J Neurophysiol 88: 3477–3486, 2002;
10.1152/jn.00107.2002.
Brain Responses Associated With the Valsalva Maneuver Revealed
by Functional Magnetic Resonance Imaging
LUKE A. HENDERSON,1 PAUL M. MACEY,1 KATHERINE E. MACEY,1 ROBERT C. FRYSINGER,1
MARY A. WOO,4 REBECCA K. HARPER,1 JEFFRY R. ALGER,2,5 FRISCA L. YAN-GO,3
AND RONALD M. HARPER1,5
1
Department of Neurobiology, 2Department of Radiological Sciences, 3Department of Neurology, 4School of Nursing,
and 5Brain Research Institute, University of California at Los Angeles, Los Angeles, California 90095
Received 11 February 2002; accepted in final form 2 August 2002
The Valsalva maneuver consists of a prolonged expiratory
effort resulting in increased intrathoracic pressure, with concomitant decreased venous return and alterations in arterial
pressure (AP) and heart rate (HR). To maintain homeostasis,
changes in sympathetic and parasympathetic outflow emerge,
and the contributions of each component have been defined in
the accompanying physiological patterns (Levin 1966; Sandroni et al. 2000). The maneuver has been valuable for assessment of autonomic disturbance in a number of clinical syndromes, including diseases of the CNS (e.g., Parkinsons
disease), neuropathies (diabetes) (Low 1996), and sleep disorders (obstructive sleep apnea) (Hanly et al. 1989; Naliboff et al.
1993; Netten et al. 1995).
Because the maneuver elicits a range of autonomic responses that may exhibit deficiencies in a number of conditions, it is important to determine the neural sites mediating
these physiologic reactions. Examination of the time course of
signal changes in these participating brain regions would assist
understanding of the mechanisms integrating the responses to
the challenge and aid in evaluation of the sympathetic or
parasympathetic components of autonomic output. Determination of the multiple neural regions that take part in afferent,
integrative, or efferent responses to the Valsalva maneuver
requires procedures that are able to simultaneously examine
diverse areas of the brain. We have previously (Harper et al.
2000) used functional magnetic resonance imaging (fMRI)
procedures to examine the participation of certain brain areas
that respond to the Valsalva effort and have shown that multiple sites, including cerebellar, cortical, and limbic regions,
mediate aspects of the response to this challenge. Technical
restrictions at that time precluded examination of signal
changes in brain stem sites or temporal characteristics of signal
intensity changes in relation to physiological variables. The
advent of improved imaging procedures has provided a means
to visualize signal changes over the entire brain, including
medullary areas. Together with magnetic resonance (MR)–
compatible electrophysiological recording equipment, the procedural developments allow examination of the time course of
the signal intensity changes within defined regions of interest,
and also allow evaluation of correlations of these signal
changes with cardiovascular and respiratory patterns.
We examined the distribution and time course of extent of
signal intensity changes in normal control subjects to Valsalva
maneuvers and correlated signal change patterns to cardiovascular and respiratory patterns.
Address for reprint requests: R.M. Harper, Dept. of Neurobiology, Univ. of
California at Los Angeles, Los Angeles, CA 90095-1763 (E-mail:
[email protected]).
The costs of publication of this article were defrayed in part by the payment
of page charges. The article must therefore be hereby marked ‘‘advertisement’’
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
INTRODUCTION
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0022-3077/02 $5.00 Copyright © 2002 The American Physiological Society
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Henderson, Luke A., Paul M. Macey, Katherine E. Macey, Robert C.
