Department of Neuroscience, Tufts University School of Medicine, Boston, Massachusetts 02111
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ABSTRACT |
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Dorries, Kathleen M. and
John S. Kauer.
Relationships Between Odor-Elicited Oscillations in the
Salamander Olfactory Epithelium and Olfactory Bulb.
J. Neurophysiol. 83: 754-765, 2000.
Oscillations in
neuronal population activity, or the synchronous neuronal spiking that
underlies them, are thought to play a functional role in sensory
processing in the CNS. In the olfactory system, stimulus-induced
oscillations are observed both in central processing areas and in the
peripheral receptor epithelium. To examine the relationship between
these peripheral and central oscillations, we recorded local field
potentials simultaneously from the olfactory epithelium and olfactory
bulb in tiger salamanders (Ambystoma tigrinum).
Stimulus-induced oscillations recorded at these two sites were matched
in frequency and slowed concurrently over the time course of the
response, suggesting that the oscillations share a common source or are
modulated together. Both the power and duration of oscillations
increased over a range of amyl acetate concentrations from 2.5 × 102 to 1 × 10
1 dilution of saturated
vapor, but peak frequency was not affected. The frequency of the
oscillation did vary with different odorant compounds in both olfactory
epithelium and bulb (OE and OB): amyl acetate, ethyl fenchol and
d-carvone elicited oscillations of significantly
different frequencies, and there was no difference in OE and OB
oscillation frequencies. No change in the power or frequency of OE
oscillations was observed after sectioning the olfactory nerve,
indicating that the OE oscillations have a peripheral source. Finally,
application of 1.0 and 10 µM tetrodotoxin to the epithelium blocked
OE oscillations in a dose-dependent and reversible manner, suggesting
that peripheral olfactory oscillations are related to receptor neuron spiking.
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INTRODUCTION |
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Oscillations in field potential recordings from
neuronal populations are a common feature in sensory systems. Field
potential oscillations generally are thought to reflect synchronous,
rhythmic firing of subsets of neurons within the global population.
Such synchronous spiking activity is believed to play a role in sensory coding: two neurons, firing together, could carry information that may
not be available in the firing patterns of either cell alone. This
phenomenon has been studied in several sensory systems at both the
individual neuron and population levels. In the visual system, where
the occurrence and possible function of synchronous activity has been
studied most thoroughly, field potential oscillations have been
recorded at multiple processing levels including the retina and optic
tract (Doty and Kimura 1963; Neuenschwander and Singer 1996
), the lateral geniculate nucleus of the thalamus
(Ghose and Freeman 1992
; Neuenschwander and
Singer 1996
), primary visual cortex (Gray and Singer
1989
), and higher cortical areas (Eckhorn 1994
;
Engel et al. 1991b
). One function proposed to be
associated with oscillatory activity in visual areas is the phenomenon
of binding of disparate stimulus properties into unitary perceived objects. According to this hypothesis, neurons that are activated by
different characteristics of the same stimulus fire synchronously and
thereby encode a single object, whereas stimuli eliciting nonsynchronous activity are perceived as distinct (Eckhorn
1994
; Engel et al. 1991a
, 1992
; Gray et
al. 1989
; Singer 1993
).
Odorant-elicited oscillatory activity was reported first by Adrian in
the olfactory bulb (OB) of hedgehogs (Adrian 1942). Oscillations since have been reported in the OBs of a wide range of
vertebrate species, including mammals, reptiles, amphibians, and fish,
as well as in olfactory processing areas of invertebrates. Several
hypotheses about the functional significance of oscillations in central
olfactory processing areas have been put forward. Freeman has suggested
that odors may be encoded by the spatial distribution of OB bursting
activity, which varies for each stimulus and which is altered within
the context of olfactory learning (Freeman 1994
). In the
snail, Limax maximus, odorant stimuli alter phase
relations in on-going oscillations in the procerebrum (PC), with
attractive and repulsive odors altering oscillatory activity
differentially (Gelperin 1994
; Gelperin and Tank
1990
; Gervais et al. 1996
). Gervais and Gelperin
and their colleagues conclude that changes in the characteristic PC
oscillations encode the presence and hedonic value of olfactory stimuli
in this animal. On the basis of work in locusts and honey bees,
Stopfer, Laurent, and colleagues argue that olfactory information is
not encoded by the oscillations per se but by whichever neurons
participate in the oscillatory activity at any given moment
(Laurent 1997
; Stopfer et al. 1997
). Using pharmacological treatments, they have provided the first direct
evidence of a role for field potential oscillations, or the underlying
synchronous firing, in sensory coding. Stopfer and his colleagues have
demonstrated that blocking field potential oscillations in bees'
antennal lobes (a structure analogous to the vertebrate OB) disrupts
the bees' ability to discriminate among odorants of similar chemical
structure (Stopfer et al. 1997
). Those results are
particularly important given the paucity of direct evidence for any
coding mechanism in olfaction. Experiments designed to disrupt spatial
components of central olfactory coding mechanisms have shown little
effect on olfactory guided behavior (Hudson and Distel
1987
; Lu and Slotnick 1998
; Slotnick et
al. 1997
).
