 |
 Previous Article | Next Article 
The Journal of Neuroscience, December 15, 1998, 18(24):10709-10723
Rhythmic Properties of the Hamster Suprachiasmatic Nucleus
In Vivo
Shin
Yamazaki,
Marie C.
Kerbeshian,
Craig G.
Hocker,
Gene D.
Block, and
Michael
Menaker
National Science Foundation Center for Biological Timing,
Department of Biology, University of Virginia, Charlottesville,
Virginia 22903
 |
ABSTRACT |
We recorded multiple unit neural activity [multiunit activity
(MUA)] from inside and outside of the suprachiasmatic nucleus (SCN) in
freely moving male golden hamsters housed in running-wheel cages under
both light/dark cycles and constant darkness. The circadian period of
MUA in the SCN matched the period of locomotor activity; it was ~24
hr in wild-type and 20 hr in homozygous tau mutant
hamsters. The peak of MUA in the SCN always occurred in the middle of
the day or, in constant darkness, the subjective day. There were
circadian rhythms of MUA outside of the SCN in the ventrolateral
thalamic nucleus, the caudate putamen, the accumbens nucleus, the
medial septum, the lateral septum, the ventromedial hypothalamic
nucleus, the medial preoptic region, and the stria medullaris. These
rhythms were out-of-phase with the electrical rhythm in the SCN but
in-phase with the rhythm of locomotor activity, peaking during the
night or subjective night. In addition to circadian rhythms, there were
significant ultradian rhythms present; one, with a period of ~80 min,
was in antiphase between the SCN and other brain areas, and another,
with a period of ~14 min, was in-phase between the SCN and other
brain areas. The periods of these ultradian rhythms were not
significantly different in wild-type and tau mutant
hamsters. Of particular interest was the unique phase relationship
between the MUA of the bed nucleus of the stria terminalis (BNST) and
the SCN; in these two areas both circadian and ultradian components
were always in-phase. This suggests that the BNST is strongly coupled
to the SCN and may be one of its major output pathways. In addition to
circadian and ultradian rhythms of MUA, neural activity both within and
outside the SCN was acutely affected by locomotor activity. Whenever a
hamster ran on its wheel, MUA in the SCN and the BNST was suppressed, and MUA in other areas was enhanced.
Key words:
circadian; ultradian; suprachiasmatic nucleus; in
vivo recording; hamster; tau mutant; locomotor
activity; bed nucleus of the stria terminalis; MUA
| |
INTRODUCTION |
Circadian locomotor activity rhythms
in mammals are generated by an endogenous pacemaker located in the
suprachiasmatic nucleus (SCN) of the hypothalamus (for review, see
Turek, 1985 ; Meijer and Rietveld, 1989; Klein et al., 1991). Lesions of
the SCN cause arrhythmicity of locomotor activity (Moore and Eichler,
1972; Stephan and Zucker, 1972; Rusak and Zucker, 1979), and
transplants of fetal SCN tissue restore circadian periodicities (Sawaki
et al., 1984; Lehman et al., 1987; Ralph et al., 1990). The SCN
exhibits circadian rhythms in several in vitro preparations:
the acute slice (Green and Gillette, 1982; Groos and Hendricks, 1982;
Shibata and Moore, 1988), slice culture (Bos and Mirmiran, 1990; Herzog et al., 1997), and dispersed cell culture (Welsh et al., 1995; Liu et
al., 1997). Both slice and dispersed cell cultures of SCN also display
circadian rhythms of peptide release (Murakami et al., 1991; Watanabe
et al., 1993; Shinohara et al., 1995). In contrast the physiology of
the SCN in vivo and its relationship to circadian behavior
in the intact animal have received little experimental attention.
To understand how the circadian clock controls locomotor behavior, we
need to understand its connections to the motor control system.
Although output pathways from the SCN circadian pacemaker are not
completely described, the motor control system in mammals is relatively
well characterized (Wichmann et al., 1995; Bergman et al., 1998).
Because there are no known direct neural connections between the SCN
and motor control areas of the brain, it is likely that either humoral
factors and/or "relay nuclei" serve to connect the SCN with the
motor centers.
Not only does the SCN regulate locomotor activity but there is reason
to believe that locomotor activity feeds back on the SCN. The period of
the free-running rhythm of rats housed in cages with a running wheel is
different from that of rats housed in cages without a wheel (Yamada et
al., 1988, 1990; Shioiri et al., 1990). Locking of the running wheel
changes the free-running period in mice (Edgar et al., 1991). Access to
running wheels induces phase shifts of locomotor activity in hamsters
(Mrosovsky, 1988; Reebs and Mrosovsky, 1989) as does injection of
triazolam, which increases locomotor activity (van Reeth et al., 1987).
In mice, forced treadmill running induces phase shifts of circadian
rhythms and is able to entrain them (Marchant and Mistlberger,
1996).
The apparent complexity of the relationship between the SCN and
locomotor centers, almost certainly involving reciprocal interactions, and the fact that direct neuronal interconnections appear to be absent
provide a strong rationale for exploring the functional relationships
in vivo. We have perfected a technique that allows us to
record neuronal activity of several brain regions in freely moving
hamsters, enabling us to correlate electrical activity within the SCN
with activity in other brain regions and with locomotor activity. We
have used this technique to describe the electrical characteristics of
the SCN in vivo, the differences between the tau
mutant and wild-type hamsters, the relationship between the SCN and
other regions of the brain, and the effect of the animal's locomotor
behavior on SCN activity. The results provide a new framework for
understanding the regulation of locomotor behavior by the circadian
timing system.
| |
MATERIALS AND METHODS |
Animals. Three- to five-month-old golden hamsters
(LVG wild type from Charles River Laboratories, Wilmington, MA;
LVG background tau mutant animals from our colony) were used
in this study. Animals were entrained for at least 2 weeks to
light/dark cycles (LDs) (14:10 hr LD for wild types; 11.7:8.3 hr LD for
tau mutants; light intensity of ~300 lux at cage level).
We monitored wheel-running activity throughout the experiments and used
only animals that showed clear locomotor rhythmicity.
Electrode implantation. We implanted one or two bipolar
electrodes constructed from pairs of Teflon-coated stainless steel wires (bare diameter, 130 µm; A-M Systems, Everett, WA; tip distance, ~150 µm for recording from the SCN and 200-300 µm for other
brain regions) and an uncoated platinum-iridium wire (diameter, 130 µm; A-M Systems) used as a signal ground in the cortex. Wires were connected to an eight pin IC socket wrapped in insulated copper tape. Distances between any two bipolar electrodes were determined according to the recording sites chosen.
Electrode implantation was performed under pentobarbital anesthesia (90 mg/kg, i.p.). Animals were placed in a stereotaxic instrument with
the nose bar set at  2 mm (David Kopf Instruments, Tujunga,
CA). Four self-tapping screws (#0 × 1/8 inch; Small Parts, Miami
Lakes, FL) were implanted into 1 mm holes in the skull made with a
dental drill. We used different stereotaxic coordinates for wild-type
and tau mutant hamsters because the shape of bregma in
tau mutants is different and more variable than is that in wild types. Wild-type SCN coordinates were 0.7 mm anterior to bregma,
0.2 mm lateral to the midsagittal, and 8.0-8.2 mm below the dural
surface. Tau mutant coordinates were 1.0-1.2 mm anterior to
bregma, 0.2 mm lateral to the midsagittal, and 7.9-8.1 mm below the
dural surface. The electrode was secured to the screws and the skull
with dental cement.
