The Journal of Neuroscience, September 3, 2003, 23(22):7993-8001
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Ketamine-Xylazine-Induced Slow (< 1.5 Hz) Oscillations in the Rat Piriform (Olfactory) Cortex Are Functionally Correlated with Respiration
Alfredo Fontanini,1,2
PierFranco Spano,2 and
James M. Bower3
1Division of Biology, California Institute of
Technology, Pasadena, California 91125, 2Division of
Pharmacology, Department of Biomedical Sciences and Biotechnology, Brescia
University Medical School, 25123 Brescia, Italy, and
3Research Imaging Center, University of Texas Health
Science Center at San Antonio, and Cajal Neuroscience Center, University of
Texas San Antonio, San Antonio, Texas 78284-6240
 |
Abstract
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The occurrence of low frequency (<1.5 Hz) cerebral cortical oscillations
during slow-wave sleep has recently lead to the suggestion that this pattern
of activity is specifically associated with conditions in which the brain is
mostly closed to external inputs and running on its own. In the current
experiments, we used a combination of in vivo intracellular and
extracellular field potential recordings obtained under conditions of
ketamine-xylazine anesthesia to examine slow-wave behavior in the olfactory
system. We demonstrate the occurrence of low-frequency oscillations in field
potentials of both the olfactory bulb and cortex and in the membrane
potentials of cortical pyramidal cells. By monitoring ongoing breathing, we
also show that these oscillations are all correlated with the natural
breathing cycle. Using a tracheotomized preparation, we demonstrate that slow
oscillatory patterns could occasionally be produced even when air is no longer
entering the nose, supporting the view that the olfactory system has an
intrinsic propensity to oscillate. However, in the case of tracheotomized
rats, the amplitude and regularity of the oscillations as well as their
patterns of correlation are disrupted. All temporal relationships were
restored when air was pulsed into the nostrils. We conclude that, in the
olfactory system of freely breathing rats, there is a strong relationship
between the occurrence and timing of slow oscillations and the ongoing
periodic sensory input resulting from respiration. This coupling between
olfactory cortex slow oscillations and respiration may result from the
interaction between respiratory-related rhythmic input and the tendency for
olfactory structures to oscillate intrinsically. We believe this finding has
important functional as well as evolutionary implications.
Key words: piriform cortex; olfactory cortex; olfactory bulb; slow oscillations; respiration; ketamine; rat
 |
Introduction
|
|---|
Although it has been known for many years that the nervous system generates
oscillatory behavior in a wide range of frequencies
(Adrian, 1942
;
Bremer, 1958
;
Freeman, 1960
), the functional
significance of this dynamical behavior has recently become a growing focus
for many physiologists (Wehr and Laurent,
1996
; Buzsaki,
1998
; Engel et al.,
2001
), modelers, and theorists
(Hopfield, 1995
;
Traub et al., 1999
;
Freeman, 2000
;
Hasselmo et al., 2000
;
Destexhe and Sejnowski, 2001
).
Central in many interpretations of the functional significance of cerebral
cortical oscillatory behavior is the question of the origins of this behavior
and, in particular, its relationship to ongoing afferent input
(Eckhorn et al., 1988
;
Gray et al., 1989
).
In this study, we analyzed the effects of afferent input on oscillations in
the olfactory system occurring at frequencies lower than 1.5 Hz. These
low-frequency oscillations have been recorded in rats under conditions of
ketamine-xylazine anesthesia, comparable with those used by Steriade and
colleagues to study slow oscillations in neocortex (Steriade et al.,
1993a
,b
).
On the basis of similarities between the neocortical oscillations and those
seen during slow-wave sleep (Steriade et
al., 2001
), it has been proposed that these slow oscillations
reflect a behavioral condition in which the brain is mostly closed to the
external environment and running on its own (Timofeev et al., 1996a;
Steriade, 2000
;
Destexhe and Sejnowski, 2001
).
This assertion is consistent with electrophysiological results demonstrating
slow-wave oscillations in deafferented neocortical slices
(Sanchez-Vives and McCormick,
2000
) and slabs (Timofeev et
al., 2000
).
Using combined simultaneous in vivo intracellular and
extracellular recording techniques, we demonstrate the presence of
ketamine-xylazine-induced slow oscillations in local field potentials in the
olfactory bulb (OB) and piriform cortex (PC) as well as in pyramidal cell
membrane potentials in the piriform cortex. Furthermore, we show that these
oscillations are correlated with the natural breathing cycle of the rat and
therefore appear to be directly related to ongoing periodic patterns of
afferent input linked to respiration. Supporting this interpretation, we
demonstrate that both the amplitude and regularity of these oscillations are
reduced in tracheotomized preparations when air is no longer entering the
nose. The temporal relationship between extracellular and intracellular
recordings also changes under these conditions. Pulsing air into the nostrils
not only restores the oscillations and the temporal relationships but also
directly entrains their frequency. On the basis of this data, we conclude
that, in freely breathing rats, there is a strong relationship between slow
oscillations in the olfactory bulb and cortex and the ongoing periodic sensory
input resulting from respiration, almost certainly interacting with an
intrinsic tendency for olfactory structures to oscillate
(Bower, 1995
). The conclusion
that respiration is reflected in the temporal behavior of the olfactory system
is consistent with previous studies on the piriform cortex
(Wilson, 1998
) and olfactory
bulb of rats (Macrides and Chorover,
1972
; Chaput et al.,
1992
; Sobel and Tank,
1993
) and with recent imaging results in humans
(Sobel et al., 1998
). This
work was first presented in abstract form
(Fontanini et al., 2001
).