To understand how neuronal population oscillations and the synchronous
activity underlying them contribute to olfactory coding, it is crucial
to learn which cells fire together and by what mechanisms their firing
becomes synchronized. The predominant view has been that oscillatory
activity is generated within the circuits of the OB in vertebrates
(Adrian 1957; Eeckman and Freeman 1990
; Ketchum and Haberly 1993
; Moulton and Tucker
1964
; Ottoson 1959
) as is the case for
oscillations recorded in the antennal lobe of insects (MacLeod
and Laurent 1996
; Stopfer et al. 1997
;
Wehr and Laurent 1999
). In vertebrates, however,
oscillations also occur in population responses recorded at the
olfactory epithelium (OE) (Adrian 1955
, 1957
;
Ottoson 1956
, 1959
; Takagi and Shibuya 1960a
,b
,
1961
). It is possible that odorant-induced oscillations initiated in peripheral populations generate or influence subsequent activity in central structures. That is, the primary oscillatory trigger may not be in central circuits but in olfactory receptor cells.
A relationship between OE and OB oscillations was considered years ago
(Adrian 1955
; Ottoson 1959
; Takagi
and Shibuya 1960a
), but there have been no formal analyses
carried out to test these ideas. The present set of experiments
characterizes the odor-induced oscillations recorded in the OE of
a major animal model for olfactory research, the tiger salamander
(Ambystoma tigrinum) (see Kauer et al.
1994
and references therein), and examines the
relationship between the peripheral oscillatory activity and
oscillations recorded in the OB.
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METHODS |
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Surgical and recording procedures
All procedures used in these experiments were carried out in
accordance with the Guide for the Care and Use of Laboratory Animals
and in accordance with Tufts University and National Institutes of
Health animal use guidelines. In 28 tiger salamanders, both electroolfactogram (EOG) and OB local field potential (LFP) were recorded simultaneously, and in 8 additional animals, EOG measurements were made alone. Salamanders were anesthetized with ketamine (10 mg/100g body wt ip), and immobilized with tubocurarine (0.7 mg/100g body wt, injected into the dorsal lymph sac). Although all animals in
these experiments did receive general anesthesia, OE oscillations also
have been observed in previous recordings from tiger salamanders that
were either pithed or immobilized using curare and received only local
anesthesia (for example, see Fig. 9C in Kauer and Shepherd 1977) and in epithelia from decapitated frogs (Ottoson
1956
). Therefore oscillations are not a result of the general
anesthesia. To expose the OBs for LFP recordings, the overlying skin,
bone, and meningeal membranes were removed. LFPs were recorded at the mitral cell layer of the OB (as determined by the characteristic response to an electric shock to the olfactory nerve) (Jahr and Nicoll 1981
; Waldow et al. 1981
) using 5-15
M
pulled capillary electrodes. The electrodes were either filled
with 3 M KCl or broken to ~10 µm and filled with amphibian Ringer
solution. Signals were amplified with a Grass AC amplifier with high
cutoff filters set at 3 Hz and 10 kHz. LFP signals were digitized at
1,000 or 2,000 Hz and stored for off-line analysis.
EOG recordings were made either with the epithelium surgically exposed
or from the intact olfactory cavity. In exposed preparations, skin and
cartilage overlying the epithelium were removed, and the olfactory sac
was opened by cutting along the lateral edge and reflecting the dorsal
epithelium toward the midline. Recordings were made using pulled glass
electrodes broken back to 5-15 µm and filled with amphibian Ringer
solution. For recording from the intact epithelium, a 36-gauge
Teflon-coated silver wire was used as an electrode. The Teflon
insulation was removed from the recording end, and the exposed wire was
coated with silver chloride. The electrode tip was placed on the
epithelium by insertion through the external naris. The impedance of
both types of electrode was ~5 M. The EOG signal was amplified
with a DC-coupled Getting microelectrode amplifier. Although the
filters used for EOG and LFP recordings differed, this was not
problematic because we examined signals only in the 10- to 40-Hz range,
and the 3-Hz AC filter setting used for LFP recordings was sufficiently
below that range. Feeding a periodic function through the EOG and LFP
amplifiers verified that neither induced a phase-shift relative to the
other. EOG signals were digitized at 500 or 1,000 Hz and stored for
off-line analysis. Stored signals from both the epithelium and bulb
were later down-sampled to 500 Hz for analysis.
Stimulus delivery
The majority of recordings were made with an intact nasal
cavity. For recording under these conditions, room air was drawn through the nasal cavity at a rate of 25 ml/min. The mouth was sealed
around a small tube using denture adhesive, and one naris was blocked
with petroleum jelly. Vacuum on the tube in the mouth drew a constant
stream of air into the nasal cavity through the open external naris,
across the OE, and out through the internal naris. Stimuli were
delivered as approximately square pulses using an air dilution
olfactometer (Kauer and Shepherd 1977) with the nozzle
placed ~3 mm from the open external naris. When recordings were made
from the surgically exposed OE, the nozzle was placed 3-5 mm from the
epithelial surface, and stimuli were applied directly. Exposed
epithelia were bathed periodically with amphibian Ringer solution to
prevent drying.
Amyl acetate (Fluka) at 1 × 101 dilution
of saturated vapor was used as the stimulus odorant for initial
experiments examining the frequency and time course of oscillations in
the OE and OB. This odorant was chosen because it commonly is used in
olfactory research, it is an effective stimulus (though not the only
effective stimulus) for eliciting oscillatory responses, and it can be
discriminated from air by tiger salamanders in behavioral assays
(Dorries et al. 1997
; Mason et al. 1980
).
