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Vigilance states, EEG spectra, and cortical temperature in the guinea pig

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Vigilance states, electroencephalogram (EEG) power spectra (0.25-25.0 Hz), and cortical temperature (TCRT) were obtained in nine guinea pigs for 24 h in a 12:12-h light-dark (LD 12:12) schedule. Sleep was markedly polyphasic and fragmented and amounted to 32% of recording time, which is a low value compared with sleep in other rodents. There was 6.8% more sleep in the light period than in the dark period. EEG power density in non-rapid eye movement (NREM) sleep showed no significant temporal trend within the light or the dark period. The homeostatic aspects of sleep regulation, as proposed in the two-process model, can account for the slow-wave activity (SWA) pattern also in the guinea pig: The small 24-h amplitude of the sleep-wakefulness pattern resulted in a small, 12% decline of SWA within the light period. In contrast to more distinctly nocturnal rodents, SWA in the dark period was not higher than in the light period. TCRT showed no difference between the light and the dark period. TCRT in REM sleep and waking was higher than TCRT in NREM sleep. TCRT increased after the transition from NREM sleep to either REM sleep or waking, and decreased in the last minute before the transition and after the transition from waking to NREM sleep. Motor activity measured in six animals for 11 days in constant darkness showed no apparent rhythm in three animals and a significant circadian rhythm in three others. Our data support the notion that guinea pigs exhibit only a weak circadian rest-activity rhythm.
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264:1125-1132, 1993. Am J Physiol Regul Integr Comp Physiol
I. Tobler, P. Franken and K. Jaggi
temperature in the guinea pig
Vigilance states, EEG spectra, and cortical
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Vigilance states, EEG spectra, and cortical temperature
in the guinea pig
IRENE TOBLER, PAUL FRANKEN, AND KARIN JAGGI
Institute
of
Pharmacology, University
of
Ziirich, CH-8006 Ziirich, Switzerland
Tobler, Irene, Paul Franken, and Karin Jaggi.
Vigi-
lance states, EEG spectra, and cortical temperature in the
guinea pig.
Am. J. Physiol. 264 (Regulatory Integrative Comp.
Physiol.
33): RI 125-R1132, 1993.-Vigilance states, electroen-
cephalogram (EEG) power spectra
(0.25-25.0
Hz), and cortical
temperature (T oRT) were obtained in nine guinea pigs for
24
h
in a 12:12-h light-dark (LD
12:12)
schedule. Sleep was markedly
polyphasic and fragmented and amounted to 32% of recording
time, which is a low value compared with sleep in other rodents.
There was 6.8% more sleep in the light period than in the dark
period. EEG power density in non-rapid eye movement
(NREM) sleep showed no significant temporal trend within the
light or the dark period. The homeostatic aspects of sleep reg-
ulation, as proposed in the two-process model, can account for
the slow-wave activity (SWA) pattern also in the guinea pig:
The small 24-h amplitude of the sleep-wakefulness pattern re-
sulted in a small, 12% decline of SWA within the light period. In
contrast to more distinctly nocturnal rodents, SWA in the dark
period was not higher than in the light period. TCRT showed no
difference between the light and the dark period. TCRT in REM
sleep and waking was higher than TCRT in NREM sleep. TCRT
increased after the transition from NREM sleep to either REM
sleep or waking, and decreased in the last minute before the
transition and after the transition from waking to NREM sleep.
Motor activity measured in six animals for
11
days in constant
darkness showed no apparent rhythm in three animals and a
significant circadian rhythm in three others. Our data support
the notion that guinea pigs exhibit only a weak circadian rest-
activity rhythm.
electroencephalogram spectral analysis; slow-wave activity; cor-
tical temperature; circadian rhythm
MAMMALS DIFFER LARGELY
in their total amount of
sleep and in the distribution of sleep and wakefulness
within 24 h (32). Rodents especially exhibit high
amounts of sleep compared with species belonging to
other orders. Electroencephalogram (EEG) spectral
analyses performed in mammals with a distinct prefer-
ence for sleep in the light (rat: Refs. 9, 39; Syrian ham-
ster: Ref. 36) or dark period (Siberian chipmunk: Ref. 5;
human: Ref. 4) have shown a high initial value of EEG
slow-wave activity (SWA; power density in the 0.75-4.0
Hz band) that decreases in the course of the main sleep
period. In addition, prolonged waking is followed by an
increase in total sleep time (TST) and the initial values
of SWA (2,6,9,33,34), supporting the assumption that
SWA can be taken as an indicator for non-rapid eye
movement (NREM) sleep intensity
(1).
The two-process
model of sleep regulation postulates that sleep propen-
sity is determined by the interaction of a homeostatic
(process S)
and a circadian process. In humans and rats,
the time course of
process S,
which increases during
waking and declines during sleep (7, l4), has been de-
rived from SWA within NREM sleep. In the cat
(19,38)
and rabbit (37), where only a small preference for sleep
occurs in the light period, it can be assumed that
process
S increases only a little within the active period. Ac-
cordingly, in these species SWA showed no marked
trend within sleep
(19, 37, 38).
There is considerable controversy in the literature re-
garding the 24-h distribution of sleep and waking and
the presence of a circadian rest-activity or sleep-wake
rhythm in the guinea pig. Rest-activity recordings re-
vealed:
1)
only a small predominance of activity in the
light period
(14)
or the dark period (3, 3l), and 2) no
predominance for either lighting period (21). In con-
stant darkness (DD) or in constant light (LL), activity
of individuals or groups was evenly distributed over the
24 h
(21))
whereas guinea pigs living in a seminatural
environment were diurnal (e.g., 25, 29), or crepuscular
(10, 17, 29).
Polysomnographic determinations of the
vigilance states for 24 h indicated that there is neither a
diurnal nor a nocturnal preference for sleep in animals
living under a natural light-dark (LD) cycle
(15, 27)
or
under artificial LD
12: 12 (13).
