = 11.43, p< .01,
h
2
p= .39), and a signicant interaction
between word order and time window (F
1
(5, 60) = 5.20,
p< .01,
h
2
p= .30; F
2
(5, 90) = 8.64, p< .01,
h
2
p= .32). The
interaction between animacy and time window was sig-
nicant in the by-participant analysis but not in the by-
item analysis (F
1
(5, 60) = 5.20, p< .05,
h
2
p= .24; F
2
(5,
90) = 1.55, p= .21,
h
2
p= .08). The main eect of animacy
(F
1
(1, 12) = 1.89, p= .19,
h
2
p= .14; F
2
(1, 18) = 0.23, p
= .64,
h
2
p= .01), the interaction between word order
and animacy (F
1
(1, 12) = 1.42, p= .26,
h
2
p= .11; F
2
(1,
18) = 2.60, p= .12,
h
2
p= .13), and the three-way inter-
action (F
1
(5, 60) = 1.11, p= .36,
h
2
p= .08; F
2
(5, 90) =
1.83, p= .14,
h
2
p= .09) were not found to be signicant.
Since the interaction between word order and time
window was signicant, we conducted follow-up ana-
lyses to test the simple-main eects of word order for
each time window. The analyses revealed that the
simple-main eect of word order was signicant for the
10002000 ms time window (F
1
(1, 12) = 14.72, p< .01,
h
2
p= .55; F
2
(1, 18) = 11.46, p< .01,
h
2
p= .39). This indi-
cated that, for this time window, the target advantage
score was higher in the SVO word order condition than
in the VOS condition. The simple-main eect was also
signicant for the 30004000 ms window (F
1
(1, 12) =
16.33, p< .01,
h
2
p= .58; F
2
(1, 18) = 15.29, p< .01,
h
2
p
= .46), and approached signicance for the 4000
5000 ms window (F
1
(1, 12) = 4.49, p= .06,
h
2
p= .27; F
2
(1, 18) = 13.53, p< .01,
h
2
p= .43). Contrary to the case of
the 10002000 ms window, the target advantage
scores were higher in the VOS condition than in the
SVO condition for 30004000 ms and 40005000 ms
windows. For the 01000 ms window (F
1
(1, 12) = 0.58,
p= .46,
h
2
p= .05; F
2
(1, 18) = 5.31, p< .05,
h
2
p= .23), the
simple-main eect was signicant in the by-item analysis
but not in the by-participant analysis. No signicant
simple-main eects were found for the 20003000 ms
(F
1
(1, 12) = 1.97, p= .19,
h
2
p= .14; F
2
(1, 18) = 0.97,
p= .34,
h
2
p= .05) and 50006000 ms (F
1
(1, 12) = 2.68,
p= .13,
h
2
p= .18; F
2
(1, 18) = 1.72, p= .21,
h
2
p= .09)
windows.
We also tested simple-main eects of time window for
each word order condition. The analyses found a signi-
cant simple-main eect of time window in the SVO
condition (F
1
(5, 60) = 12.21, p< .01,
h
2
p= .50; F
2
(5, 90)
= 21.42, p< .01,
h
2
p= .54): a multiple comparison
(Holms method) revealed (i) that the target advantage
score of the 01000 ms window was signicantly
higher than that of the 20003000 ms (p
1
< .01, p
2
< .01), 30004000 ms (p
1
< .01, p
2
< .01), and 4000
5000 ms (p
1
< .05, p
2
< .01) windows, and (ii) that the
target advantage score of the 10002000ms window
was signicantly higher than that of the 20003000 ms
−1.0
−0.5
0.0
0.5
1.0
0 2000 4000 6000
time from picture onset (ms)
target advantage score
patient animacy / word order
animate / SVO
animate / VOS
inanimate / SVO
inanimate / VOS
Figure 7. Mean target advantage scores (the proportion of looks to the agent the proportion of looks to the patient) for each exper-
imental condition. The vertical dotted lines represent the boundaries of the time windows which were used for statistical analyses.
8M. KOIZUMI ET AL.
