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Asymmetric regional cerebral blood flow in sedated baboons measured by positron emission tomography (PET).

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 121:369 –377 (2003)
Asymmetric Regional Cerebral Blood Flow in
Sedated Baboons Measured by Positron Emission
Tomography (PET)
Jason A. Kaufman,1* Jane E. Phillips-Conroy,1,2 Kevin J. Black,3–5 and Joel S. Perlmutter2,4,5
1
Department of Anthropology, Washington University, St. Louis, Missouri 63130
Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, Missouri 63110
3
Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110
4
Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110
5
Department of Neurology and Neurological Surgery, Washington University School of Medicine,
St. Louis, Missouri 63110
2
KEY WORDS
laterality; asymmetry; Papio; cerebral blood flow; rCBF; PET
ABSTRACT
The analysis of structural brain asymmetry has been a focal point in anthropological theories of
human brain evolution and the development of lateralized
behaviors. While physiological brain asymmetries have
been documented for humans and animals presenting
with pathological conditions or under certain activation
tasks, published studies on baseline asymmetries in
healthy individuals have produced conflicting results. We
tested for the presence of cerebral blood flow asymmetries
in 7 healthy, sedated baboons using positron emission
tomography, a method of in vivo autoradiography. Five of
the 7 baboons exhibited hemispheric asymmetries in
which left-sided flow was significantly greater than rightsided flow. Furthermore, the degree of asymmetry in 8 of
24 brain regions was found to be significantly correlated
with age; older individuals exhibited a higher degree of
asymmetry than younger individuals. Cerebral blood flow
itself was uncorrelated with age, and differences between
males and females were not significant. Am J Phys Anthropol 121:369 –377, 2003. © 2003 Wiley-Liss, Inc.
Anatomical asymmetries in human crania and
brains have been rigorously investigated and documented in the anthropological literature (reviewed
by Falk, 1987; Oppenheimer, 1977) since the beginnings of modern physical anthropology (e.g., Le Gros
Clark, 1933). Left-right asymmetries may appear as
gross hemispheric petalias (Falk et al., 1991;
LeMay, 1976; LeMay et al., 1982) or localized regional asymmetries such as that of Broca’s area
(Broca, 1861; Chiarelli et al., 1989), the planum
temporale (Geschwind and Levitsky, 1968), and extent of the Sylvian fissure (Watkins et al., 2001;
Westbury et al., 1999). Asymmetries have also been
reported in nonhuman primates (Falk et al., 1986;
Gannon et al., 1998; Heilbroner and Holloway, 1989)
as well as fossil hominids (Holloway, 1981; Holloway
and de LaCoste-Lareymondie, 1982).
Modern neuroimaging modalities such as positron
emission tomography (PET), functional magnetic
resonance imaging (fMRI), and single-photon emission computed tomography (SPECT) have revealed a
variety of physiological left-right asymmetries both
during motor activation tasks (Dassonville et al.,
1997; Kawashima et al., 1997, 1998; Kim et al.,
1993; Viviani et al., 1998) and during cognitive activation tasks (Buckner et al., 1995; MacLeod et al.,
1998; Ojemann et al., 1998; Petersen et al., 1990).
Physiological asymmetries are also commonly re-
ported in various disease states (Eidelberg et al.,
1991; Grimes et al., 1985; Hatazawa et al., 1988;
Haxby et al., 1985; Kushner et al., 1984; Loewenstein et al., 1989; Martinot et al., 1990; Matheja et
al., 1998; Rausch et al., 1994). However, assessments of physiological asymmetries during a baseline, healthy state in humans have produced conflicting results. While some researchers have
reported left-right asymmetries of cerebral blood
flow or glucose metabolism in the resting state (Devous et al., 1986; Gur et al., 1995; Hagstadius and
Risberg, 1989; Kolbitsch et al., 2000; Krausz et al.,
1998; Perlmutter et al., 1985; Podreka et al., 1989;
©
2003 WILEY-LISS, INC.
Grant sponsor: NIH; Grant numbers: NS31001, NS01898; Grant
sponsor: Dana Clinical Hypotheses Research Program, Charles A.
