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Proc. Jpn. Acad., Ser. B 93 (2017)

511

Activation changes of the left inferior frontal gyrus for the factorsof construction and scrambling in a sentence
By Kyohei TANAKA,*1 Shinri OHTA,*1,‡ Ryuta KINNO*2 and Kuniyoshi L. SAKAI*1,†(Communicated by Masao ITO, M.J.A.)

Abstract: Our previous functional magnetic resonance imaging (fMRI) studies haveindicated that the left dorsal inferior frontal gyrus (L. dF3op/F3t) and left lateral premotor cortex(L. LPMC) are crucial regions for syntactic processing among the syntax-related networks. In thepresent study, we further examined how activations in these regions were modiﬁed by the factors ofconstruction and scrambling (object-initial type). Using various sentence types, we clariﬁed threemajor points. First, we found that the main eﬀects of construction and scrambling consistently
activated the L. dF3op/F3t and L. LPMC. Secondly, the main eﬀects of scrambling clearly localized
activation in the L. dF3op/F3t and L. LPMC, indicating the more narrowed down processing ofsyntax. Thirdly, step-wise percent signal changes were observed in the L. dF3op/F3t, demonstratingsynergistic eﬀects of construction and scrambling. These results demonstrate the abstract andintensive nature of syntactic processing carried out by these regions, i.e., the grammar center.
Keywords:
scrambling

language, fMRI, inferior frontal gyrus, lateral premotor cortex, construction,

Introduction

Natural languages, or human languages, havevarious universal properties, such as the presenceof subject, object, and predicate in a sentence.
The grammatical relation of each noun phrase (NP)*1

Department of Basic Science, Graduate School of Arts andSciences, The University of Tokyo, Tokyo, Japan.
*2
Division of Neurology, Department of Internal Medicine,Showa University School of Medicine, Tokyo, Japan.
†
Correspondence should be addressed to: K. L. Sakai,
Department of Basic Science, Graduate School of Arts andSciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku,
Tokyo 153-8902, Japan (e-mail: sakai@mind.c.u-tokyo.ac.jp).
‡
Present address: Department of Linguistics, Faculty of
Humanities, Kyushu University, Fukuoka, Japan.
Abbreviations: Act/Pas/Pot: active/passive/potentialconditions; ActD/PasD/PotD: scrambled active/passive/potentialconditions; [!scrambling]: Act, Pas, and Pot conditions; [Dscrambling]: ActD, PasD, and PotD conditions; Easier cond.: Act, ActD,
and Pas conditions; Harder cond.: PasD, Pot, and PotD
conditions; SC: sentence control; Cont: control; NP: noun phrase;
RTs: reaction times; IES: inverse eﬃciency scores (RTs/Accuracy);
FWE: family-wise error; BA: Brodmann’s area; L: left; M: medial;
LPMC: lateral premotor cortex; F3op/F3t/F3O: opercular/
triangular/orbital parts of the inferior frontal gyrus; dF3op/F3t:
dorsal F3op/F3t; pre-SMA: pre-supplementary motor area; AG:
angular gyrus; IPS/SMG: intraparietal sulcus/supramarginal
gyrus; MTG: middle temporal gyrus; pMTG/ITG: posterior
middle/inferior temporal gyrus; LG/FG: lingual/fusiform gyrus.

doi: 10.2183/pjab.93.031©2017 The Japan Academy(“subject, direct object, or indirect object” in linguistic terms) is structurally determined,1) whereas, inJapanese, a case marker (nominative -ga, dative -ni,or accusative -o) of each NP is ﬁnalized at the surface
level. On the other hand, a predicate independently
assigns a semantic role (“agent, experiencer, or
patient” in linguistic terms; an agent initiates theaction, and an experiencer/patient is aﬀected by
the agent) to each NP. Moreover, these linguistic
relationships for individual NPs are not the simple
one-to-one correspondence. Based on Kuroda’s analyses of Japanese sentences [see Chapter 6 in Kuroda(1992)2)], subject-initial or normal sentence patterns
with NPs are as follows:
I
Transitive sentence pattern: NP-ga NP-o
Ia Transitive sentence pattern: NP-ga NP-ni
II
Ergative sentence pattern: NP-ni NP-ga
III Intransitive sentence pattern: NP-ga
The proposal of the ergative pattern II conforms
to the “Dative Subject Constructions”.3) Given these
theoretical studies, the neuroscience of language
should elucidate the neural basis of linguistic
structures/constructions as precise as possible. Functional magnetic resonance imaging (fMRI) has been
widely used as the most powerful method of visualizing localized activations as a statistical map in the512

