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1 Neuroscience Program,2 Department of Anesthesiology, and3 Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, Michigan 48014, USA
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ABSTRACT |
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 TOP ABSTRACT Memory systems and REM...REM sleep timing and...ResultsDiscussionMaterials and MethodsREFERENCES |
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Memory systems and REM sleep |
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TOPABSTRACTMemory systems and REM...REM sleep timing and...ResultsDiscussionMaterials and MethodsREFERENCES |
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;
Van Dongen et al. 2003), the
nature of the dependence of learning and memory on sleep is largely unknown.
Much of the difficulty in making a strong argument for the role of sleep in
learning (Vertes and Eastman
2000; Siegel 2001)
stems from the often temporary and subtle variations in performance exhibited
after sleep deprivation. For example, people sleeping relatively few hours per
night can still adequately perform most work-related functions most of the
time, especially with the use of a stimulant
(Bonnet and Arand 1994;
Westensten et al. 2002; Wyatt et al.
2004). Sleep deprivation increases the areas and number of brain
regions activated in completing a complex or split-attention task
(Drummond et al. 2000;
Drummond et al. 2001). As in
the case when an area of the brain normally involved in a task is compromised,
other brain regions may be invoked to compensate. For example, when age or
local anesthetic reduces hippocampal function, performance on a spatial task
can remain adequate by the use of working memory rehearsal or
non-hippocampus-dependent cue strategies
(Barnes et al. 1980;
Rapp et al. 1987;
Poe et al. 2000a). Under sleep
deprivation, the increased brain response may allow people to function
normally until a crisis or critical multifactorial decision point arrives. At
this point the reserve processing areas, already tapped for normal processing,
cannot support the additional load and judgment can be disastrously impaired.
Lack of sleep was implicated in four different nuclear power plant accidents
and near accidents as well as in decisions surrounding disastrous and near
disastrous space shuttle launches (Mitler
et al. 1988). Thus, although overall performance may be only
mildly impaired or not impaired at all under standard conditions, high-level
processing mechanisms remain dysfunctional with total sleep or selective rapid
eye movement (REM) deprivation.
A preponderance of evidence suggests that sleep is important for certain
types of complex learning requiring the fast association between different
processing regions. Spatial learning, which associates the sight, sound, and
the many contextual cues that identify the place of a reward, is dependent on
the hippocampus (O'Keefe and Nadel
1978; Vargha-Khadem et al.
1997; Eichenbaum
2000) and seems to require sleep, specifically REM sleep. Both
total sleep deprivation and selective REM sleep deprivation result in
performance impairments on spatial tasks in rodents
(Youngblood et al. 1997;
Smith et al. 1998;
Guan et al. 2004) and on
various cognitive, perceptual, and motor tasks in humans
(Wimmer et al. 1992;
Karni et al. 1994;
Stickgold et al. 2001).
In accordance with results from a number of experiments
(Seligman 1970;
Greenberg and Pearlman 1974;
McGrath and Cohen 1978;
Pearlman 1979;
Winson 1985), we hypothesize
that REM sleep is important for complex associative learning, such as spatial
learning. For spatial learning, distal allocentric (global environmental) cues
are used more than are proximal egocentric cues
(Shapiro et al. 1997).
Learning to use allocentric cues requires the hippocampus. When the
hippocampus is damaged either permanently or temporarily, tasks are solved by
using nonspatial adaptive strategies, such as procedural strategies
(DiMattia and Kesner 1988). For
example, rats with hippocampal damage can perform the Morris water maze task
by swimming around the tank at a fixed distance from the perimeter to find the
hidden platform (Morris et al.
1982). This thigmotaxic strategy is less efficient than a spatial
strategy in which animals swim directly to the hidden platform location no
matter where they are originally placed within the tank
(DiMattia and Kesner 1988). If
our hypothesis that REM sleep is important for complex associative learning is
correct, then REM restriction while learning a spatial task should impair
spatial learning while enhancing the use of less-efficient alternate
strategies. We tested our hypothesis with a task that simultaneously measures
the use of spatial solutions (using extramaze, allocentric cues) against the
use of more simple (intramaze, egocentric) cues to see if REM sleep
restriction differentially impairs complex associative learning.
