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1 Joint Graduate Program in Bioengineering, University of California, Berkeley, California 94720 2 Helen Wills Neuroscience Institute, University of California, Berkeley, California 94720 3 Department of Psychology, University of California, Berkeley, California 94720
Submitted 19 March 2003; accepted in final form 7 April 2003
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ABSTRACT |
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INTRODUCTION |
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;
Populin and Yin 1998;
Sun et al. 1987) and their
eyes to accommodate vision (Gardner and
Lisberger 2002; Lisberger et
al. 1987). The primary sensory motor component of olfaction is the
sniff. Similar to the fine control over the ears and eyes, a sniff is
accurately and rapidly modulated in accordance with sensory content. For
example, sniff volume is inversely proportional to the concentration of an
odorant (Laing 1983;
Sobel et al. 2001;
Walker et al. 2001;
Warren et al. 1994). When
smelling a concentrated odorant, mammals take a smaller volume sniff, but when
smelling a diluted odorant, they take a larger volume sniff. This relationship
is sufficiently reliable so as to serve as a nonverbal test of odorant
detection (Frank et al. 2003).
Such sniff control requires a fast feedback loop between the olfactory system,
which assesses odorant content, and the motor system, which produces an
appropriate sniff.
The speed of olfactomotor sniff modulation is limited by two mechanisms:
odorant transduction at the afferent end and neural control and biomechanics
of sniff-generation at the efferent end. When an odorant enters the nares, it
first sorbs into the nasal mucous lining the olfactory epithelium where it
binds to G-protein-coupled receptors that activate a cAMP and/or an IP3
cascade, potentially resulting in an action potential
(Buck 1996;
Firestein 2001;
Reed 1992). The duration of
sorption and the ensuing transduction cascade is estimated at 150 ms
(Duchamp-Viret et al. 2000;
Firestein et al. 1990). At the
efferent end of olfactomotor sniff modulation, inspiratory neurons (primarily
in nucleus ambiguous and solitarius) drive spinal inspiratory motor neurons
that induce a rapid and powerful contraction of the diaphragm, resulting in a
sniff. This mechanism, termed the sniff reflex
(Berger and Mitchell 1976;
Tomori 1965), can be triggered
by manual or electrical stimulation within various portions of the nasal
cavity (Benacka and Tomori
1995; Tomori et al.
1994) and has a latency of 18–40 ms to maximal response
(Nail et al. 1969). More
pertinently, the activity of the bulbar inspiratory neurons leads the ongoing
diaphragm response by as little as 4 ms
(Batsel and Lines 1973), an
adjustment rate made possible by a maintained firing rate near 400 Hz in
bulbar neurons (Batsel and Lines
1973).
By combining these rate-limiting factors, we predicted that a sniff will be
relatively odor-insensitive and uniform for approximately the first 150 ms,
during which odorant sorption and receptor binding occur and will then be
modulated to rapidly readjust sniff airflow rate. The auditory and visual
equivalents of sniff modulation, auditory-induced ear movements and the
vestibuloocular reflex, are accomplished within 25
(Populin and Yin 1998) and 14
ms (Lisberger 1984),
respectively. Considering these examples, we predicted that sniffs may be
modulated to accommodate odorant concentration within 168–179 ms (150 ms
for transduction, 14 to 25 ms for modulation, and 4 ms for airflow
correction). To test this prediction, we measured sniffs in response to
different odorant concentrations.
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METHODS |
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Thirty subjects (16 women) ranging in age from 18 to 36 participated in the main study, and an additional 17 subjects (13 men) ranging in age from 18 to 38 participated in the control study. Exclusion criteria included history of neurological disease, asthma or severe allergies, nasal surgery, or broken nose. All subjects gave informed consent to procedures approved by the University of California Berkeley Committee on Protection of Human Subjects.
Testing room
All testing was performed in a designated room that was completely coated in stainless steel to prevent odor contamination. The room was equipped with high efficiency particulate air (HEPA) and carbon high-rate filtration. During experimentation, subjects were alone in the room, which was monitored via a one-way-mirror window and video monitor in the adjacent control room. An intercom system allowed subjects to speak freely with the researcher if necessary. To prevent unintentional experimenter-generated cues, all instructions (e.g., "sniff now") presented to subjects were displayed on a video monitor and simultaneously generated by a computer-controlled digitized voice. Subjects responded to all questions presented during the experiment (e.g., intensity estimates) by pressing a key on a keyboard.
Olfactometry
The question asked in this study relied on precise delivery of the olfactory stimulus, and precise measurement of nasal airflow. To deliver odorants, we used a computer-controlled air-dilution olfactometer coupled to a high-resolution pneumatotachograph to measure nasal airflow. The salient characteristics of the olfactometer are presented in the following text.