K. TANAKA et al.

[Vol. 93,

Fig. 1. A picture-sentence matching task and a Control task. Under the two-argument (i.e., Act, ActD, Pas, PasD, Pot, and PotD) andone-argument (i.e., SC) conditions, each stimulus consisted of one picture (top) and one sentence (bottom). Pictures consisted of two
stick ﬁgures, each of which was distinguished by a “head” symbol: a circle, square, or triangle. We used four kinds of grammaticalparticles, which represent the syntactic information in Japanese: -ga, a nominative case marker; -ni, a dative case marker; -o, anaccusative case marker; and -to, a coordinator (“and ”). Under both the [!scrambling] (marked in orange) and [Dscrambling] (marked
in red) conditions, we tested three constructions: active, passive, and potential sentences. Examples of matched sentences are shown inthe ﬁrst and second rows. For examples of mismatched sentences, see Fig. 1A in Kinno et al. (2014).6) Under the SC condition,
examples of matched (left panel) and mismatched (middle panel) sentences are shown; for the Control task, a matched example isshown (right panel).

human brain. Our previous studies have clariﬁed theexistence of the grammar center, which consists of
two left frontal regions: the opercular/triangularparts of the left inferior frontal gyrus (L. F3op/F3t)
and the left lateral premotor cortex (L. LPMC).4)
According to studies using a picture-sentence matching task with short Japanese sentences, speciﬁc
syntactic loads due to more complex sentence structures signiﬁcantly activated the grammar center.5)
Moreover, this task was successfully used for patientswith a left frontal glioma, revealing three syntaxrelated networks including the grammar center.6) In
those studies, three types of sentences were tested:

active (Act) (e.g., “ -ga -o oshiteru”), passive (Pas)(e.g., “ -ga -ni osareru”), and scrambled active(ActD) sentences (e.g., “ -o -ga oshiteru”). In thisarticle, we refer to “object scrambling” as simply
scrambling, where an object to be emphasized is
moved to the initial position of a sentence. In
addition to these three sentence types, the present
fMRI study tested scrambled passive (PasD) (e.g.,“ -ni -ga osareru”), potential sentences (Pot) (e.g.,“ -ni -ga oseteru”), and scrambled potential sentences (PotD) (e.g., “ -ga -ni oseteru ”) as well(Fig. 1, Table 1). By comparing these six conditionsof constructions, we expected new synergistic eﬀects

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Frontal activation due to construction and scrambling in a sentence

Table 1.

513

Sentences used in this study!Scrambling

DScrambling

Construction

English translation

Active sentence (Act)Construction

English translation

Scrambled active sentence (ActD)-ga-o hiiteru

pulls

-o

-ga hiiteru

As for,pulls it-ga-o oshiteru

pushes-o-ga oshiteru

As for,pushes it-ga-o shikatteru

scolds-o-ga shikatteru

As for,scolds it-ga-o ketteru

kicks

-o

-ga ketteru

As for,kicks it-ga

-o tataiteru

hits

-o

-ga tataiteru

As for,hits it-ga-o yonderu

calls

-o

-ga yonderu

As for,calls it

Passive sentence (Pas)-ga -ni hikareru

Scrambled passive sentence (PasD)-ni -ga hikareru
As foris aﬀected by’s pulling it’s pulling,

is aﬀected-ga-ni osareru

is aﬀected by’s pushing it-ni-ga osareru

As for’s pushing,is aﬀected-ga-ni shikarareru

is aﬀected by’s scolding it-ni-ga shikarareru

As for’s scolding,is aﬀected-ga-ni kerareru

is aﬀected by’s kicking it-ni-ga kerareru

As for’s kicking,is aﬀected-ga-ni tatakareru

is aﬀected by’s hitting it-ni-ga tatakareru

As for’s hitting,is aﬀected-ga-ni yobareru

is aﬀected by’s calling it-ni-ga yobareru

As for’s calling,

is aﬀected

Potential sentence (Pot)

Scrambled potential sentence (PotD)

