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The Journal of Neuroscience, November 1, 1998, 18(21):8990-9001
Odorant-Induced and Sniff-Induced Activation in the Cerebellum of
the Human
Noam
Sobel1,
Vivek
Prabhakaran1,
Catherine A.
Hartley2,
John E.
Desmond3,
Zuo
Zhao3,
Gary H.
Glover4,
John D.E.
Gabrieli1, 3, and
Edith V.
Sullivan1, 5
Programs in 1 Neuroscience and 2 Symbolic
Systems, and Departments of 3 Psychology,
4 Radiology, and 5 Psychiatry and Behavioral
Sciences, Stanford University, Stanford, California, 94305
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ABSTRACT |
Functional magnetic resonance imaging was used to test whether
odorants induce activation in the cerebellum of the human. The odorants
vanillin and propionic acid both induced significant activation,
primarily in the posterior lateral hemispheres. Activation was
concentration-dependent, greater after stimulation with higher concentration odorants. By contrast, the action of sniffing nonodorized air induced significant activation in the anterior cerebellum, primarily in the central lobule. These findings demonstrate that the
cerebellum plays a role in human olfaction. A hypothesis is proposed
whereby the cerebellum maintains a feedback mechanism that regulates
sniff volume in relation to odor concentration.
Key words:
olfaction; cerebellum; sniffing; odor; smell; human
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INTRODUCTION |
The cerebellum is a brain structure
located at the back of the brain that in the human contains more
neurons than the rest of the brain combined (Williams and Herrup,
1988 ). The cerebellum has classically been considered as primarily a
motor control organ (Ito, 1984; Thach et al., 1992; Horne and Butler,
1995) with a specific role in motor learning (Lisberger, 1988;
Lisberger et al., 1994). Recent functional imaging experiments in
humans pointed to cerebellar involvement in a host of additional
functions such as tactile sensory discrimination (Gao et al., 1996),
attention (Allen et al., 1997), and cognitive function (Petersen et
al., 1988; Kim et al., 1994; Raichle et al., 1994; Fiez, 1996; Parsons and Fox, 1997; Desmond et al., 1997, 1998; Poldrack et al., 1998; Schmahmann and Sherman, 1998).
Whereas cerebellar functions in visually and auditory related tasks
have been extensively described (Snider and Eldred, 1948; Bloedel,
1973; Stein and Glickstein, 1992; Huang and Liu, 1991), no role has yet
been suggested for the cerebellum in olfaction. This is surprising
because olfaction is a sensory process largely dependent on the fine
motor process of sniffing (Adrian, 1942; Le Magnen, 1945; Rehn, 1978;
Mozell et al., 1983). Sniffing plays a major role not only in transport
of the olfactory stimulus (Hahn et al., 1994) but also in patterns of
neural activity in primary olfactory cortex in the human (Sobel et al.,
1998). Furthermore, a fine reciprocal interaction persists whereby
sniffing strategy and timing modulate odorant intake, and in turn,
odorant intake content modulates further sniffing. For example, in
response to increasing odorant concentration there is a decrease in
sniff volume (Laing, 1983; Youngentob et al., 1987).
Cerebellar involvement in respiration (Mansfeld and Tyukody, 1936;
Colebatch et al., 1991) suggests that sniff motor/sensory circuits may
be in part controlled by cerebellar circuits. Thus, considering that
odor content affects sniffing, odor content information may also be
relayed to the cerebellum. Although preliminary reports using
functional magnetic resonance imaging (fMRI) suggested that odorants
may indeed activate the cerebellum (Yousem et al., 1997; Sobel et al.,
1997a), this question has not been addressed in detail. Here we test
whether odorants induce activation in the cerebellum and whether this
activation would be dissociated from activation induced by
sniffing.
Findings of cerebellar involvement in various tasks and modalities may
still be explained within the framework of the cerebellum as a motor
control system (Thach, 1996; Bloedel and Bracha, 1997), but they have
also given rise to new theories of cerebellar function (Schmahmann,
1997). These include timing of motor performance (Ivry, 1997),
coordinating acquisition of sensory data (Bower, 1997), neural
representation of moving systems (Paulin, 1997), and facilitating
attentional shifts (Courchesne et al., 1994; Akshoomoff et al., 1997).
