Asymmetric regional cerebral blood flow in sedated baboons measured by positron emission tomography (PET).код для вставкиСкачать
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: email@example.com 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. 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