(p
1
< .01, p
2
< .01), 30004000 ms (p
1
< .01, p
2
< .01), and
40005000 ms (p
1
< .05, p
2
< .01) windows. The dier-
ences between the 01000 ms and 50006000 ms
windows, between the 10002000ms and 5000
6000 ms windows, between the 30004000 ms and
40005000 ms windows, and between the 3000
4000 ms and 50006000 ms windows were signicant
in the by-item analysis but not in the by-participant
analysis (p
1
s > .05, p
2
s < .05). No other signicant dier-
ences between time windows were found in both the
by-participant and by-item analyses (p
1
s, p
2
s > .05), in
the SVO condition. In the VOS condition, no signicant
simple-main eect of time window was found (F
1
(5,
60) = 2.02, p= .09,
h
2
p= .14; F
2
(5, 90) = 2.39, p= .07,
h
2
p= .12).
In addition to the ANOVAs, we performed one-sample
t-tests, which compare the target advantage score with a
zero value (i.e. examine whether the score is signicantly
positive or negative). Since the analyses were conducted
separately for each time window, we will report the
p-values adjusted by the Holms method. The analyses
revealed that the target advantage scores were signi-
cantly positive in the 01000 ms (t
1
(12) = 18.39, p< .01;
t
2
(19) = 5.17, p< .01), 10002000ms (t
1
(12) = 7.59,
p< .01; t
2
(19) = 6.36, p< .01), 40005000 ms (t
1
(12) =
4.38, p< .01; t
2
(19) = 3.45, p< .01), and 50006000 ms
(t
1
(12) = 4.73, p< .01; t
2
(19) = 4.48, p< .01) windows.
The target advantage scores did not signicantly dier
from zero in the 20003000 ms (t
1
(12) = 2.53, p< .05; t
2
(19) = 1.95, p= .13) and 30004000 ms windows (t
1
(12)
= 2.85, p< .05; t
2
(19) = 1.54, p= .14).
Furthermore, we conducted the same one-sample
t-tests for each word order condition. The analyses
revealed that in the SVO condition, target advantage
scores were signicantly positive in the 01000 ms (t
1
(12) = 17.69, p< .01; t
2
(19) = 5.75, p< .01), and 1000
2000ms (t
1
(12) = 7.87, p< .01; t
2
(19) = 8.09, p< .01)
windows. The target advantage scores did not signi-
cantly dier from zero in the 20003000 ms (t
1
(12) =
1.40, p= .37; t
2
(19) = 1.39, p= .36), 30004000 ms (t
1
(12) = 0.45, p= .66; t
2
(19) = 0.08, p= .94), 4000
5000 ms (t
1
(12) = 1.96, p= .22; t
2
(19) = 2.26, p= .11),
and 50006000 ms (t
1
(12) = 2.75, p= .07; t
2
(19) = 3.26,
p< .05) windows. On the other hand, in the VOS con-
dition, the target advantage score was signicantly
positive in all of the time windows (01000 ms: t
1
(12)
= 15.73, p< .01; t
2
(19) = 4.47, p< .01; 10002000ms: t
1
(12) = 6.21, p< .01; t
2
(19) = 4.13, p< .01; 20003000 ms:
t
1
(12) = 3.65, p< .01; t
2
(19) = 2.32, p< .05; 3000
4000 ms: t
1
(12) = 4.37, p< .01; t
2
(19) = 3.17, p< .05;
40005000 ms: t
1
(12) = 7.49, p< .01; t
2
(19) = 4.97,
p< .01; 50006000 ms: t
1
(12) = 6.20, p< .01; t
2
(19) =
5.60, p< .01).
