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Brain & Language 107 (2008) 81–89
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Syntax in a native language still continues to develop
in adults: Honoriﬁcation judgment in Japanese q
Kanako Momo a,b, Hiromu Sakai c, Kuniyoshi L. Sakai a,b,*a

Department of Basic Science, Graduate School of Arts and Sciences, The University of Tokyo, Komaba, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japanb
CREST, Japan Science and Technology Agency, Kawaguchi-shi 332-0012, Japanc
Graduate School of Education, Hiroshima University, 1-1-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8524, Japan
Accepted 3 December 2007
Available online 31 January 2008

Abstract
Native languages (L1s) are tacitly assumed to be complete and stable in adults. Here we report an unexpected individual variation injudgment of L1 regarding Japanese sentences including honoriﬁcation, and further clarify its neural basis with functional magnetic resonance imaging (fMRI). By contrasting an honoriﬁcation judgment task with a spelling judgment task, the lower performance group
showed more extensive activation in the left inferior frontal gyrus than did the higher performance group. Moreover, activation in
the left dorsal and ventral triangular parts negatively correlated with the performance of the honoriﬁcation judgment task. This modulation pattern demonstrates that cortical activations recruited for sentence processing depend on individual performances even in L1.
 2007 Elsevier Inc. All rights reserved.
Keywords: Language; Sentence processing; Syntax; The frontal cortex; fMRI

1. Introduction
Previous neuroimaging studies have clariﬁed the corticalactivations selective to syntactic processing (Embick, Marantz, Miyashita, O’Neil, & Sakai, 2000; Friederici, Opitz, &von Cramon, 2000; Hashimoto & Sakai, 2002; Suzuki &Sakai, 2003), but no individual diﬀerences have beenreported for such activation related to the processing of
native languages (L1s). If L1s are already complete and staq
We thank N. Saeki for her technical assistance, and S. Matsukura forher administrative assistance. This study was supported by a Core
Research for Evolutional Science and Technology (CREST) grant fromthe Japan Science and Technology Agency, by Grants-in-Aid for ScientiﬁcResearch on Priority Areas (‘‘System study on higher-order brain
functions’’, Nos. 17022013, 17022030, and 18020022) from the Ministryof Education, Culture, Sports, Science, and Technology of Japan.
*
Corresponding author. Address: Department of Basic Science, Graduate School of Arts and Sciences, The University of Tokyo, Komaba, 3-8-1
Komaba, Meguro-ku, Tokyo 153-8902, Japan. Fax: +81 3 5454 6261.
E-mail address: sakai@mind.c.u-tokyo.ac.jp (K.L. Sakai).

0093-934X/$ - see front matter  2007 Elsevier Inc. All rights reserved.
doi:10.1016/j.bandl.2007.12.003

ble in adults, as is widely assumed to be true, then there
might be no individual diﬀerences regarding its competence. However, more complex aspects of language processing may reveal individual variation even in theperformance of L1s. In the present study with native
Japanese speakers, we focus on ‘‘honoriﬁcation’’ in theJapanese language, deﬁned in a narrow sense excluding
so-called beautiﬁcation (e.g., ‘‘o-kane’’ and ‘‘o-tera’’) andpolite expression (Shibatani, 1990). The honoriﬁc expressions are commonly used to show respect to honored persons, but whose actual usage is rather complicated. For
example, in the sentence ‘‘anata-ga watasi-o o-maneki-ninaru’’ [you-Nom (nominative case) I-Acc (accusative case)invite-SH (subject honoriﬁcs); ‘‘you invite me’’], SH in theform of o-V-ni-naru (V, verb) should be used because anhonored person ‘‘anata’’ [‘‘you’’] is a subject. In contrast,in the sentence ‘‘watasi-ga anata-o o-maneki-suru’’ [I-Nom
you-Acc invite-OH (object honoriﬁcs); ‘‘I invite you’’], OH
in the form of o-V-suru should be used because the samehonored person ‘‘anata’’ [‘‘you’’] is now an object. TheseAuthor's personal copy