Dana Foundation; Grant sponsor: Greater St. Louis Chapter, American Parkinson Disease Association; Grant sponsor: Sam and Barbara
Murphy Fund; Grant sponsor: McDonnell Center for Higher Brain
Function.
*Correspondence to: Jason A. Kaufman, Department of Anthropology, Washington University, Campus Box 1114, One Brookings Drive,
St. Louis, MO 63130. E-mail: jakaufma@artsci.wustl.edu
Received 24 May 2002; accepted 22 August 2002.
DOI 10.1002/ajpa.10181
370
J.A. KAUFMAN ET AL.
TABLE 1. Variance components of two regions representing minimum and maximum ratios of variance among individuals to
variance among sessions within individuals
Region
Source of variation
SS
df
MS
F
P
Motor cortex
upper extremity
(left)
Among Individuals
Among sessions within individuals
Within sessions (error)
Total
Among Individuals
Among sessions within individuals
Within sessions (error)
Total
185,371.76
2,105.54
284.86
187,762.17
147,827.87
151.13
254.16
148,233.17
7
12
37
56
7
12
37
56
26,481.68
175.46
7.69
3,439.56
22.79
0.000
0.000
21,118.26
12.59
6.86
3,074.28
1.83
0.000
0.078
Orbitofrontal
cortex (right)
SS, sums of squares; df, degrees of freedom; MS, mean squares; F, F-statistic.
Rodriguez et al., 1991; Rootwelt et al., 1986; Tanaka
et al., 2000; Van Laere et al., 2001a,b), many have
failed to detect significant asymmetries (Catafau et
al., 1996; Moeller et al., 1996; Murphy et al., 1996;
Seitz and Roland, 1992; Younkin et al., 1988). The
purpose of this study was to test for the presence of
asymmetries of regional cerebral blood flow (rCBF)
in baboons. We used PET to calculate quantitative
rCBF in 24 bilateral regions for 7 baboons sedated
with nitrous oxide. Binomial distribution tests were
performed to test for general asymmetry among all
regions, and multiple-comparison t-tests were used
to test for asymmetries in individual regions. In
preparing the PET scans, we employed a method of
aligning individual PET images with corresponding
magnetic resonance images and mapping these images into a common stereotaxic atlas space. This
method was validated previously (Black et al., 1997)
and simplifies the collection of cerebral blood flow
data when analyzing numerous brain regions and/or
individuals. Because PET images do not directly
depict anatomic structures, mapping PET images
into stereotaxic atlas space reduces error in isolating
individual regions for evaluation.
DATA COLLECTION
We obtained quantitative PET images of rCBF for
7 normal baboons (Papio anubis) over a series of 20
scanning sessions. The animals were postadolescent, as judged by weight and dental eruption stage,
and consisted of 4 males and 3 females. Since birthdates were unknown for all individuals, we used
weight as a surrogate for age. Body weight ranged
from 13–38.3 kg.
All animals were scanned three consecutive times
per session, and each animal was scanned on at
least two separate occasions. Magnetic resonance
(3D MPRAGE) images of the brain also were acquired for each individual. PET studies were performed using a Siemens 953b system. Prior to scanning, each baboon was first anesthetized with
ketamine (10 –15 mg/kg), injected with glycopyrrolate to decrease secretions, paralyzed with pancuronium, and ventilated with 30% oxygen and 70%
nitrous oxide to maintain sedation. Actual PET imaging did not begin until 3 hr after the ketamine
injection, to allow its effects on blood flow to abate. A
20-gauge plastic catheter was inserted into a femo-
ral artery to permit arterial blood sampling. Blood
pressure, pulse, body temperature, and arterial
blood gases were monitored throughout each study.
Each baboon had been fitted with a surgicallyimplanted skull cap that attaches to the scanner to
permit precise head repositioning and prevent any
head movement during the scanning (Perlmutter et
al., 1987). Cerebral blood flow was measured using a
bolus injection of 15O-labeled water and 40-sec PET
scans. The eyes were covered during the procedure,
and ambient noise was kept as low as possible. Body
temperature was maintained between 35.5–37.5°C,
using a heating blanket. All studies were approved
by the Washington University Animal Studies Committee and were conducted according to strict animal care guidelines.