Olfactometer
The olfactometer was based on previously described theoretical designs
(Benignus and Prah 1980;
Kobal 1985;
Prah et al. 1995). All wetted
parts of the olfactometer were made of stainless steel or Teflon. The
olfactometer was driven by custom software written in LabView (National
Instruments, Austin, TX) that controlled odorant identity, odorant
concentration, flowrate, flow temperature, flow humidity, and odorant delivery
timing. All controls were based on proportional-integral-derivative (PID)
feedback loops controlled through one centralized program. Odorant identity
was achieved by flowing a carrier gas, medical-grade breathing air, over
undiluted liquid of the odorant placed in a specially designed stainless steel
canister with 507 mm2 surface area. The carrier gas pulled away the
vapor of the evaporating liquid. Concentration range was accomplished by
mixing clean and odorized air using electronic mass-flow controllers (MFCs,
M100B MKS Instruments, Methuen, MA). The olfactometer was equipped with an
on-board gas-analyzer (photo-ionization method, 8800 PID, Baseline-Mocon,
Lyons, CO) to measure the concentration of odorant in the delivered gas
stream. Temperature was controlled and maintained by four subsystems: an
inline air-heater warmed the air entering the olfactometer, a water heater
warmed the water in the humidifier, a cabinet heater maintained temperature in
the entire olfactometer, and a recirculating heater heated the lines extending
from the olfactometer to the subject's nose. The air and water heaters were
used to control stimulus temperature, and the cabinet and line heaters
primarily served to prevent condensation and heat loss. Humidification was
achieved by sparging air through distilled deionized heated water in a
humidification vessel. Humidity was measured by high-sensitivity hygrometer
(HygroFlex 1, Rotronic Instruments, Huntington, NY) at the final flow point.
Humidity was controlled by a PID feedback loop that adjusted the ratio of dry
air to humidified air in the final airflow. At the olfactometer output, MFCs
controlled a clean-air line, an odorized-air line, and two vacuum lines, all
joining at a "railroad switch" under the subject's nose
(Fig. 1). Switching between
odorant and no-odorant conditions was accomplished by activating a three-way
solenoid that pulled vacuum from only one of the two vacuum lines. This
resulted in removal of either the odorized or the clean air from the railroad
switch, allowing only the other air source to reach the nose. The outcome was
a seamless shift between odorant and no-odorant conditions with no visual,
auditory, tactile, humidity, or thermal cues as to the alteration. The
resultant airflow entered a nasal mask at a point immediately under the
nostrils. The nasal mask was designed to preserve as much of the natural
sniffing element as possible while enabling accurate measurement of sniff
airflow. The mask had an "in" port, a "vac" port, and
a "vent" port. Air, either clean or odorized, continuously flowed
into the mask through the in port and was vacuumed away at the vac port via an
MFC-controlled vacuum line set to the same flowrate as that supplying the in
port. This assured zero net pressure in the mask. A pneumatotachograph
(high-sensitivity flowmeter model No. 4719, Hans Rudolph, Kansas City, MO) was
attached in-line with the vent port where it measured the sniff. The
pneumatotachograph signal was processed with a spirometer (ADInstruments,
Grand Junction, CO), amplified (ADInstruments, PowerLab 4SP), and digitally
recorded at 100 Hz using Chart version 4.1 software (ADInstruments). The
olfactometer software, spirometry software, and experimental design software
were all triggered via one TTL pulse generated by the clock of one computer,
assuring accurate time-locked processing.
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Stimulus stability and repeatability
The success of this study depended on high stability and repeatability of the stimuli both within and between subjects. This was assessed with the olfactometer's on-board gas analyzer which drew a small fraction of the odor line [0.1 l/min (LPM)] and provided a voltage proportional to the concentration. This device can measure concentration differences as low as 10 parts per billion (ppb).
To estimate concentration stability, we set the olfactometer to 5 LPM of carrier gas, or 41.5 parts per million (ppm), and maintained this setting for 1 h (totaling 300 l of carrier gas). As seen in Fig. 2, odorant concentration was highly stable, changing by no more than 4% (SD of 0.38 ppm) over the hour of recording. The largest portion of drift occurred in the initial portion of the recording, and reflected a measurement artifact—the gas analyzer recovering from the initial overshoot of concentration in the sampling port.
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To estimate stimulus repeatability, we set the olfactometer to
automatically rove across a concentration range of 0–50 ppm. A single
experiment lasted 
3 h and was repeated six times over a period of 11
days. As seen in Fig. 3, odor
concentration was highly repeatable across experiments with a mean covariance
of 5%.