 |
Materials and Methods
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Animal surgery. All animal procedures were approved in advance by
the Animal Use Committee of the California Institute of Technology. Adult
Sprague Dawley rats (250-300 gm) were anesthetized with ketamine-xylazine (100
mg/kg, 5 mg/kg, i.p.) and mounted on a stereotaxic frame (Kopf Instruments,
Tujunga, CA). Heart rate and body temperature were monitored throughout the
experiment, and body temperature was maintained constant (36 ± 1°C)
using a custom designed biofeedback system. The general level of anesthesia
was maintained so that hindlimb pinching produced no reflex movement. When
necessary, an additional dose (30% of initial dosage) of ketamine-xylazine was
injected intraperitoneally. Xylocaine was applied topically at the edge of all
incisions and at pressure points to minimize pain. After exposure of the
skull, burr holes were drilled in its dorsal part above the olfactory bulb,
lateral olfactory tract, and anterior piriform cortex, and the dura mater was
carefully removed and the brain was covered with mineral oil to prevent
drying. The cisterna magna was widely incised, and the cerebrospinal fluid was
drained to minimize brain pulsation. In 13 rats, tracheotomy was performed,
and a small tubing was inserted in the nostril ipsilateral to the recording
site. In these experiments, puffs of clean filtered air were injected into the
right nostril using a picospritzer. The duration of the pulse was 100 msec,
and the pressure varied between 45 and 55 psi. This stimulus was strong enough
to be detected on the finger of the experimenter and capable of moving the
rats' whiskers at a distance of 4-5 mm. In preliminary experiments, air puffs
at 20 psi were shown to have no influence on neuronal activity. Respiration
was monitored by recording the chest wall movements using a piezoelectric
device.
Extracellular field potential recordings and electrical
stimulation. Extracellular field potential recordings and electrical
stimulation were both accomplished using unipolar tungsten electrodes
(MicroProbe, Potomac, MD) with a resistance of 1 M
. Stimulating and
extracellular recording electrodes were placed in the olfactory bulb, lateral
olfactory tract, and piriform cortex by relying on stereotaxic coordinates
relative to bregma (olfactory bulb: 7-8 mm anterior (AP), 1-2 mm lateral (ML),
1-2 mm ventral (DV); piriform cortex: 0.5-1.5 mm AP, 4-5 mm ML, 6-7 mm DV;
lateral olfactory tract: 3 mm AP, 3.5 mm ML, 4.5-5 mm DV)
(Paxinos and Watson, 1997
).
Recording electrodes were positioned in the granule cell layer of the
olfactory bulb and in layer I of the piriform cortex. Positioning accuracy for
stimulation and recording was determined by testing to assure that stimulating
electrodes produced the characteristic biphasic electrophysiological response
to strong lateral olfactory tract stimulation (see
Fig. 1 A, B)
(Haberly, 1973
;
Ketchum and Haberly, 1993
;
Stripling and Patneau, 1999
).
Extracellular signals were filtered (0.1-5 KHz) and amplified with an
extracellular amplifier (A-M Systems, Carlsborg, WA).

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Figure 1. Positioning of electrodes: characteristic response to LOT strong electrical
shock. A, Extracellular recording from the granule cell layer of the
olfactory bulb. B, Extracellular recording from layer I of the
piriform cortex showing the monosynaptic and disynaptic (associative)
components characteristic of that layer. C, Characteristic
intracellular response of a layer II/III pyramidal neuron to LOT stimulation
with an EPSP or spike followed by a prolonged hyperpolarization. Calibration:
1 and 0.5 mV, 20 msec (from olfactory bulb and piriform cortex, respectively);
20 mV, 50 msec for intracellular recordings. Left, Histological assessment of
extracellular electrode positioning. Note that lesions in the granule cell
layer of the olfactory bulb (top) and in layer I of the piriform cortex
(bottom) are shown. Arrows connect areas in which recordings were performed to
their characteristic response.