Recording procedure. One week after surgery, each hamster
was transferred to a 24 cm (width) × 21 cm (length) × 30 cm (height) cage with a running wheel 21 cm in diameter mounted on one side to
allow the hamster equipped with wires access to the wheel. The
electrodes were connected to head stage buffer amplifiers (J-FET
input OP Amp; TL084) located on the hamster's head. Buffer amplifiers were connected to a 12 channel slip ring (Airflyte Electronics Company, Bayonne, NJ) that allowed free movement for the
animal. The wires between the head stage amplifiers and the slip ring
were protected by a stainless steel spring. Output signals were
processed by differential input integration amplifiers (INA 101 AM; Burr-Brown, Tucson, AZ; gain, ×10) and then fed into
AC amplifiers (OP Amp, 4558; bandpass, 500 Hz to 5 kHz; gain, 10,000). Spikes were discriminated by amplitude and counted in 1 min bins using
a computer-based window discrimination system (DAS-1801ST AD
board; Keithley Metrabyte, Taunton, MA). Wheel revolutions were
recorded using the Data Quest system (Data Science International, St.
Paul, MN).
Reduction of recording noise. In recording neural activity
from freely moving animals, the biggest problem is noise. We reduced microphonic noise, which is caused by mechanical disturbances such as
wire movements, by mounting the buffer amplifiers on the head
(effectively decreasing the impedance). We directly coupled the output
signals to the integration amplifier (without any capacitors or
resistors) to provide a high common mode rejection ratio that can
reduce non-neuronal signals such as muscle potentials. We also used
shielding material around the electrode and its vicinity to reduce
noise from the animal's scratching. Because we could not entirely
remove this source of noise, we used a highly effective low-cut filter
(500 Hz). Using these techniques, we reduced electrical noise generated
by chewing or moving to undetectable levels. Although scratching did
generate detectable electrical noise, this activity was rare and did
not create a problem in the analysis.
Identification of recording sites. After the electrical
recordings, each hamster was anesthetized with halothane, the head amplifier was disconnected, and a small positive current (50 µA; 10 sec) was passed through the recording electrodes. The brain was removed
and fixed in Zamboni's fixative solution for a few days. Frozen
sections (40 µm thick) were stained with potassium ferrocyanide (5%
potassium ferrocyanide in 10% HCl). Blue spots of deposited iron were
used for identification of recording sites.
Data analysis. The first report of SCN neuronal recordings
from freely moving rodents appeared 19 years ago and played a pivotal role in identifying the SCN as the central mammalian circadian pacemaker (Inouye and Kawamura, 1979). Since then little use has been
made of this technique. A primary reason for hesitation in the use of
in vivo recording techniques is that changes in neuronal oscillations are oftentimes difficult to identify in the raw data, and
thus robust time series statistical analysis is required. No single
time series analysis tool can be applied in all cases. We applied a new
method, singular-spectrum analysis (SSA), in combination with older
methods. Periodicities in multiunit activity (MUA) recorded
in vivo were determined using SSA in combination with the
multitaper method (MTM) approach to the fast Fourier transform
(Thomson, 1982; Vautard et al., 1992).
Singular-spectrum analysis or SSA is a linear, nonparametric method
based on a principal component analysis in the vector space of
the delay coordinates for a times series (Elsner and Tsonis, 1996). In
SSA, a single time series is expanded into a set of multivariate time
series of length M, known as the "window length."
M determines what range of frequencies can be resolved as a
stationary signal in the calculated principal components. The
principal component analysis orders the expanded time series as
a new coordinate system with most information along the first coordinates. The principal components are processes of length N M + 1 that can be thought of as
weighted moving averages of the time series in which each accounts for
a certain percentage of the total variance. SSA allows optimal
detrending, identification of the noise floor in spectral estimates,
and identification of intermittent oscillatory components in the data.
In practice, we found that we could with reasonable success divide the
data into four parts (trend variance, circadian variance, ultradian components variance, and noise variance) by use of two window lengths
on the MUA data. M was set at 36 hr (M = 360 for 6 min bins) for the circadian time scale and 5 hr for the ultradian time scale. SSA cannot resolve periods longer than M and
treats them as trends. If M is much greater than the average
lifetime of an episode of oscillation, SSA cannot resolve the
intermittent oscillation.
We used SSA for signal reconstruction from the noisy MUA data. Simple
noise reduction by applying a fixed low-pass filter to the data is not
appropriate when the spectrum is not monotonic. Because steps were
taken to minimize instrument noise and a low-cut filter was used (500 Hz) before binning the impulses in the MUA data, noise is represented
here mostly by random impulses from populations of neurons near the
electrode. Optimal filtering of signals that are not completely stable
requires methods such as Wiener filtering or SSA. Both provide optimal
filters in a least squares sense. However Weiner filters arbitrarily
require harmonic functions as a basis. SSA, in contrast, uses
data-determined general functions that do not require any previous
hypotheses about the noise variance. Unlike SSA, the Wiener method
requires smooth and very reliable estimates of the power spectrum that
are impossible to obtain with very short data sets. "Noise-free"
circadian or ultradian time series were therefore reconstructed from
the SSA filters. By this method, oscillatory signals that accounted for as little as 3% of the total variance could be detected. Monte Carlo
simulations assuming either white noise or correlated noise were used
to evaluate the background noise level in the SSA spectra. By selecting
only those principal components associated with the circadian
variance of the data, we could derive an optimal (in the least squares
sense) "noiseless" reconstruction of the circadian waveform in the
data. Each waveform in the reconstructed time series is essentially a
local fit allowing us to calculate a mean period from each animal's
data set. This local noise-free fit also allowed us to determine the
phase relationship as a function of time between two different
locations in the brain. Periods of the ultradian rhythms were
determined with one or more of the following: SSA-MTM, power spectrum
estimates [e.g., maximum entropy method (MEM)], or visual inspection
of the raw data. MEM was performed on the data after the trend and
circadian variances were removed (determined by SSA). The order of the
MEM (M, number of poles in the autoregressive model) was
kept much lower than the number of data points and varied over the
range to monitor stability of peaks of interest in the spectrum
(M, 20-60; N > 1600). MEM is fully
consistent with SSA so that the additive property of the spectra is
conserved exactly (Vautard et al., 1992). Periods of very short
ultradian rhythms were determined by visual inspection; areas of
high-frequency ultradian activity were measured for the average period,
and measurements from six areas per animal were averaged to obtain the
period. The periods of the wheel-running activity were obtained by
using a standard chi-square periodogram for comparison with the other
methods (see Table 1).