Quantitative regional blood flow was calculated
using brain-tissue activity counts and simultaneous
measurements of arterial blood radionuclide concentration. Arterial blood data were shifted temporally
to match the arrival time of radioactivity to the
brain, and to provide an input for blood flow calculations (Herscovitch et al., 1983; Raichle et al.,
1983). These calculations are performed with “inhouse” software, and have been validated in baboons
(Herscovitch et al., 1983; Raichle et al., 1983). Cerebral blood flow is expressed as milliliters of blood per
100 g brain tissue per minute.
The procedure for alignment of each PET image
with the individual’s MRI, and the subsequent
transformation into atlas space, follows the method
of Black et al. (1997). First, the MR images are
mapped into coordinates corresponding to the Stereotaxic Atlas of the Baboon Brain (Davis and Huffman, 1968). The appropriate transformation factors
are determined by the position of distinct anatomical landmarks of each individual’s brain. Scaling
factors include the distance between the anterior
commissure and the posterior commissure (anteriorposterior, y dimension), the interputamenal distance (left-right, x dimension), and the vertical distance between the superior border of the caudate
nuclei and the inferior border of the optic tracts
(superior-inferior, z dimension). Common orientation planes were defined by the midsagittal plane, a
transverse plane through the center of the anterior
commissure and superior border of the posterior
commissure, and a coronal plane normal to the
371
BABOON CEREBRAL BLOOD FLOW
TABLE 2. Mean individual regional cerebral blood flow (ml/100 g/min) for seven baboons
Baboon no.
1
2
3
4
5
6
7
Sex
Weight (kg)
Motor cortex lower extremity R
Motor cortex lower extremity L
Motor cortex upper extremity R
Motor cortex upper extremity L
Motor cortex face R
Motor cortex face L
Supplementary motor area R
Supplementary motor area L
Striate cortex R
Striate cortex L
Orbitofrontal cortex R
Orbitofrontal cortex L
Dorsolateral prefrontal cortex R
Dorsolateral prefrontal cortex L
Anterior cingulate cortex R
Anterior cingulate cortex L
Posterior cingulate cortex R
Posterior cingulate cortex L
Amygdala R
Amygdala L
Hippocampus R
Hippocampus L
Caudate (ventral) R
Caudate (ventral) L
Caudate (body) R
Caudate (body) L
Putamen R
Putamen L
Nucleus accumbens R
Nucleus accumbens L
Globus pallidus pars externa R
Globus pallidus pars externa L
Globus pallidus pars interna R
Globus pallidus pars interna L
Ventral pallidum R
Ventral pallidum L
Subthalamic nucleus R
Subthalamic nucleus L
Substantia nigra R
Substantia nigra L
Thalamus (dorsomedial) R
Thalamus (dorsomedial) L
Thalamus (ventrolateral) R
Thalamus (ventrolateral) L
Cerebellum R
Cerebellum L
Lateral habenula R
Lateral habenula L
Whole brain
M
15.0
55.86
57.22
51.94
52.50
79.69
81.97
73.08
74.22
51.39
51.74
50.36
55.08
60.48
62.50
54.21
55.02
52.03
52.14
44.05
42.35
49.11
45.97
66.16
69.32
54.05
54.47
73.85
70.63
59.91
70.43
66.53
61.65
55.52
54.26
53.66
54.13
52.38
52.30
50.19
48.62
67.05
70.08
59.20
66.00
53.16
53.08
76.32
76.39
54.95
F
16.0
42.95
44.20
61.86
62.74
67.20
67.64
55.14
55.61
39.64
40.08
57.79
57.35
51.74
48.64
74.42
78.09
67.09
72.06
43.42
39.83
40.23
38.35
62.83
61.64
57.55
