Regional aerobic glycolysis in the human brain
S. Neil Vaishnavia, Andrei G. Vlassenkoa, Melissa M. Rundlea, Abraham Z. Snydera,b, Mark A. Mintuna,c,
and Marcus E. Raichlea,b,c,d,1
Departments ofaRadiology,bNeurology,dAnatomy and Neurobiology, andcBiomedical Engineering, Washington University, St. Louis, MO 63110
Contributed by Marcus E. Raichle, August 9, 2010 (sent for review July 28, 2009)
Aerobic glycolysis is defined as glucose utilization in excess of
that used for oxidative phosphorylation despite sufficient oxygen
to completely metabolize glucose to carbon dioxide and water.
Aerobic glycolysis is present in the normal human brain at rest and
increases locally during increased neuronal activity; yet its many
biological functions have received scant attention because of
a prevailing energy-centricfocus on the role of glucoseas substrate
for oxidative phosphorylation. As an initial step in redressing this
neglect, we measured the regional distribution of aerobic glycol-
ysis with positron emission tomography in 33 neurologically
normal young adults at rest. We show that the distribution of
aerobic glycolysis in the brain is differentially present in previously
well-described functional areas. In particular, aerobic glycolysis is
significantly elevated in medial and lateral parietal and prefrontal
cortices. In contrast, the cerebellum and medial temporal lobes
have levels of aerobic glycolysis significantly below the brain
mean. The levels of aerobic glycolysis are not strictly related to
the levels of brain energy metabolism. For example, sensory cor-
tices exhibit high metabolic rates for glucose and oxygen con-
sumption but low rates of aerobic glycolysis. These striking re-
gional variations in aerobic glycolysis in the normal human brain
provide an opportunity to explore how brain systems differentially
use the diverse cell biology of glucose in support of their functional
specializations in health and disease.
blood flow|glucose consumption|metabolism|oxygen consumption|
positron emission tomography
glucose to carbon dioxide and water, it has traditionally been
referred to as aerobic glycolysis. Aerobic glycolysis has a long
history in cancer cell biology, where the phenomenon was first
noted by Otto Warburg (1), for whom it is often referred to as
the “Warburg effect.” Since Warburg’s early work (2), much
research has focused on the reasons for aerobic glycolysis mainly
in cancer cells (3–5). Topics have included, but are not limited
to, the role of aerobic glycolysis in biosynthesis, the maintenance
of cellular redox states, the regulation of apoptosis and the
provision of ATP for membrane pumps and protein phosphor-
ylation. Little attention has been paid to the normal brain in this
regard, despite the well documented presence of aerobic gly-
colysis (6–8; noteworthy recent exception in ref. 9).
Froma whole-brainperspective, aerobicglycolysismayaccount
for ∼10–12% of the glucose used in the adult human (6–8). This
percentage varies in interesting ways. In the newborn, it repre-
sents more than 30% of the glucose metabolized (10). In the
adult,aerobicglycolysisvariesdiurnally froma lowinthemorning
of ∼11% to nearly 20% in the evening (7). In none of these
observations do we have any information on the regional distri-
bution of aerobic glycolysis in the brain or its role in cell biology.
The only information presently on regional brain aerobic gly-
colysis relates to task-induced changes in brain activity. Aerobic
glycolysis has been observed locally to increase in the human
brain during task-induced increases in cellular activity (11–13).
Research on this activity-induced increase in aerobic glycolysis
has focused on the mechanism by which glutamate is moved with
sodium into astrocytes from the synapse. Findings strongly im-
hen glucose metabolism exceeds that used for oxidative
phosphorylation despite sufficient oxygen to metabolize
plicate membrane-bound, astrocyte Na+/K+ATPase (14), which
relies on glycolysis for the energy needed to remove the accu-
mulated sodium from the astrocytes.
The experiments reported herein seek to expand our un-
derstanding of the role of glycolysis in the resting activity of the
adult human brain by determining whether regional variations in
glycolysis exist and how these regional variations might relate
to regional variations in overall brain energy consumption. We
were particularly interested to determine whether known func-
tional specializations among brain areas are reflected in their use
of aerobic glycolysis.
