NeuroImage 12, 147–158 (2000)
doi:10.1006/nimg.2000.0603, available online at http://www.idealibrary.com on

Functional Differentiation in the Human Auditory and Language Areas
Revealed by a Dichotic Listening Task
Ryuichiro Hashimoto,* Fumitaka Homae,* Kyoichi Nakajima,†
Yasushi Miyashita,† ,‡ and Kuniyoshi L. Sakai* ,§ ,1*Department of Cognitive and Behavioral Science, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba,
Meguro-ku, Tokyo 153-8902, Japan; †Department of Physiology, The University of Tokyo School of Medicine, 7-3-1 Hongo, Bunkyo-ku,
Tokyo 113-0033, Japan; ‡ICORP and §CREST, Japan Science and Technology Corporation (JST), Tokyo, Japan
Received February 29, 2000

The human auditory cortex plays a special role inspeech recognition. It is therefore necessary to clarify
the functional roles of individual auditory areas.
We applied functional magnetic resonance imaging(fMRI) to examine cortical responses to speechsounds, which were presented under the dichotic anddiotic (binaural) listening conditions. We found two
different response patterns in multiple auditory areas
and language-related areas. In the auditory cortex, themedial portion of the secondary auditory area (A2), as
well as a part of the planum temporale (PT) and thesuperior temporal gyrus and sulcus (ST), showed
greater responses under the dichotic condition thanunder the diotic condition. This dichotic selectivity
may reflect acoustic differences and attention-related
factors such as spatial attention and selective attention to targets. In contrast, other parts of the auditory
cortex showed comparable responses to the dichotic
and diotic conditions. We found similar functional differentiation in the inferior frontal (IF) cortex. These
results suggest that multiple auditory and language
areas may play a pivotal role in integrating the functional differentiation for speech recognition. © 2000
Academic Press

Key Words: speech recognition; functional magnetic
resonance imaging (fMRI); the auditory cortex.

INTRODUCTION
Sensory information processing in the cerebral cortex has been characterized as involving multiple areas,that are hierarchically organized and functionally specialized (Felleman and Van Essen, 1991). It is known
that speech recognition critically depends on specialized cortical regions, including auditory areas as wellas language areas (Geschwind, 1979). While cytoarchi1

To whom correspondence and reprint requests should be addressed. E-mail: sakai@mind.c.u-tokyo.ac.jp.

tectonic studies have identified multiple auditory areas(Brodmann, 1909; von Economo and Horn, 1930; Galaburda and Sanides, 1980; Rivier and Clarke, 1997),
roles of these multiple areas in auditory analysis per sehave yet to be elucidated. Using recently developed
imaging techniques, differential cortical responses tospeech stimuli could reveal functional differentiationin the auditory cortex. Previous imaging studies haveexamined the effects of cognitive factors involved in
auditory perception under various paradigms. However, consistent results have not been obtained as towhether auditory attention modulates responses in theauditory cortex. Some studies have reported attentionrelated enhancement of responses to speech and nonspeech stimuli in the auditory cortex (Woldorff et al.,
1993; O’Leary et al., 1996; Fujiwara et al., 1998; Jäncke
et al., 1999; Alho et al., 1999). Moreover, there is aclaim that this enhancement is more prominent inhigher auditory areas than that in the primary auditory area (A1); attention-related modulation of activity
occurs mainly in Brodmann’s area (BA) 42 or 22 (Grady
et al., 1997), and further, BA 22 is more susceptible toauditory selective attention than BA 42 (Pugh et al.,1996). In contrast, positron emission tomography(PET) studies have reported that attention-related factors do not increase responses in the auditory cortex(Zatorre et al., 1992, 1999; Frith and Friston, 1996;
Tzourio et al., 1997).
This controversy may be not only due to the differences of paradigms among these studies, but due toattentional influences on the cortical activities which
are manifested in only some restricted regions of theauditory cortex. The anatomical works have shownthat the auditory cortex is not organized as a homogeneous area and that the structure of the auditory cortex is highly variable among individuals (Penhune etal., 1996; Westbury et al., 1999). Therefore it is necessary that the auditory areas are mapped on an individual brain. The group analyses with PET and functional magnetic resonance imaging (fMRI), as well as

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difficulty in the identification of multiple sources withmagnetoencephalogram (MEG), may lead to conflicting
results of attentional enhancement. To examine thefunctional roles of multiple auditory areas in speech
recognition, we used fMRI with an individual analysis
approach and a dichotic listening task, which has been
well established as a paradigm of studying auditory
attention (Cherry, 1953; Treisman, 1969). A dichotic
listening (DIC) condition requires subjects to recognize
only one of different messages that are presented simultaneously to different ears. Thus it involves attention-related factors which are often necessitated in real-life events, such as spatial orientation andextraction of a relevant message from the mixture ofirrelevant messages (cocktail party phenomenon). As acontrasting condition to the dichotic listening task, weused a diotic (binaural) listening (DIO) task, in which
the same messages are presented to both ears. By
examining the cortical responses under these two conditions with speech stimuli, as well as under a control(CON) condition with listening to nonspeech sounds,
we aimed to functionally parcellate the auditory andlanguage areas into two kinds of functional regions: theregions with responses that may reflect attention-related factors, identified by the direct comparison DIC
vs DIO, and the other regions with responses to speechstimuli compared with nonspeech sounds, identified by
the comparison (DIO ⫹ DIC) vs CON. A portion of thisstudy has been reported previously in abstract form
(Hashimoto et al., 1999).
MATERIALS AND METHODS

by the subjects. For speech sounds, continuous sentences of a story (“Snow White” in Japanese) weredivided into phrases at natural break points: “Mirror,/
who is / the most / beautiful woman / in this country?”
For each target, we made three corresponding nontargets by randomizing the order of syllables of thetarget: kamigayo, kayomiga, and gakayomi (nontargets, phonotactically acceptable nonsense syllables) for
kagamiyo (target, “Mirror,” in Japanese). Prior to theexperiment, we showed the subject a script of the wholestory without any nontargets.
All speech sounds were digitized (16 bit; the normal
audio cut-off, 11,025 Hz) using a speech synthesis software (Oshaberi-mate, Fujitsu, Tokyo) that converts
Japanese written texts into sound waveforms. With
this software, target and nontarget stimuli soundednatural for the prosody of speech in Japanese. The
speech stimuli for both targets and nontargets were
presented at the maximum intensity of 67 dB SPL(sound pressure level), measured by a sound level
meter (NL-14, Rion, Tokyo) at the tip of the tube usedin the experiment. The duration of each stimulus
ranged from 400 to 700 ms. The target for nonspeechsounds was a 400-Hz sine wave with low-passed white
noise at 400 Hz (covering up to the range of the fundamental frequencies), and the nontarget was thewhite noise alone. Each nonspeech stimulus was delivered at 62 dB SPL for 600 ms. Auditory stimuli were
presented to the subject’s ears every 1 s through separate tubes (inner diameter: 9 mm, length: 5.9 m), andthe scanning sounds were confined within the interstimulus-interval of 300 – 600 ms.

Subjects

Tasks

Seven male native Japanese speakers (ages: 20 –32)
participated in the present study. All subjects showed
right-handedness (laterality quotients: 81–100) by the
Edinburgh inventory (Oldfield, 1971). The subject wasin a supine position in the magnet with eyes closed ina dark room and the subject’s head was immobilizedwith padding inside the radio-frequency coil. During
the experiment, the subject wore earplugs surrounding
the plastic tubes for sound delivery, and scanner noise
was further attenuated by insulating padding on external ears. Informed consent from each subject was
obtained after the nature and possible consequences ofthe studies were explained. Approval for these experiments was obtained from the institutional review
board of the University of Tokyo (Graduate school ofArts and Sciences), and that of the University of Tokyo
School of Medicine.