Oscillations also were observed at lower stimulus concentrations in
most animals, but all data included in the analyses were taken at the
same concentration. A 1 × 10
1 dilution of
saturated vapor was selected to maximize the number of animals included
in analyses
using the higher concentration increased the percentage of
preparations in which oscillations were observed. Ethyl fenchol
(provided by Givaudan Roure), geraniol (Fluka), and
d-carvone (Fluka), all at 2 × 10
1 dilution of saturated vapor, and butyl and
propyl acetates (Fluka) at 1 × 10
1
dilution of saturated vapor, were used in addition to amyl acetate to
examine the effects of different odorant compounds. To study the
effects of changing concentrations, amyl acetate was presented at
1 × 10
1, 5 × 10
2, and 2.5 × 10
2 dilutions of saturated vapor. A 1-s odorant
pulse was used for all stimulus presentations.
Olfactory nerve section
In tiger salamanders, olfactory receptor neuron (ORN) axons
converge from the entire OE to form a single olfactory nerve, which
passes through the cribriform plate into the OB. The nerve was exposed
within the cranium by gentle lifting with a glass probe and then cut
with surgical scissors as close to the OB as possible. Complete section
was confirmed visually by passing the glass probe under the bulb and up
across the inside of the cribriform plate. For the sham nerve section,
the bulb was lifted with the glass probe, and the scissors were placed
against the cribriform plate without touching the nerve. Approximately
2 min passed between treatment (sham or nerve section) and test.
Testing consisted of two to four trials in which a 1-s puff of amyl
acetate at 1 × 101 dilution of saturated
vapor was applied. All measures were averages of the repeated trials
for each treatment. Six preparations (4 animals: 2 using 1 side, 2 using both sides) were used. In each case, a pretest (no treatment) was
followed by a sham section and then a nerve section. Only OE data were
analyzed in this experiment because the OB received no afferent input
after nerve section.
Toxin application
The intact-epithelium preparation was used for examining the
effect of tetrodotoxin (TTX; Cal Biochem). Five animals were tested
with a Ringer solution control and three concentrations of TTX (0.1, 1.0, and 10 µM) in amphibian Ringer solution in order of increasing
concentration. A sixth animal was tested with Ringer solution and the
two lower concentrations of TTX. A 100-µl drop of TTX in solution or
Ringer solution alone was applied to the open external naris. The
vacuum on the mouth drew the solution across the epithelium and out to
waste. Recordings were made at 10-min intervals until responses
recovered or for 2 h after application of TTX or the Ringer control.
After recovery from each treatment, the next higher concentration was
applied. Amyl acetate at 1 × 10
1 dilution
of saturated vapor was used as the stimulus odorant. Again, only OE
data were analyzed in this experiment because TTX blocked afferent
input to the OB.
Data analysis
Raw data including approximately the first 4 s after
stimulus onset (see traces in Fig. 1A) were transformed for
analysis using a continuous wavelet transform with the Morlet wavelet
function (Torrence and Campo 1998). The wavelet
transform was used because OE and OB oscillations varied continuously
over the course of a response, and the wavelet transform is
particularly appropriate for localizing events in both time and
frequency in time-series data. In addition, window sizes are scaled
appropriately for each frequency component in this analysis, avoiding
the aliasing that can occur in a windowed Fourier transform. The
wavelet transform produces a two-dimensional matrix of power values,
one for each of 13 frequencies at each of the 2,048 peristimulus time
points (see grayscale matrices in Fig. 2).
Measures of peak frequency and the time and power of peak
characterizing the oscillations for further analysis were calculated from the wavelet-transformed data. The first step was to determine which activity was significantly above background levels according to
the procedures described by Torrence and Campo (1998).
Autocorrelations were done on OE traces from each animal, and the mean
lag-1 and lag-2 autocorrelations then were used to generate 50 traces
matching the background noise characteristics of OE recordings. Each
generated trace was wavelet-transformed and power spectra were taken at 100-ms intervals, resulting in a total of 2,000 generated spectra from
the 50 traces. The mean of the 2,000 spectra was taken to give a single
spectrum matching the background characteristics of the OE data. The
entire process was repeated for the OB data so that two background
spectra were generated, one for OE data and one for OB data. Because
noise levels varied in recordings from different animals, the
background OE and OB spectra were scaled to match noise levels for each
animal. After scaling, the spectra were multiplied by the
2 value for
= 0.05 to give a 95%
confidence interval. These 95% confidence interval spectra then were
expanded to make 13 (frequencies) by 2,048 (time points) matrices of
power values. The resulting 95% confidence interval matrices then were
subtracted from the power matrices for OE and OB trials, respectively,
resulting in an adjusted matrix of power values significantly above
background for each trial. Throughout RESULTS,
"significantly above background" refers to activity greater than
the 95% confidence interval.
The greatest power value in the adjusted matrix between 500 and 2,500 ms after stimulus onset was taken as the peak power. The frequency and time at which this peak occurred were recorded. The 500- to 2,500-ms time period was used in all cases to avoid effects of large-amplitude, low-frequency activity at stimulus onset (visible in both the raw data traces in Figs. 1A and 2, and in the raw OB power matrix in Fig. 2B) and edge effects of the transform at the beginning and end of data records. The absolute peak power of both OE and OB oscillations fell well within this time window (see the white box on the OE matrix in Fig. 2A).