Measures of Resting Oxygen and Glucose Metabolism. The cerebral
metabolic rate for oxygen (CMRO2) and cerebral metabolic
rate for glucose (CMRGlu) as well as the cerebral blood flow
(CBF) were imaged with PET in 33 normal right-handed adults in
the resting awake state with eyes closed. Regional CMRGlu was
measured using [18F]-labeled fluorodeoxyglucose (FDG). Re-
the administration of -labeled water, carbon monoxide, and
oxygen. In each individual, regional CMRO2and CMRGlu were
scaled toawhole-brain meanof1(local-to-global ratio;Methods).
The individual results were averaged over subjects in a standard
Aerobic glycolysis is traditionally assessed in terms of the molar
ratio of oxygen consumption to glucose utilization [i.e., the so-
called oxygen–glucose index (OGI)]. When all of the glucose
metabolized is converted to carbon dioxide and water the OGI
is 6. A number less than 6 indicates that aerobic glycolysis is
present. In this study, we estimated aerobic glycolysis in this tra-
ditional manner by the voxelwise division of relative CMRO2by
relative CMRGlu and scaling the resulting quotient imaging to
obtain a whole-brain molar ratio of 5.323 based on earlier pub-
lished work (6–8).
Although the OGI is a straightforward measure based on well-
established metabolic principles, OGI images may be noisy in
areas of low metabolism because they involve voxelwise division.
Also, the value of the OGI is inversely related to the degree of
aerobic glycolysis, a relationship sometimes confusing to readers.
To overcome these limitations, we defined a previously unchar-
acterized measure of aerobic glycolysis in the brain: the glycolytic
index (GI). The GI is obtained by conventional linear regres-
sion of CMRGlu on CMRO2(Fig. S1) and exhibiting the re-
siduals scaled by 1000 (a procedure generally preferred for re-
moval of covariates in contrast to ratio normalization). Positive
Author contributions: M.A.M. and M.E.R. designed research; S.N.V., A.G.V., and M.M.R.
performed research; S.N.V., A.G.V., M.M.R., A.Z.S., M.A.M., and M.E.R. analyzed data; and
S.N.V. and M.E.R. wrote the paper.
The authors declare no conflict of interest.
Freely available online through the PNAS open access option.
Data deposition: Data reported in this article have been deposited in the Central Neuro-
imaging Data Archive (https://cnda.wustl.edu/) (accession no. NP721).
See Commentary on page 17459.
1To whom correspondence should be addressed. E-mail: firstname.lastname@example.org.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| October 12, 2010
| vol. 107
| no. 41
GI values represent more aerobic glycolysis and negative GI
values represent less glycolysis than that predicted by the line of
regression. The two measures of aerobic glycolysis, OGI and GI,
are highly correlated in our data (r = −0.913, P < 0.001) (Fig.
S1). For descriptive purposes, we will use the GI.
Following computation of GI maps for each subject, signifi-
cance was assessed at the population level by voxelwise t tests
against the null hypothesis of uniformly proportional glucose-to-
oxygen metabolism, i.e., no deviation from the line of regression.
The t maps were converted to equi-probable Z-maps and thre-
sholded at P < 0.0001 (Z > 4.4, cluster >99 voxels) according to
previously described methodology (15, 16).
Resting Aerobic Glycolysis. Regions with significantly elevated aer-
obic glycolysis were found bilaterally in prefrontal cortex, lateral
parietal cortex, posterior cingulate/precuneus, lateral temporal
gyrus, gyrus rectus, and caudate nuclei (Fig. 1 and Table 1). In
the inferior temporal gyrus and throughout the cerebellum.
Although the GI overall correlated to varying degrees with
CBF and various metabolic measurements (Table 2), it is note-
worthy that regional variations in CMRO2, the primary measure
of the brain’s energy metabolism in this study, accounted for only
6% of the variance in aerobic glycolysis regionally. Clearly, fac-
tors other than brain work are contributing to the regional var-
iations in aerobic glycolysis in the normal human brain. Data for
all Brodmann regions are listed in Tables S1 and S2. Data for
selected subcortical regions (Fig. S2) are listed in Table S3.
