A syntactic specialization for Broca’s area
David Embick*†‡, Alec Marantz*‡, Yasushi Miyashita*§, Wayne O’Neil*‡, and Kuniyoshi L. Sakai†¶储*Mind Articulation Project, International Cooperative Research Project, Japan Science and Technology Corporation, Tokyo 113-0034, Japan; †Department of
Cognitive and Behavioral Science, the University of Tokyo, Komaba, Tokyo 153-8902, Japan; ‡Department of Linguistics and Philosophy, Massachusetts
Institute of Technology, Cambridge, MA 02139; §Department of Physiology, the University of Tokyo School of Medicine, Tokyo 113-0033, Japan; and¶Core Research for Evolutional Science and Technology, Japan Science and Technology Corporation, Kawaguchi-shi 332-0012, Japan
Communicated by Morris Halle, Massachusetts Institute of Technology, Cambridge, MA, March 7, 2000 (received for review February 15, 2000)

Despite numerous aphasia and functional imaging studies, theexact correlation between cortical language areas and subcomponents of the linguistic system has not been established. Here, weused functional MRI to identify cortical areas specifically involved
in syntactic processing. An experimental design contrasted sentences containing grammatical errors with sentences containing
spelling errors. The ungrammatical sentences produced more activation in cortical language areas than did the sentences with
spelling errors, and the difference in activation was significantly
greater in Broca’s area than in Wernicke’s area or in the angulargyrus兾supramarginal gyrus. The present findings provide direct
evidence of a syntactic specialization for Broca’s area and establish
the existence of distinct modules for our knowledge of language.

Linguistic theory divides human linguistic ability into distinct
modules responsible for distinct aspects of our knowledge oflanguage. For instance, the syntactic component governs thehierarchical organization of words and phrases in sentences,whereas the phonological component is responsible for thesound structure of a language. The identification of specialized
cortical areas responsible for these distinct aspects of linguisticcompetence is a first step toward understanding how language isinstantiated in the brain. This study uses functional MRI (fMRI)
to identify cortical areas involved specifically in syntactic processing. The focus is on the role of Broca’s area in syntax, an issue
that has been debated from a number of different perspectives.
Event-related brain potential (ERP) studies have identified acomponent, the P600, which correlates with a subject’s recognition of syntactic ill formedness (1). However, the language
specificity of this component has been challenged (2), and thespecific cortical generator of the component has not been
localized. A second component, the left anterior negativity, hasalso been associated with error detection in grammatical processing (3, 4); its source is once again unclear, but its detection
by left-anterior electrodes is suggestive of the involvement ofBroca’s area. In the imaging literature, activation in Broca’s area
has been found for some linguistic tasks, whereas other studies
have argued for the involvement of Broca’s area in decidedly
nonsyntactic tasks, such as in the phonological processing ofwords or letters (5). Two prior imaging studies by Stromswold etal. (6) and Just et al. (7) have studied syntactic complexity andmade specific claims about Broca’s area. In these studies,increased sentential complexity correlates with an increase inactivity in Broca’s area. Activity in Broca’s area in these experiments either may stem from the fact that Broca’s area is
specifically involved in syntactic processing or may reflect ageneral increase in demands on the linguistic system or on verbal
short-term memory rather than syntactic processing per se. Just
et al. (7), noting an increase in activated voxels in both Broca’s
and Wernicke’s areas that correlated with sentential complexity,
concluded that increased sentential complexity resulted in the
recruitment of more neural tissue in each of a network of corticalareas; i.e., that increases were caused by an increase in complexity, with no region more specifically involved in sentential
processing than any other. Two recent fMRI studies (8, 9) haveclaimed to have evoked differential activity in Broca’s area insyntactic as opposed to semantic processing. However, syntactic
6150 – 6154 兩 PNAS 兩 May 23, 2000 兩 vol. 97 兩 no. 11