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Temporal resolution
In addition to stimulus stability and repeatability, the success of this
study relied on accurate temporal control of the odorant stimulus. To
characterize the temporal dynamics of the olfactometer, we used the principles
of ultraviolet light spectroscopy (S. Briglin and N. Lewis, personal
communication). The olfactometer generated the odorant acetone (99.9+% HPLC
grade; Sigma Aldrich, 27,072-5). Acetone has a strong absorption peak in the
UV wavelengths of the electromagnetic energy spectrum. At the mask, odorant
flow was directed into a quartz chamber with an Hg(Ar) lamp (6035 Spectral
Calibration Lamp, Oriel Instruments, Stratford, CT) on one side and a UV
photodiode detector (model No. UV-50, UDT Sensors, Hawthorne, CA) on the other
(Fig. 4A). The lamp's
253.7 nm Hg peak was isolated with a low-pass filter (Oriel Instruments, 6041
short wave filter) that attenuated the higher, visible frequencies. With the
filter, the lamp's output was largely limited to the 253.7 nm Hg peak. At the
Hg peak, the molar absorptivity is 15,800 for acetone, providing a strong
attenuation of the lamp's radiant energy if acetone is present in the path
between the detector and lamp (the percent of transmitted radiant energy is
equal to 10^[-
* 
* Csolute], where
is the molar absorptivity, is the path length and
Csolute concentration of the solute in the solution). The
photodiode detector was connected to a transimpedence current-to-voltage
preamplifier (AD8015 Wideband/Differential Transimpedance Amplifier, Analog
Devices, Norwood, MA) and then to an instrumentation amplifier and digital
acquisition system (ADInstruments, Powerlab 4sp).
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Temporal resolution was measured by performing 20 consecutive 3-s
alternations between odorant and no-odorant conditions at each of three flow
rates; 5, 7.5, and 10 LPM. The 20 blocks in each series were zero and
first-order corrected to accommodate for decreases in acetone concentration
and shift of photodiode temperature during the experiment. The first three
corrected blocks of the 5 LPM experiment are shown in
Fig. 4B.
Figure 4C is an
enlarged view of the first block. A switching delay was then determined for
each of the 20 blocks based on the time to reach a given percentage of the
average signal during the odorant period. The average signal during the
odorant period can be referenced to the preodor signal and used to calculate
concentration ratios using the Beer-Lambert Law
(Levine 1995). The delays for
50, 75, and 95% C/Cmax are shown in
Fig. 4D. The average
delay represents the time elapsed from activation of the three-way vacuum
solenoid valve until the odorant was present in the mask/quartz chamber at the
specified percentage. The error bars at each point represent the variance in
this time, or in other words, the temporal resolution of the olfactometer. For
example, at 5 LPM, the time to reach 95% C/Cmax
was 84.6 ± 1.8 ms. Thus if we want an odorant to reach the nose at time
x, we should have the olfactometer trigger 84.6 ms earlier, and it is
assured that the odorant will indeed be present at time x ±
1.8 ms. This temporal resolution of >2 ms is more than sufficient
considering that the process of interest is predicted to occur in the
hundreds-of-milliseconds range.
Odorant triggering
In this study, we set out to measure how a sniff is modulated in accordance with an odorant. If, however, the odorant was present before a sniff took place, it could diffuse into the nares and erroneously suggest shorter latency. Similarly, if the odorant arrived only after sniff onset, this could erroneously suggest longer latency. To assure that the odorant was simultaneous with sniff onset, the odorant delivery into the subject's mask was triggered using the subject's real-time respiratory trace. Subjects were trained to only breath in and out of their mouth until an auditory instruction was presented. The instruction was: "at the tone, sniff out and then in." The olfactometer then triggered the odorant by detecting the outward expiration present in the real-time respiratory trace. In other words, when the subject sniffed out, this triggered the odorant, and by the time the subject sniffed in, the odorant was present in the mask (Fig. 5) (also see video at: http://socrates.berkeley.edu/~borp/JohnsonetalLow.mov). The force of the expiratory air is many times the concentration driven diffusion and effectively prevents any odorant molecules from entering the nose before the subject begins inspiring. Based on the results of the UV spectroscopy experiment, an automatic exclusion criteria deleted sniffs where sniff inspiratory onset occurred >100 ms after triggering, thus assuring exclusion of sniffs that started before odorant equilibrium (at 5 LPM, only 1 of 1,000 switching events will take >91.5 ms to reach 95% C/Cmax).
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Odorants
The main odorant studied was propionic acid (99+%, Sigma Aldrich,
24,035-4). This odorant was chosen because it has been commonly used in
experiments measuring odor-dependent sniffing (Kendal-Reed et al.
1998,
2001;
Sobel et al. 2001;
Walker et al. 2001). A
control study was performed with the odorant phenethyl alcohol (PEA) (99%+,
Sigma Aldrich, P1,360-6). We used four concentrations of each odorant that
corresponded to 0% (clean), 10% (low), 50% (medium), and 100% (high) of
full-maximum at 5 LPM over 8 ml of liquid odorant in the specialized stainless
steel canister. Like many analytical devices, the gas analyzer is very good at
reporting relative concentrations (which was the critical value for this
experiment) but not well suited for reporting absolute concentrations (which
would be valuable for comparison to other studies). To estimate the absolute
concentration of the stimuli used, we measured the depletion rate of liquid
odorant as a function of carrier gas flowrate.
