ORIGINAL RESEARCH
published: 09 May 2017
doi: 10.3389/fpsyg.2017.00748

Dissociating Effects of Scrambling
and Topicalization within the Left
Frontal and Temporal Language
Areas: An fMRI Study in Kaqchikel
Maya
Shinri Ohta 1,2† , Masatoshi Koizumi 3 and Kuniyoshi L. Sakai 1,2*
Edited by:Ángel J. Gallego,
Autonomous University of Barcelona,
Spain
Reviewed by:John E. Drury,
Stony Brook University, USA
Kepa Erdocia,
University of the Basque Country,
Spain*Correspondence:
Kuniyoshi L. Sakai
sakai@mind.c.u-tokyo.ac.jp† Present address:

Shinri Ohta,
Department of Linguistics, Facultyof Humanities, Kyushu University,
6-19-1 Hakozaki, Higashi-ku,
Fukuoka-shi, Fukuoka, Japan
Specialty section:
This article was submitted toLanguage Sciences,a section of the journal
Frontiers in Psychology
Received: 19 November 2016
Accepted: 25 April 2017
Published: 09 May 2017
Citation:
Ohta S, Koizumi M and Sakai KL(2017) Dissociating Effectsof Scrambling and Topicalization
within the Left Frontal and Temporal
Language Areas: An fMRI Studyin Kaqchikel Maya.
Front. Psychol. 8:748.
doi: 10.3389/fpsyg.2017.00748

1
Department of Basic Science, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan, 2 Core
Research for Evolutionary Science and Technology, Japan Science and Technology Agency, Tokyo, Japan, 3 Department ofLinguistics, Graduate School of Arts and Letters, Tohoku University, Sendai, Japan

Some natural languages grammatically allow different types of changing word orders,such as object scrambling and topicalization. Scrambling and topicalization are more
related to syntax and semantics/phonology, respectively. Here we hypothesized thatscrambling should activate the left frontal regions, while topicalization would affect thebilateral temporal regions. To examine such distinct effects in our functional magnetic
resonance imaging study, we targeted the Kaqchikel Maya language, a Mayan language
spoken in Guatemala. In Kaqchikel, the syntactically canonical word order is verbobject-subject (VOS), but at least three non-canonical word orders (i.e., SVO, VSO,
and OVS) are also grammatically allowed. We used a sentence-picture matching task,
in which the participants listened to a short Kaqchikel sentence and judged whether
a picture matched the meaning of the sentence. The advantage of applying thisexperimental paradigm to an understudied language such as Kaqchikel is that it willallow us to validate the universality of linguistic computation in the brain. We found thatthe conditions with scrambled sentences [+scrambling] elicited significant activationin the left inferior frontal gyrus and lateral premotor cortex, both of which have been
proposed as grammar centers, indicating the effects of syntactic loads. In contrast,
the conditions without topicalization [−topicalization] resulted in significant activation inbilateral Heschl’s gyrus and superior temporal gyrus, demonstrating that the syntactic
and phonological processes were clearly dissociated within the language areas.
Moreover, the pre-supplementary motor area and left superior/middle temporal gyri wereactivated under relatively demanding conditions, suggesting their supportive roles insyntactic or semantic processing. To exclude any semantic/phonological effects of theobject-subject word orders, we performed direct comparisons while making the factor
of topicalization constant, and observed localized activations in the left inferior frontal
gyrus and lateral premotor cortex. These results establish that the types of scrambling

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Scrambling and Topicalization in Brainand topicalization have different impacts on the specified language areas. These findings
further indicate that the functional roles of these left frontal and temporal regions involve
linguistic aspects themselves, namely syntax versus semantics/phonology, rather than
output/input aspects of speech processing.
Keywords: language, syntax, word order, scrambling, topicalization, inferior frontal gyrus, lateral premotor
cortex, fMRI

specialized in the construction of complex meaning (Poeppel
et al., 2012), although effects of a movement of phrases havenot been previously examined by those studies. By directly
contrasting scrambled sentences with non-scrambled ones, therelative contribution of the L. F3op/F3t and L. ATL should beclarified.
Another type of movement is topicalization, in which, forexample, a subject (S) or an object outside a verb phrase
moves to a still structurally higher position to represent a
topic, i.e., information that has already been mentioned in
the discourse/context. In English, topicalization of an object
generates a non-canonical word order (Radford, 2009), such as“John read a book. That book, Mary read at school,” in which
a two-step movement of an object is involved. Here, the given
information is presented as a topic at the initial position of thesentence, which makes sentence comprehension easier. Indeed, asentence with the same movement of a non-topic noun phrase
becomes ungrammatical: “∗ A book, Mary read at school.” In
the absence of topicalization, semantic/phonological loads andgeneral auditory attention would become larger, because allwords should be attended without prior information, rather
than a particular topicalized word. Another possibility is thata topicalized sentence becomes semantically and phonologicallymarked, which may increase semantic/phonological loads incomparison with the canonical word order. By examining
both effects of [±topicalization] in brain activation, we
would be able to determine which of these effects is more
prominent.
While topicalization and scrambling are inseparable in rigid
word-order languages such as English and Hebrew, they become
separable in flexible word-order languages like Japanese. In thelatter case, the DoM domain can be restricted to the peripheral
structure of the topic and comment (i.e., the rest of the sentence),
and thus topicalization does not produce additional syntacticloads, because the DoM remains minimal. An ERP study using
topicalization and wh-questions in German reported that bothconstructions elicited a left-anterior negativity, which is typicallyinterpreted as indexing an increase in memory burden (Felser
et al., 2003). However, in German topicalized sentences, any
effects due to a two- or multiple-step movement of an object
should be considered, where the first-step of such a movement
involves scrambling just as OVS in Kaqchikel (see Figure 1A).
Moreover, topicalization may have enhanced memory burden,
since no specific context was provided for each presented
sentence in that study. Scrambling and topicalization are thus
more related to syntax and semantics/phonology, respectively.
According to psycholinguistic studies, the differences between
these two types of movements do not seem to affect behavioral