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K. Momo et al. / Brain & Language 107 (2008) 81–89

sentences are based on a ﬁxed agreement between the caseof an honored person and the form of honoriﬁcs (SH or
OH), and thus crossed combinations become grammatically incorrect (‘‘*anata-ga watasi-o o-maneki-suru’’ and‘‘*watasi-ga anata-o o-maneki-ni-naru’’). Because honoriﬁcation is mainly used on formal occasions and thus
optional (‘‘anata-ga watasi-o maneku’’ without SH and‘‘watasi-ga anata-o maneku’’ without OH are acceptable),
we expect an individual variation in its actual performanceas well as in the associated responses of brain regions
responsible for this linguistic processing.
It is known in linguistics that the structural requirement
for sentences regulates the application of the formal syntactic operation, which includes a mechanism called ‘‘Agree’’as its core. The syntactic operation is provided by universal
grammar and thus predicted to be available to every humanlanguage (Chomsky, 2000). Its actual application is, on theother hand, subject to cross-linguistic parametric variation,
depending on the availability of the relevant syntactic features in the lexicon (Fukui & Sakai, 2003). Thus, one important purpose of the present experiment is to see whether
Japanese speakers, whose grammar does not generally
employ an agreement rule for case, number, and gender,
are nonetheless capable of carrying out such syntactic computation properly once the relevant feature is provided byhonoriﬁcation. This last point has been a subject of debate;while some linguists regard Japanese honoriﬁcation as an
example of purely semantic/pragmatic processing controlled by social factors, others have proposed that honoriﬁcation actually involves syntactic computation in addition
to semantic/pragmatic factors [(Boeckx & Niinuma, 2004;
Gunji, 1987; Harada, 1976; Ivana & Sakai, 2007) for syntactic account for Japanese honoriﬁcation, and (Bobaljik &Yatsushiro, 2006) for criticism of such account].
Besides semantic/pragmatic processing and syntactic
computation, Japanese honoriﬁcation involves morphological processing. The honoriﬁc preﬁxes o and go are added
to a noun in order to express respect toward the person
related to the noun. Only one of two honoriﬁc preﬁxes isallowed for a noun and most native speakers acquire thisknowledge. For example, ‘‘tikara’’ [‘‘power’’] takes the honoriﬁc preﬁx of o (‘‘o-tikara/*go-tikara’’), whereas ‘‘rikai’’[‘‘understanding’’] takes the honoriﬁc preﬁx of go (‘‘gorikai/*o-rikai’’). This preﬁx choice depends on morphological knowledge of idiosyncratic word class membership ofthe noun stem (Sino-Japanese versus Yamato vocabulary).
This distinction is also complicated (e.g., ‘‘o-ningyou/*goningyou’’ [‘‘doll’’]), partly because the property of being
Sino-Japanese or Yamato is not always predictable simply
from inspection of the stem (Ito & Mester, 2003). In addition to this purely word-internal morphological knowledge,
the honoriﬁc forms SH and OH have distinct morphosyntactic features as well; SH consists of three morphemes(o, ni, and naru), whereas OH consists of two morphemes(o and suru). By exchanging the morpheme ni, normal/
anomalous pairs of honoriﬁc forms can be created (‘‘o-Vni-naru/*o-V-naru’’ and ‘‘o-V-suru/*o-V-ni-suru’’). Here,naru obligatorily governs a -ni (dative) marked complement, while suru equally obligatorily governs an accusative(or bare) complement. Processing of this type of knowledge
is again independent of honoriﬁcation, because light verbs(naru and suru) can take a noun phrase without honoriﬁcation (e.g., ‘‘byoki-ni-naru’’ [‘‘get sick’’], ‘‘byoki(-o)-suru’’[‘‘have sickness’’], and ‘‘byoki-ni-suru’’ [‘‘cause sickness’’])(Ivana & Sakai, 2007). To elucidate cortical activations
elicited by the syntactic operation in Japanese honoriﬁcation, a control condition for these two types of morphological and morphosyntactic computation on honoriﬁcforms should be properly established. We thus employedhonoriﬁcation (HO) and morphological/morphosyntactic(MO) judgment tasks, in which the participants detected
an anomaly in a short sentence (Table 1). We also tested
a semantic (SE) judgment task to characterize any corticalactivation related to sentence meaning, together with aspelling (SP) judgment task to control visual and motor
factors as well as automatic linguistic processes.
In our previous studies, we proposed that the left inferior frontal gyrus (IFG), including the lateral premotor
cortex (LPMC), the triangular part of the IFG (F3t), andthe opercular part of the IFG (F3op), specialize in syntactic
processing, whereas the orbital part of the IFG (F3O) subserves sentence comprehension (Sakai, 2005). If honoriﬁcation simply reﬂects semantic processing, then the activation
would be limited to the left F3O and temporal regions.
However, if honoriﬁcation is related to syntactic processing, then the left LPMC and F3t/F3op would be signiﬁcantly activated. Conversely, the left F3O and temporal
regions would be activated in the SE task, since explicit
semantic processing is required by the task. The present
paradigm will thus be useful for elucidating multiple linguistic processes involved in sentence processing.
2. Materials and methods
2.1. Participants
In this study, 44 native speakers of Japanese (aged 18–38
years, 12 females) participated in the experiment. All participants showed right-handedness (laterality quotients:
60–100) by the Edinburgh inventory (Oldﬁeld, 1971). None
had a history of neurological or psychiatric disease.
Informed consent was obtained from each participant after
the nature and possible consequences of the studies had
been explained. Approval for these experiments was
obtained from the institutional review boards of the University of Tokyo, Komaba.
2.2. Stimuli
We prepared 144 sentences for the present study (seeTable 1 for examples). A basic stimulus set consisted of
24 normal Japanese sentences with honoriﬁcation, whichwere one of four sentence types: [S-ga N-de/ni O-o o-Vni-naru], [S-ga O1-ni O2-o o-V-ni-naru], [S-ga N-de/karaAuthor's personal copy