Phase analysis. We used the discrete Hilbert transform
of the SSA-reconstructed waveforms to estimate the instantaneous phase difference between the oscillations inside and outside the SCN. The
Hilbert transform is the imaginary part of the analytical signal of a
real time series (Bendat and Piersol, 1986). An estimate of the
imaginary part from the real part of the time series can be calculated
by assuming the signal is causal (a sequential time series) and by
using the inverse of a one-sided Fourier transform (fast Fourier
transform coefficients that correspond to negative frequencies
are set to zero before doing the inverse transform). The resultant time
series is phase shifted 90° from the original time series. This
process is sensitive to noise and requires a filtered input such as
that provided by SSA. The temporal change in the relative phase between
the oscillations recorded in different brain regions was examined using
this method. Circular statistics were used to compute the mean phase
difference for the circadian rhythms in different brain regions
(Fisher, 1995).
Experimental protocols. To observe daily and circadian
changes of neural activity in and outside of the SCN, we recorded MUA from 20 wild-type hamsters implanted with two electrodes. One electrode
was directed into the SCN, and the other was aimed at one of several
regions outside of the SCN. Animals were recorded for 4 d in a
light/dark cycle (14:10 hr LD; light intensity of ~300 lux at cage
level), followed by 6 d in constant darkness (DD). To evaluate the
effects of the tau mutation on the rhythmic properties, we
recorded MUA from 10 wild-type and 14 tau mutant hamsters
implanted with two electrodes, one aimed at the SCN and the other at
one of the following sites: the lateral septum (LS), the caudate
putamen (CP), the ventrolateral region of the thalamus, and the bed
nucleus of the stria terminalis (BNST). These hamsters were placed into
DD at the time of their normal lights off, and MUA was recorded for
7 d. We only used data from implantations in which both wires of
each electrode were located in the same nucleus. We sometimes observed
one wire located in the SCN, while the other was in the surrounding
area; in those cases the data were discarded.
| |
RESULTS |
Circadian rhythms both within and outside the SCN
MUA recorded in the SCN showed clear daily (LD) and circadian (DD)
rhythms (Fig. 1). Peak impulse frequency
of these rhythms always occurred at the middle of the day (LD) or
subjective day (DD), in antiphase with the hamster's nocturnal
wheel-running activity. The amplitude of the neuronal activity rhythms
varied from experiment to experiment and was not strongly correlated with the recording site, although recordings obtained in the ventral portion of the SCN tended to have a higher amplitude than did those
from the dorsal portion. Although the recording sites were nearly
identical for the animals whose records are shown in Figure 1,
B and C, the MUA displayed in Figure
1B has higher average amplitude oscillations than
does that in Figure 1C. SSA detected a significant circadian
(or daily) oscillation with a centered amplitude of ~10,000 spikes
per 6 min interval from the data plotted in Figure
1B. The centered amplitude from data shown in Figure 1C was approximately one-fourth as large.
View larger version (42K):
[in this window]
[in a new window]
|
Figure 1.
Examples of MUA recorded for 10 d from the
SCN of three wild-type hamsters. Animals were kept in
light/dark cycles (14:10 hr LD) for 4 d and then released into
constant darkness (lighting condition indicated at the
bottom of the figure). Neuronal spikes are plotted in 6 min bins. Wheel-running activity is plotted at the
bottom of A-C as the number of
revolutions per 6 min; the y-axis for this portion of
the figure shows 0-200 revolutions per 6 min. A,
Recorded from the ventrolateral portion of the central region of the
left SCN. B, Recorded from the ventromedial portion of
the right SCN at the center of the rostrocaudal axis. C,
Recorded from the ventromedial portion of the right SCN near the caudal
end of the nucleus.
|
|
There was no consistent relationship between overall levels of
locomotor activity and MUA activity. For example, the wheel-running activity of animals shown in Figure 1, A and B,
was quite variable (on some nights the hamsters ran much more than on
others), yet the amplitude of the MUA rhythms remained relatively
constant. Furthermore, in all three examples in Figure 1, the amplitude of MUA oscillation in the SCN did not change when the animals were
released from LD into DD. Even in the case of the animal whose data are
shown in Figure 1A, in which the electrode was located in the lateral portion of the SCN (which receives the retinal
projection), light did not have an acute effect on the MUA.
Most regions outside of the SCN also showed clear daily or
circadian rhythms (Fig. 2). The
ventrolateral thalamic nucleus (n = 3), the CP
(n = 3), the accumbens nucleus (n = 1),
the medial septum (n = 1), the LS (n = 6), the ventromedial hypothalamic nucleus (n = 2), the
medial preoptic region (n = 1), and the stria medullaris (n = 3) all exhibited circadian
rhythms with peak impulse activity occurring at night or subjective
night that, unlike the electrical activity rhythm in the SCN, was
in-phase with locomotor activity. SSA of activity in the optic chiasm
(n = 2) revealed no circadian components, but ultradian
rhythms were present and were stronger in LD than in DD.
View larger version (50K):
[in this window]
[in a new window]
|
Figure 2.
Daily and circadian rhythms of neural activity in
several regions of the brain. MUA and locomotor activity are plotted in
6 min bins as in Figure 1. Recordings were made from the following:
A, right side of the ventrolateral thalamic nucleus
(VLT); B, right side of the medial
septum (MS); C, right side of the stria
medullaris (sm); D, right side of the LS;
E, the optic chiasm (oc). Each
plot represents a different wild-type hamster except for
A (same animal as in E) and
C (same animal as in Fig. 1C). Note (most
clearly in B) that the peak of neural activity coincides
with wheel-running activity.
|
|
There were clear correlations between electrical activity in the
SCN and in other brain regions. The data in Figure
3 were recorded from a wild-type hamster
in DD. MUA from the SCN (Fig. 3A) and the LS (Fig.
3B) and wheel-running activity (Fig. 3C) were
collected simultaneously; all three data sets contain significant circadian components. Figure 4 presents
reconstructed waveforms of the circadian components using the SSA
method. Circadian rhythms in the SCN (Fig. 4A) and LS
(Fig. 4B) were tightly locked in an antiphase
relationship (Fig. 4C). Their periods were matched to that
of the wheel-running activity rhythm that was in antiphase to the SCN.
The data in Figure 5 were recorded from a
tau mutant hamster. MUA was recorded from the SCN (Fig.
5A) and CP (Fig. 5B). Both regions showed
significant circadian rhythms that matched the 20 hr period of the
wheel-running rhythm (Fig. 5C). The phase angle difference
between these two brain regions was also stable in antiphase (Fig.
6; sometimes, as in this example, stable
phase relationships did not develop the first cycle or two of constant darkness). Other examples (SCN and LS in a wild type, n = 1; SCN and ventrolateral thalamus in a wild type, n = 1; and SCN and ventrolateral thalamus in a tau mutant,
n = 1) showed similar phase relationships.
View larger version (41K):
[in this window]
[in a new window]
|
Figure 3.
Wheel-running behavior and neural activity records
from the SCN and LS of a wild-type hamster
(WT) in constant darkness. Electrodes
were located in the left ventromedial region of the central SCN and in
the right LS. The time scale shows hours after the hamster was released
into constant darkness. A, MUA in the SCN in 6 min bins.
B, MUA in the LS in 6 min bins.
C, Wheel revolutions per 6 min. The data marked by the
double-headed arrows are presented below (see
Fig. 8).
|
|
View larger version (22K):
[in this window]
[in a new window]
|
Figure 4.