The behavioral tasks used here were a control condition (CON), in which nonspeech sounds were presented diotically, and two listening conditions forspeech sounds (Fig. 1): DIO and DIC. The subject was
asked to respond to a target stimulus by pressing abulb attached to a pneumatic switch as fast as possible
with a right hand, while ensuring correct responses.
The rate of bulb pressing was 0.5 in all conditions.
Under the DIO condition, identical stimuli (either targets or nontargets) were presented to both ears simultaneously. Target phrases were presented in the orderof an original story with interventions of nontargets.
Nontargets were presented before their corresponding
targets appeared. The number of nontargets intervening between two targets varied from zero to two randomly (mean ⫽ 1, SD ⫽ 0.92). Therefore, the subjects
cannot predict exactly when the target phrase appears
in a sequence. Under the DIC condition, either a pair oftarget and nontarget or that of two different nontargets was simultaneously presented to different ears.
The side of ears, to which a target was presented, wasrandomized, and the rate of target phrase occurrence(1/4 for each ear on average) was equated between two

Auditory Stimuli
We presented two kinds of auditory stimuli: speechand nonspeech sounds. Each type of stimuli consistedof targets to be attended and nontargets to be neglectedFUNCTIONAL DIFFERENCE OF AUDITORY & LANGUAGE AREAS

149

FIG. 1. Diotic and dichotic listening stimuli for speech recognition. A story was read in Japanese and divided into phrases with three ormore syllables. Numbers below sound waveforms denote the original order of syllables in each story phrase. As a nontarget stimulus, wechanged the sequence of syllables of the phrase coming next in the story. An example of a nontarget is shown in the right panel (2-1-3), thisnontarget was formed from an original story phrase (1-2-3). These jumbled stimuli conform to the rules of Japanese phonotactics but haveno meaning.

ears. The subject has to choose one side with a target,
and to attend that target selectively. Therefore, in addition to the recognition of speech sounds required by
the DIO condition, the DIC condition also demands
selective attention to target stimuli in either ear. Because the rate of target phrase occurrence was equatedbetween DIO and DIC conditions, information rate wasbalanced for these conditions in terms of relevant targets. In a single session (238 s), DIO and DIC blocks
were presented alternately in the order of CON-DIOCON-DIC-CON. . . (Fig. 1), and each session consistedof nine CON blocks, four DIO blocks, and four DIC
blocks (14 s each). Both accuracy and RT were measured on-line, and the stimulus presentation and behavioral data collection were controlled by a PC-LabVIEW system (National Instruments, Austin, TX).
fMRI Data Acquisition and Analysis
The present study was performed using a 1.5-Tesla
fMRI system (MRH-1500, Hitachi Medical Corp., Tokyo). We scanned over four horizontal slices of 8-mm
thickness, covering between 0 and 32 mm from the
AC–PC line, with a gradient echo echoplanar imaging(EPI) sequence (TR ⫽ 2 s, TE ⫽ 22 ms, half scanning,
flip angle ⫽ 90°, field of view ⫽ 384 ⫻ 384 mm 2,
resolution ⫽ 3 ⫻ 3 mm 2) (Stehling et al., 1991; Sakai etal., 1995a, 1995b). The distance from AC–PC line to the
top of the cerebral cortex was 71.2 ⫾ 4.2 mm (mean ⫾SD) in tested subjects. In a single scanning session, we
obtained 119 images for each slice; we tested at least
eight sessions per subject. During the same session asfMRI scanning, we obtained structural images by usinga spin echo sequence (TR ⫽ 500 ms, TE ⫽ 20 ms, flip
angle ⫽ 90°, field of view ⫽ 384 ⫻ 384 mm 2, resolution ⫽ 1.5 ⫻ 1.5 ⫻ 8 mm 3) at the same slice positions as
those of EPI images. Shim currents were carefully

adjusted to minimize distortions of EPI images fromstructural images.
Analyses of fMRI time-series data were first done ona single-subject basis, using in-house software (Sakai
et al., 1995a). Time-series data of each voxel were converted to percent signal changes from the initial CON
block and corrected for baseline using linear fitting todata throughout all CON periods with a hemodynamic
delay of 6 s (a delay of 4 s was used for one subject toobtain higher signal-to-noise ratio). They were thenaveraged for multiple sessions after correction for head
movements between scans, without any spatial or temporal smoothing. We estimated the activation under
the DIO and DIC conditions using the following two
types of t- tests for each voxel: (DIO ⫹ DIC) vs CON(t ⬎ 2.6, P ⬍ 0.005, df ⫽ 135 (17 blocks ⫻ 8 sessions –1), one-tailed, uncorrected for multiple comparisons)combining DIO and DIC before comparison with CON,and DIC vs DIO (t ⬎ 2.3, P ⬍ 0.01) as direct comparison
between two experimental conditions. The significancelevel for each activated region after Bonferroni correction was P ⬍ 0.02 and P ⬍ 0.04, respectively. We use
abbreviations of these t maps as follows: t map (␣) for(DIO ⫹ DIC) vs CON, and t map (␤) for DIC vs DIO. We
set a more stringent statistical threshold for the t map(␣) with larger contrast. We identified an activatedregion as a cluster with at least four contiguous voxelsof t ⬎ 2.6 and t ⬎ 2.3 that contain a local maximum oft values in t map (␣) and t map (␤), respectively.
In case four voxels in t map (␣) overlapped with fourvoxels in t map (␤) for more than one voxel, the fourvoxels in the latter t map were used for analysis. To
compare cortical responses across conditions, signal
changes from the baseline level were averaged amongfour voxels with the highest t values in a region; we did
not compare the spatial extents of activated regions.

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TABLE 1
Multiple Auditory Areas Showing Responses to Speech Sounds
Regiont map

BAHemisphere

n

x

y

z

DIC vs DIO

DSI

A1

␣/␤

41

A2m

␤

42

A2l

␣/␤

42

STa

␣/␤

42

PT␣

␣

42/22

PT␤

␤

42/22

ST␣

␣

22

ST␤

␤

22

SMG

␣

40

L
R
L
R
L
R
L
R
L
R
L
R
L
R
L
R
L
R

6
3
7
6
7
6
6
3
7
3
6
5
6
7
7
7
5
2

⫺44 ⫾ 543 ⫾ 4⫺44 ⫾ 243 ⫾ 3⫺53 ⫾ 252 ⫾ 4⫺61 ⫾ 359 ⫾ 3⫺52 ⫾ 753 ⫾ 3⫺52 ⫾ 453 ⫾ 3⫺56 ⫾ 550 ⫾ 4⫺59 ⫾ 351 ⫾ 4⫺58 ⫾ 453 ⫾ 6⫺13 ⫾ 6
⫺13 ⫾ 3⫺27 ⫾ 5⫺21 ⫾ 4⫺15 ⫾ 6
⫺9 ⫾ 5⫺16 ⫾ 6
⫺11 ⫾ 3⫺29 ⫾ 8⫺25 ⫾ 3⫺30 ⫾ 5⫺18 ⫾ 7⫺43 ⫾ 5⫺30 ⫾ 11⫺39 ⫾ 11⫺34 ⫾ 5⫺41 ⫾ 4⫺38 ⫾ 87⫾4
10 ⫾ 1
6⫾3
9⫾3
6⫾2
7⫾3
5⫾2
8⫾3
13 ⫾ 416 ⫾ 413 ⫾ 314 ⫾ 2
7⫾4
7⫾3
8⫾4
8⫾4
20 ⫾ 426 ⫾ 2