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Intracellular recordings. Intracellular recordings in piriform
cortex were obtained using sharp electrodes pulled with a horizontal puller
(P87; Sutter Instruments, Novato, CA) from borosilicate glass (1 mm o.d., 0.58
mm i.d.) (A-M Systems). Recording electrodes with impedance ranging between 40
and 70 M
were filled with 3 M potassium acetate. Electrodes
were slowly (
100 µm/min) lowered dorsally with a hydraulic
micropositioner (Kopf Instruments) using field potential responses to lateral
olfactory tract stimulation to determine when the electrode tip reached layers
II/III of the piriform cortex (usually
6 mm ventral from the brain
surface). Recordings were performed in bridge-balance mode using an Axoclamp
2-A intracellular amplifier (Axon Instruments, Union City, CA). After
impalement, a hyperpolarizing bias current (0.5-2 nA) was injected to
stabilize the membrane potential of the cell. Once the cell activity reached a
stable state, the current was discontinued. Neurons included in this study
were required to maintain spontaneous membrane potentials more negative than
-60 mV with regenerative action potentials with an amplitude that exceeded 50
mV. In addition, all recorded neurons responded to stimulation of the lateral
olfactory tract with the biphasic response (see
Fig. 1C)
characteristic of cells identified as pyramidal type with intracellular
labeling techniques, as reported previously
(Haberly and Bower, 1984
).
Respiratory activity and intracellular and extracellular data were
simultaneously acquired at 20 kHz with a Digidata 1200 board (Axon
Instruments) connected to a personal computer running Clampex 8 acquisition
software (Axon Instruments).
Data analysis. Fifteen to sixty second long traces were used for
analysis. To allow a faster processing of data, the sampling rate was reduced
off-line from 20 to 2 kHz using the decimation algorithm implemented in
Clampfit 8 (Axon Instruments). This procedure consisted of copying to the
output data record the first point of every n points (where
n is the reduction factor; in our case, 10) for each signal. To be
sure that signals were not filtered in the frequency domain, we compared a
fast Fourier transform (FFT) performed on the data before and after
decimation; the result showed no distortion at low frequencies. Also, a
comparison of the traces before and after decimation was performed to test for
no distortion in the time domain.
Histograms of membrane potentials. Membrane potential histograms
were constructed using 30 sec data traces binned at 2 mV. The experimental
histogram was then fitted with a Lavenberg-Marquard algorithm using a sum of
two Gaussians as follows:
where b1 and b2 represent the mean of the two Gaussians.
Spectral analysis. Power spectral density was estimated using
Welch's averaged periodogram method. Traces were divided into
15 sec
windows with a 50% overlap and analyzed with a 32768 points FFT. These
parameters allowed us to achieve a resolution of 0.06 Hz, which was critical
for investigating, in the different signals, the coincidence of the peak at
low frequencies.
Cross-covariance analysis. The correlation between the membrane
potential of the piriform cortex pyramidal cell and local field potentials in
either the layer I of the piriform cortex or the granular layer of the
olfactory bulb was obtained by computing the cross-covariance
(cross-correlation normalized by the mean) between 15 and 30 sec recordings of
intracellular neuronal membrane potentials and local extracellular field
potentials. Positive or negative peaks of the cross-covariance were computed
within 0.5 and -0.5 sec lags. The correlation between the membrane potential
and respiratory activity was also investigated by estimating the respiratory
wave-triggered average. In brief, a breathing cycle (from the beginning of one
inspiration to the beginning of the next) was divided into eight bins, and the
average membrane potential was computed within each bin. We repeated this
operation for every breathing cycle in a
30 sec recording, and the
average membrane potential for each of the eight bins was then averaged across
all of the respiratory cycles. Data analysis was performed using Matlab
(Mathworks, Natick, MA).
Histology. After termination of the experiment, an electrolytic
lesion (100 µA; 5-10 sec) was made to verify the proper positioning of all
recording and stimulation electrodes (see
Fig. 1). The rat was then
deeply anesthetized (Nembutal, 1 ml, i.p.) and transcardiacally perfused with
saline solution followed by 3% paraformaldeyde. The brain was removed, stored
in 3% paraformaldeyde for at least 2 d, and sliced with a vibratome
(thickness, 200 µm). Lesions were revealed with cresyl violet staining
using standard procedures.
 |
Results
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Recordings
We report here the results of a total of 40 individually recorded neurons
obtained in 34 rats. These neurons were judged most likely to be pyramidal
cells because of the fact that recordings were obtained at a depth in which
lateral olfactory tract (LOT) stimulation induced both extracellular field
potential responses typical of layer II/III and intracellular responses
typical of pyramidal cells (Fig.
1C). All intracellular recordings were accompanied by
extracellular field potential recordings obtained from the olfactory bulb and
cortex.
Periodic variations in membrane potential
Figure 2A shows the
pattern of membrane potential behavior characteristic of all neurons
intracellularly recorded in freely breathing rats under the ketamine-xylazine
anesthesia used in these experiments. As shown, membrane potentials exhibited
large 0.7-1.5 Hz periodic fluctuations that seldom resulted in action
potential generation. Taken as a whole, the average membrane potential for the
recorded neurons was -81.85 ± 5.72 mV (n = 20); however, as
shown in the histogram in Figure
2B, the periodic variations in membrane potential result
in a bimodal distribution of instantaneous membrane voltage. When this bimodal
distribution is fitted by a sum of two Gaussians, the mean value of the
membrane potential during the "up state" is -76.08 ± 5.28
mV (n = 16), whereas the mean value is -89.54 ± 6.1 mV
(n = 16) for the "down state."