Mathematical analysis of the phase angle
difference of the circadian rhythms recorded in the SCN and LS in a
wild-type hamster. Original data are shown in Figure
3A,B. Data reconstructed by SSA for the
SCN (A) and for the LS (B).
C, Instantaneous phase angle difference between the
circadian rhythms shown in A and B. The
time series A and B were individually
converted to their Hilbert transforms (the time series with a 90°
phase shift). The resultant time series are series of complex numbers
representing the original data (real part) and the Hilbert transform
(imaginary part). The magnitude of each of these complex numbers is an
estimate at that time of the circadian rhythm amplitude (data not
shown). The angle of each of these complex numbers is an estimate at
that time of the phase of the circadian rhythm relative to the
beginning. The difference between the angles of A and
B at each point is the instantaneous phase difference
between the two circadian rhythms.
|
|
View larger version (39K):
[in this window]
[in a new window]
|
Figure 5.
Wheel-running behavior and neural activity records
from the SCN and CP of a tau mutant hamster in constant
darkness. Electrodes were located in the right ventromedial part of the
central region of the SCN and in the right CP. A, MUA in
the SCN in 6 min bins. B, MUA in the CP in 6 min bins.
C, Wheel revolutions per 6 min. The data marked by the
double-headed arrows are presented below (see Fig. 10).
SS, Homozygous tau
mutant.
|
|
View larger version (23K):
[in this window]
[in a new window]
|
Figure 6.
Mathematical analysis of the phase angle
difference of the circadian rhythms recorded in the SCN and CP in a
tau mutant hamster. Original data are shown in Figure 5.
A, B, Data reconstructed by SSA for the
SCN (A) and for the CP (B).
C, Instantaneous phase angle difference between the
circadian rhythms shown in A and
B.
|
|
Ultradian rhythms
MUA in the SCN and in other brain regions displayed ultradian
components in addition to circadian ones. We succeeded in identifying a
significant circadian component and two ultradian components from the
time series data in all brain regions analyzed. Figure 7 shows an example of MUA recorded from
the SCN in a tau mutant hamster in DD. As expected, an ~20
hr circadian component in antiphase to the wheel-running activity
rhythm was present. The record also shows a clear ultradian component
with a period of ~80 min. Furthermore, in expanded plots we could
detect a higher frequency rhythm of ~14 min that was most clearly
expressed around the peak of the 80 min oscillation.
View larger version (28K):
[in this window]
[in a new window]
|
Figure 7.
Circadian and ultradian rhythms of MUA in the SCN
of a tau mutant hamster in constant darkness. In this
case, the bipolar electrode became separated in the brain, with one
electrode positioned on the left side and the other positioned on the
right side of the ventromedial region of the caudal SCN. Top
bars of A and B show
wheel-running activity, plotted as a black bar when the
wheel revolved more than once in 6 min. The time scale shows hours
after the animal was released into constant darkness. A,
Plot of MUA in 6 min bins. B, Expanded plot of 20 hr
(one circadian cycle for the tau mutant hamster) of data
from A with neuronal activity in 1 min bins showing
ultradian rhythms of both periods as well as the negative correlation
between wheel-running activity and neural activity.
|
|
Expanded plots of 24 hr segments recorded from the SCN (Fig.
3A) and the LS (Fig. 3B) of a wild-type hamster
are shown in Figure 8, A and
B, respectively. These data contain two ultradian components, ~80 and ~14 min. The two components were
identified by spectral analysis and visual inspection, respectively.
The time domain SSA reconstructions of the ~80 min ultradian
oscillations in the SCN and the LS were in-phase with each other on the
first day after transfer from LD to DD; however by the second day in DD
they had shifted to an antiphase relationship (Fig.
9A,B). The ~14 min ultradian rhythms appeared to be in-phase between the SCN
and the LS (Fig. 8). We obtained similar results from two other
wild-type hamsters (recorded from the SCN and the ventrolateral thalamus or LS).
View larger version (30K):
[in this window]
[in a new window]
|
Figure 8.
Ultradian rhythms in neural activity records from
the SCN and LS of a wild-type hamster. A, Expanded plot
of the 24 hr neural activity record in 1 min bins from the SCN (from
Fig. 3A, double-headed arrow). The
top bar shows wheel-running activity, plotted as a
black bar whenever the wheel revolved more than once in
6 min. B, Expanded plot of the concurrent record from
the LS (from Fig. 3B, double-headed
arrow). Note the negative correlation of neural activity with
wheel-running activity in the SCN and the positive correlation in the
LS.
|
|
View larger version (40K):
[in this window]
[in a new window]
|
Figure 9.
Mathematical analysis of ultradian rhythms
recorded from the SCN and LS (from Fig.
3A,B). A,
Data reconstructed by SSA of the 80 min ultradian rhythms in the SCN
(solid line) and the LS (dotted line) for
the first 72 hr of the record. B, Phase angle difference
of the 80 min ultradian rhythms between the SCN and the LS plotted for
144 hr (see text and Fig. 4 for details).
|
|
The ultradian components recorded from tau mutant hamsters
also had periods of ~80 and ~14 min. Time series analysis and
visual inspection of simultaneous recordings from the SCN and the CP in
a tau mutant hamster revealed these two ultradian components (Fig. 10). In this data set the phase
relationships of the 80 min oscillations in the two areas were often in
antiphase, but their phase relationship was much less stable than in
similar recordings from wild types (Fig.
11). As in wild types, the ~14 min
rhythms always appeared to be in-phase (Fig. 10). A second
tau mutant hamster in which electrical recordings were
obtained from the SCN and the ventrolateral thalamus exhibited similar
properties.
View larger version (34K):
[in this window]
[in a new window]
|
Figure 10.
Ultradian rhythms in neural activity records from
the SCN and CP in a tau mutant hamster.
A, Expanded plot of 24 hr neural activity in 1 min bins
from the SCN (from Fig. 5A, double-headed
arrow). The top bar shows wheel-running
activity, plotted as a black bar whenever the wheel
revolved more than once in 6 min. B, Expanded plot of
the concurrent record from the CP (from Fig. 5B,
double-headed arrow). Note the positive
(CP) and negative (SCN)
correlations with wheel-running behavior.
|
|
View larger version (40K):
[in this window]
[in a new window]
|
Figure 11.
Mathematical analysis of the ultradian rhythms
recorded from the SCN and CP in a tau mutant hamster.
A, Data reconstructed by SSA of the 80 min ultradian
rhythms in the SCN (solid line) and the CP
(dotted line) for the first 72 hr of the record.
B, Phase angle difference of the 80 min ultradian
rhythms between the SCN and the CP plotted for 144 hr (see text and
Fig. 4 for details).
|
|
Effects of the tau mutation on the circadian and
ultradian periods of MUA
The period of the rhythm of wheel-running activity in
wild-type hamsters was ~24 hr and closely matched the circadian
component of the electrical activity in the SCN. To assess the effect
of the tau mutation on the rhythmic properties in the SCN,
we obtained four 1-week-long recordings for analysis of the period of
the rhythm in DD. The ~20 hr period of wheel-running rhythms in
tau mutants closely matched the circadian MUA rhythms in the
SCN. There were no significant differences between wild type and
tau mutants in the periods of the ultradian components (80 and 14 min). The variation in frequency among animals within each
genotype was as great as that between genotypes (Table
1).