Brain Systems Exhibiting Elevated Aerobic Glycolysis. Examination
of the GI map (Fig. 1 and Fig. 2A) suggested a correspondence
between regions showing higher than average glycolysis and two
distributed systems previously defined on the basis of func-
tional neuroimaging studies, specifically, the default mode net-
work (DMN) (17, 18) and additional areas in dorsolateral
prefrontal and parietal cortices associated with task control pro-
cesses (19–21). The DMN comprises brain regions that reliably
reduce activity during the performance of goal-directed tasks
(22). More recently, the DMN has been delineated by correlation
mapping of spontaneous fluctuations of the blood oxygen level–
dependent (BOLD) functional MRI (fMRI) signal acquired in
the resting state (23, 24).
To delineate the DMN, we performed resting BOLD corre-
lation mapping (25) in a subset (n = 20) of the present subjects.
The DMN was mapped by conjunction analysis of the signals
averaged over three nodes of the DMN (posterior cingulate
[–5, –49, 40], left lateral parietal [–45, –67, 36], and medial
prefrontal [–1, 47, –4] cortex). Similarly, the system associated
with cognitive control and working memory was mapped using
a distribution of seed regions placed bilaterally in prefrontal
[–34, 51, 12], [24, 50, 13] and anterior parietal [–43, –55, 42],
[48, –47, 42] cortex. Regions of significant BOLD correlations
default and control systems are shown in Fig. 2 B and C, re-
spectively. Figure 2D shows the overlap between regions of ele-
vated aerobic glycolysis and a mask computed as above threshold
in either the DMN or control system. These two distributed sys-
tems together account for most cortical areas showing high levels
of aerobic glycolysis at rest.
Finally, we noted various apparent hemisphere asymmetries in
context of our entire data set, none of these apparent as-
ymmetries are statistically significant when corrected for multiple
comparisons. It therefore remains for future research to deter-
driven, targeted approach.
The regional variations in aerobic glycolysis in the normal human
brain are striking (Fig. 1). The highest levels reside within two
cortical systems, the DMN (17), which has come to be associated
with a variety of self-referential functions (18) as well as a more
fundamental role in the organization of brain function (26, 27);
and areas in frontal and parietal cortex that have been associated
with task control processes (19–21) (Fig. 2). As a counterpoint to
brain systems with elevated aerobic glycolysis are areas with
significantly reduced GI levels relative to the brain mean. Most
prominent among these are the cerebellum and the hippocampal
formation, an element of the DMN (23, 28). For future research
the challenge will be to understand why levels of aerobic gly-
colysis vary so dramatically among brain systems. We examine
the possibilities in terms of functions attributed to aerobic gly-
colysis, recognizing at the outset that few answers presently exist.
Our objective is to identify opportunities for future work.
Energy. One factor responsible for ongoing aerobic glycolysis in
the brain is likely to be the need to support membrane-bound,
ATP-dependent processes. Best characterized in this regard is
the process whereby glutamate is removed from the synapse into
astrocytes along with sodium. The sodium is then returned to the
extracellular fluid by Na+/K+-ATPase. The energy needed for
the pumping action of Na+/K+-ATPase is derived from aerobic
glycolysis (29, 30).
That glycolysis might supply ATP for membrane bound Na+/
K+-ATPase is neither new nor restricted to the brain. Data from
human red cell membranes (31), skeletal muscle (32), vascular
smooth muscle (33), and neurons (34) all provide independent
evidence in support of such a possibility. The use of aerobic gly-
colysis as a brain energy source may seem surprising because it is
seemingly inefficient: glycolysis produces a net 2 ATP versus 30
ATP for complete oxidation to carbon dioxide and water. How-
ever, it produces ATP at a rate much faster than oxidative phos-
rapidly changing requirements in energy for Na+/K+-ATPase.
Because of the unique role of the astrocyte in using aerobic
glycolysis for glutamate cycling, it is interesting to note that the
ratio of neurons to nonneuronal cells can vary greatly in the hu-
33, groupwise t test, |Z|>4.4, P < 0.0001, cluster > 99, corrected for multiple
comparisons). Specifically, regions with significantly high glycolysis include
bilateral prefrontal cortex, bilateral lateral parietal lobe, posterior cingulate/
precuneus, gyrus rectus, bilateral lateral temporal gyrus, and bilateral cau-
date nuclei. In contrast, cerebellum and bilateral inferior temporal gyrus
have significantly low levels of aerobic glycolysis.