-ni
-ni

-ga hiketeru-ga oseteru

can pullcan push-ga-ga-ni hiketeru-ni oseteru

As for
As for,,can pull it
can push it-ni-ga shikareteru

can scold-ga-ni shikareteru

As for,can scold it-ni-ga kereteru

can kick-ga-ni kereteru

As for,can kick it-ni-ga tataketeru

can hit-ga-ni tataketeru

As for,can hit it-ni-ga yobeteru

can call-ga-ni yobeteru

As for,can call it

Sentence control (SC)English translation-to-ga neteiru

and

lie

-to

-ga tatteru

and

stand

-to

-ga aruiteru

and

walk

-to

-ga hashitteru

and

run

-to

-ga koronderu

andtumble-to-ga naiteru

and

cry

Only typical examples are shown here; other combinations of the symbols , , and were also used. For brevity, English translation
for the active and potential sentences was written in the present tense, although the tense of the original sentences was the progressive.
-ga, nominative case marker; -o, accusative case marker; -ni, dative case marker; and -to, coordinator “and ”.

on the cortical activation, which was not possible
with our previous paradigm. We then examined how
activations in the regions including the grammar
center were modiﬁed by the factors of construction[active, passive, potential sentences] and scrambling[!scrambling, Dscrambling]. Because these factors
are related with shared aspects of syntactic structuresin a sentence, we hypothesized that the main eﬀects
of construction and scrambling would cause overlapped enhancement of activations in the grammar
center. We believe that the present study advances
our knowledge about the cortical localization ofsyntax, in that the overlapped region reliably
identiﬁes the most critical grammar center in thebrain.

Materials and methods
Participants. We recruited 22 native Japanese
speakers, none of whom had a history of neurologicaldisorders. To ensure the reliable and stable executionof the tasks despite fatigue and/or lack of concentration, we set an inclusion criterion for theparticipants, such that the error rates of every
condition were less than 30%; six participants were
dropped for this reason. The remaining 16 participants (12 males and four females; mean ’ standard
deviation [SD] age [yrs]: 27 ’ 6.6) showed righthandedness (laterality quotients: 89 ’ 15) according
to the Edinburgh inventory.7) Prior to participationin the study, written informed consent was obtained

K. TANAKA et al.

514

from each participant after the nature and possible
consequences of the study were explained. Approval
for the experiments was obtained from the institutional review board of the University of Tokyo,
Komaba Campus.
Stimuli. The four normal sentence patterns (I–III) in the Introduction correspond to active, passive,
potential, and sentence control (SC) conditions,
respectively (Fig. 1). For the patterns I, Ia, and II,
object-initial or scrambled sentences are also grammatical in Japanese. The inclusion of patterns Ia andII in our experiments controls any eﬀects concerning
the order of grammatical particles -ga and -ni (seeTable 2). On the other hand, passiveness is marked
by the verb form -(r)are-ru, whereas potentialness isclearly marked by the verb form -e-ru. Although theverb form -(r)are-ru, e.g., kanji-rare-ru, has multiple
functions of marking the passive voice (be felt),
potential (can feel), spontaneous (be spontaneouslyfelt), and honoric form (would feel),8) our passive
sentences were least ambiguous (see Table 1). For
the active construction, we used an abbreviated form(-te-ru) of progressive tense for the verb morphology(-te-iru); for the potential construction, we also used
an abbreviated form (-e-te-ru) of progressive tense
for the verb morphology (-e-te-iru). This was doneto equate the number of letters under all tested
conditions. Utilizing this experimental paradigm, we
would be able to focus on the natural process ofsyntactic judgment, thereby excluding the surfacelevel eﬀects of grammatical features.
Each visual stimulus consisted of a picture withhead symbols ( , , or ) at the top, and of an always
grammatical sentence at the bottom (Fig. 1). For
each stimulus, we chose two diﬀerent head symbols.
The sentences describing actions were written using
a combination of the hiragana and kanji writing
systems. We used four kinds of grammatical particles, which represent the syntactic information in
Japanese: -ga, -ni, -o, and -to, a coordinator (“and ”).

Table 2.

Linguistic relationships for individual nouns

Construction
Active (Act, ActD)
Passive (Pas, PasD)
Potential (Pot, PotD)