Moreover, there is general
agreement that the sleep-wakefulness pattern is mark-
edly polyphasic and fragmented. Daily variations were
reported in some physiological variables recorded either
under LD
12:12
(plasma cortisol levels, Ref.
11;
melato-
nin levels in the retina, Ref. 23; respiratory measures,
Ref.
31)
or under LL (blood histamine response, Ref.
30). The recordings of multiple unit activity (MUA) in
the nucleus suprachiasmaticus (SCN), lasting for up to
30 days, showed a distinct 24-h oscillation of cells within
the SCN with a trough in MUA within the 12-h dark
period (18). A reversed phase with a smaller amplitude
was found in MUA recorded outside the SCN, whereas
behaviors such as motor activity and sleep-wakefulness
did not show a consistent nocturnal or diurnal pattern in
LD 12:12 or a 12-h or 24-h rhythm in DD.
In the rat it has been shown that brain temperature
undergoes a prominent 24-h modulation (6). Typically
temperature decreases at the onset of NREM sleep
and remains at a lower level than in waking. Upon en-
tering REM sleep or waking, temperature increases (e.g.,
rat: Ref. 22; cat: Ref. 24; rabbit: Ref. 16; kangaroo rat:
Ref. 12).
Taken together, the guinea pig may differ in several
aspects from species belonging to the same order. De-
tailed sleep studies and 24-h temperature recordings
are lacking. Thus our aim was to determine simulta-
neously the 24-h sleep-wakefulness pattern and brain
temperature and to analyze the EEG within the vigi-
lance states by spectral analysis.
METHODS
Animals.
Adult male guinea pigs
(Cavia porcellus; n = 9)
of
the 1bm:GOHI strain with an initial mean weight of 429.3 t 44.7
(SE) g were used. The animals were housed individually in
transparent Plexiglas cages [38
X
26 (ground floor)
X
28 cm]
placed in sound-attenuated chambers. Food and water were
available ad libitum. The animals were maintained in LD 12:12
0363-6119/93 $2.00 Copyright 0 1993 the American Physiological Society
R1125
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SLEEP AND CORTICAL TEMPERATURE IN THE GUINEA PIG
(light at
0900-2100
h; daylight-type fluorescent tubes, 18 W,
~350 lx) at an ambient temperature of 22.2-22.9”C for several
weeks before surgery. Implantation of EEG and electromyo-
gram (EMG) electrodes and a thermistor was performed under
deep pentobarbital sodium anesthesia (50 mg/kg ip) at least
11
days before the experiment. Two gold-plated round-tip minia-
ture screws
(1.19
mm diam) served as EEG electrodes and were
screwed through the skull onto the dura over the right parietal
cortex and the cerebellum. Two gold wires (0.2 mm diam) were
inserted into the neck muscles to record the EMG. A thermistor
(1.5-2.0 mm diam; 0.2”C accuracy; 0.005”C resolution) was
placed epidurally over the left parietal cortex to record cortical
temperature (T CRT). Adaptation to flexible, counterbalanced
recording leads occurred for 48 h until the beginning of the
recording.
Data acquisition and analysis.
The EEG, EMG, and TcItT
were continuously recorded for 1
(n = 6)
or 2 days
(n = 3)
(for
T
CRT, n
= 7) and were subsequently analyzed for 8-s epochs. For
each 8-s epoch, EEG spectra in the range of 0.25-25.0 Hz and
the integrated full-wave rectified EMG were computed as de-
scribed previously (6). Synchronization between the EEG re-
cordings and TCnT measures was achieved by a time signal
generated by the computer every time an 8-s TCnT value was
stored. The vigilance states waking, NREM sleep, and REM
sleep were determined on the basis of the EEG and EMG
records. Waking was scored when the integrated EMG was high
and the EEG power density in the delta band (0.75-4.0 Hz) was
low. In NREM sleep the EMG activity was low and power
density in the delta and theta (6.25-9.0 Hz) band was increased.
The amount of the vigilance states was very similar in
days 1
and 2
[n
= 3;
day
1 and
day 2:
NREM sleep, 25.9 t 3.8 (SE) and
25.7 t 2.5%; REM 1 s eep, 4.9 t 0.8 and 4.8 t 0.9%]. The further
analyses of these animals were based on
day 2.
The behavioral
correlates of REM sleep in the guinea pig have been extensively
described (26, 28). A first phase in which muscle activity begins
to decline (30-40 s) is usually but not always followed by a
second phase with atonia of the neck muscles and occasional
twitches of the ear muscles. REM sleep was scored when the
integrated EMG was lower than in NREM sleep (with the ex-
ception of activity due to twitches), power density values in the
delta band were between those of NREM sleep and waking, and
theta activity was high (see also Fig. 5).
The duration and frequency of NREM sleep, REM sleep, and
waking episodes (Table 2) were determined by the following
criteria: A REM sleep episode was terminated if followed by
three consecutive 8-s epochs of waking or NREM sleep. Shorter
interruptions were allowed if the total did not exceed nine 8-s
epochs. REM sleep episodes consisting of a single 8-s epoch
were disregarded. The termination criteria of a NREM sleep
episode were three consecutive REM sleep epochs or seven con-
secutive epochs not scored as NREM sleep. NREM sleep was
terminated also if a total of 30 waking and/or REM sleep epochs
occurred. Waking episodes were terminated by three consecu-
tive NREM sleep epochs or if a total of 30 nonwaking epochs
occurred.
