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Pediatric neuroimaging studies1, 2, 3, 4, 5, up to now exclusively cross sectional, identify linear decreases in cortical gray matter and increases in white matter across ages 4 to 20. In this large-scale longitudinal pediatric neuroimaging study, we confirmed linear increases in white matter, but demonstrated nonlinear changes in cortical gray matter, with a preadolescent increase followed by a postadolescent decrease. These changes in cortical gray matter were regionally specific, with developmental curves for the frontal and parietal lobe peaking at about age 12 and for the temporal lobe at about age 16, whereas cortical gray matter continued to increase in the occipital lobe through age 20.
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nature neuroscience • volume 2 no 10 • october 1999 861
Brain development
during childhood and
adolescence: a
longitudinal MRI study
Jay N. Giedd
1
, Jonathan Blumenthal
1
, Neal O. Jeffries
2
,
F. X. Castellanos
1
, Hong Liu
1
, Alex Zijdenbos
3
,
To m á s˘ Paus
3
, Alan C. Evans
3
and Judith L. Rapoport
1
1
Child Psychiatry Branch, National Institute of Mental Health, Building 10,
Room 4C110, 10 Center Drive, MSC 1367, Bethesda, Maryland 20892, USA
2
Biometry Branch, National Institute of Neurological Disease and Stroke, Federal
Building, Room 7C06, 7550 Wisconsin Avenue, Bethesda, Maryland, 20892, USA
3
Montreal Neurological Institute, McGill University, 3801 University Street,
Montreal, Quebec H3A 2B4, Canada
Correspondence should be addressed to J.N.G. (jgiedd@helix.nih.gov)
Pediatric neuroimaging studies
1–5
, up to now exclusively cross sec-
tional, identify linear decreases in cortical gray matter and increas-
es in white matter across ages 4 to 20. In this large-scale
longitudinal pediatric neuroimaging study, we confirmed linear
increases in white matter, but demonstrated nonlinear changes in
cortical gray matter, with a preadolescent increase followed by a
postadolescent decrease. These changes in cortical gray matter
were regionally specific, with developmental curves for the frontal
and parietal lobe peaking at about age 12 and for the temporal
lobe at about age 16, whereas cortical gray matter continued to
increase in the occipital lobe through age 20.
The subjects for this study were healthy boys and girls partici-
pating in an ongoing longitudinal pediatric brain-MRI project at
the Child Psychiatry Branch at the National Institute of Mental
Health. Subjects were recruited from the community as previous-
ly described, using phone screening, questionnaires mailed to par-
ents and teachers and face-to-face physical and psychological
testing; approximately one in six volunteers were accepted
5
. At least
1 scan was obtained from each of 145 healthy subjects (89 male). Of
these, 65 had at least 2 scans, 30 had at least 3 scans, 2 had at least
4 scans and 1 had 5 scans, acquired at approximately two-year
intervals. The age range was from 4.2 to 21.6 years. There were no
significant sex differences for age, Tanner stage, ethnicity, socioe-
conomic status, height, weight or handedness.
All subjects were scanned on the same GE 1.5 Tesla Signa scan-
ner using the same three-dimensional, spoiled-gradient, recalled
echo in the steady state (3D SPGR) imaging protocol, with an
axial-slice thickness of 1.5 mm, a time-to-echo of 5 ms, a repeti-
tion time of 24 ms, flip angle of 45°, a 192 ( 256 acquisition matrix,
1 excitation and a field of view of 24 cm. A clinical neuroradiolo-
gist evaluated all scans; no gross abnormalities were reported.
Volumes of white and cortical gray matter were quantitative-
ly analyzed by combining a technique using an artificial neural
network to classify tissues based on voxel intensity with non-lin-
ear registration to a template brain for which these tissue regions
had been manually defined
7
. This technique supplemented MRI
signal-intensity information with predetermined brain anatomy
and provides lobar (frontal, parietal, temporal and occipital) par-
cellation of cortical gray- and white-matter volumes.