9.1*
5.2
18.3**
9.8*
3.1
1.7
0.9
0.8
2.4
2.8
15.5**
15.5**
0.1
1.4
9.8*
9.8*
3.0
0.1

0.35 ⫾ 0.22
0.17 ⫾ 0.13
0.52 ⫾ 0.09†
0.60 ⫾ 0.19†
0.32 ⫾ 0.09
0.24 ⫾ 0.19
0.19 ⫾ 0.11
0.30 ⫾ 0.01
0.25 ⫾ 0.11
0.30 ⫾ 0.16
0.72 ⫾ 0.13†
0.71 ⫾ 0.12†
0.11 ⫾ 0.31
0.20 ⫾ 0.10
0.61 ⫾ 0.08†
0.75 ⫾ 0.12†
0.32 ⫾ 0.12
0.01 ⫾ 0.25

Note. For the definition of each region, see text. Column t map refers to either the t map (␣) of (DIO ⫹ DIC) vs CON or the t map (␤) of
DIC vs DIO, which was used for identification of each region. In the case of ␣/␤, a region was identified either in the t map (␣) or in the t map(␤) (see Fig. 3). n is the number of subjects who showed significant activation. Columns x, y, and z correspond to the coordinates (mean ⫾ SD)of centers of activated regions, stated as millimeters from the anterior end of the AC-PC line, after affine transformation of individual
hemispheres to the standard brain (Talairach and Tournoux, 1988). Column DIC vs DIO refers to F values obtained by F test between the
DIO and DIC conditions in each region: F(1,2n-2). Single (*) and double (**) asterisks denote statistical significance at P ⬍ 0.05 and P ⬍0.005, respectively. Column DSI refers to DSI values (mean ⫾ SD) in each region: DSI ⫽ (DIC–DIO)/DIC. †A mean DSI value above 0.5.
Abbreviations: A1, primary auditory cortex; A2, secondary auditory cortex; A2l, lateral secondary auditory cortex; A2m, medial secondary
auditory cortex; BA, Brodmann’s area; DIC, dichotic listening; DIO, diotic listening; DSI, DIC selectivity index; PT, planum temporale; SMG,
supramarginal gyrus; ST, superior temporal gyrus and sulcus; STa, anterior superior temporal gyrus.

When two or more clusters were identified in one t map
as separate but still within the same predefined anatomical region, signal changes were averaged among
these clusters. These clusters might be candidates forfurther functional parcellation, but it is possible thatslicing undulate gyri resulted in apparently separated
clusters.
For signal changes in each region identified by t map(␣) and/or t map (␤), we performed F test between the
DIO and DIC conditions, thereby pooling the data fromall subjects (Tables 1 and 2). Furthermore, in order toestimate the degree of DIC selectivity in each region,
we calculated DIC selectivity index (DSI) using thesignal changes from baseline under DIO and DIC conditions: DSI ⫽ (DIC – DIO)/DIC.
Anatomical Identification
A three-dimensional structural image of a wholebrain of each subject was obtained using a gradient

TABLE 2
Frontal Regions Showing Responses to Speech Sounds
Regiont map

BAHemisphere

n

x

y

z

DIC vs DIO

DSI

IF␣

␣

44/45

IF␤

␤

44/45

Anterior insula

␣
␤
␣

—
—
4/6

L
R
L
R
R
R
L
R

5
5
6
7
3
4
3
3

⫺46 ⫾ 749 ⫾ 7⫺43 ⫾ 439 ⫾ 628 ⫾ 136 ⫾ 2⫺55 ⫾ 253 ⫾ 417 ⫾ 715 ⫾ 415 ⫾ 617 ⫾ 314 ⫾ 216 ⫾ 6⫺2 ⫾ 72⫾2

14 ⫾ 919 ⫾ 1022 ⫾ 420 ⫾ 412 ⫾ 714 ⫾ 914 ⫾ 416 ⫾ 2

13.2*
2.7
6.7*
30.4**
6.2
25.2**
0.001
0.7

0.26 ⫾ 0.08
0.35 ⫾ 0.13
0.69 ⫾ 0.17†
0.78 ⫾ 0.20†
0.54 ⫾ 0.08†
0.74 ⫾ 0.16†⫺0.02 ⫾ 0.15
0.20 ⫾ 0.15

Precentral gyrus

Note. For the definition of each region, see text. The regions that were identified in more than two subjects are listed here. Single (*) anddouble (**) asterisks denote statistical significance at P ⬍ 0.05 and P ⬍ 0.005, respectively. †A mean DSI value above 0.5 (see Table 1).
Abbreviations: IF, inferior frontal gyrus and sulcus.

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151

FIG. 2. Representative horizontal slices showing multiple auditory areas in one subject. (A) A series of t maps (␣) of (DIO ⫹ DIC) vs CON. (B)A series of t maps (␤) of DIC vs DIO. Color bars denote t values for each comparison. The left side of the brain is shown left in each horizontal slice.
The centers of the slices are z ⫽ 4, 12, 20, 28 (see Table 1) from left panel to right. Anatomical and functional images in this figure were interpolated
bilinearly. Multiple activated regions were found in the auditory and language-related areas, mostly in the left hemisphere of this subject.
FIG. 3. Spatial relationship among A1, A2m, A2l, and STa in the left hemisphere. Each panel (A–G) represents individual subjects. The left
side of the brain is shown left in the individual horizontal slices. Voxel size, 3 ⫻ 3 mm2. The area shown in (A) is a portion of the t maps shownin Fig. 2 (the leftmost column). Yellow voxels are significant voxels in the t map (␣) of (DIO ⫹ DIC) vs CON. Significant voxels in the t map (␤) of
DIC vs DIO are superimposed and shown in yellow-orange. All of the yellow-orange voxels fall onto yellow voxels. The four contiguous voxels withthe highest t values, which were chosen for each region in either the t map (␣) or the t map (␤), are shown in red. To show the spatial extent ofactivation in A2m, two or three adjacent voxels with higher t values (DIC vs DIO) are shown in orange. Plus (⫹) indicates a local maximum of tvalues in each activated region. Solid lines represent Heschl’s sulcus in individual subjects, and it is clear that A2m and A2l extend along HS. Notethat red voxels in A1, A2m, A2l, and STa are well separated and that their spatial relationship is consistent among all subjects.