Propionic acid was loaded into the olfactometer after measuring the initial
mass with an analytical balance (L-Series, 0.1-mg precision, Acculab,
Bradford, MA). Odorized air at 1 LPM carrier gas flowrate was produced by the
olfactometer for a 20- to 30-min period, after which the remaining propionic
acid mass was measured. The total volume of air was measured by integrating
the flow measurement by the olfactometer. This procedure was repeated at
additional flowrates (2.5, 5, and 10 LPM). The mass-loss was converted to
moles (mass/ molecular weight) and then to molar concentration (moles of odor
vapor per million moles of carrier gas at 1 atm and 37°C). The obtained
values were then used to assess the diluted concentration for the flowrates
used in this experiment. On the basis of these measurements, we estimated the
final sniffed concentrations in the mask to be 9 ppm for the low
concentration, 12 ppm for the medium concentration, and 27 ppm for
the high concentration.
Experimental design
Subjects initially practiced the sniffing procedure ("at the tone
sniff out and then in") using only clean air until they mastered the
technique of triggering the olfactometer with an expiration. For some
subjects, three or four practice sniffs were sufficient, other subjects
practiced for a few minutes. Subjects were naive as to the goals of the
experiment and were misled to think that the experimental goal was to assess
the populational variance in intensity estimates. Subjects were neither aware
of the experimental interest in sniffing nor that their sniff airflow was
being measured. Each experiment consisted of 17 trials: 5 clean air events, 4
low concentration events, 4 medium concentration events, and 4 high
concentration events. These odor events were presented pseudorandomly—
counterbalanced for one-back trial history. The first event (clean) was not
one-back counterbalanced and was excluded from any analysis. After the sniff,
the subject rated the odor intensity of the event on a discrete scale from one
(no odor) to nine (very strong) by entering his/her response on a keyboard.
After the response was keyed, a 35-s inter-trial-interval delay began. During
the delay, a trivia question followed by its answer was presented on the
monitor to maintain the subject's attention. The number of events per
experiment was chosen as a compromise between the increased statistical power
offered by a greater number of events on one side, contrasted by the
habituation inherent to a larger number of olfactory events on the other
(Cain and Johnson 1978).
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RESULTS |
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Perceived intensity
A one-way repeated-measures ANOVA was used to examine the effect of odor concentration on subjects' perceived intensity. The mean responses across subjects are shown in Fig. 6. Perceived intensity closely followed actual concentration of propionic acid [F(3,28) = 170.534, P > 0.0001]. A significant perceptual difference was apparent for each concentration step [mean clean = 1.8 ± 0.2, mean low = 4.0 ± 0.2, t(28) = 13.733, P > 0.0001; mean low = 1.8 ± 0.2, mean medium = 4.9 ± 0.3, t(28) = 4.950, P > 0.0001; mean medium = 4.9 ± 0.3, mean high = 6.3 ± 0.3, t(28) = 6.944, P > 0.0001], suggesting successful creation of the intended perceptual odor space.
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Airflow volumetrics
Sniffs were preprocessed by removing baseline offsets and aligned in time by setting the point where the sniff passed from the expiratory phase to the inspiratory phase as time 0. The first four preprocessed sniffs (clean, low, medium, and high concentrations) of a typical subject are shown in Fig. 5. Sniff-inspired volume, max flowrate, and duration were calculated for all sniffs. Volume was calculated by the trapezoidal Reimann sum method. Both the volume integration and sniff duration ended at the first data point where the sniff returned to zero flow, or 6 s, whichever occurred first. This 6-s window was arbitrarily set as a safety to prevent the software from missing the end of a sniff and combining it with the next sniff. In practice, the longest single sniff measured in this study was 5.1 s, and therefore this safety was never activated. To allow cross-subject comparison, each subject's airflow values were divided by the maximum value within that subject, resulting in normalized values between zero and one.
The relation of sniff volumetrics to odorant concentration was consistent
with previous findings (Laing
1983; Sobel et al.
2001; Walker et al.
2001; Warren et al.
1994). An ANOVA revealed an overall effect for sniff volume
[F(3,28) = 11.205, P > 0.0001;
Fig. 7A], reflecting
greater sniff volume for low versus medium [mean low = 21.7 ± 2.3, mean
medium = 21.0 ± 2.2, t(28) = 2.039, P > 0.0510]
and medium versus high [mean medium = 21.0 ± 2.2, mean high = 19.6
± 2.1, t(28) = 3.537, P > 0.0014]. There was no
difference in volume for clean versus low [mean clean = 22.0 ± 2.3,
mean low = 21.7 ± 2.3, t(28) = 0.475, P > 0.6388].
There was an overall effect for sniff max flowrate [F(3,28) = 7.151,
P > 0.0002; Fig.