To determine the changes of TCnT at vigilance state transi-
tions, intervals with a duration of 4 min [waking - NREM sleep
(WN) and NREM sleep - waking (NW)] and 200 s [NREM
sleep - REM sleep (NR) and REM sleep - waking (RW)] were
selected by the following criteria: In the interval preceding the
transitions NW, NR, and WN, 75% or more had to be scored as
NREM sleep or waking, or in the RW transition, 70% as REM
sleep, and not more than two epochs of the subsequent state
were allowed. Similarly, after the transitions WN, NW, and
RW, 75% or more had to be scored as NREM sleep or waking,
or after NR, 70% as REM sleep. Furthermore, three 8-s epochs
before and after a transition had to belong to the vigilance state
corresponding to the transition. The criteria for the length of
NR and RW transitions differed from WN and NW transitions
because of the low frequency and short duration of REM sleep
episodes (see Table 2). The effect of the LD period and time on
the change in T CRT was examined for each transition by two-
way analysis of variance (ANOVA) with the factors “LD-peri-
od” (light vs. dark) and “time” (16-s intervals). If significance of
P < 0.05 was reached, contrasts were tested with the paired t
test.
Motor activity recordings.
After the sleep recordings, the an-
imals were transferred to different chambers for motor activity
recordings. They were exposed to the same LD 12:12 schedule as
before (light at 0900-2100 h; 60-130 lx; 7 W) for 7
(n = 3)
or 20
days
(n
= 6). The second group was then exposed to DD for 11
days. Ambient temperature varied between 22.5 and 24.O”C.
Food and water were available ad libitum. Cages were changed
and food and water were provided twice a week at random times
of the light period or in the subjective active phase in DD.
Motor activity was detected by an infrared sensor (type
ZE2152,
Optex OP-06B) located over the cage, which reacted to changes
in heat radiation due to movements of the animals that were
counted for I-min intervals and stored on a PC once every 24 h.
The sensitivities of the sensors were adjusted individually so
that activity values could vary between 0 and 190 counts/min.
The calibration was performed with a rotating light bulb (0.5 W;
20 rotations/min resulted in 129 counts/min). The presence of
circadian rhythmicity in the last 6 days in
DD
was determined
by periodogram analysis.
RESULTS
Vigilance states.
Sleep amounted to
32.2%
of
24
h, i.e.,
7.7
h (Table
1).
There was a small predominance of
NREM sleep and REM sleep in the light period (P <
0.003, ANOVA for 12-h intervals; Fig. 2). Sleep was at a
relatively constant level in the first 10 h of the light
period and was decreased in the last 2-h interval of the
light period and the first 2-h interval of the dark period.
The lowest values for sleep were reached in the first hour
after lights off and the last hour before lights on (data for
l-h intervals are not shown). The sleep pattern was mark-
edly polyphasic and fragmented: both NREM sleep and
REM sleep episodes were short, lasting not more than 4
and
1.5
min, respectively, whereas waking episodes lasted
for more than 38 min (Fig. 1, Table 2). The frequency and
duration of REM sleep and waking episodes and the fre-
quency of NREM sleep episodes did not differ between
the light and the dark period, whereas the duration of
NREM sleep episodes was slightly but significantly
longer in the light period (Table 2). The fragmentation of
sleep was assessed by counting the number of brief awak-
enings (nBA; Table 2). A BA was defined as a waking
episode with a duration of one or two 8-s epochs within
TST. The nBA did not differ significantly between the
light and the dark period (paired
t
test, 2-tailed).
Cortical temperature.
ToRT was not different in the
light and the dark period, either overall (Fig. 2) or within
the vigilance states (Fig. 3). The comparison of mean
values for 2-h intervals showed that ToRT was invariably
higher in waking and REM sleep than in NREM sleep,
with the exception of the first 2-h after dark onset where
TCRT in waking was higher than in the other two states.
TCRT at the transitions between vigilance states is il-
lustrated in Fig. 4. No significant differences were present
between the curves for the light and the dark period,
whereas the ANOVA for the factor “time” was significant
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SLEEP AND CORTICAL TEMPERATURE IN THE GUINEA PIG
R1127
Table 1.
Vigilance states and cortical temperature computed for 6-, 12-, and 24-h intervals
Hours
% of Recording Time
Waking NREMS
REMS
REMS/TST
?xT, “C
O-6
6-12
O-12
12-18
18-24
12-24
O-24
62.5kl.7
66.2t2.2
64.3kl.8
72.9tl.9
69.4kl.3
7l.ltl.3*
67.8tl.2
Light period
31.2tl.2 6.3t0.8 16.2tl.6 37.36t0.14
27.2tl.5
6.6t0.6 18.8tl.2 37.40t0.15
29.3tl.3
6.4t0.6 17.8tl.l 37.38t0.14
Dark period
23.1tl.6 4.3t0.6 15.Ok2.0 37.45t0.14
25.8tl.2
4.8t0.7 15.lt2.1 37.42t0.14
24.5tl.l*
4.4&0.6* 15.Otl.9 37.44t0.14
Total
26.8tl.l 5.4t0.4 16.4kl.l
37.4lt0.14
Values are means t SE; n = 9 animals; n = 7 animals for cortical temperature (T CRT). REMS, rapid eye movement sleep; NREMS, non-rapid
eye movement sleep. REMS is also expressed as a percentage of total sleep time (REMS/TST). * P < 0.05; comparison between the light and dark
period; Z-tailed paired t test.
for all transitions (P < 0.0001). Typically, at the WN
many frequencies. Thus power density in NREM sleep
transition, a decrease in T
was higher than that of waking and REM sleep in
CRT occurred before the tran-
sition and T
most frequencies, whereas REM sleep differed from wak-
CRT continued to decline after the onset of
NREM sleep. Before the NW and NR transitions ToRT
was at a relatively constant level ., and after the transition
ToRT increased a s
mall extent in waking an .d more steeply
in REM sleep. After the RW transition ToRT decreased.
EEG power spectra.