Elucidating a cerebellar role in olfaction may enable further
characterization of the role of the cerebellum in relation to these
theories.
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MATERIALS AND METHODS |
Subjects
Participants included nine men and eight women; all were
right-handed and ranged in age from 20 to 39 (mean age, 25). Six subjects performed all three main experiments: two odorant tasks and a
sniffing task. The remaining subjects performed one or two of the main
experiments and the relevant control tasks. Each scanning session
lasted ~2 hr. The study was approved by the Stanford University Institutional Review Board, and all subjects signed informed
consent.
Stimuli and stimuli generation
Methods of air dilution olfactometry were modified to
accommodate the MRI environment (for methods in detail, see Sobel et al., 1997b). The system enabled switching from odorant to no odorant conditions in <500 msec. The alternation from odorant to no odorant conditions produced no auditory, visual, tactile, or thermal cues regarding the alteration between conditions. The odorants used were
high (3% v/v in the liquid) and low (0.3% v/v) concentrations of
vanillin (VAN), and high (5% v/v), intermediate (2% v/v), and low
(0.5% v/v) concentrations of propionic acid (PROP), both
diluted in double-distilled deionized water. Whereas VAN is a pure
olfactant (Doty et al., 1978), PROP is an odorant with a strong
trigeminal component (Kendal-Reed et al., 1998).
Task design
Smelling tasks. Alternating half blocks of diluent
with odorant versus diluent only were generated (Fig.
1). Eight such 40 sec half blocks, for a
total duration of 320 sec constituted a single scan. During a scan, a
line of script reading: "Sniff and respond, is there an odor? Press
the right button for yes or the left button for no" was projected to
the subject once every 5 sec. Subjects sniffed and then responded by
using the right index finger only to press one of two buttons. The
number of sniffs and button presses was thus balanced over the odorant
and the no odorant conditions, and constituted a constant baseline. The only difference between the half blocks was in the presence or absence
of the odorant. Sniff duration was held constant by instructing the
subjects to maintain the inhalation of the sniff for the duration of
the projected message that was set to 800 msec. Response accuracy was
recorded on a computer that controlled the olfactometer determining stimulus presence and triggered the scanner, thus maintaining synchronization between the task, stimulus presentation, and data acquisition.
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Figure 1.
Task design of the smelling and sniffing tasks.
Whereas in the smelling tasks sniffs constituted a constant baseline,
and odorant presence alternated with odorant absence, in the sniffing
task periods of sniffing alternated with periods of no sniffing.
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Sniffing task. Alternating half blocks of sniffing versus no
sniffing were generated (Fig. 1). Eight such 40 sec half blocks, for a
total duration of 320 sec constituted a single scan. During a sniffing
half block, a line of script reading: "Sniff" was projected every 5 sec for 40 sec. During a no sniffing half block, a line of script
reading "No sniff" was projected every 5 sec for 40 sec. Sniff
duration was held constant by instructing the subjects to maintain the
inhalation of the sniff for the duration of the projected message that
was set to 800 msec. The air sniffed in these tasks was clean air
passed through active charcoal filters.
Data acquisition
In previous fMRI studies of the primary olfactory cortex, we
used a slice orientation that serendipitously contained the cerebellum in the posterior tail of the acquisition (Sobel et al., 1997b, 1998).
In these studies, in which we consistently noticed odorant-induced activation in the cerebellum, we used anteriorly placed surface coils
for maximizing signal reception from primary olfactory regions. This
led to a significant fMRI signal drop at the posterior end of the image
that contained the cerebellum. We were, therefore, cautious in
interpreting our initial findings of cerebellar activation. Here we use
a slice orientation centered at the cerebellum combined with
coil-placement maximizing cerebellar signal.
Imaging was performed using a 1.5 T whole-body MRI scanner (GE Signa,
Revision 5.6 Echospeed). For functional imaging, a single 5-inch-diameter local receive coil was positioned centered at the inion
under the back of the head. Head movement was minimized using a
custom-built bite bar that was made to the dental impression of each
subject. A T2*-sensitive gradient echo spiral sequence (Glover and Lai,
1998), which is relatively insensitive to cardiac pulsatility motion
artifacts was used with parameters of repetition time (TR) = 540 msec,
echo time (TE) = 40 msec, flip angle = 60°. Spatial resolution
was set by a 153 × 153 voxel matrix covering a 36 × 36 cm
field of view resulting in an in-plane resolution of 2.35 × 2.35 mm. Four interleaves were collected for each frame, with total
acquisition time of 2.16 sec per frame; 153 frames were acquired for a
total scan duration of 330.5 sec.