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Figure 2. Characteristic ongoing membrane potential fluctuations in layer II/III
pyramidal cells. A, Membrane potential recording from a
representative neuron; the spiky events occurring in the down states are PSP
spontaneously generated. B, Bimodal distribution of the histogram of
membrane potential in a slowly oscillating cell: fitting with a sum of two
Gaussians (continuous line). C, An example of less frequently seen
behavior in which ongoing slow-wave oscillations were occasionally interrupted
by periods of sustained membrane depolarization and accompanying action
potential generation.
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The mean width of these slow periodicities is 13.45 ± 5.04 mV
(n = 16), and the power of the peak at the power spectral density is
270.66 ± 213.45 mV2/Hz (n = 18). As shown in
Figure 2C,
occasionally in some cells (n = 5), this ongoing periodic pattern of
activity was interrupted for short periods (usually shorter than 10 sec) of a
steady, more depolarized membrane potential that was often accompanied by
action potential generation. These short periods of steady membrane
depolarization subsequently returned to the more hyperpolarized, large
amplitude periodic behavior.
Relationship between membrane periodicity and other measures of
periodicity in the olfactory system
Given the similarity between the membrane periodicities reported here and
those suggested by Steriade and colleagues to be characteristic of the
relatively sensory deafferented condition of slow-wave sleep (Steriade et al.,
1993a
,b
),
we elected to look more closely at the relationship between these membrane
fluctuations and periodic patterns of sensory activity in the olfactory
system. It is well known that the olfactory bulb, which provides the primary
afferent projection to the piriform cortex, shows periodic activity
(Bressler and Freeman, 1980
;
Bressler, 1984
), and that the
sniffing activity of rats is rhythmic as well
(Macrides and Chorover, 1972
;
Bhalla and Bower, 1997
).
The data shown in Figure
3A compare pyramidal cell membrane potential
(Vm) recordings with those obtained with extracellular electrodes
in the PC and OB. The bottom trace in
Figure 3A was obtained
from a body cuff measuring ongoing extension and contraction of the chest
associated with respiration. All four traces were recorded simultaneously.
Visual inspection of the raw data obtained with these four types of recordings
indicates similar slow-wave periodicities in each trace. This is quantified in
the power spectral analysis (Fig.
3B--E), which demonstrates peaks between 0.7 and
1.5 Hz in recordings of membrane voltage
(Fig. 3B), field
potentials in the piriform cortex (Fig.
3C), and olfactory bulb
(Fig. 3D), as well as
in the animal's ongoing respiration (Fig.
3E). The average peak frequency is 0.97 ± 0.13 Hz
(n = 18) for all signals.

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Figure 3. Comparisons of cortical, bulbar, and respiratory oscillations. A,
Representative raw traces of pyramidal cell membrane potential (Vm), local
field potentials in layer I of PC, in the granule cell layer of the OB and
respiratory wave as recorded from chest wall movements (Resp). In the
respiratory wave, the downward deflection represents the inspiration. All
traces were recorded simultaneously. The dotted line highlights a single
hyperpolarization-depolarization cycle. The vertical scale for the
intracellular records is 10 mV, whereas the extracellular records are 1 mV.
The graphs B--E indicate the power spectral density for the
recorded membrane potentials (B), local field potentials recorded in
the piriform cortex (C), in the olfactory bulb (D), and
ongoing respiration (E). F, Representative cross-covariance
between membrane potential of a layer II/III pyramidal cell and layer I
olfactory cortex local field potentials. Note that the negative peak
(asterisk) at a time close to 0 sec is shown; such a negative peak reflects
the anticorrelation existing between membrane potential and local field
potentials in layer I of the piriform cortex. G, Representative
cross-covariance between membrane potential and local field potentials in the
granule cell layer of the olfactory bulb. In this case, the peak near time 0
is positive, consistent with the positive correlation between membrane
potential and field potentials in the olfactory bulb. H, Respiratory
wave-triggered average of membrane potential; 0° phase represents the
beginning of the inspiration.
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Correlations in periodic behavior
In addition to similarities in slow-wave behavior, visual inspection
suggests both strong correlations and consistent phase relationships in the
periodic behavior seen in these records
(Fig. 3A, dotted box).
These temporal relationships were confirmed using cross-covariance analysis
(Fig. 3F--G).
Figure 3F indicates
that the depolarized component of the intracellularly recorded membrane
potential is strongly associated with the negative deflection of layer I local
field potential in the piriform cortex. When assessed using the negative peak
of the cross-covariance within a ±0.5 sec time lag
(Fig. 3F, asterisk),
the peak correlation value was found to be -0.55 ± 0.17 (n =
17). The average lag of the peak between membrane potential and cortical local
field potential was only 0.002 ± 0.07 sec (n = 17). There was
also a strong correlation between the local field potential recorded in the
granule cell layer of the olfactory bulb and the pyramidal cell membrane
potential. Assessing the positive peak within a ±0.5 sec of the
cross-covariance between membrane potential and local field potentials
recorded in the olfactory bulb (Fig.