The relative power spectrum dis-
tribution in NREM sleep and REM sleep was very similar
between the light and the dark period (Fig. 5). Small
differences were found in the waking spectrum
over a
large frequency range. The vigilance- states differed in
periodogram analysis, whereas the other three individuals
exhibited significant peaks (P c 0.001) at 23.4 h, 15.4 h,
and 7.7 h; 22.2 h and 24.5 h; and 23.2 h, 15.4 h, and 7.7 h
(Fig.
8, right, guinea pig
09, where in DD the period
shorter than 24 h is clearly visible).
DISCUSSION
Vigilance states.
The amount of sleep
(32%)
was similar
to the one reported in other studies (28.0%: Ref. 27;
pared with other rodents recorded in a similar experimen-
34.7%: n =
tal set up (e.g., rat: 11.5 h, Refs. 6, 35; Syrian hamster:
15, Ref. 13; 27.5-52.5%:
n
= 2, the higher
value after prolonged habituation, Ref. 15). Thus, com-
15.5 h, Ref. 36; Siberian chipmunk: 12.2 h, Ref. 6; for
ing in the lower
theta range.
frequencies of the spectrum and in the
The time course of EEG power density in NREM sleep
showed no effect of time within either of the lighting
periods in any of the 30 single frequency bands (ANOVA,
factor time on the basis of 2-h intervals; Fig. 6) or for
SWA or high frequency EEG activity (HFA; power den-
sity in the 10.0-25.0 Hz band; Fig. 2). The computation
over the entire 24-h baseline revealed a significant effect
of time for both SWA activity and HFA (P < 0.0001;
ANOVA for 2-h intervals). There was a gradual decline of
SWA over the entire 24 h: The first three 2-h values for
SWA and for HFA differed significantly from the respec-
tive last three values (P < 0.05; Duncan’s multiple range
review see Ref. 32), the guinea pig exhibits the
amount of sleep.
smallest
Sleep was markedly fragmented. This was reflected in
the short NREM sleep episodes, which rarely exceeded 4
min, and in the large nBA (32.3 and 36.1 compared with
15.3 and 16.9 in the light and dark period in the rat; Ref.
6). In the rat, which is distinctly nocturnal, a mean du-
ration of NREM sleep episodes of 3.8 min was obtained
in the dark period (8), which is similar to the values
obtained in the guinea pig both in the light and the
dark period.
The duration of REM sleep episodes (1.6 min) was in
accordance with prior studies (1.8 min: Refs. 20, 27; 1.2
min: Ref. 15). Although the guinea pig slept little com-
test). The overall decline of SWA within the 24 h was pared with other rodents, the relative REM sleep percent-
most marked in four individuals (first 2-h interval vs. last
age of total sleep (16.4%) is similar to the one in the rat
2-h interval: 123.2 vs. 80.4%), whereas it was small and (18.2%; Ref. 6). In the rat, where identical criteria for
not significant in five individuals (107.7 vs. 83.3%). REM sleep episode duration had been applied, a mean
Motor activity.
Mean activity per hour
(n
= 3 for 7 duration of 1.7 min was obtained (8). This comparison
days;
n
= 6 for 19 days) in the 12-h light period was 40.1 indicates that different rodent species may be less flexible
+ 1.7 (arbitrary units) and in the dark period was 30.4 t - in the ratio of REM sleep to NREM sleep than for the
2.7 (SE) (P < 0.001; paired
t
test, Ztailed). Motor activ-
amounts of REM sleep and NREM sleep.
ity within the light period exhibited two peaks, one at the
Diurnal variations.
Most measures showed a small di-
beginning and one at the end of the light period (Figs. 7 urnal variation. A preference for sleep (only 6.8% more
and 8), whereas in the dark, with the exception of the first
than in the dark period) and slightly longer NREM sleep
hour, where activity was still high, activity remained at a episodes were found in the light period. There was no
relatively low, constant level. The activity records of
evidence for a diurnal variation in ToRT (Figs. l-4). The
three animals showed a complete absence of a circadian differences in T
CRT within the vigilance states and in the
rhythm in DD (e.g., Fig. 8,
left),
which was confirmed by vigilance-state transitions were similar to those recorded
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RI128
SLEEP AND CORTICAL TEMPERATURE IN THE GUINEA PIG
Table 2.
Episode frequency and duration of the three
vigilance states, NREMS, REMS and waking,
and brief awakenings
NREMS REMS Waking BA/TST
12-h light period
Frequency,
62.8t2.4
29.1t2.4 86.4t3.4 32.3k3.8
episodes/l2 h
Duration, min 3.9t0.2* 1.6tO.l 38.1t2.3
12-h dark period
Frequency, 62.1t3.9 23.1k3.5 89.8t7.1 36.1k3.8
episodes/l2 h
Duration, min
3.5t0.2 1.4tO.l 42.4t3.5
Values for the vigilance states are 12-h means t, SE; n = 9 animals;
the brief awakenings (BA) are expressed per hour of TST. Significant
differences between the light and the dark period: * P < 0.02, paired t
test, 2-tailed.
in the rat (7, 8). In the rat several transitions differed
between the light and the dark period, whereas in the
guinea pig all transitions were the same in both lighting
periods. In contrast to the polysomnographic data, where
waking was more prominent in the dark period, motor
activity showed a small predominance in the light period
38.0
4
9 I I
II ii I I I I I Y
0
4
8
12 16 20 24
HOURS
Fig. 2. Vigilance states, cortical temperature, and EEG parameters. Val-
ues are means t SE; n = 9 animals. Top
panels:
curves connect mean
hourly values of non-REM sleep and REM sleep, and of cortical tem-
perature. Bottom
panels:
EEG SWA in non-REM sleep (power density
in the frequency band 0.75-4.5 Hz) and high-frequency activity (HFA;
10.0-25.0 Hz). Curves connect mean values of 2-h intervals expressed as
percentage of the mean 24-h value of the corresponding frequency band
(=lOO%). The 12:12-h light-dark cycle is indicated by the vertical line
and the black bar.