Six 5-mm-thick slices with a 1.5 mm interslice gap were acquired at an
oblique coronal plane parallel to the brainstem (Fig. 2). The experimental sequence
automatically initiated 10.5 sec after scanning onset, allowing the
first five frames to be discarded from the analysis. This eliminated
transients arising before the achievement of dynamic equilibrium.
T1-weighted flow compensated spin-warp anatomy images (TR = 500 msec, minimum TE) were acquired at the same plane as a substrate on
which to overlay functional data. For each subject, an additional
acquisition of 20 T1-weighted flow-compensated spin-warp anatomy images
was collected in the sagittal plane to later assist in the validation
of localization of cerebellar regions.
Analysis of functional data
Analysis was performed using standard methods (Friston et al.,
1994, 1996; Desmond et al., 1995, 1997). Image reconstruction was
performed off-line on a Sun SparcStation. A gridding algorithm was used
to resample the raw data into a Cartesian matrix before processing with
two-dimensional fast Fourier transform. Motion artifacts
were assessed (Friston et al., 1996) and corrected (Woods et al.,
1992). Once individual images were reconstructed, the time series of
each pixel was correlated with a reference waveform and transformed
into a Z score map, SPM{Z} (Friston et al.,
1994). The waveform was calculated by convolving a square wave
representing the time course of the alternating conditions (odorant/no
odorant or sniffing/no sniffing) with a data-derived estimate of the
hemodynamic response function. The frequency of the square wave in
these experiments was four cycles/320 sec = 0.0125 Hz.
SPM{Z} map averaging and subject-by-subject-based region
of interest (ROI) analysis were then used to analyze patterns of
functional activation across subjects. Averaging was performed by first
creating an outline of each oblique coronal section using a T1-weighted
anatomy image of a representative subject to form a template for that
slice. Then each subject's functional map at each section was
transformed into the region specified by the template, as described by
Desmond et al. (1997), using the following steps: (1) translating,
scaling, and rotating the functional map to match the centroid and
dimensions of the template; (2) defining a matching set of points
around the perimeter of the functional map and that of the template; (3) creating a grid of points from the perimeter points of the functional map and a corresponding grid on the template such that a
one-to-one mapping existed for the grid points in each set; and (4)
mapping the values from the grid points of the functional image to the
grid points of the template. The resulting averaged functional
activation maps were then intensity thresholded at a p < 0.01 level (two-tailed), and each slice was subjected to a cluster
analysis procedure (Xiong et al., 1995) to correct for multiple
statistical comparisons, using a spatial extent threshold that yielded
a p < 0.01 significance level over the entire
composite image. The composite image that is obtained through this
process inherently contains a loss in spatial resolution in comparison to the single subject SPM{Z} and ROI-based analysis.
Thus, to faithfully represent the spatial resolution of the composite, rather than present it overlaid on the template subject or line drawing, the composite is presented overlaid on similarly composited T1
anatomy images of all subjects (Fig.
3).
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Figure 3.
Composite activations overlaid on the composite
anatomy of six subjects who performed all tasks. Left
column is an example of the ROIs drawn for each subject shown
here for the left cerebellar hemisphere, spanning from the anterior
(slice #1) to the posterior (slice
#6) cerebellum. Second column is the
averaged fMRI activation induced by PROP. Third column
is the averaged fMRI activation induced by VAN. Right
column is the averaged fMRI activation induced by sniffing
clean air. Significance of in-phase activation is color coded from
red to yellow, and out-of-phase
activation is coded from dark blue to light
blue. The right side of the image corresponds to
the right side of the brain.
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The ROI-based analysis was accomplished by first manually outlining
ROIs for the entire volume of the acquisition in each subject (Fig. 3).
The outlining was performed in the absence of any functional
activation. Published atlases (Courchesne et al., 1989; Press et al.,
1989; Press and Courchesne, 1992) were referenced to identify on each
slice all relevant fissures that separate the cerebellar lobules.