INTRODUCTION
There are natural languages that grammatically allow different
types of changing word orders (Karimi, 2003). This phenomenon
can be explained by movement of phrases, which is a key
operation proposed in modern linguistics. A word order withthe simplest syntactic structure is syntactically canonical, andword orders that are a result of a movement of phrases
are non-canonical. The notion of such canonicity, as well as
syntactic knowledge, is independent of the frequency/probabilityof usage, or learning of words (Chomsky, 1957). One typeof movement is object scrambling, where an object (O) tobe emphasized is extracted from the original position in a
verb phrase and moved to a structurally higher position,
skipping other phrases and resulting in more complex tree
structures. In this article, we refer to “object scrambling” assimply “scrambling.” Scrambling is not allowed in English, but
scrambled sentences are grammatical in Japanese. Although
there are information structure distinctions (e.g., emphasis)
related to scrambling, scrambling in Japanese does not change
the grammatical relations (e.g., subject, direct object, andindirect object) and semantic roles (e.g., agent, patient, andexperiencer) of a sentence (Fukui, 1993; Saito and Fukui,1998).
Our previous study using functional magnetic resonanceimaging (fMRI) revealed selective responses to scrambled
sentences in the left frontal regions: the opercular and triangularparts (L. F3op/F3t) of the left inferior frontal gyrus (IFG), as
well as the left lateral premotor cortex (L. LPMC) (Kinno et al.,2008). In our magnetoencephalography (MEG) study (Inubushi
et al., 2012), we observed the effects of canonicity in the left
IFG in response to more complex ditransitive sentences (i.e.,
those including a verb and two objects). We also demonstrated
that the Degree of Merger (DoM) accounted for syntax-selective
activations in the L. F3op/F3t (Ohta et al., 2013b). The DoM isthe maximum depth of merged subtrees (i.e., Mergers) within
an entire sentence, and it properly measures the complexityof tree structures. The DoM domain, i.e., the subtrees where
the DoM is calculated, is an entire sentence when there isno constraint, but this changes dynamically in accord withsyntactic operations and/or task requirements (Ohta et al.,2013a). Scrambling induces higher syntactic loads, because theDoM becomes at least one unit larger in accord with an additional
branch for an extracted object, where the DoM domain also
becomes larger covering entire sentences with a verb phrase(see Figure 6 of Ohta et al., 2013a). In addition to the L.
F3op/F3t and L. LPMC, some fMRI and MEG studies haveproposed that the left anterior temporal lobe (L. ATL) is also

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data (Sekerina, 2003). The use of fMRI would dissociate theeffects of these movements among multiple language areas.
Our previous studies have clarified that syntactic processing,i.e., movement or merger of phrases, activates the L. F3op/F3t(Kinno et al., 2008; Ohta et al., 2013a,b), while phonologicalloads and auditory attention activates the bilateral superior
temporal gyrus (STG) (Suzuki and Sakai, 2003). Based on thesestudies, we hypothesized that the main effects of scrambling
should activate the L. F3op/F3t and L. LPMC, while the main
effects of topicalization would affect the bilateral temporal
regions.
To dissociate the effects of [+scrambling] and[±topicalization], a flexible word-order language thatgrammatically allows four different word orders, i.e.,[±scrambling, ±topicalization], should be targeted, which
can be realized with Kaqchikel Maya (hereafter “Kaqchikel”),
a Mayan language spoken in Guatemala. To our knowledge,
the present study is the first to examine that [±scrambling]and [±topicalization] can be separated symmetrically within
participants, sessions, and a language. In Kaqchikel, thesyntactically canonical word order is verb-object-subject (VOS),
but at least three non-canonical word orders (i.e., SVO, VSO,
and OVS) are also grammatically allowed (Figure 1; García
Matzar and Rodríguez Guaján, 1997; Brown et al., 2006).
Previous neuroimaging and psycholinguistic studies havemainly targeted SO languages, where the S precedes the O ina canonical word order (e.g., SVO and SOV), such as English,
Japanese, and German. Sentences with the non-canonical OS
word order (e.g., scrambling) are more difficult to process
than those with the canonical word order, while keeping allother factors such as semantic roles equal (Marantz, 2005).
Indeed, fMRI studies have reported increased activation by
non-canonical word orders in the left IFG (Bahlmann et al.,2007; Kinno et al., 2008; Kim et al., 2009), which may reflect
the effects of scrambling. A neuroimaging study has describedthe enhanced neural effects of topicalization (Ben-Shachar et al.,2004), in which a two-step movement of an object is involved
in Hebrew sentences as in English and German. Because no
specific context was provided for each presented sentence inthat latter study, it is also possible that topicalization artificiallyenhanced syntactic and semantic/phonological processes. Suchan activation increase might be triggered by the OS word
order itself, which is related to one of “irregular prominence
factors of noun phrases,” such as Patient vs. Agent, Inanimate
vs. Animate, etc. (Bornkessel et al., 2005; Grewe et al., 2006).
To conclusively examine which of these accounts is correct
in fMRI experiments, we have targeted the OS language of
Kaqchikel, where the O precedes the S in a canonical word
order. If the last possibility is correct, and the activation increaseis triggered by the OS word order itself, then the canonicalword order in Kaqchikel (VOS) would elicit higher activations
than the non-canonical word order (VSO), which seems
unlikely. We predict that VSO elicits higher activations than
VOS.
Kaqchikel is a head-marking language, in which prefixes ofa verb (i.e., a head in a sentence) specify numbers (singular orplural) and persons (first, second, or third) of the object/subject,

FIGURE 1 | Scrambling and topicalization induce non-canonical word
orders. (A) A right-specifier model assumes specifiers positioned at the rightbranches outside the verb phrase (Aissen, 1992; Koizumi et al., 2014). The
VOS word order is syntactically canonical in Kaqchikel. Among the four
possible word orders, the VSO and OVS word orders include scrambling[+scrambling], whereas VOS and SVO do not [−scrambling]. The SVO andOVS word orders include topicalization [+topicalization], and VOS and VSO do
not [−topicalization]. The symbol ±S denotes the [±scrambling] condition,and ±T indicates the [±topicalization] condition, which are used in
Figures 3, 4. Scrambling (red arrow) and topicalization (blue arrow) areapplied in sequential steps in this order. Scrambling induces higher syntacticloads, because the DoM becomes at least one unit larger in accord with anadditional branch for an extracted object, where the DoM domain also
becomes larger, covering the entire sentence with the verb phrase. On theother hand, topicalization does not produce additional syntactic loads,
because the DoM remains always minimal, where the DoM domain isrestricted to the peripheral structure of the topic and comment. After these
movements, actual word orders (shown in black) are obtained. Gray lettersdenote the original positions of the phrases. (B) A predicate-fronting model. In
this model, scrambling in the right-specifier model is replaced with the notionof object shift. The predicate fronting is assumed as a default and obligatory
movement even for a canonical word order (Coon, 2010). A black rectangle
denotes a predicate in each sentence. Object shift (red arrow), predicate
fronting (green arrow), and topicalization (blue arrow) are applied in sequential
steps in this order. For the OVS word order, both models propose that theobject is further extracted while preserving the entire syntactic structures of
the VSO word order, denoted by a gray arrow and a gray square.

