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Gray or White? – The Contributionof Gray Matter in a Glioma
to Language Deficits
Ryuta Kinno1,2, Yoshihiro Muragaki3 and Kuniyoshi L. Sakai2

1Division of Neurology, Department of Internal Medicine,Showa University Northern Yokohama Hospital

2Department of Basic Science, Graduate School of Arts and Sciences,

The University of Tokyo

3Department of Neurosurgery, Tokyo Women’s Medical University

Japan
1. Introduction
Symptoms of a glioma include not only headaches and seizures, but cognitive deficits
including aphasia. One of the most important regions for aphasia is the anterior speech area,
the damage of which causes Broca’s aphasia, marked by effortful, distorted articulation,
reduced speech output, and agrammatic syntax. These patients show relatively goodcomprehension of single words and simple sentences, but show trouble understanding
sentences with more complex syntactic structures, such as passive sentences and sentenceswith object relative clauses (Schwartz et al., 1980; Caplan et al., 1985; Grodzinsky, 2000); this
aspect of Broca’s aphasia is called agrammatic comprehension (Goodglass & Menn, 1985;
Menn and Obler, 1990; Pulvermüller, 1995). However, methodological problems have beenraised (Badecker & Caramazza, 1985), and general processes of short-term memory or
decision-making have been proposed to be disrupted in agrammatic comprehension (Just &Carpenter, 1992; Cupples & Inglis, 1993; Dick et al., 2001). Thus, for appropriately assessing
a coginitive deficit, it is crucial to use an experimental task in which general cognitive
demands such as the memory load are stricly controlled.
In our recent functional magnetic resonance imaging (fMRI) study with a picture-sentence
matching task, we examined the effect of sentence structures strictly controlling general
cognitive demands such as the memory load (Kinno et al., 2008), where a sentence wasvisually presented with a picture representing an action (Fig. 1; the same task and stimuli
were used in the present study). The participants indicated whether or not the meaning ofeach sentence matched the action depicted by the corresponding picture. There were threemain conditions with different sentence types: canonical / subject-initial active sentences(AS) (e.g., “ ∆-ga ○-o hiiteru”, “ ∆ pulls ○”), noncanonical / subject-initial passive sentences(PS) (e.g., “ ○-ga ∆-ni hikareru”, “ ○ is affected by ∆'s pulling it”; see Kinno et al. (2008) for ni
direct passive form), and noncanonical / object-initial scrambled sentences (SS) (e.g., “ ○-o∆-ga hiireru”, “as for □, ○ pulling it”; this form is allowed not only in Japanese but in
German, Finnish, and other languages). Under these conditions, each sentence had a108