3.3 Brain activity
The averaged z-scores of the oxy-Hb values in the inter-
ested channels are shown in Figure 8. A two-way ANOVA
with word order (2) × patient animacy (2) revealed a sig-
nicant main eect of word order only in ch-29 (F(1, 12)
= 5.08, p< .05,
h
2
p= .30), indicating that the participants
exhibited lower values in the VOS condition than the
SVO condition. The main eect of word order was not
signicant in the other channels (ch-30: F(1, 12) = 0.71,
p= .42,
h
2
p= .06; ch-31: F(1, 12) = 0.02, p= .90,
h
2
p= .02;
ch-33: F(1, 12) = 0.22, p= .65,
h
2
p= .02). Both the main
eect of patient animacy (ch-29: F(1, 12) = 1.45, p=.25,
h
2
p= .11; ch-30: F(1, 12) = 4.19, p= .06,
h
2
p= .26; ch-31:
F(1, 12) = 0.28, p= .61,
h
2
p= .02; ch-33: F(1, 12) = 0.00,
p= .97,
h
2
p= .00) and the two-way interaction (ch-29:
F(1, 12) = 0.15, p= .70,
h
2
p= .01; ch-30: F(1, 12) = 0.27,
p= .61,
h
2
p= .02; ch-31: F(1, 12) = 0.43, p= .53,
h
2
p= .03;
ch-33: F(1, 12) = 4.72, p= .05,
h
2
p= .28) were not signi-
cant in any of the four channels.
4. Discussion
We began this paper by stating the following four pre-
dictions (or expectations) drawn from the ndings in
previous studies. If subject-initial sentences are easier
to initiate than verb-initial sentences because of the
head-marking nature of Kaqchikel and the conceptual
saliency of the agent among speakers of Kaqchikel,
then (1) utterance latency should be shorter for SVO
than VOS sentences. If the agent is conceptually more
salient than the patient for speakers of Kaqchikel, (2)
they should pay more attention to the agent than to
the patient during sentence production. (3) Despite
(1) and (2), the cognitive load during sentence pro-
duction should be higher for SVO sentences than for
the corresponding VOS sentences, because the former
are syntactically more complex than the latter. Further-
more, if there occurs larger similarity-based competition
between the subject and the object in VOS than in SVO,
(4) the dierence between SVO and VOS in cognitive
load should be smaller in the inanimate patient con-
dition than in the human patient condition. The
results of the Kaqchikel experiment reported in the pre-
vious section conrmed all these predictions except the
last. This constituted empirical support for the con-
clusion that Kaqchikel speakers preferentially employ
the SVO word order at least partly because of the con-
ceptual saliency of the agent. However, SVO incurs a
greater cognitive load than the syntactically basic VOS
word order primarily due to its syntactic complexity
during both sentence production and sentence
comprehension.
LANGUAGE, COGNITION AND NEUROSCIENCE 9
The utterance latencies were shorter for SOV than OSV
in Japanese (Takeshima et al., 2014), and shorter for SVO
than VOS in Kaqchikel. What is common between these
results is that the subject-initial word orders had the
shorter utterance latencies, meaning that utterance
latency is not correlated with the syntactic complexity
of the entire utterance, as SOV is syntactically simpler
than OSV in Japanese and SVO is syntactically more
complex than VOS in Kaqchikel. The results fall in line
with the view that the conceptual saliency of the initial
constituent has a relatively large eect on how early
the utterance starts. Another possible factor in the
longer latency of VOS utterances in Kaqchikel is, as men-
tioned in the Introduction, the conceptually and mor-
phologically complex verb, with two agreement
markers for the subject and object that are required to
initiate such an utterance. This may also be a reason
why the dierence in utterance latency between the
two word orders is larger in Kaqchikel (SVO vs. VOS)
than in Japanese (SOV vs. OSV).
The conceptual saliency of the agent received further
support from the eye tracking data. Both Japanese and
Kaqchikel speakers initially xated on the agent prefer-
entially and continued to do so for most of the sub-
sequent time periods. An initial xation on the agent
Figure 8. Average peak concentration changes of oxyhemoglobin under the four conditions in the four channels, which are estimated
to be in the left dorsolateral prefrontal cortex and the left IFG. The error bars represent the standard errors of the means.
(b) VOS
(a) SVO
0 2000 4000 6000
0.0
0.2
0.4
0.6
0.8
1.0
0.0
0.2
0.4
0.6
0.8
1.0
time from picture onset (ms)
looks to AOI (prop.)