Frysinger, Mary A. Woo, Rebecca K. Harper, Jeffry R. Alger, Frisca
L. Yan-Go, and Ronald M. Harper. Brain responses associated with
the Valsalva maneuver revealed by functional magnetic resonance imaging. J Neurophysiol 88: 3477–3486, 2002; 10.1152/jn.00107.2002. The
Valsalva maneuver, a test frequently used to evaluate autonomic
function, recruits discrete neural sites. The time courses of neural
recruitment relative to accompanying cardiovascular and breathing
patterns are unknown. We examined functional magnetic resonance
imaging signal changes within the brain to repeated Valsalva maneuvers and correlated these changes with physiological trends. In 12
healthy subjects (age, 30 –58 yr), a series of 25 volumes (20 gradient
echo echo-planar image slices per volume) was collected using a
1.5-Tesla scanner during a 60-s baseline and 90-s challenge period
consisting of three Valsalva maneuvers. Regions of interest were
examined for signal intensity changes over baseline and challenge
conditions in cardiorespiratory-related regions. In addition, whole
brain correlations between signal intensity and heart rate and airway
load pressure were performed on a voxel-by-voxel basis. Significant
signal changes, correlated with the time course of load pressure and
heart rate, emerged within multiple areas, including the amygdala and
hippocampus, insular and lateral frontal cortices, dorsal pons, dorsal
medulla, lentiform nucleus, and fastigial and dentate nuclei of the
cerebellum. Signal intensities peaked early in the Valsalva maneuver
within the hippocampus and amygdala, later within the dorsal medulla, pons and midbrain, and deep cerebellar nuclei, and last within
the lentiform nuclei and the lateral prefrontal cortex. The ventral
pontine signals increased during the challenge, but not in a fashion
correlated to load pressure or heart rate. Sites showing little or no
correlation included the vermis and medial prefrontal cortex. These
data suggest an initiating component arising in rostral brain areas, a
later contribution from cerebellar nuclei, basal ganglia, and lateral
prefrontal cortex, and a role for the ventral pons in mediating longer
term processes.
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METHODS
Subjects
Twelve healthy subjects (11 male and 1 female; mean age, 47 ⫾ 3
yr; range, 30 –58 yr) participated in the study. No subjects exhibited a
history of autonomic dysfunction and none were currently taking
beta-blockers, alpha-agonists, vasodilators, angiotensin-converting
enzyme inhibitors, or cholinergic-stimulating drugs. All procedures
were carried out with the adequate understanding and written consent
of the subjects, and the study was approved by the Institutional
Review Board at University of California, Los Angeles (UCLA).
Physiological recording
MR imaging
Images were collected with a 1.5-Tesla MR scanner (General
Electric Signa, Milwaukee, WI), and a standard head coil at the UCLA
Center for the Health Sciences. Foam pads were placed on either side
of the head and masking tape applied to the forehead to minimize head
movement. Gradient echo echo-planar imaging–sensitive blood oxygen level– dependent (BOLD) contrast (Kwong et al. 1992; Ogawa et
Data analysis
Image analysis was performed with MedX (Sensor Systems, Sterling, VA) and SPM99 software (Friston et al. 1995). Following
removal of the first volume to account for scanner saturation, image
volumes were corrected for slice timing and motion-corrected. Images
were then spatially normalized so that image volumes of all subjects
were in the same three-dimensional (3D) space. This spatial normalization was carefully refined to ensure that, in particular, brain stem
sites were located in the same 3D space in all subjects. Spatially
normalized images were Gaussian smoothed (full-width at half maximum ⫽ 8 mm). To evaluate whether global signal changes produced
by the Valsalva maneuver varied across different regions of the brain,
overall raw signal intensities for individual slices, averaged across all
subjects, were calculated at each time point (Fig. 1A). The percent of
total brain signal intensity at each time point for individual slices was
FIG. 1. A: raw signal intensity (SI) of 13 axial brain slices numbered caudally (1) to rostrally (13). Each line represents the
average of the same axial slice in all 12 subjects. B: percent signal intensity compared with global signal intensity for each of the
13 axial brain slices. Although global signal intensity changes during the Valsalva maneuver, the change is spread uniformly across
different axial slices, suggesting that global changes are distributed evenly across the brain. Dashed vertical lines indicate the onset
and termination of each of the 3 Valsalva maneuvers (V).
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Subjects practiced the Valsalva maneuver three times outside the
scanner for procedure familiarization. Each participant wore nose
clips and breathed via a mouthpiece through a two-way nonrebreather
respiratory valve (Hans Rudolph, Kansas City, MO). Two small
airtight tubes were attached to the distal end of the mouthpiece. One
tube was used to monitor end-tidal CO2 and the other was led outside
the scanner room to a pressure transducer for monitoring of airway
load pressure. An electrocardiogram (ECG) was obtained using standard MR-compatible surface electrodes and oxygen saturation was
measured using a Nonin oximeter. The ECG and oximetry signals
were fed to low noise amplifiers (Parker et al. 1999) and transferred
outside the MR room via infrared devices (Harper et al. 2001).