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Scrambling and Topicalization in Brainki-: plural for an ergative case, followed by a consonant-initial
stem.

whereas English, Japanese, and German are dependent-marking
languages, in which noun phrases (dependents) that depend
on a verb are always marked for subjects and objects whenpossible (like English pronouns). Regarding Mayan sentences,a right-specifier model has been proposed for the syntactic
structures of a sentence (Aissen, 1992; Koizumi et al., 2014),
assuming specifiers positioned at the right branches outside theverb phrase VO, in addition to specifiers of a complementizer
phrase (e.g., “that”) positioned at the left branches (Figure 1A).
For the canonical word order (VOS), the S is a specifier
positioned at a right branch. Moreover, for the VSO and OVS
word orders, scrambling of the O results in a right-specifier. On
the other hand, for the SVO and OVS word orders, topicalizationof the S or O results in a left-specifier of a complementizer
phrase. These four word orders thus have the following factors:
VOS [−scrambling, −topicalization], SVO [−scrambling,+topicalization], VSO [+scrambling, −topicalization], OVS[+scrambling, +topicalization]. Another linguistic study has
proposed an alternative model, i.e., a predicate-fronting model(Figure 1B; Coon, 2010), which is basically consistent with theright-specifier model and will be discussed later.
Based on our earlier investigations (Kinno et al., 2008,2014), we used here a modified sentence-picture matching task,
in which each participant listened to a Kaqchikel sentence
and judged whether a picture matched the meaning of thesentence (Figure 2). The advantage of applying this experimental
paradigm to an understudied language such as Kaqchikel is that it
will allow us to validate the universality of linguistic computationin the brain.

MATERIALS AND METHODS
Participants
We recruited 20 Kaqchikel speakers, who lived in Chimaltenango,
Sololá, or Sacatepéquez (the Departamentos of Guatemala).
They spoke the Northern, Western, or Southern Kaqchikel
dialects spread in these regions (six, nine, or two participants
for each dialect, respectively). Recruiting Kaqchikel speakers
for the present fMRI experiment was challenging, because
they were not accustomed to being the participants ofexperiments and felt fatigue due to the unfamiliar environmentin Tokyo during their week-long stay. One participant retired
from the experiment after the second run. Two participants
whose accuracy under the OVS condition was <75% were
excluded from the subsequent behavioral and fMRI analyses.
We eventually analyzed 17 participants (7 males, 10 females;mean ± standard deviation [SD] age [years]: 32 ± 7.9),
who correctly achieved >75% correct answers under each of
the four sentence conditions. This criterion was based on amodel-based clustering analysis (Fraley and Raftery, 2002), in
which the classification into two clusters showed the highest
likelihood.
All of the 17 participants were Kaqchikel-Spanish bilinguals(age of acquisition of Spanish: 4.9 ± 2.8 years), who showed
right-handedness (laterality quotient: 72 ± 28) as determinedby the Edinburgh Handedness Inventory (Oldfield, 1971).
None had a history of neurological disease. There were three
Kaqchikel speakers from Patzún (a town in Guatemala) in
the present study. A linguistic study of Kaqchikel reported
that speakers in Patzún prefer a subject-initial word orderin transitives and intransitives (e.g., SVO, SV), and that theytend to interpret the VOS word order as an interrogative
sentence (Clemens, 2013). However, interrogative sentences can
be clearly distinguished by a rise in intonation (García Matzar andRodríguez Guaján, 1997), and there was no interrogative sentencein our stimuli.
Thirteen participants acquired Kaqchikel from infancy,
and the other four participants acquired Kaqchikel fromthe age of 5–8 years (age of acquisition of Kaqchikel:
2.4 ± 2.4 years). These four participants did not show
any significant differences in the performance accuracy of
the task compared to those who acquired Kaqchikel from
infancy (two sample t-tests; [t(66) = 0.065, p = 0.95]).
These four participants showed even shorter RTs [t(66) = 3.6,
p = 0.0007], i.e., better performances. Moreover, a sub-analysis
excluding these four participants showed basically similar
activation patterns for the main effects of scrambling andtopicalization.
During the experiments, translation was realized both ways
through a Japanese-Spanish translator and a Spanish-Kaqchikeltranslator. To minimize the effects of Spanish usage during theexperiment, we explained the stimuli and tasks to the participantsin Kaqchikel through these translators. Prior to participation inBASICS OF KAQCHIKEL SYNTAXKaqchikel is an ergative language, in which a subject of atransitive verb is marked by an ergative case, whereas an objectof a transitive verb, as well as a subject of an intransitive
verb, is marked by an absolutive case; here we used transitive
verbs alone, with absolutive and ergative cases. The order ofmorphemes in a transitive verb is fixed as [Aspect-B-A-Verbstem] (Koizumi et al., 2014). In Kaqchikel syntax, ergative casemarkers are called set A, and absolutive case markers are called
set B. As an “Aspect”
prefix, we used a completive marker “xR(pronounced [ ])” alone (similar to a suffix -ed or -en as a perfectparticiple in English). Each set further makes agreement of
number (singular and plural) and person (first, second, and third)
between a verb and object/subject (i.e., absolutive/ergative). In
the present study, we used only third persons with the following
prefixes:
φ- (unmarked): singular for an absolutive case,e-: plural for an absolutive case,r-: singular for an ergative case, followed by a vowel-initialstem,
ru-: singular for an ergative case, followed by a consonantinitial stem,k-: plural for an ergative case, followed by a vowel-initial stem,
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FIGURE 2 | An experimental paradigm with various grammatical word orders in Kaqchikel. (A) A sentence-picture matching task (marked in red). We tested
four task conditions based on the different word orders: VOS, SVO, VSO, and OVS; the VOS is the canonical word order, and the others are non-canonical word
orders that are always grammatical. Each sentence with one of these word orders is auditorily presented, and a simultaneously presented picture consisted of asingle man and two men with the same or different colors (white, blue, red, or black). The participants judged whether a picture matched the meaning of thesentence. For each example sentence in Kaqchikel and its word-by-word translation in English, a pair of matched and mismatched pictures are shown in the firstand second rows, respectively. For display purposes, the blue and white words match the blue and white men in the pictures of the first row, respectively. (B) A
color-picture matching task (the control task; marked in blue). Examples of matched and mismatched stimuli are shown in the left and right panels of the third row,
respectively. The participants judged whether the colors in a picture matched the color words in the auditory stimuli, irrespective of their order. (C) Reaction times(RTs) from the onset of the picture for the sentence-picture and control tasks. Only correct trials were included. Error bars indicate the standard error of the mean
(SEM) for the participants. ∗ Corrected p < 0.05. (D) Accuracy for the sentence-picture and control tasks.