K. Momo et al. / Brain & Language 107 (2008) 81–89

83

Table 1
Examples of stimuli used in the honoriﬁcation (HO), morphological/morphosyntactic (MO), semantic (SE), and spelling (SP) judgment tasks
Tasks

Normal sentences

Anomalous sentencesHO

anata-ga watasi-ni booru-o o-nage-ni-naru
you-Nom I-Dat ball-Acc throw-SH‘you throw a ball to me’anata-ga watasi-ni booru-o o-nage-suru
you-Nom I-Dat ball-Acc throw-OH‘you throw a ball to me’MOwatasi-ga anata-ni go-iken-o o-kiki-suru
I-Nom you-Dat HP-opinion-Acc ask-OH‘I ask your opinion’watasi-ga anata-ni o-iken-o o-kiki-suru
I-Nom you-Dat HP-opinion-Acc ask-OH‘I ask your opinion’SE

sensei-ga denwa-de gakusei-o o-home-ni-naru
teacher-Nom telephone-PP student-Acc praise-SH‘the teacher praises the student on the phone’sensei-ga booru-de gakusei-o o-home-ni-naru
teacher-Nom ball-PP student-Acc praise-SH‘the teacher praises the student on the ball’SPgakusei-ga sensei-ni o-kaban-o o-moti-suru
student-Nom teacher-Dat HP-bag-Acc bring-OH‘the student brings the teacher his bag’

gakusei-ga sensei-ni o-kaban-o o-timo-suru
student-Nom teacher-Dat HP-bag-Acc bring-OH‘the student brings the teacher his bag’Abbreviations used: Nom, nominative case; Dat, dative case; Acc, accusative case; PP, postposition; HP, honoriﬁc preﬁx; SH, subject honoriﬁcs; OH,
object honoriﬁcs. Errors are underlined.

O-o o-V-suru], and [S-ga O1-ni O2-o o-V-suru] (S, subject;
N, noun; O1, indirect object; O2, direct object; V, verb;-ga, nominative marker; -de/-ni/-kara, postpositions meaning ‘‘by means of’’, ‘‘to’’, and ‘‘from’’, respectively; -o, accusative marker; -ni, dative marker). We also included
another set of 24 normal sentences without honoriﬁc
expressions, so that the participants paid full attention towords other than honoriﬁc forms.
By modifying the basic set of sentences, we created four
diﬀerent types of anomalous sentences for the HO, MO,
SE, and SP tasks (24 each; Table 1), which had the same
lexical materials and diﬀered only regard to the types oferrors. HO errors were made by exchanging the SH andOH forms. MO errors were made either by exchanging
the honoriﬁc preﬁxes (o-N/go-N) or by using morphosyntactically incorrect forms of SH and OH (*o-V-ni-suru/*o-V-naru). SE errors were made by exchanging nouns
between two sentences, so that there was a contextually
inappropriate noun in a sentence. SP errors were madeby exchanging two adjacent letters in a word. The stimulus
presentation and behavioral data collection were controlledusing the LabVIEW software and interface (National
Instruments, Austin, TX). Each sentence was shown in yellow letters in the hiragana and kanji writing system against
a dark background. For ﬁxation, a red cross was always
shown at the center of the screen.
2.3. Tasks
In the functional magnetic resonance imaging (fMRI)
sessions, the HO, MO, SE, and SP tasks were conductedin a block design with twelve runs; each run consisted of
24 sentences (6 sentences · 4 tasks). In each block, normal
and anomalous sentences were included in the proportionof 3:3, 2:4, or 1:5 in a pseudo-randomized manner. In orderto reduce any eﬀects related to task order, we used four
sequences for each run: SP–HO–SE–MO and SE–MO–
SP–HO alternatively for one-half of the participants, aswell as SP–MO–SE–HO and SE–HO–SP–MO alternatively