7B], reflecting greater max flowrate for low versus high
[mean low = 30.4 ± 3.1, mean high = 27.8 ± 2.9, t(28) =
3.899, P > 0.0005] and medium versus high [mean medium = 29.6
± 3.1, mean high = 27.8 ± 2.9, t(28) = 2.996,
P > 0.0057] but not for low versus medium [mean low = 30.4
± 3.1, mean medium = 29.6 ± 3.1, t(28) = 1.323,
P > 0.1966]. There was an overall effect for sniff duration
[F(3,28) = 2.827, P > 0.0434;
Fig. 7C] that
reflected significant differences between clean and high [mean clean = 2.0
± 0.1, mean high = 1.8 ± 0.1, t(28) = 2.227, P
> 0.0342] but not clean versus low [mean clean = 2.0 ± 0.1, mean low
= 1.9 ± 0.1, t(28) = 1.558, P > 0.1304], low
versus medium [mean low = 1.9 ± 0.1, mean medium = 1.9 ± 0.1,
t(28) = 0.580, P > 0.5669] or medium versus high [mean
medium = 1.9 ± 0.1, mean high = 1.8 ± 0.1, t(28) =
1.158, P > 0.2565]. Figure
7D contains the individual raw sniff volume data
comparison between medium and high concentrations of propionic acid. The panel
shows the consistency of concentration-dependent volumetric effects across
subjects.
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Sniffgram analysis
The volumetric analysis showed that sniffs were concentration dependent. To ask at which point during the sniff had concentration-dependent separation in airflow occurred, we displayed the average normalized sniffgrams of all subjects. As can be seen in Fig. 8, sniffs appeared to be highly uniform and concentration independent for the initial 150 ms after sniff onset but were clearly concentration dependent and separated after 1 s. To examine the early portion of the sniff more closely, we displayed airflow rate and variance during only the first second of the sniff following the high- and low-concentration odorants. As can be seen in Fig. 9A, the initially uniform sniffs began separating in a concentration dependent manner, and this group separation was significant by 160 ± 78 ms following sniff onset, at which point the median separation was 4.1 ± 1.9% in flowrate [t(28) = 2.146, P > 0.041]. Once separated, this difference was maintained throughout the first second of the sniff. The yellow line in Fig. 9A reflects the P value for a point-by-point t-test on airflow rate for the high- and low-concentration sniffs. The continued separation is reflected in the flat significance plot maintained following the 160-ms point. Examining the data in Fig. 9A suggested that the separation obtained at 160 ms was not a fluctuation in the data but rather a point of separation that was maintained from then on. However, to also examine a more conservative criterion, we repeated the test adding Bonferroni correction for multiple comparisons. The corrected test suggested significant separation within 220 ± 80 ms at which point median separation in airflow was 5.6 ± 1.7% [t(28) = 3.204, P > 0.0033].
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Control experiment
Most odorants induce an olfactory percept by activating receptors of
several types. Specifically, odorants are transduced to varying degrees at
both olfactory nerve endings (CN I) and trigeminal nerve endings (CN V), and
an odor percept is the result of interaction between these subsystems.
Propionic acid, chosen for its popularity in the literature, has a significant
trigeminal component (Doty
1995; Doty et al.
1978). Trigeminal processing through CN V may be faster than pure
olfactory processing through CN I (Hummel
and Kobal 1992; Livermore et
al. 1992), yet some studies suggest the opposite, namely that
olfactory CN I processing is faster
(Geisler and Murphy 2000). To
ask whether the trigeminal component was largely responsible for the rapid
sniff modulation seen here, we repeated the study in a control group, using
the nontrigeminal odorant PEA. In view of the results obtained in the main
study, we initiated the control study with a specific prediction of separation
within 220 ± 80 ms (the mean ± SE of the conservative estimate
in the main study). This specific prediction allowed us to test fewer subjects
than in the main study, and apply a one-tailed comparison.
Of the 272 sniffs in the control study, 14 were removed from the analysis, but none of the 17 subjects were excluded. All data reduction was identical to that presented in the preceding text for propionic acid. Although a lower dynamic range was obtained with PEA compared with propionic acid, perceived intensity closely followed actual concentration of PEA [F(3,17) = 24.229, P > 0.0001; Fig. 6]. A significant perceptual difference was apparent for each concentration step [mean clean = 3.2 ± 0.4, mean low = 3.9 ± 0.4, t(16) = 3.616, P > 0.0021; mean low = 3.9 ± 0.4, mean medium = 4.3 ± 0.4, t(16) = 2.315, P > 0.0334; mean medium = 4.3 ± 0.4, mean high = 5.2 ± 0.4, t(16) = 3.965, P > 0.001], suggesting successful creation of the intended perceptual odor space.
To probe the latency of sniff modulation to PEA, sniffgrams were analyzed as in the main experiment. As seen in Fig. 9B, significant separation was obtained within 260 ± 150 ms at which point the median separation was 4.8 ± 2.7% in flowrate [1-tailed t(16) = 1.79, P > 0.047].
To examine a stricter criterion, we repeated the analysis using a two-tailed test, which pointed to significant separation at 280 ± 150 ms at which point the median separation was 5.6 ± 2.6% in flowrate [t(16) = 2.13, P > 0.049]. Using the conservative estimate for propionic acid as a measure of direct comparison between olfactomotor modulation to the two odorants, we observed that at 220 ms, 20 of the 29 (69%) subjects had obtained a concentration-specific flowrate for propionic acid (binomial, P > 0.03), but only 9 of 17 (53%) had obtained such a pattern for PEA (binomial, P = 0.5).