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both of the color and number were changed from associatedsentences. Half of the pictures depicted actions occurring fromleft to right, and the other half depicted actions occurring fromright to left; colors of the single man and two men were alsocounterbalanced for both sides. The complexity of the pictures,
as well as the frequency of action/color/number, was perfectly
controlled among the sentence conditions.
All visual stimuli were presented against a gray background(Figures 2A,B). Each picture was presented for 5500 ms followed
by a 500-ms blank interval. For fixation, a red cross wasalways shown at the center of the display, and the participants
were instructed to keep their eyes on this position. Each
auditory stimulus was presented 200 ms after the onset of each
picture. The stimulus presentation and collection of behavioral
data were controlled using the Presentation software package(Neurobehavioral Systems, Albany, CA, USA). The participants
wore an MRI-compatible audio headset and an eyeglass-like
MRI-compatible display (resolution, 800 × 600; VisuaStim
Digital, Resonance Technology, Northridge, CA, USA).

the study, written informed consent was obtained from eachparticipant after the nature and possible consequences of thestudy were explained. Approval for the experiments was obtained
from the institutional review board of the University of Tokyo,
Komaba Campus.

Stimuli
For each trial of the sentence-picture matching task, auditory
and visual stimuli were simultaneously presented. As auditory
stimuli, a set of 64 original sentences was prepared for matchedstimuli (16 sentences for each sentence condition), and a setof 64 sentences, consisting of 36 original sentences and 28
additional sentences (6–8 for each condition), was used formismatched stimuli (16 sentences for each condition). Here wecall the sentence-picture stimuli mismatched, when a picture
does not match the meaning of a sentence. All sentences weregrammatical, and word frequencies were controlled among theconditions.
Under each of the four sentence conditions with VOS, SVO,
VSO, and OVS, we used the same set of verbs, nouns, a definite
article “ri,” and a plural marker for nouns “taq.” We used only
men with a definite article for nouns, but did not use an indefinite
article or an animal, because a mixed use of definiteness (definite
and indefinite) or animacy (human being, animal, etc.) of nounphrases may affect word orders (García Matzar and Rodríguez
Guaján, 1997). Either a single man or two men in a sentence wererepresented by one of four colors: “käq (red), q’ëq (black), säq(white), and xar (blue)” in Kaqchikel (see Figure 2A). We used
one of the following six Kaqchikel verbs: “ch’äy (hit), jïk’ (pull),nïm (push), oyoj (call), pixab’aj (bless), and xib’ij (surprise).” A
sentence example with VOS is “X-e-ru-nïm [ri taq säq] [ri xar]
(The blue pushed the whites).”In our stimuli, both the subject and object were humans. Notethat the two sentences “The blue pushed the white” and “Thewhite pushed the blue” (both men in singular or plural) cannot be
distinguished by a prefix or noun phrase in Kaqchikel; the S and O
cannot be formally determined. To resolve this type of ambiguity,each sentence included three men, which always consisted of one
man (singular without “taq”) and two men (plural with “taq”).
All of the Kaqchikel sentences were spoken as a whole
by a male native Kaqchikel speaker at a constant speed withnatural prosody/intonation of declarative sentences, and thosesentences were digitally recorded (16 bit; the normal audio
cut-off, 44100 Hz). It should be noted that the spoken sentence
contained rich information about prosody. With Sound Forge
Pro 10 software (Sony Creative Software, Middleton, WI, USA),speech sounds were edited and their volumes were adjusted
within the range from −50 to 0 dB full scale. A one-way repeatedmeasures analysis of variance (rANOVA) showed that the mean
length of the auditory stimuli (2701 ± 168 ms) under each of
the VOS, SVO, VSO, and OVS conditions was not significantly
different [F(3,124) = 0.14, p = 0.94]. The input volume was set to
a comfortable hearing level for each participant.
As visual stimuli, a set of 16 original pictures was prepared formatched stimuli, which were used for every sentence condition.
For mismatched stimuli, 64 pictures were additionally made(16 pictures for each sentence condition), in which either or

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The Sentence-Picture Matching andColor-Picture Matching Tasks
In the sentence-picture matching task, each participant listened
to a Kaqchikel sentence and judged whether a picture matched
the meaning of the sentence (Figure 2A). To minimize theinclusion of short term memory, we presented the sentence while
the participant looked at the picture. Trials with matched andmismatched stimuli were presented equally often (16 trials eachfor matched and mismatched stimuli under one condition). They
responded by pressing one of two buttons that were aligned ina row (right for the matched pair and left for the mismatchedpair) with their right thumb. Matching a picture with a sentence
required the four following linguistic properties:(1) color matching at the lowest lexical level,(2) plurality matching with or without the plural marker “taq,”(3) number and case (object/subject) matching, based on theverb prefixes, and(4) sentence construction based on syntactic structures.
The first property involved lexico-semantics, and for the
next two properties, checking syntactic/semantic features was
essential. For the last property, syntactic decisions were required.
The judgment of mismatch was possible either at the phrase
presented second or at the phrase presented third of the heard
sentence, with the same frequency. Note that the comparison
between trials with the matched and mismatched stimuli was notwithin the scope of the present study.
In the sentence-picture matching task, mismatched stimuli(e.g., pictures in the middle row of Figure 2A) involved only oneof the following four variations: (1) 24 pictures (four or eightunder each condition) with one color alone, while two colors
were used in the sentence (e.g., the leftmost picture); (2) 16
pictures (four under each condition) with a color different fromthat used in the sentence (e.g., the second and fourth pictures),thereby controlling the frequency of colors under each condition;(3) eight pictures (four under the VOS and VSO conditions),

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line in the vertical direction, using a gradient-echo echo-planar
imaging (EPI) sequence (repetition time [TR] = 2 s, echo
time [TE] = 30 ms, flip angle [FA] = 90◦ , field of view
[FOV] = 192 mm × 192 mm, resolution = 3 mm × 3 mm). Ina single scan, we obtained 102 volumes where the first six images
were discarded, which allowed for the rise of the MR signals.
After the completion of the fMRI session, high-resolution
T1-weighted images of the whole brain (192 axial slices,
1.0 mm × 1.0 mm × 1.0 mm) were acquired fromall participants with a three-dimensional fast spoiled
gradient recalled acquisition in the steady state (3D
FSPGR) sequence (TR = 8.6 ms, TE = 2.6 ms, FA = 25◦ ,FOV = 256 mm × 256 mm). These structural images were used
for normalizing the fMRI data.