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transitive verb and two arguments (phrases associated with the predicate) with different
grammatical relations, i.e., which the subject (S) of a verb (V) is, and which its indirect
object (IO) or direct object (DO) is. Sentence comprehension under each condition also
explicitly required analysis of two different thematic roles, i.e., who initiates the action,
and who is affected by it. In Japanese syntax, the grammatical relations are first marked
by case markers (nominative, dative, or accusative in the present stimuli; Fig. 1), which inturn allow the assignment of thematic roles (agent, experiencer, or patient), whereas
passiveness is also marked in the verb morphology (-areru). More specifically, the AS, PS,
and SS sentences correspond to S-DO-V (agent and patient), S-IO-V (experiencer andagent), and DO-S-V (patient and agent) types, respectively. Therefore, these syntactic
analyses for the two-argument relationships were critically required in our paradigm. In
the fMRI study, we observed that activations in L. dF3t (extending to L. F3op) and L.
LPMC were differentially modulated by these three main conditions. Moreover, we haverecently found that a glioma in the opercular and triangular parts of the left inferior
frontal gyrus (L. F3op/F3t) or left lateral premotor cortex (L. LPMC) is indeed sufficient tocause agrammatic comprehension that is selective to syntactic decision (Kinno et al.,2009). These findings indicated that our paradigm with three distinct syntactic conditionsof AS, PS, and SS would be ideal for appropriately assessing agrammatic comprehension,
because the same set of actions depicted by pictures was used under the main conditions,thus controlling semantic comprehension per se. However, it remains to be elucidated
whether a cognitive deficit such as agrammatic comprehension is due to the glioma ingray matter (GM) or not, as a glioma extends to both gray and white matter. It is typicallysupposed that a glioma in a gray matter causes dysfunction of the localized region,
whereas a glioma in white matter leads to the disconnection of neural networks.
Therefore, a lesion-symptom method, in which brain lesions are precisely divided intogray and white matter, is required to examine the relative contribution of gray matter in a
glioma to cognitive deficits.
In this chapter, we firstly propose a modified lesion-symptom method for examining theeffect of a GM lesion. Our method is based on the following two methods for processing
the structural magnetic resonance imaging (MRI) data and the behavioural data ofpatients with a glioma: the voxel-based lesion-symptom mapping (VLSM) (Bates et al.,2003) and the “unified segmentation” algorithm (Ashburner & Friston, 2005). The VLSM
is a method to analyze the relationship between a lesion location in the structural MRI
and behavioural data such as the error rates (ERs) or reaction times (RTs) on a voxel-byvoxel basis. The unified segmentation algorithm is a generative model that combines
tissue segmentation, bias correction and spatial normalization in a single unified model.
Using our picture-sentence matching task (Fig. 1), we actually applied this new method toreal data of patients with a glioma in the left frontal cortex. The tumor locations covered
the most of the left frontal regions and thus included L. F3op/F3t and L. LPMC. To
precisely localize the glioma, all patients underwent a high-resolution 3D-MRI on thesame day as the task examination. All of these results were actually utilized for the
preoperative evaluation of detailed language function and for planning a resection ofglioma, thereby minimizing the risk of postoperative language deficits (Haglund,
Ojemann, & Hochman, 1992). Because neurological data about the real roles of the left
frontal regions in syntactic comprehension have been limited, our lesion-symptom
method would have both fundamental and clinical implications, which are useful forpreserving the quality of life (QOL) for each patient.

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Fig. 1. The three main conditions used in the picture-sentence matching task.

2. Material and methods
2.1 Participants
All patients were native Japanese speakers newly diagnosed as having a glioma in the left
frontal region, who were scheduled for surgery at the Department of Neurosurgery ofTokyo Women’s Medical University. The following conditions comprised the criteria forinclusion of patients in the present study: (i) right-handedness, (ii) no deficits in verbal /written communication or other cognitive abilities reported by the patients or physicians,(iii) no history of neurological or psychiatric disorders other than glioma and seizures, (iv)
freedom from seizures with or without antiepileptic drug, and (v) no medical problems for
MRI acquisition. Twenty-one patients (Fig. 2 and Table 1) preoperatively underwent a highresolution MRI scan and performed the picture-sentence matching task at the University ofTokyo, Komaba. The laterality quotient (LQ) was also determined by the Edinburgh
handedness inventory (Oldfield, 1971). The verbal / nonverbal intelligence quotient (IQ)
was assessed with the Japanese version of the WAIS-III (1997, 2006; Harcourt Assessment,
Inc., San Antonio, TX, USA), including more general and demanding tests than the aphasic
tests. All but one patient underwent amytal testing. Following injection of amytal, thepatient counted numbers with both hands raised. As soon as the contralateral hemiplegia
occurred, a picture naming task was used to determine hemispheric dominance, which waseither left or bilateral. The tumour type and grade were postoperatively and pathologicallydiagnosed by the WHO Classification of Tumours of the Nervous System (2000). Using thesame paradigm and parameters, we also tested 21 right-handed participants with no historyof neurological or psychiatric disorders. These age-matched normal controls included 12
males and 9 females (age: 20-58; mean: 37 years). Informed consent was obtained from eachparticipant after the nature and possible consequences of the studies were explained.
Approval for the experiments was obtained from the institutional review board of the
University of Tokyo, Komaba.
Age
34 ± 10LQ
88 ± 16

VIQ
98 ± 5.7

non-VIQ
99 ± 6.5

Tumor Volume44088 ± 21227

GM Ratio
55 ± 3.0

Table 1. Characteristics of Patients
The patients in our previous study (Kinno et al., 2009), who were scanned with the same
protocol of MRI in the present study, were all included. Date are shown as mean ± standard
deviation MR images were normalized with SPM8 for determination of tumor location and110

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volume (mm3), as well as the ratio (%) of gray matter (GM) for each tumor. LQ = laterality
quotient VIQ = verbal intelligence quotient.