and semantic processing were involved in both contrasting
experimental conditions in these studies; moreover, neither
provides any independent support for their claims about theprocessing behind the experimental tasks, as the tasks lack anexperimental history in both cases.
Research on aphasia also provides contradictory hypotheses
about whether Broca’s area is specifically involved in syntax.
After Broca’s initial insight, Broca’s area was first regarded as aspeech production area, because patients diagnosed with Broca’s
aphasia were relatively or grossly inarticulate. Subsequent workon aphasic patients argued that Broca’s area is the locus ofsyntactic processing or of the grammatical system because of theagrammatism of Broca’s aphasics (10, 11). More recent studies,
however, have argued that there is dissociation between Broca’s
aphasics’ problems with syntactic processing兾comprehension
and lesions in Broca’s area (12, 13), although dissenting views
continue to be voiced (14).
Given this uncertainty about the role played by Broca’s area
in syntax, the present study seeks to identify brain areas associated specifically with syntactic processing, independent oferror detection requiring verbal short-term memory and of error
detection in a linguistic context. Our study combines a version of
the error-detection paradigm well exemplified in ERP studies ofsyntactic anomaly (15) with a linguistic control condition thatinvolves both normal sentence processing and error detection of
misspelled words, comparable in difficulty to syntactic error
detection.
Methods
Tasks. Sentences were divided into two conditions, grammar(GR) and spelling (SP). The sentential stimuli use the same
lexical material across conditions and differ only in the types oferrors they contain (Table 1). Sentences of the GR type contained one or two errors in word order; sentences of the SP typecontained one or two errors in spelling. In each condition,
stimuli were presented visually, and the task was to respondwhether the sentence contained one or two errors by pressing
one of two buttons attached to pneumatic switches. By using thisone- vs. two-error design, we were able to place stimuli of thesame error type in blocks, while maintaining a task that requires
the processing of each stimulus. Subjects were instructed to readevery sentence slowly and carefully before responding. In an
additional control (CO) condition, subjects viewed rows ofcolored Ls and Ts, with a basic association between a single color
and a letter, for instance, purple Ts and yellow Ls. In this case,the task was to find matches for a target combination in the
Abbreviations: AG/SMG, angular gyrus/supramarginal gyrus; CO, control; fMRI, functional
MRI; GR, grammar; RT, reaction time; SP, spelling; ERP, event-related brain potential.
储To whom correspondence and reprint requests should be addressed at: Department of

Cognitive and Behavioral Science, Graduate School of Arts and Sciences, the University ofTokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan. E-mail: sakai@mind.c.u-tokyo.ac.jp.
The publication costs of this article were defrayed in part by page charge payment. This
article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C.
§1734 solely to indicate this fact.
Article published online before print: Proc. Natl. Acad. Sci. USA, 10.1073兾pnas.100098897.
Article and publication date are at www.pnas.org兾cgi兾doi兾10.1073兾pnas.100098897

Table 1. Sample stimuli used in GR and SP conditions
Error
1
1
1
2
2
2

GR

SP

Bill wrote paper a about the discussion of the treaty.
Mary wanted to read about the destruction the of city
John drove to store the in a very fast car two weeks ago.
Mary asked question a about theorem the in class.
The editor read article the with revisions Anne’s after lunch.
Tom drove the to beach on Will’s fast extremely motorcycle.

Bill wrote a papger about the discussion of the treaty.
Mary waanted to read about the destruction of the city.
John drove to the store in a very fasvt car two weeks ago.
Mary askepd a question about the theorem in cllass.
The editor read the artilce with Anne’s rezvisions after lunch.
Tom drove to tfe beach on Will’s extremely fqast motorcycle.

upper left-hand corner, where the letter兾color violated the basic
pattern; the subject, scanning the further rows of letters, responded as to whether there was a single match to this combination or two matches. Each of the SP and GR conditions
combines linguistic processing with an error-detection task. The
difference between the two lies in the different types of errors:
grammatical errors, which induce syntactic violations, and spelling errors, which concern orthographic representations. The CO
condition controls for both serial search and short-term memoryof targets.

sentences silently. Both accuracy and reaction times (RTs) were
measured on line, and the stimulus presentation and behavioral
data collection were controlled by a PC-LabVIEW system(National Instruments, Austin, TX), which was synchronizedwith the PC-Linux system. Stimuli were presented in blocks of
CO-SP-CO-GR-CO. . . Each block contained three one-error
stimuli and three two-error stimuli in a random sequence. Eachrun consisted of five CO blocks, two SP blocks, and two GR
blocks.