3F, asterisk), a correlation with peak value 0.44
± 0.14 (n = 17) was found. In the case of the olfactory bulb,
the membrane potential depolarization was correlated with the positive
deflection of the olfactory bulb field potential with a lag of 0.13 ±
0.05 sec (n = 17).
The raw data in Figure
3A also suggest a regular phase relationship between
membrane potential and ongoing respiration. This is quantified in
Figure 3H, in which
the phase of respiration is plotted against the mean membrane potential during
eight phases of the breathing cycle. The zero phase in this plot corresponds
to the start of inhalation (i.e., minimum circumference of the diaphragm). The
results show, at least in freely breathing rats, a consistent and strong
relationship of pyramidal cell membrane potential on the respiratory cycle
during periods of slow oscillations, with the largest amplitude membrane
potential occurring at a lag of 225-315°. Membrane potential is
essentially flat for the first 180° in the cycle.
Effect of tracheotomy on membrane potential slow oscillations
The analysis shown in Figure
3 suggests that the slow periodicity seen in membrane potentials,
as well as in the olfactory bulb and piriform cortex, could be directly
related to some feature of the periodic breathing of the rat. To determine
whether the neuronal periodicity was related to the act of breathing or the
actual passage of air into the nostrils, in several animals, all four
physiological measures were obtained after tracheotomy. In tracheotomized
animals, air flows directly into the trachea without passing through the
nostrils.
Figure 4 shows variations in
the pattern of membrane potentials recorded in the tracheotomized rats. Under
these conditions, we found a higher degree of variability in the pattern of
membrane fluctuations in the same cell. All 13 recorded cells generated
periods of spontaneous slow fluctuations with little or no spiking activity
(Fig. 4A) similar to
those seen in the intact preparation (Fig.
2A). However, in the intact preparation, this pattern of
activity is generally sustained for much longer periods (on the order of
minutes) than is the case in tracheotomized rats (typically only 10-30 sec).
Tracheotomized rats also had a reduction in the amplitude of slow membrane
potential fluctuations with the average SDs being 3.43 ± 1.21 mV
(n = 13) versus 6.44 ± 2.37 mV (n = 20; p
< 0.001) in the case of intact preparation. Patterns of slow oscillations
in these rats alternated with periods of hyperpolarized membrane potential
(Fig. 4B) as well as
the depolarized potential also seen in intact animals
(Fig. 4C). Given the
focus of this paper on slow oscillations, analysis of responses in the
tracheotomized animals was restricted to times when membrane potentials showed
slow oscillations similar to those seen in intact preparations.

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Figure 4. Patterns of intracellular activity in tracheotomized rats. A, Slow
oscillations in absence of rhythmic respiratory input. B,
Hyperpolarized membrane potential with large synaptic potentials. C,
Depolarized membrane potential with high-frequency, low-amplitude
oscillations.
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Figure 5A compares
Vm, local field potentials in the PC and OB, and the respiratory rhythm
recorded during a period of slow oscillations in a tracheotomized preparation.
Note that while air was not flowing through the nasal epithelium, the animal
was still controlling its own breathing in these experiments. The records
shown in Figure 5A
clearly indicate that intracellular membrane potential continues to be
periodic, as does the activity seen with extracellular field potentials in the
piriform cortex, olfactory bulb, and of course respiration. However, whereas
all four measures show periodicities, there are clear differences between
tracheotomized and intact rats (Fig.
3) in the power spectral analysis of the data
(Fig. 5B--E).
The average peak value of the power spectral density for membrane potential is
37.08 ± 75.43 mV2/Hz (n = 13), which is lower than
in the intact animal at 270.66 ± 213.45 mV2/Hz (n =
20; p < 0.0001). Moreover, the main oscillatory frequency is less
narrowly peaked (see Fig.
3B for comparison) and is also centered at a lower
frequency than in the intact case; the average peak frequency is 0.80 ±
0.27 Hz (n = 13) for the membrane potential, 0.75 ± 0.25 Hz
(n = 13) for local field potentials in the olfactory cortex, and 0.81
± 0.35 Hz (n = 13) for local field potentials in the olfactory
bulb. The average respiratory frequency in tracheotomized rats is similar to
that in intact rats: 0.99 ± 0.10 Hz (n = 13) and 0.97 ±
0.13 Hz (n = 20), respectively.

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Figure 5. Comparisons of cortical, bulbar, and respiratory oscillations in
tracheotomized rats. A, Raw traces of pyramidal cell membrane
potential (Vm), local field potentials in layer I of PC, in the granule cell
layer of the OB, and respiratory wave (Resp). In the respiratory wave, the
downward deflection represents the inspiration. As in
Figure 3, the graphs
B-E indicate the power spectral density for the recorded membrane
potentials (B), local field potentials recorded in piriform cortex
(C), olfactory bulb (D), and ongoing respiration
(E). F, Cross-covariance between membrane potential (Vm) of
a layer II/III pyramidal cell and layer I olfactory cortex local field
potentials. G, Cross-covariance between Vm and local field potentials
in the granule cell layer of the olfactory bulb. H, Respiratory
wave-triggered average of membrane potential. As in
Figure 3H, the 0°
phase represents the beginning of the inspiration. Dashed line, Intact
preparation; continuous line, tracheotomized preparation.