Case

Grammatical

Semantic

markers

relations

roles

-ga

subjectagent-odirect object

patient-ga

subject

experiencer-niindirect object

agent

-ni

subject

agent

-ga

direct object

patient[Vol. 93,

As listed in Table 1, two sets of Japanese verbs (sixtransitive verbs: pull, push, scold, kick, hit, and call;and six intransitive verbs: lie, stand, walk, run,tumble, and cry) were used, each of which, including
the passive forms, had either four or ﬁve syllables.
Note that the verb “call ” is used only as a transitive
verb in Japanese. There was no signiﬁcant diﬀerencein frequency between the two sets of verbs (t(10) F
0.7, P F 0.5), according to the Japanese lexical
database (“Nihongo-no Goitokusei” (Lexical Properties of Japanese), Nippon Telegraph and Telephone
Corporation Communication Science Laboratories,
Tokyo, Japan, 2003). The numbers of syllables andletters were strictly controlled among all conditions.
Under the two-argument conditions (i.e., Act,
ActD, Pas, PasD, Pot, and PotD), in which eachsentence ended with a transitive verb and had twoarguments (phrases associated with the predicate),
the number of lines used in each picture except thehead symbols was 14 ’ 2.4. Under the one-argument(i.e., SC) condition, equally complex pictures (number of lines, 14 ’ 2.5) were used, in which eachsentence ended with an intransitive verb andcorresponded to a double subjects (double agents)
type, which did not involve two-argument relationships. Under these conditions, half of the pictures
depicted actions occurring from left to right, and theother half depicted actions occurring from right toleft (see Fig. 1); head symbols were also counterbalanced for both sides. These pictures further
excluded the involvement of pragmatic information
about word use (e.g., “An oﬃcer chases a thief ” ismore acceptable than “A thief chases an oﬃcer ”).
There were 24 diﬀerent stimuli (i.e., diﬀerent
combinations between pictures and sentences) undereach of these conditions.
All stimuli were presented visually in yellow
against a dark background (Fig. 1). Each stimulus
was presented for 6-s (intratrial interval) followed by
a 2-s blank interval. The intratrial interval was ﬁxed
for 6 s irrespective of participants’ responses. To
minimize the eﬀect of general memory demands, awhole sentence of a minimal length (i.e., two nounphrases and a verb) was visually presented for an
ample time for the participants to respond, even forpatients who were to be tested in a subsequent study.
The stimuli were thus more appropriate thansequentially presented stimuli that involve memorization. For ﬁxation, a red cross was also shown at thecenter of the screen to initiate eye movements fromthe same ﬁxed position, and the participants were
instructed to return their eyes to this position afterNo. 7]

Frontal activation due to construction and scrambling in a sentence

the response. The stimulus presentation and collection of behavioral data [error rate and reaction times(RTs)] were controlled using the LabVIEW softwareand interface (National Instruments, Austin, TX).
The participants wore earplugs and an eyeglasslike MRI-compatible display (resolution, 800 # 600,
within the visual angle of 7°) (VisuaStim XGA;
Resonance Technology Inc., Northridge, CA).
Tasks. In the picture-sentence matching task
(Fig. 1), the participants read a sentence silently
and judged whether or not the action depicted in a
picture matched the meaning of the sentence. They
were instructed to respond by pressing one of two
buttons in a row (right for a matched pair, and left fora mismatched pair) with the right hand as quickly as
possible while ensuring correct responses. Under the
two-argument conditions, all mismatched sentenceswere made by exchanging two symbols in the original
sentences, e.g., “ pushes ” instead of “ pushes ”.
Under the SC condition, both symbol-mismatchedsentences and action-mismatched ones were presented equally often, requiring the sentences to beread completely. The participants underwent shortpractice sessions before the task sessions to become
fully familiarized with this task. For some participants, the stimuli under the potential conditions
were relatively harder to comprehend. Before theexperiment, we explained typical potential sentencessuch as “Taroo-ni(-wa) eigo-ga hanas-e-ru” (“Taroo
can speak English”). We did not use the particle -wa
for the subject, because topicalization with -wa had
diﬀerential eﬀects other than scrambling.9)
For the Control (Cont) task, using the same
stimulus sets of pictures and letters presented under
the conditions described above, the participants
judged whether or not the two head symbols in the
picture matched those at the bottom, irrespective of
their order (Fig. 1). The letters in hiragana were
jumbled without changing the head symbols andkanji, so that the letter string prevented even basic
word recognition. General cognitive factors such as
visual perception of the stimuli, matching, response
selection, and motor response were controlled byusing the SC condition. The Cont task was used tolower the baseline activity. A single run of the task
sessions (256 s) contained 32 trial events (four foreach of the Act, ActD, Pas, PasD, Pot, PotD, SC,
and Cont task conditions), the order of which was
pseudorandomized to prevent any condition-speciﬁc
strategy. Half of the stimuli consisted of matched
picture-sentence pairs, and the other half consistedof mismatched pairs. Six runs were performed and515