Stimuli. We presented each sentence in three or four rows ofages: 20 ⫺ 35) participated in the present study. All subjects
showed right handedness (laterality quotients: 54 ⫺ 100) by the
Edinburgh inventory (16). During the study, the subject wore
earplugs and was in a supine position in the magnet, while thesubject’s head was immobilized with padding inside the radiofrequency coil. Informed consent from each subject was obtained after the nature and possible consequences of the studies
were explained. Approval for these experiments was obtained

NEUROBIOLOGY

yellow letters against a dark background. Each visual stimulus(maximum visual angle: 5° ⫻ 15°; presentation time, 5,500 ms)
was back projected onto a translucent screen near the subject’s
feet with a liquid crystal projector (XV-E300, Sharp, Osaka),
driven by a PC-Linux system. The subjects viewed the stimuli
through prism glasses in front of eyes and were asked to fixate
on a red central cross, where the stimuli appeared, and to read

Subjects. Eight native speakers of English (6 male and 2 female,Fig. 1. Cortical activation in GR and SP conditions. Thresholded fMRI images in t-maps were superimposed on structural images showing z ⫽ 4, 12, 20, and 28
horizontal slices (see Table 3) for a single representative subject. The left side (L) of the brain is shown left. (A) GR vs. CO; (B) SP vs. CO. The color bars at rightindicate the t-values of the comparison. Activation in the GR condition is generally greater in language areas than activation in the SP condition; this differenceis particularly prominent in Broca’s area (B), compared with Wernicke’s area (W) and AG兾SMG.

Embick et al.

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Table 2. Behavioral data and similarity in task difficulty between
CO, SP, and GR conditions
Condition

Error

RT, ms

Accuracy, %

1
1
1
2
2
2

4,069 ⫾ 280
4,266 ⫾ 454
4,293 ⫾ 384
3,421 ⫾ 416
3,610 ⫾ 446
4,109 ⫾ 400

97.5 ⫾ 1.7
96.1 ⫾ 2.1
92.2 ⫾ 4.5
93.2 ⫾ 2.3
89.6 ⫾ 5.1
84.4 ⫾ 7.5

CO
SP
GR
CO
SP
GR

Data are shown in mean ⫾ SD.