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SLEEP AND CORTICAL TEMPERATURE IN THE GUINEA PIG
R1129
g37.50
if
;i
037.25
F:
\
1
- NREMS
----- REMS
----II-----
W
N-R
W-R
W-
III I I I I I I I I I I
N
- 12-h LIGHT PERIOD
-m-- 12-h DARK PERIOD
is
s
0
n 1.0
$
nnf
TIME OF DAY
Fig. 3. Cortical temperature in the three vigilance states, NREMS,
REMS, and W. Curves connect mean values for Z-h intervals (n = 7
animals). Lines at the bottom indicate significant differences between
the states (P
c
0.05; two-tailed paired t test; SE varied between 0.13 and
0.17”C).
and a large individual variation (Fig. 7). Because the an-
imals were more isolated in these boxes they may have
been more sensitive to the LD/DL transitions. The prom-
inence of activity in the light period was, as in the study
of Jilge
(14),
largely determined by a distinct bimodal
pattern (Fig. 8), with activity peaks occurring after lights
on and before lights off. Prominent effects of the changes
in lighting have been previously reported for the guinea
pig (3, 18) and are a well known phenomenon in many
species. Kurumiya and Kawamura (18), who found also a
bimodal activity pattern, exposed the animals to a light
intensity of - 100 lx, which is comparable to the intensity
in our activity boxes. The pattern of animals in outdoor
conditions closely resembles the patterns of our animals
in isolation. Thus activity protocols obtained in summer
in a colony of guinea pigs living in an open-air pen re-
vealed the highest number of active animals after the
beginning and before the end of the natural light period
(lo), i.e., they exhibited the crepuscular pattern, which is
typical for many species exposed to natural light-dark
beg&rig of the major rest period have been interpreted
by assuming an accumulation of S in the preceding active
period. Thus, in species with a large amount of waking in
one lighting period (e.g., humans, rats, Syrian hamsters,
Siberian chipmunks), process S becomes high in the main
activity period and is dissipated in the subsequent period
in which sleep predominates
(4,7,35,39).
For example, in
the rat there is 42% more waking in the dark period than
in the light period and an overall decline of SWA within
the light period of -60% (35).
o*15’W
,
N
-N W N
R
W
0.10 -
I
0.05 -
I
000 -
1
r’
1’
*
-0.05 -
\
\,
-0.10 -
?
-0.15-j ,
I
+I I 1 r
I
-2 0 2 -2 0 2 -2 0 2 -2 0
2 tion of waking over 24 h results in a constant level of
TIME (mid
process S, and therefore of SWA. In accordance with this
Fig. 4. Changes in T CRT in the 2 min before and 2 min after (-2 to 2)
prediction, the small predominance of waking in the dark
vigilance state transitions (W, N, and R). Curves connect 16-s mean
period in the guinea pigs was accompanied by a small
values (n = 7 animals), calculated for the 12-h light and the 12-h dark
period. All values are expressed as the difference from the temperature
decline of SWA of
-8.4%
within the light period (Fig. 2).
at the transition (horizontal reference line at O”C, vertical reference line
Similar patterns have been found in other mammalian
at 0 min). No significant differences were found between the curves of
species in which only a small preference for sleep was seen
the light and the dark period (paired t test).
in one of the lighting periods (cat: 5.2%, Refs. 19, 38;
The two-process model predicts that an even distribu-
D -
B -
11,,,,,,, ,,,, ,111 ,111
L vs. D -
-
i”“(““l”“1”“~““~
i
0
5
10
15 20
25
Hz
Fig. 5. Spectral distribution of EEG power density during waking,
NREMS, and REMS computed separately for the 12-h light (L) and
12-h dark (D) period (n = 9 animals). Values are plotted at the upper
limits of each bin. The curves represent logarithms of power densities
(pV2/H2). Lines below the abscissa indicate the frequency bands for
which the vigilance states differ significantly (P c 0.05; paired t test,
2-tailed).
transitions. In contrast, the guinea pigs recorded in LD
12:12 by Buttner and Wollnik (3) were dark active, with
a prominent activity peak after lights off and a secondary
peak 8 h later, but no measure for the light intensity was
provided. The discrepancies in the light-dark preference
could be due to differences in the light intensity, other
environmental factors, individual differences, and record-
ing methods. In DD we obtained marked individual vari-
ations, thus some animals had a distinct free-running
circadian rhythm, whereas others were arrhythmic.
EEG poever spectra. According to the two-process
model of sleep regulation a homeostatic process S builds
up during waking and is dissipated during sleep (4). S WA
in NREM sleep was taken as a measure for the level of S.
The high values of SWA found in several species at the
Tcrt (&I
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R1130
SLEEP AND CORTICAL TEMPERATURE IN THE GUINEA PIG
12-h LIGHT PERIOD
12-h DARK PERIOD
$80+
iti
E
. 2
s
607 ~1~~. .v.r,....,.... . ...> -+.. . . . . .,.. . . . . . . ..J
I
I
I
0
a,
0 5 lb
Ik
20 2b
0
5
IO
15
20 25 Hz
Fig. 6. Spectral distribution of relative EEG power density in NREM sleep computed for consecutive 2-h intervals.
Curves connect mean values (n = 9 animals) of the 12-h light period (Left) and the 12-h dark period (right); plotted for
0.5 or l.O-Hz bins. For each animal the mean value of the first 2 h of the light period was defined as 100% (horizontal
line). Thus values for the subsequent 2-h periods are plotted relative to the value for hours O-2. The numbers on the
curves designate the first and the last 2-h interval in the dark. No significant differences were found between the curves.
rabbit:
l&l%,
Ref.