Effect of wheel running on MUA
Locomotor activity affects the expression of MUA in the SCN and
elsewhere in the brain. MUA in the SCN was decreased during wheel
running, whereas MUA in other areas was enhanced (Figs. 1-3, 5, 7, 8,
10). These changes in the levels of MUA were precisely correlated with
locomotor activity and were more pronounced the more vigorously the
animals ran in their wheels.
Phase of MUA in the BNST
In contrast to MUA from all other recording sites outside of the
SCN, MUA recorded from the anteromedial part of the BNST exhibited
oscillations (circadian and ultradian) in-phase with the SCN (Figs.
12, 13,
14,
15). As seen in the SCN and again in
contrast to that seen at other sites, neural activity in the BNST was
suppressed during wheel running (Figs. 12, 14). We also observed
similar phase relationships in one recording from the posteromedial
part of the BNST of a wild-type animal and from the anteromedial part of the BNST in one tau mutant.
View larger version (39K):
[in this window]
[in a new window]
|
Figure 12.
Neural activity records obtained simultaneously
from the SCN and the BNST in a wild-type hamster in constant darkness.
Electrodes were located in the right ventromedial portion of the
central SCN and in the right anteromedial portion of the BNST.
A, MUA in the SCN in 6 min bins. B, MUA
in the BNST in 6 min bins. C, Wheel revolutions per 6 min. The data marked by the double-headed arrows are
presented below (see Fig. 14). Note the almost perfect phase lock
between these two regions and that both are in antiphase with wheel
running.
|
|
View larger version (22K):
[in this window]
[in a new window]
|
Figure 13.
Mathematical analysis of the phase angle
difference of the circadian rhythms recorded in the SCN and the BNST in
a wild-type hamster (original data in Fig. 12). A,
B, Data reconstructed by SSA for the SCN
(A) and for the BNST (B).
C, Instantaneous phase angle difference between the
circadian rhythms shown in A and B (see
text and Fig. 4 for details).
|
|
View larger version (29K):
[in this window]
[in a new window]
|
Figure 14.
Ultradian rhythms of neural activity recorded
from the SCN and the BNST in a wild-type hamster. A,
Expanded plot of 24 hr neural activity record in 1 min bins from the
SCN (from Fig. 12A, double-headed
arrow). The top bar shows wheel-running
activity, plotted as a black bar whenever the wheel
revolved more than once in 6 min. B, Expanded plot of 24 hr neural activity record in 1 min bins from the BNST (from Fig.
12B, double-headed arrow). Note
that both the 80 and 14 min ultradian rhythms are usually
in-phase.
|
|
View larger version (36K):
[in this window]
[in a new window]
|
Figure 15.
Mathematical analysis of the ultradian rhythms
recorded from the SCN and the BNST in a wild-type hamster.
A, Data reconstructed by SSA of the 80 min ultradian
rhythms in the SCN (solid line) and the BNST
(dotted line) for the first 72 hr of the record.
B, Phase angle difference of the 80 min ultradian
rhythms between the SCN and the BNST plotted for 144 hr (see text and
Fig. 4 for details).
|
|
| |
DISCUSSION |
Circadian rhythms in electrical activity
Inouye and Kawamura (1979) reported that the MUA in the SCN
recorded from freely moving rats displayed a circadian rhythm with peak
impulse frequency occurring during the day. They also recorded MUA
circadian rhythms from regions outside the SCN that exhibited peak
activity at night, out-of-phase with the SCN rhythm and in-phase with
the animal's locomotor activity. Because MUA in the SCN remained
rhythmic after the nucleus was isolated (within a hypothalamic island),
while the rhythms outside of the SCN disappeared, they concluded that
the circadian pacemaker was in the SCN and that rhythms outside the SCN
were being driven (in antiphase) by the SCN (Inouye and Kawamura,
1982). Later, Yamazaki et al. (1994) showed that the circadian rhythm
of ATP content in the SCN of rats is also in antiphase with this
rhythm in the anterior hypothalamus and CP. Our results with hamsters
are in good general agreement with the results in rats. We find that
the circadian rhythms of MUA within the SCN are out-of-phase with those
recorded from brain areas outside the SCN, with the important exception of the BNST, an area from which Inouye and Kawamura did not record.
We found that the period of the circadian rhythm in MUA both within and
outside of the SCN was affected as expected by the tau
mutation and matched the period of wheel-running behavior both in
wild-type hamsters (~24 hr) and in tau mutants (~20 hr). Davies and Mason (1994) reported a circadian electrical activity rhythm
with a period of ~20 hr from tau mutant SCN in acute slice preparation that was monitored for 36 hr. Liu et al. (1997) reported that circadian periodicities of electrical activity in SCN cells dispersed in cell culture from homozygous, heterozygous, and wild-type hamsters exhibit free-running periods that correlate with their genotype. Our results obtained in vivo confirm that the
altered period of neuronal activity is expressed within the SCN of
intact tau mutant hamsters. The correspondence of the
in vivo with the in vitro results provides
important confirmation of the usefulness of the in vitro
model. We know that at least the normal period of the intact SCN is
conserved in the dish.
The genetically determined period of the SCN is also conserved in
transplantation experiments in which the locomotor rhythms restored by
transplanted SCN tissue have the periods determined by the genotype of
the donor not the host (Ralph et al., 1990; Vogelbaum and Menaker,
1992; Silver et al., 1996). However, the data of Silver et al. (1996)
suggest strongly that in the transplant experiments the link between
the transplanted tissue and the host's locomotor system is hormonal
not neural. Therefore, although the several studies of SCN rhythmicity
using in vitro, transplant, and in vivo methods
are consistent, they leave open questions about the functional
connections of the SCN with the motor control system. In particular, it
will be important to determine the roles of both neural and humoral SCN
outputs in controlling locomotor behavior in intact animals.
Ultradian rhythms
MUA from the SCN exhibited two different, clearly discernable
ultradian components after several days in constant darkness. The 80 min ultradian rhythm was out-of-phase with other brain regions (except
the BNST in which all rhythms were always in-phase with those in the
SCN). However, immediately after transfer from LD to DD, the 80 min
rhythms within and outside the SCN were temporarily in-phase. In the
tau mutant, these rhythms sometimes ran independently. This
suggests that 80 min ultradian pacemakers may be located both in and
outside of the SCN and that the light/dark cycle may influence their
phase relationships. A similar ultradian rhythm can be observed in
figures published by Kawamura and Inouye (1979; their Fig. 5) and
Inouye and Kawamura (1982; their Fig. 7), which show data from MUA
recorded in rat within a hypothalamic island containing the SCN as well
as outside of the island. That observation supports the idea that
ultradian periodicities are generated from sites both within and
outside the SCN. Recently, Meijer et al. (1997) found significant
ultradian periods of 4 hr and 170, 130, and 100 min in rat SCN in
vivo and a significant period of 3.5 hr in rat SCN in
vitro. MUA from optic chiasm in hamster and rat (Inouye and
Kawamura, 1979; Omata and Kawamura, 1988) has been reported to contain
circadian components. However, in our recordings we observed only
ultradian rhythms from this site.