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echo sequence (TR ⫽ 30 ms, TE ⫽ 8 ms, flip angle ⫽60°, field of view ⫽ 384 ⫻ 384 mm 2, resolution 1.5 ⫻1.5 ⫻ 3 mm 3) in a separate session. For each subject,
the horizontal slices of structural and functional images were coregistered by translation and rotation onto
the subject’s three-dimensional structural image. After
selecting activated clusters on t maps (see fMRI Data
Acquisition and Analysis), we labeled those activatedclusters as belonging to a particular region, based on
the three-dimensional structures of sulci and gyri withthe following definitions of the boundaries: A1 (primary auditory area), the anteromedial part of Heschl’s
gyrus (HG); A2 (secondary auditory area), the regions
located along Heschl’s sulcus (HS) and within BA 42;
PT (planum temporale), the area that spans from theposterolateral border of A2 to the posterior end of thesupratemporal plane (Steinmetz et al., 1989; Moffat etal., 1998); ST (superior temporal gyrus and sulcus), thelateral area that spans from anterior end of the superior temporal sulcus (STS) to ascending ramus of STS,
as well as STS itself; SMG (supramarginal gyrus), thearea that lies between the postcentral sulcus and theintermediate sulcus of Jensen; IF (inferior frontal gyrus and sulcus), pars triangularis and pars opercularis;
anterior insula, the area that lies anterior to the central insular sulcus; precental gyrus, the area that lies
between the precentral sulcus and the central sulcus.
After affine transformation of individual hemispheresto the standard brain (Talairach and Tournoux, 1988),
the average coordinates of each region among all subjects was calculated (Tables 1 and 2).
RESULTS
Task Performance
The accuracy under the DIO and DIC conditions was
88 ⫾ 4.5 and 77 ⫾ 5.1% (mean ⫾ SD, n ⫽ 7), respectively. The errors under these conditions contained
time-out errors, as the current paradigm required thesubject to respond within 980 ms from the onset of thestimulus. RT under the DIO and DIC conditions was
910 ⫾ 41 and 920 ⫾ 26 ms, respectively. Althoughaccuracy was different between these conditions(F(1,12) ⫽ 16.6, P ⬍ 0.005), there was no significant
difference in RT (F(1,12) ⫽ 0.39, P ⬎ 0.5).
Functional Parcellation of Auditory Cortex
We identified multiple regions that were activatedunder the DIO and DIC conditions (Fig. 2). Here wewill focus on auditory areas first, describing activatedregions in the frontal lobe later. In the t map (␣) of(DIO ⫹ DIC) vs CON, activation was observed in A1,A2 (both lateral and medial portions), PT, ST, andSMG (Fig. 2A). In the t map (␤) of DIC vs DIO, on theother hand, we identified regions in A2 (medial portion), PT, and ST that responded more prominently to

the DIC condition (Fig. 2B). In A2, the medial portion
clearly showed DIC selectivity, though this selectivity
was not apparent in the lateral portion. These lateraland medial regions correspond to two local maxima oft values along HS (Fig. 3), which we call A2l (lateral
A2) and A2m (medial A2), respectively. We identified
STa (anterior ST) as an activated region just posterior
to HS and on the lateral surface of the anterior superior temporal gyrus. Functionally distinct subareas
were also found in PT and ST; some regions wereidentified in the t map (␤): PT␤ and ST␤, while otherareas were identified only in the t map (␣): PT␣ andST␣. The location of each region and the corresponding
BA are shown in Table 1. In the left hemisphere, we
observed these regions in at least five subjects. Although some regions in the right hemisphere wereactivated in a smaller number of subjects, all the regions identified in the left hemisphere were also foundin the right hemisphere at similar coordinates.
Spatial Relationship among Early Auditory Areas
We observed clear spatial segregation between A1
and A2 (Figs. 2A and 3). A2 was located either justanterior or posterior to HS, depending on the subjects(Fig. 3). This individual variation agrees with previous
anatomical reports, which have shown that the boundary between A1 and A2 is not always HS itself, but issometimes anterior to HS (Rademacher et al., 1993;
Hutsler and Gazzaniga, 1996). Though A2m and A2lwere activated both under DIO and DIC conditions, wefound functional differentiation between A2m and A2l
as described above. Further, we confirmed that the
spatial relationship between A2m and A2l was consistent among all subjects (Fig. 3); A2m located posteromedial to A2l (Table 1), and the difference in x and ycoordinates between A2m and A2l was significant inboth left hemisphere (x: F(1,12) ⫽ 54.4, P ⬍ 0.0001; y:F(1,12) ⫽ 13.4, P ⬍ 0.005) and right hemisphere (x:F(1,10) ⫽ 16.8, P ⬍ 0.005; y: F(1,10) ⫽ 15.6, P ⬍ 0.005).
STa was consistently located just lateral to A2l, andthe difference between A2l and STa in x coordinates
was significant in both hemispheres (left: F(1,11) ⫽38.9, P ⬍ 0.0001; right: F(1,7) ⫽ 6.6, P ⬍ 0.05).
Differential Activation under the DIO and DIC
Conditions
Representative temporal signal changes in the auditory areas are shown in Fig. 4. Signal changes in all
auditory regions observed and difference in conditions
are summarized in Fig. 5 and Table 1. The DIC condition elicited larger mean signal changes than the DIO
condition in all regions. The difference between thesetwo conditions was most prominent in A2m, PT␤, andST␤ for both hemispheres (Figs. 5B and 5E, see also
Figs. 4A and 4C for left A2m and ST␤), whereas A2l,STa, PT␣, ST␣, and SMG showed smaller response
difference in both hemispheres (Figs. 5C and 5F, seeFUNCTIONAL DIFFERENCE OF AUDITORY & LANGUAGE AREAS

153

FIG. 4. Mean time-series for representative regions in the study. (A) Temporal percent signal change in left A2m, averaged among all
subjects. (B) Temporal signal change in left A2l. (C) Temporal signal change in left ST␤. (D) Temporal signal change in left ST␣. Note thedifference between signal changes under the DIO condition (o) and the DIC condition (c) in each region. All panels are shown with the sameordinate scale.

also Figs. 4B and 4D for left A2l and ST␣). We confirmed that the difference between the DIO and DIC
conditions was not due to habituation or repetition
effects, based on the observation of no signal difference
between the second blocks and the fourth blocks underboth conditions for A2m (DIO:t (6) ⫽ ⫺1.0, P ⬎ 0.1;
DIC: t (6) ⫽ ⫺2.1, P ⬎ 0.05; paired t test, two-tailed),PT␤ (DIO: t (5) ⫽ ⫺1.4, P ⬎ 0.1; DIC: t (5) ⫽ ⫺1.3, P ⬎0.1), and ST␤ (DIO: t (6) ⫽ ⫺0.33, P ⬎ 0.5; DIC: t (6) ⫽⫺1.3, P ⬎ 0.1) in the left hemisphere.
The differential signal changes in multiple auditory
areas were further confirmed by an analysis of variance (ANOVA) with three variables (condition ⫻ region ⫻ hemisphere). We found a significant interaction
between regions (9 levels of the region factor: A1, A2m,
A2l, STa, PT␣, PT␤, ST␣, ST␤, SMG) and conditions(F(8,170) ⫽ 2.0, P ⬍ 0.05), indicating that responses insome regions were more prominently enhanced by the
DIC condition than in the other regions. This result
demonstrates clear functional differentiation among
multiple auditory areas. Although the location of activated regions is matched for both hemispheres (Table1), the signal changes in the left regions were significantly larger than those in the right regions (a main
effect of hemispheres, F(1,170) ⫽ 5.1, P ⬍ 0.05). The
activated regions shown in Fig. 2 also demonstrate theleft dominance in a representative subject. There wasneither a main effect of subjects (F(6,176) ⫽ 2.1, P ⬎0.05) nor interactions between subjects and other factors (conditions: F(6,176) ⫽ 0.42, P ⬎ 0.5; hemispheres:F(6,176) ⫽ 1.3, P ⬎ 0.1).
Activated Regions in the Frontal Lobe
Besides the auditory areas, we also found activatedregions in the frontal lobe; left and right IF, the rightanterior insula, and the left and right precentral gyrus.
Similar to PT and ST, we identified activated regions in
IF in the t map (␣) and in the t map (␤), which we
named as IF␣ and IF␤, respectively. Signal changes inthese regions are shown in Figs. 5B, 5C, 5E, and 5F.
The location of each frontal region and corresponding
BA, as well as the difference in conditions, are shownin Table 2. We observed significant difference in conditions for left IF␤, right IF␤, left IF␣, and the rightanterior insula (␤) (Table 2). These results suggest that
IF and the right anterior insula are further subdivided
into functionally distinct regions, and a functional roleof the anterior insula may be different between hemispheres in our paradigms.
Spatial Relationship among Language Areas
Though the spatial relationship among A2m, A2l,
and STa was consistent among subjects, the spatial
relationship among activated regions in PT, ST, and IF
was not apparent. According to the definition of indi-