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Comparison of the traces shown in Figure
5A with those in the intact animal
(Fig. 3A) also
indicates clear changes in the relationships between the periodic behavior
seen in the olfactory system. This is shown in
Figure 5, F and
G, which superimposes cross-covariance analysis in the
intact animal (dashed lines) with those performed in exactly the same manner
for the tracheotomized rats. These comparisons show that although there
continues to be a strong correlation between membrane potential and local
cortical (Fig. 5F) and
bulbar (Fig. 5G)
extracellular potentials, the phase relationships are completely different. In
both cases, there is a shift in correlation of almost 180° after
tracheotomy. Thus, in the piriform cortex, the intracellular depolarization is
now associated with a positive deflection in the cortical local field
potentials, and the peak near 0 sec lag of the cross-covariance is now
positive (0.61 ± 0.14; n = 13). In the case of the olfactory
bulb, the intracellular depolarization is now associated with the negative
deflection of the local field potential, and consistently the peak near 0 sec
lag of the cross-covariance is negative (-0.70 ± 0.09; n =
13). These changes were seen in all 13 cells recorded under tracheotomized
conditions.
Effects of respiration on intracellular slow oscillations
The original intent in examining responses in the tracheotomized animal was
to determine the influence of respiration itself on the periodicities seen in
the olfactory system. Figure
5H shows comparisons made between the membrane potential
and phase of respiration in each condition (dashed line, intact preparation).
These data clearly indicate that the periodic behavior of the olfactory system
is not dependent on respiration in the tracheotomized rats. This result
suggests that the correlation seen between respiration and neural oscillations
in the olfactory system of intact rats is related to the influx of air into
the nasal cavity.
To conclusively demonstrate this hypothesis, we conducted several
experiments in which air was pressure injected into the nostrils of
tracheotomized rats. The results are shown in
Figure 6. Injection of air in
tracheotomized rats produced regular and sustained slow membrane potential
fluctuations lasting as long as the air-puff injection continued. Furthermore,
the frequency of the slow oscillations could be directly controlled by the
frequency of the air puff. Thus, air puffs at
0.5 Hz
(Fig. 6A),
1 Hz
(Fig. 6B), and
2
Hz (Fig. 6C) produced
oscillations with corresponding frequencies. The lines under each trace
indicate the onset of the air puff and clearly show a temporal relationship
between the onset of the air puff and depolarization of cell membrane
potential. This result is also reflected in the power spectral analysis data
after each set of traces (Fig.
6D--F). The peaks of power spectral density were
always narrow and occurred at the same frequency at which the air was puffed
into the nostrils.
Finally, Figure 7 examines
the correlation between Vm and extracellular recordings in the PC and OB in
tracheotomized animals receiving air-puff stimuli. Data obtained at a
1
Hz stimulus frequency are shown, although data at the other two frequencies
were similar. The results show that air-puff stimulation returns the patterns
of correlation to those seen in the intact animal
(Fig. 3, compare F and
G). The plot of the cross-covariance between membrane
potential and cortical local field potentials
(Fig. 7B) shows that
the two signals are anticorrelated (value of the negative peak, -0.49 ±
0.10; n = 10). The plot in Figure
7C displays the cross-covariance between membrane
potential and local field potentials in the olfactory bulb; in this case, the
actual shape of the correlation differs somewhat from the intact preparation
but still includes a large phase-delayed positive peak.

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Figure 7. Effects of air forced in the nostrils on cross-covariance patterns. Air
forced in the nostrils produces activity and cross-covariance patterns similar
to those present in deeply anesthetized, freely breathing rats. A,
Air puff-induced oscillations: Vm, membrane potential; PC piriform cortex
local field potentials; OB, olfactory bulb local field potentials. Black lines
represent the timing of the occurrence of air puffs. B,
Representative cross-covariance between membrane potential and piriform cortex
local field potentials. C, Representative cross-covariance between
membrane potential and olfactory bulb local field potentials.
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Discussion
|
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Slow (< 1.5 Hz) oscillations in the olfactory system
The results presented here demonstrate for the first time the presence of
slow (<1.5 Hz) respiratory-related oscillations in the olfactory system
under conditions of ketamine-xylazine anesthesia. This study is also the first
to examine the relationship between slow olfactory field potential
oscillations, intracellular membrane potential, and respiratory activity.