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REM sleep timing and learning |
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TOPABSTRACTMemory systems and REM...REM sleep timing and...ResultsDiscussionMaterials and MethodsREFERENCES |
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) and
on the Morris water maze (Smith and Rose
1997). REM sleep expression is not uniform in timing and/or
duration across the sleep cycle in both rats
(Borbely and Neuhaus 1979;
Borbely 1980;
Wurts and Edgar 2000) and
humans (Feinberg and Floyd
1979), allowing for the possibility that REM during one portion of
the sleep cycle may be more or less important for the retention or
consolidation of newly learned information. The time period when REM sleep
restriction significantly impairs learning coincides with spontaneous
increases in REM sleep subsequent to the training sessions (rats,
Smith and Butler 1982;
Smith 1985; humans,
De Koninck et al. 1989) and has
been called the "REM window." When application of a protein
synthesis inhibitor or an acetylcholine antagonist, both of which impair
memory (Eckerman et al. 1980;
Okaichi et al. 1989;
Meiri and Rosenblum 1998;
Naghdi et al. 2003), coincides
with the beginning of the REM window, shuttle box learning is impaired in rats
(Smith et al. 1991). The REM
window for intensive training (e.g., many trials over a short period of time)
tends to occur in the first few hours of sleep after learning
(Smith 1985;
Smith and Rose 1996), while
the REM window for fewer trials occurs relatively later, according to animal
studies (Smith 1985). This REM
window phenomenon may explain why researchers have mixed results when using
REM deprivation at various times post-training (for review, see
Smith 1985). If the REM window
concept is pertinent to complex associative learning, then total overall REM
sleep deprivation should not be necessary to impair learning. Restricting
animals from entering REM in key hours, even if the total REM sleep time is
unchanged, should be enough to impede the function of REM for learning. We
tested this idea by not allowing animals to enter REM only for the first 4 h
after training each day, or by allowing them to sleep normally for 4 h
following training, then restricting them from REM in the second 4-h
period. In a preliminary study we found that, unlike control animals, the performance of rats deprived of REM sleep for 4 h after training did not reach asymptote (no performance improvement across three consecutive days) within a 6-d experimental period. In the present study, we continued daily training until REM-restricted and control groups reached performance asymptote to see whether REM-restricted animals could reach the same overall performance level as controls, and if so, how long it would take each group to reach that level. Finally, to see if REM-restricted animals ever learned the complex associative spatial task, we assessed the various performance strategies of the rats with procedures that tested simple cue use versus complex spatial learning over the entire 15-d learning period.
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Results |
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TOPABSTRACTMemory systems and REM...REM sleep timing and...ResultsDiscussionMaterials and MethodsREFERENCES |
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), for 30 min/d
for 15 d. Each day, after training, rats in one group (control) were returned
to their home cage, while two groups were deprived of REM sleep for 4 h either
immediately after training (0-4 REMr) or 4 h after training (4-8 REMr).
Relatively selective REM sleep deprivation was accomplished by the standard
multiple platform over water method (see Materials and Methods).
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Learning curve (errors per lap)
All rats started the experiment making approximately four errors per lap on the novel maze. In the first 5-d segment, there was no difference in performance between groups (P = 0.526) (Fig. 1A, segment 1). Presumably the availability of food within the corncob bedding of all the rats in the first 4 d was responsible for delayed weight loss and the few laps completed each day (see Fig. 4 below). Overall performance also did not significantly differ between groups during the final 5-d segment of the experiment (P = 0.132) (Fig. 1A, segment 3). Thus, across the entire 15-d period there was no overall significant difference in errors per lap between the groups (P = 0.162). However, in the mid portion of the experiment (days 6-10), controls committed significantly fewer errors per lap (P = 0.052) than did animals restricted from entering REM in the first 4 h after training (Fig. 1A, segment 2). The control group reached criterion (less than one error per lap) and maintained performance by day 10 onward, after completing an average of 108.8 laps. The 0-4 REMr group reached criterion and asymptote 3 d later, after completing an average of 139.5 laps (lap effect between groups, P = 0.421).