the participants did not encounter the same sentence
twice.
MRI data acquisition.
For the MRI dataacquisition, the participant was in a supine position,and his or her head was immobilized inside the radiofrequency coil. The MRI scans were conducted on a
3.0 T system (GE Signa HDxt 3.0 T; GE Healthcare,
Milwaukee, WI). We scanned 30 horizontal slices,each 3-mm thick and having a 0.5-mm gap, covering
the range of z F !38.5 to 66 mm from the anterior toposterior commissure (AC-PC) line in the verticaldirection, using a gradient-echo echo-planar imaging(EPI) sequence (repetition time (TR) F 2 s, echo
time (TE) F 30 ms, ﬂip angle (FA) F 90°, ﬁeld ofview (FOV) F 192 # 192 mm2, resolution F 3 #3 mm2). In a single run, we obtained 128 volumes
following four dummy images, which allowed for therise of the MR signals. After completion of the fMRI
session, high-resolution T1-weighted images of thewhole brain (192 axial slices, 1.0 # 1.0 # 1.0 mm3)
were acquired from all participants with a threedimensional fast spoiled gradient recalled acquisitionin the steady state (3D FSPGR) sequence (TR F
8.4 ms, TE F 2.6 ms, FA F 25°, FOV F 256 #256 mm2). These structural images were used fornormalizing fMRI data.
fMRI data analyses.
The fMRI data wereanalyzed in a standard manner using SPM12 statistical parametric mapping software (Wellcome
Trust Center for Neuroimaging, http://www.ﬁl.ion.
ucl.ac.uk/spm/)10) implemented on MATLAB (MathWorks, Natick, MA). The acquisition timing of eachslice was corrected using the middle slice (the 15th
slice chronologically) as a reference for the EPI data.
We realigned the time-series data in multiple runs tothe ﬁrst volume in all runs, and further realigned thedata to the mean volume of all runs. The realigned
data were resliced using seventh-degree B-splineinterpolation, so that each voxel of each functional
image matched that of the ﬁrst volume.
After alignment to the AC-PC line, eachparticipant’s T1-weighted structural image wascoregistered to the mean functional image generated
during realignment. T1-weighted images were biascorrected with light regularization, and segmented 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 tothe International Consortium for Brain Mapping
East Asian brain template.11) Inter-subject registration was achieved with Diﬀeomorphic Anatomical

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Registration using the Exponentiated Lie algebra(DARTEL) toolbox in the SPM12.12) 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 byusing DARTEL’s Normalize to MNI Space tool,
which converted voxel sizes to 3 # 3 # 3 mm3 andsmoothed the images with an isotropic Gaussian
kernel of 9-mm full-width at half maximum. Lowfrequency noise was removed by high-pass ﬁltering at
1/128 Hz.
In a ﬁrst-level analysis (i.e., the ﬁxed-eﬀects
analysis), each participant’s hemodynamic responses
induced by the two-argument and SC conditions, aswell as the Cont task, in each session were modeledwith a boxcar function with a duration of 6 s from theonset of each visual stimulus. Because the maximum
RTs for correct responses of each participant ranged
from 3.8 s to 6.8 s, and 13 participants out of 16 took
more than 5 s under some trials, we chose the wholepresentation period of 6 s for analyses. The boxcar
function was then convolved with a hemodynamic
response function. Only the functional data for trials
with correct responses were modeled. To minimize
the eﬀects of head movement, the six realignment
parameters obtained from preprocessing were included as a nuisance factor in a general linear model.
The images under each of the two-argument conditions, minus those under the SC condition, werethen generated in the general linear model for eachparticipant and used for the intersubject, acrosssubject, 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.
A repeated-measures analysis of variance(rANOVA) with t-tests was performed with two
factors (construction # scrambling), the results ofwhich were thresholded at uncorrected P < 0.001 forthe voxel level, and at corrected P < 0.05 for thecluster level, with family-wise error (FWE) correction
across the whole brain. For the anatomical identiﬁcation of activated regions, we basically used theAnatomical Automatic Labeling method (http://
www.gin.cnrs.fr/AAL2/)13) and the labeled dataas provided by Neuromorphometrics Inc. (http://
Neuromorphometrics.com/) under academic sub-[Vol. 93,