from the institutional review boards of the University of Tokyo,
Komaba.
fMRI Data Acquisition and Analysis. The fMRI scans were con-ducted on a conventional 1.5T scanner (Stratis II, Hitachi
Medical Corporation, Tokyo), by using a steady-state acquisition
with rewinded gradient echo sequence (repetition time ⫽ 70 ms,
echo time ⫽ 40 ms, respectively, flip angle ⫽ 30°, field of view ⫽256 ⫻ 256 mm2, resolution ⫽ 2 ⫻ 2 mm2) for four horizontal
slices (thickness ⫽ 8 mm), covering z ⫽ 0 ⬇ ⫹ 32 from thehorizontal bicommissural plane (up to 40 in the case of two
subjects). In a single scanning session, we acquired each image
every 6 s. During the same session as fMRI scanning, we
obtained structural images by using a spin echo sequence(repetition time ⫽ 150 ms, echo time ⫽ 15 ms, flip angle ⫽ 90°,
field of view ⫽ 256 ⫻ 256 mm2, resolution ⫽ 1 ⫻ 1 ⫻ 8 mm3)
at the same slice positions. For anatomical localization, a threedimensional structural image of a whole brain of each subject
was obtained by using a gradient echo sequence (repetition
time ⫽ 30 ms, echo time ⫽ 8 ms, flip angle ⫽ 60°, field of view ⫽256 ⫻ 256 mm2, resolution ⫽ 1 ⫻ 1 ⫻ 3 mm3) in a separate
session.
For the analysis of fMRI time-series data, we used in-house
software developed with Hitachi Seibu Software (Tokyo) (17).
Time-series data of each voxel were converted to percent
signal changes from the initial target block and corrected forbaseline by using linear fitting to data throughout all target
periods with a hemodynamic delay of 6 s. They were thenaveraged for multiple sessions after correction for head movements between scans with no spatial or temporal smoothing.
Regions consisting of four contiguous voxels with the highest
t-values above a threshold of 2.57 (P ⬍ 0.005, one-tailed; P ⬍0.02 after Bonferroni correction) were selected, thus excluding
the spatial extents of activated regions. We compared signal
changes in GR and SP for each region defined in the t-map of
GR vs. CO; the location of an activated region in the t-map of
GR vs. CO matched with that in SP vs. CO when activation wasobserved in both conditions (Fig. 1). When two or moreclusters were identified in the t-map as separate but still within
the same predefined anatomical area, signal changes wereaveraged among these clusters. These clusters might be candidates for further functional parcellation, but it is possiblethat slicing undulate gyri resulted in apparently separated
clusters. Points of activation in each subject were identified
anatomically by using three-dimensional structural images ofeach subject’s brain. Separation of angular gyrus兾supramarginal gyrus (AG兾SMG) and Wernicke’s area followed criteria
reported previously (18). For each subject, the data included
values for each of the two SP and GR blocks per activated area.
Results
According to an ANOVA on behavioral data (Table 2), there
was a main effect of conditions (CO, SP, and GR) in accuracy(P ⬍ 0.05), but RT showed such a main effect only under thecondition with two errors (P ⬍ 0.05; with one error, P ⬎ 0.1).
According to a post-hoc test (Fisher’s protected least significant
difference), the difference between SP and CO was not significant in either RT or accuracy (P ⬎ 0.1). As to the comparison
between GR and SP, there was no consistent significant difference in both RT and accuracy across conditions with one error
and two errors; whereas RT showed a significant difference
between GR and SP only under the condition with two errors(P ⬍ 0.05), accuracy showed such a difference only under thecondition with one error (P ⬍ 0.05). Overall, there was a strong
main effect of errors (one and two) in both RT and accuracy (P ⬍0.0005). Conditions with one error showed longer RTs andhigher accuracy rates than conditions with two errors, indicatingthat the subject paid more attention when checking for an
additional (absent) error.
We found that each of the cortical language areas, i.e.,AG兾SMG, Wernicke’s area, and Broca’s area (Table 3),
showed significant increases in signal change in both GR and
SP when each condition was compared with CO (Fig. 1). In
addition, the GR condition produced significantly more activation than SP across language areas. As the time courses
show, activation in the language conditions was stimulus
locked and did not show an effect of habituation or repetition
for the different language blocks (Fig. 2). Neither the main
effect of blocks nor the interaction between conditions and blocks
was significant (P ⬎ 0.1).
An ANOVA for the left hemisphere (region ⫻ condition ⫻block) showed significant main effects of regions and conditions(P ⬍ 0.0001) but no main effect of blocks (P ⫽ 0.8). Moreover,there was a significant interaction between regions and conditions (P ⬍ 0.05), but there were no other significant interactions(P ⬎ 0.1). These results suggest that the cortical language areas
were not uniformly activated under the GR and SP conditions;rather, there was a clear dissociation among language-related
regions. The differential response between GR and SP was
significantly greater in Broca’s area than in Wernicke’s area,
AG兾SMG, and the right homolog of Broca’s area (Fig. 3 andTable 3). A post-hoc test by using Fisher’s protected leastsignificant difference revealed that pairs consisting of the signal
changes in Broca’s area and those in each other region wereTable 3. Activated regions and differences between GR and SP conditions
RegionBA

Hemisphere

n

x

y

z

GR vs. SP

AG兾SMG
Wernicke
Broca

39兾40
22
44兾45

L
L
L
R

7
6
7
5

⫺49 ⫾ 7⫺58 ⫾ 5⫺51 ⫾ 446 ⫾ 4⫺51 ⫾ 8⫺33 ⫾ 1611 ⫾ 717 ⫾ 316 ⫾ 1010 ⫾ 517 ⫾ 514 ⫾ 11

7.1*
6.9*
22.9**
5.7*

Identification of regions is described in Methods. BA denotes Brodmann’s area and n is the number of subjects
showing significant activation in the region in GR vs. CO. Columns x, y, and z show coordinates (mean ⫾ SD) of
the centers of active regions in each subject, presented in terms of millimeters from the anterior end of thebicommissural line. Column GR vs. SP shows F-values of the main effect of tasks in an ANOVA (condition ⫻ block)for each region. *, P ⬍ 0.05; **, P ⬍ 0.0001.
6152 兩 www.pnas.org

Embick et al.