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Improvement
Similar to the overall performance levels, controls showed a higher rate of improvement in the mid portion of the experiment did than 0-4 REMr rats (P = 0.024) (Fig. 1B, segment 2). Improved performance from baseline remained higher for controls than for 0-4 REMr animals in the last portion of the experiment as well (P = 0.008) (Fig. 1B, segment 3). Regression analysis showed the slope of improvement to be greatest for controls during the first segment (r = 0.352; day effect, P = 0.011), then decreasing over the second (r = 0.216; day effect, P = 0.045) and third segments (r = 0.059; no significant day effect, P = 0.327). Over the entire experiment, the slope of improvement for controls was 0.220 (day effect, P < 0.001). The 0-4 REMr animals had a similar overall slope of improvement (r = 0.228; day effect, P < 0.001). However, unlike controls, 0-4 REMr animals showed the greatest rate of improvement during the second and third segments of training (r = 0.191; day effect, P = 0.016 and r = 0.226; day effect, P = 0.039, respectively). Improvement rate was lower during the first segment (r = 0.149; no significant day effect, P = 0.16). Controls tended to have a steeper slope and therefore improved more than 0-4 REMr animals during the first segment (P = 0.093), while 0-4 REMr animals tended to have a steeper slope and improved more than did controls during the third segment (P = 0.087). Thus, the pattern of improvement varied between groups, with controls showing larger day-to-day improvement in the early part of the learning curve and 0-4 REMr showing little improvement early on, and most improvement later.
Error types
Three types of errors were scored. Across days, errors of commission (EC; when an animal investigated an unbaited box) were greater than the number of errors of hesitation (EH; when an animal hesitated at an unbaited box) or of omission (EO; when an animal ignored a baited box) for both groups (0-4 REMr, P < 0.001; control, P < 0.001) (Fig. 2). Errors of commission primarily accounted for the difference in errors per lap between 0-4 REMr and control groups. The number of commission errors had a significant day-by-group interaction (P = 0.031). Though the number of laps completed increased in both groups after the first 5 d (see Fig. 4 below), the number of errors of commission committed by controls did not change whereas they rose in 0-4 REMr animals in the second segment and were significantly different from control levels on day 10 (P = 0.009) and day 11 (P = 0.007). In the third segment, the number of errors of commission committed by 0-4 REMr animals decreased to control levels.
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Improvement within and between days
Although the large variance in performance day to day washed out group differences with ANOVA comparisons, on 14 out of 15 d, 0-4 REMr animals committed a higher number of errors through the first five laps compared with controls (Sign test, P = 0.005) (Fig. 3A). There was no significant difference between groups for the remaining lap sets (laps 6-10 and laps 11-15), although the low number of laps completed early in training reduced the number of days included in the analysis (7 d for laps 6-10; 6 d for laps 11-15). All rats improved performance within a practice session (Fig. 3B), but control animals started most days with fewer errors and, so, retained more information about the location of food boxes between days.
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Across the 15-d experiment, body weight decreased significantly in both 0-4 REMr and control groups (P < 0.001) (Fig. 4). There was no day-by-group interaction. In the first and second 5-d segments, there was also no difference in weight between groups (segment 1, P = 0.248; segment 2, P = 0.312), but in the third segment, controls weighed slightly more than did 0-4 REMr animals (P = 0.046).
Number of laps completed
There was a significant increase in the number of laps completed across the
15-d experiment in both groups (P < 0.001)
(Fig. 4). However, there was no
difference in the number of laps completed each day between groups (P
= 0.983). Additionally, there was no group difference in laps completed daily
in any of the 5-d segments (segment 1, P = 0.429; segment 2,
P = 0.683; segment 3, P = 0.544). Both groups averaged
approximately five laps per day for the first 5 d. Laps completed increased
dramatically over the next 5 d. By day 15, rats averaged 
25 laps for the
session.
Time of REM deprivation
As noted earlier, animals restricted from entering REM sleep 4 h after training (4-8 REMr) performed at an intermediate level between 0-4 REMr and control groups for most measures. However, on 13 of 15 d, rats in the 0-4 REMr group committed more errors in the first five laps of the training period than did the 4-8 REMr group (P = 0.003) (Fig. 5A). The 4-8 REMr group weighed less on average across the 15-d training period (0-4 REMr, 280.4 ± 5.5 g; 4-8 REMr, 254.2 ± 6.1 g; P = 0.015). There was no difference between the two REM-restricted groups in errors per lap across 15 d (P = 0.867) or within the three 5-d segments (segment 1, P = 0.761; segment 2, P = 0.953; segment 3, P = 0.803). There was also no difference between REM-restricted groups in improvement (P = 0.841), types of errors committed (EC, P = 0.492; EH, P = 0.824; EO, P = 0.655), or number of laps completed each day (P = 0.488). There was no significant difference in the number of laps needed to reach criterion (0-4 REMr, 139.6; 4-8 REMr, 107.2; P = 0.47). One rat in the 4-8 REMr group, however, never performed to criterion.