We used previously described statistical analysis techniques
that combine cross-sectional and longitudinal data
8
. These lon-
gitudinal methods are more sensitive to detecting individual
growth patterns, even in the presence of large interindividual
variation
9
. We assessed if there was significant change with age, if
developmental curves differed by sex and/or region and whether
the developmental curves were linear or quadratic.
The volume of white matter increased linearly with age
(Fig. 1; Table 1), increasing less in females than in males. The net
increase across ages 4 to 22 was 12.4%. Curves for white-matter
development did not significantly differ among various lobes. In
contrast, changes in volume of cortical gray matter were non-
linear and regionally specific. Gray matter in the frontal lobe
increased during pre-adolescence with a maximum size occur-
ring at 12.1 years for males and 11.0 years for females, followed by
a decline during post-adolescence that resulted in a net decrease
in volume across this age span. Parietal-lobe gray matter followed
a similar pattern, increasing during pre-adolescence to a maxi-
mum size at age 11.8 years for males and 10.2 years for females,
followed by decline during postadolescence and a net decrease
scientific correspondence
RECEIVED 17 MAY; ACCEPTED 12 AUGUST 1999
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the frontal cortex
15
. Striatal structures are involved in cognitive
functions such as learning, which is linked to frontal system func-
tion
15
and improves throughout adolescence
8
. This suggests tem-
poral and functional relationships between simultaneous
postadolescent reductions in gray-matter density in frontal and
striatal regions.
Thus, we describe in-vivo documentation for a temporal and
spatial progression of postadolescent maturation into the frontal
lobes, highlighting the potential importance of frontal/striatal
maturation to adult cognition.
A
CKNOWLEDGEMENTS
We thank the McConnell Brain Imaging Center at the Montreal Neurological
Institute and the SPM software developers at the Wellcome Department of Cognitive
Neurology. Finally, we thank David Kornsand for assistance in anatomical analyses
and John Bacheller for artwork. This study was supported by grants P50 NS22343,
and R01 HD 23854, and NIMH NRSA grant 5T32 MH16381, NSF DBI 9601356,
the NCRR (P41 RR13642), NINDS (NS38753) and the pediatric supplement of the
Human Brain Project, funded jointly by NIMH and NIDA (P20 MH/DA52176).
© 1999 Nature America Inc. • http://neurosci.nature.com
© 1999 Nature America Inc. • http://neurosci.nature.com
862 nature neuroscience • volume 2 no 10 • october 1999
in volume; however, pre- and post-adolescent slopes were steep-
er for parietal than for frontal lobes. Temporal-lobe gray matter
also followed a nonlinear developmental course, but maximum
size was not reached until 16.5 years for males and 16.7 years for
females, with a slight decline thereafter. Occipital-lobe gray mat-
ter increased linearly over the age range, without evidence of sig-
nificant decline or leveling. Developmental curves for the different
cortical regions significantly differed from each other; those for
frontal and parietal lobes were the most similar. The
absolute size of the cortical gray matter was approxi-
mately 10% larger in boys, and peaked slightly earlier
in girls, but the shapes of the curves were not signifi-
cantly different between boys and girls.
The regional specificity of findings in cortical gray
matter sheds light on the debate regarding synchro-
nous versus heterochronous development of the cere-
bral cortex. Nonhuman primate studies generally
reveal synchronous cortical development (that is, with
similar timing in diverse cortical regions)
10
. However,
in humans there are limited but compelling histologi-
cal data to suggest that synapse elimination is hete-
rochronous, with changes in primary visual and
auditory cortex occurring before those in frontal cor-
tex
11
. The present data support heterochronic devel-
opment in human cerebral cortex. The pre-adolescent
increase and post-adolescent decrease in cortical gray
matter parallel developmental PET studies of cerebral
glucose metabolism
12
and EEG studies of slow-wave
sleep amplitude
13
.