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DISCUSSION |
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;
Sobel et al. 2001;
Walker et al. 2001;
Warren et al. 1994). Here we
probed the time course of this mechanism and found that this concentration
dependence was achieved rapidly through the action of an olfactomotor system.
In this manner, olfaction is not different from other distal senses that are
dependent on the function of a dedicated sensory-motor system. Whereas
sensory-motor integration has been exhaustively studied in vision and
audition, early interest in the olfactomotor system
(Brodal 1947) was rarely
pursued with current methods (Vanderwolf
1992,
2001). Overlooking the
olfactomotor system, however, may skew our view of olfactory coding, a case in
point being intensity coding.
In most studies of mammalian odor-intensity coding, odorants of different
concentrations are artificially delivered in identical quanta to the olfactory
epithelium of an anesthetized animal. Such increases in concentration resulted
in increased spatial extent of activity on the surface of the olfactory bulb,
initially in 2-deoxyglucose studies
(Stewart et al. 1979) and
later with optical imaging (Meister and
Bonhoeffer 2001; Rubin and
Katz 1999; Spors and Grinvald
2002; Uchida et al.
2000). From these studies, one might conclude that increased
concentration was encoded through recruitment of additional glomeruli. In
awake behaving mammals, however, the olfactomotor system would have prevented
continued equal-flow-rate sampling of a high-concentration odorant. In the
awake animal, an odorant would be sampled (sniffed) for a long duration with a
high maximum flowrate when at low concentrations, but for a short duration
with a low maximum flowrate when at high concentrations. Therefore the
increased glomeruli recruitment with increased odor concentration shown in
these imaging studies might have resulted from negation of the olfactomotor
system through anesthesia rather than having represented a realistic mammalian
encoding strategy. Indeed, the few studies that directly recorded neural
activity in the olfactory system of behaving mammals revealed patterns of
activity very different from those in the anesthetized preparation
(Bhalla and Bower 1997;
Schoenbaum and Eichenbaum
1995). Most pertinently, increasing odor concentration did not
necessarily induce higher rates of activity in the olfactory bulb but rather
modulated complex patterns of excitation and suppression in awake behaving
rabbits (Chaput and Lankheet
1987) and temporally shifted the peak of activity to coincide with
an earlier respiratory cycle following odor onset in awake behaving rats
(Chalansonnet and Chaput
1998). Although it is possible the differences between results
from the anesthetized and unanesthetized animals reflected direct effects of
anesthesia on neural activity, we suggest they reflected anesthetic negation
of the olfactomotor system and sniffing. Indeed, when unanesthetized sniffing
rats were studied with 2-deoxy-glucose, for three of five odorants in one
study (Johnson and Leon 2000)
and for nine of nine odorants in a later study
(Johnson et al. 2002),
increasing concentration did not induce different patterns of activity in the
olfactory bulb.
Sniffs not only modulate the odor stimulus by determining its quantity
(Halpern 1983;
Laing 1983;
Le Magnen 1945;
Rehn 1978) and identity
(Sobel et al. 1999) but also
are in themselves a major component of the olfactory percept. In a series of
elegant studies, Teghtsoonian and colleagues (Teghtsoonian and Teghtsoonian
1982,
1984;
Teghtsoonian et al. 1978)
suggested that the information about sniff content is combined with the
information about sniff vigor to produce an invariant precept of odorant
strength. To accurately estimate concentration, the olfactory system must know
exactly what quantity it was that gave rise to a specific level of neural
discharge. An equal duration high-flow-rate sniff of a low-concentration or a
low-flow-rate sniff of a high-concentration may transport a similar quantity
of odorant to the olfactory receptors. Therefore information regarding sniff
vigor and duration is essential to maintain olfactory size constancy. That the
sniff itself is part of the olfactory percept has received extensive
experimental support (Hornung et al.
1997,
2001;
Keyhani et al. 1997;
Laing 1983; Mozell et al.
1984,
1991;
Rehn 1978; Sobel et al.
1999–2001; Tatchell et al.
1985; Teghtsoonian and Teghtsoonian
1982,
1984;
Teghtsoonian et al. 1978;
Tucker 1963; Youngentob et al.
1986,
1987) and is further
reflected in that sniffs directly modulate patterns of neural activity
throughout the olfactory system of animals
(Adrian 1942;
Bhalla and Bower 1997;
Bressler and Freeman 1980;
Domino and Ueki 1960;
Ketchum and Haberly 1991;
Macrides 1975;
Ogawa 1998;
Young and Wilson 1999) and
humans (Hughes et al. 1969;
Sobel et al.
1998a,b,
2000).