AOI
agent
patient
Figure 9. The proportion of looks to the agent/patient AOI
during the picture presentation for (a) SVO and (b) VOS utter-
ances. The black vertical (dotted) lines represent speech onset
(oset).
10 M. KOIZUMI ET AL.
was observed even when OSV sentences were being pro-
duced in Japanese, which shows that speakers initially
pay more attention to the agent (subject) than the
patient (object) regardless of the word order of the utter-
ance to be generated. While producing SVO sentences,
Kaqchikel speakers looked quickly at the agent, contin-
ued xating on this character until the onset of speech,
and nally shifted their gaze to the patient (Figure 9a).
Kaqchikel VOS sentences exhibited a dierent xation
pattern than either SVO sentences in Kaqchikel or SOV
and OSV sentences in Japanese. During the production
of the latter three types, speakers initially xated on
the agent and then shifted their attention to the
patient to some extent. In addition, the speakers in the
Japanese experiment nally reverted to the agent in
both the SOV and OSV conditions. During the production
of VOS sentences in Kaqchikel, however, such a bi- or tri-
phasic pattern was not observed. The relative ratios of
agent and patient xations were fairly uniform across
the entire time span (Figure 9b). This result is similar to
Norclie et al.s(2015) observation that the patterns of
eye xation during the conceptual encoding and linguis-
tic encoding periods dier between VOS and SVO sen-
tence production in Tzeltal. This suggests that, while
producing VOS sentences, Kaqchikel (and Tzeltal) speak-
ers process agent, patient, and action, as well as their cor-
responding linguistic representations, more in parallel
(or less linearly) than when producing SVO sentences.
This may be because initiating an utterance with a verb
in a head-marking language such as Kaqchikel requires
both agent and patient, as well as action, to have been
processed to a certain degree in order to determine
the form of the verb before its onset.
The brain activation data obtained using NIRS
revealed that the production of OSV utterances yielded
a higher left IFG activation than did the production of
SOV utterances in Japanese, and the production of SVO
utterances did the same with respect to VOS utterances
in Kaqchikel.
4
This clearly shows that sentences with a
syntactically derived word order require more cognitive
resources to represent than comparable sentences with
the syntactically basic word order in a given language
not only in sentence comprehension but also in sentence
production both in SO and OS languages.
Finally, we could not nd evidence for larger simi-
larity-based competition eects in VOS sentences than
SVO sentences. The NIRS data show that the dierences
in the cognitive loads between SVO and VOS sentences
are comparable in the human patient condition and
the inanimate patient condition. This is in line with the
results of Kiyama et al.s(2013) Kaqchikel sentence com-
prehension experiment that VOS was processed faster
than SVO regardless of the animacy of the object, and
that the eect of the object animacy and the interaction
between the word order and the object animacy were
not signicant. This indicates that the similarity-based
competition, if present, may not be the primary factor
for the higher production ratio of SVO in the reversible
event condition than in the non-reversible event con-
dition. Although it is beyond the scope of this paper to
elucidate the reasons for this eect of event reversibility
on word order preference, communicative approaches
such as the noisy channel hypothesis by Gibson et al.
(2013) and the role conict hypothesis by Hall, Mayberry,
and Ferreira (2013) seem to be a promising avenue to
pursue.
5. Conclusion
The results of the eye-tracked picture description exper-
iment reported in this paper support the conclusion that
although Kaqchikel speakers preferentially use the SVO
word order partly because of the saliency of the agent
and the complexity of the verbal predicate, SVO sen-
tences require more processing resources than do VOS
sentences both in comprehension and production.
Notes
1. The syntactically basic word order of a language is
dened here as the word order associated with the sim-
plest syntactic structures among grammatically possible
transitive sentences with a nominal subject and a
nominal object in that language. In Japanese, for
instance, the syntactically basic word order is SOV, and
OSV is derived from it by scrambling the object across
the subject. OSV sentences are, therefore, syntactically
more complex than are comparable SOV sentences, as
schematically shown in (i). In (ib) the fronted object
and the gap in the object position forms a ller-gap
dependency, which is lacking in (ia).