This MRI study demonstrates a pre-adolescent
increase in cortical gray matter; this phenomenon was
previously obscured, probably by the lack of longitudi-
nal data, as even in an analysis of the 145 cross-section-
al data points in our sample, the largest to date, we could
not detect nonlinearity in these developmental curves.
Whether this gray-matter increase is related to changes
in neuropil, neuronal size or dendritic or axonal
arborization will be best addressed by methods other
scientific correspondence
Fig. 1. Predicted size with 95% confidence intervals for
cortical gray matter in frontal, parietal, temporal and occip-
ital lobes for 243 scans from 89 males and 56 females, ages
4 to 22 years. The arrows indicate peaks of the curves.
250
300
350
400
450
4 6 8 10121416182022
80
90
100
110
120
130
140
4 6 8 10121416182022
800
1000
1200
1400
1600
1800
4 6 8 10121416182022
150
160
170
180
190
200
210
220
230
240
250
4 6 8 10121416182022
100
120
140
160
180
200
220
4 6 8 10121416182022
Male (Predicted) peak
Female (Predicted)
95% Confidence Intervals
40
45
50
55
60
65
70
75
80
85
4 6 8 10121416182022
Female
Male
Table 1. Developmental curves for different regions.
p value for p value for
Age Age
2
p value for no only linear curves
Male Female coefficient coefficient change change having same
Structure intercept intercept β
1
β
2
(β
1=
0, β
2=
0) (β
2=
0) shape
Total 1382 1260 5.6 –0.72 p < 0.0001 p < 0.0001 p = 0.83
cerebrum (12.3) (19.3) (10.0) (0.15)
Total 758 686 –0.50 –0.39 p = 0.001 p = 0.001 p = 0.47
gray (7.3) (11.3) (0.80) (0.12)
Frontal 235 214 –0.38 –0.18 p < 0.0001 p < 0.0001 p = 0.84
gray (2.3) (3.8) (0.28) (0.04)
Temporal 191 175 0.81 –0.10 p < 0.0001 p = 0.002 p = 0.99
gray (1.7) (2.6) (0.22) (0.03)
Parietal 126 116 –0.31 –0.10 p < 0.0001 p < 0.0001 p = 0.51
gray (1.3) (20.0) (0.15) (0.02)
Occipital 70.1 61.5 0.41 0.009 p = 0.007 p = 0.69 p = 0.07
gray (1.2) (1.7) (0.14) (0.02)
The developmental curves are modeled by the equation: size = intercept + β
1
(age – mean age) + β
2
(age – mean age)
2
+ ε
where the intercept term is a random effect that varies by individual and intra-individual correlation of ε is taken into account. A Wald statistic assesses
whether the curve changes with age (that is, whether β
1
and β
2
are both 0). A z statistic of β
2
assesses whether the curve is best fit by a linear (β
2
= 0) or
quadratic curve (β
2
0). The curves were found to have similar shapes by sex (no significant differences for any structure), but because the height of the
curves did vary, separate terms were used for boys and girls. Multivariate analysis showed that shapes for the four regions of gray matter significantly differed
from one another (p < 0.0001), with parietal and frontal regions most similar and temporal the most distinct.
Total cerebral volume
White matter
Parietal gray matter
Temporal gray matter
Frontal gray matter
Age in years
Volume in cubic cm
Volume in cubic cm
Volume in cubic cm
Volume in cubic cm
Volume in cubic cm
Volume in cubic cm
Age in years
Age in years
Age in years
Age in years
Age in years
Occipital gray matter
© 1999 Nature America Inc. • http://neurosci.nature.com
© 1999 Nature America Inc. • http://neurosci.nature.com
nature neuroscience • volume 2 no 10 • october 1999 863
A contingent aftereffect
in the auditory system
C.-J. Dong, N. V. Swindale and M. S. Cynader
Department of Ophthalmology, University of British Columbia, 2550 Willow
Street, Vancouver, British Columbia V5Z 3N9, Canada
Correspondence should be addressed to C.-J.D. (cdong@interchg.ubc.ca)
Pairs of stimulus attributes, such as color and orientation, that
are normally uncorrelated in the real world are generally per-
ceived independently; that is, the perception of color is usually
uninfluenced by orientation and vice versa. Yet this independence
can be altered by relatively brief exposure to artificially correlat-
ed stimuli, as has been shown for vision
1
. Here we report an anal-
ogous contingent aftereffect in the auditory system that can
persist for four hours after the initial adaptation.