in which two colors were swapped between a single man andtwo men (e.g., the third picture); and (4) 16 pictures (eight eachunder the SVO and OVS conditions), in which the numbersof men were swapped. The first three variations of mismatchedstimuli led to a violation in the linguistic properties mentioned
above, thus requiring the comprehension of a whole sentence.
The fourth variation, which involved attention to the exact verb
prefixes due to the swapping of the number of men, may haverequired much higher loads than we had initially expected;
we thus excluded those trials of mismatched stimuli from thesubsequent behavioral and fMRI analyses.
In addition to the sentence-picture matching task, we also
used a color-picture matching task (the control task), in which
the participants judged whether colors in a picture matched thecolor words in the auditory stimuli (Figure 2B). By contrastingeach of the four task conditions in the sentence-picture matchingtask with the control task at the first level of analysis, we could
minimize the involvement of the first and second properties (seeabove) in any activation. For the auditory stimuli in the control
task, we played the verb backward; as a result, the auditory stimuli
contained the color words, plural marker, and definite articles. To
indicate the control task, we added a white line at the bottom of
the pictures, which were 128 different stimuli for the control task
(64 each for matched and mismatched stimuli).
In the control task, mismatched stimuli involved only oneof the following two variations: (1) 16 pictures with one color
alone, while two colors were used in the auditory stimuli, and(2) 48 pictures with a color different from that in the auditory
stimuli (e.g., the right picture of Figure 2B), thereby controllingthe frequency of colors. General cognitive factors such as visual orauditory perception of the stimuli, matching, response selection,and motor responses were also controlled by the control task.
We used the control condition as a baseline of the first-level
analyses of the fMRI data to exclude these sensory and general
cognitive factors as much as possible. The participants underwent
short practice sessions before the task sessions to become fully
familiarized with these tasks.
A single run of the task sessions (192 s) contained 16 “testevents” of the sentence-picture matching task (four times eachfor the VOS, SVO, VSO, and OVS conditions), with inter-trial
intervals of one control task. The order of the test events was
pseudorandomized without repetition of the same condition, toprevent any condition-specific strategy. A single run contained
16 trials of the control task. Seven or eight runs were tested per
one participant in a day. Only trials with participants’ correct
responses were used for analyzing the RTs and fMRI data. For
each participant, seven or eight runs without head movement
were used for the behavior and fMRI analyses.

fMRI Data Analyses
The fMRI data were analyzed in a standard manner using
SPM12 statistical parametric mapping software (Wellcome TrustCentre for Neuroimaging1 ) (Friston et al., 1995), implemented
on MATLAB software (MathWorks, Natick, MA, USA). The
acquisition timing of each slice was corrected using the middle
slice (the 17th slice chronologically) as a reference for the EPI
data. We realigned the time-series data in multiple runs to thefirst volume in all runs, and further realigned the data to themean volume of all runs. The realigned data were resliced using
seventh-degree B-spline interpolation, so that each voxel of eachfunctional image matched that of the first volume. We removed
runs that included data with a translation of >2 mm in any of thethree directions and with a rotation of >1.4◦ around any of thethree axes; these thresholds of head movement were empiricallydetermined from our previous studies (Hashimoto and Sakai,
2002; Suzuki and Sakai, 2003; Kinno et al., 2008; Ohta et al.,2013b). For this reason, a single run was removed from one
participant.
After alignment to the AC-PC line, each participant’s
T1-weighted structural image was coregistered to the meanfunctional image generated during realignment. T1-weighted
images were bias-corrected with light regularization, andsegmented to the gray matter, white matter, cerebrospinal fluid,bone, other soft tissues, and air by using default tissue probability
maps and the Segment tool in the SPM12, which uses an affine
regularization to warp images to the International Consortiumfor Brain Mapping European brain template (Ashburner andFriston, 2005). Inter-subject registration was achieved withDiffeomorphic Anatomical Registration using the ExponentiatedLie algebra (DARTEL) toolbox in the SPM12 (Ashburner, 2007).
The coregistered structural images were spatially normalized tothe standard brain space as defined by the Montreal Neurological
Institute (MNI) using DARTEL’s Normalize to MNI Space tool.
All of the normalized structural images were visually inspected
and compared with the standard brain for the absence of any
further deformation. The realigned functional images were also
spatially normalized to the MNI space by using DARTEL’s
Normalize to MNI Space tool, which converted voxel sizes to

MRI Data Acquisition
For the MRI data acquisition, the participant was in a supine
position, and his or her head was immobilized inside the radiofrequency coil with straps. The MRI scans were conducted on
a 3.0 T MRI system (GE Signa HDxt 3.0T; GE Healthcare,
Milwaukee, WI, USA). We scanned 32 axial slices of 3-mm thickwith a 0.3-mm gap, covering the volume range of −42.9 to
62.4 mm from the anterior to posterior commissure (AC-PC)

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Regarding the accuracy, the participants made reliable andconsistent judgments, and the accuracy under every condition
was higher than 90%. Under the sentence conditions, anrANOVA with these two factors on the accuracy showedsignificant main effects of scrambling and topicalization[scrambling, F(1,16) = 12, p = 0.0036; topicalization,
F(1,16) = 9.5, p = 0.0072], and an interaction between thesefactors was marginally significant [F(1,16) = 4.4, p = 0.052].
Post hoc paired t-tests showed that the accuracy under the SVO
condition was significantly higher than that under the otherconditions (corrected p < 0.0024), indicating that SVO was theeasiest condition.

3 mm × 3 mm × 3 mm and smoothed the images with anisotropic Gaussian kernel of 9-mm full-width at half maximum.
In a first-level analysis (i.e., the fixed-effects analysis), eachparticipant’s hemodynamic responses induced by the four
sentence conditions as well as the control task for each session
were modeled with a boxcar function with a duration of 5.5 sfrom the onset of each visual stimulus. The boxcar function
was then convolved with a hemodynamic response function.
Low-frequency noise was removed by high-pass filtering at
1/128 Hz. To minimize the effects of head movement, thesix realignment parameters obtained from preprocessing were
included as a nuisance factor in a general linear model. The
images of the VOS − control, SVO − control, VSO − control,and OVS − control contrasts were then generated in the generallinear model for each participant and used for the intersubject
comparison in a second-level analysis (i.e., the random-effects
analysis). To examine the activation of the regions in an unbiased
manner, we adopted whole-brain analyses (Friston and Henson,2006).
A repeated-measures analysis of covariance with t-tests was
performed with two factors (scrambling × topicalization), theresults of which were thresholded at uncorrected p < 0.0001(t > 4.8) for the voxel level, and at corrected p < 0.05 forthe cluster level, with topological false discovery rate (FDR)
correction across the whole brain (Chumbley and Friston, 2009).
We used the differences of accuracy between each sentence
condition and control (e.g., VOS − control, SVO − control, VSO− control, and OVS − control) as a covariate of no interest(i.e., a nuisance factor). For the anatomical identification ofactivated regions, we basically used the Anatomical Automatic
Labeling method2 (Tzourio-Mazoyer et al., 2002) and the labeleddata as provided by Neuromorphometrics Inc.3 under academic
subscription. For each region of interest, we extracted the mean
percent signal changes for each participant from the local maxima(i.e., peak voxel) of each region in the second-level group analysis,using the MarsBaR-toolbox4 .