55.08
63.40
61.32
56.97
60.90
54.67
53.02
50.60
49.23
52.03
49.85
54.85
52.56
56.86
55.35
65.75
64.56
58.46
59.10
53.50
53.15
74.58
73.80
55.81
M
13.0
58.98
59.76
56.28
57.93
77.19
81.33
66.62
66.21
39.95
40.44
45.16
48.04
56.40
56.23
60.07
61.92
50.86
53.67
42.87
45.98
44.91
45.70
59.58
64.40
53.00
54.43
64.08
65.60
53.83
64.73
53.16
55.25
48.91
50.68
50.30
52.08
50.68
52.46
52.78
52.93
62.75
63.71
55.45
59.47
57.70
56.50
65.32
64.40
53.11
F
25.0
74.42
74.23
54.04
57.77
52.18
50.85
63.79
67.16
45.57
45.70
40.45
40.84
50.68
50.06
54.56
57.39
59.23
62.99
37.09
39.95
36.20
36.55
52.01
53.46
48.16
51.33
60.68
62.17
47.94
53.28
56.53
58.39
50.11
53.19
47.60
50.70
50.34
49.80
48.34
46.20
72.74
74.75
60.51
65.35
49.96
51.83
78.09
79.50
53.84
M
38.0
55.68
59.71
46.04
62.44
49.42
74.33
61.07
67.19
39.31
41.21
49.38
49.80
43.54
57.37
56.24
61.25
56.94
65.92
39.75
44.87
37.47
38.88
57.81
59.48
46.09
48.47
66.28
58.48
56.01
59.52
62.21
54.53
55.39
50.13
56.49
50.96
48.24
47.11
47.43
42.77
52.36
55.05
49.61
54.78
42.18
46.41
56.37
58.28
54.68
F
13.0
73.93
75.86
58.70
60.07
71.67
71.44
70.68
72.55
26.86
28.09
44.42
48.64
53.55
48.54
68.74
70.19
68.62
72.39
47.37
51.20
45.25
50.06
57.23
60.21
48.13
47.51
58.38
57.16
49.23
58.20
55.54
53.34
53.25
52.60
53.38
53.44
50.03
51.70
52.53
53.07
56.01
56.80
48.27
50.61
45.64
45.68
60.28
60.68
52.34
F
18.0
61.69
64.45
64.23
69.24
53.49
64.16
64.18
68.49
50.07
52.68
45.69
48.91
51.13
50.51
61.10
66.00
55.74
62.13
43.97
52.06
45.81
49.21
66.69
69.06
49.53
51.85
62.98
68.45
67.33
68.58
59.21
66.09
58.30
64.23
61.97
69.30
60.81
62.83
59.66
63.39
67.96
68.38
64.54
66.12
59.11
59.41
65.22
66.12
57.86
AC-PC line. Using these orientation and scaling factors, each MR image was rotated and stretched to
the common atlas orientation.
Finally, we identified volumes of interest by selecting boundary coordinates of labeled brain regions in the reference atlas (Davis and Huffman,
1968), or outlining regions unnamed in the atlas
with the assistance of a neuroradiologist experienced in nonhuman primate anatomy. Twentyfour bilateral regions were analyzed in this study,
and are listed in Table 3. The atlas coordinates for
these regions are available online by contacting
J.A.K.
We performed several independent tests to ensure
that detected asymmetries were not artifacts of the
scanner or scanning properties. These tests included
confirmation of the midline position in the atlas-
transformed images, as well as test scans of a “phantom,” or container with uniform radioactivity. The
tests indicated no inherent asymmetries or distortions in the PET detection system.
The degree of left-right asymmetry was expressed
according to the ratio (Right ⫺ Left)/[(Right ⫹ Left)/
2]. Positive values indicate R ⬎ L asymmetry, and
negative values indicate L ⬎ R. Smith (1999) noted
that this ratio is numerically and proportionally
symmetric but is asymptotic. Therefore, he suggested the use of ln(Right/Left) instead, since this
ratio is nonasymptotic. However, our analyses
yielded identical results using either ratio with our
data. Since asymmetry is commonly reported as
(R ⫺ L)/[(R ⫹ L)/2] in the neurology literature, we
present our results in that form. The relationship
between asymmetry and age was examined by re-
372
J.A. KAUFMAN ET AL.