(1) [SOV]
(2) [O
i
[S gap
i
V]]
2. The rst two factors mentioned below are in line with the
general idea of availability-based models of sentence pro-
duction, according to which speakers favour sentence
structures in which more readily available words are
placed earlier. In contrast, eciency-based theories focus
more on ease of comprehension. See Ros, Santesteban,
Fukumura, and Laka (2015) for a review. See also
Koizumi et al. (2014) for the related notions of the univer-
sal cognitive view vs. the individual grammar view.
Koizumi et al. (2014) argue that the cognitive load
during sentence comprehension is primarily determined
by grammatical processes operating on linguistic rep-
resentations (in congruent with the individual grammar
view), whereas word order selection in sentence pro-
duction more faithfully reects event apprehension and
LANGUAGE, COGNITION AND NEUROSCIENCE 11
preverbal message construction at the stage of concep-
tual processing (consistent with the universal cognition
view).
3. The categories of utterances excluded from analysis and
their ratios in each of the SVO and VOS conditions are as
follows: transitive sentences in a word order other than
the specied one (SVO = 2.69 ± 3.30%, VOS = 8.08 ±
13.77%, p= .21), intransitive sentences (SVO = 6.15 ±
4.16%, VOS = 6.54 ± 6.25%, p= .75), adjectival sentences
(SVO = 11.92 ± 12.00%, VOS = 9.23 ± 7.87%, p= .25),
passive sentences (SVO = 0.38 ± 1.39%, VOS = 2.69 ±
8.32%, p= .35), antipassive sentences (SVO = 1.92 ±
3.84%, VOS = 4.23 ± 7.32%, p= .19), and others (SVO =
2.31 ± 3.88%, VOS = 1.92 ± 3.25%, p= .67). The removed
responses were equally distributed between the two
word order conditions, and there was no signicant
dierence in each category as shown above nor in
total (SVO = 25.38 ± 12.33%, VOS = 32.69 ± 16.28%, p
= .19).
4. The activated channel (channel 29) in this study and the
one (channel 32) reported in Takeshima et al. (2014) are
adjacent to each other. Although they are not the same,
given the relatively low spatial resolution and rough
spatial correspondence of the NIRS system, compared
to the magnetic resonance imaging system (Strangman,
Culver, Thompson, & Boas, 2002), it is reasonable to con-
clude that similar brain regions (i.e., regions in the left
IFG) activated in our current and previous studies. Note
that some previous studies have analyzed NIRS signals
by combining multi-channels responses together and
have interpreted global brain activities (e.g., Minagawa-
Kawai, Mori, Furuya, Hayashi, & Sato, 2002; Minagawa-
Kawai, Mori, Sato, & Koizumi, 2004). It is beyond the
scope of the present study to identify the precise locus
of activation.
Acknowledgment
Earlier versions of this paper were presented at the 68th
Meeting of the Tohoku Psychological Association (Akita Univer-
sity, Japan) and the 53rd Meeting of the Korean Society for Cog-
nitive and Biological Psychology (Jeju Island, Republic of Korea)
as well as MIT and Harvard University. We are grateful to the
participants and audience for their feedback and to two anon-
ymous reviewers for their insightful and instructive comments
on an earlier draft. We also thank Juan Esteban Ajsivinac Sian,
Filiberto Patal Majzul, Lolmay Pedro Oscar García Matzar, and
Yoshiho Yasugi for their invaluable support of the current
study throughout its various stages. This work was supported
in part by JSPS KAKENHI Grant Numbers 15H02603, 19H05589.
Disclosure statement
No potential conict of interest was reported by the authors.
Funding
This work was supported in part by Japan Society for the Pro-
motion of Science (JSPS) KAKENHI [grant numbers 15H02603,
19H05589].
ORCID
Masatoshi Koizumi http://orcid.org/0000-0003-0719-7128
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14 M. KOIZUMI ET AL.
... languages, but a few hints come from recent work on Kaqchikel, an endangered Mayan language spoken in Guatemala (Koizumi et al., 2014(Koizumi et al., , 2020Yasunaga et al., 2015;Koizumi and Kim, 2016). First, however, the following caveat should be noted. ...
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