The Basic Design of the Functional
AnalysesHere we outline the basic design of the main functional
analyses. Based on the two-by-two experimental design(scrambling × topicalization), we first examined the main effects
of scrambling [±S], i.e., (VSO + OVS) − (VOS + SVO), where
the [+S] conditions mainly induced higher syntactic loads(see the Introduction). We then examined the main effects of
topicalization [±T], i.e., (VOS + VSO) vs. (SVO + OVS), related
to the semantic/phonological loads. To examine any effects
associated with the accuracy for each condition, we also tested(VOS + VSO + OVS) − SVO, based on the behavioral results
shown above.
To exclude any semantic/phonological effects of the objectsubject word orders, we performed two direct comparisons while
making the factor of topicalization constant: VSO [+S, −T] vs.
VOS [−S, −T], and OVS [+S, +T] vs. SVO [−S, +T]. Lastly,
we examined the activation profiles under the four sentence
conditions in each of the identified regions of interest, and theresults confirmed significant activation in these regions for a
diagonal contrast of VSO [+S, −T] vs. SVO [−S, +T].

The Cortical Activation Reflecting
Syntactic Loads or
Semantic/Phonological Loads

RESULTS

The main effects of scrambling, i.e., (VSO + OVS) − (VOS +SVO), were observed in language areas such as the L. LPMC,
L. F3op/F3t, and L. F3t/F3O (corrected p < 0.05) (Figure 3A
and Table 1). Additional activation was observed in the presupplementary motor area (pre-SMA) and the left intraparietal
sulcus (L. IPS). In contrast, the main effects of topicalization, i.e.,(VOS + VSO) − (SVO + OVS), were observed in completely
different regions: Heschl’s gyrus (HG) and the STG in bothhemispheres (Figure 3B and Table 1). The reverse contrast,i.e., (SVO + OVS) − (VOS + VSO), did not show any
significant activation (corrected p > 0.9). These results support
the possibility that phonological loads and general auditory
attention would become larger in the absence of topicalization(see the Introduction).
In contrast, the contrast of (VOS + VSO + OVS) –SVO showed activation in the pre-SMA and left superior andmiddle temporal gyri (L. STG/MTG), sparing the lateral frontal
regions (Figure 3C and Table 1). The pre-SMA activation

Behavioral Data
We used a two-by-two experimental design (factors:
scrambling × topicalization). The behavioral data for thesentence-picture matching task are shown in Figures 2C,D.
Under the sentence conditions, an rANOVA with these
two factors on the RTs showed significant main effects ofscrambling [F(1,16) = 153, p < 0.0001], but the main effect of
topicalization and an interaction between these factors were notsignificant [topicalization, F(1,16) = 0.61, p = 0.45; interaction,
F(1,16) = 0.24, p = 0.63]. Consistent with our theoreticalpredictions, these results indicated that the VSO and OVS
conditions [+scrambling] produce greater syntactic loads thanthe VOS and SVO conditions [−scrambling].
2

http://www.gin.cnrs.fr/AAL2/
http://Neuromorphometrics.com/
4
http://marsbar.sourceforge.net/
3

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FIGURE 3 | Cortical activation modulated by the main effects of scrambling and topicalization. (A) Regions identified by the main effects of scrambling, i.e.,(VSO + OVS) − (VOS + SVO). Activations were projected onto the left (L) and right lateral surfaces of a standard brain (topological FDR-corrected p < 0.05). Medial
sections are also shown. The activation of pre-SMA was also projected onto the lateral surfaces. Each blue dot indicates the local maximum of an activated region.
See Table 1 for the stereotactic coordinates of the activation foci. (B) Regions identified by the main effects of topicalization; i.e., (VOS + VSO) − (SVO + OVS).
(C) Regions identified by the contrast of (VOS + VSO + OVS) – SVO.

replicated activation in the main effects of scrambling, while the
L. STG/MTG activation was left-lateralized and located more
ventrally than that in the main effects of topicalization.
We directly compared the cortical activation in VSO – VOS,
and we observed localized activation in the L. LPMC, L. F3op/F3t,
and L. F3t/F3O (Figure 4A and Table 1), i.e., the frontal language
areas, which were consistent with the main effects of scrambling.
Activation in the pre-SMA and L. IPS also replicated the main
effects of scrambling, but the R. IPS was additionally activated.
On the other hand, the reverse contrast, i.e., VOS − VSO, did
not show any significant activation (corrected p > 0.9). In OVS −Frontiers in Psychology | www.frontiersin.org

SVO, the overall activation pattern was similar to that in VSO –VOS (Figure 4B and Table 1). It is notable that the L. F3op/F3t
activation shifted more dorsally (15 mm for the local maxima) in
OVS – SVO. Compared with the main effects of scrambling, these
activated regions were highly localized in such stringent contrasts
as VSO − VOS and OVS − SVO.
At the local maxima of the L. LPMC, L. F3op/F3t, L. F3t/F3O,
and pre-SMA in the second-level analysis, which were selectedfrom the contrast OVS – SVO (shown as blue dots in Figure 4B),
we examined the percent signal changes. In all of these regions,the overall activation profiles under the four sentence conditions

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TABLE 1 | Regions identified by the effects of word order.
Brain regions

BA

Side

x

z

Z

Voxels

6/9

L

−42
−45

3

51

6.3

625

12

42

5.4

∗

−36

12

33

4.9

∗

−48

18

27

5.1

∗
∗

y

Main effects of scrambling: (VSO + OVS) − (VOS + SVO)
LPMC

F3op/F3t

44/45

L

−54

12

15

5.8

F3t/F3O

45/47

L

−54

27

0

6.1

∗

pre-SMA

6/8/32

M

−6

15

48

6.5

352

0

24

42

6.2

∗

7

L

−27

−69

42

5.2

71

HG

41/42

L

−51

−21

6

5.6

213

STG

22

L

−51

−33

9

5.7

∗

−63

−15

3

4.7

∗

48

−15

6

5.6

326

39

−24

6

5.8

∗

66

−18

9

5.6

∗

5.1

∗

235

IPS
Main effects of topicalization: (VOS + VSO) − (SVO + OVS)