Frequencies ranging from 9.8 to 39.2 Hz were included in the determination of the peak power and peak frequency. This range was chosen to include the oscillatory activity of interest and exclude both slower and faster events that were not relevant for the present studies (for example, slow changes at stimulus onset and 60-cycle noise). For many traces, particularly OB recordings, large-amplitude, low frequency activity had components in this range, resulting in peaks occurring at 9.8 Hz (see, for example, the summed spectrum for the OB trace in Fig. 2B). In these cases, local maxima in the 95% confidence interval matrix (that is, peaks in the 10- to 40-Hz range that occurred for shorter time periods during the recordings) were used. To find these local peaks, and also to examine changes in frequency over time, power spectra were generated for individual time points at 100-ms intervals for the 4 s after stimulus onset. For example, Fig. 2B, bottom, shows the spectra for two time points: 1,200 and 1,600 ms after stimulus onset. Although the overall peak in power is the low-frequency activity apparent in the 1,200-ms spectrum, the peak power in the 1,600-ms spectrum is at ~17 Hz. The peak power and frequency were taken from each of those interval spectra, and the local peak with the greatest power in the range of interest was taken as the absolute peak for that trial. For all analyses examining changes in peak frequency over time, data consisted of these 100-ms interval peaks. Whenever multiple trials were available for an experimental condition, mean values from those trials were used. For illustration purposes only, "summed power spectra" were generated for some examples by summing the power spectra for each of the 2,048 time-points. This gave a power spectrum for the entire response period (for example, see the summed spectra in Fig. 2, right).
Data from all experiments were analyzed with general linear models
analyses using SAS statistical software on a mainframe computer. A
multivariate repeated-measures design was used whenever possible, but
when there were empty cells (for example, when oscillations did not
occur at the same time points in all animals), we used a univariate
design and controlled for "animal" in the analysis. SYSTAT
statistical software on a PC was used for t-tests, using the
Bonferroni layering method (Darlington 1990) to correct
for multiple tests. The Mathematica programming environment was used to
generate wavelet transforms, power spectra, and auto- and
cross-correlograms.
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RESULTS |
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Odorant-elicited oscillations can be recorded in both olfactory epithelium and olfactory bulb
Odorant-elicited oscillations were observed in the OE and OB in most, but not all, tiger salamander preparations. Oscillatory OB field potential responses occurred in 22 of 28 animals examined, and oscillations occurred in the OEs from 34 of 36 animals. The epithelia of the two salamanders lacking OE oscillations had the appearance of larval epithelia, indicating that those animals had not completely metamorphosed from the aquatic to the adult terrestrial form. There were no apparent morphological differences between animals that did and did not have OB oscillations. OE and OB field potential oscillations occurred in response to odor stimulation and were generally absent from background activity (Figs. 1, A and B, and 2). Figures 1A and 2 show recordings from two different tiger salamanders in which oscillations can be seen in traces recorded simultaneously from the OE (top) and OB (bottom) for 4 s after odorant onset. Peaks in the summed power spectra for the traces in Fig. 1A reflect the odorant-induced oscillations (Fig. 1B, left, top and bottom) and are absent from summed power spectra for 4 s of data recorded before odorant delivery (Fig. 1B, right, top and bottom). Autocorrelations (for example, Fig. 1C; OE, left; OB, center) confirm the oscillatory nature of the activity. An oscillatory pattern could be elicited in the OB field potential using a train of shocks to the olfactory nerve at an intensity just above the threshold for eliciting a field potential response but not using single shocks. No oscillations were observed in the epithelium in response to single shocks or shock trains to the olfactory nerve (data not shown).
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The time course of oscillations was examined in 14 animals for which peaks significantly above background could be measured at 100-ms intervals in both the OE and OB. The mean time (± SD) at which the power of the EOG oscillations first exceeded background was 821 ± 331 ms after odorant onset. OB field potential oscillations began 1,100 ± 413 ms after odorant onset. The mean duration of oscillations was 1,757 ± 518 ms in the epithelium and 971 ± 448 ms in the bulb.
Oscillation frequencies in the OE and OB are the same, and decrease together over the course of the response
Figure 2, A and B, shows traces recorded simultaneously at the OE and OB, respectively, with the power matrices generated from those data beneath them. The main features of the OE matrix are from the slow negative potential of the EOG (~1 Hz) and the odor-induced oscillations, outlined in white. In the summed power spectrum for the OE trace, to the right of the matrix, the peak at 16.5 Hz from the odor-induced oscillations is well above background activity. By contrast, large-amplitude activity in addition to the 16.5-Hz odor-induced oscillations is apparent in the OB power matrix. Most prominent is the 3- to 10-Hz event that is the initial bulbar response to the stimulus at ~200-500 ms (see the OB trace above the matrix), and the 5- to 10-Hz activity intermittent throughout the 4-s period. Peaks relating to both of these features are apparent in the summed OB power spectrum (Fig. 2B, right). The 5- to 10-Hz activity is not odor-induced; it also is present in background activity (for example, see summed spectrum for OB background activity in Fig. 1B, bottom right).