for the other half of the participants. In each trial, thename of each task was presented for 400 ms, followed bya sentence presented for 4300 ms. Participants covertly
read sentences and judged whether or not it was a correctsentence, responding by pushing one of two buttons.
Before the fMRI sessions, the participants received a shorttraining session outside the scanner.
2.4. fMRI data acquisition and analyses
The participants were in a supine position, wearing earplugs and an eyeglass-like MRI-compatible display (resolution, 800 · 600; VisuaStim XGA; Resonance Technology,
Northridge, CA), and their heads were immobilized withpadding inside the radio-frequency coil. The fMRI scans
were conducted using a 1.5 T MRI system (STRATIS II, Premium; Hitachi Medical Corporation, Tokyo, Japan). Usinga gradient-echo echo-planar imaging sequence (repetitiontime, 5 s; echo time, 50.5 ms; ﬂip angle, 90; ﬁeld of view,
192 · 192 mm2; resolution, 3 · 3 mm2), 16 horizontal slices
were scanned, each 6 mm thick and having a 1 mm gap.
Data analyses were performed using SPM2 statisticalparametric mapping software (Wellcome Department of
Imaging Neuroscience, London, UK). The functional volume data were realigned in multiple runs and we removed
runs that included data with a translation of >2 mm in
one of the three directions and a rotation of >1.4. The data
were normalized to the standard brain, resampled every
3 mm using bilinear interpolation, and smoothed with anisotropic Gaussian kernel of 9 mm full-width at half-maximum. Low-frequency noise and global changes in activity
were further removed. In order to investigate task-speciﬁc
eﬀects, random-eﬀects analyses (one sample t-test) were performed. In each comparison, thresholds were established instatistical parametric maps at the uncorrected p < .0001 forthe voxel level. Statistical signiﬁcance of correlation between
the behavioral data and the signal changes was further
tested using Spearman rank correlation, which is resistantto outliers, i.e., high leverage points. Mean signal changes

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K. Momo et al. / Brain & Language 107 (2008) 81–89

at an activation focus under each condition were estimatedusing a 5-s shifted block for the hemodynamic delay.

A 100

3. Results

Accuracy of MO (%)

84

80

60

40
40

B 100
Accuracy (%)