The source and mechanism for the generation of ultradian periodicities
within the brain are obscure, and there are many possible candidates
[e.g., in the posterior hypothalamic area of the conscious rat, the
release rates of the catecholamines and histamine fluctuate with the
following periods: histamine, 83 min; dopamine and noradrenaline, 92 min; and adrenaline, 99 min (Dietl et al., 1992; Prast et al., 1992;
Grass et al., 1996)].
Very short (~14 min) ultradian rhythms were present in all brain
regions from which we recorded. Although not observable by our spectral
analysis methods because of limitations in sampling frequency
resolution and signal frequency variability, this periodicity was
easily detectable visually in displays of the recordings. The rhythm
was in-phase among all brain regions. The ~14 min period is
significantly longer than an ultradian periodicity reported previously
by Miller and Fuller (1992), who observed rhythms with periods of
~120 sec that were lengthened by retinal illumination in
urethane-anesthetized rats.
We failed to find any differences in the periods of ultradian rhythms
of tau mutant and wild-type hamsters, even though the circadian periodicity of the tau mutant is shortened by >15
percent. This suggests that the tau mutation may affect
circadian but not ultradian rhythms of MUA. This is in contrast to its
effect on luteinizing hormone pulsatility (Loudon et al., 1994)
and to the effect of mutations in the per gene in
Drosophila that alter the periods of both circadian rhythms
and high-frequency neural rhythms involved in the control of the
courtship song (Kyriacou, 1990). However, our data do suggest that
ultradian rhythms of MUA in tau mutants may have more
variable periods and phase relationships than do those in wild types,
although we are presently unable to quantify this difference.
Bed nucleus rhythmicity
Unexpectedly, and uniquely among all sites in which
recordings have been made, the circadian rhythm of electrical activity in the BNST is in-phase with the SCN electrical activity rhythm. In a previous study Inouye (1983) recorded MUA from seven regions of
the rat brain (not including the BNST), but only the SCN showed a
circadian rhythm that peaked during the day; rhythms from all the other
sites peaked at night. In our recordings, ultradian rhythms in the BNST
were also in-phase with those in the SCN. Cross-spectral estimates
suggest that the BNST and SCN are tightly coupled to each other (data
not shown).
There is anatomical evidence that SCN efferent pathways reach the BNST
(Kalsbeek et al., 1993; Morin et al., 1994). However, it does not
appear that the BNST projects to the SCN (Numan and Numan, 1996). The
BNST may therefore be part of an output pathway from the SCN to
locomotor centers. This would be completely consistent with our data.
The BNST is a complex nucleus with several subdivisions; it has been
reported to be involved in the control of photoperiod measurement
(Raitiere et al., 1995), maternal behavior (Numan and Numan, 1996), and
mating behavior (Wood and Newman, 1993), all of which may be influenced
by the circadian system. Our preliminary data from lesion studies
suggest that the BNST may be involved in controlling the level and
pattern of locomotor activity (Yamazaki et al., 1997).
Effects of locomotor activity on SCN electrical activity
Our data demonstrate that an animal's movements affect electrical
activity in several brain areas. Wheel-running activity acutely
decreased SCN (and BNST) neural activity and enhanced neural activity
outside the SCN (see also Meijer et al., 1997). Although we were not
able to determine the causal relationship involved (i.e., does
increased activity in extra-SCN regions lead to inhibition of SCN
activity or vice versa?), we believe that this finding has great
potential significance. It is intriguing to speculate that reductions
in SCN neural activity associated with locomotor activity may underlie
the "nonphotic" phase shifts of circadian rhythms that are produced
by vigorous wheel running (Reebs and Mrosovsky, 1989).
The work reported here represents a level of analysis of mammalian
circadian organization that has been almost completely neglected since
it was pioneered by Inouye and Kawamura 20 years ago. Technical and
conceptual advances over the past two decades have made it more
tractable, although it is still labor intensive. In spite of the
inherent difficulty of obtaining it, knowledge of the dynamics of
electrical activity in the several brain regions controlling circadian
behavior in intact, unanesthetized animals is likely to be essential
for an understanding of this important regulatory system.
| |
FOOTNOTES |
Received July 29, 1998; revised Sept. 28, 1998; accepted Oct. 1, 1998.
This research was supported by the National Science Foundation (NSF)
Science and Technology Center for Biological Timing along with Air
Force Grants F49620-98-1-0174 to M.M. and F49620-97-1-0012 to G.D.B and
M.M., by the National Institutes of Health postdoctoral National
Research Service Award NS09329 to C.G.H., and by an NSF postdoctoral
fellowship in Biosciences Related to the Environment to M.C.K. We thank
Dr. M. E. Geusz for computer programming for recording neural
activity (for spike discrimination) and Dr. M. Kawasaki for discussing
amplifier circuit design. Also our special thanks to Drs. M. Takahashi
and M. Nishihara for general information on multiunit activity
recording and to Dr. S.-I. T. Inouye for information on electrode design.
We dedicate this work to Professor Hiroshi Kawamura on the occasion of
his 70th birthday (January 26, 1997).
Correspondence should be addressed to Dr. Shin Yamazaki, National
Science Foundation Center for Biological Timing, Department of Biology,
Gilmer Hall, University of Virginia, Charlottesville, VA 22903.
| |
REFERENCES |
-
Bendat JS,
Piersol AG
(1986)
The Hilbert transform.
In: Random data: analysis and measurement procedures, 2nd Edition, pp 484-516. New York: Wiley.
-
Bergman H,
Feingold A,
Nini A,
Raz A,
Slovin H,
Abeles M,
Vaadia E
(1998)
Physiological aspects of information processing in the basal ganglia of normal and Parkinsonian primates.
Trend Neurosci
21:32-38[Web of Science][Medline].
-
Bos NPA,
Mirmiran M
(1990)
Circadian rhythms in spontaneous neuronal discharges of the cultured suprachiasmatic nucleus.
Brain Res
511:158-162[Web of Science][Medline].
-
Davies IR,
Mason R
(1994)
Tau-mutant hamster SCN clock neurons express a 20 h firing rate rhythm in vitro.
NeuroReport
5:2165-2168[Web of Science][Medline].
-
Dietl H,
Prast H,
Philippu A
(1992)
Pulsatile release of catecholamines in the hypothalamus of conscious rats.
Naunyn Schmiedebergs Arch Pharmacol
347:28-33[Web of Science].
-
Edgar DM,
Martin CE,
Dement WC
(1991)
Activity feedback to the mammalian circadian pacemaker: influence on observed measures of rhythm period length.
J Biol Rhythms
6:185-199[Abstract/Free Full Text].
-
Elsner JB,
Tsonis AA
(1996)
In: Singular spectrum analysis: a new tool in time series analysis. New York: Plenum.
-
Fisher NI
(1995)
In: Statistical analysis of circular data. Cambridge, UK: Cambridge UP.
-
Grass K,
Prast H,
Philippu A
(1996)
Influence of mediobasal hypothalamic lesion and catecholamine receptor antagonists on ultradian rhythm of EEG in the posterior hypothalamus of the rat.
Neurosci Lett
207:93-96[Web of Science][Medline].