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FIG. 5. Differential responses under the DIO and DIC conditions in multiple auditory areas. Histogram comparing the percent signal
changes (mean ⫾ SEM of subjects) for each auditory condition vs CON is shown in each region. Filled and open bars denote signal changes
under DIO and DIC, respectively. (A–C) Regions in the left hemisphere. (D–F) Regions in the right hemisphere. Regions that show different
response patterns are shown in separate panels. (A and D) Signal changes in A1, A2m, A2l, and STa; areas with close anatomical
relationships. They show progressive signal increases under the DIO and DIC conditions. A and D are shown with the same ordinate scale.
(B and E) Signal changes in A2m, PT␤, ST␤, and IF␤; areas with DIC-selective responses. A2m is shown again here for comparison. (C andF) Signal changes in PT␣, ST␣, SMG, and IF␣; areas with comparable responses to the DIO and DIC conditions. Panels B, C, E, and F are
shown with the same ordinate scale. Single (*) and double (**) asterisks denote statistical significance at P ⬍ 0.05 and P ⬍ 0.005, respectively(see Tables 1 and 2).

vidual regions (see Materials and Methods), PT␣, PT␤,ST␣, ST␤, IF␣, and IF␤ were clearly segregated. Eachof these regions was not always unitary but consistedof multiple clusters within a single subject, as shown in
Fig. 2, while A2m, A2l, and STa were unitary regions.
The number and locations of these clusters, as well as
the spatial relationship between PT␣ and PT␤, ST␣
and ST␤, or IF␣ and IF␤, were not consistent among
subjects, which may be due to individual variability offunctional organization or structural complexity inthese areas. It has been reported that PT is structurally highly variable even within right-handed individuals (Steinmetz, 1996; Westbury et al., 1999), and that
IF also showed individual variation in spatial relationship of functional subregions (Kim et al., 1997). Mean
coordinates of centers of PT␣ and PT␤, ST␣ and ST␤, orIF␣ and IF␤ were almost identical (Tables 1 and 2), in
spite of the fact that each of multiple clusters was
separated. The present study is significant in its identification of regions in PT, ST, and IF with two distinct
response patterns in individual subjects.
Classification of Auditory and Language Areas
In order to estimate the degree of DIC selectivity ineach region, we used DSI (see Materials and Methods).
Among regions with activation found in both hemi-

spheres, A2m, PT␤, ST␤, and IF␤ were the only regionswith DSI above 0.5 (Tables 1 and 2), corresponding to
our identification of these DIC-selective regions basedon the t map (␤). According to an ANOVA (region ⫻hemisphere) for DSI of these regions, there was a main
effect of regions (F(3,43) ⫽ 3.8, P ⬍ 0.05) and hemispheres (F(1,43) ⫽ 4.1, P ⬍ 0.05) without a significant
interaction (F(3,43) ⫽ 0.59, P ⬎ 0.5), and A2m showeda significantly smaller DSI (Fisher’s PLSD, P ⬍ 0.05).
This result suggests progressive processing of DICselective information among these regions. In contrast,
there was no main effect of regions (F(3,32) ⫽ 2.1, P ⬎0.1) and hemispheres (F(1,32) ⫽ 0.11, P ⬎ 0.5) among
PT␣, ST␣, SMG, and IF␣ regions without a significant
interaction (F(3,32) ⫽ 2.2, P ⬎ 0.1) in both hemispheres.
Among the multiple auditory areas identified in thet maps, A1, A2m, A2l, and STa have close anatomical
relationships (Figs. 2 and 3). Signal changes for the
DIO and DIC conditions showed a progressive increasein the mediolateral order, from A1 to STa in bothhemispheres (Figs. 5A and 5D). While A1 and A2mshowed greater responses to the DIC condition than to
the DIO condition, the difference between the two conditions was attenuated in A2l and STa, the more lateral regions. According to an ANOVA (region ⫻ hemi-

FUNCTIONAL DIFFERENCE OF AUDITORY & LANGUAGE AREAS

sphere) for DSI of these regions, there was a strong
main effect of regions (F(3,36) ⫽ 12.1, P ⬍ 0.0001) withneither a main effect of hemispheres (F(1,36) ⫽ 0.15,
P ⬎ 0.5) nor a significant interaction (F(3,36) ⫽ 2.1,
P ⬎ 0.1). A1 showed a significantly smaller DSI thanA2m (Fisher’s PLSD, P ⬍ 0.0005). Furthermore, there
was a significant decrease in DSI along the same spatial progression of left A2m, A2l, and STa (P ⬍ 0.05).
DISCUSSION
Functional Differentiation in Multiple Auditory Areas
The present study clearly demonstrates that the DIO
and DIC conditions modulate cortical responses differentially among multiple auditory areas. Some areas
showed greater responses to the DIC condition than to
the DIO condition, while other areas did not show sucha difference. These contrasting response patterns suggest functional differentiation among multiple auditory areas. Furthermore, we found functional differentiation within A2. The DIC selective response wasobserved in the medial portion of A2 (A2m) as well as
in restricted regions of PT and ST (PT␤ and ST␤,
respectively), whereas the lateral portion of A2 (A2l)and other regions in PT and ST (PT␣, ST␣, and STa)
did not show such selectivity. A recent fMRI study has
identified areas of T1b, T2, and T3 in the supratemporal plane (Scheich et al., 1998), which may correspondto A1, A2, and PT in our study, respectively. The
present study further revealed functional parcellation
within A2, PT, and ST.
There are several possible differences between cognitive factors involved in the DIO condition and thosein the DIC condition, which could produce the DICselective response pattern. First, an interaural stimulus difference is present only under the DIC condition.
Second, spatial attention to either ear is involved under the DIC condition. The subject has to direct attention to one ear when a target is presented and to switch
attention to the other ear when a target is shifted tothe other side. Third, selective attention, which is related to figure-background segregation, is required
only under the DIC condition. The subject has to process an acoustically complex mixture of a target and anontarget in order to extract a target from that mixture. Fourth, the DIC condition may require maintaining a higher state of alertness than the DIO condition
because the DIC task might be more difficult, as indicated by its lower accuracy. However, we should notethe absence of difference in RT as to behavioral control
for task difficulty.
The rate of stimulus presentation may be anotherfactor for the difference observed between the DIO andDIC conditions. According to previous PET studies(Price et al., 1992, 1996), the primary auditory cortex
and middle regions of ST showed a linear relationshipbetween their presentation rate and the blood flow