A question arises as to which of the nerves that transduce airborne
chemicals was responsible for the olfactomotor modulation seen here. Whereas
high concentrations of propionic acid are transduced at both the olfactory and
trigeminal nerves, PEA is transduced at the olfactory nerve only. It is
therefore tempting to conclude that the 160-ms modulation to propionic acid
was achieved through the trigeminal nerve and the 260-ms modulation to PEA was
achieved through the olfactory nerve. However, the threshold for trigeminal
versus olfactory responses is a topic of some debate
(Cain 1976;
Cometto-Muniz and Cain 1998;
Cometto-Muniz et al. 2002;
Dalton 2001;
Hummel 2000;
Hummel and Livermore 2002),
and it is unclear if the propionic acid concentrations used here were
sufficiently high to activate trigeminal receptors. Furthermore, there are
three additional equally viable explanations as to the difference between the
speed of modulation to propionic acid and PEA besides the CN V versus CN I
transduction explanation.
The first explanation relates to the lower dynamic range of perceived PEA
intensities. High-concentration odors are processed faster than
low-concentration odors (Pause et al.
1997). In our study, the high-concentration PEA was perceived as
similar in intensity to the low-concentration propionic acid
(Fig. 6). Thus the low
perceived intensity of PEA may underlie the slow olfactomotor response to the
odor. This alternative would ideally be addressed using a high-intensity pure
olfactant. Unfortunately, the three pure olfactants identified by Doty
(Doty 1995;
Doty et al. 1978) are
vanillin, decanoic acid, and PEA, none of which are perceived as very intense
even when generated as a saturated vapor.
A second potential explanation for the faster sniff modulation to propionic
acid versus PEA is related to the predicted rate of sorption of these odorants
across the olfactory mucosa. Most of the olfactomotor latency is due to the
afferent rate-limiting factors, namely events leading up to transduction. Of
these events, odorant sorption across the mucosa and receptor binding vary
greatly in duration depending on the odorant's molecular properties,
especially solubility. High aqueous solubility odorants cross the mucosa (and
are transduced) much faster than low solubility odorants
(Mozell and Jagodowicz 1973).
Propionic acid has a very high solubility in water of 370 g/ml, PEA has a much
lower solubility in water of 22 g/ml. Because of the large difference in
solubility, transduction of PEA is expected to be much slower than
transduction of propionic acid, and this difference may underlie the
difference in olfactomotor modulation latency seen here for these two
odorants. This may constitute one additional aspect in which odorant mucosal
sorption rate is a component of the olfactory percept
(Hornung et al. 1975;
Kent and Mozell 1992;
Kent et al. 1996;
Keyhani et al. 1997;
Mozell 1970;
Mozell and Jagodowicz 1973;
Sobel et al. 1999).
The third possible explanation relates to hedonics. Our data suggest odor
intensity modulates olfactomotor function. One might suggest that differences
in hedonic tone also modulate olfactomotor function and that hedonic
differences between PEA (pleasant) and propionic acid (unpleasant) partially
underlie the differences in sniff modulation speed in response to these two
odorants. Such an hedonic effect would necessitate that hedonicity be encoded
at a location afferent to the olfactomotor system with a latency shorter than
160 ms. Whereas odor intensity is encoded at loci early in the olfactory
processing stream (e.g., amygdala), odor hedonics are encoded at loci further
down this stream (e.g., orbitofrontal cortex)
(Anderson et al. 2003). It is
unlikely that this higher processing in orbitofrontal cortex subserves the
nearly reflexive system described here. We cannot rule out, however, that
intensity and hedonics are encoded in parallel in the olfactory system
(Savic et al. 2000), and that
hedonics could influence olfactomotor function.
Considering the above-mentioned potential sources of variance, we conclude that our data are not sufficient to dissociate the 160-ms response from the 260-ms response as reflecting CN I versus CN V contributions to sniff modulation. It is likely the 260-ms modulation time obtained for PEA is mediated by CN I only, and the 160-ms modulation time obtained for propionic acid may reflect transduction by CN I, CN V, or an interaction of the two. Regardless, the 160-ms modulation to propionic acid reflects a rapid olfactomotor response to an odorant. Future studies using CO2, odorants varying in trigeminality, and odorants varying in hedonic tone, will enable quantification of the different factors contributing to differences in sniff modulation timing.
Finally, one may ask which neural structures subserve the olfactomotor
system. We find the current data suggest that the olfactomotor system is
subcortical. This is because the typical latency for olfactory cortical evoked
potentials is between 171 and 400 ms
(Hummel and Kobal 1992;
Livermore et al. 1992;
Murphy et al. 2000),
suggesting the generators of the olfactory cortical evoked response lag behind
the olfactomotor response measured here. Vanderwolf
(Vanderwolf 2001) has
suggested a possible hippocampal circuit involved in olfactomotor function.
Although the current study did not provide specific neurolocalization
information that would enable to test this suggestion, we would like to
conclude here with predicting a cerebellar role in olfactomotor function. The
cerebellum receives visual input to modulate eye movements
(Lisberger and Sejnowski 1992;
Robinson 1976) and receives
auditory input that may then serve to modulate pinna movements
(Bower 1997b)
(Cicirata et al. 1992;
Huang et al. 1991;
Sun et al. 1987;
Young et al. 1992). FMRI data
suggest that the cerebellum also receives olfactory input
(Cerf-Ducastel and Murphy
2001; Qureshy et al.