Distribution of aerobic glycolysis in resting human brain using GI (n =
| www.pnas.org/cgi/doi/10.1073/pnas.1010459107 Vaishnavi et al.
man brain (36). For example, the cerebral cortex contains ≈19%
of the brain’s neurons and nearly 72% of its nonneuronal cells,
whereas in the cerebellum the percentages are reversed
[i.e., 80% and 19%, respectively (36)]. This observation suggests
that one of the factors contributing to the regional variation in
aerobic glycolysis may be the percentage of nonneuronal cells.
An analysis of the cerebral cortex with regard to regional var-
iations in the ratio of neurons to nonneuronal cells would be
most interesting particularly if it could identify the percentage of
nonneuronal cells that are astrocytes.
A more extended view of the role of aerobic glycolysis in the
generation of ATP has emerged from the observation that gly-
colytic enzymes are found in the postsynaptic density (PSD) (34),
a very dynamic complex containing various ion channel proteins,
synaptic receptors, and signal transduction pathways (37, 38) that
are turning over and being replaced with half-lives of minutes,
hours, days, or weeks (39). In the PSD, Na/K-ATPase has been
identified as critical for AMPA receptor turnover (40). Na/K-
ATPase dysfunction leads to a loss of cell-surface expression of
AMPA receptors and a long-lasting depression in synaptic trans-
mission (40). If one of the reasons for positioning glycolytic
enzymes in the PSD is to fuel the Na/K-ATPase pump, then
aerobic glycolysis assumes a critical role in synaptic plasticity.
With regard to the energy needs of the PSD, it should be
noted that mitochondria are rarely seen in dendritic spines (41,
42) in contrast to axons (43), notwithstanding the fact that lac-
using the GI and BOLD correlation maps of the default and cognitive control
systems. (A) Regions with elevated aerobic glycolysis (n = 33, groupwise t
test, Z > 4.4, P < 0.0001, cluster > 99, corrected for multiple comparisons). (B)
Default system as delineated by BOLD correlation mapping (n = 20, group-
wise t test, Z > 3.0, P < 0.01, cluster > 17, corrected for multiple compar-
isons). (C) Cognitive control system defined as in B. (D) Intersection of voxels
showing significantly elevated GI and membership in either the default or
cognitive control systems.
Results of conjunction analysis between resting aerobic glycolysis
(n = 33, groupwise t test, Z > 4.4, cluster >99, corrected for multiple comparisons) under the assumption of a homogenous normal
bivariate distribution of CMRO2and CMRGlu
Regions with aerobic glycolysis, as determined by glycolytic index, significantly (P < 0.0001) different from line of regression
RegionZ score AVG Z scoreCoordinates GIOGICMRO2
9.30 6.30 [ 41, 13, 34] 271.36 102.74 ± 18.924.61 ± 0.11 1.07 ± 0.02 1.18 ± 0.021.10 ± 0.02
9.06 5.74[–41, –61, 36]33.1785.55 ± 22.354.70 ± 0.161.10 ± 0.021.19 ± 0.031.06 ± 0.03
8.165.70[47, –57, 40] 30.3882.37 ± 26.97 4.71 ± 0.16 1.11 ± 0.031.19 ± 0.03 1.08 ± 0.03
8.035.90[1, –59, 24]29.97 107.55 ± 29.18 4.73 ± 0.161.30 ± 0.04 1.39 ± 0.041.27 ± 0.03
[31, 27, –14]
[61, –35, –8]
75.15 ± 32.94
66.45 ± 35.03
4.76 ± 0.22
4.75 ± 0.20
1.02 ± 0.04
1.10 ± 0.04
1.08 ± 0.05
1.16 ± 0.05
1.03 ± 0.05
1.06 ± 0.04
6.01 4.98[–57, –31, –18]5.26 64.88 ± 34.364.71 ± 0.24 1.02 ± 0.06 1.09 ± 0.061.00 ± 0.05
[7, 9, 8]
[–11, 5, 16]
[1, –11, –24]
78.45 ± 56.24
79.08 ± 61.48
−94.52 ± 22.88
4.47 ± 0.32
4.55 ± 0.39
5.67 ± 0.28
0.84 ± 0.09
0.94 ± 0.10
0.92 ± 0.04
0.94 ± 0.11
1.04 ± 0.09
0.83 ± 0.03
0.86 ± 0.10
0.95 ± 0.09
0.99 ± 0.04
−5.94[33, 5, –18]32.86
−101.59 ± 21.215.70 ± 0.220.93 ± 0.030.83 ± 0.03 1.00 ± 0.03
−6.64 [1, –61, –22]259.42
−143.46 ± 25.055.94 ± 0.231.04 ± 0.03 0.89 ± 0.031.06 ± 0.03
Data are shown as mean ± SD. Coordinates represent peak GI Z score location in Talairach system. CBF, cerebral blood flow; CMRGlu, cerebral metabolic
rate of glucose; CMRO2, cerebral metabolic rate of oxygen; GI, glycolytic index; L, left; R, right; AVG, average.