scription. For each region of interest, we extracted
the mean percent signal changes for each participantfrom the local maxima of each region using theMarsBaR-toolbox (http://marsbar.sourceforge.net/).
Results
Behavioral data. The error rate and RTs areshown in Fig. 2. For the error rate, an rANOVA
with two factors (construction [active, passive,
potential] # scrambling [!scrambling, Dscrambling])
showed that both main eﬀects of construction (F(2,30) F 9.1, P F 0.0008) and scrambling (F(1, 15) F
6.5, P F 0.02) were signiﬁcant without the interaction of construction by scrambling (F(2, 30) F 0.47,
P F 0.9) (Fig. 2A). These main eﬀects were due tothe fact that scrambled sentences were more diﬃcult
than the others, and the tasks became more diﬃcult
under the active, passive and potential conditions inthis order.
Regarding RTs, there were signiﬁcant maineﬀects of construction (F(2, 30) F 52, P < 0.0001)
and scrambling (F(1, 15) F 30, P < 0.0001), as well
as a signiﬁcant interaction between them (F(2, 30) F
7.3, P F 0.03) (Fig. 2B). Based on these results, we
designated Act, ActD, and Pas the easier conditions,and called PasD, Pot, and PotD the harderconditions. Indeed, paired t-tests showed that themean of the RTs of the harder conditions was
signiﬁcantly longer than that of the easier conditions(t(47) F 12, P < 0.0001). Potential eﬀects of task
diﬃculty on brain activations will be considered laterin the Results section.
Syntax-related activations in localized regions. Noting the signiﬁcant diﬀerence in the RTs
between the harder and easier conditions, we ﬁrst
examined brain activations by the contrast [Hardercond.] ! [Easier cond.] (Fig. 3A). The most prominent activation was observed in the left frontal
cortex including the grammar center, i.e., the L.
F3op/F3t and L. LPMC. The overall activation
was consistent with the results of the contrast [Twoargument ! Control] reported previously;6) additional activation was observed in the thalamus, caudate,and putamen, as well as in the midbrain (Table 3).
Next we examined the main eﬀects of construction by the conjunction of contrasts [Passive !
Active] and [Potential ! Passive] (Fig. 3B). The
most prominent activation was found in the L.
F3op/F3t and L. LPMC, and ventrally extended to
the L. F3O. The medial pre-supplementary motor
area (pre-SMA) was also activated (Table 3). We
further examined the main eﬀects of scrambling, i.e.,

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Frontal activation due to construction and scrambling in a sentence517

Fig. 2. Histograms for the error rate (A) and reaction times (RTs) (B). Error bars indicate the standard error of the mean for theparticipants. The RTs under the harder conditions (PasD, Pot, and PotD) were signiﬁcantly longer than those under the easierconditions (Act, ActD, and Pas). An asterisk indicates P < 0.0001 (Paired t-test).

[Dscrambling] ! [!scrambling]. The activation was
clearly localized in the L. dF3op/F3t and extended
to the L. LPMC (Fig. 3C, Table 3), which wasconsistent with our hypothesis.
The cortical activations modiﬁed by syntactic loads. We further selected a local maximumof the L. dF3op/F3t based on the focal activation
shown in Fig. 3C and Table 3. Figure 4A shows the
step-wise percent signal changes for the two-argument conditions, demonstrating synergistic eﬀects
of construction and scrambling, in the order of theactive, passive and potential conditions, as well as in

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[Vol. 93,

the order of the [!scrambling] and [Dscrambling].
We also selected each local maximum of the L.
LPMC, L. F3O, and medial pre-SMA (left local
maximum) based on the activation shown in Fig. 3B;
the potential sentences induced signiﬁcantly higher
activations than the active sentences in these regions(Fig. 4B–D). We further selected a local maximumof R. F3op/F3t from the various activated regions
shown in Fig. 3A, which showed signiﬁcant activations only under the harder conditions (Fig. 4E). To
examine any eﬀects of task diﬃculty or general
cognitive loads (other than linguistic eﬀects) on theactivations, we further tested whether there was acorrelation between the performances and percent
signal changes in the L. dF3op/F3t under the harderconditions, which was consistently activated byboth main eﬀects. To estimate the performances ofindividual participants, we used inverse eﬃciency
scores (IES F RTs/Accuracy)14) under the harderconditions. As shown in Fig. 4F, no signiﬁcantcorrelation was observed (R F 0.32, P F 0.23), excluding the possibility that activations were due totask diﬃculty. We conclude that the activations in
the L. dF3op/F3t were mainly reﬂected the loads ofsyntactic processing.
Discussion

Fig. 3. Syntax-related activations in localized regions. (A)Cortical regions identiﬁed by [Harder cond.] ! [Easier cond.].
Activations were projected onto the left (L) and right lateralsurfaces of a standard brain (FWE-corrected P < 0.05). Medial
sections are also shown. (B) Cortical regions identiﬁed by the
conjunction of [Passive ! Active] and [Potential ! Passive].
Note the prominent activations in the left inferior frontal gyrus.
(C) Cortical regions identiﬁed by [Dscrambling] ! [!scrambling]. Activations were further localized in the L. dF3op/F3t,
extended to the L. LPMC.