After a few minutes of alternately viewing an orange-black
vertical grating and a blue-black horizontal grating, the white
stripes in a vertical black-and-white grating appear blue-green,
whereas the white stripes in a horizontal grating appear orange
1
.
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P. A. Cereb. Cortex. 6, 726–736 (1996).
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Psychiatry Res. (in press).
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scientific correspondence
than MRI. If the increase is related to a second wave of overpro-
duction of synapses, it may herald a critical stage of development
when the environment or activities of the teenager may guide selec-
tive synapse elimination during adolescence. The relative promi-
nence of the role of the environment in shaping late synaptogenesis
is supported by rat studies
14,15
. That the frontal and parietal gray
matter peaks approximately one year earlier in females, corre-
sponding with the earlier age of onset of puberty, suggests a possi-
ble influence of gonadal hormones. Studies of healthy monozygotic
and dizygotic twins, chromosomal aneuploidies (XXY, XXYY, XYY),
congenital adrenal hyperplasia (producing high levels of testos-
terone in utero) and psychiatric illnesses are underway to address
the effects of genes, hormones and environment on this process.
RECEIVED 21 MAY;
ACCEPTED 9 A
UGUST 1999
1. Jernigan, T. L., Trauner, D. A., Hesselink, J. R. & Tallal, P. A. Brain 114,
2037–2049 (1991).
There are numerous demonstrations of other types of visual con-
tingent aftereffect, such as color-contingent orientation
2
and
motion
3,4
aftereffects and spatial frequency
5
- and motion
6,7
-con-
tingent color aftereffects. These visual contingent aftereffects can
be extremely persistent. For example, the motion-contingent
color aftereffect and the color-contingent motion aftereffect can
persist for at least 24 hours
3,6
. The motion-contingent color after-
effect can last as long as six weeks in some cases
7
.
In contrast to the rich variety of reported visual contingent
aftereffects, there are no reports of contingent aftereffects for
Fig. 1. Stimulus protocols. (a) Time sequence of stimuli. Each run began
with 10 minutes of adaptation, followed by a series of brief test sounds
(1 s), with either a rising (0.7 octaves per s) or a falling (–0.7 octaves per
s) pitch presented by a loudspeaker moving at one of six different veloc-
ities (2°, 6° or 10° per s, either to the left or the right). For each test
presentation, the subject was asked to press one of two buttons to indi-
cate the direction (leftward or rightward) of spatial movement.
(b) Detailed time sequence of adapting stimuli. While the central fre-
quency of an adapting sound (1-octave band-pass noise) was moving
upward (0.7 octave per s), the loudspeaker moved to the left (30° per s)
for 1 second (from –15° to 15° in azimuth). Following a silent interval of
1.4 seconds, the loudspeaker moved to the right (–30° per s) for 1 sec-
ond, while the central frequency of the sound moved downward (–0.7
octave per s). During adaptation, this sequence was repeated continu-
ously. In the control condition, the loudspeaker moved over the same
trajectory with the same time course, but the center frequency of the
adapting sound was kept constant at 1.5 kHz. Note that the vertical axis
in the top panel has a logarithmic scale.
a
b
Speaker position (deg)
Frequency (Hz)
Sound on
t
10 min 1 s
Initial adapt. Test Resp.
High
Right
Left
Low
© 1999 Nature America Inc. • http://neurosci.nature.com
© 1999 Nature America Inc. • http://neurosci.nature.com
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