Correlations over Brodmann regions between
CBF, cerebral blood flow; CMRGlu, cerebral metabolic rate of glucose;
CMRO2, cerebral metabolic rate of oxygen; GI, glycolytic index; OGI, oxygen-
*P < 0.001.
**P < 0.05.
Vaishnavi et al. PNAS
| October 12, 2010
| vol. 107
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tate transporters designed to import lactate into dendritic spines
as mitochondrial fuel are present (44). Reconciling such seem-
ingly contradictory observations with the energy needs of den-
dritic spines presently is difficult. Regardless of the outcome it is
important to note that aerobic glycolysis makes many other im-
portant contributions to the cell biology of the brain that may be
equally important to the synapse. We review these next.
Biosynthesis. Glucose makes important contributions to anabolic
processes in all organs of the body providing needed inter-
mediates for cellular proliferation including NADPH, nucleo-
tides for DNA replication (45), and intermediates for fatty acid
synthesis (46, 47) all largely by way of the pentose phosphate
pathway (PPP). In animal experiments, estimates of the amount
of glucose entering the PPP in the mature brain have been vari-
able but generally low (reviewed in ref. 48). Recent work in cul-
tured neurons places this figure considerably higher because of an
apparently low level of phosphofructokinase-2 (PFK-2) in neu-
rons (49). PFK-2 is a key regulator of PFK-1, the gatekeeper of
glycolysis (49). Could this difference between cultured neurons,
usually harvested from immature animals, and in vivo measure-
ments be a function of development, with maturity shifting glu-
cose away from the PPP toward glycolysis?
Several lines of research provide a perspective from which to
evaluate the above question. These include brain development
and the sleep–wake cycle in adults. In the developing nervous
system, aerobic glycolysis appears to play a substantial role, con-
sistent with its potential to provide the building blocks for cell
development and proliferation. In the preterm human infant,
glycolysis accounts for more than 90% of the glucose consumed
(50, 51). By term, 35% of the glucose consumed by the human
infant represents aerobic glycolysis (10) compared with 10–12%
in the adult (6, 8).
From term to adulthood, we have information only on the
CMRGlu (52) preventing the assessment of aerobic glycolysis
specifically during this critical developmental period. This is a se-
rious void in our knowledge. Nevertheless, it is noteworthy that
CMRGlu achieves adult levels by 2 y of age and continues to rise
over the first decade to levels twice that of the adult (an aston-
ishing increase if it truly represents oxidative phosphorylation,
which seems unlikely) and then commences a gradual decline
to adult levels by the early 20s (52). This trajectory in CMRGlu
parallels the known overproduction of neuropil components fol-
lowed by their pruning as the brain achieves adult status. Refining
of development should receive high priority in future research.
The necessary data must come from parallel measurements of
CMRO2and CMRGlu that are required for the quantification of
activity of enzymes critical for the control of the brain’s inter-
mediary metabolism during development. Although it is unlikely
that such experiments will be conducted in humans, primate mod-
els of spinogenesis (53) provide an ideal model system for quan-
titative in vivo metabolic studies with PET and complementary
studies of enzyme activity.