TABLE 3. Mean CBF values of study group and results of paired-samples t-tests
Cerebral blood flow (ml/100 g/min)
Left
Paired-samples t-tests
(right vs. left)
Right
Region
Mean
SD
Mean
SD
t
P
Motor cortex lower extremity
Motor cortex upper extremity
Motor cortex face
Supplementary motor area
Striate cortex
Orbitofrontal cortex
Dorsolateral prefrontal cortex
Anterior cingulate
Posterior cingulate
Amygdala
Hippocampus
Ventral caudate
Caudate body
Putamen
Nucleus accumbens
Globus pallidus pars externa
Globus pallidus pars interna
Ventral pallidum
Subthalamic nucleus
Substantia nigra
Medial/dorsal thalamus
Ventral/lateral thalamus
Cerebellar hemisphere
Lateral habenula
62.2
60.4
70.3
67.4
42.9
49.8
53.4
64.3
63.0
45.2
43.5
62.5
51.9
63.4
62.2
57.57
53.5
54.4
52.7
51.8
64.8
60.2
52.3
68.5
10.8
5.2
10.8
6.0
8.4
5.3
5.4
7.9
8.0
5.0
5.5
5.6
3.0
5.0
6.1
4.9
5.1
6.8
4.9
6.7
7.1
6.0
5.0
8.1
60.5
56.2
64.4
64.9
41.8
47.6
52.5
61.3
58.6
42.6
42.7
60.3
50.9
64.2
55.9
58.3
53.2
53.6
52.5
52.5
63.5
56.6
51.6
68.0
11.0
6.2
12.6
6.0
8.3
5.6
5.3
7.6
6.9
3.3
4.8
5.3
4.1
4.9
6.6
4.7
3.4
4.6
4.2
4.5
7.1
5.9
6.1
8.4
⫺3.28
⫺2.00
⫺1.66
⫺2.76
⫺2.91
⫺2.84
⫺0.39
⫺4.67
⫺4.16
⫺1.68
⫺0.78
⫺3.10
⫺1.26
0.52
⫺4.44
0.44
⫺0.24
⫺0.47
⫺0.33
0.79
⫺2.25
⫺4.37
⫺1.00
⫺1.06
0.017*
0.093
0.148
0.033*
0.027*
0.030*
0.709
0.003**
0.006**
0.143
0.465
0.021*
0.254
0.619
0.004**
0.678
0.822
0.655
0.755
0.460
0.065
0.005**
0.354
0.329
* P ⬍ 0.05.
** P ⬍ 0.01.
gressing body weight, as a surrogate for age, on the
absolute value of the asymmetry ratio.
RESULTS
Prior to pooling the scan data, we first analyzed
the sample variation in cerebral blood flow within
each region (left and right). By using nested
ANOVA, we computed variance components characterizing variation in rCBF: 1) among individuals, 2)
among sessions within individuals (nested component), and 3) within sessions (measurement error).
We then computed the ratio of variance among individuals to variance among sessions within individuals by dividing the mean-square values. In every
case, this ratio was greater than 150. In Table 1, we
present the ANOVA results for the two regions representing the minimum and maximum of these variance ratios. We note that the right orbitofrontal
cortex was the only region in which variation among
sessions within individuals was not significant.
Although there was significant variation among
sessions within individuals (with the one exception
just mentioned), the magnitude of this component is
miniscule compared to the magnitude of variation
among individuals. Given that the variation among
scanning sessions within individuals is so much
smaller than the variation among individuals as a
whole, we feel that the session data can be accurately and appropriately pooled for each individual.
Moreover, the variation within sessions is very
small, confirming that measurement error was successfully minimized.
The mean rCBF values for each individual are
presented in Table 2, and the group means and
standard deviations (SD) are summarized in Table
3. Blood flow varied significantly among regions (coefficient of variation ⫽ 13.3%). Blood flow was lowest
in the visual striate cortex (left, 42.9 ml/100 g/min;
right, 41.8 ml/100 g/min), hippocampus (left, 43.5
ml/100 g/min; right, 42.7 ml/100 g/min), and amygdala (left, 45.2 ml/100 g/min; right, 42.6 ml/100
g/min). The highest flow was recorded in the motor
cortex devoted to the face (left, 70.3 ml/100 g/min;
right, 64.4 ml/100 g/min). High CBF was also
present in the cingulate cortex and the lateral habenula. Additionally, the motor cortex of the face
and lower extremity were the most variable regions
in terms of blood flow (SD ⫽ 11.68 and 10.91, respectively). The mean value for global cerebral blood flow
among the seven individuals was 54.7 ml/100 g/min.