Thoracic wall movement was monitored using an air-filled bag placed
against the thoracic wall and held in place using a cloth belt. A
nondistensible tube attached to this bag was passed outside the scanner room to a pressure transducer. Arterial pressure readings were
obtained immediately prior to and immediately following each scanning period. All physiological signals were digitized at 1 kHz. Respiratory and heart rates were calculated using a peak-detection algorithm.
al. 1990) was used to identify brain areas in which blood flow and/or
metabolism activated in accordance with the challenge. BOLD fMRI
signal changes have been shown to correlate with local field potentials
and reflect input and intracortical processing that occurs within a
given area (Logothetis et al. 2001). A time series of 25 echo-planar
image volumes [time to repetition (TR) ⫽ 6 s per volume, time to
echo ⫽ 60 ms, flip angle ⫽ 90°, field of view ⫽ 30 ⫻ 30 cm, no
interslice gap, voxel size ⫽ 2.3 ⫻ 2.3 ⫻ 5.0 mm thick], composed of
20 oblique sections, was acquired continuously during a 150-s period.
The scanning period was divided into an initial 60-s baseline (10
volumes) followed by a 90-s challenge period (15 volumes).
During the challenge, three Valsalva maneuvers were performed.
Subjects were instructed to exhale strongly into the mouthpiece for a
period of 18 s (3 volumes). The expiratory limb of the breathing
circuit was fitted with a flow resistor during this period. This resistor
had a very small opening that allowed a slow air leak, ensuring that
the patient had an open glottis and an accurate measure of intrathoracic pressure was obtained. Following this 18-s period, the flow
resistor was removed and the subject breathed freely for 18 s. The
Valsalva maneuver was then repeated twice more for a total of three
trials. During the three maneuvers, subjects were required to maintain
a mean load pressure (LP) above 30 mmHg. A series of T1-weighted
anatomical images (time to repetition ⫽ 500 ms, time to echo ⫽ 9 ms,
field of view ⫽ 30 ⫻ 30 cm, no interslice gap, voxel size ⫽ 1.2 ⫻
1.6 ⫻ 5.0 mm thick) was collected at the same levels as the functional
images.
NEURAL RESPONSES TO VALSALVA MANEUVER
FIG.
2.
used to establish statistical significance. Since we calculated mean
signal intensity for each ROI and did not correlate individual voxel
signal patterns with an a priori sequence of physiological changes,
small volume correction was not performed. Cross-correlations were
calculated between signal intensity change and both LP and HR.
Maximum temporal resolution was limited by the TR of 6 s, giving
three data points for each Valsalva maneuver per subject.
Using points of maximal correlation of signal intensity change
with LP, a conjunction analysis, using a fixed effects model, was
performed on a voxel-by-voxel basis between mean LP and signal
intensity across all subjects. Significant voxels, corrected for multiple comparisons, (Resel corrected P ⬍ 0.01) were color-coded for
significance and overlaid onto spatially normalized mean T1weighted anatomical brain slices and rendered onto the surface of
the brain. These significant voxels were initially overlaid onto a
mean functional image to ensure that any nonlinear distortions did
not affect the location of these significant regions when overlaid
onto the anatomical image sets. The conjunction analysis identifies
regions significantly activated in every subject of the study and
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calculated and plotted over time (Fig. 1B). Since the small decrease in
global signal intensity was spread uniformly across the brain, images
were intensity normalized so that the signal intensity of each slice
remained constant.
Using the nonsmoothed, functional images, regions of interest
(ROI) were selected using anatomical landmarks (Fig. 2). The medulla, dorsal pons, deep cerebellar nuclei, cerebellar vermis, dorsal
midbrain, amygdala, hippocampus, and insular cortex were chosen on
the basis of closely defined relationships. The striatum was selected
for its role in motor control, and the frontal cortex for its participation
in motor expression. The ventral pons and midbrain were chosen as
control sites. These ROIs were then overlaid onto the intensity normalized and smoothed images, and a single mean signal intensity
value for each region of interest was calculated. The percent changes
of these values, relative to baseline at each time point, were calculated, and these values were then averaged over all subjects. The
mean ⫾ SE values at each time point were then subjected to a
repeated measures ANOVA analysis, which accounts for multiple
comparisons within subjects, and a probability value of P ⬍ 0.01 was
Regions of interest (ROI) used for detailed time-trend analysis are outlined.