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Strategy used to find food
To determine whether animals relied on a spatial or nonspatial strategy to solve the task, two types of probe tests were employed. To reveal local, simple cue use, the maze was rotated 180° following lap 10, and the same box positions relative to the room (different physical boxes) were baited. To reveal thigmotaxic strategies, rats were moved after every five laps to a resting pot for 2 min and then replaced at semirandom positions on the maze. The performance on lap 10 (before maze rotation) was compared to performance on lap 11 (following maze rotation). A decrease or no change in errors between these two laps suggests the animals relied on a spatial strategy since the relative food box positions to extramaze cues remained the same. On the other hand, an increase in errors on lap 11 suggests animals relied on nonspatial strategies since the food box positions relative to intramaze cues deposited by rats within a session (such as urine, food crumbs, etc.) changed with maze rotation. While both 4-8 REMr and control groups showed no difference in average errors between laps 10 and 11 (Sign test, 4-8 REMr: lap 10, 1.08 ± 0.4; lap 11, 1.04 ± 0.4; P = 0.31; control: lap 10, 0.52 ± 0.12; lap 11, 0.96 ± 0.14; P = 0.09) (Fig. 5C,D), the average errors committed by the 0-4 REMr group on lap 11 increased compared with lap 10 (lap 10, 0.75 ± 0.19; lap 11, 1.33 ± 0.2; P = 0.02) (Figs. 5B, 3B). There was no difference in errors committed between laps 5 and 6 (when the animal had a 2-min break and was replaced on the track) for the 0-4 REMr group (P = 0.226), indicating that removal from and replacement on the track in a different location is not responsible for the performance disruption on lap 11. The 4-8 REMr group also did not show a difference in errors committed on lap 5 versus lap 6 (P = 0.205); however, the control group showed a slight trend of increased errors on lap 6 (P = 0.081). The lack of disruption with random placement on the maze combined with the errors after uncoupling local and global cues (maze rotation after lap 10) suggests that 0-4 REMr animals were relying on simple, intramaze cues rather than using an allocentric spatial strategy to find food. Controls and 4-8 REMr animals were not disrupted by maze rotation, indicating that they relied on a spatial strategy.
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Discussion |
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TOPABSTRACTMemory systems and REM...REM sleep timing and...ResultsDiscussionMaterials and MethodsREFERENCES |
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). Thus, the
first day effect in the present study should not account for the continued
impairments of the 0-4 REMr group. Animals with early REM sleep restriction also continued to make more errors after maze rotation each day (lap 11) through the end of the study, even after their overall daily performance reached asymptote. Thus, 4 h of REM restriction immediately following learning seems to have increased the use of alternate, nonspatial, cue-based learning strategies. Early REM restriction did not affect the use of working memory within a day since, after the "reminder" of the first few laps of the day and after the first few laps following maze rotation each day, there was no difference in errors per lap between groups (Fig. 3B). REM sleep restriction also did not affect the rate of learning the procedures of the task, since the pattern of errors of hesitation and omission were the same between REM-restricted and control groups. Errors of omission generally occurred early in training when the rats were still learning that food was present in three boxes. Errors of hesitation increased as the rats learned that food was available in some boxes. It is perhaps a misnomer to call hesitations errors, but we felt it important to include these pausing behaviors as they probably reflected uncertainty as to exactly which boxes contained food, but showed they learned the procedure of checking boxes for food.
A selective effect on reference versus simple cued memory fits with results
of REM deprivation in several other studies
(Youngblood et al. 1997;
Smith et al. 1998;
Ruskin et al. 2004). The
ability of rats to use alternative strategies to solve spatial tasks has
heretofore made it difficult to make strong conclusions about the role of REM
sleep in learning. The use of alternate strategies may mask significant
impairments when only overall performance is considered (e.g., the small,
temporary effects seen in Fig.
1; see White and McDonald
2002). When the strategies and active brain areas used to solve a
task are measured, as here and in Drummond's studies, (2000, 2001)
respectively, effects of REM restriction are consistently seen. In this task,
alternate nonspatial strategies enabled the 0-4 REMr animals to find food with
few errors on most trials, but when those strategies were rendered
ineffective, the deficits in learning were revealed.