Fig. 2. Lesion overlap map for 21 patients with a glioma in the left frontal cortex
2.2 Stimuli
Each visual stimulus consisted of a picture at the top and a Japanese sentence at the bottom(Fig. 1). The pictures used for AS, PS, and SS were identical (the number of lines used ineach picture, mean ± SD: 14 ± 2.4, n = 6). There was one sentence control (SC) condition withintransitive verbs (e.g., “□-to ∆-ga hashitteru”, “□ and ∆ run”) and equally complex pictures(14 ± 2.5, n = 6), which were all different from those used under the three main conditions.
Half of the pictures depicted action occurring from left to right, and the other half depictedaction from right to left. In the pictures, the use of symbols was also counterbalanced forboth sides within each condition.
The sentences describing actions were written in a combination of the “hiragana” and“kanji” writing systems, and all sentence stimuli were grammatical in Japanese. Eachsentence included two noun phrases and one verb; for example, a noun phrase (□-ga)
consisted of a symbol (□) and a hiragana (ga). Two sets of Japanese verbs (six transitive
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 orfive syllables. Note that the verb “call” is used only as a transitive verb in Japanese. There
was no significant difference in frequency between the two sets of verbs (t (10) = 0.7, p =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). We prepared eight stimuli for each verb; there
were 48 stimuli for each condition.
Each stimulus consisted of one picture (top) and one sentence (bottom). Pictures depicting
actions consisted of two stick figures; each stick figure was distinguished by one of three“head” symbols: a circle (○), square (□), or triangle (∆).The participants indicated whether or
not the meaning of each sentence matched the action depicted in the corresponding picture

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by pressing one of two buttons. (A) Under the active sentence (AS) condition, canonical /subject-initial active sentences were presented (“∆-ga ○-o hiiteru”). Below each example, aword-by-word translation in English is shown. Nom, nominative case; Acc, accusative case;Dat, dative case. (B) Under the passive sentence (PS) condition, non-canonical / subjectinitial passive sentences were presented (“○-ga ∆-ni hikareru”). (C) Under the scrambled
sentence (SS) condition, non-canonical / object-initial scrambled sentences were presented(“○-o ∆-ga hiireru”). An identical picture set was used under these three conditions. The
sentence stimuli were all grammatical and commonly used in Japanese.All stimuli were
presented visually in yellow against a dark background. Each stimulus was presented for
5800 ms followed by a 200 ms blank interval, which was ample time for the patients (seeTable 2). For fixation, a red cross was also shown at the center of the screen. Stimulus
presentation and behavioural data collection were controlled using the LabVIEW softwareand interface (National Instruments, Austin, TX, USA).
2.3 Tasks
In the picture-sentence matching task (Fig. 1), the participants read a sentence silently andindicated whether or not the meaning of each sentence matched the action of thecorresponding picture by pressing one of two buttons. For AS, PS, and SS, all mismatchedsentences were made by exchanging two symbols in the original sentences, e.g., “□ pushes○” instead of “○ pushes □”. For SC, symbol-mismatched and action-mismatched sentenceswere presented equally often, requiring the sentences to be read completely in order for theparticipants to arrive at a correct judgment.
In addition to the picture-sentence matching task, we used a visual control task (VC), which
required neither word nor sentence processing, as a baseline condition (Kinno et al., 2008).
For VC, the same sets of pictures used in the picture-sentence matching task were presented,
together with a string of jumbled letters taken from a single sentence in which the symbols(○, □, or ∆) and “kanji” appeared at the same positions in the string as in the picturesentence matching task. The participants were asked to judge whether or not all the symbols
in a letter string were the same as those in the picture, irrespective of the order of thesymbols. The participants underwent practice sessions before testing to become fully
familiarized with the tasks.
A single run of the testing sessions contained 24 “trial events” of the picture-sentence
matching task (six times each for AS, PS, SS, and SC), with variable inter-trial intervals of 6
and 12 s (one and two VC, respectively), pseudorandomized within a run. Since
meaningless letter strings were presented throughout VC while sentences were presented
only in the trial events, the participants could switch from VC to the trial events according
to the stimulus type. The order of AS, PS, SS, and SC was pseudorandomized in each run toprevent any condition-specific strategy. Eight runs were tested in a day per one participant.
Half of the stimuli consisted of matched picture-sentence pairs (24 trials for each condition),and the other half consisted of mismatched pairs (24 trials for each condition). All patients
underwent the testing sessions inside the scanner while they received three to six fMRI runs,
and then they completed the rest of the eight runs outside the scanner. Because the numberof fMRI runs was limited by the patients’ medical conditions, here we focused on the
behavioural data and the anatomical MRI scans alone. All of the behavioural data fromnormal controls were acquired outside the scanner.