In Fig. 2, the white contour of the OE odor-induced activity on the OE matrix is superimposed on the OB matrix to demonstrate that the location of the OB oscillations in time and frequency matches that of the OE oscillations. From the negative slope of those outlined areas on the power matrices, it is evident that the frequencies of both OE and OB oscillations change over time. In this example, a peak in OE activity occurs at 16.5 Hz ~1,500 ms after odorant onset, but the oscillation frequency is higher before that peak and lower after it. The frequency of OB oscillations also drops over time: note the interval spectra in Fig. 2B (bottom) for the 1,200- and 1,600-ms time points. The corresponding peak (asterisk) is lower in frequency at 1,600 ms. In an analysis of data from 14 animals for which spectra measured at 100-ms intervals were available, the mean frequencies of OE and OB oscillations decreased in parallel over the course of the response (Fig. 3A). A multivariate repeated measures analysis with recording location as the repeating factor, and time and animal as regressors showed a significant effect of time (F(1,123) = 107.192, P < 0.0001), but no effect of recording location (F(1,123) = 0.107) and no location by time interaction (F(1,123) = 0.731). The oscillation frequencies in the OE and OB did not differ overall and varied together over time (Figs. 2 and 3A). The mean frequency of oscillation was 21.25 ± 5.36 Hz in the OE and 18.67 ± 4.04 Hz in the OB when oscillations first significantly exceeded background. Oscillations slowed to 14.57 ± 3.11 Hz in the OE and 13.85 ± 2.05 Hz in the OB by the end of the response (2,579 and 2,071 ms, respectively). The frequency of oscillation in the two locations did not differ significantly at either the beginning (t(13) = 0.651) or the end of the OB oscillation (t(13) = 1.638).
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Cross-correlograms of OE and OB traces confirmed that OE and OB oscillations are correlated (for example, Fig. 1C, right). Phase relations between the two locations were difficult to interpret, however, because in some preparations relative phase varied considerably from trial to trial under consistent recording and stimulus conditions. Although it is not clear from the present data why this is occurs, further studies would be necessary to investigate phase relations and the associated variability, examining such variables as electrode distances and recording depth.
Both the OE and the OB peak oscillation frequencies were in the range
of ~10 to 25 Hz, similar to the frequency range reported for OB field
potential oscillations in frogs (Delaney and Hall 1996).
Figure 3B shows the distribution of frequencies of OE
oscillations for all 34 individual animals. For 22 of those animals in
which absolute peak frequencies could be measured in both OE and OB, the mean frequency of OE oscillations was 16.14 ± 2.65 Hz, and frequency of OB oscillations was 17.10 ± 3.92 Hz. The range of oscillation frequencies for those animals is shown in Fig.
3C. The OE and OB frequencies were not significantly
different (paired samples t-test,
t(22) = 1.233).
Stimulus concentration does not affect OE or OB oscillation frequency
Oscillatory responses were elicited over a range of odorant
concentrations. OE oscillations were commonly observed at 2.5 × 102 dilution of saturated vapor and
occasionally at lower concentrations. The effects of concentration on
the power, duration, and frequency of oscillations were examined using
data from 12 animals in which oscillations were apparent in the OE for
repeated trials for three concentrations of amyl acetate: 1 × 10
1, 5 × 10
2, and
2.5 × 10
2 dilutions of saturated vapor.
Oscillations increased in power (F(2,11) = 7.22, P = 0.011) with increasing stimulus concentration (Fig.
4A). Mean power at peak
frequency for the lowest concentration differed significantly for the
two higher concentration in paired samples t-tests with
P values corrected for multiple tests (low vs. medium:
t(11) = 3.719, P = 0.003; low vs. high: t(11) = 3.906, P = 0.004). Duration of oscillations also increased
with increasing stimulus concentration
(F(2,8) = 85.464, P < 0.0001; Fig. 4B). Paired samples t-tests
showed that the oscillations were significantly shorter in duration at
the lowest concentration than at either the high
(t(9) = 11.743, P < 0.0001) or medium (t(9) = 5.045, P = 0.0001) concentrations.
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Ten animals had OE peaks with power greater than background at
individual time points for all concentrations and could be used to
assess changes in frequency over time. Figure 4C illustrates that the change in frequency over time of OE oscillations is not affected by odorant concentration
(F(2,88) = 0.070). Corresponding individual time-point data were not available for OB recordings at the
lower concentrations, but repeated measures analyses were carried out
on peak frequency data from six animals. OE and OB oscillation
frequencies were matched and unaffected by concentration (recording
location: F(1,5) = 1.645;
concentration F(1,5) = 1.155; Fig.
4D). Figure 5 shows a set of
traces from one animal including OE and OB responses to a series of
odorant concentrations ranging from 1 × 101 to 1 × 10
2
dilutions of saturated vapor.
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Oscillation is elicited by a variety of odorants
Amyl acetate was used as the stimulus in the above experiments
because it elicits large, easily measured responses over a range of
concentrations. To demonstrate that OE and OB oscillatory responses are
not specific to that compound, recordings were made using five
additional compounds. The amplitude of the slow negative component of
the EOG response was quite small for some of these odorants relative to
responses to amyl acetate. For this reason, higher concentrations were
used for those odorants to elicit a maximum response. OE oscillations
were observed in five or more animals for each of the following
odorants: butyl acetate (1 × 101 dilution
of saturated vapor; n = 9), propyl acetate (1 × 10
1 dilution of saturated vapor;
n = 5), d-carvone (2 × 10
1 dilution of saturated vapor;
n = 7), ethyl fenchol (2 × 10
1 dilution of saturated vapor;
n = 7), and geraniol (2 × 10
1 dilution of saturated vapor;
n = 5). OB oscillations also were observed in response
to all odorants but were only occasionally seen in response to geraniol
(n = 4), which elicited very-small-amplitude OE
responses (both in terms of the power of OE oscillation and the
amplitude of the slow negative component of the EOG recording).