Data supporting the possible role of aerobic glycolysis in an-
abolic processes in the adult brain come from two sources. First,
whole-brain studies of CMRO2and CMRGlu in humans reveal
a diurnal variation in both CMRO2, which is 20% higher, and
CMRGlu, which is 38% higher, in the evening before sleep as
compared with the next morning. From these data it can be es-
timated that aerobic glycolysis almost doubles during wakeful-
ness. Second, Madsen et al. (54) reported a persistent resetting
of the OGI (i.e., ∼10% increase in aerobic glycolysis) following
the performance of a demanding cognitive task. Together these
two studies provide a tentative link between the metabolism of
learning-induced biosynthesis and a hypothesis that associates
wakefulness with synaptic potentiation and sleep with synaptic
renormalization (55, 56), a process that has been associated with
changes in brain glucose consumption in laboratory animals (57).
Redox States. Glucose plays an important role regulating the re-
dox state of the brain. This occurs both during the production of
ATP via glycolysis and also through the operation of the PPP.
The importance of the redox state to energy production and the
regulation of CBF via glycolysis has received considerable at-
tention (see refs. 58 and 59 regarding the recent work on CBF),
whereas the importance of glucose in regulating the redox state
of the brain via the PPP has not. A recent paper (9) redresses this
neglect by suggesting that glucose acting via the PPP inhibits
apoptosis in both cancer cells and neurons by the redox in-
activation of cytochrome c. The insight that this work provides is
that both cancer cells and neurons achieve an adaptive advan-
tage for long-term survival through management of their redox
state via the PPP. Particularly interesting in this regard is the fact
that areas of the normal human brain with elevated aerobic
glycolysis (Fig. 1) are nearly identical with those that accumulate
amyloid, and exhibit atrophy and disrupted metabolism in Alz-
heimer’s disease as detailed in our companion paper (60) as well
as elsewhere (61). This observation suggests to us that a loss of
an adaptive advantage provided by aerobic glycolysis in brain
systems that are particularly dependent upon it might be a critical
component in the pathophysiology of Alzheimer’s disease, a sub-
ject that we have previously explored in more detail (60).
In summary, we hope that our work will serve to stimulate
the interest of the neuroscience community in the many critical
functions glucose serves in the brain including, but not limited to,
substrate for energy generation through glycolysis and oxidative
phosphorylation. The opportunities for a deeper understanding
of brain function in health and disease this affords seem plentiful.
Participants. A total of 33 healthy, right-handed neurologically normal par-
ticipants (19 women and 14 men) aged 20–33 y (mean 25.4 ± 2.6 y) were
recruited from the Washington University community. Subjects were ex-
cluded if they had contraindications to MRI, history of mental illness, pos-
sible pregnancy, or medication use that could interfere with brain function.
All experiments were approved by the Human Research Protection Office
and the Radioactive Drug Research Committee at Washington University in
St. Louis. Written informed consent was provided by all participants.
Image Acquisition. MRI scans for structural and functional imaging were
obtained on a 3-T Allegra scanner (Siemens), and all PET studies were per-
formed on a Siemens model 961 ECAT EXACT HR 47 PET scanner (Siemens/
CTI). Image acquisition details are available in SI Text.
General PET Data Analysis. We have assessed regional differences in resting
CMRO2, CMRGlu, and aerobic glycolysis in a manner independent of whole-
brain quantitative measures. This strategy (Methods) differs somewhat from
that originally described (11, 62–64) in which absolute rates for CMRGlu and
CMRO2were determined. The primary advantage of the present strategy is
its improved accuracy in determining the regional variations in CMRO2and
CMRGlu. This is due to the elimination of rapid arterial blood sampling for
the determination of an arterial input function for quantitative measure-
ments of CMRO2 and CMRGlu. Arterial blood sampling of rapidly time-
varying radioactivity is an inherently noisy measurement that would have
significantly compromised our ability to accurately assess levels of metabo-
lism regionally. Because our primary interest was in regional variations in
our measurements and not absolute values, we elected to forego arterial
blood sampling in this study.