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with 99% confidence that at least one-half the population would
show this effect (Friston et al. 1999).
Valsalva ratios (VR) for each subject were calculated (maximum R-R
interval divided by the minimum R-R interval) for each of the three
maneuvers. This ratio was used to establish that those physiologic values
were within normal limits. Correlations of VR with age and LP with age
were calculated to evaluate age as a confounding factor.
RESULTS
Physiology
fMRI signal changes
During each Valsalva maneuver, minor global signal intensity changes were distributed evenly throughout the entire
brain and were removed by intensity normalization (Fig. 1).
Brain stem
Brain regions in which fMRI signal intensity was significantly
correlated to LP with a lag-time of 5 s are shown in Figs. 4 and 5.
Significant increases in signal intensity emerged within the dorsal
medulla, the midline medulla, the dorsal pons, and the dorsal and
ventral midbrain, reaching mean maxima of 2.0 ⫾ 0.8%, 3.1 ⫾
1.5%, 3.3 ⫾ 0.9%, 2.0 ⫾ 0.8%, and 1.6 ⫾ 0.5%, respectively
(Fig. 6). The signal intensity increases of all these areas began
shortly after the onset of the Valsalva maneuver, reached maxima
approximately 14 s after the start of each Valsalva period, and
declined in the intervening rest periods (Fig. 7A). In contrast, the
signal intensity within the ventral pons increased gradually over
the entire three-trial challenge period and was not correlated to
either LP or HR.
Cerebellum
The Valsalva maneuvers evoked significant increases in
signal intensity within the cerebellum, which were correlated
to HR and LP. These signal intensity increases, which were
limited to the fastigial (mean max ⫽ 2.1 ⫾ 0.7%) and dentate
nuclei (mean max ⫽ 1.7 ⫾ 0.5%), peaked on average 15 s after
the start of each Valsalva maneuver, and returned to baseline
during the rest periods. No significant change in signal occurred in other cerebellar structures.
Rostral sites
FIG. 3. A: mean (black) ⫾ SE (gray) heart rate (HR), respiratory rate (RR),
arterial oxygen saturation (O2sat), and load pressure (LP) for all 12 subjects.
Dashed vertical lines indicate the onset and termination of each of the 3
Valsalva maneuvers (V). Heart rate increased during, and for a period of time,
following each Valsalva maneuver. B: Valsalva ratios (MaxR-R/MinR-R) for
each of the 3 Valsalva maneuvers in all 12 subjects, expressed as a function of
age. Valsalva ratio decreased significantly with increasing age. C: load pressure expressed as a function of age. Load pressure did not change with
increasing age.
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Within limbic structures, significant increases in signal intensity developed immediately following the onset of each
Valsalva maneuver in the amygdala (mean max: 1.2 ⫾ 0.7%)
and hippocampus (mean max: 1.2 ⫾ 0.5%; Fig. 6). These
regions reached maxima shortly after the onset of each Valsalva maneuver (amygdala: 5.4 ⫾ 1.6 s; hippocampus: 5.5 ⫾
1.8 s); afterward, they rapidly returned to baseline levels.
In basal ganglia and cortex, significant increases in signal
intensity occurred in the lentiform nucleus (mean max: 0.9 ⫾
0.4%) and the insular cortex (mean max: 1.3 ⫾ 0.4%; Figs.
4 – 6). As was the case with brain stem structures, the signal in
the insular cortex began to increase early and peaked 14 ⫾ 1 s
after onset of each Valsalva effort. The rendered view of the
cerebral cortex in Fig. 5 shows significant activation of a
discrete region in the lateral prefrontal cortex (mean max:
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Subjects showed a mean blood pressure of 93 ⫾ 3 mmHg
(systolic ⫽ 128 ⫾ 4 mmHg; diastolic ⫽ 79 ⫾ 2 mmHg) prior
to onset of the maneuver. Prior to the challenge period, mean
resting respiratory rate was 10 ⫾ 1 bpm. During each Valsalva
maneuver, subjects exerted a mean airway LP of 39 ⫾ 3
mmHg (Fig. 3A). Approximately 7 s after the beginning of
each effort, HR began to increase from a baseline value of
62 ⫾ 3 bpm. Heart rate continued to increase during the effort,
reaching a peak 3.4 ⫾ 0.3 s after the completion of each
Valsalva maneuver (mean max ⫽ 88 ⫾ 5 bpm). This peak was
followed by a rapid decrease below baseline (nadir ⫽ 53 ⫾ 3
bpm), and a slow return toward baseline during the remainder
of the 18-s recovery period. VR values ranged from 1.3 to 3.6
(mean ⫽ 2.1 ⫾ 0.2); values for the three trials for all 12
subjects as a function of age are plotted in Fig. 3B. The decline
in VR as a function of increasing age was revealed by a
significant correlation between age and VR (Pearson’s r ⫽
0.75, df ⫽ 34, P ⬍ 0.01). This significant correlation did not
result from changes in LP with increasing age (Pearson’s r ⫽
0.22, df ⫽34, P ⬎ 0.2; Fig. 3C).