Lobular regions were then outlined and titled with the abbreviations
used by Press and Courchesne (1992) (Table
1). These abbreviations will be used from
here on in the text. All localizations were cross-validated on the
sagittal acquisition. This was performed using a cross-referencing
program that matched any point on the x, y, and
z coordinates in the coronal acquisition to the identical
point in the sagittal acquisition (Desmond et al., 1995; Desmond and
Lim, 1997). In contrast to the cerebellar lobules that can be
accurately delineated, the exact borders of the cerebellar deep nuclei
are not readily discernible on the MR images. The dentate nucleus (D)
that is partially evident as a difference in signal contrast on the
anatomical image, was outlined separately; the remaining deep nuclei
are embedded within the ROI of the corpus medullare (Cm).
After outlining of the ROIs, activations were quantified using two
methods. The first was computing the mean Z score in the SPM
correlation Z map for that ROI, and the second was computing the percentage fMRI-signal change that occurred in that ROI relative to
baseline. Mean Z was calculated rather than counting the
number of pixels that satisfied the significance criteria used in the composite image, because using a threshold can lead to a loss of
potentially important subthreshold differences in activation. The
values obtained with this method are typically small, because the mean
Z is diluted over the large anatomical region.
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RESULTS |
Main experiments
Subjects responded to the detection command 40 times within a
scan. Detection accuracy was computed by: ([(hits + correct rejections)/40] * 100). Detection accuracy during the scans for PROP
ranged from 84 to 100% (mean 93%) and for VAN ranged from 80 to 95%
(mean 88%). One subject was at 52% accuracy in one scan with VAN.
Because performance in this scan was at chance, it was omitted from
further analysis.
In the smelling tasks, both PROP and VAN induced significant activation
in all subjects (all statistical tests are presented in the figure
captions). Odorant-induced activation occurred primarily in the lateral
hemispheres and was greater in the posterior than anterior cerebellum.
The composite image revealed significant group activations for both
PROP and VAN primarily in the superior portion of the semilunar lobule
(SeS), the posterior portion of the quadrangular lobule (Qup), and the
inferior portion of the semilunar lobule (SeI) (Fig. 3).
By contrast, sniffing induced activation primarily in the anterior
central portion of the cerebellum in all subjects. The composite image
revealed significant group activations for sniffing primarily in the
central lobule (C), the lobules of the anterior vermis (Ave), and the
SeI (Fig. 3). Significant out-of-phase activation occurred in the
posterior cerebellum during the sniffing task (out-of-phase activation
reflects an increase in activation during the baseline condition in
comparison to the experimental condition).
The results of the ROI-based analysis for each region for the six
subjects that participated in all three basic tasks is seen in Figure
4. The mean SPM{Z} scores
and percentage signal change values obtained for each region in all
tasks were significantly correlated (Table 1).
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Figure 4.
Percentage fMRI signal change in all 13 cerebellar
regions in the six subjects who performed all three tasks. Note
doubling of Y scale for Qup, SeI, and SeS from 3 to 6%. Error bars are
SEM. An omnibus within subject repeated-measures ANOVA with factors of
region (13 ROIs), task (Prop., Van., and
Sniff.), and hemisphere (left and
right) revealed a significant effect for region
(F(12) = 2.27; p < 0.02), and a significant interaction for region  task
(F(24) = 3.1; p = 0.0001), reflecting significant differences in regions C
(Sniff. > Van.,
t(5) = 3.27, p = 0.02;
Sniff. > Prop.,
t(5) = 2.17, p = 0.08),
D (Prop. > Sniff.,
t(5) = 2.94, p = 0.03;
Van. > Sniff.,
t(5) = 2.58, p = 0.05),
Qua (Prop. > Sniff.,
t(5) = 4.1, p = 0.009),
Qup (Prop. > Sniff.,
t(5) = 4.7, p = 0.005;
Van. > Sniff.,
t(5) = 2.8, p = 0.04),
and SeS (Prop. > Sniff.,
t(5) = 3.36, p = 0.02;
Van. > Sniff.,
t(5) = 2.73, p = 0.04).
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The magnitude of activation in all regions was rank ordered (Table
2). Rank ordering of the activations was
consistent with the composite image in showing that whereas the
odorants induced activation primarily in Qup, SeI, and SeS, sniffing
induced activation primarily in C, Ave, and SeI.