Phase coupling within the olfactory system
Intracellular slow oscillations appeared to be highly correlated with
extracellular field potentials recorded at a distance of
1-2 mm; this
observation indicates a high degree of synchrony of slow oscillations within
the olfactory cortex. Cortical slow oscillations were also found to be
strongly correlated with bulbar activity, again suggesting a high level of
phase coupling in the whole olfactory bulb-olfactory cortex system. This
observation allows us to draw an analogy between the olfactory system and the
thalamocortical system. In fact, as in the case of the olfactory cortex,
neocortical slow oscillations are strongly correlated among wide cortical
areas (Destexhe et al., 1999
)
and with the thalamus (Timofeev and Steriade, 1996b). The main difference
between these two systems is in the genesis of these oscillatory patterns. In
the thalamocortical system, slow oscillations are generated within the cortex
and reverberated in a thalamocortical loop
(Bazhenov et al., 2002
); our
data support the view that in the bulbar-cortical system, slow oscillations
are generated by barrages of synaptic inputs rhythmically activating the
olfactory bulb and propagating in the cortex. Of course, our data cannot
exclude the possibility that feedback projections from the olfactory cortex to
the olfactory bulb may play a role in the genesis or maintenance of this
oscillatory pattern.
Relationship of slow-wave oscillations to afferent input
Steriade and colleagues proposed that the presence of these slow
oscillations reflects a behavioral condition in which the brain is mostly
closed to the external environment and running on its own (Timofeev et al.,
1996a; Steriade 2000
).
Electrophysiological results demonstrate slow-wave oscillations in neocortical
slices (Sanchez-Vives and McCormick,
2000
) and slabs (Timofeev et
al., 2000
), supporting Steriade's proposal that slow-wave
oscillations are a specific indication of an isolated deafferented state.
The results of this study demonstrate that this is clearly not the case in
the olfactory system. The respiratory wave-triggered average of intracellular
recordings in the olfactory cortex demonstrates a strong relationship between
the timing of respiration and cortical slow oscillations. Furthermore, the
occurrence of slow oscillations, similar to those observed in freely breathing
rats, is modified when airflow through the nostrils is removed by tracheotomy.
After tracheotomy, membrane potentials in piriform cortex pyramidal cells
become more variable; when present, periods of slow oscillation have shorter
duration, smaller amplitudes, no correlation with respiration, and reversed
cross-covariance patterns. Slow oscillations similar to those occurring in the
intact preparation were then reestablished when air was forced in the nostrils
independent of the rat's breathing cycle. Under these conditions, the
frequency of membrane potential oscillations followed the frequency of air
stimulation. Therefore, at least under ketamine anesthesia, the timing and to
some extent the occurrence of slow oscillations in the olfactory system appear
to be directly related to the flow of air into the nostrils. Our data are
consistent with previous intracellular recordings in the piriform cortex of
urethane-anesthetized rats (Wilson,
1998
), showing a correlation between membrane potential
fluctuations and phase of respiration. Under urethane anesthesia, however,
spontaneous membrane potential fluctuations appeared to be faster, consistent
with a higher respiratory frequency with such anesthetic, and to have lower
amplitude. Our results are also consistent with recent imaging studies in
humans showing a direct correlation between breathing and activity in the
olfactory cortex (Sobel et al.,
1998
). Of course, the particular frequencies of slow wave and
respiratory rhythms are likely to differ, depending on the species involved
(Achermann and Borbély,
1997
; Amzica and Steriade,
1997
).
What input is responsible for this correlation?
Our finding that air puffed into the nostrils of a tracheotomized rat
correlates bulbar and cortical activity leaves open the question as to what
specific neural signal is responsible. The fact that respiratory movement of
the diaphragm is not correlated with neural activity in the tracheotomized rat
indicates that the signal is not paced by ascending signals coming from bulbar
respiratory centers. Instead, the neuronal correlation appears to be directly
related to the movement of air into the nostrils.
Air moving into the nostrils influences several different sensory afferent
systems, which could in turn influence bulbar and cortical activitiy. First,
recordings from primary olfactory sensory neurons clearly show a correlation
between neural activity in the olfactory epithelium and breathing
(Chaput, 2000
). Second, it is
known that the there are pressure detectors in the walls of the nasal cavity
that also respond periodically during inhalation
(Tsubone, 1990
). Additional
studies will be necessary to determine which or what combination of this
sensory information is responsible for the observed correlations. Again,
however, the data makes it clear that these correlations are dependent on some
form of sensory input resulting from entry or air into the nostrils.
Interestingly, in some instances, the slow oscillatory pattern was
disrupted, and slow oscillations were replaced by high-frequency,
low-amplitude fluctuations resembling rapid eye movement-like activity. During
these periods, there was also a decoupling between membrane potential and
respiratory input. Although we did not monitor other possible sources of input
to the olfactory system (for example, neuromodulatory systems) in these
experiments, it is possible that these periods of decoupling result from other
influences modifying the relationship between respiratory input and neural
activity.
Afferent compared with intrinsic oscillatory mechanisms
Beyond the specific afferent signal or signals responsible for producing a
correlation between inhalation and neural activity in the bulb and cortex, the
results presented here also suggest that the contrast between extrinsic and
intrinsic oscillatory mechanisms may be artificial. Although slow oscillations
occur more regularly and at higher amplitude in the intact animals than in the
tracheotomized animals, extracellular field potentials in the bulb and cortex,
as well as intracellular membrane potentials in cortical pyramidal cells,
continue to include activity at these frequencies, even in the absence of
inhalation. Therefore, both the bulb and cortex appear to be capable of
generating slow-frequency oscillations in the absence of periodic afferent
input. However, afferent input clearly affects the coupling between the
neuronal activity.