-
Green DJ,
Gillette R
(1982)
Circadian rhythm of firing rate recorded from single cells in the rat suprachiasmatic brain slice.
Brain Res
245:198-200[Web of Science][Medline].
-
Groos G,
Hendricks I
(1982)
Circadian rhythms in electrical discharge of rat suprachiasmatic neurons recorded in vitro.
Neurosci Lett
34:283-288[Web of Science][Medline].
-
Herzog ED,
Geusz ME,
Khalsa SBS,
Straume M,
Block GD
(1997)
Circadian rhythms in mouse suprachiasmatic nucleus explants on multimicroelectrode plates.
Brain Res
757:285-290[Web of Science][Medline].
-
Inouye S-IT
(1983)
Does the ventromedial hypothalamic nucleus contain a self-sustained circadian oscillator associated with periodic feedings?
Brain Res
279:53-63[Web of Science][Medline].
-
Inouye S-IT,
Kawamura H
(1979)
Persistence of circadian rhythmicity in a mammalian hypothalamic "island" containing the suprachiasmatic nucleus.
Proc Natl Acad Sci USA
76:5962-5966[Abstract/Free Full Text].
-
Inouye S-IT,
Kawamura H
(1982)
Characteristics of a circadian pacemaker in the suprachiasmatic nucleus.
J Comp Physiol [A]
146:153-160.
-
Kalsbeek A,
Teclemariam-Mesbah R,
Pevet P
(1993)
Efferent projections of the suprachiasmatic nucleus in the golden hamster (Mesocricetus auratus).
J Comp Neurol
332:293-314[Web of Science][Medline].
-
Kawamura H,
Inouye S-IT
(1979)
Circadian rhythm in a hypothalamic island containing the suprachiasmatic nucleus.
In: Biological rhythms and their central mechanism (Suda M,
Hayaishi O,
Nakagawa H,
eds), pp 335-341. Amsterdam: Elsevier Science.
-
Klein DC,
Moore RY,
Reppert SM
(1991)
In: Suprachiasmatic nucleus: the mind's clock. New York: Oxford UP.
-
Kyriacou CP
(1990)
The molecular ethology of the period gene in Drosophila.
Behav Genet
20:191-211[Web of Science][Medline].
-
Lehman MN,
Silver R,
Gladstone WR,
Kahn RM,
Gibson M,
Bittman EL
(1987)
Circadian rhythmicity restored by neural transplant: immunocytochemical characterization of the graft and its integration with the host brain.
J Neurosci
7:1626-1638[Abstract].
-
Liu C,
Weaver DR,
Strogatz SH,
Reppert SM
(1997)
Cellular construction of a circadian clock: period determination in the suprachiasmatic nuclei.
Cell
91:855-860[Web of Science][Medline].
-
Loudon ASI,
Wayne NL,
Krieg R,
Iranmanesh A,
Veldhuis JD,
Menaker M
(1994)
Ultradian endocrine rhythms are altered by a circadian mutation in the Syrian hamster.
Endocrinology
135:712-718[Abstract].
-
Marchant EG,
Mistlberger RE
(1996)
Entrainment and phase shifting of circadian rhythms in mice by forced treadmill running.
Physiol Behav
60:657-663[Medline].
-
Meijer JH,
Rietveld WJ
(1989)
Neurophysiology of the suprachiasmatic circadian pacemaker in rodents.
Physiol Rev
69:671-707[Free Full Text].
-
Meijer JH,
Schaap J,
Watanabe K,
Albus H
(1997)
Multiunit activity recordings in the suprachiasmatic nuclei: in vivo versus in vitro models.
Brain Res
753:322-327[Web of Science][Medline].
-
Miller JD,
Fuller CA
(1992)
Isoperiodic neuronal activity in suprachiasmatic nucleus of the rat.
Am J Physiol
263:R51-R58[Abstract/Free Full Text].
-
Moore RY,
Eichler VB
(1972)
Loss of a circadian adrenal corticosterone rhythm following suprachiasmatic nucleus lesions in the rat.
Brain Res
42:201-206[Web of Science][Medline].
-
Morin LP,
Goodless-Sanchez N,
Smale L,
Moore RY
(1994)
Projection of the suprachiasmatic nuclei, subparaventricular zone and retrochiasmatic area in the golden hamster.
Neuroscience
61:391-410[Web of Science][Medline].
-
Mrosovsky N
(1988)
Phase response curves for social entrainment.
J Comp Physiol [A]
162:35-46[Medline].
-
Murakami N,
Takamure M,
Takahashi K,
Utunomiya K,
Kuroda H,
Etoh T
(1991)
Long-term cultured neurons from rat suprachiasmatic nucleus retain the capacity for circadian oscillation of vasopressin release.
Brain Res
545:347-350[Web of Science][Medline].
-
Numan M,
Numan M
(1996)
A lesion and neuroanatomical tract-tracing analysis of the role of the bed nucleus of the stria terminalis in retrieval behavior and other aspects of maternal responsiveness in rats.
Dev Psychobiol
29:23-51[Web of Science][Medline].
-
Omata K,
Kawamura H
(1988)
Effect of methamphetamine upon circadian rhythms in multiple unit activity inside and outside the suprachiasmatic nucleus in the golden hamster (Mesocricetus auratus).
Neurosci Lett
95:218-222[Web of Science][Medline].
-
Prast H,
Dietl H,
Philippu A
(1992)
Pulsatile release of histamine in the hypothalamus of conscious rats.
J Auton Nerv Syst
39:105-110[Web of Science][Medline].
-
Raitiere MN,
Garyfallou VT,
Urbanski HF
(1995)
Lesions in the bed nucleus of the stria terminalis, but not in the lateral septum, inhibit short-photoperiod-induced testicular regression in Syrian hamsters.
Brain Res
705:159-167[Web of Science][Medline].
-
Ralph MR,
Foster RG,
Davis FC,
Menaker M
(1990)
Transplanted suprachiasmatic nucleus determines circadian period.
Science
247:975-978[Abstract/Free Full Text].
-
Reebs SG,
Mrosovsky N
(1989)
Effects of induced wheel running on the circadian activity rhythms of Syrian hamsters: entrainment and phase response curve.
J Biol Rhythms
4:39-48[Abstract/Free Full Text].
-
Rusak B,
Zucker I
(1979)
Neural regulation of circadian rhythms.
Physiol Rev
59:449-526[Free Full Text].
-
Sawaki Y,
Nihonmatsu I,
Kawamura H
(1984)
Transplantation of the neonatal suprachiasmatic nuclei into rats with complete bilateral suprachiasmatic lesions.
Neurosci Res
1:67-72[Medline].
-
Shibata S,
Moore RY
(1988)
Electrical and metabolic activity of suprachiasmatic nucleus neurons in hamster hypothalamic slices.
Brain Res
438:374-378[Web of Science][Medline].
-
Shinohara K,
Honma S,
Katsno Y,
Abe H,
Honma K
(1995)
Two distinct oscillators in the rat suprachiasmatic nucleus in vitro.
Proc Natl Acad Sci USA
92:7396-7400[Abstract/Free Full Text].
-
Shioiri T,
Takahashi K,
Yamada N,
Takahashi S
(1990)
Motor activity correlates negatively with free-running period, while positively with serotonin contents in SCN in free-running rats.