Continued reliance on simple cue relationships rather than on allocentric
spatial cues (maze rotation effects) implies that early REM restriction
rendered rats selectively less able to use the more efficient,
hippocampus-dependent spatial strategy to solve the task. However, procedural
learning (as illustrated by a reduction in errors of omission and a concurrent
increase in errors of hesitation) and working memory (as illustrated by a
preservation of performance across 2 min breaks) were unaffected by REM
restriction. Thus, REM restriction seems to selectively impair hippocampal
function. The activity of place cells in the hippocampus should also be
measured during various manipulations of the eight-box task, and we have begun
such a study. If REM restriction results in a diminished ability to use a
spatial strategy as these data indicate, then place cells within the
hippocampus should also show altered ensemble activity compared with that of
controls, similar to the alteration observed in aged rats who are also
relatively impaired on spatial tasks
(Barnes et al. 1997).
REM sleep timing relative to training
Rats in the 4-8 REMr group differed from those in the 0-4 REMr group in
that they seemed to rely on a spatial strategy to a similar degree as
controls. They were not disrupted by maze rotation, and they performed better
than did early REM-restricted rats on the first few laps each day. This
difference in strategies between REM-restricted groups may indicate that REM
sleep immediately following training is more important for learning the
spatial solution to this task. In order to draw strong conclusions regarding
the importance of REM sleep timing, groups of rats restricted from entering
REM sleep at other windows, e.g., 12-16 h after training, are needed. Also,
the spontaneous increase in REM sleep that is seen after training on other
tasks (Lucero 1970;
Fishbein et al. 1974;
Smith and Rose 1997) could be
measured to determine the most critical time of REM sleep for this task, which
may change as the number of laps completed each day rises.
Motivation
There was no difference in the number of total laps completed per group, ruling out the possibility that control rats had more practice within a day. Weight loss also did not correlate with performance, suggesting motivation differences did not underlie performance deficits. Thus, any difference in performance across groups should be due to the only factor that varied consistently across groups, that is, REM restriction.
Possible influences of REM restriction stress
Stress is a confounding factor with any sleep restriction procedure. The
most prevalent argument against the hypothesis that REM facilitates learning
is that the stress of the REM restriction procedure results in a general
cognitive impairment irrespective of learning and is unrelated to any memory
processing during sleep (for review, see
Horne and McGrath 1984;
Vertes and Eastman 2000).
Stress, or a rise in stress-related hormones such as corticosterone, can
modify learning positively or negatively (for review, see
Luine 1994;
Sapolsky 2003;
Wolf 2003), depending on the
type of stressor and level of hormone rise. Several procedures were used to
reduce stress in this experiment. First, multiple platforms were used to
reduce immobility stress (Coenen and
Van-Luijtelaar 1985). This multiple platform REM restriction
technique has been shown to be less stressful than the single platform
technique (Coenen and Van Luijtelaar
1985). Second, the water level was well below the platform so
animals' tails did not touch the water, unlike most other REM restriction
studies. When animals fell or jumped into the shallow water, they were able to
climb back atop the platforms without delay and were toweled dry to eliminate
a thermal stress load. Third, rats had access to fresh, drinkable water at all
times. Fourth, the restriction period lasted only 4 h, which is much shorter
than other studies of stress caused by REM deprivation (usually 
24 h)
(Mendelson et al. 1974;
Coenen and VanLuijtelaar 1985).
Finally, the time exposed to the pedestals and the putative sleep restriction
stressor were equal between the two REM-restricted groups, yet performance
differed according to the timing of REM restriction. Restriction in different
REM windows differentially affected spatial learning both in the present study
and in that conducted by Smith and Butler
(1982), although REM
restriction in either window would presumably cause similar stress levels.
Conclusions
This experiment supports the idea that REM sleep is important for complex, associative learning such as tested by the eight-box spatial task. These data also support the hypothesis that the timing of REM sleep relative to training is important for some types of learning. This experiment adds to the literature by restricting REM in two windows and doing so on multiple days to determine which learning deficits caused by REM restriction are long lasting and whether the effects can ever be overcome by enough practice and/or use of alternative strategies. Significant deficits in complex associative learning continued throughout the course of chronic REM restriction. This study highlights the fact that learning strategy changes can be difficult to discern in overall performance, and careful dissection of performance after challenges such as REM restriction can make an otherwise seemingly small or temporary deficit stand out as a continuous obstruction of complex associative learning.