Perhaps the most surprising difference in neuronal coupling between the
tracheotomized and intact preparations is the reversal of correlation between
intracellular and extracellular recordings in the olfactory cortex. The
association of positive field potentials with negative membrane potential in
the intact animal is what one would expect from standard assumptions
concerning current flow in cortical circuits
(Ketchum and Haberly, 1993
).
The 180° shift in what has been thought to be a fundamental relationship
in the tracheotomized animal was unexpected. Although current source-density
analysis has demonstrated that reversals of this sort occur at different
recording depths in the cortex (Ketchum
and Haberly, 1993
), we could shift these phase relationships back
and forth with air puffs in the tracheotomized rat. Thus, this change would
seem to reflect a fundamental difference in the organization of cortical
activity between these two preparations. The change in correlation raises
important questions regarding the relationship between intracellular- and
extracellular-recorded activity, which will require additional experimental
and network-modeling studies (Protopapas
et al., 1998
).
The influence of inhalation on slow oscillations in other regions of
the olfactory-limbic axis
Given the influence of inhalation on neural activity in the olfactory bulb
and cortex, we believe it is worth considering whether the temporal pattern of
inhalation might also influence the periodic behavior of other forebrain
structures. Within the olfactory-limbic axis, slow oscillations have been
reported to occur in the entorhinal cortex
(Biella et al., 2001
),
perirhinal cortex, and lateral amygdala
(Collins et al., 1999
;
Collins et al., 2001
).
Although often considered separate from the olfactory system, each of these
structures does receive a substantial projection from olfactory structures,
including the olfactory bulb (Haberly,
1998
). Although there is evidence in subcortical areas for the
influence of other descending systems on oscillations
(Steriade, 2001
), at present,
it is not known what if any role the olfactory system might play in generating
or modulating slow oscillations in the limbic system. Our findings suggest
that it might be fruitful to examine these oscillations with respect to
respiration.
Relationship to neocortical slow oscillations
Slow oscillations, similar to those demonstrated here to occur in olfactory
cortex, are also a stereotyped phenomenon present throughout the neocortex
that has been recorded in visual, motor, and association areas
(Steriade et al., 1993a
). From
a functional point of view, the neocortical slow oscillation has been
interpreted as a state of sensory deafferentation of the cortex
(Steriade, 2000
). Our finding
that the temporal structure of slow oscillations in the olfactory system is
related to air entering the nostrils supports the view that slow oscillations
seen in the olfactory system under ketamine-xylazine anesthesia are associated
with periodic sensory input at the same frequencies. Our data therefore
suggest that the slow oscillation in the olfactory system does not represent a
state of deafferentation from the sensory input. To conclusively generalize
the conclusions obtained in the olfactory system under ketamine-xylazine
anesthesia to the sleep state, additional experiments will be necessary.
Unfortunately, we are aware of no full study of olfactory bulbar or olfactory
cortical activity during actual sleep; although, Freeman briefly noted that
sleep was associated with an irregular slow-wave behavior that did not appear
to be correlated with respiration
(Freeman, 1959
).
We suggested previously, on structural and computational grounds, that the
fundamental neuronal architecture of the cerebral cortex perhaps first evolved
in the context of the olfactory system and was then adapted for the use of
other sensory systems through the evolution of neocortex (Wilson and Bower,
1991
,
1992
;
Bower, 1995
; Morrissette and
Bower, 1996). As part of that adaptation, we speculated that thalamocortical
sensory pathways may have had to adapt to pattern neuronal activity into the
dynamic frequencies native to the olfactory system (e.g.,
,
).
The results of this study suggest that the oscillatory activity patterns
generated in the thalamo-neocortical system in the sleep state
(Bazhenov et al., 2002
) may
also mimic the slow periodic inputs generated by the resting respiratory
rhythm in the olfactory system. The essential point and prediction is that
proper function of cortical circuitry during sleep, whatever that function is
(Wilson and McNaughton, 1994
;
Lee and Wilson, 2002
),
requires or expects such slow periodic input because of an evolutionary link
between cortical circuitry and olfaction.
 |
Footnotes
|
|---|
Received March 19, 2003;
revised July 8, 2003;
accepted July 9, 2003.
Correspondence should be addressed to Alfredo Fontanini, Department of
Biology, MS 008, Brandeis University, 415 South Street, Waltham, MA 02454.
E-mail:
alfredof{at}brandeis.edu.
This work was supported by a Multidiciplinary University Research
Initiative grant managed by the Army Research Office. We thank Drs. Marco
DeCurtis and Arianna Maffei for helpful comments on this manuscript.
Copyright © 2003 Society for Neuroscience
0270-6474/03/237993-09$15.00/0
 |
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