Using the various sentence types under the twoargument conditions, we clariﬁed three major points.
First, we found that the main eﬀects of construction
and scrambling, as well as the contrast [Hardercond. ! Easier cond.], consistently activated the left
frontal cortex including the L. dF3op/F3t and L.
LPMC (Fig. 3). Secondly, the main eﬀects of scrambling clearly localized activation in the L. dF3op/
F3t and L. LPMC (Fig. 3C), indicating the morenarrowed down processing of syntax. Thirdly, stepwise percent signal changes were observed in the L.
dF3op/F3t (Fig. 4A), demonstrating synergistic
eﬀects of construction and scrambling, in the orderof the active, passive, and potential conditions, aswell as in the order of the [!scrambling] and[Dscrambling]. Moreover, from those activations, we
successfully excluded any eﬀects of the order ofgrammatical particles, -ga and -ni, which would beﬁnalized at the surface level. If the order of -ga and -ni
were a key factor, then the responses to Pas and
PotD, or those to PasD and Pot, should have been
comparable (see Table 1). These results demonstrate
the abstract and intensive nature of syntactic processing carried out by the grammar center, which wasmuch greater than expected from previous results.

No. 7]

Frontal activation due to construction and scrambling in a sentence

Table 3.

519

Cortical regions identiﬁed by the contrasts

Brain region

BA

Side

x

L

!42

L

!42

z

Z

Voxels

2

47

6.7

4119

2

26

6.7

*

y

[Harder cond.] ! [Easier cond.]
LPMC

6/8

F3op/F3t

44/45

L

!48

11

23

7.0

*

F3t
F3O

45
47

L
L

!42
!33

44
26

2
!4

6.7
7.0

*
*

pre-SMA

6/8

M

!3

11

50

7.1

*

M

!9

!16

5

4.8

*

Caudate/Putamen

L

!15

8

5

4.9

*

Midbrain

M

!6

!19

!13

4.9

*

Thalamus

6

!25

!13

4.6

*

IPS/AG

7/39

L

!33

!58

35

7.1

2007

IPS/AG/SMG

7/39/40

R
R

36
48

!58
!34

41
44

6.0
3.3

*
*

M

!6

!76

35

4.9

*

LPMC

6/8

R

33

!1

47

5.2

1173

F3op/F3t

44/45

R

51

23

32

5.4

*

F3O

47

R

30

29

!1

6.8

*

MTG

21

L

!60

!37

!7

5.0

580

Cuneus/Precuneus

pMTG/ITG

37/19

L

!45

!49

!22

4.1

*

LG/FG
LG/FG

18/19
18/19

L
R

!24
24

!85
!85

!19
!13

5.5
4.1

*
272

R

27

!64

!34

4.4

*

L

!42

2

47

4.2

840

L

!42

2

26

4.4

*

L

!45

11

23

4.7

*

L

!54

26

14

3.4

*

L
L

!45
!51

44
17

2
!1

4.2
3.5

*
*

Cerebellum[Passive ! Active] & [Potential ! Passive]
LPMC
F3op/F3t

6/8
44/45

F3O

47

L

!33

26

!1

4.4

*

pre-SMA

6

M

!3

14

50

5.1

197

LPMC

6/8

L

!42

!1

26

3.8

229

dF3op/F3t

44/45

L

!48

14

20

4.0

*

L

!60

11

17

3.2

*

[DScrambling] ! [!Scrambling]

Stereotactic coordinates (x, y, z) in the MNI space are shown for each activation peak of Z values. The threshold is set at uncorrected
P < 0.001 for the voxel level and at corrected P < 0.05 for the cluster level, with FWE correction across the whole brain. The region
with an asterisk is included within the same cluster shown one row above.