37).
In both species SWA showed a
decreasing trend in the range of
20-22%
in the subse-
quent sleep period. However, both species exhibited
larger amounts of TST than the guinea pig (cat:
11.3
h,
14.6
h, Refs.
19, 38;
rabbit:
11.4
h, Ref. 37). In contrast to
other rodents, where little sleep occurred in the dark pe-
riod and SWA values were high, in the guinea pig SWA
was lower in the dark period than in the light period.
Both in the cat
(19, 38)
and in the guinea pig a small
overall declining trend was present over the
24
h (Fig.
2).
We do not attribute a great significance to this trend
because it was most marked in four individuals, whereas
in
n
= 5 it was smaller and no significant trend was
observed.
It remains unresolved why among rodents the guinea
pig has such low SWA values for sleep. According to the
model, the large amount and long duration of waking
episodes should have induced a build-up ofprocess S. It is
possible that in the short NREM sleep episodes S was
dissipated, since in the rat SWA can exhibit high values
already in short NREM sleep episodes (39). However, it
cannot be verified if SWA in NREM sleep was high,
because the level of SWA cannot be directly compared
between species. Furthermore, the large number of BA in
the guinea pigs did not support the notion that the large
incidence of waking induced a high sleep pressure. Sim-
ulations of process S may help to understand the sleep-
wake regulation in guinea pigs. In the rat process S was
simulated on the basis of both baseline and sleep depri-
vation (SD) experiments (7). The results showed that the
dynamics of process S are species specific, e.g., the time
constant for the increase ofprocess S was
18.5
in humans
(4)
and 8.6 in rats (7). Also in the guinea pig SD experi-
ments will provide the data base to determine the dynam-
ics of process S for this species.
Other species differences may contribute to the low
amount of sleep generally found in guinea pigs. The pos-
sibility that sleep was disturbed by the recording leads
and other environmental conditions because guinea pigs
could be more susceptible than other species recorded in
a similar way cannot be excluded, although noninvasive
motor activity recordings in guinea pigs adapted for 3-4
wk to their environment resulted in 6 h
(+I
h SD) of rest
(3) and a predominance of
3-4
or 5-min rest episodes (3,
21),
which is similar to the TST and the mean duration of
NREM sleep episodes we obtained by polysomnography.
Because in the field guinea pigs are usually in groups (29))
recording of individuals in isolation may induce larger
amounts of waking. No significant difference was found
in the amount of motor activity of individual, isolated
guinea pigs or groups of six animals
(21).
It is well known that some animals, e.g. the herbivores,
which exhibit little sleep, spend several hours in “drows-
iness.” During episodes of drowsiness, the animals were
behaviorally quiescent, and the EEG exhibited a larger
amplitude and lower frequency than in waking. In the
guinea pigs low EMG values were usually accompanied by
an increase in SWA. Such episodes were scored as NREM
sleep. There was a marked similarity in the spectra of the
vigilance states (Fig. 5) to those of the rat (39) and the
rabbit (37), which exhibit little drowsiness. In both spe-
cies power density in the lower frequencies in NREM
0 2 4 6 8 10 12 14 16 18
20 22 24
HOURS
Fig. 7. Motor activity pattern in a 12:12-h light-dark cycle. Mean hourly
values are in arbitrary units (n = 3 animals, 7 days; n = 6 animals, 19
days) +: SE. Light-dark bars at the top indicate the 12:12-h LD cycle.
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SLEEP AND CORTICAL TEMPERATURE IN THE GUINEA PIG
R1131
0 24 48 0 24
48 (h)
Fig. 8. Motor activity of two individuals (left: 01; right: 09) in a 12:12-h light-dark cycle (days 1-20) and in constant
darkness (DD; days 21-32) plotted in arbitrary units/min. Top: mean motor activity of 15min intervals computed for
the days in the 1212-h LD cycle.
sleep was distinctly higher than in REM sleep and wak-
ing. Thus we have no indication that the guinea pig com-
pensates for the small amount of sleep by prolonged ep-
isodes of drowsiness.
In three other rodent species where EEG spectral anal-
ysis has been performed, HFA in NREM sleep showed a
distinct variation within 24 h (35, 37, 39). Thus, in the
rat, Syrian hamster, and Siberian chipmunk, peak values
were reached in the first hours of the 12-h period with
predominant waking, and the minimum occurred in the
first hours of the 12-h period of predominant sleep (35).
In contrast, in rabbits, where the 24-h amplitude of sleep-
wakefulness was small, HFA was evenly distributed over
the 24 h (37). It was suggested that in contrast to SWA,
HFA is less affected by prior waking than by circadian
factors (35, 39). Our results support this notion, because
the small circadian sleep-wake amplitude was not accom-
panied by marked variations of HFA.
Conclusions. In conclusion, the question whether the
guinea pig is a nocturnal or diurnal species remains un-
resolved. Its activity pattern is dominated by an activity
peak at each of the light-dark transitions, which may last
for several hours. It does however exhibit only a small
24-h amplitude of the sleep-wakefulness pattern, which
may be responsible for the decline of SWA. These results
can be accounted for by the two-process model of sleep
regulation (1, 4). It needs to be examined whether the
guinea pig can sleep little because its sleep is of high
intensity or whether the dynamics of process S are dif-
ferent from other rodents. We are performing SD studies
to clarify these questions.
We thank Drs. A. A. Borbely, P. Achermann, B. M. Barnes, and an
anonymous referee for their valuable comments on the manuscript.
This study was supported by Swiss National Science Foundation
Grants 31-25634.88 and 31-32574.91.
Address for reprint requests: I. Tobler, Institute of Pharmacology,
Univ. of Zurich, Gloriastrasse 32, CH-8006 Zurich, Switzerland.
Received 23 April 1992; accepted in final form 16 December 1992.