The accuracy of the HO, MO, SE, and SP tasks was
78.4 ± 16.1%, 81.2 ± 11.7%, 93.4 ± 4.8%, and 95.0 ±
4.7% (mean ± SD, n = 44), respectively, and the reaction
times (RTs) of each task were 2957 ± 458 ms, 2867 ±424 ms, 2623 ± 384 ms, and 2389 ± 450 ms, respectively.
According to an analysis of variance (ANOVA), there weresigniﬁcant main eﬀects of task on both accuracy(F(3, 172) = 28, p < .0001) and RTs (F(3, 172) = 16, p <.0001). According to post hoc Tukey–Kramer tests, theaccuracy of the HO task was signiﬁcantly lower than thoseof the SE and SP tasks (p < .05), and the RTs of the HO
task were signiﬁcantly longer than those of the SE andSP tasks (p < .05). Similarly, the accuracy of the MO task
was signiﬁcantly lower than those of the SE and SP tasks(p < .05), and the RTs of the MO task were signiﬁcantly
longer than those of the SE and SP tasks (p < .05). However, both the accuracy and the RTs of the HO and MO
tasks, as well as the accuracy of the SE and SP tasks,
showed no signiﬁcant diﬀerence.
Because there were large individual diﬀerences in the
behavioral data of the HO and MO tasks, we examinedthe correlation between the performance of the HO andMO tasks. We found that the accuracy of the HO andMO tasks was signiﬁcantly correlated (r = .70, p < .0001)(Fig. 1A). The RTs of these tasks were also signiﬁcantly
correlated with each other (r = .87, p < .0001). We further
analyzed the distinct types of the MO task separately,
namely the morphological (o and go) and morphosyntactic(ni-naru and suru) types. There was a signiﬁcant correlation
between the accuracy for the two types of the MO task(r = .36, p = .02). Moreover, the accuracy of the HO tasksigniﬁcantly correlated with that for the morphologicaltype (r = .35, p = .02), and even more clearly with thatfor the morphosyntactic type (r = .73, p < .0001). Therefore, the capability of processing honoriﬁcation was also
related to more fundamental performances of both morphological and morphosyntactic computation.
All participants were then divided into two groups at the
84% accuracy level (the median) of the HO task: low andhigh performance groups. An ANOVA on the accuracy(task · group) showed a signiﬁcant interaction (F(3,168) = 21, p < .0001), whereas there was no interaction
on the RTs (F(3, 168) = .2, p = .88). According to pairedt tests, there was a signiﬁcant diﬀerence in the accuracyof the HO and MO tasks for both groups, but in opposite
directions (Fig. 1B); the diﬀerence in RTs of the HO andMO tasks was signiﬁcant for the low performance groupalone (Fig. 1C). The behavioral results also indicated thatthe HO and MO tasks were more demanding than the
SE and SP tasks for both groups.

60
80
Accuracy of HO (%)

*

*

*

100

*

80
60
40
20
0

C
Reaction time (ms)3.1. Behavioral results

HO MO SE SP

*
3000

*

*

HO MO SE SP

*

*

2000

1000

0

HO MO SE SP

HO MO SE SP

Fig. 1. Behavioral data. (A) Signiﬁcant correlation between the accuracyof HO and MO. (B) Accuracy (means ± SEM) of each task in the low andhigh performance groups. Filled and open circles/bars denote the low andhigh performance groups, respectively. (C) RTs of each task in the low andhigh performance groups. *p < .05 (paired t-test).

3.2. The task-selective activations in the left IFG
To elucidate any task-selective activations, the contrastsof HO–SP, MO–SP, and SE–SP were examined in eachgroup (Fig. 2 and Table 2). In the contrast of HO–SP,
we observed a marked diﬀerence in activated regions
between the low and high performance groups. The low
performance group showed signiﬁcant activations mostly
localized in the left IFG, including the left LPMC, dorsal
F3t (dF3t), ventral F3t (vF3t), and F3O (Fig. 2A). In thesame contrast for the high performance group, the left
IFG activation was greatly reduced and only the left
LPMC was signiﬁcantly activated within the left IFG,
together with the left parietal region and the cerebellum

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K. Momo et al. / Brain & Language 107 (2008) 81–89

85

Fig. 2. Task-selective eﬀects in the low and high performance groups. (A) The contrast of HO–SP in the low performance group. Note the signiﬁcantactivation in the left IFG. (B) The contrast of HO–SP in the high performance group. (C) The contrast of MO–SP in the low performance group. (D) The
contrast of MO–SP in the high performance group. (E) The contrast of SE–SP in the low performance group. (F) The contrast of SE–SP in the highperformance group. Note the selective activation in the left MTG.

(Fig. 2B). The contrast of MO–SP for the low performancegroup showed signiﬁcant activation in the left dF3t, left
F3O, and the right cerebellum (Fig. 2C). The same contrast
in the high performance group showed signiﬁcant activation in the left LPMC and left dF3t, together with the leftparietal region and the cerebellum (Fig. 2D). It is interesting to note that the activation patterns for the high performance group were similar between HO–SP and MO–SP,
whereas those for the low performance group were more
focal in MO–SP than in HO–SP. On the other hand, thecontrast of SE–SP resulted in similar activation patterns
for both the low and high performance groups, such thatthe left F3O and the left middle temporal gyrus (MTG)
showed signiﬁcant activation.
To further elucidate the task-selective activations in theleft IFG, the signal changes at the local maxima of the left
LPMC, dF3t, and vF3t (yellow1 dots in Fig. 2A) were compared among the tasks and groups (Fig. 3). In the left
LPMC ( 39, 3, 51), the signal change in the HO task
was signiﬁcantly larger than that of the SE task for the
low performance group (p = .001, paired t-test). For thehigh performance group, the signal change in the MO task
was signiﬁcantly larger than that of the SE task (p < .005)(Fig. 3A). In the left dF3t ( 42, 18, 27), the signal change
in both the HO and MO tasks was signiﬁcantly larger than1
For interpretation of the references to color in this text, the reader isreferred to the web version of this article.