Scrambling in Japanese does not change thegrammatical relations and semantic roles of asentence (see Table 2),15),16) whereas there areinformation structure distinctions (e.g., emphasis)
related to scrambling. Regarding the signal enhancement for the L. dF3op/F3t under the [Dscrambling]
conditions, we propose that this can be estimatedbased on the syntactic structures of a sentence, more

speciﬁcally by the Degree of Merge (DoM), a key
computational concept that we previously introduced.17) The DoM is deﬁned as the maximum depthof merged subtrees within a given tree structure of asentence, thereby quantifying the complexity of that
sentence. Indeed, the DoM was able to successfully
account for syntax-selective activations in the L.
dF3op/F3t and supramarginal gyrus (SMG).18) As

520

K. TANAKA et al.

[Vol. 93,

Fig. 4. The cortical activations modiﬁed by syntactic loads. Histograms for the percent signal changes are shown for each local maximumof the L. dF3op/F3t (A), L. LPMC (B), L. F3O (C), pre-SMA (D), and R. F3op/F3t (E). An asterisk indicates P < 0.0001 (Paired
t-test). The signal changes are shown with reference to the SC condition. (F) The scatter plot for the percent signal changes in the L.
dF3op/F3t and the IES (F RTs/accuracy) under the harder conditions, without a signiﬁcant correlation.

discussed previously (see Fig. 6B in Ohta et al.
(2013)17)), the DoM of a scrambled sentence “ -o-ga hiiteru” becomes three, while that of thecorresponding active sentence “ -ga -o hiiteru”
becomes two. Likewise, the scrambled sentences

always yielded at least one more DoM than thecorresponding passive or potential sentences, explaining the signal enhancement observed here.
It should be noted that the DoM of a passive
sentence becomes larger than that of the corre-

No. 7]

Frontal activation due to construction and scrambling in a sentence

sponding active sentence, because of forming asubordinate clause within the main clause “ -ga +-(r)are-ru”.17) On the other hand, the DoMs under
the Pas and ActD conditions become comparable(see Figs. 6B and 7 in Ohta et al. (2013)17)),consistent with the similar signal changes observed
under these conditions (Fig. 4A–D). As indicated bya linguistic study,2) the base form of “Taroo-ni(-wa)
eigo-ga hanas-e-ru” (“Taroo can speak English”) is
an embedded sentence “Taroo [Taroo eigo hanas]e-ru”, explaining the larger DoM of the potential
sentences than active sentences. In addition, potential sentences require an NP-deletion together with
“Subject ni-Raising”,2) which may explain the signal
enhancement for the potential sentences relative tothe passive sentences (Fig. 4A–D). The activatedregions for the main eﬀects of construction (Fig. 3B),
which were much wider than those for the maineﬀects of scrambling (Fig. 3C), indicate the presenceof such additional syntactic processes. Moreover,the determination of the grammatical relations andsemantic roles would become more intricate underthe mixed conditions of the Act, ActD, Pas, PasD,
Pot, and PotD (see Table 2), which explains moreenhanced activations than our previous work.5)
In a previous study using the picture-sentence
matching task, we examined functional connectivity
among 14 regions in the normal brain, and identiﬁed
three syntax-related networks among these regions.6)
The ﬁve activated regions shown in Fig. 4 were
all included in these networks. The L. dF3op/F3t,
medial pre-SMA, and R. F3op/F3t were included
in Network I, which is related to syntax and its
supportive system; the L. LPMC was included in
Network II, which plays a role of syntax and input/
output interface for linguistic processing; and the L.
F3O was included in Network III, which subserves
the syntax-semantic interaction. Another patient
study also indicated critical connections between
the L. dF3op/F3t and the left intraparietal sulcus(L. IPS), between the L. LPMC and L. angular gyrus(AG), and between the L. F3t (ventral F3t) and L.
F3O.19) It is interesting to note that all of theseregions were actually more activated under the newly
introduced Harder conditions (Fig. 3A, Table 3).
These results indicate that all of the three syntaxrelated networks contribute to the synergistic eﬀects
of construction and scrambling on the corticalactivation.
We also found additional activations in thethalamus and caudate/putamen, as well as the
midbrain by the contrast [Harder cond. ! Easier521

cond.]. The left caudate has been suggested to besensitive to changes in the language or word
meaning.20) In a study using depth recordings, thethalamus responded to syntactic or semantic errors
in auditorily presented sentences.21) Because the headof the caudate receives strong projections from theprefrontal cortex and thalamus, the cortico- andthalamic-caudate pathways may play a role inlinguistic processing as well. In the present study,
we clearly showed that activations of the syntaxrelated regions were modiﬁed by the two factors ofconstruction and scrambling. It remains a question
for future studies how the syntax-related networks
are aﬀected by lesions in the grammar center, when
the same task and conditions are used. Such lesion
studies could elucidate the causal link between
activations and speciﬁc processes of syntax in thebrain.
Acknowledgements

We thank N. Yusa for suggesting the use of
potential sentences and other helpful input, N.
Komoro for technical assistance, and H. Matsuda
for administrative assistance.
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(Received Mar. 13, 2017; accepted May 26, 2017)