Fig. 2. Mean-time series for each region of interest in the study. The ordinate
indicates percent signal change; the abscissa is time, with stimulus blocks
indicated and labeled. The time courses show stimulus-locked activation foreach of the three language areas in the left hemisphere: AG兾SMG (A), Wernicke (B), and Broca (C).

significant: (Broca, AG兾SMG) P ⬍ 0.0001, (Broca, Wernicke)P ⬍ 0.01, (Broca, right Broca) P ⬍ 0.0001, whereas comparisonsof other regions did not show significant differences (AG兾SMG,
Wernicke) P ⫽ 0.1, (AG兾SMG, right Broca) P ⫽ 0.7, (Wernicke,right Broca) P ⫽ 0.07.
Embick et al.

Discussion
These data indicate that Broca’s area is specifically involved insyntactic processing. They also preclude an interpretation according to which general computational complexity is the only
difference between the GR and SP conditions, as the behavioral data did not reveal a consistent complexity contrast
between these two conditions. Differences in activation foundbetween GR and SP are instead attributable to the different
linguistic systems involved in each condition: syntactic error
detection in GR, as opposed to orthographic error detection
and normal syntactic processing in SP. The source of thedifferences between GR and SP in Wernicke’s area andAG兾SMG is less clear. It could be that error detection focusedin Broca’s area induces an increase in activation in otherlanguage areas through feedback projections as the subject
attempts reanalysis of the apparently deviant sentence. Or it
could be that a certain amount of syntactic processing also
takes place in Wernicke’s area and AG兾SMG. Finally, by
claiming that Broca’s area is involved in syntax in a special way,
we are making no claims about exclusivity; whether Broca’s
area is directly associated with other linguistic and兾or nonlinguistic modules is still an open question. The involvement ofBroca’s area in the process of speech production is anotherissue for future study (19).
The idea that Broca’s area is a locus of syntax stems initiallyfrom the aphasia literature (10, 11). The imaging literature on
syntax has attributed activation in Broca’s area in syntactic
tasks to an increase in general complexity, rather than to a
specific role for this area in syntax (6, 7). Recent fMRI studies
reported that a part of Broca’s area (BA 44) is implicated inprocessing syntactic information as opposed to semantic information (8, 9). However, each contrastive experimental
condition in these studies involved both syntactic and semantic
processing under the same task instructions, and in neither
study is there any experimental history or independent evidence to support the authors’ claims about implicit andconf licting task demands across conditions. In addition, different sets of sentences were used for two conditions, thus
involving uncontrolled cognitive factors. In contrast, thepresent study used an explicit syntactic paradigm with anestablished experimental history and cognitive theory of the
PNAS 兩 May 23, 2000 兩 vol. 97 兩 no. 11 兩 6153

NEUROBIOLOGY

Fig. 3.
The effect of two language conditions in the language areas.
Histogram comparing the values for percent signal change (mean ⫾ SEM ofsubjects and blocks) for each language condition vs. CO (white ⫽ SP, black ⫽GR) is shown in each region of interest. Note the prominent condition difference in left Broca’s area (L. Broca), which is larger than in other language areas
and the right homolog of Broca’s area (R. Broca).

work will allow us to move beyond the functional anatomy of
the brain to ask questions about how module-specific brain
areas actually perform linguistic computations.

task and further used the same lexical material across conditions. Our results suggest a correlation with results from the
ERP literature (3, 4) in the possibility that ERP components
observed in syntactic error-detection experiments result fromenhanced activation in Broca’s area. Future work combining
electrophysiological (ERP, magnetoencephalography) and hemodynamic (e.g., fMRI, positron emission tomography) methods should clarify the relationship between temporal responsecomponents like the left anterior negativity兾P600 and theactivation in Broca’s area observed in this experiment. Such

We thank F. Homae for help with data analysis and H. Matsuda
for administrative assistance. This work was supported by an International Cooperative Research Project grant from Japan Science andTechnology Corporation (JST) (D.E., A.M., Y.M., and W.O.) and aCore Research for Evolutional Science and Technology grant fromJST (K.L.S.).

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