Although a detailed examination of the relationship between odorant
molecule and oscillation frequency is beyond the scope of this paper, a
stimulus-related variation in frequency would speak to the relationship
between oscillations in the OE and OB. If a given treatment alters the
oscillation frequency in the OE and oscillations in the two areas are
related, one would expect that the oscillation frequency in the other
area also would be affected. Eight animals were tested with three
different odorants, amyl acetate (1 × 101
dilution of saturated vapor), d-carvone (2 × 10
1 dilution of saturated vapor), and ethyl
fenchol (2 × 10
1 dilution of saturated
vapor). Table 1 shows the number of
animals with oscillations and the mean (± SD) frequency of OE and OB
oscillation for each odorant. Five animals had OE peaks greater than
background for individual time points and could be used to examine
changing frequency over time. Figure
6A shows mean frequency of OE
oscillation in response to the three odorants over time. In a
repeated-measures analysis using time as a regressor and odorant as the
repeating factor, there were significant effects of odorant
(F(2,70) = 18.97, P < 0.0001) and time (F(1,71) = 273.90, P < 0.0001) with no time by odorant interaction
(F(2,70) = 0.03). Oscillation
frequency decreased throughout the response for all odorants, but the
peak frequency across time points differed significantly for the three odorants. The absolute peak frequencies of oscillation for amyl acetate
and d-carvone were not significantly different
(t(5) = 1.520), but the frequencies
were significantly different after taking into account the change in
frequency over time (F(1,76) = 10.05;
P = 0.0022) with d-carvone eliciting lower
frequency oscillations than amyl acetate. Both the absolute peak
frequency of oscillation in response to ethyl fenchol and peak
frequency over time were significantly lower than those elicited by
both amyl acetate (absolute peak: t(6) = 2.967, P = 0.025; peak over time:
F(1,93) = 60.15; P < 0.0001) and d-carvone (absolute peak: t(5) =
3.825, P = 0.012; peak over time: F(1,71) = 4.85;
P = 0.0309). Although these three stimulus molecules
may differ in intensity as well as quality, the effect of odorant
compound is not likely due to intensity differences because stimulus
concentration does not affect oscillation frequency (see preceding text
and Fig. 4D).
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Both OE and OB oscillations were detected in five animals in response
to amyl acetate and ethyl fenchol (d-carvone was not included in this analysis because only 3 animals showed both OE and OB
oscillations in response to all 3 odorants). In a repeated-measures analysis, there was a significant main effect of odorant
(F(1,4) = 13.129; P = 0.022) but not recording location
(F(1,4) = 0.292) or odorant by
location interaction (F(1,4) = 0.228).
Thus a condition that affects oscillation frequency at the
peripherystimulus molecule
also influences central oscillatory
frequency. Figure 6B shows the mean frequencies of OE and OB
oscillation (± SE) elicited by amyl acetate and ethyl fenchol.
OE oscillations are not eliminated by olfactory nerve section
To determine whether oscillations recorded in the olfactory epithelium have their origins in the olfactory bulb, we examined the effect of olfactory nerve section on the power and frequency of EOG oscillations in six preparations. Four animals were used, and two animals received bilateral lesions. As illustrated by the example in Fig. 7A, OE oscillations remained after nerve section in every case. Repeated-measures multivariate analyses with treatment as the repeating factor showed that nerve section had no effect on frequency of oscillation (F(2,5) = 2.775) or on the power at peak frequency (F(2,5) = 1.457). The frequency and power of oscillations after nerve section did not differ from either the pretest (frequency: t(5) = 0.853; power: t(5) = 0.685) or sham measurements (frequency: t(5) = 1.927 power: t(5) = 0.183).
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Oscillations in the olfactory epithelium are blocked by TTX
To investigate the source of the odorant-induced OE oscillations further, we examined the effect of blocking ORN spiking using the Na+ channel blocker, TTX, in five salamanders. The power at peak frequency was measured before and at 10, 20, and (for higher drug concentrations) 30 min after treatment for three concentrations of TTX in Ringer solution (0.1, 1.0, and 10 µM) and a Ringer solution control. TTX blocked OE oscillations in a concentration-dependent manner and did not affect the overall amplitude of the EOG (Fig. 7, C and D). In a regression analysis using each trial as a case and controlling for animal, there were significant main effects of drug concentration (F(3,52) = 15.51, P < 0.0001) and time after treatment (F(2,52) = 17.89, P < 0.0001), and a significant time by concentration interaction (F(6,52) = 5.85, P = 0.0001). These results indicate that the effect of the drug over time varied significantly with concentration. Power was the same for all treatment conditions before drug application (F(1,16) = 1.04), but effects of drug concentration were significant at all postdrug time points tested (Fig. 7C; 10 min: F(1,16) = 23.93, P = 0.0004; 20 min: F(1,16) = 39.38, P < 0.0001; 30 min: F(1,6) = 12.39, P = 0.0125). There was no change in power after application of the Ringer control (F(2,10) = 0.57) or the lowest concentration of TTX (F(2,10) = 3.35). The drug significantly reduced power at both 1.0 µM (F(2,10) = 7.19, P = 0.0116) and 10 µM (F(2,10) = 23.57, P = 0.0008; all P values corrected for multiple tests).
Responses recovered from 1.0 µM TTX treatments within ~30 min. At 10 µM, TTX almost completely abolished oscillations in most preparations (for example, see Fig. 7B), with the greatest mean reduction in power at 10 min after drug application. Recovery took >60 min (with or without a Ringer wash), and in some preparations was not complete at 120 min. Figure 7C shows the effect of TTX at three concentrations for trials recorded 0, 10, and 30 min after drug delivery and after recovery for the highest concentration. Data for a Ringer solution control are shown for 10 min post-treatment. The decrease in power after TTX treatment was not due to an overall reduction in the amplitude of the EOG: As shown in Fig. 7D, EOG amplitude was not affected by TTX treatment (time: F(4,66) = 2.01; concentration: F(3,66) = 1.50; time by concentration: F(9,66) = 0.86).