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2.4 MRI data acquisition and analyses
The MRI scans were conducted on a 1.5 T scanner (Stratis II, Premium; Hitachi Medical
Corporation, Tokyo, Japan), and a high-resolution T1-weighted 3D image (repetition time:

Fig. 2. Schematic representation of methods for making GM images.

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30 ms, acquisition time: 8 ms, flip angle: 60°, field of view: 192 × 192 mm2, resolution: 0.75 ×
0.75 × 1 mm3) was acquired for each patient. The location of the glioma was first identified
on this MR image, and the glioma boundary was semi-automatically determined using
MRIcroN software (http://www.mricro.com/) (Rorden & Brett, 2000). T2-weighted MR
images (Department of Neurosurgery of Tokyo Women’s Medical University) and positronemission tomography (PET) data (Chubu Medical Center for Prolonged Traumatic Brain
Dysfunction, Mino-Kamo-shi, Japan) were also used to assist the precise determination of
the boundary. Each individual’s structural image was spatially normalized to the standard
brain space as defined by the Montreal Neurological Institute (MNI) using the “unified
segmentation" algorithm, which is a generative model that combines tissue segmentation,
bias correction and spatial normalization in a single unified model (Ashburner & Friston,2005), which was resampled to 1 × 1 × 1 mm3 voxel size using statistical parametric mapping
SPM8 software (Wellcome Department of Cognitive Neurology, London, UK) (Friston et al.,1995) on MATLAB (Math Works, Natick, MA, USA).
These resultant individually normalized images were divided into gray and white matters
as follows (Fig. 2). Firstly, a GM image was made by dividing the standard brain into grayand white matters using MRIcroN software. This GM image was used as a mask, whichapplied to the individually normalized image of each glioma.
Using the resultant GM image of each glioma, we next employed voxel-based lesionsymptom mapping (VLSM) to analyze the relationship between glioma location and theerror rates on a voxel-by-voxel basis (Bates et al., 2003). The patients were divided into twogroups according to whether they did or did not have a glioma including that voxel. The
error rates for each condition or the difference in error rates between two conditions (e.g., PS– AS) were then compared for these two groups by a t-test, in which the statistical threshold
was set to p = 0.05 after correction for multiple comparisons using the false discovery rate(FDR). To minimize the effects of outlier observations, the voxels used in the VLSM analysis
were within the gliomas of at least two patients. Finally, the result of VLSM was projected
onto a standard brain using MRIcroN software.

3. Results
In our paradigm with three main conditions of AS, PS, and SS, under which two-argument
relationships were critically required (see the Introduction), the same set of actions depictedby pictures was used, thus controlling semantic comprehension per se. In contrast, adifferent set of pictures were used under the SC condition (e.g., “□ and ∆ run”), whichbasically required matching between words (symbols and verbs) and pictures alone,
without syntactic analyses for the two-argument relationships. Thus, the SC condition was
syntactically less complex and easier to comprehend than other conditions. It was therefore
mandatory to analyze the three main conditions and SC separately. Moreover, the analyses
also match with our fMRI study (Kinno et al., 2008), in which SC was used as a separate
control. In the sections 3.1-3.3, we focus on the main conditions of AS, PS, and SS, and theresults of SC are presented in the section 3.4.
3.1 Behavioral analyses
The ERs for the patients and the normal controls are shown in Table 2. A repeated-measures
analysis of variance (rANOVA) with two factors (group [patients, normal controls] ×