The SeI was highly activated by both the smelling tasks and the
sniffing task (Table 2). The SeI spans from the anterior to the
posterior cerebellum, and the composite image suggested a dissociation
within SeI, whereby sniffing induced activation primarily in the
anterior portion of the SeI, and odorants induced activation primarily
in the posterior portion of the SeI. To quantify this effect, the SeI
was separated into an anterior portion composed of its representation
in slices 1 and 2, versus a posterior portion composed of its
representation in slices 5 and 6. This separation clearly revealed that
sniffing induced greater activation in the anterior portion of the SeI
and the odorants induced greater activation in the posterior portion of
the SeI (Fig. 5).
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Figure 5.
Activation in the anterior and posterior SeI.
Activation in slices 1 and 2 was combined to form the anterior portion,
and activation in slices 5 and 6 was combined to form the posterior
portion. The odorants induced greater activation in the posterior than
the anterior portions, and sniffing induced greater activation in the
anterior than the posterior portions.
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Whereas SeI was significantly activated during both sniffing and
smelling, two other regions exhibited highly task-dependent activation:
C was activated almost exclusively during sniffing, and SeS was
activated almost exclusively during smelling (Table 2). These two
regions significantly dissociated on these tasks (Fig.
6). This dissociation between activation
induced by sniffing and activation induced by the odorants was evident
in the Fourier transform of the signal-time-series in each subject
(Fig. 7).
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Figure 6.
C and SeS dissociated in activation patterns after
sniffing and smelling (odorant tasks). The two odorants were collapsed
to a single smelling condition. A repeated-measures ANOVA with factors
of region (C and SeS) and task (odorants
and sniffing) revealed a significant effect for task
(F(1) = 9.64; p = 0.03)
and a significant interaction for region * task
(F(1) = 10.84; p = 0.02), reflecting greater activation in the posterior region during
smelling than during sniffing (t(5) = 3.22;
p = 0.02) but greater activation in the anterior
region during sniffing than during smelling
(t(5) = 2.75; p = 0.04).
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Figure 7.
Fourier transform of activity in C and posterior
SeS of the same subject during the same scan. The subject sniffed once
every 5 sec (0.2 Hz), and odorant presence was alternated with odorant
absence every 40 sec throughout the 320 sec scan (0.0125 Hz). Whereas
the primary frequency of activity in C is that of sniffing, the primary
frequency of activity in the posterior SeS is that of odorant presence
(smelling). The out-of-phase activation that is related to sniffing is
also evident in the posterior region, but at a lower amplitude
than smelling. Thus, the cerebellum is viewed here performing two
tasks at two different frequencies, simultaneously.
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Control experiments
To assess the effects of variations in odor content on the
different regions, four subjects were scanned with both high and low
concentrations of PROP, and five subjects were scanned with both high
and low concentrations of VAN. One of the subjects was scanned with
three concentrations of PROP (Fig. 8).
Activation in all regions but the biventer (Bi) showed a trend toward
concentration dependence that was significant in D, Qua, Qup, and SeS
(Fig. 9). Rank ordering of the
concentration dependency of the region showed significant positive
correlation with the rank order of the odor regions but a
nonsignificant negative correlation with the rank order of the sniff
regions (Table 2). This significant difference between the correlations
shows that the regions that were more responsive to odorant presence
were also more responsive to concentration changes. By contrast,
regions that were more responsive to sniffing were less responsive to
odorant concentration changes.
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Figure 8.
SPM{Z}s of anterior and
posterior slices of a single subject during separate scans in which
either odor concentration or sniff rate were varied parametrically.
Activation was both odor concentration- and sniff rate-dependent. A
greater odor concentration dependency is evident in the posterior
versus the anterior slice, and greater sniff rate dependency is evident
in the anterior versus the posterior slice. Note that only in-phase
activation is shown in this figure.
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Figure 9.
Concentration dependence in all 13 regions.
The difference in fMRI response to the high versus the low
concentration of the odorants was significant in regions
D (t(8) = 2.5;
p = 0.04), Qua
(t(8) = 2.7; p = 0.03),
Qup (t(8) = 3.2;
p = 0.01), and SeS
(t(8) = 3.3; p = 0.01).