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DISCUSSION |
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Oscillations in the population activity of the OE and OB are related
In these experiments, the relationship between odor-induced oscillations in field potential recordings from the OE and the OB in tiger salamanders was examined. Oscillations were observed in both the OE and OB over a range of concentrations and for several different odorants. Odor-elicited OE and OB oscillations were matched in peak frequency, and the oscillation frequencies in the two sites were modulated together. OE and OB peak frequencies changed concurrently over the time course of the response, both slowing significantly (Figs. 2 and 3A). Further, OE and OB oscillations varied together with odorant molecule type. A detailed examination of the relationship between odorant molecule and oscillation frequency is beyond the scope of this paper, but the observation of a stimulus-related change in frequency at both recording sites (Fig. 6B) is of interest. Together with the concurrent slowing over the course of the response, it suggests that the oscillations in the two areas share a common source or are modulated together, such that effects on oscillations at one site also are observed at the other.
Adrian (1955), Ottoson (1959)
, and
Takagi and Shibuya (1960a)
all considered the
possibility of a relationship between central and peripheral
oscillations in their studies of olfactory activity. Ottoson concluded
they were unrelated because they observed the oscillations to be of
different frequencies with the oscillations in the epithelium
"considerably higher" in frequency than the oscillations in the
bulb (Ottoson 1959
). Although this might have been a
species difference, as Ottoson recorded from frogs and Takagi and
Shibuya recorded from toads, it is more likely that they were comparing
the OE oscillations to lower-frequency OB activity that is often
prominent in both stimulated and background traces (see, for example,
the final second of the OB traces in Figs. 1A and
2B and the summed spectrum in Fig. 2B,
right). In some preparations (for example, Fig. 2), the peak
in power at this lower frequency (~5-10 Hz) is larger than the
higher frequency peak that matches the OE oscillations. Although
Adrian, like Ottoson, did no formal analysis of the frequency of
oscillations in either the OE or OB, he did conclude that the
frequencies were the same in the two sites and assumed that the
oscillations were related (Adrian 1955
, 1956
). The
present studies confirm his hypothesis.
Source of oscillations may be synchronous ORN spiking
OE oscillations were elicited, with no change in power or
frequency, after the epithelium was isolated from the bulb by olfactory nerve section. This demonstrates that the peripheral oscillations are
generated within the OE and thus might modulate or drive OB oscillations. The OE oscillations were blocked by TTX, indicating that
the oscillatory response requires sodium channel activity and is
therefore likely due to synchronous spiking of the single neuronal cell
type in the OE, the ORNs. The observed frequencies of oscillation and
the slowing over the time course of the response in fact match the
spiking characteristics of activated individual tiger salamander ORNs
(Baylin 1979; Trotier and MacLeod 1983
). Thus the frequency of oscillation might simply reflect the firing rate
of ORNs. The question, then, is how ORN spiking becomes synchronized.
Synchronous activity theoretically can arise in a number of ways,
involving interactions between elements in a network or endogenously
oscillatory neurons (Dudek et al. 1986; Ritz and Sejnowski 1997
; Singer 1993
). Cortical
oscillations in other sensory systems may be driven by oscillatory
interneurons within the neocortex (Amitai 1994
;
Gray and McCormick 1996
) or arise from interactions between cortical neurons (Engel et al. 1992
;
Plenz and Kitai 1996
; Silva et al. 1991
;
Sukov and Barth 1998
). In insect olfactory systems,
GABAergic inhibitory interactions appear to play a critical role in
generating oscillatory activity: oscillations in the antennal lobe of
locusts (MacLeod and Laurent 1996
) and honey bees
(Stopfer et al. 1997
) can be abolished by blocking
inhibition with the GABA receptor antagonist, picrotoxin. Similar
interactions within OB are thought to be the source of central
olfactory oscillations (Eeckman and Freeman 1990
;
Ketchum and Haberly 1993
; Scott and Aaron
1977
). Synaptic interactions likely give rise to the
oscillatory activity recorded in another sensory end organ, the retina
(Neuenschwander and Singer 1996
). Unlike the retina,
however, the OE contains no known explicitly inhibitory or excitatory interconnections.
Although there are no known chemical synapses between ORNs, there are
other potential means of communication between the cells, including
gaseous messengers, gap junctions, ephaptic interactions, and
electrical field effects. Numerous reports have indicated that the
gaseous messengers, carbon monoxide and nitric oxide, might function as
second messengers in ORNs (Breer and Shepherd 1993;
Breer et al. 1992
; Broillet and Firestein
1996
; Ingi and Ronnett 1995
;
Leinder-Zufall et al. 1995
). Nitric oxide also plays a
role in modulating oscillation frequency in the procerebral lobe of an
invertebrate, Limax maximus (Gelperin 1994
).
It has been suggested that gaseous second messengers might diffuse
through cell membranes and affect neighboring ORNs in the vertebrate OE (Breer and Shepherd 1993
; Shepherd 1994
),
but at present there is no evidence for such an extracellular effect.