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condition [AS, PS, SS]) revealed significant main effects of group (F (1, 40) = 16, p = 0.0003)
and condition (F (2, 80) = 8.9, p = 0.0003), as well as a significant interaction of group by
condition (F (2, 80) = 9.2, p = 0.0003). The patients showed significantly higher error rates
than the normal controls for each of AS, PS, and SS (t-test; AS: t (40) = 2.5, p = 0.016; PS: t(40) = 2.9, p = 0.0055; SS: t (40) = 4.1 p = 0.0002). According to paired t-tests on the threemain conditions, the patients’ error rates were significantly higher for SS than for AS and PS(AS: t (20) = 3.8, p = 0.0010; PS: t (20) = 2.5, p = 0.021), whereas the difference was marginal
between AS and PS (t (20) = 1.9, p = 0.07). However, there was no significant difference
among the normal controls’ error rates under the main conditions (p > 0.7). The resuls fromthe normal controls is consistent with our previous results (Kinno et al 2008).
These significant errors were observed in spite of the patient’s normal verbal and nonverbal
IQs (Table 1; range: 86-113 within 1 SD of ± 15; one sample t-test for the difference from 100:
verbal, t (20) =1.2, p = 0.25 and nonverbal, t (20) = 0.51, p = 0.62). According to correlation
analyses, the error rates for each condition could not be attributed to their ages, verbal /nonverbal IQs, or tumor volumes and GM ratio (all, p > 0.1). These results correspondedwith our previous findings (Kinno et al., 2009), demonstrating that the tumor locations
affected the actual performance of the three main conditions.
The RTs for the patients and the normal controls are also shown in Table 2. An rANOVA
with two factors (group [patients, normal controls] × condition [AS, PS, SS]) showed thatneither a main effect of group (F (1, 40) = 2.1, p = 0.2) nor that of condition was significant (F(2, 80) = 2.8, p = 0.1), with no significant interaction of group by condition (F (2, 80) = 0.30, p= 0.7). Because there was a significant main effect of condition regarding the error rates, theerror rates were better indicators than RTs for estimating condition-selective effects.
Therefore, we used error rates as indicators in the following VLSM analyses.
Participant Error Rate (%)
RT (ms)
AS
PS
SS
SC
AS
PS
SS
SC
Normal
1.8 ± 2.6 2.1 ± 2.4 2.4 ± 2.6 1.8 ± 1.4 3334 ± 470 3524 ± 466 3599 ± 405 2712± 535
controls
Patients
8.1 ± 7.4 12 ± 12 22 ± 21 2.4 ± 2.3 3372 ± 423 3476 ± 453 3499 ± 455 2760± 298
Table 2. Behavioral Data under Each Condition. ERs and RTs (for correct trials only) are
shown as mean ± standard deviation.
3.1.1 VLSM analyses for gray and white matters
To identify any critical regions for the main conditions of AS, PS, and SS, we first conducted
VLSM analyses, in which error rates for each condition were evaluated among the left
frontal-damaged patients (n = 21). We found that significantly higher error rates for AS wereassociated with lesions in L. IFG, including L. dorsal F3op/F3t, as well as isolated lesions in
L. LPMC (Fig. 3A). Moreover, significantly higher error rates for PS were associated withlesions in L. dorsal F3op/F3t, further extending to ventral F3op/F3t (Fig. 3B). In contrast,
significantly higher error rates for SS were associated with lesions in L. LPMC and ventral
IFG (Fig. 3C). These results indicate that both of L. F3op/F3t and L. LPMC are the criticalregions for AS, PS, and SS.
Next we examined which regions were critically involved in the comprehension ofsyntactically complex sentences. For this purpose, we conducted VLSM analyses, in which
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i.e., PS – AS or SS – AS, was evaluated among the left frontal-damaged patients. We foundthat the significantly larger difference in PS – AS was associated with lesions in L. F3op/F3t(Fig. 3D). In contrast, we found that the significantly larger difference in SS – AS was
associated mostly with lesions in L. LPMC (Fig. 3E). These results are consistent with ourprevious results (Kinno et al., 2009) with better sensitivity, indicating that both of L.
F3op/F3t and L. LPMC are sufficient to cause agrammatic comprehension.