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To assess the effects of sniff rate on the different regions, a single
subject was scanned while sniffing at different sniff rates within the
sniffing half block. Increasing sniff rate induced an increase in
significant activation primarily in the anterior cerebellum in C and
less in the posterior cerebellum (Fig. 8).
Significant out-of-phase activation occurred in the posterior
cerebellum during the sniffing task, i.e., activation associated with
the specific instruction not to sniff (Fig. 3, slices
5 and 6). This suggests that this
activation may be related to an inhibitory process of suppressing
olfactory input. To address this issue, four subjects were scanned
twice, once in a sniffing task that contained the "no sniff"
instruction and once in an identical sniffing task, but without the
"no sniff" instruction. The only difference between these scans was
that whereas in the first scan not sniffing was achieved by
specifically instructing the subject not to sniff, in the second scan
not sniffing was achieved merely by not instructing to sniff. Sniff
rate and number were identical in these two scans. Deleting the "no
sniff" instruction induced a dramatic decrease in out-of-phase
activation in three of the four subjects that participated in this
control (Fig.
10A).
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Figure 10.
A, SPM{Z}s of
the posterior cerebellum of a single subject during sniffing in a task
balanced with a "no sniff" instruction versus a task sniffing
without a "no sniff" instruction. The "no sniff" instruction
induced a significant increase in out-of-phase activation. This effect
was evident in three of the four subjects tested. Deleting the "no
sniff" instruction induced a mean reduction of 26.4% in out-of-phase
activity in the four subjects. B,
SPM{Z} map of a single subject during passive
stimulation with an odorant. No motor action was performed during this
scan.
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The behavior of sniffing to the instruction "sniff" versus sniffing
to the instruction "sniff and respond, is there an odor?" may not
be the same. Whereas the former is purely a motor function, the latter
is a motor function directed at sensory acquisition. To address any
possible differences in activation related to this difference, four
subjects were scanned twice, once at a regular sniffing task, and once
at a sniffing task in which the instruction "sniff" was replaced
with the instruction "sniff and respond, is there an odor?".
Although there was no odorant generated in these tasks, subjects were
led to believe that an odorant would be generated and were instructed
to try and detect an odor that they would be questioned about after the
scan. No consistent significant difference was seen in the resulting
activation after these two tasks.
Natural olfactory behavior consists of sniffing. To test whether the
odorant-induced activations in this study were dependent on sniffing,
four subjects were scanned during passive exposure to odorants. In
these experiments, subjects lay passively in the dark, did not press
any buttons, and were instructed to breathe in and out only through the
mouth and never through the nose. Two Teflon pipes that were inserted
in the nostrils delivered 40 sec alternating epochs of odorant and no
odorant that were embedded in a constant air stream. Each subject was
scanned three times, once with VAN, once with PROP, and once with an
additional trigeminal odorant; citral. In three of the subjects, all
nine scans revealed significant activations induced by passive
smelling, in the same regions in which active smelling previously
induced activation (Fig. 10B). In the fourth subject,
only two of the scans (PROP and citral) induced in-phase activation,
but VAN induced out-of-phase activation. In sum, 11 of the 12 scans in
which passive smelling was performed induced activation in the same
regions in which active smelling induced activation.
In a final control, a "sham" scan was performed, in which a subject
performed the smelling task, i.e., constantly sniffing and trying to
detect an odorant, but no odorant was generated. This scan was
identical in behavior to the pure sniffing scans, but it was analyzed
at the frequency of previous odor presentations rather than at the
frequency of sniffing. This was done to test for noise at that
frequency (0.0125 Hz). No significant activation was evident in this
scan in any region of the cerebellum (this control was also replicated
by later reanalyzing the sniffing tasks at the 0.0125 Hz
frequency).
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DISCUSSION |
These results demonstrate that the cerebellum is involved in
olfaction in the human. Both the composite SPM{Z} map
and the individual ROI-based analysis were consistent in showing that the posterior lateral cerebellar hemispheres were significantly activated by odorants. This activation was concentration-dependent and
independent of sniffing. Whereas PROP stimulates both the trigeminal
and olfactory nerves (Kendal-Reed et al., 1998), VAN stimulates only
the olfactory nerve (Doty et al., 1978). No significant differences
were observed between the activations induced by the two odorants.