ORNs also might interact directly, via gap junctions. In tiger
salamanders, Lucifer yellow injections have revealed that some cells in
the OE are dye-coupled and thus may contain gap junctions
(Schwartz Levey et al. 1992
). Dye coupling occurs to
some degree between all cell types in the epithelium, including ORN
pairs (Schwartz Levey et al. 1992
). It is also possible
that gated gap junctions might exist between ORNs. If this was the
case, connections could form, for example, between depolarized cells,
linking only ORNs that respond to the same odorant. It also might
account for the latency of the oscillation: more connections would form
over time as an increasing number of ORNs became depolarized.
Alternatively, odorant-activated ORNs might become synchronized as a
result of ephaptic interactions or electrical field effects. The
nonmyelinated ORN axons run to the bulb in tightly packed fascicles
(Daston et al. 1990; Gasser 1956
;
Rafols and Getchell 1983
). These are conditions that
permit ephaptic interactions (direct transmission of electrical
signals) (Daston et al. 1990
; Jefferys
1995
) or large extracellular electrical fields, either of which
could influence the membrane potential of cells within the fascicle
(Jefferys 1995
). This was one of the mechanisms for generating OE oscillations initially suggested by Adrian and later by
other investigators (Adrian 1956
; Getchell
1986
). Modeling studies have shown that field effects in an
axon bundle could synchronize spiking (Eilbeck et al.
1981
).
OE and OB might constitute two linked oscillators
The match in oscillation frequency between OE and OB populations
does not necessarily indicate that one drives the other. It may be that
both the epithelium and the bulb are distinct, but linked, oscillators.
Oscillations might arise independently in either or both populations
and activity in one, most likely the OE, could modulate the frequency
of the other. The present data show that the OE can generate
oscillations independently. They do not, however, address the question
of whether OB oscillations are driven by those in the OE or arise
independently but are modulated by them. There are several observations
that support the latter view. First, Freeman (1972)
demonstrated that ~100-Hz oscillations can be elicited in rabbit OBs
using single electric shocks to the olfactory nerve or olfactory tract
under precise stimulus conditions. Failure to generate such responses
in the present study may have been due to using too high a stimulus
intensity, as Freeman found that using a shock at field potential
threshold was critical in his experiments (Freeman
1972
).
Second, Scott and Aaron (1977) found that although
shocks to the olfactory tract did not elicit oscillations on their own, they could alter the phase of odor-induced 50- to 60-Hz oscillations in
rat OBs. Scott and Aaron found no consistent phase relations among
odor-induced oscillations elicited in independent trials, such that
little oscillatory activity was seen in averaged responses. When a
shock was applied to the olfactory tract during odorant stimulation,
however, the waveforms generated over many trials fell in phase, locked
to the shock. Their results indicated that shocks can reset on-going OB
oscillations and thus the phase of the oscillation may be independent
of the afferent input. Finally, 5- to 10-Hz oscillations are commonly
observed in background recordings in salamander OBs (see the final
1,000 ms of OB traces in Fig. 1A and 2B) but not
in OE recordings. Thus it appears that oscillations at various
frequencies can be generated by OB circuitry itself, and OE
oscillations may modulate that ongoing process.
Are OE oscillations functionally significant?
It has been suggested that oscillations in the OE may occur only
at very high odorant concentrations and perhaps only when the
epithelium is damaged (Ottoson 1956, 1959
). The data
reported here show that the oscillations are present at moderate
concentrations commonly used in studies of single cell function
(Hamilton and Kauer 1989
; Kauer 1974
) and
to which salamanders can be conditioned to respond differentially
(Dorries et al. 1997
; Mason et al. 1980
). The progressive decline in power of the oscillatory activity with decreasing concentration (Figs. 4B and 5) suggests that at
lower concentrations, smaller populations of neurons may be
participating in the synchronous activity that underlies the
oscillatory response. Although it might be that oscillations are not
observed at very low odorant concentrations because weak stimuli elicit
no synchronous activity, it is also possible that synchronous activity
is present but the strength of the active population at low
concentrations is too small to generate detectable signals. In either
case, the oscillatory activity or the underlying synchronized spiking
may be more functionally significant at higher concentrations when a
large percentage of the ORN population is active. Increased stimulus
concentrations activate a broader range of ORNs (Sato et al.
1994
). It may be that synchronous firing is a mechanism that
facilitates fine discrimination among similar signals under these
conditions, a role suggested by Stopfer and his colleagues in
invertebrate olfactory systems (Stopfer et al. 1998
).
Determining whether OE oscillation has a role in encoding odor
information will require studies like theirs that measure animals'
ability to discriminate odorant stimuli after OE spiking is
desynchronized. Although we have tested a number of possibilities,
including low external calcium and octanol to block gap junctions and
zinc deuteroporphyrin to block possible effects of gaseous oxides, we
have not yet found any treatment that will abolish OE oscillations
without eliminating spiking.
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ACKNOWLEDGMENTS |
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We thank T. Alkasab for both suggesting and implementing the wavelet transform analyses and for help in writing additional Mathematica routines. We gratefully acknowledge the participation of D. Jay in pilot studies on the TTX experiment and J. White, H. Eisthen, and two anonymous reviewers for comments on the manuscript.
This work was supported by National Institute on Deafness and Other Communication Disorders Grants 1 F32 DC-00198-01 and 2 R01-DC-00228 and by grants from the Office of Naval Research.
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FOOTNOTES |
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Address for reprint requests: K. M. Dorries, Dept. of Neuroscience, Tufts University School of Medicine, 136 Harrison Ave., Boston, MA 02111.
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.
Received 22 February 1999; accepted in final form 5 October 1999.
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REFERENCES |
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