Fig. 3. Brain regions identified by the VLSM analysis for gray and white matters
Brain regions identified by the VLSM analysis for gray and white matters among the left
frontal-damaged patients (n = 21) for AS, PS, SS, PS – AS, and SS – AS, respectively. The
resultant t-map is projected on the left (L) lateral surface; the threshold was established at t >2.0 (FDR corrected p < .05).
3.1.2 VLSM analyses for gray matter
We performed the modified VLSM analyses to identify the relateve contribution of graymatter to syntactic processing required for the main conditions of AS, PS, and SS, inwhich a GM image of each glioma was used. We found that significantly higher error
rates for AS were associated with ventral lesions in L. IFG, as well as isolated lesions in L.
LPMC (Fig. 4).

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Fig. 4. Brain regions identified by the VLSM analysis for gray matter.
Moreover, significantly higher error rates for PS were associated with lesions in L. ventral
F3op/F3t, further extending to dorsal F3op/F3t. In contrast, significantly higher error rates
for SS were associated with lesions in L. LPMC and ventral IFG. These results arecompatible to our previous findings.
Next we examined the effect of gray matter on the comprehension of syntactically complex
sentences. We found that the significantly larger difference in PS – AS was associated withlesions in L. F3op/F3t (Fig. 4). In contrast, we found that the significantly larger differencein SS – AS was associated mostly with lesions in L. LPMC. These results indicate that thegray matter of L. F3op/F3t as well as L. LPMC are critically involved in the comprehensionof syntactically complex sentences.

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3.2 The analyses of the SC condition
We compared the performance data for SC between all patients and the normal controls to
examine whether or not such basic comprehension of sentences was affected for thepatients. The patients showed no significant difference in error rates for SC when comparedwith the normal controls (t (40) = 0.87, p = 0.4) (Table 2). Regarding RTs for SC, there was no
significant difference between the patients and normal controls (t (40) = 0.36, p = 0.7).
Moreover, paired t-tests showed that the patients’ error rates were significantly lower for SC
than for AS, PS, and SS (AS: t (20) = 3.6, p = 0.020; PS: t (20) = 3.4, p = 0.0029; SS: t (20) = 4.5,
p = 0.0002), whereas the normal controls’ error rates for SC were not significantly different
from those for the three main conditions (p > 0.7). For both the patients and normal controls,
RTs were significantly shorter for SC than for the three main conditions (all, p < 0.0001).
These results indicate that basic comprehension of sentences under the SC condition waspreserved among the patients.

4. Discussion
In this chapter, we have presented the modified VLSM method that can directly examine theeffect of a GM lesion on a cognitive process. The present study successfully demonstrates
that GM of L. F3op/F3t and L. LPMC are actually essential for AS, PS, and SS (Fig. 4), andthat both regions are indeed critically involved in the comprehension of syntacticallycomplex sentences. The patients with a lesion in GM of L. F3op/F3t or L. LPMC had
significant deficits in syntactic analyses for the two-argument relationships required for thethree main conditions, but without deficits in any factors required for SC. These results
provide crucial evidence that GM of L. F3op/F3t and L. LPMC subserves syntactic
comprehension.
The condition-selectivity in error rates for the patients with a GM lesion in either L.
F3op/F3t or L. LPMC cannot be explained by general disorders of the patients, including
visual / memory / motor impairment, attention disturbance due to drowsiness or dizziness,and perseveration for a particular sentence type. It is natural to assume that the patientswith normal verbal IQ would not otherwise experience or exhibit difficulty in language
comprehension with such simple sentences; however the patients indeed exhibited clear
deficits even for canonical sentences for AS in the present study. In daily conversation,
pragmatic information about word use resolves syntactic difficulty (e.g., “The officer chased
the thief” is more acceptable than “The thief chased the officer.”). The use of appropriate
syntactic judgment tests is thus necessary for a proper assessment of syntactic
comprehension. The importance of GM of L. F3op/F3t and L. LPMC has been underpinnedby accumulating results from fMRI studies, which demonstrated the selectivity for syntactic
processing in L. F3op/F3t and /or L. LPMC (Dapretto & Bookheimer, 1999; Embick et al.,
2000; Hashimoto & Sakai, 2002; Bornkessel et al., 2005; Grewe et al., 2006), indicating thecritical role of the two left frontal regions on the language network for syntactic processing(Sakai, 2005). Moreover, the present results are consistent with another recent fMRI study, inwhich both L. dF3t and L. LPMC were selectively activated for the syntactic comprehensionof honorification, in which two-argument relationships of either subject honorifics or object
honorifics were critically involved (Momo, Sakai, & Sakai, 2008). Further research is
required for understanding both anatomical and functional bases for the differential roles ofthese two critical regions.