155

response, while the activity in the left posterior ST(Wernicke’s area) did not depend on the rate of presentation of heard words. Though the frequency of presenting meaningful phrases (target stimuli to which
the subject attended) was equated for both conditions
in our study, there was twice more acoustic materialpresented in the DIC condition relative to the DIO
condition, which could possibly evoke DIC-selective responses in regions closely adjacent to A1. However,higher presentation rate of nonsense syllables (nontarget stimuli that the subject neglected) may not cause
enhanced cortical activity under the DIC condition inregions that are distant from A1; PT, ST, and IF, forexample. Recent fMRI studies reported that signal
changes in the posterior periauditory regions exhibiteda nonlinear (inverted U) relationship to word rate,
reaching a peak at about 60 words per minute (wpm)(Büchel et al., 1998) or at 90 wpm in the primary
auditory cortex as well (Dhankhar et al., 1997). Furthermore, frontal regions showed a response to words
irrespective of their presentation rate (Büchel et al.,1998).
It should be noted that the same response pattern in
two regions may not reflect the same cognitive factors
in each region. However, different response patterns in
two regions reflect either the processing of different
cognitive factors or a different sensitivity to the same
factors. In either case, differential responses among
multiple areas correspond to differences in cognitive
function. Therefore, in the present study, we can conclude that the DIC-selective areas such as A2m, PT␤,and ST␤ are functionally distinct from other regions.
Influence of Auditory Stimulation on the Activityof the Auditory Cortex
Significant activity was observed in A1 and A2 underspeech sound conditions (DIO and DIC), in comparison
with the nonspeech sound condition (CON). This result
indicates that these areas are related to the processingof complex temporal and spectral features of speechsounds at the early stages of auditory perception. Further studies are necessary to examine whether theactivation in these areas reflects general spectro-temporal complexity or speech-specific acoustic characteristics instead. A recent fMRI study has reported voiceselective regions along the upper bank of the superior
temporal sulcus (Belin et al., 2000), which may correspond to a higher stage of sound processing. It would beinteresting to note the possibility that responses invoice-selective regions are enhanced by selective attention to human vocal sounds, as our results indicatethat the response in ST␤ is modulated by attentionrelated factors.
The masking effect of acoustic noise generated byscanner may influence responses in the auditory cortex, either by masking the auditory stimuli

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by the temporal overlaps with scanner noise (Edmister
et al., 1999) or by saturating cortical responses to auditory stimuli in the presence of scanner noise (Talavage et al., 1999; Hall et al., 1999). As to the first point,
we minimized acoustic contamination with scannernoise in the auditory stimuli (see Materials and Methods). For the second point, it has been reported thatsignal enhancement due to scanner noise was observed
mainly in the primary auditory cortex (Bandettini etal., 1998; Talavage et al., 1999), whereas PT, ST, SMG,
and IF were affected in less than half of the subjects
tested (Ulmer et al., 1998). It is possible that, in thepresent experimental conditions, responses in the primary auditory cortex were affected by scanner noise.
Nevertheless, consistent activation among subjects indicates absence of idiosyncratic effects of scanner noisein our experiments. On the other hand, it might bepossible that an interaction with scanner noise madethe DIC condition more difficult, which resulted in
DIC-selective responses. However, we should note thattask difference (DIC vs DIO) is the necessary condition
to observe the differential responses, in which thephysical characteristics of scanner noise were constantthroughout each sequence.
Functional Anatomy of Multiple Auditory Areas
We found four regions around HG showing responses
to speech sounds: A1, A2m, A2l, and STa. With theirclose spatial relationship and their progressive increase in responses to both the DIO and DIC conditions, it is likely that these regions constitute a functional pathway in the order of A1, A2m, A2l, and STa.
In other words, these regions have progressively
greater selectivity for the stimuli presented. The auditory pathway proposed here corresponds to previous
anatomical findings. Based on the gradient in acetylcholinesterase staining and cytochrome oxidase activity, a hierarchical order of A1, PA (posterior area), LA(lateral area), and STA (superior temporal area) has
been proposed (Rivier and Clarke, 1997). A1 (TC of(von Economo and Horn, 1930)) was surrounded posteromedially by PA (the posterior part of TA) and posterolaterally by LA (TB) along HS. Moreover, STA (lateral part of TA) was on the STG, which locates lateral
to LA. Except the other “intermediate level” auditory
areas in that study, AA (anterior area) and MA (medialarea), we found corresponding regions in our fMRI
study. Specifically, the spatial configuration of A1, PA,
LA, and STA corresponds to that of A1, A2m, A2l, andSTa (Fig. 3). It is notable that the anatomical study
and our functional study match with respect to theanatomical location of these areas and the order of the
proposed hierarchical levels.
The auditory cortex of nonhuman primates has been
extensively studied, and the concept of dividing theauditory cortex into core, belt, and parabelt areas has

been proposed based on several different neuroanatomical techniques, including retrograde tracer injections and histochemical staining (Pandya and Sanides,
1973; Hackett et al., 1998). The core areas are locatedinside the lateral sulcus, laterally surrounded by the
belt areas. The parabelt areas are further lateral to thebelt and located on the exposed surface of the superior
temporal gyrus. A hierarchical processing along core,belt, and parabelt has been suggested (Kaas et al.,1999). This hierarchical order has been partially confirmed by an electrophysiological study, showing thatneurons in the belt area prefer certain complex stimuli,
in contrast to neurons in the core area (Rauschecker etal., 1995). While A1 corresponds to the core area (Pandya and Sanides, 1973), the belt area corresponds to
A2, though a subdivision has been suggested (Hackett
et al., 1998). It is possible that A2m and A2l of thepresent human study are related to the belt area, andthat regions identified in PT and ST (PT␤, PT␣, ST␤,ST␣, and STa) are related to the belt and parabelt
areas. However, we should note the presence of somecritical differences in structure and function between
the human and nonhuman primate auditory cortex
that make it difficult to find counterparts of PT and ST,
which are language-related areas, in nonhuman primates. Furthermore, it has been known in many cortical areas, such as visual areas, that functional mapping is able to divide an anatomically unseparated
region into multiple subregions (Van Essen et al.,1998). Our functional parcellation in PT and ST indicates that future studies with some histochemicalmarkers may clarify their anatomical substrates at thecellular level, just like A1, A2m, A2l, and STa.
Functional Differentiation in the Frontal Lobe
The result of the present study suggested that theinferior frontal area is also related to speech recognition as to the DIO and DIC conditions. This area wasshown to differentiate into multiple regions, as well as
in PT and ST. It is notable that both cortical language
areas, Wernicke’s area and Broca’s area, are parcellated into two types of regions with different response
patterns.
We observed DIC-selective response in the right anterior insula, and this region may correspond to AIA(anterior insula area) in a previous cytoarchitectual
work (Rivier and Clarke, 1997). A functional imaging
study (Griffiths et al., 1994) reported that the rightanterior insula was selectively activated by apparent
sound motion. The activation of this region in our study
may reflect common factors between dichotic listening
and auditory motion perception, such as spatial attention or interaural stimulus differences. The role of theanterior insula, however, needs to be further studied
because we found a less selective region (␣) in the rightanterior insula of some subjects (Table 2).