Physiol Behav
49:779-786.
-
Silver R,
LeSauter J,
Tresco PA,
Lehman MN
(1996)
A diffusible coupling signal from the transplanted suprachiasmatic nucleus controlling circadian locomotor rhythms.
Nature
382:810-813[Medline].
-
Stephan FK,
Zucker I
(1972)
Circadian rhythms in drinking behavior and locomotor activity of rats are eliminated by hypothalamic lesions.
Proc Natl Acad Sci USA
69:1583-1586[Abstract/Free Full Text].
-
Thomson DJ
(1982)
Spectrum estimation and harmonic analysis.
Proc IEEE
70:1055-1096.
-
Turek FW
(1985)
Circadian neural rhythms in mammals.
Annu Rev Physiol
47:49-64[Web of Science][Medline].
-
van Reeth O,
Losee-Olson S,
Turek FW
(1987)
Phase shifts in the circadian activity rhythm induced by triazolam are not mediated by the eyes or the pineal gland in the hamster.
Neurosci Lett
80:185-190[Web of Science][Medline].
-
Vautard R,
Yiou P,
Ghil M
(1992)
Singular-spectrum analysis: a toolkit for short, noisy chaotic signals.
Physica D
58:95-126.[Web of Science]
-
Vogelbaum MA,
Menaker M
(1992)
Temporal chimeras produced by hypothalamic transplants.
J Neurosci
12:3619-3627[Abstract].
-
Watanabe K,
Koibuchi N,
Ohtake H,
Yamaoka S
(1993)
Circadian rhythms of vasopressin release in primary cultures of rat suprachiasmatic nucleus.
Brain Res
624:115-120[Web of Science][Medline].
-
Welsh DK,
Logothetis DE,
Meister M,
Reppert SM
(1995)
Individual neurons dissociated from rat suprachiasmatic nucleus express independently phased circadian firing rhythms.
Neuron
14:697-706[Web of Science][Medline].
-
Wichmann T,
Vitek JL,
DeLong MR
(1995)
Parkinson's disease and the basal ganglia: lessons from the laboratory and from neurosurgery.
The Neuroscientist
1:236-244.
-
Wood RI,
Newman SW
(1993)
Mating activates androgen receptor-containing neurons in chemosensory pathways of the male Syrian hamster brain.
Brain Res
614:65-77[Web of Science][Medline].
-
Yamada N,
Shimoda K,
Ohi K,
Takahashi S,
Takahashi K
(1988)
Free-access to a running wheel shortens the period of free-running rhythm in blinded rats.
Physiol Behav
42:87-91[Medline].
-
Yamada N,
Shimoda K,
Takahashi K,
Takahashi S
(1990)
Relationship between free-running period and motor activity in blinded rats.
Brain Res Bull
25:115-119[Web of Science][Medline].
-
Yamazaki S,
Ishida Y,
Inouye S-IT
(1994)
Circadian rhythms of adenosine triphosphate contents in the suprachiasmatic nucleus, anterior hypothalamic area and caudate putamen of the rat: negative correlation with electrical activity.
Brain Res
664:237-240[Web of Science][Medline].
-
Yamazaki S,
Alones VE,
Block GD,
Menaker M
(1997)
Functional connection between the circadian and motor systems.
Soc Neurosci Abstr
23:790.
Copyright © 1998 Society for Neuroscience 0270-6474/98/182410709-15$05.00/0
This article has been cited by other articles:
|
|
|
|
 
I. N. Karatsoreos and R. Silver
Minireview: The Neuroendocrinology of the Suprachiasmatic Nucleus as a Conductor of Body Time in Mammals
Endocrinology,
December 1, 2007;
148(12):
5640 - 5647.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
T. M. Brown, A. T. Hughes, and H. D. Piggins
Gastrin-Releasing Peptide Promotes Suprachiasmatic Nuclei Cellular Rhythmicity in the Absence of Vasoactive Intestinal Polypeptide-VPAC2 Receptor Signaling
J. Neurosci.,
November 30, 2005;
25(48):
11155 - 11164.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
W. Nakamura, S. Yamazaki, N. N. Takasu, K. Mishima, and G. D. Block
Differential Response of Period 1 Expression within the Suprachiasmatic Nucleus
J. Neurosci.,
June 8, 2005;
25(23):
5481 - 5487.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
S. J. Aton, G. D. Block, H. Tei, S. Yamazaki, and E. D. Herzog
Plasticity of Circadian Behavior and the Suprachiasmatic Nucleus Following Exposure to Non-24-Hour Light Cycles
J Biol Rhythms,
June 1, 2004;
19(3):
198 - 207.
[Abstract]
[PDF]
|
|
|
|
|
|
|
S. Amir, E. W. Lamont, B. Robinson, and J. Stewart
A Circadian Rhythm in the Expression of PERIOD2 Protein Reveals a Novel SCN-Controlled Oscillator in the Oval Nucleus of the Bed Nucleus of the Stria Terminalis
J. Neurosci.,
January 28, 2004;
24(4):
781 - 790.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
J. E. Quintero, S. J. Kuhlman, and D. G. McMahon
The Biological Clock Nucleus: A Multiphasic Oscillator Network Regulated by Light
J. Neurosci.,
September 3, 2003;
23(22):
8070 - 8076.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
S. Yamazaki, V. Alones, and M. Menaker
Interaction of the Retina with Suprachiasmatic Pacemakers in the Control of Circadian Behavior
J Biol Rhythms,
August 1, 2002;
17(4):
315 - 329.
[Abstract]
[PDF]
|
|
|
|
|
|
|
M. Abe, E. D. Herzog, S. Yamazaki, M. Straume, H. Tei, Y. Sakaki, M. Menaker, and G. D. Block
Circadian Rhythms in Isolated Brain Regions
J. Neurosci.,
January 1, 2002;
22(1):
350 - 356.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. P. Pando and P. Sassone-Corsi
Signaling to the Mammalian Circadian Clocks: In Pursuit of the Primary Mammalian Circadian Photoreceptor
Sci. Signal.,
November 6, 2001;
2001(107):
re16 - re16.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
K.-A. Stokkan, S. Yamazaki, H. Tei, Y. Sakaki, and M. Menaker
Entrainment of the Circadian Clock in the Liver by Feeding
Science,
January 19, 2001;
291(5503):
490 - 493.
[Abstract]
[Full Text]
|
|
|
|
|
|
|
C. M. Novak, L. Smale, and A. A. Nunez
Rhythms in Fos expression in brain areas related to the sleep-wake cycle in the diurnal Arvicanthis niloticus
Am J Physiol Regulatory Integrative Comp Physiol,
May 1, 2000;
278(5):
R1267 - R1274.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
N. C Aggelopoulos and H. Meissl
Responses of neurones of the rat suprachiasmatic nucleus to retinal illumination under photopic and scotopic conditions
J. Physiol.,
February 15, 2000;
523(1):
211 - 222.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
J. Rutter, M. Reick, L. C. Wu, and S. L. McKnight
Regulation of Clock and NPAS2 DNA Binding by the Redox State of NAD Cofactors
Science,
July 20, 2001;
293(5529):
510 - 514.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
Top
Abstract
Introduction