NEURAL RESPONSES TO VALSALVA MANEUVER
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FIG. 4. Areas significantly correlated (P ⬍ 0.01 corresponding to t ⬎0.72) with mean load pressure with a lag-time of 5 s.
Voxels are coded-coded for significance level and overlaid on anatomical images in sagittal (A and B), coronal (i and ii), and axial
(1– 8) views. Image levels are shown in inferior and lateral outlines of the brain.
2.4 ⫾ 0.6%). Although signal intensity within the lentiform
and lateral prefrontal cortex began to increase at approximately
the same time as brain stem structures, they were last of all
structures to peak, reaching maxima approximately 21 s after
onset of the Valsalva effort (Figs. 7 and 8).
Time onset
Cross-correlations of neural signal changes with the LP and
HR values, during the first Valsalva maneuver, were calculated
and plotted (Fig. 7B). The morphology of cross-correlation
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plots for each ROI relative to LP and HR were similar, but the
maximum cross-correlations of most structures showed an
approximate 6-s delay in the HR peak with respect to LP.
Signal maxima in the hippocampus and amygdala occurred
earliest, followed by signal intensity peaks in the brain stem,
cerebellum, and insular cortex. Later peaks occurred within the
lentiform nucleus and the lateral prefrontal cortex (Fig. 7A). A
summary of the mean HR, LP, O2 saturation, and global and
regional signal intensity traces is shown in Fig. 8. The regional
changes in signal intensity are divided into three broad groups:
short, medium, and long latency to peak.
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HENDERSON ET AL.
FIG. 5. Areas significantly correlated (P ⬍ 0.01; t ⬎0.72) with mean load pressure showing a lag-time of 5 s rendered onto the
left and right surfaces of the brain. Significant voxels are color-coded.
Physiology
The HR response to the Valsalva maneuver was consistent
with previous reports for subjects with no autonomic dysfunction (Ravits 1997). At onset of strain, the increased intratho-
FIG. 6. Averaged (⫾SE) time trends of functional magnetic resonance
imaging (fMRI) signal changes during the course of 3 Valsalva maneuvers
(gray shaded areas) for 17 brain areas outlined in Fig. 2. *Significant points
(P ⬍ 0.01) of the white square graphs. †Significant points of the black circle
graphs. ‡Significant points of the white triangle graphs.
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racic pressure compresses the great vessels, resulting in a
transient increase in arterial pressure (AP). As increased thoracic pressures continues, venous return decreases, reducing
AP to or below baseline levels. In an attempt to offset this fall
in AP, the autonomic nervous system is recruited, evoking an
initial withdrawal of vagal tone and a later increase in sympathetic drive resulting in increasing HR. Finally, as the strain is
FIG. 7. A: mean time to maximum in signal intensity for the 1st Valsalva
maneuvers in all 12 subjects for 12 ROIs. Time is relative to the onset of the
1st Valsalva maneuver. B: cross-correlation coefficients between fMRI signal
and load pressure and heart rate for defined regions (in color) during the 1st
Valsalva maneuver. Peak at 0 indicates a simultaneous change in inferred
neural activity and the physiology measures. Peak to the right of 0 indicates the
neural response lags the physiology.
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DISCUSSION
NEURAL RESPONSES TO VALSALVA MANEUVER
released, a transient fall in AP below baseline occurs, followed
by an overshoot of AP above baseline and HR below baseline.
The Valsalva maneuver has been standardized at a load
pressure of 40 mmHg for a minimum of 15 s. We set a protocol
that required subjects to initiate and maintain load pressures of
30 –50 mmHg for ⱖ15 s. All subjects were able to meet this
criterion and exhibited normal HR response to the Valsalva
maneuver. All subjects produced mean VRs within normal
limits (Baldwa and Ewing 1977; Levin 1966).