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Materials and Methods |
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TOPABSTRACTMemory systems and REM...REM sleep timing and...ResultsDiscussionMaterials and MethodsREFERENCES |
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Subjects and housing
Twenty-five Fisher 344 rats aged 5 mo and weighing 250-350 g, were obtained
from Harlan (Indianapolis, IN). Following acclimatization, visual acuity was
tested by using the visual platform version of the Morris water maze
(Morris 1984). The visual
version of the Morris water maze requires animals to swim to a visible
platform 2 cm above the water's surface as the only means of escape from a
standard circular water tank. Animals performed five trials per day for two
consecutive days. Only rats with performance <2 SD above the 2 d average
latency to platform were deemed visually and physically fit and selected to
continue the experiment. Rats were rank-ordered by average latency to platform
across the 2 d and were divided to ensure that each group had equivalent
numbers of relatively fast, moderate, and slow performers. Following
completion of the Morris water maze task, rats were moved to individual
standard Plexiglas cages (45.7 x 24.1 x 20.3 cm) placed inside one
of three environmentally (light, sound, and temperature) controlled chambers.
The housing temperature was set at 22.5 ± 0.5°C, with a 12:12 h
light/dark cycle. Testing for all animals occurred 30 min after light
onset each day. Fresh water was available ad libitum at all times, except
during performance of the behavioral task. Initially, animals were housed with
corncob bedding and were able to find edible corn pieces within this bedding,
so their weight was not declining and their motivation for running multiple
laps each day was low: The average number of laps per day was only five for
the first 5 d. Bedding type was switched to (inedible) pine shavings from day
4 onward, and thereafter, the number of laps completed per day increased
steadily.
Motivation
Ad libitum feeding was stopped prior to the initiation of training by
removing food pellets. Rats only received food in the form of mash (pellets
dissolved in water) during the daily 30-min training session to motivate them
to run as many laps as possible in the session. However, if their weight
approached the 80% free feeding minimum, they were supplemented with food mash
in their home cage. By the end of the study, most rats were supplemented
daily, as they were generally unable to maintain weight on the 25 laps/d
they were completing.
Task description
Eight-box spatial task
The eight-box task (Poe et al.
2002) is a rectangular raised track outfitted with eight
symmetrically positioned boxes (Fig.
6).
Three of the eight-box positions were selected as goals where 0.2 cc
of food was available in a shallow food cup behind a hinged door. To encourage
forward motion for accurate assessment of errors per lap, the rats were
required to complete a full lap before the three boxes were rebaited. Errors
were scored visually by an experimenter during the session when a rat visited
a box position that never contained food (commission), slowed or stopped in
front of a nonbaited box (hesitation), or ignored a baited box (omission).
Since each lap was considered a new trial, many trials could be completed in a
short period of time, allowing for the type of intensive training sessions
that make the REM sleep immediately following training most germane to
learning (Smith and Rose
1997). All rats were naive to the maze task prior to the first day
of the experiment, so they had to learn the procedures of running for food
reward as well as the spatial location of the three boxes always baited with
food.
Making procedural strategies less effective
In order to increase the relative accuracy of allocentric, i.e., global
referenced, spatial cues over simple intramaze cues to indicate food placement
sites, the following measures were employed: (1) all boxes contained
inaccessible food to equalize odor cues; (2) rats were removed from the track
after every fifth lap, placed in a towel-lined shallow clay pot to rest for 2
min, and then replaced on the track at a new start location to render
inaccurate an egocentric, self-motion-related strategy such as visiting the
first, third, and seventh boxes from the starting position; and (3) after
every 10 laps completed (lap 10, 20, etc.) the track was rotated 180° and
the boxes cleaned and rebaited such that the boxes at the same room positions
(not the same physical boxes) were baited for the next 10 laps. The maze
rotation procedure made the positions of scent or visible cues that were left
on the track unreliable relative to the places of food rewards and provided an
indication of strategy used. Since the maze rotation alters any intramaze
cue-to-baited box relations, but leaves all extramaze (global, spatial)
cue-to-baited box relations intact, a rat relying on the simple, intramaze
cues to find food rewards would show increased errors following maze rotation,
while a rat relying on the spatial, extramaze cues would not be affected by
rotation.