Absolute regional blood flow was uncorrelated with
age. There was an indication of sex-related differences (P ⬍ 0.05; df ⫽ 5) in two regions: the anterior
cingulate cortex and the substantia nigra. However,
when significance levels are adjusted for multiple
comparisons, we cannot statistically reject the null
hypothesis.
Figure 1 presents the percent asymmetry in rCBF
for each individual as calculated by (R ⫺ L)/[(R ⫹
L)/2] multiplied by 100. Individuals 3– 6 and 7 demonstrate consistent left-sided predominance in 18 or
more brain regions. The probability of 18 or more
regions exhibiting a common directionality purely
by random chance is less than 0.008 (binomial dis-
BABOON CEREBRAL BLOOD FLOW
373
Fig. 1. (See legend following page.)
tribution: n ⫽ 24, probability of occurrence ⫽ 0.5).
Individuals 4, 5, and 7 each exhibit 10 or more
regions with an asymmetry greater than 5%. Regional asymmetry on the order of 10% or more was
recorded in at least one region in all but one individual (number 2).
Table 3 also presents paired-sample t-values
(right vs. left) for the group means for each of the 24
374
J.A. KAUFMAN ET AL.
TABLE 4. Body weight regressed on absolute value of
asymmetry index
Fig. 1. Relative difference in cerebral blood flow between left
and right sides, calculated as (R ⫺ L)/[(R ⫹ L)/2]. Negative values
indicate left ⬎ right. See Tables for region abbreviations.
regions, along with uncorrected probabilities. We
also performed repeated trials in which each one of
the 7 individuals was sequentially omitted. The results were consistent, regardless of any single individual’s omission. Using a Bonferroni correction
(Sokal and Rohlf, 1995), three regions (anterior cingulate, posterior cingulate, and nucleus accumbens)
reach t-values corresponding to experimentwise significance adjusted for multiple comparisons tests
(adjusted ␣ ⫽ 0.10/24 ⫽ 0.0042). Six other regions
(motor cortex of the lower extremity, supplementary
motor area, striate cortex, orbitofrontal cortex, ventral caudate, and ventral thalamus) also showed
indications of left-dominant asymmetry; however,
the t-values for these regions did not reach the adjusted significance level.
Results for the relationship between asymmetry
and age are presented in Table 4. Significant correlations between degree of asymmetry and age were
detected in eight regions: the motor cortex of the
upper extremity and face, supplementary motor
area, anterior cingulate cortex, globus pallidus pars
interna, substantia nigra, lateral habenula, and cerebellum. In each case, a greater degree of left-right
asymmetry was associated with increased age.
DISCUSSION
It has been suggested that cerebral asymmetries
may be correlates of behavioral laterality. Handedness, for example, has been associated with both
structural asymmetry (Amunts et al., 1996; Foundas
et al., 1998; Hopkins and Rilling, 2000) and physiological asymmetry (Dassonville et al., 1997; Kawashima et al., 1997; Kim et al., 1993; Volkmann et
al., 1998) in the human brain.