Limitations
AUTOREGULATION. The Valsalva maneuver has been used as a
test of cerebral autoregulatory capacity. In healthy individuals,
middle cerebral artery flow declines during the middle stages
of the Valsalva maneuver but is quickly restored to baseline
levels prior to the restoration of AP, indicative of appropriate
autoregulatory functioning. These changes in flow are significantly smaller in the supine position than during standing (Pott
et al. 2000; Tiecks et al. 1996). We observed a small overall
decrease in global signal intensity during each Valsalva maneuver, likely resulting from changes in perfusion pressure as
well as from alterations in arterial CO2. However, photic
stimulation evokes regional signal intensity changes in the
primary visual cortex even during extremely large changes in
overall cerebral perfusion induced by changes in inspired CO2;
the responses to photic stimulation are superimposed on the
large increase in overall global signal intensity (Corfield et al.
2001; Kemna and Posse 2001; Li et al. 2000). Further, follow-
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ing intensity normalization, which removes global signal intensity changes, the signal intensity changes in the visual
cortex were similar to those found during photic stimulation in
the absence of increased CO2. Although the magnitude and
timing of these changes differ slightly from those found without CO2, the overall pattern and direction remain unchanged.
The normalization procedure, together with the findings that
areas immediately adjacent to recruited sites showed different
patterns of signal intensity response, including no signal intensity change, suggests that the signal changes reported in this
study result from differential recruitment of brain sites and not
from global changes in cerebral blood flow.
MOTION ARTIFACTS. Motion artifact is an issue of concern for
all studies employing fMRI. To avoid motion artifact, we
placed foam pads on either side of the head and secured the
forehead of each subject to the scanner using tape. In addition,
before scanning, each subject was trained to perform the maneuver while concentrating on keeping his/her head stationary.
The success of these procedures was evident by the finding that
at no time did any subject’s head move more than 1 mm in any
direction. Despite the absence of gross movement, motioncorrection was performed on the image sets of all subjects.
These corrections, combined with the highly localized and
varying nature of the signal intensity changes, provide confidence that the signal changes observed during the Valsalva
maneuver resulted from recruitment of neural structures, and
not as a result of movement artifact.
HEMODYNAMIC DELAY. The hemodynamic response varies in
timing, amplitude, and pattern across brain regions. The central
tendency of the response, however, is reproducible to within a
second within any single brain site (Aguirre et al. 1998; Henson et al. 2002; Huettel and McCarthy 2001; Miezin et al.
2000), and some studies show no systematic difference in
hemodynamic differences between the cortex and brain stem
(Backes and van Dijk 2002). Sequential trial presentations can
modify the hemodynamic response of subsequent trials (Huettel and McCarthy 2001; Miezin et al. 2000). To avoid this
interaction, we measured the time to peak only to the first
Valsalva maneuver. The 6-s scan interval in this study limits
the resolution of this time to peak measurement. We therefore
restricted our description to three broad groups—short, medium, and long latency to peak. The short latency group peaks
at approximately 6 s, the medium latency at approximately
14 s, and the long latency group at approximately 21 s. The
Valsalva maneuver results in a defined sequence of physiologic
events including onset of a respiratory effort, a parasympathetic withdrawal and a subsequent sympathetic outflow increase. This physiologic sequence occurs over a period of ⱖ30
s, a period sufficiently long that recruitment of structures can
be assessed despite a coarse sampling resolution. The timing of
signal change over this prolonged period may give insights into
contributions of particular areas to physiologic patterns. These
large differences in timing suggest that any small hemodynamic timing differences that may occur between different
brain regions would not significantly affect the relative order of
the short, medium, and late latency to peak groups.
Short latency to peak
Regions in which signal intensity peaked at the onset of the
Valsalva maneuver are likely to be involved in mediating the
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FIG. 8. Summary of the mean HR, LP, O2sat, and global and regional SI
changes plotted over time. Regional SI changes are divided into 3 groups:
short, medium, and long latency to maximum peak in signal intensity as in Fig.
7A.