Odorant-induced activation patterns appeared somewhat patchy. It is
tempting to relate this patchiness to the patchy organization of the
granule cell layer and the resulting fractured patterns of activity
that represent the somatotopy of tactile projections to the cerebellum
(Shambes et al., 1978; Bower et al., 1981). It is unclear, however, if
this patchiness could be represented at the spatial resolution of
fMRI.
Whereas odorants induced activation primarily in the posterior lateral
regions, sniffing induced activation primarily in the anterior central
regions. During the sniffing condition, significant out-of-phase
activation was evident in the posterior cerebellum, medially to the
odorant activations. This activation was induced by the instruction not
to sniff. Deleting the "no sniff" instruction dramatically reduced
this activation. The latter leads us to propose that this activation
reflects the active process of inhibiting olfactory exploration. The
activation differences between not sniffing when specifically told not
to, versus not sniffing just because no instruction to do so was
generated, constitute an intriguing example of attentional effects on
cerebellar activation. This effect resembles activity that occurs in
motor association regions after merely anticipating or rehearsing a
movement without actually performing it (Evarts and Tanji, 1974; Tanji
and Evarts, 1976; Roland et al., 1987; Decety, 1996).
Might all the activations in this study be related to inhibiting
olfactory exploration? One could raise the concern that although subjects were instructed to maintain an identical sniff throughout the
odorant and no odorant conditions, they may not have successfully followed this instruction. Thus, a sniff when an odorant was present may have been inhibited in comparison to a sniff without an odorant, because an increase in odorant concentration induces a sniff of lesser
volume (Laing, 1983). Such limiting of a sniff would result in an
increase in activation, as seen in the form of out-of-phase activation
in the sniffing tasks. Thus, we may erroneously attribute activation to
the presence of an odorant when it is actually related to inhibiting
sniffing (because of the presence of that odorant). The latter concern
was largely negated by the passive task: The presence of an odorant
induced activation in the cerebellum in the absence of any motor
function, sniffing included. The activation induced by passive smelling
was less robust than that induced by odorants perceived via a sniff. In
fact, we have found that passive smelling does not induce a consistent
fMRI signal in primary olfactory cortex [the latter, however, may be
related to the possibility of temporal encoding of odor information in
the ventral temporal areas that would not induce increased activation
as assessed with these methods (Sobel et al., 1998)]. That said, the
remote possibility remains that the activation was related to the
intention to inhibit the sniff once an odorant was perceived,
regardless of whether the sniff was ultimately executed or not.
What may be the role of the cerebellum in olfaction? The following is a
working hypothesis: sniff volume is inversely proportional to odor
concentration (Laing, 1983). Maintaining this inverse proportionality
calls for an accurate rapid feedback mechanism that monitors the
sensory input (odor concentration) and modulates the motor output
(sniff volume). Cerebellar maintenance of such feedback mechanisms has
been extensively described for tactile information, as well as other
senses, like the cerebellum receiving sensory information regarding
retinal slip to then effect the vestibulo-ocular reflex to reduce that
slip (Robinson, 1976; Lisberger and Sejnowski, 1992), and like the
cerebellum receiving auditory input that may then effect the pinna,
thus modulating further auditory input (suggested by Bower 1997; see
also Huang et al., 1991; Cicirata et al., 1992; Young et al., 1992).
Here we suggest that the cerebellum is receiving olfactory information
for modulating the sniff, which in turn modulates further olfactory
input. In this capacity, the cerebellum could be subserving maintenance of the Teghtsoonian model of olfactory size constancy (Teghtsoonian et
al., 1978).
By which pathway may the olfactory information reach the cerebellum?
Whereas well described trigeminal projections to the cerebellum (Yatim
et al., 1996) may explain activation induced by PROP, a candidate
pathway for both PROP and VAN is less evident. Olfactory information is
initially projected from the olfactory bulb directly to primary
olfactory cortex (piriform) (Price, 1990). Olfactory projections are
then widely spread within the ventral temporal region and throughout
the brain. Although a well described candidate pathway would be the
hypothalamocerebellar fibers (Haines et al., 1997), a pathway that
traverses primary olfactory cortex is also available. The ventral
tegmental area (VTA) in the rat is strongly interconnected to primary
olfactory cortex (Oades and Halliday, 1987). Using double labeling,
Ikai et al. (1992) first found projections from the VTA of the rat to
the cerebellar cortex and lateral cerebellar nucleus, and later single
neurons in the VTA that project collaterals to both piriform cortex and the cerebellum (Ikai et al., 1994). As these authors note, the dopaminergic axons of VTA neurons project to the pontocerebellum, which
also subserves programming and coordination of voluntary motor
behaviors. This circuit that contains a direct connection between
primary olfactory cortex and the cerebellum is a well suited candidate
to control the sniff-volume odorant-concentration feedback mechanism
that we have proposed. Thus, odor information may be relayed from
primary olfactory cortex to the posterior lateral cerebellum; based on
odor content, cerebellar circuits would then determine optimal sniff
volume for further odorant sampling. Cerebellar efferents would then
modulate sniff parameters.