that of the SE task (p < .0005 and p = .01, respectively) forthe low performance group (Fig. 3B). In the left vF3t ( 57,
15, 9), the signal change in the HO task was signiﬁcantly
larger than that of the SE task (p < .05) for the low performance group (Fig. 3C). Among these three regions, the signal change in the HO task for the low performance groupwas signiﬁcantly larger than that for the high performancegroup (p < .05). To summarize, both the HO and MO tasks
activated the left IFG in the low performance group, andthis eﬀect was stronger in the HO task than in the MO task.
3.3. The left dF3t and vF3t activations selectively modulatedby the accuracy of HO
To investigate whether individual diﬀerences in performance modulated cortical activations, regression analyses
were performed using all participants’ data regardless of
the low and high performance groups. A signiﬁcant negative correlation between the signal change in HO–SP and
the accuracy of the HO task was observed in the left
dF3t, vF3t, and other regions (Z > 3.25, uncorrectedp < .001) (Table 3). According to Spearman rank correlation tests, the negative correlation between the accuracyof the HO task and the signal change in HO–SP at each
local maximum of the left dF3t (rs = .37, p = .015) andvF3t (rs = .51, p = .0008; Fig. 3D) was signiﬁcant,whereas the RTs of the HO task were not signiﬁcantly correlated with the signal change (Table 4). In contrast, no signiﬁcant correlation was observed between the accuracy ofAuthor's personal copy

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K. Momo et al. / Brain & Language 107 (2008) 81–89

Table 2
Activated regions for each task in the low and high performance groups
Brain regions

BA

Side

x

y

z

Z

Low
HO–SP
LPMC
dF3t

6/8
45

vF3t
F3O
F2O
F2

45
47
47
46

F2/F1
F1
MTG
Angular g
Inferior parietal g
Precuneus
Cerebellum

10
8
21/22
39
7
19

MO–SP
LPMC
dF3t
vF3t
F3O
F2O
F2
F1
InsulaInferior parietal g
Precuneus
Cerebellum

SE–SP
dF3t
F3O
F1
MTG
Cerebellum

6/8
45
45
47
47
10
8
7
19

45
47
8
21/22

L
L
R
L
L
R
L
R
L
M
L
L
L
M
M
R
L
L
L
L
R
L
M
R
L
M
M
M
R
L
L
L
L
L
R

y

z

Z

45

9

48

4.6

6

30

45

3.8

24
57
54
30
39

3.9
4.8
4.7
3.9
5.1

48
33

4.2
3.8

High

39
42
45
57
42
45
42
42
33
6
57
39

3
18
30
15
36
51
51
42
60
42
30
60

51
27
24
9
3
12
3
21
6
42
9
33

5.5
4.8
3.7
4.3
3.8
3.8
4.3
4.5
3.9
4.5
3.9
4.2

0

69
84
75

33
15
48

4.3
4.4
4.6

6
24

x

51
51
42
39
36

18
24
24
54
57

27
3
9
9
3

5.2
3.8
4.2
3.9
3.8

39

21

9

3.8

42
45
27
42

4.3
4.3
3.8
5.2

27
12

3.9
4.2

9
6

4.1
3.9

51
30
0
9
36
39
48

9
18

45
42
39
3

42
45
51
21

21
3
0
9
30
54
27
51
51

69
66
84
84
21
27
18
33

66
66
66
87
78

12
30

45
12
63
33

72

6
15
3
57

4.7
4.5
4.3
3.9

54

4.5

84
75

27
48

5.0
5.2

30
36
51

12
48
3

4.2
4.1
4.3

78

45

5.3

Stereotactic coordinates (x, y, z) in the MNI space are shown for each activation peak of Z values. The threshold was set at uncorrected p < .0001 for voxel
level. Abbreviations used: BA, Brodmann’s area; L, left hemisphere; R, right hemisphere; M, Medial; g, gyrus; LPMC, lateral premotor cortex; dF3t, dorsal
triangular part of IFG; vF3t, ventral triangular part of IFG; F3O, orbital part of IFG; F2, middle frontal gyrus (MFG); F2O, orbital part of MFG; F1,
superior frontal gyrus; MTG, middle temporal gyrus.