HG
STG

41/42

R

22

R

63

−18

−6

15

48

5.5

0

27

42

5.7

∗

−6

(VOS + VSO + OVS) − SVO
pre-SMA
STG/MTG

6/8/32

M

22/21

L

−63

−21

−6

5.7

96

6/8

L

−36

6

57

4.5

112

−48

0

45

5.4

∗

−48

12

42

4.6

∗

VSO − VOS
LPMC

F3op/F3t

44/45

L

−57

12

12

5.5

78

F3t/F3O

45/47

L

−54

24

0

4.4

∗

pre-SMA

6/8/32

M

−6

15

48

5.4

134

IPS

7/19

L

−12

−78

45

4.7

149

−27

−69

39

5.5

∗

−30

−75

24

4.7

∗

18

−69

51

5.5

95

30

−66

51

5.1

∗

7/19

R

OVS − SVO
LPMC

6/8

L

−42

3

54

5.5

74

F3op/F3t

44/45

L

−51

18

27

4.7

35

F3t/F3O

45/47

L

−54

30

0

5.5

46

pre-SMA

6/8/32

M

−3

15

60

4.9

149

−6

15

48

5.1

∗

−3

27

42

5.5

∗

Stereotactic coordinates (x, y, z) in the MNI space (mm) are shown for each activation peak of Z values. The threshold was set at corrected p < 0.05 for the cluster level.
BA = Brodmann’s area; L = left; M = medial; R = right; LPMC = lateral premotor cortex; F3op/F3t/F3O = opercular/triangular/orbital parts of the inferior frontal gyrus;
pre-SMA = pre-supplementary motor area; IPS = intraparietal sulcus; HG = Heschl’s gyrus; STG = superior temporal gyrus; MTG = middle temporal gyrus. The region
with an asterisk is included within the same cluster shown one row above.

were consistent. More specifically, the activations under VSO
and OVS were always evident at the same level, whereas theactivations under VOS and SVO were near or below thebaseline level. Furthermore, the signal changes under VSO weresignificantly larger than those under SVO in each of the four
regions (corrected p < 0.002).
The bilateral IPS activation, which was observed in
VSO – VOS (shown as blue dots in Figure 4A), but not in

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OVS − SVO, may indicate the presence of an interaction.
This effect was due to more activations under the VSO
condition than the other conditions. A significant interaction
was present in the R. IPS [F(1,16) = 6.5, p = 0.022], but notin the L. IPS [F(1,16) = 0.17, p = 0.69]. The VSO [+S, −T]
condition reflected a synergistic effect of multiple linguistic
factors, which may employ additional cortical regions like thebilateral IPS.

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FIGURE 4 | Direct comparison of cortical activation between conditions. The VSO − VOS contrast (A) and the OVS − SVO contrast (B). Activations were
projected onto the left (L) and right lateral surfaces of a standard brain (topological FDR-corrected p < 0.05). See Table 1 for the stereotactic coordinates of theactivation foci. (C) Histograms for the percent signal changes at the local maxima of the L. LPMC, L. F3op/F3t, L. F3t/F3O, and pre-SMA in OVS − SVO. The signal
changes for VOS, SVO, VSO, and OVS are shown with reference to the baseline level of the control task. Error bars indicate SEM for the participants. ∗ p < 0.0005.

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experimental evidence of linguistic computation that dissociates[+scrambling] and [−topicalization].
Here we observed activation in the bilateral HG and STG
under the [−topicalization] conditions, which may reflectphonological loads and attention in the absence of topicalization.
Our previous fMRI study revealed that the bilateral STG
activations were selectively enhanced by phonological decisiontasks (Suzuki and Sakai, 2003). The same study further
demonstrated that the localized activations in the L. MTG weremodulated by the presence of syntactic or semantic errors, which
may enhance processing loads to correct sentences. Consistent
with this possibility, here we observed the localized L. STG/MTG
activation in the contrast of (VOS + VSO + OVS) – SVO.
In recent studies using a visual sentence-picture matchingtask similar to that used here, we tested 21 patients witha left frontal glioma and observed abnormal overactivity
and/or underactivity in 14 syntax-related regions (Kinno et al.,2014, 2015). Those investigations also revealed three syntaxrelated networks: network I (syntax and its supportive system),
network II (syntax and input/output interface), and network III(syntax and semantics). Functional and anatomical connectivity
was observed within individual networks in normal controls,
whereas in the agrammatic patients almost all of the functional
connectivity exhibited chaotic changes. Moreover, the patients
who showed normal performances showed normal connectivity
between the L. F3op/F3t and L. IPS, as well as normal connectivity
between the L. F3t and L. F3O, indicating that these pathways
are the most crucial among the syntax-related networks. In thepresent study, we observed significant activation in the pre-SMA
and L. IPS (Figures 3, 4), which are included in network I (which
consists of the L. F3op/F3t, pre-SMA, right lateral frontal regions,
L. IPS, and right temporal regions). The consistent activationof the pre-SMA and L. IPS suggests their supportive roles insyntactic processing.
Another possible model for the syntactic structures of Mayan
sentences has been proposed in a linguistic study: a predicatefronting model (Figure 1B; Coon, 2010). In this model, which
is more complex than the right-specifier model even for thecanonical word order (VOS), predicate fronting is assumed asa default and obligatory movement. This model was basedon similar syntactic analyses for another verb-initial language:
Niuean, a Polynesian language that is markedly distant from
Mayan languages (Massam, 2010). The notion of object shift,which precedes predicate fronting, replaces scrambling in theright-specifier model. Note that the verification of the rightspecifier model or predicate fronting model was not within thescope of the present study; both models predict consistent resultsin our paradigm. The explanatory adequacy of these two models
should be further examined in future experiments.
A previous fMRI study in Kaqchikel with a sentenceplausibility judgment task has reported higher activation in
the left IFG close to its border with the left middle frontal
gyrus (BA 46) in the SVO − VOS contrast (Koizumi andKim, 2016), clearly different activation from the present results.
In that task, the participants listened to a sentence with ahuman (S) and an inanimate entity (O), and judged whether
a sentence was semantically plausible or not, where no specific