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... SWA increases as a function of prior time spent awake and decreases as a function of prior time spent asleep. This very reliable predictive relationship has been documented across a broad range of mammalian species (Borbely, 1982;Trachsel et al., 1988;Franken et al., 1991;Tobler et al., 1993) and has been modeled mathematically by a set of saturating exponential equations known as process S. Sleep state-dependent changes in the concentrations of neuromodulatory molecules, sleep substances, in the cerebral cortex may underlie the sleep state-dependent dynamics of SWA. If lactate is a sleep substance its concentration would be expected to vary inversely with SWA in the cerebral cortex as a function of sleep and wake states. ...
... The previously reported data do not address the possibility that lactate concentration exhibits longerterm state-dependent dynamics in parallel with the homeostatic dynamics of EEG SWA. In order to gauge this possibility, it was necessary to describe lactate dynamics on the minutes-to-hours time scale on which EEG slow wave dynamics have previously been be described mathematically with a general homeostatic model known as "Process S" (Borbely, 1982;Trachsel et al., 1988;Franken et al., 1991;Tobler et al., 1993). ...
... Additionally, we applied a well-known method of parameter optimization, the Nelder-Mead algorithm, in modeling the homeostatic dynamics of SWA and lactate concentration. This algorithm, in contrast to the previously used "brute force" methods (Borbely, 1982;Trachsel et al., 1988;Franken et al., 1991;Tobler et al., 1993) (where every possible combination of the parameters within the parameter space is investigated), systematically restricts the parameter space in which iterations of the model are run, thereby reducing computational time by orders of magnitude relative to the brute force method. The goals of the current study are (1) to quantify the sleep/wake dependent dynamics of cerebral lactate concentration in a common mouse strain using a general homeostatic model akin to Process S and (2) to demonstrate a computationally efficient mathematical method for optimizing the values of the model parameters. ...
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Cerebral metabolism varies dramatically as a function of sleep state. Brain concentration of lactate, the end product of glucose utilization via glycolysis, varies as a function of sleep state, and like slow wave activity (SWA) in the electroencephalogram (EEG), increases as a function of time spent awake or in rapid eye movement sleep and declines as a function of time spent in slow wave sleep (SWS). We sought to determine whether lactate concentration exhibits homeostatic dynamics akin to those of SWA in SWS. Lactate concentration in the cerebral cortex was measured by indwelling enzymatic biosensors. A set of equations based conceptually on Process S (previously used to quantify the homeostatic dynamics of SWA) was used to predict the sleep/wake state-dependent dynamics of lactate concentration in the cerebral cortex. Additionally, we applied an iterative parameter space-restricting algorithm (the Nelder-Mead method) to reduce computational time to find the optimal values of the free parameters. Compared to an exhaustive search, this algorithm reduced the computation time required by orders of magnitude. We show that state-dependent lactate concentration dynamics can be described by a homeostatic model, but that the optimal time constants for describing lactate dynamics are much smaller than those of SWA. This disconnect between lactate dynamics and SWA dynamics does not support the concept that lactate concentration is a biochemical mediator of sleep homeostasis. However, lactate synthesis in the cerebral cortex may nonetheless be informative with regard to sleep function, since the impact of glycolysis on sleep slow wave regulation is only just now being investigated.
... Eating and drinking occurs throughout the light phase and dark phase. By contrast, published reports suggest that rats and mice spend about 50% of their time sleeping during the light phase, and they are active during the dark phase (Tobler et al., 1993;Ibuka, 1984). Our findings are consistent with reports in the field indicating that guinea pigs were extraordinarily active and were without alternations between protracted complete rest periods and activity (Nicholls, 1922;Akita et al., 2001;Tobler et al, 1993). ...
... By contrast, published reports suggest that rats and mice spend about 50% of their time sleeping during the light phase, and they are active during the dark phase (Tobler et al., 1993;Ibuka, 1984). Our findings are consistent with reports in the field indicating that guinea pigs were extraordinarily active and were without alternations between protracted complete rest periods and activity (Nicholls, 1922;Akita et al., 2001;Tobler et al, 1993). For example, Nicholls (1922) found that the guinea pig's time was divided into periods of continuous activity and intermittent activity, whereby, the animals exhibited small rest periods averaging 3-4 minutes in length. ...
... Therefore, like rats and mice, guinea pigs would be amenable to experiments involving fear conditioning and/or operant learning paradigms. Additionally, guinea pigs stand out in other key areas such as being non-nocturnal animals and exhibiting polyphasic, fragmented sleep patterns (Ibuka, 1984;Tobler et al., 1993;Xi and Chase, 2008). Firstly, guinea pigs are voracious eaters (Nicholls, 1922) which make them ideal in studies utilizing food as a reward in operant condition. ...
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Though not commonly used in behavior tests guinea pigs may offer subtle behavior repertoires that better mimic human activity and warrant study. To test this, 31 Hartley guinea pigs (male, 200-250 g) were evaluated in PhenoTyper cages using the video-tracking EthoVision XT 7.0 software. Results showed that guinea pigs spent more time in the hidden zone (small box in corner of cage) than the food/water zone, or arena zone. Guinea pigs exhibited thigmotaxis (a wall following strategy) and were active throughout the light and dark phases. Eating and drinking occurred throughout the light and dark phases. An injection of 0.25 mg/kg SCH23390, the dopamine D1 receptors (D1R) antagonist, produced significant decreases in time spent in the hidden zone. There were insignificant changes in time spent in the hidden zone for guinea pigs treated with 7.5 mg SKF38393 (D1R agonist), 1.0 mg/kg sulpiride (D2R antagonist), and 1.0 or 10.0 mg/kg methamphetamine. Locomotor activity profiles were unchanged after injections of saline, SKF38393, SCH23390 and sulpiride. By contrast, a single injection or repeated administration for 7 days of low-dose methamphetamine induced transient hyperactivity but this declined to baseline levels over the 22-hour observation period. Guinea pigs treated with high-dose methamphetamine displayed sustained hyperactivity and travelled significantly greater distances over the circadian cycle. Subsequent 7-day treatment with high-dose methamphetamine induced motor sensitization and significant increases in total distances moved relative to single drug injections or saline controls. These results highlight the versatility and unique features of the guinea pig for studying brain-behavior interactions. Synapse, 2014. © 2014 Wiley Periodicals, Inc.