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It has been well known that the left temporal cortex is also engaged during sentencecomprehension. In our fMRI study with the same paradigm, we have reported that a
localized activation in the left posterior superior / middle temporal gyrus (L. pSTG/MTG)
was also enhanced for SS when compared with AS and PS (Kinno et al., 2008). Other fMRI
studies have also reported that this region was activated by contrasting object-initial vs.
subject-initial sentences (Bornkessel et al., 2005), as well as by contrasting sentences withsyntactic / semantic anomaly and normal sentences (Suzuki & Sakai, 2003). A lesion in L.
pSTG/MTG may thus result in the SS-selective deficit. A recent intraoperativeelectrocorticography study in humans showed bidirectional connectivity between L. IFG
and L. pSTG/MTG (Matsumoto et al., 2004), and additional evidence for this connectivity
has been reported in studies using MRI to investigate structural connectivity (Catani, Jones,& Ffytche, 2005; Friederici et al., 2006). Therefore, it is possible that this network subserves
syntactic integration, thereby combining multiple linguistic information. Further lesion
studies are required to examine whether or not a lesion in gray or white matter of the left
temporal region is sufficient to cause deficits in such a linguistic process. Our lesionsymptom method would be useful for this purpose.
Compared with a cerebrovascular disease such as an infarct or a hemorrhage, a glioma
has both advantages and disadvantages in neuropsychological and neurolinguistic
research. First, it is advantageous that the location of a glioma is basically random in the
cerebrum and not restricted by the cerebrovascular distribution. Indeed, damage to the
middle cerebral artery affects the perisylvian cortex including F3op/F3t, but it spares
more dorsal regions including LPMC. Using the lesion data with a glioma, we
successfully showed the functional roles of L. F3op/F3t and L. LPMC. Second, the precise
determination of the location and extent of a glioma is often difficult, because a glioma
may induce edemas, abnormalities by compressing its peripheral region, and infiltration.
In the present study, we used both T2-weighted MR images and PET data, which enabled
us to determine precise boundary of lesions including brain edemas and abnormalities of
perfusion. Third, some neural functions may be still preserved within a glioma, as
indicated by cortical stimulation and fMRI studies (Ojemann, Miller, & Silbergeld, 1996;
Krainik et al., 2003). It has been also reported that patients with tumors in the left
hemisphere showed less language impairment than their counterparts with stroke(Anderson, Damasio, & Tranel, 1990). In the present study, however, we regarded an
entire glioma as a lesion, and clear language deficits were observed despite such residualfunctions. Fourth, the onset and time course of a glioma is difficult to determine; a glioma
develops gradually without apparent symptoms such as hemiplegia or dysarthria. In thepresent study, the patients were at least 21 years old at their start of medication, and had
no prior history of benign or malignant brain tumors, indicating an adult-onset glioma.
For evaluating the real function of a cortical region, it is thus important to compare thelesion symptom data from our lesion-symptom method with the functional neuroimaging
data from normal controls.
It has been recently demonstrated that slow-growing lesions like WHO grade II gliomas,
but not high-grade gliomas, may induce cortical reorganization even before operation(Desmurget, Bonnetblanc, & Duffau, 2007). Moreover, the grade II gliomas undergo
anaplastic transformation over the years, i.e., the progression into grade III gliomas (Behin
et al., 2003), which may be enough time for cortical reorganization. Such a functional