Reports of physiological asymmetries in humans
during the resting state have been mixed, with
many studies finding no evidence for left-right dif-
Region
r
P
Motor cortex lower extremity
Motor cortex upper extremity
Motor cortex face
Supplementary motor area
Striate cortex
Orbitofrontal cortex
Dorsolateral prefrontal cortex
Anterior cingulate cortex
Posterior cingulate cortex
Amygdala
Hippocampus
Caudate (ventral)
Caudate (body)
Putamen
Nucleus accumbens
Globus pallidus pars externa
Globus pallidus pars interna
Ventral pallidum
Subthalamic nucleus
Substantia nigra
Thalamus (dorsomedial)
Thalamus (ventrolateral)
Lateral habenula
Cerebellum
0.56
0.89
0.78
0.87
0.22
⫺0.69
0.69
0.75
0.69
0.35
⫺0.42
⫺0.59
0.69
0.74
⫺0.54
0.59
0.75
0.69
⫺0.30
0.92
0.64
0.41
0.86
0.90
0.193
0.007**
0.037*
0.012*
0.631
0.084
0.084
0.051
0.085
0.439
0.353
0.167
0.087
0.060
0.207
0.161
0.053
0.086
0.515
0.004**
0.119
0.366
0.014*
0.005**
* P ⬍ 0.05.
** P ⬍ 0.01.
ferences (Catafau et al., 1996; Moeller et al., 1996;
Murphy et al., 1996; Seitz and Roland, 1992;
Younkin et al., 1988). We have summarized the results of those studies that do report significant baseline physiological asymmetries in Table 5. For humans, the direction of asymmetry is generally
indicative of right-hemispheric predominance (but
see Gur et al., 1995; Podreka et al., 1989). Regionally, asymmetries have most often been reported for
the temporal region, but also appear in the somatosensory cortex, occipital, frontal, and parietal cortex,
and basal ganglia. The prevalence of right-sided
physiological predominance in the temporal region
seems at odds with the left-predominant anatomical
asymmetries of the planum temporale, thought to
indicate left-hemispheric predominance in language
(Geschwind and Galaburda, 1987; Geschwind and
Levitsky, 1968). Indeed, Mazziotta et al. (1982) reported higher glucose metabolic rates in the left
temporal regions in 22 normal, right-handed subjects. It is possible that the discrepancy arises from
differences in scanning technique or resolution that
could increase errors related to partial-volume averaging. However, until a specific cause (whether
methodological or functional) is identified, it would
be premature to equate structural predominance
with physiological predominance.
Four of the 11 studies in Table 5 did not report the
magnitude of differences when presenting significance tests. In one study (Krausz et al., 1998, p.
430), it was reported that “although the difference
. . . between the sides was highly significant, the
magnitude of the absolute difference between the
sides was only marginal.” In contrast, Rodriguez et
al. (1991, p. 61) reported that the differences they
375
BABOON CEREBRAL BLOOD FLOW
TABLE 5. Summary of physiological asymmetries reported in literature1
Species
(source)
Pig
Macaque
Human
Human
(Madsen et al., 1990)
(Eberling et al., 1995)
(Devous et al., 1986)
(Hagstadius and Risberg,
1989)
(Kolbitsch et al., 2000)
(Van Laere et al., 2001b)
(Podreka et al., 1989)
(Krausz et al., 1998)
(Rootwelt et al., 1986)
(Gur et al., 1995)
(Rodriguez et al., 1991)
(Fujita et al., 1990)
(Perlmutter et al., 1987)
Human
Human
Human
Human
Human
Human
Human
Human
Human
HmS
WM
Tmpl
SM
Occ
Frnt
Prtl
R (NR)
R (NR)
STR
Hipp
L (6.6%)
L (2.9%)
L (2.6%)
L (4.8%)
L (12.0%)
R (NR)
R (2.9%)
R (NR)
R (4.3%)
R (NR)
R (4.1%)
R (4.9%)
R (1.4%)
R (5.5%)
R (6.9%)
R (5.7%)
L (2.2%)
R (1.6%)
R (8.2%)
B (2.4%)
R (NR)
R (3.3%)
R (NR)
L (NR)
L (NR)
L (1.4%)
R (2.6%)
L (NR)
R (8.5%)
L (NR)
L (1.8%)
R (NR)
R (11.3%)
R (5.5%)
1
R, right predominant; L, left predominant; B, bidirectional asymmetry; HmS; hemisphere; WM, white matter; Tmpl, temporal cortex;
SM, sensorimotor cortex; Occ, occipital cortex; Frnt, frontal cortex; Prtl, parietal cortex; STR, striatum; Hipp, hippocampus. Asymmetry index appears in parentheses. NR, not reported.
detected were “so small in magnitude (⬍2%), that
we believe this finding to be of little physiological
meaning.” At present there is no standard threshold
in effect size below which even a statistically significant difference is considered to be of no functional
consequence. Furthermore, the null hypothesis being tested is always false in the real world, i.e., the
difference between left and right is never exactly
zero (Cohen, 1990, 1994). For this reason, it is incumbent upon researchers to address the magnitude
of differences, even when those differences are statistically significant.