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Medium latency to peak
Regions exhibiting a delayed onset and gradual increase in
signal intensity, a pattern similar to the HR response, are likely
to represent those areas mediating the decrease in cardiac
parasympathetic and increase in cardiac sympathetic drive. The
medial medulla, dorsal medulla, dorsal pons, midbrain, and
insular cortex all exhibited this response pattern, with the
greatest magnitude in signal intensity change occurring in the
dorsal pons (Figs. 6 and 8). The parabrachial complex, which
lies within the dorsolateral aspect of the pons, sends direct
projections to medullary sites that contain both respiratory and
cardiovascular motor neurons [the nucleus of the solitary tract
(NTS) and the rostral ventrolateral medulla (RVLM)] (Herbert
et al. 1990). On activation, the parabrachial complex can evoke
increases in sympathetic activity and HR (Chamberlin and
Saper 1992) and alter the functioning of the baroreceptor reflex
(Saleh and Connell 1997).
The NTS, which lies within the dorsal medulla, exhibited
substantial signal increases with the challenge. The NTS is the
primary termination site of afferents arising from almost all
cardiovascular receptors, and on activation, can elicit profound
changes in AP and HR. The NTS alters sympathetic cardiac
outflow via projections to the RVLM, either directly or via the
caudal ventrolateral medulla, and can modify parasympathetic
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cardiac outflow via direct projections to the vagal cardiac
preganglionics near the nucleus ambiguus (Dampney 1994).
Despite the close interconnectivity, increased NTS signal intensity did not alter ventrolateral medullary activity, a surprising outcome. The lack of significant signal intensity change
may have been the product of the multiplicity of neuronal types
in the ventrolateral medulla, which contains cells that both
increase sympathetic and decrease parasympathetic outflow to
the heart. The relatively poor spatial resolution of the fMRI
technique may not allow sufficient resolution to differentiate
discrete subsets of neurons. Localization within a region must
await higher-resolution mapping.
The midline medulla (medullary raphe nuclei) plays a significant role in cardiac and respiratory control. Chemical activation of this region results in marked AP and HR changes,
alters respiratory patterning and enhances phrenic nerve discharge (Bernard 1998; Haxhiu et al. 1998; Henderson et al.
1998). The increased signal intensity in the midline raphe
during the Valsalva maneuver may represent compensatory
responses to alter AP or may reflect action to increase phrenic
nerve discharge and thus maintain the greatly enhanced respiratory effort.
The late onset, gradual rise in signal intensity in the insular
cortex is consistent with previous work of King et al. (1999).
Both animal and human studies show that the insular cortex
plays a role in autonomic function, as indicated by electrical
stimulation, stroke, lesion, and fMRI data (Corfield et al. 1995;
Oppenheimer 1994). Strokes localized to insular cortex result
in a great number of cardiovascular complications and increased mortality due to autonomic imbalance compared with
strokes located in other cortical regions (Oppenheimer et al.
1996; Tokgozoglu et al. 1999). Previous PET studies reveal
significant activation in insular cortex during air hunger (Banzett et al. 2000; Liotti et al. 2001; Peiffer et al. 2001), a feeling
subjects in this study experienced, by self-report, toward the
end of each Valsalva maneuver. In addition to a role in the
autonomic component of the Valsalva maneuver, the insular
cortex may also be involved in dyspnea. Unlike the dorsal
pons, the ventral pons did not show a correlation with the HR
or LP; instead, signal intensity increased over time and remained elevated in the inter-trial gap (Fig. 6). This action may
represent an overall arousal to the challenge.
As was the case in brain stem regions, deep cerebellar nuclei
began to increase signal intensity early in the Valsalva maneuver; intensity remained significantly increased until after completion of each Valsalva effort. A cough bears many resemblances to the respiratory pattern of the Valsalva maneuver,
with an initial deep inspiration followed by expiration against
a closed glottis. Studies in the cat have revealed that lesions
encompassing the rostral interpositis nucleus, a deep cerebellar
nucleus, attenuate coughing (Xu and Frazier 1997). During
active expiration, PET studies also show significant increases
in activation in the cerebellum (Ramsay et al. 1993). The
cerebellar nuclei may act in a compensatory or “error correction” mode, mediating both somatomotor and AP components
of the Valsalva response. Cerebellar structures play a significant role in somatomotor control of respiration; cerebellar
damage can result in impaired breathing when coordination
with other body movements is necessary, even if breathing at
rest is normal (Ebert and Hefter 2001). The active somatomotor efforts required for the Valsalva challenge may require
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initiation of the respiratory effort or a preparatory component
of the challenge. Taking into account a general hemodynamic
delay of 5 s, the signal intensity in the amygdala peaked at
approximately the onset of the Valsalva effort and slightly later
in the hippocampus, both returning to baseline shortly thereafter (Figs. 6 – 8). Immediately prior to each Valsalva maneuver, subjects inspired deeply to ensure adequate air supply for
the 18-s effort. The early onset of the hippocampal response
suggests a role in mediating this initial inspiratory effort, an
expected finding considering the demonstration of close interactions of breathing patterns and hippocampal single cell discharge (Frysinger and Harper 1989), electroencephalographic
activity (Whishaw and Schallert 1977), electrical stimulation
(Ruit and Neafsey 1988), and optical imaging findings (Poe et
al. 1996). Collectively, this evidence suggests that the hippocampus participates in aspects of breathing control and is
associated with initiation of the sequence of respiratory events
accompanying the Valsalva maneuver.