the MO task and the signal change in MO–SP. Because ofthis HO task-selective modulation of activations in the left
dF3t and vF3t, we can exclude the possibility that the activations reﬂected any general cognitive factors including
task diﬃculty.
3.4. The contribution of other left frontal and temporal
regions in the tasks
In the left F3O ( 42, 24, 9) (a yellow1 dot in Fig. 2C),
the signal changes for the HO, MO, and SE tasks were all
signiﬁcantly larger than that of the SP task for both the low
and high performance groups (Fig. 4A). This result suggests that the F3O activation was equally enhanced bythese three tasks involving sentence comprehension, which

was in contrast to task-selective syntactic processing. In theleft MTG (–63, –51, 3) (a yellow1 dot in Fig. 2F), on theother hand, the signal change in the SE task was signiﬁcantly larger than that in the HO and MO tasks for thehigh performance group (p < .05), and the low performance group also showed similar tendency (Fig. 4B). This
result suggests that the MTG activation was selectively
required by the SE task involving explicit semantic
processing.
4. Discussion
The present study demonstrated that both the HO andMO tasks activated the left dF3t more in the low performance group than in the high performance group, and that

Author's personal copy

K. Momo et al. / Brain & Language 107 (2008) 81–89

L. LPMC
*

A
0.3

0.1

B

HO MO SE HO MO SE

L. dF3t
*
*
*

Side

45
45

F2
ITG
Fusiform g
Lingual/calcarine
Cerebellum

46
20/21
37
18

L
L
R
R
R
R
R
M

x

y
54
57
45
39
39
33
21
9

z
18
18
24
42
57
75
48
63

Z
30
3
24
21
3
3
0
42

3.3
3.4
3.4
3.6
3.9
3.4
3.4
3.7

Stereotactic coordinates (x, y, z) in the MNI space are shown for eachactivation peak of Z values. ITG, inferior temporal gyrus.

Table 4The correlation between the signal change of the left frontal regions andthe behavioral data

0.3
0.2

AccuracyHO

0.1
0L. dF3t
L. vF3t

HO MO SE HO MO SE

L. vF3tC*

0.4
Signal Change (%)

BA

dF3t
vF3t

RTs
MO

rs =
rs =

.37*
.51**

rs =
rs =

.26
.21

HO

MO

rs = .16
rs = .23

rs =
rs =

.08
.14

The signal changes in the left dF3t and vF3t were calculated at the local
maxima shown in Table 3. In these regions, the signal change in HO–SP
negatively correlated with the accuracy of the HO task, but the signal
change in MO–SP did not signiﬁcantly correlate with the accuracy of the
MO task. *p < .05, **p < .001 (Spearman rank correlation test).

*
0.3

A

0.2

L. F3O0.3

0.1
0

HO MO SE HO MO SE

L. vF3t
1.2

Signal Change (%)

Signal Change (%)

0.4

Signal Change (%)

Brain regions

0.2

0

D

*

*

Table 3The negative correlation between the signal change of HO–SP and theaccuracy of HO

0.2

0.1

0

0.8

HO MO SE

0.4

0.3

0
-0.4
30 40 50 60 70 80 90 100
Accuracy of HO (%)

Fig. 3. Signal changes in the left LPMC, dF3t, and vF3t. Taking the SP
task as a reference, the percent signal changes (means ± SEM ofparticipants in each group) in the HO, MO, and SE tasks are shown forthe left LPMC (A), dF3t (B), and vF3t (C) at the local maxima shown in
Fig. 2A and Table 2. (D) Signiﬁcant correlation between the accuracy of
the HO task and the signal change in HO–SP at the local maximum of theleft vF3t shown in Table 3. Filled and open bars denote the low and highperformance groups, respectively. *p < .05 (paired t-test).

HO MO SEL. MTGB
Signal Change (%)

Signal Change (%)

0.4

87

*
*

0.2

*

0.1

0
HO MO SEHO MO SE

Fig. 4. The signal changes of the left F3O and left MTG. (A) The signal
changes at the local maximum of the left F3O shown in Fig. 2C and Table
2. (B) The signal changes at the local maximum of the left MTG shown in
Fig. 2F and Table 2. *p < .05 (paired t-test).