DISCUSSION
By using the sentence-picture matching task in the Kaqchikel
language, we obtained four striking results. First, we found thatthe [+scrambling] conditions elicited significant activation in
the left frontal regions of the L. LPMC, L. F3op/F3t, and L.
F3t/F3O (Figure 3A), indicating the effects of syntactic loads
in Kaqchikel, a head-marking and OS language. These results
indicate that the L. LPMC, L. F3op/F3t, and L. F3t/F3O, but not
the L. ATL, are crucial for a movement of phrases. Secondly,
the [−topicalization] conditions resulted in significant activationin the bilateral HG and STG (Figure 3B), demonstratingthat the syntactic and phonological processes were clearly
dissociated within the language areas. Thirdly, the pre-SMA
and L. STG/MTG were activated under the more demanding
conditions other than SVO (Figure 3C), suggesting theirsupportive roles in syntactic or semantic processing. Fourthly,
two direct comparisons of VSO – VOS and OVS – SVO
showed consistent and localized activations in the L. LPMC, L.
F3op/F3t, and L. F3t/F3O, as well as the pre-SMA (Figures 4A,B),
while VOS – VSO did not show any significant activation.
This last point fits the syntactic account for the selective
activation in these frontal regions, excluding any semantic
effects of the OS word order itself, which might be related
to “irregular prominence factors of noun phrases” (see theIntroduction). Our findings further indicate that the functionalroles of these left frontal and temporal regions involve linguistic
aspects themselves, namely syntax versus semantics/phonology,rather than output/input aspects of speech processing. Moreover,the present study with Kaqchikel clearly contributes to theconcept that such universal operations as scrambling andtopicalization are differentially processed in specified corticalregions.
“Merge” is a fundamental local structure-building operation
proposed by modern linguistics (Chomsky, 1995), and is a key tosyntactic processing. Neuroimaging studies have established thatsyntactic processing selectively activates the L. F3op/F3t and L.
LPMC (Stromswold et al., 1996; Dapretto and Bookheimer, 1999;
Embick et al., 2000; Hashimoto and Sakai, 2002; Friederici et al.,
2003; Musso et al., 2003), indicating that these regions have a
critical role as grammar centers (Sakai, 2005). Activations in the
L. F3op/F3t and L. LPMC have also been observed in our studies
using Japanese sentences with non-canonical word orders (Kinno
et al., 2008). Moreover, our MEG studies showed a significant
increase of responses in the L. IFG, which reflected predictive
effects on a verb caused by a preceding object in a short sentence(Iijima et al., 2009; Inubushi et al., 2012; Iijima and Sakai, 2014).
In the present study, we observed selective activation in the L.
F3op/F3t and L. LPMC under the [+scrambling] conditions,which is consistent with these previous findings. Our results
also support the explanation based on the DoM (Ohta et al.,2013a,b), in that the [+scrambling] conditions with the larger
DoM enhanced the L. F3op/F3t and L. LPMC activations. It
should be noted that activation in the L. LPMC, L. F3op/F3t, andL. F3t/F3O were more localized in both VSO – VOS and OVS –SVO, which excluded any differences in semantic/phonologicalloads. To our knowledge, our present findings are the first

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context was provided. The authors of that study interpreted
this activation as the higher processing load related to more
complex structures of SVO. They further argued that this higher
load was related to the discourse-pragmatic requirements for the
non-canonical SVO word order. A topicalized sentence incurs
higher processing loads when presented out of context, as in thecase of the sentence plausibility judgment task. In our present
study, where both the subject and object were humans, weobserved significant activation in the bilateral HG and STG as
the main effects of topicalization, i.e., (VOS + VSO) − (SVO+ OVS). This activation reflected increased phonological loads
under the [−topicalization] conditions. Note that the reverse
contrast did not show any significant activation, indicating thatthe [+topicalization] conditions had little syntactic effects where
DoM remains minimal (see the Introduction). By naturally
providing a discourse context as a picture, we were able
to dissociate the main effects of topicalization related tosemantics/phonology from those related to pragmatics.
In Kaqchikel, it has been reported that SVO is more
frequently used than VOS (73% versus 15%) (Kubo et al.,2011). In that study, the native Kaqchikel speakers madea sentence describing a picture, which depicted a transitive
action between a human agent and human/animal/inanimate
patient. Although the concept of “basic word order” has been
problematic (Brody, 1984), the word order with the simplest
syntactic structure, i.e., syntactically canonical word order, is
VOS (García Matzar and Rodríguez Guaján, 1997, p. 333). It
has been suggested that “when examining the basic word orderof Mayan languages, syntactically determined word order fromthe standpoint of syntactic complexity needs to be distinguishedfrom pragmatically determined word order, commonly used
for pragmatic purposes” (Yasunaga et al., 2015). This pointis also related to our present observation that SVO was theeasiest condition in our paradigm (Figure 2D). Both the higher
production frequency and the higher accuracy of SVO may becaused by the effects associated with [+topicalization]. In a study
using Japanese sentences, the production frequency of subjecttopicalized sentences (S-wa OV) was several times higher thanthat of canonical sentences (S-ga OV), and the subject-topicalized
sentences were more easily processed than the object-topicalized
sentences (O-wa S-ga V) (Imamura and Koizumi, 2011); notethat an S is considered as a default topic (Koster, 1978). Thesephenomena could be parallel to those for SVO versus canonical
VOS in Kaqchikel, in that subject-topicalized sentences havelower semantic/phonological loads. On the other hand, one
crucial difference between Japanese and Kaqchikel is that bothcanonical and subject-topicalized sentences are SOV in Japanese.
Moreover, a string-vacuous movement, i.e., a movement withouta change in the order of strings, is prohibited (Chomsky, 1986).
Because both scrambling and topicalization are not stringvacuous movements in Kaqchikel, Kaqchikel is an ideal languagefor dissociating the effects of scrambling and topicalization. By
targeting such understudied languages as Kaqchikel, we wereable to integrate previous findings of neuroimaging and linguistic
studies with our new findings, which will contribute to theunderstanding of the biological basis of language.

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AUTHOR CONTRIBUTIONS
All authors listed, have made substantial, direct and intellectual
contribution to the work, and approved it for publication.

FUNDING
This research was supported by a Core Research for Evolutional
Science and Technology (CREST) grant from the Japan Scienceand Technology Agency (JST), a Grant-in-Aid for Scientific
Research (A; No. 15H02603), a Grant-in-Aid for Young Scientists(B; No. 15K16733) from the Ministry of Education, Culture,
Sports, Science, and Technology of Japan, and a Grant-in-Aid
for Japan Society for the Promotion of Science (JSPS) Fellows(No. 24·8931).

ACKNOWLEDGMENTS
We thank J. E. Ajsivinac Sian, L. P. O. García Matzar, andA. Yamagata (a Spanish interpreter) for their assistance withthe experiments, N. Komoro and H. Tada for their technicalassistance, and H. Matsuda for her administrative assistance.

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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2017 Ohta, Koizumi and Sakai. This is an open-access article distributed
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