... In the rabbit, guinea pig, cat, and blind mole rat, species that exhibit only a small preference for sleep in the light period, the decline of SWA is minor or absent. [35][36][37][38] This relationship between the sleep-wake pattern and SWA was also evident in experiments in the rat and Djungarian hamster when the photoperiod was changed. The total amount of sleep was the same in both photoperiods, but sleep was redistributed according to the new light-to-dark ratio. ...
... In further similar experiments in the rat and other rodents (guinea pigs and laboratory mice), the reduction in the number of brief awakenings correlated with the increase of SWA. 13,26,36,82 The inverse relationship indicates that brief awakenings may represent a behavioral correlate of sleep intensity. 26 The decrease of brief awakenings under sleep pressure may contribute to the reduced variability of the NREM-REM sleep cycle in the rat 82 and bottle-nosed dolphin, 68 and in the cat 84 to the shortening of the sleep cycle and increase in its regularity, and the duration of the single-cell activity discharge cycle in brainstem dorsal raphe nucleus. ...
... Similar to starlings, 1-18 Hz activity in magpies was higher following 6-h of sleep loss. Conversely, animals that take frequent naps, such as guinea pigs (Cavia porcellus) [58] and pigeons [24,34,52,59], do not show a clear decline in SWA during undisturbed sleep. ...
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Study Objectives We explore NREM and REM sleep homeostasis in Australian magpies (Cracticus tibicen tyrannica). We predicted that magpies would recover lost sleep by spending more time in NREM and REM sleep, and by engaging in more intense NREM sleep as indicated by increased slow-wave activity (SWA). Methods Continuous 72-h recordings of EEG, EMG and tri-axial accelerometry, along with EEG spectral analyses, were performed on wild-caught Australian magpies housed in indoor aviaries. Australian magpies were subjected to two protocols of night-time sleep deprivation: full 12-h night (n = 8) and first 6-h half of the night (n = 5), which were preceded by a 36-h baseline recording and followed by a 24-h recovery period. Results Australian magpies recovered lost NREM sleep by sleeping more, with increased NREM sleep consolidation, and increased SWA during recovery sleep. Following 12-h of night-time sleep loss, magpies also showed reduced SWA the following night after napping more during the recovery day. Surprisingly, the magpies did not recover any lost REM sleep. Conclusions Only NREM sleep is homeostatically regulated in Australian magpies with the level of SWA reflecting prior sleep/wake history. The significance of emerging patterns on the apparent absence of REM sleep homeostasis, now observed in multiple species, remains unclear.
... Although EEG-based measures of sleep intensity are preferred, experimental studies have identified behavioral correlates of sleep intensity. For example, in rodents, the reduction in the number of brief awakenings correlates with increased SWA (Franken et al., 1991;Tobler, Franken, & Jaggi, 1993;Tobler et al., 1996). In sleepdeprived dogs, motor activity measured continuously using actigraphy was reduced up to 40% during recovery (Tobler & Sigg, 1986). ...
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Objectives Primates spend almost half their lives asleep, yet we know little about how evolution has shaped variation in the duration or intensity of sleep (i.e., sleep regulation) across primate species. Our objective was to test hypotheses related to how sleeping site security influences sleep intensity in different lemur species. Methods We used actigraphy and infrared videography to generate sleep measures in 100 individuals (males = 51, females = 49) of seven lemur species (genera: Eulemur, Lemur, Propithecus, and Varecia) at the Duke Lemur Center in Durham, NC. We also generated experimental data using sleep deprivation for 16 individuals. This experiment used a pair‐wise design for two sets of paired lemurs from each genus, where the experimental pair experienced a sleep deprivation protocol while the control experienced normal sleeping conditions. We calculated a sleep depth composite metric from weighted z scores of three sleep intensity variables. Results We found that, relative to cathemeral lemurs, diurnal Propithecus was characterized by the deepest sleep and exhibited the most disruptions to normal sleep‐wake regulation when sleep deprived. In contrast, Eulemur mongoz was characterized by significantly lighter sleep than Propithecus, and E. mongoz showed the fewest disruptions to normal sleep‐wake regulation when sleep deprived. Security of the sleeping site led to greater sleep depth, with access to outdoor housing linked to lighter sleep in all lemurs that were studied. Conclusions We propose that sleeping site security was an essential component of sleep regulation throughout primate evolution. This work suggests that sleeping site security may have been an important factor associated with the evolution of sleep in early and later hominins.
... Sleep after SD is usually enhanced, with respect to both its total duration and its intensity as measured with EEG SWA, 96,141,180,181 although notable differences have been found between studies, species, genetic backgrounds, age, the time of day, environmental conditions, and the method used to perform SD. 97,[182][183][184][185][186][187][188][189][190][191][192] Moreover, substantial interindividual variability in the response to SD has also been found. 35,66 The terminology used to denote the response to SD would benefit from clarification and improvement. ...
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... Fourth, we found guinea pigs to be robust small animal models with unique features that render them well suited for assessments of mnemonic functions and behaviors. They are neither nocturnal nor diurnal [42,53] and, therefore, do not require reversal of light-dark cycles often necessary when using mice or rats. Their relatively consistent exploratory activity allows for unambiguous characterization of behaviors. ...
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