2000; Savic et al.
2000; Small et al.
1997; Sobel et al.
1998b; Yousem et al.
1997; Zatorre et al.
2000). We suggest the cerebellum uses this information from the
olfactory system to modulate diaphragm movements (a sniff) in the olfactomotor
response. This prediction follows the suggested role of the cerebellum in the
accurately timed (Ivry 2000)
process of modulating motor function to subserve sensory acquisition (Bower
1997a,b).
Considering the direct hippocampal-cerebellar projection
(Green and Morin 1953;
Saintcyr and Woodward
1980a,b),
our cerebellar prediction is not mutually exclusive with Vanderwolf's
suggested hippocampal role in olfactomotorics. That said, there are anatomical
pathways that would enable cerebellar olfactomotor control without a
hippocampal relay. Using double labeling, Ikai et al.
(1992,
1994) have identified single
neurons in the rat ventral tegmental area (VTA) that project collaterals to
both primary olfactory (piriform) cortex and the cerebellum. As Ikai et al.
noted, the dopaminergic axons of VTA neurons project to the pontocerebellum,
which also subserves programming and coordination of voluntary motor
behaviors. The piriform-VTA-pontocerebellum pathway is a direct connection
between primary olfactory cortex and the cerebellum and is well suited to
control the sniff-volume odorant-concentration feedback mechanism described
here.
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DISCLOSURES |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests: B. N. Johnson, 3210 Tolman Hall, MC1650, University of California at Berkeley, Berkeley, CA 94720 (E-mail: bnjohnso{at}socrates.berkeley.edu).
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B. N. Johnson, C. Russell, R. M. Khan, and N. Sobel A Comparison of Methods for Sniff Measurement Concurrent with Olfactory Tasks in Humans Chem Senses, November 1, 2006; 31(9): 795 - 806. [Abstract] [Full Text] [PDF]
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R. A. Frank, R. C. Gesteland, J. Bailie, K. Rybalsky, A. Seiden, and M. F. Dulay Characterization of the sniff magnitude test. Arch Otolaryngol Head Neck Surg, May 1, 2006; 132(5): 532 - 536. [Abstract] [Full Text] [PDF]
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R. S. Vetter, A. E. Sage, K. A. Justus, R. T. Carde, and C. G. Galizia Temporal Integrity of an Airborne Odor Stimulus is Greatly Affected by Physical Aspects of the Odor Delivery System Chem Senses, May 1, 2006; 31(4): 359 - 369. [Abstract] [Full Text] [PDF]
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N. Buonviso, C. Amat, and P. Litaudon Respiratory Modulation of Olfactory Neurons in the Rodent Brain Chem Senses, February 1, 2006; 31(2): 145 - 154. [Abstract] [Full Text] [PDF]
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J. Mainland and N. Sobel The Sniff Is Part of the Olfactory Percept Chem Senses, February 1, 2006; 31(2): 181 - 196. [Abstract] [Full Text] [PDF]
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A. Kepecs, N. Uchida, and Z. F. Mainen The Sniff as a Unit of Olfactory Processing Chem Senses, February 1, 2006; 31(2): 167 - 179. [Abstract] [Full Text] [PDF]
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J. W. Scott Sniffing and Spatiotemporal Coding in Olfaction Chem Senses, February 1, 2006; 31(2): 119 - 130. [Abstract] [Full Text] [PDF]
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H. Spors, M. Wachowiak, L. B. Cohen, and R. W. Friedrich Temporal Dynamics and Latency Patterns of Receptor Neuron Input to the Olfactory Bulb J. Neurosci., January 25, 2006; 26(4): 1247 - 1259. [Abstract] [Full Text] [PDF]
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J. Frasnelli, S. van Ruth, I. Kriukova, and T. Hummel Intranasal Concentrations of Orally Administered Flavors Chem Senses, September 1, 2005; 30(7): 575 - 582. [Abstract] [Full Text] [PDF]
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J. D. Mainland, B. N. Johnson, R. Khan, R. B. Ivry, and N. Sobel Olfactory Impairments in Patients with Unilateral Cerebellar Lesions Are Selective to Inputs from the Contralesional Nostril J. Neurosci., July 6, 2005; 25(27): 6362 - 6371. [Abstract] [Full Text] [PDF]
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M. Bensafi, S. Pouliot, and N. Sobel Odorant-specific Patterns of Sniffing during Imagery Distinguish 'Bad' and 'Good' Olfactory Imagers Chem Senses, July 1, 2005; 30(6): 521 - 529. [Abstract] [Full Text] [PDF]
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ABSTRACT
INTRODUCTION
, propionic acid; 
, phenethyl
alcohol. Although the dynamic range of perceived intensity of PEA was lower
than that of propionic acid, in both odorants perceived intensity was
significantly related to actual odorant concentration.