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reshaping might affect the observation of the present study, because the tumor types ofthe patients were heterogeneous including WHO grade II (n = 10), and III (n = 11), withdifferent biological processes for each tumor. However, it should be noted that thepatients with a glioma in either L. F3op/F3t or L. LPMC showed marked deficits insyntactic comprehension, which had not been rescued by any functional reshaping. It is
possible that the reorganization of other cortical regions due to a lesion in L. F3op/F3t or
L. LPMC is entirely different each other, thus leading to the differential patterns ofcondition-selective deficits. Further functional neuroimaging studies for brain-damaged
patients are required to clarify real mechanisms of cortical reorganization.
Understanding cortical networks for a cognitive process requires knowledge of functional aswell as anatomical connections between brain regions. Not only lesion symptom mapping
but also functional imaging studies of patients with a well-defined lesion are useful forunderstanding cortical networks by revealing abnormal activations: overactivity (i.e.,
regions where patients activate more than normal controls) or underactivity (i.e., regions
where patients activate less than normal controls) (Price & Friston, 1999; Price, Crinion , &Friston, 2006). These differential activations can imply a change in cognitive or neuronal
implementation. Changes in cognitive implementation occur when a patient uses a different
set of cognitive processes either because a new cognitive strategy has been learned, or
because of increased demands on normal processing due to a brain damage. Changes inneuronal implementation are mediated by changes in the strength of pre-existing
connections. Abnormal activations distant to the lesion location suggest the dysfunctional
region has been disconnected from its normal inputs. This disconnection may result inoveractivity, due to disinhibition of an inhibitory network, or underactivity, due to a failure
to activate a cortical region. These abnormal activations can reveal a duplicate system for a
cognitive process, in which the dominant system inhibits the others. Within the duplicate
system, the less dominant systems are able to respond when the dominant system isdamaged. This duplication of functionality renders a function immune from the effects offocal damage. Functional imaging studies of patients, therefore, have an important role toplay in the identification of a duplicate system—the multiplicity of sufficient brain systems
for a cognitive function. Further study is required to investigate the language-specificsystem for the human brain.

5. Conclusion
In this chapter, we have presented a lesion-symptom mapping method that can directly
examine the effect of a GM lesion on a cognitive process. As a glioma extends to both grayand white matter, it remains to be elucidated whether the cognitive deficits are due to theglioma in gray or white matter. It is typically supposed that a glioma in GM causes
dysfunction of the localized region, whereas a glioma in white matter leads to thedisconnection of neural networks. Therefore, the effect of GM lesion should be assessed
precisely; for this purpose, our method would be useful. While a glioma in the cerebral
cortex causes a deficit in cognitive function, the severity and course of such a dysfunctionneed to be thoroughly assessed (Wefel, Kayl, & Meyers, 2004). An extensive study of tumors
with multiple neuropsychological tests have confirmed that patients with left hemispherictumors exhibited poorer verbal fluency and verbal learning than those with righthemispheric tumors (Hahn et al., 2003). The present study demonstrated the severity ofdysfunction, such that a GM lesion in L. F3op/F3t and/or L. LPMC can cause clear deficits

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in syntactic comprehension. Our language task would be thus sensitive enough and usefulfor a general assessment of linguistic knowledge. Our findings further indicate that brain
surgery for a glioma in the left frontal cortex requires careful assessment for maintaining
syntactic abilities, which are indeed the source of the creative faculty for producing infinite
expressions (Hauser, Chomsky, & Fitch, 2002), and thus for ensuring the best possible QOL
for individual patients.

6. Acknowledgment
We thank M. Kawamura for his suggestion regarding neurological issues, N. Komoro forher technical assistance, H. Matsuda for her administrative assistance. This research was
supported by a research grant from the Narishige Neuroscience Research Foundation (R. K.)
and a Core Research for Evolutional Science and Technology (CREST) grant from the Japan
Science and Technology Agency (JST) (K. L. S.).

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