Groups
To test the contribution of REM sleep to learning on this complex associative task, we restricted six rats from entering REM sleep in the 4-h period immediately following training (0-4 REMr). Another eight rats were returned to their home cage immediately after training to serve as normally sleeping controls. To test the specificity of the first 4-h REM window, another group of six rats was REM sleep restricted in the second 4-h period after training (4-8 REMr) and compared with the first REM-restricted group for performance.
REM sleep restriction method
The multiple platforms-over-water method
(Coenen and van Luijtelaar
1985) was used to restrict REM sleep for 4 h each day. Three
platforms of equal dimension (6.35-cm diameter, 24 cm tall) were placed next
to each other in a bin (39 cm deep). The platforms stood above 2 cm of water.
This water level is much lower than the standard level (level usually just
below top of platforms) and prevents animals' tails from hanging in the water,
reducing cold stress. The edges of the platforms were 9 cm apart. The rat was
placed atop one of the platforms and was able to move between them, sit with
its feet beneath it, and to sleep as long as it maintained enough muscle tone
to hold their position. During the transition to REM sleep, antigravity
muscles are inhibited (Chase and Morales
1990), causing muscle atonia
(Jouvet et al. 1959), and rats
begin to fall. Such strong vestibular stimulation usually awakens the animals
before they actually fall off the pedestal, but if they do, the platform is
low enough that they can climb back atop the pedestal themselves. These rats
were not instrumented for assessing sleep/waking state. However, the multiple
platform method of deprivation is relatively selective for REM sleep
disruption as non-REM sleep is usually only moderately reduced (70%-85%
of baseline) compared with the near total elimination of REM sleep
(van Luijtelaar and Coenen
1986; Maloney et al.
1999). Behavioral observations confirm that during REM
restriction, rats were generally quiescent during the 4-h platform
session.
Our study had a comparable rat weight/platform diameter ratio as other
studies, so we expect the same degree of REM restriction was achieved,
although we cannot be sure that home cage controls did not also have reduced
REM sleep compared with baseline after such an intensive learning session.
Spontaneous increases in REM sleep after spatial learning on this task (data
not shown) and shown in other studies
(Lucero 1970;
Fishbein et al. 1974;
Smith and Rose 1997) make REM
reductions in controls unlikely here.
Statistical analysis
Analysis of the type and timing of errors within a training session and across days was performed to reveal the relative use of nonspatial adaptive strategies. SPSS (SPSS Inc.) statistical software package was used for all parametric analyses. Repeated-measures ANOVA was used to analyze the changes in errors per lap, performance improvement, and number of laps completed per training session between groups and days of testing. A post hoc analysis of each of three segments of the experiment was performed on the same comparisons. Segment 1 represented the first 5 d. The second segment was the next 5 d. And the third segment was the final 5 d. Repeated-measures ANOVAs were performed, correcting for violation of sphericity by using the Hung-Feldt adjustment when necessary to adjust nonuniform variance across days or groups. Performance improvement was calculated by subtracting each day's mean number of errors per lap for each rat from the group average number of errors per lap on day 1. Regression analyses were performed on the 15-d performance improvement curve, and ANCOVA analysis was used to compare improvement slope across groups. The regression and ANCOVA analyses were repeated for each 5-d segment. Regression analyses were also performed for the improvement within a day curve. The improvement within a day curve was made by averaging errors for each lap (1-30) across animals and days. The cutoff was set at lap 30 because this was the last lap which multiple animals per group completed.
To determine the difference between groups on the first lap each day, a repeated-measures ANOVA was performed. A repeated-measures ANOVA was also used to compare the average number of each type of error (commission, hesitation, omission) within groups and to test for weight differences between groups.
We measured the effect of the maze rotation (comparing errors on lap 11,
after rotation, to lap 10, before rotation) on performance. The last 6 d of
the experiment were used to compare lap 10 to lap 11 since, by then, a
majority of animals were completing >11 laps consistently. A nonparametric
Sign test (Freund 1999) was
used since different numbers of animals contributed to the analysis each day.
A Sign test was also used to compare errors made on the first lap each day
between groups. Total errors on laps 1-5, 6-10, and 11-15 were binned for each
rat on each day and defined as lap sets.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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4 E-mail ginapoe{at}umich.edu; fax (734) 764-9332.
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