The central nucleus of the amygdala projects heavily to the
parabrachial pons, nucleus of the solitary tract, and the periambigual region (Hopkins and Holstege 1978), sites which
contribute significantly to respiratory phase-switching or other
aspects of autonomic control. Single pulse electrical stimulation of the amygdala central nucleus results in a switch to
inspiration (Harper et al. 1984); thus the amygdala may also be
participating, with the hippocampus, in the initial inspiratory
effort required for the Valsalva maneuver. Structures within
the amygdala mediate aspects of affect, and in particular,
anxiety (Buchel and Dolan 2000; Lang et al. 2000). The
confined space of the MR scanner, combined with the extreme
effort required to perform the Valsalva maneuver, often lead to
a mild feeling of anxiety, particularly during the first trial. The
initial increase and subsequent decrease in signal intensity may
reflect this feeling. We do not, however, have an independent
measure showing such a decline in anxiety level.
NEURAL RESPONSES TO VALSALVA MANEUVER
participation of cerebellar structures, particularly the dentate
nuclei. Arterial pressure manipulations, such as cold pressor
challenges or mental stressor tasks that have an absence of
motoric action, show recruitment of cerebellar sites, especially
the deep cerebellar nuclei (Critchley et al. 2000; Harper et al.
2000). The fastigial nucleus appears to play a significant role in
compensating for extremes in AP; fastigial nuclei lesions result
in a failure to restore AP during hypovolemia or endotoxic
shock in animals, resulting in death (Lutherer et al. 1983).
Patients presenting with multiple system atrophy, of which
cerebellar pathology is a feature, or olivepontocerebellar degeneration, show central autonomic dysfunction (Chokroverty
1984; Smith et al. 1996). We speculate that the dentate and
fastigial nuclei participate in regulatory roles for breathing and
AP control, respectively, and that deficits in capability to
develop LP or appropriate HR responses to the Valsalva maneuver may involve these cerebellar nuclei.
A discrete region of the lateral prefrontal cortex, corresponding to the supplementary motor area of the upper airway, and
the lentiform nucleus, another motor region, showed significant
increases in signal intensity during each Valsalva maneuver,
with long latency to peak (Fig. 8). The supplementary motor
area of the upper airway, on the left side, is known as Broca’s
area. This region is involved in motor aspects of speech,
involving complex interactions of upper airway muscle action.
This region is also consistently activated during swallowing
(Mosier et al. 1999), a task also integrating upper airway
muscle activity. Given that this region is activated during the
entire maneuver and has a signal intensity peak at the completion of each maneuver, we suggest that it is involved in
mediating muscle control of the upper airway during the challenge.
The Valsalva maneuver recruits neural structures throughout
the rostrocaudal extent of the brain. Early recruitment occurs
within limbic structures, which may help initiate the maneuver.
Slightly delayed, gradual increases were found in the dorsal
brain stem, insular cortex, and cerebellum, and likely represent
regions involved in increasing sympathetic and decreasing
parasympathetic cardiac drive. Structures showing maximal
increases in signal even later include regions of the basal
ganglia and supplementary motor cortex. The findings emphasize the distributed nature of a relatively simple challenge, and
suggest that participation of discrete brain sites can be partitioned by consideration of timing of signal changes.
We thank C. Valderama for technical assistance.
This research was supported by National Heart, Lung, and Blood Institute
Grant HL-60296.
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