In what way do our findings relate to the ongoing debate regarding the
role of the cerebellum? The role we have suggested for the cerebellum
in olfaction supports the model proposed by Bower et al. (1981),
suggesting that the cerebellum coordinates acquisition of sensory
information. For tactile information, Bower (1997) proposed that "the
cerebellum is responsible for monitoring incoming sensory data from
these surfaces and adjusting their positions relative to each other and
relative to the object being explored, in real time". Here too, we
suggest that the cerebellum is monitoring incoming data (odorant
concentration) and adjusting the position of the stimulus (odorant air
stream) relative to the sensory surface (olfactory epithelium) by
controlling the motor behavior (sniff), in real time. That said, our
findings may still be incorporated within other models of cerebellar
function noted in the introduction, as here to, there is an element of timing, an element of attentional modulation, and most importantly, an
element of feedback for motor control.
The cerebellar model of Bower et al. (1981) was supported in an fMRI
study in which an increase in dentate activation was seen during a
tactile stimulation task when it included an element of tactile
discrimination (Gao et al., 1996). We, therefore, expected an increase
in dentate activation when sniffing in response to the "sniff and
respond, is there an odor" instruction in comparison to sniffing to
the "sniff" instruction. In the four subjects that participated in
this task, two showed an increase in dentate activation, and two showed
a decrease. Whereas the latter finding does not support the Bower
(1981) model, it may be attributed to that in the context of an
olfaction experiment, subjects may be searching for odorants even in a
scan in which they are instructed just to sniff and informed that no
odorants will be present.
If the cerebellum plays a role in olfactory processing, one would
expect an olfactory deficit in patients with cerebellar lesions. To the
best of our knowledge, in every disease in which there is cerebellar
damage and olfaction has been tested, an olfactory deficit has been
found [e.g., Alzheimer's disease (olfactory deficit [OD]: Moberg et
al., 1987; Doty et al., 1991; cerebellar damage (CD): Joachim et al.,
1989); Parkinson's disease (OD: Doty et al., 1988; CD: Heimburger,
1969), Korsakoff (OD: Jones et al., 1975; CD: Butterworth, 1993; Shear
et al., 1996), schizophrenia (OD: Kopala et al., 1994; CD: Taylor,
1991; Deshmukh et al., 1997), multiple sclerosis (OD: Doty et al.,
1997; CD: Seitelberger, 1973; Davie et al., 1995), and alcoholism (OD:
Ditraglia et al., 1991; CD: Gilman et al., 1990; Shear et al., 1996)].
We do not intend to imply that the cerebellar lesion is primarily
or even largely responsible for the olfactory deficit in these
diseases. Indeed, some of the above diseases include specific
damage to primary olfactory structures outside of the cerebellum. We do
suggest, however, that cerebellar lesions may contribute to
olfactory deficits in these diseases [in keeping with the notion of
the cerebellum as important but not necessary in maintaining various functions (Thach, 1996; Bower, 1997)].
| |
FOOTNOTES |
Received June 16, 1998; revised Aug. 13, 1998; accepted Aug. 19, 1998.
N.S. was supported by an SGF Smith fellowship. E.V.S was supported by
National Institutes of Health Grants AA10723 and AA05965. This work was
made possible by Professor Lubert Stryer whom we thank for his advice
and generosity. We also thank Rehan Khan for his advice (see World Book
of Khans), Anne Sawyer, Jeff Wine, and Elite HaArak.
Correspondence should be addressed to Dr. Noam Sobel, Jordan Hall
Building 420, Stanford University, Stanford, CA 94305.
| |
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Top
Abstract
Introduction