Preprocessing. For each subject, measures of CBF, cerebral blood volume,
CMRO2, and CMRGlu were aligned to each other and then to the subject’s
MRI scan [magnetization-prepared 180° radio-frequency pulses and rapid
gradient-echo image (MP-RAGE)]. The realigned data were then trans-
formed to atlas space using in-house software and scaled to a whole-brain
mean of 1 (local-to-global ratio as in ref. 22). Our atlas representative target
image represents Talairach space as defined by Lancaster et al. (65).
| www.pnas.org/cgi/doi/10.1073/pnas.1010459107Vaishnavi et al.
OGI. OGI was computed by a voxelwise division of CMRO2by CMRGlu to
compute a local-to-global OGI. For comparison with traditional OGI meas-
ures, this ratio was scaled by 5.323 (6).
GI. To quantitatively assess aerobic glycolysis, we performed a linear re-
gression of CMRGlu on CMRO2. The residuals were scaled by 1,000 to pro-
duce the GI, which represents glucose consumption above or below that
predicted by oxygen consumption.
PET statistics. Tocombineresultsacrosssubjects,wecomputed agenerallinear
model that contained metabolic data for CMRO2, CMRGlu, CBF, OGI, and GI
for each subject. We performed groupwise random effects analysis (one-
sample t test; n = 33) to determine regions with significant deviations in
their metabolic values from the whole-brain mean. Images were thresholded
at a Z > 4.4 (P < 0.0001, cluster >99, corrected for multiple comparisons).
Surface mapping. Volumetric statistical results were projected onto the cortical
surface of the PALS B12 (population-average landmark and surface-based)
atlas by multifiducial mapping (66). Surface mapping was performed using
CARET v5.512 (http://brainmap.wustl.edu/caret).
Brodmann regions. Brodmann regions were extracted from the PALS B12 atlas
using CARET v5.512 (http://brainmap.wustl.edu/caret). Values for CMRO2,
CMRGlu, CBF, OGI, and GI were extracted for each Brodmann region in the
brain (41 regions for each hemisphere) from the general linear model
computed for each subject. Comparison of metabolic values between dif-
ferent Brodmann regions involved paired group wise t tests (n = 33, two-
tailed α = 0.05).
Correlations. Pearson product–moment correlations between metabolic val-
ues were performed over cortical Brodmann regions. Correlations were
weighted by the size (number of voxels) of the Brodmann regions used.
Weighted correlation across Brodmann regions is equivalent to voxelwise
computation of the standard Pearson product–moment correlation after
assigning to every voxel within a Brodmann region the value of its regional
mean. Significance of correlations was computed using α = 0.05 and 80 df.
Statistical analysis was performed using SPSS for Windows v16.0 (SPSS Inc).
Subcortical regions. As CARET (http://brainmap.wustl.edu/caret) does not pro-
vide subcortical parcellations, regions of bilateral caudate, putamen, globus
pallidus, and thalamus were manually drawn on our representative atlas
MPRAGE using Analyze v6.1 (Mayo) as shown in Fig. S2 and presented in
Default mode network and control system regions. Details of the seed-based,
resting-state fMRI strategy used in the delineation of elements of these two
systems are presented in Figs. S3 and S4. The results of this analysis are
presented in Tables S4 and S5.
Conjunction analysis. A conjunction analysis was performed to qualitatively
compare regions with elevated aerobic glycolysis measured via PET and the
default and cognitive control systems delineated by resting-state fMRI corre-
lation mapping (image acquisition section in SI Text). Z score maps of aerobic
glycolysis were thresholded at a Z > 4.4 (P < 0.0001, cluster > 99 voxels, cor-
rected for multiple comparisons). The conjunction image (Fig. 2D) was com-
puted by identifying voxels showing significantly elevated aerobic glycolysis
and being within either default or control systems (conjunction = GI signifi-
cantly high Λ [voxel ∈ default system V voxel ∈ cognitive control system]).
ACKNOWLEDGMENTS. We thank Lenis Lich for many years of skilled tech-
nical assistance in PET imaging and Lars Couture and Russ Hornbeck for help
with data processing and analysis. This work was supported by the National
Institutes of Health Grants NS06833, NS057901, NS048056, and MH077967
and by a grant from the James S. McDonnell Foundation.
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