FUNCTIONAL DIFFERENCE OF AUDITORY & LANGUAGE AREAS

Multiple Auditory Pathway Hypothesis
Since a dichotic listening paradigm was established
for the study of selective listening (Cherry, 1953), somemodels of selective attention have been proposed (Treisman, 1969; Posner and Dehaene, 1994; Sakai andMiyashita, 1994). In our paradigm, the DIC condition
requires selective attention, which is related to figurebackground segregation. If auditory areas at the earlystage process both the story phrases and the nonsense
syllables in the course of figure-background segregation, the DIC condition would elicit larger responses
than the DIO condition. In contrast, at the later stage,
after filtering out the nonsense syllables as unattended
stimuli, responses to the DIO and DIC conditions
would become comparable. This “filter” process agrees
with the decrease in DSI along the pathway of A2m,
A2l, and STa.
Other than selective attention and acoustic differences, the interaural stimulus difference and spatialattention may also result in the DIC-selective responses of A2m, PT␤, ST␤, and IF␤. On the other hand,cognitive factors such as speech sound recognition,
which are independent of interaural difference, would
be processed in areas with comparable responses toboth conditions, that is, PT␣, ST␣, SMG, and IF␣. It is
possible that the pathway of A2m, PT␤, ST␤, and IF␤is critical in orienting the location of sound sources byusing dichotic cues, whereas the pathway of PT␣, ST␣,SMG, and IF␣ is useful for processing the patterns ofspeech sounds themselves. A recent study reported
both inferior and superior parietal activation at theslices of z ⬎ 40 during a spatial localization task
(Bushara et al., 1999), while SMG activation in ourstudy was found at lower slices (z ⬍ 32), suggesting
further parcellation in the posterior parietal lobe. Thisdichotomy of the central auditory pathways is relevant
to previously proposed “what” and “where” mechanisms in audition (Deutsch and Roll, 1976; Romanski
et al., 1999), similar to the visual system in primates(Mishkin et al., 1983). Our findings further suggestthat A2 and cortical language areas, such as Wernicke’s and Broca’s areas, play a pivotal role in combining these two mechanisms and in processing language beyond the primary auditory area.
ACKNOWLEDGMENTS
We thank Dr. Juro Kawachi for his encouragement, Dr. Albert
Galaburda and Dr. David Embick for their helpful comments, Mr.
Hiroki Sato and Mr. Tatsuya Takeuchi for their technical assistance,and Ms. Hiromi Matsuda for her administrative assistance. This
research was supported by an ICORP grant from JST to Y.M., and a
CREST grant from JST to K.L.S.

REFERENCES
Alho, K., Medvedev, S. V., Pakhomov, S. V., Roudas, M. S., Tervaniemi, M., Reinikainen, K., Zeffiro, T., and Näätänen, R. 1999. Se-

157

lective tuning of the left and right auditory cortices during spatially directed attention. Cognit. Brain Res. 7: 335–341.
Bandettini, P. A., Jesmanowicz, A., Van Kylen, J., Birn, R. M., andHyde, J. S. 1998. Functional MRI of brain activation induced byscanner acoustic noise. Magn. Reson. Med. 39: 410 – 416.
Belin, P., Zatorre, R. J., Lafaille, P., Ahad, P., and Pike, B. 2000.
Voice-selective areas in human auditory cortex. Nature 403: 309 –312.
Brodmann, K. 1909. Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues,
Verlag von Johann Ambrosius Barth, Leipzig.
Bushara, K. O., Weeks, R. A., Ishii, K., Catalan, M.-J., Tian, B.,
Rauschecker, J. P., and Hallett, M. 1999. Modality-specific frontal
and parietal areas for auditory and visual spatial localization inhumans. Nat. Neurosci. 2: 759 –766.
Büchel, C., Holmes, A. P., Rees, G., and Friston, K. J. 1998. Characterizing stimulus-response functions using nonlinear regressors
in parametric fMRI experiments. Neuroimage 8: 140 –148.
Cherry, E. C. 1953. Some experiments on the recognition of speech,with one and with two ears. J. Acoust. Soc. Am. 25: 975–979.
Deutsch, D., and Roll, P. L. 1976. Separate “what” and “where”
decision mechanisms in processing a dichotic tonal sequence. J.
Exp. Psychol. (Hum. Percept. Perform.) 2: 23–29.
Dhankhar, A., Wexler, B. E., Fulbright, R. K., Halwes, T., Blamire,
A. M., and Shulman, R. G. 1997. Functional magnetic resonanceimaging assessment of the human brain auditory cortex response
to increasing word presentation rates. J. Neurophysiol. 77: 476 –483.
Edmister, W. B., Talavage, T. M., Ledden, P. J., and Weisskoff, R. M.
1999. Improved auditory cortex imaging using clustered volume
acquisitions. Hum. Brain Mapp. 7: 89 –97.
Felleman, D. J., and Van Essen, D. C. 1991. Distributed hierarchicalprocessing in the primate cerebral cortex. Cereb. Cortex 1: 1– 47.
Frith, C. D., and Friston, K. J. 1996. The role of the thalamus in “topdown” modulation of attention to sound. Neuroimage 4: 210 –215.
Fujiwara, N., Nagamine, T., Imai, M., Tanaka, T., and Shibasaki, H.
1998. Role of the primary auditory cortex in auditory selective
attention studied by whole-head neuromagnetometer. Cognit.
Brain Res. 7: 99 –109.
Galaburda, A. M., and Sanides, F. 1980. Cytoarchitectonic organization of the human auditory cortex. J. Comp. Neurol. 190: 597– 610.
Geschwind, N. 1979. Specializations of the human brain. Sci. Am.
241: 158 –168.
Grady, C. L., Van Meter, J. W., Maisog, J. M., Pietrini, P., Krasuski,J., and Rauschecker, J. P. 1997. Attention-related modulation ofactivity in primary and secondary auditory cortex. NeuroReport 8:
2511–2516.
Griffiths, T. D., Bench, C. J., and Frackowiak, R. S. J. 1994. Human
cortical areas selectively activated by apparent sound movement.
Curr. Biol. 4: 892– 895.
Hackett, T. A., Stepniewska, I., and Kaas, J. H. 1998. Subdivisions ofauditory cortex and ipsilateral cortical connections of the parabelt
auditory cortex in macaque monkeys. J. Comp. Neurol. 394: 475–
495.
Hall, D. A., Haggard, M. P., Akeroyd, M. A., Palmer, A. R., Summerfield, A. Q., Elliott, M. R., Gurney, E. M., and Bowtell, R. W. 1999.
“Sparse” temporal sampling in auditory fMRI. Hum. Brain Mapp.
7: 213–223.
Hashimoto, R., Homae, F., Nakajima, K., Miyashita, Y., and Sakai,
K. 1999. Attentional influence on speech recognition: An fMRI
study of multiple auditory areas. Neuroimage 9: S1057.
Hutsler, J. J., and Gazzaniga, M. S. 1996. Acetylcholinesterase staining in human auditory and language cortices: Regional variation of
structural features. Cereb. Cortex 6: 260 –270.

158

HASHIMOTO ET AL.