For those studies that do report effect sizes, the
asymmetry indices range from 1.4 –12%, with a
mean of 5% (Table 5). In comparison, the effect sizes
in our study on baboons are relatively large. One
individual (number 5) showed a left-right asymmetry of 40%, though this was the most extreme. However, differences of 10% or more were not uncommon
among the individuals we examined (Fig. 1).
Our data for baboons also indicate general lefthemispheric predominance in cerebral blood flow, in
contrast to the generalized right-hemispheric predominance reported for humans. Given the relative
inconsistency of the comparative data, it would be
premature to impute a functional significance to
these results. However, the presence of baseline
physiological asymmetry in the nonhuman primate
brain is itself an interesting result. We are aware of
two other animal studies that reported baseline
physiological asymmetries: one in the pig (Madsen
et al., 1990), and one in the macaque (Eberling et al.,
1995) (see Table 5). Other animal studies, however,
have not detected asymmetry (e.g., Jacobs et al.,
1995), so the data remain inconsistent. Until the
discrepancy is resolved, it would be premature to
assume that physiological brain asymmetry is a
uniquely human characteristic (if it is truly a human
characteristic at all!).
Age-related decline in cerebral blood flow and metabolism is commonly reported (e.g., Devous et al.,
1986; Tanaka et al., 2000; Van Laere et al., 2001b;
Waldemar et al., 1991), and several studies documented increases in left-right asymmetries with in-
creasing age (Markus et al., 1993; Van Laere et al.,
2001b; Waldemar et al., 1991; Yamaguchi et al.,
1986). However, other studies found patterns of
asymmetry to be age-invariant (Hagstadius and Risberg, 1989; Krausz et al., 1998). One possible explanation is age range. It may be that asymmetries are
more pronounced in individuals of advanced age.
There is support for this hypothesis in pathological
cases of Alzheimer’s disease or elderly depression.
Our results indicate that left-right physiological
asymmetries increase with age, even in normally
functioning animals.
One of the limitations of any baseline study is the
issue of defining a baseline or “resting” state, as well
as the difficulties of achieving that state with a
subject in the scanner. This is a formidable problem
with a human subject, and clearly more so with a
nonhuman primate. We are encouraged, though, by
the partitioning of variance components in our data
set, and the resulting ratios of variance among individuals to variance among sessions within individuals (Table 1). These results indicate that regional
blood flow measurements are highly reproducible,
with little day-to-day variation in comparison to the
differences among animals.
Although nitrous oxide has minimal effects on
cerebral blood flow and metabolism (Crosby et al.,
1984; Ingvar et al., 1980; Ingvar and Siesjo, 1982),
sedation is clearly not equivalent to the conscious,
resting state. Yet, one may anticipate that anxiety
and stress of restraint in an awake, trained animal
may produce greater variations in cerebral physiology. Until imaging technologies permit quantitative
measurements of rCBF with little or no invasive
procedures using brief scanning sequences lasting
only a few seconds, we must continue to accept the
artificial baseline state provided by sedation.
CONCLUSIONS
We found asymmetric regional cerebral blood flow
in healthy, sedated baboons. This asymmetry was
apparent both hemispherically as well as on the
regional level. Furthermore, the degree of asymmetry, as calculated by an asymmetry index, increased
376
J.A. KAUFMAN ET AL.
with age. This result agrees with previous studies on
human aging. We conclude that physiological asymmetry may characterize the baseline state of the
brain in nonhuman primates as well as humans.
Furthermore, age is an important factor in the magnitude of asymmetries of cerebral blood flow, and
should be considered in future studies.
ACKNOWLEDGMENTS
We thank two anonymous reviewers for their
valuable suggestions.
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