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88

K. Momo et al. / Brain & Language 107 (2008) 81–89

the HO task elicited signiﬁcant responses in extensive left
IFG regions (the left LPMC, dF3t, and vF3t) when compared with other tasks. Moreover, the activations in the left
dF3t and vF3t were negatively correlated with the accuracyof HO. In contrast, the left F3O activation represents processing for sentence meaning, which is consistent with ourprevious proposal (Sakai, 2005). These results were striking
in three ways. First, the neuroimaging data suggested thatsyntactic computation is indeed involved in the processingof honoriﬁcation. Since the same basic set of sentences wasused for all of the four tasks, the direct comparisons
between two tasks eliminated any automatic syntactic processes that were sensitive to phrase structure building or
grammatical function assignment. We suggest the involvement of an agreement rule at some abstract levels in the
HO task, though the actual applications of the Agree operation should be further examined in the future study,
thereby comparing the Agree operation with other syntactic operations. Second, adults exhibit individual diﬀerences
regarding performances even in L1 syntax, which indeed
modulate cortical activations in speciﬁc regions. Third,
the lower activations in the left dF3t and vF3t may correspond to the higher proﬁciency in applying the syntactic
operation associated with honoriﬁcation. Taking theseresults together, they provide the ﬁrst direct evidence thatthe individual variation in proﬁciency of L1 syntax is speciﬁcally related to the left IFG function.
In contrast to the performance in second languages(L2s), that in L1 is by deﬁnition at the native-level of perfection, and there is little individual variation in its performance. However, the present results demonstrated thateven for native speakers there exists a grammatical feature,i.e., honoriﬁcation, which is diﬃcult to acquire and exhibit
individual diﬀerences in performance. It is also striking tonote that distinct activation patterns can be observed forthe low and high performance groups. The enhanced activations of the left LPMC, dF3t, and vF3t for the HO task
in the low performance group are consistent with previous
fMRI studies, as mentioned above. These enhanced activations cannot be explained by task diﬃculty in general, since
the contrast of MO–SP did not show such extensive activations, in spite of similar performances for the HO and MO
tasks when compared with the SP task (Fig. 1). This result
provides further support for our previous ﬁnding of selective activations in the left LPMC and dIFG, which were
demonstrated by direct contrasts between syntactic decision and recency memory tasks (Hashimoto & Sakai,2002).
Left F3O activation was observed consistently in theHO, MO, and SE tasks, suggesting that this activation subserves the sentence comprehension involved in these tasks.
This result is consistent with that of our previous studies(Homae, Hashimoto, Nakajima, Miyashita, & Sakai,
2002; Homae, Yahata, & Sakai, 2003), which clariﬁed
selective activation in this region for a sentence comprehension task. Furthermore, another fMRI study has demonstrated that the left MTG was more activated inanomalous sentences than in normal sentences (Suzuki &Sakai, 2003), which is consistent with our ﬁnding with
SE–SP. The left MTG activation in the present paradigm
may reﬂect enhanced semantic processing for explicitly
judging semantically normal/anomalous sentences.
Our recent fMRI study using English past tense verbs
has demonstrated that activations in the left dF3t ( 51,24, 24) and the left F3t/F3O ( 48, 21, 3) are negatively
correlated with the distinct factors of proﬁciency level andlanguage task demands in L2, respectively (Tatsuno &Sakai, 2005). In the present study, the left dF3t andvF3t activations were also negatively correlated with theaccuracy of the HO task even in L1 (Fig. 3D, Table 4).
Moreover, this signiﬁcant modulation was observed for
the HO task alone, indicating that activation in theseregions was more clearly sensitive to syntactic processingof honoriﬁcation than to morphological and morphosyntactic processing. There are at least two possibilities for
explaining such marked individual variation in L1. First,
the honoriﬁc expressions are fully acquired in a rich social
environment encountered at matured ages (Cook, 1996),
which are thus later than the hypothetical ‘‘sensitive period’’ for L1 and L2. Second, individual variation actuallyexists in every faculties of L1, but the ceiling eﬀects ofhigh performances might mask the most individual diﬀerences in L1 capability, except for morphology, morphosyntax, and syntactic computation reveled in the present
study. The direction of future research should be thus
the elucidation of the neural and computational mechanisms of L1 and L2 acquisition, as well as their developmental changes under the inﬂuence of education andsocialization.
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