Jäncke, L., Mirzazade, S., and Shah, N. J. 1999. Attention modulates
activity in the primary and the secondary auditory cortex: A functional magnetic resonance imaging study in human subjects. Neurosci. Lett. 266: 125–128.
Kaas, J. H., Hackett, T. A., and Tramo, M. J. 1999. Auditory processing
in primate cerebral cortex. Curr. Opin. Neurobiol. 9: 164 –170.
Kim, K. H. S., Relkin, N. R., Lee, K. M., and Hirsch, J. 1997. Distinct
cortical areas associated with native and second languages. Nature
388: 171–174.
Mishkin, M., Ungerleider, L. G., and Macko, K. A. 1983. Object visionand spatial vision: Two cortical pathways. Trends Neurosci. 6:
414 – 417.
Moffat, S. D., Hampson, E., and Lee, D. H. 1998. Morphology of theplanum temporale and corpus callosum in left handers with evidence of left and right hemisphere speech representation. Brain
121: 2369 –2379.
O’Leary, D. S., Andreasen, N. C., Hurtig, R. R., Hichwa, R. D.,
Watkins, G. L., Ponto, L. L. B., Rogers, M., and Kirchner, P. T.
1996. A positron emission tomography study of binaurally anddichotically presented stimuli: Effects of level of language anddirected attention. Brain Lang. 53: 20 –39.
Oldfield, R. C. 1971. The assessment and analysis of handedness:
The Edinburgh inventory. Neuropsychologia 9: 97–113.
Pandya, D. N., and Sanides, F. 1973. Architectonic parcellation of thetemporal operculum in rhesus monkey and its projection pattern.
Z. Anat. Entwickl.-Gesch. 139: 127–161.
Penhune, V. B., Zatorre, R. J., MacDonald, J. D., and Evans, A. C.
1996. Interhemispheric anatomical differences in human primary
auditory cortex: Probabilistic mapping and volume measurementfrom magnetic resonance scans. Cereb. Cortex 6: 661– 672.
Posner, M. I., and Dehaene, S. 1994. Attentional networks. Trends
Neurosci. 17: 75–79.
Price, C., Wise, R. J. S., Ramsay, S., Friston, K. J., Howard, D.,
Patterson, K., and Frackowiak, R. S. J. 1992. Regional response
differences within the human auditory cortex when listening towords. Neurosci. Lett. 146: 179 –182.
Price, C. J., Moore, C. J., and Frackowiak, R. S. J. 1996. The effect ofvarying stimulus rate and duration on brain activity during reading. Neuroimage 3: 40 –52.
Pugh, K. R., Shaywitz, B. A., Shaywitz, S. E., Fulbright, R. K., Byrd,
D., Skudlarski, P., Shankweiler, D. P., Katz, L., Constable, R. T.,
Fletcher, J., Lacadie, C., Marchione, K., and Gore, J. C. 1996.
Auditory selective attention: An fMRI investigation. Neuroimage
4: 159 –173.
Rademacher, J., Caviness, V. S., Jr., Steinmetz, H., and Galaburda,
A. M. 1993. Topographical variation of the human primary cortices: Implications for neuroimaging, brain mapping, and neurobiology. Cereb. Cortex 3: 313–329.
Rauschecker, J. P., Tian, B., and Hauser, M. 1995. Processing ofcomplex sounds in the macaque nonprimary auditory cortex. Science 268: 111–114.
Rivier, F., and Clarke, S. 1997. Cytochrome oxidase, acetylcholinesterase, and NADPH-diaphorase staining in human supratemporaland insular cortex: Evidence for multiple auditory areas. Neuroimage 6: 288 –304.
Romanski, L. M., Tian, B., Fritz, J., Mishkin, M., Goldman-Rakic,
P. S., and Rauschecker, J. P. 1999. Dual streams of auditory
afferents target multiple domains in the primate prefrontal cortex.
Nat. Neurosci. 2: 1131–1136.
Sakai, K., and Miyashita, Y. 1994. Visual imagery: An interaction
between memory retrieval and focal attention. Trends Neurosci.
17: 287–289.

Sakai, K., Watanabe, E., Onodera, Y., Itagaki, H., Yamamoto, E.,
Koizumi, H., and Miyashita, Y. 1995a. Functional mapping of thehuman somatosensory cortex with echo-planar magnetic resonance imaging. Magn. Reson. Med. 33: 736 –743.
Sakai, K., Watanabe, E., Onodera, Y., Uchida, I., Kato, H.,
Yamamoto, E., Koizumi, H., and Miyashita, Y. 1995b. Functional
mapping of the human colour centre with echo-planar magnetic
resonance imaging. Proc. R. Soc. Lond. Biol. 261: 89 –98.
Scheich, H., Baumgart, F., Gaschler-Markefski, B., Tegeler, C., Tempelmann, C., Heinze, H. J., Schindler, F., and Stiller, D. 1998.
Functional magnetic resonance imaging of a human auditory cortex area involved in foreground-background decomposition. Euro.
J. Neurosci. 10: 803– 809.
Stehling, M. K., Turner, R., and Mansfield, P. 1991. Echo-planar
imaging: Magnetic resonance imaging in a fraction of a second.
Science 254: 43–50.
Steinmetz, H. 1996. Structure, function and cerebral asymmetry: In
vivo morphometry of the planum temporale. Neurosci. Biobehav.
Rev. 20: 587–591.
Steinmetz, H., Rademacher, J., Huang, Y., Hefter, H., Zilles, K.,
Thron, A., and Freund, H.-J. 1989. Cerebral asymmetry: MR
planimetry of the human planum temporale. J. Comput. Assist.
Tomogr. 13: 996 –1005.
Talairach, J., and Tournoux, P. 1988. Co-Planar Stereotaxic Atlas of
the Human Brain. 3-Dimensional Proportional System: An Approach to Cerebral Imaging, Thieme, Stuttgart.
Talavage, T. M., Edmister, W. B., Ledden, P. J., and Weisskoff, R. M.
1999. Quantitative assessment of auditory cortex responses induced by imager acoustic noise. Hum. Brain Mapp. 7: 79 – 88.
Treisman, A. M. 1969. Strategies and models of selective attention.
Psychol. Rev. 76: 282–299.
Tzourio, N., Massioui, F. E., Crivello, F., Joliot, M., RenaulT, B., andMazoyer, B. 1997. Functional anatomy of human auditory attention studied with PET. Neuroimage 5: 63–77.
Ulmer, J. L., Biswal, B. B., Yetkin, F. Z., Mark, L. P., Mathews, V. P.,
Prost, R. W., Estkowski, L. D., McAuliffe, T. L., Haughton, V. M.,
and Daniels, D. L. 1998. Cortical activation response to acoustic
echo planar scanner noise. J. Comput. Assist. Tomogr. 22: 111–
119.
Van Essen, D. C., Drury, H. A., Joshi, S., and Miller, M. I. 1998.
Functional and structural mapping of human cerebral cortex: Solutions are in the surfaces. Proc. Natl. Acad. Sci. USA 95: 788 –795.
von Economo, C., and Horn, L. 1930. Über Windungsrelief, Ma␤e
und Rindenarchitektonik der Supratemporalfläche, ihre individuellen und ihre Seitenunterschiede. Z. Neurol. Psychiat. 130: 678 –757.
Westbury, C. F., Zatorre, R. J., and Evans, A. C. 1999. Quantifying
variability in the planum temporale: A probability map. Cereb.
Cortex 9: 392– 405.
Woldorff, M. G., Gallen, C. C., Hampson, S. A., Hillyard, S. A.,
Pantev, C., Sobel, D., and Bloom, F. E. 1993. Modulation of early
sensory processing in human auditory cortex during auditory selective attention. Proc. Natl. Acad. Sci. USA 90: 8722– 8726.
Zatorre, R. J., Evans, A. C., Meyer, E., and Gjedde, A. 1992. Lateralization of phonetic and pitch discrimination in speech processing. Science 256: 846 – 849.
Zatorre, R. J., Mondor, T. A., and Evans, A. C. 1999. Auditory
attention to space and frequency activates similar cerebral systems. Neuroimage 10: 544 –554.